. 2“,: y A . _ . . . .
.. ....§w..am.sa . . . ‘ . . . rnuﬁuw... ‘ ,
a? 3.? V , ‘ ... , m1 , z ‘ z
. .mmﬁ . .. , . . . I’anlx.”
a: D v , «V 1:55: : . V v .
on,
.L». . tuna. ,

.

t n
. 9.71”.»
V 9 . .l.
t u» I???
with: It .Vb.
‘ .Avntvaﬂklthnvcl
. 0.3.1.5) ‘
. 1..
.. .= . .
”may“ . . A
.5

\Iﬁ Efw‘lﬂﬁ
x........_.!.«.., .
urgua a 1
V1,:

gem
. . by“;
.55.. i
1.3. .25». .
.. x»? itﬁwpi ..

x)

a a)?

(3...!
I

 

a
31.50
01!?!

II;

. .\
..: . 2....
VJ... purl? -bn...’....

t.-.!‘r. .n

J
a

I (9!.
. .7 1| .
it}: 1|?

. . A. 1,111,011. . V .IH.‘ u‘k aw it];
a? :ﬁﬁﬁ‘? $3§~§f§ mgﬁg

_, v .2, .1“.
1:1... z 4‘ a. ..

 

 

”ob LIBRARY
Michigan State
University

 

 

 

This is to certify that the
dissertation entitled

A STUDY OF MARKET KNOWLEDGE COMPETENC E
AS A SOURCE OF SBU PERFORMANCE

presented by

DESTAN KANDEMIR

has been accepted towards fulfillment
of the requirements for the

PhD. degree in Marketing and Supply Chain
Management

 

 

  

 

/ Major Pééssor’s Signature

/¢- @jM/' 3005'”

 

Date

MSU is an Affirmatrve Action/Equal Opportunity Institution

 

PLACE IN RETURN Box to remove this checkout from your record.
To AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE

DATE DUE

DATE DUE

 

 

APB 2 .4 2007

 

 

 

 

 

 

 

 

 

 

 

 

 

m

A STUDY OF MARKET KNOWLEDGE COMPETENC E
AS A SOURCE OF SBU PERFORMANCE

By

Destan Kandemir

A DISSERTATION

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

DOCTOR OF PHILOSOPHY
Department of Marketing and Supply Chain Management

2005

ABSTRACT

A STUDY OF MARKET KNOWLEDGE COMPETENCE
AS A SOURCE OF SBU PERFORMANCE

By

Destan Kandemir

This dissertation integrates two streams of literature in strategic management,
namely resource-based theory and the competence-based approach, and provides a link to
marketing. In this context, ﬁrm-speciﬁc resources and activities, and ﬁrm performance
are examined in a single model. The proposed model suggests that resources are
leveraged through activities in order to develop and sustain a competitive advantage. This
advancement will improve our understanding of how ﬁrm-speciﬁc resources and
activities are interrelated to inﬂuence competitive advantage.

In view of this, ﬁrm-speciﬁc marketing resources include relational assets
consisting of retailer/distributor equity, supplier equity, and market orientation culture.
Activities, which involve the market knowledge generation and utilization process,
include market scanning, market information transmission, market information
interpretation, and market knowledge utilization. These market knowledge activities
represent the components of market knowledge competence. Finally, the components of
ﬁrm performance are identiﬁed as customer performance, marketing strategy formulation
and implementation speed, marketing learning performance, and ﬁnancial performance.

The ﬁndings of this dissertation suggest that retailer/distributor equity increases

market knowledge competence; however no association is found for the relationship

between supplier equity and market knowledge competence. Further, market orientation
culture contributes to the level of market knowledge competence.

Market knowledge competence inﬂuences ﬁrm performance in several ways.
First, market knowledge competence enhances customer performance. Second, it
increases the speed of marketing strategy formulation and implementation. Third, market
knowledge competence improves marketing learning performance.

Marketing strategy formulation and implementation speed also produces positive
returns to the ﬁrm. Fast marketing strategy formulation and implementation increases
customer performance, ﬁnancial performance, and marketing learning performance.
Finally, ﬁnancial performance is enhanced by customer and marketing learning
performance. These results and plausible explanations are discussed and future research

directions are provided.

