....‘Ar.r,r...... ...... .. . ... .. ~. _ . 4‘ _ , _ . . . ‘ ,4 .» ...._.<- I . - v. ...-.—A-.-.-‘~V,‘ IBRARIES l\\\\\\\\\ “WWWL\\\\1\\\\J\l ill\\\\\\\\\\\\l 1293 This is to certify that the dissertation entitled An Analysis of Competitive Positioning Strategies in the U.S. Ethical Pharmaceutical Industry : An EQS Application presented by Poh-Lin Yeoh has been accepted [towards fulfillment of the requirements for Doctorate degree in Marketing QR? (iv/W Major professor May 159 1992 Date MS U is an Affirmative Action/Equal Opportunity Institution 0- 12771 ‘LVBWAE’W meuqan State vaersity PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or belore one due. DATE DUE : DATE DUE DATE DUE " #Wl 1“. . ....I _ ‘t‘ xi." ' "'° 5 5.. K i \[ ]i[ l MSU Is An Affirmothle ActlorVEquel Opponunlty Institution chna-M AN ANALYSIS OF COMPETITIVE POSITIONING STRATEGIES IN THE U.S. ETHICAL PHARMACEUTICAL INDUSTRY : AN EQS APPLICATION BY POE-LIN YEOH A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements DOCTOR OF PHILOSOPHY Department of Marketing and . Transportation Administration 1992 r .I .’ I #- “’r/ // ; I) - I“, ) ./ ABSTRACT AN ANALYSIS OF COMPETITIVE POSITIONING STRATEGIES IN THE U.S. ETHICAL PHARMACEUTICAL INDUSTRY : AN EQS APPLICATION By pan-LIN arson To examine the effect of competitive positioning strategies on firm performance, the following research questions were addressed in the context of the U.S. ethical pharmaceutical industry between 1971 to 1989: (1) How are the competitive positioning variables causally related to one another? (2) Which competitive positioning variables have the greatest effect on performance? and (3) How do early and late entrants differ in terms of their competitive positioning variables and overall performance? The key constructs considered were: (1) R&D intensity: ( 2 ) advertising intensity: ( 3 ) therapeutic market diversification: (4) therapeutic differentiation: (5) spatial strategy: (6) outlicensing: (7) internal Rab efforts: and (8) new product development efforts. Performance was measured with respect to two indicators: global and domestic market share. Based on a review of the new product deve10pment, innovation , and strategic marketing literature , twenty hypotheses were proposed and tested using 808. Findings from this study suggest that the timing of entry is not a random or independent variables but rather, is part of the firm's entry strategy. The following factors are fundamental for success in the industry: an emphasis on product innovation: looking beyond the U.S. market as a source of sales: maintaining strong commitments to.R&D: and focusing and exploiting internal R&D competency. Late entrants must address how they can overcome competitive advantages achieved by early entrants: (1) higher quality and differentiated products: and (2) stronger new product development efforts. Since the direct relationship between new product development efforts and late entrants' performance is negative, electing to concentrate their RED and marketing efforts on NCE development may be detrimental to this group of firms' performance in the long run. Findings suggest that they should focus instead on less innovative product development efforts. In addition, late entrants also need to commit more resources to their advertising efforts. Superiority in this marketing activity will spell the difference between success and failure for many products in the future as the market continues to be filled with similar chemical entities. A strategy that is recommended for late entrants is to concentrate RED efforts on one therapeutic market at a time. This strategy will produce a niche until the resources become available to permit an assault on another niche. This niche- by-niche strategy will allow global exploitation of their products more successfully despite being "technological followers." Overall, firms identified as early entrants are doing what is necessary to maintain market share advantages: they offer innovative products which provide further opportunities for product advantages and differentiation. However, they need to be more selective in their choice of therapeutic markets. Since the development of highly innovative products involve greater uncertainties and riskiness, management must ensure that these projects should only be undertaken when there is a good match between the resource base of the firm and the needs of the project. Firms should also identify opportunities in a certain therapeutic market by comparing its relative market size and degree of unmet needs as well as evaluating the competitive intensity and diversity of approaches in the research area. These criteria will help early entrants employ their RED and marketing resources more effectively. Although this study was limited to a single industry, insights obtained on the relationship between strategy and performance may have implications for other high technology industries. Copyright by POE-LIN YEOH 1992 ACKNOWLEDGEMENTS The success of a dissertation depends on the contributions of many persons. I would first like to gratefully acknowledge the guidance of Dr. Tamer S. Cavusgil whose extensive support, criticisms, and comments critically shaped the present research: and the other members of my dissertation committee : Dr. Robert Mason, Chairperson of the Marketing Department, who took the time to share his thoughtful criticisms and suggestions: Dr. Roger Calantone who devoted a lot of his time to introduce and help me with the methodology section of the research, and Dr. Tom Page who made invaluable criticisms at various stages of the research. To all of you, I say thank you. A special acknowledgement must be given to the Upjohn Company who generously permitted me to access their library materials, and to Mr. John Hornick who provided valuable insights into the complexity of competition in the pharmaceutical industry. I also wish to acknowledge the support of a special friend, Mr. Hakan Saraoglu, who has been a constant source of encouragement in my moments of doubt and frustration. Finally, I would like to especially thank my parents, Mr. and Mrs. Yeoh Sang Choon. Without their encouragement, sacrifices, love and support, this work would not have been possible. Because they were the basic motivation behind this work, I dedicate this dissertation to them. vi TABLE OF CONTENTS Page LIST OF TABLES0000000000000000000 ...... 0000000000.... x LISTOFFIGURES00.00.000000000000.00.000.00000000000. Xiii CHAPTER ONE-INTRODUCTION............................. l 1.1 Motivation For The Study...................... 1 1.2 Uniqueness of the Pharmaceutical Industry..... 7 1.3 Scope of Research............................. 9 1.4 Purpose of Research........................... 13 1.5 Expected Contribution of the Research......... 15 1.6 Organization of the Research.................. 19 CHAPTER TWO-THE U.S. PHARMACEUTICAL INDUSTRY......... 21 2.1 Historical Development of the Drug Industry... 21 2.2 Origin of the Major Drug Firms................ 23 2.3 Expansion Strategy............................ 25 2.4 Environmental Trends in the U.S. Pharmaceutical Industry................ 27 2.4.1 Economic Environment................... 27 2.4.2 Political Environment.................. 43 2.4.3 Trends in the Technological Environment.......................... 51 2.4.4 Trends in the Social Environment....... 59 2.5 Globalization of the Pharmaceutical Industry............................. 73 2.6 Conclusion.................................... 73 vii CHAPTER THREE-REVIEW OF THE LITERATURE................. Structure-Conduct-Performance (SCP) Paradigm.... Action Sets..................................... Resource Allocations/Commitments................ Firm Performance................................ Competitive Positioning Components..............v 30501 Timing Of Entry00000000000000000000000000 3.5.2 Means of Competition - Competitive Position in R&D and Marketing............ 3.5.3 Source of Innovation and Firm's Competitive Position in R80.............. 3.5.4 Therapeutic Market Diversification....... 3.5.5 Therapeutic Differentiation.............. 3.5.6 Spatial Strategy......................... Co nclusion...................................... CHAPTER FOUR-HYPOTHESES AND RESEARCH DESIGN............ 4.1 4.2 4.3 4.4 4.5 4.6 Variable Definition............................. 4.1.1 Competitive Positioning Variables........ 4.1.2 Variables Measuring Performance.......... An Overview of the Data Bases Used in the Study of Competitive Positioning Strategy..... Sample Selection................................ Research Hypothesis............................. Methodology..................................... 4.5.1 Description of EQS....................... 4.5.2 Assumptions.............................. Conclusions..................................... CHAPTER FIVE-RESULTS.00000000000000.0000000000000000000 5.1 5.2 Identification of Early and Late Entrants....... Comparison Between Early and Late Entrants...... 5.2.1 Equivalence of the Structural Models - Assessment of Input Data and Statistical Assumptions.................. 5.2.2 Assessment of Overall Model Fit.......... 5.2.3 Assessment of Pit of Internal Structure.. 50204 Multiple Group Analysis 0.000000000000000 smaryOfFind1n98000000000000000eoooeeoooeoooe 75 76 79 81 82 86 87 100 107 117 118 120 134 125 125 125 135 135 137 140 152 154 157 167 168 168 170 173 176 176 187 191 con01u81ons0000000000000000.00.000000000000000000 192 viii CHAPTER SIX-CONCLUSIONS0000000000000000000000000.000000 601 DiscuSSion Of Results00000000.000000000000000000 6.1.1 Relationships Among the Competitive Positioning Variables.................... 6.1.2 The Influence of Competitive Positioning 0‘01 0 0 UN Variables on Performance................. Limitations of the Study........................* Contributions of Research....................... 6.3.1 Theoretical and Empirical Contributions.. 6.3.2 Managerial Implications.................. 6.4 Suggestions for Future Research................. LIST OF REFMCES...000000000000000.000000000000000000 APPENDICES Appendix A Appendix B Sub-Categories of Drugs................. Mathematical Derivation of Normed and Mon-normed Fit Indices.................. ix 198 198 198 205 211 213 213 216 221 224 246 248 Table 2.1 2.2 2.13 LIST OF TABLES Origins of Selected Pharmaceutical Companies.... Mergers and Acquisitions Within the U.S. Drug IndustrY' 1960-1990000000000000000000000000 Acquisition of U.S. Drug Firms by Foreign companies, 1971-199000000000000000oooeeeeoeeecoo Sales of Prescription Pharmaceuticals by Therapeutic Classes, 1976-1991................... Concentration Ratio for the Pharmaceutical Industry, Selected Years, l963-l982.............. Herfindahl-Hirschman Index Values for the Prescription Pharmaceutical Industry, 1978-19860000000000000000.00000000000000000000000 Concentration in the Therapeutic Classes, 1963-1982000000000000000000.0000000000000000...00 Market Share Rank Turnover of Top Ten Firms in Each Therapeutic Class, 1963-1982................ Comparison of Concentration Evolution and Changes in Market Share Rank Turnover in Each Therapeutic Category Between 1963 and 1982................... New Chemical Entity Drug Introductions to U.S. Markets, 1940-19860000000000.00000000000000000000 Concentration of Innovational Output in the U.S. Ethical Drug Industry0000000000000000000000000000 Research and Development Costs Per NCE Drug : Before and After 1962 (in millions of 1980 dallar8)000000000000.00.00000.0000000000000000... Average R50 Cost for a Sample of 37 NCEs by Therapeutic Category, 1963-1975 (in millions or1967d0116r80000000000000000000000000000000000 Selected Examples of Joint Ventures and Long -term Ran Contracts Between Pharmaceutical Firms X Page 24 28 29 33 35 36 38 41 42 48 50 52 54 3.5 4.1 4.2 4.3 and University Laboratories..................... Selected Examples of R&D Collaborations Between Pharmaceutical Fims0000000000000000000000000000 Patents Issued in the U.S. Pharmaceutical Industry, 1963-1986000.0.00000000000000000000000 Total Prescriptions, Drug Expenditures, and Drug Expenditures as a Proportion of the Total Health Care Costs (in millions of 1967 dollars)........................................ Percentage of U.S. Population Age 65 and Above000000000000000000000000000000000000000 Contribution of Third-party Payments to Drug and Total Health Care Expenditures.................. Top 30 Pharmaceutical Companies' Worldwide Sales, Market Shares, RSD Expenditures, and Detail Force, 19880000000000.000000000000000...00000000 Leading Pharmaceutical Companies : Worldwide Distribution of Corporate Sales, 1980 and 198800000000.00000000000000000000000000 Postmarketing Experience in Diuretics : Number of Single Entity Follow-on Brands Marketed and Their “arket Share in 19690000000000.0000000 Returns to Pharmaceutical RED................... Cumulative Number of Drugs, Developed Both In-house and by Licensing, Top 50 Pharmaceutical Fins, 19890000000000000000000000 Licensed versus Self-originated Drugs Sold by U.S. Firms, Stratified by Firm Size............. Summary of Research Questions................... Measures Used in the Study...................... Drug Firms in the Study Sample.................. Sales of U.S. Prescription Pharmaceuticals by Therapeutic Categories, 1976-1991, in Millions Of dallar8000000.0000000000000000000000000.00000 Expected Direction of Hypothesis for Early and Late Entrants.0.00000000000000000000000000000000 xi 56 57 58 61 63 64 67 69 91 104 113 115 123 127 139 140 150 5.4 5.5 5.6 5.7 5.8 5.9 5.10 The Structural Equation Model Set................ Procedure to Identify Early and Late Entrants... Identification of Firms Into Early and Late EntrantSoooooeeooeoooooeooooooeoeeeoooooeee T-Tests of Difference in Means Between Early and Late Entrant800000000000000000000000000.0000" Skewness and Kurtosis (Early Entrants).......... Skewness and Kurtosis (Late Entrants)........... Correlation Matrix for Early Entrants........... Correlation Matrix for Late Entrants............ Goodness-of-Fit Indices for Early Entrants...... Goodness-of—Fit Indices for Early Entrants...... Structural Parameter Estimates for Early Entrants00000000000000000000000000000000000.0000 Structural Parameter Estimates for Late Entrants00000000000000000000000.0000000000000000 Direct, Indirect, and Total Effects for Perfomance00000000000000000000000000.0000000000 Lagrange Multiplier Results..................... xii 157 169 171 172 175 175 177 178 179 179 181 182 188 192 LIST OF FIGURES Figure Page 1.1 Schematic Difference Between Perceptual Positioning and Product Positioning............. v 4 102 8881c Entry Strategy “0661000000000000000.000000 11 1.3 Product Market Positioning : Conceptual Framework000000000000000000000000000000000000000 14 2.1 Drug Development and Approval Process........... 46 2.2 Comparison of R&D Expenditure Growth and Health Care Product Sales for 20 Major Pharmaceutical Fins, 1985-198800000000000000000000000000000000 72 401 Hmth681zed causal ”“6100000000.00000000000000 149 xiii CHAPTER ONE INTRODUCTION 1.1 W31! In the strategic management literature, strategy often is defined as (1) the set of activities involving the analysis of perceived environmental opportunities and constraints, ( 2) the development of organizational capabilities, and (3) the evaluation of present and proposed organizational strategies and their potential to create and sustain competitive advantages and economic rents (Cool 1985). Strategic marketing is very similar to strategic management, that is, it also is concerned with management of the organization-environment interface and with coordination of the marketing mix decisions to create long-run competitive and consumer advantages. There is, however, a fundamental difference between strategic management and strategic marketing (Wind and Robertson (1983, p. 12): larketing strateqy's difference is that it serves a boundary role function between the fir: and its custolers, coapetitors, and other stakeholders. Marketing develops strategy based on analysis of consulers, carpetitors, and other environrental forces which then should be coabined with other strategic inputs (such as financial, Rib, and hulan resources) to arrive unmimEnmedhsmussHMsy. 2 Achieving and sustaining competitive and consumer advantages have emerged as the cornerstones of strategic thinking, and a focus on strategic marketing has become a means of attaining these goals. Particularly, the emphasis on competitive advantage raises a variety of questions, for example: (1) What are the firm's core products and markets? (2) What.new'product.markets should the firm.enter? (3) Should a firm be in a particular product market? (4) How should resources be allocated among product markets? In the pharmaceutical industry, product markets can be classified into different therapeutic categories, such as nutritional, pain control, internal medicine, mental health, topical, antiinfectives, respiratory, and cancer. These major categories can be divided into therapeutic classes and further subdivided into subclasses. Hypertension exemplifies a therapeutic class within the cardiovascular category. To treat hypertension, several subclassess of drugs can be used, such as beta-blockers, calcium-channel blockers, ACE inhibitors, and diuretics. Similar to market segments, therapeutic subclasses can be viewed as a set of products with similarities according to the diseases or conditions treated and the character of treatment. Kemp (1975, p. 257) argues that drugs belonging to a particular subclass [tend to have] "similar therapeutic properties, not similar chemical structures, even though products of the same subclass frequently are chemically similar." 3 Once the firm has chosen the choice of product markets to serve, it then must decide on how to position itself against other competitors in those markets. In this study, the concept of positioning is different from that which is common in the buyer behavior literature (for example, Aaker and Shansby 1982: Arabie et a1. 1981: Shocker and.Srinivasan 1979: Wind 1973). Dimingo (1988) notes that the literature often does not distinguish clearly between psychological or perceptual positioning and product market positioning. The schematic difference between the two concepts is shown in Figure 1.1. Perceptual positioning is often viewed from a buyer perspective. Six approaches to a perceptual positioning strategy are proposed by Aaker and Shansby (1982): positioning by (1) attribute: (2) price-quality: (3) use or applications: (4) product user: (5) product class: and (6) competitor. In general, perceptual positioning is defined as an attempt to move a product/brand to a particular location. within a perceptual product space (Dillion, Domzal, and Madden 1986). The key factor is to develop a product/brand positioning program congruent with the psychological meaning that consumers associate with the product or brand. Perceptual positioning is a key concept in marketing and communication strategies, and various quantitative research tools have been employed to provide information about consumers' evaluations of products. Examples include multidimensional scaling (Ness Figure 1.1 Schematic Difference between Perceptual and Product Positioning Developingldeaof TARGET PERCEPTUAL PRODUCT POSITIONING POSITIONING 5 1986) and conjoint analysis (Greene and Nkonge 1989). Psychological positioning is an outgrowth of product market positioning. In other words, the success of psychological positioning strategies depends on “ the information uncovered in the market positioning process, that is, a clear identification of the target markets and how they react to various strategies. Psychological positioning "involves forging a distinctive product or corporate identity based on the market positioning factors and then using the tools of communication to move the [consumers] toward a buying decision" (Dimingo 1988, p. 35). Market positioning is viewed from the perspective of the marketer. It is the process of identifying and selecting target markets with business potential, targeting vulnerable competitors, and devising a strategy to compete with them (Dimingo 1988). As noted by Abell (1975), differences in firms’ skills, resources, and historical perspectives as well as differences in product markets require firms to adopt different postures in their positioning strategies. This type of positioning is quite similar to Aaker and Shansby's (1988) discussion of positioning with respect to a competitor, although they were concerned with how this positioning strategy can be exploited in an advertising contexts For this study, the following definition of competitive positioning is employed : 6 Competitive positioning is the pattern of decisions in a company that defines the range of product markets to compete in and in a way that focuses the company's resources to convert distinctive competencies into competitive and buyer advantages. As such, competitive positioning has a high degree of overlap with business strategy1 and should be viewed as an integral part of business strategy. The present study is concerned with competitive positioning strategy within the U.S. pharmaceutical industry. An extensive review of the literature revealed limited empirical research on pharmaceutical firms’ competitive positioning strategies. The basic objective of this research is to help fill this gap by addressing three pertinent issues. (1) How do pharmaceutical firms choose to compete in terms of their competitive positioning strategy? (2) Do different market positioning strategies have varying degrees of success? (3) How do these strategies influence firm performance? The remainder of this chapter is organized into five sections. The first briefly discusses the uniqueness of the pharmaceutical industry and why it offers an opportunity for the study of market positioning strategies. The second highlights the scope of the research. The third reviews the purpose of the reSearch. The fourth discusses the expected contribution of the research from both a managerial and 11 distinction often is Iade between corporate strategy and business strategy. the toner deals with the line of business in which a fir: should participate, while the latter addresses how the firl should colpete in each line of business in which it participates. 7 academic perspective. The final section gives an overview of the organization of the dissertation. 1.2 W The high level of R&D investment in sophisticated technologies places the pharmaceutical industry among the leading technology-driven industries. All such industries share certain characteristics: 1. A rapidly changing technological environment in which products are sold. 2. Global competition in many areas of product discovery, development, and commercialization. 3. High investments in research and development (R&D), both absolutely and as a percentage of sales. 4. A higher proportion of technical professionals in the workforce, such as scientists, engineers, and technologists, compared to other industries. Certain other characteristics are unique to the pharmaceutical industry.2 First, there is a long lead time for drug discovery and development. Second, significant R&D expenses are incurred. All research-based drug companies depend on new ethical drugs for economic success, and in this area pharmaceutical firms compete vigorously. R&D plays a key role in the drug firm’s success because (1) there is a high dependency on a very large cash flow from a small number of drugs, usually three or four, (Thomas 1988: Spilker 1989) to recoup funds spent on unsuccessful drugs: (2) revenue from 21 fuller description of each of these characteristics is provided in Chapter two. 8 successful drugs is used to offset declining margins on older drugs whose patents have expired and which have been imitated and marketed as low-price generic drugs: and (3) higher RED allocations may lead to drugs superior to those of the competition (Murray 1989). Third, the U.S. drug industry is extensively and rigorously regulated by the federal government. The constraints imposed by the Food and Drug Administration (FDA) are a key difference between the pharmaceutical industry and other high-technology industries. Fourth, the industry supplies its products and technologies in a complex industrial goods market (Roberts 1981) in which medical practitioners serve as intermediaries between the manufacturers and ultimate end-users. Therefore, much of the marketing effort tends to be directed at physicians and pharmacists rather than the customers. These unique features of the pharmaceutical industry raise a variety of questions pertaining to firms' competitive positioning strategy which have yet to be addressed in the literature. For example, since there is a considerable lead time from drug development to approval, do firms that license- in their drugs perform better than firms that develop their own drugs from internal R&D? Does the stringency of FDA regulations lead U.S. firms to introduce their products overseas? If so, how does this affect firm performance? To the extent.that.there is high brand loyalty among physicians, 9 do early entrants consistently outperform later entrants into particular product markets? Product innovation is universally recognized as a key component in corporate strategy in technology-intensive industries and is assuming an increasing importance (for example, Cooper and Kleinschmidt 1987: Moore 1987: Urban, Hauser and Dholakia 1987). Firms also must decide on the types of product markets to enter and how to compete in those markets. (Day 1986: Roberts and Berry 1987). The research- intensive pharmaceutical industry provides an opportunity to examine these decisions. 1-3 W Once the firm has targeted one or more product markets in which to compete, the next critical step is to identify the distinctive competencies that will allow the company to compete vis-a-vis its competitors in the selected markets. Day and Wensley ( 1988) identified two areas of potential distinctive competence for an organization: superior skills and superior resources. Superior skills arise from the ability to perform certain functions more effectively than competitors: for example, superior technical skills can allow a firm to produce a better quality product than its competitors. Superior resources are tangible factors that enable a firm to develop an advantage over its competitors such as an established brand name. To capture the two underlying dimensions proposed by Day 10 and Wensley (1988), three variables are considered in this research : (1) means of competition, that is, the type of approach (internal development versus externalization) and the level of resource commitments: (2) market entry timing, that is, whether the firm should attempt to be the pioneer, an early follower, or a late entrant: and (3) geographical scope, that is, the location of target markets in which to compete. The means of competition reflects the competitive advantage, while the other two variables relate, respectively, to the firm's advantage over competitors by being first in the market and by adopting a global strategy. The timing of entry and means of competition variables were formally addressed by Day (1986) in his discussion of entry into new markets. Using Day's framework, Green and Ryans (1990) empirically tested the relationship between entry strategy and firm performance using the Markstrat simulation. Their conceptual model is shown in Figure 1.2. In addition to studying the effect of entry strategy on performance, they attempted to study the effects of product-market characteristics on performance. All but one of their hypotheses about the relationship between entry strategy and performance were supported. 1.3.1 We There are three level of analysis at which this study 11 Figure12 Basic Entry Strasgy Model ENTRY STRATEGY QARKB’ CONDITIONS - Tming of Entry - Magn’uude of Invemments - Areas of Competitive Advantage Soups : DonnaH.GreenmdA.B. Ryans (1990), 'EMy Strategies and Market Pertomwne:0awalModelhgotaBusimShUfiion.'Jounal otProductlmovaionManagemem7(3),45-8. PERFORMANCE 12 could be conducted. At the MM, the objective would be to determine how firms position their products in specific market segments. Product management studies have tended to concentrate on this unit of analysis (Rubenstein et a1. 1976: Maidique and zirger 1984: Cooper and Kleinschmidt 1987). The most publicized research dealing with product success and failure is the British SAPPHO studies (Rothwell et a1. 1974) and NewProd studies (Cooper 1979a, 1979b). Concentrating on product success or failure does not help explain how firms organize Ran efforts over time. In addition, focusing on individual new products rather than the firm's entire new product program has been criticized by some researchers as myopic (Gold 1980). As argued by Cooper (1985b), "it is conceivable that a firm could have a steady stream of successful new products, but may lack significant new products in its portfolio," thereby jeopardizing the long- run future of a business. Although the product is a useful level of analysis from a strategic marketing perspective, it does not give an overall picture of the competitive positioning strategy pursued by each firm in the industry. At the diyisign_1gyg1, the emphasis is on how a certain segment of the firm positions itself in the industry. When a firm has several divisions, however, each competing in the same or different markets within the same industry, the identification of the firm's positioning strategy at this level of analysis is tenuous. It is not uncommon for l3 pharmaceutical firms to have both ethical and generic drugs that compete in the same therapeutic classes. Since this study is only concerned with ethical drugs, using the division as the unit of analysis could make it difficult or impossible to differentiate results. Analysis at the fiizm_leye1 permits a more representative assessment of the strategy pursued by each firm in the industry considered, 'This is the level of analysis used here. By focusing on this level, consideration can be given to such strategic questions as: (1) Does the firm need to change its positioning strategy? (2) Should the firm increase its R&D.and marketing spending? (3) How is overall firm performance affected by its competitive positioning strategy? 1.4 W This dissertation is concerned with the relationship between competitive positioning strategy and overall performance of firms in the U.S. pharmaceutical industry. A systematic relationship is posited between the two variables. The conceptual framework that guides the research is shown in Figure 1.3. This study deals only with successful entry by firms into the various therapeutic categories. Given that the standard duration of research on a pharmaceutical product is 10-15 years, high failure rates are not unusual as the drug goes through the FDA approval process (see p.46). Since very few of these product failures are fully documented, it is 808% Ema mic... 89.82 Hanoi 869mm 15 easier to examine successful products than unsuccessful ones. Therefore, products that have failed to enter product markets for various reasons will not be considered. Three major research questions are of interest: (1) How are the competitive positioning variables causally related to one another? (2) Which competitive positioning variable have the greatest effect on performance? What is the relative importance of these direct and indirect effects? (3) How do early and late entrants differ in terms of competitive positioning variables and overall performance? 1-5 W This dissertation builds on two major studies. The first, an empirical analysis by Bond and Lean (1977) examined two prescription drug markets. It attempted to demonstrate how the order of entry and the circumstances surrounding entry affected brand sales, promotion, and product differentiation in the diuretics and antianginals therapeutic submarkets. The present research attempts to extend their findings to a wider range of therapeutic markets at various stages of maturity. The second study, by Green and Ryan (1990) developed and tested a model within the simulated Markstrat environment involving only one product market and five firms. One objective of the present research is to assess whether their results can be validated. with empirical data. In the Markstrat world, a "controlled" business environment, the lack ‘of variance may not yield meaningful results even though 16 findings may be theoretically significant. This study examines "actual" data on pharmaceutical firms competing over a broader range of product markets. By building upon these prior works, this dissertation attempts to make the following contributions: (1) conceptualization of the competitive positioning strategy from a marketing perspective, (2) detailed measurement and longitudinal analysis of strategy, and (3) development of qualified insights into strategy-performance relationships of significant use to managers. This research approaches the pharmaceutical industry from a marketing perspective. Because of its prominence in the health care sector and its unique characteristics, such as the rapid rate of technological development, reliance on patent protection, and the effects of governmental regulation, the industry has been a popular arena for testing concepts and paradigms in the fields of industrial economics and policy analysis. Most articles on the marketing aspects of the industry have been descriptive in nature, although there are a few exceptions. Harrell (1972) used the Fishbein Model to determine physicians' prescribing behavior. A maximum likelihood estimation procedure was used by Bearden and Mason (1980) to study how confidence in regulation, potential savings, and effect on drug research represent possible determinants of physician and pharmacist support of generic 17 drugs. In two studies, Statmand and Tyebjee (1981, 1985) examined, respectively, the extent to which brand loyalty and patent protection influence the market position of an ethical drug and how marketing efforts of pharmaceutical firms have changed in response to the Drug Substitution Laws. Only recently has the ethical drug industry been studied from a strategic management perspective, using the strategic group paradigm (for example, Cool and Schendel 1987, 1988: Fiegenbaum, Sudharshan, and Thomas 1990): and transaction costs analysis (Tapon 1989). While marketing variables such as product competition, price behavior and advertising were considered in earlier studies, they were mainly viewed from an economic perspective. Some examples include looking at relationships between product competition and monopolistic powers (Steele 1962: Schifrin 1967): market instability (Comanor 1964), price levels and market shares (Schwartzman 1976), advertising and sales levels (Harrell 1978: Leffler 1981), and the effect of advertising on competition (Walker 1971: Schwartzman 1976: Bond and Lean 1977). The current research examines several key marketing constructs identified by past researchers as critical in influencing firm level performance. Theoretical and empirical studies from the strategic marketing and innovation literature will be used to identify these key marketing constructs. The empirical contribution of this dissertation relates 18 to two major aspects: a longitudinal versus cross-sectional analysis of the data and the methodology used. This study examines the competitive positioning strategy of U.S. pharmaceutical firms from 1971-1989. The 19-year is sufficient for a longitudinal evaluation of shifts in firms' entry strategies and any effects on performance. Due to the lag time effect between implementation of a strategy and the evaluation of how well it worked, cross-sectional analysis may be inadequate for examining strategy-performance relationships. The methodology used to model the dynamic aspects of competitive positioning strategy on performance is also a contribution of this research. Performance often is influenced by a host of factors and, testing each one is less superior than considering all in their entirety. Structural equation modelling is used here to gain insights into indirect and direct effects of the constructs shown in Figure 1.3. In addition, rather than test a single model against the data, a two-group analysis is conducted to test whether the hypothesized model is invariant between late entrants and early entrants. Finally, from a managerial perspective, competitive positioning is an important strategic issue as it provides the platform from which competitive advantage can be achieved. Although performance results from the interaction of many ‘Variables, this study attempts to identify the competitive 19 positioning strategy variables that relate significantly to And a longitudinal analysis provides a systematic way to address this task. I Although this study focuses on the U.S. pharmaceutical industry, the findings have implications for strategic marketing in any industry. Any firm needs to understand what strategies are being pursued by competitors. This information enables evaluation of the relative strengths and weaknesses of certain strategic positions and determine of how best to position the firm against its rivals so as to achieve a sustainable competitive advantage. 1.6 W This dissertation is organized in six chapters. Chapter 2 is an overview of the operating environment of the drug industry. Knowledge of the environment is necessary to understand how the industry dynamics affect firm strategies and performance and also to provide a rationale for the selection of variables in Chapter 4. Chapter 3 defines the key constructs employed in this study, drawing on relevant theoretical and empirical studies from the strategic marketing and innovation literature. This chapter concludes with a complete statement of research questions. Chapter 4 develops the research hypotheses. The operationalization of the variables and the data bases used in ‘this study are discussed. The methodology for testing the 20 hypotheses also is explained. Chapter 5 discusses the findings from the statistical analysis. Chapter 6 summarizes the findings and points out their contribution to strategic marketing research and practice. Limitations of the study and suggestions for future research also are outlined. CHAPTER TWO THE U.S. PHARMACEUTICAL INDUSTRY Major changes took place in the U.S. pharmaceutical industry during' the 1970s and 19805, and the strategic management literature suggests that adaptive strategies were a major tool used by firms in dealing with their changing environment. This study assumes that the success of a firm's strategy in the face of environmental challenge and complexity is reflected in its level of performance, although more extensive analysis is undoubtedly needed to establish the complex causal relationships among strategy, performance, and environment. In this chapter, a brief historical account of the institutional development of the U.S. pharmaceutical industry is provided, along with a review of the major developments in its market and institutional environment. Particular attention is paid to the economic, political, technological, and social events and trends that have been instrumental in shaping ‘the industry. Finally, three 'major responses in reaction to these environmental shifts are discussed. 