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MAKING INTANGIBLES TANGIBLE:
ANTECEDENTS AND CONSEQUENCES OF MARKETING EQUITY

By

BRIAN R. CHABOWSKI

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Marketing and Supply Chain Management

2007

ABSTRACT

MAKING INTANGIBLES TANGIBLE:
ANTECEDENTS AND CONSEQUENCES OF MARKETING EQUITY

By

Brian R. Chabowski

Our understanding of the interface between marketing outcomes and ﬁnancial
performance has just begun. In fact, though recent research has explored these
relationships to some degree, we lack a comprehensive framework that is based on
proven theoretical underpinnings and responds to the need for marketing activities to be
ﬁnancially justiﬁable. As part of this move toward ﬁnancially justiﬁable marketing
studies, this study introduces the notion of marketing equity - or, ownership in the
marketplace provided by the marketing function. Based on studies related to customer
satisfaction, brand equity, and corporate reputation, the analysis here provides and tests a
model of cross-functional marketing resources that may inﬂuence marketing equity and

ﬁnancial performance.

Copyright by
BRIAN R. CHABOWSKI

2007

ACKNOWLEDGEMENTS

Most importantly, I would like to thank my wife, Tiffany, for her undying and
unwavering support — without which I may never have completed this educational
odyssey. Equally important, I would like to thank my daughter, Amber, whose
unexpectedly phenomenal inspiration has provided purpose of an existential sort to my
life. To my parents, Elaine Bradford and Richard Chabowski, who encouraged me to
think creatively and develop a sense of self. To Alfred S. Rosenfelder, my great-uncle,
for his thoughts and serenity at important transitions in my life. To my parents—in-law,
Kenneth D. Ramsey and Patricia Ramsey, for their support and encouragement during
this process. To my paternal grandparents, Harry J. Chabowski and Evelyn M.
Chabowski, whose insistence that I take a high school “bookkeeping” class may have
ﬁnally paid off. To my maternal grandparents, Fern Bradford and Charles E. A. Bradford,
who saw something in me early in my life. To two of my great-aunts, Estelle Sackarnd
and Rose Figiel, whose sisterly arguments taught me the ﬁner points of professional and
personal debate. To Frank Chabowski, whose pioneering spirit all those decades ago
acted as a catalyst in the path of my life thus far.

Throughout this journey toward completion of my dissertation, G. Tomas M. Hult
deserves much more than a simple ‘thank you’ for his patience, fortitude, and guidance.
His insights over the past three years have informed me well as to the world of academia.
He has effectively managed the forces of “nature and nurture” to get me to this point. To
S. Tamer Cavusgil, his thoughts on the international aspects of my dissertation were
immensely invaluable in positioning my thoughts. To Roger J. Calantone, who provided

unselﬁsh guidance on methods and other key issues to help me complete this intellectual

iv

adventure. To David J. Closs, his insights into topics concerning supply chain
management and logistics were quite informative and practical to me and rightfully
forced me to remain grounded in reality.

To the many professors I had the opportunity to learn from while an
undergraduate student (William Urban, Douglas Spitz, Andrew Weiss, Ken McMillan,
Cheryl Meeker, J aroslava Honova, Susan Holm, Lee McGaan, William J. Wallace, James
DeYoung, Craig Watson, Alfred Keller, and others), whose inﬂuences have marked me
in ways they probably could not have anticipated. To Julius Zareckas, who gave me the
chance to prove myself in Lithuania when few others would. To George Baillie and P.
Roberto Garcia, who gave me opportunities to continue my international aspirations. To
Daniel C. Smith, J onlee Andrews, and Idalene (Idie) Kesner, who were pivotal in
enlightening me as to how to become a well-rounded and more complete educator in
business. To J. Chris White, who introduced me to the rigors of academia. To J anell
Townsend and Sengun Yeniyurt, whose thoughts were guideposts for me as I sought to
understand the intriguing world around me.

Undoubtedly, I may have missed mentioning other important individuals who had
an inﬂuence on my career to date. The countless folks in the Marketing and Supply Chain
Department and the International Business Center who successfully navigated me
through the labyrinth of procedures and processes required for survival at Michigan State
University. For those who remain unnamed (as well as those who are named above), I
sincerely thank you. I hope to see you all in the future to breathe life into my earnest

words of gratitude.

TABLE OF CONTENTS

LIST OF TABLES .............................................................................. vii

LIST OF FIGURES .............................................................................. ix

CHAPTER ONE

INTRODUCTION ................................................................................. 1

CHAPTER TWO

THEORETICAL UNDERPINNINGS ........................................................ 6
RESOURCE-BASED VIEW .................................................................. 6
MARKET KNOWLEDGE COMPETENCE 13
STRATEGIC CHOICE .......................................................................... 17

CHAPTER THREE

MODEL DEVELOPMENT .................................................................... 22
LITERATURE REVIEW .................................................................... 22
CONSTRUCTS ............................................................................... 36
HYPOTHESIS DEVELOPMENT .......................................................... 49

CHAPTER FOUR

METHODS ......................................................................................... 65
VARIABLE OPERATIONALIZATION .................................................. 65
INDEX OPERATIONALIZATION ........................................................ 73

CHAPTER FIVE

RESULTS .......................................................................................... 77
CROSS-FUNCTIONAL MARKETING RESOURCES
AND MARKETING EQUITY ............................................................... 77
CROSS-FUNCTIONAL MARKETING RESOURCES
AND FINANCIAL PERFORMANCE ..................................................... 94
MARKETING EQUITY AND FINANCIAL PERFORMANCE .................... 104

CHAPTER SIX

DISCUSSION .................................................................................... 117
RELEVANT FINDINGS ................................................................... l 18
LIMITATIONS ............................................................................... 128

REFERENCES .................................................................................. 131

vi

Table 1:
Table 2:

Table 3:

Table 4:

Table 5:

Table 6:

Table 7:

Table 8:

Table 9:

Table 10:

Table 11:

Table 12:

Table 13:

LIST OF TABLES

Sample’s Most Prominent Industries and Classiﬁcation Scheme...... . . ..64
Correlation Matrix of Variables in Study .................................... 76

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Components: Overall Sample ...................... 78

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Components: High Technology Sub- -
Sample ............................................................................ 79

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Components: Stable & Low Technology
Sub-Sample ...................................................................... 80

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Components: Stable Technology Mini-
Sample ............................................................................ 8 1

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Components: Stable Technology Mini-
Sample ............................................................................ 82

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Index: Overall Sample .............................. 87

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Index: High Technology Sub-Sample ............. 88

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Index: Stable & Low Technology Sub-
Sample ............................................................................. 89

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Index: Stable Technology Mini-Sample .......... 90

Relationship Between Cross-Functional Marketing Resources
and Marketing Equity Index: Low Technology Mini-Sample ............ 91

Relationship Between Cross-Functional Marketing Resources
and Financial Performance: Overall Sample ................................. 95

vii

Table 14:

Table 15:

Table 16:

Table 17:

Table 18:

Table 19:

Table 20:

Table 21:

Table 22:

Table 23:

Table 24:

Table 25:

Table 26:

Table 27:

Relationship Between Cross-Functional Marketing Resources
and Financial Performance: High Technology Sub-Sample ............... 96

Relationship Between Cross-Functional Marketing Resources
and Financial Performance: Stable & Low Technology Sub-
Sample ............................................................................ 97

Relationship Between Cross-Functional Marketing Resources
and Financial Performance: Stable Technology Mini—Sample ............ 98

Relationship Between Cross-Functional Marketing Resources

and Financial Performance: Low Technology Mini-Sample. . . . . . . ........99
Relationship Between Marketing Equity and Financial

Performance: Overall Sample 104
Relationship Between Marketing Equity and Financial

Performance: High Technology Sub-Sample .............................. 105
Relationship Between Marketing Equity and Financial

Performance: Stable & Low Technology Sub-Sample ................... 106
Relationship Between Marketing Equity and Financial

Performance: Stable Technology Mini-Sample ............................ 107
Relationship Between Marketing Equity and Financial

Performance: Low Technology Mini-Sample .............................. 108
Summary of Findings for Hypothesized Relationships ................... 109
Summary of Relationship Between Cross-Functional

Marketing Resources and Marketing Equity Components ............... 113
Summary of Relationship Between Cross-Functional

Marketing Resources and Marketing Equity Index ....................... 114
Summary of Relationship Between Cross-Functional

Marketing Resources and Financial Performance ......................... 115

Summary of Relationship Between Marketing Equity
and Financial Performance ................................................... 116

viii

LIST OF FIGURES

Figure 1: Model of Cross-Functional Marketing Resources,
Marketing Equity, and Financial Performance .............................. 37

Figure 2: Hypotheses Relating Cross-Functional Marketing
Resources, Marketing Equity, and Financial Performance. . . . . . . . . . .......50

Figure 3: Model Including Indices of Cross-Functional Marketing
Resources, Marketing Equity, and Financial Performance ................ 74

ix

CHAPTER ONE
INTRODUCTION
“Not everything that can be counted counts, and not
everything that counts can be counted. ”
— Albert Einstein (1879-1955)

Recently, scholars have begun to explore the conceptual and empirical
underpinnings of the relationship between marketing and ﬁnance (Hyman and Mathur
2005; Moorman and Rust 1999; Rust et a1. 2004). In fact, in doing so, opportunities are
being set forth for scholars to assess the ﬁnancial relevance of the marketing function in
ﬁrms. In discussions concerning the strategic readiness of a ﬁrm’s intangible assets
(Kaplan and Norton 2004) or ﬁndings concerning the importance of customer satisfaction
in increasing shareholder and market value (Anderson et a1. 2004; Fomell et al. 2006),
the ﬁnancial imperative facing marketing researchers is apparent. For example, Rao et al.
(2004) speculate that a corporate brand strategy may be best for ﬁrms aiming to
maximize their overall value.

An equally important component of the marketing process is the level of
creativity and innovation that a ﬁrm can create (Andrews and Smith 1996; Chandy and
Tellis 1998, 2000; Sorescu et al. 2003; Wuyts et al. 2004; Zhou et al. 2005). Innovation
has been analyzed in a variety of ways. These include: consequences of innovation and
proﬁtability in interﬁrm agreements (Wuyts et al. 2004); innovation, organizational
learning, and market orientation (Hurley and Hult 1998); strategic business unit (SBU)
level innovation (Zhou et al. 2005); and the ﬁnancial valuation of different types of

innovations themselves (Sorescu et al. 2003). In work paralleling the innovation stream

of research but focusing on more traditional marketing functions, the relevance of
creativity in marketing programs (Andrews and Smith 1996) as well as its relation to both
new product development and ﬁnancial success have also been pursued (Im and
Workman 2004).

Some previous attempts have been made to introduce ﬁnancially-based concepts
to industries with different marketing characteristics in the literature (e. g., Mizik and
Jacobson 2003). However, the marketing function has been constricted by the notion that
ﬁnancial and accounting measures are incapable of capturing basic marketing principles.
For instance, the innovation and related concepts described above refer to tangible and
intangible assets that are “lumped [together] by accountants under the heading of
goodwill and include things such as patents, trademarks, and licensing agreements, as
well as “softer” considerations such as the skill of the management and customer
relations” (Keller 2003, p. 493).

At the same time, extensive research projects have taken place in the ﬁnance and
accounting literatures to attempt to relate a ﬁrm’s assets and expenses as proxies for both
tangible and intangible assets to performance. An alternative hegemony of measurement
to real options valuation, the valuation of a ﬁrm’s intangibles by the level of opportunity
related to the investment can give a more exact analysis of “the vast array of
discretionary expenditures available to support growth options” (Gaver and Gaver 1993,
p. 132). While ﬁnancial measures have been used in a limited way in the marketing
literature (Mizik and Jacobson 2003; Rao et al. 2004; Wuyts et al. 2004), a
comprehensive assessment of ﬁnancial measures driven by marketing concepts has yet to

be accomplished. Consequently, this study’s overarching goal is to ﬁll the gap in the

literature involving interrelationships among intangible and tangible technological and
marketing resources, intermediate marketing outcomes, and ﬁnancial performance
consequences.

The focus of this study is supported by a number of recent studies. For example, a
recent meta-analysis by Daniel et al. (2004) concluded that intervening variables between
slack (e.g., inventory) and ﬁnancial performance has yet to be studied effectively. The
topic of resource slack has begun to be discussed in the marketing literature. Based on
discussions in the management literature (Bourgeois 1981), its relevance has been
highlighted in analysis of intangible resources (Slotegraaf et al. 2003). In fact, resource
slack of the ﬁrm has been found to be better able to develop its knowledge of customers
(J oshi and Sharma 2004). However, in attempting to relate resource slack to ﬁnancial
performance, a negative association has resulted (Lee and Grewal 2004). This indicates
that the relationship between slack and ﬁnancial measures may be inﬂuenced by other
factors not yet studied in an integrative framework. As such, the ﬁrst major contribution
of this study is to assess comprehensively these mediating marketing variables.

In addition, the present study attempts to resolve an apparent conﬂict that has
emerged in the literature by taking a more wholistic approach to resource allocation in the
ﬁrm. Speciﬁcally, in a comparison between intangible marketing (e. g., brands,
trademarks, etc.) and intangible technological (e.g., intellectual property, patents, etc.)
resources, recent ﬁndings indicate that intangible marketing resources are more important
in nearly all sizes of ﬁrms except those with massive amounts of ﬁnancial resources
(Slotegraaf et al. 2003). This ﬁnding would imply that only the very largest ﬁrms would

ﬁnd greater value in intangible technological resources. However, in a recent cross-

industry survey of practitioners from large and small ﬁrms in the health, technology, and
industrial sectors, intangible technological resources were consistently considered of
higher importance than intangible marketing resources (Razgaitis 2005).

These contradictory ﬁndings point out a disparity in the literature as to the
importance of intangible marketing and technological resources. An explanation for such
results may be the cross-functional nature of intangible resources. Posited as important in
the emerging discussion concerning the strategic assessment of business practices (Vargo
and Lusch 2004), cross-functional coordination has been found to increase
responsiveness (Hult et al. 2005) as well as new product and marketing program
creativity (Im and Workman 2004). In fact, recent literature has indicated the importance
of cross-functionality in the development of customer knowledge for new product
development teams (J oshi and Sharma 2004), cooperative and competitive interactions
between marketing and other functions (Luo et al. 2006), competence exploration and
exploitation for radical innovation performance (Atuahene-Gima 2005), and reductions in
preannounced product introductions (Wu et al. 2004).

Thus, rather than categorizing a ﬁrm’s resources as only technology- or
marketing-based, this study presumes that the resources included in the model to be
tested have elements based in both technology and marketing. However, some ﬁrm
resources in the present study’s model are more closely associated with technology (e. g.,
R&D intensity, Star scientist index, etc.) while other resources are more closely
associated with marketing (e.g., Intangible assets, Sales, general, and administrative

expenditures, etc.). As such, a second major contribution of this study is to develop a

typology of both intangible technological and intangible marketing resources to assess

their combined inﬂuence on marketing outcomes and ﬁnancial performance.

CHAPTER TWO
THEORETICAL UNDERPINNINGS
“The moment a person forms a theory, hisl/her]
imagination sees in every object only the tracts which
favor that theory. ”
— Thomas Jefferson (1 743-1826)

There are three streams of research on which this project will be based: the
resource-based view (e. g., Barney 1991; Wemerfelt 1984), market knowledge
competence (e.g., Li and Calantone 1998), and strategic choice (e. g., Child 1972; Child et
al. 2003). The amalgam of these three theories provide for both an overlapping and
synergistic foundation to explain the phenomena studied as well as the linkages in the

developed model that represent the research hypotheses. Each of the three theories is

introduced next to set the foundation for the subsequent hypothesis development.

RESOURCE-BASED VIEW

Throughout this study, the notion of resources will follow the tradition set forth
by Barney (1991) and Peteraf (1993). Within this line of reasoning, resources must create
or generate differential rents such that the ﬁrm may have a competitive advantage in the
marketplace. As such, the study of ﬁrm utilization of resources, using the resource-based
view (RBV — Barney 1991; Wemerfelt 1984), in the marketing literature can be
categorized into four groups: 1) resources and responsiveness; 2) resource control; 3)
resource input and performance; and 4) resources and competitors. Though covering a
variety of topics within the ﬁeld of marketing, these topics have a common focus in that

they address the importance of ﬁrm resources and capabilities in gaining an advantage in

the marketplace (e. g., Hunt 2000). In particular, the latter two topics — resource input and
performance and resources and competitors — apply effectively to the focus of this study,
i.e., the intellectual property process generating a competitive advantage for the ﬁrm. For
completeness, all four groups are discussed below to distinguish their relative

importance.

Resources and Responsiveness

Few researchers have devoted efforts to discussing the speciﬁc relationship
between ﬁrm resources and overall responsiveness (J ap 1999; Srinivasan et al. 2002).
Deﬁned as the proactive response by the ﬁrm to new opportunities not violating
principles of fairness, Srinivasan et al. (2002) found that top management’s advocacy of
new technologies heighten awareness within the ﬁrm to new technological opportunities
to be used by the ﬁrm. This, in turn, leads to a response by the ﬁrm to react to and utilize
technological developments occurring in the marketplace, thus enhancing the ﬁrm’s
resource base for future usage. Another topic receiving scant attention has been J ap’s
(1999) focus on collaborative exchange in a buyer-supplier dyadic relationship. Resulting
from a combination of environmental factors, goal congruence, complementary
capabilities, and trustworthiness, J ap (1999) set forth that the coordination efforts and
idiosyncratic investments made by each ﬁrm in such a relationship become part of its
resources and capabilities. In addition, these relation-speciﬁc resources were found to
inﬂuence proﬁt performance and competitive advantages unattainable without the

relationship (Jap 1999).

Resource Control

In contrast, the topic of resource control has found more interest in the ﬁeld of
marketing. It consists of two subsets: l) acquisition and integration; and 2) market
deployment (Capron and Hulland 1999; Homburg and Bucerius 2005; Slotegraaf et al.
2003; Varadarajan et al. 2001). Pursued originally in Capron and Hulland’s (1999)
analysis of resource redeployment after horizontal acquisitions, three marketing resources
were posited as being subject to redistribution between the targeted and acquiring ﬁrms:
brands, sales forces, and general marketing expertise (GME). Extending this issue,
Homburg and Bucerius (2005) found that, after a merger or an acquisition, the extent and
speed of integration between ﬁrms is important in determining the successor ﬁrm’s
performance.

While considered a subset of the resource control category of the RBV, the issue
of market deployment, as discussed by Slotegraaf et al. (2003), is more applicable to the
present study than studies addressing acquisition and integration of marketing activities
between ﬁrms. Slootegraf et al.’s study pursued the market deployment effectiveness of
intangible marketing (e. g., brand equity) and intangible technological (e.g., patent stock)
resources in a consumer products setting (Slotegraaf et al. 2003). After testing for results
in both distribution and coupon deployment, ﬁndings indicated that an increased
accumulation of overall ﬁnancial resources to each condition brought higher returns to

the deployment initiative (Slotegraaf et al. 2003).

Resource Input and Performance

Addressing speciﬁcally the internal attributes of the ﬁrm, the theme of resource
input and performance was originally conceptualized in the marketing literature by Day
(1994). Forwarding that resources (be they brand equity, location, or other assets) lead to
positions of advantage, Day (1994) stated that this relationship may be partially mediated
by the capabilities and core competencies of the ﬁrm, but also the distinctive capabilities
that result from such an internal integration and application of knowledge. Referred to as
the ﬁrm’s innovation effort (Marinova 2004), the resulting capabilities, competencies,
and positions of advantage lead to enhanced performance (Day 1994; Hult and Ketchen
2001).

A similar approach is taken in studies adopting an emphasis on input-output
process and results models (Dutta et al. 1999; Thieme et al. 2000). Though Thieme et al.
(2000) posited that a “hidden layer” of internal capabilities mediated the relationship
between the “input layer” and “output layer” of the new product development (NPD)
process, the essence of raw resources undergoing conversion within the ﬁrm to
capabilities which, in turn, result in performance, remains relevant to this study. A similar
statement was made concerning a model by Dutta et al. (1999) addressing ﬁrm
capabilities and performance. With marketing, R&D, and operations acting as
antecedents to demand- and supply-side effects in the marketplace, a resulting increased
performance (a transformed function of ﬁrm sales) was found. More exactly, marketing-
speciﬁc resources (e. g., marketing expenditures) led to marketing capabilities in the study
while R&D capabilities resulted from R&D-speciﬁc resources (e.g., R&D expenditures)

(Dutta et al. 1999).

Resources and Competitors

Resources and competitors as a scholarly contribution begins with Day and
Wensley’s (1988) conceptual approach to the elements of competitive advantage. They
differentiate between competitor-focused and customer-focused positions of superiority.
Stating that a ﬁrm’s sources of advantage typically come from superior resources and
skills, their conceptual view holds that positional advantages (e. g., superior customer
value, lower relative costs, etc.) result in and subsequently inﬂuence a ﬁrm’s
performance outcomes (e.g., satisfaction, loyalty, market share, proﬁtability, etc.) (Day
and Fahey 1988; Day and Montgomery 1999; Hult and Ketchen 2001).

Day and Wensley’s (1988) conceptualization is mirrored in other conceptual
works. In their framework addressing the services sector, Bharadwaj et al. (1993) posited
that the accumulation of resources and skills creates imitation barriers, thus transforming
a temporary positional advantage into a much more sustainable positional advantage.
However, the importance of these resources and skills is not merely in their
accumulation, but in the gaining of efﬁciencies within the ﬁrm due to the
interconnectedness of its stock of resources and skills (Bharadwaj et al. 1993).

Recent qualitative extensions in relation to the RBV have also been pursued in the
marketing literature (Johnson et al. 2003; Srivastava et al. 1999). In their discussion
concerning marketing, business processes, and shareholder value, Srivastava et al. (1999)
introduced two novel concepts applicable to product development and ﬁrm resources.
First, to enhance cash ﬂows, the conditions of striving for value and product

differentiation, obtaining customer inputs, sharing modular designs across products, and

10

acquiring or licensing technology were forwarded as important business processes to
pursue (Srivastava et al. 1999). Second, Srivastava et al. (1999) stated that, to reduce risk
— and, subsequently, decrease vulnerability to volatile cash ﬂows — ﬁrms must increase
their rates of innovation, design products difﬁcult to imitate with a unique product and/or
service bundling, and maximize synergies across product portfolios. By creating
conditions under which competitors ﬁnd reproduction of a ﬁrm’s seemingly innovative
product and/or service line complex, a sustainable competitive advantage is more likely
(usually as a function of ﬁrm-speciﬁc idiosyncrasies).

Paralleling earlier work by Day and Wensley (1988) that posited that capabilities
may result from endowments focusing on customers and/or competitors, Johnson et al.
(2003) introduce the notion of strategic ﬂexibility. With application of the market
orientation literature to justify strategic ﬂexibility as a capability (Kohli and Jaworski
1990; N arver and Slater 1990), Johnson et al. (2003) argue that the mediating role of such
a construct inﬂuences short- and long-term performance outcomes. Basing their argument
on a ﬁrm’s intent rather than outright actions per se, this initial momentum leads the ﬁrm
to identify, acquire, and/or develop a resource portfolio that gives it strategic options for
future positioning (Johnson et al. 2003; Olson, Slater, and Hult 2005).