Copyright by
DESTAN KANDEMIR

2005

ACKNOWLEDGEMENTS

I would like to express my sincere thanks and gratitude to my committee
members who provided me with guidance and encouragement throughout the course of
the dissertation. I am very appreciative of Dr. G. Tomas M. Hult, my dissertation chair.
for generously giving me his time and advice, which allowed me to complete this
dissertation. I am truly indebted to Dr. S. Tamer Cavusgil, my dissertation co-chair, for
his guidance and for graciously supporting me through my academic life. I would like to
express my gratitude to Dr. Roger J. Calantone for the methodology expertise that
enabled me to advance the dissertation. I am very thankful to Dr. J. Chris White for his
help and for his thorough comments on this dissertation.

I would like to further extend my thanks to the department’s staff. My sincere
thanks also go to Kathy Waldie for her willingness to always be of help and for her
friendly smile. Finally, I would like to thank the Center for International Business
Education and Research (ClBER) at Michigan State University for its ﬁnancial support of

my dissertation research.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................. viii
LIST OF FIGURES ................................................................................ ix
CHAPTER I
BACKGROUND ..................................................................................... l
1.1 The Role of Finn-Speciﬁc Resources and Activities in Marketing Strategy ......... l
1.2 Research Objectives and Questions ........................................................... 3
1.3 Importance of Research Study ................................................................. 5
1.4 Organization of the Dissertation .............................................................. 7
CHAPTER II
THEORETICAL FOUNDATIONS ............................................................... 8
2.1 The Evolution of the Resource-Based Theory ............................................... 8
2. l .l Resource-Based Theory in Relation to Strategy .................................... 8
2.1.2 Resource-Based Theory in Relation to Industrial Organization:
Porter‘s Competitive Strategy Framework ........................................ l l
2.2 The Resource-Based Theory of Strategy ................................................... 13
2.3 The Competence-Based Approach to Strategy ............................................ 18
2.4 Resources ....................................................................................... 20
2.5 Market Knowledge Activities ................................................................ 31

CHAPTER III

MODEL DEVELOPMENT AND RESEARCH HYPOTHESES ........................... 4]
3.1 Relational Assets and Market Knowledge Competence .................................. 44
3.2 Market Orientation Culture and Market Knowledge Competence ...................... 45
3.3 Firm Performance Outcomes ................................................................. 47
3.3.l Outcomes of Market Knowledge Competence ................................... 50
3.3.2 Outcomes of Marketing Strategy Formulation and Implementation Speed... 53
3.3.3 Customer Performance and Financial Performance .............................. 55
3.3.4 Marketing Learning Performance and Financial Performance ................. 56

vi

CHAPTER IV

RESEARCH DESIGN AND METHODOLOGY ............................................. 57
4.1 Sampling Frame ................................................................................ 57
4.2 Data Collection Process ....................................................................... 58
4.3 Constructs and Measure Development Procedures ........................................ 60
4.3.1 Resources .............................................................................. 61
4.3.1.1 Relational Assets ............................................................. 61
4.3.1.2 Market Orientation Culture ................................................. 63
4.3.2 Market Knowledge Competence .................................................... 67
4.3.3 Fimi Perfomtance .................................................................... 72
CHAPTER V
ANALYSIS AND FINDINGS .................................................................... 76
5.] Evaluation of Data Quality ................................................................... 76
5.2 Measurement Model .......................................................................... 78
5.3 Measurement Model Validation via Bootstrapping ....................................... 84
5.3.1 Bootstrap Method ..................................................................... 85
5.3.2 Bootstrapping Measurement Model ................................................ 88
5.4 Hypothesis Testing ............................................................................. 91
C I IAPTER VI
CONTRIBUTIONS TO THEORY AND MANAGEMENT ................................ 98
6.1 Discussion of the Results ..................................................................... 98
6.l.l Relational Assets and Market Knowledge Competence ......................... 98
6.1.2 Market Orientation Culture and Market Knowledge C om petence ............. 99
6.1.3 Firm Performance Outcomes ........................................................ 99
6.2 Contributions to Theory ..................................................................... 101
6.3 Contributions to Management .............................................................. 103
6.4 Limitations and Additional Future Research Directions ................................. 105
6.5 Conclusion ...................................................................................... 107
APPENDICES ..................................................................................... l09
Appendix: Final Measurement Items ............................................................ 1 l0
BIBLIOGRAPHY ................................................................................ 1 l3

vii

Table I:

