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This is to certify that the

dissertation entitled

A COMPARATIVE ANALYSIS OF THE INFLUENCE OF BUSINESS
ENVIRONMENT FACTORS ON DECISION MAKING IN VARIOUS
INDUSTRIAL SECTIORS WITH EMPHASIS ON
TOURISM AND SMALL BUSINESSES

presented by

Yonghee Park

has been accepted towards fulﬁllment
of the requirements for

Ph.D. degreein Park, Recreation, and

Tourism Resources

,WM

7 Major p’éfessor V

Date W9

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1/98 chIRCJDateDquS—p.“

A COMPARATIVE ANALYSIS OF THE INFLUENCE OF BUSINESS
ENVIRONMENT FACTORS ON DECISION MAKING IN VARIOUS
INDUSTRIAL SECTORS WITH EMPHASIS ON
TOURISM AND SMALL BUSINESSES

By

Yonghee Park

A DISSERTATION
Submitted to
Michigan State University

in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Park, Recreation, and Tourism Resources

1999

ABSTRACT

A COMPARATIVE ANALYSIS OF THE INFLUENCE OF BUSINESS
ENVIRONMENT FACTORS ON DECISION MAKING IN VARIOUS INDUSTRIAL
SECTORS WITH EMPHAIS ON TOURISM AND SMALL BUSINESSES

By

Yonghee Park

Business decisions involving start-up, retention, investment, and expansion are
affected by factors that comprise the ever-changing external environment. Of various
external environment factors, government policy is of strategic importance to businesses,
because it often impacts the size and structure of markets, the cost of doing business, and
many aspects of making business decisions. Although previous research has examined
the inﬂuence of state-govemment policies on large manufacturing businesses, few studies
have examined the impact of various environment factors on the decisions made by
different types or sizes of businesses, including services and hospitality/tourism and small
businesses.

The primary purposes of this study were to (1) determine the extent to which
various external environment factors inﬂuence businesses’ hiring decisions; (2) assess
whether or not size or type of a business inﬂuences how a business responds to external
factors, including state-govemment policies; and (3) compare the perceptions that owners
and managers of different types and sizes of businesses have of state agencies, their

services and their expertise.

Focus groups were conducted ﬁrst with 21 agriculture, manufacturing, and
service-sector business owners and managers. Insights from the focus groups were then
utilized to guide development of a state-wide mail questionnaire that was administered
during the summer of 1995 by the Tax Policy Center at Michigan State University. The
responding businesses (953) were categorized into six industries and three sizes. Factor
analysis, ANOVA, and T-tests are performed to test six hypotheses.

Five general conclusions were drawn from the results of the hypotheses tests: (1)

the market environment—consumer demand and supply of labor-—is more inﬂuential in

business hiring decisions than are state regulations and programs across different sizes
and types of businesses; (2) the market environment is of greater importance to medium-
and large-sized businesses than to small businesses; (3) businesses comprising the
primary and the hospitality/tourism industries are more inﬂuenced by the state-imposed
cost of doing business factor compared to the general-services and the
managerial/personal—services industries. In general, secondary industry businesses are
more significantly inﬂuenced by both the market environment and the state-imposed cost
of doing business factors than are service industries, except for the hospitality/tourism
industry; (4) businesses generally have negative perceptions about the quality of state-
provided business services and the level of expertise of state-agency personnel. The
wholesale/retail and the hospitality/tourism industries, however, have more unfavorable
perceptions of government services than does the general-services industry; and (5) the
more agencies with which businesses have had contact, the more unfavorable are their
perceptions of the overall quality of state-provided services. In this case, contact with

more agencies does not improve the perceptions of state-services provided to businesses.

ACKNOWLEDGEMENTS

This research is the fruit of efforts and encouragement provided by many
important individuals. Expression of appreciation here may be limited to only a few. I
am deeply grateful to my major advisor and the chairperson of the dissertation committee,
Dr. Edward M. Mahoney for his encouragement, support, guidance to reﬁne the work,
persistent revision until the last moment, and insights throughout completion of this
research.

A special thanks is extended to Dr. Donald F. Holecek, the director of my
dissertation, for involving me in the Michigan 2000 project. This project underpinned
much of this research. The author is truly grateful for his suggested reﬁnements and
editing.

I especially wish to acknowledge the members of my committee, Dr. Joseph
Fridgen (the chairperson of Department of Park, Recreation, and Tourism Resources) and
Dr. Bonnie Knutson (School of Hospitality Business), for their constructive ideas and
criticisms.

The deepest measure of appreciation goes to my farme and friends for their
constant encouragement, support, patience, and love. They stood beside me and shared

the exhaustion, frustration, and joy that the research and my academic work produced.

iv

TABLE OF CONTENTS

 

 

LIST OF TABLES viii
LIST OF FIGURES -- ........................... xiv
1. INTRODUCTION .................................................................................................... l

1.1 Problem Statement ........................................................................................ 10

1.2 Purpose of the Study ..................................................................................... 12

1.3 Objectives of the Study ................................................................................. 13

1.4 Research Hypotheses .................................................................................... 14

2. REVIEW OF THE LITERATURE ........................................................................ 15

2.1 Conceptualization of the Relationship Between External Environment
and Business Decisions ................................................................................. 17

2.1.1 Environment and Businesses in Organization Theory ........................ 20

2.1.2 Two Views of Environment in Organization Theory: Objective
and Perceived Environment ............................................................... 20

2.2 Research on Inﬂuence of Various Business Environment Factors on
Business Decisions ........................................................................................ 23

2.2.1 Economic/ Market Environment and Its Effect on Business
Decisions ............................................................................................ 25

2.2.2 Government Regulations and the Legal Environment ........................ 31

2.2.3 State Economic Development Policy as an Environment Factor
and Its Effects on Employment and Businesses ................................. 42

3. RESEARCH METHODS ...................................................................................... 68

3.1 Research Design and Data Collection ........................................................... 69

3.1.1 Focus Groups ...................................................................................... 69
3.1.2 Data Collection Method: The Mail Survey ......................................... 73
3.1.3 Data Preparation ................................................................................. 79
3.1.4 Data Analysis ...................................................................................... 80
3.1.5 Limitations of the Data ....................................................................... 87

4. RESULTS .............................................................................................................. 89
4.1 Descriptive Analysis of the Sample .............................................................. 89
4.1.1 General Characteristics of Responding Businesses ............................ 89
4.1.2 External Environment Variables and Businesses ............................... 95
4.1.3 Businesses Perceptions of State Government ................................... 102

4.2 Factor Analysis of External Environment Variables .................................. 111
4.2.1 Appropriateness of Data for Factor Analysis .................................... 112
4.2.2 Factor Extraction .............................................................................. 1 13
4.2.3 The Rotation of Factors .................................................................... 116

4.3 Hypothesis Test Results .............................................................................. 119
5. SUMMARY AND CONCLUSIONS ................................................................... 153
5.1 Review of the Study’s Theoretical Basis and Research Methods ............... 154
5.2 Major Findings ............................................................................................ 157
5.3 Implications and Contributions ................................................................... 159
5.4 Limitations .................................................................................................. 161
5.5 Directions for Future Research ................................................................... 163

vi

APPENDIX A

 

US. AND MICHIGAN ECONOMY AND EMPLOYMENT ENVIRONMENT

APPENDIX B

 

MICHIGAN BUSINESSES QUESTIONNAIRE

 

 

APPENDIX C

REMINDER POST CARD

 

APPENDIX D

 

REGIONS FOR CLUSTER SAMPLING

 

BIBLIOGRAPHY

 

vii

166

167

172

173

177

178

179

180

181

 

 

 

LIST OF TABLES

TABLE l-I TYPES OF GOVERNMENT ACTIONS ..................................................................... 8

TABLE 2-1 IJTERATURE PERTAINING TO KEY ELEMENTS OF FOUR THEORETICAL
CONSTRUCTs/ THEORIES OF How BUSINESSES RELATE TO THEIR
ENVIRONMENTS ............................................................................................. 19

TABLE 2-2 LITERATURE PERTAINING TO OBJECTIVE AND PERCEIVED ENVIRONMENT ....... 23

TABLE 2-3 LITERATURE THAT IDENTIFIES VARIOUS BUSINESS ENVIRONMENT
FACTORS ........................................................................................................ 24

TABLE 24 LITERATURE RELATING TO THE IMPACT OF THE ECONOMIC ENVIRONMENT
ON BUSINESS DECISIONS ................................................................................ 30

TABLE 2-5 LITERATURE PERTAINING To THE IMPACT OF EMPLOYMENT-RELATED
LAWS (LEGAL ENVIRONMENT) ON BUSINESSES AND HIRING DECISIONS ........ 41

TABLE 2-6 LITERATURE DESCRIBING IMPACTS OF STATE GOVERNMENT PROGRAMS
ON BUSINESS LOCATION DECISIONS ............................................................... 53

TABLE 2-7 LITERATURE RELATING To THE IMPACT OF STATE GOVERNMENT
PROGRAMS ON EMPLOYMENT ...................................................................... 53

TABLE 2-8 COMPREHENSIVE RESEARCH ON THE IMPACT OF EXTERNAL ENVIRONMENT
ON BUSINESS DECISIONS ................................................................................ 54

TABLE 2-9 SMALL BUSINESS INVENTORY PLANS (NET PERCENT: INCREASE MINUS
DECREASE, SEASONALLY ADJUSTED) ............................................................ 56

TABLE 2-10 SMALL BUSINESS HIRING PLANS (NET PERCENT: INCREASE MINUS
DECREASE, SEASONALLY ADJUSTED) ............................................................ 56

viii

TABLE 2-1 1 NUMBER OF FIRMS AND EMPLOYEES BY SMALL BUSINESS CATEGORY
IN THE US. .................................................................................................... 57

TABLE 2-12 LITERATURE RELATING To EXTERNAL ENVIRONMENT PROBLEMS OF
SMALL BUSINESSES ........................................................................................ 61

TABLE 2- 13 COMPREHENSIVE RESEARCH ON SMALL BUSINESS DECISION MAKING ......... 61

TABLE 3-1 INDUSTRIES AND SIZE OF BUSINESS THAT PARTICIPATED IN THE FOCUS
GROUP ........................................................................................................... 71

TABLE 3-2 CORRELATION AMONG 12 EXTERNAL ENVIRONMENTAL VARIABLES .............. 84

TABLE 4-1 THE SIZE—TOTAL NUMBER OF EMPLOYEES—OF BUSINESSES THAT
RETURNED A MAIL QUESTIONNAIRE .............................................................. 90

TABLE 4-2 THE NUMBER OF DIFFERENT TYPES OF BUSINESSES THAT RETURNED
A MAIL QUESTIONNAIRE ................................................................................. 91

TABLE 4-3 THE NUMBER OF BUSINESSES IN RE-CODED INDUSTRY SECTORS THAT

RETURNED A MAIL QUESTIONNAIRE .............................................................. 92
TABLE 4-4 TYPE OF OWNERSHIP OF RESPONDING BUSINESSES ......................................... 93
TABLE 4-5 THE NUMBER OF YEARS IN BUSINESS OF RESPONDING BUSINESSES ................ 93

TABLE 4-6 THE NUMBER OF YEAR-ROUND AND SEASONAL BUSINESSES THAT
RETURNED A MAIL QUESTIONNAIRE .............................................................. 94

TABLE 4-7 NUMBER OF RESPONDING BUSINESSES THAT CLASSIFIED THEMSELVES
To BE TOURISM BUSINESSES .......................................................................... 94

TABLE 4-8 PERCENTAGE OF TOURISM ATTRIBUTED SALES BY BUSINESSES THAT
CLASSIFIED THEMSELVES TO BE TOURISM BUSINESSES .................................. 95

ix

 

 

TABLE 4-9 RELATIVE IMPORTANCE OF EXTERNAL ENVIRONMENT VARIABLES BY
BUSINESS SIZE CLASS .................................................................................... 96

TABLE 4-10 RELATIVE IMPORTANCE OF EXTERNAL ENVIRONMENT VARIABLES BY
TYPE OF BUSINESS ......................................................................................... 98

TABLE 4-1 1 RELATIVE IMPORTANCE OF EXTERNAL ENVIRONMENT FACTORS BY
SIZE AND TYPE OF BUSINESS ........................................................................ 100

 

TABLE 4-12 DEGREE OF SATISFACTION WITH STATE AGENCIES BY BUSINESS
SIZE CLASS .................................................................................................. 104

TABLE 4-13 MEAN SATISFACTION WITH STATE AGENCIES BY BUSINESSES SIZE
CLASS .......................................................................................................... 106

 

TABLE 4-14 MEAN SATISFACTION WITH STATE AGENCIES BY TYPE OF BUSINESS .......... 107

TABLE 4-15 BUSINESS PERCEPTIONS OF THE QUALITY OF STATE SERVICES, NEEDS
FOR MARKETING OF STATE SERVICES, AND EXPERTISE OF AGENCY
EMPLOYEES ................................................................................................. 108

TABLE 4-16 PERCEPTIONS OF THE QUALITY OF STATE SERVICES, NEEDS FOR
MARKETING OF STATE SERVICES, AND EXPERTISE OF AGENCY STAFF
BY SIZE CLASS ............................................................................................. 109

TABLE 4-17 PERCEPTIONS OF BUSINESSES IN DIFFERENT INDUSTRIES HAVE OF THE
QUALITY OF STATE SERVICES, NEEDS FOR MARKETING OF STATE
SERVICES, AND EXPERTISE OF AGENCY STAFF ............................................. 1 10

TABLE 4-18 MEAN PERCEPTIONS OF THE QUALITY OF STATE SERVICES, N EEDS FOR
MARKETING OF STATE SERVICES, AND EXPERTISE OF AGENCY STAFF
BY TYPE OF BUSINESS .................................................................................. 1 10

TABLE 4-19 RESULTS OF THE KMO (KAISER-MEYER-OLKIN) AND BARTLETT’S TEST
OF APPROPRIATENESS OF THE DATA FOR FACTOR ANALYSIS ....................... 1 13

TABLE 4-20 THE PRINCIPAL COMPONENTS ANALYSIS: EIGENVALUES AND PERCENT
OF VARIANCE EXPLAINED ............................................................................ 1 15

TABLE 4-21 THE ROTATED AND UNROTATED FACTOR LOADINGS FOR TWO FACTOR
SOLUTION .................................................................................................... 1 17

TABLE 4-22 SUMMARY OF THE TWO-FACTOR SOLUTION: VARIABLE LOADINGS ON
THE FACTORS AND COMMUNALITY .............................................................. 1 19

TABLE 4-23 MEAN INFLUENCE OF THE STA TE-IMPOSED COST OF DOING BUSINESS
AND MARKET ENVIRONMENT FACTORS ......................................................... 120

TABLE 4-24 RESULTS OF T-TESTS FOR IMPORTANCE BUSINESSES ASSIGN TO THE
STA TE-IMPOSED COST OF DOING BUSINESS AND MARKET ENVIRONMENT
FACTORS IN THEIR HIRING DECISIONS .......................................................... 121

TABLE 4-25 MEAN IMPORTANCE ASSIGNED TO THE STATE-IMPOSED COST OF DOING
BUSINESS AND MARKET ENVIRONMENT FACTORS BY DIFFERENT SIZE OF
BUSINESS ..................................................................................................... 122

TABLE 4-26 TEST FOR HOMOGENEITY OF VARIANCES FOR DIFFERENT SIZE OF
BUSINESS ..................................................................................................... 123

TABLE 4-27 RESULTS OF AN OVA TESTS COMPARING THE MEAN IMPORTANCE
ASSIGNED TO THE TWO ENVIRONMENT FACTORS BY DIFFERENT SIZE
OF BUSINESS ................................................................................................ 124

TABLE 4-28 RESULTS OF T-TESTS COMPARING THE IMPORTANCE THAT SMALL,
MEDIUM, AND LARGE BUSINESSES ASSIGN To THE MARKET
ENVIRONMENT WHEN MAKING HIRING DECISIONS ...................................... 125

TABLE 4-29 SUMMARY OF T—TESTS COMPARING THE IMPORTANCE THAT SMALL,
MEDIUM, AND LARGE BUSINESSES ASSIGN To THE MARKET
ENVIRONMENT WHEN MAKING HIRING DECISIONS ...................................... 126

xi

TABLE 4-30 MEAN IMPORTANCE/ INFLUENCE OF THE STATE-IMPOSED COST OF
DOING BUSINESS AND MARKET ENVIRONMENT FACTORS ON HIRING
DECISIONS BY DIFFERENT TYPE OF BUSINESS .............................................. 127

TABLE 4-31' AN OVA TESTS OF TYPE OF BUSINESS DIFFERENCES ON THE IMPORTANCE
OF STA TE-IMPOSED COST OF DOING BUSINESS AND MARKET ENVIRONMENT
FACTORS ...................................................................................................... 128

TABLE 4-32 RESULTS OF T-TESTS COMPARING THE INFLUENCE OF STA TE-IMPOSED
COST OF DOING BUSINESS FACTOR FOR DIFFERENT TYPE OF BUSINESS ........ 130

TABLE 4-33 RESULTS OF T-TESTS COMPARING THE INFLUENCE OF THE MARKET
ENVIRONMENT FACTOR FOR DIFFERENT TYPE OF BUSINESS ......................... 133

TABLE 4-34 SUMMARY OF T-TESTS FOR THE STA TE-IMPOSED COST OF DOING
BUSINESS FACTOR BY DIFFERENT TYPE OF BUSINESS ................................... 135

TABLE 4-35 SUMMARY OF T-TESTS FOR THE MARKET ENVIRONMENT FACTOR BY
DIFFERENT TYPE OF BUSINESS ..................................................................... 136

TABLE 4-36 PERCEPTIONS OF STATE- SERVICES BY DIFFERENT TYPE AND SIZE OF
BUSINESS ..................................................................................................... 138

TABLE 4—37 TWO-WAY INTERACTIONS BETWEEN BUSINESS SIZE AND TYPE FOR
SERVICE QUALITY ........................................................................................ 140

TABLE 4-38 Two-WAY INTERACTIONS OF BUSINESS SIZE AND TYPE FOR NEEDS FOR
MARKETING OF STATE SERVICES ................................................................. 141

TABLE 4-39 TWO-WAY INTERACTIONS BETWEEN BUSINESS SIZE AND TYPE FOR
PERCEPTION OF EXPERTISE OF AGENCY STAFF ............................................ 141

TABLE 440 AN OVA FOR PERCEPTIONS OF STATE SERVICES BY SIZE OF BUSINESS ....... 142

TABLE 44] AN OVA FOR PERCEPTION S OF STATE SERVICES BY TYPE OF BUSINESS ..... I43

xii

TABLE 442 T-TESTS FOR PERCEPTION OF THE QUALITY OF STATE SERVICE BY
DIFFERENT TYPE OF BUSINESS ..................................................................... 143

TABLE 4-43 NUMBER OF STATE AGENCIES THAT BUSINESS HAVE HAD CONTACT WITH.. 145

TABLE 444 TOTAL NUMBER OF BUSINESSES THAT HAVE HAD CONTACT WITH STATE
AGENCIES .................................................................................................... 145

TABLE 4-45 MEANS PERCEPTIONS OF STATE SERVICES BY BUSINESSES THAT HAVE
AND HAVE NOT HAD PRIOR EXPERIENCE WITH 12 STATE AGENCIES .......... 146

TABLE 446 RESULTS OF T-TESTS FOR DIFFERENCES IN PERCEPTIONS BETWEEN
BUSINESSES HAVING HAD AND NOT HAVING HAD PRIOR CONTACT/
EXPERIENCE WITH 12 STATE AGENCIES ....................................................... 147

TABLE 4-47 MEAN AND S. D. FOR NUMBER OF AGENCIES CONTACTED BY BUSINESSES
AND BUSINESS PERCEPTIONS OF QUALITY OF STATE SERVICES, NEED OF
MARKETING, STAFF EXPERTISE ................................................................... 148

TABLE 4-48 CORRELATION BETWEEN EXTENT OF CONTACT WITH 12 STATE
AGENCIES AND PERCEPTIONS OF QUALITY OF STATE SERVICES, NEED
OF MARKETING, STAFF EXPERTISE ............................................................... 149

TABLE 4-49 MEAN PERCEPTIONS OF STATE GOVERNMENT AGENCIES BY BUSINESSES
WITH DIFFERENT AMOUNT (NUMBER OF AGENCIES) OF CONTACT WITH
THESE AGENCIES .......................................................................................... 150

TABLE 4-50 RESULTS OF AN OVA TEST OF BUSINESS PERCEPTIONS BY NUMBER OF
AGENCIES CONTACTED BY BUSINESSES ....................................................... 151

TABLE 4-51 RESULT OF T-TESTS FOR DIFFERENCES m PERCEPTIONS OF QUALITY OF
STATE SERVICES BETWEEN BUSINESSES WITH ONE To FIVE AND SIX TO
12 STATE AGENCIES CONTACTED BY BUSINESSES ....................................... 152

xiii

LIST OF FIGURES

FIGURE 2-1 MODEL OF THE RELATIONSHIP BETWEEN EXTERNAL ENVIRONMENT AND

BUSINESS DECISIONS ..................................................................................... 16

FIGURE 3-1 THE OVERALL RESEARCH PROCESS ............................................................... 68

FIGURE 3-2 OVERVIEW AND SEQUENCE OF THE STATISTICAL ANALYSES IN THIS

STUDY ............................................................................................................ 86
FIGURE 4-3 SCREE PLOT FOR SELECTING FACTOR SOLUTIONS ........................................ 1 15
FIGURE 4-4 COMPONENT PLOT IN ROTATED SPACE ......................................................... 1 18
FIGURE-A 1 TREND IN US. CTVILIAN EMPLOYMENT (THOUSANDs)—1986-1996 ........... 167

FIGURE-A 2 NON-AGRICULTURAL EMPLOYMENT DISTRIBUTION BY SECTOR,

U.S. & MI, 1997 .......................................................................................... 168
FIGURE-A 3 UNEMPLOYMENT RATE, U.S. & M1, 1970-1997 ......................................... 169
FIGURE-A 4 EMPLOYMENT GROWTH RATE, U.S. & M1, 1980-1997 ............................... 170

FIGURE-A 5 MICHIGAN PER CAPITA INCOME AS PERCENTAGE OF US. PER CAPITA
INCOME, 1950-1996 ..................................................................................... 171

FIGURE-A 6 MICHIGAN MOTOR VEHICLE PRODUCTION AS A PERCENTAGE OF US.
PRODUCTION, 1970-1996 ............................................................................ 171

xiv

Chapter 1

1. INTRODUCTION

Over the last twenty years there have been signiﬁcant changes in the structure of
the economies of both the US. and the state of Michigan (Kutscher and Mark, 1983;
Fosler, 1988). The national income produced by the service industry (1,230.7 billion
dollars in the last quarter of 1994, 1,335.9 billion in the last quarter of 1995, and 1,399.5
billion in the ﬁrst quarter of 1996) has exceeded that of the manufacturing industry (991.2
billion dollars in the last quarter of 1994, 1,026.3 billion in the last quarter of 1995, and
1,041.2 billion in the ﬁrst quarter of 1996). If the ﬁnance (938.8 billion dollars),
insurance (991.9 billion dollars), and real estate industries (1,017.8 billion dollars) are
included as part of the service sector, the total income generated by the service sector
becomes even larger (US. Department of Commerce, 1996, p.25).

The annual average employment of all manufacturing businesses in the United
States of America declined from 1967 (19.3 million) to 1972 (19.0 million), increased
brieﬂy in 1977 (19.6 million), and then continued to decline in 1982 (19.1 million), 1987
(18.9 million), 1991 (18.1 million) and 1992 (18.3 million) (US. Bureau of the Census,
Census of Manufactures, 1967, 1972, 1977, 1982, 1987 and 1992 ; Annual Survey of
Manufactures, 1992). Between 1960 and 1981, the number of jobs in goods-producing
industries (manufacturing, mining, and construction) increased at an average rate of 1.0
percent a year. By comparison, employment in service industries (all other industries,

such as hotel, tourism, medical, professional, personal, and several other services) grew

by 3.2 percent annually (Kutscher and Mark, 1983, p.21). These growth trends have
continued in the 19903. For instance, employment in the service sector was 28,000,000 in
1990 and increased to 30,654,000 in 1992 (The National Data Bank, 1995). In 1993 and
1994 the number of full-time and part-time employees accounted for by the service sector
was 32,633,000 and 33,634,000, respectively, whereas for the same years the number of
full-time jobs in the manufacturing industry was 18,173,000 and 18,429,000 respectively
(US. Department of Commerce, 1996, p. D-3 1).

The Michigan economy reﬂects the nation-wide growth of the service industry
and the decline of the manufacturing industry. Although manufacturing, especially the
automotive industry, has served as the basis of the Michigan economy, signiﬁcant
changes in the composition of Michigan’s economy were inevitable during the last two
decades. The proportion of all employment in the manufacturing and automobile
industries in Michigan was higher than in the other states until the late 19705. Due to
foreign competition in the automobile and other manufacturing industries, e. g. machine
tools and primary metals, and the high cost of doing business, e. g. workers’
compensation, unemployment insurance, and state and local taxes; high wages; high
energy costs; and an overly bureaucratized, insensitive government regulatory system, in
the state, Michigan had a poor business climate in the early 19803 (Kutscher and Mark,
1983; Fosler, 1988). As a consequence, Michigan lost its traditional advantage over the
rest of the nation in basic manufacturing. A more detailed description of Michigan

economic trends is included in Appendix A.

In contrast, a total of 83,000 new jobs were created in the service sector between
1978 and 1984. The number of new service businesses in Michigan outpaced business
failures by 3 to 2, and 60 percent of the continuing service businesses grew in Size by an
average of nearly 60 percent (Leveson, 1985; Fosler, 1988). In the years following 1984,
service businesses continued to grow at very rapid rates and became a substantial part of
the state economy in terms of employment. These jobs were generally high-skill and
high-status jobs, not fast-food industry jobs (Fosler, 1988). The service industry also
provided the main avenue for absorbing the large labor supply of women, minorities
youth, immigrants, and displaced workers (Leveson, 1985).

There has been a similar growth in the tourism sector of the service industry.
During the transition from a manufacturing to a service economy in Michigan, tourism
provided a needed boost to the economy by creating jobs and promoting regional
economic development (Fosler, 1988). Bonnett (1993) suggested the tourism strategy as
a basis for entrepreneurial activity by using tourism as a means of drawing the outside
market into the local economy. As more tourists visit the state, more opportunities can be
created for business development and job creation in: hotels, restaurants, and various
service businesses.

Business Environment

The continued growth and success of these businesses are heavily dependent on
how cost effectively they respond to changes in the external environment, including the
actions of different levels of government, e. g. taxation and safety regulation

(Marcus,l993). To succeed, both manufacturing and service businesses must take

advantage of opportunities and respond to outside threats. Businesses must continuously
make decisions related to their people, ﬁnancial resources, innovations, and strategies
(Sturdivant and Vemon-Wortzel, 1990). Business decisions involving start-up, retention,
investment, and expansion are affected by factors that comprise the ever-changing
external environment. Understanding the relationship of businesses with elements of
their external environments is, therefore, an important area of inquiry.

The important elements of the external environment are: (1) the economy and
economic trends; (2) cultural and social trends; (3) legal and political decisions and
actions, including government policies; and (4) technologies, e. 3. service technologies
and communication technologies (Chamberlain, 1970; Steiner, 1975; Hofstede, 1981;
Marx, 1985; Sturdivant and Vemon-Wortzel, 1990).

The economy and economic factors, including inﬂation, employment, wage rates,
and interest rates, are of Significant interest to businesses. Changes in the economy can
create disadvantages, such as uneven income distribution, imbalance of payments,
unemployment, and a low rate of savings or capital investment (Sturdivant and Vemon-
Wortzel, 1990). On the other hand, economic changes and trends can create expansion
and proﬁt opportunities, such as the increasing size of the American market itself, a better
qualiﬁed labor market, and favorable consumer demand for business (Steiner, 1975).

External trends, such as changing consumer tastes and needs, have a major
inﬂuence on the economy, because the production of services and goods are dependent on
consumer preferences that are expressed in the marketplace (Marx, 1985). The

characteristics and quality of the labor market, such as changes in age structure, racial

composition, and the work ethic, are also important elements of the external environment
(Chamberlain, 1970). In the case of micro—economic environments, stakeholders, such as
competitors, suppliers, lenders, and shareholders, are also important elements (Sturdivant
and Vemon-Wortzel, 1990).

Culture, another element of the external environment of businesses, provides
guidance and a common framework for people and institutions of a society (Hofstede,
1981). In every society there is a continuous interaction among social values, institutions
(e. g. governments, businesses, and schools), and individuals (e.g. Consumers, employers,
and employees).

Many of the economic and social conﬂicts caused by these interactions (e. g.
conﬂicts in values and attitudes among individuals) are resolved in the legal and political
sphere. For example, social activists may try to accomplish their goals by pressing for the
passage of legislation to restrict or eliminate certain business practices or product
categories. On the other hand, businesses Often use political inﬂuence to prevent the
passage of restrictive legislation or to try to weaken proposed laws or policies (Steiner,
1975; Marcus, 1993).

The legal environment includes acts passed by various lawmaking bodies, as well
as administrative rules to implement legislation (Sturdivant and Vernon-Wortzel, 1990).
The principal purpose of many laws and regulations aimed at businesses, such as price
and wage regulations, labor laws, product laws, environment regulations, safety laws, and
business licensing laws, is to encourage and maintain a desirable level of competition.

Managers and owners of businesses need to use a variety of methods to inﬂuence the

political and legal process. It is important, therefore, for business people to know the
administrative agencies that enforce laws and implement policies, to understand how they
make decisions, and to determine the most effective ways that businesses can work with
them (Pfeffer and Salancik, 1978).

Since technology can contribute to economic growth and development,
forecasting technological change is important to managers and owners of businesses.
Generally speaking, the technological environment is concerned with technological
progress, e. g. new processes or materials and even advances in fundamental science
(Narayanan and Fahey, 1987; Sturdivant and Vemon-Wortzel, 1990). Technological
advance provides new products and automation services to all industries. For example,
electronic mail systems make instant transfer possible and erase the delay of time-zone
differences. Marketing through Internet web pages reaches vast numbers of prospects and
changes the way a business communicates with customers. The new technologies Of
multimedia communications Via video conferencing, global reservation systems, and
automated booking systems especially affect the travel and hospitality industries
(Kasavana and Cahill, 1992).

Relevancy and Importance of Government

None of these environment factors is more prevalent and evasive than
government(s). According to Porter (1990), no structural analysis of an industry is
complete without a diagnosis of how government policy, at all levels, affects businesses.
Government policy is of strategic importance to businesses, because it often impacts the

size and structure of markets, the cost of doing business, and many aspects of making

business decisions (Marcus, 1993). A study by Franklin and Goodwin (1983) found that
small businesses, as well as large businesses, ranked external factors, including
government policies, as the major cause of their problems. According to Peterson,
Kozmetsky and Ridgway ( 1983), approximately 40 percent of the small businesses they
studied also cited external factors as the major determinants of small business failure,
most of them government related.

The role of state government in economic development has recently emerged.
The US. federal and state governments have acted to encourage and support economic
development and the growth of various industries (Scheible, 1991; Boeckelman, 1989).
Many state governments have attempted to lure and retain mobile capital by creating a
“good” business climate through the Offering of incentives to businesses that lower their
costs. In Michigan’s case, the former governor, James Blanchard, and his administration
tried to provide a good business climate by changing the business community’s negative
View of state government (Osborne 1988, p.171). More recently, Governor Engler has
acted to reduce the tax rate on new businesses. He reduced taxes by eliminating the cost
of workers’ compensation, social security, and unemployment insurance from the
business tax base, by cutting the Single business tax (SBT), and the alternative proﬁts tax,
by reducing the minimum unemployment insurance tax, and by providing property tax
relief for farmers. In order to create more jobs, Governor Engler released a compilation
of 28 projects that have chosen to locate in the state’s 11 tax-free “Renaissance Zones” in
several economically distressed areas of Michigan (Rothwell, 1997a). The incentives

Offered by state governments are categorized in Table 1- 1.

Table 1-1 Types of Government Actions

 

incentives

Description

 

Tax policy
General Tax Structure

Types and rates of taxes imposed on individuals and businesses.
Low taxes are viewed as desirable.

 

Tax incentives

Exemptions, credits, and abatements to reduce taxes for businesses
in order to encourag investment.

 

Debt Financing

Direct Loans, publicly chartered but privately financed pooled
development funds, loamuarantees, and revenue bond financing.