The focus on resources and competitors has been addressed empirically in a
number of studies. For example, the inﬂuence of resources and capabilities on
performance has been studied in exporting and marketing strategy contexts (Menon et a1.
1999; Morgan et al. 2004; Slotegraaf and Inman 2004; Vorhies and Morgan 2005; Zou
and Cavusgil 2002). Morgan et al. (2004) found that resources available for an export

venture inﬂuenced the capabilities of such a venture, but also impacted the venture’s

11

competitive strategy. This, in turn, led to positional advantages in the export market and —
eventually — the performance of the export venture (Morgan et a1. 2004). Also, Zou and
Cavusgil (2002) found support for the premise that intangible resources and skills
associated with the ﬁrm’s international experience (as a representation of intrinsic
expertise) and global orientation (as a manifestation of organizational culture) drive
global marketing strategy, strategic marketing performance, and ﬁnancial performance.
In addition, Menon et al. (1999) empirically established that an organizational culture
emphasizing either centralization or innovation impacts marketing-strategy-making
components closely linked to the RBV (e. g., strategic resource commitment). Considered
an actionable endowment of the ﬁrm, strategic resource commitment was also found to
inﬂuence organizational learning and market performance (Menon et al. 1999).

More recent studies have sought to extend the basic tenets of the RBV with
comparisons of ideal competitive strategies and the effectiveness of marketing planning
capabilities (Slotegraaf and Inman 2004; Vorhies and Morgan 2005). By identifying
speciﬁc marketing capabilities to benchmark top performers in their cross- and within-
industry study, Vorhies and Morgan (2005) found that deviations from an ideal mix of
marketing capabilities diminished ﬁrm performance on a number of performance
measures (e. g., customer satisfaction, market effectiveness, proﬁtability, return on
assets). Analogous to the ability of the ﬁrm to sense and subsequently respond to
technological opportunities in the marketplace after encouragement by top management
(Srinivasan et al. 2002), it can be inferred from Vorhies and Morgan’s (2005) study that a

ﬁrm’s multi-component construct of marketing capability interdependence inﬂuences

l2

ﬁrm performance. In other words, ﬁrms that are able to sense and respond more readily
to market conditions generally outperform those lacking such skills.

Slotegraaf and Dickson (2004) extended the study of marketing plan capabilities
as an internal resource. Their study suggests more directly than previous works that the
inﬂuence of marketing planning capabilities (deﬁned generally as the ﬁrm’s ability to
match resources to demands in the market) on ﬁrm performance (in both a proﬁt and
brand equity context) is curvilinear (i.e., an inverted U-shape). While support for this
notion was found in the brand equity model, the diminishing returns of marketing plan
capabilities posited for the proﬁt model was not supported (Slotegraaf and Inman 2004).
Taken the application of a transformed function of ﬁrm sales by Dutta et al. (1999) as an
indication of increased performance, this provides an indication that future applications
of marketing-based endowments and capabilities utilizing an RBV perspective may not

ﬁnd similar results when comparing brand- and proﬁt-oriented measures.

MARKETING KNOWLEDGE COMPETENCE

Based on results from the US. software industry, a basic tenet of market
knowledge competence (MKC) is that the interface between marketing and research and
development (R&D) inﬂuences new product advantage which, in turn, inﬂuences market
performance (Li and Calantone 1998). Similar ﬁndings have been found among Japanese
ﬁrms where cross—functional integration and product competitive advantage inﬂuencing
new product success was the focus (Song and Parry 1997). Cross-functional integration
was also found to increase new product and marketing program creativity, both of which

subsequently inﬂuenced performance outcomes (i.e., market-, ﬁnancial-, and qualitative-

13

based outcomes) (Im and Workman 2004). In addition, cross-functional integration has
been found in a multinational computer manufacturer to foster stronger relational norms,
perceived effectiveness, and new product success (Ayers et al. 1997). Interestingly,
research ﬁndings have also suggested that cross-functional teams are more important in
new product development projects that involve potential innovations that are less familiar
to the ﬁrm (Grifﬁn 1997).

On a somewhat related note, with multiple antecedents (formalized and clannish
administration, mutual dependence, and institutional support) the construct of cooperative
competency has also been found as important in new product success (Sivadas and
Dwyer 2000). This ﬁnding runs contrary to the ﬁndings that social cohesion is negatively
related with innovativeness at the product development level (Sethi et a1. 2001). In fact,
the discussion of inter-functional communication and cooperation involving the
marketing function has been in the literature for quite some time, with a relatively large
literature base having been formed. An early discussion of the interface between
marketing and R&D proposed ﬁve approaches that could facilitate the process (Berenson
1968): increasing inputs to R&D; developing better R&D consumption systems;
changing organizational forms; improving communication between marketing and
technical groups; and optimizing the mix between basic and applied research.

At the product development level, the strength of team identity, the
encouragement to take risks, and active monitoring by senior management all appear to
inﬂuence innovativeness (Sethi et al. 2001). Extending this further, the degree of
integration between R&D and marketing have been suggested to require both individual

and organizational factors (Gupta and Raj 1986). The primary individual factor

14

inﬂuencing the possible integration between these two functions according to Gupta and
Raj (1986) is the sociocultural differences between a ﬁrm’s managers in R&D and
marketing. The organizational factors that appear important are overall ﬁrm structural
characteristics, senior management, and operating characteristics between R&D and
marketing (Gupta and Raj 1986).

However, the differences in perspective between different functional groups may
be behind the importance — yet difﬁculty — in appropriately integrating marketing and
R&D at the project or ﬁrm level to enhance performance. In a comparison of marketing,
organizational, engineering, and operations perspectives, typical performance measures
differ between marketing (ﬁt with market, market share, consumer utility, proﬁts) and
engineering (form and function, technical performance, innovativeness, and direct cost)
(Krishnan and Ulrich 2001). Krishnan and Ulrich (2001) also indicate that the critical
success factors of marketing (product positioning and pricing, collecting and meeting
customer needs) and engineering (creative concept and conﬁguration, performance
optimization) can have a profound inﬂuence in how these two functional groups
communicate.

The marketing function also tends to perceive that the R&D function does not
require inﬂuence in the organization to enhance performance in the new product
development process (Atuahene-Gima and Evangelista 2000). However, Atuahene-Gima
and Evangelista (2000) also indicate that the R&D function perceives that marketing
must have organizational inﬂuence to contribute to new product success. This places
marketing at the forefront in importance in a ﬁrm’s achievement of potential product

success. Meanwhile, in a study of SBUs among high-technology industrial equipment

15

manufacturers, the number of mechanisms used to reduce inter-functional conﬂict
between marketing, manufacturing, R&D, and ﬁnance did not improve relations (Maltz
and Kohli 2000). However, Maltz and Kohli (2000) also found that the use of cross-
functional teams for decision making purposes appeared to reduce manifest conﬂict.

A similar approach used to accomplish communication and conﬂict reduction is
Quality Function Deployment (QFD) (Grifﬁn 1993; Grifﬁn and Hauser 1992). In fact,
with its expressed intent on customer satisfaction, ﬁndings suggest that QFD increases
communication levels between the functions of marketing, engineering, and
manufacturing (Grifﬁn and Hauser 1992). As a result, Grifﬁn and Hauser (1992) ﬁnd that
these functions (also called the core team) communicate less with those external to the
core team. Depending on the information available to the core team, this can be good (if
it has adequate information) or bad (if it does not) (Grifﬁn and Hauser 1992). As such,
customers are clearly more likely to be satisﬁed if the products are designed based on the
traits deemed important to customers (Grifﬁn 1993).

In addition, there is a strong sub-component of innovation and product
development research that is devoted to the concept of slack. In a study focusing on the
notion of slack and innovation, an inverse-U shaped relationship was found among 264
functional departments in two multinational corporations (Nohria and Gulati 1996). At
the same time, resource constraints (not resource slack) were found to enhance
performance among privately-held ﬁrms (George 2005). In a series of studies in China,
the inﬂuence of slack on general ﬁrm performance was also found to have an inverse-U
relationship (Tan and Peng 2003). In fact, Tan and Peng (2003) also conclude that — at

least in the transitional economy setting of China — unabsorbed slack positively

16

inﬂuenced ﬁnancial performance while absorbed slack negatively inﬂuenced ﬁnancial
performance (Tan and Peng 2003).

For more generalizable results, however, a meta-analysis found a positive
relationship between all three types of slack (available, recoverable, and potential) and
ﬁnancial performance (Daniel et al. 2004). In fact, while lagged slack measures did not
show any improvement in the relationship between slack and performance, controls used
for industry-relative performance demonstrated stronger positive inﬂuence of potential
slack on performance (Daniel et al. 2004). This ﬁnding can be used to support the notion
put forward in the RBV literature that studies comparing relative (rather than absolute)
performance of ﬁrms is a better test of the RBV (Ray et al. 2004; for an interesting
discussion on the use and testing of the RBV, see Lado et al. 2006).

In summary, the discussion concerning measurement of research, development,
and engineering (R,D&E) indicates that a more comprehensive approach should be
employed. Based on interviews with top executives, more direct measures of research
effort (e. g., citations, patents, citations to patents, etc.) should be used (Hauser 1998). In
addition, rather than using an approach characterized as “best people,” better
performance may result from “research tourism” which emphasizes knowledge and

research spillovers from universities, other industries, and competitors (Hauser 1998).

STRATEGIC CHOICE
Beginning with the conceptual framework established by Child (1972), the
research stream focusing on strategic choice is equally applicable as a theoretical

underpinning for this study. As such, there appear to be four main tenets of this

17

theoretical approach: 1) competitive strategies reﬂect the choices of managers; 2) also
akin to the RBV, emphasis on the link between managerial competence and strategy; 3)
the effectiveness of strategic decision making on organizational performance; and 4) the
importance of the dominant coalition in developing organizational strategy as manifest
through resource allocations (Child 1972; Child et al. 2003).

As with the implementation of any strategy at any level, the testing of different
components of top managers’ power led to a methodology that included four facets:
structural power, ownership power, expert power, and prestige power (Finkelstein 1992).
As such, in a sample of Fortune 500 ﬁrms, companies were more likely to conduct
corporate strategic change if top managers were of lower average age, higher team
tenure, higher education level, higher education specialization heterogeneity, and higher
academic training in the sciences (Wiersema and Bantel 1992).

In addition to the competitive strategies of architectural woodworking ﬁrms, the
competencies and motivations of CEOs in this industry were directly associated with
venture growth (Baum et al. 2001). Thus, manufacturing ﬂexibility may have been a.
driving force in such decisions (Gerwin 1993).

The dynamics of decision making have also been discussed in this literature
stream. In a conceptual framework focusing on institution transitions in emerging
economies characterized as shifting from relationship-based to rule-based strategies, such
an emphasis (on rule-based strategies) should be particularly strong at the regulative,
normative, and cognitive levels in late phases of economic transitions (Peng 2003).

Such changes - as well as others - can result in relative levels of conﬂict,

dysfunction, and turmoil in an organization. Among food-processing and furniture

18

manufacturing ﬁrms, cognitive conﬂict was foundto improve decision quality while
affective conﬂict degraded decision quality (Amason 1996). As such, greater past success
tended to inﬂuence a greater strategic persistence after radical environmental change,
thus inducing performance declines in the airline and trucking industry (Audia et al.
2000). In a series of related experimental studies, such dysfunctional persistence was
found to be a result of greater satisfaction with past performance, more conﬁdence in
correctness of current strategies, higher goals and self-efﬁcacy, and less information-
seeking from critics (Audia et al. 2000).

An extension of the original approach set forth by Child (1972), the strategic
archetypes forwarded by Miles and Snow (1978) have been acknowledged as directly
applicable to this stream of research (Matsuno and Mentzer 2000; Mizik and Jacobson
2003; Olson et al. 2005). Introduced and tested quite early as a typology relevant to the
ﬁeld of marketing (McDaniel and Kolari 1987), four characterized business strategies are
identiﬁed by prominent researchers with this emerging approach to strategic marketing:
prospectors, analyzers, low-cost defenders, and differentiated defenders (Matsuno and
Mentzer 2000; Miles and Snow 1978; Noble et al. 2002; Olson et al. 2005; Webster
1992; Vorhies and Morgan 2003). In essence, prospectors aim to locate and leverage new
opportunities in the marketplace, defenders attempt to cordon a part of the market to
establish a stable clientele, analyzers seek to cautiously follow prospectors into new
markets while protecting their current base clientele, and reactors have little consistency
in their strategic approach.

As the Miles and Snow (1978) typology has been discussed in a variety of

settings, some previous research relates their business strategies to the following topics:

19

- the general nature of competition (Carpenter et al. 1994);
- the degree of marketing strategy aggressiveness (Day and Nedungadi 1994);
- the dangers of overspecialization (Kalwani and Narayandas 1994);
- the considerations of ﬁt between environmental opportunities and
organizational skills and resources (Kerin et al. 1992);

- the development of an “organic” organizational structure (Slater and Narver
1995); and

- the choices of management styles in instances of goal incongruity (Song et a].
2000).

The implicit underpinning of this facet of discussion concerning strategic choice
focusing on managerial ability to ﬁt strategically the ﬁrm’s resources and abilities to
marketplace conditions. In fact, such theoretical development has led researchers to posit
that the marketing function in the ﬁrm tends to become more active in other functional
areas (and vice versa) in ﬁrms with higher information intensity (Glazer 1991). Also,
previous conceptual work has proposed that higher levels of market turbulence tend to
increase the value of decisions perceived as time-sensitive (Glazer and Weiss 1993).

However, ﬁndings in this research stream have increased its overall acceptance,
as well. As such, previous research has found that heterogeneous channel environments
tend to be associated with less formal procedures, decentralized decision structures, high
channel participation, and more retailer control over marketing decisions (Dwyer and
Welsh 1985). Stated additionally, environmental uncertainty has been found to result in
increased integration, performance control, and specialization in the ﬁrm (Germain and

Droge 1994).

20

Implicit thus far is the role of strategic choice in overall ﬁrm ﬂexibility, the
championing of organizational goals, and distinctive marketing competence. As such, in
cases of strategic ﬂexibility, ﬁndings indicate that the marketing function’s inﬂuence is
particularly related to differentiation strategies (Grewal and Tansuhaj 2001). In addition,
the championing of product leadership as an organizational goal has been positively
associated with customer knowledge development (J oshi and Sharma 2004). Thus, the
marketing competence of a ﬁrm can have positive inﬂuence on many marketing functions
a ﬁrm may face -— including line extensions (Matsuno and Mentzer 2000) as well as
leveraging local resources to develop trust between a MNC parent and its afﬁliates (Child

et al. 2003).

21

CHAPTER THREE
MODEL DEVELOPMENT
“Measure what is measurable and make measurable
what is not so. ”
— Galileo Galilei (1564-1642)
This section discusses the relevance of each construct and the theoretical
underpinnings related to each construct used in the study. After the introduction of the
constructs, a series of integrated hypotheses will be developed based on the amalgam of

theories introduced in the previous section (i.e., the resource-based view, market

knowledge competence, and strategic choice).

LITERATURE REVIEW

Lee and Grewal’s (2004) deﬁnition of Tobin’s Q is comprised of a variety of
rapid channel response variables in an assessment of strategic responses to new
technologies. However, more directly related to this study, there have been two general
approaches of Tobin’s Q to date in the marketing literature. The ﬁrst advance generally
indicates that this measure of ﬁrm value is the ratio of the market value of the ﬁrm to the
replacement cost of its tangible assets (e. g., property, equipment, inventory, cash,
investments in stock and bonds, etc.) (Anderson et al. 2004; Rust et al. 2004).

Resulting from its use as a measure of a ﬁrm’s investment opportunities, one of
the drawbacks with Tobin’s Q identiﬁed in the literature is that is has been posited to
have measurement error (Lu and Beamish 2004; Whited 2001). In fact, intangible
resources have been discussed by Simon and Sullivan (1993) as comprised of brand

equity, non-brand factors that reduce a ﬁrm’s costs vis-a-vis competitors (e. g., R&D,

22

intellectual property, etc.), and industry-wide factors that allow value through non-
marketplace forces (e. g., governmental regulation). However, recent ﬁndings indicate
that this level of error is most likely an artifact of the correlation between investment
opportunities and liquidity (Whited 2001). Thus, given that this study’s ﬁrms - vis-a-vis
small start-ups (Stickel 1985) — most likely do not suffer from excessive liquidity,
difﬁculties with Tobin’s Q are not expected.

Regardless, upon direct comparison with return on assets (ROA), some ﬁndings
including Tobin’s Q have been found to be relatively unstable. For instance, an analysis
of persistent economic performance and sustainable competitive advantage in 40
industries indicated that ﬁrm size had a positive impact on ROA, but a negative impact
on Tobin’s Q (Wiggins and Rueﬂi 2002). Most likely not caused by inﬂationary
inﬂuences (Lu and Beamish 2004), results from the same study were not as generalizable
across industries in the model with Tobin’s Q as a dependent variable (Wiggins and
Rueﬂi 2002).

Given that Tobin’s Q is inherently a forward-looking measure (Anderson et al.
2004; Rao et al. 2004; Szymanski et al. 1993), thus leading to its unpredictability, there is
an alternative accounting-based measure that may account for a ﬁrm’s value: intangible
resources. However, this topic has been widely conceptualized and operationalized. Thus,
prior to its usage in this model, a review and justiﬁcation is needed.

Following a long tradition of literature concerning resources, there are typically
three distinct sources of competitive advantage: physical, intangible, and ﬁnancial
resources (Chatterjee and Wemerfelt 1991). In fact, intangible resources have become a

pivotal factor in the development and explanation of the resource-based view (RBV)

23

(e.g., Barney 1991). However, as acknowledged by the subjectivity of the concept, any
attempt to explain the relevance of intangible resources entails signiﬁcant measurement
difﬁculties (Fiegenbaum et al. 1997; Fomell et al. 2006; Hult and Ketchen 2001; Roberts
and Dowling 2002).

Though researchers have attempted to categorize intangible resources in the past
(Avery 1942), perhaps the most comprehensive discussion of intangibles, as applicable to
this study was in a presentation of nine distinct categories (Hall 1993). In this
conceptualization, the nine categories include: 1) intellectual property (e. g., patents,
trademarks, and copyrights and registered designs); 2) trade secrets; 3) contracts and
licenses; 4) databases; 5) information accessible publicly; 6) personal and organizational
networks; 7) the know-how of employees, professional advisers, suppliers, and
distributors; 8) a product and/or company’s reputation; and 9) organizational culture (e. g.,
ability to react to challenge and cope with change). As such, Hall (1993) states that only
the ﬁrst four categories can be protected through legal action. Based on these nine
categories, a series of case studies in a cross-section of industries (e.g., apparel,
automotive, retail, and transportation) revealed that the three most important intangibles
that lead to competitive advantage were the reputation of the company and product,
employee know-how, and the culture and networks of an organization.

More speciﬁc to strategic marketing, an equally wide conceptualization states that
a ﬁrm’s intangible resources include product development management (PDM), supply
chain management (SCM), and customer relationship management (CRM) (Srivastava et
al. 1999). According to this general classiﬁcation, various aspects of these three tenets of

intangible resources (product, channel, and customer) have been discussed in the

24

literature. As noted below, there are common themes found, but there is also signiﬁcant

variation in the multi-faceted concepts discussed to warrant listing:

intellectual, relational, and human assets (Rousseau and Shperling 2003);

- brand, employee, and customer equity (Gupta et al. 2004);

- ﬁnancial reserves, equipment, employee skills, channel equity, brand equity,
and marketing expertise (Geyskens et al. 2002);

- research and development (R&D) capabilities, information technology, and
brands (Aaker and Jacobson 2001);

- corporate culture, customer relationships, and brand equity (Srivastava et al.
1998); and

- equipment and buildings, reputation, and customer loyalty (Pearson and Clair
1998).

As such, there are two general types of intangible resources discussed in the
literature. The ﬁrst category beneﬁts from a very fruitful literature base and focuses on
internal aspects of the ﬁrm. The second category addresses elements focused externally
from the ﬁrm. Though not nearly as proliﬁc as the former category, externally focused
intangible resources are nonetheless important in any discussion concerning intangible
resources due to their usefulness in the marketplace to gain competitive positioning for

possible sustainable growth and performance.
Intangible Resources - Internal Aspects

The most common empirical applications of intangible resources in the literature

are based on advertising, marketing, and R&D expenditures (e.g., Aaker and Jacobson

25

2001; Fiegenbaum et al. 1997; Geyskens et al. 2002; Seth et al. 2002). In fact, focusing
on the use of R&D and advertising intensity, some researchers have suggested that the
firm’s ability to internally develop or secure sufﬁcient resources (as in internalization
theory — Denenkamp 1995) is implicit in the use of these concepts (Denekamp 1995;
Dunning 1995; Markides and Ittner 1994), thus making the internal focus of intangible
resources much more focused on process-orientation than external focuses.

Independent of the way that intangible resources are valued in a company’s
ﬁnancial statements, the most general conceptualization of intangible resources at the
level of the individual is the notion of human assets (Hall 1993; Rousseau and Shperling
2003). From this, a wide variety of individual-level intangible resources in the ﬁrm have
been discussed to at least some degree including: employee skills (Geyskens et al. 2002),
employee processes (Gilly and Wolﬁnbarger 1998), employee equity (Gupta et al. 2004),
implementation skills (Gruca and Suddharshan 1995), management style (Oviatt and
McDougall 1994), management procedures and processes (Brown et al. 2000; Gilly and
Wolﬁnbarger 1998), and strategic decision making skills (Szymanski et al. 1993). In
addition, the creative use of managerial and management skills have even been forwarded
as elements of a ﬁrm’s general intangible resources (Fiegenbaum et a1. 1997; Houston
and Johnson 2000).

Meanwhile, at the ﬁrm-level, the general notion of corporate or organizational
culture and values are sometimes considered a key intangible resource (Mosakowski
1998; Srivastava et al. 1998). As a part of this, a company’s ability to develop a culture of
entrepreneurship (e. g., the ability to innovate and imitate) to remain competitive is

important in forwarding this notion (Im and Workman 2004; Zhou et al. 2005).

26

Sometimes conceptualized as a proxy for innovation (Ireland et al. 2005), others have
forwarded the related concept of “intrapreneurship” (Agarwal et al. 2004; Irn and
Workman 2004). Pivotal in explaining the ability of a ﬁrm to harness the knowledge and
understanding of lower-level actors in an organization (Achrol 1991; Hart 1992;
Levinthal and Warglien 1999; Stopford and Baden-Fuller 1994), the general concept is
that individual performance inﬂuences overall organizational effectiveness (Frese et al.
1996).

However, these ﬁrm-level intangible resources are sometimes difﬁcult to
measure. As such, more quantiﬁable notions of this general concept have also been
murmured in the literature. For instance, equipment and buildings (Geyskens et al. 2002;
Pearson and Clair 1998), organizational structure (Gruca and Suddharshan 1995),
information technology and systems (Aaker and Jacobson 2001; Brown et al. 2000), ﬁrm
processes (Brown et al. 2000; Gilly and Wolﬁnbarger 1998; Contractor and Kundu
1998), superior production knowledge and skills (Fiegenbaum et al. 1997; Kotabe and
Swan 1994), training (Contractor and Kundu 1998), and scale and scope economies
(Fiegenbaum et a1. 1997; Jacobson 1988) have all been forwarded as associated to some
degree with intangible resources. Underlying these notions is the ability of the ﬁrm to
distinctly use these resources to its own advantage in a maximizing way. This is most
clearly evident in how a ﬁrm manages its product development process, supply chain,
and customer relationships (Srivastava et al. 1999).