Table 2:

Table 3:

Table 4:

Table 5:

Table 6:

Table 7:

Table 8:

Table 9:

LIST OF TABLES

Resources .................................................................................. 2
Market Knowledge Activities ....................................................... 33
Summary of the Hypotheses ......................................................... 43
Sample Characteristics ............................................................... 77
Non-Response Bias ..................................................................... 78
Results of the Measurement Model Analysis ..................................... 80
Results of the Bootstrapped Measurement Model Analysis ................... 89
Evaluation of Fit lndices for Measurement Model ............................. 91
Results of the Path Model Analysis ................................................ 96

viii

LIST OF FIGURES

Figure 1: Theoretical Model of Resources, Market Knowledge Activities

and Firm Performance ............................................................... 3
Figure 2: Porter’s (1991) Activity Based-View of Competitive Advantage ........... 13
Figure 3: Hamel and Prahalad’s (1994) Competence-Based Framework ............. 20
Figure 4: The Hypothesized Model of Market Knowledge Competence .............. 42
Figure 5: Sampling Error versus Nonsampling Error for CF I and AGFI ............ 86
Figure 6: Hypothesis Test Results ............................................................. 93

ix

CHAPTER 1
1.1 The Role of F irm-Specific Resources and Activities in Marketing Strategy

Research in marketing strategy has been inﬂuenced by resource-based theory
(Day and Wensley 1998; Hunt and Morgan 1995). Strategy researchers propose that
resources are primary sources for competitive advantage (Amit and Schoemaker I993;
Barney 1991; Grant 1991). This perspective, grounded in the resource-based theory, has
also recognized the role of marketing-speciﬁc resources such as brands and customer and
channel relationships in gaining and sustaining a competitive advantage. For example,
marketing scholars have examined the competitive effects of market knowledge assets
(Glazer 1991), market-based assets (Srivastava, Shervani, and Fahey 1998), and
relational resources (e.g., brands and sales forces) (Capron and Hulland 1999).

Other strategy researchers, under the competence-based approach, have focused
on the value of coordinated deployment of resources (Prahalad and Hamel 1990; Reed
and deFilippi 1990; Teece, Pisano, and Shuen 1997). This approach gives attention to the
deployment or implementation of resources. The key task of management is to maintain
the effectiveness of the ﬁrm’s competence building and leveraging processes to attain
ﬁrm-speciﬁc goals (Sanchez, Heene, and Thomas 1996). Accordingly, marketing-speciﬁc
competences should enable the ﬁrm to attain a competitive position in the served
markets, and may include such activities as market knowledge management, customer
relationship management, and channel bonding (Day 1994; Li and Calantone 1998;
Srivastava, Shervani, and Fahey 1998).

2 Although resource-based theory and the competence-based approach have

evolved separately. the value of integration of resources and competences (i.e., activities)

is being recognized by both marketing and strategy researchers (Mahoney 1995;
Makadok 2001; Slotegraaf, Moorman, and Inman 2003; Srivastava, Shervani, and F ahey
1998). Makadok (2001) suggests that resources and activities should be synthesized
together in order to achieve a complete understanding of how ﬁrms generate and sustain
competitive advantage. Using the resource-based view, Capron and Hulland (1990)
examine how ﬁrms use key marketing resources across merging ﬁrms after horizontal
acquisitions and the impact of resource deployment on ﬁrm performance. The ﬁndings of
their study suggest that immobility is a critical determinant of resource redeployment.
Slotegraaf, Moorman, and Inman (2003) investigate how ﬁrm-speciﬁc resources
inﬂuence the effectiveness of a ﬁnn’s market deployment, which is the degree of action
to generate a market response, and ﬁnd that accumulated organizational resources
increase the returns on market deployment actions.