2.1 W512! In the 19308, U.S. pharmaceutical firms manufactured a 21 22 limited number of unpatented drugs which were marketed without prescription to the consumeru Many' of the compounding functions were performed by retail pharmacists rather than manufacturers, and the pharmaceutical industry was essentially a commodity business. According to Harold Clymer (1975), R&D as such was nonexistent in most firms....it was in 1939 that I joined SmithKline: you can judge the magnitude of their R&D at the time by the fact that I was told I would have to consider the position temporary since they had already hired two people within the previous year for their laboratory and were not sure that the business would warrant the continued expenditure. Almost all of the minimal advertising was placed in newspapers and quality magazines, stressing the quality and purity of drugs, rather than their therapeutic advantages. Advances in drug therapy were minimal before the 19305. ”Passive therapy” or the vaccination method dominated until 1910 when Ehrlich's discovery of salvarsan for the treatment of syphilis marked a radical departure. His discovery opened the field of chemotherapy by demonstrating how drugs could act as "magic bullets", that is, how particular chemicals could. kill particular organisms without harming the patient. Even though Ehrlich demonstrated the opportunities available for R&D, a quarter of a century passed before the age of the wonder drugs. The discovery of sulfonamides in 1932 and the demand for drugs during World War II transformed pharmaceuticals from a 23 commodity business centered around bulk products to a technology-intensive industry characterized by very specialized and.differentiated products. Manufacturers began investing in facilities as well as RaD to exploit“ new opportunities and potential profits. At the same time, power shifted from the retail pharmacist to the manufacturers, who had assumed the compounding functions by the end of the war. The mass production of penicillin in 1942 further stimulated the development and large-scale production of therapeutic discoveries, particularly broad-spectrum antibiotics, hormones and vitamins. Intensified innovation resulted in the introduction of more than 700 new drugs between 1940 and 1960. These extended to new therapeutic categories as well, such as cardiovascular, steroids, oral contraceptives, and tranquilizers which did not exist prior to the 19508. Further developments included the discovery of specific chemical agents capable of acting upon certain parts of the body and upon the diseases each part contracted within these therapeutic classes. Both patent protection and brand name promotion further allowed manufacturers to maximize the commercial exploitation of their discoveries. The period (1940-1960) often is called the Golden Age of Discovery. 2.2 9:11 gin 9f the uajgr Drug Finns As shown in Table 2.1, the major U.S. drug firms Originated as pharmaceutical supply houses. In contrast, 241 Table 2.1 Origins of Selected Pharlaoeutical Corpanies Date of Origin Colpany Hone Country (1) miginal Activity : Pharnaceutical Supplies 1618 Ii. llerck Genany 1715 Glaxo United KinngI 1817 Boehringer Ianhein Ger-any 1828 Slithfline United States 1851 Schering 1.6. Ger-any 1855 Sterling Drugs United States 1353 Squibb United States 1860 herican none Products United States 1866 Warner Hubert/Parke Davis United States 1876 s11 Lilly United States 1880 Richardson-Herrell United States 1885 Upjohn United States 1885 Boehringer Ingelheir GerIany 1886 iiellcoae United Kingdol 1887 Bristol-Myers United States 1888 Boots United Kingdon 1888 Searle United States 1906 Lederle United States 1913 Astra Sweden 1923 Organon letherlands 1927 Derek 8 Co. United States 1929 Schering Plough United States 1944 Syntax (originally llexico: since 1958, PM) (2) (kiginal Activity : Dyestuffs 1758 Ciba-Geigy Switzerland 1812 lloechst Ger-any 1848 Pfizer United States 1863 Bayer Gerlany 1884 Iontedison Italy 1886 Sandor Switzerland 1888 Abbott United States 25 Table 4 .1 continued Date of Origin Company Hone Country 1890 Horton-Norwich United States 1895 Don United States 1896 Hoff-an La-Rocbe Switzerland 1911 M80 Netherlands 1926 ICI United Kingdon W = Jam Barrie (1977). W W. New York = John Wiley and 801:8. Appendix 4. 26 their European counterparts, which were established earlier, had origins in organic chemicals and dyestuffs. The first wonder drug, Salvarsan, was developed in 1910 in the laboratories of the chemical group 1.6. Farben industries (Bayer division) of West Germany. 2.3- W During the 1960s and 1970s, U.S. drug firms began expanding into related areas, such as agricultural chemicals, cosmetics, and medical equipment and diagnostic aids. These businesses provided potential synergies with the firms’ traditional products. Because of the transferability of knowledge from the development of chemical drug compounds to chemicals for agricultural purposes, many drug firms entered the agribusiness field. Examples include Eli Lilly, Merck, Pfizer, Syntex, and Upjohn. Experience in consumer goods marketing also prompted entry into the cosmetics industry. For example, Pfizer bought Coty in 1963, and Eli Lilly purchased.Elizabeth Arden in 1971. The medical equipment and diagnostic aids industry was a likely extension for two reasons. Hospitals, the major customers for these products, were already major purchasers of drugs, and these devices were regulated by the FDA, with.which drug firms already had developed extensive experience. Firms active in this line of business include Syntex, SmithKline- Beckman, and the Rorer Group. 27 Expansions also occurred within the drug industry, mainly through acquisitions and mergers. Table 2.2 lists the major activity from 1960-1990. In the latter part of the 19803, notable acquisitions were made by Kodak (Sterling Drugs) and American Home Products (Robins). In 1989, there were several large mergers, SmithKline with Beecham, Merrell Dow with Marion and Bristol-Myers with Squibb. Another major trend has been the acquisition of U.S. firms by foreign companies. Notable purchases are listed in Table 2.3. The attractive opportunities provided by the U.S. market have made it a favored regional area of expansion for British, German, and Swiss drug firms. In summary, the ’chemotherapeutic' revolution of the 1940s transformed the drug industry from a commodity business to a technology-intensive industry. Whereas European companies entered the drug industry as chemical concerns, U.S. firms originated as drug supply houses. The significant mergers and acquisitions in recent years suggest that worldwide consolidation may lead to the domination of the industry by a dozen companies by the year 2000. Different aspects of the operating environment of the pharmaceutical industry are highlighted in the next section. Economic, technological, political, and social aspects are emphasized. 2.4 W 2-4-1 W 223 nmzzmmnmmmMmmmnmmmm Industry, 1960-1990 I . . E. Abbott Anerican Hole Products Beecbal Bristol Myers Kodak Harrell Dov Procter and Galble Schering Uarner-Lanbert 3! Source : Annual reports. . I I E' Ross (1964), Sorenson Research (1980) Robins (1988) SIithKline (1989) lead-Johnson (1967), vestuood (1969), Squibb (1989) Allied Labs (1960), Richardson-Herrell (1981) Sterling Drugs (1988) Marion (1989) lorvicb-Baton (1982), Richardson-Picks (1985) Plough (1911) Texas Pbanacal (1967) , Parke-Davis (1970) Riker (1970) Conpanies, 1971-1990 mm Bayer (Ger-any) Beechal (UK) Boehringer-Ingelhein (Gerlany) Boots (U.K.) Ciha Geigy (Switzerland) Glaxo (U.K.) Ilperial Chelical Industries (ICI) (0.11.) Mestle (Switzerland) SQUID: : Annual reports. 25) Table 2.3 Acquisition of U.S. Drug Pirls by Foreign Assured Cutter (1973), Done Labs (1978), Miles Labs (1978), Cooper (1980) Massingill (1971) Hexagon (1975), Philips Roxane (1979) Riker (1977) Alza (1977), Tutag (1978) Meyer Labs (1977) Stuart Pharlaceuticals (1971) Alcon (1977), Lafayette Pharlaceuticals (1978) 30 Various aspects of the economic environment are reviewed below. To understand competition in the pharmaceutical industry, it is necessary to define different industry segments. The effects of seller concentration on the industry as well as on the various therapeutic classes then are analyzed. 2.4.1.1 W The pharmaceutical industry has three major market segments, each with its own form of competition : ethical (prescribed) drugs, proprietary (non-prescribed) drugs, and generic drugs. Ethical drugs are patented and sold primarily through prescriptions. Advertisements are directed to the medical and pharmacy professions only. Patented drugs were the driving force of the modern pharmaceutical industry and accounted for the spectacular sales growth after 1940. Competition in this segment exemplifies the "creative destruction" described by Schumpeter (1975). The result was revolutionary treatment and prevention of disease through the discovery of new patented therapies to replace existing ones and the application of new technologies to drug discovery processes. Branded prescription drugs eventually become either proprietary or generic drugs. Proprietary drugs, more commonly known as over-the-counter (OTC) drugs, are sold directly to consumers without prescription and usually are 31 to OTC status. Advertising and other promotional efforts are key competitive strategies used by the original manufacturers to exploit the advantage of brandname recognition in this segment. Generic drugs generally are those which have lost patent protection and can be manufactured by any firm. Within the generic class, a further distinction can be made between branded and commodity generics. For example, acetaminophen, the generic name of the drug marketed by McNeil as Tylenol, is no longer protected by patent, can be made by other manufacturers, and can be sold under its generic name, making it a commodity generic. Only McNeil can sell acetaminophen under the branded generic name Tylenol. Competition in the generic drug segment follows closely the neoclassical model. There are numerous sellers and buyers, and price competition dominates. Unlike primary drug producers, generic manufacturers do not incur heavy RaD or advertising costs and do not engage in the lengthy FDA approval process. The desire to control health care costs has led many governments to encourage substitution of brand name drugs with generics. Specifically, the repeal of antisubstitution laws and the passage of the 1984 Drug Price Competition and Patent Restoration Act have encouraged greater generic competition in the United States. The loss of market share of branded drugs by generics occur gradually after the patent of a pioneering brand expired (Statman and Tyebjee 32 1981) , but a recent study found that generics achieve an average unit market share of 49 percent within two years of entry (Grabowski and Vernon 1989). In addition to the three market segments noted above, .two other distinctions made in the industry should be mentioned: whether ‘the drugs are single-source or :multi-source and whether drugs are for acute care or for maintenance purposes. W- Single-source drugs are those available only from one supplier. Although multi-source drugs generally are equated with generics, a patented holder may license out a drug to other firms, a strategy often used to prevent a competitor's brand from gaining market share dominance. W. A distinction is made in the industry between acute and maintenance drugs. The first type treatment diseases which can be cured within a short, period, anti-infective drugs are an example. Maintenance drugs are intended for chronic diseases, examples are cardiovascular and cancer drugs. The upward trend in sales of maintenance drugs is evident in Table 2.4. Since chronic diseases imply a longer period of medication, the market. potential for’ maintenance drugs is much. greater, ceteris paribus than for acute drugs. In addition, because maintenance drugs are characteristically repeat purchases, a certain sales volume can be achieved on a smaller per capita basis than is the case for acute drugs. 323 Table 2.4 Sales of Prescription Pharlaceuticals by Therapeutic Classes, 1976- 1991 Therapeutic Classes 1976 1981 1984 1985 1986 1991 Cardiovascular 1,035 2,100 3,565 4,150 4,695 7,550 Antiinfective 1,185 1,770 2,725 3,000 3,510 5,150 Internal Medicine 1,495 2,310 3,095 3,400 4,025 5,400 Pain control 785 1,560 2,070 2,305 2,610 3,190 Respiratory 480 730 760 900 1,060 1,375 lutritional 435 725 1,310 1,365 1,430 2,000 Topical 320 590 900 990 1,065 1,250 Mental health 935 1,150 1,790 2,070 2,275 3,025 Other 330 965 1,735 1,900 2,120 2,850 Total 7,050 11,950 17,950 20,030 22,840 31,790 Source : Arthur D. Little Decision Resources (1988), 'Sales of Prescription Phanaceuticals to 1991,‘ W, 1-4. Mote : A full description of the therapeutic classes is shown in Appendix A. 34 In.conclusion, there are several ways to segment the drug market: ethical versus proprietary versus generic drugs, single—source versus multi-source drugs, and acute versus maintenance drugs. 2.4.1.2 WW There are two areas of concentration in the U.S. pharmaceutical industry: among sellers and in various therapeutic classes. Seller_ggnggntza§ign. The concentration ratio is often used as a summary measure of the size and distribution of firms in an industry. Based on the value of shipments, it is constructed by relating the size of the largest sellers in the market to overall market volume. Statistics collected by the U.S. Bureau of the Census rank the pharmaceutical industry in the bottom 40 percent among a total of 450 industries. Table 2.5 lists the concentration ratios for the four and eight largest pharmaceutical firms. Both indicators show that concentration remained fairly stable and low over 20 years. Another measure of concentration is the Herfindahl- Hirschman Index (HHI),’ which often is used as an indicator of market power for antitrust purposes. In examining merger activity, a value greater than 1,000 would suggest a high level of market power in an industry. Table 2.6 shows the HHI 3The 11111 is conputed by squaring the narket share for each firn, expressed in percent, and sunning the result. The sun is then nultiplef by 10,000 to express the 1181 index in whole nunbers. 355 Table 2.5 Concentration Ratio for the Pharnaceutical Industry, Selected Years, 1963 - 1982 Percent of values of indtstry shipnents accounted for by: Munber of Four largest Eight largest Year firns conpanies conpanies 1963 1,011 22 37 1967 875 24 40 1972 756 25 43 1977 756 25 41 1982 683 26 41 Source : U.S. Bureau of the Census (1986), W, Concentration Ratios in Manufacturing, MC77(SR) -9, Washington, D.C. 236 Table 2.6 Uerfindahl-Uirschnan Index Values for the Prescription Pharnaceutical Industry, 1978-1986. Year Index Value 1978 440 1979 453 1980 446 1981 439 1982 414 1983 411 1984 394 1985 368 1986 342 Source : Pharnaceutical Manufacturers Association, internal_|engrandun 37 index in the prescription (Rx) pharmaceutical industry for selected years. The figure is less than half the usually accepted value, and the RBI has declined steadily in the last decade. WW It has been argued that the use of four- and eight-digit concentration ratios are too broad. Meadsay (1977, p. 279) states : In short, concentration ratios for the pharnaceutical industry as a whole convey a sonevhat nisleading inpression of the industry, although they are useful in the broad sense of supplying infornation on the nunber and approxinate size distribution of drug firns. Tron a standpoint of the influence of industry structure on conpetitive behavior, it is necessary to go beyond the indistry-vide ratios and exanine concentration in therapeutically significant categories and in bulk drug production. On this basis, it appears that high concentration in these separate categories, rather than the noderate concentration of the entire industry, is the doninant structural characteristic. In other words, since substitutability is particular pertinent in the drug industry, a concentration measure should include demand cross-elasticities between or among therapeutic markets. Antiinfective treatments do not intersect with cardiovascular drugs, and sales in these markets should not be combined. Based on this argument, concentration and market share turnover should be gauged at the therapeutic class level. From Table 2.7 which shows the concentration ratios for the nine major therapeutic classes for selected years, two important observations can be made. First, the four-firm and eight-firm concentration ratios are significantly higher in individual therapeutic classes than when overall firm sales 383 Table 2.7 Concentration in the Therapeutic Classes, 1963-1982 Therapeutic Classes Pour- and Eight-Pin Concentration Ratios Cardiovascular C, 59.2 49.6 47.0 46.9 48.3 43.0 C8 70.9 64.3 65.9 65.8 65.1 60. 6 nutritional C, 29.2 33.2 47.1 48.7 47.5 48.5 C8 42.9 46.2 64.2 62 1 58.9 57.6 Pain Control C4 46.0 53.2 48.0 44.1 52.7 51.4 C8 64.4 70.0 72.4 68.6 74.1 70.5 Internal Medicine C‘ 36.0 31.2 29.1 28.2 31.1 38.4 C8 50 7 47.1 46.6 44.8 50.8 57.3 Mental Health C, 58.6 60.1 61.6 65.9 60.3 51.1 C8 75 3 78.5 79.5 82.0 80.2 75.4 Topical C, 28.6 35.5 36.8 36.2 31.6 38.8 C8 43.9 52.7 52.5 52.6 44.6 52.4 Antiinfectives C, 39.3 41.7 46.5 46.4 46.6 48.6 C8 60.2 66.6 68.7 66.0 63.7 65.6 Respiratory C4 35.4 41.9 45.8 43.4 38.2 35.2 C8 51.9 57.9 65.8 65.5 58 2 53.5 Cancer C4 65.7 68.0 76.3 66.8 58.9 61.6 C8 n.a. n.a. 95.8 78.0 66.7 67.5 Average C4 44.1 46.0 48.7 47.4 46.1 46.3 C8 57.4 60.4 67.9 65.0 62.5 62.3 Source: Karel C001 (1985) , 'Strategic Group Pornation and Strategic Group Shifts: A Longitudinal Analysis of the U. S. Pharnaceutical Indmtry, 1963-1982," WWW University, p. 226. 39 are considered. The average four-firm concentration ratio ranged from 44.1 percent in 1963 to 46.3 percent in 1982. The corresponding eight-firm ratio is between 57.4 percent and 62.3 pecent. ' Second, significant shifts have also occurred among therapeutic classes. As mentioned earlier, more and more firms are pursuing R&D in chronic diseases, resulting in overcrowding in a few therapeutic classes. For example, in the cardiovascular category, concentration ratios (C, and C.) have steadily declined: in the nutritional and antiinfective classes, concentration has steadily increased. Finally, other categories (pain control, topicals, and cancer) have experienced irregular ups and downs over the two decades. Table 2.7 clearly shows the dynamics of competition and illustrates the value of analysis by therapeutic classes rather than by aggregate level. A further indication of the competitive dynamics of the pharmaceutical industry can be seen by the changes in market share rank turnover in each of the therapeutic classes. Table 2.8 ranks the top ten firms in each class for 1963, 1972, and 1982 and shows the average. market share rank changes among the top ten leading firms in each class. Market share turnover obviously is affected by the entry and exit of firms. Entrants into a therapeutic class could be entirely new firms from outside the drug industry or by pharmaceutical firms with new products in that particular market. In either case, the 44) market position of existing firms is likely to change. Some interesting patterns can be observed from these two tables. Changes in market share rank turnover caused some instability in certain therapeutic classes vis-a-vis others, as can be seen in Table 2.8. For 1972 compared to 1963, the largest absolute average rank change observed was in the nutrition and topical (8.4) classes and the smallest was in mental health (5.1).‘ For the second decade, the largest and smallest changes were observed in topical (11.1) and mental health (4.4), respectively. Comparing Table 2.8 with Table 2.7, although one would expect concentration evolution and market share rank turnover to be inversely correlated, opposite patterns are observed for certain therapeutic classes. Table 2.9 summarizes the comparisons between concentration evolution and market share turnover for the different therapeutic categories between 1963 and 1982. In the mental health category, the four-firm concentration ratio declines, and.there is a negative rank,turnoveru This signals a more entrenched market position among competing firms. In contrast, the topical category was characterized by both growing concentration and a positive rank turnover, suggesting intense competition from new entrants and existing firms. ‘The average narket share rank in each therapeutic category vas conputed by taking the average of the absolute rank changes of the topten firns fron 1963 to 1972. Thesane procedure was applied for 1972 to 1982. 4fl1 Table 2.8 Market Share Rank Turnover of Top Ten Firns in Each Therapeutic Class, 1963-1982. 1. CARDIOVASCULAR Average Absolute Rank I II III IV V VI VII VIII IX x Change in Ranks Year 1963 8 24 15 18 1 7 2 3 10 13 1972 8 24 3 25 20 13 4 18 15 14 6.7 1982 3 8 24 14 10 15 25 18 13 20 9.4 2. MUTRITIOI 1963 1 7 15 17 3 2 26 11 22 10 1972 4 l 15 18 7 17 2 11 3 22 8.4 1982 4 1 24 2 15 18 20 3 11 9 8.1 3. P81! COITROL 1963 7 3 23 11 16 24 1 5 8 6 1972 7 8 3 6 23 16 24 11 1 5 8.2 1982 6 8 17 7 19 10 23 16 3 24 5.3 4. IITERIAL MBDICIME 1963 17 14 13 7 8 22 24 10 2 3 1972 17 13 3 6 14 18 7 10 15 22 7.1 1982 14 3 6 17 7 13 10 19 15 12 6.1 5. MEITAL MEALTU 1963 26 3 14 24 5 7 10 6 1 8 1972 26 8 14 10 3 24 18 6 5 7 5.1 1982 26 8 14 12 18 23 15 2 20 3 4.4 6. TOPICAL 1963 23 12 14 3 15 18 6 1 16 8 1972 18 12 15 23 3 1 6 14 8 16 8.4 1982 6 8 14 12 18 23 15 2 20 3 11.1 7. AITIIMPUCTIVUS 1963 2 10 15 7 17 26 3 4 16 9 1972 7 4 10 17 15 3 2 9 1 12 7.5 1982 7 10 4 17 8 2 1 3 26 14 5.4 8. RESPIRATORY 1963 14 12 16 11 18 24 17 7 23 3 1972 12 11 18 16 14 23 3 4 10 24 6.6 1982 12 11 18 23 4 16 24 14 3 5 8.3 9. CAICUR 1963 23 2 7 26 na na na na 1972 4 7 26 2 23 17 15 10 1982 4 7 2 23 26 17 3 8 Skmuce: Karel C001 (1985), Strategic Group Pornation And Strategic Group Shifts. A Longitudinal Analysis of the U. S. Pharnaceutical Industry, Eh,n_nissertation, Purdue University. 462 Table 2.9 Conparison of Concentration Evolution and Changes in Market Share Rank Turnover in Each Therapeutic Category between 1963 and 1982 Therapeutic Pour-fin Market share Category concentration rank turnover Cardiovascular Decline Positive lutrition Increase Megative Pain Control Increase negative Internal Medicine Increase legative Mental health Decline Megative Topical Increase Positive Antiinfectives Increase legative Respiratory Decline Positive 43 In summary, to understand the competitive dynamics of the drugs industry's economic environment, it is necessary to look beyond aggregate firm level data. Although the concentration ratios in Table 2.5 indicate stability over the last' two decades, shifts in market share rankings among the largest firms show otherwise. Because concentration levels and trends differ significantly among therapeutic categories, it is more valid and meaningful to conduct a competitive analysis at that level. Comparisons between concentration ratios and market share turnover at the therapeutic level revealed that the two do not always correlate negatively. In the next section, the political aspects of the pharmaceutical environment are discussed. 2.4.2 MW The drug industry has come under increasingly stringent scrutiny and in the United States, it is extensively and rigorously regulated by the federal government. The constraints imposed by FDA are a key distinguishing feature of the pharmaceutical sector vis-a-vis other high-technology industries. Studies by Ashford et a1. (1977), Temin (1979), and Young (1982) indicate the significant link between regulatory constraints and research productivity in this industry. Government involvement in the control of therapeutic drugs dates to the early twentieth century in the United States. Since it would be impossible to discuss all relevant 44 laws, only the most significant are noted here. 2.4-2.1 £ederal.£egnlatign Enrs_Eeed§_and_Drug;Act_LIQQ§l- The primary concern of this act was to prevent and control food adulteration and abuse: drug regulation was of secondary importance. l218_Eggd,_Dzng‘_§nd_ggsmgtig_Ag§. This was the first direct.drug regulation prompted by the exilir tragedy of 1937. It imposed better procedures for premarketing clearance in order to protect the public from untested and potentially harmful drugs. Kefauxer:Harris_Amendments_112§Zl- While the 1938 Law was significant, the testing of new drugs remained unregulated. The birth defects caused by thalidomide prompted the 1962 amendments, which established closer FDA control over the premarket testing of new drugs and altered the criteria for the approval to market new drugs. Specifically, drug manufacturers had to show proof-of-efficacy in addition to the proof-of-safety requirement, and approval hinged on the Investigational New Drug (IND) requirement for clinical testing. The major effect of the IND was to stipulate a comprehensive data on animal tests before the FDA.would allow human trials. As a result of the IND procedures, the FDA shifted after 1962 from essentially an evaluator of evidence and research findings at the end of the RED process to an active participant in the whole discovery and development process. 45 Figure 2.1 explains the various steps in the drug development and approval process. Industry experts estimate that the course from pharmaceutical research to a marketable drug averages 10-15 years and costs about $200 million: As can be seen from the chart, the attrition rate is fairly high between the time a drug is filed as an IND to the time it is finally approved by the FDA. A fuller historical description of the process is provided by Wardell (1979). W. This legislation made it easier for generic drug manufacturers to market their products by eliminating much duplicated testing and by permitting them to prove that their products were the bioequivalent of existing ethical drugs. In addition, ethical drug manufacturers were given a five-year extension to the 17 years of patent protection. 2.4-2.2 W State government actions also have affected the drug industry, most especially by repeal of anti-substitution laws. In the 1960s all states prohibited pharmacists from substituting any drug for the one prescribed by a physician: by 1981 all states, only Indiana and Oklahoma, had not repealed these. Two factors contributed to the repeal: pressure from consumer groups and third-party payers increased as health care costs spiralled, and many pharmacists wanted to assume a greater role in drug selection. .Esosouofioa accuoucfi .COwuofioommc mucusuoouzccz Hoofluzoomaucnm «QOHQOW 32— .n... mn—Z- .0A-Z— muA—Z.— mn—Z— ’23.... .59: .3 «SN .3 RBN .... earn .2 8:5 :3: a 6032:. 9.1.0.3226»: d 25.3- 53 ......33... ans-039:. )9: :6 :36:— .5553... . cute... 3 3033...?» _: 9:. ..u .. 83.... "nose: .65.»...a H m E . a . 92.33.. m .3553 fl .......:..:.=. or... 2 .N .wwmbfihwofl...aume_ .....mauwmfiuzl ...... Sign M 1.5.23.5: ...... O . ......“W....e.“_: m 3.53:. 5.3.3:. .32....3533 05.53.42 0 to...“ 3.3.2 B ..o._..:6..o.u..mu“:. 3.550.. 63:03.33“. 3:32 u::..a>m_ 352.55.: 3v»: navy-=3...) 2324.. tux—......) 3.02:.- twu::.-...a ...-:33: ‘31:; .5::..< .52....535 a...:¢::...a:.. 03:6 5. 83.. 8n a. .2: :8 G. :~ 3:: hung-3:278 3v.— Ail ... a h c n v n ~ . 9.5; .: : . Tara. 323...; <2". 0.3...- uaa._._ 9.227— €35.99..— mmoooum Ho>oumm< use unmamoHo>on mane H.~ ouzmfim 47 Conclusion. Government regulation are two-fold: removal of ineffective new drugs from reaching the marketplace and has enabled.greater participation by consumers and pharmacists in the drug selection process. Regulation has had signifiCant negative effects however, and these are discussed in the following section. 2.4.2.3 The Negative Effects of Regulation on the Drug Industrv The Kefauver-Harris amendments have been controversial since their passage in 1962. Two major negative consequences are cited: (1) a decline in RED innovation and shortened patent lives: and (2) increased concentration among larger firms. W. New chemical entities (NCEs) are drugs characterized by chemical differentiation and have therapeutic advantage over existing products. The development of NCEs is important to society and contributes to the overall growth of the industry. Between 1961 and 1980, 710 NCEs were registered by European firms, 353 by U.S. firms, and 155 by Japanese firms (Burstall, 1985). Table 2.10 gives an overview'of the total number of NCEs introduced in the United States between 1940 and 1986. The pre- and post-1962 average was 47 and 25, respectively. Econometric studies (for example, Baily 1972: Sarett 1974: Wardell 1973) indicate that regulation has depressed drug' innovation. Wardell and Lasagna (1975) also found a majority 443 Table 2.10 Mew Chenical Entity Drug Introductions to U.S. Markets, 1940-1986 Year lunber of Entities Year Munber 0f Entities 1940 14 1963 16 1941 17 1964 17 1942 13 1964 25 1943 10 1966 13 1944 13 1967 25 1945 13 1968 12 1946 19 1969 9 1947 26 1970 16 1948 29 1971 14 1949 38 1972 10 1950 32 1973 17 1951 38 1974 18 1952 40 1975 15 1953 53 1976 14 1954 42 1977 16 1955 36 1978 23 1956 48 1979 15 1957 52 1980 13 1958 47 1981 19 1959 65 1982 26 1960 50 1983 22 1961 45 1984 15 1962 24 1985 20 1986 24 TOTAL : 1,178 Source : Paul de Eaen database, various years. 49 of U.S. drug companies shifting their research efforts overseas, where regulation was less stringent. Regulatory practices are not the only factor, however, and the depletion of research opportunities has been offered as another. In a comparative analysis of drug innovation in the United States and United Kingdom (Grabowski, Vernon and Thomas 1976) found that R&D productivity had declined more in the former than the latter, but regulation explained only one- third of the decline. The remaining two-thirds of the U.S. decline was matched by a similar decline in the United Kingdom, where regulation is less stringent, an effect that the researchers state is ”consistent with the hypothesis of a worldwide depletion of research opportunities" (p. 36). Ingzgasing__ggnggntratign. Enforcement of the 1982 amendments also seems to have strengthened the position of larger firms and resulted in increased concentration (Peltzman 1974: Vernon and Gusen 1974: Grabowski et al. 1976; Schwartzman 1976). Table 2.11 confirms the trend toward firm, concentration in innovational output. Despite a decrease in the number of NCEs and firms since 1962, the four-firm concentration ratio has steadily risen. One reason for the increasing dominance of large firms is that fewer new, effective drugs are challenging the market position of older drugs._ Furthermore, larger firms have an R&D advantage because they have the financial resources to sustain long periods of product development and approval . The 50 Table 2.11 Concentration of Innovational Output in the U.S. Ethical Drug Industry Concentration ratio Total nunber Munber of firns innovational output Period of ACES having an MCE 4-firn 8-firn 20-firn 1957-1961 233 51 0.462 0.712 0.931 1962-1966 93 34 0.546 0.789 0.976 1967-1971 76 23 0.610 0.815 0.978 Source: Uenry G. Grabowski, John M. Vernon, and Lacy G. Thonas (1976), 'The Effects of Regulatory lote Policy on the Incentives to Innovate. An International Conparative Analysis,‘ in DRESS—91 WM. 5.4 Mitchellandn- Link (eds ).Vashin9t°n. :The Anerican University, p. 72. : Innovational output is neasured as MCE sales during the first three full years after product introduction 51 costs of drug development have made it increasingly difficult for smaller firms to remain in the "innovation race" (Clymer 1970). The uncertainties in pharmaceutical research also requires large financial investments which small-scale firms lack. Yoshikawa (1989) found that it takes approximately 7,000 compounds to develop one successful pharmaceutical drug in Japan while in the European Community it may take as high as 10,000 compounds to one promising new drug. anglnfiign. Two exogenous factors may account for the decline in drug innovation: stringent regulation and a depletion of research opportunities. Trends in the drug industry support the thesis advanced by Schumpeter (1950) and Galbraith (1952) that larger firms not. only are better equipped for rapid technological innovation but also achieve increasing returns to scale. The next section looks at the interface between the regulatory and technological environments. 2.4.3 WW Three important aspects of the technological environment are: the increasing cost of druglRSD and.concentration in.drug research, conservatism in mm, and foreign competition in drug innovation. 2.4-3.1 mamas Table 2.12 summarizes the results of six studies that examined the costs of discovering and developing NCEs before 52 Table 2.12 Research and Developnent Costs Per MCB Drug, Before and After 1962 (in nillions of 1980 dollars) 1980 Dollars Pre-1962 Post-1962 Baily (1972) $16.0 $ - Clyner (1972) - 56 5 Sarett (1974) 3.4 25.9 Schwartznan (1975) 3.7 48.6 Schnee (1977) 3.1 - llansen (1979) - 47.6 53 and after 1962, excluding the cost of capital. These studies clearly demonstrate the substantial increase, on average about 7 times more. Based on NCEs approved between 1970 and 1985, a study by Wiggin (1987) showed that the total cost far an approved drug had inflated to $125 million (expressed in 1986 dollars). A study by DiMasi et al. (1990) found that total pharmaceutical costs had escalated to $231 million by 1989. The increasing cost of developing a new drug is also the result of the shift in. R&D focus to chronic diseases, requiring more R&D time and financial resources. The differential costs of conducting R&D in different therapeutic classes were calculated by Hansen (1980), using an accounting approach, for a sample of 37 NCEs tested on human beings from 1963 to 1975. Because R&D expenditures for a new drug are made over time, they were capitalized in the study. The results are summarized in Table 2.13. The most expensive research category is psychopharmacological ($70.3 million), and the least expensive is antiinfective ($19.1 million). 2 . 4 . 3 . 2 Wan The decline in R&D productivity is also attributed to pharmaceutical laboratories . An article in Wis; (1987, p. 67), "Mismanaging Drug Research," about research done at the Harvard Business School of Public Health, notes : Drug conpanies pour nore of their revenue into RRD than nost other industries, but new products reaching the narket have declined. The indmtry blanes stringent governnent controls to ensure drug safety. Critics blane the conpanies’ own hmamxuiammfis. 54 Table 2.13 Average 1140 Cost for a Sanple of 37 ICES by Therapeutic Category, 1963-1975 (in nillions of 1967 dollars) Therapeutic category RLD cost Munber of MCES Cardiovascular 30.6 4 Meurologic, Analgesic 36.3 6 Psychopharnacological 70.0 3 Metabolic, Antifertility 65.3 5 Antiinfective 19.1 12 Antiinflannatory 68.3 4 Gastrointestinal, 28.5 3 Respiratory, Surgical Source. Ronald R. Ransen (1980) , 'Pharnaceutical Developnent Cost by Therapeutic Category, W, University of Rochester Graduate School of Managenent, " (March). 55 Downs (1967, p. 20) summarizes this tendency in his Law of Increasing Conservatism: "All organizations tend to become more conservative as they grow older, unless they experience periods of rapid growth or internal turnover." In an era of "transition and shakeout" (Einanginl_flgzld 1987) and "greater turbulence and interdependence" (W 1987) , drug firms are finding that superiority in all aspects of discovery and development of new' drugs is difficult to 'maintain. Technological innovations come so fast and in so many areas that virtually no company can afford the staff to keep abreast of all new discoveries. The riskiness and high cost of R&D also are forcing firms to seek promising innovations from sources outside their own laboratories. The number' of licensing agreements, mergers, and joint ventures jumped from six in 1979 to twenty in 1988 (Wall Street JOurnal Indices 1979 and 1988). Some examples of long-term R&D contracts and joint ventures between pharmaceutical firms and university laboratories are summarized in Table 2.14. Drug firms also are collaborating on R&D projects. Table 2.15 provides a few examples. 2.3-4.4 Winch Patent activity is another measure of research intensity and indicates the extent of competition from foreign drug firms. 'Table 2.16 shows the percentages of patents issued for drugs between 1963 and 1986 in. the U.S. pharmaceutical industry. Of particular significance is the decline in the relative 56 Table 2.14 Selected Hxanples of Joint Ventures and Long-tern RRD Contracts between Pharnaceutical Tirns and University Laboratories Year Conpany University Anount ($nillion) Duration (years) Area of Research 1988 Squibb Massachusetts 6.4 5 Molecular Meurogenetics General Hospital 1988 Snithkline Johns Hopkins 2.2 5 Respiratory Disease 1987 Upjohn University College, 5.0 5 Central Mervous Systen London a Center Paul Broca IMSERM, Paris 1987 Squibb Oxford 32.0 12 Central Mervous Systen 1985 Cynanid Rice n.a. n.a. Artherosclerosis and Heart Disease 1982 Bristol-Myers Yale 3.0 5 Anti-cancer drugs 1981 Johnson a Scripps Clinic 30.0 n.a. Synthetic Vaccines Johnson 8 Research Foundation 1975 Monsanto Harvard Medical 23.5 12 Tunor, Angiogenesis School factor Source. Prank Tapon (1989) , 'A Transaction Costs Analysis of Innovations in the Organization of Pharaoeutical Rm" W. 12. 197-213 57 Table 2.15 Selected Exanples of R&D Collaborations Between Pharnaceutical Firns Pharnaceutical Pirns Project Description Dupont and Merck Johnson 4 Johnson, Chiron and Abbott Rorer Group and Bolar Syntax and Innunax Boots and Hoechst Chenex Pharnaceuticals and Senju Pharnaceuticals Geritech and Tananouchi Pharnaceutical Snithxline French and Movo-lordisk Joint developnent and narketing of blood pressure and heart disease nechanisns Johnson a Johnson and Chiron will develop and d0 narket tests for the hepatitis C virus, while Abbott will license worldwide rights to nanufacture and narket hepatitis tests fron the other two conpanies Joint venture to develop and narket drugs for the treatnent of hypertension A research and licensing agreenent for a chenotherapy drug: Innunex will acquire the narket rights, and Syntax will retain rights to the drug outside the United States. A 50/50 venture to nanufacture bulk ibuprofen in the United States. A drug evaluation and licensing agreenent for an antiinflannatory drug. This alliance was notivated to develop and connercialize products ainad at treating nany of the health effects of diabetes and aging. The arrangenent includes collaboration on RAD and offers Yananouchi an exclusive license to narket Geritech technologies in the Far East. An agreenent to develop a calciun channel blocker currently in preclinical trials. lovo-Mordisk will have narketing rights to the drug within Europe, and Snithkline will have rights outside Europe. Some : WW (1989)- 5583 Table 2.16 Patents Issued in the U.S. Pharnaceutical Industry, 1963-1986 Year 1963-1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1 Total Patents with 0.3. Origin 65 58 55 57 53 51 52 50 49 51 47 47 51 50 48 Foreign Origin' 35 42 45 43 47 49 48 50 51 49 53 53 49 50 52 Foreign Origin : U.S. Olhed 6 6 8 6 7 7 8 7 6 7 6 4 6 5 6 FOreiqn Oined 29 36 37 37 40 42 42 43 43 46 47 44 45 47 40 0.8. share ofb 71 64 63 63 60 59 60 57 55 58 53 51 56 55 54 total patents 4 of 0.8. patents 8 9 13 9 12 12 13 12 11 12 11 8 11 9 11 with foreign origin Source : U.S. Patent and Tradenark Office, various years. ‘ Foreign origin refers to residence in a foreign country. ” Percentage of patents issued to U.S. firns, U.S. governnent, and U.S. individuals residing ahead of total patents of U.S. firns, U.S. governnent, and U.S. individuals. 59 share of patents held by firms of U.S. origin: this figure dropped from 66 percent from 1963-1972 to about 48 percent in 1986. Meanwhile, innovational activity abroad grew substantially: the percentage of patents of foreign origin rose steadily from about.35 percent in 1963-1972 to 52 percent in 1986. The stringent demands of clinical trials and toxicology testing by the FDA have forced firms to locate their research facilities overseas. anglnsign. The decline in pharmaceutical innovation since 1962 has been accompanied by sharp increases in the cost, duration, and risk of new product development. The rise in R&D cost has been more pronounced in certain therapeutic classes than others, and smaller drug firms have been more affected than larger companies. The higher costs per innovation render small-scale research operations relatively less productive per dollar spent and hence less profitable. One response has been collaborative and joint venture arrangements between pharmaceutical firms or with university laboratories. The performance of foreign drug firms has increased over the last two decades, as indicated by their increase in patent activity. In the next section, social trends affecting the pharmaceutical industry are discussed. 