To remedy this difﬁculty in measurement, some researchers have applied Tobin’s
Q as an appropriate proxy for intangible resources (Balasubramanian et al. 2005; David et

al. 2001; Slotegraaf et al. 2003). For example, Tobin’s Q has been used as a moderator in

27

the relationship between institutional investor activism and R&D (David et al. 2001 ). In
their study on ﬁrm resources and market deployment, Slotegraaf et al. (2003) use Tobin’s
Q to measure a frrrn’s intangible value, thus providing the basis for the indices of brand
equity and patent citation. Also, in a comparison of ﬁrms awarded high-quality
achievement honors, Tobin’s Q was found to be a statistically signiﬁcant determinant of
whether a ﬁrm received the JD Power and Associates Award -— a prestigious honor based
on administered consumer surveys and conferred to ﬁrms ranking high on measures of
product quality and customer satisfaction (Balasubramanian et al. 2005).

While some researchers may use advertising or marketing expenditures (or
intensity) as a proxy for brand equity, a more exact conceptualization is that these
variables are similar to the branding effort of a ﬁrm. With discussions and uses in the
literature concerning marketing expertise and abilities as well as the use of the sales force
to forward brands (Capron and Hulland 1999; Fiegenbaum et al. 1997; Geyskens et al.
2002), advertising and marketing expenditures capture these concepts as intangible
resources nicely.

In fact, while awareness is an important component of a customer-focused
concept of brand equity (Aaker 1996; Keller 2003), other aspects of the marketing
process - such as research, development, and production — are also pivotal in bringing a
product or service to the marketplace. When using a ﬁrm’s ﬁnancial statements,
advertising and/or marketing expenditures frequently accomplish the ﬁnal task of
awareness generation - or, in other words, informing the market of an innovation or new
product. This is a very important contribution to the success of the ﬁrm, but it

nonetheless should not be used as a proxy for brand equity. Thus, the use of advertising

28

and marketing expenditures/intensity as possible proxies for brand equity will not be
performed here.

The use of R&D expenditures/intensity in the literature is also well-documented,
but as a measure of innovation in the ﬁrm. In fact, the notion of R&D as an intangible
resource has been forwarded by many researchers. Ranging from R&D capabilities to
intellectual capital (Aaker and Jacobson 2001; Hall 1993; Rousseau and Shperling 2003,
2004), R&D has been noted to capture intangible resources involved in both a ﬁrm’s
technological and production prowess, but also may bring the ﬁrm superior patents as a
result (Fiegenbaum et al. 1997).

The application of this component of intangible resources falls into three main
approaches. The ﬁrst way that studies typically conceptualize R&D is as R&D
expenditures, The second approach is to use a measure of R&D intensity, but to have
total assets as a denominator to R&D expenditures (Fiegenbaum et al. 1997). Finally, the
more common application of R&D intensity is with R&D expenditures as the numerator
and total sales as the denominator (Chang 1995; Delios and Henisz 2000; Henisz and
Delios 2001; Knott et al. 2003; Lu and Beamish 2004; Sharma and Kesner 1996). This
study employs the latter conceptualization. Given that this study aims to standardize the
resources used on R&D in the ﬁrm, the latter two approaches are more applicable to this
study’s context.

Related to the discussion of intangible resources, one study merged the
innovation, advertising, and marketing components as previously mentioned into a single
intangible construct (Seth et al. 2002). In an evaluation of value creation and destruction

in the foreign acquisition of ﬁrms in the US, Seth et al. (2002) found that their

29

“umbrella” construct standardized by ﬁrm sales had an inﬂuence on the total post-
acquisition gain in samples deemed synergistic (or, where the sum of two ﬁrms was
greater than its parts). In parallel, another unique conceptualization of a ﬁrm’s intangible
resources has been as legal intensity (Denekamp 1995). Deﬁned as the relative ability to
secure and contract legal services in a study of US. manufacturers, Denekamp (1995)
found that legal intensity had a positive relationship with a ﬁrm’s foreign direct
investment (FDI) in an industry. As a result, one could conclude that the more legal
representation a ﬁrm has, the more conﬁdent it may be in its investment of large capital
projects in speciﬁc industries.

Even more interesting in the discussion of intangible resources in the literature is
the luxury a ﬁrm may have to make conditional choices (Adner and Levinthal 2004; Day
and Fahey 1988; Day and Wensley 1988; McGrath et al. 2004). For example, based on a
ﬁrm’s ﬁnancial reserves (Geyskens et al. 2002), the ability to purchase excess production
capacity for competitive purposes (e.g., to heighten the required commitment for
potential new entrants) can be a formidable intangible resource for large ﬁrms to use to
their advantage. In essence, one could imply that any investments a ﬁrm makes — be it in
celebrity endorsers, innovativeness, or brand quality — may be considered akin to an

intangible resource (Agarwal and Kamakura 1995).

30

Intangible Resources — External Aspects

Contrasting the previous discussion related to intemally-oriented intangible
resources, external aspects of this concept in the literature falls into two wide and
somewhat related categories: customer- and channel-related. Some customer-oriented
intangible resources may be protected legally, such as a ﬁrm’s brand(s) and/or brand
equity (Aaker 1991; Aaker and Jacobson 2001; Geyskens et al. 2002; Gupta et al. 2004;
Rao et al. 2004; Srivastava et al. 1998). However, Hall (1993) would refer to others as
more dependent on people and much more difﬁcult to protect legally, particularly quality
image (Aaker 1991), customer relations (Srivastava et al. 1998), customer loyalty
(Pearson and Clair 1998), and customer equity (Gupta et a1. 2004).

One of the most widely channel-related intangible resources as mentioned in the
literature is a ﬁrm’s reputation (Aragon-Correa and Sharma 2003; Dyer and Singh 1998;
Oliver 1997; Pearson and Clair 1998; Rindova et al. 2005; Rindova et al. 2006; Roberts
and Dowling 2002). Though difﬁcult to protect legally (Hall 1993), this
conceptualization can include a ﬁrm’s value nets or networks (Frels et al. 2003), channel
equity (Geyskens et al. 2002), stakeholder relations (Godfrey 2005), relational assets
(Rousseau and Shperling 2003), relations with various market players (Peng 2003), and
transaction-speciﬁc assets to protect the ﬁrm’s processes and management procedures
(Brown et al. 2000). Recent research has even found that CRM applications tend to have
a positive inﬂuence on customer satisfaction while investments in information technology

have a negative inﬂuence (Mithas et al. 2005).

31

The preceding sections on intangible resources have attempted to summarize the
categorization of intangible resources in the marketing and management literature to date.
Inspired partly by previous studies relating intangible resources to speciﬁc proxies in a
company’s ﬁnancial statements (Barth and Kasznik 1999), the next sections will focus on
a related concept that allows the operationalization of some of the hitherto mentioned
ideas. Thinking that it is taking its signal from literature addressing company ﬁnancial
statements, the marketing literature generally considers intangibles and intangible
resources in the research to this point to be “lumped by accountants under the heading of
goodwill and include things such as patents, trademarks, and licensing agreements, as
well as “softer” considerations such as the skill of the management and customer
relations” (Keller 2003, p. 493).

However, based on the concept of ﬁnancial investments as opportunities in the
ﬁnance and accounting literature (Gaver and Gaver 1993), the intangible value proxies
(IVP) introduced here emphasize that — to have sufﬁcient opportunities to invest in a
variety of potential projects, products, and ventures — ﬁrms must take advantage of the
ﬂexibility they possess. Similar notions of this concept appearing in the management and
marketing literatures include slack and excess capacity (George 2005; Geyskens et al.
2002). In essence, the skills of management and employees to utilize and implement the
resources available for shepherding a product or service to market. Thus, an overview of
issues supporting the concept of IVP is provided below and subsequently followed by
constructs aiming to capture the elements of ﬂexibility, slack, and/or excess capacity that

the 108 literature discusses.

32

Intangible Value Proxies — Overview

Recent conceptual development in the marketing literature has emphasized that,
in utilizing intangible resources in the ﬁrm, managers must keep in mind the ﬁnancial
consequences of any marketing decisions (Moorman and Rust 1999; Rust et al. 2004).
This is not new, as concepts such as strategic emphasis have been explained in detail with
the use of ﬁnancial statements in previous marketing studies (Mizik and Jacobson 2003).
As such, there is embedded in this notion an implication from the marketing literature
that ﬁnancial statements can be used to make inferences about intangible resources. In
fact, as discussed throughout the literature related to intangibility and investments, the
use of ﬁnancial statements is a key component of any discussion on a ﬁrm’s ﬂexibility,
slack, and/or excess capacity in a variety of contexts.

Based on the literature devoted to investments and intangibility, there are three
general types of IV P measures found in the literature: price-, investment—, and variance-
based (Kallapur and Trombley 1999). Price-based proxies involve various elements of a
ﬁrm’s assets in its balance sheet (e. g., property, plant, and equipment; depreciation;
Tobin’s Q; earnings-to-price ratio, etc.). Meanwhile, investment-based typically include
elements of a ﬁrm’s expenditures in its income statement (e. g., R&D expenditures and
capital expenditures). Also, variance-based measures are based on the notion that
variations in key ﬁrm indicators (e. g., returns, asset betas, etc.) indicate opportunities to
invest in future ﬁrm Opportunities. This study will focus on the ﬁrst two categories as
underpinnings for empirical analysis. However, this does not preclude this study from

pursuing variability of the constructs discussed below as viable measures. Given their

33

appearance in the ﬁnancial statements of individual ﬁrms, the proxy variables based on
intangible value can be categorized as asset-based and expenditure-based.

Thus, continuing with the typology under development concerning technology-
and marketing-based resources, the subsections below will address the following IV P
measures as they appear in ﬁnancial statements: property, plant, and equipment; capital
expenditures; cash; cost of (goods) sold; inventory; sales, general, and administrative

expenditures; and intangible assets.

Intangible Value Proxies and Real Options Valuation

While IV P and the supporting literature on investment opportunities may seem
quite similar to a real options valuation (ROV) approach in its emphasis on ﬂexibility as
a value-added component to a ﬁrm’s strategy, there are some distinct differences making
ROV inappropriate in this study. In fact, Sorescu et al. (2003) expressed that radical
innovation could be considered a real option, particularly as it permits preferential access
to future ﬁrm development activities. Additionally, ROV discusses the usefulness of
irreversible investments in the presence of uncertainty and additional expenses, thus
implying that ﬁrms prefer lower ﬁxed costs and higher variable costs to delay
commitment as long as possible until viability is apparent (Kallapur and Eldenburg
2005). However, at least in a study of inventory conditions, support has not been found
for lower committed costs bringing improved performance such as return on assets
(ROA) (Balakrishnan et al. 1996).

Generally, ROV is used as a ﬁnancial tool at the project-level. Ranging from an

idea that it is a component of a ﬁrms total value or 5 speciﬁc investment proposal to

34

choices involving more than one proposal or even a reasoning heuristic for strategy
development, recent work has stated that there is little consistency regarding the concept
and application of real option (McGrath et al. 2004). As this study is at the corporate (or,
ﬁrm) level, the justiﬁcation of ROV for expressing and pursuing the notion of intangible
resources would be weak and unclear at best and potentially catastrophically ﬂawed at
worst.

More stringent and focused discussion concerning ROV proposes that its
applicability should be in cases in which both the target market and technical agenda are
ﬁxed, while other, path—dependent investment approaches should be used as either/both
the target market and/or technical agenda become ﬂexible (Adner and Levinthal 2004).
As ﬁrms can be considered inherently a portfolio of resources and investments in a
changing marketplace that must remain ﬂexible to maintain competitiveness (c.f.,
Wemerfelt 1984), the ROV approach may not be the most optimal for ﬁrm-level analysis.

While the herein described IVP approach may not be considered an ideal method
to measure and test path-dependent investments, it nonetheless captures the dynamics
involved in any ﬁrm: that past decisions in resource allocation inﬂuence — to some extent
- future resource allocations. In fact, researchers have stated that such accounting-related
data is required as it provides guidance concerning the capital investments of the ﬁrm
leading to underlying value creation (Chen and Zhang 2003; Zhang 2000). Thus, since
the ﬁrm-level manifestation of resource allocations is a ﬁrm’s ﬁnancial data, this model
hereby uses the IDS approach for conceptualization and analysis. As a ﬁrm’s sets of IVP
and investment opportunities are not directly observable (Gaver and Gaver 1993;

Kallapur and Trombley 1999), this notion is supported in that a variety of IVP measures

35

from ﬁnancial statements are used throughout the literature focusing on the opportunities

provided by ﬁnancial investment.

CONSTRUCTS

Generally, there are two general types of intangible resources discussed in the
literature (Aaker and Jacobson 2001; Geyskens, Gielens, and Dekimpe 2002; Gupta,
Lehmann, and Stuart 2004): intangible technology resources and intangible marketing
resources (Razgaitis 2005; Slotegraaf, Moorman, and Inman 2003). As such, a typical
description of intangible technology resources may be in the form of registered
innovations while the latter would be the brands a ﬁrm possesses. However, the premise
underlying this categorization of marketing resources does not directly address the cross-
functionality of common business practices (Vargo and Lusch 2004). Long discussed as
important in the marketing process, programs that aim to increase inter-departmental
behaviors among traditional manufacturing, engineering, and marketing functions
typically can reduce conﬂict and satisfy customers (Grifﬁn and Hauser 1992, 1993).
Found to not only reduce cross-functional conﬂict and increase responsiveness (Hult,
Ketchen, and Slater 2005; Maltz and Kohli 2000), recent marketing research results
indicate that such wholistic marketing behaviors are imperative to remain competitive in
new product development teams (J oshi and Shanna 2004), radical innovation
performance (Atuahene-Gima 2005), and preannounced product introductions (Wu,

Balasubramanian, and Mahajan 2004).

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3

Therefore, following the conceptual framework of Srivastava, Shervani, and
Fahey (1999), this study proposes that there are three distinct types of cross-functional
marketing resources that inﬂuence a ﬁrm’s marketing equity: customer-focused, supply
chain-focused, and innovation-focused resources. In addition, the notion of intangible
resources follows previous work that indicates intangibles are dynamic, dependent on
their application, and may be embedded in tangible resources (Vargo and Lusch 2004).
However, extending this discussion, this study speciﬁes precisely the nature of each
category of intangible marketing resources. This is supported by the notion that a ﬁrm’s
intangibles and future growth opportunities may be valued in relation to the current stock
of resources available in the ﬁrm (Gaver and Gaver 1993). From this, the long-term
inﬂuence of the following intangible marketing resources on marketing equity and
ﬁnancial performance is plausible. This study subsequently integrates the elements of
cross-functional marketing resources (customer-, supply chain—, and innovation focused

resources) and its different facets into a framework driven by extant literature.

(histomer-focused Resources

This study deﬁnes customer-focused resources as three-fold: business-to-business
(BZB) expenditures, business—to—consumer (B2C) expenditures, and seemed intellectual
property. Previous studies indicate that B2B marketing expenditures are an important
element in any marketing strategy selling to constituents in the next step of the value
chain (Wuyts, Stremersch, and Dutta 2004). Also, BZC marketing expenditures are

strategically signiﬁcant for communicating to consumers (Kirmani and Rao 2000).

38

Additionally, given the stock of unspeciﬁed intangibles that may be used by the
marketing function, the secured intellectual property of the ﬁrm is a third vital component
of customer-focused resources (Keller 2003; Vargo and Lusch 2004).

828 marketing expenditures. The role of marketing expenditures of suppliers and
in the value chain is fundamental to the analysis of ﬁrm sales and relevant to the
facilitation of its strategy in the competitive landscape (Gatignon and Xuereb 1997). In
the pharmaceutical industry, allocating resources for a sales force to sell directly to
medical representatives has been discussed as an important element of marketing strategy
(Wuyts, Stremersch, and Dutta 2004). Additionally, researchers have forwarded that B2B
marketing expenditures provide a reliable measure for the amount spent by a ﬁrm on its
market research, sales effort, and related trade expenses (Dutta, Narasimhan, and Rajiv
1999).

Regarded as a driver of growth opportunities (Lev and Thiagarajan 1993), B2B
marketing expenditures can indicate the capacity of the ﬁrm to synthesize customer-
focused information and respond appropriately. In fact, this is supported in that ﬁrms are
typically more responsive to increases of B2B marketing expenditures rather than
decreases (Anderson, Banker, and J anakiraman 2003). Referred to as a type of
administrative stickiness, ﬁrms anticipating or beneﬁting from increases in sales typically
use more resources to support such changes in the marketplace.

More importantly, previous ﬁndings indicate that BZB marketing expenditures
have a positive inﬂuence on performance (Kalwani and Narayandas 1995; Wuyts,
Stremersch, and Dutta 2004). Generally, the notion that the inﬂuence of BZB marketing

expenditures on proﬁtability widely validates such resource outlays in the value chain

39

(W uyts, Stremersch, and Dutta 2004). Meanwhile, in a study of suppliers in long-term
relationships, Kalwani and Narayandas ( 1995) found that reductions in B2B marketing
expenditures brought higher proﬁtability, as well. These disparate results may be the
artifacts of speciﬁc industry conditions. Nevertheless, they point to the importance of
B2B marketing expenditures in developing, implementing, and maintaining a ﬁrm’s
marketing strategy.

BZC marketing expenditures. Contrary to the role of B2B marketing expenditures,
B2C marketing expenditures take on a different role and focus on the end-user. An
equally important element of a ﬁrm’s marketing strategy, B2C marketing expenditures
represent the strategic investment made by the ﬁrm in informing the consumer of its
product or service (Dutta, Narasimhan, and Rajiv 1999). In particular, BZC marketing
expenditures can act as a signal to the market that the ﬁrm has speciﬁc intentions of
becoming or maintaining its position as market leader (Heil and Langth 1994). This
distribution of resources focusing more heavily on the end-user can signal deﬁnitive
quality vis-a-vis competitors, but can easily become ineffective if the ﬁrm lacks a true
point of competitive differentiation (Kirmani and Rao 2000).

In addition, researchers have linked BZC marketing expenditures with
performance (Mulhem and Padgett 1995; Rao, Agarwal, and Dahlhoff 2004; Singh,
Faircloth, and Nejadmalayeri 2005). Found as one of the drivers of proﬁtability (Mulhem
and Padgett 1995) and a ﬁrm’s market value added (Singh, Faircloth, and Nejadmalayeri
2005), previous studies have also compared the conditions under which B2C marketing
expenditures impact performance. Generally, in corporate branding circumstances, the

inﬂuence of BZC marketing expenditures on Tobin’s Q was found to be positive, but

40

when a house-of-brands strategy was employed a negative relationship resulted (Rao,
Agarwal, and Dahlhoff 2004). Possibly the result of B2C marketing expenditures as more
effective when a corporate brand strategy is used, it can be concluded that B2C marketing
expenditures are essential in the development of this typology of intangible marketing
resources.

Secured intellectual property. In addition, secured intellectual property refers to
the stock of intangibles that can be used by the ﬁrm’s marketing function and is to be
focused on its customers (Hall 1993; Lusch and Vargo 2004). Typically, a ﬁrm is only
able to protect intangibles such as research designs, copyrights, trademarks, trade secrets,
contracts, licenses, and databases through legal action (Hall 1993). Encompassing the
speciﬁc expertise embedded in the ﬁrm as a resource (J ap 1999), this notion of
intellectual property is far-reaching in scope and is a vital component of customer-
focused resources. Thus, there is a clear incentive for ﬁrms to secure as much intellectual
property as possible to remain competitive.

Comprised of both people and systems, intellectual property is thought of as
comprised of three inter-related elements: human capital, social capital, and organization
capital Oil/right, Dunford, and Snell 2001). However, for the purposes of this model, there
are the two distinct levels of intellectual property that are relevant: the individual and the
ﬁrm (Hall 1993; Mosakowski 1998; Rousseau and Shperling 2003; Srivastava, Shervani,
and Fahey 1998). For example, a ﬁrm’s intellectual property at the individual level may
include the skills, processes, and procedures used in routine, implementation, or strategic
capacities by employees and managers on a daily basis (Brown, Dev, and Lee 2000;

Geyskens, Gielens, and Dekimpe 2002; Gruca and Sudharshan 1995; Houston and

41

Johnson 2000). While a ﬁrm’s intellectual property at the individual level may be more
difﬁcult to secure should an employee or manager leave the ﬁrm, they nonetheless can be
used until such an event occurs.

In contrast, ﬁrm level intellectual property may be considered the accumulation of
a ﬁrm’s registered trademarks and innovations (Keller 2003), but also other design,
developmental, electronic resources that competitors may not have access to or be able to
create (Hall 1993). However, there is always the possibility that such secured intellectual
property may leak into the marketplace. As such, the literature has also identiﬁed an even
more elusive form of intellectual property: organizational culture and values (Carmeli
and Tishler 2004; Hall 1993; Mosakowski 1998; Srivastava, Shervani, and Fahey 1998).
Though not very visible, this social architecture is quite resistant to imitation and
therefore is strategically valuable (Mueller 1996).

At times referred to as the level of organizational entrepreneurship, a company’s
ability to innovate and imitate as needed in the market is of utmost importance (Im and
Workman 2004; Zhou, Yim, and Tse 2005). Equally compelling is the development of
intrapreneurship (Agarwal, Echambadi, Franco, and Sarkar 2004; Irn and Workman
2004). Pivotal in explaining the ability of a ﬁrm to harness the knowledge and
understanding of lower-level actors in an organization (Achrol 1991; Hart 1992;
Levinthal and Warglien 1999; Stopford and Baden-Fuller 1994), intrapreneurship
explains how individual performance inﬂuences overall organizational effectiveness
(Frese, Kring, Soose, and Zempel 1996). Thus, secured intellectual property as outlined

here indicates its pertinence as a cross-functional marketing resource.

42

Supply Chain-focused Resources

Our description of supply chain-focused resources includes three distinct
elements: sourcing attentiveness, inventory readiness, and production capacity. Identiﬁed
recently as important in considerations of product design and innovation (Wemerfelt
2005), the interconnected nature of supply chain resources with the overall marketing
function has been conﬁrmed conceptually and empirically (Dutta, N arasimhan, and Rajiv
1999; Ghosh and John 1999; Srivastava, Shervani, and Fahey 1999). In fact, ﬁndings
suggestion that implementation of programs such as Quality Function Deployment (QFD)
tend to increase communication between the traditional manufacturing, engineering, and
marketing functions and reduce conﬂict to satisfy customers (Grifﬁn and Hauser 1992).
Therefore, the intangible value of applying personal and organizational networks for
competitiveness both upstream and downstream emphasizes the importance of supply
chain-focused resources in marketing (Frels, Shervani, and Srivastava 2003; Ghosh and
John 1999; Hall 1993).

Sourcing attentiveness. The effectiveness of a ﬁrm’s sourcing practices and
procedures as a supply chain-focused resource is an important component of this model.
Generally, the literature has found purchasing and sourcing management an integral part
of maintaining sourcing processes effective (Zsidisin, Ellram, and Ogden 2003). In fact,
ﬁndings indicate that speciﬁc sourcing processes such as product quality and time to
market to inﬂuence sales and customer satisfaction (Tatikonda and Montoya-Weiss
2001). With superior production quality at a reduced cost, the ﬁrm is then positioned to

create and deliver better competitive value to its customers (Ghosh and John 1999).

43

The underlying notion here is that a ﬁrm’s competitiveness may be diminished
should it utilize too many resources (that could otherwise be deployed elsewhere in the
ﬁrm) to produce a set of goods or services. Though typically conceptualized as related to
the cost of production (Dutta, Narasimhan, and Rajiv 1999), sourcing attentiveness would
allow the ﬁrm’s remaining resources to be utilized in other functions. Therefore, by
maintaining competitiveness in its sourcing and purchasing of materials for production of
goods and/or services, the signiﬁcance of a ﬁrm’s sourcing attentiveness is evident.