 

Labor Incentives

Right-to work laws, job training programs, workers’ compensation and
unemployment insurance

 

Regulatory Policy

Minimal environmental regulations and a streamlined process for
obtaining business permits are viewed positively by businesses.

 

Industrial and Commercial
Site Development

Subsidized industrial parks and land banks

 

Targeted Financial
Assistance for Capital and
Infrastructure

Tax abatements and capital subsidies only to the firms that locate in
high unemployment areas

 

Tax Increment Financing

Municipalities earmark all of the anticipated increased property tax
revenue that will result from a new development project to back
bonds that go to help certain elements of that project.

 

State Enterprise Zones

Specific zones in which barriers to entrepreneurial activity are
reduced.

 

Venture Capital Programs

Provide high risk financing to small businesses at the gestation, start-
up, and early expansion stages (e.g. development credit corporations,
venture capital loan programs, product-development corporations,
pension fund venture pools, and venture capital corporations)

 

High Technology Policy

High-technology research and product development to respond to
emerging markets are encouraged (e.g. research grant programs,
“human capital” programs, gubernatorial task forces and
commissions, and university-industry research centeg).

 

Science or Research
Parks

These are reservations for firms engaged in high-tech research
efforts that can profit from close proximity to a university's research
efforts (e.g. technical assistance).

 

 

Export Promotion
Activities

 

State and local governments promote the export of goods produced
by local businesses to capitalize upon sources of demand (e.g.
service activities, and market-development functions).

 

Source: Complied from Peter K. Eisinger, The Rise of the Entrepreneurial State, 1988,

pp.128-l99.

 

Although there has been a very noticeable shift toward service employment and
growth, most of these government programs appear to be aimed more at promoting large
manufacturing ﬁrms, not service and tourism businesses. Employment growth of the
service industry, including tourism and small businesses, however, is beginning to attract
more attention from policy makers (Eisinger, 1988).

Both federal and state governments are actively engaged in various efforts which
attempt to develop and market the tourism industry. More and more they have
recognized the importance of tourism to the nation’s economy and its vital role in
marketing the country as a travel destination both domestically and internationally. For
instance, President Bush appeared in a tourism promotion video program called,
“America, Yours to Discover” (Lee, 1993, p.109). The state of Michigan has invested in
two major tourism image campaigns, the “Say Yes to Michigan” in the 1980s and
recently “Great Lakes. Great Times” (Rothwell, 1997”).

Small businesses are also attracting greater attention by federal and state policy
makers, because they have an important position in job creation and regional economic
development (Birch, 1979). Studies conducted by Birch (1979) concluded that small
businesses create the majority of all new jobs in the United Sates and contribute to the
strength of regional economies. Unlike large industries, the proﬁt attained by locally
owned small business tends to be reinvested locally and strengthen the local economy
(Basset, 1995). Michigan’s evolution into a service and tourism economy from the

automobile manufacturing dominated economy has played a signiﬁcant role in the

process of small business development that has contributed to increased employment

(Leveson, 1985).

1.1 Problem Statement

1n recognizing government policies as an important external inﬂuence on
businesses, a number of previous studies have examined the effect of speciﬁc government
policies on various industries, e. g. expansion, investments, and proﬁts, according to
changes in tax policy. No study could be identiﬁed that examines the relative inﬂuence
of various government actions and policies on different types and Sizes of businesses. A
better understanding of the comparative impacts of government policies and programs on
different industries would be helpful in assessing proposed laws, regulations, and
business attraction and retention strategies (Due, 1961; Kienschnick, 1981; Schmenner,
1982; Schmenner et al., 1987; Newman and Sullivan, 1988).

The majority of state economic development and business retention strategies
have focused on enticing and retaining manufacturing companies by offering low tax
rates and other forms of tax incentives. As a consequence, research in this area has been
primarily directed at factors that inﬂuence business-location decisions. Much of this
research centers on the impact of taxes on business location and investment decisions
(Boeckelman, 1989). The author was unable to locate a study that simultaneously
assessed the impact of factors in the external environment or a broad range of government

actions and policies across different types and Sizes of businesses.

10

Almost all state governments have developed and implemented programs that
encourage business (for example, manufacturing) location, expansion, and retention
Without having sufﬁcient knowledge about the potential and actual effectiveness of
policies, regulations, and incentives on different sizes and types of businesses. States
offer tax exemptions on inventories, on new equipment, and on various forms of land and
capital improvements, but there are few follow-up studies on the impact of these tax
exemptions (Dubnick, 1983). There are even fewer published studies of the long-term
beneﬁts versus cost of these programs. Many of the studies that have been conducted
raise questions relating to the cost-effectiveness of various tax incentive programs
(Hellman, Wassall, and Falk, 1976; McHone, 1984).

Despite the increasing importance of the service and tourism industries in regional
and local economic development and job creation, there has been less effort aimed at
attracting and retaining these businesses than there has been in attracting manufacturing
businesses (Smith and Fox, 1991; Luxenberg, 1994). No studies addressing the inﬂuence
of the external environment, especially government actions targeted at these industries,
could be identiﬁed (Johnson and Thomas, 1992). There is little scientiﬁc information
that indicates Whether or to what extent service businesses respond to government
programs (e. g. tax incentives) as do the government programs offered to manufacturing
businesses. Nor is there much information pertaining to how tourism- and service-related
businesses respond to other external environment factors, such as consumer and labor

markets, or whether they respond in the same fashion as manufacturers.

ll

The lack of such information makes it difﬁcult for governments to develop and
assess the potential impact of policies and actions that will effectively attract, retain, and
stimulate the expansion of the service and tourism sectors. There is a continuing need for
studies and evaluations of the relative effectiveness and sustainability of various policies

and incentives that could be developed for tourism and service businesses.

1.2 Purpose of the Study

The primary purpose of this study is to identify and better understand the relative
importance of various external environment factors, especially the effects of government
actions on business decisions, particularly in the hiring of additional employees. Another
purpose is to determine whether and to what extent different types (e. 3. service, tourism,
manufacturing, and agriculture) and sizes of businesses respond differently to various
factors that comprise their external environments, with special attention given to state
government policy.

This study is designed to provide policy makers with information and analyses to
help them to better understand how different industries respond to various government
policies and actions. Such understanding provides the basis for developing policies that
achieve different objectives for different types and sizes of businesses. For instance, if
policy makers understand that the service industry is inﬂuenced mostly by labor market
conditions rather than by tax policy, they will have clues to better meet the needs of this
industry. Such knowledge can allow policy makers to provide appropriate policies and

programs for different industries that will improve the economy in Michigan.

12

1.3 Objectives of the Study

The purposes of this study will be achieved by accomplishing the following ﬁve

objectives:

1.

Determine the underlying environment factors that inﬂuence business decisions which
relate to the number of employees that businesses hire.

Determine the importance that different types and sizes of businesses assign to various
environment factors, including government policy, in making their business decisions.
Determine whether and the extent to which the characteristics of a business (e. g.
ownership, number of years in business, or seasonal vs. year-round) inﬂuence
perceptions of state government services and expertise.

Compare the perceptions that owners and managers of different types and sizes of

businesses have of state agencies, their services and their expertise.

. Determine if and to what extent, previous experiences with state agencies inﬂuence the

perceptions that owners and managers have of those agencies and the quality of the

services they provide.

13

1.4 Research Hypotheses

The following research hypotheses were tested to achieve the research objectives.

1. The market environment factor is more important than the state-govemment-imposed
cost of doing business factor in ﬁrms’ hiring decisions.

2. There is a signiﬁcant difference between small, medium, and large businesses
(determined by total number of employees) in terms of the relative importance of
various environment factors on their hiring decisions.

3. Small businesses are less inﬂuenced by the market environment, consumer demand
and access to qualiﬁed labor, in their decision making than are medium- or large-Sized
businesses.

4. There is a signiﬁcant difference between businesses in different industry sectors in
terms of the relative inﬂuence of various environment factors on their hiring decisions.

5. The perceptions of state government, including the expertise of state personnel and the
degree of satisfaction with State-govemment services, are inﬂuenced by the business
type and Size.

6. Businesses that have had prior experience with state agencies are generally more
satisﬁed with the quality of their services than are businesses that have had no or very

limited prior experience with government agencies.

14

Chapter 2

2. REVIEW OF THE LITERATURE

This section provides an overview of literature pertaining to the inﬂuence and
impact of various external environment factors upon business strategies and business
decisions relating to hiring. AS presented in Figure 2-1, the literature search identiﬁed a
vast amount of relevant theories and empirical studies exploring the importance and
inﬂuence of various external environment factors on ﬁrms’ decisions. This review,
however, focuses more on government policies and actions that impact business
development and expansion.

A substantial body of research has long established that the external environment
is Signiﬁcant to business outcomes or behavior (Mockler, 1975; Steiner, 1975; Sawyer,
1979; Marx, 1985; Sturdivant and Vemon-Wortzel, 1990; Marcus, 1993). Furthermore,
today’s managers face external inﬂuences that are changing dramatically. The managerial
task today, therefore, is more complex than in the past because of the rapid changes
taking place in the external environment to which organizations must adapt for survival

and development (Steiner, 1975; Dilts and Prough, 1987).

15

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16

Figure 2-1 Model of the Relationship Between External Environment and Business Decisions

2.1 Conceptualization of the Relationship Between External Environment
and Business Decisions

The general theoretical notion that environment factors inﬂuence organizational
strategies and decisions is not a new one. These types of relationships have been
conceptualized and evaluated in a number of ﬁelds. Theoretical development has been
stimulated by organization theory (OT) regarding organization-environment strategic
decision making (Bourgeois, 1980). Organization theory (OT) has assumed a more
reactive stance by viewing the environment as a deterministic force to which
organizations must respond. An elaboration of the notion of environment can be
accomplished by categorizing the environment into its Objective and perceived states
(Bourgeois, 1980).

The objective environment can be further divided into “task” and “general.”
Bourgeois (1980) suggests that the objective external environment and its variability are
the source of ﬁrms’ opportunities and risks and as such must be included when decisions
are made and executed, whereas managers’ perceptions of the environment are part of the
decision making process. Organizational researchers have investigated the causal
relationship between different environments, organizational strategic decision making,
and ﬁrm performance (Dill, 1958; Burns and Stalker; 1961; Duncan, 1972; Bourgeois,
1978, 1980).

Industrial organization economics (IOE) theory is mostly concerned with the
impact of environment factors, such as business position and industry structure on ﬁrm
performance or behavior (Bain, 1956; Scherer, 1970; Gale, 1972; Caves and Porter, 1978;
Newman, 1978; Hatten, Schendel and Cooper, 1978; Porter, 1980,1981). On the other

17

hand, the business policy (strategic management) literature has evaluated the extent to
which organizational performance is inﬂuenced by strategy decisions at the expense of
external or industry factors (Chandler, 1962; Bower, 1970, 1972; Rumelt, 1974).

Finally, organizational ecology has contributed two research streams relevant to
the question of ﬁrms and their environments. One of the streams, population ecology, has
focused primarily on the issue of external environmental control of organizational
behavior (Aldrich, 1978). This approach posits that organizational actions are dependent
on the availability of critical resources usually controlled by other organizations or
institutions. Since organizations are not internally self-sufﬁcient, they require resources
from the environment. The other stream, resource dependence theory, also addresses
intra-organizational constructs (Pfeffer and Salancik, 1978). The latter theory holds that
organizational behavior becomes externally inﬂuenced by the elements of environment,
because the organization must obtain resources necessary for its continued survival and
success (Pfeffer and Salancik, 1978). Elements of the four major research streams related

to environmental inﬂuence are presented for comparison in Table 2-1.

18

Table 2-1 Literature Pertaining to Key Elements of Four Theoretical Constructs] Theories
of How Businesses Relate to Their Environments

 

 

 

 

 

 

Theoretical Approach Environment Factors/ Firm Behaviors Author (Year)
Concepts Affected (Decisions)
Organization Theory Uncertainty Managerial Dill (1958);
(OT) Variety Autonomy Burns & Stalker (1961);
Dynamism Organizational Lawrence & Lorsch
Complexity Form/ Structure (1967);
Performance Galbraith (1973, 1977)
Information
Processigng
Industrial Organization Industry Structure Economic Gale (1972);
Economics (IOE) (Barriers, Numbers of Performance Caves & Porter (1978)
buyers and sellers, Competitive Hatten, Schendel, &
etc.) Business Position Strategy Cooper (1978);
(Market Share, Porter (1980, 1981 ,
Strategic Groups, etc.) 1990)
Business Policy (BP) Product! Market Business Strategy Hofer (1975);
Characteristics Performance Ansoff (1 965);
Corporate Strategy Organizational Anderson & Zeithaml
(e.g. diversification) structure (1 984);
Resource Allocation Strategy (Decision Chandler (1962);
(within Functional Making) Rumelt (1974);
areas) Bower (1 970, 1972)
Organizational Uncertainty Survival (Through Aldrich (1979);
Ecology Compatibility of Variation, Selection Pfeffer & Salancik
Population Ecology Resource States and Retention) (1978)
Resource Environmental Gain Strategies (Adapting
Dependence lnterorganizational or Modifying the
Dependence Environment)

 

Organization Set
Resource-Dependence
lntraorganizational
Power

 

 

 

Source of literature: White and Hamermesh, 1981; Bourgeois and Astley, 1979;
Bourgeois, 1980; Pfeffer, 1982; Carroll, 1984

19

 

2.1.1 Environment and Businesses in Organization Theory

Since the fundamental premise of this study is to test the impact of external
environments on business decisions (strategic decisions), organization theory provides the
conceptual basis which can be used to guide this research. Organization theory has
conceptualized organizations as open systems engaging in transactions with their
environments. Dill (1958) pioneered a study that both deﬁned the components of top
management’s task environment and suggested a causal relationship in which this task
environment affected managerial autonomy. Subsequent researchers have utilized larger
sample sizes than the two-ﬁrm sample used by Dill (1958) and have enriched the
deﬁnitions of environment (Bourgeois, 1980). Also conceptual pieces, such as written by
Thompson (1967) and Terreberry (1968), emphasized that organizations must adapt to
external forces in order to maintain viability. Woodward (1965) and Perrow (1967)
extended the research to include technology as a determinant of environments. Galbraith
(1973, 1977) bridged environment and technology by focusing on the environmental
information-processing needs of an organization. Most of these works utilized ﬁeld
studies and correlation techniques to impute a causal link from environment to

organization.

2.1.2 Two Views of Environment in Organization Theory: Objective and
Perceived Environment

The environment literature centers on two questions, one philosophical and the
other methodological. The philosophical question is: Which perspective of the construct
of “environment” is most relevant to an organization’s behavior—its manager’s

20

perceptions of environmental states or some objective characteristics of its environment?
Since most of the literature does not distinguish between the environment as an objective
set of components and the environment as perceived by owners or managers of the
organization, uniform treatment of the environment emerges as a methodological issue
(Bourgeois, 1980).

Environments are classiﬁed into two categories based upon the perspectives of
environmental research and organization theory. Organizational environments have been
deﬁned as (1) objects and (2) perceptions. In the ﬁrst category, Dill (1958) made the
distinction between general and task environments. The task environment is viewed as
the most direct short-term impact on the organization, while the general environment (the
environment beyond the task environment) is Viewed as a ﬁeld into which an organization
may enter at some point in the future (Thompson, 1967). Thompson (1967) also
distinguished between the task environment and an additional “residual” environment
composed of potential task environments. The task environment was composed of the
four environmental components: (1) customers (distributors and users); (2) suppliers (of
material, labor, equipment, and capital); (3) competitors (for both markets and resources,
such as ﬁnancial resources); and (4) regulatory groups (governments, government
agencies, and unions) (Dill, 1958; Thompson, 1967). Duncan (1972) later added
technology into these components.

The second category consists of deﬁnitions that treat environment in terms of
managerial perceptions of environmental uncertainty. While the perspective of objective

environment focuses on the environmental components that are “outside” the

21

organization and uses objective indicators of the environment, some researchers consider
management’s perceptions of the components (Bourgeois, 1980). For example, Weick
(1969) argues that the environment becomes known to the organization only through
managerial perceptions (Tosi, Aldag, and Storey, 1973; Miles, Snow, and Pfeffer, 1974;
Anderson and Paine, 1975; Downey, Hellriegel, and Slocum, 1975; Starbuck, 1976;).

Hambrick and Snow (1977) later argue in support of this paradigm and assert that
the objective reality of physical environmental attributes is consequently less important in
determining or inﬂuencing organizational action or decision making. Every ﬁrm has an
objective environment that places constraints on the way it operates and makes decisions
(e. g. an industry group has certain technical characteristics that must be attended to).
Therefore, it is the differing perceptions of owners or managers that are considered to be a
crucial input to the strategic decision making process (Bourgeois, 1980). As an example,
in a study on the decision making behavior of a proﬁt-maximizing ﬁrm that perceived a
recession, Leban and Lesoume (1983) concluded that the perceived problem of a
recession by a ﬁrm was enough to launch a real recession. In order to manage the
perceived change, the ﬁrm was confronted with three choices: (1) investment; (2)
recruitment; and (3) ﬁring. Management chose the third. Table 2-2 summarizes the two
different perspectives of the environment as treated in the operational literature.

Many researchers have later agreed that environments can affect ﬁrms’ strategic
decisions (Clark, 1971; Rockart, 1979; Jauch et al., 1980; Jemison, 1981; White and
Hamermesh, 1981; Hambrick, 1983). Research has also shown that external business

environments can affect a ﬁrrn’s performance and success (Porter, 1981; Kefalas, 1981;

22

Hansen and Wemerfelt, 1989). Kefalas (1981) has argued that managers can perceive
and analyze Six sectors of their external environments: (1) public; (2) government; (3)
technology; (4) domestic market; (5) world market; and (6) ecology and anticipate the
impact of these six sectors on their businesses to make better decisions. Such anticipation
guarantees greater probability of survival in the face of sudden changes and better

performance in the long term (McArthur and N ystrom, 1991).

Table 2-2 Literature Pertaining to Objective and Perceived Environment

 

 

Perspectives Dimensions Operational Definitions
Objective Environment General Environment Not Operationalized for
organization theory;
Task Environment Customers, competitors,

suppliers, and regulatory
agencies (Dill, 1958;
Thompson, 1967; Duncan,

 

 

1 972)
Perceived Environment Perceived Environmental Lack of information;
Uncertainty knowledge about decision

outcomes; ability to estimate
the effects of the environment
on a firm's performance
(Duncan, 1972; Lawrence &
Lorsch, 1967L

 

 

 

Sources of literature: Duncan, 1972; Starbuck, 1976; Bourgeois, 1980.

2.2 Research on Inﬂuence of Various Business Environment Factors on Business
Decisions

The impact of external environments on ﬁrms has received some research
attention in the form of empirical studies that attempt to identify the factors or elements
of external environments that may impinge on the success of a business. The early work
by Bruno and Tyebjee (1982) summarized the ﬁndings of 17 Studies reporting the

importance of 12 environment factors. Articles reviewed by Bruno and Tyebjee were

23

 

either based on observational type studies or surveys of the perceptions of business

owners or mangers (Bruno and Tyebjee, 1982). After reviewing previous studies of the

impact of external environments on businesses, economic or market factors (e. g.

consumer and labor markets), governmental and legal factors, ﬁnancial or operating cost

factors (e.g. taxes, workers’ compensation, unemployment insurance, and cost of

beneﬁts), and technological factors seem to emerge as recurrent and important factors that

inﬂuence business decisions. Table 2-3 lists the factors identiﬁed in the research

reviewed by Bruno and Tyebjee.

Table 2-3 Literature that Identiﬁes Various Business Environment Factors

 

 

Environment Factors Author (Year)
Accessibility of Suppliers Cooper (1970);
Shapero (1972);

Schollhammer & Kuriloff (1979)

 

Accessibility of Customers or New Markets

Stanford Research Institute (1962)

 

Favorable Government Policies

Hollingsworth & Hand (1979); Cooper (1973);
Mahar & Coddington (1965); Vesper 8. Albaum
1 979)

 

Availability of Supportingéervices

Naumes (1978)

 

Availability of Land or Facilities

Mahar & Coddinﬂcgon (1965L0uirt (1978)

 

Availability of Transportation

Mahar & Coddington (1965); Cooper (1973);
Schary (1979L

 

Experienced Entrepreneurs and Incubator Cooper (1970);
Organizations Naumegﬂ 978)

 

Technically Skilled Labor Force

Draheim (1972); Stanford Research Institute
(1 962)

 

Venture Capital Availability

Cooper (1970); Susbauer (1972); Hoffman
(1 972)

 

Proximity of Universities

Shapero (1972); Cooper (1973); Mapes (1967):
Allison (1965)

 

Receptive Population

Mahar & Coddington (1965); Cooper (1970)

 

 

Attractive Living Conditions

 

Shapero (1 972); Cooper (1 970, 1973); Mahar &
Coddington (1 965)

 

Note: Adapted from Bruno and Tyebjee, 1982.

24

 

2.2.1 Economic] Market Environment and Its Effect on Business Decisions

Factors comprising the economic environment (e.g. interest rates, consumer
demand, labor-market trends, and inﬂation) can be characterized as the “competitiveness”
of the external business environment. These factors are also like double-edged swords, in
that they can represent both threats and opportunities to businesses. For example, the
US. economic upturn after the recession of 1990-1991 and the growth in the number of
service businesses created a shortage of service workers, which pushed up wages for
front-line service staff (Marcus, 1993). In the same context, Conan (1994) Stated that the
food service industry faced a declining number of skilled kitchen workers for moderately
priced restaurants, which was due to a labor Shortage. In the Hospitality’s 5th Vision
Forum in 1996, the participants from Papa Ginos of America, Inc., ITT Sheraton Corp.,
and Bugaboo Creek Steak House, Inc. agreed that the labor shortage was a problem in the
hospitality industry for which they discussed strategies to face the issue (DeLuca, 1996).
The economic recovery in the US. stimulated growth in consumer demand for domestic
production, in corporate cash ﬂow (up 15 percent in 1992 and 10 percent in 1993), and in
weekly working hours of manufacturing employees (the longest since October 1966)
(Anonymous, 1992“).

The research on decision-making behavior of businesses by Leban et al. (1983)
also supported the premise that economic trends, including consumer demand, inﬂuence
ﬁrms’ hiring decisions. Their results showed that businesses facing recession and
decreased consumer demand increased the number of employee ﬁrings and demonstrated

a stronger irregularity in recruitment.

25

Today, the deﬁnition of economic environment must be expanded to include
economic conditions and actions of other countries. For example, recent downturns in
the economies of several Asian Paciﬁc countries have caused major economic challenges
for those countries and have created enormous amounts of unemployment, high interest
rates, and high inﬂation. Such Situations have caused big corporations to downsize and
have forced a systematic internal restructuring of many ﬁrms in the Asian Paciﬁc region.
The recent economic collapse in Asian countries has also begun to inﬂuence the US.
market and economy mainly in unfavorable ways (e. g. dampening the ﬂow of US.
exports).

Conversely, changes in the economic environment can also create Opportunities
for business development and increased proﬁts. Although the current challenging Asian
economic situation has led to increased rates of unemployment, it has also been an
opportunity for many companies to build a more qualiﬁed labor force than would be
possible in rapidly growing economy. For many Asian countries, high unemployment
rates can be an opportunity, especially for foreign companies or small businesses, to hire
more qualiﬁed labor. Thanks to downsizing among big companies, small businesses can
gain the upper hand when they hire skilled labor (Mamis, 1997). Furthermore, many low-
Wage, yet qualiﬁed laborers from foreign countries, serve to offset the tightening US.
labor market. For example, the US. government has recently allowed high-tech
companies to resume hiring foreign engineers in order to solve the engineer shortage

situation (Elliott, 1997).

26

 

Today’s strong consumer demand for products and services, easier access to credit
by ﬁrms, and low interest rates represent a positive economic environment (Hymans,
Cary, and Wolfe, 1996; Curtin, 1996; Cary, Fulton, and Hymans, 1996). The results of
“The Survey of Consumers “ published by the Survey Research Center at the University
of Michigan, also reﬂects the trends of a strong economy and stable consumer conﬁdence
in recent years, as indicated by the favorable consumer sentiment index, cited by Curtin
(1996): average 92.3 in 1994, 92.2 in 1995, and 92.7 in October, 1996.

Consumers’ conﬁdence in their ﬁnancial Situations lead to higher demand for
products and services, which in turn stimulates employment growth. Keyser (1997)
reports that customers’ demands are currently high, with focus on higher levels of service
and more value. A report from the National Federation of Independent Business (NFIB
Education Foundation, 1998; Anonymous, 1998) also supports the case of a positive
impact of a favorable consumer market on businesses. According to the report, even
small businesses have added more employees at a high rate during the period 1996-1997
and plan to hire more in the near future. The recent job market in other business sectors
also shows signs of a hiring boom and low unemployment rates (Berrnan, 1997).
According to a recent report on the prospects for the US. economy, the average
unemployment rate was 5.65 percent in the third quarter of 1995, 5.24 percent in third
quarter of 1996, and projected to steady rates of 5.27 percent in third quarter of 1997 and
5.36 percent in same quarter of 1998 (Hymans, Cary and Wolfe, 1996).

Businesses currently face a tightening labor market that has been accelerated by a

Strong economy fueled by strong consumer demand. The US. Bureau of Labor Statistics

27

also predicts a continuing shortage Of qualiﬁed workers for the 18 million new jobs that
will be created by the year 2000 (Sullivan and Duplaga, 1997). As a result, a growing
body of research has emerged that is concerned with the impact Of a tighter labor market
on businesses. The main impact on employers is the increased cost of doing business that
is due to higher wages, more employee beneﬁts (e. g. more incentives, bonuses, and
higher compensation), time-consuming recruitment, and expanded training requirements
(Sargent, 1988; Cooper and Madigan, 1996). Coping strategies for businesses to reduce
costs related with tightening labor markets have been identiﬁed. Golden and Appelbaum
(1992) recommend increased use of temporary employees (a rise of 2.5 times already
between 1982 and 1988) as a strategic decision by businesses for reducing labor costs.
Such employment decisions that trend toward hiring older workers (Sullivan and
Duplaga, 1997), hiring more part-time workers than full-time (Higgins, 1996), hiring low-
wage foreign workers (Vijayan, 1997), providing more training opportunities for
employees to upgrade their skills (e. g. developing apprenticeships for the food service
industry by The American Culinary Federation), and proViding incentives for skill-based
compensation programs (Conan, 1994; DeLuca, 1996; Ermel and Bhol, 1997) have been
tried by employers and managers with the aim of attracting and retaining Skilled workers,
as well as simultaneously reducing labor costs.

Another impact of a tight labor market that has been discussed in the literature is
the constraint of economic grth throughout the U.S., especially in the Midwestern
States (Buss, 1996; Cobb, 1996). Structural changes in the Midwest during the1990s have

left the economy very different from what it was in the late 19708 and early 19803. By

28

 

 

IL

1994, however, job growth in the nation had caught up to the Midwest and by 1996, had
surpassed it. In 1997, Midwest job growth was only about 1.4 percent compared with the
nation’s 2.2 percent, which was mainly due to a labor shortage (Kaglic, 1998).
Furthermore, Kaglic (1998) explains that the economic growth potential of Midwestern
states will be limited by the shortage of qualiﬁed workers, even though many businesses
in the region have developed optimistic hiring plans. Buss (1996) also argues that labor
Shortages produce the tightest labor market for small businesses and deters small business
development more so than for larger businesses. Since businesses, especially small
businesses, are very reluctant to raise wage offers to ﬁll incremental positions and are
concerned about cost reductions, few ﬁrms increase current holdings and remove
inventory investment as a source of growth (Dunkelberg, 1996).

The labor shortage and related problems for most businesses throughout the US.
call for government actions to improve the situation. Examples are the Welfare to Work
Partnership, a non-proﬁt organization launched in May 1997 that encourages (Cobb,
1996; Hersch, 1997) and assists businesses in hiring individuals from public assistance,
and policies favorable for businesses (e. g. the permitting of high—tech companies to hire
foreign workers) (Elliott, 1997). In Michigan, for instance, Battle Creek Unlimited
(BCU) is a non-proﬁt economic development corporation responsible for marketing Fort
Custer Industrial Park that has developed an enterprising program to produce a skilled
workforce for the city. The program was designed to serve as a liaison among
employment and training agencies, educators, and employers. This program has

increased its visibility and has examined collaborative possibilities through state

29

economic development agencies where the availability of an adequate pool of qualiﬁed

labor has become a critical issue (Elferdinck, 1992). These examples indicate that

government is an important source of constraints and opportunities within the market

environment Of businesses.

Research on the impact of consumer demand and a tightening labor market on

ﬁrms’ decisions and economic development are summarized in Table 2-4.

Table 2-4 Literature Relating to the Impact of the Economic Environment on Business

 

 

 

 

Decisions
Economic Environment Firms Decisions 8 Economy Author (Year)
Factors
Strong Consumer Demand Hiring more full-time employees Anonymous (1998)
Growth in weekly working hours of Anonymous (1992)
manufacturing employees
Weak Consumer Demand Slow hiring Cooper & Madigan (1996)

 

Reduce work week

 

Slowdown in outputs in all
industries

 

Increased number of firings and
irregular recruitment

Leban et al. (1983)

 

 

Labor Shortage

 

 

 

 

Increased cost of doigq business Sargent (1988)
Hiring more temporary workers Golden 8 Appelbaum
(1 992)
Hirianore older workers Sullivan & Duplaga (1997)
Hiring more part-time workers/ Higgins (1996)
fewer full-time workers
HirirLg low-wage foreign workers Vijayan (1997)

 

Providing more training programs

DeLuca (1996); Ermel and
Bhol (1 997)

 

 

 

 

Limited economic growth potential Kaglic (1998)

(Midwestern States)

Deter small business development Buss (1996);
Dunkelberg (1996)

Call for government actions to Hersch (1997);

address the labor shortage related Elliott (1997)

problems

 

 

3O

 

2.2.2 Government Regulations and the Legal Environment
2.2.2.1 Relevant Legislation and Its Effects on Business Decisions

The government has traditionally been and will continue to be the major element
in the environment of businesses. Trends in government budgets and taxes, trade and
anti-trust legislation, regulation, deregulation, and economic-development incentive
programs have important effects on the US. economy and businesses (Marcus, 1993).

Government intervention and regulation of business operations have gradually
increased since the end of the nineteenth century (Mockler, 1975). From 1787 to 1860,
there was almost no government regulation of business, which was due to laissez-faire
capitalism (Marcus, 1993). During this period, businesses had such privileges as
monopoly rights, tax exemptions, and the right of eminent domain that were all designed
to encourage scarce capital to ﬁnd its way into business and so help the country grow
economically strong. A new phase in business-govemment relations began after the Civil
War as monopolies grew in Size and began to stiﬂe competition and inﬂate prices.
During this period, small businesses found it difﬁcult to survive (Mockler, 1975). The
Interstate Commerce Act of 1887, the ﬁrst signiﬁcant federal law affecting businesses,
was enacted to protect farmers and small businesses. Farmers and small businessmen,
however, were still subjected to high interest rates, high grain storage fees, and high
prices for industrial goods. Three years later, the Sherman Anti—trust Act (1890) was
enacted to protect small businesses from monopolies. Even after this legislation was
enacted, public pressure continued to grow for the government to take more decisive

action against large monopolies. For example, President Theodore Roosevelt at the

31

beginning of the twentieth century supported the Sherman Anti-Trust Act and started a
movement that resulted in the breaking up of two major monopolies, the Standard Oil
Company of New Jersey and the American Tobacco Company. In the beginning of the
twentieth century, the US. government introduced legislation designed to increase
competition and prevent unfair restraint of trade, such as the Robinson-Patman Act
(1936) and the Cellar-Kefauver amendment (1950) (Mockler, 1975).

In recent years, government action has been taken in the area of environmental
protection. This line of legislative began with the Federal Water Pollution Control Act of
1948 and was followed by other acts to protect natural resources (e. g. the Clean Air Act,
the Clean Water Bill, and the Federal Pesticide Control Act). This legislation required a
Si gniﬁcant reduction by the mid-19805 in the amount of water pollution that was
produced by industry and local governments (Mockler, 1975). Later provisions of the
1990 Clean Air Act further lowered the level of air pollutants that could be legally
released, which affected industry by forcing many ﬁrms to begin to develop a long-term
strategy for complying with the act’s new requirements. Along with any parallel state
regulatory actions, businesses needed to adopt new control technologies and alternative
processes, as well as allocate appropriate management resources to comply effectively.