2.4.4 WW In general, the social environment strongly influences and is influenced by the political-economic environment. Certain social trends warrant special attention here: 60 consumer’drug use, changing demographics, and.the financing of health care services. 2-4-4-1 Consumer_nrug_use U.S. health care expenditures have almost tripled in the past three decades. Health care financing was about $500 billion in 1987, compared to about $27 billion in 1960. Despite the decline in drugs as a percentage of national health care expenditures,” consumer use has steadily increased. Table 2.17 shows that the total number of prescriptions, drug expenditures, and the proportion that drug expenditures contribute to health care costs have increased over the last two decades. One factor contributing significantly to rising drug expenditures is higher drug prices. Over the past twenty years, price inflation has continually outpaced the economy's overall inflation rate. In 1981 and 1982, however, drug expenditures in total and as a percentage of heath care expenditures declined slightly. This decrease may have been due to the greater use of generics, particularly by hospitals. 2.4.4.2 W A contributory factor to the increasing use of drugs is the aging of the population. Substantial improvements in 5Drugs as a percentage of national health care expenditures have declined fron 13.6% in 1960 to 7% in 1987. (51 Table 2.17 Total Prescriptions, Drug Expenditures, and Drug Expenditures as a Proportion of Total Health Care Costs (in nillions of 1967 dollars) Drug expenditure as Year Prescription Drug expenditure a t of health care costs 1963 4.5 22.2 10.3 1964 4.5 22.9 9.9 1965 5.0 25.2 10.6 1966 5.4 27.0 10.8 1967 5.4 28.2 11.0 1968 5.7 30.9 11.6 1969 5.9 33.1 11.9 1970 6.2 34.1 11.3 1971 6.5 35.6 11.4 1972 6.9 38.6 11.5 1973 7.2 41.5 11.7 1974 7.1 45.3 12.5 1975 7.0 46.3 12.7 1976 6.8 46.8 12.6 1977 6.5 46.8 12.3 1978 6.2 47.2 12.4 1979 6.1 49.8 12.5 1980 6.2 50.5 12.3 1981 6.2 50.0 11.8 1982 6.4 46.6 11.0 m : U.S. Health Care Financing Adninistration, WW, various years. 62 health care have extended the age-adjusted death rate in the United States. Table 2.18 gives the actual and projected proportion of the U.S. population age 65 and older for selected years. Older Americans are the most important group of consumers for the pharmaceutical industry, as they are the most susceptible to illness, and thus spend a disproportionate amount on drugs. Being an important source of revenue, this segment has developed "countervailing power" in the industry, particularly with respect to public policy pertaining to health. 2-4-4-3 Wannabe While demographic trends point toward continued growth, the pace of drug inflation is likely to slow due to tightened third-party reimbursements and as increased competition for the health care dollar controls utilization and restrains pricing. As used here, third-party payment systems refer to government programs, such as Medicare and Medicaid, corporate- financed employee health insurance, and private insurance. The proportion of drug expenditures accounted for by government programs versus all third-party payers is shown in Table 2.19. It reveals that the rapid rise in health care expenditures has contributed to the increasing portion of drug costs covered by third-party payers. At the same time, the share of health care costs paid directly by consumers dropped from 51.7 percent in 1963 to 31.5 percent in 1982. 63 Table 2.18 Percentage of U.S. Population Age 65 and Older Year Percentage 1963 9.4 1967 9.6 1971 10.0 1975 10.6 1979 11.4 1982 11.5 1995a 13.1 2025a 19.5 Source : U.S. Bureau of Census, MW, various years. ' Estinates by the U.S. Bureau of the Census. £54 Table 2.19 Contribution of Third-Party Paynents to Drug and Total Health Care Expenditures Year 3 of expenditures paid by 3 of expenditures paid by governnent progras all third-party payers m mm m W 1963 2.6 17.0 4.1 48.3 1964 2.9 17.9 4.7 47.5 1965 2.9 18.8 4.9 48.0 1966 3.5 24.2 5.9 49.5 1967 4.2 29.8 7.0 56.5 1968 4.8 37.8 7.9 60.2 1969 5.1 37.1 8.7 60.5 1970 6.8 36.0 11.0 60.1 1971 6.6 36.9 11.2 61.3 1972 7.1 36.8 12.0 62.7 1973 7.2 37.3 12.7 63.7 1974 6.9 39.0 12.7 63.7 1975 7.2 42.4 13.4 66.6 1976 8.4 41.6 15.8 68.3 1977 8.3 41.0 16.4 67.2 1978 8.4 42.0 16.8 67.5 1979 8.3 42.1 17.3 67.3 1980 8.5 42.3 18.9 67.1 1981 8.9 42.7 20.1 67.9 1982 8.7 42.4 21.6 68.5 Source : U.S. Health Care Financing Adninistration, We!) and W 211131111. various years. 65 While not shown in the table, increasing per-capita drug outlays currently make up a large portion of drug costs covered by private heath insurance. The share of total drug costs for private insurance increased to 14 percent in 1984, up from only 4 percent in 1972. Over the same period, payments by consumers fell from 88 percent to 78 percent, while government's total drug expenditures rose from 6 percent to 8 percent. A growing cost consciousness on the part of the government and other third-party payers has resulted in the implementation of several cost containment measures. Examples of government initiatives are the Prospective Payment for Medicare Inpatient Services, the Drug Price Competition, the Patent Restoration, and the Medicare Catastrophic Coverage acts. At the same time, insurance companies, employers, and others are raising employee deductibles and co-payments, implementing out-patient incentives, and encouraging employees to join health maintenance organizations (HMOs). The effect of these actions remain uncertain, but it is clear that "attempts to pass the buck on health costs [to the consumer] will give the industry a monumental headache in 1991” (Wk 1991. p-90)- anglnsign. Transformations in the U.S. health care system are shifting industry policy from indiscriminate expansion to a more conventional, businesslike approach that is more sensitive to the marketplace. While prescription drug 66 firms should.benefit from the growing number of elderly in the population, the initiation of various cost containment measures by the government and other third-party payers is expected to affect the performance of many drug firms unless they continue to develop and market drugs that offer real patient.care advantages or that prove more>cost.effective than alternatives. So far, discussion of the pharmaceutical industry has focused on the U.S. environment. The next section gives a brief overview of the world pharmaceutical industry. 2.5 WW Before the 1950s, pharmaceutical competition remained largely national in scope, with the significant exception of the Swiss multinationals. Today, competition in the industry is truly worldwide, and national markets are interdependent. In the face of growing cost pressures and escalating R&D budgets, drug companies must achieve a global presence, supported by more efficient and effective RGD efforts and large detail forces. 2.5.1 W Figures for worldwide Rx (prescription) sales, Rx market share, R&D expenditures, and size of detail force for the top 30 pharmaceutical companies are shown in Table 2.20. Sales totaled nearly $209 billion in 1988 and accounted for 50.95 percent of worldwide sales of all pharmaceutical companies. (57 Table 2.20. Top 30 Pharnaceutical Conpanias' Worldwide Sales, Market Shares, RAD Expenditures, and Detail Force, 1988. Sales worldwide RAD as a RX Total RED percentage Market share Detail Conpany (nil) (nil) (nil) of sales 1988 1983 force Merck (USA) $4,240 $5.94 $615 14.5 3.95% 3.80% 6,200 Glaxo Holdings (UK) 3,160 3.52 405 12.8 3.00 1.40 5,500 Ciba-Geigy (SUZ) 3,020 12.73 440 14.6 2.80 3.20 5,300 Hoechst (GER) 2,700 25.53 330 12.2 2.50 3.00 4,400 Anerican lone Products (USA) 2,420 5.50 250 10.3 2.25 3.10 4,330 Bayer (GER) 2,370 23.65 480 20.3 2.20 2.00 4,000 Johnson A Johnson (USA) 2,350 9.00 385 16.4 2.20 2.30 3,500 SIitbKline (USA) 2,200 4.75 285 13.0 2.15 2.80 3,000 Pfizer (USA) 2,260 5.39 380 16.8 2.10 2.90 3,600 Sandoz (SUI) 2,230 7.26 390 17.5 2.10 2.00 3,400 Eli Lilly (USA) 2,090 4.07 375 17.9 1.95 2.50 3,250 Bristol-Myers (USA) 2,010 5.97 275 13.7 1.90 2.10 4,000 Hofflan La-Roche ($02) 1,940 2.79 470 24.2 1.85 2.20 3,500 Squibb (USA) 1,710 2.59 275 16.1 1.60 1.30 3,950 Scherinq-Plougb (USA) 1,670 2.97 300 18.0 1.55 1.60 IA Upjohn (USA) 1,650 2.70 320 19.4 1.55 1.60 3,500 Iarner-Lanbert (USA) 1,590 3.91 220 13.8 1.50 1.90 IA Anerican Cynanid (USA) 1,560 4.59 190 12.2 1.45 IA IA Takeda (JAP) 1,480 5.06 312 12.1 1.40 1.10 1,800 Abbott (USA) 1,450 4.94 250 17.2 1.15 1.10 1,600 Ilperial CbeIiGals (UK) 1,450 21.06 240 16.6 1.35 1.60 IA Beacban Group (UK) 1,400 4.68 140 10.0 1.35 1.40 IA Hellc0Ie (UK) 1,340 2.11 205 15.3 1.25 1.10 IA Rbone-Poulanc (IRA) 1,300 10.72 250 19.2 1.20 1.30 IA Sankyo (JAP) 1,190 3.25 IA IA 1.10 1.00 IA Dow Cbelicals (USA) 1,070 16.68 160 15.0 1.00 0.90 IA Fujisawa Pharnaceuticals (JAP) 1,060 1.52 160 15.1 1.00 0.90 IA Astra ($38) 1,050 1.08 200 19.0 0.80 0.70 IA Sanofi (ERA) 1,046 2.40 200 19.1 0.60 0.50 IA Yananouchi Pharnaceuticals (JAP) 1,000 1.48 140 14.0 0.95 0.60 IA Syntax (PA!) 330 1.27 175 20.0 0.30 0.90 in m : Financial Morld (1989a) MA = not available 68 Judging by the percentages of world market share of individual companies, the global pharmaceutical industry is an oligopoly. Fourteen of the top 30 companies are located in the United States, four each in Japan and the United Kingdom, three each in Switzerland and Germany, and one each in Sweden and France. Among the top twenty firms, the drug industry is still dominated by U.S. and European multinationals with the exception of Takeda. In general, the major Japanese drug companies (Takeda, Sankyo, Fujisawa, and Yamanouchi) are a fragmented and highly diversified group. While they have traditionally focused on their domestic market (Burdstall 1985), they are increasingly becoming more globally oriented (Yashikawa 1989) . Licensing and joint ventures tend to be the most frequent entry modes used by Japanese drug firms. Because Western Europe, the United States and Japan accounts for approximately 75 percent of total world demand for health care products, most of the leading players seek to establish an insider position in each of these markets. The worldwide distribution of corporate sales for North American- based companies and European-based companies is shown in Table 2.21. Between 1980 and 1988, the average percentage of sales received outside the home region by all pharmaceutical companies increased slightly, from 37 percent to 40 percent. Over the same period, European-based companies aggressively increased their global presence, while that of North American- (59 Table 2.21 Leading Pharnaceutical Conpanies : Worldwide Distribution of Corporate Sales, 1980 and 1988 Year All Pharnaceutical Conpanies 1980 1988 Hone Region 63% 60% Rest of the World 373 404 Morth Anerican-based Conpanies lorth Anerica 634 64% Europe 24% 22% Asia 7% 94 Others 6% 5% European-based Conpanies Europe 574 503 North Anerica 18% 29% Asia 104 12% Others 151 9% Source : Conpany reports, various years. 70 based companies remained relatively stable. European penetration of the U.S. market increased to 29 percent, compared to only 18 percent over the 1980-1989 period. 2.5.2 DetaiLEarcs In an increasingly competitive and globalized health care product industry, marketing plays a critical role. One way to achieve a global presence is to support a critical mass of detail people for the marketing or co-marketing of one’s own or other companies’ products as well. As was shown in Table 2.20, Merck and Glaxo fielded the largest detail forces in 1985-88. Through extensive international marketing and selling, both Merck and Glaxo managed to turn Vasotec (an ACE inhibitor‘) and Zantac (antiucler), respectively, into billion-dollar products. Zantac was sold in the United States through a co-marketing deal with Roche, which "rented out" 800 salesmen to Glaxo. The detail force is considered essential to the success of a new drug. A typical U.K. pharmaceutical company makes about 17,000 calls to 24,500 physicians at least once a year. The U.S. Pharmaceutical Manufacturers Association estimates that 25,000 detail representatives were employed at a cost of $25,000 per employee (Silverman and Lee 1974). 2.5.3 KW Much of the discussion on industry RED was covered in ‘ACE inhibitor is a drug for the treatnent of hypertension. 71 section 2.4.3. Here the focus is on R&D at the firm level. Figure 2.2 compares R&D expenditure and health care product sales from 1985 to 1988 among the major pharmaceutical firms. The similarity’ in.(corporate strategies. is evident: Umost increased. their' R&D investments faster' than ‘their’ sales growth. Exceptions were Hoffmann La-Roche, Merck, and Upjohn, which experienced above-average sales growth and.were already either making large R&D investments or allocating a high percentage of health care product sales to RED. Leading all companies in R&D expenditure growth was Glaxo, highly dependent on the antiucler drug Zantac, which attained sales of $1.7 billion in 1988. To avoid over- reliance on this "cash cow", the company invested heavily in mm. Two other leading companies, SmithKline Beckman and Squibb, also depended on bullion-dollar drugs, Tagamet and Capoten, respectively, for nearly 50 percent of their 1988 ethical pharmaceutical sales. The inability to generate a stream of new drugs and overdependency on a single blockbuster drug led, in part, to the 1989 mergers of SmithKline Beckman with Beecham and of Squibb with Bristol-Myers. anglnsigns, To compete more effectively in the global market, major pharmaceutical firms have made massive investments in R&D and enlarged their detail force. Compared to their North American counterparts, Western European firms have been especially aggressive in establishing their presence in overseas markets. Escalating pressure to develop new 72 36v 325 2.20900 .0 maficmuemd 00— cm om on om on 9. cm cm or _ _ _ _ _ _ _ _ . " mcmEo_m O cesiumm mc__vE:Em m 5.6 (v . _ m ab .1 O . O . 5562.7 Siam modxmh I" Noocmm O O O - oEuoE Emcoo mzuoa 5 Emcee: " 360.35 $2.0: 8952. w 8.3.22.9 " ---- {1-1.41 omflo>< . " 5.3.63 0 " mefilofitm O es=ao e l 1 zoop< " o O . neaqm 32605 9:01 cmotoE< o 61;: 0x30 0 1 5.86.2 modem uosooum sumo guano: one susouu ousuwosomxm new no somwuomaoo Assomvom~_a>< op 0N mN 3L mm_mm 990900 co 526m mmmaummm. .mausm Hoosuzooaeuenm none: om you ~.~ decode 73 products, which requires high-risk and expensive R&D, calls for a worldwide presence to fund such.development. This force will drive U.S. companies to seek a broader global reach during the 1990s. 2-6 QQDanfiiQn Major changes in the environment of the U.S. pharmaceutical industry as well as the global context have been analyzed in some detail. Such an analysis is important as it permits identification of the major trends and forces pharmaceutical firms need to consider in planning their strategic posture. Following is a summary for each environmental domain. 2.6.1. Wu: The pharmaceutical industry can be analyzed along several dimensions: (1) ethical versus proprietary versus generic drugs: (2) single-source versus multisource drugs: and (3) acute versus maintenance drugs. Seller concentration was analyzed on an industry level and for individual therapeutic classes. From the standpoint of the influence of industry structure on competitive behavior, it is necessary to go beyond industry wide ratios and examine concentration in therapeutically significant categories. An analysis of concentration and .market share rank turnover at the therapeutic category level reveals certain categories have exhibited more instability than others. 2.6-2. mm The effects of government regulation since the passage of the Kefauver amendments in 1962 are believed to have contributed to the declining rate of R&D innovation and higher RSD costs. Spiralling health care costs have prompted both federal and state governments to implement several cost containment measures. 74 2.6-3. W The shift in R&D focus from acute to chronic diseases has contributed to the differential costs of conducting RAD in different therapeutic classes. There is also increasing concentration of R&D among larger firms. The prohibitive cost and risk of pharmaceutical R&D suggest that a certain economy of scale may be necessary to compete in the industry. These same forces are also encouraging firms to form collaborative RED ventures with other companies and university laboratories. An analysis of the patent activity among U.S. and foreign firms reveals that the latter have increased their share in innovative activity. 2-6-4- W Consumer drug use has grown substantially, partly because of an aging population and the dramatic expansion of third-party payments. As third-party payers and governments attempt to control health care costs, generic substitution programs are expected to rise. 2.6-5. filehalJnximnment The global pharmaceutical industry is dominated by Western Europe and U.S. firms, but Japanese companies are increasing their presence worldwide through licensing and joint ventures. RSD has become the undisputed chief basis of competition in the global pharmaceutical industry. To support new product introductions from these RaD efforts, companies also have increased their detail force size to wring the greatest revenue from new products, as soon as possible, in the maximum number of markets. The changes that have taken place in these five major environments strongly reinforce the notion that a longitudinal analysis is necessary to capture the dynamics of these changes. In the next chapter, the literature review pertaining to the concepts in Figure 1.3 is discussed. CHAPTER THREE REVIEW OF THE LITERATURE This chapter reviews the literature pertaining to the concept of competitive positioning. The purpose of this review iS‘tO assess what has been accomplished in the field to date and to present a synthesis of the empirical and theoretical literature. The review will also cover a discussion of the dependent variable, firm performance. First, the basic research framework is presented. This is the structure-conduct-performance (SCP) paradigmwwhich.has its roots in industrial organization (IO) research. Structure was covered in chapter 2. Both conduct and performance are discussed in this chapter. Second, while there is general agreement about how to define strategic performance, there is, little consensus about how to measure it. Therefore, it is necessary to define and identify measures of strategic performance that adequately reflect pharmaceutical firms' positioning strategies. Third, firm conduct is discussed in terms of choice of product markets, timing of entry, mode of competition, and degree of geographical diversification (refer to Figure 1.3). Since this study is concerned with the relationship not only between competitive positioning strategy and performance 75 76 but also among the components of the positioning strategy, research questions relating to these associations are addressed in detail. The research questions provide the basis for hypotheses stated in chapter 4. 3 .1 WWW 3.1.1. Desgnipgign First offered by Mason (1939), the SCP paradigm postulates that market structure influences the firm's conduct which in turn affects performance. This paradigm is widely used by economists and organizational behaviorists to understand and evaluate industry rivalry and performance. In IO terminology, market structure refers to the stable characteristics of the industry environment that influence the nature of competition among buyers and sellers operating in it (Caves 1982). Market structure is usually assessed. by measures such as seller and buyer concentration, barriers to entry and exit, and degree of product differentiation. Firm conduct consists of firm's competitive reactions toward the structural elements and toward rivalry moves made by other firms. Finally, while industry performance has been the central concern in IO research, recent studies have shifted their focus to performance at the firm level. 3.1.2. W Few IO studies simultaneously examine or measure the inter relationships among structure, conduct, and performance. 77 For example, such "structuralists" as Mason (1939) and Bain (1958) argue that relationships between market structure- conduct and conduct-performance are not necessary for evaluating overall firm performance. Since structure determines conduct, it is sufficient to relate market structural elements to performance to assess the nature of competition. [For an excellent review of empirical research in the area of market structure and industrial performance, see Vernon (1982).] The structuralist approach has come under attack in recent years, despite the value of this extensive body of research, as inadequate to explain all the ‘variance in performance (Vernon 1972: Phillips 1976). :Researchers such as Bass, Cattin, and Wittink (1978) argue that the performance implications of a particular aspect of market structure depend upon the market.under consideration. Generalizing structure- performance relationships across different product classes and industries can only lead to erroneous results. Alternatively, “behaviorists" argue that the linkage between structure and performance appears to be moderated by the relative competitive position of the firm. Early proponents of this view include Hunt (1972), Newman (1972) and Porter (1973). - From the behaviorist school emerged the concept of 78 "strategic groups" of firms.’ Research.by Hatten and Schendel (1977), Porter (1977), Schendel and Patton (1978), and Cool and Schendel (1987) suggests that firm performance partially depends upon membership in a particular strategic group and that all firms are not equally able to adapt to changes in competitive conditions and market structural elements. Overall, the relationships among firm performance, conduct, and market structure can be expressed as : Firm Performance = f(Conduct, Market Structure), where conduct relates to the controllable variables endogenous to the firm, while market structure relates to the notion of uncontrollable or environmental variables exogenous to the firm. The joint influence of conduct and structure on performance is increasingly recognized and adopted in several disciplines. In marketing, the PIMS studies (for example, Schoeffler 1977: Schoeffler, Buzzell, and Heany 1974: Buzzell, Gale, and Sultan 1975) attempt to explain performance across a diverse sample of industrial firms by using the concepts of strategy and environment. From this perspective, performance is conceptualized as: Firm Performance = f(Strategy, Environmental Variables). 7For nore detailed analysis about strategic groups, readers can refer to studies by McGee and Thonas (1986), and Thonas and Venkatranan (1988). 79 In strategic management research, several studies have focused on firm performance within one industry. For example, studies in the U.S. brewing industry (Hatten 1974: Hatten and Schendel 1977: Hatten, Schendel, and Cooper 1978: Schendel and Patton 1978), consumer goods industries (Oster 1982; Porter 1973), and banking industry (Hayes, Spence, and Marks 1983: Ramsler 1982) confirm the interdependencies between strategic variables and industry structure in influencing firm performance. Accordingly, performance can be expressed as: Firm Performance = f (Strategic Conduct, Industry Structure) . This is the formulation adopted in this study. Industry structure will be assessed in terms of the different therapeutic categories in‘which pharmaceutical firms compete. Strategic conduct will be defined in terms of firms' competitive positioning strategies. Implied in this concept is a focus on how’ a company competes in the selected therapeutic categories and positions itself among competitors. In the strategic management literature, action sets and resource allocations or commitments generically characterize strategy. While the variables in this study are not defined in these specific terms, they are somewhat similar in operationalization. 3.2 21911321111125 Action sets refer to directional choices to achieve organizational objectives in light of environmental 84) opportunities and constraints. Action sets also are known as "scope" choices. According to Walters (1986), the components of these choices are: the range of market segments or customer groups, types of products across the segments, and geographic scope. We. As pointed out in chapter 2. there are several market sectors in‘which firms compete in the pharmaceutical industry: ethical versus proprietary versus generic drug sales: single-source versus multi source drugs: and acute versus maintenance drugs. This study focuses on the ethical drug sector, where new drug development is greater than in the proprietary or generic sectors. W. New drugs can be classified into four categories: (1) law Chanical Entity - products that are new, single chenical entities not previously known, including new salts: (2) Duplicate Single Products - followbup narketing of a new chenical entity, previously introduced by another nanufacturer: ( 3) Oonpotmded Predicts - any products having nore than one active ingredient: (4) Alternate Dosage Forns - products previously narketad in tablets and now offered in anpules, capsules, liquid, and so forth. NCEs are only considered in this study as they are regarded as "breakthroughs" in the truest sense. Economists concerned with RSD activity in the drug industry generally have argued.that.NCEs represent the most innovative of the new products developed (Grabowski 1968). The other categories 81 described above are not "new" products, merely outgrowth of previously marketed chemical entities. W. As mentioned in chapter 2, maintaining a presence overseas is necessary in an industry undergoing rapid globalization. Pharmaceutical firms may differ in their degree of geographic diversification or concentration and/or their timing of a geographic expansion strategy. Therefore, global marketing efforts of drug firms are investigated in this study. 3.3 MAW In addition to action sets, strategy is characterized by the allocation of resources, that is the commitment of distinctive resources and the creation and deployment of new resource combinations to pursue intended action sets. Since the types of resources necessary for competitive advantages will vary among industries, it is necessary to identify resource commitments that are unique to an industry. For example, in his study of the international financial services industry, Walters (1986) identifies the following as key contributors to competitive advantage: (1) adequacy of an institution's capital base and risk base: (2) human resources: (3) access to information and markets; and (4) technology base. In the pharmaceutical industry, resource commitments in both marketing and R&D are considered central in attaining and maintaining a position of sustainable competitive advantage. Section 3.5.2 provides a fuller description of these 82 resources 0 3 .4 W Firm performance refers to the achievement of a firm with respect to a certain criterion or criteria. The measurement of firm performance always has been problematic. While some researchers adhere to a multidimensional measure (for example, Bagozzi and Phillips 1982: Benson 1974: Chakravarthy 1986: Keats 1983), others assert that various aspects of performance can be captured in a single measure (for example, Kirchoff 1977: Hatten, Schendel, and Cooper 1978). Yet.others argue that performance encompasses not only the interests of organizations but also those of society (for example, Parsons 1960: Price 1972: Steers 1975). Some even suggest that the construct be abandoned altogether (Hannan and Freeman 1977). Although the determination of performance descriptors is complex, a performance measure is necessary. It allows firms to evaluate objectively the quality of their strategic decisions. The next section develops this issue in greater detail and provides the background for the selection of performance measures used in this study. 3-4-1- HBaEDI§§_QI_E£QaniQ_SHQQ§§§ This research employs multiple performance indicators as they relate to the firm, not the pharmaceutical industry. Three types of performance measures are discussed: accounting 83 indicators, financial-market measures, and output market descriptors. The advantages and disadvantages of each are discussed briefly below. 3.4-1.1 WW Such accounting indicators as return on investment (ROI) , return on sales (ROS), and cash flow to investment are commonly used in assessing firms' profitability.' Shrader, Taylor, and Dalton (1986) noted that both ROI and ROS are predominant measures of economic performance in studies relating planning process and strategy content to organizational performance. Despite limitations (see Dearden 1969: Jacobsen 1987: Reece and Cool 1978), Woo and Willard (1983, p. 13) also concluded that profitability measures such as ROI and ROS are important measures of performance: Despite the prohlens inherent in ROI, results fron [our study] support their continual use ...... .when properly conplenented by other neasures, [our study] shows that R01 is essential to the conprehansive representation of perfornance. The advantages of using these accounting measures are that, as ratios, they facilitate the comparison of firms of different sizes, and they are often publicly reported. Recent critics (McQuire and Schneeweis 1983) have cited several problems, however: (1) the scope for accounting manipulation: (2) undervaluation of assets: (3) distortions due to depreciation policies, inventory valuation, and treatment of certain revenue and expenditure items: and (4) differences in methods of consolidating accounts. 84 3.4.1.2. WWW Accounting indicators record only the historical performance of the firth Monitoring’ a firm's strategy requires measures that will capture future performance, that is, a long-term valuation rather than the short-term perspective characteristic of accounting measures. The most popular financial market measure of performance is the M/B ratio, or the spread between the market and book value of the firm. This indicator has been shown to measure the perceived ability of the firm to return to its shareholders an amount in the future in excess of expected return (Rappaport 1981). Peters andflWaterman (1982) also used this indicator as a performance screen to evaluate the long- term wealth creation potential of a firm. The M/B ratio, however is not without problems. It is not entirely free from accounting manipulation, that is, the book value of a firm can be distorted. Financial market measures also are not equipped to deal with changes in business performance over time. Although they may provide a good estimate of the performance effect of an event at the time it occurs, subsequent effects are difficult to identify. For this research, financial market measures were deemed inappropriate for this longitudinal study. 3.4.1.3. WW These indicators which refer to the operational performance of the firm in its markets, include such measures 85 as market share, market share growth, market share rank, and sales growth. venkatraman and Ramanujan (1986) argue that there are two separate domains, financial accounting measures, which reflect "fulfillment of the economic goals of the firm" (p. 803), and operational measures, which reflect "key operational success factors that might lead to financial performance" (p. 804). The relationship between market share and profitability is*widely recognized in the PIMS research (Gale 1972: Buzzell, Gale, and Sultan 1975). Under most circumstances, businesses that achieve a high share of the markets they serve are also considerably more profitable than their small share counterparts. As empirically demonstrated by Woo (1979) and Rumelt and Wensley (1981), the positive relationship between market share and profitability is far from universally valid and is mediated by various firm and market characteristics. Therefore, the market share indicator should not be taken as an absolute indicator of performance and its relationship to profitability is not clearly established. Nevertheless, market share indicators will continue to hold a central place in marketing studies as measures of performance. The relationship between marketing effort and market share is specified in attraction models (Lilien and Kotler 1983: Moriarty 1975: Weiss 1968) and is monitored closely in the measurement of a firm's performance against those plans (Wind and Mahajan 1981). In developing a dynamic 86 model of a marketing system, Lambkin (1989) employed market share as a factor preceding profits. Since market share plays a central role in strategic marketing, and given its frequent use as a key objective in the strategic planning process, this measure of performance will be examined here. The lack of information pertaining to depreciation rates excludes the consideration of accounting indicators for this study (see p. 92). 3.5. ggmpgtigiyg Egsigigning ggmpgngngs This section discusses the antecedents of firm performance. - Three key components of the competitive positioning strategy will be discussed: (1) timing of entry, (2) means of competition, and (3) geographic scope. From a strategic marketing perspective, the initial positioning of a product in a particular market is an important factor in success or failure. The literature has focused mainly on the individual components of the competitive positioning strategy. It is argued here that a full understanding of performance over time in relation to positioning strategies requires an analysis of all dimensions. In this study, attention is restricted to firms which had success 'with. their' positioning strategy; .Although some researchers such as Glazer (1985) maintain that "successful" firms should not be studied in isolation from firms that "failed," it is often difficult to collect information about 87 failures. Furthermore, since the pharmaceutical industry tends to be dominated by large firms, this study excludes the experiences of small, independent ventures. The large and established pharmaceutical companies very often possess organizational capabilities in "downstream" functions, such as bringing new drugs from the laboratory to the market, economies of scale, and political clout over smaller firms. This selection bias limits the generalizabilty of the study’s findings to firms of all sizes. 3.5.1. minimum The choice of market entry strategy has been found to influence product failure and success (Urban et al. 1986: Schnaars 1986). Whether to be a pioneer or follower is an important strategic question. The decision to enter a market balances the risks of "sinking the boat" or "missing the boat." .Abell (1978, p.21) states that "there are only limited periods in which the 'fit' between the key requirements of a market and the particular competency of a firm competing in the market is at an optimum." If the firm enters a new and emerging product market early, it can push an underdeveloped product into the marketplace and gain customer acceptance. If entry is delayed too long, the firm may sacrifice the benefits of being first with a new product or technology. In analyses of market entry, different aspects of the issue have been emphasized. One set of studies has stressed 88 the sources of advantage of early entrants. A second set has focused on timing of entry and performance. 3.5.1.1. W While timing of entry is an important factor, studies have shown that it is not the order of entry per se that determines market position. More important are the entry barriers that the pioneer builds (see Robinson and Fornell 1985: Lieberman and Montgomery 1988: Fershtman, Mahajan, and Muller 1990). Theoretical arguments in the literature illustrate how entry barriers can provide pioneers with sustainable advantage. Bain (1956) , who was the first to study this issue, cited economies of scale, product differentiation, and absolute cost advantages as barriers to market entry. Entry barriers can be both structural (exogenous) and behavioral (endogenous). Examples of the former include market concentration (King and Thompson 1982): seller concentration (Crawford 1975: Mann 1966): number of competitors (Harrigan 1981): and government policy (Grabowski and Vernon 1986: Porter 1980a). The following discussion focuses on firm-specific actions that influence endogenous barriers. Mechanisms or forms of entry barriers leading to first- mover advantages and disadvantages are provided in an excellent review by Lieberman and Mbntgomery (1988). They define first-mover advantages in terms of the ability of 39 pioneering firms to earn positive economic profits. First- mover advantages can be attained through: (1) leadership in product and process technology: (2) development of buyer switching costs : and (3) preemption of assets. Potential disadvantages include: (1) free-rider problems: (2) shifts in technology or customer needs: and (3) a tendency toward inertia by established incumbents. Only the mechanisms leading to first-mover advantages are discussed here. WW For firms in high-technology industries, the ability to protect intellectual property though patents is an important entry barrier when the product technology is a function of R&D expenditures.‘ In a research using the PIMS data base, Robinson (1988) found that pioneer firms benefit from patents to a greater extent than do followers (29 percent versus 13 percent). In a study involving 48 patented product innovations in pharmaceuticals, chemicals, and electronic products, Mansfield et al. (1981) found that, on average, imitators could duplicate patented innovations for about 65 percent of the innovator's cost. Imitation appears more costly in the pharmaceutical industry, however, because imitators must go through the same regulatory procedures to get their drugs approved. A study by Kemp (1975) of the diuretics drug market showed contrary to traditional economic theory on market aBecause product patents rather than process patents offer nore protection in the pharnaceutical industry, they are considered here. 90 imperfections, patent holders did not have total monopolistic power during the period of patent protection. Very often, economic theory does not take into explicit consideration the effect of entry in situations in which replication of the product is possible. Therefore, what has not been appreciated is that the development of additional products in the same subclass makes entry possible when it otherwise would be barred by the patent of the pioneering drug. As indicated by Table 3.1, in the diuretics subclasses,’ follow-on drugs had a minimal effect on market shares in carbonic anhydrase inhibitors and fast-acting diuretics, while follow-ons in the other two sub classes had a marked effect on physicians' prescribing patterns and on market share. Judging from this example, follow-ans may be as attractive a form of entry as pioneering a breakthrough product. W. Switching costs refer to supplier- specific learning by the buyer over time. First-mover advantages that arise from buyer switching costs are particularly strong for high-involvement products such as prescription drugs. Over time, the buyer adapts to the characteristics of these products and their suppliers and finds it costly to change to another brand (Wernerfelt 1985). For example, Porter (1980b) found that nurses were reluctant 9The four sub-classes are : carbonic anhydrase inhibitors, fast-acting diuretics, thiazidas and related conpoimds, and potassiun-conserving conpounds. 571 Table 3.1. Postnarketing Experience in Diuretics : Munber of Single Entity Follow-0n Brands Marketed and Their Market Share in 1969 Share of narket 0f single entity follow-0n Munber of follow-on products narketed brands narketed Share of narket (percent) of breakthrough, Breakthrough Out- (percent) Breakthrough Out- Subclass conpany siders conpany siders Carbonic anhydrase 1 2 97.9 0.0 2.1 inhibitors Fast-acting 0 1 90.9 - 9.1 diuretics Thiarides and related 1 15 27.2 25.2 40.9 conpounds Potassiun-consarving 1 2 11.6 40.3 48.1 conpounds Source : Bernard Reap (1975), 'The Follow-on Developnent Process and the Market for Diuretics in nrug_nayelopnent_gnd_flarketing,' Robert Helns, (ed.), pp.255-76. 