Inventory readiness. The readiness at which a ﬁrm manages its supply of products
or services to downstream partners in the value chain is also particularly relevant (Ghosh
and John 1999). Acknowledged as another facet of supply chain-focused resources, the
ability of the ﬁrm to respond to varying levels of demand in the marketplace is
considered a driver of ﬁrm value (Balakrishnan, Linsmeier, and Venkatachalam 1996;
Lev and Thiagarajan 1993).

The general consensus is that a ﬁrm’s inventory readiness is contingent on a
ﬁrm’s mix of product and materials inventory. By developing cross-functional marketing
resources that are designed for both pull and push strategies, a ﬁrm is better able to keep
lower inventories and maintain a level of work in progress such that it can respond
quickly to changing market demand (Hopp and Spearman 2001). This is particularly
important in conditions of high market turbulence. Some ﬁrms are better able to practice
efﬁcient inventory readiness by conducting a just-in-time strategy that can lead to
superior returns (Balakrishnan, Linsmeier, and Venkatachalam 1996). As a result, there is
little doubt that inventory readiness is another essential part of a ﬁrm’s supply chain-

focused resources.

Production capacity. Beyond a ﬁrm’s sourcing attentiveness and inventory
readiness, the capacity of the ﬁrm to produce goods or services is the last supply chain-
focused resource in this model. As such, it is forwarded here that the equipment under a
ﬁrm’s control can be considered an intangible resource in its own right (Barth and
Kasznik 1999; Jap 1999). In fact, depending on its strategic application, the capacity to
produce can either contribute to or detract from performance in the marketplace.

Some have indicated that a ﬁrm’s production capacity is very rarely maximized
(Hopp and Spearman 2001), thus leaving the potential for slack creation and ﬂexibility to
respond to the market. Equally compelling are ﬁndings noting that the capacity to
produce may decrease responsiveness and value (Kallapur and Trombley 1999). One can
only conclude that a ﬁrm’s production capacity can impact how materials are used but
also how those ﬁnished materials are directed to customers and end-users. Therefore, this

model incorporates this central component of supply chain-focused resources.

Innovation-focused Resources

The innovation-focused resources described in this model have three parts, as
well: discovery expenditures, ideation personnel centralization, and overall innovation
creativity. Based on the concept that the innovation process includes not only research
and development, it is proposed here that the individual as well as the ﬁrm’s accumulated
innovations efforts in new product development (NPD) also have a role (Cooper 2001).
Thus, the cross—functional nature of innovation-focused marketing resources underscores

the relevance of each construct in this model (Srivastava, Shervani, and Fahey 1999).

45

Discovery expenditures. Be it from knowledge spillovers or organic, internal
growth, the level of resources used in the discovery, research, development, and
engineering process may be considered one of the only ways that a ﬁrm may differentiate
itself (Cooper 2001; Hauser 1998). This measurement of resource allocation is common
in the innovation literature and has been applied in a variety of settings that range from
the pharmaceutical and shipbuilding industries to analyses of slack, innovation, customer
satisfaction, and shareholder value (Greve 2003; Gruca and Rego 2005 ; J oshi and Sharma
2004; O’Brien 2003; Prabhu, Chandy, and Ellis 2005).

Nonetheless, at least two important issues related to the NPD process are
accomplished with the discovery expenditures conceptual construct. First, the amount of
organizational slack allowed for innovation is taken into account as it has been shown to
inﬂuence the NPD process considerably (Greve 2003). Second, the strategic importance
of the NPD process in the ﬁrm is directly measured (O’Brien 2003; Mizik and Jacobson
2003). Therefore, the level of resources devoted to the design of product and service
discovery is a valuable contribution to the overall allocation of a ﬁrm’s innovation-
focused resources.

Ideation personnel centralization. This study extends the notion of the individual
as an intangible resource with the concept of ideation personnel centralization. This is
based on the notion of ideation personnel centralization in previous marketing research
concerning ideation (Goldenberg, Mazursky, and Solomon 1999). However, rather than
discuss the ideation process, this study forwards the concept of ideation personnel (or,

inventors) as an important innovation-focused resource.

46

In essence, this is based on the innovation level of the most productive inventors
in a ﬁrm. Typically associated with radical technology shifts rather than gradual
technological developments (Zyglidopoulos 1999), the importance of inventors in the
innovation process has considerable basis in the literature (e. g., Hargadon and Sutton
1997; Singh 2005). Findings indicate that the development of innovation and knowledge
generally clusters around top inventors in a region or industry (Almeida and Kogut 1999),
thus inferring their value as a resource to ﬁrms.

As a result, inventors are considered knowledge and technology brokers that are
characterized as intensely curious to develop new ideas from sources internal or external
to the ﬁrm (Hargadon and Sutton 1997). The most successful of these inventors have
been found as deeply involved in the commercialization of inventions (Zucker and Darby
1997). By striking a balance between familiar and original traits, these inventors are able
to recombine previous innovations to develop new discoveries, formulations, and
products that may be useful and appealing to a wider audience (Hargadon and Douglas
2001). As such, inventors identify useful solutions by keeping in mind their potential
usefulness in the marketplace (Goldenberg, Lehmann, and Mazursky 2001). Therefore,
the centralization of such unique and rare talents in a ﬁrm can be considered a distinct
advantage that contributes to its competitiveness.

Overall innovation creativity. The concept of overall innovation creativity varies
with the context in which it is used. In fact, more creative teams beneﬁted from a
perceived notion that tasks required high creativity levels, participative problem-solving,
and a supportive climate for creativity (Gilson and Shalley 2004). However, whether

studied in the implementation of marketing programs (Andrews and Smith 1996; Irn and

47

Workman 2004), at the cross—functional project level (Sethi, Smith, and Park 2001), or at
the individual innovator level (Hargadon and Sutton 1997), the commonality of creativity
is that it is used to explain the resultant of a wide variety of work, experience, and
analysis.

As such, the basis of the use of creativity level in this model is rooted in the
literature on incremental product innovation, radical product innovation, and the level of
newness the innovation is to the intended marketplace. An underlying notion of this topic
is that incremental innovations lack original information in the development process
(W uyts, Stremersch, and Dutta 2004). Meanwhile, radical product innovation concerns
the level to which a ﬁrm’s cumulative product and/or technological innovations are new.
Including instances of disruptive innovations, radical product innovation relies on the
integration of concepts from different innovation categories (Cooper 2001; J oshi and
Sharma 2004).

Contrary to incremental innovation, this variable expresses the novelty of
information and development associated with the innovation (J oshi and Sharma 2004;
Wuyts, Stremersch, and Dutta 2004). In addition, market newness concerns the level to
which the cumulative innovations developed by the ﬁrm are original to the marketplace
and are unrelated to current (or past) products or technologies in the marketplace. In fact,
the originality of a ﬁrm’s product or service offerings is generally associated with the
level of newness vis-a-vis competitors, thus creating a new product advantage (Li and
Calantone 1998). Given these different aspects of overall innovation creativity, it is

concluded here that innovation originality is also an innovation-focused resource.

48

HYPOTHESIS DEVELOPMENT

Based on the deﬁnition of equity as “a right, claim, or interest existing or
valid. ..[or]... a risk interest or ownership right” (Merriam-Webster 1967, p. 281), three
fundamental elements of marketing equity are forwarded: customer satisfaction, brand
equity, and corporate reputation. Measuring different facets of marketing outcomes and
representing a ﬁrm’s customer-based interests in the marketplace, it is forwarded here
that these three components of marketing equity are indeed essential to explaining overall
ﬁnancial performance. In fact, this framework responds to calls in the literature to better
understand the inﬂuence of a ﬁrm’s resource allocations on ﬁnancial performance by
proposing models with the role of mediating, comparative outcome measures (Daniel,
Lohrke, Fomaciari, and Turner 2004; Ray, Barney, and Muhanna 2004). Due to the
dynamics of competitive rivalries that inherently drive customer decisions, customer
satisfaction, brand equity, and corporate reputation are viewed here as comparative
measures of performance and inherently vital to the development of the literature.

To develop this model, the following section introduces the synergistic
relationship of these three elements of marketing equity. This study aims to synthesize
previous work on marketing measures and provide a comprehensive framework
clarifying theoretical relationships that may exist concerning these three essential
marketing metrics as well as their antecedents and consequences. As inferred previously,
this study forwards that the hitherto mentioned cross-functional marketing resources are
antecedents in this model. In addition, forward commonly used ﬁnancial performance

measures as consequences of each of marketing equity’s three fundamental elements.

49

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Customer Satisfaction

Typically used as a consumer-based measure of marketing performance, extant
research has usually used the concept of customer satisfaction as a short-term marketing
measure driving channel equity and brand equity (Rust et al. 2004). Some studies suggest
that customer satisfaction is indeed a marketing variable that is formed over a period of
time (Anderson, Fomell, and Lehmann 1994). However, it is posited here that customer
satisfaction is inﬂuenced by both the short-term actions taken by the ﬁrm as well as the
accumulated actions that relate to the immediate satisfaction of the customer. As such, it
is a vital component of marketing equity and is included in this model as the result of a
ﬁrm’s allocation of cross-functional intangible marketing resources.

Based on the customer’s assessment of a ﬁrm’s perceived quality, perceived
value, and customer expectations, the construct of customer satisfaction measures the
level of overall customer satisfaction with the ﬁrm’s products or services. Acknowledged
as another variable that is formed over the long-term (Anderson et al. 1994), ﬁndings
have indicated that ﬁrms which are market-oriented tend to enjoy higher customer
satisfaction ratings (Homburg and Pﬂesser 2000). With quality considered much more
inﬂuential than price, the drivers established that inﬂuence this variable are overall
perceived quality and previous performance based on customer expectations and
perceived value (Anderson and Sullivan 1993; Fomell 1992; Fomell et al. 1996). Thus, to
manage customer expectations, ﬁrms should be careful of promising a product or service

that it cannot deliver (Anderson et al. 1994).

51

In addition, customer satisfaction is generally considered higher when there is an
alignment between industry characteristics and customer tastes. For instance, this variable
is higher with conditions where customer tastes are homogeneous in industries which are
not differentiated; the same was found for heterogeneous customer preferences and
highly differentiated industries (Fomell 1992). In addition, similar ﬁndings are implied
from a comparison of goods, services, and government agencies: goods industries were
highest in customer satisfaction and government agencies were lowest (Fomell et al.
1996). As such, customer satisfaction has been forwarded as inﬂuencing the likelihood of
repurchase and general loyalty (Mittal and Kamakura 2001; Oliva et al. 1992; Olsen
2002). However, the ability of ﬁrm to develop strategies to identify and respond to these
conditions is contingent it ﬁnding the appropriate ﬁt between the dominant strategic
archetype in the ﬁrm and the optimal strategy for success in the market (Miles and Snow
1978).

However, as found in other aspects of marketing (e.g., the brand literature),
negative experiences tend to outweigh positive ones (Bolton 1998; Mittal et al. 1998).
Given that customer expectations can be set excessively high to the point where a ﬁrm
cannot fulﬁll expectations, there are certain tradeoffs concerning quality and overall
performance leading some to conclude that too much can be spent on quality (Rust et al.
1995). Along this same line of thought, too much attention may be paid to loyal
customers and such actions may be counter-productive (Rust et al. 1999; Rust and Oliver
2000). In fact, some researchers go even further and ﬁnd that there is a trade-off between
customer satisfaction and market share (Anderson et al. 1994; Fomell 1995). These

indications lead the researcher to conclude that there are instances in which resources can

52

be unduly wasted by a ﬁrm attempting to satisfy customers who cannot be satisﬁed. As
result, fewer resources are available to prevent negative experiences and may damage the
ﬁrm’s overall customer satisfaction in the marketplace. Thus, the ﬁrm’s competitive
advantage could be endangered, potentially leading to damaging consequences in its
ability to sustain any sort of competitive advantage in the long-term (Barney 1991).

A recent meta-analysis focusing on this topic indicates that two important
antecedents of customer satisfaction are equity (a judgment of fairness, rightness, or
deservingness made by consumers to note how it is perceived others will beneﬁt) and
disconﬁrmation (Szymanski and Henard 2001). In addition, customer satisfaction of a
ﬁrm has been related to shareholder value at varying degrees of industry concentration
(Anderson et al. 2004), thus lending credence to the notion that the level of customer
satisfaction a ﬁrm enjoys may be a competitive advantage while shareholder value may
be a sustained competitive advantage (Barney 1991).

The general notion in this research stream is that a ﬁrm’s ability to communicate
and deliver its product or service to buyers (customers or consumers) leads to ﬁnancial
returns and more exact customer information (Parasuraman and Grewal 2000a). In
response to the proposition that technology may contribute to quality, value, and
customer loyalty (Parasuraman and Grewal 2000b), in a study exploring the inﬂuence of
customer relationship management on customer knowledge and customer satisfaction,
three main drivers of a ﬁrm’s customer satisfaction were evident: 1) the presence of a
CRM application (positive association); 2) investments in information technology
(negative association); and 3) a general improvement in customer knowledge (positive

association) (Mithas et al. 2005). Similar to the general tenets of market knowledge

53

competence in that the antecedents of its three primary constructs (customer knowledge
process, the marketing-R&D interface, and the competitor knowledge process) are both
external and internal forces, effective implementation of these processes in the ﬁrm

contribute to new product advantage and market performance (Li and Calantone 1998).

A recent meta-analysis indicates that two important antecedents of customer
satisfaction are equity (a judgment of fairness, tightness, or deservingness made by
consumers to note how it is perceived others will beneﬁt) and disconﬁrmation
(Szymanski and Henard 2001). In addition, customer satisfaction of a ﬁrm has been
related to shareholder value at varying degrees of industry concentration (Anderson,
Fomell, and Mazvancheryl 2004), thus lending support to the notion that the level of
customer satisfaction a ﬁrm enjoys may be a competitive advantage while ﬁnancial
measures (e. g., shareholder value) may be a sustained competitive advantage (Barney
1991).

As such, a ﬁrm would need to ﬁnd the appropriate mix of cross—functional
resources that incorporate product development, supply chain, and customer relationship
concerns to ﬁll need in the marketplace and attain a competitive advantage (Child 1972;
Li and Calantone 1998; Song and Parry 1997). Therefore, the allocation of a ﬁrm’s
customer-, supply chain-, and innovation-focused resources should inﬂuence customer
satisfaction.

Since a ﬁrm’s properly-directed and developed new product advantage should be

appropriately geared for the marketplace, the following should result:

54

H I : There should be a positive relationship between a ﬁrm ’s (a) 323 marketing
expenditures, (b) BZC marketing expenditures, (c) secured intellectual
property, (d) sourcing attentiveness, (e) inventory readiness, 0‘)
production capacity, (g) discovery expenditures, (h) ideation personnel
centralization, and (i) overall innovation creativity, and its customer

satisfaction.

Brand Equity

A popular application of the concept of a ﬁrm’s brand equity is that it is
comprised of two components: I) demand in the marketplace that enhanced brand equity;
and 2) the reduction of required marketing expenses as a result of enhanced brand equity
(Simon and Sullivan 1993).

In fact, the construct of brand equity is deﬁned as the strength of a ﬁrm-level
brand in the marketplace. The most widely accepted conceptualization of this variable
includes four components: brand loyalty, name awareness, perceived quality, and brand
associations (Aaker 1991; Reddy et al. 1994). However, conceptualizations and
measurements of brand equity in this vein are typically at the consumer level.

Considered an important contribution from the ﬁeld of marketing to overall ﬁrm
value (Varadarajan and J ayachandran 1999), brand equity must be considered in any
model addressing the topic of brands. In fact, there are many different types of brands as
per the literature and practice. Brand strategies employed by ﬁrms can usually be
categorized in three types: corporate brands, house of brands, and mixed brands (Laforet
and Saunders 1994; Rao et al. 2004). A similar approach looks at the phenomenon as

corporate, family, and product brands (Keller 2003). In addition, an even more detailed

55

assessment of the brand landscape identiﬁes product, line, range, umbrella, source (or,
parent), and endorsing brands (Kapferer 1992).

This implies that the relationship customers have with a ﬁrm-level brand can be
quite broad. In fact, the conclusion is that a ﬁrm’s brand equity may be inﬂuenced by not
only customer-focused resources, but also by the innovation process and the process and
delivery of a product or service to the end-user. Therefore, the comparative nature of
brand equity as a performance measure driven by the appropriate allocation of cross-
functional resources to ﬁt with demand in the marketplace is essential (Child 1972; Li
and Calantone 1998; Ray, Barney, and Muhanna 2004; Song and Parry 1997).

Since the current study is assessing ﬁrm-level characteristics, results can be
classiﬁed as applicable to the study of corporate brands. Studies of brand equity have
pursued its relevance as compared to private labels (Ailawadi et al. 2003) and the direct
negative experiences and unclear corporate responses (Dawar and Pillutla 2000).
Advertising has been found to have a long-term impact on brand equity (J edidi et al.
1999), but many experiments conducted on the subject to date may not be entirely
accurate (Mackenzie 2001). Thus, this paper is including it as a ﬁrm-level variable with
more objective data. Though accomplished in previous studies (Slotegraaf et al. 2003),
this project aims to potentially develop a new, customer-based brand equity index.
However, given the competitive strategies chosen through resource allocation, the
effectiveness of managerial decision making on performance is crucial (Child 1972).

The construct of brand quality is based on customer perceptions and has been
used in the literature as a viable alternative to brand equity (Aaker and Jacobson 1994).

As such, it has been used and deﬁned as the level that consumers associate the ﬁrm-level

56

brand with quality. The importance of this variable must be noted since it has been
acknowledged as having long—term effects in the marketplace (Aaker and Keller 1990).
The general consensus in the literature is that brands with higher perceived quality tend to
perform better among consumers when extensions are introduced in complementary and
substitutable product classes (Aaker and Keller 1990). This was further supported when a
very similar construct, brand strength, was found to moderate positively the relationship
between a brand extension and the brand’s overall market share (Smith and Park 1992).
As such, the relation of a ﬁrm’s tangible and intangible resources to its brand equity
reﬂect the need to measure marketing outcomes comparatively to better assess a ﬁrm’s
competitive advantage (Ray et al. 2004). Thus:
H2: There should be a positive relationship between a ﬁrm ’s (a) 828 marketing
expenditures, (b) BZC marketing expenditures, (c) secured intellectual
property, (d) sourcing attentiveness, (e) inventory readiness, (I)
production capacity, (g) discovery expenditures, (h) ideation personnel

centralization, (i) and overall innovation creativity, and its brand equity.

Corporate Reputation

Contrasting the use of customer satisfaction and brand equity in the literature, the
essence of the corporate reputation construct has been conceptualized in the literature as
akin to a ﬁrm’s channel equity (Fombrun and Shanley 1990; Geyskens, Gielens, and
Dekimpe 2002; Houston and Johnson 2000; Srivastava, Shervani, and Fahey 1998).
Recently established as a driver of marketing communication productivity (Luo and

Donthu 2006), its reputation is generally considered relatively stable (Gioia, Schultz, and

57

Corley 2000). The use of corporate reputation in the literature is based on the notion that
ﬁrms typically serve multiple stakeholders (Brown et al. 2006; Fombrun and Shanley
1990; Houston and Johnson 2000). As such, the ability of the ﬁrm to fulﬁll the demands
of outside stakeholders can be reﬂected in its standing among industry experts and
partners (Roberts and Dowling 2002).

There is little doubt that a ﬁrm’s reputation is an integral element of marketing
equity. Identiﬁed as a relevant strategic indicator, the corporate reputation of a ﬁrm in the
value chain can even inﬂuence consumer knowledge among end-users (Sen and
Bhattacharya 2001). This indicates the importance of a channel-based measure of
marketing equity to measure a ﬁrm’s true standing in the marketplace (Srivastava,
Shervani, and Fahey 1998). In fact, scholars typically follow Fombrun and Shanley’s
(1990) view of corporation reputation and interpret it as “the outcome of a competitive
process in which ﬁrms signal their key characteristics to constituents to maximize their
social status” (p. 234).

Implicit in any competitive process is the allocation and direction of resources to
respond to market conditions for a positional advantage (Barney 1991; Child 1972; Day
and Wensley 1988; Peteraf 1993; Wemerfelt 1984). Furthermore, the appropriate cross-
functionality of such resource distributions (be they across teams, business units, or
marketing tactics) is a critical factor for success in the marketplace (Duncan and Moriarty

1998; Fombrun and Shanley 1990; Grifﬁn 1997; Li and Calantone 1998). Therefore:

58

H3: There should be a positive relationship between a ﬁrm ’s (a) 823 marketing
expenditures, (b) BZC marketing expenditures, (c) secured intellectual
property, (d) sourcing attentiveness, (e) inventory readiness, 0‘)
production capacity, (g) discovery expenditures, (h) ideation personnel
centralization, and (i) overall innovation creativity, and its corporate

reputation.

Return on Assets
The use of return on assets (ROA) as an objective measure of a ﬁrm’s proﬁtability is
quite common (Anderson, Fomell, and Mazvancheryl 2004; Sorescu, Chandy, and
Prabhu 2003; Rust, Moorman, and Dickson 2002; Vorhies and Morgan 2005). In fact,
scholars indicate that ROA is a traditional ﬁnancial measure that may be used as an
alternative to constructs such as shareholder value and stock return (Aaker and Jacobson
2001; Gruca and Rego 2005). Therefore, ROA is an appropriate ﬁnancial performance
measure to assess the impact of each distinct component of marketing equity on a ﬁrm’s
proﬁtability. Given that customer satisfaction, brand equity, and corporate reputation
each measure different facets of a ﬁrm’s marketplace performance (or, marketing equity),
it is forwarded that these comparative performance measures will indeed inﬂuence
absolute ﬁnancial outcomes (Daniel et al. 2004; Ray, Barney, and Muhanna 2004).
Previous research has indicated that customer satisfaction, brand equity, and
corporate reputation can impact ﬁnancial performance. However, to date such studies
have typically assessed the inﬂuence of elements of marketing equity on accounting-

based performance measures in isolation (Aaker and Jacobson 2001; Anderson, Fomell,

59

and Mazvancheryl 2004; Gruca and Rego 2005 Roberts and Dowling 2002; Slotegraaf,
Moorman, and Inman 2003). Contrary to this, this study propose an integrative
framework indicating that — inﬂuenced by the allocation and direction of cross-functional
marketing resources - each component of marketing equity contributes to ﬁnancial
performance (Child 1972; Li and Calantone 1998; Ray, Barney, and Muhanna 2004).
Therefore: ‘
H4: There should be a positive relationship between a ﬁrm ’s customer
satisfaction and its ROA.
H5: There should be a positive relationship between a ﬁrm ’s brand equity and its,
ROA.
H6: There should be a positive relationship between a ﬁrm ’s corporate reputation

and its ROA.