The shift to proactive environmental management has been driven by pressure
from government, customers, employees, and competitors. Moreover, the trend toward
proactive environmental management is being accelerated by public pressures on
government to assure a cleaner and safer environment. Accordingly, government

regulations have become more stringent and, consequently, legal liabilities for

32

environmental damage have become more burdensome and costly. The ﬁrms have
become “cost strategic” to face the issue (Berry and Rondinelli, 1998).

There have also been a number of consumer protection laws that have increased
the regulation of businesses. Examples of these laws include the Meat Inspection Act, the
Pure Food and Drug Act, the Fair Credit Reporting Act, the Equal Credit Opportunity
Act, the Real Estate Settlement Procedures Act, the Truth in Lending Act, the Fair Debt
Collection Practices Act, the Fair Housing Act, etc. (Mortgage Library, 1998). When it
comes to fairness, one relatively recent piece of legislation is worth noting. The
Americans with Disabilities Act of 1990 (ADA) added a new layer of state and local
government regulation to the Rehabilitation Act of 1973. The employment provision of
ADA became effective for almost all businesses with 25 or more employees on July 26,
1992 and affected the employment practices and operations of many businesses (Candris,
and Anderson, 1991).

Other areas of governmental concern over business activities include product
safety and worker safety. Government, however, has been supportive of businesses by
providing, for example, tax incentives to address certain issues (Marcus, 1993).
Businesses that fail to comply with these state and federal regulations face criminal
charges, large ﬁnes, intervention, or Shutdown by regulatory agencies (Galer, 1990).
Food service facilities are especially affected by more health and building code
regulations (e.g. standards for life, safety, indoor air quality, structural integrity, and
accessibility for the physically disabled) than most retail or service businesses (Frable,

1997).

33

State and local government agencies also impose economic regulations on
businesses with regard to zoning, controlling pollution, maintaining health standards, and
licensing (e.g. the licensing of installers of telecommunications cabling) (Kuehn, 1997;
US. Bureau of the Census, 1972, p. 18; Wells, 1992; Ceniceros, 1997; Finnegan, 1997).
Since the Occupational Safety and Health Administration (OSHA) promulgated
Signiﬁcant environmental and safety-related regulations and many States have imposed
Similar restrictions, businesses have begun spending signiﬁcant sums to comply with
these guidelines. Consequently, businesses have tried to manage the situation with cost-
sensitive strategies, for example, by seeking tax deductions for compliance (Rocheleau,
1992).

Currently, most states in the US. (41) have shifted into a deregulation mode with
respect to economic regulation (Calderwood, 1994; Gawla and Rundle, 1982).
Movement from a regulated to a deregulated environment changes fundamental
managerial assumptions, criteria, and decision making to the degree that the business is
transformed. According to Mahon and Murray (1980), “in a deregulated environment,
ﬁrms have a tendency to overextend themselves ﬁnancially, managerially, and
structurally,” which implies that today’s managers and owners need to strategically adjust
to an evolving business environment that deregulation might bring (Mahon and Murray,

1980, p. 123).

34

2.2.2.2 Employment Related Laws and Expansion Decisions
2.2.2.2.] Impact of Workers’ Compensation on Business Expansion

Workers’ compensation laws and regulations require “employers to provide cash
beneﬁts, medical care, and rehabilitation services to their employees for injury or
illnesses arising out of or in the course of employment” (Butler and Appel, 1990, p. 595).
“Employers can fulﬁll the obligations to provide workers with compensation coverage by
purchasing insurance from a private insurance carrier or from an insurance fund run by
the state, or by self-insuring. Provision of this coverage is mandatory in 47 states with
New Jersey, South Carolina, and Texas being elective states” (Butler and Appel, 1990,
pp. 594-595).

Workers’ compensation is the fastest rising cost problem facing organizations
both large and small in the US. (Miller, 1992). Workers’ compensation costs as a
proportion of covered payroll doubled from the mid-19605 to the mid-19803. “The total
workers’ compensation beneﬁt payments received by individuals soared from 18.3 billion
dollars in 1980 to 44.1 billion dollars in 1990, while employer Spending on workers’
compensation rose from 19.3 billion dollars to 45.9 billion dollars” (Miller, 1992, pp. 22-
28). The result of a NFIB (National Federation of Independent Business) survey lists
workers’ compensation as the second leading problem among business owners with
employees (NFIB Education Foundation, 1988). Similar results were found in an
Alexander and Alexander risk-management survey. Most respondents (91 percent)
ranked cost containment strategies for workers’ compensation as the premiere topic of

importance (Butler and Appel, 1990; Miller, 1992). Miller (1992, p.27) explained that

35

“the reasons for the increasing costs were: (1) the rising cost of medical care; (2) the
increasing litigiousness of the system; and (3) the expansion of the deﬁnition of
‘compensable injury’.” Much empirical research on the effect of the workers’
compensation system has indicated that the patterns of claims frequency and duration
have varied directly with workers’ compensation beneﬁts (Chelius, 1973, 1974, 1977,
1982; Ruster and Appel, 1982; Butler and Worrall, 1983, 1985; Ruster, 1985), and wage
decreases intended to compensate for higher beneﬁts (Stuart and Walzer, 1983; Butler
and Worrall, 1983, 1985; Moor and Viscusi, 1986).

In order to reduce workers’ compensation costs, employers have tried such
management strategies as developing a better hiring process, tracking insurance coverage
and rates, setting up safety programs, and considering self-insurance (Bork, 1989).
Despite of the risk of getting discrimination complaints by disabled job applicants over
hiring decisions (Fletcher and Harty, 1992), some employers prescreen applicants by
using accident history data and by asking questions about medical conditions that may
reasonably relate to job performance (Lucas, 1991). Some ﬁrms consider using robots to
reduce the high costs of employee illness and injury. These ﬁrms feel that robots can
substantially increase a ﬁrrn’s level of employee health and safety leading to reduced
workers’ compensation costs, health insurance premiums, risk of being sued for
occupation-related illness, costs associated with absenteeism, lost output caused by
illness, and costs of hiring and training replacements for disabled workers (Lambrinos
and Johnson, 1984; O’Mara, 1997). These cost-reduction strategies may either manifest

themselves in increased layoffs or in the slowing down of hiring, e. g. Wal-Mart stores

36

(Soderquist, 1994). Instead of hiring full-time workers (Gawla and Rundle, 1982),
however, companies may hire more temporary or leased employees, e. g. small—chain
restaurants lease employees (Hayes, 1997). AS another effective way of lowering labor
costs, an increasing number of employers have Started to adopt the fostering of workplace

safety as a way to address the requirements of workers’ compensation legislation (Dembe,

1995).

2.2.2.2.2 Impact of Unemployment Insurance Beneﬁts on Businesses

A federal-state unemployment insurance system was started under the Social
Security Act signed by President Franklin D. Roosevelt in 1935 (Drake and Moskowitz,
1997). Unemployment insurance funds are derived from taxes levied on employers,
except in Alaska, New Jersey, and Pennsylvania (Drake and Moskowitz, 1997).
Unemployment insurance taxes are based on the number of employees, the duration of
their employment, and the number of claims workers have charged against the employer
(Anonymous, 1992b).

In early studies of the effects of unemployment insurance on the labor market,
researchers had found that unemployment insurance was an inﬂuencing factor on ﬁrms’
decisions to lay off workers to reduce costs (Kaplan, 1976; Baily, 1977; Feldstein, 1976,
1978; Topel, 1983; Kahn, 1987). Later authors agreed that there is a relationship between
unemployment insurance and ﬁrms’ hiring decisions, for example, unemployment
insurance causes downsizing (Rejda and Rosenbaum, 1990; Dauffebach, Penn and

Knutson, 1996) and business strategies (e. g. effects on the choice of locations and

37

investment). In researching the relationship between unemployment insurance and
regional economic development, Testa and Davila (1989) found that unemployment costs
inﬂuence the geography of business investment by manufacturing ﬁrms, which deters
regional economic development. Since each state can determine the terms and Size of
unemployment beneﬁts paid to workers (decentralized), regional cost of doing business,
especially for manufacturing ﬁrms, vary depending on the unemployment insurance cost

in a state (Singletary, 1991).

2.2.2.2.3 Impact of Healthcare Beneﬁts on Businesses

A historical record of healthcare data shows that national healthcare expenditure
as a percentage of GDP in 1995 at15.4 percent has nearly tripled since 1965 (5.9 percent),
and the trend is expected to continue growing into the year 2000 (Musgrave, 1994).
Farrell (1993) also estimates that annual spending by companies for healthcare has more
than tripled to 225 billion dollars over the past decade. These statistics have raised
concerns over the cost of doing business, especially among small businesses (DePalma,
1997), and the cost of healthcare affects hiring decisions for all companies. High labor
costs discourage smaller companies more than large ones from hiring more employees
(Begany, 1991; Farrell, 1993; Soderquist, 1994). Since 1989, employment taxes and
beneﬁts for minimum-wage workers at small businesses have increased more than 15
percent. This high cost of hiring has caused lower wages for workers (Farrell, 1993) and

more hiring of leased employees (Begany, 1991).

38

2.2.2.2.4 Impact of Unions on Business Decisions

Labor unions can be deﬁned as “organizations of workers whose primary
Objectives are to improve the pecuniary and non-pecuniary conditions of employment
among their members” (Ehrenberg and Smith, 1997, p. 472). In order to achieve their
goal, unions bargain with employers over various employment issues, including pay,
employee beneﬁts, conditions of work, hiring practices, work time, and layoff guidelines
(Farber, 1989; Ehrenberg and Smith, 1997; Drake and Moskowitz, 1997).

Even though union membership has declined over the years, such important
regulations as “workers’ compensation law, welfare programs, equal employment
opportunity laws, health and safety laws (passed in 1970), and legislation to improve
healthcare are largely the result of pressures exerted by them [unions]” (Leap, 1995, p. 6;
Drake and Moskowitz, 1997; Freeman, 1981; Alpert, 1982). Unions, therefore, have a
hand in management decisions concerning employees, such as pay, employee transfers,
promotions, training programs, incentive programs, performance appraisal methods, job
design, the hiring process (DeRoy, 1995; Burns; 1995, 1996; Leap, 1995; Kennedy and
Tisch, 1996; Drake and Moskowitz, 1997), and even hiring decision, such as ﬁrms’ hiring
temporary replacement of. striking workers and hiring part-time workers in unionized
organizations (Zeytinoglu, 1992; Schnell and Gramm, 1994). In a study of the inﬂuence
of unions on 37 human resource management practices, ranging from hiring to promotion
practices, researchers found that unionization inﬂuences ﬁrms to be more selective in
new hiring by adopting a formal probationary period for new employees (Ignace and

Maki, 1994). Another empirical study on the inﬂuence of unions on ﬁrms’ hiring

39

decisions, using the National Longitudinal Surveys of young men and women, also
conﬁrms the previous ﬁndings that the union sector as a whole upgrades labor quality by
inﬂuencing employers to upgrade the labor quality of new hires (Krishnan, 1994).
Unions are often accused of being responsible for driving up the costs of goods
and services by forcing employers into paying high wages and by providing more beneﬁts
and incentives (Duncan and Stafford, 1980; Leap, 1995; Drake and Moskowitz, 1997).
Raising wages by union activities, for example, may cause a decline in employment. The
results of several studies suggest that unions reduce employment growth (Leonard, 1992;
Dunne and MacPherson, 1994; Boal and Pencavel, 1994). An early study of the
relationship between trade unions and layoffs in the US. manufacturing industry found
that adjustment through layoffs was substantially greater in unionized ﬁrms than in non-
unionized ﬁrms (Medoff, 1979). One of the studies conducted by Leonard (1992)
concluded that the growth rates in unionized ﬁrms was Slower than in nonunion ﬁrms.
Other studies have found similar employment effects of unions for the United States, as
well as for Canada and the United Kingdom (Blanchﬂower, Millward and Oswald, 1991;
Valletta, 1993; Long, 1993; Dunne and MacPherson, 1994; Bronars, Deere and Tracy,

1994). Previous studies are summarized in Table 2-5.

40

Table 2-5 Literature Pertaining to the Impact of Employment-Related Laws (legal

environment) on Businesses and Hiring Decisions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Employment Impact on businesses and hiring decisions Author (Year)
related laws
Workers’ Increases cost of doing business for large and Miller (1992)
Compensation small firms
Decreases wage rates Butler and Worrall (1983,
1985); Stuart & Walzer
(1983); Moor 8 Viscusi
(1 986L
Developing a better hiring process using Bork (1989); Lucas (1991)
accident history data and checking medical
conditions
Using robotics to reduce hiring and training Lambrinos & Johnson
costs (1 984); O’Mara (1 997)
Increasing layoffs or slowingdown of hiring Sodercmist (1994)
Hiring more temporary or leased employees Hayes (1997)
Adopt provisions for fostering workplace safety Dembe (1995)
as part of workers’ compensation legislation
Unemployment Decisions to lay off workers to reduce the costs Kaplan (1976); Baily (1977);
Insurance Feldstein (1976, 1978); Topel
Benefits (1 983); Kahn (1987)
Decisions to downsize Rejda 8. Rosenbaum (1990);
Dauffebach, Penn, 8
Knutson (1996)
Influence the geography of business Testa & Davila (1989)
investment by manufacturing firms and location
decision
Cost reduction strategy by carefully scheduling Kaplan (1976)
roduction and inventory
Healthcare Increase costs and effect hiring decisions by DePalma (1997)
Benefits small businesses

 

Compare effects of the high costs on firms’
hiring decisions by size of businesses (smaller
companies are more influenced by high costs
than larger ones in hirinldecisions)

Soderquist (1994); Begany
(1991); Farrell (1993)

 

 

Lower wages for workers and promote hiring of

 

leased employees

Begany (1 991)

 

41

 

Table 2-5 (cont’d)

 

 

Unions Influence management decisions concerning Drake 8 Moskowitz (1997);
employees, such as pay, employee transfers, Kennedy 8 Tisch (1996);
promotions, training programs, incentive DeRoy (1995); Burns (1995,

programs, performance appraisal methods, job 1996); Leap (1995)
design, and the hiringprocess

 

Promote hiring of more temporary and part-time Schnell 8 Gramm (1994);
workers Zeytinoglu (1992)

 

Influence firms to be more selective in new Ignace 8 Maki (1994)
hiring by adopting a formal probationary period
for new employees

 

Influence employers to upgrade the labor quality Krishnan (1994)

 

of new hires
Reduce employment growth due to high costs Leap (1995); Drake 8
caused by unionization Moskowitz (1997); Duncan 8

Stafford (1 980); Leonard
(1992); Dunne 8 MacPherson
(1994); Boal 8 Pencavel
(1994); Bronars, Deere 8
Tracy (1994); Valletta (1993);
Long (1993); Blanchflower,
Millward 8 Oswald (1991)

 

Layoffs in manufacturing firms are substantially Medoff (1979)
greater in unionized firms than in non-unionized
firms

 

 

 

2.2.3 State Economic Development Policy as an Environment Factor and Its
Effects on Employment and Businesses

Many state and local governments started to emphasize economic development
during the 19705 and 19805 as a result of the forces of de-industrialization, government
ﬁscal crises, and pressure from politically mobilized business communities (Osborne,
1988; Scheible, 1991). Many factors affect state economic development and also the
general business environment, including proximity to markets and materials, quality of its
economic infrastructure (e. g. roads and airports), quality of public services (e. g.
education, police, and ﬁre protection), labor availability, labor costs, labor relations,

business costs, and the condition of national and international economies (Public Sector

42

 

Consultants, Inc., 1998). As economic development policy has become an increasingly
important concern for state government, government industrial programs and actions for
businesses have become an important environment of businesses. Businesses have also
recognized the inﬂuence of state economic development policy on their decision making

related to location, expansion, and general Operational decisions.

2.2.3.1 State Economic Development Policy and Employment

Economic development has been deﬁned as an effort by regions to redress the
cumulative impact of broader social, cultural, and economic trends, including the shift
from a manufacturing to a service-based economy (Ladd and Yinger, 1989).

According to Sanford (1967), state economic development is an attempt by state
governments to stimulate employment by mainly encouraging the manufacturing industry
and, in turn, by increasing income and wealth, and, in some cases, by revitalizing
distressed communities. Later, Blakely (1989) agreed with Sanford (1967) by deﬁning
economic development policy as a process of policy making whereby governments
manage their existing resources and enter into new partnership arrangements with the
private sector, or with each other, to create new jobs, thus, increase employment, and to
stimulate economic activity in a well-deﬁned economic zone (Dawson and Robinson,
1963; Sharkansky, 1971; Sharkansky and Hofferbert, 1971; Tompkins, 1975; Lewis-
Beck, 1977; Danziger, 1978; Stonecash and Hayes, 1981; Dye, 1990).

Unfortunately, states frequently engage in a competitive struggle to improve their

locational advantage by attracting new businesses and by expanding existing businesses

43

to create new jobs (Dubnick, 1984; Chubb, 1988; Grady, 1987; Eisinger, 1988; Osborne,
1988; Fainstein and Fainstein, 1989; Williams, 1990; Dye, 1990).

Even though most states engage in economic development efforts by offering
programs and incentives, debates continue as to whether or not this is a legitimate
function of state governments (US. Congressional Budget Ofﬁce, 1984; Grady, 1987;
Lugar, 1987; Fosler, 1988; Osborne, 1988; Scheible, 1991). Those arguing in support of
state economic development efforts include Osborne ( 1988) who argues that states serve
as “laboratories of democracy” which test new policy ideas. He further contends that
state, rather than federal, government can better attune to local and regional strengths and
weaknesses. Boeckelman (1989) adds that state governments are closer to people’s
preferences and, hence, are more responsive to them than the federal government.

There are also arguments against state government involvement in economic
development policy. One argument asserts that because state industrial policies primarily
encourage the relocation of ﬁrms, this type of incentive can distort market-based
decision-making and hamper the overall efﬁciency of the economy. Another is that state
policies may lead to a negative-sum game, because the resources that states depend on for
attracting businesses do little to increase overall economic growth. Also, state economic
development objectives and programs may conﬂict with national objectives (US.
Congressional Budget Ofﬁce, 1984). Programs for attracting and maintaining businesses
include low tax rates, cheap labor, and various other incentives. Instead of developing the
state’s economy, however, they can erode wages and the tax base over the long term

(Boeckelman, 1989).

Conversely, Fosler (1988) emphasizes the cause and effect relationship between
state policies and economic growth. He argues that the economic development process
involves an explicit planning process and implicit strategies that make the state an
attractive place in which to do business. Some supporters of economic development
policy also agree that State development policy can positively affect the level of local
private investment, as well as employment growth, by providing a favorable business
climate and result in a net local and national economic beneﬁt (Dubnick and Holt, 1985;
Fieock and Cable, 1990; Bartik, 1992).

On the other hand, opponents of economic development argue that these policies
have no net-positive effect on the local economy and have net negative-effects (Barker,
1983; Gray and Lowery, 1988; Ambrosius, 1988; Testa and Davila, 1989). Ambrosius
(1988) States that traditional economic development tools, such as tax abatements, have
no net-positive economic effect locally. Barker (1983) suggests in his study that business
tax incentives have little or no effect on business-decision makers, and they usually
support decisions that would be taken regardless of the incentives offered. Others assert
that incentives and other economic development policies generate market inefﬁciencies
by artiﬁcially supporting economically inefﬁcient businesses or their practices (Fieock
and Cable, 1990; Reich, 1992). These researchers emphasize the reduction of
government intervention and regulation of businesses.

Since the overall effectiveness of state economic development policies and

programs have been questioned, many researchers have tried to answer the question of the

45

impact of such policies and programs by utilizing business location theory and evaluation

studies.

2.2.3.2 Evaluations of the Effects of Economic Development Programs on Location
Decisions

Since the era of the New Deal, traditional state economic development programs
have focused on creating jobs by recruiting mainly large manufacturing plants from other
states or countries by offering ﬁnancial incentives (e. g. usually tax-related programs)
(Boeckelman, 1989; Smith and Fox, 1991). States have, therefore, been involved in a
competitive struggle to improve their locational advantage in an effort to attract new
businesses and encourage intra—state expansion of existing businesses (Dubnick, 1984;
Chubb, 1988; Grady, 1987; Eisinger, 1988; Osborne, 1988; Fainstein and Fainstein, 1989;
Dye, 1990; Williams, 1990).

There has been considerable research that focuses on the factors that actually
inﬂuence the choice of business locations (Schmenner, 1982; Carton, 1983; Bartik, 1985;
Boeckelman, 1989; Smith and Fox, 1991). Most studies Show that tax breaks and related
incentives have little inﬂuence on a ﬁrrn’s location decision regarding business start-up
and expansion (Due, 1961; Kienschnick, 1981; Schmenner, 1982; Schmenner et al.,1987;
Newman and Sullivan, 1988). In one of the earliest studies on the subject, the Survey
Research Center of the University of Michigan (1950) showed that taxes were not
signiﬁcant in location decisions. This survey (ﬁeld interview) found that only nine
percent of the ﬁrms interviewed mentioned taxes as an unfavorable location factor.

Beginning with Due (1961) and followed by Kienschnick (1981), surveys of corporate

46

decision makers conﬁrmed the early study result that taxes play a negligible role in
location decisions. Based on interviews with key location decision makers from 410 of
the Fortune 500 companies, Schmenner (1982) also found that taxes were a minor
consideration in location decisions; tax considerations were more likely to push a
company away from an Old location rather than to pull it toward another. This suggests
that high tax rates may encourage existing businesses to look elsewhere, but low taxes
probably do little to attract new businesses.

In Farmer’s investigative study (1983) on the effect of tax abatement as a deciding
factor in location decisions by ﬁrms in a Reinvestment Area within the state of Ohio, he
concluded that tax abatement did not serve as a signiﬁcant attraction for ﬁrms to locate in
the area. Schmenner (1982) also reported that 75 percent of the respondents cited a
favorable labor climate as the most important factor in starting or relocating a plant.

Sixty percent cited low land costs, but only 35 percent cited low taxes. He concluded that
taxes affect only those location decisions where all other factors are equal. Quality of
labor and its costs generally far outweigh taxes in inﬂuencing business decisions, because
labor accounts for 66 cents of each dollar of value—added costs for the average industry
(Smith et al., 1985). This means that businesses pay an average of only one dollar in state
and local taxes for every 20 dollars paid out in wages; therefore, tax considerations do not
come into play unless other factors (e. g. labor costs) are equal. Later, Schmenner et al.
(1987) again argued that the importance of taxes to the business location decision-makers
also depends on the decision-making stage: ﬁrst, the narrowing-down Stage, when a ﬁrm

decides which states to consider seriously; secondly, the ﬁnal decision stage, when a

47

speciﬁc location is selected. Although states can do little to control the decision-making
process in the second stage, it appears that certain negative aspects of their “business
climates,” including high taxes, in some cases can keep them out of the running during
the initial consideration stage. These researchers also found that ﬁrms differ in their
responses to state incentives. In other words, more footloose companies that are not tied
to a certain location by local factors or resources react more to speciﬁc state
characteristics. For example, a travel agency or an insurance company is relatively
footloose, while a coal mine or any other manufacturing plant is not.

Based on the examination of the effects of taxes and recruitment, Carlton (1983)
found that energy price, ﬁrm size, availability of engineers, as well as other workers in
the local labor market, and the concentration of employment in an area were important
location factors. Bartik (1985) agreed with previous results that state recruitment efforts
had only a small inﬂuence on plant location after studying the effects of several factors
(unemployment insurance, workers’ compensation, corporate income, and property tax
rates) on the location of 1,607 manufacturing plants from 1972 to 1978. Even if the
corporate income tax rate inﬂuenced the location decision, a 10 percent increase in a
state’s corporate income tax rate would deter only two to three percent of businesses, and
other tax rates did not inﬂuence location decisions. He also stressed the importance of
state infrastructure programs, such as building more roads to more plant locations,
because ﬁrms reported this infra-structure factor as an important one in making location
decisions. Also worth noting here is that a high level of labor unionization in a state had

a negative inﬂuence on attracting plants (Bartik, 1985).

48

Other attempts to analyze business location decisions have used econometric
techniques. In a review of research by Newman and Sullivan (1988) it was argued that
econometric models call into question the earlier conclusions, based on previous survey
research, that tax incentives have no bearing on location. Even if they do not claim that
taxes inﬂuence location decisions of a ﬁrm, they treat the issue as an open question.
Nevertheless, an econometric-based study by Kienschnick (1981) found that tax burden
affected investment share for only a few industries, such as rubber and transportation.
Most industries, however, appeared to be unaffected. The results indicate that tax
considerations are minor for a ﬁrm’s location decision, but the inﬂuence varies by
industry and the Size of businesses. For example, the tourism industry might consider
taxes as an important factor in locating their businesses (e. g. over-taxation might damage
the tourism industry by forcing up prices and depressing travel and tourism demand)
(Seal, 1994). Fox and Murray (1990) conducted an extensive study on the effects of taxes
and other programs on location and business start-up using 68,520 businesses relocating
or starting up in Tennessee from 1980 to 1986. They found that high taxes were generally
more important to small businesses than to large ones (having more than 50 employees).
Compared to other industries, however, durable-goods producing manufacturers were
discouraged by high sales-tax rates. Moreover, such factors as a highly educated work-
force and access to interstate highways (infrastructure) also help to attract businesses.

Empirical studies of business location practices reveal that traditional recruitment
activities which focus on tax incentives has little or no effect on business location

decisions. Some researchers concentrate on manipulating labor costs rather than tax rates

49

to inﬂuence business decisions (Boeckelman, 1989). One common method of
manipulating lower labor costs is to pass a right—to-work law prohibiting mandatory
unionization. Moor and Newman (1985) studied the impact of right-to-work laws on
business locations and found that such statutes only inﬂuence relations Shortly after the
law is initially passed but have little impact thereafter. They also found that right-to-work

laws have the greatest locational impact on labor intensive industries.

2.2.3.3 Evaluation of the Effects of Business Development and Retention Programs
on Employment Growth

During the 19705 and 19805, economic development policy became an important
concern for state government as they strove to stimulate employment and economy.
Government industrial programs and actions directed at businesses became an important
environment for businesses (Osborne, 1988; Scheible, 1991). State economic
development efforts, however, mainly focused on creating jobs by recruiting and
encouraging mainly large manufacturing ﬁrms by offering ﬁnancial incentives (e. g.
usually tax-related programs). Following these efforts, a research tradition has developed
that evaluates the impact of environment factors on business location decisions,
especially with regard to the impact of taxes. Much of the research has concluded that
taxes have little or no effect on ﬁrms’ location decisions. Availability of qualiﬁed labor,
labor costs, energy prices, infrastructure, ﬁrm Size, and unionization of labor in a state are
important location factors. Although many studies have evaluated the impact of taxes on
location decisions, only a few comprehensive studies have compared their inﬂuence on

location decisions by different types and Sizes of businesses.

50

Some studies have analyzed the impact of state incentives and programs on
regional economic growth and employment. In an early study of the relationship between
Iowa’s manufacturing employment growth and state and local tax collections, Bloom
(1955) concluded that there was no demonstrable evidence that high tax levies had
retarded the growth of the state’s economy. Thomson and Mattila (1959) also conﬁrmed
that there was no signiﬁcant correlation between interstate tax differentials and
employment growth in 29 studied manufacturing industries. In another study of tax
inﬂuence on regional economic growth in 24 states, Struyk (1967) found a negative
impact of tax structure (e. g. per capita property tax, per capita sales and gross receipts tax,
or per capita licensing tax) on regional growth. A later study by Aki (1983) agreed with
the previous results on the effect of local tax rates and public expenditures on the growth
of employment in non-metropolitan counties of the northern central region of the US.
and reported no signiﬁcant relationship.

Lugar (1987) found that states often expend a considerable amount of effort on
economic development without sufﬁcient knowledge of the likely effectiveness of
individual policies and programs. He believed that states were well aware of the impact
of their programs but were not pursuing the goals that he attributed to them.

Dorfman (1988) contended that the most successful examples of regional
development, such as Califomia’s Silicon Valley and Massachusetts’ Route 128,
appeared to result from luck and economic factors beyond direct governmental control,

rather than from successful state policies. Sander and Schaeffer (1988) concluded,

51

 

III.

however, that increasing funding for general education does over time lead to higher
levels of state employment.

The general implication of the literature reviewed above is that state economic
development policies have no effect on ﬁrms’ location decisions and do not promote
growth nor maximize wages and rates of employment (Boeckelman, 1989). Tax
incentives do little to attract businesses, while alternative policies fail to achieve
economic growth. For instance, Kienschnick (1981) stressed the stronger effects of other
business environment factors, such as state initiatives in labor markets, capital markets,
transportation, regulation, and the quality of life, rather than tax incentives to encourage
economic development and employment growth.

A number of authors have questioned why states continue to pursue business
attraction and retention programs when these programs often do not achieve the intended
results (Lugar, 1987; Harrison and Kanter, 1978). One possible answer may be based
upon a lack of information (Boeckelman, 1989). Another reason might be that most
studies adopt simplistic assumptions about successful programs and policies. For
example, Lugar’s (1987) study assumes that the main concern of states engaging in
economic development is to promote growth by maximizing wages and by minimizing
the unemployment rate. If tax incentives are a means of satisfying the demands of
existing politically powerful businesses, then the result of the policy can be successful
(Harrison and Kanter, 1978). Supplying alternative assumptions can, then, lead to
opposite conclusions. The point is that the evaluation of results of states’ development

policies and programs depends on the programs’ underlying goals. Table 2-6 and Table

52

2-7 summarize the inﬂuences of state government programs on business location

decisions and employment growth respectively.

Table 2-6 Literature Describing Impacts of State Government Programs on Business
Location Decisions

 

State Recruitment

Programs

Impact on Location Decisions

Author (Year)

 

Tax Incentives
(tax credits, low business
tax liabilities,

Little or no significant influence on
firms’ location decisions regarding
start-up and expansion

Due (1961); Kienschnick
(1981); Bartik (1985);
Schmenner et al. (1987);

 

 

 

 

 

intensive industries

tax reduction) Tax has more pushing effect than Newman 8 Sullivan (1988);
pulling effect Boeckelman (1 989)
A favorable labor climate, quality of Schmenner (1982)
labor and its costs as more important
factors than taxes
Energy prices, firm size, the Carton (1983)
availability of skilled workers, and
concentration of employment in an
area are more important factors than
taxes.

Right-to-Work Laws Greater locational impact for labor Moor 8 Newman (1985)

 

 

Table 2-7 Literature Relating to the Impact of State Government Programs on Employment

 

Business Development and
Retention Programs

Impact on Employment Growth

Author (Year)

 

Taxes

High tax levies have no effect

Bloom (1955); Thomson 8

 

 

 

 

Manufacturing Firms

 

growth —> New direction for
state economic programs
focusing more on service and
small businesses assistance

 

 

on employment growth Mattila (1 959); Struyk (1967);
Aki (1983)
General State Programs, Regulatory relief, and debt and Lugar (1987)
including Regulatory Relief, equity programs are
Tax, Debt, and Equity associated with lower average
Programs wages, but no effect on
unemployment
General Education Funding Induces higher levels of state Sander 8 Schaeffer (1988)
Program employment
State Incentives in Labor Strong effect on economic Kienschnick (1981)
Markets, Transportation, development and employment
Regulation, and Quality of Life growth
Retention Programs for Large No effect on employment Smith 8 Fox (1991)

 

53

 

 

Table 2-8 presents research on impact of external environment factors, rather than

government actions, on ﬁrms’ decision making.

Table 2-8 Comprehensive Research on the Impact of External Environment on Business

 

 

 

 

 

 

Decisions

Environment Factors Findings Author (Year)

A firm’s innovativeness , major There is a relationship Lamont (1991)

markets, and marketing between the study variables

activities (external environment) and
firms' decision making

Financial Resources Induce firms’ strategic decision Braden (1977)
makirLtLto face the difficulties

Economic, Political, and Socio- Different effects on different Kelman (1988); Porter

cultural Environment sizes and types of firms (1980)

Taxes Comparative impact on Ireland, Hitt, Bettis, 8
manufacturing and service Deporas (1987)
industries (Low tax rate has
positive impact on the growth
of service sector employment)

 

 

 

 

2.2.3.4 The Importance of Small Businesses in Economic Development Policy

The ability of small businesses to create and increase employment has been
recognized in many studies. For instance, the majority of job creation in Tennessee came
from new small businesses or expansions of existingbusinesses from 1979 to 1986
(Smith and Fox, 1991). Studies reveal that govemment-related problems (e. g. taxes,
regulations, and cost of paperwork), cash ﬂow, expense management, quality of labor,
and promotion are major external environment factors (challenges) faced by small
businesses (Peterson, Kozmetsky, and Ridgway, 1983; Franklin and Goodwin 1983;
Covin and Slevin, 1989; Michigan Small Business Center, 1998; Kean, Gaskill, Leistritz,

and Jasper, 1998).