92 to switch to other suppliers' intravenous solution delivery systems once they were accustomed to a certain supplier's brand” Thus, switching costs can enhance the value of market share obtained early in the evolution of a new market ceteris paribus. Under conditions of uncertainty about product quality, buyers may rationally stick to the first brand that performs the job satisfactorily. As suggested by Comanor and Wilson (1974, p. 24), ”much brand loyalty is a device for reducing the risks of consumer decisions.” A consumer behavior study by Carpenter and Nakamoto (1986) found that order of entry influences the formation of consumer preferences. The first product introduced tends to capture significant attention, which may yield an asymmetric competitive advantage for the pioneering firm. Products such as Coca-Cola and Kleenex are classic examples. In another study by Carpenter and Nakamoto (1990) , it was found that later entrants can increase profits by differentiating their products with a high advertising budget and high price if the dominant brand has a powerful asymmetric competitive advantage. Attempts to position near the dominant brand with a "me-too" strategy, however, led to relatively poor performance. These perceptual effects have ben confirmed in other research. In a study of two therapeutic submarkets in the ethical pharmaceutical industry, diuretics and antianginals, 93 Bond and Lean (1977) found support for Bain’s (1956) hypothesis of consumer-based information advantages. Physicians tend to ignore "me-too" products even ifloffered at lower prices and with substantial marketing support. Considering the environment in which physicians dispense drugs to their patients, Thomas (1988) noted the following three characteristics: (1) physicians are time conscious and thus attempt to reduce their search time for alternatives beyond satisfactory therapies: (2) physicians are price insensitive, as they do not pay for the products: and (3) physicians are highly concerned about the therapeutic quality of drugs. The last factor points to the importance of asymmetry of consumer acceptance between existing and entering brands. In such an environment, when physicians become convinced that the first brand is performing satisfactorily, that brand becomes the standard against which subsequent entrants are judged. It becomes harder for follow-on entrants to persuade consumers to invest in learning the qualities of their products.10 Loyalty also is strong for branded ethical drugs after patents expire (Statman and Tyebjee 1981) . The loyalty created through experience with existing brands is a disadvantage for later entrants (Comanor and Wilson 1974). The lack of economic incentives on the part of the 10In addition, for certain therapeutic subclasses, the physician nay be faced with a bewildering array of alternatives. Physicians have a linited processing infornation capacity, so they learn about and work with only a few (U.S. Senate 1972), which reinforces brand loyalty. 94 physician to prescribe cheaper alternatives also amplifies brand loyalty. According to the FTC (1979, p. 2), "the basic problem is the economic forces of competition do not work well in a market where the consumer who pays does not choose, and the physician who chooses does not pay." This point was confirmed by Gagnon (1983), who also found that physicians were unaware of price differences among competing brands. In a similar study, Kemp (1975) hypothesized that follow— on brands were unsuccessful in capturing market share from the breakthrough product because of the promotional activity by the pioneering company and the difficulty of overcoming the first-of-a-type syndrome. In one case, that of fast-acting diuretics, the company that introduced the breakthrough, Hoechst, was new and small in the U.S . market, although not small internationally. Its successful promotional campaign enabled it to obtain and maintain its market position. (Kemp 1975, p. 270). 2rggmntign_gf_nssets. First movers can gain advantage by controlling physical assets or can deter entry through strategies of spatial preemption. The most relevant strategy for this study is preemption in product characteristics space or niches in product differentiation. The theory of spatial preemption (Prescott and Visscher 1977: Schmalensee 1978: Rao and Rutenberg 1979) argues that first movers can establish positions in product space such that latecomers find it unprofitable to occupy the interstices. 95 A PIMS study by Robinson and Fornell (1985) found that new consumer product pioneers initially held product quality superiority over imitators and subsequently developed advantages in the form of a broader product line. .9 This suggests that pioneers attempt to reinforce their early lead by filling product differentiation niches. W. In summary, three major forces act as important first-mover advantages in the pharmaceutical industry. First, the ability to protect the firm's technology through patents may limit the number of entrants into the market and allow a firm to market a product superior to that of competitors. Second, drugs have high switching costs and, therefore, higher brand loyalty. Third, pioneering firms that offer products with distinct advantages can extend their brand advantage to their other product lines. 3.5-1.2. BMW Theoretical and empirical work on the order of entry suggests long-term market share rewards for pioneering brands. Studies have concentrated on the consumer and industrial goods industry. The PIMS database often has been used as the main source of data to test hypotheses. In a study involving the PIMS data base, Biggadike (1976) examined 40 industrial product entries into new markets by large firms. After four years, the average market share of these entrants was 15 percent, but the largest share of the 96 largest existing competitor in each of the 40 businesses decreased from 47 percent.to 28 percent when new entrants came into the market. Similar results were obtained by Dillion, Calantone, and Worthing (1979) in their study of" 174 industrial products: they found that pioneering was a major determinant of the long-term success of a new product. Robinson and Fornell (1985) found a significant market share penalty for late entry. Using the PIMS data, they sampled 371 consumer goods units in the mature stage of the life-cycle. The average market share for pioneer firms was 29 percent, compared to 16 percent for early followers and 11 percent for late entrants. In comparing these results with those found in a study involving a cross-section of industrial goods businesses, Robinson (1988) again showed that market pioneers tend to have higher market shares than late entrants. A recent study by Lambkin (1989) strongly supports the relationship between order of entry and competitive performance. Propositions were tested on a sample of new business ventures from the PIMS start-up data base and were validated on a hold-out sample of adolescent business from the main PIMS data base. A multidimensional measure of performance was considered. Overall, order of entry loaded significantly on market share, relative market share, return on sales, and.return«on investment.but insignificantly on.cash flow/investment. 97 Another study using the PIMS data to test the effects of entry order, by Miller et al. (1989), analyzed 119 nonservice businesses (consumer and industrial). It found that pioneers had.significantly higher market.shares than followers andfithat little "degree of lateness effect" existed between early and late followers. An empirical analysis by Urban et al. (1986) found that the order of entry of a brand into»a consumer product category is inversely related.to its market share. 'This study differed from similar research in two respects: (1) brands were chosen as the unit of analysis instead of firms: and (2) market share was constructed. by“ evoking’ consumers' evaluation. of the product. Consumer preferences and rating data were later used in product positioning and differentiation. Nevertheless, similar results in terms of pioneering advantages were found in this study; Second entrants obtained on average only about three-quarters of the market share of pioneers, and later entrants garnered progressively smaller shares. Longitudinal studies in the ethical pharmaceutical and cigarette industries also confirm the order of entry effects. From their examination of two related prescription drugs (diuretics and antianginals), Bond and Lean (1977, p. vi) concluded that "the first firm to offer and promote a new type of product received a substantial and enduring sales advantage." Research on trends in seven cigarette submarkets by Whitten (1979, p. 41) led to the finding that the "first 98 entry brand received a substantial and enduring sales advantage" in six of the seven segments." The effect of entry timing on performance also was identified in the Markstrat study by Green and Ryans (1990). Since the Markstrat environment is "controlled," it could be argued that the results may be an artifact of the simulation. However, their findings found support in "real world" studies (for example, Biggadike 1976: Bond and Lean 1977: Whitten 1979: Dillion et al. 1979: Robinson and Fornell 1985: Urban et al. 1986: Robinson 1988: Lambkin 1989: Miller et al. 1989). Despite the strong empirical support, several researchers have questioned the validity of the premises underlying the order of entry hypothesis (Aaker and Day 1986). Study of a sample of 100 new'product failures and successes found no real advantages for pioneering brands (Cooper 1979b). This contention was supported by Dillion et al. (1979). Despite the advantages of being a market pioneer, a follower strategy can pay (Haines et al. 1989). Besides those identified by Lieberman and Montgomery (1988), other advantages of a follower strategy are knowing the market is really there, learning from the pioneer's experience, introducing superior manufacturing techniques, introducing products with superior design attributes, and fine-tuning the marketing mix. The ability to compete with a superior product and creative positioning of the marketing mix has been extensively studied. Since these factors pertain to "how" firms compete, 99 and is discussed in detail in Section 3.5.2., only a brief mention is made here. One way later entrants can "leapfrog" pioneering business is to develop an innovative product with superior features and/or lower price (Urban et al. 1986). Follow-on brands of the potassium-conserving compounds were successful because of firms' market research to "discover and counteract the effect of promotional strategies of rivals" (Kemp 1975, p. 27). The competition also led to an improved understanding by physicians and pharmaceutical manufacturers of the modes of action, therapeutic properties, and side effects of the drugs on the market. Bond and Lean (1977) found that later entrants offering drugs with distinct therapeutic benefits can overcome first- entrant advantages through heavy promotional expenditures. Neither these outlays nor low price alone dislodged the pioneers, however, which led the authors to conclude that “large-scale promotion of brands that offer nothing new is likely to go unrewarded" (p. vi). Although "me-too" entries are unlikely to be successful, a well-conceived "second-but-better" entry, backed by aggressive advertising and superior positioning, may gain competitive advantage over the pioneer's products (Urban et al. 1986). This is the strategy recommended by Carpenter and Nakamoto (1990) for late entry into a market dominated by an entrenched competitor. 100 anglgsign. The basic premise that order of entry is systematically related to performance is strongly supported, although studies have shown the moderating influence of variations in firm strategy in different entrant categories. A basic limitation of prior studies on timing of entry should be recognized, namely they tend to be cross-sectional. As noted by Bass, Cattin, and Wittink (1978), a cross- sectional study can be affected by sample heterogeneity, often resulting in misleading conclusions. Even though some research has focused specifically on the consumer or industrial goods industries, the broad range of businesses studied.within each sector does not eliminate the possibility of alternative explanations. This ambiguity is avoided here by looking at only major firms in the ethical pharmaceutical industry. Heterogeneity is reduced because one industry and firms of the same size are considered. Past research findings about the timing of entry and firm performance lead to the following research question: Question 1 : How is timing of entry related to firm performance? 3.5.2. Means of Competition - COmpetitive Position in R&D and This section discusses the two resource deployment areas most important in achieving economic success in the pharmaceutical industry: R&D and marketing. In many situations, it is reasonable to assume that the greater the investment the firm makes in its product- 101 positioning strategy, the more likely it will be to succeed. For example, MacMillian and Day (1987) split their sample of new' corporate ‘ventures .into "high" and "low" investment groups. For most of the strategic options considered such as plant size, relative sales promotion, size of salesforce, and advertising expenditures, relative price, relative quality, the higher the level of investment, the higher was the return on investment and the larger the market size. The fundamental theorem of ”market share determination" holds that the market shares of various competitors are proportional to their shares of total marketing effort (Kotler 1984). This relationship is also pivotal in the market share attraction models (Little, Bell, and Keeney 1975). The major resource commitments that capture the bases of competition and competitive advantage in the ethical pharmaceutical industry are research and development (Ram and marketing (Cool and Schendel 1987). The application of these resources is discussed in the next two sections, along with the relationship between timing of entry and resource commitments. 3.5.2-1. MW To ascertain a firm's competitive position with respect to the R&D function, two factors will be evaluated: the degree of commitment to R&D and the effectiveness of R&D efforts. 102 ggnmigngngngg_3§n_LR§Q_1n;gn§ity1. Expenditures on research and development constitute an important form of non price competition in high-technology industries. Macro studies on economic growth in industrialized nations have accepted technological innovation (and, by extension or proxy, business investments in IRED) as 'the leading' determinantn variable (Schumpeter 1934: Denison 1967: Harberger 1984). Similarly, micro studies have attempted to show the causal link between RED investment and growth of individual industrial firms. This causal relationship has been strongly supported (Mansfield 1968: Scherer 1976: Jarrell 1983: Comanor 1986: Morbey 1988: Franko 1989). In a cross-sectional examination of various industries, Franko (1989) argued that the RED intensity of individual firms is positively and significantly related to subsequent relative worldwide corporate sales growth and hence to global market share. Many studies show that RED intensity positively affects corporate performance in terms of five measures : 1. valuation measures, such as stock market value, P/E and investment value (for example, Elia 1980: Pakes 1985): 2. Profit measures such as profitability, gross margins, earnings per share, earnings per sales, return on investment (for example, Grabowski and Mueller 1978: Parasuraman and Zeren 1983: Reynard 1979: Wagner 1984): 3. Returns versus other investments (for example, Grabowski and Mueller 1978): 4. Technical output parameters, such as patents, papers, patents per employee, patents per sales, product quality (for example, Cooper 1984: Hambrick and Macmillain 1985: Kamien and Schwartz 1975): and 103 5. Size and growth measures, such as sales growth, market share, new product sales, and diversification (for example, Buzzell, Gale, and Sultan 1975: Hambrick et al. 1983: Schoeffler, Buzzell, and Heany 1974). Performance in the pharmaceutical industry has been largely evaluated from a profitability perspective. Some of the major findings on the returns to RED in the industry are shown in Table 3.2. As mentioned on p. 93, for the purpose of this research, corporate performance will be evaluated using size and growth measures (that is, market share). ; ' ;.---. ;.n .g.— -.,. n;- ....e. . 1 , Studies of new product development have shown that equal RED commitments do not necessarily translate into effective RED efforts. Effectiveness is considered to reflect the differential competencies of firms to convert RED resources into actual product developments, that is their success in converting New drug Applications (NDAs) to New Chemical Entities (NCEs) and in concentrating on NCEs versus other new products. Both these measures capture a firm's commitment to new product development efforts through RED. 3.5-2.2. WW Organizational behavior studies lend preliminary support to the view that the mean level of marketing effort increases from‘the "reactor" to "defender" to "analyzer" to "prospector" strategy types. According to Miles and Snow (1978), prospectors are often pioneers into new markets, while analyzers are often "second-in" after prospectors, and 104 Table 3.2. Returns to Pharmaceutical RED Author/Year Major Findings Baily (1972) Statman (1983) Joglekar and Patterson (1986) Grabowski and Vernon (1990) Econometric analysis showed that nominal pretax returns to pharmaceutical RED dropped from more than 30 percent before 1962 to less than 15 percent after 1962. Nominal after-tax returns on pharmaceutical RED declined from 20 percent in the mid-1950s to about 10 percent in the late 1970s. Real after-tax return on RED pharmaceutical was approximately 6 percent for a new drug compound beginning in the mid-1970s. Average new product introductions in the 1970s earned an after-tax return of 9 percent, which was in line with the industry's cost of capital. 105 frequently achieve above-average new product success rates. McDaniel and Kolari (1987) found that the mean marketing effort was higher for analyzers than for defenders for 15 of the 16 marketing variables, and the reported mean was higher for prospectors than for analyzers for 14 of the 16 marketing variables. Similar results were found by Meyer (1982) and Hambrick (1983) . The higher RED and marketing effort expended by prospectors supports the image of these organizations as active in the development of new products (Hambrick 1983). The development of NCEs that are true blockbusters is extremely rare today. Most new products are incremental improvements over existing therapies (W5; 1987: W51 1987) , and companies must promote these products into a market already using those therapies. The importance of marketing as a success factor in the pharmaceutical industry is illustrated by Zantac, which was the largest selling drug in 1988. When it was first introduced by Glaxo, it was only marginally different from the previous world leader, Tagamet. There was relatively little medical incentive to use Zantac rather than Tagamet and many physicians continued to prescribe Tagamet. Without a creative and powerful market effort, Zantac probably would have been another "me-too" product. Glaxo’s aggressive marketing efforts made the difference. To capture a firms’ competitive position with respect to the marketing function, the level of advertising expenditure 106 is considered here. 3.5.2.4. Relationship between Entry Timing and Resource Commitments To obtain a complete picture of a firm’s past andf current strategic investments, Day and Wensley (1988) proposed linking the firm’s effort level to the value of first-mover advantages. Timing of entry should be consistent with the firm’s capabilities on the point in time that the market is observed. A firm with strong RED capabilities would find it advantageous to be a first mover. A firm with strong marketing skills would find it advantageous to enter later (Lieberman and Montgomery 1988). In analyzing twelve case histories from various industries, Schnaars (1986) found that firms with strong marketing skills tend to engage in later entry. For example, IBM entered mainframes after Sperry-Rand and personal computers after Apple: in both cases, IBM was able to gain a commanding market share over the earlier entrants. In the consumer goods industry, Procter and Gamble relies heavily on later entry to dominate markets opened up by pioneers. Miller, William, and Wilson (1989) explored not only the extent to which entry order determines market share but also competitive factors that later' entrants. might. employ' to overcome a pioneer’s advantages. Their results showed that pioneers invest heavily in product RED and are relatively more competitive in trems of superior product quality and 107 differentiation. Overall, followers had few successful competitive options other than promotion for gaining market share. This was confirmed in the study by Urban et al. (1986). Conglusign. In the ethical pharmaceutical industry, new product development occupies a central role in strategic resource deployment. The extent of a drug firm’s commitment to this activity can be assessed with respect to its RED function. Marketing commitments also are key in influencing firm performance. Finally, the literature also suggests that the level of commitment to strategic resources and timing of entry can affect performance. The theoretical and empirical findings related to RED and marketing commitments and performance suggest the following research questions : Question 2 : How is a firm’s new product development effort related to its commitment to RED? Question 3 : How does a firm’s commitment to RED affect performance? Question 4 : How does a firm’s commitment to marketing affect performance? Question 5 : What is the relationship between new product development efforts and firm performance? 3.5.3. Source of Innovation and Firm’s Competitive Position in_RED. In the discussion of the firm’s competitive position in RED, a factor that should be considered is whether the products are developed internally or obtained externally. 108 While a firm’s internal RED often is viewed as a critical determinant of technological leadership, this is not the only source of technical know-how. A firm that trails in product technology still may still be competitive by borrowing ideas from external sources and developing them for their market segments (Abell and Hammond 1979: Porter 1985). Transaction cost analysis provides a theoretical perspective for explaining how pharmaceutical firms organize for RED. 3.5.3.1. WM Transaction cost analysis (Williamson 1975, 1981, 1985) is increasingly ‘used to explain. how firms organize for activities along the value-added chain. This theory has been applied in the empirical analyses of production and supply activities (Monteverde and Teece 1982a, 1982b: Balakrishan and Wernerfelt 1986): the personal selling function (Anderson 1985): and channels of distribution (Klein 1986: Anderson and Coughlan 1987). With. respect. to iRED activities, the application. of transaction cost analysis has been limited (Willimanson 1975: Teece and Armour 1977: and Teece 1988) and only recently has it been tested in the pharmaceutical industry (Tapon 1989: Pisano 1990). Tapon (1989) argues that transaction costs are lower when firms negotiate contracts with outside laboratories for certain steps in the RED process, particularly basic research, that is, these costs are higher when firms conduct the same activities internally. Therefore, transaction costs 109 vary according to institutional arrangement and, it is the differences between transaction costs, rather than their magnitude, which determines the choice of arrangement. Transaction costs arise from three factors (Williamson 1985): (1) the frequency of transactions: (2) uncertainty surrounding the transactions: and (3) whether transactions are supported by any transaction-specific assets. RED projects in the pharmaceutical industry run for several years, and relevant transactions do not occur frequently. Therefore, the first factor is not applicable to the pharmaceutical industry. Uncertainty may have different effects. For example, in an uncertain environment, firms may desire greater flexibility and consequently avoid internationalization (Leifer and Huber 1977). Technological uncertainty may have the same effect (Balakrishan and Wernerfelt 1986: Walker and Weber 1984), that is the greater the level of technological uncertainty, the greater the disincentive to make versus buy. Walker and Weber (1984) found, however, that volume uncertainty provides an incentive to internalize. An empirical study of pharmaceutical firms (Pisano 1990) found that higher uncertainty, expressed in small numbers of RED suppliers, leads firms to internalize biotechnology RED in areas in which RED capabilities are concentrated in a few suppliers. Technological uncertainty has the most relevance for this study. As mentioned in chapter 2, the risks and 110 costs of pharmaceutical research are forcing firms to be more innovative and selective. As pharmaceutical innovation becomes more complex and. dependent. on increasingly sophisticated scientific investigation, firms increasingly will seek promising drug innovations from outside their own laboratories. Transaction-specific assets are defined as durable investments undertaken to support particular transactions and whose opportunity cost is much lower in other transactions, in other uses, or by other users should the original transaction be terminated. prematurely (Day' and. Klein 1987). Asset specificity can be expressed in terms of specific physical assets, specific sites, specific human assets, and specific dedicated assets. Higher transaction-specific assets arising from the latter three will encourage firms to RED (Tapon 1989). 3 .5. 3. 2 Sourcing of Innovation Patterns in the Pharmaceutical 113th One distinguishing feature of firms that successfully manage technology is a balanced strategy of both internally and externally developed technologies (Mansfield 1987). The discussion on how pharmaceuticals firms organize for RED (Section 2.4.3.2) suggests that an increasing number of firms are moving toward external acquisition. Tapon (1989) proposes three major factors driving pharmaceutical firms to form long-term RED projects with other firms and university 111 laboratories: the effectiveness of patent protection, the rising importance of basic research in the innovation process, and the relative failure of traditionally organized, in-house laboratories. According to industry experts, two major forces are: (1) cost reduction, when outside services are cheaper, including avoiding investment in large, expensive operations, and (2) the inability to maintain a pipeline of successful drugs. Since many costs are related to product development and sales, external procurement means the firm need not maintain high fixed-cost operations in either facilities or salesforce, (that is, it can avoid transaction-specific assets). Since technological innovations come so fast and from such diverse origins, it would be impossible for a company to be adequately staffed internally to keep abreast of all new discoveries. A successful strategy is to harvest discoveries from the myriad innovative research locations. The external strategy chosen for examination in this study is licensing: it is a more rapid mode of entry than other alternatives such as joint ventures and it is the most widely used.mechanism in the pharmaceutical industry. Marion Laboratories exemplifies a firm that has successfully used a licensing strategy for product market expansion. By licensing products with therapeutic value from foreign competitors, Marion has gained a strong foothold in the cardiovascular therapeutic category with the drug Cardizem, licensed from a 112 Japanese company. As suggested in the literature (see Crawford 1985; Killing 1978; Lowe and Crawford 1983: Shahrohki 1987) the need to ensure speedy market introductions, reduce or avoid high R&D investments, reduce new product failures, diversify product range, and keep abreast of external technology are powerful internal motivators for technology acquisition through licensing. For this study, a distinction is made between outlicensing and inlicensing. The former refers to the external licensing of a drug for another overseas firm to market, while the latter refers to drugs acquired from another firm. Table 3 . 3 shows the cumulative number of drugs developed in-house and licensed-in by the top 50 pharmaceutical firms in 1989. An earlier study by the National Academy of Sciences (1983) found that almost one-third of new drug introductions into the U.S. market have been sold under a patent license (see Table 3.4). There are advantages and disadvantages to product market entry through either internal mm or licensing. For the former, the major advantage is the use of existing resources, while the major drawbacks are the long time lag to breakeven and unfamiliarity with new markets which may lead to financial errors. The two key advantages to licensing are rapid access to proven technology and reduced financial exposure. As Killing (1978) points out, licensing avoids the risks of Table lJlIB Table 3.3. Cumulative nunber of Drugs, Developed Both In-house and by Licensing, 10;) 50 Pharnaceutical Fine, 1989 0M8 Position Position Conpany Total In- in 1989 in 1988 drug house License 1 (4) Bristol-Iver: 103 79 24 2 (1) lord: 4 Co. 98 75 23 3 (9) Ciba-Geiqy 96 62 34 4 (3) Rbone-Poulenc 94 58 36 5 (2) Johnson 4 Johnson 92 62 3o 6 (8) Lilly 91 78 13 7 (5) Elan 90 90 0 8 (6) Roche 90 65 25 9 (10) Hoechst 88 71 17 10 (7) SIithKline 81 54 27 11 (18) Anerican lone 64 46 18 Products 12 (15) Upjohn 64 45 19 13 (12) Fujisaua 62 45 17 l4 (l7) lrbalont 60 46 14 15 (13) Sandoz 60 41 19 16 (11) Warner-Lalbert 56 44 12 17 (28) Roussel Uclaf 56 29 27 1s (25) Anerican Cynalid 55 34 21 19 (22) Balloons 53 39 14 20 (27) Pfizer 52 37 15 21 (37) Genetecn 50 44 6 22 (19) Harrell Dow 50 42 8 23 (21) Boenrinqer Inqelheil 50 36 14 24 (29) Bastian Kodak 49 29 20 25 (16) Sonating as 43 4o 3 26 (20) Sanofi 48 37 11 27 (36) Yananouchi 48 29 19 23 (35) Scherinqulough 47 35 12 29 (14) Takeda 46 42 4 30 (43) Abbott 46 28 18 31 (39) Mitsubishi Kasei 44 36 8 32 (42) lkzo 44 35 9 33 (33) Squibb 41 34 7 34 (41) Kyova Mo 41 34 7 35 (24) Glaxo 40 21 19 36 (62) Row: 39 31 8 37 (25) syntax 39 27 12 38 (32) Monsanto 39 26 13 39 (31) Beechal 38 32 6 40 (40) Ylssul 36 36 0 :11u4 Table 3.3. continued 41 (49) Sulitolo 36 23 13 42 (34) Astra 36 19 17 43 (23) Sankyo 35 26 9 44 (50) Pharlaetec 34 33 1 45 (44) ICI 34 28 6 46 (48) Dupont 34 26 8 47 (30) Bayer 34 22 12 48 (45) Meiji seika 34 21 13 49 (51) snionogi 34 21 13 50 (- ) Pincus 33 27 6 Source : 35:19 (1989), World Pharnaceutical leis, (January 20), pp.1 - 20. 115 Table 3.4. Licensed versus. Self-Originated Drugs Sold by U.S. Firm, Stratified by Pin Size 1963-1968 1969-1974 1975-1980 8 Self Originated Snail 50.00 51.72 41.67 lediul 55.56 26.67 52.63 Large 77.27 00.00 43.33 8 Licensed tron U.S. Sources Slall 20.59 17.24 22.22 Rodin 0.00 26.67 21.05 13:94 4.55 0.00 0.00 8 Licenm fro- !oreig) Sources Snail 29.41 31.03 36.11 ledlul 44.44 46.67 26.32 large 18.18 20.00 16.67 Source : lational Acadely of Sciences (1983), .. A Washington, D.C. : Iational Academy Press. 116 product development by exploiting the experience of firms that have already developed and marketed the product. This access to technology is particularly important to firms that want to establish a broad product portfolio of drugs to treat a broad spectrum of interrelated ailments.“ Licensing is not a substitute for internal technical competence, however, and the acquired technology will not be proprietary. Another drawback is that licensing agreements is they restrict sales to certain areas such as only the U.S. market. Marion, for example, had to limit its sales of Cardizem to the United States. For long-term sustained growth, an increasing market penetration or a steady stream of new drugs is necessary. Conclusion. Although internal research and development capabilities often are viewed as critical determinants of competitiveness, these are not the only possible source of technical know-how. Through a variety of licensing agreements, an increasing number of major pharmaceutical firms are tapping into the RED capabilities of competitors and other organizations to supplement their own RED. Transaction cost analysis was used to explain firms' choices between in-house and external sources of R80. The above discussion leads to the following research questions: uln era-pie is the treatnent for cancer. Became cancer patients have to go extrenely painful chenotherapy, vhich increases their anexiety vhile lowering their inunity, both tranquilixing and antiinfective drugs are given. simplelental nutritional products are also necessary to Iaintain the health of cancer patients. 117 Question 6 : Is there a relationship between a firm’s internal RED and its new product development efforts? mestion 7 : How is performance influenced by a firm's internal RED? Question 8 : Do firms that develop drugs internally also engage in greater outlicensing? Question 9 : Do firms with strong new product development efforts also engage in more outlicensing? Question 10 : Does high commitment to R&D affect the firm's outlicensing behavior? Question 11 Does a firm's outlicensing behavior affect performance? 3.5.4 W The decision by pharmaceutical firms to develop drugs depends largely on how they perceive their strengths and weaknesses. Marked differences among companies often are based on their relative strengths in different therapeutic markets and on whether the market is in the growth, maturity, or decline stage. Previous research on technological innovation (Nelson and White 1977) suggests that when technical advance is cumulative, a firm's efficiency in performing a particular type of R&D project depends on its experience with similar projects. This learning curve effect allows the firm to build in-house expertise, thereby reducing transaction costs for subsequent projects undertaken internally. This line of argument also is supported by Porter (1990) and Foxall (1983) . Porter strongly advocates the continual replacement of old 118 products with improved or new ones. Foxall suggests that by concentrating efforts on established patterns of product development, the search for new products is facilitated. Some pharmaceutical firms commit themselves to -'many therapeutic areas and spread their resources too thin. In other firms, the diversification into many therapeutic subclasses is indicative of both their manufacturing and their RSD mobility and implies some basic knowledge of several classes of products. This may enable the firm more readily to transfer or add manufacturing resources in yet another therapeutic area. In other words, the firms have some basic knowledge in several areas of chemotherapy and can build on this knowledge as scientific opportunities become evident (Cocks 1975). This leads to the following research question: Question 12 : How is therapeutic market diversification related to a firm's new product development efforts? 3-5-5 Therapeutiuifferentiation The FDA drug classification scheme provides a basis for distinguishing drugs that are first to offer some new therapeutic advantage from drugs that merely duplicate existing therapies. This scheme classifies three types of drugs. Type A : Important Therapeutic Gain - the drug may provide effective therapy or diagnosis for a disease not adequately treated or diagnosed by any marketed drug, or provide improved treatment of a disease through improved effectiveness or safety (including decreased abuse potential). 119 Type B : lbdest Therapeutic Gain - the drug has a modest but real potential advantage over other available marketed drugs, such as greater patient convenience, elimination of a significant adverse reaction, less frequent dosage schedule, usefulness in specific subpopulation of those with the disease (for example, those allergic to other available drugs), and so forth. Type C : Little or No Therapeutic Gain - the drug essentially duplicates in medical importance and therapeutic usage one or more drug already marketed. The first drug to be marketed, even if not a blockbuster, generally earns significant market recognition. Factors that lead to first-mover advantages were discussed earlier in this chapter. Followers must differentiate themselves from the first product in order to gain market share. There is a concern among industry analysts that much of the increased NCE activity in the late 19803 simply produced "me-toos”' rather than major breakthroughs . According to the industry, however , products that are launched later generally do better because they are based on more recent scientific discoveries. Since drugs differentiated as Type A and Type 8 offer firms a stronger advantage over competitors, it is of interest to determine what factors influence the ability of the firm to develop highly differentiated drugs. Therefore : Question 13 : Are firms that are successful in their new product development efforts also likely to have higher therapeutically differentiated drugs? 121 're-too' is generally a product which has been developed by Iodifying the stmctme of an existing product. In sole cases, however, research paths converge, and siailar products are .MMMMmdhnoumauhnwfihhshutmmhdufieahoflmn 120 Question 14 : How is a firm's internal RSD related to its ability to produce therapeutically differentiated drugs? Question 15 Does diversification into may therapeutic markets encourage the development of highly therapeutically differentiated drugs? ' Question 16 What is the relationship between therapeutic differentiation and firm performance? Question 17 How is outlicensing influenced by therapeutic differentiation? 3 ~5-6 Wrasse! The rapid rate of technological change and lengthy approval process shorten the commercial period in which R&D investment must be recovered. As a consequence, firms must operate globally to maximize the sales potential of new products (Burstall 1985). A firm's spatial strategy can be assessed by looking at where NCEs are first marketed. It was mentioned in chapter 2 that a successful product must be introduced simultaneously into each of the three major regions: the United States, Europe, and Japan. These markets currently account for at least 60 percent of worldwide pharmaceutical sales. Ohmae's (1986) "triad view" states that, to be successful, firms must simultaneously begin marketing new products in these three major developed regions. Although this is the conventional wisdom in the industry, no empirical research has attempted systematically to determine whether the firm's spatial strategy influences performance. 