Altman’s Z

The use of ROA as the only measure of ﬁnancial performance has its drawbacks. In fact,
scholars have forwarded that the use of ROA only captures short-term effects for one
ﬁscal year and may not be suitable to understand ﬁnancial performance over a
considerable period of time (Pauwels, Silva-Russo, Srinivasan, and Hanssens 2004;
Varadarajan, J ayachandran, and White 2001). Therefore, this study proposes Altman’s Z
as a measure that identiﬁes the likelihood of a ﬁrm’s bankruptcy (Altman 1984; Altman,
Haldeman, and Narayanan 1977). As an assessment of a ﬁrm’s ﬁnancial health (Sen and
Bhattacharya 2001), this measure of performance has been used in a variety of contexts

(Grice and Ingram 2001). In fact, there is a considerable literature base that studies

60

privatization, audit-related litigation, and ﬁnancial risk (Andrews and Dowling 1998;
Carcello and Palmrose 1994; Krishnan and Krishnan 1997; Stice 1991).
However, recent research has also related Altman’s Z to advertising expenses, the
cost of capital, and strategies of joint-ventures by multinational corporations (Reuer and
Leiblein 2000; Singh, Faircloth, and Nejadmalayeri 2005). As such, the possibility of a
ﬁrm’s bankruptcy may be used in this framework as a longer-term measure of ﬁnancial
performance than ROA. The result is that it is posited that the adoption of such a metric
by researchers since it can offer an alternative measurement to explicitly assess the
quality of cumulative strategic decisions made by the ﬁrm and its managers (Child 1972).
Thus:
H7: There should be a positive relationship between a ﬁrm ’s customer
satisfaction and its Altman ’3 Z

H8: There should be a positive relationship between a ﬁrm ’s brand equity and its
Altman 's Z.

H9: There should be a positive relationship between a ﬁrm ’5 corporate reputation

and its Altman ’s Z.

Tobin’s Q

Used to indicate the level of a ﬁrm’s intangibles, Tobin’s Q has been applied in
many settings and is well-recognized as a dependent variable measuring ﬁnancial
performance (Anderson, Fomell, and Mazvancheryl 2004; Rao, Agarwal, and Dahlhoff
2004; Rust et al. 2004). Based on early approaches introducing and popularizing this

measure of shareholder value through intangibility (Montgomery and Wemerfelt 1988;

61

Tobin 1969, 1978), a multi-industry study strangely found that ﬁrm size negatively
impacted a ﬁrm’s Tobin’s Q while it positively impacted a ﬁrm’s other accounting-based
performance measures (Wiggins and Rueﬂi 2002). One could speculate the reason for
such ﬁndings is that the competitive strategies employed by the ﬁrm emphasize short-
term ﬁnancial performance rather than developing longer-term sustainable competitive
advantage (Barney 1991; Child 1972; Pauwels et a1. 2004; Varadarajan, Jayachandran,
and White 2001).

Many studies employ Tobin’s Q as a measure of overall ﬁrm performance, be it
relative proﬁtability (Dutta, N arasimhan, and Rajiv 1999), shareholder value in the ﬁrm
(Gruca and Rego 2005), market valuation of the ﬁrm (Lee and Grewal 2004), or as a
replacement construct for return on investment (ROI) (Anderson, Fomell, and
Mazvancheryl 2004). Recently, Tobin’s Q has been used to measure the contribution of
differing branding strategies (Rao, Agarwal, and Dahlhoff 2004) as well as contribute to
the customer satisfaction literature (Anderson, Fornell, and Mazvancheryl 2004; Gruca
and Rego 2005). Additionally, corporate reputation research has shown that a ﬁrm’s
reputation can lead to trustworthiness and a price premium (Rindova et al. 2005;
Sirdeshmukh, Singh, and Sabol 2002). This study proposes that the trust (and the price
premium associated with such trust) placed in a ﬁrm by outside stakeholders is a result of
the standing relationships it has with B2B and B2C customers. As a result, this should
have an indelible inﬂuence the ﬁrm’s overall ﬁnancial performance (Srivastava,
Shervani, and Fahey 1998; Gioia, Schultz, and Corley 2000).

Using Tobin’s Q as an outcome variable indicates that, through B2C-based

(customer satisfaction and brand equity) and B2B-based elements of marketing equity

62

(corporate reputation), it may be employed to measure the long-term intangible value of
cross-functional decisions made by managers to bring the ﬁrm a sustainable competitive
advantage (Barney 1991; Child 1972; Li and Calantone 1998). Thus:
H10: There should be a positive relationship between a ﬁrm 's customer
satisfaction and its Tobin ’s Q.
H11: There should be a positive relationship between a ﬁrm ’s brand equity and
its Tobin ’s Q.
H12: There should be a positive relationship between a ﬁrm ’s corporate

reputation and its Tobin ’s Q.

Moderator Variables

Firstly, among the variables to be considered as moderators on the path from the
category of ﬁrm resources to marketing outcomes will be marketing expenditures, sales
force expenditures, and advertising expenditures. As all three of these are marketing
related, the general notion is that the marketing function assists in properly directly ﬁrm
resources to optimal marketing outcomes.

Secondly, the variable that is proposed here as having a moderating effect on the
category of marketing outcome variables to ﬁnancial performance variables is the level of
ﬁrm newness of the overall innovations in the ﬁrm. As such, this will either accentuate or
diminish the main effects proposed in the model.

Thirdly, there may also be the opportunity to test two overall moderating
variables on the model: ﬁrm growth and industry growth. (Please note that industry

growth is thought of here as similar to technological stability.) While conceptual

63

development has not yet been fully realized or articulated, these may prove to be further
interesting in their impact on not only the aforementioned moderating variables (e. g.,
marketing, sales force, and advertising expenditures; ﬁrm newness of innovations; etc.),
but also on the main effects of the model. As such, by analyzing the model not only based
on resources, but also on the dynamics of a particular industry, the propositions
forwarded may changed substantially as a result. For instance, this study will use Mizik
and J acobson’s (2003) approach to differentiating industries as high, medium, and low

growth if this is determined to be a moderating variable of sufﬁcient merit.

Table 1: Sample’s Most Prominent Industries and Classiﬁcation Scheme

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SIC Technology

INDUSTRY codes Classiﬁcation Freq,
CRUDE PETROLEUM & NATURAL GAS 1311 low technology 11
OPERATIVE BUILDERS 1531 low technoltrjy 10
PHARMACEUTICAL PREPARATIONS 2834 high technglcgy 10
PETROLEUM REFINING 2911 stable technolgy 8
SEMICONDUCTOR & RELATED DEVICES 3674 high technol_ogy 9
MOTOR VEHICLE PARTS & ACCESSORIES 3714 stable technology 9
TRUCKING, EXCEPT LOCAL 4213 low technology 9
AIR TRANSPORT, SCHEDULED 4512 high technology 10
PHONE COMMUNICATIONS EX RADIOTELEPHONE 4813 high technology 8
ELECTRIC SERVICES 491 1 stable techrLlogy 21
ELECTRIC & OTHER SERVICES COMBINED 4931 stable technology 15
GROCERY STORES 5411 low technology 9
EATING PLACES 5812 low technology 13
COMMERCIAL BANKS 6020 stable technolggy 21
SECURITY BROKERS & DEALERS 6211 stable technMy 9
LIFE INSURANCE 6311 stable technology 13
HOSPITAL & MEDICAL SERVICE PLANS 6324 stable technology_ 8
COMPUTER PROGRAMMING & DATA PROCESSING 7370 high technology 12
PREPACKAGED SOFTWARE 7372 high technology 10

 

 

 

 

 

 

CHAPTER FOUR
METHODS
“You ’ve got to be very careful if you don ’t know where
you’re going, because you might not get there. ”
— Lawrence Peter ‘Yogi’ Berra (1925-)

The research hypotheses presented above were tested from ﬁve distinct secondary
data sources and employed an enhanced least squares approach. The unit of analysis for
this study is at the level of the ﬁrm. Each variable discussed below was standardized to
minimize spurious measurement, multicollinearity, and non-normality effects that may
confound the study. Additionally, the logarithmic function of each ﬁrm’s net sales was
used as a control variable. Variance inﬂation factors for all variables tests in all models
were below 10, indicating that multicollinearity is likely not confounding analysis of the
data.

First, the sample was tested as a whole. Then, the sample was divided into distinct
groups based on industry technology level: high technology, stable technology, and low
technology (Chandler 1994; Mizik and Jacobson 2003). Tests were also performed to
contrast high technology industries with stable and low technology industries combined.
The operationalization of each variable in the model is discussed below. Then, the

operationalization of each index also tested in the model is covered.

VARIABLE OPERATIONALIZATION
B2B Marketing Expenditures
The ﬁrst of three customer-focused resources measured in this study, the role of

marketing expenditures on the B2B level in marketing focuses on the ﬁrm’s efforts to sell

65

a product or service to another ﬁrm. The literature has indicated that there may be
possible double-counting if a ﬁrm reports both its Selling, General and Administrative
Expenses along with Advertising Expenses. Additionally, following Mizik and

J acobson’s (2003) use of ﬁnancial data to determine a ﬁrm’s strategic emphasis, this
study used the following calculation taken from items in the Wharton Research Data
Services (WRDS) Compustat database:

32B = (SG&A — Adv) / TA

where
B2B = B2B marketing expenditures
SG&A = Selling, General, and Administrative Expenses (DATA189)
Adv = Advertising Expenses (DATA45)
TA = Total Assets (DATA6)
B2C Marketing Expenditures

The second of three customer-focused resources studied here, the conceptual
domain of B2C marketing expenditures is contrary to B2B marketing expenditures.
Instead, its focus is on the ﬁrm’s efforts to communicate directly to the end-user about a
product or service. An appropriate calculation using data from the WRDS database was:

B2C = Adv / TA
where
B2C = B2C marketing expenditures

Adv = Advertising Expenses (DATA45)
TA = Total Assets (DATA6)

66

Secured Intellectual Property

The third of three customer-focused resources measured in this study, the role of
secured intellectual property (SIP) deals with an exact, managerially-reported measure of
a ﬁrm’s intangible assets. A considerable portion of this measure is the valuation of a
company’s purchase of external entities (e.g., brands, strategic business units, ﬁrms to be
taken over, etc.). Therefore, to determine the strategic emphasis a ﬁrm places in
purchasing and valuing reported intangible assets, the following calculation with data
from the WRDS database was used:

SIP = Intangs / TA

where
SIP = secured intellectual property
Intangs = Intangibles (DATA33)
TA = Total Assets (DATA6)
Sourcing Attentiveness

The ﬁrst of three supply chain-focuses resources studied here, sourcing
attentiveness addresses the ability of the ﬁrm to deliver value to customers. Given the
continuous push for proﬁtability, managers inherently attempt to minimize costs.
Therefore, the costs saved by a ﬁrm should be translated into speciﬁc beneﬁts that can be
passed on in the value chain. The calculation used for this variable with data from the
WRDS database was:

Sourcing = 1 — (COGS / Sales)
where
Sourcing = sourcing attentiveness

COGS = Cost of Goods Sold (DATA41)
Sales = Net Sales (DATA12)

67

Inventory Readiness
The second of three supply chain-focused resources in this study, inventory
readiness quantiﬁes the level of inventory ready for distribution or sale in the
marketplace. Essentially, the level of ﬁnished goods a ﬁrm has in its inventory can be
considered an indication of its responsiveness to readiness to the marketplace. The
calculation used with data from the WRDS database was:
Inv = FG / TotInv

except when FG is not available, then

Inv = 1
where
Inv = inventory readiness
FG = Inventories — Finished Goods (DATA78)
TotInv = Total Inventories (DATA3)
Production Capacity

The third of three supply chain-focused resources studied here, production
capacity reﬂects the level of production readily available for a ﬁrm’s products or
services. However, to measure this relative to the expenses of a ﬁrm makes to develop
new or upgrade current facilities, the calculation used with data from the WRDS database
was:

ProdCap = PPE / CapEx
where

ProdCap = production capacity

68

PPE = Net Property, Plant & Equipment (DATA8)
CapEx = Capital Expenditures (DATA128)

Discovery Expenditures
The ﬁrst of three innovation-focused resources in this study, discovery
expenditures provides an indication of the ﬁnancial support a ﬁrm gives to its innovation
efforts. Rather than measuring this variable relative to sales or assets, this study employs
a third alternative - a level of a ﬁrm’s liquidity. Therefore, the following calculation was
used with data from the WRDS database:
DiscExp = R&D / Cash&STI
where
DiscExp = discovery expenditures

R&D = Research and Development Expense (DATA46)
Cash&STI = Cash and Short-Term Investments (DATAl)

Ideation Personnel Centralization

The second of three innovation-focused resources studied here, this variable
indicates the level of centralization of a ﬁrm’s innovation efforts. Similar to the
Herﬁndahl index, ideation personnel centralization is measured as the percentage of a
ﬁrm’s registered innovations completed by its top 4 inventors. This variable is drawn
from a proprietary innovation-focused database based on data from the United States

Patent and Trademark Ofﬁce (USPTO).

69

Overall Innovation Creativity

The third of three innovation-focused resources in this study, the measurement of
a ﬁrm’s overall innovation creativity reﬂects the breadth of a ﬁrm’s innovation efforts.
Based on data provided by the USPTO to a proprietary innovation-focused database, the

creativity of an individual innovation registered by a ﬁrm is calculated as:
. . "i 2
Creatlvrtyi — 1 — z}, s1.j

where Sij denotes the percentage of citations made by patent i belonging to patent class j
from n,- patent classes.

For analysis at the level of the ﬁrm, the mean of this variable was taken from a
ﬁrm’s complete stock of registered innovations to determine the overall creativity of a

ﬁrm’s innovation efforts.

Customer Satisfaction

Reported on a scale of O to 100, this ﬁrst measure of Marketing Equity is an
overall indication of customer satisfaction drawn from proprietary data compiled by the
American Customer Satisfaction Index (ACSI). This measure is a function of perceived

quality, customer expectations, and perceived value among consumers.

Brand Equity

The second measure of Marketing Equity in this study, brand equity is drawn
from a consumer-focused proprietary database. This measure is reported on a scale of 0
to 100. For this study, brand equity is considered a function of familiarity, brand

expectations, trust, distinctiveness, purchase intent, and quality.

70

Corporate Reputation

Generally reported on a scale of 0 to 10, this third measure of Marketing Equity is
drawn from executives, directors, and securities analysts knowledgeable about their
specialized industries. The measure of corporate reputation is considered a function of a
ﬁrm’s innovativeness, ﬁnancial soundness, employee talent, corporate asset utilization,
long-term investment value, social responsibility, management quality, and product or

service quality.

Return on Assets (ROA)
The ﬁrst of three ﬁnancial performance measures, ROA measures the general
level of a ﬁrm’s overall ﬁnancial success. Based on data drawn from the WDRS

database, the calculation used is:

ROA = N1 / TA
where
ROA = return on assets
N1 = Net Income (DATA172)
TA = Total Assets (DATA6)
Altman’s Z

The second of three ﬁnancial performance variables in this study, Altman’s Z is a
measure used by some banking and lending institutions to rate the overall ﬁnancial risk of

a ﬁrm. However, contrary to other ﬁnancial performance measures used, this variable is

71

inversely related to ﬁnancial health. Drawn from the WDRS database, the following

calculation was used:

where

Tobin’s Q

AZ = ((WC/TA) * 1.2)
+ ((RE / TA) * 1.4)
+ ((EBIT / TA) * 3.3)
+ ((MVE / TL) * 0.6)
+ ((Sales / TA) * 0.999)

AZ = Altman’s Z

WC = Working Capital (DATA179)

TA = Total Assets (DATA6)

RE = Retained Earnings (DATA36)

EBIT = Earnings Before Income Taxes (or, Operating Income Before
Depreciation) (DATA13)

MVE = Market Value of Equity (or, Total Stockholders’ Equity)
(DATA216)

TL = Total Liabilities (DATA181)

Sales = Net Sales (DATA12)

The third of three ﬁnancial performance variables studied here, Tobin’s Q is

distinct from the conceptual domain of secured intellectual property. Rather than a

tangible measure of a ﬁrm’s intangibles as managerially reported, Tobin’s Q is used as a

measure that ﬁnancial markets utilize to assess the overall present and future value of a

fn'rn’s tangibles and intangibles. Therefore, the following calculation was used with data

from the WRDS database:
TQ = (TSE + CL + LTD + DT + Intangs) / TA
where
TQ = Tobin’s Q
TSE = Total Shareholder Equity (or, Total Stockholders’ Equity)
(DATA216)

CL = Current Liabilities (DATAS)

72

LTD = Long-Term Debt (DATA9)
DT = Deferred Taxes (DATA74)
Intangs = Intangibles (DATA33)
TA = Total Assets (DATA6)

INDEX OPERATIONALIZATION
For additional analysis in this study, indices were created for four variables to test
possible overall inﬂuences in the model. Each component of the resource groups

mentioned below was standardized to minimize confounding measurement effects.

Customer-focused Resources
The ﬁrst of three categories of cross-functional marketing resources, customer-
focused resources was measured as the standardized average of a ﬁrm’s BZB marketing

expenditures, B2C marketing expenditures, and secured intellectual property.

Supply Chain-focused Resources
The second of three categories of cross-functional marketing resources, supply
chain-focused resources was measured as the standardized average of a ﬁrm’s sourcing

attentiveness, inventory readiness, and production capacity.

Innovation-focused Resources
The third of three categories of cross-functional marketing resources, innovation-
focused resources was measured as the standardized average of a firm’s discovery

expenditures, ideation personnel centralization, and overall innovation creativity.

73

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Marketing Equity

The only overall measure of marketing performance in this study, two different
approaches to measuring Marketing Equity were used. First, Marketing Equity was
measured as the standardized average of a ﬁrm’s customer satisfaction, brand equity, and
corporate reputation. Second, Marketing Equity was measured as a trended standardized

average of these three components.

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CHAPTER FIVE
RESULTS
“Always listen to experts. They will tell you what
cannot be done and why. Then do it. ”
— Robert Heinlein (1907-1988)

CROSS-FUNCTIONAL MARKETING RESOURCES AND MARKETING
EQUITY
Customer-focused Resources and Customer Satisfaction

This study’s results indicate that B2C marketing expenditures inﬂuences customer
satisfaction (8:0.268, p-value S 0.001) in the overall sample, thus supporting Hlb.
However, H1, and me were not supported in the overall sample. Still, both B2C
marketing expenditures (3:0.329, p-value S 0.01) and secured intellectual property
(B=0.219, p-value S 0.10) were found to influence customer satisfaction in high
technology industries.

An index of customer-focused resources was formed based on the standardized
measures of each individual customer-focused resource. This index was found to have an
inﬂuence on customer satisfaction in the overall sample (3:0.100, p-value S 0.05). Also,
customer-focused resources were found to inﬂuence customer satisfaction in a combined
sub-sample of companies in stable and low technology industn'es combined (B=0.197, p-
value S 0.001). Furthermore, this inﬂuence appears to be particularly inﬂuential in low

technology industries (8:0.223, p-value 5 0.001).

77

Table 3: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Components: Overall Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

OVERALL Customer Brand Equity Corporate
SAMPLE Satisfaction Reputation

B28 Marketing Expenditures 0.104 0.071 -0.076
B2C Marketing Expenditures 0268““ 0.157“ -0.082
Secured Intellectual PrgenL 0.121 0.028 0.091
Sourcing Attentiveness 0159* 0.073 O.324****
Inventory Readiness 0.117 -0.126 0.113
Production Capacity 0.061 -0.082 0157*
Discovery Expenditures 0031 0143* -0.121
Ideation Personnel 0020 0.038 -0.010
Centralization
Overall Innovation 0.018 0.147** -0.172**
Creativity
Sales_lg10 0.134 0.373**** 0.256***
Adjusted R2 0.123**** 0.145**** 0.148****
Observations 160 160 153

 

an“ _ p-value 5 0.001 (two-sided); *** - p-value 5 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p—value S 0.10 level (two-sided)

 

Corporate

 

 

 

 

 

 

 

OVERALL Customer Brand Equity
SAMPLE Satisfaction Reputation

Customer-focused resources 0.100** 0.031 0.058
and capabilities
Supply chain-focused —0.033 -0.041 0.053
resources and capabilities
Innovation-focused —0.052 -0.004 -0.053
resources and capabilities
Sales_lg10 0.107 0.223**** 0.225****
Adjusted R2 0.013*** o.045**** 0.053****
Observations 693 693 627

 

 

 

 

 

 

**** - p-value 5 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);
* - p-value _<_ 0.10 level (two-sided)

78

Table 4: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Components: High Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

HIGH Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
B2B Marketing Expenditures 0035 -0.042 -0.075
B2C Marketirgﬂrpenditures 0.329*** 0.087 -0.212*
Secured Intellectual Pr0perty 0219* 0.083 -0.001
Sourcing Attentiveness 0.080 -0.112 0.304"
Inventory Readiness -0.06l -0.l94 0.128
Production Capacity -0.127 0.067 0.050
Discovery Expenditures 0146 -0.253** -0. 197*
Ideation Personnel 0153 -0.097 0.012
Centralization
Overall Innovation 0.016 -0.031 -0.203*
Creativity
Sales_lg10 -0.061 0.260" 0.176
Adjusted R2 0.118** 0.034 0.145"
Observations 78 78 76

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p—value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

HIGH Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
Customer-focused resources 0.023 0.042 0.019
and capabilities
Supply chain-focused 0.030 -0.066 0.102
resources and capabilities
Innovation-focused -0.042 -0.035 -0.107
resources and capabilities
SaleLngo -0.001 0.204*** 0.150M
Adjusted R2 0.015 0.030** 0.030**
Observations 230 230 205

 

**** - p-value 5 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - pcvalue S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

79

 

 

Table 5: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Components: Stable & Low Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE & LOW Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
BZB Marketing EQenditures 0.168 0.154 -0.122
B2C Marketing Expenditures 0.092 0.201* 0.060
Secured Intellectual Property 0.075 ~0.015 0.175
Sourcing Attentiveness 0.33 1** 0.205 0.350**
Inventory Readiness 0.169 -0.108 0.122
Production Capacity 0.158 -0.131 -0.257**
Discovery Expenditures -0.003 -0. 140 -0.118
Ideation Personnel 0.000 0.138 0.014
Centralization
Overall Innovation 0016 0.261 *** -0. 167
Creativity
Sales_lg10 0.298*** 0.421**** 0.297**
Adjusted R2 0.255**** 0.338**** 0.120**
Observations 82 82 77

 

**** - p-value 5 0.001 (two-sided); *** - p—value 5 0.01 (two-sided); ** - p-value 5 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

STABLE & LOW Customer Brand Equity Corporate
TECHNOLOGY Satisfaction Reputation

Customer-focused resources 0.197**** 0.039 0083*
and capabilities
Supply chain—focused -0.052 -0.041 0.042
resources and capabilities
Innovation-focused -0.058 0.023 -0.01 1
resources and capabilities
Salesglo 0.169**** 0.239**** 0.263****
AgiUSted R2 0.068**** 0.049**** 0.064#***
Observations 463 463 422

 

**** - p-value 5 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

80

 

 

Table 6: Relationship Between Cross-Functional Marketing Resources and

Marketing Equity Components: Stable Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
B2B Marketing Expenditures 0238 -0.058 -0.l23
B2C MarketingExpenditures 0.131 0.541*** 0.265
Secured Intellectual Property 0004 -0.121 -0.068
Sourcing Attentiveness 0.160 -0.142 0.161
Inventory Readiness 0145 -0.416** 0032
Production Capacity 0204 0.028 -0.135
Discovery Expenditures 0.060 0.069 0.004
Ideation Personnel 0.299 0.161 0.330
Centralization
Overall Innovation 0.188 0.408** 0.01 1
Creativity
Sales_lg10 0.608*** 0343* 0.502”
Adjusted R’- 0224* 0.347** 0235*
Observations 37 37 36

 

**** - p-value 5 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p—value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

STABLE Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
Customer-focused resources 0.034 0.160** 0.127 *
and capabilities
Supply chain-focused -0.127* -0.105* 0.073
resources and capabilities
Innovation-focused -0.042 -0.068 0.035
resources and caJJabilities
Sales_lg10 0.099 0.343**** 0.386****
Adjusted R2 0019* 0.151**** 0.123****
Observations 244 244 218

 

**** - p-value 5 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p—value S 0.10 level (two—sided)

81

 

 

Table 7: Relationship Between Cross-Functional Marketing Resources and

Marketing Equity Components: Stable Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LOW Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
B23 Marketing Expenditures 0.194 0338* -0.063
B2C Marketing Expenditures 0.113 0.120 -0.107
Secured Intellectual Property 0.160 0.066 0.371 *
Sourcing Attentiveness 0.327 0.286 0.306
Inventory Readiness 0294* 0.043 0.250
Production Capacity 0.063 -0.217 -0.317*
Discovery Expenditures 0008 -0.333** 0124
Ideation Personnel 0061 0.195 -0.183
Centralization
Overall Innovation -0. l 13 0.124 -0.269
Creativity
Sales__lg10 0.319** 0.520**** 0.170
Adpsted RZ 0.261 ** 0.424**** 0.031
Observations 45 45 41

 

**** - p-value _<_ 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

LOW Customer Brand Equity Corporate

TECHNOLOGY Satisfaction Reputation
Customer-focused resources 0.223**** -0039 0.047
and capabilities
Supply chain-focused 0.290 0.140" 0.042
resources and capabilities
Innovation-focused -0.035 0. 104 -0.049
resources and capabilities
Sales_l&10 0.247**** 0.186*** 0.159**
Adjusted RT 0.104**** 0.045*** 0.016
Observations 219 219 204

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* — p—valuc S 0.10 level (two-sided)

82

 

 

Supply Chain-focused Resources and Customer Satisfaction

This study’s results indicate that only de is partially supported in the overall
sample. Sourcing attentiveness was found to inﬂuence customer satisfaction (3:0.159, p-
value 5 0.10). However, H1e and H 1f were not supported. Still, the inﬂuence of sourcing
attentiveness appears more prominently in a combined sub-sample of ﬁrms in stable and
low technology industries (13:0.331, p-value S 0.05). Also, inventory readiness has a
partial inﬂuence on customer satisfaction in low technology industries (13:0.294, p-value
S 0.10)

Additionally, an index of supply chain-focused resources was formed based on
the standardized measures of each individual supply chain-focused resource. This index
was found to slightly inﬂuence customer satisfaction in the stable technology sub-sample

(B=-0. 127, p-value S 0.10).