This dissertation integrates resource-based theory and the competence-based
approach, and examines how ﬁrm-speciﬁc resources related to marketing are leveraged
via market knowledge activities to create superior ﬁrm performance. Here, it is proposed
that market knowledge activities in the context of marketing strategy formulation and
implementation link ﬁrm-speciﬁc resources to ﬁrm performance. As illustrated in Figure
1, by examining resources and activities in a single model, it is possible to assess whether
the level of resources inﬂuence the intensity of activities. Then, the effects of market

knowledge activities on ﬁrm performance are explored.

Figure 1: Theoretical Model of Resources, Market Knowledge Activities and
Firm Performance

 

 

 

Market Firm
K 1 d
Resources ’ Auctixiiieie . Performance

 

 

 

 

 

 

 

 

 

1.2 Research Objectives and Questions

Based on the discussion above, the research objectives of this dissertation are as
follows:

The ﬁrst objective is to investigate how ﬁrm-speciﬁc resources are leveraged via
market knowledge activities, which, in turn, will affect ﬁrm performance. Both marketing
and strategy researchers have overlooked the activities stage and focused on the effects of
resources on ﬁrm performance. Porter (1991, p. 108) suggests, “Resources are not
valuable in and of themselves, but because they allow ﬁrms to perform activities that
create advantages in particular markets. Resources are only meaningful in the context of
performing activities to achieve certain competitive advantages.” This dissertation
identiﬁes resources and activities in the context of marketing strategy formulation and
implementation, and explores the role that market knowledge activities play in achieving
a superior ﬁrm performance.

In association with the ﬁrst objective, resources and activities speciﬁc to
marketing are identiﬁed. In examining ﬁrm-speciﬁc resources, this dissertation focuses

on intangible resources. Intangible resources are composed of both strategic assets and

capabilities. Then, this dissertation conceptually and empirically distinguishes among
strategic assets, capabilities, and activities.

The second objective is to identify what type of capabilities might facilitate
market knowledge activities. Market orientation culture is identiﬁed as a cultural
capability, which is an important source of competitive advantage. The distinction
between market orientation culture and market oriented behaviors has been widely
recognized by market orientation scholars. However, there is little empirical research that
contributes to the measurement of market orientation as culture. Further, the effects of
market orientation culture on market knowledge activities are examined.

The third objective is to identify market knowledge activities and examine their
contribution to market knowledge competence, which is deﬁned as a market knowledge
generation and utilization process. Then, the implications of market knowledge
competence for ﬁrm performance are examined.

The issues that will be considered in this dissertation are summarized in the
following research questions:

1. How are ﬁrm-speciﬁc marketing resources leveraged through market knowledge
activities? Are there meaningful distinctions among strategic assets, capabilities,
and activities that are speciﬁc to marketing?

2. What kind of organizational culture facilitates market knowledge competence?
Are there speciﬁc values and beliefs associated with customers, competitors, and
retailers/distributors?

3. Does market knowledge competence inﬂuence competitive advantage? What

market knowledge activities contribute to market knowledge competence?

1.3 Importance of Research Study

Based on the research objectives, this study contributes to the literature in several
ways.

Initially, ﬁrm resources and market knowledge activities are examined in a single
model by integrating resource-based theory and the competence-based approach. This
dissertation investigates the direct effects of resources on activities, which, in turn, are
expected to contribute to ﬁrm performance. However, most research in marketing has
examined the direct effects of resource levels or activities on ﬁrm performance.

Moreover, marketing researchers have started only recently to apply the resource-
based framework in analyzing the theory’s implications in marketing (e.g., Capron and
Hulland 1999; Hunt and Morgan 1995; Srivastava, Shervani, and F ahey 1998). The
primary focus has been on explaining the relationship between performance and sources
of competitive advantage by developing and applying core constructs including market
orientation (Deshpandé, Farley, and Webster 1993; Kohli and Jaworski 1990; Narver and
Slater 1990), marketing resources and skills (Calantone and di Benedetto 1988; McKee
et a1. 1992), market-based assets (Srivastava, Shervani, and Fahey 1998) and market
knowledge (Glazer 1991). However, these studies do not provide a link back to resource-
based theory (e.g., Srivastava, F ahey, and Christensen 2001). Further, it has been
suggested that specifying the distinctive advantages of different types of resources may
provide precision to resource-based theory and the competence-based approach (Miller
and Sharnsie 1996). Accordingly, this dissertation integrates both streams of research by
providing a link to marketing. Further, a distinction is made among strategic assets,

capabilities, and activities.