121 When a drug is developed, it is not necessarily introduced in the home country. Countries that attract NCEs are likely to have a strong demand for pharmaceuticals, tend to have higher levels of real prices and GDP growth, and are likely to have consumers who spend a higher proportion of their income on medical expenses. In chapter 2, discussion of the U.S. health care industry pointed to increasing drug prices and household expenditures on health care. This suggests that the United States should be an attractive first market for drugs, but the strict regulatory approval considered the most costly in terms of time and.resources) may mean that other countries are more attractive first markets. Therefore : Question 18 Does therapeutic market diversification influence whether a firm markets drugs first in the United States? Question 19 Are firms that are strong in new product development efforts likely to market drugs first in the United States? Question 20 What is the relationship between internal R&D and a firm's marketing of drugs first in the United States? What is the relationship between drugs that are first marketed in the United States and firm performance? Question 21 3.6 Conclusion The above discussion centered on proposed relationships among (1) each component of the competitive positioning strategy variable and performance: and (2) the competitive positioning strategy components. The purpose of this chapter 122 was to provide a theoretical framework for studying the competitive positioning strategy conceptual framework developed in chapter 1. A summary of the research questions is provided in Table 3.5. In the next chapter, a discussion of the specific hypotheses to be tested will be addressed. 123 Table 3.5 Sunary of Research Questions 1. Tiling of entry Ql. How is entry tiling related to perforaance? 2. nan and Marketing Couitlents Q2. How is a firn’s new product developnent efforts related to its conth to RSD? Q3. How does a firl’s coalitlent to RED affect perfornance? Q4. How does a firl's couitlent to narketing affect perfornance? Q5. What is the relationship between new product developnent efforts and fire perfornance? 3. Source of Innovation and Outlicensing Q6. Is there a relationship between a fin's internal RED and its new product developnent efforts? - Q7. How is perforaance influenced by a firl’s internal RiD efforts? Q8. Do fires that develop dnigs internally also engage in greater outlicensing? Q9. Do firns with strong new product developnent efforts also engage in greater outlicensing? Q10. Does high conitnent to MD affect on the firl’s outlicensing behavior? Q11. Does a firl's outlicensing behavior affect perfornance? 4. Therapeutic Diversification Q12. How is therapeutic narket diversification related to a firl's new product developnent efforts? 5. Therapeutic Differentiation 013. Are firm that are successful in their new product developnent efforts also likely to have higher therapeutically differentiated drugs? on. now is a firn’s internal RED related to its ability to produce therapeutically differentiated drugs? on. Does diversification in any therapeutic narkets encourage the developnent of highly therapeutically differentiated drugs? lw244 Table 3.5 (cont) 6. 016. What is the relationship between therapeutic differentiation and firl perfornance? Q17. How is outlicensing influenced by therapeutic differentiation? Spatial Strategy Q18. Does therapeutic narket diversification influence whether a fire narkets drugs first in the United States? 019. Are fires that are strong in new product developnent efforts likely to narket drugs first in the United States? 0mwmsmnmmmmmMnmmmmmm“mumsmmmMnmfim in the United States? Q21. What is the relationship between drugs that are first narketed in the United States and fire perforaance? CHAPTER FOUR HYPOTHESES AND RESEARCH DESIGN The focus of this study is on the relationship between competitive positioning strategy and performance. The research questions addressing this association were presented in chapter 3. This chapter reviews the measurements of competitive positioning and defines and operationalizes the performance criteria employed to evaluate the effectiveness of a firm’s strategic actions. The databases used and the sample selection procedure are discussed. The statistical hypotheses then are presented, and the chapter concludes with a discussion of the statistical methodology. 4.1 Winn-.1911 4.1-1. W In ‘this section, the components. of the competitive positioning strategy are defined and measured. The specific manifest variables are: (1) timing of entry: (2) competitive position in R&D: (3) competitive position in marketing: (4) source of innovation: (5) therapeutic market diversification: (6) therapeutic differentiation: (7) outlicensing behavior: (8) spatial strategy: and (9) new product development efforts. Each construct is presented below: their measurement and data 125 126 bases are summarized in Table 4.1. 4.1.1.1. Timing_gfi_fintzy Many studies of first-mover advantages have tested their propositions on either the PIMS data (for example, Robinson and Fornell 1985: Robinson 1988: Lambkin 1988: Miller et al. 1989) or on primary data (Urban et al. 1986). In the PIMS data, entry timing is based on the time a business entered its market. A pioneer is first in developing products or services, an early follower then enters the still growing and dynamic market, and a late entrant arrives in a more established market (Robinson 1988: Lambkin 1988). The timing of entry variable will be used here to differentiate firms as early or late entrants, a dichotomous classification supported in the Urban et al. study (1986) which suggests that entry order can best (most parsimoniously, at least) be considered a dichotomy: early and late. There is a consensus in the literature that timing of market entry is the appropriate criterion for first-movership (Lieberman and Montgomery 1988) . ‘ Here, for the order of entry, 1 = first, 2 = second, and so forth. This measurement also was used by Urban et. al. (1986) and by Green and Ryans (1990). To differentiate a firm as an early or late entrant, three figures are considered: the total number of therapeutic markets in which a firm competes in, the number of times a firm enters first (=1) or second.(=2) in different therapeutic 14217 Table 4.1 Measures Used in the Study CUMSTRUCTS MEASURES DATA SOURCES Product Market Positioning Variables 1. Conpetitive Position in Research and Developnent la. Conitaent to RID RID intensity (Total fire R6D)/( Worldwide Annual Reports (RSDIITRMSITY) health care sales) 10—x reports 1h. RSD effectiveness (New Product Developnent Efforts) (1) RED orientation (Cumulative number of MCEs FDA, Paul de Uaen (RSDORIRMT) approved)/(Cumulative number Drug Product of [Ms subaitted) Index/Mew Drug Analysis (ii) Fire’s conth to (Cumulative nunber of lens Paul de Raen Mew ICE developnent introduced)/(Qmulative Product Analysis/ (PRODUCT) number of all products low Product Survey introduced) 2. CoIpetitive Position in Marketing Advertising (Total advertising dollars)/ Annual Report, intensity (worldwide health care CUIPUSTAT (ADVERTISE) sales) 3. Source of Innovation Internal RED efforts (Cumulative number of own RAD SCRIP (EISTORY) drugs in developnent) /(cumulative RID products in developnent) 4. Therapeutic Market Diversification Diversity in therapeutic ( lumber of therapeutic aarkets Annual reports, aarkets (DIVERSITY) in which the fire has sales)/ Paul de Saen New (Total number of aarkets) Drug Survey [Mew Product Survey 128 Table 4.1 (con’t) 5. Therapeutic Differentiation Therapeutic (Cumulative number of drugs given a FDA Differentiation (le8) Type A and B rating)/(Cumulative nunber of NCEs) 6. Outlicensing Outlicensing behavior (Cumulative number of MCEs licensed)/ Paul de Raen (LICEISB) (Cumulative number of internally Drug Product developed new drugs) Index 7. Spatial strategy Marketing of (Cumulative number of ICES introduced Paul de Raen drugs first in the in the United States) /(Cumu1ative nunber Drug Product United States (ORIGIN) of internally developed new drugs) Index Perforlance Variables 8. Perforaance (i) Dowestic narket share (Total dowestic RX sales/Total Annual Reports, (MSTIC) U.S. narket volume of all 10-uu Reports ethical drug sales) (ii) Global narket share (Total foreign Rx sales /Total Annual Reports (GLOBAL) global narket volule of all 10-x Reports ethical drug sales) 129 markets, and the ratio of the number of times a firm enters first and second to the total number of therapeutic markets it competes in. Firms that compete in fewer than 35 therapeutic markets, have fewer than 20 first and second entries, and have a ratio of less than 0.5 are classified as late entrants. 4-1-1-2. W The importance of both R&D and marketing in the pharmaceutical industry was covered in chapter 3. DiscusSed below is the R&D strategy measurement, followed by the marketing strategy measurement. To determine a pharmaceutical firm's competitive position with respect to R&D, its degree of commitment to R&D activity and the effectiveness of its RSD efforts should be considered. W. This variable also reflects a firm's RSD intensity and is measured by the RSD-to-sales ratio (RDINTENSITY). Wall Street analysts use an absolute (gross R&D spending) and a relative measure (R&D as a percentage of sales) to quantify R&D productivity among pharmaceutical firms (W 1989b) . Absolute measures of R&D are plagued with problems, however, as they do not offer evidence of how effectively one company spends its research dollars relative to its competitors. ‘When firms are of equal size, the RED-to- sales ratio is a good descriptor of the relative emphasis firms place on R&D. When the size distribution has a high 130 variance, this ratio fails to capture one important aspect of differences in R&D commitment: the absolute amount of resources allocated to RSD. Since absolute R&D spending increased dramatically among some firms during the 19805, the size factor needs to be taken into account. 3&D_Effegtiyeng§§. A real challenge in the pharmaceutical industry is introducing a steady stream of drugs from R&D efforts. To measure firms’ competency at turning RSD resources into actual new products, a latent variable, New Product Development Efforts, is captured by two variables: RaD orientation and Commitments to NCE Development. RSD orientation (R8DORIENT) is the ratio of cumulative NCEs approved to the cumulative NDAs submitted. To ascertain a firm's commitment to NCEs versus other types of new product introductions (PRODUCT), the ratio of cumulative NCEs introduced to cumulative new product introductions is used. This measure reflects the firm's commitment to developing NCEs rather than imitative products, such as combination or modified products. Obviously, compared to "me-toos" or combined products, NCEs are more rare and require substantially larger resource commitments, but their potential for competitive differentiation and profit is much greater. Substantially more duplicate products need to be introduced to achieve the same sales level, and often these products are unsuccessful. 131 Cumulative figures for the two measures of R&D effectiveness were considered between 1971 and 1989. The use of cumulative rather than annual figures was necessary to smooth out short-term fluctuations and to account for-the lags between NDA filing and NCE approval. This is the method recommended by Cool (1985). Due to a lack of systematic data on firms' submission of Investigational New Drugs (INDs), this study cannot directly determine a f irm's competency in converting INDs to NDAs. Since only about 3 percent of IND filings reach the NCE approval stage, the two measures used here, R&DORIENT and PRODUCT, provide stronger measures of a firm's RSD effectiveness. 4.1-1.3 Ccmnetitixe_Rcsiticn_in_narketins In this study, a firm’s competitive position in marketing is reflected in the firm's advertising strategy. Advertising is a key marketing tool in the pharmaceutical industry. This study focuses on adverising efforts to the medical and paramedical professions. Here, advertising intensity is determined by taking the ratio of total advertising dollars to worldwide health care sales (ADVERTISE). In summary, the key variables used to capture a firm's competitive position in R&D and marketing are as follows. 132 Research and Development Commitment to RED 1. RED intensity (RDINTENSITY) = (Total firm RED)/(Worldwide health care sales) RED Effectiveness (New Product Development Efforts) 2. RED Orientation (R&DORIENT) = (Cumulative number of NCEs approved)/ (Cumulative number of NDAs submitted) 3. Firm’s commitment to NCE development (PRODUCT) = (Cumulative number of NCEs introduced)/ (Cumulative number of all products introduced) Marketing Commitment to Marketing Advertising intensity (ADVERTISE) = (Total advertising dollars)/ (Worldwide health.care sales) 4.1-1.4. W As discussed in chapter 3, the ability of firms to develop and exploit technological know-how internally is an important dimension of competition. Many factors, however, may prompt firms to consider external sourcing of RED. Decisions about which technical capabilities to develop internally and which to access through licensing arrangements with external sources will affect a pharmaceutical firm's viability in an evolving technological environment. A firm's tendency to rely on external sources for RED also depends on the firm’s historical pattern of RED procurement. For example, firms with experience in licensing arrangements are likely to continue engaging in this form of 133 external sourcing. Firms lacking that experience are more likely to find in-house RED more attractive. The historical propensity (HISTORY) of a firm to procure RED ideas internally or externally is operationalized by taking' the ratio of the cumulative number of "own .RED products" in development to the "cumulative number of RED products" in development where, the former refer to the drugs that originated in the firm's laboratories, and the latter refer to the total number of drugs developed both internally and externally. The difference between the numerator and denominator gives the total number of drugs sourced externally. To summarize, the source of innovation construct is measured by : Internal RED Efforts (HISTORY) = (Cumulative number of own RED drugs in development)/(Cumulative number of RED products in development) 4.1-1.5. W The degree of therapeutic market diversification is indicated by the variable DIVERSIFY, that is, the ratio of the number of therapeutic markets in which the firm has sales to the total number of markets considered for this study. As mentioned in Section 3.5.4. market diversification is indicative of the RED and manufacturing mobility within pharmaceutical firms. In addition, this index also shows the extent to which a firm follows a "focused" strategy, targeting efforts on only a few therapeutic markets, or a 134 "differentiated" strategy, spreading resources over several markets. Therefore, DIVERSIFY = (Number of therapeutic markets in which the firm has sales)/(Total number of markets). 4.1.1-6 WW Therapeutic differentiation is measured by the ratio between the cumulative number of drugs given a Type A and B rating by the FDA to the cumulative number of NCEs. Therefore : Therapeutic differentiation (DIFF) = (Cumulative number of drugs given a Type A and B rating)/(Cumulative . number of NCEs). 4.1.1.7 Outlicensins_flshaxior The outlicensing behavior of the firm is measured by the ratio of cumulative number of NCEs licensed overseas to the cumulative number of new product introductions: (OUTLICENSE) = (Cumulative number of NCEs licensed overseas)/(Cumulative number of internally developed new products). 4.1.1.8. W In order to determine a pharmaceutical f irm's commitment to the United States as a key market, the variable ORIGIN is considered in this study. Therefore, Marketing of drugs first in the United States (ORIGIN) = (Cumulative number of drugs that are marketed in the U.S.)/(Cumulative number of internally developed new products) 135 4.1.2. W In chapter 3, a distinction was made among financial accounting indicators, financial measures, and output market success indicators of performance. 'The latter, itf was concluded, best captured strategic performance for the purpose of this study. The importance of market share earned by pioneering brands has been established in chapter 3. Two market share measures will be used here: domestic market share (DOMESTIC), and global market share (GLOBAL). Both are based on sales volume, the most common way to define market share (Spilker 1989). Domestic market share is determined by dividing the firm's total U.S. market ethical drug sales volume by total U.S. market ethical drug sales volume. Global market share is computed similarly by dividing the firm's total worldwide ethical drug sales volume by total global market sales volume of all ethical sales. Therefore: 1. Domestic Market Share (DOMESTIC) = (Total domestic RX sales)/(Total U.S. market sales volume of all ethical drugs) 2. Global Market Share (GLOBAL) = (Total worldwide Rx sales)/(Total global market volume of all ethical drug sales) 4.2. W W 4-2-1- ERIE—QD_HQAE 136 Data on the effectiveness of each firm's RED efforts was obtained from the FDA. Under the Freedom of Information Act, the author requested annual data on the number of NDAs submitted by firms between 1971 and 1989. The request was made in January 1991 and the information was received in April 1991. 4.2-2. W Paul de Haen data bases provided much of the information for the study. His periodical publications include New Drug Analysis, which surveys all NCES introduced nationally, and new Product Survey, which covers all new drug products introduced. These data bases were consulted to obtain information on firms' new product introductions between 1971 and 1989. Paul de Haen also publishes Drug Product Index in an international and a U.S. edition, covering eight countries and the U.S. market, respectively. Both currently span the years 1950-1989 and focus on: nonproprietary drug name: trade name: therapeutic subclass: manufacturer: country of manufacturer: originating firm: originating country: date of beginning marketing in country: and country market. Paul de Haen International, Inc., is now a division of Micromedia, Inc., headquartered in Englewood, Colorado. 137 4.2.3. Wham Data on the source of innovation variables was collected from Scrip WOrld Pharmaceutical News, 1971-1989. At the end of every year, Scrip reviews the global pharmaceutical industry and ranks the top 100 firms based on the number of drug products a firm has in development. This number includes new products originating from both internal and external RED sources . 4-2-4- BEIIQIDBD§§_H§§§HI£§ Measures of performance were mainly extracted from company annual reports and lo-K statements. This concludes the overview of the major databases used in the study. Besides these databases, other information sources were made available by Upjohn. The next section discusses the issues involved in the sample selection for this study. 4.3. Won 4.3.1- W Several factors had to be considered in selecting a suitable sampling frame for this study. First, foreign firms were excluded due to the unavailability or unreliability of data on some of the strategic and performance dimensions. 138 Second, firms had to be operating as separate entities from 1971-1989. This criterion was adopted to reduce any bias that might result from a changing sample. Therefore, firms that were acquired or merged during this time were eliminated. Third, only firms with a significant commitment to the ethical drug business were chosen. That committment was defined as as more than 50 percent of sales from ethical drugs. 'Therefore, firms with.a large percentage of sales from either proprietary or generic drugs were excluded. The companies that met the criteria are listed in Table 4.2. 4-3-2. We There are ten major therapeutic categories in which a pharmaceutical firm may compete. Each can be further differentiated into subclasses. Since it was not possible to analyze all these subclasses, the study was limited to a few within each. Therapeutic categories dominated by OTC drugs were eliminated. Given the nature of competition in the OTC sector, these categories were eliminated to avoid possible confounding effects. This consideration also eliminated drugs from the nutritional and topical categories. As shown in Table 4.3, these two therapeutic categories contributed insignificantly to the sales of all prescription pharmaceuticals (about 11 percent) between 1976 and 1991. The subclassess chosen for examination in this study are 139 Table 4.2 Drug Tires in the Study Sanple fin. N e - e 10. ll. 12. 13. 14. 15. 16. 17. 18. Abbott Laboratories Anerican Cyanawid Anerican Bole Products Bristol-Myers Carter-Wallace Johnson and Johnson Eli Lilly and Conpany Marion Laboratories Merck and Conpany Pfizer Laboratories A.E. Robins Rorer Group Scbering-Plough G.D. Searle Saithkline Badman LR. Squibb and Sons Sterling Drugs Syntex The Upjohn Conpany Warner-Lalbert n...a Abbott Laboratories Lederle Ayerst Wyeth Bristol Laboratories Wallace Laboratories Walpole Laboratories Johnson and Johnson Mclleil Laboratories Ortho Pharnaceutical Corp. 8. Lilly Dista Marion Labs Merck and Co. Merck, Sharpe and Dohle Pfizer Roerig Robins Williaw B. Rorer, Inc. Plough Schering Searle Saithkline and french Squibb Breon Winthrop Syntax Borden Upjohn Laabert Parke Davis Warner-Chilcott a Only the ethical division is considered. Table 4.3. Sales of U.S. Prescription Pharnaceuticals by Therapeutic Categories, 1976-1991, in Millions of Dollars 1n4‘) Therapeutic Category 1976 1981 1984 1985 1986 1991 Cardiovascular $1,035 $2,100 $3,565 $4,150 $4,696 $7,550 Antiinfective 1,185 1,770 2,725 3,000 3,510 5,150 Internal Medicine 1,495 2,310 3,095 3,400 4,025 5,400 Mental Health 935 1,150 1,790 2,070 2,275 3,025 Total $4,650 $7,330 $11,175 $12,620 $14,506 $21,125 Percentage of Total 66 61 62 63 64 66 Drug Market Pain Control 785 1,560 2,070 2,305 2,610 3,190 Respiratory 430 730 750 900 1,060 1,375 lutritional 435 725 1,310 1,365 1,480 2,000 Topical 320 590 900 990 1,065 1,250 Total 2,020 3,655 5,040 5,560 6,215 7,815 percentage of Total 29 31 20 23 27 25 Drug Market Other 380 965 1,735 1,900 2,120 2,850 Total Drug Market $7,050 $11,950 $17,950 $20,080 $22,840 $31,790 Spource : Adapted froa Arthur 0. Little (1988). 141 cardiovascular, mental health, antiinfective, and internal medicine markets, which consistently have accounted for more than 60 percent of total prescription sales in the last two decades. In Appendix A, each drug is allocated to a therapeutic category according to its primary function in therapy for a certain body system, rather than in terms of the drug's chemical compound. Paul de Haen's classification system is useful in this respect. This concludes the discussion of the sampling frame and the therapeutic markets that are considered for this research. The next section looks at the research hypotheses that are tested in this dissertation. 4.4. Wheels At the end of the literature review in chapter 3, a number of research questions were raised. Specific research hypothesis will now be developed to reflect the basic research questions underlying this study. 4.4.1 W The discussion on the timing of entry effects tends to conclude that there is a negative relationship between timing of entry and performance. That is, pioneers tend to earn higher market shares relative to early followers, and early followers tend to have higher market share than late followers. To answer research question 1, that is, 142 the extent to what timing of entry is related to firm performance, the sample of firms is classified into two groups, early entrants and late entrants. Although no formed hypothesis was developed for research question 1, implied in the distinction between early and late entrants is the effect of entry timing on performance. 4.4.2 nggggigiyg Egfiigign in RED and ugzkgging As mentioned earlier, a firm's competitive position in RED and marketing is determined by its RED intensity and advertising intensity, respectively. Therefore, the following research hypotheses were posited. For early and late entrants: Research Question 2. How is a firm's new product development effort related to its commitment to RED? Hypothesis (H1). High commitment to RED has a positive effect on new product development efforts. Research Question 3. How does a firm’s commitment to RED affect performance? Hypothesis (H2). There is a positive relationship between a firm's commitment to RED and performance. Research Question 4. How does a firm's commitment to marketing affect performance? Hypothesis (H3). There is a positive relationship between a firm's commitment to marketing and performance. Research Question 5. What is the relationship between new product development efforts and firm performance? 143 Hypothesis (H4). There is a positive relationship between new product development efforts and firm performance. 4.4-3 W While licensing and collaborative research are expected to increase in the pharmaceutical industry, the discussion on the internalization of RED strongly suggests that a firm’s long-term economic success depends on its ability to develop and exploit internal technological know-how; Hence, for both early and late entrants: Research Question 6. Is there a relationship between a firm's internal RED and its new product development efforts? Hypothesis (H5). There is a positive relationship between internal RED and new product development efforts. Research Question 7. How is performance influenced by a firm’s internal RED? Hypothesis (H6). There is a positive relationship between internal RED and firm performance. 4.4-4 Qutlisensing Although U.S. pharmaceutical firms continue to derive much of their net income from domestic sales, the increasing globalization of the industry requires U.S. firms to expand to overseas markets as more and more European and Japanese firms make inroads into U.S. markets. The next three hypotheses are concerned with the factors that influence outlicensing behavior: the fourth hypothesis investigates the relationship 144 between outlicensing and performance. Research Question 8. Do firms that develop drugs internally also engage in greater outlicensing? Hypothesis (H7). Internal RED has a positive effect on outlicensing for the late entrants. This relationship is negative for the early entrants. The expected direction for the next three hypotheses are expected to be the same for both early and late entrants. Research Question 9. Do firms with strong new product development efforts also engage in greater outlicensing? Hypothesis (H8). There is a positive relationship between new product development efforts and outlicensing. Research Question 10. Does a high commitment to RED affect the firm's outlicensing behavior? Hypothesis (H9). High commitments to RED lead to greater outlicensing. Research Question 11. Does a firm's outlicensing behavior affect performance? Hypothesis (H10). There is a positive relationship between outlicensing activity and firm performance. 4.4-5 W In chapter 2, it was argued that competition in the pharmaceutical industry is best examined at the individual therapeutic level. The subclassess considered in this study are at different growth stages: in particular, the mental health, antiinfective, and internal medicine subcategories are experiencing greater competition as they approach the mature 145 stages. Consequently, one way to reduce risks is to diversify into emerging and growing markets is. A firm's level of therapeutic market diversity can positively influence its competitive position in RED. As argued on pp. 117/118, this diversity reflects the firm’s mobility in RED resources. Therefore, a high degree of diversification would be positively reflected in a firm's product development efforts, that is: Research Question 12. How is therapeutic market diversification related to a firm's new product development efforts? Hypothesis (H11). There is a positive relationship between therapeutic market diversification and new product development efforts. 4.4-6 W A drug's therapeutically differentiated properties are expected to covary positively with the firm's product development efforts and internal RED and negatively with a high level of therapeutic market diversification. In the pharmaceutical industry, specialization is often necessary to acquire in-depth knowledge of particular diseases before developing drugs with highly differentiated properties to treat them. Therefore, for both groups: Research Question 13. Are firms that are successful in their new product development efforts also likely to have higher therapeutically differentiated drugs? Hypothesis (H12). Research Question 14. Hypothesis (H13). Research Question 15. Hypothesis (H14). Research Question 16. Hypothesis (H15). The relationship outlicensing activity entrants and negative 146 Strong new product development efforts lead to higher therapeutically differentiated drugs. How is a firm' s internal RED efforts related to its ability to produce therapeutically differentiated drugs? There is a positive relationship between internal RED and therapeutic differentiation. Does diversification into many therapeutic markets encourage the development of highly therapeutically differentiated drugs? High therapeutic market diversification is negatively related to therapeutic differentiation. What is the relationship between therapeutic differentiation and firm performance? There is a positive relationship between therapeutic differentiation and firm performance. between therapeutic differentiation and is expected to be positive for early for late entrants. Because of first-mover advantages associated with early entrants, these firms are able to exploit their development of highly differentiated drugs on a global basis more effectively than late entrants. Therefore: Research Question 17. Hypothesis (H16). How is outlicensing influenced by therapeutic differentiation? Therapeutic differentiation is positively associated with the 147 outlicensing activity of early entrants. This relationship is negative for late entrants. 4.4-7 W A high degree of therapeutic market diversification can affect the firm's spatial strategy. Although some countries still have a high demand for acute drugs (such as antiinfectives), in industrialized countries demand has shifted increasingly to maintenance drugs (such.as medication for AIDS and cancer). This shift was illustrated in Table 4.3. Therefore, firms that have diversified into these therapeutic categories are in a better position to exploit opportunities in the growing U.S. market. Research Question 18. Does therapeutic market diversification influence a firm's marketing of drugs first in the United States? Hypothesis (H17). There is a positive relationship between therapeutic market diversification and the marketing of drugs first in the United States. New product development efforts and internal RED are expected to have a positive effect on the firm's spatial strategy. This is because of the firm's need to exploit economic opportunities in the U.S. market. Therefore: Research Question 19. Are firms that are strong in new product development likely to market drugs first in the United States? Hypothesis (H18). There is a positive relationship between new product development and the marketing of drugs first in 148 the United States. Research Question 20. What is the relationship between internal RED and a firm’s marketing of drugs first in the United States? Hypothesis (H19). There is a positive relationship between internal RED and the marketing of drugs first in the United States. The effect of the firm’s spatial strategy for product introduction on performance is expected to be negative for both late and early entrants. The global nature of the industry requires all firms to be major players in the the global market rather than concentrate on the U.S. market as their key source of sales. Therefore: Research Question 21. What is the relationship between drugs that are first marketed in the United States and performance? Hypothesis (H20). There is a negative relationship between drugs that are first marketed in the United States and firm performance. The causal relationships among the variables are shown in Figure 4.1: Table 4.4. summarizes the expected direction of the twenty hypotheses for both early and late entrants. The next section discusses the methodology used to test the statistical hypotheses. 4.5 Methodology To test the hypothesis in a simultaneous manner, covariance structure modelling was used. It merges the logic ES... .8 on 55.3. .825. .63.... .632 891.98 .8855. 595 so 38:38.5; $23... 115() Table 4.4 Expected Direction of Hypothesis for Early and Late Entrants Hypothesis Early Entrants Late Entrants 81. High conitnent to RED has a positive effect on + + . new product developnent efforts. ‘ 82. There is a positive relationship between a fin's + + conitaent to RED and perfornance. E3. There is a positive relationship between a fin’s + + couitnent to narketing and perfornance. B4. There is a positive relationship between new product + + developnent efforts and fire perfornance. ES. There is a positive relationship between internal + + RED and new product developnent efforts. B6. There is a positive relationship between internal + + RED and fire perfornance. 87. Internal RED has a positive effect on - + outlicensing for the late entrants. This relationship is negative for the early entrants. 88. There is a positive relationship between new product + + developnent efforts and outlicensing. 89. Sign oonitaents to RED lead to greater outlicensing. + + 810. There is a positive relationship between outlicensing + + activity and fin perfornance. 811. There is a positive relationship between therapeutic + + narket diversification and new product developnent efforts. 1112. Strong new product developnent efforts lead to higher 4 + therapeutically differentiated drugs. 813. There is a positive relationship between internal RED 4 + and therapeutic differentiation. 1114. Eigh therapeutic narket diversification is negatively - - related to therapeutic differentiation. 815. There is a positive relationship between therapeutic + + differentiation and fire perfornance. 115]. Table 4.4 (cont) Hypothesis Early Entrants Late Entrants 816. Therapeutic differentiation is positively associated + -' with the outlicensing activity of early entrants. This relationship is negative for late entrants. 817. There is a positive relationship between therapeutic + + narket diversification and the narketing of drugs first in the United States. 818. There is a positive relationship between new product + + developnent efforts and the narketing of drugs first in the United States. 819. There is a positive relationship between internal RED + + andtbelarketingofdrugsfirstintheUnitedStates. 820. There is a negative relationship between drugs that - arefirstaarketedintheUnitedStatesandfin perfornance. 152 of confirmatory factor analysis, multiple regression, and path analysis within a single analytical framework (see Bentler 1980) , selling (Aaker and Bagozzi 1979: Churchill and Pecotich 1982) , 1980) . Recent textbooks on multivariate analysis-have included chapters on covariance structure modelling (Bernstein 1988: Pedhauzer 1982) , and several textbooks have been devoted to this topic (for example, Hayduk 1987: Loehlin 1987). Applications of covariance structure modelling are now popular in such marketing fields as consumer behavior (Arora 1982: Burnkrant and Page 1982: Droge 1989: Ryan 1982), personal product adoption (Bagozzi 1983: Bearden and Shimp 1982), and marketing strategy and distribution channels (Gaski 1986: John and Reve 1982). Fornell (1987) regards covariance structure modelling as one of the ”second-generation multivariate analysis" that allows a more theory-based approach to research.” In fact, a fundamental feature of second-generation multivariate methods is their ability to integrate both theory and data. Specifically, covariance structure methods combine theoretical and empirical knowledge by: (1) modelling errors in observation (measurement or nonsampling error): ( 2) incorporating both theoretical (unobservable) and empirical (observable) variables in the analysis: (3) confronting theory 13First-generation aethods include multiple regression, wultiple discrininant analysis, factor analysis, principal cowponents, wultidiaensional scaling, and cluster analysis. 153 with data (hypothesis testing): and (4) combining theory and data (theory building). Although covariance structure methods often are used for causal analysis, they are not methods for determining causes: rather, they' are techniques applied. to a "causal model formulated by the researcher on the basis of knowledge and theoretical considerations" (Kerlinger and Pedhauzer 1982, p. 305) . Therefore, these techniques are useful in testing rather than generating a theory by requiring the analyst to be explicit about the theoretical knowledge, or lack thereof, s/he wishes to bring to bear on the analysis. Since causal modelling forces one to make explicit the assumptions, variables, and hypothesized relationships in a theory, a degree of certainty and precision is added to the theory and the research effort. In summary, covariance structure modelling rests on the logic of confirmatory analysis. "Confirmatory" implies that the analyst must make some explicit, substantive (theoretical), and measurable assumptions or hypotheses that can be tested statistically. When the observed data structure (as measured by the covariances) is closely reproduced by the set of estimated parameters, the model is confirmed, that is, the proposed theoretical model is judged to be consistent with the data. 4.5.1 We: 154 Several models for the analysis of covariance structure have been developed, and most applications use the LISREL (Linear Structural RELations) representation (Joreskorg and Sorbom 1978, 1981, 1984, 1988). A more recent program, EQS (Bentler 1985), is gaining popularity because it is easy to learn and apply to new modelling situations. LISREL can only be applied to standard.models, while EQS is equally robust for both standard and nonstandard types of models. An illustration of standard and non-standard models is provided by Bentler (1989, Chapter 5). In LISREL, errors of measurement.must be taken into account by the use of latent variables. In addition, key variables of relevance to the structural system must not have been omitted, and conditions and times of measurement must be correctly specified to obtain the hypothesized effects. These considerations often lead to standard types of designs characteristic of latent variable models, with repeatedly measured constructs, and each construct having multiple indicators. In this respect, Bentler (1986) describes the LISREL program as a factor analytical simultaneous equation model (FASEM) , highly analogous to cannonical correlations. Various types of effects of interest, such as direct.paths between the measured constructs and paths from residuals to latent factors, are not permitted. In addition, when the latent factor has only one indicator, the relationship between the 155 factor (F) and its measured construct (V) is set up as F e V, whereas careful study ‘will show ‘that a single measured variable cannot create a factor. Despite this limitation, this technique is often used in LISREL.to allow the program to run (for example, Jaworski and MacInnis 1989). EQS overcomes some of the limitations identified in the LISREL program by allowing both measured and latent variables to be used as criteria in the model. That is, the F8 and Vs are allowed to correlate. In addition, the Es and Vs are allowed to covary which is inadmissible in the LISREL program. In EQS terminology, observed or measured yariables are called Vs. Hypothetical constructs or unmeasured latent variables are called factors or F3. Residuals in measured variables are errors, or Es. Finally, the corresponding residuals in factors are called disturbances, or Ds. As in most model-building efforts, covariance structure analysis begins with the identification of relevant variables and hypothesizes which are exogenous and endogenous. For the former, variability is assumed to be determined by causes outside the causal model. In path analysis, no attempt is made to explain the variability of an exogenous variable with other exogenous variables. For endogenous variables, variation is explained by exogenous or other endogenous variables. In Figure 4.1, internal RED efforts (V2), therapeutic market diversification (V3), RED intensity (V4), and 156 advertising intensity (V5) are exogenous variables: the remaining variables (V1, V8, V9) and latent factors (F1, F2) are endogenous variables. Although not shown in Figure 4.1, relationships among the exogenous variables in the model are represented by curved lines with arrowheads at each end, indicating that one variable is not conceived as a cause of the other: This allows the exogenous variables to be correlated. The remaining relationships are causal, as indicated by the unidirectional arrows. The structural equation model set for Figure 4.1 is summarized in Table 4.5. 