Innovation-focused Resources and Customer Satisfaction

The study’s results indicate that none of the measures used to test the inﬂuence of
innovation-focused resources on customer satisfaction were statistically signiﬁcant. Thus,
H1 g, th, and H“ were not supported in the overall sample. In addition, no inﬂuences

were found in the sub-sample tests performed.

Customer-focused Resources and Brand Equity
The results indicate that B2C marketing expenditures inﬂuence brand equity in
the overall sample (13:0. 157, p-value _<_ 0.05), thus supporting sz. H2, and Hzc were not

supported in the overall sample. Still, B2C marketing expenditures has a mild inﬂuence

83

on brand equity in the stable and low technology sub-sample (3:0.201, p-value .<_ 0.10).
This relationship appears more clearly in the stable technology sub-sample (8:0.541, p-
value 5 0.01).

Additionally, the customer-focused resources index was not found to inﬂuence
brand equity in the overall sample. However, this relationship was found to be

statistically signiﬁcant in the stable technology sub-sample (3:0.160, p-value S 0.05).

Supply Chain-focused Resources and Brand Equity

Generally, little evidence was found in the overall sample for the relationships
posited between each supply chain-focused resource and brand equity. Therefore, H2d,
H2.” and H2f are rejected in this model. However, a negative relationship between
inventory readiness and brand equity was found in the stable technology sub-sample (B:-
0.416, p-value S 0.05). 8

Interestingly, the supply chain-focused resources index was found to have a
negative inﬂuence on brand equity among stable technology ﬁrms (B=-0.105, p-value S
0.10), but a positive inﬂuence as found in the low technology industry sub-sample

(B=0.140, p-value S 0.05).

Innovation-focused Resources and Brand Equity

This study’s results indicate a negative inﬂuence of discovery expenditures (8:-
0.143, p-value S 0.10) and positive inﬂuence of overall innovation creativity (B=O.147, p-
value _<_ 0.05) in the overall sample, thus supporting H25 and presenting contradictory

evidence for H23. Little evidence was found to support H2h.

84

In fact, the negative relationship between discovery expenditures and brand equity
were quite evident in the high technology (B=-0.253, p-value S 0.05) and low technology
(B=O.333, p-value S 0.05) sub-samples. Meanwhile, support for H2, was found among
stable and low technology ﬁrms (B=0.26l, p-value S 0.01) and was particularly strong in

the stable technology sub-sample (B=0.408, p-value S 0.05).

Customer-focused Resources and Corporate Reputation

The study did not ﬁnd any support for H33, H3b, or H3c in the overall sample.
However, a mild negative relationship was found between B2C marketing expenditures
and corporate reputation among high technology ﬁrms (B=-0.212, p-value S 0.10). In
addition, seemed intellectual property seemed to inﬂuence corporate reputation in the low
technology sub—sample (3:0.371, p-value S 0.10).

The customer-focused resources index created for this study was found to mildly
inﬂuence corporate reputation in the stable and low technology sub-sample (3:0.083, p-
value S 0.10). Additionally, this inﬂuence appears most prominently among stable

technology companies (13:0.127, p—value S 0.10).

Supply Chain-focused Resources and Corporate Reputation

The study found that sourcing attentiveness inﬂuences corporate reputation
(3:0.324, p—value S 0.0001), thus supporting H3d. Additionally, production capacity was
found to negatively inﬂuence corporate reputation (B=-0.157, p-value S 0.10), thus

partially contradicting H39 Little evidence was found to support H36.

85

Sourcing attentiveness appeared to inﬂuence corporate reputation in both the high
technology (8:0.304, p-value S 0.10) and stable and low technology (B=0.350, p-value S
0.10) sub-samples. Also, the negative relationship between production capacity and
corporate reputation was detected in the stable and low technology sub-sample (B=-0.257,
p-value S 0.05). In fact, it appears this relationship was most inﬂuenced by the low

technology sub-sample (8:0.371, p-value S 0.10).

Innovation-focused Resources and Corporate Reputation

Findings from this study show that overall innovation creativity has a negative
inﬂuence on corporate reputation (B=-0.l72, p—value S 0.05), thus contradicting H3i. No
support was found for H33 or H3h. Also, negative inﬂuences of both discovery
expenditures (B=-0.197, p-value S 0.10) and overall innovation creativity (B=-0.203, p-
value S 0.10) on corporate reputation were found in the high technology industry sub-

sample.

86

Table 8: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Index: Overall Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

OVERALL Marketing Marketing
SAMPLE Etpiity, Avg. Equity, Trend

B2B Marketing Expenditures 0.088 0.099
BZC Marketing Expenditures 0.287**** 0.250****
Secured Intellectual Property 0.076 0.045
Sourcing Attentiveness 0.160* 0.068
Inventory Readiness -0.039 -0. 150*
Production Capacity 0.024 -0.038
Discovery Expenditures -0. 140* -0. 147*
Ideation Personnel 0017 0.021
Centralization
Overall Innovation 0.023 0.057
Creativity
Sales’ngO 0.362**** 0347““
Adjusted R2 0.212**** 0.163***
Observations 160 160

 

 

 

“an: _ p-value g 0,001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

OVERALL Marketing Marketing
SAMPLE Equity, Atgg. Equity, Trend

Customer-focused resources 0.111*** 0.146****
and capabilities
Supply chain-focused 0.013 0.041
resources and capabilities
Innovation-focused -0.068* -0.065*
resources and capabilities
Sales_l£L10 0.279**** 0.138****
Adjusted RT 0.080**** 0.032****
Observations 693 693

 

**** - p-value S 0.001 (two—sided); *** - p—value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

87

 

 

Table 9: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Index: High Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

HIGH Marketing Marketing

TECHNOLOGY Equity, Av& Equity, Trend
B2B Marktm Expenditures 0034 0.038
BZC Marketing Expenditures 0.181 0.096
Secured Intellectual Property 0.084 0.043
Sourcing Attentiveness -0.017 0151
Inventory Readiness -0.125 0207
Production Capacity 0.033 0.098
DiscoverLExpenditures -0.286** -0.232*
Ideation Personnel 0126 -0.102
Centralization
Overall Innovation 0069 -0.047
Creativity
Sales_lg10 0223* 0241*
Adjusted R2 0.036 0.020
Observations 78 78

 

 

*akakak - p—value g 0,001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p—value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

HIGH Marketing, Marketing

TECHNOLOGY Equity, Avg. Equity, Trend
Customer-focused resources 0.028 0.149**
and capabilities
Supply chain-focused 0.006 -0.067
resources and capabilities
Innovation-focused -0.064 -0.1 15*
resources and capabilities
Sales£10 0.218*** 0.070
Adjusted R2 0.035** 0022*
Observations 230 230

 

**** - p—value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

88

 

 

Table 10: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Index: Stable & Low Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE & LOW Marketing Marketing

TECHNOLOGY Equity, Agg. Equity, Trend
B2B Marketing Expenditures 0.115 0.103
BZC Marketing Expenditures 0.362**** 0.388****
Secured Intellectual Property 0.061 0.067
Sourcing Attentiveness 0.357*** 0.310***
Inventory Readiness -0.029 -0.1 19
Production Capacity 0.065 -0.094
Discovery Expenditures 0092 -0.157*
Ideation Personnel 0.061 0.126
Centralization
Overall Innovation 0.074 0.129
Creativity
Salesﬂlglo 0.428**** 0.391****
Adjusted R2 0.503**** 0.488****
Observations 82 82

 

 

 

um»: - p.va]ue g 0,001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

STABLE & LOW Marketing Marketing
TECHNOLOGY Equity, Avg Equity, Trend
Customer-focused resources 0.232**** 0.145***
and capabilities
Supply chain-focused 0.027 0.087*
resources and capabilities
Innovation-focused —0.069 -0.019
resources and capabilities
Sales_lg10 0.308**** 0.190****
Adjusted R2 0.138**** 0.046****
Observations 463 463

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

89

 

 

Table 11: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Index: Stable Technology Mini-Sample

‘

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE Marketing Marketing

TECHNOLOGY Equity, Avg. Equity, Trend
B2B Marketig Expenditures 0135 -0.005
B2C Marketig Expenditures 0.442** 0.611***
Secured Intellectual Property —0.1 15 -0.139
Sourcing Attentiveness —0.026 0079
Inventory Readiness -0.253 -0.366**
Production Capacity 0.004 0036
Discovery Expenditures 0.040 0.022
Ideation Personnel 0.243 0.254
Centralization
Overall Innovation 0308* 0287*
Creativity
Sales__lg10 0.546*** 0351*
Adjusted R2 0.335** 0.394***
Observations 37 37

 

 

an“ - p-value g 0,001 (two—sided); *** - p—value S 0.01 (two-sided);
an: _ p-valuc g 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

STABLE Marketing Marketing

TECHNOLOGY Equity, Avg. Equity, Trend
Customer-focused resources 0.134" 0.162**
and capabilities
Supply chain-focused -0.006 0.119*
resources and capabilities
Innovation-focused -0.026 -0.012
resources and capabilities
Sales_l&0 0.337**** 0243“"
Adjusted R2 0.105*** 0.054***
Observations 244 244

 

 

 

 

**** - p-value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided);
** - p—value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

9O

 

Table 12: Relationship Between Cross-Functional Marketing Resources and
Marketing Equity Index: Low Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LOW Marketing Marketing

TECHNOLOGY Equity, Avg. Equity, Trend
82B Marketing Expenditures 0.075 0.042
B2C Marketing Expenditures 0410““ 0.417 ****
Secured Intellectual Property 0.128 0.097
Sourcing Attentiveness 0.455**** 0.412***
Inventory Readiness 0.025 0108
Production Capacity 0103 -0.226**
DiscoverLExpenditures -0.045 -0. 151
Ideation Personnel 0.020 0.110
Centralization
Overall Innovation 0087 0.006
Creativity
Sales_lg10 0.494**** 0.500****
Adjusted R2 0.687**** 0.631****
Observations 45 45

 

 

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

LOW Marketing Marketing

TECHNOLOGY Equity, Avg. Equity, Trend
Customer-focused resources 0.219**** 0.113
and capabilities
Supply chain-focused 0.122* 0.091
resources and capabilities
Innovation-focused -0.073 —0.017
resources and capabilities
Sales_lg10 0.304**** 0.159**
Adjusted R2 0.159**** 0.030**
Observations 219 219

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
** - pevalue S 0.05 (two-sided); * - p—value S 0.10 level (two-sided)

91

 

 

Customer-focused Resources and Marketing Equity

B2C marketing expenditures was found to inﬂuence both the averaged Marketing
Equity measure (B=0.287, p-value S 0.001) and the trended Marketing Equity measure
(B=0.250, p-value S 0.001) in the overall sample, thus showing the relative stability of
this relationship. However, these relationships were detected in the stable and low
technology sub-sample (Marketing Equity average: B=O.362, p-value S 0.001; Marketing
Equity trend: B=O.388, p-value S 0.001). The relationship between B2C marketing
expenditures and Marketing Equity appeared more prominently among low technology
ﬁrms (Marketing Equity average: B=0.410, p-value S 0.001; Marketing Equity trend:
B=0.417, p-value S 0.001), but it also was found among stable technology ﬁrms
(Marketing Equity average: B=0.442, p-value S 0.05; Marketing Equity trend: B=0.611,
p-value S 0.01). I

Additionally, the customer-focused resources index used above was found to
inﬂuence the Marketing Equity average (B=0.111, p-value S 0.01) and the Marketing
Equity trend (B=0.146, p-value S 0.001) in the overall sample. Among high technology
ﬁrms, customer-focused resources inﬂuenced this study’s trended Market Equity variable
(3:0.149, p-value S 0.05). This index was found to inﬂuence both variations of
Marketing Equity among stable and low technology ﬁrms (Marketing Equity average:
B=0.232, p-value S 0.001; Marketing Equity trend: B=0.145, p-value S 0.01). Similar
results were found in a more detailed analysis of only stable technology ﬁrms (Marketing

Equity average: 3:0.134, p-value S 0.05; Marketing Equity trend: B=0.162, p-value S

92

0.05). However, in the low technology industry sub-sample, only the average Marketing

Equity measure was inﬂuenced (B=0.219, p—value S 0.001).

Supply Chain-focused Resources and Marketing Equity

Sourcing attentiveness was found to somewhat inﬂuence the averaged Marketing
Equity measure in the overall sample (3:0.160, p-value S 0.10). Additionally, inventory
readiness was found to have a partial negative inﬂuence on the trended Marketing Equity
measure (B=-0.150, p-value S 0.10) in the full sample. Sourcing attentiveness had a
strong inﬂuence in the stable and low technology industries (Marketing Equity average:
B=O.357, p-value S 0.01; Marketing Equity trend: B=O.310, p-value S 0.01) as well as in
the more exact sub-sample of low technology ﬁrms (Marketing Equity average: B=0.455,
p-value S 0.001; Marketing Equity trend: B=0.417, p-value S 0.001). Meanwhile,
inventory readiness was found to only inﬂuence the trended Marketing Equity measure in
the stable technology sub-sample (B=-0.366, p-value S 0.05).

The supply chain-focused resources index was found to inﬂuence the trended
Marketing Equity measure among stable and low technology ﬁrms (B=0.087, p-value S
0.10). This was also apparent in the stable technology industry sub-sample (B=0.119, p-
value S 0.10). Interestingly, this index was found to inﬂuence the averaged Marketing

Equity measure among low technology ﬁrms (13:0. 122, p-value S 0.10).

Innovation-focused Resources and Marketing Equity

Discovery expenditures was found to have a slight negative inﬂuence on both

measures of Marketing Equity in the overall sample (Marketing Equity average: B=-

93

Vader-tr]

0.140, p-value S 0.10; Marketing Equity trend: B=-0.147, p-value S 0.10). This
relationship was particularly prevalent among high technology ﬁrms (Marketing Equity
average: B=-0.286, p-value S 0.05; Marketing Equity trend: B=-0.232, p—value S 0.10).
Additionally, discovery expenditures was found to inﬂuence the trended Marketing
Equity measure in the stable and low technology sub-sample (B=-0.157, p-value S 0.10).
In the overall sample, the innovation-focused resources index had a mild negative
inﬂuence on both Marketing Equity measures (Marketing Equity average: B=-0.068, p-
value S 0.10; Marketing Equity trend: B=-0.065, p-value S 0.10). This negative
relationship was also detected on the trended Marketing Equity measure among high

technology ﬁrms (B=—0.115, p-value S 0.10).

CROSS-FUNCTIONAL MARKETING RESOURCES AND FINANCIAL
PERFORMANCE i
Customer-focused Resources and ROA

The current study indicates that B2C marketing expenditures mildly inﬂuence
ROA in the overall sample (B=0.130, p-value S 0.10). This relationship was also detected
in the stable technology industry sub-segment (B=O.327, p-value S 0.10).

The customer-focused resources index was found to inﬂuence ROA in the overall
sample (B=0.106, p-value S 0.05). This relationship was also detected in the high
technology (3:0.124, p-value S 0.10) and stable technology (3:0.259, p-value S 0.001)

sub-samples.

94

Table 13: Relationship Between Cross-Functional Marketing Resources and
Financial Performance: Overall Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

OVERALL Return on Altman’s Z Tobin’s Q
SAMPLE Assets (ROA)

BZB Marketing Expenditures 0.091 0.201** 0.171**
BZC Marketing Expenditures 0130* 0.075 0.078
Secured Intellectual Property 0.074 0.014 0.421****
Sourgg Attentiveness 0.362**** 0.120 0.060
Inventory Readiness 0.096 0.066 0.248****
Production CapaciLy -0.083 -0.276**** 0035
Discovery Expenditures 0066 -0.156** 0.103
Ideation Personnel 0.032 0.115 -0.024
Centralization
Overall Innovation 0082 -0.028 -0.161**
Creativity
Sales_lﬂ) 0.161** -0.040 .0122
Apjusted R2 0.176**** 0.172**** 0.260****
Observations 160 160 160

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

OVERALL Return on Altman’s Z Tobin’s Q
SAMPLE Assets (ROA)

Customer-focused resources 0.106** 0.089** 0.387****
and capabilities
Supply chain-focused -0.004 -0.201**** -0.104***
resources and capabilities
Innovation-focused 0.019 -0.030 -0.066*
resources and capabilities
Sales_lg10 -0.019 0.034 -0. 175****
Adjusted R2 0006* 0.049**** 0.226****
Observations 613 613 613

 

**** - p-value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

95

 

 

Table 14: Relationship Between Cross-Functional Marketing Resources and
Financial Performance: High Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

HIGH Return on Altman’s Z Tobin’s Q

TECHNOLOGY Assets (ROA)
B2B Marketing Expenditures 0.195 0.136 0.065
B2C Marketing Expenditures 0.031 0.040 0.024
Secured Intellectual Property 0.159 -0.041 0.461****
Sourcing Attentiveness 0.305** 0.168 0.081
Inventory Readiness —0.047 -0.022 0202"
Production Capacity 0060 -0.257** -0.085
Discovery Expenditures 0065 -0.151 0.141
Ideation Personnel 0035 0.041 0164*
Centralization
Overall Innovation 0.075 0.136 -0.212**
Creativity
Sales_lg10 0.187 -0001 -0.321****
Adjusted R2 0216* 0.087* 0.436****
Observations 78 78 78

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two—sided)

 

 

 

 

 

 

 

 

 

 

 

HIGH Return on Altman’s Z Tobin’s Q

TECHNOLOGY Assets (ROA) .
Customer-focused resources 0.124* 0.061 0.309****
and capabilities
Supply chain-focused 0.026 -0.047 0.091
resources and capabilities
Innovation-focused 0.022 -0.021 -0.047
resources and capabilities
Sales_lg10 -0.043 0.108 -0.266****
Adjusted RT 0.003 .0002 0.205****
Observations 212 212 212

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

96

 

 

Table 15: Relationship Between Cross-Functional Marketing Resources and

Financial Performance: Stable & Low Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE & LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
BZB MarketingExpenditures -0.058 0.312** 0.137
BZC Marketing Expenditures 0.150 0.101 0.092
Secured Intellectual Property 0.108 0.103 0.398****
Sourcirg Attentiveness 0.470**** 0.048 0.074
Inventory Readiness 0216* 0.131 0.270**
Production Capacity -0.130 -0.300*** 0.037
Discovery Expenditures -0.87 -0.201* 0.064
Ideation Personnel 0.021 0.157 -0.065
Centralization
Overall Innovation -0. 186* -0.181 * -0. 159
Creativity
Sales_lg10 0.124 -0.081 -0.0 l 2
Adjusted R2 0.201*** 0.217*** 0.176***
Observations 82 82 82

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

STABLE & LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Customer-focused resources 0.044 0.159**** 0.460****
and capabilities
Supply chain-focused -0.092* 0336"" -0.104**
resources and capabilities
Innovation-focused 0.012 -0.030 -0.041
resources and capabilities
Sales_lg10 0.054 —0.043 -0.144****
Adjusted R2 0.004 0.160**** 0279"“
L Observations 401 401 401

 

 

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p—value S 0.10 level (two-sided)

97

 

 

Table 16: Relationship Between Cross-Functional Marketing Resources and
Financial Performance: Stable Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE Return on Altman’s Z Tobin’s Q

TECHNOLOGY Assets (ROA)
B2B Marketing Expenditures 0.160 0.440*** 0.056
B2C Marketing Expenditures 0327* 0327* 0.169
Secured Intellectual Property 0.017 -0.003 0.631***
Sourcing Attentiveness 0.201 -0.019 0203
Inventory Readiness 0.167 0.181 0.078
Production Capacity 0.092 -0.020 0.021
Discovery Expenditures -0.107 0175 0.002
Ideation Personnel -0.047 0.048 0.287
Centralization
Overall Innovation -0.514*** -0.326** -0.503***
Creativity
Sales_lg10 -0.l69 -0.321* 0.242
Adjusted R2 0.362*** 0.482**** 0.262**
Observations 37 37 37

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p—value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

STABLE Return on Altman’s Z Tobin’s Q

TECHNOLOGY Assets (ROA)
Customer-focused resources 0.259**** 0.309**** 0.459****
and capabilities
Supply chain-focused -0.073 -0.324**** -0.060
resources and capabilities
Innovation-focused -0.005 -0.085 -0.048
resources and capabilities
Sales_lg10 0.034 -0.137** -0.l92***
Adjusted R2 0.064*** 0.290**** 0.286****
Observations 209 209 209

 

**** - p-value 5 0.001 (two-sided); *** - p—value s 0.01 (two-sided); ** - p-value S 0-05 (two-sided):

* - p-value S 0.10 level (two-sided)

98

 

 

Table 17: Relationship Between Cross-Functional Marketing Resources and
Financial Performance: Low Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LOW Return on Altman’s Z Tobin’s Q

TECHNOLOGY Assets (ROA)
B2B Marketing Expenditures 0335 0.157 -0.057
B2C Marketing Expenditures 0.113 -0.037 0.036
Secured Intellectual Property 0.133 0.042 0.368“
Sourcing Attentiveness 0735**** 0.142 0.139
Inventory Readiness 0.204 -0.060 0.234
Production Capacity 0110 -0.324* 0.015
DiscoverLEmnditures -0.037 -0. 181 0279*
Ideation Personnel 0019 0.110 -0.355**
Centralization
Overall Innovation 0029 -0.121 -0.160
Creativity
Sales_lg10 0269* 0.043 0057
Adjusted R2 0.273** 0021 0.331***
Observations 45 45 45

 

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p—value S 0.10 level (two-sided)

 

 

 

 

 

 

 

 

 

 

 

LOW Return on Altman’s Z Tobin’s Q

TECHNOLOGY Assets (ROA)
Customer-focused resources -0119 -0.015 0.47 8****
and capabilities
Supply chain-focused 0.010 -0.237**** 0.010
resources and capabilities
Innovation-focused 0.029 0.019 -0.025
resources and capabilities
Sales_lg10 0127* 0.1 15 0003
Adjusted R2 0.012 0.047** 0.217****
Observations 192 192 192

 

**** - p-value S 0.00] (two-sided); *** - p—value S 0.01 (two-sided); ** - p-value S 0.05 (two-sided);

* - p-value S 0.10 level (two-sided)

99

 

 

 

Customer-focused Resources and Altman’s Z

Findings also indicate that B2B marketing expenditures positively inﬂuence
Altman’s Z in the overall sample (8:0.201, p-value S 0.05). Similar ﬁndings were found
in the stable and low technology (B=O.312, p-value S 0.05) and stable technology
(B=0.440, p-value S 0.01) sub-segments. Also, ﬁndings show that B2C marketing
expenditures positively inﬂuence Alunan’s Z among stable technology ﬁrms (B=O.327, p-
value S 0.10).