54

Small businesses have been playing a big role in the restructuring of the US.
economy. Historically dominant sectors, such as manufacturing, are declining in overall
employment share (manufacturing employment share was 33 percent in 1950 and 16
percent in 1993) (Michigan Small Business Development, 1998). This reﬂects that small
businesses are an important contributor of jobs, especially new jobs, innovative products
and services, and ﬂexible management strategies in increasingly turbulent economic and
ﬁnancial market conditions in the US.

In early studies, the ability of small businesses to create new jobs was afﬁrmed.
Birch (1979, 1987) in studying the Speciﬁc contributions of small businesses to economic
development focused primarily on the job-creation ability of small businesses. According
to his study, small ﬁrms (having less than 20 workers) create between 66 percent and 80
percent of all new jobs in the US. Even in rural areas in the U.S. small businesses
provide 88 percent of all new jobs (Popovich and Buss, 1987, 1990). From 1976 to 1990,
two-thirds of the 31.1 million net new jobs in the private sector originated among small
businesses which, in total, accounted for about one-half of the total private—sector
employment. Of these, the ﬁrms having one to 19 employees (46.9 percent) produced
almost one-half of these net new jobs (17.9 percent in ﬁrms having 20 to 499 employees
and 35.2 percent in ﬁrms having more than 500 employees). Small business “births”
provide two to three times as many net new jobs as the number created by small business
expansion (ﬁve percent of small ﬁrms account for 75 percent of net new jobs from
expansion) (Brophy, 1994, pp. 232-239). The largest creators of new jobs in 1991 were

businesses with less than ﬁve employees (2.6 million jobs) followed by businesses having

55

50 to 99 employees. This smallest sector also created 95 percent of all new jobs in 1993.
Furthermore, 71 percent of the 1.9 million new jobs created in 1993 were created by
small businesses. By comparison, large ﬁrms (having more than 500 employees) had a
net loss of 4.5 million jobs in same year (Michigan Small Business Development Center,
1998). The number of small businesses is also projected to increase in the future.
According to the Survey of Small and Independent Business Owners in 1997, hiring plans
are currently at a record high, and 20 percent of all respondents plan to expand
inventories (see Table 2-9) and employment, the highest quarterly reading in 25 years (see

Table 2-10).

Table 2-9 Small Business Inventory Plans (Net Percent: Increase mnus Decrease,

 

 

 

 

 

 

 

Seasonally Adjusted)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1993 5 3 9 4 2 1 O 2 3 2 8 4
1994 4 4 2 5 7 8 5 7 9 5 10 6
1995 5 -1 -3 5 6 8 9 6 7 5 5 6
1996 2 3 6 5 10 1 4 4 6 6 3 2
1997 5 6 1 7 6 4 6 6 7 5 4 4

 

 

 

 

 

 

 

 

 

 

 

 

 

Source: NFIB Education Foundation. (1998). Monthly Report-November 1998. Small

Business Economic Trends. p. 14.

Table 2-10 Small Business Hiring Plans (Net Percent: Increase minus Decrease, Seasonally

 

 

 

 

 

 

 

Adjusted)
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1993 8 6 6 8 7 6 4 6 7 7 11 12
1994 12 11 14 10 12 10 12 11 10 14 18 10
1995 15 18 16 14 15 13 14 16 17 12 15 15
1996 16 13 12 15 15 17 13 16 13 15 15 15
1997 17 16 11 15 16 15 18 20 18 18 20 20

 

 

 

 

 

 

 

 

 

 

 

 

 

Source: NFIB Education Foundation. (1998). Monthly Report-November 1998. Small
Business Economic Trends. P. 6.

56

 

 

Small businesses’ contribution to Michigan’s economy is also enormous. The 15

largest job generators among small-busineSS-dominated industries contributed almost four

times as many new jobs as the 15 largest job contributors among large-business-

dominated industries. In 1994, about 16,000 new businesses were started in Michigan

and over 800,000 small businesses in the US. (Michigan Small Business Development

Center, 1998). The number of ﬁrms and employees by small business category is proﬁled

in Table 2-11.

Table 2-11 Number of Firms and Employees by Small Business Category in the US.

 

 

 

 

 

 

 

 

 

Business Size Number of Firms Percent Total Employees Percent
(# of employees)

500+ 13,977 0.5 43,304,946 47.0
100-499 68,338 1.0 13,143,390 14.0
20-99 439,811 9.0 17,146,411 19.0
10-19 551,229 11.0 7,386,939 8.0

59 941,296 18.5 6,174,730 7.0

1-4 3,036,304 60.0 5,151,143 5.0
Total 5,051,125 100.0 98,005,226 100.0

 

 

 

 

 

Source: Michigan Small Business Development Center at Wayne State University. Facts

About Small Businesses. [Online] Available. http://michigansbdc.org/

smallbusfactshtml, July 20, 1998.

Factors that encourage small-busineSS-expansion decisions come not only from

within a business but also from the environment in which the business operates (Bassett,

1995). In a study by Peterson, Kozmetsky, and Ridgway (1983), approximately 40

percent of the participants cited external environment factors as the major determinants of

their failures, and most of them were govemment-related. Their results also agree with

those from a study by Franklin and Goodwin (1983), which showed that the top eight

problems facing management were external, including inﬂation, taxes, government

57

 

regulation, cost of paperwork, and quality of labor. In the same context, results of the
Survey of Small and Independent Businesses also suggested that taxes (27 percent),
ﬁnding qualiﬁed labor (16 percent) (about 28 percent reported at least one hard-to—ﬁll job
openings), and regulation and red tape (17 percent) were the most important problems
faced by small businesses in recent years (Anonymous, 1998). According to results of a
1998 study by the Michigan Small Business Development Center, businesses having ﬁve
to 99 employees cited cash ﬂow, controlling costs, competition, supplier relationships,
advertising and promotion, quality of labor, government regulation, employee
productivity, and health insurance as their top ten challenges.

Lawrence, Osborn, and Glueck (1980) examined the impact of environmental
challenges and strategic decision making on the short-term success of 358 large ﬁrms
from 1930 to 1974. They found signiﬁcant relationships between changes in the
environments facing businesses and subsequent strategic decisions to face the challenges;
for example, retrenchment in segments of their businesses as government regulations
increase, seek mergers as competitive and ownership challenges increase, penetrate
existing markets or increase production efﬁciency to cope with distributor excess or
shortage, alter marketing strategies as socio-economic changes redistribute demand
patterns, and increase R & D expenditures or production capacity to maintain
technological competitiveness.

In the same context, a study of interrelationships between business environments
and strategic decisions, Kean, Gaskill, Leistritz, and Jasper (1998) studied 456 small

retail businesses (service industry) in 48 rural communities across 12 states and found

58

 

 

that small retailers respond strategically by putting more emphasis on target market
(consumers) by offering innovative products and services to cope with changes. Covin
and Slevin (1989) agreed that small ﬁrms should be particularly careful in dealing with
environmental changes because of their limited resources and the more devastating
consequences of poor managerial decisions than would be suffered by large ﬁrms. When
compared with larger businesses, which have technological innovative advantages, small
businesses have innovative advantages based upon acquisitions of Skilled labor (Acs and
Audretsch,1988; Grimm, Corsi, and Smith, 1993).

Results from previous research imply that government Should focus on small
business needs (e. g. small businesses are particularly sensitive to taxes and expense-
related issues) as well as improving the general business climate to encourage small
businesses to generate new employment. The emphasis upon small businesses in
government economic development policy drew its impetus from the recognition of small
ﬁrms’ ability to create employment (Judd, Greenwood, and Becker, 1988; Atkinson and
Storey, 1994).

In the early 19805, the Michigan state government already realized that the growth
and stability of the Michigan economy is especially dependent upon the development,
maintenance and growth of small businesses which are capable of overcoming the
relatively high cost of conducting business in Michigan. The government also recognized
that a successful strategy for the continued Vitality of Michigan’s durable-goods
dominated economy was dependent upon the ability of Michigan to provide an

environment conducive to the generation of new businesses and supportive of the

59

 

continued existence of smaller growth-oriented businesses. Governor Milliken Started a
pilot Small Business Development Center Program. The purpose was to develop new
businesses and enhance the growth of existing small businesses (State of Michigan,
1982).

Recently, the Michigan Jobs Commission began to offer programs and ﬁnancial
incentives designed to encourage the economic development of small businesses in the
state. In 1995, the Michigan Economic Growth Authority (MEGA) was established for
the purpose of reducing taxes for ﬁrms planning to locate or expand facilities in the state
(e. 3. grant Single business tax credits based on the number of new jobs created for up to
25 years). The creation of Renaissance Zones started in January 1, 1997 is one of the
programs to encourage businesses to locate in Michigan. Eleven Renaissance Zones (six
urban zones, three rural zones, and two former military bases) have been designated as
tax-free locations for spurring the creation of new jobs and investments (Public Sector
Consultants, 1998). Further programs intended to aid small businesses include: the Small
Business Administration (SBA) ﬁnancing program that guarantees up to 90 percent of a
business loan provided by commercial lenders; the Small Business Innovation Research
(SBIRS) program that provides opportunity to support small-business R & D; the
Business Export Assistance program and the Government Procurement Assistance
program that assist small businesses in obtaining contracts from federal, state, and local
governments; and various small business assistance agencies, such as the Michigan Job

Commission, the Michigan Minority Business Development Center, the Michigan Small

Business Development Center, the Small Business Association of Michigan, and the US.

Small Business Administration (Michigan Small Business Development Center, 1998).

Table 2-12 summarizes the problems in external environment that small

businesses face.

Table 2-12 Literature Relating to External Environment Problems of Small Businesses

 

Problems of Small Businesses

Author (Year)

 

Government Related

Peterson, Kozmetsky, 8 Ridgway(1983)

 

of Paperwork, Quality of Labor

Inflation, Taxes, Government Regulation, Costs

Franklin 8 Goodwin (1983)

 

Red Tape

Taxes, Finding Qualified Labor, Regulation, and

Anonymous (1 998)

 

 

Cash Flow, Controlling Costs, Competition,
Supplier Relationships, Advertising! Promotion,
Quality of Labor, Government Regulation,
Employee Productiviy, and Health Insurance

Center (1 998)

 

Michigan Small Business Development

 

Table 2-13 shows studies of decision making by small businesses to respond,

external environment.

Table 2-13 Comprehensive Research on Small Business Decision Making

 

 

 

 

Purchasing Power

 

and product seLmentation

 

Problems Decisions Author (Year)

Hostile Economic Environment Concentrate on the target Kean, Gaskill, Leistritz, and
and Competition with Large market, innovative products and Jasper (1998)

Firms services

Changes in Population and Emphasis on the (target) market Covin and Slevin (1989)

 

2.2.3.5 Hospitality/Tourism and Economic Development Programs

Although Michigan’s economy has been dominated by the automotive industry,

this is not the only major industry in the state (Fosler, p. 91; Kutscher and Mark, 1983;

61

 

 

Cary. Ful
the state'
and ChClT
loss of In
Northern
the servic
from mm
A:
also treat:
lntematim
generated
1011mm III
is ranked ;
ADOlher 5i
dOmeSu‘c r.
Amerit-Ins
and IOllrisr
Res
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Hm bEDEfIt

IF. 1
“QUSPORQII.

Cary, Fulton, and Hymans, 1996). In the 18705 and 18805, agriculture and lumber were
the state’s largest industries. These industries, however, have been superseded by tourism
and chemicals. As the lumber industry was dying out and the railroads faced the obvious
loss of business, the railroads ﬁnanced large resort hotels on the Upper Peninsula and the
Northern Lower Peninsula (e.g. the Grand Hotel on Mackinac Island), giving tourism and
the service industry a major boost. By contrast, some towns that failed in the transition
from lumbering to tourism quickly became ghost towns (Fosler, 1988).

As one of the fastest-growing service sectors, the tourism and hospitality industry
also creates jobs and promotes regional economic development. U.S. earnings from both
international and domestic tourism were 260 billion dollars in 1986, and payroll income
generated by tourism was 58 billion dollars (Edgell, 1988; Ticknor, 1988). The American
tourism industry is second only to health services in private employment in the US. and
is ranked as the ﬁrst, second, or third largest industry sector in 39 states (Heller, 1992).
Another sign of this fast growing sector is that, “demand for airline tickets for US.
domestic travelers in 1998 was up 3.5 percent over last summer’s record breaker and
Americans are expected to shell out more than half a trillion dollars on vacation travel
and tourism this year” (ABC News, August 4, 1998).

Researchers also have discerned economic beneﬁts of rural tourism development
and have begun to explore tourism as a tool for the development of both rural and urban
communities (Lewis, 1996). Edgell (1988) argues that the growth of tourism and travel
can beneﬁt such interrelated areas as construction and maintenance of tourism facilities,

transportation, retail sales, recreation facilities, lodging, restaurants, and other related

62

 

hospitality services by providing job creation opportunities and urban and rural area
economic development (e. g. employing tourism as a method for developing inner cities
and new communities). Bonnett (1993) also supports the importance of tourism as an
economic development tool and as a basis for entrepreneurial activity to draw the outside
market into the local economy. AS more tourists Visit a region, more opportunities can be
created for business development and jobs in hotels, restaurants, and various hospitality
businesses. For example, US. travel and tourism posted a record-setting 16.8-billion-
dollar trade surplus in 1991 and 15.3-billion-dollors in 1995, with prospects for increased
spending by foreigners in the coming years (Gatty, 1992; WTO, 1997).

Research on the economic impact of tourism has been conducted as an effort to
understand the advantages and disadvantages of tourism to a community. In a cost-
beneﬁt study of tourism (using the monetary beneﬁt-cost model), Ohadweh (1983) found
that tourism provides signiﬁcant employment creation and income generation
possibilities and that tourism beneﬁts surpass the costs in metropolitan areas, such as
Portland, Oregon. Schneider (1993), however, raised a concern about adopting tourism
development in agricultural communities Without any appraisal of the town’s ability
(inventory) to make tourism successful. Tooman (1995) also raised the same caution
about adopting tourism as a means of rapid economic development. A study examining
the correlation between tourism infrastructure components and economic impacts of
tourism in rural counties in Indiana might be an answer for those concerns. Nadkarni
(1995) found that three of the attraction components (culture, nature-related tourism

component, and amusements and outdoor recreation component) are positively correlated

63

with the tourism economic impact, that is, tourism expenditures and direct impact on
employment, resident earnings, and state and local government revenues. In a study on
the relationship between tourism and rural community economic development in
Montana, Moisey (1997) suggested that local initiatives are the most effective strategy to
provide more immediate economic gains while minimizing potential costs (e. g. social
costs).

In recognizing the economic beneﬁts of tourism, both federal and state
governments viewed tourism as an important urban and rural economic development
strategy (Seal, 1994; Lankford, 1997). The demands for rural tourism also grew as a result
of domestic and international tourists who venture out to see and experience rural
America (Edgell and Harbaugh, 1993). AS a result, an increasing number of state
governments have adopted tourism as an efﬁcient tool for keeping rural communities
economically viable (e. g. Michigan’s rural tourism areas in traditionally agriculture
regions). For example, the Wyoming state government recently announced an aggressive
new strategy having the major goals of creating jobs and increasing tourism to boost their
economy (Nelson, 1998).

In realizing the increasing role of state tourism policy and tourism related state
agencies, Van Hoof (1996) found that the State ofﬁce of tourism is an important state
organization in charge of implementing state tourism policies. Fagan and Longino, Jr.
(1993) stated that communities depending solely on manufacturing industries for
economic growth and development might be missing opportunities to better succeed with

their efforts and stressed the contribution of the tourism and retirement industries on

 

economic growth in rural areas. Economic planners encourage the utilization of
underdeveloped rural resources for tourism to replace low- to negative-growth industries,
because the tourism industry easily ﬁts into the infrastructures of these rural communities.
For instance, Kansas City linked with nearby rural areas (historic Harrisonville, the
Lexington Mountain area, and historic and cultural Kansas City Hub) to develop tourism
jointly (Edgell and Harbaugh, 1993).

Furthermore, there are many examples of utilizing tourism as a means of
economic development to create more jobs and revenue. JohnsOn County, Tennessee, is
one of the successful examples of rural tourism as an important tool of economic
development for creating jobs and bringing in new businesses. Johnson County
consistently suffered from high unemployment until the 19805. This region, however,
proves that rural areas can integrate innovative tourism programs with other efforts to
successfully achieve economic development (Edgell and Staiger, 1992). Since
Connecticut started promoting itself as a vacation spot that has many convention sites and
weekend getaways, the beneﬁts have been substantial. Tourists in Connecticut spent
about 2.5 billion dollars (only 685 million dollars in 1977) on gasoline, food, hotels, and
admission fees, and about 50,000 residents had tourism related jobs in 1985. The state
estimates that every two dollars spent on tourism generates between three and ﬁve dollars
in related industries. Further, tax revenues from tourism are 150 million dollars a year
(Hall, 1986). Upper Little Tennessee Valley had begun to use tourism as a means of
economic growth in the 19905, because residents found tourism provided the sole

opportunity for escaping the poverty which a half century of extractive growth could not

65

 

eliminate. Their growth decreased, however, because neighboring counties were adjacent
to a National Park (Taylor, 1996).

The failure of Illinois tourism development, based on riverboat casino gambling,
to revitalize a community’s economy, particularly its tourism industry, provides insight to
policy makers considering methods of tying legalized gaming licenses with capital
investment in order to accomplish development goals (Truitt, 1996). South Carolina’s
tourism is the state’s second largest industry, providing more than 272,000 jobs and
generating 428 million revenue dollars. This success is predicted to continue in the future
because of carefully planned strategies: (1) implementing an aggressive marketing
strategy that reaches beyond traditional advertising; (2) focusing on business development
as a way to create more products and therefore more capital for investment; (3) generating
economic growth in rural areas, while safeguarding traditional values and lifestyles; and
(4) using technology to stay ahead of competition (McKown, 1995). These strategies
indicate the future direction that the tourism industry and policy makers should consider
if there is to be continued success in building regional economies.

When considering the growing importance of the hospitality/ tourism industry in
the US. economy, some questions should be addressed as to whether or not the
hospitality/ tourism and service industries are different from other industries in perceiving
elements of business environments, including State government policies and what the
appropriate policies for the tourism and hospitality industry should be.

Little research, however, has addressed these questions nor identiﬁed external

environmental problems that the hospitality/ tourism industry faces. Some authors have

66

identiﬁed an adequate location for tourism development as important for maximizing the
positive impact of tourism development. The location of a major destination attraction
requires an adequate market within 100 to 200 miles having a population with sufﬁcient
disposable income, a large site, excellent access to the site, appropriate zoning, available
supply of part-time labor, and acceptable weather. These elements provide a favorable
external environment to tourism businesses as well (Tuttle, Baier, and Alexander, 1986).
In an assessment report of tourism and its environment, tourism, including the hotel
industry, was shown to be inﬂuenced negatively by savings and loan association failures,
overbuilding, the recession, labor availability, taxes, and government regulations (Hasek,
1991). Even if the results above provide important insights to policy makers, these
ﬁndings are not comprehensive enough to address the different environment factors that

inﬂuence the hospitality/ tourism industry.

67

Chapter 3

3. RESEARCH METHODS

This chapter outlines and discusses the research procedures and a variety of

different methods that were employed to address this study’s research objectives and

hypotheses. The overall research process is presented in Figure 3-1.

 

 

 

 

 

 

 

 

 

 

Problem 5 &
Trends

 

 

 

Focus A
Group F
I I
Research < Literature
Hypotheses Review

 

 

 

 

 

 

 

 

l

 

 

Questionnaire &
Research Design

 

 

 

I

 

 

Analysis &
Hypotheses
Tbsﬁng

 

 

 

 

 

 

 

 

 

Conclusions

 

 

 

 

Figure 3-1 The Overall Research Process

68

3.1 Research Design and Data Collection

The data used in this research were collected by the Tax Policy Center at
Michigan State University. Data were collected through focus-group sessions and
through a mail questionnaire. The methods employed to conduct the focus groups and the

mail survey are described below.

3.1.1 Focus Groups

Focus group interviews were conducted by staff members of the Tax Policy
Center at Michigan State University in June, 1995. The businesses used in the focus-
group interviews were identiﬁed on the “The American Business Lists” that were
provided by a division of American Business Information, Inc. The objective of the focus
groups was not to gather information that could be generalized to all businesses in
Michigan. Rather, the goal was to: (1) determine factors (e. g. regulations, taxes,
consumer demand, and labor market) that may inﬂuence business decisions; (2)
determine perceptions relating to whether or not government requirements hurt or beneﬁt
their businesses; (3) understand factors that contribute to how business owners and
managers perceive State agencies and services; (4) gather the information to help
formulate research hypotheses; and (5) use the information to develop a questionnaire to
be mailed to a state-wide stratiﬁed cluster sample of primary, secondary, and service
businesses.

The results of the literature review, especially literature dealing with attitudes and

opinions of businesses toward state government agencies and policies, provided the basis

69

for three primary questions that framed the focus group interviews. The focus group
participants were asked: (1) what are the things that State government programs, ofﬁcials
and agencies do, have done, or may be planning to do, that do or can help you to
successfully manage a business?; (2) What are the things that state government programs,
ofﬁcials, and agencies do, have done, or may be planning to do, that make it difﬁcult to
manage a business?; and (3) what should state government do to change those things, or
put another way, what would you change so that state government could better serve the
needs of the business community?

Focus groups were conducted with business owners and managers in three key
geographic regions of the state: the northern lower peninsula (Alcona, Alpena, Antrim,
Charlevoix, Cheboygan, Chippewa, Crawford, Emmett, Kalkaska, Luce, Mackinac,
Montmorency, Oscoda, Otsego, and Presque Isle), the eastern part of the upper peninsula,
and the central western portion of the state (Allegan, Barry, Calhoun, Eaton, Ionia,
Kalamazoo, Kent, Mecosta, Montcalm, Muskegon, Newaygo, Ottawa, and VanBuren),
including the greater Detroit area (Genesee, Lapeer, Lenawee, Livingston, Macomb,
Monroe, Oakland, St. Clair, Washtenaw, and Wayne).

The initial plan was to have 12 businesses participate in each of the three focus
group sessions. Businesses in each of the three regions were then stratiﬁed by Standard
Industrial Codes (SIC) and by number of employees. American Business Information,
Inc. generated a stratiﬁed random sample of businesses for each region. The sample was
comprised of one business representing ﬁrms that employed one to nine employees and

ﬁrms having 10 to 19 employees, respectively, for each of the three SIC codes

70

 

(Agriculture, Manufacturing and Services). Two businesses were selected to represent
businesses in each SIC code that employed 20 or more employees.

Twenty-one businesses actually participated in the focus group sessions as Table
3-1 Shows. The focus groups consisted of eight participants from agriculture-related
businesses; ﬁve of these were businesses of 20 or more employees. Twelve service
businesses participated. Half were businesses that employed 20 or more employees.
Only one small manufacturing business participated. Clearly, manufacturing businesses
were underrepresented even though the 12 manufacturing businesses responded positively

to the invitation to participate in the focus group sessions.

Table 3-1 Industries and Size of Business that Participated in the Focus Group

 

 

 

 

 

Number Of Emplor ees
Industry SIC 1-9 | 1-19 20+
Agriculture 01-09 1 2 5
Manufacturing 01-19 1 0 0
All Services 70-89 4 2 6

 

 

 

 

A qualitative content analysis was performed on the transcripts of the three focus
groups. There was no separate analysis by geographic region or by SIC category. The
purpose of the content analysis was to summarize key perspectives and points of View
that could be included in the state-wide questionnaire. Quotes that represented these
perspectives and points of View were captured to provide additional insight that could be
helpful in drafting the questionnaire.

By and large, the focus group participants did not View government as being

helpful in terms of the operation of their businesses. They were more prone to identify

71

ways that government negatively impacted their businesses, rather than being helpful.
Most commented that complying with regulations was costly. Some state regulations,
however, were seen as beneﬁcial to businesses. Most participants agreed that regulations
were often a double-edged sword, because they were seen to protect the public and
standardize the way business is done in the state. The businesses expressed positive
acknowledgment for various incentives and grant programs. There was also anxiety that
some agencies or programs that were helpful to businesses had been eliminated or scaled
back.

Certain regulations (e. g. pesticides), agencies (e.g. MIOSHA and DNR), and laws
(e.g. polluter pays and motor carrier) were considered to be disincentives for business
growth. There was also frustration that many times businesses are required to comply
with the interpretation and perception of state ofﬁcials and inspectors, rather than with the
law itself. This complicates and frustrates compliance. Small businesses argued that the
amount of compliance- and application-related paperwork is too burdensome and a
barrier to expansion. Taxes (e. g. payroll, SBT, and Federal Unemployment Tax
Administration) also emerged as a concern among businesses. Some felt that too many
taxes and over-taxation stiﬂe growth, while others believed that there were too many
different taxes and would prefer a ﬂat tax. Labor and employment issues were a major
concern across different types and sizes of business. MESC (Michigan Employment and
Security Commission) and Department of Labor were perceived as being biased on the

side of employees, and not always fair to employers.

72

The participants also mentioned poor quality of service provided by government
agencies (e. g. hard to talk to a person, time involved in ﬁnding the right contact,
incompetent or uncaring employees, and no business-orientation) as a signiﬁcant
problem.

Participants felt that state agencies need to be more service- or business-oriented
(e. g. government needs to market itself; a grievance procedure against state employees
needs to be established; and faster response time is necessary). Businesses also believed
that government Should be more innovative in its perspective and approach to serving the

business community.

3.1.2 Data Collection Method: The Mail Survey

A mail questionnaire was administered during the summer of 1995 by the Tax
Policy Center at Michigan State University. The results and issues that emerged in the
focus group sessions guided the development of the questionnaire in the state-wide

survey.

3.1.2.1 Instrumentation

The questionnaire was designed to collect three primary types of data: (1)
perceptions of the importance of external business environment factors (economic, legal
and government, and consumer and labor markets as business environment factors) in
hiring decisions; (2) perceptions and satisfaction levels relating to government services

provided by various state agencies; and (3) the characteristics of responding businesses

73

 

(e. g. business sectors, ownership, length of business establishment, business seasonality,
and number of employees) and whether or not the business was part of the tourism
industry (percentage of total tourist dollars of total sales). A copy of the survey

questionnaire is included in Appendix B.

3.1.2.2 Operational Deﬁnitions and Measures of the Perceived External
Environment

The operational deﬁnitions and measures of the variables used for testing the
research hypotheses are presented here. Speciﬁcally, operational deﬁnitions and
measures associated with the external environment variables that impact ﬁrms’ hiring
decisions, the importance of the inﬂuence of those variables to ﬁrms’ hiring decisions,
and different business sizes and types are presented. The method of measuring the
satisfaction level with various state agencies, state government services, and state
employees’ expertise are also described.

In this study, the external environment variables mainly focus on: (1) state-
govemment-related variables, such as laws, regulations, taxes, paperwork, and
employment-related regulations (e. g. unemployment insurance, workers’ compensation,
healthcare, and unions) and (2) market-related variables, such as labor supply and
consumer demand for the products and services.

The impact of these variables on ﬁrms’ hiring decisions are measured by the
perceptions of business owners and managers. The inﬂuence of external environment
variables are based on the subjective evaluation of respondents (perceived environment)

in terms of the impact that the variables have on their ﬁrms’ hiring decisions. The

74

relative importance of the variables to businesses is deﬁned as “the extent to which the
owners and managers of the businesses perceive external environment variables that
inﬂuence the ﬁrm’s decisions to hire more full-time employees.” The extent to which the
variables inﬂuence the ﬁrm’s hiring decisions was assessed by asking respondents about:
(1) state labor laws and regulations; (2) state regulations that govern workplace safety; (3)
state taxes; (4) access to credit; (5) labor unions; (6) workers’ compensation; (7) the
paperwork required by state government; (8) access to qualiﬁed labor; (9) the start of the
school years prior to labor day; (10) unemployment insurance; (11) consumer demand for
the products and services offered by the business; and (12) the cost of beneﬁts (e. g.
healthcare). Importance was measured using a ﬁve-point scale.

Respondents were asked to use the ﬁve-point scale to express their degree of
satisfaction with the following 12 state agencies with which they may have had contact
during the preceding 12 months: (1) Michigan Jobs Commission; (2) Michigan
Department of Natural Resources; (3) Michigan Employment Security Commission; (4)
Michigan Department of Transportation; (5) Michigan Occupational Safety and Health
Agency; (6) Michigan Travel Bureau; (7) Michigan State Police; (8) Michigan
Department of Social Services; (9) Michigan Department of Agriculture; (10) Michigan
Department of Commerce; (11) Michigan Department of Treasury; and (12) Michigan
Department of Education.

General satisfaction with state government services and with state employees’
expertise was also measured by assessing agreement and disagreement (on a ﬁve-point

scale) with the following statements: (1) “The quality of services offered by state

75

government meets the needs of this business;”(2) “State government needs to market
itself better SO that this business will know more about the products/ services government
has to offer;” and (3) “State government employees do not know enough about this type

of business to be of any help.”

3.1.2.3 Operational Deﬁnition of Business Size

In this study, businesses were stratiﬁed into three groups for sampling purposes;
they are: businesses having one to nine, 10 to 19, and 20 or more employees in terms of
“full—time equivalents”(FTEs). As prescribed by the Michigan Employment Security
Commission, the number of FTES is calculated by taking the total number of hours
worked by all of the employees of a business and then by dividing that number by 35
working hours a week. All the businesses in the sample are categorized into three FIE

groups: one to nine, 10 to 19, and 20 or more.

3.1.2.4 Population and Sample

The population for the study is all Michigan "for-proﬁt" ﬁrms in existence in
1995. Non-proﬁt ﬁrms and government organizations were excluded from the study
population, because this study focuses on private and proﬁt-oriented ﬁrms’ decision
making that strategically copes with external environments (e. g. cost-effective strategies).

A stratiﬁed (by sizes) cluster (by regions) sampling technique was used to select a
sample of businesses of different sizes in different geographic regions. The sampling

frame consisted of 3,000 Michigan businesses compiled from the American Business

76

Lists provided by a division of American Business Information, Inc. Stratiﬁcation
categories are deﬁned as businesses having one to nine, 10 to 19, and 20 or more
employees measured in terms of “full-time equivalents”(FIEs). Clusters are deﬁned by
six different geographic regions: Upper Peninsula, Northeast, Northwest, Southwest,
Southeast, and Metro Detroit area. The sampling strategy produced a representative and
adequate number of responses within each geographic and size strata to permit

subsequent analysis (Appendix D).

3.1.2.5 Pretest and Survey Administration

The questionnaire and cover letter were pre-tested by sending them ﬁrst to 10
businesses in the East Lansing area. The purpose of the pretest was to make sure that the
questionnaire was easy to complete. The owners or managers of each of the businesses
completed the questionnaire and provided additional comments about wording, format,
and instructions. For the most part, the businesses that participated in the pretest felt that
the cover letter clearly communicated the purpose of the research, and few respondents
encountered any difﬁculty in completing the questionnaire. Based on recommendations
from the pretest, additional open-ended questions were incorporated in Sections Two and
Three of the questionnaire.

A package consisting of the cover letter, questionnaire (Appendix B), and a
postage-paid return envelope was mailed to the 3,000 businesses that comprised the
stratiﬁed cluster sample acquired during the summer of 1995. In most cases, the

envelope and cover letter were addressed to a speciﬁc, named, contact person within the

77

organization. These people were owners and/ or managers of the businesses. In the event
that a contact person could not be identiﬁed, the envelope and cover letter were addressed
to the “owner/ manager.” The cover letter stressed that the study was endorsed by the
Tax Policy Center at Michigan State University and by the Michigan Chamber of

Commerce.

3.1.2.6 Response Rate

In order to maximize response rate and to reduce non-response bias, a reminder
post card (Appendix C) was mailed one week after the questionnaire. The post card
thanked those who had already completed and returned the questionnaire and encouraged
others to also respond. Approximately two weeks after the post card reminder was
mailed, those who had not yet responded were sent a second questionnaire and a letter
that urged them to participate.

Of 3,000 questionnaires mailed, a total of 2,899 questionnaires were successfully
delivered. The remaining 111 questionnaires did not reach the businesses and were
returned because of address changes or incorrect addresses. Approximately one-third
(968 businesses, 33.4 percent) of the 2,899 Michigan businesses completed and returned
questionnaires. Thirty-three percent of respondents were presidents, 23 percent were
owners, 15 percent were (general) managers, and the remaining were CEOs, VPs,

Directors, etc.