4.5.2 minus Since covariance structure analysis is similar to multiple regression, several key assumptions underlying multiple regression also hold true for covariance structure modelling. (l) The relationships among the variables are linear, additive, and causal. Consequently, curvilinear, interactive, or multiplicative relationships are excluded. (2) The model is recursive, that is, reciprocal causation between variables is ruled out. (3) The variables are measured on an interval scale. (4) Residuals are not correlated with the variables that precede them in the model. This assumption creates, for each endogenous variable, a causal path that is a weighted function of variables prior to this variable and an error term (the residual) that is unrelated to other system variables or other residuals. 157 TABLE 4 . 5 THE STRUCTURAL EQUATION MODEL SET 1 = Marketing of drugs first in the United States (endogenous) V2 = Internal RED (exogenous) ' V3 = Therapeutic narket diversification (exogenous) 74 = RED intensity (exogenous) V5 = Advertising intensity (exogenous) V6 = RED orientation (endogenous) V7 = Conitnents to ICE developnent (endogenous) 78 = Therapeutic differentiation (endogenous) V9 = Outlicensing (endogenous) V10 = Dowestic narket share (endogenous) V11 = Global narket share (endogenous) 1'1 = lew product developnent efforts (endogenous factor) 1’2 = Perforlance (endogenous factor) The structural equations corresponding to the nodal are as follows. (1) V1 = 8*81+ 844V2 + 84493 + 81. (2) 76 = 8481 + 82. (3) V7 = 8*1'1 + E3. (4) V8 = 6*8'1 + 8W2 - 6*73 4» E4. (5) V10 = 8482 + 85. (6) vii = 8*1’2 + E6. 0) v9 =Mq+zw2+uu+swa+a. a) El suu+8w3+my+u. 11563 (9) F2 = -B*V1 + 8*V2 + SW4 + BEVS + 8*V8 + 8*V9 + 3*F1 + D2° In these equations, 8 = standardized partial regression coefficients, which represent the path coefficients: V = variables defined in Figure 4.1: as = latent factors defined in Figure 4.1: = error terns in the V variables: and D = disturbance terns in the 8 variables. 159 (5) The variables have a multivariate normal distribution. To determine whether any of the assumptions are violated, several statistical analyses are used. These are discussed in the following section. 4.5-3 Statistioal_yalidation_of_tho_Assumotions Linearity. To determine whether relationships between or among variables are linear, a scatterplot of the residuals is examined. If nonlinearity is suggested by the scatterplots, three alternatives in correcting this problem are proposed. (1) The significance of nonlinear relationships can be determined by computing the correlation ratio: called eta squared (Hayes 1973), (2) Exponential terms can be added to the equation and tested for significant increases in variance for which they account for (Kerlinger and Pedhauzer 1973), 3) The predictor may be treated as a categorical variable by using either dummy coding or exponential terms in the path analysis (Kerlinger and Pedhauzer 1973). Recursivity. One way causality is assumed. Models involving reciprocal causation can be handled through two- stage-least squares (Duncan 1975) . Whether a certain model is recursive or nonrecursive can be determined only on the basis of knowledge, theoretical formulations, assumptions, and logical analysis of the research. Interval Scales. Billings and Wroten (1978) argue that the assumption of interval scale property is often 160 questionable, given the primitive state of measurement of many variables in the industrial/organization literature. Even though the data may not satisfy the requirement of interval scales, Bohrnstedt and Carten (1971) argue that multiple regression is still the recommended technique in the presence of ordinal data. Uncorrelated Residuals. The presence of autocorrelation has several effects on the analysis. (1) Least-squares estimates are unbiased but are not efficient, that is, they do not have minimum variance, (2) The estimate of 6’ and standard errors of the regression coefficients may be seriously understated, thereby giving a spurious impression of accuracy, and (3) Tests of significance may be invalid. The Durbin-Watson d statistic is used to determine whether the residuals of the endogenous variables are autocorrelated (Dillon and Goldstein 1984) . The test is based on the assumption that the errors constitute a first-order autoregressive series, that is, u. = put.1 + 64 |p| < 1, and the statistic is defined as : d = 2"- (9e " 6MP 2 en? The closer the d statistic is to the value of 2, the stronger the evidence that there is no autocorrelation in the 161 error. Evidence of autocorrelation is indicated by the deviation of d from 2 (Johnston 1984). Multivariate Normal Distribution. Besides estimating parameters and testing models with the traditional ' multivariate normal theory, EQS also allows the use of distribution-free estimation procedures, such as the elliptical and arbitrary distribution theoriesu When the raw data are available, the EQS (Bentler 1985) computer program also will calculate the Mardia (1974) coefficient for testing this assumption. For the normalized estimate of multivariate kurtosis, an objective is to have values close to zero: large values indicate a presence of positive kurtosis, while negative values indicate significant negative kurtosis. Highly skewed data and excessive kurtosis can affect parameter estimates, standard errors, and overall fit. The problem of data not meeting the normal distribution assumptions has received attention in the psychometric literature. J6reskog and SOrbom (1984) warned that standard errors must be interpreted with caution when the normality assumption is violated. Boomsma (1983) recommends using Maximum Likelihood (ML) estimation with caution when the skewness of the observed variables is larger than 1.00. Muthen and.Kaplan (1985) found that both ML and GLS estimators have inflated chi-square values when the skewness of the observed variables is approximately 2.00 in 162 absolute value. 4.5-4 W The framework for evaluating structural equation models follows closely the one proposed by Bagozzi and Ti (1988). When the assessment of input data and statistical assumptions are adequately met, the next two steps involve the assessment of the overall model fit and the internal structure of the model consecutively. 4.5-4-1 WIN- A popular indicator of the overall goodness-of-fit of any model is the 2:3 test. Essentially, the chi-square statistic compares the goodness- of-f it between the covariance matrix for the observed data and the covariance matrix derived from a theoretically specified structural model. Well-fitting models tend to produce a small chi-square value, or fail to reject the null hypothesis. Researchers such as Fornell and Larcker (1981), Satorra and Saris (1985), and Bearden et al. (1982) have identified several problems associated.with the chi-square test and have recommended the use of multiple fit criteria rather than reliance on a single statistic. For example, the chi-square test can be sensitive to small differences between observed and estimated data, especially when the sample size is large. Several supplemental fit indices have been proposed. For example, Bentler and Bonnett (1980) have developed normed and 163 nonnormed indices to indicate the fit of a theoretical model relative to the worst case (null) model. The normed fit index (NFI) is a measure of the percentage of total variation explained by the proposed model versus the null model.“ The authors argue that an NFI 2 0.90 indicates adequate fit. The nonnormed fit index (NNFI) takes into account the degrees of freedom in the model, and it can exceed the normed index in magnitude and can be outside the 0-1 range.“ 4-5-4-2 W. Concerns regarding the internal assessment of fit include looking at: (1) composite reliabilities for the latent variables: ( 2) normalized residuals: and (3) the significance of the parameters. The composite reliability is defined as : p. = (27).)3 var(T) (2:7).)a var(T) + 2:8,, where A = factor loadings: T - underlying true score: and e = error of measurement. the summation of the items comprising the composite variable (that is, the underlying latent variable). Composite reliabilities 2 0.6 are desirable. Normalized residuals greater than two indicate that significant amounts of variances are left unexplained by the 1‘ The Iatbeaatical derivation of the MRI and [MRI is presented in Appendix B. 164 model and, hence a specification error is likely. The evaluation of the fit of individual equations within a model involves computing (1) a squared multiple correlation for each structural equation and (2) t-values for individual parameter estimates. The squared. multiple correlations indicate the proportion of variance in each variable/latent factor accounted for by the equation. A t-value 2 1.96 indicates that the parameters are significantly different from zero . 4.5.4.3. Assessmenuflaliditx The criteria discussed so far have focused on issues of model fit. In addition, Bagozzi and Ti (1988) proposed broadening model evaluation criteria to include questions of validity. One way to assess validity is through a multiple group analysis. The need to perform a multiple group analysis can best be understood by considering two extremes. At one extreme, the populations differ with respect to the variables being measured. One then would expect the covariance structures in the various groups to be different" This in turn implies that the structural models which generate the corresponding covariance matrices also would be completely different. In such a case, doing a multiple group analysis is unnecessary: one could propose and test a different structural model for each group. 165 At the other extreme, assume that the covariance structures of the different groups are indistinguishable as far as the measured variables are concerned. In this case, one would like (1) to verify that one structural model describes each of the populations and (2) obtain a single set of parameter estimates for the model. Finding this single model is difficult if one analyses the data from each sample separately since parameter estimates would be less precise than if all the samples were analyzed simultaneously. Hence, a multiple group analysis should be able to verify whether a model that is invariant across all groups reproduces the sample data of each group to within sampling accuracy. Symbolically, assume m populations. Each has a covariance matrix, 2,, E,,. ....E,. If all the populations are identical, then 2:1 as 2, =..... -= 2,. If they differ, that is, a covariance matrix of a population differs from the others (such as It), then multiple group analysis can be used to investigate such similarities and differences. The goodness-of-fit X’ is used to assess the adequacy of the model across the groups. On the one hand, a significant x= test points to the rejection of the hypothesis of invariance, suggesting that there is an interaction between population membership and structural model. In other words, the resulting covariance matrices are different, and the various samples must be treated from different populations. 166 On the other hand, a non-significant X1 leads to a failure to reject invariance. This means that the model having identical parameters in all groups fit acceptably and the resulting covariance matrices are identical. One can then conclude'that the samples can be treated as arising from the same population. Hypotheses of equality across groups can be conducted anywhere along a continuum ranging from all parameters or testing a single parameter of interest. Hypotheses that are often tested across multiple populations include: > Equal Factor Loadings -- to determine whether the observed variables are measuring the same factors in each of the groups, that is, whether the factor loadings are the same: > Equal Factor Variances and Covariances -- if these are equal across groups while factor loadings are also equal, then the factors are more specifically similar in the various groups: > Equal Factor Regression Coefficients -- to determine whether path coefficients among latent factors are the same across groups: > Equal Factor Residual variances and Covariances -- to determine whether, in a model with latent dependent variables, the variances and covariances are equal across groups: and v Equal Unique or Error variances and Covariances -- except in special models, equality of error variances or covariances is the least important hypothesis to test. This is because if the prior hypotheses are accepted, then all of the parameters of the model are equal across groups. 167 4-6 Conolllsion In this chapter, an overview of the variables used in the study was followed by discussion of the data bases employed to construct the variables. The selection of pharmaceutical firms and therapeutic subclasses also was considered. It was pointed out that covariance structure modelling is used here to test whether the hypothesized structure model (Figure 4.1) is consistent with the data. It was noted that the EQS program will be used to estimate the structural model. The research findings are presented in the next chapter. CHAPTER FIVE RESULTS This chapter is divided into five sections. First, the firms are categorized into early and late entrants using the three criteria discussed on p. 129. Second, a comparison is made between the early and late entrants using the t-test difference of means. Third, the equivalence of the structural model across the two groups is demonstrated. The purpose is to show whether the model proposed in Figure 4.1 describes adequately the two groups and whether there are differences in structural paths between early and late entrants. Hypotheses one through twenty are examined for the two groups at this stage. Fourth, the findings from the two group are analyzed. Finally, the results are summarized. Implications are discussed in the following chapter. 5.1 MW Table 5.1 indicates how early and late entrants are identified in the study. The first column shows the total number of therapeutic markets in which each firm competes. The second column shows the number of times a firm entered those markets either first or second, which reflects the technological superiority of the firm. That is, a first 168 169 Table 5 . 1 Identification of Early and Late Entrants fin lmawwHCMHMs lfnaor mun 2 narkets in which coapeted second entry Coluwn 1 Abbott 42 22 .524 Anerican Cyanarid 44 24 .545 Anerican Bone 48 32 .667 Mamas Bristol Myers 41 22 .536 Carter Wallace 24 9 .375 Eli Lilly 46 28 .609 Johnson 6 48 20 .417 Rmmmu Marion 20 12 .600 Laboratories 148er 43 30 .698 Pfizer 42 22 .524 Robins 35 16 .457 Rorer 28 10 .357 Schering-Plougb 34 12 .353 Rune 20 7 .no SIithKline 45 34 .756 Squibb 42 22 .524 Sterling Drugs 30 lo .300 Syntax 26 11 .423 Upjohn 40 28 .700 Warner [Albert 44 28 .636 Mote: Data froa 1971 to 1989 were used for the identification procedure. 170 entrant is usually a leader in research and development while a second entrant may lag in research but has strong development capability. The third column is the ratio of the second to the first column. At one extreme, a firm entering first and/or second in all therapeutic markets would have a ratio of one. Ratios close to one suggest that the firm is an early entrant. At the other extreme, a ratio of zero indicates late entry in all therapeutic markets. A firm was classified as a late entrant if it: (1) competed in S 35 therapeutic markets: (2) had 5 20 first and second entries: and (3) had a ratio 5 0.5. Firms identified as early and late entrants are shown in Table 5.2. Only Marion Laboratories and Johnson and Johnson did not satisfy all three criteria. Although the former had a ratio of 0.6 and the latter competed in 48 therapeutic markets, they were classified as late entrants because they satisfied the other two criteria. The other seven firms in the late entrant category satisfied all three criteria. 5.2 W Table 5.3 presents the t-tests of differences between means of all the variables for early and late entrants. The significant t-values (p < 0.001) for all eleven variables strongly suggest that early and late entrants differ considerably in all the competitive positioning constructs. Since these constructs are contingent on timing of entry, this factor is appropriate as a discriminatory construct for this 171 Table 5.2 Firms Identified as Early and Late Entrants EARLY ENTRANTS LATE ENTRANTS Abbott American Cynamid American Home Products Bristol Myers Eli Lilly Merck Pfizer SmithKline Squibb Upjohn Warner Lambert Carter Wallace Johnson E Johnson Marion Laboratories A.H. Robins Rorer Group Schering-Plough Searle Sterling Drugs Syntex T-TESTS of DIFFERENCE in MEAMS between EARLY and LATE EMTRAITS 13713 Table 5.3 Early Entrants Late Entrants t- Variable Mean S.D. Mean S.D. value. Marketing of drugs 0.5717 0.096 0.4578 0.118 10.39 first in the United States (ORIGIN) Internal RED efforts 0.5183 0.084 0.3900 0.089 14.30 (EISTORY) Therapeutic narket 0.6639 0.080 0.3274 0.063 44.85 diversification (DIVERSITY) Outlicensing 0.5231 0.093 0.1799 0.108 33.30 (LICEISE) RED intensity 0.2332 0.031 0.1861 0.046 11.97 (RDIITEI) Advertising intensity 0.1828 0.031 0.1449 0.032 11.48 (ADVERTISE) RED Orientation 0.4127 0.106 0.2815 0.050 14.84 (RDORIflT) coalitlent to ICE 0.3110 0.094 0.1796 0.037 17.15 developlent (PRODUCT) Therapeutic differentiation 0.3577 0.081 0.2139 0.089 16.26 (DIET) Global narket share 0.0619 0.024 0.0289 0.018 14.80 (GLOBAL) Dowestic narket share 0.0599 0.024 0.0246 0.017 16.08 (DOMESTIC) * A11 t-values have p < 0.001. 173 study. In addition, the significant differences between the two groups suggest that analyzing the data in terms of samples belonging to two different populations is an appropriate method of analysis. 5.2.1 Equivalence of the Structural Models - Assessment of W The first step in evaluating structural equation models is to assess input data and the statistical assumptions underlying the estimation method- The assessment will reveal five important findings. (1) An examination of scatterplots of the residuals indicated that the residuals were randomly dispersed and.that the relationships proposed are most likely to be linear. (2) The scatterplots showed few problems with outliers, which suggests that the model has no mispecification problem. (3) All the variables in the model are measured on ratio scales. (4) The model is recursive in that the causal flow is unidirectional. (5) The Durbin-Watson statistic for early and late entrants is 2.079 and 2.021, respectively. Since these values are close to the value of 2 proposed by Johnson (1984) , the problem of autocorrelation is not severe in this study. The first autocorrelation is -0.046 for early entrants and -0.010 for late entrants. The method of estimation used, Generalized Least Squares (GLS), assumes multivariate normality of the observed indicators. As mentioned in Chapter 4, the objective is to 174 have estimates of multivariate kurtosis close to zero. Tables 5.4 and 5.5 present results on the skewness and kurtosis for the eleven variables in the model for early and late entrants, respectively. With the exception of domestic market share (DOMSH) for the late entrant group, all other variables have reasonable kurtosis and skewness (that is, < 1.00). Thus, the data for the two groups suggest that GLS, a normal theory based estimation procedure, poses no problem for this study since all the observed variables, with the exception of one, possess skewness of less than 1.00 in absolute value. As suggested by Bagozzi and Yi (1988) , any further anomalies in the output should be identified such as negative error' 'variances, nonsignificant. error' ‘variances, and correlations greater than one. These often point to problems with model specification errors and/or identification problems. For example, since the square of the regression parameter is the variance of the reparameterized residual, error variances must be positive (Rindskopf 1983) . Nonsignificant error variances suggest specification problems, since it is unreasonable to expect the absence of random error. Finally, correlations that do not fall within the i 1 range imply theoretical or empirical underidentification. In both groups, error variances were positive and significant given the sample size. Bivariate correlations among the variables were between i 1. For the data analyzed in the present research, none of the anomalies identifiedwwere 175 0000.9 u0u0.9 00h0.9 «H0094 030.94 000.94 000.794 0.30.94 900N.94 000N.9 N9s9.9 00033 0900.." 0059.9 9900.94 0009.9 0usfl.94 90NN9 9090.94 300.94 0Nhu.9 0009.9 9009.94 omega g g EH9 923 Eng 9< gun- 300 Panama Sauna .008 can-«Me» an; 090.5 mHmoHMDM 2 0002355 0 . 0 933—. 0000.94 9N09.94 0000.94 00N0.94 uflsn.94 9090.94 9909.9 9u00.94 0.30.94 909.".94 09NN.94 0000.05 N080 . 9 900a . 9 N000 . 9 900." . 9 n0: . 9 9909 . 94 ~9N0 . 9 0900 . 9 0090 . 9 «000 . 94 9000 . 9 0003510 g g :09 g Eng 2 Elus— guna EHEQ 98.0000 lung Ida—lune’ a; H.253 360.550— 2 0002357.. 0 . 0 0.309. 176 Tables 5.6 and 5.7 present the correlation matrix for early and late entrants, respectively. 5. 2 - 2 WM . The overall goodness-of—fit indices for early and late entrants are presented in Table 5.8 and Table 5.9, respectively. The p-values for the chi-square tests indicate a good fit of the overall model for both groupss The p-values for early and late entrants are 0.07787 and 0.19152, respectively. Using a p-value of 0.05, the models are not rejected for the two groups. Therefore, there is strong statistical evidence to suggest that the covariance matrix for the observed data and the covariance matrix derived from the theoretically specified structural model are similar to each other. The high normed fit index (NFI) and non-normed fit index (NNFI) verify the goodness-of-fit and indicate that a large percentage of the variation is accounted for by the model in both groups. The high values for these indices suggest that no further statistically significant improvement in fit is possible by adding structural paths to the model. 5.2.3 WW Although goodness-of-fit indices address the overall adequacy of a model, they do not explicitly provide information on the nature of individual parameters and other aspects of the internal structure of a model. 177 9999.0 0900. 0099. 0000. 0000. 0000. 0000. 9999.0 0909. 0090. 9000. 0900. 0000. 9999.0 0000. 0000. 0909.4 0000. 9999.0 0000. 0009. 0090. 9999.0 0009. 0900. 9999.0 0099. 9999.0 90:99 99999 0009 0999900 00000990 9G 0000090 0000. 0990. 0000. 0900. 9000. 0009. 0900. 9999.0 9000. 0000. 9090. 0000. 9900. 0000. 0090. 0090. 0000. 0900. 0009. 0900. 0900. 0000. 9900. 0000. 9999.0 0000. 9999.0 0000 . g 9000. 99909 0000. 0009 0000. 0999990 0900 . 30g 0090. 9< 0000. 000.090 0000. 0000900 0090. hh0000>09 0000. 0090009 9999.0 009009 9900900 000000>09 0090009 009009 e0ne0ue> 369020 00.59 uou x053: :o0ue0ouuoo 0.0 .60an 178 r-Enlfl’l L . 9999.0 0090. 0000. 0000. 0090. 9090.0 0000. 0000. 0000. 0000. 0000. 00899 9999.0 0000. 0000. 0000. 0909.: 9090. 0900. 0090. 9900. 0000. 00999 9999.0 0000. 0900. 0090. 9000. 0000. 0000. 0000. 0900. 0009 9999.0 0090. 9900. 0090. 0000. 9000. 9000. 9000. 0999900 9999.0 0000. 9000. 0000. 0000. 9000. 9000. 00000990 9000. 9< 9999.0 0990. 9000. 0009. 0909. 9999.0 0000. 0000. 0000. 0000. 0000090 9999.0 0000. 0000. 0900. 0000900 9999.0 9000. 9900. 000000909 9999.0 0000. 0090000 9999.0 009009 00299 00909 0009 0999900 00000990 9< 0000090 0000900 000000>09 0090000 009009 .09I0HID 369590 a»: you “3.3:: :00uu0ouuou 0.0 00900 179 Table 5.8 GOODNESS-OF-FIT INDICES FOR EARLY ENTRANTS x= = 25.816, d.f. = 18 p = 0.07737 NFI = 1.000 NNFI 0.999 Table 5.9 GOODNESS-OF-FIT INDICES FOR LATE ENTRANTS x2 = 20.671, d.f. = 13 p = 0.19152 NFI i 1.000 NNFI = 1.000 180 The composite reliabilities for the latent constructs, new product development efforts and performance, are 0.8716 and 0.9345, respectively, for late entrants and 0.9314 and 0.9301, respectively, for early entrants. All construct reliabilities are high in value (:5 2 0.6) for both groups, indicating that the measurement parameters are satisfactory. The internal quality of a model also can be assessed by examining the normalized residuals. For the late entrant group, the highest normalized residual was 0.116; for early entrants, the corresponding value was 0.126. These indices point to a good model fit for both groups, as normalized residuals greater than 2 indicate that significant amounts of variance remain unexplained and that a specification error is likely. To determine the significance of the structural parameters of the model, an investigation of the signs of the parameters and their standard errors using the t-test is required. The structural parameter estimates for the early entrant model are shown in Table 5.10; results for the late entrant model are reported in Table 5.11. Both the nonstandardized and standardized parameter estimates are provided. Within the context of an appropriate model, the test statistic in the nonstandardized solution is the univariate 2 test, where the null hypothesis is that a given parameter is zero in a given population. Large values (exceeding 1 1.96 for a = 0.05) suggest that the null 181 Table 5.10 STRUCTURAL PARAMETERS FOR EARLY ENTRAHTS [Instandudized Solution m PROMO! .264*V2 + .749*V3 + 1.125*V4 nzvznopnnur (P1) (.064) (.060) (.149 07701415 4.107’“ 12.400“ 7.568’)* nnmmsm(0)=.nwn -.mvw +.mmw macs ms'r III (.025)“ (.003) (.003.) mama ILMO -u% 25m WRITER (V8) = .453*F1 + .178*V2 - .055*V3 DIWIATIOI ( '091410 ( .077) (.078) 4.981 2.322 -.704 MLICEISE (V9) = .0675*V8 + .907*F1 - .198*V2 + .447*V4 (.0596) (.076 (.066 (.11 1.149 11.094)“ 2904‘1 3.940% mmncz = -.111*V1 + .174*V2 + .091*V4 + .025*V5 + .207*V8 + .095*V9 + 096*1'1 (.017)m (.017)... (.032) (.028) (.016)“ (.023)“ (.023) -6.662 10.295 2.341 .904 12.646 4.122 3.330 t u p < 0.05 p 0.42). With the exception of the licensing construct, all the equations for the early and late entrant groups had similar R”. For the licensing construct, the variance accounted for in the late and early entrant groups was 0.669 and 0.815, respectively. While the independent variables better explained licensing in the early entrant group, the fact that nearly half the variance was accounted for by these same variables in the late entrant group suggests a relatively good fit for this construct. 5.2.3.3 W The direct, indirect, and total effects for early and late entrants, respectively, are shown in Table 5.12. These decomposed effects only pertain to the correlations between the seven variables and firm performance. The analysis of decomposed effects is useful in certain situations: when indirect effects outweigh direct effects and when these two effects assume opposite directions, thereby canceling each other's impact to yield a trivial zero-order correlation. 188 Table 5.12 Direct, Indirect and Total Effects for Performance umwnmmme (swimmmes* Ramadan Variable Direct Indirect Total Direct Indirect Total Internal Ran Efforts (V2) .650’“ .102’“ .752’“ .965’“ -.000 .077’“ Therapeutic Diversification (V3) .040 .040 -.121“ -.121“ m Intensity (V4) .120’“ .116'“ .244‘“ .176’ .023 .199‘ Advertising Intensity .030 - .030 -.230*“ - -.230“’ low Product Developnent .432‘“ .179‘“ .611’“ -.4o0*“ .112“ -.293“* Efforts (r1) Therapeutic Differentiation (V0) .760‘“ .025 .735‘“ .136’ -.016 .120 Outlicensing (V9) .395’“ - .395’“ .120 - .120 narketing of Drugs First in -.479*“ - -.479“* -.o11 - -.o11 the 0.0. (V1) *“ p < .001 p < .01 ' p<.05 szaflilu-hum. _ ...‘. - 1 “2.1—0% 0 189 Important managerial insights can also be gained from analyzing the relative impact of the total effect of each variable on firm performance. Going by the direct impact alone is insufficient. With the exception of therapeutic differentiation (V8) and new product development efforts (F1), there are differences between the early and late entrants in terms of the magnitude and direction of their indirect effects. In particular, therapeutic diversification (V3) has a nonsignificant indirect for early entrants. This variable, however, had a significant but negative indirect effect for late entrants. Indirect effects of internal RSD efforts (V2) and R&D intensity (V4) were significant and nonsignificant for early and late entrants, respectively. In terms of the relative impact of the total effect of each independent variable, the three most significant variables that positively impact early entrants’ performance are internal RRD efforts, therapeutic differentiation, and new product development efforts. While RED intensity and outlicensing also had significant total effects on firm performance, they are marginally less important. Internal RSD efforts had the most significant total effect on late entrants' performance, followed by R&D intensity. Findings from 'Table 5.12 suggest that late entrants suffer from less successful new product development efforts, less effective advertising efforts and therapeutic 190 diversification efforts. In addition, the total correlation between therapeutic differentiation and firm performance became nonsignificant in the presence of indirect effects, although the direct effect of the independent variable was significant. Going by the direct impact alone would lead one to expect gains in market share from therapeutic differentiation. 5.2.4 Waits Discussion thus far has centered on model adequacy with respect to whether the data are consistent with the hypotheses. The t-tests (see Table 5.1) strongly suggested that it is appropriate to analyze the data as samples from.two different populations rather than a single population. Yet to be considered is whether the proposed structural model is equivalent across these two groups. Three paths are hypothesized to be equal between the two groups: new product development efforts and therapeutic market diversification as related to the firm's marketing of drugs first in the United States (V. e F.; V. -v V.), and therapeutic market diversification as related to new product development efforts (V. -v F.). The Lagrange Multiplier (Lu) test was used to evaluate whether cross-group constraints on the equality of parameters were appropriate or not. A univariate Ln test was provided for each cross-group constraint. If the probability of the L11 statistic for a constraint is small (p < .05), then this 191 particular constraint should be released. A high probability value suggests that the constraint cannot be rejected. The overall goodness-of-fit for the multiple group analysis with the three constraints was X2 = 86.585 (dzf. = 35: p < 0.001). The univariate test statistics, cumulative multivariate statistics, and univariate increment for the three constraints are shown in Table 5.13. The univariate test results suggested that constraints #2 and #3 (p < .05) are not consistent with the data, that is, the null hypotheses that these two constraints are zero should be rejected. These conclusions were confirmed in the multivariate analysis. The multivariate test is a forward stepwise procedure, and the constraint with the largest univariate chi-square is entered first. In this case, it yielded the same statistic as in the univariate analysis. Constraint #3 then was added, since it contributed most to the chi-square statistic. This yielded an increment of 6.951 chi- square points for a total 2 d.f. multivariate test of 21.504. Constraint #1, however, added marginally to the chi-square: its p value of 0.738 was not significant at the .05 level, which suggested that this constraint cannot be rejected. Releasing constraints #2 and #3 yielded an overall Xa fit of 50.458 (d.f. = 37: p =- 0.05545). When the model was reestimated with constraint #1, the probability for the LB test was 0.246. This suggested that this cross-group constraint is equal in both the early and late entrants. 192 Table 5 . 13 Lagrange Multiplier Results Univariate Test Statistic Constraint Chi-square Probability .3" 1. (1131) 0.550 0.445 ’- 2. (V3,V1) 14.553 0.000 unulative Multivariate Analysis Univariate Increnent Paraleter Chi-square d.f. Probability (mi-square Probability Constraint 2 14.553 1 0.000 14.553 0.000 Constraint 3 21.504 2 0.000 6.951 0.008 Constraint 1 21.615 3 0.000 0.111 0.738 193 Since the model with three constraints is a nested version“ of the model with one constraint, it is possible to test for statistical significance with a x3 difference test (X’.). The x3. was 36.127 (d.f. -= 2, p < .001), which implies that the constraints imposed in the first model (constraints #2 and #3) should be rejected. Because the significant difference in the x1. may be due to nonsignificance of either or both paths (F. -v V. and V. -v V.) , these paths were evaluated independently. For both early and late entrants, the path P. -0 V. was significant: the path V. -» V. was significant in the early entrant group (t =- 2.503) but nonsignificant in the late entrant group (t = 1.854). 5.3 W Table 5.14 summarizes observed results regarding the 20 hypotheses for early and late entrants. For early entrants, five findings are notable. (1) New product development efforts are influenced by internal RED efforts, therapeutic market diversification, and RED intensity. (2) New product development efforts and therapeutic market diversification lead firms to introduce drugs first in the United States. ( 3) Therapeutic differentiation is influenced by both new product development efforts and internal RED efforts. (4) RED intensity, new product development efforts, and therapeutic differentiation are positively related to outlicensing activity. 15Rested Iodels are special cases of lore general Iodels: the toner is obtained tron the latter by restricting para-stars t0 equalities or constants, usually zero. 194 (5) Performance is significantly influenced by direct effects from outlicensing activity, internal RED efforts, RED intensity, therapeutic differentiation, and new product development efforts. Concentrating on the United States as the key market for drug introductions has a negative effect on performance. Internal RED efforts, RED intensity, and new product development efforts also had positive and significant indirect effects on firm performance. Four hypotheses were not supported for early entrants: the effect of internal RED efforts on the marketing of drugs first in the United States, therapeutic differentiation on outlicensing, of therapeutic market diversification on therapeutic differentiation, and of advertising intensity on firm performance. For late entrants, the following five findings are of particular interest. (1) Product development efforts are only influenced by internal RED efforts and therapeutic market diversification. (2) New product development efforts and internal RED efforts tend to encourage drugs to be first marketed in the United States. (3) Two‘variables.only influenced these firms' ability to develop highly therapeutically differentiated drugs: new product development efforts and therapeutic market diversification. The effect of the latter was positive. (4) Outlicensing activity is positively influenced by new (5) product development efforts, internal RED efforts, and RED intensity. Therapeutic differentiation is negatively related to outlicensing activity, suggesting that FDA ratings are not that important for late entrants. Performance is positively influenced by direct effects from internal RED efforts, therapeutic differentiation, and RED intensity. Late entrants are less successful than early entrants in new 195 product development and advertising efforts. These variables have a negative effect on late entrants' performance. However, in the presence of indirect effects, the total effect of therapeutic differentiation on firm performance became nonsignificant. The indirect effect of new product development efforts was positive and significant, while that of therapeutic diversification was significant but negative. Five hypotheses were not supported for late entrants: the effect of therapeutic market diversification on the marketing of drugs first in the United States, of internal RED efforts on therapeutic differentiation, of RED intensity on new product development efforts, of marketing of drugs first in the United States and outlicensing on firm performance. 5.4 Conclusions In this chapter, the twenty hypotheses in Figure 4.1 were tested. Findings indicate several similarities as well as differences between early and late entrants in terms of how the competitive positing variables are causally related to one another and the relative impact of the seven variables on firm performance. This suggests that early and late entrants have different differential advantages and distinct performance characteristics. Implications of these findings are discussed in Chapter 6. 196 Table 5.13 Observed Results for Early and Late Entrants Hypothesis Early Entrants Late mtrants (standardized sol.) (standardized 801.) 111. High conitnent to RED has a positive effect on .351“r .078 (~nonsig.) new product developnent efforts. 112. There is a positive relationship between a firn’s .128. .176“ conitnent t0 RED and perfornance. 113. There is a positive relatiomhip between a firw’s .038 (nonsig.) -.238m oonitnent to narketing and perfornance. 114. There is a positive relatiomhip between new product .432“. -.408'“ developnent efforts and fin perfornance. 115. There is a positive relationship between internal .218.“ .36?” RED and new product developnent efforts. 116. There is a positive relationship between internal .650.” .965.“ RED and fit: perfornance. 117. Internal 140 has a positive effect on outlicensing -.170“ .165‘ for late entrants. This relationship is negative for early entrants. us. There is a positive relationship between new .986“ .562." product developnent efforts and outlicuusing. n9. nigh couiuents to its lead to greater .152’“ .306’“ outlicensing. R10. There is a positive relationship between .395.“ .120 (wig) outlicensing activity and fin perfornance. 1111. There is a positive relationship between .612” .531’“ therapeutic narket diversification and new product developnent efforts. n12. strong new product developnent efforts lead to .557‘“ .400’“ higher therapeutic differentiation. 1113. There is a positive relationship between internal .181' .032 (nonsig.) RED and therapeutic differentiation. 1114. High therapeutic narket diversification is -.055 (nomig.) .295. negatively related to therapeutic differentiation. £1517 Table 5.12 (cont) Hypothesis Early Entrants Late Entrants (standardized sol.) (standardized sol.) 1115. There is a positive relationship between therapeutic .760“fr differentiation and tin perfornance. 0 136. 1116. Therapeutic differentiation is positively associated .059 (nonsig.) -.129' with the outlicensing activity of early entrants. This relationship is negative for late entrants. "m"! 1117. There is a positive relationship between therapeutic .199 narket diversification and the narketing of drugs first in the United States. .210 (nomig.) n10. There is a positive relationship between new product .333“. .312 developnent efforts and the narketing of drugs first in the United States. 1r" ““7“ ‘ R19. There is a positive relationship between internal RED -.033 (nonsig.) .329'" andthelarketingofdrugsfirstintheUnitedStates. 1120. There is a negative relationship between drugs that M79“ -.011 (nonsig.) are first narketed in the United States and fin perfornance. .. p < 0.05 p < 0.01 p < 0.001 CHAPTER SIX CONCLUSIONS The data were analyzed in relation to the theoretical structural model discussed in Chapter 5. This chapter begins with a discussion of the results, then notes the limitations of the studyu Next, the ‘theoretical contributions and managerial implications of the findings are discussed. Finally, suggestions for future research are proposed. 