The customer-focused resources index was found to positively inﬂuence Altman’s
Z in the overall sample (B=0.089, p-value S 0.05). This relationship was also found in the
stable and low technology (13:0159, p-value S 0.001) and the stable technology

(B=O.309, p-value S 0.001) sub-segments.

Customer-focused Resources and Tobin’s Q

This study’s ﬁndings indicate that both 32B marketing expenditures and secured
intellectual property inﬂuence Tobin’s Q in the overall sample (32B marketing
expenditures: B=0.171, p-value S 0.05; secured intellectual property: 8:042], p-value S
0.001). The inﬂuence of secured intellectual property on Tobin’s Q is consistent across
the many sub-samples tested. Findings among high technology (B=O.461, p-value S
0.001), stable and low technology (B=O.398, p-value S 0.001), stable technology
(3:063 l, p-value S 0.01), and low technology (B=O.368, p-value S 0.05) ﬁrms indicates

the wide-reaching inﬂuence of secured intellectual property on a ﬁrm’s Tobin’s Q.

100

The customer-focused resources index was found to inﬂuence Tobin’s Q in the
overall sample (B=O.387, p-value S 0.001). Likewise, this relationship was found
consistently across this study’s high technology (B=O.309, p-value S 0.001), stable and
low technology (B=0.460, p-value S 0.001), stable technology (B=0.459, p-value S 0.01),

and low technology (B=0.478, p-value S 0.05) sub—segments.

Supply Chain-focused Resources and ROA

Interestingly, this study indicates that sourcing attentiveness has a positive
inﬂuence on ROA in the overall sample (B=O.362, p-value S 0.001). Similar results were
found for the high technology (13:0305, p-value S 0.05), stable and low technology
(B=0.470, p-value S 0.001), and low technology (13:0735, p-value S 0.001) sub-
segments. Additionally, a positive relationship between inventory readiness and ROA
was detected in the stable and low technology sub-sample (B=0.216, p-value S 0.10).

Contrary to expectations, the supply chain-focused resources index was found to
negatively inﬂuence ROA only in the stable and low technology sub-sample (B=-0.092,

p-value S O. 10).

Supply Chain-focused Resources and Altman’s Z

Production capacity was found to negatively inﬂuence Altman’s Z in the overall
sample (B=-0.276, p-value S 0.001). This relationship was also detected in the high
technology (B=-0.257, p-value S 0.05), stable and low technology (B=-0.300, p-value S

0.01), and low technology (B=-0.324, p-value S 0.10) sub—segments.

101

A negative relationship between the supply chain-focused resources index and
Altman’s Z was found in the overall sample (B=-0.201, p-value S 0.001). Additionally,
similar results were found in the stable and low technology sub-segments (B=-0.336, p-
value S 0.001) as well as some stable technology (B=-0.324, p—value S 0.001) and low

technology (B=-0.237, p-value S 0.001) ﬁrms.

Supply Chain-focused Resources and Tobin’s Q

In the overall sample, this study’s ﬁndings indicate that inventory readiness is
positively related to Tobin’s Q (B=0.248, p-value S 0.001). Similar results were found in
the high technology (13:0202, p-value S 0.05) and stable and low technology (B=0.270,
p-value S 0.05) sub-samples.

Interestingly, a negative relationship was found between the supply chain-focused
resources index and Tobin’s Q in the overall sample (B=-0.104, p-value S 0.001).
Additionally, this relationship was found in the stable and low technology sub-sample

(B=-O.104, p-value S 0.05).

Innovation-focused Resources and ROA

Overall innovation creativity was detected to have a negative inﬂuence on ROA
in the stable and low technology industry sub-segment (B=-0.186, p-value S 0.10). This
relationship was considerably stronger among stable technology ﬁrms (B=-0.514, p-value

S 0.01).

102

Innovation-focused Resources and Altman’s Z

This study’s ﬁndings indicate that a negative statistical relationship exists
between discovery expenditures and Altman’s Z in the overall sample (B=-0. 156, p-value
S 0.05). Also, this relationship was detected in the stable and low technology industry
sub-sample (B=-0.201, p-value S 0.10). Additionally, overall innovation creativity
appears to be related negatively with Altman’s Z in the stable and low technology
industry sub-sample (B=-0.181, p-value S 0.10). More precisely, this relationship appears

most prominently among stable technology ﬁrms (B=-0326, p-value S 0.05).

Innovation-focused Resources and Tobin’s Q

Findings indicate that overall innovation creativity has a negative inﬂuence on
Tobin’s Q in the overall sample (B=-0.161, p-value S 0.05). This relationship was found
in the high technology industry sub-sample (B=-0.212, p—value S 0.05) as well as among
stable technology ﬁrms (B=-0.503, p-value S 0.01). Also, discovery expenditures were
detected to have a positive inﬂuence on Tobin’s Q (8:0.279, p-value S 0.10) among low
technology ﬁrms. Additionally, a positive relationship was detected between ideation
personnel centralization and Tobin’s Q in the high technology sub-sample (B=0.164, p-
value S 0.10). Interestingly, a negative relationship was found between ideation personnel
centralization and low technology ﬁrms (B=-0.355, p-value S 0.05).

This study’s ﬁndings also show a mild negative relationship between the

innovation-focused resources index and Tobin’s Q (B=-0.066, p-value S 0.10).

103

MARKETING EQUITY AND FINANCIAL PERFORMANCE
As noted below, sufﬁcient evidence exists for marketing equity and its
components to mediate the relationship between cross-functional marketing resources

and ﬁnancial performance.

Table 18: Relationship Between Marketing Equity and Financial Performance:
Overall Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

OVERALL Return on Altman’s Z Tobin’s Q
SAMPLE Assets (ROA)
Customer 0.170**** 0.098“ 0.178****
Satisfaction
Brand Equity 0.130** 0.042 0013
Corporate 0.078 0.109** 0.020
Reputation
Sales_lg10 -0.033 -0.016 -0.224****
Adjusted R2 0.074**** 0.030*** 0.073***
Observations 562 562 562
**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S O. 10 level (two-sided)
OVERALL Return on Altman’s Z Tobin’s Q
SAMPLE Assets (ROA)
Marketing Equity, -0.081* 0.160**** 0.144****
Avg.
Sales_lg10 —0.022 -0.015 -0.273****
Adjusted R2 0005* 0.021*** 0.072****
Observations 613 613 613
**** - p-value S 0.00] (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
OVERALL Return on Altman’s Z Tobin’s Q
SAMPLE Assets (ROA)
Marketing Equity, 0059 0.067 0.093**
Trend
Sales pglo -0.036 0.018 -0.247****
Adjusted R2 0.002 0.002 0.061****
Observations 613 613 613

 

 

 

 

 

 

 

MM _ p-value 5 0,001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p—value S 0.05 (two-sided); * - pevalue S 0.10 level (two-sided)

104

Table 19: Relationship Between Marketing Equity and Financial Performance:
High Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

HIGH Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Customer Satisfaction 0.264**** 0.118 0.178**
Brand Equity 0.085 -0.005 -0.045
Corporate Reputation 0.084 0.200** 0.160**
Sales_lg10 0.054 0.116 -0.278****
Adjusted R2 0.128**** 0.071**** 0.132****
Observations 192 192 192
**** - p—value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided);
** - p—value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
HIGH Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Marketing Equity, 0.172** 0.164** 0.098
Avg.
Sales_lg10 -0.046 0.068 -0.373****
Adjusted R2 0026’” 0.027** 0.125****
Observations 212 212 212
**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
HIGH Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Marketing Equity, -0.128* 0.089 0111*
Trend
Sales_lg10 -0.075 0.097 0359““
Adjusted R2 0014* 0.009 0.128****
Observations 212 212 212

 

 

 

 

 

 

nu _ p-value g 0,001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

105

Table 20: Relationship Between Marketing Equity and Financial Performance:
Stable & Low Technology Sub-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE & LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)

Customer Satisfaction 0109* 0.113** 0.209****

Brand Equity 0.135** 0.067 0.018

Corporate Reputation 0083 0.049 -0.019

Sales_lg10 -0.073 -0.140*** -0.229****

Adjusted R2 0045**** 0.028*** 0072****

Observations 370 370 370

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);

** - p-value S 0.05 (two-sided); * - p—value S 0.10 level (two-sided)

STABLE & LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)

Marketing @ity, Avg. 0.193**** 0169“" 0.223****

Sales_lg10 0013 -0.116** -0261****

Adjusted R2 0.031**** 0.026*** 0.079****

Observations 401 401 401

**** - p-value S 0.001 (two-sided); *** - p-value S 0.01 (two-sided);

** - p.value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

STABLE & LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)

Marketing Equity, Trend 0147*” 0.046 0.111**

Sales_lg10 0.019 -0.074 -0.2l4****

Adjusted R2 0018*** 0.001 0046

Observations 401 401 401

 

 

 

 

**** - p-value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)

106

 

 

 

Table 21: Relationship Between Marketing Equity and Financial Performance:
Stable Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

STABLE Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Customer Satisfaction -0.080 0.104 0.054
Brand Equity 0.198** 0.178** 0160*
Corporate Reputation 0.224** -0.151 -0.060
Sales_lg10 -0. 121 -0. l 7 l ** -0.269***
Adjusted R2 0.084**** 0050*** 0.072****
Observations 188 188 188
**** - p-value S 0.001 (two—sided); *** - p—value S 0.01 (two-sided);
** - p—value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
STABLE Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Marketing Equity, Avg. 0135* 0.031 0115*
Sales_lg10 —0.046 -0. 180'” -0.293****
Adjusted 1?.2 0.008 0.021** 0074“...
Observations 209 209 209
**** - p-value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
STABLE Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Marketing Equity, Trend 0115* 0.021** 0.155**
Sales_lg10 -0.024 -0.027 -0.280****
Adjusted R2 0.004 -0l69** 0.085****
Observations 209 209 209

 

 

 

 

***-t: - p-value 5 0,001 (two-sided); *** - p-value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p—value S 0.10 level (two-sided)

107

 

 

 

Table 22: Relationship Between Marketing Equity and Financial Performance: Low
Technology Mini-Sample

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA) ‘ .
Customer Satisfaction 0.114 -0.052 0.161**
Brand Eqpity 0.119 -0.007 0133*
Corporate Reputation 0.034 0.254*** 0.098
Sales_lg10 0.018 0.031 0.054
Adjusted R2 0.012 0.038** 0.032**
Observations 182 182 182
**** - p-value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided);
** - p—value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Marketing Equity, Avg. 0150* 0.153** 0.193**
Sales_lg10 0.070 0.046 0092
Adjusted R2 0.025** 0021* 0022**
Observations 192 192 192
**** - p-value S 0.001 (two-sided); *** - p—value S 0.01 (two-sided);
** - p-value S 0.05 (two-sided); * - p-value S 0.10 level (two-sided)
LOW Return on Altman’s Z Tobin’s Q
TECHNOLOGY Assets (ROA)
Marketing Equity, Trend 0.147** 0.064 0.024
Sales_lg10 0.094 0.090 0.025
Adjusted RT 0.026** 0.004 0.010
Observations 192 192 192

 

 

 

 

nu _ ‘3-“qu 5 0.001 (two-sided); *** - p-value S 0.01 (two-sided);
ant - p-value 3 0,05 (two-sided); * - p—value S 0.10 level (two-sided)

108

 

 

 

Table 23: Summary of Findings for Hypothesized Relationships

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Hmthesized Relationships Results
Hla: B2B marketing expenditures (+) 9 Customer Satisfaction Rejected
Hlb: B2C marketing expenditures (+) 9 Customer Satisfaction Supported
Hle: Secured intellectual property (+) 9 Customer Satisfaction Rejected
H1 (1: Sourcing attentiveness ( +) 9 Customer Satisfaction Partially supported
Hle: Inventory readiness (+) 9 Customer Satisfaction Rejected
Hlf: Production capacity (+) 9 Customer Satisfaction Rejected
H1 g: Discovery expenditures (+) 9 Customer Satisfaction Rejected
th: Ideation personnel centralization (+) 9 Customer Satisfaction Rejected
Hli: Overall innovation creativity (+) 9 Customer Satisfaction Rejected
H2a: BZB marketing expenditures (+) 9 Brand Equity Rejected
H2b: B2C marketing expenditures (+) 9 Brand Equity Supported
H2e: Secured intellectual property (+) 9 Brand Equity Rejected
H2d: Sourcing attentiveness (+) 9 Brand Equity Rejected
H2e: Inventory readiness (+) 9 Brand Equity Rejected
H2f: Production capacity (+) 9 Brand Equity Rejected

 

H2g: Discovery expenditures (+) 9 Brand @uity

Partially contradicted

 

H2b: Ideation personnel centralization (+) 9 Brand Equity

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Rejected
H2i: Overall innovation creativity (+) 9 Brand Equity Supported
H3a: BZB marketing expenditures (+) 9 Corporate Reputation Rejected
H3b: B2C marketing expenditures (+) 9 Corporate Reputation Rejected
H3e: Secured intellectual property (+) ‘) Corporate Reputation Rg'jected
H3d: Sourcing attentiveness (+) 9 Corporate Reputation Supported
H3e: Inventory readiness (+) 9 Corporate Reputation Rejected
H3f: Production capacitv (+) 9 Corporate RCDUm Partially contradicted
H3g: Discovery expenditures (+) 9 Corporate Reputation Rejected
H3h: Ideation personnel centralization (+) 9 Corporate Reputation Rejected
H31: Overall innovation creativit + Co rate Re utation Contradicted
H4: Customer Satisfaction (+) 9 ROA Supported
H5: Brand Equity (+) 9 ROA Supported
H6: Corporate Reputation (+) 9 ROA Rejected
H7: Customer Satisfaction (+) 9 Altman’s Z Supported
H8: Brand Equity (+) 9 Altman’s Z Rejected
H9: Corporate Reputation (+) 9 Altman’s Z Supported
H10: Customer Satisfaction (+) 9 Tobin’s Q Supported
H11: Brand Equity (+) 9 Tobin’s Q Rejected
H12: Corporate Reputation (+) 9 Tobin’s Q Rejected

 

 

109

 

Marketing Equity and ROA

Customer satisfaction was found to have a positive inﬂuence on ROA in the
overall sample (B=0.170, p-value S 0.001), thus supporting H4. This relationship was also
detected in the high technology (B=0.264, p-value S 0.001) and stable and low technology
(B=0.109, p-value S 0.10) sub-samples.

Brand equity was found to positively inﬂuence ROA in the overall sample
(1320.130, p-value S 0.05) to support H5. This relationship was also found in the stable
and low technology sub-segment (8:0. 135, p-value S 0.05). More exactly, stable
technology ﬁrms appear to increase their ROA with enhanced brand equity (B=0.198, p-
value S 0.05).

Corporate reputation was not found to inﬂuence ROA in the overall sample, thus
rejecting H6. However, the ROA of stable technology frrrns appears to beneﬁt from
increased corporate reputation (B=0.224, p-value S 0.05). 1

Interestingly, the averaged Marketing Equity index was found to negatively
inﬂuence ROA (B=-0.081, p-value S 0.10) in the overall sample. This relationship was
more profound in the high technology industry sub-sample (Marketing Equity average:
B=-0.l72, p-value S 0.05; Marketing Equity trend: B=-0128, p-value S 0.10). Then, a
positive relationship was found in the stable and low technology sub-sample (Marketing
Equity average: B=0.193, p-value S 0.001; Marketing Equity trend: 8:0.147, p-value S
0.01). For further conﬁrmation, a positive relationship was found among stable
technology (Marketing Equity average: 8:0.135, p—value S 0.10; Marketing Equity trend:
B=0.115, p-value S 0.10) and low technology (Marketing Equity average: B=0.150, p-

value S 0.10; Marketing Equity trend: 13:0. 147, p-value S 0.05) ﬁrms.

110

Marketing Equity and Altman’s Z

The expected relationship between customer satisfaction and Alunan’s Z was
found. A positive relationship was detected (B=0.098, p-value S 0.05), thus providing
evidence for H7. This relationship was also found in the stable and low technology sub-
sample (13:01 13, p-value S 0.05).

Little evidence was provided to support H3. However, a positive relationship
between brand equity and Altman’s Z was found only among stable technology ﬁrms
(B=0.l78, p-value S 0.05).

Corporate reputation was found to have a positive inﬂuence on Altman’s Z in the
overall sample (B=0.109, p-value S 0.05), thus supporting H9. This relationship was
detected in high technology (B=0.200, p—value S 0.05) and low technology (B=0.254, p-
value S 0.01) industries, as well. I

A positive relationship was found between the averaged Marketing Equity and
Altman’s Z (B=0.160, p-value S 0.001) in the overall sample. Similar results were found
in the high technology (B=0.164, p-value S 0.05) and stable and low technology industry
(B=0.169, p-value S 0.001) sub-samples. Additionally, this positive relationship was
found among low technology ﬁrms (B=0.153, p-value S 0.05). Interestingly, a
relationship between the trended Marketing Equity index and Altman’s Z was found

among stable technology ﬁrms (B=0.021, p-value S 0.05).

111

Marketing Equity and Tobin’s Q

A relationship between customer satisfaction and Tobin’s Q was found in the
overall sample (B=0.178, p-value S 0.001), thus supporting H10. Similar ﬁndings were
detected in the high technology (13:0178, p—value S 0.05) and stable and low technology
(B=0.209, p—value S 0.001) sub-samples. More exactly, this inﬂuence was found among
low technology ﬁrms (13:0. 161, p-value S 0.05).

Very little evidence was found to support H11 in the overall sample. However, a
positive relationship between brand equity and Tobin’s Q was detected among stable
technology ﬁrms (13:0160, p-value S 0.10). Additionally, a negative relationship was
detected in the low technology industry sub-sample (B=-0. 133, p-value S 0.10).

Corporate reputation was not found to inﬂuence Tobin’s Q in the overall sample,
thus rejecting H12. In fact, a relationship between these two variables was found only in
the high technology industry sub-sample (B=-0. 160, p-value S 0.05).

A positive relationship was found between both measures of Marketing Equity
and Tobin’s Q (Marketing Equity average: 13:0. 144, p-value S 0.001; Marketing Equity
trend: 13:0093, p-value S 0.05) in the overall sample. In the high technology industry
sub-sample, only the trended Marketing Equity index was found to have a statistical
relationship with Tobin’s Q (B=O.111, p-value S 0.10). However, both Marketing Equity
indices were found to relate with Tobin’s Q among stable and low technology (Marketing
Equity average: B=0.223, p-value S 0.001; Marketing Equity trend: B=0.111, p-value S
0.05) and stable technology (Marketing Equity average: 13:0115, p-value S 0.10;

Marketing Equity trend: B=0.155, p-value S 0.05) ﬁrms. Additionally, in the low

112

technology industry sub-sample, a statistical relationship was detected using the averaged
Marketing Equity index (B=0.193, p-value S 0.05).