78

3.1.3 Data Preparation

The returned questionnaires were dated and checked for completeness. After
examining the 968 returned questionnaires, a total of 953 questionnaires were qualiﬁed
for further data processing and analysis. Fifteen questionnaires were eliminated from
further processing due to signiﬁcant incompleteness. SPSS for Windows Release 6.3 was
employed to enter data. After the completion of data entry, data cleaning was performed
by checking each variable’s frequency distribution. Obvious coding errors were corrected
by checking the original questionnaire or re-coding.

Respondents were asked to: (1) identify the their business sector (Question 2 in
Section Six) and (2) indicate whether or not the business was part of the tourism industry
(Question 8 in Section Six). The problems with these questions were that businesses
could identify more than one business sector (e.g., ﬁshing, wholesale/retail), and that they
could identify themselves as tourism businesses based on their perception of the amount
of their revenues related to tourism and tourists. For example, a commercial ﬁshing
business that sells both wholesale and retail could classify themselves as a tourism
business if the majority of their wholesale business is with resorts and hotels, and/or the
majority of their retail sales are to tourists. Although this may be conceptually correct, it
differs signiﬁcantly from Standard Industrial Classiﬁcation (SIC) designation of business
sectors and tourism businesses. By checking the original questionnaires using the
descriptions of the business provided by respondents, along with the business sectors they
checked, some businesses’ self classiﬁcations were re-coded into more SIC consistent

categories. For purpose of the analyses, businesses were only classiﬁed as tourism

79

 

businesses if they provided services or products to tourists, not if they provided products
and services to tourism businesses.

After this process, the businesses were categorized into six industry groups: (1)
primary industry, which included agriculture, ﬁshing, mining, and forestry; (2) secondary
industry, which included manufacturing and construction; (3) wholesale/retail; (4) general
services, which included ﬁnance, insurance, real estate, transportation, and
communications; (5) personal and managerial services, which included legal, medical,
repairing, and managerial services; and (6) hospitality/tourism industry, which included

lodging, food, recreational, and tourism.

3.1.4 Data Analysis

To obtain an overall proﬁle of the sample, descriptive statistics were performed.
This analysis provides a picture of the perceptions of the importance of external
environment factors including: (1) the inﬂuence of state government policies in hiring
decisions among Michigan businesses and (2) business’ level of satisfaction with state
agencies and agency services. The descriptive statistics also provide proﬁles of the
responding businesses in Michigan (e. g. business sector classiﬁcation, ownership type,
duration of business establishment, business seasonality, and number of full-time-
equivalent employees in the business).

One of the main hypotheses of this study is that different types and sizes of
businesses differ in terms of the inﬂuence of various environmental factors, including

state government policies, on their hiring decisions. Also, the degree of satisfaction with

80

state agencies and their services is assumed to be different for various types and sizes of
businesses. For the purpose of analysis, businesses were classiﬁed into three groups: (1)
“small” businesses having less than 50 total employees; (2) “medium-sized” businesses
having 50 to 100 total employees; and (3) “large” businesses having more than 100 total
employees. This breakdown provided enough responding businesses in each size
category for statistical analyses. Although the sampling was based on different size
categories: ( 1) one to nine; (2) 10 to 19; and (3) more than 20 employees, there is no
generally accepted deﬁnition of small, medium, or large businesses. The sampling was
designed to produce enough small businesses to allow statistical comparisons across
“different size of businesses” categories. For the comparisons across “different types of
businesses” category, the six re-coded industry sectors were used.

Since the external environment variables were drawn from the results of focus
group sessions, there might be redundant information for a number of environment
variables. Thus, it is useful to conduct further analyses to determine the underlying
structure of the variables. According to the Review of the Literature, external
environment variables are conceptually classiﬁed into two groupings: (1) a state
govemment-imposed cost of doing business grouping that consists of state labor laws and
regulations, state workplace safety regulations, state taxes, workers’ compensation, the
paperwork required by state government, unemployment insurance, and the cost of
beneﬁts (e. g. healthcare) and (2) a market environment grouping that includes such
variables as access to qualiﬁed labor and the consumer demand for the products and

services offered by the business. The latter grouping represents labor- and consumer-

81

 

market-related variables. These two groupings of external environment variables are
based on the Review of the Literature, the results of correlation testing among 12 external
environment variables examined in this study, and reliability tests of those groupings
(factors).

Table 3-2 shows the results of correlation testing among 12 external environment
variables that were used in this study. Such variables as access to credit, labor unions, the
start of the school year, access to qualiﬁed labor, and consumer demand show low
correlation with state-government-related variables, such as state laws and regulations,
safety regulations, state taxes, workers’ compensation, paperwork required by state
government, unemployment insurance, and the cost of beneﬁts. The results indicate that
these variables are different sets of variables. In order to test if these factors were
reliable, reliability tests were conducted. The alpha value of seven state-govemment-
related variables is 0.92. Furthermore, the alpha value of market-related variables, such
as access to qualiﬁed labor and consumer demand is 0.54. Since the alpha values of these
factors are greater than 0.5, the variables in each grouping correlate with each other and
can be considered reliable.

A factor analysis was performed to determine if the factors produced by factor
analysis were consistent with these two conceptual groupings. Factor analysis was
conducted to identify groups of variables that have shared common variance. The factors
are mutually independent without redundancy (Johnston, 1991). These factors were then
used to test the hypothesis that different types and sizes of businesses are inﬂuenced by

different factors in their decision making (e. g. hiring additional full-time employees).

82

A principal-components analysis method that extracts the factors from the
correlation matrix in serial order of eigenvalue size was employed as an initial factor
extraction. In order to decide the number of factors to extract, the following four criteria
were applied: ( 1) unit eigenvalue (>1); (2) scree test (plotting the eigenvalues against the
number of factors); (3) variance explained to account for as much of the variance as
possible; and (4) interpretability of factors. The reasons for using the criterion of
interpretability of factors are that: (1) statistical considerations alone are not entirely
satisfactory and (2) in most instances the meaning or interpretability of the retained
factors plays an important role. Then, the varimax rotation procedure was employed.
This rotation technique produces some high loadings and some near-zero loadings on

each

83

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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84

factor, by simplifying the columns of a factor matrix (Nie et al., 1975). The rotation
procedure is also necessary to identify variables as approximations to simple structure
when there are groups of variables with a lot of shared common variance (Johnston, p.
163). The results of the factor analysis will be discussed in the next chapter.

Mean scores for each factor by different types and sizes of businesses were then
analyzed using the Analysis of Variance (AN OVA) test. An independent T-test was
employed to test if there was a non-zero mean difference between any two types of
businesses in terms of each external environment factor. The same technique was used to
examine if each size of business was inﬂuenced differently by different environment
factors or variables.

As another means of testing the hypotheses, the AN OVA test was used to
compare mean differences of each factor for different types and sizes of businesses. The
ANOVA test was also used to test degree of satisfaction of different types and sizes of
businesses with various state agencies, quality of their services, and the expertise of state-
agency personnel. Figure 3-2 summarizes the framework of the statistical analyses used
in this study.

All the statistical analyses were performed with the Statistical Package for the
Social Sciences (SPSS). SPSS v. 7.5 was also employed for data modiﬁcations and
transformations, as well as for other statistical tests used in this study. Throughout this

study, a 0.05 level of statistical signiﬁcance (or level) was used for testing hypotheses.

85

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Figure 3-2 Overview and Sequence of the Statistical Analyses in This Study

86

 

 

3.1.5 Limitations of the Data

First, manufacturing businesses were under-represented in the focus group
sessions; however, the results of the focus groups were only utilized to design the
questionnaire.

Second, the questionnaire was not designed with all of the speciﬁc objectives and
hypotheses in mind that constitute the focus of this study. The data produced are, in
effect, secondary data; and, like most secondary data, they are less than ideal for some of
this study’s purposes. Even if this researcher assisted the research process except the
focus group sessions, the questionnaire and research were designed to fulﬁll the
objectives of other participants in this project, such as the Michigan 2000 Foundation and
the university Research Director. Some variables in the questionnaire, therefore, could
not be used for this research.

Third, the size of businesses sampled in this study was skewed toward small
businesses because of the original sampling scheme that stratiﬁed size into categories of
one to nine, 10 to 19, and more than 20 employees. There is no complete list of the
number of different-sized businesses that are sampled. As a result it was impossible to
assess the representativeness of the mail questionnaire returns, or to assess the extent and
direction of non-response bias.

Fourth, since the respondents could select more than one sector, type of business,
that applied to their businesses, it was not always clear into which sector to classify each
business. Even if data were re-coded into six industry sectors after reviewing the

description of each business that the respondents provided and the business sectors they

87

checked (multiple choices), critics might question this researcher’s judgment in

classifying the businesses.

88

Chapter 4

4. RESULTS

This chapter presents the results of various data analyses obtained from
implementing the previously described methods. The chapter consists of three parts: (1) a
descriptive analysis of the responses to the mail survey; (2) results from factor analysis
conducted to identify external environment factors of businesses before conducting the
hypotheses tests; and (3) a statistical analysis implemented to test each of the six

hypotheses.

4.1 Descriptive Analysis of the Sample

The descriptive analyses were performed on data generated from the 953 useable

questionnaires. All the questionnaires were returned during the summer of 1995.

4.1.1 General Characteristics of Responding Businesses

The number and percentage of small (less than 50 employees), medium (51 to 100
employees) and large businesses (more than 100 employees) that returned a mail
questionnaire are shown in Table 4- 1. Since the sampling scheme was orientated toward
small businesses, 82.7 percent of the responses were from this target group (Table 4-1).
The distribution of responses generally reﬂected the size distribution of Michigan
businesses in 1995 (La Lopa and Holecek, 1996). The mean number of employees of the

businesses that responded to the survey is 94 employees (mean: 93.5). Businesses having

89

more than 100 total employees were classiﬁed as large businesses and businesses having
less than 100 total employees are classiﬁed as small businesses if they had less than 50

employees and medium sized-businesses if they employed 51 to 100 employees.

Table 4-1 The Size—Total Number of Employees—of Businesses
that Returned a Mail Questionnaire

 

 

Valid

Business Size Frequency Percent
Small Businesses 666 82.7
Medium Businesses 59 7.3
Large Businesses 80 9.9
Subtotal 805 100.0
Missing Cases 148

Total 953

 

 

 

 

 

Note: Small Businesses = less than 50 employees; Medium Businesses = 50 to 100;

Large Businesses = more than 100 employees

The business sectors represented by responding businesses are shown in Table 4-
2. The percentage exceeds 100 percent, because respondents were able to select more
than one sector in classifying their businesses, for example, service and retail. Only 7.4
percent of the participating businesses were in primary industry. Wholesale and retail
businesses comprised a large portion of the respondents (42.7 percent). More than 50
percent (53.8) of the businesses classiﬁed themselves as service-related businesses,
including ﬁnance, communications, transportation, insurance, real estate, and hospitality.
Many of the businesses that selected more than one classiﬁcation chose the service sector
as one category. To better distinguish the types of service businesses, the 513 businesses

that included themselves as part of the service sector were re-coded with more speciﬁcity

90

(see Table 4-3). They are: (1) general services, including transportation, ﬁnance,
communications, insurance, and real estate ( 14.2 percent); (2) managerial/personal
services, including legal, medical, managerial, and personal care services (25.0 percent);
and (3) hospitality/tourism, including recreation, food, lodging and travel-related

businesses (1 1.5 percent).

Table 4-2 The Number of Different Types of Businesses
that Returned a Mail Questionnaire

 

 

 

Business Sectors Frequency Percent
Agriculture 47 4.9
Forestry 1 1 1.2
Mining 5 .5
Fishing 8 .8
Manufacturing 152 15.9
Construction 102 10.7
Retail Trade 293 30.7
Wholesale Trade 1 14 12.0
Transportation 71 7.5
Finance 47 4.9
Communications 37 3.9
Insurance 26 2.7
Real Estate 45 4.7
Services 513 53.8
Total 1471 154.2

 

 

 

 

91

Table 4-3 The Number of Businesses in Re-Coded Industry Sectors that Returned a Mail

 

 

Questionnaire
Valid Cumulative
Tm of Business Frequency Percent Percent Percent
Primary
Industry 19 2.0 2.0 2.0
Secondary
Industry 210 22.0 22.5 24.6
Wholesale/Retail
Services 231 24.2 24.8 49.4
General Services 132 13.9 14.2 63.5
Manageriav
Personal Services 233 24.4 25.0 88.5
Hospitality/Tau rism
Industry 107 11.2 11.5 100.0
Subtotal 932 97.8 100.0
Missing Cases 21 2.2
Total 953 1 00.0

 

 

 

 

 

 

 

The form of ownership of the responding businesses is presented in Table 4-4.
Corporations (63.6 percent) are the dominant type of ownership followed by sole
proprietors (25.9 percent) and partnerships (6.4 percent). The majority of the individuals
that completed the questionnaire was composed of the key-decision makers of the
responding businesses. A third (33 percent) were presidents, 23 percent owners, and 15
percent (general) managers.

The number of years that responding businesses have been in operation is
presented in Table 4-5. The years in business range from three years to 180 years with
the mean number of operating years at 30. One-ﬁfth (20.5 percent) have been in
operation less than 10 years and almost half of the sample is less than 20 years old (48.2

percent).

92

Table 44 Type of Ownership of Responding Businesses

 

 

Valid Cumulative

Ownership Frequency Percent Percent Percent
Sole
Proprietor 246 25.8 25.9 25.9
Partnership 61 6.4 6.4 32.4
Co-operative 12 1 .3 1 .3 33.6
Corporation 603 63.3 63.6 97.3
Other 26 2.7 2.7 100.0
Subtotal 948 99.5 100.0

Missing Cases 5 .5

Total 953 100.0

 

 

 

 

 

 

 

Table 4-5 The Number of Years in Business of Responding Businesses

 

 

Valid Cumulative

Years Frequency Percent Percent Percent
< 10 190 19.9 20.5 20.5
11 - 20 256 26.9 27.6 48.2
21 - 30 168 17.6 18.1 66.3
31-40 106 11.1 11.4 77.8
41+ 206 21.6 22.2 100.0
Subtotal 926 97.2 100.0

Missing Cases 27 2.8

Total 953 100.0

 

 

 

 

 

 

 

Note: mean length of operation, 29.8 years (minimum three years, maximum 180 years)

As shown in Table 4-6, most of the businesses (95 percent) that participated in the

study operate on a year-round basis.

93

Table 4-6 The Number of Year-Round and Seasonal Businesses that Returned

 

 

a Mail Questionnaire
Valid Cumulative
Seasonali Frequency Percent Percent Percent
Year-Round 899 94.3 95.0 95.0
Seasonal 47 4.9 5.0 100.0
Subtotal 946 99.3 100.0
Missing Cases 7 .7
Total 953 100.0

 

 

 

 

 

 

 

Twenty-two percent of the businesses consider themselves as part of the tourism
industry. However, most of these businesses are not solely dependent on tourism for their
revenues. About two-thirds (65 percent) of these businesses generate 40 percent or less
of their revenues from the sale of tourism-related products and services. Approximately
one-ﬁfth generate more than 80 percent of their total sales from tourism. Table 4-8
shows the distribution of tourism-related businesses in terms of their total sales attributed

to tourist dollars. About 77 percent of the businesses are not part of the tourism industry.

Table 4-7 Number of Responding Businesses that Classiﬁed
Themselves to be Tourism Businesses

 

 

 

 

 

 

Cumulative
Tourism Business Frequency Percent Percent
Yes 21 1 22.1 22.1
No 735 77.1 99.3
Missing Cases 7 .7 100.0
Total 953 100.0

 

 

94

Table 4—8 Percentage of Tourism Attributed Sales by Businesses that Classified
Themselves to be Tourism Businesses

 

 

 

 

 

 

 

 

Valid Cumulative
Proportion of Sales Frequency Percent Percent Percent
< 20 % 86 9.0 41.7 41.7
20.1-40 % 47 4.9 22.8 64.6
40.1-60 °/o 34 3.6 16.5 81.1
60.1-80 °/o 19 2.0 9.2 90.3
80.1-100 °/o 20 2.1 9.7 100.0
Total 20% 21.6 100.0

 

 

4.1.2 External Environment Variables and Businesses

A primary goal of the survey was to determine those environment factors that
inﬂuence hiring decisions. Table 4-9 compares the relative inﬂuence of environment
factors on hiring by different-sized businesses. Respondents indicated the inﬂuence of
factors on their hiring decisions on a scale from 1 (very little) to 5 (very much). In
general, all sizes of businesses are inﬂuenced by state-govemment—imposed regulations
and laws that increase their cost of doing business, such as the cost of beneﬁts (mean:
3.49), unemployment insurance (mean: 3.09), workers’ compensation (mean: 3.09), state
taxes (mean: 2.85), paperwork required by state government (mean: 2.72), and laws and
regulations (mean: 2.40). Small businesses are highly inﬂuenced by consumer demand
(mean: 3.66) and access to qualiﬁed labor (mean: 3.27). Large businesses are more
inﬂuenced by consumer demand (mean: 4.08) and labor unions (mean: 2.58) than any
other business size. Variables, such as access to credit, the start of the school year, and
labor unions, are not inﬂuential factors for any businesses. The results of AN OVA tests,

that will be reported subsequently, determined that there are no statistically signiﬁcant

95

differences in the inﬂuence of the state-government-related environment factor on

different—sized businesses.

Table 4-9 Relative Importance of External Environment Variables by Business Size Class

 

Business Size

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Small Medium Large
External Businesses Businesses Businesses Total
Environment Statistics Statistics Statistics Statistics
Variables Mean N Mean N Mean N Mean N
Laws 8
Regulations 2.40 653 2.72 58 2.53 78 2.44 789
Safety
Regulations 2.06 652 2.39 59 2.22 80 2.10 791
State Taxes 2.85 653 2.61 59 2.53 80 2.80 792
Access to
Credit 1 .82 647 1 .81 59 1 .66 79 1 .80 785
Labor Unions 1.42 655 2.37 59 2.58 80 1.61 794
Workers’
Compensation 3.09 654 3.36 59 3.04 79 3.10 792
Paperwork 2.72 652 2.85 59 2.53 80 2.71 791
Access to
Qualified Labor 3.27 658 3.83 59 3.51 80 3.33 797
Start of the
School Year 1 .47 655 1 .22 59 1 .43 80 1 .45 794
Unemployment
Insurance 3.09 655 3.15 59 2.86 80 3.07 794
Consumer
Demand 3.66 651 3.85 59 4.08 77 3.72 787
Cost of
Benefits 3.49 653 3.64 59 3.54 78 3.51 790

 

 

 

 

 

 

 

 

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

96

Table 4-10 compares the inﬂuence of various factors on hiring decisions by
different business sectors. Primary industry ﬁrms are mainly inﬂuenced by state-
government-imposed laws and regulations and the cost of doing business variables, such
as state laws and regulations (mean: 3.00), safety regulation (mean: 2.79), state taxes
(mean: 3.11), paperwork required by state government (mean: 3.16), unemployment
insurance (mean: 3.47), and the cost of beneﬁts (mean: 3.84). The hospitality/tourism
industry is also inﬂuenced by state-govemment-imposed laws and regulations and cost of
doing business variables, such as state laws and regulations (mean: 2.78), state taxes
(mean: 2.92), paperwork required by state government (mean: 2.83), unemployment
insurance (mean: 3.24), and the cost of beneﬁts (mean: 3.14). Later in this chapter,

AN OVA and T-tests will be utilized to test if there are signiﬁcant mean differences

between six industries in terms of the impact of the external environment variables.

97

Table 4-10 Relative Importance of External Environment Variables by Type of Business

 

 

 

 

 

 

Typea Business
Wholesale/ Managerial! Hospitality/
Primary Secondary Retail General Personal Tourism
External Industry Industry Services Services Services Industry Total
Environment Statistics Statistics Statistics Statistics Statistics Statistics Statistics
Variables Mean N Mean N Mean N Mean N Mean N Mean N Mean N
Laws 8
Regulations 3.00 19 2.71 207 2.36 221 2.29 129 2.11 227 2.78 99 2.43 902
Safety
Regulations 2.79 19 2.36 207 2.02 224 1.85 129 1.92 228 2.08 99 2.07 906

 

StateTaxes 3.11 19 2.92 208 2.76 226 2.50 129 2.72 228 2.92 100 2.77 910

2:33:35” 2.05 19 2.03 206 1.81 224 1.66 128 1.60 227 1.66 98 1.78 902
1.58 911

LaborUnions 1.79 19 2.36 209 1.42 226 1.60 129 1.09 229 1.41

 

 

8

 

 

 

 

 

 

Workers’

Compensation 3.42 19 3.67 210 2.99 225 2.63 127 2.76 229 3.18 100 3.07 910

Paperwork 3.16 19 2.97 207 2.67 226 2.52 129 2.43 226 2.83 99 2.68 906

Access to

Qualified Labor 3.21 19 3.60 210 3.10 227 3.20 129 2.99 227 3.52 100 3.25 912

3:: Of School 2.16 19 1.05 209 1.54 226 1.16 129 1.16 229 2.58 99 1.40 911

Unemployment

Insurance 3.47 19 3.44 209 2.96 226 2.83 129 2.76 228 3.24 100 3.05 911

Consumer

Demand 3.58 19 3.73 205 3.60 224 3.79 129 3.44 229 3.27 97 3.58 903 '

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

CostotBenetits 3.84 19 3.69 209 3.47 224 3.58 128 3.28 228 3.14 100 3.46 908

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

Table 4-11 presents mean ratings of inﬂuence of two conceptual groupings,
"state-govemment-imposed cost of doing business” and “market environment,” for small,
medium, and large businesses. The “state-govemment-imposed cost of doing business”
grouping includes such state—government-related variables as state laws and regulations,
safety regulation, state taxes, paperwork required by state government, unemployment
insurance, workers’ compensation, and the cost of beneﬁts. The “market environment”
grouping includes such market-related variables as consumer demand for the products
and services offered by the business and access to qualiﬁed labor. Variables, such as

access to credit, the start of the school year, and labor unions are not included in any of

98

the groupings, because they are not inﬂuential factors for all businesses based on the
correlation analysis.

There are some interesting differences among various-sized businesses in an
assortment of industrial sectors. The “market environment” grouping exerts a similar
degree of inﬂuence across industrial sectors. Hiring by large and small businesses in all

sectors is signiﬁcantly inﬂuenced by the “market environment” grouping.

99

Table 4-11 Relative Importance of External Environment Factors by Size and Type

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

of Business
State Imposed Market
Business Cost of Doing Environment
Size Business Type Business Factor Factor
Small Primary Industry Mean 3.4805 3.7273
Businesses N 11 1 1
Secondary Industry Mean 3.0845 3.6538
N 130 130
Wholesale/ Retail Mean 2.7374 3.3916
Services N 166 166
General Services Mean 2.7029 3.5000
N 100 100
ManageriaV Mean 2.7245 3.3344
Personal Services N 163 163
Hospitality/Tourism Mam 2.7571 3.5438
Industry N 80 30
Total Mean 2.8133 3.4708
N 650 650
Medium Primary Industry Mean 1.7143 .5000
Businesses N 1 1
Secondary Industry Mean 2.9116 4.0476
N 21 21
Wholesale’ Retail Mean 3.5729 4.1250
Services N 16 16
General Services Mean 2.4082 3.5000
N 7 7
ManageriaV Mean 2.3766 3.8182
Personal Services N 11 11
Hospitality/Tourism Mean 3.6429 2.2500
Industry N 2 2
Total Mean 2.9364 3.8362
N 58 58

 

 

 

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

100

 

Table 4-11 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Large Primary Industry Mean 3.0000 3.8333
Businesses N 3 3
Secondary Industry Mean 3.3238 3.9600

N 25 25

Wholesale! Retail Mean 2.2044 3.5417

Services N 12 12

General Sen/ices Mean 2.7381 4.0000

N 13 13

ManageriaV Mean 1 .9474 3.5526

Personal Services N 19 1 9
Hospitality/Tourism Mean 3.9619 4.0000

Industry N 5 5

Total Mean 2.7396 3.7987

N ' 77 77

Total Primary Industry Mean 3.2667 3.5333
N 15 15

Secondary Industry Mean 3.0979 3.7443

N 176 176

Wholesale/ Retail Mean 2.7733 3.4613

Services N 194 194

General Services Mean 2.6895 3.5542

N 120 120

ManageriaV Mean 2.6282 3.3834

Personal Services N 193 193
Hospitalityfl’ourism Mean 2.8467 3.5402

Industry N 37 37

Total Mean 2.81 51 3.5299

N 785 785

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

101

 

4.1.3 Businesses Perceptions of State Government

The questionnaire also asked business owners and managers to indicate: (1) their
contact with various state agencies; (2) their degree of satisfaction with various state
agencies; and (3) their evaluations of the quality of state-govemment services and of the
expertise of state-govemment personnel. Their satisfaction was measured on a ﬁve-point
scale.

There was considerable variation in the amount of contact that different-sized
businesses had with state agencies. More than half of all businesses have had no contact
with the Michigan Jobs Commission (68.5 percent), Michigan Occupational Safety and
Health Agency (57 percent), Michigan Department of Transportation (64.7 percent),
Michigan Travel Bureau (75.1 percent), Michigan Department of Social Services (56.3
percent), Michigan Department of Agriculture (76.6 percent), Michigan Department of
Commerce (64.5 percent), and Michigan Department of Education (68.0 percent). An
even higher percentage of small businesses had no contact with various state agencies:
Michigan Jobs Commission (72.4 percent); Michigan Department of Natural Resources
(57.3 percent); Michigan Department of Transportation (67.4 percent); Michigan
Occupational Safety and Health Agency (62.3 percent); Michigan Travel Bureau (75.6
percent); Michigan Department of Social Services (57.1 percent); Michigan Department
of Agriculture (77.0 percent); Michigan Department of Commerce (65.6 percent); and
Michigan Department of Education (69.7 percent). Only about half of the medium and
large businesses had contact with various state agencies, as shown in Table 4-12.

Medium- (49.1 percent) and large-sized businesses (60.0 percent) had less contact with

102

the Michigan Department of Treasury than did small businesses (62.8 percent). However,
the Michigan Employment Security Commission had considerable contact with all
businesses, regardless of size (65.6 percent by small businesses, 87.5 percent by medium-
sized businesses, and 75.0 percent by large businesses).

About half of those businesses that had contact with a state agency were satisﬁed
with the contact (see percenta in Table 4- 12). Noteworthy was a relatively high
percentage of the businesses that were undecided about their satisfaction with state-
agency contact. There was generally more satisfaction with the contacts with the
Michigan Travel Bureau (satisﬁed: 60.9 percent vs. dissatisﬁed: 12.9 percent), the
Michigan State Police (satisﬁed: 72.9 percent vs. dissatisﬁed: 14.0 percent), and the
Michigan Department of Treasury (satisﬁed: 40.2 percent vs. dissatisﬁed: 27.0 percent).

Table 4-13 shows the satisfaction levels of businesses that had some types of
contact with a particular state agency. In general, businesses are not very satisﬁed with

state agencies.

103

Table 4-12 Degree of Satisfaction with State Agencies by Business Size Class

 

 

Frequencies (Percent/ Percent‘)

 

 

 

 

 

 

 

 

 

 

 

 

 

State Satisfaction Small Medium Large Total

A encies Level Firms Firms Firms 7 Firms

Michigan Jobs NC. No Contact 469 72.4 30 55.6 67F 46.3 536 68.5
Commission 1.Very Satisfied 21 3.2 11.7 4 7.4 16.7 2 2.5 4.7 27 3.5 11.0
2. Satisfied 47 7.3 26.3 1 1.9 4.2 15 18.8 34.9 63 8.1 25.6
3. Undecided 72 11.1 40.2 12 22.2 50.0 18122.5 41.9 102 13.0 41.5
4. Dissatisfied 23i 3.5 12.8 5 9.3 20.8 6 7.5 14.0 34 4.3 13.8
5. Very Dissatisfied 16 2.5 8.9 2 3.7 8.3 2 2.5 4.7 20 2.6 8.1

Michigan NC. No Contact 371 57.3 21 36.2 37 46.8 429 54.6
Department of 1.Very Satisfied 26 4.0 9.4 1 1.7 2.7 1 1.3 2.4 28 3.6 7.9
Natural 2. Satisfied 75 11.6 27.1 6 10.3 16.2 9 11.4 21.4 90 11.5 25.3
Resources 3. Undecided 75 11.6 27.1 12 20.7 32.4 21 26.6 50.0 108 13.8 30.3
4. Dissatisfied 36 5.6 13.0 6110.3 16.2 6 7.6 14.3 48 6.1 13.5
5. Very Dissatisfied 65 10.0 23.5 12 20.7 32.4 5 6.3 11.9 82 10.4 23.0

Michigan NC. No Contact 224 34.4 7 12.1 20 25.0 251 31.8
Employment 1.Very Satisfied 42 6.4 9.8 1 1.7 2.0 ‘3 3.8 5.0 46 5.8 8.5
Security 2. Satisfied 137 21.0 32.0 12 20.7 23.5 11 13.8 18.3 160 20.3 29.7
Commission 3. Undecided 107 16.4 25.0 18I 31.0 35.3 23 28.8 38.3 148i 18.7 27.5
4. Dissatisfied 80 12.3 18.7 10 17.2 19.6 15 18.8 25.0 105 13.3 19.5
5. Very Dissatisfied 62 9.5 14.5 10 17.2 19.6 8 10.0 13.3 80 10.1 14.8

Michigan NC. No Contact 435 67.4 22 38.6 48 60.8 505 63.4
Department of 1.Very Satisfied 18 2.8 8.6 31 5.3 8.6 1 1.3 3.2 22 2.8 7.6
Transportation 2. Satisfied 66 10.2 31.4 11 19.3 31.4 8 10.1 25.8 100 12.6 34.4
3. Undecided 68 10.5 32.4 15 26.3 42.9 13 16.5 41.9 96 12.1 33.0
4. Dissatisfied 27 4.2 12.9 1 1.8 2.9 6 7.6 19.4 34 4.3 11.7
5. Very Dissatisfied 31 4.8 14.8 5 8.8 14.3 3 3.8 9.7 391 4.9 13.4

Michigan NC. No Contact 403 62.3 20 35.1 24 30.0 447 65.4
Occupational 1.Very Satisfied 16 2.5 6.6 1 1.8 2.7 3 3.8 5.4 20 2.9 8.4
Safety and 2. Satisfied 67 10.4 27.5 4 7.0 10.8 19 23.8 33.9 90 13.2 38.0
Health 3. Undecided 85 13.1 34.8 18131.6 48.6 13 16.3 23.2 16I 2.3 6.8
Agency 4. Dissatisfied 42 6.5 17.2 12 21.1 32.4 17 21.3 30.4 71 10.4 30.0
5. Very Dissatisfied 34 5.3 13.9 2 3.5 5.4 4 5.0 7.1 40 5.8 16.9

Michigan NC. No Contact 487 75.6 40 70.2 59 74.7 586 75.1
Travel Bureau 1.Very Satisfied 38 5.9 24.2 4 7.0 23.5 1 1.3 5.0 43I 5.5 22.2
2. Satisfied 57 8.9 36.3 5 8.8 29.4 13l 16.5 65.0 75 9.6 38.7
3. Undecided 40 6.2 25.5 7 12.3 41.2 4 5.1 20.0 51 6.5 26.3
4. Dissatisfied 15 2.3 9.6 15 1.9 7.7
5. Very Dissatisfied 7 1.1 4.5 1 1.8 5.9 2 2.5 10.0 10 1.3 5.2

rMichigan NC. No Contact 343 52.6 26 49.1 42 53.2 4131 52.5
State Police 1.Very Satisfied 120 18.5 39.1 11 19.3 37.9 9 11.4 24.3 140 17.8 37.5
2. Satisfied 107 16.5 34.9 6 10.5 20.7 19 24.1 51.4 132 16.8 35.4
3. Undecided 40 6.2 13.0 5 8.8 17.2 4 5.1 10.8 491 6.2 13.1
4. Dissatisfied 19 2.9 6.2 6 10.5 20.7 1 1.3 2.7 26 3.3 7.0
5. Very Dissatisfied 21 3.2 6.8 1 1.8 3.4 4 5.1 10.8 26 3.3 7.0

Michigan NC. No Contact 370 57.1 331 57.9 38 48.1 441 56.3
Department of 1.Very Satisfied 25 3.9 9.0 1 1.8 4.2 2 2.5 4.9 28 3.6 8.2
Social 2. Satisfied 51 7.9 18.3 5 8.8 20.8 11 13.9 26.8 67 8.5 19.5
Services 3. Undecided 72 11.1 25.9 6 10.5 25.0 15 19.0 36.6 93 11.9 27.1
4. Dissatisfied 69 10.6 24.8 8 14.0 33.3 8 10.1 19.5 85 10.8 24.8
5. Very Dissatisfied 61 9.4 21.9 4| 7.0 16.7 5 6.3 12.2 70 8.9 20.4

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Note: 1 = very satisﬁed; 5 = very dissatisﬁed

104

 

Table 4-12 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

[Michigan N5. No Contact 495 77.0 42 75.0 59 74.7 596 76.6
Department of 1.Very Satisfied 31 4.8 20.9 3 5.4 21.4 6 7.6 30.0 40 5.1 22.0
Agriculture 2. Satisfied 46 7.2 31.1 4 7.1 28.6 3 3.8 15.0 53 6.8 29.1
3. Undecided 47 7.3 31.8 7 12.5 50.0 9 11.4 45.0 63 8.1 34.6
4. Dissatisfied 16 2.5 10.8 1 1.3 5.0 17 2.2 9.3
5. Very Dissatisfied 8 1.2 5.4 1 1.3 5.0 9 1.2 4.9
Michigan NC.No Contact 423 65.6 34 59.6 46 59.0 503 64.5
Department of 1.Very Satisfied 29 4.5 13.1 4 7.0 17.4 1 1.3 3.1 34 4.4 12.3
Commerce 2. Satisfied 91 14.1 41.0 9 15.8 39.1 11 14.1 34.4 111 14.2 40.1
3. Undecided 70 10.9 31.5 10 17.5 43.5 11 14.1 34.4 91 11.7 32.9
4. Dissatisfied 23 3.6 10.4 6 7.7 18.8 29 3.7 10.5
5. Very Dissatisfied 9 1.4 4.1 3 3.8 9.4 12 1.5 4.3
Michigan NC. No Contact 242 37.2 29 50.9 32 40.0 303 38.5
Department of 1.Very Satisfied 35 5.4 8.6 3 5.3 10.7 1 1.3 2.1 39 4.9 8.0
Treasury 2. Satisfied 135 20.7 33.0 6 10.5 21.4 15 18.8 31.3 156 19.8 32.2
3. Undecided 131 20.1 32.0 8 14.0 28.6 20 25.0 41.7 159 20.2 32.8
4. Dissatisfied 71 10.9 17.4 9 15.8 32.1 7 8.8 14.6 87 11.0 17.9
5. Very Dissatisfied 37 5.7 9.0 2 3.5 7.1 5 6.3 10.4 44 5.6 9.1
IMichigan NC. No Contact 448 69.7 34 61.8 46 58.2 528 68.0
Department of 1. Very Satisfied 27 4.2 13.8 1 1.3 3.0 28 3.6 11.2
Education 2. Satisfied 34 5.3 17.4 4 7.3 19.0 9 11.4 27.3 47 6.0 18.9
3. Undecided 57 8.9 29.2 6 10.9 28.6 11 13.9 33.3 74 9.5 29.7
4. Dissatisfied 37 5.8 19.0 5 9.1 23.8 7 8.9 21.2 49 6.3 19.7
5. Very Dissatisfied 40 6.2 20.5 6 10.9 28.6 5 6.3 15.2 51 6.6 20.5

 

 

Note: 1 = very satisﬁed; 5 = very dissatisﬁed

Percent 3': percent calculated within businesses that had contact with any of 12

agencies.