6.1 Wilts The three research questions guiding this research are : (1) How are competitive positioning variables causally related to one another? (2) Which competitive positioning variables have the greatest effect on performance? What is the relative importance of their direct and indirect effects? (3) How do early and late entrants differ in terms of competitive positioning variables and overall performance? The answers to each of these questions are addressed below. 6.1.1 Relationshimamongjwmpetitimzositming hassles 6.1-1.1 W For both early and late entrants, internal RED efforts and therapeutic market diversification are significant predictors of firms' new product development efforts. This 198 .2. IJ WW“ 1. 199 suggests that a firm's ability to develop and exploit technological know-how internally are important dimensions of competition in the pharmaceutical industry (Thomas 1988) . While external sourcing' of RED ideas. will continue' for established firms confronted with broad and rapid changes in their core technologies, the long-term success of a firm requires the development and successful exploitation of their internal RED capabilities. Diversification into many therapeutic markets is indicative of manufacturing and RED mobility for both early and late entrants (Cocks 1975) . This suggests that these technology-intensive firms have the ability to adapt their RED and manufacturing processes so that they can produce drugs in several therapy areas. The relationship between RED intensity and new product development efforts is significant for early entrants but not for late entrants. .Acs and others (1988) found that the total number of innovations is positively related to RED, while Cooper (1982) found no direct link between RED spending and effectiveness of firms' new product programs. Cooper noted that how the research dollar was spent and how the product was subsequently marketed were more important determinants of success than how much was invested. Therefore, the positive relationship between RED intensity and new product development efforts of early entrants suggest that this group of firms manage their RED resources more effectively than late .- . .- f... "NHL-..-] 200 entrants. 6.1-1-2 W W Findings suggest that firms with strong new prOduct development efforts tend to introduce their drugs in the United States. Both early and late entrants view the United States as a key market for drug introductions. Between 1940 and 1988, domestic firms accounted for about 62 percent of new drugs introduced in the United States while West European firms accounted for 27 percent. Grabowski (1990) concludes that in terms of both ownership and location, the United States will continue to be a leading source of consensus drugs (those that gain worldwide acceptance). Therapeutic market diversification has a positive influence on early entrants' introduction of drugs in the United States: this relationship is nonsignificant for late entrants. As discussed earlier, pharmaceutical firms are shifting from acute to chronic disease therapy. In 1929 almost 70 percent of illnesses were acute, but by the 19808, the figure‘was 20 percent (Levin 1982). Chronic(diseases have become a major concern and.a major drug market. Over the past few years, companies increasingly have shifted research priorities from infection-fighters, such as antibiotics, to maintenance drugs, such as cardiovascular drugs, central nervous system products, and antineoplastics. These three therapeutic categories represent key growing product areas in 201 the United States: "because so many companies are working on these same [therapeutic areas]" (WW1 Mission 1991), it is economically advantageous for U.S. firms to exploit these product categories first in the United States and then overseas. Strong internal RED efforts encourage late entrants to market their drugs first in the United States, but this relationship is nonsignificant for early entrants. There are two possible explanations for this finding. First, the internal RED efforts of early entrants may already be captured by another variable, new product development efforts. The magnitude of the indirect effect of internal RED efforts was large (.121) and significant (p < .001). Second, although the hypothesis was not supported for this group, the negative finding suggests a strong likelihood that early entrants, because of their technological superiority, will attempt to exploit their internal know-how on a global basis, whereas late entrants find the domestic market more attractive for launching new products. 6.1.1-3 W The therapeutic differentiation of a drug as indicated by the FDA ratings can be thought of as a dimension of product quality. Perceived product quality in the pharmaceutical industry is a function of its intrinsic quality as well as a number of intangibles, such as corporate image and reputation, and the effectiveness of a firm's promotional efforts in 202 communicating superior product quality. Findings suggest that new product development efforts may lead to drugs that represent important therapeutic gains or only modest gains. This variable has a greater influence on early entrants (.557) than late entrants (.400), reflecting the higher technological sophistication and orientation of early entrants. Link (1987) found that high technology/ innovative firms are more successful at developing products with higher quality and significant user benefits. This technological superiority is also reflected in the positive effect of internal RED efforts on therapeutic differentiation for early entrants. As noted by Capon and Glazer (1987), one reason for enhancing the firm’s technology portfolio through internal RED development is to encourage learning on the part of the firm. That is, firms invest in internal RED to generate and gain proprietary access to technologies in specific products and to the more general know-how related to these products. An RED project that yields a specific therapeutic compound also may create knowledge and build RED capabilities that are valuable for discovering other drugs for the same disease. The effect of internal RED efforts on therapeutic differentiation is nonsignificant for late entrants. Therefore, the prior argument that early entrants are more successful in converting their "learned" internal know-how into ‘more highly differentiated drugs is supported. n 31“.“?! EFT-fl ... '- - 203 For late entrants, therapeutic market diversification or the breadth of product-market scope enhances their ability to develop therapeutically differentiated drugs. This suggests that late entrants’ diversification in product markets that are closely related to their areas of technical expertise facilitate the development of highly differentiated drugs. This relationship is nonsignificant and negative for early entrants which suggests that they have "overdiversify." The negative relationship found for early entrants suggests that a smaller range of product market scope is recommended. While an expansion in the scope of product-market activities is driven by management’s desire for effective use of the firm’s financial, human, and material resources, the direction of diversification is also important. Researchers such as Rumelt (1974), Salter and Weinhold (1978), and Varadarajan and Ramanujam (1987) suggest that diversification into product markets in which a company can use its existing functional skills and resources leads to greater synergy. 6.1-1.4 Outlicensing The effect of new product development efforts on outlicensing is significant and in the predicted direction for both groups. The needs to recoup RED costs, expand geographical reach, and exploit sales from new drugs are significant motivators for firms to license out. The direct effect of therapeutic differentiation on outlicensing was nonsignificant for early entrants but 204 negative for late entrants. This suggests that FDA ratings are unimportant for the former in their outlicensing of drugs overseas. As for the latter firms, despite having differentiated products which provide significant therapeutic advantages over’ competing’ drugs, this advantage ‘was not significant to overcome first mover advantages established by early entrants in overseas markets. For example, early entrants may have established captive relationships with their overseas licensees such that switching costs increase for the latter. As argued by Wernerfelt (1985), over time, buyers adapt to the characteristics of products and their suppliers and find it costly to change to another brand. The effect of RED intensity and internal RED efforts on early and late entrants’ outlicensing activity is supported. Firms that are RED intensive engage in greater outlicensing. While internal RED efforts have a positive effect on late entrants’ outlicensing activity, this relationship is negative for early entrants. In general, a firm licenses a drug for sale in a country where the licensor does not have an adequate sales force to compete in the market. Table 2.20 showed that most of the early entrant firms in this study have a large worldwide detailforce, which would decrease their reliance on outlicensing as an entry strategy into foreign markets. This explains the negative relationship between internal RED efforts and outlicensing for early entrants. 205 6.1.2 W Performance Prior findings suggest that market share advantage of early entrants is derived from their deployment of strategic resources. Firms strong in technological RED are first to the market with products based on new technologies. How do RED expenditures translate into barriers to entry for late entrants? The positive effect of RED intensity on firm performance for late entrants suggests that if they invest heavily in RED they can perform as well as early entrants. Therefore, even though late entrants are followers in research, they can recover through strong development capabilities. The relationship between advertising intensity and performance was found nonsignificant for early entrants and negative for late entrants. The latter finding was unexpected, as researchers such as Lieberman and Montgomery (1988) suggest that a firm strong in marketing skills will find late entry to be in its interest. Miller et al. (1989) and Urban et al. (1986) also~concluded.that.promotion for late followers was one of the few competitive options available for gaining market share. Their findings were confirmed within the consumer and industrial goods industry of the PIMS study. The negative finding for late entrants in this study suggests that they need to invest more in advertising to overcome the brand and firm loyalty created by early entrants. 71". 1 '.'.' L! 'L‘m'lfi. 206 Total self-sufficiency in new product discovery and development is unrealistic, and many pharmaceutical firms will continue to concentrate on both internal and external RED for drug procurement purposes. Of course, from a control and profitability standpoint, the ideal is an internal RED organization so creative and productive that it provides a steady flow of competitively superior products. The results of this study show that internal RED efforts are significant predictors of firm performance, more so for late entrants (0.965) than early entrants (0.650). This finding confirms a recent study by the U.S. International Trade Commission (1991) , which found that higher global market shares are associated with firms that develop a larger portion of their own RED compounds, since there is higher probability of developing an innovative drug from one’s own internal RED efforts. The effect of the firm’s spatial strategy on performance is supported: it is negative for early entrants but nonsignificant for late entrants. The negative finding for early entrants strongly suggests that a policy of simultaneously introducing NCEs in several major countries should lead to better performance. Another explanation for the negative finding is that, although drugs produced in the United States have a worldwide reputation for quality, U.S. firms are likely to be at a disadvantage because of the significantly longer U.S. regulatory reviews. This stringent 207 regulation should encourage firms to introduce their drugs abroad, pending marketing approval of the new drugs in the United States. Therapeutic differentiation has a greater effect on early entrants’ performance (0.760) than late entrants’ performance (0.136). As noted by Abernathy and Utterback (1978), early entrants may be viewed as offering improved differentiated products simply because their products are technologically new. As proposed by Porter (1980b), product differentiation is the second business-level strategy. Therefore, early entrants may attempt to differentiate their products to facilitate entry into foreign markets as well as to deter other firms from entering these markets. As hypothesized, outlicensing is proactively used by early entrants to broaden their geographic scope, and this variable has a significant effect on their performance. For late entrants, the effect of outlicensing on firm performance is nonsignificant. Finally, new product development efforts significantly affect early entrants’ performance. Unexpectedly, this effect is negative for late entrants. 'This suggests that the product innovative abilities of early entrants tend to outperform those of late entrants. Cooper (1985) stressed the strong connection between the firm’s new product strategy and performance. A firm needs a clear defined new product strategy as a central and integral aspect of its corporate 208 strategy. Among the twenty hypotheses tested, sixteen and fifteen structural paths were significant for early and late entrants, respectively. Paths which are significant across both groups are summarized below. These paths suggest fundamental bases of competition in the industry. 1 1. Internal RED efforts ( V2) F [ lew product developnent efforts (1‘1) 9 2. Therapeutic narket diversification ( V3) 3. new product developnent efforts + Harketing of drugs first in the 1 United States (111) L 4. law product developnent efforts - Therapeutic differentiation (V8) 5. New product developnent efforts 6. 0:0 intensity Outlicensing (V9) L Imumalflmefimts & RMRMURH) 9. RED intensity Perforwance (12) 10. Therapeutic differentiation “ . 'f' I f' I' W W 1. Internal 2&0 efforts (V2) » 1400 Intensity (V4) ~ wevgroduct Introduction of dntgs first in Developnent Efforts (1'1) the United States (V1) ... O 2. Therapeutic diffefpntiation (V8) 2. Internal RED efforts (V2) .. Outlicensing (V9) Therapeutic differentiation (V8)" * Structural patls which are significant and in the hypothesized direction across both groups. ** Significant in other group. 209 3. Therapeutic narket diversification 3. Therapeutic narket (V3) (113).; Therapeutic differentiation diversification -v Marketing of (V8) drugs first .in the United States (V1) 4. Advertising intemity (V5) - Pin 4. Outlicensing (V9.1 .. Perforwance (12) Perfornance (1'2) 5. Iarketing of drugs first in the “ United States (V1) 9 Perfornance (12) WW 1. lew product developnent efforts [ - ] (11) * Perfornawe (12) 2. Advertising intemity (V5) 4 [ ‘ ] Perfornance (1'2) 3. Therapeutic narket diversification [+1 (V3) ~ Therapeutic differentiation (V3) Among the late entrants, two major weaknesses are evident: insufficient spending on advertising and a lack of product innovative abilities. Findings for this group indicated, however, that internal RED efforts, high commitments to RED, and therapeutic differentiation positively influence performance. The new product development strategies of late entrants are characteristic of firms belonging to the two clusters proposed by Cooper (1985a): the technologically deficient strategy and the low-budget, conservative strategy. Cooper found that firms pursuing the former strategy lacked technological sophistication, orientation, and innovativeness (their products were mainly "me-toos") , lacked 44* Significant in other group. N Paths are significant but in unexpected directions for other group. IYAI'h 210 an RED orientation, and were technologically proactive. Firms adopting this strategy, however, had focused new product programs that employed related development technologies and production methods aimed at related markets. Firms pursuing a low-budget, conservative strategy tended to have the lowest RED spending and also tended to launch products with the least differential advantage. Similar to firms pursuing technologically deficient strategies, low—budget firms tended to balance their technological and product deficiencies with a conservative or "stay close to home" approach. New development efforts were chosen that had the highest technological and production synergy. As for early entrants, it appears that they seem to have "overdiversify" into therapeutic categories that share little synergistic fit with their internal RED capabilities. They also need to increase their advertising efforts. Positive effects on performance, however, ar derived from their emphasis on : (1) development and exploitation of internal technological know-how: (2) high investments in RED: (3) development of highly differentiated drugs: (4) successful outlicensing arrangements: and (5) strong new product development efforts . In terms of new product development efforts, many of the early entrants in this study are characteristic of firms with technologically driven strategies and a balanced strategy (Cooper 1985a) . Cooper found that both groups of firms are high-technology, high-risk, 211 innovative firms that emphasize the development of technologically complex products featuring state-of-the-art know-how. They also have a strong RED- oriented and proactive new product program. While firms pursuing technologically driven strategies lack market synergy with their existing market resource base, balanced strategy firms differ from them in the degree of product fit and focus as well as in market orientation. 6.2 LimitationstJhLmdx The first limitation to be noted is the focus of this study on a single industry. The competitive positioning variables proposed in the structural model were specifically identified as key strategic variables in the ethical pharmaceutical industry. Whether the research findings and the structural model can be generalized to other high- technology industries requires an in-depth understanding of the variables that uniquely describe competitive advantages for those industries. This may mean a reconceptualizing of the structural model to describe more adequately the competitive positioning strategies used in other industries. A second limitation relates to the sample selection procedure. Due to data constraints, foreign pharmaceutical firms (particularly those from Japan and Western Europe) competing in the United States were deleted. These firms have made significant inroads into the U.S. market over the last few years and have changed the domestic competitive ' no.1? 212 environment for U.S. firms. Future research will have to develop ways to capture the effect of foreign competition on domestic markets. A third limitation relates to the assumption that changes invand adaptations to the external environment are captured in the firm’s strategic variables. 11ow firms strategically adapt to environmental changes in the pharmaceutical industry and the consequent effect on performance need to be researched. A fourth limitation concerns the selection and measurement of the performance indicators. Profitability measures were not included in 'the study' because: of their' substantial measurement error. Since many of the pharmaceutical firms are diversified, and frequently change their patterns of diversification, constructing consistent sales and income figures poses formidable problems. In addition, accounting measures are likely to be distorted by price level changes, especially in times of high inflation. The United States, where price controls have yet to be implemented, is considered by many to be the last free pricing country (U.S. International Trade Commission 1991). Therefore, to capture the ‘true jprofitability' of ‘U.S. firms, accounting' return measures have to be restated for inf lation-adjusted depreciation expense. A fifth limitation relates to the grouping of firms into two major groups: early and late entrants. This study adopted the view of Urban et al. (1986) that timing of entry can be 213 parsimoniously considered as early and late. Robinson and Fornell (1985), however, found a significant degree of lateness effect: Early followers had significantly higher market shares than late followers, although the difference was much smaller than the difference between pioneers and early followers. A different operationalization of timing of entry into pioneers, early entrants, and late entrants might yield a different set of findings. 6.3 ContributionsoLRoseoroh 6.3.1 W In terms of theory, this study has shown that timing of entry is systematically related to competitive performance and that this relationship is likely to be moderated by variations in the strategy of firms. Specifically, it seems that underlying sources of competitive advantages are enjoyed by early entrants over late entrants (for example, Lambkin 1988: Robinson and Fornell 1985: Robinson 1988). These sources of competitive advantages are analogous to entry barriers created by early entrants. Specifically, in this study, product differentiation. (Bain. 1956: Schmalensee 1982: and. Porter 1980b) and strong new product development efforts (Cooper 1985a: Johne and Snelson 1988) were found to be important sources of competitive advantage for early entrants. ., . '.._ . .- (g -.. 0; :....-. The new product development literature has rarely dealt with the distinction between internally developed and 214 licensed-in technologies. This issue is critical for many firms in high technology industries when they are being confronted with broad and rapid changes in their core technologies and lack the capabilities to deal with' new technologies. The results of this research show that internal RED efforts have a positive influence on firms’ new product development efforts. Therefore, even though corporations have many' reasons for' acquiring' technology, rarely' are 'these purchases a substitute for technical competence (Oliver 1982) . In addition, as noted by Capon and Glazer (1987), one reason for enhancing the f irm’s technology through internal RED development is to encourage learning on the part of the firm. That is, firms invest in internal RED to generate and gain proprietary access to technologies in- specific products and to the more general know-how related to these products. An RED project that yields a specific therapeutic compound also may create knowledge and build.RED capabilities that are valuable for discovering other drugs for the same disease. Findings show that early entrants are more successful in converting their "learned" internal know-how into more highly differentiated drugs. Diversification is also an area rarely treated in the new product development literature. Either as a means of spreading overall risk and/or expanding the base of the firm’s business, diversification is found to have a positive influence on firm’ s product innovativeness. Similar to other ' nuns—P1 _1 215 findings (Cooper and Kleinschmidt 1987: Link 1987), this study confirms the importance of diversification into many therapeutic markets that are synergistic with the firm’s marketing and technical capabilities. An emphasis on internal RED efforts also necessitates high RED spending. As noted by Cooper (1982, 1983), how the research dollar is spent and how the product is marketed are more important. determinants of success. It seems ‘that technological leaders (early entrants) are abLe to convert their RED spending into successful new products that are of high quality and which offer distinctive therapeutic advantages to customers. WW For both early and late entrants, high RED spending and strong new product development efforts lead to greater outlicensing. Since new products are usually backed by large RED investments, manufacturers need to recover their development costs: increasing overseas sales through outlicensing arrangements is one way to achieve this objective. Maintaining a strong global presence is also necessary because of heightened generic competition and increasing drug substitution practices. As expected, early entrants tend to use their worldwide salesforce to distribute their internally developed products overseas. This finding is consistent with Anderson and Coughlan’s (1987) argument that firms tend to erect a protective, restrictive governance .eem_q 216 structure around the distribution of complex, sophisticated products that require an investment in learning. The effect of therapeutic differentiation on late entrants’ outlicensing was negative. Early entrants may already have established captive relationships with licensees in certain markets thus making it more difficult for late entrants to gain access to these distribution channels. In addition, the nature of the product also encourages high switching costs which prevent the licensees from changing from one licensor to another. _ O 0 0 I I [-0. 4°. 0 ,. .z 49 0 '11-. -. 4 4‘ 4 ’0 The high demand for pharmaceuticals encourages U.S. firms to exploit their new product development efforts in the domestic market. However, the negative relationship between this variable and firm performance strongly suggest negative consequences for firms who continually focus on the U.S. market as their key source of sales. Findings from this study also point to the importance of differentiating between the types of therapeutic markets that pharmaceutical firms compete in. Since demand for chronic drugs are much higher in the United States than other developed nations, firms who have diversified into these therapeutic categories are in a strong position to exploit sales from these categories in the U.S. Finally, the high costs from internally developed drugs compel firms to look beyond the U.S. market in an attempt to maximize sales from their internal efforts. 6-3-2 W _ T1....1.f‘t “...—q -I 217 It is of central importance for firms to understand what strategies are being pursued by their competitors. This knowledge is necessary to evaluate the relative strengths and weaknesses of certain strategic positions and to determine how defensible these positions are. A competitive positioning framework.has been proposed to examine this matter in detail. Success factors for competition in the industry are summarized below. E l . E l ! I l' First, the importance of developing and exploiting internal know-how as well as diversifying into related therapeutic markets is crucial for enhancing product innovativeness. Second, increasing product innovativeness can lead to important payoffs -- drugs that are therapeutically differentiated and which offer significant benefits over competing brands. Cooper and Kleinschmidt (1991) argued that product innovativeness have a central role and impact in new product success. Innovative products tend to be more unique, differentiated, and patentable. The innovative firm thus achieves a differentiated and proprietary position, and has a higher likelihood of success than the follower. Strong new product development efforts also enhance firms’ ability to outlicense. Since licensees’ size of income is tied to the economic potential of a drug, they are more likely to enter into contractual arrangements with firms that can offer innovative and differentiated products for a 4 d '3 n n 218 outlicensing. WEI. Firms who emphasize drugs introductions first in the United States are in a disadvantaged position in the long' run. The increasing presence of Western Europe and Japanese firms as well as increasing competition from generics compels U.S. firms to adopt a strong commitment to other foreign markets. "Think globally." WW9); Increasing domestic and global competition together with higher'new'product.development.costs suggest.that.for firms in many technologically advanced industries to succeed, they need to develop "better" new products and to do it faster. Many pharmaceutical firms have entered into product licensing alliances to supplement and accelerate product development. However, this study stresses that internal RED efforts is a critical determination of long-term competitiveness in the pharmaceutical industry. A recent study by the U.S. 1W (1991) found that higher global market shares are associated with firms that develop a large portion of its own RED compounds since the probability of developing an innovative drug is higher from one’s internal RED efforts. H . l . E! : .! ! ! BED The importance of RED as a key strategic resource to the development of distinctive competency has been stressed in 219 earlier studies (e.g. , Cool 1985) . Harrigan (1981) and Schmalensee (1983) argued that although incumbent firms may prevent the entry of new firms by investing effectively in RED, thereby increasing technological scale economies, this barrier is usually short-lived. The positive total effect of RED intensity on late entrants’ performance suggests that if they make significant commitments to RED, they can perform as well as early entrants. '. .. - - ... ., .- n. . e e .... ' ° - -. ' ..-? The two most significant variables that affect late entrants’ performance are internal RED efforts and RED intensity, respectively; However, late entrants must address how they can overcome competitive advantages achieved by early entrants: (1) higher quality and differentiated products: and (2) stronger new product development efforts. A recent study by Cooper and Kleinschmidt (1991) found that non-innovative products, namely modifications and revisions, also perform well in terms of return-on-investment and domestic market share. One reason for their success is they "stick close to their knitting." Non-innovative products also tend to do well because of high levels of marketing and technological synergies. Hence, for late entrants, electing to concentrate on NCE development versus other types of new product developments can be a negative factor. Although they should concentrate their marketing and RED resources on less innovative product _ mm... ‘— J L N. 220 development. efforts, they' should. not ignore attempts to develop NCEs that are therapeutically differentiated. In these efforts, a recommendation for late entrants is to focus efforts on one therapeutic market at a time. This approach will produce a niche until the resources become available to permit an assault on another niche. This niche-by-niche strategy will allow global exploitation of their products more successfully despite being "technological followers." In addition, late entrants also need to commit more . resources to advertising efforts. Superiority in this marketing activity will spell the difference between success and failure for many products in the future as the market continues to be filled with similar chemical entities. Jain (1981) suggests that late entrants may come into the market as "me-too" competitors. Pharmaceutical experts claim that even a less effective me-too drug (for example, a "C" drug) can do well in the market, depending on the way it is promoted and marketed (Bond and Lean 1977: U.S. International Trade Commission 1991). ., .. . - ... a. .- ,.', .'. o. ...; -..' '.,,9 Overall, early entrants are doing what is necessary to maintain market share advantages: they offer innovative products which provide further opportunities for product advantages and differentiation. However, they need to be more selective in their choice of therapeutic markets. Since the development of highly innovative products involve greater 221 uncertainties and riskiness, management must ensure that these projects should only be undertaken when there is a good match between the resource base of the firm and the needs of the project. Firms should also identify opportunities in a certain therapeutic market by comparing the relative market size and its degree of unmet needs as well as evaluating the competitive intensity and diversity of approaches in the research area. These criteria will help early entrants employ their RED and marketing resources more effectively. 6-4 W In addition to replicating this study in other industries, several questions require further research. First, an attempt should be made to include foreign firms in the analysis. Since the pharmaceutical industry operates in a global market, it would be interesting to examine how Japanese and Western European firms differ in their competitive positioning strategies. Since Japanese pharmaceutical companies are traditionally smaller and are less innovative when compared to western European and U.S. firms, what strategies do they employ to enhance their new product development efforts and performance? Second, because some of the firms in the sample have merged with or been acquired by other pharmaceutical firms, a follow-up study is necessary. The merger of SmithKline and Beecham created one of the largest ethical drug companies in the world in terms of research budget and worldwide detail ”'1 FE ._ T fifuf. ~1-__T; ”and: um: 222 force. In Europe, the merger between Rhone-Poulenc and Rorer gave the French firm access to the U.S. market. Given that these merged firms have economies of scale in. RED and distribution, how does this change the competitive structure of the pharmaceutical industry for other pharmaceutical firms? Third, although this study looked at a wide range of therapeutic markets, it did not distinguish them by their stage in the technology life cycle (TLC). Timing of entry at the technology level within the product market has not been extensively studied. Most research on entry issues has concentrated on either mature or new/start-up businesses. Studying the timing of entry variable over a broad range of therapeutic markets at various stages of technological growth can offer better insights to several questions. (1).Are firms identified as early entrants in mature therapeutic markets also likely to be early entrants in growing therapeutic markets? (2) How do the competitive positioning variables vary across stages of the TLC? (3) What competitive positioning variables are associated with performance at each stage of the TLC? Finally, the performance effect of the environment- strategy linkage needs to be addressed. Current regulation and changes in the drug selection process are expected to affect significantly on a firm’s RED efforts and marketing mix. For example: (1) How are pharmaceutical firms responding to the U.S. government’ 5 health policies and various cost- 223 containment measures? (2) Will product liability exposure affect the industry’s RED efforts? (3) Since physicians will become less influential in the drug selection process compared to other major buying groups, such as HMOs, how "will pharmaceutical firms’ marketing mix change in response to the needs of major buying groups? ‘9 a."..' I‘d". W“ 224 LIST OF REFERENCES Aaker, David A. and George S. Day (1986), The Perils of High Growth Markets, Strategic Management JOurnal, Vol.7, pp.409- 421. Aaker, David A. and Shansby, J.G. (1982), Positioning Your Product, Business HOrizons, Vol.25, No.3, pp.56-62. Aaker, David A. and Richard P. Bagozzi (1979), Unobservable Variables in Structural Equation Models with an Application in Industrial Selling, Journal of Marketing Research, Vol.16 (May), pp.147-58. Abell, Derek F. (1978), Strategic Windows, Journal of Marketing, Vol.42 (July), pp.21-26. Abell, Derek F. (1975), Competitive Market Strategies : Some Generalizations and Hypothesis, MSI Proceedings, Report No.75- 107. Abell, D.F. and J.S. Hammond, (1979), Strategic Market Planning, Englewood.Cliffs, N.J. : Prentice Hall, pp.116-119. Abernathy. W.J. and J.M. Utterback (1978), Patterns of Industrial Innovations, Technology Review, Vol.80, (June- July), pp.2-9. Acs, Zoltar and David B. Audtresch (1988) , Innovation in Large and Small Firms : An Empirical Analysis, American Economic Review, Vol.78 No.4, pp.678-90. Anderson, Erin (1985), The Salesperson as Outside Agent or Employee : A'Transactional Cost.Analysis, Management Science, Vol.4 (Summer), pp.234-54. Anderson, Erin and A.T. Coughlan (1987), International Market Entry and Expansion via Independent or Integrated Channels of Distribution, JOurnal of‘Marketing, Vol.51, (January), pp.71- 82. Anderson, James E. and David W. Gerbing (1984), The Effect of Sampling Error on Convergence, Improper Solutions, and Goodness-of-Fit Indices for Maximum Likelihood Confirmatory Factor Analysis, Psychometrika, Vol.49, No.2, pp.155-73. Arabie P., Carroll, D., Desarbo, W., and Wind, Y. (1981), Overlapping Clustering : A New Method for Product Positioning, 225 Journal of Marketing Research, Vol.18, (August), pp.310-317. Arora, Raj (1982), validation of an S-O-R Model for Situation, Enduring, and Response Components of Involvement, JOurnal of Marketing Research, Vol.19 (November-December), pp.505-16. Arthur D. Little (1988) , Sales of Prescription Pharmaceuticals to 1991, Spectrum, pp.1-4. Ashford, N.A., S.E. Butler, and E.M. Zolt (1977), Comment on Drug Regulation and Innovation in the Pharmaceutical Industry, Unpublished manuscript, Cambridge, MA : MIT Center for Policy Alternatives. Bagozzi, Richard. P. (1983), A Holistic Methodology for Modelling Consumer Response to Innovation, Operations Research, Vol.31 (January-February), pp.128-76. Bagozzi, Richard P. and L.W Phillips (1982), Representing and Testing Organizational Theories : A Holistic Construct, Administrative Science Quarterly, Vol.17, pp.459-89. Bagozzi, Richard P. and Youjae Yi (1988), On the Evaluation of Structural Equation Models , Journal of Marketing Research , Vol.16 No.1, pp.74-94. Baily, M.N. (1972), Research and Development Costs and Returns : The U.S. Pharmaceutical Industry. JOurnal of Political Economy, (January/February). Bain, J.S. (1956), Barriers To New Cbmpetition, Cambridge, MA : Harvard University Press. Balaskrishnan, S. and B. Wernerfelt (1986), Technical Change, Competition and Vertical Integration, Strategic Management JOurnal, Vol.7, pp.347-359. Bass, F., P. Cattin and D. Witttink (1978), Firm Effects and Industry Effects in the Analysis of Market Structure and Profitability, Journal of Marketing Research, Vol.15, pp.3-10. Bearden, William 0., S. Sharma, and J.E. Teel (1982), Sample Size Effects on Chi-square and Other Statistics Used In Evaluating Causal Models , Journal of Marketing Research, Vol.19, pp.425-30. Bearden, William O. and Terence A. Shimp (1982), The Use of Extrinsic Cues to Facilitate Product Adoption, Journal of Marketing Research, Vol.19 (May), pp.229-39. Bearden, William O. and J.B. Mason (1980), Determinants of Physician and Pharmacist Support of Generic Drugs, JOurnal of or n . Ian; i $1.1... 