This study also attempts to contribute to market orientation literature by
conceptualizing and operationalizing market orientation from a culture perspective.
Although the distinction between market orientation culture and market oriented
behaviors has been recognized (Matsuno, Mentzer, and Rentz 2000; Slater and Narver
1995), there is little empirical research that operationalizes market orientation as culture.
Homburg and Pﬂesser (2000), for example, operationalizes market oriented culture as
composed of values, norms, artifacts, and behaviors, and suggests market oriented
behaviors are inﬂuenced by artifacts and norms. Though they consider values and
behaviors as distinct constructs, their operationalization of market orientation culture also
covers behaviors. Another study by Gray et a1. (1998) conceptually distinguishes between
market orientation culture and market oriented behaviors; however, it does not provide
new scales for market orientation from a culture perspective. Instead, their study links
Narver and Slater’s (1990) market orientation scale considered as culture with the
behavioral market orientation scale of Jaworski and Kohli (1993). This study will
advance our understanding of how culture affects a ﬁrm’s market knowledge activities by
developing new scales for market orientation culture.

Next, the resource-based theory does not tell us how differential managerial
cognitions contribute to competitive advantage. The identiﬁcation of market knowledge
activities recognizes the role of managerial cognition, and complements the cognitive gap
in the resource-based theory of strategy.

Finally, the effects of market knowledge activities on ﬁrm performance are
examined by implementing a balanced scorecard approach. This enables the ﬁrm not only

to assess their performance in the external environment, but also to examine their

performance in the internal environment, thereby providing a more balanced approach for
evaluating ﬁrm performance.
1.4 Organization of the Dissertation

This dissertation is divided into six chapters. Chapter I has provided the research
objectives and questions and explained the importance of the research study. Chapter 11
presents the theoretical foundation for the present research and reviews the relevant
conceptual and empirical literature from, primarily, the areas of marketing, management,
economics, and sociology. Primary topics include the resource-based theory of strategy.
the competence-based approach to strategy, and organizational learning.

Chapter III presents the augmented hypothesized model and supporting literature.
Chapter IV presents the research design and methodology, including an explanation of
the study design and descriptions of the scales used to operationalize the constructs.
Chapter V reports the ﬁndings of the research. Chapter VI discusses the research
ﬁndings, provides a detailed discussion of theoretical and managerial contributions
structured around the research questions and addresses the limitations of research and

suggests directions for future research.

CHAPTER II
THEORETICAL FOUNDATIONS

Based on the discussion in Chapter I, the competitive advantage of a ﬁrm is
dependent on two factors: (1) resources consisting of strategic assets and capabilities, and
(2) market knowledge activities. Chapter II explores the theoretical and empirical
foundations of the constructs and relationships overviewed in Chapter I and included in
the hypothesized model developed in Chapter 111. As such, this chapter is organized
around three main areas of discussion: (1) Porter’s competitive strategy framework, (2) a
resource-based theory of strategy, and (3) a competence-based approach to strategy.
2.1 The Evolution of the Resource-Based Theory

Two major research streams are intertwined in the resource-based framework: (1)
mainstream strategy research and (2) the industrial organization approach to strategy
(e.g., Foss 1997; Hunt 2000; Mahoney and Pandian 1992; Porter 1991).
2.1.1 Resource-Based Theory in Relation to Strategy

The intellectual roots of the resource-based theory of strategy are found in the
mainstream of American management thinking, which started in the late 19503 including
the works of Selznick (1957), Penrose (1959), Chandler (1962), Ansoff (1965), Andrews
(1980), and Rumelt (1984). Chandler (1962, p. 42) deﬁnes strategy as “the determination
of the basic long-term goals and objectives of an enterprise, and the adoption of courses
of action and the allocation of resources necessary for carrying out these goals.”
Accordingly, strategic management can be described as a continuous search for rents by:
analyzing the ﬁrm’s strengths and weaknesses (Andrews 1980), deﬁning the ﬁrm’s use of

synergy and competitive advantage to develop new markets and products (Ansoff 1965),

building upon the distinctive competence of a ﬁrm (Selznick 1957), and evaluating the
ﬁrm’s method of expansion (Chandler 1962).