105

 

Table 4-13 Mean Satisfaction with State Agencies by Businesses Size Class

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Education

 

 

 

 

 

State Mean (Number)
Agencies Small Firms Medium Firms Large Firms Total
Michigan Jobs Commission 2.89 (179) 3.00 (24) 2.79 (43) 2.83 (246)
Michigan Department of 3.14 (277) 3.59 (37) 3.12 (42) 3.19 (356)
Natural Resources
Michigan Employment 2.96 (428) 3.31 (51) 3.23 (60) 3.02 (539)
Security Commission
Michigan Department of 2.94 (210) 2.83 (35) 3.06 (31) 2.94 (276)
Transportation
Michigan Occupational Safety 3.05 (244) 3.27 (37) 3.00 (56) 3.06 (337)
and Health Agefncy
Michigan Travel Bureau 2.34 (157) 2.35 (17) 2.45 (20) 2.35 (194)
Michiggn State Police 2.07 (307) 2.31 (29) 2.24 (37) 2.10 (373)
Michigan Department of 3.32 (278) 3.38 (24) 3.07 (41) 3.30 (343)
Social Services
Michigan Department of 2.49 (148) 2.29 (14) 2.40 (20) 2.46 (182)
rAgriculture
Michigan Department of 2.51 (222) 2.26 (23) 2.97 (32) 2.55 (277)
Commerce
Michigan Department of 2.85 (409) 3.04 (28) 3.00 (48) 2.88 (485)
Treasury
Michigan Department of 3.15 (195) 3.62 (21) 3.18 (33) 3.19 (249)

 

Note: 1 = very satisﬁed; 5 = very dissatisﬁed

Regardless of industry sectors, most businesses revealed a neutral attitude toward

various state agencies (Table 4-14). The hospitality/tourism industry is, however, not

satisﬁed with the Michigan Department of Natural Resources (3.20) nor the Michigan

Department of Education (3.17). On the other hand, this industry has high levels of

satisfaction with the Michigan Travel Bureau (2.09), the Michigan State Police (2.04), the

Michigan Department of Transportation (2.60), and the Michigan Department of

Agriculture (2.38).

106

 

Table 4-14 Mean Satisfaction with State Agencies by Type of Business

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Mean (Number)
State Primary Second. Wholes. General MgriaIJ Hospitality Total
Agencies Industry Industry / Retail Services Personal / Tourism
Services Industry

Michigan 2.43 2.56 2.98 2.66 3.06 2.71 2.78
Jobs (7) (90) (54) (35) (62) (41) (289)
Commission
Michigan 4.00 3.07 3.29 2.97 3.05 3.20 3.14
Department (10) (113) (94) (68) (83) (46) (414)
of Natu ral
Resources
Michigan 3.00 2.94 3.06 2.99 3.08 3.15 3.04
Employment (14) (151) (136) (77) (147) (74) (599)
Security
Commission
Michigan 2.89 2.82 3.03 3.02 2.97 2.60 2.90
Department (9) (82) (79) (46) (59) (40) (315)
of Transport.
Michigan 3.70 3.05 2.90 2.95 3.17 2.77 3.02
Occupational (10) (126) (72) (39) (93) (48) (388)
Safety and
Health
ﬂenw
Michigan 2.00 2.43 2.31 2.85 2.19 2.09 2.36
Travel (4) (47) (52) (39) (36) (45) (223)
Bureau
Michigan 1.56 2.10 2.14 2.36 2.02 2.04 2.12
State Police (9) (91) (108) (75) (86) (56) (425
Michigan 3.00 3.14 3.15 3.23 3.28 3.53 3.24
Dep. Of (9) (77) (85) (56) (108) (49) (384)
Social
Services
Michigan 2.15 2.44 2.47 2.48 2.74 2.38 2.48
Department (13) (50) (75) (23) (34) (26) (221)
of Agriculture
Michigan 2.57 2.36 2.54 2.59 2.53 2.59 2.51
Department (7) (74) (63) (66) (59) (39) (308)
of Commerce
Michigan 2.40 2.98 2.76 2.81 2.95 2.84 2.87
Department (1 O) (1 22) (1 31 ) (84) (1 29) (69) (545)
of Treasury
Michigan 2.57 3.21 3.09 3.05 3.16 3.17 3.13
Department (7) (77) (53) (40) (73) (42) (292)
of Education

 

Note: 1 = very satisﬁed; 5 = very dissatisﬁed

107

 

Business perceptions of the quality of state-govemment services and of the
expertise of their personnel are presented in Table 4-15. The original ﬁve-point scale (1
= strongly disagree; 5 = strongly agree) was re-coded to a three-point scale (1 = disagree;
2 = neutral; 3 = agree). For instance, respondents that indicated either “strongly disagree”
or “disagree” with any of the three statements were re-coded as “disagreeing.”

The respondents, for the most part, have negative perceptions regarding the
quality of govemment-provided business services. The Michigan business community, in
general, has a negative perception of the quality of state—govemment services and of the
expertise of their personnel. Only a quarter (25.8 percent) of the respondents agree with
the statement that “the quality of services offered by state government meets the needs of
the business.” More than one-third (36.1 percent) do not believe that government service
quality is adequate. More than half of the respondents (55.5 percent) perceive that state—
govemment employees do not know enough about their type of business to be of any
help. About 70 percent of businesses indicate that state government needs to market
itself better so that businesses will know more about the products and services that state

has to offer.

Table 4-15 Business Perceptiom of the Quality of State Services, Needs for
Marketing of State Services, and Expertise of Agency Employees

 

 

 

Perceptions toward All Firms
State Services N Disagree (°/o) Neutral C/o) Agree ("/62 1
The quality of services by 932 36.1 38.2 25.8

state government meets
the needs of the business.

 

State government needs to 932 1 1.5 18.3 70.2
market itself about the
services it has to offer.
State government 928 12.5 32.0 55.5
employees lack the
knowledge to be helpful.

 

 

 

 

 

 

 

 

108

Table 4-16 shows a comparison of how different sized businesses evaluate the

quality of state-govemment-provided services and the expertise of agency personnel.

Table 4—17 presents a similar comparison for businesses in different industry sectors. The

tables reveal that there is little difference in evaluations across different sized businesses.

Table 4-16 Perceptions of the Quality of State Services, Needs for Marketing of State
Services, and Expertise of Agency Staff by Size Class

 

 

 

 

 

 

N (Percent)
Perceptions Satisfaction Small Firms Medium Firms Large Firms Total
Level

Quality of 1. Disagree 231 (35.2) 24 (40.7) 31 (38.8) 286 (36.0)
Services 2. Neutral 247 (37.7) 22 (37.3) 29 (36.3) 298 (37.5)

3. Agee 178 (27.1) 13 (22.0) 20 (25.0) 21 1 (26.5)
Needs for 1. Disagree 72 (1 1.0) 5 (8.5) 14 (17.5) 91 (1 1.4)
Marketing of 2. Neutral 1 18 (18.0) 15 (25.4) 1 1 (13.8) 144 (18.1)
State 3. Agree 466 (71.0) 39 (66.1) 55 (68.8) 560 (70.4)
Business
Services
Lack of 1. Disagree 80 (12.3) 4 (6.8) 12 (15.0) 96 (12.2)
Expertise of 2. Neutral 215 (33.1) 20 (33.9) 20 (25.0) 255 (32.3)
State Agency 3. Agree 355 (54.6) 35 (59.3) 48 (60.0) 438 (55.5)
Staff

 

 

 

 

 

 

 

However, there are some interesting differences across industrial sectors (Table 4-
17). The majority of the primary industry businesses (66.7 percent) do not feel that state
agency personnel have the necessary expertise to provide them with adequate service. A
relatively high percentage (44.3) of the hospitality/tourism businesses did not feel that the
quality of services offered by state government meets the needs of the tourism business.

In general, all types of industries have a negative attitude toward the quality of
services and the expertise provided by state government personnel. Also, most
businesses agree that state government needs to market itself better to the business

community (Table 4-18).

109

Table 4-17 Perceptions of Businesses in Diﬂ'erent Industries have of the Quality of State
Services, Needs for Marketing of State Services, and Expertise of Agency Staff

 

 

 

 

 

 

 

 

 

 

 

 

 

N (341
Perceptions The The Wholsl. Gen. Mag./ Hosp./ Total
Prim. Sec. /Retail. Serv. Persl Tourism
Ind. Ind. Serv. Serv Ind.
Quality of 1.Disagree 7 76 81 39 75 47 325
Services (38.9) (36.4) (36.2) (29.5) (33.6) (44.3) (35.6)
2. Neutral 6 76 98 44 89 36 349
(33.3) (36.4) (43.8) (33.3) (39.9) (34.0) (38.3)
3. Agree 5 57 45 49 59 23 238
(27.8) (27.3) (20.1) (37.1) (26.5) (21.7) (26.1
Needs for 1.Disagree 5 22 24 19 25 10 105
Marketing (27.8) (10.5) (10.7) (14.5) (11.1) (9.5) (11.5)
of State 2. Neutral 4 35 34 24 45 23 165
Business (22.2) (16.7) (15.2) (18.3) (20.0) (21.9) (18.1)
Services 3. Agree 9 152 166 88 155 72 642
(50.0) (72.7) (74.1) (67.2) (68.9) (68.6) (70.4)
Lack of 1.Disagree 1 24 28 25 30 8 1 16
Expertise of (5.6) (11.7) (12.6) (19.1) (13.3) (7.7) (12.8)
State 2. Neutral 5 64 71 39 78 36 293
Agency (27.8) (31 .1 ) (31 .8) (29.8) (34.7) (34.6) (32.3)
Staff 3. Agree 12 118 124 67 117 60 498
(66.7) (573) (55.6) (51.1) (52.0) (57.7) (54.9)

 

 

 

Table 4-18 Mean Perceptions of the Quality of State Services, Needs for Marketing of State
Services, and Expertise of Agency Staff by Type of Business

 

 

 

 

 

 

 

 

Quality of Marketing Lack of

TIE of Business Services Gov't Expertise
The Primary Mean 1.89 2.22 2.61
Industry N 16 16 16
The Secondary Mean 1.91 2.62 2.46
Industry N 209 209 206
Wholesale/Retail Mean 1 .84 2.63 2.43
Services N 224 224 223
General Services Mean 2.08 2.53 2.32

N 132 131 131
Managerial & Mean 1.93 2.58 2.39
Personal Services N 223 225 225
Hospitality/Tourism Mean 1.77 2.59 2.50
Industry N 106 105 104
Total Mean 1 .90 2.59 2.42

N 912 912 907

 

 

 

 

 

 

Note: 1 = disagree; 2 = neutral; 3 = agree

110

4.2 Factor Analysis of External Environment Variables

As previously mentioned, the external environment variables for this study were
identiﬁed during the focus group sessions with 21 businesses. These external
environment variables were conceptually classiﬁed (combined) into two groupings based
on a review of literature. The “state-govemment-imposed cost of doing business”
grouping incorporated seven variables: (1) state labor laws and regulations; (2) state
workplace safety regulations; (3) state taxes; (4) workers’ compensation; (5) the
paperwork required by state government; (6) unemployment insurance; and (7) the cost of
beneﬁts (6. g. healthcare). A second grouping, “market environment,” incorporated: (1)
access to qualiﬁed labor and (2) consumer demand for the products and services offered
by the business. Correlation tests among the 12 variables and reliability tests on the two
groupings (factors) indicate that these are reliable.

Validity of the two conceptual factors was further examined through a comparison
with the factors produced by a factor analysis. Factor analysis is a method commonly
employed to identify underlying factors with shared common variance that are mutually
independent without redundancy. In order to determine the underlying structure of data,
factor analysis uses the common variance and weighs the variables according to their
inter-relationships with the others. Since factor analysis reduces the number of variables
by identifying groups of inter-correlated variables, the analysis provides useful insights

for the construction of variables being studied (Johnston, 1991).

111

4.2.1 Appropriateness of Data for Factor Analysis

Prior to conducting a factor analysis, appropriateness of the data for factor
analysis was ﬁrst examined on three criteria recommended by Stewart (1981): (l) the
sample size; (2) Bartlett’s test of sphericity; and (3) the Kaiser-Meyer-Olkin (KMO)
measure of sampling adequacy. According to Comrey (1973), a sample size from 500 to
1,000 is very appropriate for factor analysis. The sample of 953 businesses is more than
appropriate based on this criterion.

Bartlett’s test of sphericity, using a chi-square test, is used to test the hypothesis
that the correlation matrix of 12 external environment variables is an identity matrix, that
is, the variables correlate perfectly with themselves but are not correlated with other
variables; all diagonal terms are 1 and all off-diagonal terms are 0. For data to be
appropriate for factor analysis, a KMO value should be greater than 0.50 and the result of
Bartlett’s test should be signiﬁcant. The chi-square value (4989.459) of 12 variables was
signiﬁcant at 0.000 (Table 4-19). The result indicates that the hypothesis is rejected,

_ indicating that the data are not an identity matrix and are appropriate for factor analysis
(Jung and Choi, 1997).

The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy provides a
measure of the extent to which the variables belong together (Jung and Choi, pp. 169-
170). A KMO value smaller than 0.50 indicates that data may not be appropriate for
factor analysis, because correlation between pairs of variables can not be explained by the
other variables (Norusis, 1988). The KMO statistic is 0.921(Table 4-19), indicating that

the data are appropriate for factor analysis. The combination of the three criteria

112

indicates that the data are appropriate for factor analysis, and there is an underlying

structure to this data.

Table 4-19 Results of the KMO (Kaiser-Meyer-Olkin) and Bartlett’s Test of
Appropriateness of the Data for Factor Analysis

 

 

 

 

Kaiser-Meyer—Cikin Measure of Sampling Adequacy.
.921
Bartlett’s Test of Sphericity Approx. Chi-Square 4989.459
(11 66
Sig .000

 

4.2.2 Factor Extraction

A principal component analysis (PCA) was used to extract an initial set of factors.
In order to identify and extract a group of inter-related variables (a factor), a PCA method
was utilized. Since the components model investigates all of the variances in the original
variables, this method produces a set of components whose number equals the number of
variables that are uncorrelated to each of the other 12 independent components in this
study (Johnston, 1980; Aczel, 1993). Thus, this method minimizes the loss of
information in the original data set (Chea, Kim, and Lee, 1992).

A principal components analysis method extracts the factors from the correlation
matrix in serial order of eigenvalue size. Table 4-20 shows the eigenvalues, percentages
of variance explained, and the cumulative percentage of variance explained for different

factor solutions. The eigenvalue is the sum of squared component (factor) loadings. The

113

eigenvalues and percentage of total variance explained are different for each of the 12
solutions.

The results from the different principal component solutions were evaluated
against the four criteria described in Chapter 3: (l) eigenvalue greater than 1; (2) variance
explained to account for as much of the variance as possible; (3) scree test that plots the
eigenvalues against the number of components (factors); and (4) interpretability of
extracted factors (Aczel, 1993). Two of the potential solutions have eigenvalues greater
than 1 (Table 4-20). The two factors have eigenvalues 5.557 and 1.188, and the total
variance explained is 56.210 percent. Extracting an additional (third) component results
in an eigenvalue less than 1 and only contributes an additional 7.731 percent of variance
explained. The scree plot (Figure 4-3) also identiﬁes the two-component (factor)

solution.

114

Table 4-20 The Principal Components Analysis: Eigenvalues

and Percent of Variance Explained

 

 

 

 

 

 

 

 

 

 

 

 

Eigenvalue and % of Variance for 12

1 External Environmental Variables

Cumulative

Percent of Percent of

Variance Variance

Component Eyenvalue Explained Explained

1 5.557 46.312 46.312

2 1.188 9.898 56.210

3 .928 7.731 63.941

4 .804 6.698 70.639

5 .734 6.113 76.752

6 .658 5.484 82.235

7 .574 4.783 87.019

8 .439 3.661 90.679

9 .332 2.769 93.448

10 .310 2.579 96.028

11 .266 2.218 98.246

12 .210 1.754 100.000
8
51
44
31
21
:1.

1 2 3 4 5 6 7 8 9 10 11 12

Component (Factor) Number

Figure 4-3 Scree Plot for Selecting Factor Solutions

115

 

4.2.3 The Rotation of Factors

One of the primary purposes of factor analysis is to identify groups of variables
with shared common variance. Given that this method only extracts principal
components, it does not achieve this purpose. The ﬁrst factor is placed in the average
position closest to all of the variables which may not identify (or select) groups of
variables. Rotating the principal components that are extracted better identiﬁes groups of
inter-related variables. Rotated factors provide for better group identiﬁcation and more
clearly separates the factors (Johnston, 1991). Rotation also facilitates discovery of
variables as approximations to simple structure when there are groups of variables with a
signiﬁcant amount of shared common variance (Johnston, p. 163).

There are many different potential rotation methods each with its own beneﬁts
and limitations (Nie er al., 1975; Johnston, 1991; Aczel, 1993). Kaiser’s varimax
orthogonal rotation was employed, because it maximizes variance and produces some
high loadings and some near-zero loadings on each factor by simplifying the columns of a
factor matrix (Nie et al., 1975). The ﬁnal rotated solution is easier to interpret and
understand, because there are factors with loadings that are high on some variables and
low on others (Aczel, 1993).

Rotated and unrotated factor loadings for the two-factor solution are presented in
Table 4-21. While three variables, including access to credit (0.579), labor unions
(0.526), and the start of the school year (0.329) have fairly high loadings in the unrotated
solution, they are not loaded highly on any of the rotated factors. Variables related to

state programs and regulations that increase the cost of doing business, including

116

workers’ compensation (0.844), unemployment insurance (0.820), paperwork (0.820),
state taxes (0.817), laws and regulations (0.824), safety regulations (0.754), and the cost
of beneﬁts (0.646) are highly loaded on one of the factors. Consumer demand (0.802)
and access to qualiﬁed labor (0.737) are loaded on the other factor. Variables, such as
access to credit (0.470), labor unions (0.446), and the start of the school year (0.178) are

not related (loaded) on either factor.

Table 4-21 The Rotated and Unrotated Factor Loadings for Two Factor Solution

 

 

 

 

 

 

 

External Environmental UnroatatedﬁFactor Loadings [ Roatated Factor Loadingg_

I Variables 1 [ 2 f 1 i 2 .4
Workers' Compensation 0.853 0149' 0.844 0.195
Unemployment Insurance 0.832 -0.138 0.820 0.198
Paperwork 0.823 -0.159 0.820 0.174
State Taxes 0.812 -0.178 0.817 0.153
Laws & Regulations 0.803 -0.217 0.824 0.1 13
Safety Regulations 0.763 -0.1 33 0.754 0.175
Cost of Benefits 0.709 0.017 0.646 0.292
Access to Credit 0.579 0.161 0.470 0.373
Labor Unions 0.526 0.097 0.446 0.294
Start of School Year 0.329 0.321 0.178 0.424
Consumer Demand 0.326 0.733 0.014 0.802
Access to Qualified Labor 0.496 0.590 0.226 0.737

 

 

 

Figure 4-4 shows clearly that state programs and regulations that are generally
perceived as increasing the cost of doing business are clustered as Factor 1. Consumer
demand and access to qualiﬁed labor are grouped as Factor 2. This is consistent with the
hypothesized conceptual groupings described in Chapter 3.

Loadings, “the proportion of the variance in the variable associated with the

variance in the factor,” are frequently used to identify and label factors (Johnston, p. 168).

117

Because the variables with the highest loading on Factor 1 are related to state-govemment
regulations and programs, this factor is labeled as the state-imposed cost of doing
business factor. The second factor is named the market environment factor, because the

variables with the highest loadings are consumer demand and access to qualiﬁed labor.

 

 

 

 

 

 

Factor 2 1-0
$2
.5 i
0 3-1 0 3-2
0 3-3
X 1
0.0
-.5 d
1.0
-1.0 -.5 0.0 .5 1.0
Factor 1

Note: 1 = Factor 1, state-imposed cost of doing business (Variables: state laws and
regulations, state safety regulations, state taxes, workers’ compensation,
paperwork, unemployment insurance, and the cost of beneﬁts)

2 = Factor 2, market environment (Variables: consumer demand and access to

qualiﬁed labor)
3 = Unrelated Variables (3-1, the start of the school year; 3-2, access to credit; 3-3,
labor unions)

Figure 44 Component Plot in Rotated Space

The communality is “the proportion of the variance that each variable accounted

for by all of the factors” (Johnston, p.142). In other words, the communality is the part of

118

“the total variance in the data that is composed of the common-factor component” (Aczel,
p.807). The communality values, therefore, show the proportion of the variance which
each variable has in common. The larger the communality, the more a factor is drawn
towards a variable (Johnston, 1980). Although most of the state-regulations—related
variables have about 70 percent of communality values, safety regulations (59.9 percent)
and the cost of beneﬁts (50.2 percent) have values of less than 70 percent. The variables
included in the market environment factor, such as consumer demand (64.4 percent) and
access to qualiﬁed labor (59.4 percent) have almost the same communality values. Table
4-22 provides a summary description for the factor analyses conducted on the external

environment variables.

Table 4-22 Summary of the Two-Factor Solution: Variable Loadings on the
Factors and Communality

 

 

 

 

 

 

 

 

 

 

 

 

 

 

External Environment Factor
Variables State-Imposed Cost of Market Communality
DomBusiness (F1) Environment (F2)
Workers’ Compensation 0.844 0.195 0.750
Laws & Regulations 0.824 0.113 0.692
Unemployment Insurance 0.820 0.198 0.712
Paper work 0.820 0.174 0.703
State Taxes 0.817 0.153 0.691
Safety Regulations 0.754 0.175 0.599
Cost of Benefits 0.646 0.292 0.502
Consumer Demand 0.226 0.802 0.644
Access to Qualified Labor 0.178 0.737 0.594
ﬂenvalue 5.557 1 .188

 

 

 

 

4.3 Hypothesis Test Results

This section reports the results of the tests of hypotheses. The state-imposed cost

of doing business and market environment factors, rather than the original 12 variables,

119

are used to test hypotheses relating to the impact of environment factors. Factor scores
were computed for each factor by multiplying the original raw data measurements by the
corresponding factor-score (regression) coefﬁcients.

Hypothesis One: The market environment factor is more important than the state-
govemment-imposed cost of doing business factor in ﬁrms’ hiring decisions.

To test this hypothesis, the mean importance of variables comprising (loaded on)
the two factors were compared with one another. As described earlier, the businesses that
completed a questionnaire ranked the importance of the 12 environment factors in their
hiring decisions on a ﬁve-point scale (1 = very little importance; 5 = very much
importance). The mean importance of the market-environment-related variables is 3.4,
compared to 2.8 for the state-imposed cost of doing business variables (Table 4-23). All
businesses are more inﬂuenced by the market environment factor (mean 3.4: “much”
inﬂuenced by the factor) than by the state-imposed cost of doing businesses factor (mean

2.8: “little” inﬂuenced by the factor).

Table 4-23 Mean Influence of the State-Imposed Cost of Doing Business
and Market Environment Factors

 

 

Std.
Environment Factor Mean N Deviation
State-Imposed Cost of
Doing Business Factor 2'80” 936 13475
Market Environment
Factor 3.4172 936 , 1.3999

 

 

 

 

 

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

120

The results of a paired T-test (Table 4-24) indicate that there is a statistically
signiﬁcant difference between the mean importance businesses assign to the market
environment and the state-imposed cost of doing business factors in their hiring decisions.
On average, businesses assign greater importance to consumer demand and availability of
labor when making hiring decisions than they do to state programs and regulations that

increase the cost of doing business. The F -value of 12.13 is signiﬁcant at the 0.05 or level

(p-value = 0.000) and the null hypothesis is rejected. Businesses are signiﬁcantly

inﬂuenced by the market environment factor in their hiring decision making.

Table 4-24 Results of T-tests for Importance Businesses Assign to the State-Imposed Cost of
Doing Business and Market Environment Factors in their Hiring Decisions

 

Paired Differences

 

Std. Std. Error Sig.
Mean Deviation Mean t df (2-tailed)
State
Imposed
Cost of
Doing
Business .6158 1.5538 .0508 12.125 935 .000'
Factor -
Market
Environment
Factor

 

 

 

 

 

 

 

 

 

 

Hypothesis Two: There is a signiﬁcant difference between small, medium, and
large businesses (determined by total number of employees) in terms of the relative
importance of various environment factors on their hiring decisions.

Mean importance assigned to variables comprising each of the two factors is

presented in Table 4-25. There does not appear to be any major differences in the degree

121

of importance placed on the state-imposed cost of doing business factor by different-sized
businesses. Conversely, there are noticeable differences in the mean importance of the
market environment factor. On average , small businesses assign this factor a 3.47,

compared to 3.80 for large businesses and 3.84 for medium-sized businesses.

Table 4-25 Mean Importance Assigned to the State-Imposed Cost of Doing Business and
Market Environment Factors by Different Size of Business

 

 

 

 

 

1=sma|| State
business, Imposed
2=medium Cost of
sizes Doing Market
business, Business Environment
3=Iarge Factor Factor
small Mean 2.8143 3.4689
businesses N 559 559
medium size Mean 2.9617 3.8390
businesses N 59 59
large Mean 2.7518 3.8000
businesses N 30 30
Total Mean 2.8189 3.5294
N ' 798 798

 

 

 

 

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

One-way AN OVA (Analysis of Variance) was used to determine whether or not
there was a statistically signiﬁcant difference in the importance different-sized businesses
assign to variables comprising the two factors. A requirement for the use of AN OVA is
that the variances for three sizes of businesses (three groups) are equal. The results from
the Levene test of homogeneity of variances (Table 4—26) indicate that the variances are
not statistically different. The Levene statistic for the state-imposed cost of doing

business factor is 1.232 (p-value = 0.292, > 0.05 Ct). The Levene statistic for the market

122

environment factor is 3.077 (p-value = 0.67, > 0.05 Ct). Based on these results, ANOVA

can be used to test for difference across the three sizes of businesses.

Table 4-26 Test for Homogeneity of Variances for Different Size of Business

 

Levene
Statistic df1 df2 Sig.

 

"FIRTH

factor
score 1
for
analysis
1

REGR
factor
score 2
for
analysis
1

1 .232 2 757 .292

3.077 2 757 .067

 

 

 

 

 

 

 

The ANOVA indicates no statistically signiﬁcant difference in the mean
importance placed on the two factors by different size of business. The F -value (Table 4-
27) for the state-imposed cost of doing business factor is 0.477 with a signiﬁcance of

0.621 and the null hypothesis is accepted at the 0.05 signiﬁcance level (or). The F -value
for the market environment factor is 4.088 with a signiﬁcance of 0.017 (< 0.05 or). The

null hypothesis is rejected. Based on the statistical analyses, there is a difference across
different sizes of businesses in the importance assigned to the market environment factor
in their hiring decisions. There is no size-related difference when it comes to the

importance of the state-imposed cost of business factor.

123

Table 4-27 Results of ANOVA Tests Comparing the Mean Importance Assigned
to the Two Environment Factors by Different Size of Business

 

 

 

 

 

Environmental Sum of Mean
Factors by Business T pe Squares df Square F Sig.
Erato Imposed ost etween 1.577 2 .766 .477 .621
of Doing Business Whithin Groups 1315.291 795 1.654
Fad“ 1316.868 797
Market Environment Between 13.925 2 6.963 4.088 .017‘
Factor Whithin Groups 1354.133 795 1.703
1368.058 797

 

 

 

 

 

 

 

Hypothesis Three: Small businesses are less inﬂuenced by the market
environment, consumer demand and access to qualiﬁed labor, in their decision making
than are medium- or large-sized businesses.

Responses to the mail questionnaire appear to conﬁrm the literature that indicates
that small businesses are more sensitive to ﬁnancial factors and the cost of doing business
than are larger businesses (Atkinson and Storey, 1994; Judd, Greenwood, and Becker,
1988).

Again, a Levene test was conducted to determine whether or not population
variances are equal. The results shown in Table 4-28 indicate that the hypothesis of equal
variance should be rejected. Equal variance can, therefore, not be assumed when the T-
test was used to test for differences between small— and medium-sized businesses and

between small- and large-sized businesses.

124

Table 4-28 Results of T-tests Comparing the Importance that Small, Medium, and Large
Businesses Assign to the Market Environment when Making Hiring Decisions

 

 

 

 

 

 

 

 

 

 

 

 

 

Levene's Test for
Equality of Variances t-test for Equalityof Means
Sig. Mean Std. Error
L F Sig. t df (2-tailed) Difference Difference
Market Equal
Environment variances 6.474 .011 -2.063 716 .04 -.3701 .1794
Factor assumed
(Small and Equal
Medium) variances
not 2349 72.95 .021' -.3701 .1576
assumed
Market Equal
Environment variances 5.176 .023 2.123 737 .034 -.3311 .1559
Factor assumed
(Small and Equal
Large) variances
not -2.374 106.3 .019* -.3311 .1394
assumed
Market Equal
Environment variances .211 .646 .197 137 .844 .0389 .1975
Factor assumed
(Medium and Equal
Large) variances
not .198 126 .844 .0389 .1971
assumed

 

The results from the different T-tests are also reported in Table 4-29. The results

(p-value of one tailed T-test = 0.011 < 0.05 or) indicate a statistically signiﬁcant

difference in the importance that small and medium businesses assign to the market

environment when making their hiring decisions. Small businesses place signiﬁcantly

less importance on consumer demand and availability of qualiﬁed labor when deciding

whether or not to hire more employees (see Table 4-25 for mean importance). There is

also a statistically signiﬁcant difference between small and large businesses in terms of

the importance assigned to market environment in hiring decisions. As hypothesized,

large- and medium-sized businesses place greater emphasis on the market environment

125

 

than do small businesses. The T-test does not ﬁnd a statistically signiﬁcant difference
between large- and medium-sized businesses on the importance of market environment in
hiring decisions. Hiring decisions by medium- and large-sized businesses are more

sensitive to the market environment.