226 Consumer Research, Vol.7, (September), pp.121-130. Benson, J.E. (1974), Comment on Price’s ”The Study of Organizational Effectiveness" Sociological Quarterly, Vol.14, pp. 273-76 0 Bentler, Peter M. (1989), Theory and Implementation of EQS : A Structural Equations Program, Los Angeles : BMDP Statistical Software. Bentler, Peter' M. (1986), Structural Modelling’ and Psychometrika : An Historical Perspective on Growth and Achievements, Psychometrika, Vol.51, pp.35-51. Bentler, Peter M. (1985), Theory and Implementation of EDS : A Structural Equations Program, Los Angeles : BMDP Statistical Software. Bentler, Peter M. (1980), Multivariate Analysis with Latent Variables : Causal Modelling, Annual Review of Psychology, VOl.3l, pp.419-56. Bentler, Peter M. and Douglas G. Bonnett (1980), Significance Tests and Goodness of Fit in Analysis of Covariance Structures, Psychological Bulletin, Vol.88, pp.588-606. Bernstein, I.H. (1988), Applied MMltivariate Analysis, New York : Springer-Verlag. Biggadike, E.R. (1979) , The Risky Business of Diversification, Harvard Business Review, May/June, pp.103-1ll. Biggadike, E.R. (1976), Corporate Diversification : Entry Strategy and Performance, Cambridge, MA : Harvard University Press. Billings, R.S. and S.P. Wroten (1978), Use of Path Analysis in Industrial Organizational Psychology : Criticism and Suggestions, Journal of Applied Psychology, Vol.63 No.6, pp.677-88. Bohrnstedt, G.W. and T.M. Carten (1971), Robustness in Regression Analysis in Sociological Methodology 1971, H.L. Costner (ed.), San Francisco : Jossey-Bass, pp.118-46. Bond, R.S. and D.F. Lean (1977), Sales Promotion and Product Differentiation in Two Prescription Drug Markets, Economic Report, U.S. Federal Trade Commission, February. Boomsma, A. (1983) , On the Robustness of LISREL (Maximum Likelihood) Estimation Against Small Sample Size and Non- normality, Unpublished Dissertation, University of Groningen, 227 Groningen, The Netherlands. Burnkrant, Robert E. and Thomas Page, Jr. (1982), An Examination of Convergent, Discriminant, and Predictive Validity of Fishbein’s Behavioral Intention Model, JOurnal of Marketing Research, Vol.19 (November), pp.550-61. Burstall, M.L. (1985), Regulation of the Pharmaceutical Industry, London : The IEA Health and Welfare Unit. Buzzell, R., B.T. Gale, and R.G.M. Sultan (1975), Market Share - A Key to Profitability, Harvard Business Review, vol.53, (January/February), pp.97-106. Calantone, R.J., C. di Benedetto, and M.S. Meloche (1988), Strategies of Product and Process Innovation : A Loglinear Analysis, RED Management, V01.18 No.1, pp.13-21. Capon, Noel and R. Glazer (1987), Marketing and Technology : A Strategic Co-alingment, JOurnal of Marketing, Vol.51 No.3, pp01-14o Carpenter, G.S.. and K. Nakamoto (1990), Competitive Strategies for Late Entry into a Market with a Dominant Brand, Management Science, Vol.36 No.10, pp.1268-1278. Carpenter, G.S. and K. Nakamoto (1986) , Market Pioneers, Consumer Learning, and Product Perceptions : A Theory of Persistent Competitive Advantage, Research Paper, Columbia University and University of California, (November). Caves, R. (1982), American Industry': Structure, Conduct, and Performance, Englewood Cliffs, N.J. : Prentice Hall. Chakravarthy, 3.8. (1986), Measuring Strategic Performance, Strategic Management JOurnal, Vol.7, pp.437-458. Chakrabarti, A.K. (1985), Managing High Technology RED : Some Critical Issues in Managing High Technology, B.W. Mar, W.T. Nowell, and B.O. Saxberg (eds.), Amsterdam : Elseveir Science Publishers, pp.7-12. Churchill, Gilbert A. and Anthony Pecotich (1982), A Structural Equation Investigation of the Pay Satisfaction - Valence Relationships Among Salespeople, Journal of Marketing, Vol.46 (Fall), pp.114-24. Clymer, Harold A. (1975), The Economic and Regulatory Climate : U.S. and Overseas Trends in Drug Development and Marketing, R.S. Helms (ed.), Washington, D.C. : American Enterprise Institute. 228 Clymer, Harold A. (1970) , The Changing Costs of Pharmaceutical Innovation in Proceedings of the First Seminar on Economics of Pharmaceutical Innovation, Joseph D. Cooper (ed. ) , Washington, D.C. : The American University. Cocks, Douglas L. (1975), Product Innovation and The Dynamic Elements of Competition in the Ethical Pharmaceutical Industry, in Drug Development and Marketing, Robert B. Helms (ed.), American Enterprise Institute for Public Policy Research. Comanor, William S. (1986), The Political Economy of the Pharmaceutical Industry, Journal of Economic Literature, XXIV, (September), pp.1178-1217, Comanor, William S. (1964), Research and Competitive Product Differentiation in the Pharmaceutical Industry in the United States, Economics, Vol.32, (November), pp.372-384. Comanor, W.S. and T.A. Wilson (1974), Advertising, Market Structure and Performance, Review of Economics and Statistics , V01. XLIX, No.4, pp.423-440. Comanor, W.S. and T.S. Wilson (1967) , Advertising, Market Structure and Performance, Review of Economics and Statistics , V01049, pp.423'400 Cool, Karel (1985), Strategic Group Formation and Strategic Group Shifts : A Longitudinal Analysis of the U.S. Pharmaceutical Industry, 1963-1982, unpublished Doctoral Dissertation, Purdue University. Cool , Karel C. and Dan Schendel (1988) , Performance Differences Among Strategic Groups Members , Strategic Management JOurnal, Vol.9, pp.207-223. Cool , Karel C. and Dan Schendel (1987) , Strategic Group Formation and Performance : The Case of the U.S. Pharmaceutical Industry, 1963-1982, Management Science, Vol.33 No.9, pp.1102-1124. Cooper, Robert G. (1985a), Selecting Winning New Product Projects : The NewProd System , Journal of Product Management , NO. 2 ' pp. 34-44 0 Cooper, Robert G. (1985b), Overall Corporate Strategies for New Product Programs , Industrial Marketing Management , Vol . 14 , pp.179-193. Cooper, Robert G. (1983), The New Product Process : An Empirically-Based Classification Scheme, Vol.13 No.1, pp.1-13. “.131 I ' M".- 229 Cooper, Robert G. (1982), New Product Success in Industrial Firms, Industrial Marketing Management, Vol.11, pp.215-24. Cooper, Robert G. (1979a), Identifying Industrial New Product Success : Project NewProd, Industrial Marketing Management, Vol.8, pp.124-135. Cooper, Robert G. (1979b), The Dimensions of Industrial New Product Success and Failures, JOurnal of Marketing, Vol.43, No.3 (Summer). Cooper, Robert G. and E.J. Kleinschmidt (1987), New Products : What Separates Winners From Losers , Journal of Product Innovation Management, Vol.4, pp.169-184. Cooper, Robert G. and E.J. Kleinschmidt (1991), The Impact of Product Innovativeness on Performance, Journal of Product Innovation Management, Vol.4, pp.169-84. Crawford, J. (1975) , Seller Concentration, Entry Barriers, and Profit Margins : A Comment, Industrial Organization Review, Vol.3, No.3, pp.176-178. Crawford, N .K. (1985) , The Role of Technology Licensing in the Diversification Strategies of Small Firms, Unpublished Dissertation, University of Bath. Day. George S. (1986), Analysis for Strategic Marketing Decision, St. Paul, MN : West Publishing. Day, George S. and Saul Klein (1987), Cooperative Behavior in Vertical Markets : The Influence of Transaction Costa and Competitive Strategies in Review of Marketing, Chicago, Ill : American Marketing Association. Day, George and Robert Wensley (1988), Assessing Advantage : A Framework for Diagnosing Competitive Superiority, Journal of Marketing, Vol.52, (May), pp.1-20. Dearden, J. (1969) , The Case Against ROI Control, Harvard Business Review, Vol.47, No.3, p.124-135. Denison E. (1967), Why Growth Rates Differ : Postwar EXperience in Nine Western Countries, Brookings Institution, Washington, DC. Dillion, W.R., R. Calantone, and P. Worthing (1979), The New Product Problem : An Approach for Investigating Product Failures, Management Science, Vol.25, (December), pp.1184-96. Dillion, W.R., T. Domzal, and T.J. Madden (1986), Evaluating Alternative Product Positioning Strategies, JOurnal of 230 Advertising Research, Vol.26, No.4, pp.29-35. Dillion, W.R. and M. Goldstein (1984), Maltivariate Analysis : Methods and Applications, New York : John Wiley. Dimasi, Joseph A., Ronald W. Hansen, Henry G. Grabowski, and Louis Lasagna (1989), The Cost of Innovation in' the Pharmaceutical Industry; JOurnal of.Health.Economics, Vol.10, No.2, pp.107-142. Dimingo, E. (1988), The Fine Art of Positioning, JOurnal of Business Strategy, (March/April), pp.34-38. Downs, A. (1967) , Inside Bureaucracy, Brown, Ma : Brown Little. Droge, Cornelia (1989), Shaping the Route to Attitude Change : Central Versus Peripheral Processing Through Comparative versus Noncomparative Advertising, Journal of Marketing Research, Vol.26 (May), pp.193-204. Duncan, G.D. (1975) , Introduction to Structural Equation Medals, New York : Academic Press. Duncan, G.D. (1966), Path Analysis : Sociological Examples, American JOurnal of Sociology, Vol.72, No.1, pp.1-16. The.Economist (1987), Pharmaceuticals, (February 7), pp.3-12. Elia, C.J. (1980) , Ratio of Stock Price to Firm's RED Spending on Per-Share Basis Found to be Useful Gauge, Wall Street JOurnal, (June 19), pp.47. Fershtman, C., V. Mahajan, and E. Muller (1990), Market Share Pioneering Advertising : A Theoretical Approach, Management Science. Financial World (1989a), Pharmaceuticals, (May), pp.54-75. Financial World (1989b), Grading RSD, (January 24), pp.22-24. Financial World (1987) , The Coming Shakeout in Drugs, (January 20), pp.103-106. Fiegenbaum, A. , D. Sudharshan, and H. Thomas (1990) , Strategic Time Periods and Strategic Groups Research : Concepts and Empirical Example, Journal of Management Studies, Vol .27, No.2, pp.133-148. Fornell, Claes (1987), A Second Generation of Multivariate Analysis : Classification of Methods and Implications for Marketing Research in Review of.Marketing, Michael J. Houston 231 (ed.), Chicago : American Marketing Association, pp.407-50. Fornell, Claes and David F. Larcker (1981), Evaluating Structural Equation Models With unobservable variables and Measurement Error, Psychological Review, Vol.81, pp.39-50. Foxall, G. (1983), Limited Strategic Innovation : Coping with the Complexity of New Product Development, Marketing Intelligence and Planning, Vol.1, pp.28-39. Franko, L.G. (1989), Global Corporate Competition : Who's Winning, Who's Losing, and the RED Factor as One Reason Why, Strategic Management Journal, Vol.10, pp.449-474. Gagnon, J. (1983), Physician Prescribing Behavior in Principals of .Pharmaceutical Marketing, M. Smith (ed.), Philadelphia, PA : Lea and Febiger, pp.68-87. Galbraith, J.K. (1952), American Capitalism : The Concept of Countervailing Power, Boston : Houghton Mifflin. Garvin, David A. (1984), What Does Product Quality Really Mean?, Sloan Management Review, Vol.26, (Fall), pp.25-43. Gaski, John F. (1986) , Interrelations Among A Channel Entity's Power Sources : Impact of the Exercise of Reward and Coercion on Expert, Referent, and Legitimate Power Sources, Journal of Marketing Research, Vol.23 (February), pp.62-77. Glazer, A. (1985) , The Advantages of Being First, The American Economic Review, (June), pp.473-480. Gobeli, D.H. and Brown, D.J. (1987), Analyzing Product Innovations, Research Management, Vol. 30 (July-August), pp. 25-31. Gold, B. (1980), Rediscovering the Technology Foundations of Industrial Competitiveness, Omega, Vol.8, No.5, pp.503-4. Grabowski, Henry (1976) , Drug Regulation and Innovation Empirical Evidence and Policy Options, Washington, D.C. American Enterprise Institute for Public Policy Research. Grabowski, Henry (1990), Innovation and International Competitiveness in Pharmaceuticals in The Proceedings of the 2nd International Joseph Schumpeter Society Meetings, Ann Arbor, Mi : University of Michigan Press, pp.167-85. Grabowski, Henry and J. Vernon (1990) , A New Look at the Returns and Risks to Pharmaceutical RED, Management Science, Vol.36, No.7, pp.804-821. 232 Grabowski, Henry and J. Vernon (1989), The Effect of Generic Entry on Market Prices in the Pharmaceutical Industry, Duke University, (June). Grabowski, H. and J. Vernon (1986), Longer Patents for Lower Imitation Barriers : The 1984 Drug Act, American Economic Review, Vol. 76 (May), pp. 395-412. Grabowski, H. and J. Vernon (1982), A Sensitivity Analysis of Expected Profitability of Pharmaceutical Research and Development, Managerial and.Decision.Economics, Vol.3, pp.36- 40. Grabowski, H. and Mueller (1978), Industrial Research and Development Intangible, Capital Stock and Firm Profit Rates, The Bell JOurnal of Economics, Vol.9, No.2 (Autumn). Grabowski, Henry (1968), The Determinants of Industrial Research and Development: A Study of the Chemical, Drugs, and Petroleum Industries, Jaurnal of Political Economy, Vol. 74, (March-April), p.294. Grabowski, Henry, Vernon J.M. and Thomas, L.G. (1976), The Effects of Regulatory Policy on the Incentives to Innovate : An International Comparative Analysis in Impact of Public Policy on Drug Innovation and Pricing, S. A. Mitchell and E. A. Link (eds. ), Washington, D. C. : The American University. Green, Donna H. and Adrian B. Ryans (1990), Entry Strategies and Market Performance : Causal Modelling of a Business Simulation, JOurnal of Product Innovation Management, Vol.7, pp.45-58. Green C. and J. Nkonge (1989), Gaining a Competitive Edge Through Conjoint Analysis, Business, vel.39, No.2, pp.14-18. Haines, D. W., R. Chandran, and A Parkhe (1989), Winning by Being the First to Market. . . .or Second, The Journal of Consumer Marketing, Vol.6, No.1, pp.63-69. Hambrick, D.C. (1983), High Profit. Strategies in. Mature Capital Goods Industries : A Contingency Approach, Academy of Management JOurnal, Vol.26 (December), pp.687-707. Hambrick, D.C. and LC. Macmillian (1985), Efficiency of Product R&D in Business Units : The Role of Strategic Context, Academy of Management Journal, Vol.28, No.3. Hambrick, D.C., I.C. Macmillian, and R.R. Barbosa (1983), Business Unit Strategy and Changes in the Product RED Budget, Management Science, Vol.29, No.7. 233 Hannan, M.T. and J. Freeman (1977), The Population Ecology of Organization, American JOurnal of Sociology, Vol.82, pp.929- 964. Hansen, R. W. (1980), Pharmaceutical Development Cost by Therapeutic Category, University'of Rochester Graduate School of Management, WOrking Paper, (March). Hansen, R.W. (1979), The Pharmaceutical Development Process : Estimates of Development Costs and Times and Effects of Proposed Regulatory Changes in Issues in Pharmaceutical Economics, Robert I. Chien (ed.), Lexington, Mass : D.C. Heath, pp.151-187 Harberger, A.C. (1984), World Economic Growth, ICS Press : San Francisco, CA. Harrell, Gilbert (1978), Pharmaceutical Marketing in The Pharmaceutical Industry, Cotton M. Lindsay (ed.), New York : John Wiley, pp.69-90. Harrell, Gilbert (1972), Modelling Physician Prescribing Behavior : Attitudes, Normative Beliefs, Motivation to comply, Confidence, Behavioral Intention and Behavior, Unpublished Dissertation, The Pennsylvania State University. Harrigan, R.R. (1981), Barriers to Entry and Competitive Strategies, Strategic Management Journal, Vol.2, No.4, pp.395- 412. Hatten, K. (1974), Strategic Models in the U.S. Brewing Industry, unpublished Doctoral Dissertation, Purdue University. Hatten, K. and D. Schendel (1977), Heterogeneity Within an Industry : Firm Conduct in the U.S. Brewing Industry, The JOurnal of Industrial Economics, Vol.26, pp.91-112. Hatten, K., D, Schendel, and A. Cooper (1978), A Strategic Model of the U.S. Brewing Industry, Academy of Management JOurnal, pp.784-810. Hayduk, L.A. (1987), Structural Equation Modelling with LISREL, Baltimore, MD : John Hopkins University Press. Hayes, S.L. III, A. Spence, and D.V.P. Marks (1983), Competition in the Investment Banking Industry, Cambridge, MA : Harvard University. Hayes, W.L. (1973), Statistics for the Social Sciences, New York : Holt, Rinehart and Winston. 234 Hunt, Michael (1972), Competition in the Major Home Appliance Industry, 1960-1970, Unpublished Doctoral Dissertation, Harvard University. Jacobsen, R. (1987), The Validity of ROI as a Measure of Business Performance, American Economic Review, Vol.77 (June), pp.470-478. , Jain, Subhash (1981), Marketing Planning and Strategy, Cincinnati, OH : South Western Publishing Company. Jarrell, S. (1983), Research and Development and Firm Size in the Pharmaceutical Industry, Business.Economics, (September), pp. 26-39 0 James, Barrie (1977), The Future of the Multinational Pharmaceutical Industry to 1990, New York : John Wiley and Sons, Appendix 4. Jaworski, Bernard J. and Deborah, J. MacInnis (1989), Marketing Jobs and Management Controls : Toward a Framework, Journal of Marketing Research, Vol.26 (November), pp.406-19. Jensen, Elizabeth J; (1987), Research Expenditures and the Discovery of New Drugs, The Journal of Industrial Economics, Vol.36 (September), pp.83-95. Joglekar, P. and Paterson, M.L. (1986), A Closer Look at Returns and Risks of Pharmaceutical RED, Journal of Health Economics, Vol.5, pp.153-177. John, George and Torger Reve (1982), The Reliability and Validity of Key Informant Data from Dyadic Relationships in Marketing Channels , Journal of Marketing Research, Vol . 19 (November), pp.517-24. Johne, F.Axel and Patricia A. Snelson (1988), Success factors in Product Innovation : A Selective Review of the Literature, Journal of Product Innovation Management, Vol.5, No.2, pp.114- 128. Johnson, J (1984) , Econometric Models, New York : McGraw Hill. Joreskorg, Karl and Dag Sbrbom (1978), Structural Analysis of Covariance and Correlation Matrices, Psychometrika, Vol.43, pp.443-77. Jereskorg, Karl and Dag SOrbom (1981),.LISREL V : Analysis of Linear Structural Relationships by Maximum Likelihood and Least Squares Method, Chicago : National Educational Resources. 235 Joreskorg, Karl and Dag SOrbom (1984) , LISREL VI, Mooresville, IN : Scientific Software. JOreskorg, Karl and Dag Sbrbom (1988), LISREL‘V, Mooresville, IN : Scientific Software. Kamien, M.L. and Schwartz, N.L. (1975), Market Structure and Innovation : A Survey, Journal of Economic Literature, Vol.13, No.1 (March). Keats, B. N. (1983), On the Measurement of Strategic Performance, Paper Presented at the Third Annual Conference of the Strategic Management Society, Paris. Kemp, Bernard A. (1975) , The Follow-On Development Process and the Market For Diuretics in R.B. Helms (ed. ) , Drug Development and Marketing, The American Enterprise Institute for Public Policy Research : Washington, D.C., pp.255-276. Kerlinger, F.N. and E.J. Pedhauzer (1973), Multiple Regression in Behavioral Research, New York : Holt, Rinehart and Winston. Kerlinger, F.N. and E.J. Pedhauzer (1982) , Multiple Regression in Behavioral Research, (2 edition), Mew York : Holt, Rinehart, and Winston. Killing, J.P. (1978), Diversification Through Licensing, RED Management, (June), pp.159-163. King, R.H., and A.A. Thompson Jr. (1982), Entry and Market Share Success of New Brands in Concentrated Markets, JOurnal of Business Research, Vol.10, No.3, pp.371-383. Kirchhoff, B. (1977) , Organizational Effectiveness Measurement and Policy Research, Academy of Management Review, Vol.2, pp.347-55. Klein, S. (1986) , Fostering Development Through Backward Integration of Import Channels, Journal of Macromarketing, Vol.6 (Spring), pp.17-27. Kotler, P. (1984), Marketing Management : Analysis, Planning and'Control, (5th edition), Englewood Cliffs, N.J. : Prentice Hall Inc. Lambkin, M. (1989), Order of Entry and Performance in New Markets, Strategic Management JOurnal, Vol.9, pp.127-140. Leffler, K.B. (1981) , Persuasion or Information? The Economics of Prescription Drug Advertising, Journal of Law and Economics, Vol.24, No.1, pp.45-74. 236 Leifer, R. and G. Huber (1977), Relationships Among Perceived Environmental Uncertainty, Organization Structure, and Boundary-Spanning Behavior, Administrative Science Quarterly, (June), pp.235-247. Liebermann, M.B. and D.B. Montgomery (1988), First-Mover Advantages, Strategic Management JOurnal, Vol.9, pp.41-58. Lilien, Gary L. and Philip Kotler (1983), Marketing Decisions Making : A Model Building Approach, New York : Harper and Row. Link, Peter L. (1987) , Keys to New Product Success and Failure, Industrial Marketing Management, Vol.16, pp.109-18. Little, J.D.C., D. Bell and R. Keeney (1975), A Market Share Theorem, Journal of Marketing Research, Vol .12 (May), pp. 136- 41. Loehlin, J.C. (1987) , Latent Variable Models : An Introduction to Factor, Path, and Structural Analysis, Hillsdale, NJ : Eribaum. Lowe, J. and N. Crawford (1983), New Product Development and Technology Licensing for the Small Firm, Industrial Management and Data Systems, (Sept/Oct), pp.26-29. Macmillian, LC. and D.L. Day (1987), Corporate Ventures into Industrial Markets : Dynamics of Aggressive Entry, Journal of Business Venturing, Vol.2, pp.29-39. Maidique, M.A. and Zirger, E.J. (1984), A|Study of Success and Failure in Product Innovation : The Case of U.S. Electronics Industry, IEEE'Transactions in.Engineering Management, Em-31, Vol.4, (November), pp.192-203. Mann, M.H. (1966) , Seller Concentration, Barriers to Entry and Rates of Return in Thirty Industries, 1950-1960, Review of Economics and Statistics, Vol.48 (August), pp.296-307. Mansfield, E. (1987), The Speed and Cost of Industrial Innovation in Japan and the United States : External versus Internal Technology, Paper Presented at Annual Meeting of American Economic Association. Mansfield, E. (1968), Industrial Research and Technological Innovation, W.W. Norton : New York. Mansfield, E., M. Schwartz, and S. Wagner (1981), Imitation Costs and Patents : An Empirical Study, Economic‘Journal, 91, Mardia. K.V. (1974), Applications of Some Measures of 237 Multivariate Skewness and Kurtosis in Testing Normality and Robustness Studies, Sankhya, Vol.36B, pp.115-28. Mason, E. (1939) , Price and Production Policies of Large-scale Enterprises, American Economic Review, (March), pp.61-74. McDaniel, S.W. and J.W. Kolari (1987), Marketing Strategy Implications of the Miles and Snow Typology, Journal of Marketing, Vol.51 (October), pp.19-30. McGee, J. and H. Thomas (1986), Strategic Groups : Theory, Research and Taxonomy, Strategic Management JOurnal, Vol.7, (March-April), pp.141-160. McQuire, J. and T. Schneeweis (1983), An Analysis of Alternate Measures of Strategic Performance, Paper presented at the third annual conference at the Strategic Management Society, Par s. Meadsay, W. (1977), in The Pharmaceutical Industry in The Structure of American Industry, Walter Adams (ed. ) , New York : Macmillian. Meyer, A.D. (1982), Adapting to Environmental Jolts, Administrative Science Quarterly, Vol.28, (December), pp.515- 537. Miles, R.E. and C.C. Snow (1978), Organizational Strategy, Structure, and Process, New York : McGraw Hill Book Company. Miller, A., G. B. William, and R. Wilson (1989), Entry Order, Market Share, and Competitive Advantages : A Study of Their Relationships in New Corporate Ventures, JOurnal of Business venturing, Vol.4, No.3, pp.197-209. Monteverde, K. and D. Teece (1982a), Supplier switching Costs and Vertical Integration in the Automobile Industry, Bell JOurnal of Economics, Vol.13 (Spring), pp.206-213. Monteverde, K. and D. Teece (1982b), Appropriable Rents and Quasi-Vertical Integration, Journal of Law and Economics, Vol.25 (October), pp.321-328. Moore, William L. (1987) , New Product Development Practices of Industrial Marketers, JOurnal of .Product Innovation Management, Vol.4 No.1, pp.6-20. Morbey, G.K. (1988), RED : Its Relationship to Company Performance, Jaurnal of.Product Innovation‘Management, Vol.5, Moriarty, M. (1975), Cross-sectional, Time-series Issues in 238 the Analysis of Marketing Decision Variables, Journal of Marketing Research, Vol.12 (may), pp.142-150. Murray, J.A. (1989) , Post-Marketing Surveillance in Pharmaceuticals : Reactions, Journal of Public Policy and Marketing, pp.44-60. Muthen, B. and D. Kaplan (1985), A Comparison of Some Methodologies for the factor Analysis of Non-normal Likert Variables, British Journal of Mathematical and Statistical Psychology, Vol.38, pp.171-89. Namboodiri, N.K., L.F. Carter, and H.M. Blalock (1975), Applied Multivariate Analysis and Experimental Design, New York : McGraw Hill. National Academy of Sciences (1983) , Competitive Status of the U.S. Pharmaceutical Industry, Washington, D.C. : National Academy Press. Nelson, R. and S. White (1977), In Search of a Useful Theory of Innovation, Research Policy, Vol.6, Summer, pp.36-76. Ness, M.R. (1986), Product Positioning Using Quantitative Research : A Strategic Perspective, Food Marketing, Vol.2, No.3, pp.145-162. Newman, H. (1972) , Strategic Groups and the Structure- Performance Relationships : A Study with Respect to the Chemical Process Industries , Unpublished Doctoral Dissertation, Harvard University. Ohmae, K. (1986), Becoming a Triad Power : The New Global Corporation, International Marketing Review, (Autumn), pp.7- 20. Oliver, Dennis S. (1982) , Some Aspects of Technology Transfer, Society of Research Administrators Journal , Vol. 14 (Summer) , pp.5-16. Oster, S. (1982) , Intraindustry Structure and the Ease of Strategic Change, Review of Economics and Statistics, (August), pp.417-427. Pakes, A. (1985), On Patents, RED, and the Stock Market Rate of Return, Jaurnal of Political Economy, Vol.93, Vol.2. Parasuraman, A. and L.M. Zeren (1983), RED's Relationship with Profit and Sales, Research Management, (January/February). Parsons, F. (1960) , Strategy and Process in Modern Societies, New York : The Free Press. 239 Pedhauzer, E.J. (1982), Multiple Regression in Behavioral Research, (2nd ed.), New York : Holt, Rinehart, and Winston. Pelztman, S. (1974), Regulation of Pharmaceutical Innovation : The 1962 Amendments, Washington, D.C. : American Enterprise Institute for Public Policy Research. Peters, T.J. and R.H. Waterman (1982), In Search of EXcellence : Lessons from America’s Best Run Companies, New York : Harper and Row. Phillips, A. (1976), A Critique of Empirical Studies of Relations Between Market Structure and Profitability , The JOurnal of Industrial Economics, Vol.24, pp.241-9. Pisano, G.P. (1990), The RED Boundaries of the Firm : An Empirical Analysis, Administrative Science Quarterly, Vol.35, pp.153-76. Porter, Michael (1990), The Competitive Advantage of Nations, Harvard Business Review, (March/April), pp.73-93. Porter, Michael (1985), Technology and Competitive Advantage in Competitive Advantage : Creating and sustaining Superior Performance, Michael Porter (ed.), New York : The Free Press. Porter, Michael (1980a), Industry Structure and Competitive Strategy : Keys to Profitability, Financial Analysis Jaurnal, Vol.50, (October), pp.510-520. Porter, Michael (1980b), Competitive Strategy, New York : The Free Press. Porter, Michael (1977), Market Structure, Strategy Formulation, and Firm Profitability’: The Theory of Strategic Groups and Mobility Barriers, Werking Paper, Harvard University, Boston. Porter, Michael (1973) , Retailer Power, Manufacturing Strategy and Performance in Consumer Goods Industry, Unpublished Doctoral Dissertation, Harvard University. Prescott, J.E., and M. Visscher (1977), Sequential Location Among Firms with Foresight, Bell Journal of Economics, vel.8, pp.378-393. Price, J. (1972), The Study of Organizational Effectiveness, The Sociological Quarterly, Vol.13, pp.3-15. Ramsler, M. (1982), Strategic Groups and Foreign Market Entry in Global Banking Competition, unpublished .Doctoral Dissertation, Harvard University. 240 Rao,. R. and D. Rutenberg (1979), Pre-empting an Alert Rival : Strategic Timing of the First Plant by Analysis of Sophisticated Rivalry, Bell Journal of Economics, Vol.8, pp.378-393. Rappaport, A. (1981), Selecting Strategies that Create Shareholder Value, Harvard Business Review, Vol. 3 , No.59 pp.139-49. Reece, J.S. and W.R. Cool (1978), Measuring Investment Center Performance, Harvard.Business.Review, Vol.56, No.3, pp.28-46. Reynard, E.L. (1979), A.Method for Relating Research Spending to Net Profits, Research Management, (July). Rindskopf , David (1983) , Parameterizing Inequality Constraints on Unique Variances in Linear Structural Models, Psychometrika, Vol.48, pp.78-83. Robinson, W.T. (1988), Sources of Market Pioneer Advantages : The Case of Industrial Goods Industries, JOurnal of Marketing Research, Vol.25, pp.87-94. Robinson, W.T. and C. Fornell (1985), The Sources of Market Pioneer Advantages in Consumer Goods Industries, JOurnal of Marketing Research, Vol.22, pp.305-317. Roberts, E.B. (1981), Influences on Innovation : Extrapolations to Biomedical Technology, in Biomedical Innovation, Roberts et al. (eds), Cambridge, MA : MIT Press, pp. 50-74 0 Roberts, E.B. and C.A. Berry (1987), Entering New Businesses : Selecting Strategies for Success, Sloan Management Review, Vol.26, No.3. Rothwell, R., C. Freeman, A. Horsley, V. Jervis, A.B. Roberston, and J. Townsend (1974), Sappho Updated - Project SAPPHO, Phase II, Research Policy, Vol.3, pp.258-291. Rubenstein R., et al. (1976), Factors Influencing Innovation Success at the Project Level , Research Management, (May), pp.15-20. Rumelt, Richard P. (1974), Strategy, Structure and Economic Performance, Boston, MA : Division of Research, Graduate School of Business Administration, Harvard University. Rumelt, Richard P. and R. Wensley (1981), In Search of the Market Share Effect, Academy of Management Proceedings, pp.2- 6. 241 Ryan, Michael J. (1982), Behavioral Intention Formation : A Structural Equation Analysis of Attitudinal and Social Influence Interdependency, Journal of Consumer Research, Vol . 9 No.3, pp.263-78. Salter, Malcom S. and Wolf. S. Weinhold (1979), Diversification Through Acquisition, New York : The" Free Press. Sarett, L. H. (1974), FDA Regulations and Their Influence on Future RED, Research Management, Vol.27 (March), pp.18-20. Satorra, A. and William E. Saris (1985), The Power of the Likelihood Ratio Test in Covariance Structure Analysis, Psychometrika, Vol.50, pp.83-90. Schendel, D. and R. Patton (1978), A Simultaneous Equation Model of Corporate Strategy, Management Science, (November), Scherer, F.N. (1976), Corporate Inventive’Output, Profits and Growth, Journal of Political Economy, Vol.73 No.3, pp.101-111. Schifrin, L.G. (1967), The Ethical Drug Industry : The Case for Compulsory Patent Licensing, Antitrust Bulletin, Vol.12, Fall, pp.901. Schmalensee, R. (1982), Product Differentiation Advantages of Pioneering Brands, The.American.Economic.Reviewy Vol.72 No.3, pp.349-365. Schmalensee, R. (1978), On the Use of Economic Models in Antitrust.: The Realemon Case, university'of Pennsylvania Law Review, Vol.127, pp.345-365. Schnaars, S.P. (1986), When Entering Growth Markets, Are Pioneers Better Than Poachers , Business Horizons , (March- April), pp.28-36. Schoeffler, S. (1977), Cross-sectional Study of Strategy, Structure, and Performance : Aspects of PIMS Programs in Strategy + Structure :- Performance, Hans Thorelli (ed. ) , Bloomington, Ill : Indiana University Press. Schoeffler, S., R.D. Buzzell, and D.F. Heany (1974), Impact.of Strategic Planning on Profit Performance, Harvard Business Review, (March/April). Schumpeter, J.A. (1975), The Process of Creative Destruction, New York : Harper Colophon Books, pp.81-86. Schumpeter, Joseph A. (1950) , Capitalism, Socialism, and 242 Democracy, New York : Harper Colophon Books. Schumpeter, Joseph A. (1934), The Theory of Economic Development, Harvard University Press, Cambridge, MA. Schwartzman, D. (1976) , Innovation in the Pharmaceutical Industry, The John Hopkins University Press, Baltimore, MD. Schwartzman, D. (1975) , The Expected Return from Pharmaceutical Research, Washington, D.C. : American Enterprize Institute for Public Policy Research. Shahrokhi, M. (1987) , Reverse Licensing : International Transfer of Technology to the United States, Praeger, New York. Shocker, A.D. and V. Srinivasan (1979), Multiattribute Approaches for Product Concept Evaluation and Generation : A Critical Review, (JOurnal of (Marketing’ Research, Vol.16, pp 0 158-80 0 Shrader, C.B. , L. Taylor, and D. Dalton (1984) , Strategic Planning and Organizational Performance : A Critical Appraisal, Journal of Management, Vol.10 (Summer) , pp.149-171. Shrader, C.B. (1975) , The Expected Return from Pharmaceutical Research, Washington, D.C. : American Economic Enterprise Institute for Public Policy Research. Spilker, B. (1989), Multinational Drug Companies : Issues in Drug Discovery and Development, New York : Raven Press. Statman, Meir (1983), Competition in the Pharmaceutical Industry : The Declining Profitability of Drug Innovation, American Enterprise Institute, Washington, D.C. Statman, Meir and Tyzoon T. Tyebjee (1985), Strategic Responses to Changes in Public Policy : The Case of the Pharmaceutical Industry and Drug Substitution Laws, Journal of Public Policy and Marketing, pp.99-112. Statman, Meir and Tyzoon T. Tyebjee (1981) , Trademarks, Patents, and Innovation in the Ethical Drug Industry, Journal of Marketing, Vol.45, (Summer), pp.71-81. Steele, H. (1962), Monopoly and Competition in the Ethical Drug Industry, Journal of Law and Economics , Vol . 5 , (October), pp.13l-136. Steers, R. (1975) , Problems in the Measurement of Organizational Effectiveness , Administrative Science Quarterly, Vol.20, pp.546-558. 243 Tapon, Frank (1989), A Transaction Costs Analysis of Innovations in the Organization of Pharmaceutical RED, Journal of Economic Behavior and Organization, Vol.12, pp.197-213. Temin, P. (1979), Technology, Regulations, and Market Structure in the Modern Pharmaceutical Industry, Bell JOurnal of Economics, Vol. 10, pp. 426-446. . Thomas, L.G. (1988), Multifirm Strategies in the U.S. Pharmaceutical Industry, in International Collaborative ventures in.U.S. Manufacturing, D.C. Mowery (ed.), Cambridge, Mass : Ballinger Publishing Company. Urban, G, T. Carter, 8. Gaskin, and Z. Mucha (1986), Market Share Rewards to Pioneering Brands : An Empirical Analysis and Strategic Implications, Management Science, Vol.32, No.6, pp.645-659. U.S. Bureau of Census (1986), 1982 Census of Manufacturing, Concentration Ratios in Manufacturing, MC77 (SR) - 9, Washington , D . C . U.S. International Trade Commission (1991), Global Competi tiveness of U . S . Advanced-Technology Manufacturing Industries : Pharmaceuticals, Washington, D.C. U.S. Senate (1972), Hearings on Competitive Problems in the Drug Industry, Select Committee on Small Business, Subcommittee on Monopoly. Varadarajan, P. Rajan and V. Ramanujam (1987 ), Diversification and Performance : A Reexamination Using a New Two-dimensional Conceptualization of Diversity in Firms, Academy of Management Jaurnal, Vol.30 (June), pp.380-97. Venkatranan, N. and V. Ramanujan (1986) , Measurements of Business Performance In Strategy Research : A Comparison of Approaches, Academy of Management Review, Vol.11 (October), pp.801-814. Vernon, J.M. (1972), Market Structure and Industrial Performance : A Review of Statistical Findings, Allyn and Bacon. Vernon, J.M. and P. Gusen (1974), Technical Change and Firm Size : The Pharmaceutical Industry, Review of Economics and Statistics, Vol.56 (August), pp.294-301. Virts. J.R. and Weston, J.E. (1980), Returns to Research and Development in the U.S. Pharmaceutical Industry, Managerial and Decision Economies, Vol.1, pp.103-11. 244 Wagner, H.M. (1984), Profit Wonders, Investment Blunders, Harvard Business Review, Vol.62, (September-October) , pp.121- 135. Walker, G. and D. Weber (1984), A Transaction Cost Approach to Make-or-Buy Decisions, Administrative Science Quarterly, Vol.29 (September), pp.373-391. = Walker, H.E. (1971), Market Power and Price Levels in the Ethical Drug Industry, Bloomington : Indiana University Press. Walters, (1986), Competitive Performance and Strategic Positioning in International Financial Services, paper presented for a conference at the International University of Japan, Tokyo, 1-2 September, Wardell, W.M. (1973) , Introduction of New Therapeutic Drugs in the United States and Great Britain : An International Comparison, Clinical Pharmacology and Therapeutics, Vol.14 (September/October), pp.773-90. Wardell, W.M. and L. Lasagna (1975), The Rate of New Drug Discovery in Drug Development and Marketing, Robert Helms (ed.), Washington, D.C. :American Enterprise Institute for Public Policy Research. Weiss, D.L. (1968), Determinants of Market Share, JOurnal of Marketing Research, Vol.5 (August), pp.290-295. Wernefelt, B. (1985), Brand Loyalty and User Skills, Journal of Economic Behavior and Organizations, Vol.6, pp.381-385. Wernerfelt, B. (1984), Stagflation, New Products, and Speculation, Journal of Macromarketing, Vol . 6 (Summer) , pp.295-309. Whitten, LT. (1979), Brand Performance in the Cigarette Industry and the Advantage of Early Entry, 1913-1974, Economic Report, U.S. Federal Trade Commission, June. Wiggin, S. (1987), The Cost of Developing a New Drug, Pharmaceutical Manufacturers Association, Washington, D.C. (June). Williamson, Oliver E. (1985), The Economic Institutions of Capitalism, New York : The Free Press. Williamson, Oliver E. (1981) , The Modern Corporation Origins, Evolution, Attributes, Journal of Economic Literature, Vol.19, pp.1537-1568. 245 Williamson, Oliver E. (1975) , Markets and Hierarchies Analysis and Antitrust Implications, New York : The Free Press. Wind, Yoram (1973), A New Procedure for Concept Evaluation, Journal of Marketing, Vol.37, (October), pp.2-11. Wind, Yoram and V. Mahajan (1981), Designing Product and Business Portfolios, Harvard Business Review, Vol.59, (January-February), pp.155-165. Wind, Yoram and Robertson, Thomas S. (1983), Marketing Strategy : New Directions for Theory and Practice, JOurnal of Marketing, Vol.4? (Spring), pp.12-25. Woo, C.Y. and G. Willard (1983), Performance representation in Business Policy Research : Discussions and Recommendation, Paper Presented at the 23rd Annual National Meetings of the Academy of Management. . Woo, C.Y. (1979), Strategies of Effective Low Share Businesses, Unpublished .Doctoral .Dissertation, Purdue University. APPENDICES 246 APPENDIX A SUB-CATEGORIES OF DRUGS‘ Antiinfsotixos Cephalosporins Macrolides Penicillins Tetracyclines Sulfonamides Antifungals Antibiotics Aminoglycosides Urinary Germicides Wm Antimetabolites Antibiotics Hormones Antineoplastics l l'l' I . Antihistamine Autonomios Autonomics W Antilipemics Antianginals Beta-blockers Antiarrhythmics Antihypertensives Vasolidators Calcium Channel Blockers QBDIIEI.H§I¥QHE_5¥§IBD Antiparkinson Benzodiazepines Anxiolytics Anorexics Tranquilizers Tranquilizers Phenothiazines Sedative Hypnotic 247 Psychotherapeutics Antidepressants Respiratory and Cerebral Stimulants Analgesics Non-narcotic Analgesics and Antipyretics Antidepressants Tri and Tetracyclines Wino]. - Antiucler - Cathartics - Antidiarrheal WWW - Adrenals - Insulins - Progestrones W - Anti-inflammatory (non-steriods) - Anti-inflammatory Eiolooioalo - Vaccines W - Antiinflammatory - Fungicides - Keratolyt-antiacne Antibiotics W - Respiratory ‘ Extracted from Paul de Haen Modified American Formulatory Service Therapeutic Classification System. 248 APPENDIX B MATHEMATICAL DERIVATION 0F NORMED AND NON-NORMED FIT INDICES The normed and nonnormed fit indices proposed by Bentler and Bonnett (1980) are essentially comparative fit indices. These indices evaluate the adequacy of a particular model M, in relation to a continuum models ranging from M, to M. where M, is the most restricted model and M. is the least restricted or saturated model. In practice, this is done by evaluating where the goodness-of-fit index T, falls in relation to T, and T,,. If T, is close to T,, M, is hardly and improvement over M,, and the fit index is close to zero. If T, is close to T,, M, is almost as good as the saturated model, which corresponds to the data, and the fit index is close to one. Bentler and Bonnett (1980) proposed to evaluate model M, by comparing T, to T, via NFI = L--_I.. T1 which equals zero when T, =- T,, equals 1.0 when T, = 0, and is in the 0-1 range. Because of the 0-1 range, this index is called the normed fit index. A disadvantage of the NFI is that it is affected by the sample size (Bearden, Sharma, and Tool 1982). In small samples, it may not reach 1.0 when the model is correct. This can occur because the expected value of T, may be greater than 0, for example, when T, is a X’(d,) variate (T,,) = d,. This difficulty of range was resolved by 249 the modification index. NNFI = I. _-_d.d...T.“ '1', - d, called the nonnormed fit index. The degrees of freedom adjustment in this index was designed to improve. its performance near 1.0, not necessarily to permit the index to reflect other model features such as parsimony. When T,-= (1;) = at, the NNFI - 1.0, thus obviating a major difficulty with NFI. However, the NNFI can fall outside the 0-1 range. It will be negative when d,d,“T, > T,, since usually T, >> d,. It will exceed 1.0 when T,‘< d,. In fact, the index can be anomalously small, especialLy in small samples, implying a terrible fit when other indexes suggest an acceptable model fit (Anderson and Gerbing 1984) . As a consequence, the variance of NNFI is substantially larger than the variance of NFI. Despite this negative feature, the NNFI has the major advantage of reflecting model fit very well at all sample sizes (Anderson and Gerbing 1984). MICHIGAN STATE UNIV. LIBRRRIES \lHlWW‘II’"HIMIlllmulw\IWNW‘IW 31293010559833