The resource-based view integrates the insights from the traditional concept of
strategy to explain how ﬁrms generate rents (Andrews 1980; Ansoff 1965). For a
successful formulation and implementation of corporate strategy to generate rents, the
assessment of resources and capabilities is very important (Andrews 1980). In view of
that, a ﬁrm ﬁrst identiﬁes opportunities and threats in its environment, and then evaluates
its strengths and weaknesses with the resources available, and ﬁnally, it matches
opportunity and corporate capability at an acceptable level of risk. The capabilities may
inherent in (l) accumulated experience in making and/or marketing a product line or a
service; (2) the developing strengths and weaknesses of the individuals comprising the
organization; (3) the degree to which individual capability is effectively applied to the
common task; and (4) the quality of coordination of individual and group effort (Andrews
1980). The ﬁrm’s unique capabilities such as technical know-how, market experience,
and managerial skills are important sources of heterogeneity that may result in sustained
competitive advantage (Richardson 1972). It is the indivisibility, specialized use, and
heterogeneity of the productive services available or potentially available from its
resources that give each ﬁrm its unique character (Penrose 1959). Accordingly, a ﬁrm
may achieve rents not because it has attractive resources, but rather the ﬁrm’s distinctive
competence (Selznick 1957) involves making the best use of its existing resources. As
noted by Selznick (1957), the creativity role of the leader is to guide the
institutionalization process in which the ﬁrm takes on a special character and becomes

competent in certain activities.

Penrose’s theory of ﬁrm growth is believed to be central to a resource-based
theory (Conner 1991; Foss 1997; Mahoney and Pandian 1992). Penrose (1959, p. 31)
describes a ﬁrm as “both an administrative organization and a collection of productive
resources.” The productive resources consist of physical and human resources, the use of
which is determined by administrative decisions. The physical resources of a ﬁrm include
tangible things (e.g., plant, equipment, land, raw materials, semi-ﬁnished goods, etc.),
whereas human resources contain unskilled and skilled labor, clerical, administrative,
ﬁnancial, legal, technical and managerial staff. Penrose (1959) makes a crucial distinction
between resources and capabilities (services). Accordingly, resources consist of a bundle
of potential services, and are independent of their use, while capabilities (services) are a
function of the way in which they are used, and imply a function or an activity.
Capabilities can be regarded as contributions these resources can make to the productive
operations of the ﬁrm.

The theory of ﬁrm growth is developed as a theory of the internal growth of a
ﬁrm, emphasizing the analysis of internal resources (Penrose 1959). The growth of a
ﬁrm, which can be described as an administrative and planning organization, requires
planning that implies the organization of resources in order to accomplish the purpose in
some desired manner (Penrose 1959). The role of a ﬁrm’s managerial and entrepreneurial
services is important to seeing and acting upon productive opportunities for the proﬁtable
growth of the ﬁrm (Chandler 1962; Penrose 1959). Entrepreneurial decisions and actions
refer to those administrative activities that involve long range planning and appraising
and coordinating the activities of the enterprise, and affect the allocation or reallocation

of resources (Chandler 1962). Thus, it is the capacities of the existing managerial and

10

entrepreneurial services of the ﬁrm that set limits to ﬁrm growth. Because an
administrative group is viewed as a collection of individuals who have had experience
working together, such management cannot be bought in the marketplace.

In addition, from a resource perspective, Penrose (1959) examines the motivation
for expansion. Resources are necessary to achieve productive services that provide the
needed “inputs” for the production. However, resources must be acquired as a bundle of
services due to their “indivisibility,” even if a ﬁrm needs only a single service. As a result
of the unused productive services, a ﬁrm has an incentive to expand if they are used
proﬁtably. However, in the process of expansion the ﬁrm will continue acquiring further
resources that vary in the amount and type of service they can provide. The use of
productive resources may require diversiﬁcation of output because further expansion may
not be warranted by market conditions, and thus specialization can take place based on
the extent of output. As a ﬁrm grows in size, it will reorganize its resources to take
advantage of the specialization, which, in turn, will lead to expansion and diversiﬁcation
to fully utilize unused productive services (Penrose 1959). To achieve optimal growth,
the ﬁrm should create a balance between exploitation of its resources and development of
new ones (Penrose 1959; Rubin 1973; Wernerfelt 1984).