Table 4-29 Summary of T-tests Comparing the Importance that Small, Medium, and Large
Businesses Assign to the Market Environment when Making Hiring Decisions

 

 

 

 

Sizes of Medium Large
Business Businesses Businesses

T p T 9
Small -2.349 0.011" -2.374 0.009*
Businesses
Medium 0.197 0.422
Business

 

 

 

 

 

 

 

Hypothesis Four: There is a signiﬁcant difference between businesses in
different industry sectors in terms of the relative inﬂuence of various environment factors
on their hiring decisions.

AN OVA was used to determine if there is a signiﬁcant difference in the
importance businesses in six industries place on the state-imposed cost of doing business
and the market environment factors in decisions as to the number of employees to hire or
retain. The industries include: (1) primary industry; (2) secondary industry; (3) wholesale
and retail services; (4) general services; (5) managerial and personal services; and (6)
hospitality/tourism. The hypothesis was tested by utilizing (1) ANOVA tests for
differences in mean importance assigned to the two factors across the six industries and
(2) T-tests to examine mean differences in importance assigned to the factors between

each pair of groups of different types of businesses. The industry types are the

126

independent variable (groups), and the mean importance (inﬂuence) of the two external
environment factors are the dependent variables in both the ANOVA and T-test.

Table 4-30 reports the sensitivity to the two factors by businesses in different
industries. Hiring decisions by both primary and secondary industries are more
inﬂuenced by the state-imposed cost of doing business factor than are other industry
sectors. Hiring decisions in most industry sectors are highly sensitive to the market

environment factor.

Table 4-30 Mean Importance] Influence of the State-Imposed Cost of Doing Business and
Market Environment Factors on Hiring Decisions by Different Type of Business

 

 

 

 

 

 

 

 

 

 

 

State
Imposed
Cost of
Doing Market
Business Environment
lype of Business Factor Factor

Primary Mean 3.2556 3.3947
Industry N 1 g 1 9
Secondary Mean 3.1 132 3.6690
Industry N 210 210
Wholesale/Retail Mean 2.7556 3.3480
Services N 227 227
General Services Mean 2.5993 3.4961
N 129 129

Managerial! Mean 2.5737 3.2174
Personal Services N 230 230
Hospitality/Tourism Mean 2.8680 3.4208
Industry N 101 101
Total Mean 2.7927 3.4187
N 916 916

 

 

Note: 1 = very little inﬂuence; 5 = very much inﬂuence

The results of the AN VOA indicate a signiﬁcant difference (F = 4.767, p-value =

0.000 < 0.05 or) in the importance different industries assign to the state-imposed cost of

127

doing business factor in their hiring decisions (Table 4-31). There is also a signiﬁcant
difference (F = 2.520, p-value = 0.026 < 0.05 or) in the importance of the market

environment factor in hiring decisions across the six industries. The results of the
ANOVA imply that at least one industry differed signiﬁcantly from at least one other
industry in terms of the inﬂuence (importance) of a factor. To determine the type(s) and

magnitude(s) of the differences, additional statistical tests are required.

Table 4-31 ANOVA Tests of Type of Business Differences on the Importance of
State-Imposed Cost of Doing Business and Market Environment Factors

 

 

 

Environmental Sum of Mean
Ectors by Business Type Squares df Square F Sig;-
State Imposed Cost Between 42.384 5 8.477 4.767 .000*

otDoins Business Whithin Groups 1618.173 910 1.776

 

Fad" 1660.557 915
Market Environment Between 24.401 5 4.880 2.520 .028"
Factor Whithin Groups 1762.290 910 1.967

1786.691 915

 

 

 

 

 

 

 

 

Table 4-32 and Table 4-33 present the results (T-statistics and p-value, level of
signiﬁcance) from the independent T—tests of the six industries. The tables also provide
the results (F -value and p-value) from the Levene test for homogeneity of variances. The
T-tests reveal some interesting differences and similarities with regard to their sensitivity
to the two factors in hiring decisions by businesses comprising different industries.

There is no statistically signiﬁcant difference between primary and secondary
industries or between the primary and the wholesale/retail industries in terms of the
inﬂuence that the two factors have on their hiring decisions. The primary industry does

differ signiﬁcantly from both the general services sector and the managerial/personal-

128

service sector when it comes to the inﬂuence of the state-imposed cost of doing business
factor in their hiring decisions. Primary-industry businesses are more sensitive to the
inﬂuence of this factor when making hiring decisions. There is no statistically signiﬁcant
difference between the primary industry and either the general services or the
managerial/personal service sectors when it comes to the inﬂuence of the market
environment factor in the making of their hiring decisions.

Secondary-indusz businesses are more highly inﬂuenced by the state-
government—imposed cost of doing business factor than are the general-services, the
wholesale/retail-service, or the managerial/personal-service industries. While there is no
statistically signiﬁcant difference between the relative inﬂuence of the market
environment factor in the hiring decisions of the secondary industry, the general services
industry, or the managerial/personal service industry, this factor does have greater
inﬂuence (importance) on the hiring decisions of the secondary industry than on the
wholesale/retail-service industry.

Interestingly, there is no signiﬁcant difference between the hospitality industry
and the primary, secondary, general-services, wholesale/retail, or the
managerial/personal- service industries in terms of the relative inﬂuence of either the
state-government-imposed cost of doing business factor or the market environment factor

in the making of hiring decisions.

129

Table 4-32 Results of T-tests Comparing the Influence of State-Imposed Cost of Doing
Business Factor for Different Type of Business

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

State Imposed Levene’s Test
Cost of Doing Business for Equality
Factor of Variances t-test for Equalityof Means
Sig. Mean Std. Error
F Sig. t df (2-tailed) Difference Difference
Pﬁrimary Equal
Industry8 variances .485 .487 .473 227 .637 .1425 .3013
Secondary assumed
Industry Equal
Comparison variances .419 20.519 .679 .1425 .3397
not assumed
Primary Eual
Industry8 variances .074 .785 1.495 244 .136 .5000 .3345
Wholesale assumed
lRetaiI Equal
Services variances 1.464 20.971 .158 .5000 .3416
rgomparison got assumed
Primary Equal
Industry& variances .310 .579 2.073 146 .040' .6563 .3166
General assumed
Services Equal
Comparison variances 1.891 22.340 .072 .6563 .3472
not assumed
Primary Equal
Industry8 variances .002 .962 2.063 247 .040* .6820 .3306
Managerial assumed
[Personal Equal
Services variances 1.999 20.860 .059 .6820 .3411
Comparison r_10t assumed
Primary Equal
Industryat variances .034 .853 1.156 118 .250 .3877 .3353
Hospitality assumed
[Tourism Equal
Industry variances 1.095 24.130 .285 .3877 .3542
Comparison £01 assumed
Secondary Equal
Industryat variances 5.902 .016 2.819 435 .005 .3576 .1269
Wholesale assumed
[Retail Equal
Services variances 2.832 434.286 .005' .3576 .1263
Comparison not assumed

 

130

Table 4-32 (cont’d)

 

 

 

 

 

 

 

 

ry Equal
Industry& variances .056 .813 3.627 337 .000’ .5139 .1400
assumed
Equal
Comparison variances 3.654 266.717 .000 .5139 .1406
not assumed
Secondary ﬁal
Industry& variances 3.299 .070 4.294 438 .000’ .5395 .1256
Managenal assumed
ersonal Equal
' variances 4.315 437.894 .000 .5395 .1250
Comparison not assumed
Secondary thual
lndustry& variances .957 .324 1.596 309 .111 .2452 .1536
Hospitality assumed
fi'ourism Equal
Industry variances 1.561 186.525 .120 .2452 .1571
Comparison not assumed
Wholesale Eual
/RetaiI& variances 3.418 .065 1.049 354 .295 .1563 .1491
General assumed
Services Equal
Comparison variances 1.077 288.258 .282 .1563 .1451
not assumed
IWholesale Equal
lRetaiI& variances .318 .573 1.399 455 .162 .1819 .1300
Managerial assumed
[Personal Equal
Services variances 1.399 454.715 .162 .1819 .1300
Comparison not assumed
I'IIEV—holesale EWaI
/Retail& variances .895 .345 -.683 326 .495 -.1124 .1645
Hospitality assumed
[Tourism Equal
Industry variances -.698 201.864 .486 —.1124 .1611
Comparison not assumed
General ELquaI
Services & variances 1.746 .187 .174 357 .862 .0256 .1475
Managerial assumed
lPersonaI Equal
Services variances .178 284.839 .859 .0256 .1440

Comparison not assumed

 

 

 

 

 

 

 

 

 

 

131

 

Table 4-32 (cont’d)

 

Eeneral Equal

 

Comparison not assumed

 

 

 

 

 

 

 

 

Services& variances .476 .491 -1.565 228 .119 -.2687 .1717
Hospitality assumed

/Tourism Equal

Industry variances -1.557 210.337 .121 -.2687 .1726
Comparison not assumed

Managerial Equal

lPersonaI variances .229 .632 -1.807 329 .072 -.2943 .1628
Services & assumed

Hospitality Equal

IT ourism variances -1.838 198.666 .068 -.2943 .1601

 

132

 

Table 4-33 Results of T-tests Comparing the Influence of the Market Environment Factor

 

 

 

 

 

 

 

 

for Different Type of Business
[Market Environment Levene’siTest
Factor for Equality
of Variances t-test for Equali 0f Means
Sig. Mean Std. Error
F Sig. t (11 (2-tailed) Difference Differencel

Erimary Equal
Industryar variances .453 .501 -.924 227 .356 -.2743 .2969
Secondary assumed
Industry Equal
iCompanson variances -.786 20.269 .441 -.2743 .3492
_ Jot assumed
Primary Equal
Industry& variances .007 .934 .145 244 .885 .0467 .3321
Wholesale assumed
[Retail Equal
Services variances .133 20.548 .895 .0467 .3504
IComparison not assumed
Erimary Equal
lndustry& variances .113 .737 -.290 146 .773 -.1014 .3502
General assumed
Services Equal
Comparison variances -.281 23.153 .781 -.1014 .3612

not assumed
Erimary Equal
lndustry& variances .674 .412 .480 247 .631 .1773 .3692
Managerial assumed
VPersonaI Equal
Services variances .501 21.1418 .622 .1773 .3541
Comparison not assumed
ﬁmary Equal
Industry& variances .332 .566 -.073 118 .942 -.0261 .3564
Hospitality assumed
[Tourism Equal
Industry variances -.071 24.621 .944 -.0261 .3670
CLomparison not assumed
Secondary Equal
Industry8 variances 2.073 .151 2.618 435 .009* .3210 .0799
Wholesale assumed
[Retail Equal
Services variances 2.627 434.873 .009 .3210 .0808
Comparison not assumed

 

 

 

 

 

 

 

 

 

 

133

Table 4-33 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Egondary Eq—ual

Industry8t variances 4.971 .026 1.192 337 .234 .1729 .1450

General assumed

Services Equal

Comparison variances 1.150 239.907 0.251 .1729 .1504

r rltLassumed

Secondary Equal

Industry8t variances 14.445 .000 3.375 438 .001 .4517 .1338

Managerial assumed

[Personal Equal

Services variances 3.412 428.346 .001‘ .4517 .1324

20mparison not assumed

Secondary Earl

Industry8 variances 6.892 .009 1.596 309 .111 .2483 .1555

Hospitality assumed

[Tourism Equal

Industry variances 1.514 173.196 .132 .2483 .1640

Comparison not assumed

Wholesale Equal

[Retailar variances .924 .337 -.982 354 .327 -.1481 .1508

General assumed

Services Equal

Comparison variances -.967 253.564 .335 -.1481 .1532
not assumed

Wholesale gal

[Retail & variances 5.902 .016 .963 455 .336 .1306 .1356

Managerial assumed

[Personal Equal

Services variances .964 446.926 .336 .1306 .1355

lComparison ggt assumed

Wholesale Equal

[Retail & variances 1.891 .170 -.447 326 .655 -.0728 .1629

Hospitality assumed

[Tourism Equal

Industry variances -.437 182.530 .663 -.0728 .1665

Comparison not assumed

General Erqual

Servicesat variances 1.277 .259 1.683 357 .093 .2787 .1656

Managerial assumed

[Personal Equal

Services variances 1.727 285.759 .085 .2787 .1614

Comparison not assumed

 

134

 

Table 4-33 (cont’d)

 

 

 

 

 

 

 

 

 

 

General Equal

Services& variances .173 .678 .400 228 .689 .0753 .1882
Hospitality assumed

[Tourism Equal

Industry variances .400 215.099 .689 .0753 .1882
Comparison not assumed

Managerial Equal

[Personal variances .403 .526 -1.127 329 .261 -.2034 .1805
Services& assumed

Hospitality Equal

[Tourism variances 4.168] 206.126 .244 -.2034 .1741
Comparison not assumed

 

Table 4-34 and Table 4-35 review the results of the paired industry T-tests. To

summarize, hiring decisions in the primary industry are signiﬁcantly more inﬂuenced by

the state-imposed cost of doing business factor than are the general service and the

managerial/personal service industries. The secondary industry is signiﬁcantly more

influenced by this factor than are the wholesale/retail, the general-services, and the

managerial/personal-service industries. The market environment has greater inﬂuence on

the secondary industry than on the wholesale/retail and the managerial/personal-service

industries.

Table 4-34 Summary of T-tests for the State-Imposed Cost of Doing Business Factor by

 

 

 

 

 

 

 

 

Different Type of Business
Ind. Secondary Wholesale/ General ManagJPerson. Hospitality/
Retail Services Services Tourism
T p T J9 T p T p T p
Prim. 0.473 0.637 1.495 0.136 2.073 0.040* 2.063 0.040* 1.156 0.250
Sec. 2.832 0.005" 3.672 0.000* 4.294 0.000* 1.596 0.1 1 1
W.[R. 1.049 0.295 1.399 0.162 0.683 0.495
G. S. 0.174 0.862 1.565 0.119
MJP. -1.807 0.072

 

 

 

 

 

 

 

 

 

 

 

135

 

 

Table 4-35 Summary of T-tests for the Market Environment Factor by Different Type of

 

 

 

 

 

 

 

 

Business
Ind. Secondary Wholesale/ General Manag./Person. Hospitality/
Retail Services Services Tourism
T p T p T p T p T p
Prim. -0.924 0.356 0.145 0.885 -0.29 0.773 0.480 0.631 -0.073 0.942
Sec. 2.681 0.009* 1.150 0.251 3.412 0.001* 1.514 0.132
W.[R. -0.98 0.335 0.964 0.336 -0.447 0.655
G. S. 1.683 0.093 0.400 0.689
M./P. -1.127 0.244

 

 

 

 

 

 

 

 

 

 

 

 

Hypothesis Five: The perceptions of state government, including the expertise of
state personnel and the degree of satisfaction with state-govemment services, are
inﬂuenced by the business type and size.

The purpose of testing this hypothesis is to examine (1) how the Michigan
business community perceives state-govemment services and the expertise of state
personnel and (2) whether or not their perceptions and degree of satisfaction is related to
the type and size of businesses. Table 4-36 presents mean values of the perceptions of the
quality of state-provided services and the expertise of state personnel by different size and
type of businesses. The original responses on the mail questionnaire were re-coded from
a ﬁve-point scale, 1 = strongly disagree to 5 = strongly agree, into three categories, 1 =
disagree, 2 = neutral, and 3 = agree. The re-coding was performed, because a simple
comparison was possible between those businesses that had negative and positive
perceptions of the quality of state- government services and the expertise of state
personnel.

The businesses that responded either “strongly disagree” or “disagree” with any of

the three statements (Section Four in the questionnaire) regarding their perceptions of the

136

quality of state-government services and the expertise of state personnel were combined
into the “disagree” category. Those businesses that were “undecided” represent the
“neutral” category. Those who indicated that they “agree” or “strongly agree” were
combined into the “agree” category.

Businesses, regardless of size, generally have negative perceptions of the quality
of state-government services. Small businesses indicate the quality of state services at
1.92 on a three-point scale. Most of the industries have a negative perception. Large
businesses (1.90) also show negative perceptions toward the quality of services provided
by state government.

Most of the businesses, regardless of size and type, fairly agree that state
government needs to market itself better about the products and services government
offers to the business community. The Michigan business community also has a negative
perception about the expertise of state-govemment personnel. Thus, most of the
businesses, across various types and sizes of businesses, perceive that state employees do

not have enough knowledge to be helpful for the business community.

137

Table 4-36 Perceptions of State- Services by Different Type and Size of Business

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Marketing of W
Business Quality of State Buiness of State
Size Business Type Services Services Agency Staff
Ema" Enmaw Industry Mean 1.91 2.27 2.55
Businesses N 1 1 11 1 1
Secondary Industry Mean 1.93 2.59 2.46
N 129 129 127
Wholesale/ Retail Mean 1.84 2.67 2.46
Services N 162 162 161
General Services Mean 2.03 2.55 2.26
N 102 102 101
ManageriaV Mean 1 .98 2.57 2.39
Personal Services N 150 151 150
Hospitality/ Tourism Mean 1.82 2.66 2.52
Industry N 63 62 61
Total Mean 1 .92 2.60 2.42
N 647 647 641
Medium Primary Industry Mean 3.00 3.00 2.00
Businesses N 1 1 1
Secondary Industry Mean 1.90 2.67 2.67
N 21 21 21
Wholesale/ Retail Mean 1.44 2.50 2.56
Services N 16 16 16
General Services Mean 2.00 2.57 2.57
N 7 7 7
Managerial/ Mean 2.00 2.55 2.36
Personal Services N 11 11 11
Hospitality/ Tourism Mean 1.50 2.00 2.00
Industry N 2 2 2
Total Mean 1.81 2.57 2.53
N 58 58 58

 

 

 

Note: 1 = disagree, 2 = neutral, 3 = agree

138

Table 4-36 (cont’d)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Large Primary Industry Mean 2.00 1.33 2.67
Businesses N 3 3 3
Secondary Industry Mean 2.08 2.84 2.16

N 25 25 25

Wholesale/ Retail Mean 2.00 2.50 2.17

Services N 12 12 12

General Services Mean 2.23 2.23 2.62

N 13 13 13

Managerial/ Mean 1 .58 2.63 2.68

Personal Services N 19 1 9 19

Hospitality/ Tourism Mean 1.00 2.20 2.80

Industry N 5 5 5

Total Mean 1 .90 2.53 2.43

N 77 77 77

Total Primary Industry Mean 2.00 2.13 2.53
N 15 15 15

Secondary Industry Mean 1.95 2.63 2.45

N 175 175 173

Wholesale/ Retail Mean 1.82 2.65 2.45

Services N 190 190 169

General Services Mean 2.05 2.52 2.31

N 122 122 121

ManageriaV Mean 1 .94 2.57 2.42

Personal Services N 190 191 190

Hospitality/ Tourism Mean 1.77 2.62 2.52

Industry N 90 59 53

Total Mean 1 .91 2.59 2.43

N 782 782 776-

 

 

Note: 1 = disagree, 2 = neutral, 3 = agree

139

Prior to testing for differences of perceptions among the businesses, a two-way

AN OVA was performed to assess whether or not there is a two-way interaction between

size and type of business. The results shown in Table 4-37 through Table 4-39 indicate

no interaction effect between size and type of business, which could be related to

perceptions of the quality of state-business services, the need for the state to better market

its business services, and the expertise of state agency personnel. The absence of any

signiﬁcant interaction between size and type of business allowed for the use of one-way

AN OVA tests for each independent variable.

Table 4-37 Two-Way Interactions between Business Size and Type for Service Quality

 

Services

 

 

 

 

 

 

 

 

Hierarchical Method
Sum of Mean
Squares df Square F Sig. ‘
Duality of Main Eﬁects (Combined) 7.396 7 1.057 1.739 .097
1=Small
Business,
2=Medium
Sizes .671 2 .336 .552 .576
Business,
3=Large
Business
Industry Typel 6.724 5 1.345 2.213 .051
2-Way 1=Small
Interactions Business,
2=Medium
Sizes
Business, 10.059 10 1.006 1.655 .087
3=Large
Business ’
Industry Type
Model 17.455 17 1 .027 1.690 .040
Residual 464.279 764 .608
Total 481.734 781 .617

 

140

 

Table 4-38 Two-Way Interactions of Business Size and Type for Needs for Marketing of
State Services

 

 

 

 

Marketing Main Effects (Combined)

Of State
Business
Services

 

2-Way
Interactions

Model
Residual
Total

 

Hierarchical Method
Sum of Mean
Squares Square F Sig.
5.190 7 .741 1.591 .135

1=SmaII
Business,
2=Medium
Sizes .359 2 .1 79 .385 .681
Business,
3=Large
Business
Industry Type 4.831 5 .966 2.074 .067
1=SmaII
Bsiness,
2=Medium
Sizes
Business, 7.691 10 .769 1.651 .088
3=Large
Business "
Industry Type

12.881 17 .758 1.626 .052

355.990 764 .466
368.871 781 .472

 

 

 

 

 

 

Table 4-39 Two-Way Interactions between Business Size and Type for Perception of

 

 

 

Expertise of Agency Staff
Hierarchical Method
Sum of Mean
Squares df Square F Sig.
xpertise orMainEITects (Combined) 3,413 7 .488 .998 .431
SW9 1 =SmaII
Agency Staff Business,
2=Medium
Sizes .701 2 .351 .718 .488
Business,
3=Large
Business
Industry Type 2.712 5 .542 1.1 10 .353
2-Way 1=Small
Interactions Business,
2=Medium
Sizes
Business, 8.339 10 .834 1 .707 .075
3=Large
Business '
Industry Type
Model 11.753 17 .691 1.415 .122
Residual 370.349 758 .489
Total 382_.1_Q_2 775 .493

 

 

 

 

 

 

 

141

 

 

Table 4—40 suggests that there is no signiﬁcant variation in perceptions of the
quality of state-business services across different sizes of businesses; i.e. opinions on
whether or not the state should better market its business services or try to improve the
business community’s perceptions of staff expertise. Based on the ANOVA, one can
conclude that perceptions of state-business services and the expertise of state agency
personnel are not related to the size of businesses. Regardless of size, businesses

generally have a negative perception of state-government services for businesses.

Table 4-40 ANOVA for Perceptions of State Services by Size of Business

 

 

 

 

 

 

 

 

 

 

 

Sum of Mean
_ i Squares df Square F Sig.
Quality of Between
Services Groups .770 2 .385 .623 .536
aims 489.155 792 .618
Total 489.925 794
Marketing Between
Of State Groups '565 2 233 -599 .550
Business Within
Total 374.31 9 794
Expertise Between
of State Groups '591 2 295 503 -547
Agency Within
Staff Groups 385.166 786 .490
Total 385.757 788

 

The ANOVA table (Table 441) shows no statistically significant differences
across industries regarding perceptions of (1) the need for the state to better market its
business services and (2) the expertise of state-agency staff. Conversely, the results of
ANOVA indicate signiﬁcant differences in perceptions of the quality of state-business

services across different industries.

142

Table 4-41 ANOVA for Perceptions of State Services by Type of Business

 

 

 

 

 

 

Sum of Mean
_ _ Squares d1 Square F Sig.
$336? 33%;? 6.775 5 1.355 2.241 .048*
Within
Groups 547.925 906 505
Total 554.701 91 1
Marketing Between
Of State Groups 3.638 5 .728 1.543 .174
Business Within
Services Groups 427.168 906 .471
Total 430.806 911
5:33? gimp"? 3.162 5 .632 1.266 .276
Agency Within
Staff Groups 449.952 901 .499
Total 45_3f.1 14 906

 

 

 

 

 

 

T-tests were then performed to ascertain statistically signiﬁcant differences

between different industries. The results (Table 4-42) show that, on average, businesses
in the general service industry (mean: 7.05) rate the quality of state-business services to
be signiﬁcantly better than wholesale/retail services (mean: 6.82) and hospitality/tourism

businesses (mean: 6.77).

Table 4-42 T-tests for Perception of the Quality of State Service by Different
Type of Business

 

Hospitality/Tourism Industry I
t: 2.889, p = 0004* |

| Wholesale/Retail Services
t= -2.85, p = 0005"

Industry
General Services |

 

For the most part, perceptions of state-govemment services to businesses are not
inﬂuenced by type and size of business. Differences were, however, found among the

general, the wholesale/retail, and the hospitality/tourism industries in their perceptions of

143

the quality of state-provided services for businesses. On average, businesses in the
wholesale/retail, and the hospitality/tourism industries have more negative perceptions
than do other industries examined in this study (see Table 4-36).

Hypothesis Six: Businesses that have had prior experience with state agencies are
generally more satisﬁed with the quality of their services than are businesses that have
had no or very limited prior experience with government agencies.

The intent behind testing this hypothesis is to determine whether or not businesses
that have prior experience with state agencies have more positive perceptions about those
agencies than do businesses that have no experience with these agencies. It is assumed
that, in part, the negative perceptions of state agencies are due to a lack of exposure and
familiarity.

Independent T—tests were employed to examine if there is a signiﬁcant mean
difference in the perceptions of businesses that have had and those that have not had prior
experience with state agencies. Table 4-47 displays the mean perceptions of the quality
of state-govemment-provided services and the expertise of agency personnel of
businesses having had and not having had prior contact. Eight-hundred and ﬁfty-one
businesses (90.4 percent) of the companies that completed a questionnaire had some prior
experience with at least one of the 12 state agencies (Table 4435). Around 10 percent (9.6
percent) had no experience with any of these agencies. Almost 50 percent of businesses
(44.1 percent) had contact with more than ﬁve agencies. The Michigan Employment

Security Commission (contacted by 609 businesses) and the Michigan Department of

144

Treasury (contacted by 554 businesses) were the agencies that were most frequently

contacted by businesses (Table 4-44).

Table 4-43 Number of State Agencies that Business have had Contact with

 

 

Valid Cumulative

Number of Contacts Frequency Percent Percent Percent
NC 90 9.4 9.6 9.6
1 .00 89 9.3 9.5 19.0
2.00 114 12.0 12.1 31.1
3.00 116 12.2 12.3 43.5
4.00 112 11.8 11.9 55.4
5.00 91 9.5 9.7 65.0
6.00 66 6.9 7.0 72.1
7.00 68 7.1 7.2 79.3
8.00 35 3.7 3.7 83.0
9.00 24 2.5 2.6 85.5
10.00 27 2.8 2.9 88.4
11.00 17 1.8 1.8 90.2
12.00 92 9.7 9.8 100.0
Total 941 98.7 100.0

Missing Cases 12 1.3

Total 953 100.0

 

 

 

 

 

 

 

Note: NC = no contact, 1 = one agency contact; 12 = twelve agencies contact

Table 444 Total Number of Businesses that Have Had Contact with State Agencies

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Total Number
State Agencies of
Businesses

Making

Contact
Michigan Jobs Commission 296
Michign Dep. of Natural Resources 422
Michigan Employment Security Commission 609
Michiggn Department of Transport. 322
Michigan Occupational Safety 8 Health Agency 397
Michigan Travel Bureau - 228
Michigan State Police 434
Michign Department Of Social Services 395
Micfigan Department of Agriculture 226
Michigan Department of Commerce 314
Michiggn Department of Treasury 554
Michigan Department of Education 300

 

 

 

145

The results of mean perceptions (Table 4-45) and T-tests (Table 4-46) indicate

should better market its services that are available to businesses.

that business perceptions of state agency services and staff expertise are not related to
priorexperiences with the agencies. Nor do they differ in their opinions as to whether or
not state agencies need to better market the business services they provide. Businesses,

regardless of their prior experiences with state agencies, generally feel that the state

Table 4-45 Means Perceptions of State Services by Businesses that Have
and Have Not Had Prior Experience with 12 State Agencies

 

 

 

 

 

 

 

 

 

Perception Contact N Mean I
Quality of No Prior Experience 75 1.92
Services Prior Experience 784 1.90
Marketing of State No Prior Experience 78 2.67'
Business Services Prior Experience 783 2.59
Expertise of State No Prior Experience 77 2.38
|Agency Staff Prior Experience 778 2.44

 

Note: 1 = disagree, 2 = neutral, 3 = agree

146

Table 446 Results of T-Tests for Differences in Perceptions between Businesses Having
Had and Not Having Had Prior Contact! Experience with 12 State Agencies

 

 

 

 

 

 

 

 

 

 

 

 

Eerception Levene’s Test
for Equality
of Variances t-test for Equality of Means
Sig. Mean Std. Error
F Sig. t (if (2—tailed) Difference Difference
auality of ELqual
Services variances 9.844 .002 .221 857 .825 .0208 .0940!
assumed
Equal
variances .251 94.476 .802 .0208 .0826
not assumed
Marketing Equal
of State variances 3.871 .049 .910 859 .363 .0728 .0800-
Business assumed
Services Equal
variances 1.015 98.194 .313 .0728 .0717
not assumed
Expertise Equal
of State variances .697 .404 -.740 853 .460 -.0617 .0834
Agency assumed
Staff Equal
variances -.768 93.260 .445 -.0617 .0803
not assumed

 

 

 

On average, businesses participating in the study had prior contact or experience

with ﬁve of the 12 state agencies (Table 4-47). Further statistical analyses were

conducted to examine whether or not perceptions of state-government services and staff

expertise are related to the number of agencies with which businesses have had

experience. A bivariate correlation was performed to determine the relationship between

the number of agencies with which companies have had experience and their perceptions

of state business services and staff expertise.

147

Table 447 Mean and S. D. for Number of Agendas Contacted by Businesses and Business
Perceptions of Quality of State Services, Need of Marketing, Staff Expertise

 

 

 

 

 

 

 

No. of Agencies Std.
and Perception Mean Deviation N
No. of Agencies
Contact ed 4.7790 3.5822 941
Quality of Services 1.90 .78 932
Marketing of
State Business 2.59 .69 932
Services
Expertise of State

_Agency Staff 2.43 .70 928

 

Note: 1 = disagree, 2 = neutral, 3 = agree

Interestingly, the results from the Pearson correlation analysis indicate a
signiﬁcant negative linear correlation between the number of agencies that a business has
experienced and the perception of the quality of state-govemment services (r = -0.091, p-

value = 0.005 < 0.01 or) and the need to better market government-provided services (r =
-0.079, p-value = 0.016 < 0.05 or). The more agencies with which businesses have had

experience, the more negative were their perceptions of the quality of agency services.
The analysis also detected a signiﬁcant negative linear correlation (r = -3.45, p-value =
0.000 < 0.01 or) between the perception of the quality of state-govemment services and
the perception of the expertise of agency staff (the more negative the perception of the
expertise of state personnel, the more negative was the perception of the quality of state

services).

148

Table 4-48 Correlation between Extent of Contact with 12 State Agencies and Perceptions
of Quality of State Services, Need of Marketing, Staff Expertise

 

Number of Marketing Expertise
Agencies of Sate of State
Contacted by Quality of Business Agency
Businesses Services Services Staff

 

hI-Dearson No. of
Correlation Agencies “ .
Contacted by 1.000 -.091 -.079 .037

Businesses
Quality of
Services
Marketing
of State
Business
Services
Expertise of v
State Agenc .037 -.345*‘ .030 1.000
Staff 1
Sig. No. of
(2-tailed) Agencies
Contacted b
Businesses
Quality of
Services
Marketing
of State
Business
Services
Expertise of
State Agency: .263 .000 .360
Staff
N No. of
Agencies
Contacted by
Businesses
Quality of
Services
Marketing
of State
Business
Services

Expertise of
State Agencﬁ 919 921 923 928

 

-.091“ 1.000 .051 -.345"

 

-.079* .051 1 .000 .030

 

 

 

.005 .016 .263

 

.005 . .117 .000

 

.016 .117 . .360

 

 

941 924 925 91 9

 

924 932 928 921

 

925 928 932 923

 

 

Staff
Note: “. Correlation is significant at the 0.01 level (2-tailed).
' . Correlation is significant at the 0.05 level (2-tailed).