Table 24: Summary of Relationship Between Cross-Functional Marketing
Resources and Marketing Equity Components

 

 

 

 

 

 

 

 

 

 

 

 

 

RESULTS Customer Brand Equity Corporate
SUMMARY Satisfaction Reputation
B2B Marketig Expenditures Low +
B2C Marketing Expenditures Overall +; High + Overall +; Stable & High -
Low +; Stable +
Secured Intellectual Preperty High + Low +
Sourcing Attentiveness Overall +; Stable & Overall +; High +;
~ Low + Stable & Low +
Inventory Readiness _L_mv_+ Steble;
Production Capacity Overall —; Stable &
Low -; Low -
Discovery Expenditures Overall -—; High -; High -
Q0;
Ideation Personnel
Centralization
Overall Innovation Overall +; Stable & Overall -; High -
Creativity Low +; $29193;
Sales_lg10 Stable & Low 4»; Overall +; High +; Overall +; Stable &
Sable +; 2w + Stable & Low +; Low +; Stable +
Stable +; Low +

 

 

 

 

 

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High Technology, Stable & Low
Technology, Stable Technology, and Low Technology samples

if p—valuc S 0.10 level (two-sided), then italics

if N < 50, then underlined

 

 

 

 

 

 

RESULTS Customer Brand Equity Corporate
SUMMARY Satisfaction Reputation
Customer-focused resources Overall +; Stable & Stable + Stable & Low +;
and capabilities LOW +; LOW + Stable +
Supply chain-focused Stable - Stable -; Low+
resources and capabilities
Innovation-focused
resources and capabilities
Sales_lg10 Stable & Low +; Overall +; High +; Overall +; High +;
Low + Stable & Low +; Stable & Low +;
Stable +; Low + Stable +; Low +

 

 

 

 

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High Technology, Stable & Low
Technology, Stable Technology, and Low Technology samples

if p-value S 0.10 level (two-sided), then italics

if N < 50, then underlined

113

Table 25: Summary of Relationship Between Cross-Functional Marketing
Resources and Marketing Equity Index

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

RESULTS Marketing Marketing
SUMMARY Equity, Avg. Equity, Trend
B2B Marketing Expenditures
B2C Marketing Expenditures Overall +; Stable & Overall +; Stable &
Low +; Stable +; Low +; Stable +;
Lew + Low 4-
Secured Intellectual Property
Sourcing Attentiveness Overall +; Stable & Stable & bow +;
Low +; _I=.ow + 41:0w +
Inventory Readiness Overall —; Stable —
Production Capacity Low -
Discovery Expenditures Overall -; High - Overall -; High -;
Stable & Low -
Ideation Personnel
Centralization
Overall Innovation SEM. MIL:
Creativity
Sales_lg10 Overall +; High +; Overall +; High +;
Stable & Low +; Stable & Low +;
Stable +; Low + Stable +; Low 4-

 

listed if beta coefﬁcient has p—value S 0.05 (two-sided) for Overall, High
Technology, Stable & Low Technology, Stable Technology, and Low Technology
samples '

if p—value S 0.10 level (two-sided), then italics

if N < 50, then underlined

 

 

 

 

 

RESULTS Marketing Marketing
SUMMARY Equity, Avg. Equity, Trend
Customer-focused resources Overall +; Stable & Overall +; High 4*;
and capabilities LOW +; Stable +; Stable & LOW +;
Low + Stable +
Supply chain-focused Low + Stable & Low +;
resources and capabilities Stable +
Innovation-focused Overall - Overall —; High —
resources and capabilities
Sales_lg10 Overall +; High +; Overall 4»; Stable &
Stable & Low +; Low +; Stable +;
Stable +; Low + Low +

 

 

 

 

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High
Technology, Stable & Low Technology, Stable Technology, and Low Technology
samples

if p-value S 0.10 level (two—sided), then italics

if N < 50, then underlined

114

Table 26: Summary of Relationship Between Cross-Functional Marketing
Resources and Financial Performance

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

RESULTS Return on Altman’s Z Tobin’s Q
SUMMARY Assets (ROA)
B2B Marketing Expenditures Overall +; Stable & Overall +
Low +; Stable +
B2C Marketing Expenditures Overall +; Stable + Stable +
Secured Intellectual Property ‘ Overall +; High +;
Stable & Low +;
Stable +; Low +
Sourcing Attentiveness Overall +; High +;
Stable & Low +;
I_.9yw +
Inventory Readiness Stable & Low + Overall +; High +;
Stable & Low +
Production Capacity Overall -; High -;
Stable & Low —;
_LOW -
Discovery Expenditures Overall -; Stable & Low +
Low -
Ideation Personnel High +; %
Centralization
Overall Innovation Stable & Low -; Stable & Low —; Overall —; High —;
Creativity Stable - Stable — Stable —
Sales_lg10 Overall +; Low + Stable -— High —

 

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High Technology, Stable & Low
Technology, Stable Technology, and Low Technology samples
if p-value S 0.10 level (two-sided), then italics

if N < 50, then underlined

 

 

 

 

 

 

 

 

 

RESULTS Return on Altman’s Z Tobin’s Q
SUMMARY Assets (ROA)

Customer-focused resources Overall +; High +; Overall +; Stable & Overall +; High +;
and capabilities Stable + LOW +; Stable + Stable & LOW +;

Stable +; Low +
Supply chain-focused Stable & Low — Overall —; Stable & Overall —; Stable &
resources and capabilities LOW £0 Stable —; Low —

w —
Innovation-focused Overall -
resources and capabilities
Sales_lg10 Low + Stable — Overall -; High -;
Stable —

 

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High Technology. Stable & Low
Technology, Stable Technology, and Low Technology samples
if p-value S 0.10 level (two-sided), then italics

if N < 50, then underlined

115

‘mj‘ ‘

Table 27 : Summary of Relationship Between Marketing Equity and Financial

 

 

 

 

 

 

 

 

 

Performance
RESULTS Return on Altman’s Z Tobin’s Q
SUMMARY Assets (ROA)
Customer Overall +; High +; Overall +; Stable & Overall +; High +;
Satisfaction Stable & LOW + LOW + Stable & LOW +;
Low «1-
Brand Equity Overall +; Stable & Stable + Stable +; Low —
Low +; Stable +

Corporate Stable + Overall +; High +; High +

Rgutation LOW +

Sales_lg10 Stable & Low -; Overall —; High -;
Stable - Stable & Low —;

Stable -

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High Technology,
Stable & Low Technology, Stable Technology, and Low Technology samples

if p-value S 0.10 level (two-sided), then italics
if N < 50, then underlined

 

 

 

 

 

 

RESULTS Return on Altman’s Z Tobin’s Q
SUMMARY Assets (ROA)
Marketing Equity, Overall —; High —; Overall +; High +; Overall +; Stable &
Avg. Stable & Low +; Stable & Low +; Low +; Stable +;
Stable +; Low + Low + Low 4-

Sales_lg10 Stable & Low -; Overall -; High —;

Stable —- Stable & Low —;
Stable -

 

 

listed if beta coefﬁcient has p-value S 0.05 (two-sided) for Overall, High Technology,
Stable & Low Technology, Stable Technology, and Low Technology samples

if p-value S 0.10 level (two-sided), then italics
if N < 50, then underlined

 

 

 

 

RESULTS Return on Altman’s Z Tobin’s Q
SUMMARY Assets (ROA)
Marketing Equity, High —; Stable & Stable + Overall +; High +;
Trend Low +; Stable +; Stable & Low +;
Low + Stable +
Sales_lg10 Overall —; Stable &
Low -; Stable —

 

 

 

 

listed if beta coefﬁcient has p—valuc S 0.05 (two-sided) for Overall, High Technology,
Stable & Low Technology, Stable Technology, and Low Technology samples

if p-value S 0.10 level (two-sided), then italics
if N < 50, then underlined

116

 

 

 

CHAPT ER SIX

DISCUSSION

“Reality is merely an illusion, albeit a very persistent

9’

one.
- Albert Einstein (1879-1955)

This study expands the notion of customer equity and customer lifetime value
(CLV) by testing the marketing ﬁmction’s ownership in the marketplace as measured by
competing marketing outcomes and a wholistic measurement, Marketing Equity. In
addition, this study not only analyzes the role of resource allocations on marketing’s
ownership in the marketplace, but it also assesses the impact of these different elements
of Marketing Equity on ﬁnancial performance.

In this section, a detailed discussion is provided concerning the results from this
study. Considering the context of this study, three overarching conclusions can be
established: 1) customer-focused resources are necessary for continued competitiveness;
2) ﬁnding the Optimum balance for effective utilization of supply chain-focused resources
can be challenging; and 3) innovation focused resources can be a hedge against future
developments that may occur in the marketplace.

The subsequent sections discuss in more detail the ﬁner points of each of these
main conclusions that can be derived from this study. First, analysis is performed
concerning the inﬂuence of each cross-functional marketing resource on the distinct
components of Marketing Equity in different industry-based technology conditions.
Then, discussion is included concerning the direct inﬂuence of cross-functional
marketing resources on each measure of ﬁnancial performance. Finally, the impact of

each element of Marketing Equity on the distinct measures of ﬁnancial performance is

117

considered. Additionally, some limitations to the present study are discussed as possible

areas for future research in the literature.

RELEVANT FINDINGS
Cross-Functional Marketing Resources and Marketing Equity

Customer-focused resources and marketing equity. The ﬁrst overarching
conclusion that can be made from this study is that customer-focused resources are
necessary for continued competitiveness. An effective way to discuss the standing of
customer-focused resources as contributing to the position advantage of the ﬁrm is in
relationship discovered between concerning B2C marketing expenditures and different
components of Marketing Equity. The negative relationship found between B2C
marketing expenditures and corporate reputation in the high technology industry sub-
sample indicates that excessive marketing expenditures focusing on the end-customer
may adversely inﬂuence how the company is seen in a B2B context. However, B2C
marketing expenditures were found to positively inﬂuence customer satisfaction in the
overall sample as well as in high technology industries. Additionally, the positive
inﬂuence of B2C marketing expenditures on brand equity in the overall sample, the stable
and low technology sub-sample, and the low technology industry mini-group is indicative
of the lasting inﬂuences of such directed resources.

This seems to indicate that B2C marketing expenditures have a multiple role in
the relationship that a ﬁrm may develop with its end-customers. In fact, the positive
inﬂuence of BZC marketing expenditures on customer satisfaction appears to show that

these types of customer-focused resources assist the process of exposure, awareness, and

118

purchase intent in the marketplace. The result is that a ﬁrm’s immediate position in the
market should be enhanced somewhat closely to the deployment of such resources
relative to other alternatives in the ﬁrm. As ﬁndings supported this notion in the analysis
of distinct sub-samples previously discussed, one could also posit that the role of B2C
marketing expenditures is particularly important to this process in high technology
industries.

AdditiOnally, the inﬂuence of B2C marketing expenditures on brand equity
appears to indicate the second facet of the role of this variable. In essence, this study’s
ﬁndings show that the relationship between B2C marketing expenditures and brand
equity is indicative of the ﬁrm’s ability to develop a relationship with end-customers. The
implicit nature of the brand equity construct lends itself to the conclusion that it is a
measure of a longer-term relationship that may develop between consumers and a ﬁrm-
level brand. Therefore, it seems that the positive inﬂuence of B2C marketing
expenditures shows that it is an important element in a ﬁrm’s strategy to accomplish and
maintain such a relationship. In fact, this also holds in the stable and low technology
industry sub-segment and — more particularly - in the stable technology mini-segment,
further indicating the distinction of brand equity from customer satisfaction.

As such, the negative associations of B2C marketing expenditures with corporate
reputation may be a result of the sample employed. Since corporate reputation was drawn
from executives, directors, and securities analysts, the sample may generally perceive that
BZC marketing expenditures negatively impact the ﬁrm. Also, the eight measures used to
assess corporate reputation — a ﬁrm’s innovativeness, ﬁnancial soundness, employee

talent, corporate asset utilization, long-term investment value, social responsibility,

119

management quality, and product or service quality — lend themselves to the notion that
resources in any ﬁrm are ﬁnite. As such, if resources are spent to communicate with the
end-customer among a sample that is more focused on business marketing issues, then
one conclusion may be that the resources used may be better spent elsewhere.

Interestingly, B2C marketing expenditures were negatively correlated with two
different variables in this study’s sample: inventory readiness and sales. The negative
correlation between B2C marketing expenditures and inventory readiness seems to
indicate that customer—focused resources (e.g., B2C marketing expenditures) may create a
pull in the marketplace for which a ﬁrm’s supply chain-focused resources (e.g., inventory
readiness) may not be entirely prepared. This could very well be due to a greater
effectiveness of B2C customer expenditures than expected. Also, this may be the result of
managers’ unwillingness to take the risk of strategically having excessive inventory for
response to the marketplace. Additionally, there might be issues related to a conceptual
disconnect in decision-making between the efﬁciency of a ﬁrm’s production processes or
sourcing tactics and its customer-focused strategies.

However, an equally compelling reason for the negative relationship between
B2C marketing expenditures and inventory readiness may reside in the negative
correlation this study’s sales variable holds with B2C marketing expenditures. More
explicitly, a lack of sales can induce a ﬁrm to facilitate demand by deploying B2C
marketing expenditures, but may also encourage an inability to respond to demand
because of the market conditions to which a ﬁrm’s supply chain is accustomed.

Additionally, 32B marketing expenditures had a positive inﬂuence on brand

equity in the low technology industry mini-sample. This appears to indicate that the use

120

of B2B marketing expenditures also contributes to the relationship a ﬁrm attempts to
develop with its end-customers. The nature of low technology industries is typically not a
hyper-competitive as in high technology industries. Thus, the use of resources to facilitate
the delivery of products or services to the marketplace via internal functional groups

(e.g., sales force) or external intermediaries (e.g., independent distributors) seems to
assist in developing a ﬁrm’s relationship with consumers.

Also, there appear to be two relevant statistical relationships concerning secured
intellectual property. First, it appears that secured intellectual property has a positive
inﬂuence on customer satisfaction in the high technology sub—sample. This seems to
indicate that the stock of a frrm’s secured intellectual property acts as a way for high-
technology ﬁrms to immediately and effectively respond to market conditions. As a
result, this is shown in a frrm’s positional advantage of enhanced customer satisfaction
vis-a-vis competitors. Second, the positive inﬂuence of secured intellectual property on
corporate reputation in the low technology mini-sample may be an indication of the
immediacy market sector analysts and industry experts place on this customer-focused
variable. More exactly, it appears that the decreased competitive intensity inherent in low
technology industries lends itself to the applicability of secured intellectual property in
the sample used to arrive at the corporate reputation variable.

Supply chain-focused resources and marketing equity. The second overarching
conclusion of this study that an Optimum balance of supply chain-focused resources is
daunting yet imperative for competitiveness is best explained in results concerning a
ﬁrm’s production capacity. Findings concerning the negative inﬂuence of production

capacity on corporate reputation in the overall sample, the stable and low technology

121

industry, and the low technology mini-segment indicate that a ﬁrm’s responsiveness to
the production requirements in marketplace is of utmost importance. In essence, the more
able a ﬁrm is to align, upgrade, and maintain its production facilities, the more likely its
corporate reputation will beneﬁt.

By analyzing the variables which have two strong correlations with production
capacity, an even more interesting picture emerges concerning the importance of this
variable in relation to other resources included in this study. First, the strong negative
correlation between production capacity and B2B marketing expenditures seems to relate
back to the issue of responsiveness. In fact, the role of B2B marketing expenditures
appears to act as a compensating effect for a ﬁrm’s production capacity (or, lack thereof).
More precisely, a ﬁrm’s sales force or independent distributors may have a better idea of
how best to utilize the production abilities of the ﬁrm, thus acting as a buffer that can best
optimize for market conditions. I

Secondly, the notable positive correlation between production capacity and
inventory readiness seems to indicate that these two concepts are related in terms of the
production process. More exactly, this seems in line with the notion of responsiveness as
being key to the inﬂuence of supply chain-focused resources on the components of
marketing equity. This positive correlation appears to indicate that a ﬁrm has less of its
inventory as ﬁnished goods to remain competitive. In relation to production capacity, this
seems to mean that, by keeping more of its inventory as raw materials or work-in-
progress (WIP), the ﬁrm is better able to avoid the danger of trying to release obsolete

inventory into the marketplace.

122

The inﬂuence of inventory readiness on customer satisfaction in the low
technology mini-sample is related to this in that the nature of low technology industries
typically does not have nearly the threat of inventory obsolescence as higher technology
industries. As such, the ability of the ﬁrm to stockpile inventory to respond to
marketplace conditions makes this a strategy that may only exclusively be useful in lower
technology industries. An indication of this is the negative relationship between inventory
readiness and brand equity in the stable technology mini-sample. It would seem that in
this type of industry that possessing too much inventory that might very well be obsolete
may provide a signal to end—customers that a tenuous relationship with the ﬁrm may exist
in the future.

Another signal of the complexity of relating supply chain-focused resources to
marketing equity is the dual positive inﬂuence of sourcing attentiveness on customer
satisfaction and corporate reputation in the overall sample. In addition to the ﬁndings
concerning the responsiveness of ﬁrms to the marketplace mentioned above, the results
concerning sourcing attentiveness indicates the importance of keeping costs under control
so that the ﬁrm can pass such value on in some way to the end-customer. For example, by
reducing costs of production, a ﬁrm is better able to expend its resources and capabilities
elsewhere to better calibrate its product or service offerings to satisfy customers more
effectively. Even though the measure for corporate reputation is not derived from end-
customers like customer satisfaction, this logic holds true for the relationships between
sourcing attentiveness and corporate reputation in the overall sample as it does for

customer satisfaction. Equally interesting is that similar ﬁndings are indicated in the

123

stable and low technology sub-sample, thus indicating the particular importance of this
relationship in these types of industries.

However, most compelling is that the positive inﬂuence of sourcing attentiveness
on corporate reputation was also found in high technology industries. Though possibly a
relic of the sample for deriving corporate reputation, it nonetheless re-iterates the
importance of cost control and its relation to delivering value to the customer.

Innovation-focused resources and marketing equity. The third overarching
conclusion of this study is that innovation-focused resources can act as a hedge against
future developments that may occur in the marketplace. In fact, this is perhaps most
adequately shown in this study’s ﬁndings concerning discovery expenditures and overall
innovation creativity. The negative inﬂuence of discovery expenditures on brand equity
in the overall sample as well as among the high and low technology sub-segments
provides an interesting dilemma for marketing research. A complex picture emerges with
ﬁndings indicating that overall innovation creativity positively inﬂuences brand equity in
the overall sample, the stable and low technology sub-segment, and the low technology
mini-segment. In fact, the ﬁndings imply that research and development efforts must be
more focused and efﬁcient for high and low technology ﬁrms. Equally important, though,
is the element of differentiation through a ﬁrm’s overall innovation creativity particularly
in the stable and low technology industries.

However, overall innovation creativity can damage a ﬁrm’s corporate reputation,
as well. According to this study’s ﬁndings, a negative relationship exists between overall
innovation creativity and corporate reputation in the overall sample and among high

technology ﬁrms. Essentially, this may occur for two reasons: 1) resources used for

124

creative products and/or processes may not be the optimum use of company resources;
and 2) to align with demands in the marketplace, incremental innovation will be more
widely accepted and contribute more to a ﬁrm’s Marketing Equity. This is supported
further by the negative relationship between overall innovation creativity and ROA,
Altman’s Z, and Tobin’s Q.

The notable negative correlation between overall innovation creativity and
discovery expenditures must also be discussed to conclude the emphasis of innovation-
focused resources as relevant to this study. With reference to the negative inﬂuence of
discovery expenditures on brand equity and corporate reputation in a variety of contexts,
it would appear that overall innovation creativity - in these speciﬁc conditions - may
very well provide beneﬁt. However, should discovery expenditures be left uncontrolled,
then it would appear that overall innovation creativity would lose its effectiveness. In
essence, the directed nature of a ﬁrm’s innovation efforts and its overall innovation

creativity appears as an emerging issue from the data in this study.

Cross-Functional Marketing Resources and Financial Performance

The positive inﬂuence of BZB marketing expenditures on Altman’s Z in the
overall sample, the stable and low technology sub-segment, and the stable mini-segment
indicates that this customer-focused resource reduces the likelihood that the ﬁrm will go
bankrupt. Also, B2C marketing expenditures appear important as well in ensuring a
ﬁrm’s ﬁnancial status among stable technology ﬁrms. In addition, given the positive

relationship between 32B marketing expenditures and Tobin’s Q in the overall sample,

125

this study implies that such actions should positively impact the future value of the
company.

This study ﬁnds that sourcing attentiveness positively inﬂuences ROA in the
overall sample, the high technology sub-sample, the stable and low technology sub-
sample, and the low technology mini-sample. As such, this study states that cost-cutting
measures taken in an earlier period (1994-1999) have a positive ﬁnancial impact later in
the ﬁrm’s development (2003-2005).

Inventory readiness also appears to have a positive inﬂuence on ﬁnancial
performance. Given the inﬂuence of inventory readiness on ROA in the stable and low
technology sub—sample, this study proposes that having inventory ready to respond to
market conditions can impact ﬁnancial performance later. Similar ﬁndings exist in the
positive relationship between inventory readiness and Tobin’s Q in the overall sample,
the high technology sub-sample, and the stable & low technology sub-sample.

Like in ﬁndings discussed above, the role of responsive production capacity is
important. This can be seen in the negative inﬂuence of production capacity on Altman’s
Z in the overall sample, the high technology sub-segment, the stable and low technology
sub-sample, and the low technology mini-sample. In essence, having too much
production capacity and spending too little on capital expenditures indicates a lack of
upgrade of current facilities. As such, without sufﬁcient upgrades, a ﬁrm can risk
bankruptcy.

Interestingly, the negative relationship between discovery expenditures and
Altman’s Z in the overall sample and the stable and low technology sub-sample appears

to indicate a different issue: the efﬁciency and effectiveness of a ﬁrm’s innovation

126

efforts. Spending too much on research and development can risk a ﬁrm’s ﬁnancial
stability. However, in the low technology sub-sample, a positive relationship between
discovery expenditures and Tobin’s Q was found. This appears to indicate that research
and development efforts can impact the marketplace’s assessment of future performance
of the ﬁrm.

Ideation personnel centralization appears to have a positive impact on Tobin’s Q
among high technology ﬁrms but a negative impact among low technology ﬁrms. This
may imply that — given the dynamics high technology ﬁrms face —- centralization of
inventors is imperative to properly respond to the marketplace. Meanwhile, among low
technology ﬁrms, decentralization may be more important for two reasons: 1) innovation
may not be as important as in other industry types; and 2) innovation efforts must be
embodied in every aspect of the ﬁrm. As such, the more decentralized the ﬁrm’s
innovative activities, the better able it would be to response to the speciﬁc nuances of low

technology industries.

Marketing Equity and Financial Performance

Customer satisfaction appears to have a positive inﬂuence on ROA and Tobin’s Q
in the overall sample as well as the high technology and stable and low technology sub-
samples. Additionally, the inﬂuence of ROA on Tobin’s Q appears to exist in the low
technology mini-sample. As such, there is little surprise that these relationships have been
studied extensively by extant literature. However, equally interesting is that customer

satisfaction can increase a ﬁrrn’s likelihood of avoiding bankruptcy.

127

Though less studied to date, brand equity’s inﬂuence on ROA appears to hold
well in the overall sample, the stable and low technology sub-sample, and the stable
technology mini-sample. In addition, brand equity appears to impact a frrm’s ﬁnancial
stability among stable technology ﬁrms. The lack of ﬁndings addressing high technology
ﬁrms may be due to the dynamics of these speciﬁc types of industries. Since
competitiveness is typically more competitive, the time it takes to develop a ﬁrm’s brand
equity may not be an effective utilization of ﬁrm resources. This appears to be supported
in the positive relationship between brand equity and Tobin’s Q in the high technology
sub-sample. If a ﬁrm has brand equity, it can positively impact the marketplace’s
assessment of a ﬁrm’s assets. However, this is the extent to which one can discuss this
within the context of high technology industries.

Corporate reputation also appears to be a reasonable insurance against
bankruptcy. A positive relationship was found between corporate reputation and
Altman’s Z in the overall sample, the high technology sub-sample, and the low
technology mini-sample. Also, like brand equity, corporate reputation was found to
impact a ﬁrm’s valuation in the marketplace of future success as measured by Tobin’s Q.
Given these and other ﬁndings, this study concludes that evidence exists for the various

elements of marketing equity are adequate mediators in this study.

LIMITATIONS
There are at least three topics that related to limitations of this study: 1) sample
size; 2) marketing equity; and 3) sample parameters. First, the sample size is not ideal for

testing all the relationships included. In fact, the analysis of the stable technology and low

128

technology mini-samples is indicative of this problem. To partially account for this issue,
an enhanced least squares approach was used. However, gathering more actual data to
avoid the use of such a method is needed for future research.

At that point, a more rigorous method might be used: 1) structural equation
modeling to analyze the relationships as a system; 2) generalized least squares, two-
stages least squares, or three-stages least squares to account for correlated error terms,
non-normality, and possible recursive relationships; 3) partial least squares to account for
non-normality in the data and a small sample size.

Second, the deﬁnition of Marketing Equity is not complete. While it incorporates
customer satisfaction, brand equity, and corporate reputation to represent the marketing
function’s ownership in the marketplace, this conceptual construct is missing other
elements that either are not current in the literature or have yet to be adequately explored
in the literature.

One example of this is the measure of corporate reputation. The use of this
measure is sufﬁcient to capture the standing of a ﬁrm in a speciﬁc industry within a B2B
context. However, corporate reputation as deﬁned here accounts only for the decision-
makcrs (be they executives, directors, or securities analysts) as they operate within the
industry and business marketing context. This study fails to account for this sample type
as acting as inﬂuential end-customers, as well.

Third, while many of the issues involved are either explicitly or implicitly
international, this entire study is based on data gathered in the United States. The data
drawn from the WRDS Compustat database was the North American Industrial Annual

database. Future research may aim to use Compustat’s Global and Emerging Markets

129

database in the future to better account for international issues. Also, some of the
innovation-focused resources used in this study were drawn from registered innovations
in the United States. As such, future research may wish to incorporate innovation
registration data from the European Union, Japan, or the World Intellectual Property
Organization. Also, international measures for customer satisfaction, brand equity, and
corporate reputation exist. Future studies may wish to secure these data sources for more
study and applicability, as well.

Therefore, future studies may aim to incorporate any or all of these limitations in

their analyses.

130

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