2.1.2 Resource-Based Theory in Relation to Industrial Organization: Porter’s
Competitive Strategy Framework

Within the classical industrial organization literature, the structure-conduct-
performance (SCP) paradigm has been the most popular theoretical framework (Bain
1956; Mason 1939). The SCP framework suggests that industry structure determines a
ﬁrm’s conduct (e.g., strategy), which inﬂuences performance. Because ﬁrm conduct is

constrained by industry forces, management’s role can be ignored. Porter’s (1980)

11

competitive strategy ﬁamework emerged due to the limitations of IO for strategy
formulation. The industry-based theory of strategy turns 10 economics “upside down.”

As suggested by Porter (1980, p. 4), “the goal of the competitive strategy for a
business in an industry is to ﬁnd a position in the industry where the company can best
defend itself against competitive forces or can inﬂuence them in its favor.” The modiﬁed
framework departs markedly from the Bain/Mason IO paradigm in three ways (Porter
1980, 1985): (1) it focuses on ﬁrm performance rather than industry performance; (2)
industry structure is partly exogenous, and partly subject to inﬂuence by ﬁrm actions; and
(3) it explicitly recognizes that ﬁrm success is a ﬁmction of both the attractiveness of the
industry in which the ﬁrm competes and its relative position in that industry.

The underlying structure of the industry is reﬂected in the strength of ﬁve
competitive forces: bargaining power of suppliers, bargaining power of buyers, threat of
substitute products, threat of new entrants, and rivalry among current competitors (Porter
1980). The structural analysis is a crucial step in competitive strategy formulation. The
success of a ﬁrm, holding industry structure constant, can arise from a ﬁrm’s ability to
cope with the ﬁve forces and build an attractive relative position. A ﬁrm can achieve an
attractive relative position, and thus superior proﬁtability, either by establishing a cost
base lower than the competition or by differentiating its product or service that is
perceived industrywide as being unique (Porter 1980). Hence, a relative attractive
position can stem from three primary types of competitive advantage: (1) cost leadership,
(2) differentiation, and (3) focus. In Porter’s early work, the manager’s role was to
analyze industry structures, identify attractive industries and superior positions within

them, and take these positions through generic strategies. Porter’s framework views

12

strategy as ﬁt since industry structure is given and strategy is thus choosing one of the
three generic strategies.

The goal of any generic strategy is to create “customer value,” referring to the
amount customers are willing to pay for what a ﬁrm provides them. A ﬁrm’s strategy
deﬁnes its conﬁguration of activities and the relationships among them. Hence, activities
provide the bridge between strategy and implementation. Speciﬁcally, Porter (1985)
argues that for a ﬁrm to gain competitive advantage, it should implement its strategy by
performing all the strategically important activities in its value chain (e.g.,
manufacturing, marketing, and distribution) at a lower cost or better than its competitors
(Porter 1985). Because the conﬁguration of each activity embodies the way that activity
is performed, competencies, then, become part of activities. Porter’s (1991) activity-
based view (see Figure 2), which emphasizes the “discrete activity” as the basic unit of
competitive advantage, provides the link to the notions of the competence-based
approach strategy.

Figure 2: Porter’s (1991) Activity Based-View of Competitive Advantage

Attractive Relative Position
U

Drivers :> Activities 3 Competitive Advantage :> Firm Performance

ll

Attractive Industry Structure
(5 competitive forces)

2.2 The Resource-Based Theory of Strategy
The resource-based theory can be seen as complementary to Porter‘s (1980)

competitive strategy framework (Amit and Schoemaker 1993; Mahoney and Pandian

l3

1992; Miller and Shamsie 1996; Peteraf 1993; Porter 1991). While Porter’s competitive
strategy framework views the ﬁrm as a bundle of activities, resource-based theory of
strategy views the ﬁrm as a bundle of resources. As noted by Wemerfelt (1984, p. 171),
“products and resources are two sides of the same coin.” From a resource perspective, it
is possible to ﬁnd the optimal product-market activities by specifying a resource proﬁle
for a ﬁrm. Conversely, from a product-market perspective, it is possible to identify the
minimum resource commitments by specifying the size of a ﬁrm’s activity.