 

 

 

 

 

 

149

The correlation results only indicate the strength of a linear association, but they
do not provide a measure of comparison nor do they summarize the relationships between
pairs of variables. AN OVA tests were performed to better describe and summarize the
relationship between the extent of prior experience and the perceptions of state agencies.
Table 449 shows the mean perceptions of state agencies by businesses grouped
according to their number of contacts or experiences with state agencies. The following
groups were formed: (1) businesses with no contact with any of the 12 agencies (9.6
percent); (2) businesses that had contact with one to ﬁve agencies (54.8 percent); and (3)

businesses that had contact with six to 12 agencies (34.5 percent).

Table 449 Mean Perceptions of State Government Agencies by Businesses with Diﬂ‘erent
Amount (Number of Agencies) of Contact with these Agencies

 

 

 

 

 

 

 

 

 

 

Marketing Expertise
State of State
Number of Contacted Quality of Business Agency
Aﬁncies Services Services Staff
No Contact Mean 1.91 2.67 2.40
N 80 83 82
1 to 5 Agencies Contacted Mean 1.97 2.62 2.42
by Businesses N 516 516 512
6 to 12 Agencies Mean 1.79 2.52 2.45
Contacted by Businesses N 323 326 325
Total Mean 1 .90 2.59 2.43
N 924 925 919
Note: 1 = disagree, 2 = neutral, 3 = agree

 

There is a signiﬁcant mean difference (F = 6.207, p-value = 0.02 < 0.05 or) in the
perceptions of the quality of state-government services among businesses with different
amounts of prior contact with the 12 agencies (Table 4-50). Generally, perception of the
quality of state-agency service is lower as companies have more contact with more of the

150

12 state agencies. Businesses having had contact or experience with six to 12 agencies
have signiﬁcantly lower perceptions of the quality of state-agency services.

The results show that there is no signiﬁcant difference in the perceptions of the
expertise of state-agency personnel between businesses that have had or had not had prior
contact experience with state agencies. However, businesses that have had contact with
more state agencies generally have more negative perceptions of the quality of state-

government services.

Table 4-50 Results of ANOVA Test of Business Perceptions by Number of Agencies

 

 

 

 

Contacted by Businesses
Sum of Mean
_ _ Swares df Square F Sig._

Quality of Services Between Groups 6.412 2 3.206 5.303 .005*

Within Groups 556.821 921 .605

Total 563.233 923
Marketing State Between Groups 2.403 2 1.202 2.569 .077
Business Services . .

Within Groups 431.309 922 .468

Total 433.712 924
Expertise of State Between Groups .216 2 .108 .218 .804
Agency Staff . .

Within Groups 455.007 916 .497

Total 455.223 918

 

 

 

 

 

 

 

 

 

T-tests were then employed to ascertain statistically signiﬁcant differences
between different business groups that contacted a different number of agencies: (1)
businesses having had no prior contact with any of the 12 state agencies; (2) businesses
having had contact with one to ﬁve state agencies; and (3) businesses having had contact

with six to 12 state agencies. The result (I = 3.139, p-value = 0.001 < 0.05 a) (Table 4-
51) shows a signiﬁcant difference in the perception of the quality of state services

151

between businesses that had contact with one to ﬁve state agencies and those that had
contact with six to 12 agencies. Businesses having had contact with six to 12 agencies

have a more negative perception than do other group of businesses.

Table 4-51 Result of T-tests for Differences in Perceptions of Quality of State Services
between Businesses with One to Five and Six to 12 State Agencies Contacted
by Businesses

 

 

 

 

I Statistics
lLevene’s Test
for Equality
of Variances t-test for Ec uality of Means
Dependent
Variables Assumptions Sig. Mean
_ F Sig. 1 df (2-tailed) Difference
Quality of Equal variances
Services assumed 7.441 .007 3.210 842 .001 .18
Equal variances not .
assumed 3.192 683.505 .001 .18

 

 

 

 

 

 

 

 

 

152

Chapter 5

5. SUMMARY AND CONCLUSIONS

The primary purposes of this study were to (1) determine the extent to which
various external environment factors inﬂuence business decisions, particularly in
expanding the business by hiring of additional employees; (2) assess whether or not size
or type of a business inﬂuences how a business responds to external factors, including
state-govemment policies and actions; and (3) compare the perceptions that owners and
managers of different types and sizes of businesses have of state agencies, their services
and their expertise. Although previous research has examined the inﬂuence of state-
govemment policies on manufacturing businesses, few studies have examined the impact
of various environment factors on the decisions made by different types or sizes of
businesses, including the services and the hospitality/tourism and small businesses. In
part, this was due to a long-standing emphasis by economic development organizations
on manufacturing businesses and the use of certain strategies (e.g. tax breaks and other
ﬁnancial incentives) to locate or remain large manufacturing companies in Michigan.
This study was undertaken to compare the relative inﬂuence of various environment
factors, including government actions, on expansion decisions, particularly hiring
decisions, made by different types and sizes of businesses.

This chapter summarizes. the results and discusses the implications of key
ﬁndings. Implications and contributions of this research are also discussed. Limitations

of the study are identiﬁed, and recommendations are made for future research.

153

5.1 Review of the Study’s Theoretical Basis and Research Methods

The Review of the Literature, conducted as part of this study, determined that
economic environment (e. g. consumer demand and labor supply) and the actions of state
government have an important inﬂuence on businesses’ decision making. As part of their
effort to stimulate economic growth, state governments have offered various business
incentives and implemented policies intended to stimulate employment. The majority of
these incentives and programs are directed primarily at large manufacturing industries,
while ignoring services and tourism/hospitality businesses.

Previous research on the effect of tax and other ﬁnancial incentives has

determined that consumer market demand and labor supply—not just taxes—have a

signiﬁcant inﬂuence on business decisions, including expansion and hiring. Previous
research also indicates that state governments need to recognize the economic beneﬁts of
and encourage the development of the services, tourism/hospitality, and small businesses.
Various authors have contend that this will require a better understanding of how these
businesses respond to factors comprising the external environment, as well as to
attraction and retention programs and incentives. This study was designed to provide
state-level policy makers with information and analyses to help them to understand and
anticipate how different types and sizes of businesses, including hospitality/tourism and
small businesses, are likely to respond to various policies and programs.

A conceptual framework for this study was developed by integrating various
approaches stemming from a stream of research concerned with the manner in which

businesses respond to factors comprising the external environment. The core of the

154

conceptual framework is organization theory (OT), which holds that the decisions and
behavior of organizations are inﬂuenced by factors in their external environment.
Organizations must acquire external resources, e. g. labor, for their continued survival and
success. According to this theory, organizational environments are deﬁned as objects and
perceptions. The four components of the objective environment are: (1) customers; (2)
suppliers of labor, material, equipment, and capital; (3) competitors; and (4) regulatory
groups (government, government agencies, and unions). The perceived environment is
deﬁned in terms of managerial perceptions of environmental uncertainty.

Studies that were reviewed identiﬁed the perceived inﬂuence of consumer
demand and labor supply (economic environment) on ﬁrms’ hiring decisions. Research
has shown that state employment-related regulations and laws are generally perceived by
businesses as adding to the cost of doing business. Research on the effects of different
economic development programs has found that taxes and ﬁnancial incentives offered by
states to businesses have little or no effect on strategic decisions, including business
location, expansion, and the hiring of more employees. Availability of qualiﬁed labor,
labor costs, and infrastructure have more inﬂuence on these decisions.

Even though there has been greater recognition of the economic development
potential associated with small business and the service and the hospitality/tourism
industries, there has been little research on factors that inﬂuence the development and
expansion of these businesses. No comparative studies have been conducted that identify
the relative inﬂuence of environment factors, policies, or incentives on different types and

sizes of businesses, including hospitality/tourism businesses. As a consequence, there is

155

no empirical information to determine whether or not or in what ways small, services, and
hospitality/tourism businesses are different from other types of businesses and how they
differ in terms of their perception and response to the external environment and state-
govemment policies and programs.

This study examined the importance and inﬂuence of three elements of the
perceived environments: (1) the market environment, including consumer demand and
labor supply; (2) employment-related legal and regulatory environment, including
workers’ compensation, unemployment insurance, healthcare beneﬁts, unions, and other
laws and regulations; and (3) state economic-development policy, particularly small-
business and tourism development policies.

Focus groups were conducted ﬁrst with 21 agriculture, manufacturing, and
service-sector business owners and managers. The focus group sessions identiﬁed
environment factors that are most important to different types and sizes of business and
explored owner and manager perceptions of state policies and the quality of services
provided to businesses.

The insights from the focus groups were then utilized to guide the development of
a mail questionnaire that collected data on: (1) the perceived importance of various
external environment factors in ﬁrms’ hiring decisions; (2) owner or manager perceptions
of services provided by 12 state agencies; and (3) the characteristics of the responding
businesses. Thirty-three percent (968) of the businesses that received a questionnaire
completed and returned it. To test the hypotheses, the responding businesses were

categorized into six industries: (1) the primary industry; (2) the secondary industry; (3)

56

wholesale/retail industry; (4) the general-services sector; (5) the personal/managerial
service sector; and (6) the hospitality/tourism industry. These responding businesses
were also classiﬁed by size: ( 1) “small,” less than 50 total employees; (2) “medium,” 50
to 100 total employees; and (3) “large,” more than 100 total employees. Factor analysis,

ANOVA, and T-tests were performed to test the six hypotheses.

5.2 Major Findings

Five general conclusions can be drawn from the results of the tests of the
hypotheses.

First, the market environment—consumer demand and supply of labor—is

generally more inﬂuential in business (expansion and hiring) decisions than are state
regulations and programs. This is generally true across different sizes and types of
businesses.

Second, small and large businesses, and small and medium businesses, differ in
terms of the inﬂuence of the market environment factor. The market environment is of
greater importance to medium- and large-sized businesses than to small-sized businesses.
Different-sized businesses do not differ with regard to the importance that the state-
imposed cost of doing business factor has in their decisions.

Third, businesses (e. g. agriculture, forestry, ﬁshing, and mining) comprising the
primary industry are more signiﬁcantly inﬂuenced by the state-imposed cost of doing
business factor, compared to the general-services (e.g. ﬁnance, insurance, real estate,

transportation, and communications) and managerial/personal-services (e. g. medical,

157

legal, day-care, auto repairing, management, and consulting services) industries.
Secondary industry businesses (e. g. manufacturing and construction) are more
signiﬁcantly inﬂuenced by the market environment than are the wholesale/retail, general-
services, and managerial/personal-service industries. In general, secondary industry
businesses are more signiﬁcantly inﬂuenced by both the market environment and the
state-imposed cost of doing business factors than are service industries, except for the
hospitality/tourism industry.

A fourth conclusion is that perceptions of the quality of state-govemment-
provided services do not vary signiﬁcantly across different types and sizes of businesses.
Generally, businesses have negative perceptions about the quality of state—provided
business services and the level of expertise of state-agency personnel. The
wholesale/retail and the hospitality/tourism industries have more unfavorable perceptions
of government services than does the general-services industry.

Fifth, businesses with prior contact, or experience, with 12 state agencies do not
have signiﬁcantly different perceptions of state-agency service quality or staff expertise
than do businesses that have not had previous contact. However, the more agencies with
which businesses have had contact, the more unfavorable are their perceptions of the
overall quality of state-provided services. In this case, contact with more agencies does

not improve the perceptions of service provided to businesses by the state agencies.

158

5.3 Implications and Contributions

The ﬁndings indicate that the market environment, such as consumer demand and
access to qualiﬁed labor, is a more important factor in making business decisions that are
related to expansion and the hiring of new employees than are government programs and
incentives. Offering ﬁnancial incentives or lower tax rates may have only limited
inﬂuence on ﬁrms’ decisions to expand by hiring additional employees. Tax and other
ﬁnancial incentives offered by states will be less effective if there is a shortage of
qualiﬁed employees in those states. Government efforts that enhance the availability of
qualiﬁed labor may have a greater affect. This may be even more important in the future
as labor availability decreases and competition among businesses increases.

The sensitivity to labor supply and consumer demand also has implications for the
hospitality/tourism industry, given rising competition and an expected shortage of front-
line service workers. This could indicate that tourism development will be dependent on
(1) the amount and success of state marketing efforts to expand markets and (2) the
availability of unskilled and skilled service workers. This suggests that states need to
look at more integrated strategies for attracting and retaining tourism businesses by
providing favorable labor and market environments, i. e. strategies that focus less on
ﬁnancial incentives and more on market and labor-force development.

Given the ﬁnding that larger businesses (more than 50 employees) are
signiﬁcantly more sensitive to consumer demand and the supply of qualiﬁed labor than
are small businesses (less than 50 employees), state government should consider a multi-

dimensional business attraction and retention effort that also includes programs and

159

policies that improve market conditions. Limiting efforts only to offering tax and
ﬁnancial incentives may not be effective.

Traditionally, to attract and retain businesses in their states, many state authorities
have focused on offering primarily ﬁnancial incentives without evaluating the response
sensitivities of particular industries. The ﬁndings of this study indicate, however, that
different types and sizes of businesses are more or less sensitive to various external
environment factors. For instance, expansion and hiring decisions by businesses in the
primary and the hospitality/tourism industries are more sensitive to state govemment-
imposed cost of doing business than are other service industries. Policy makers should,
therefore, realize that the hospitality/tourism businesses respond differently to external
environments than do other service businesses. This suggests that efforts to attract and
retain different types and sizes of businesses (e.g. service, tourism, and small businesses)
may require more industry- and size-speciﬁc policies, programs, and services.

The results of this study also indicates that Michigan businesses generally had
negative perceptions of services and expertise of state agencies. Michigan businesses,
regardless of type or size, generally have unfavorable perceptions of state agencies, the
quality of their services, and the expertise of their personnel. These negative perceptions
were more intense as businesses have contact with more agencies, which strongly
suggests a need for state agencies to understand and focus more effort on enhancing
perceptions of their services, including a better understanding of the criteria that are the
basis for business perceptions. Since 1995 there have been signiﬁcant efforts to reduce

unnecessary regulations and to make state-provided business services more convenient

160

and higher quality. It would be useful to determine, if and to what extent business
perceptions of state agencies has changed since 1995. This study could provide some
base—line information to assess the changes that have occurred.

This research contributes to the body of literature in the realm of “business
environment.” This study’s uniqueness is its comprehensive approach that compares the
relative inﬂuence of external environments on different types and sizes of businesses.
The ﬁndings of this study demonstrate that the inﬂuence of external environments varies
by different size and type of business. Until now, most of the research in this area has
examined the effect of speciﬁc external environments, including government programs
and policies (e. g. taxes), particularly on large manufacturing companies. This research,
however, provides a comprehensive examination of the relative inﬂuence of various
external environments on different types and sizes of businesses and is particularly
unique for distinguishing two external environment factors, the state-government—related
regulation factor and the market environment factor, and for concurrently comparing the

relative impact of these two factors on different sizes and types of businesses.

5.4 Limitations

The interpretation of the ﬁndings, conclusions, and implications of this research,
which has been outlined in this chapter, is subject to a number of limitations not
previously discussed.

First, this study investigated a limited number of external environment variables

in developing an underlying structure of external environment factors. More variables

161

may be needed to better understand various external environment factors, e.g.
technological and cultural environment variables.

Second, the data on the tourism industry was not adequate for drawing any general
conclusions regarding perceptions of the tourism industry toward the external
environment factors and state-govemment services. In this study, the tourism industry
was categorized by the reported percentage of total sales attributed to tourist dollars
earned from all types of businesses. Consequently, the way the questionnaire was
designed might have created confusion in identifying tourism businesses. For instance,
some construction businesses cannot be categorized in the tourism industry only because
they reported some percentage of tourist earnings. This inability to adequately categorize
tourism businesses marred the statistical analysis of the tourism industry in Michigan.

Third, this research identiﬁed differences in factors that impact the expansion
decisions or the hiring of more employees by different types of ﬁrms, including
tourism/hospitality businesses. A ﬁnding of this study, that shows that
tourism/hospitality businesses are more sensitive to the state-imposed cost of doing
business factor than are other service businesses, e. g. wholesale/retail, general, and
personal/managerial services, is subject to further investigation. Although other business
sectors are highly inﬂuenced by the market environment factor, tourism/hospitality
businesses seem to be more inﬂuenced by the state-imposed cost of doing business factor
than are other service businesses. These ﬁndings imply that policy makers need to be

aware of the differences between the tourism/hospitality industry and other service

162

industries. As mentioned earlier, however, this study was not originally designed to focus
on the tourism industry nor the factors that affect their expansion decisions.

Fourth, although this researcher assisted throughout the entire research process,
except for the focus group sessions, the questionnaire and research were designed to
fulﬁll the objectives of many interested parties, such as the Michigan 2000 Foundation
and the Research Director, which is analogous to using secondary data. Some variables
in the questionnaire could not, therefore, be used for this research. Also, this study
initially was designed as a descriptive study on the relationship between the perceptions
of the Michigan business community and state government policies, but subsequently
evolved into a more comprehensive study. These problems limited the in-depth analyses
regarding the main purpose of this study.

Fifth, this study’s results could not be generalized or updated, because the
analyses were done with 1995 data. Other limitations regarding data were presented in

Chapter 3.

5.5 Directions for Future Research

First, a more in-depth study can be designed to better deﬁne the relationship
between the external environment and business decision-making behavior—not just
ﬁrms’ hiring-decision behavior, e. g. location, relocation, and expansion in terms of
facilities, as well as employment.

Second, the ﬁnding of differences in sensitivity to the factors tested in this study

suggests that additional research would be beneﬁcial, e. 3. research that investigates more

163

precisely and in more depth the factors that impact tourism business decisions related to
expansion and hiring. Factors that should especially be investigated are how tourism
businesses evaluate market growth potential, perceptions of availability of qualiﬁed
employees, and how perceptions of these factors inﬂuence their business decisions.
Third, the results of this study provide numerous hypotheses that can be evaluated
with an improved sampling method, improved measures, and better methodologies, e. g.
using different size scheme to avoid skewed sample toward small businesses, utilizing
correlation technique in hypotheses testing (Hypothesis Six), and structuring models.
Fourth, potential lag effects need to be considered. For instance, the results found
regarding perceptions of businesses toward state-government services may be manifested
within a certain period of time. The businesses’ perceptions of the external
environments, including state government polices, can be updated by longitudinal

research to capture lag effects.

164

APPENDICES

165

 

Appendix A

US. and Michigan Economy and Employment Environment

166

 

A brief overview of US. economic trends is necessary to better understand the
economic /market environment of businesses and its impact on them. The US. economy
from the early 1980s to 90s is characterized as the longest economic expansion since the
Second World War. Figure-A 1 shows U.S. civilian employment growth during the past

10 years.

 

 

Source: Trend in US. Civilian Employment (thousands)—1 986-1996. [Online Image]
Available http://www.globalexposure.com/pages/a0m442.html, August 4, 1998.

Figure-A 1 Trend in US. Civilian Employment (thousands)—I986-96

After a recession during the period 1990-1991, the economy resumed and
continued to improve. During the last 10 years, the US. economy has experienced a
fundamental change. Manufacturing jobs have declined in number, while service-based

employment has continued to grow (see Figure-A 2).

167

...... gm

Mutual. and
fetal u-ade

Government

"Meaning
Fhmlwumand
mlmﬂ‘llﬁ)

Tm mmunlu-

m. and uni-an (rev)

     

l ‘4 20% 30%

Imm-

‘i. IOK
- I vs
Sourcez. Nonagricultural Employment Distribution, by Sector, United States and

Michigan, 1997. [Online Image] Available http://www.michiganinbrief.org/text/
appendix/append-F.html/afex3.gif, August 4, 1998.

Figure-A 2 Non-agricultural Employment Distribution by Sector, U.S. & MI, 1997

As the nation moves from manufacturing-based industrial economy to a service
economy, states’ economic policies are affected in many ways (e.g. policies focusing
more on service and tourism industries) (Deming, 1996).

The following snapshot of Michigan’s economy will be useful as a baseline for
this study. In 1992, the Michigan unemployment rate was 8.8 percent, above the national
rate of 7.4 percent; by 1997, state’s unemployment rate was not only down to 4.2 percent,
but also was below the national rate of 4.9 percent. In fact, the Michigan unemployment
rate has been below the national average since 1994, which was the ﬁrst time since 1966
that this had happened. In brief, the unemployment rate in Michigan had been
consistently higher than the US. average rate, but in 1994 there was a dramatic reversal

and the state rate has been lower than the nation-wide rate (see Figure-A 3).

168

 

 

 

Source: Unemployment Rate, United States and Michigan, 1970-1997. [Online Image]
Available http://www.rnichiganinbrief.org/text/appendix/append-F.html/afex2.gif,
August 4, 1998.

F igure-A 3 Unemployment Rate, U.S. & MI, 1970-1997

Although the job growth rate in Michigan exceeded that of the U.S. during the
1980s, the state’s rate declined during the recession of the early 19908 (see Figure-A 4).
Until recent years, however, Michigan’s business environment had been ranked near the
bottom among all the states. For instance, it was ranked 40th from 1980 to 1990. A study
of state manufacturing climates by Grant Thornton Company (1986) also found Michigan
ranked last among the 29 “high manufacturing intensity” states due to high production
costs. In another study of state-local tax systems conducted in 1992 by Public Sector
Consultants, Inc., Michigan ranked 47th among the 50 states in business climate due to
overall tax burden, marginal income tax rates, public-service expenditures, workers’
compensation rates, and unemployment insurance costs. Conversely, recently Michigan
was ranked 6th in new plants and expansion with 400 in 1996 and was recognized as a

leading state as an attractive business location with 1,285 new plants and expansions

169

announced and 278 new manufacturing facilities announced in 1997 (Public Sector

Consultants, Inc. 1998).

 

 

 

I US. I Michigan

Source: Employment Growth Rate, United Sates and Michigan, 1980-1997. [Online
Image] Available http://www.rnichiganinbrief.org/text/appendix/append-
F.html/afexl.gif, August 4, 1998.

Figure-A 4 Employment Growth Rate, U.S. & M1, 1980-1997

The Michigan economy and employment growth have been described as “static,
neither moving up or down,” from the early 19905 until 1994 when manufacturing
employment was at the highest point in a decade (Cary, Fulton, and Hymans, 1996, p.
213). Michigan’s per capita income data indicate the decline of the automobile industry.
It exceeded that of the U.S. from 1950s to 1970s (see Figure-A 5). However, it fell below
the national average in the 19805, when the automobile industry began experiencing

serious trouble and layoffs (see Figure-A 6).

170

 

 

95%.--.iswii'i"iiiiiiﬁiiilsiltwwué'iweiiiiiii'i
'50" '53 '56 "59' '62 '55 ’68 '71 '74 '77 "do 113 "as '69 '92 '45

 

__-U$ Per up“. lncom — Michigan per capita income in relation to
US. level

Source: Michigan per Capita Income as Percentage of U.S. per Capita Income, 1950-
1996. [Online Image] Available httpzllwww.rrrichiganinbrief.org/text/appendix
lappend-F.htm1/afex4.gif, August 4, 1998.

Figure-A 5 Michigan per Capita Income as Percentage of U.S. per Capita Income, 1950-
1996

 

 

 

I970 I975 193) I985 I990 I995

——-Trend line — Michigan production

Source: Michigan Motor Vehicle Production as a Percentage of U.S. Production, 1970-
1996. [Online Image] Available httpzllwww.michiganinbrief.org /text/appendix/
append -F.html/afex6.gif, August 4, 1998.

Figure-A 6 Michigan Motor Vehicle Production as a Percentage of U.S. Production, 1970-
1996

171

Appendix B

Michigan Businesses Questionnaire

172

 

 

1998 SURVEY OF MICHIGAN BUSINESSES
MOTION ON!

Thisacﬁmkwdetanimthaefamthatmﬂuemthededdmbythhbusimmhimmm
mm EMPLOYEES. prmpmsdtﬁsmmn-timemployeumdeﬁneduthm
whoworkatleastﬂhounaweek. Pleeaecirclethenumberbesideeachfactorbuedonthe

following scale:

 

 

Not
Anil- V-rr Vary
cable [Jule Inch
NA I 8 8 4 8
l Misha-hummus“. NA 1 8 8 4 8
2. ”mummm NA 1 8 8 4 8
3 Staten“. NA 1 8 8 4 8
4 ”bandit. NA 1 8 8 4 8
8 hborumone. NA 1 8 8 4 8
6 Worker-compensation. NA 1 8 8 4 8
7 'l'hepeperworkrequindbym government NA 1 8 8 4 8
8. Acne-bum labor. NA 1 8 8 4 8
9. 'l‘hemottheeehoolyeerpriortohborbay. NA 1 8 8 4 8
10 Unnploymentm NA 1 8 8 4 8
11. ‘l'hedemandtortheprodwmoﬂendby
theta-into. NA 1 8 8 4 8
12. The cost ofbeneﬁte (e.g. health care). NA 1 8 8 4 8
13. ceramic-um r a a 4 s
8 8

14. l 8 4

 

18. Fmthehatdmmbaedahue,whnmtbetopthuthathmtbemoueﬂeaonthe
deddontohhemmmm Pleuewritetheapmpriatenumberinthespeee
provided:

__Ilest Important __Seeond Neat Input-at __'l'ln'rd Most lupin-tent

PLEASE CONTINUE TO THE NEXT PAGE——>

 

173

 

 

 

COTTON "0

With the help of a cusp of biraineas people, we have identiﬁed the following eight actions that
staugwemmentemddtaketomakeiteaaiertoeenduetbusinusinuichigan. PleaseRANKthe
followingactionsinorderoftheirimportaneetothisbusiness (withlbeingthemostimportant
andeeingtheleastimportanttothisbusinem):

__CendustBenlatqudeua _RepeallinimamWageLaw

__Prwide'l‘aaw __BedueetheBmeaumneyofStateGover-nmem

”Warm-am __Cuaistmtly InheeStateRegalatieu

__Crmductlnsm-anseReferm _I.mpovetbeQImlityefServiceeOﬂeredhyStateGov‘t
Anthmsawdhreeﬁmthtmmebddmhthummmeimpmuntmttnsmthm
theeeeightthatanlisterlabeve?

 

‘I'hiseeetionistodeterminehowuﬁsﬂedthisbuainemiswiththeeontactithuhadwithvmious
state agencies/institutions in the last twelve months. Please circle the number beside each agency
basedonthefollowingeeale:

 

1. MichiganJobsComan-ien NC 1 8 8 4 8
8. IlichiganDspartmmttet'Natu'alReesureee NC 1 8 8 4 8
8. WWWW NC 1 8 8 4 8
4. MichiganDepaltmentet'haaspee-tatiea NC 1 8 8 4 8
8. wehiganOeeupatienalSafetyand HealthAgeney NC I 8 8 4 8
8. Miehigan’l‘ravelnmeau rec I 8 8 4 8
7. liehiganﬂatel’eiiee NC 1 8 8 4 8
8. MiehiganDeparuaentefSeciaISeﬂices NC 1 8 8 4 8
9. IiehiganDepartmmtdApleultue NC 1 8 8 4 8
10%de no I 8 8 4 8
lLﬂichiganDeparuuentetM no 1 8 8 4 8
Illichigaanartmentefldueatien NC 1 8 8 4 8

 

 

174

 

 

 

MON POUR

Inthiaeectionwewanttokncwbowthisbusineasperceivesthequalityofstetegovemment
services. Pleuedrclethenumberbeloweachstatementbasedcnthefollowingecale:

 

‘.' '1‘ ' t" ' p ‘ .. o A. 1 _.il .0 A

Inc-d7 III-ace Undecided Apes Delve-(b
Disagree . 48700
1. Thequahtydsavicmcd‘medbystatemnmmtmeetstheneedsctthisbusinms.
1 8 8 4 8
2. ”Wandammwmnthnthiemwﬂlhwmmabmthe
paednsmIees-viceeithastccder.
l 8 8 4 8 .
8. MWemplcyembmthewenoughabcutthietypecfhmineumbeofany help.
1 8 8 4 8
may:

Repurpmeofthhueﬁonistcﬂndoutmmaboutthenatmeofthiebuainem. Pleasedaclethe
numberwhichbstdeecribesthishrsinemfcreaehpdrcttermahstedbelow. For-example,ifALL
OFﬂIEPEOPLEcmployedbythishtdmasmuemmixctmkmedandhithlyskined
worker-gymnishtdothefotlowing:

Unsﬂlled 1 8 8 4 8 Highly Skilled

 

8 4 8 Brain-Powered

 

8

Repetitive l 8 8 4 8 Creative

ample l 8 4 8 Complicated
W

Unskilled 1 8 8 4 8 Highly Skilled

Generalists 1 8 8 4 8 Specialists

Easily Replaced l 8 8 4 8 Hard To Replace

WorkingOn'niePruisee l 8 8 4 8 WerkingOutOfCarlI-Icme
W

Law Technology 1 8 8 4 8 High Technology

Goods-Pmducing 1 8 8 4 8 Services-Producing

Open '9-to-8" l 8 8 4 8 Open Round 'lhe Clock

Sold locally 1 8 8 4 8 Sold My

Standardized 1 8 8 4 8 Customized
W

Management Driven 1 8 8 4 8 Cum Driven

Bureau-sue l 8 8 4 8 Neu-Bunaua'atic

WWWNMMPAGH>

 

175

 

 

 

 

MON SIX

 

 

Thequestam' inthisseeticnaredutgnsd' tchelpusbetterunder'standandapprcpna'tielyclaasifythis"

business.

1. Yourjobtitle:

2. Towhichdthfdlcwingbudnmecmrsdouthisﬁmhhntﬂplmeheekanthatapply)
_Agrieulture _l-‘ceestry _Fishing _Servicee
_Wholeeale‘l‘rade __Finance' _Inmrance __RealEstatie
_‘I‘ransportaticn _Ccmmumcatacns' '

2; mmmmmmmm' (e.g.,hctelJandaeapentcoltdie):

.4991"

 

 

'I'heownershipct'ttnabusineeeis:
_Other,pleasespedfy:

 

Dceethisbusineeehavelccaticnsinctherhlichigancetmties?_Yee _No
Whatyearwasthisparticularbusineasestabliahed?__

'I'hisbusineesiscpen/operaticnal: _Yeachund __Seascnal
PleaseindicatethenumberchUIJrMEQIHVALEN'l'Sms) thatwerecnpayrollfcrthe
ﬁrstweekinJune,1994and1888. PIeaeecalculateF'I'E’e bytakingthetotalnumbercfhotm
mksdbyAILEMPLOYEES (botht'ull-andpartptimelandthenDl'VIDEBYuI-IOURS.

Panther: FirstWeek
M W

Wouldycuconaiderthisbuaineaeaspartct'theteurismindastry? _Yee __No
Umwhatpaeentagecftctalsalescanbeattributedtotomistdellan?

 

 

Ihaveagreedtovoluntarlly cunplete thisqnestiamaire,aslcngasmynameandthe
. i .

' pertainingtcthisbusineeaankeptsuictlyccnﬁdennal.

 

Signature ‘ Date

mmvmvmmnrmmmmoommmoumom

 

176

 

Appendix C

Reminder Post Card

177

 

DearBusineasOwnerManager:

Werceently sentyoualeuerandquestiounaireaskingforyomparticipetionina
research project being conducted by Michigan State University, in cooperation with
theMichiganCInmberot’Commcrce. 'I'hepm'poseofthereeearchistodetermine
howstategovernmentcanbeueraervcthcneedsofmebusinesscommunity. Your

rcspeneehaiticaltothisraearcbbecauscyourbusinesswasselccwdnnndom
torcpreeenttheviewsofoverm.000Michiganbusinesses. Tohcaparticipantin
thievelyimponantreeearch,simplycompletcandreuunmequeenonnahewe
recentlysenttoyom'husinees.

Ifyouhavealreadyeompletedandreuuncdyour questionnairepleaseaeeeptoin
sincerethanksforyoiupmticipeﬁomlfhychaneeyoudidnotreceivethe
oritgotmisplacedpleasecontactthe‘l‘axPolicyCeuteratMichigan

questionnaire.
State University (517)353-0793), and we will immediately send you another one.

213%; wee

MlStateUnivei-sity ChamhcrofCouuneree

Michigan State University

Tax Policy Center

172 Natural Resources Building
East Lansing, MI 48824-1222

 

 

178

 

 

Appendix D

Regions for Cluster Sampling

179

 

 

 

 

 

 

 

 

 

Key:

1 = Upper Peninsula
2 = Northwest

3 = Northeast

4 = Southwest

5 = Southeast

6 = Metro Detroit

 

180

 

 

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181

 

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