In the strategic management literature, the relationship between a ﬁrm’s resources
and its proﬁtability was ﬁrst presented formally in the work of Wemerfelt (1984). Firm
resources are said to be the sources of competitive advantage (Amit and Schoemaker
1993; Barney 1991; Grant 1991; Mahoney and Pandian 1992; Miller and Shamsie 1996;
Penrose 1959; Peteraf 1993; Rumelt 1984, 1991; Wemerfelt 1984). The individual
resources of the ﬁrm may include all assets, capabilities, organizational processes,
information, and knowledge, which are tied semipermanently to the ﬁrm and enable it to
conceive of and implement value-creating strategies that improve its efﬁciency and
effectiveness in the marketplace (Amit and Schoemaker 1993; Barney 1991; Mahoney
and Pandian 1992; Miller and Shamsie 1996; Peteraf 1993; Wemerfelt 1984).

A resource-based framework primarily focuses on the identiﬁcation of (1) sources
likely to generate rents and (2) characteristics of these sources to which long-lived rents
may accrue. The returns to a ﬁrm’s resources depend on the sustainability of competitive
advantage. To understand the sources of sustained competitive advantage, it is necessary
to distinguish between competitive advantage and sustained competitive advantage. The

basis for analyzing the competitive advantage of a ﬁrm is the “value” (Porter 1985).

14

Value is the amount customers are willing to pay for what a ﬁrm provides them.
Competitive advantage arises from the value that exceeds the costs involved in providing
a product or a service. A ﬁrm is said to achieve a unique position in relation to its
competitors by offering superior value embedded in either low prices or unique beneﬁts
(Porter 1985).

Not all ﬁrm resources hold the potential of generating superior value and enabling
sustained competitive advantages. “A ﬁrm is said to have a competitive advantage or a
sustained competitive advantage when it is implementing a value-creating strategy not
simultaneously being implemented by any current or potential competitors” (Barney
1991, p. 102). The resource-based theory contributes to our understanding of how
resources are applied and combined, what makes competitive advantage sustainable, and
the origins of heterogeneity. In chronological order, the notable contributions to the
resource-based framework include Teece (1980); Lippman and Rumelt (1982); Rumelt
(1984); Wemerfelt (1984); Barney (1986, 1991); Dierickx and C001 (1989); Reed and
DeFillippi (1990); Castanias and Helfat (1991); Conner (1991); Grant (1991); Mahoney
and Pandian (1992); Amit and Schoemaker (1993); Peteraf (1993); Black and Boal
(1994); Chi (1994); and Miller and Shamsie (1996). While each study offers a distinct
contribution, there is also considerable overlap of ideas.

In analyzing sources of competitive advantage, the resource-based framework
substitutes two assumptions (Barney 1991): (1) ﬁrms within a strategic group may be
heterogeneous with respect to the strategic resources they control, and (2) resources may
not be perfectly mobile, and thus resource heterogeneity can be long-lasting. The

resource-based model, then, evolved in the direction of recognizing resource immobility

15

or speciﬁcity (Rumelt 1991). In investigating the contribution of the resource-based
framework to competitive advantage, this dissertation adopts a parsimonious model
developed by Peteraf (1993). Accordingly, for ﬁrm resources to contribute to value
generation, they must meet four conditions: (1) heterogeneity, (2) imperfect mobility, (3)
ex ante limits to competition, and (4) ex post limits to competition.

Resource heterogeneity and imperfect mobility are the primary assumptions of the
resource-based model (Barney 1991). In industrial organization theory, Caves and Porter
(1977) extend the “entry barrier” concept (Bain 1956) by deﬁning “mobility barriers.”
Mobility barriers serve to isolate groups of similar ﬁrms in a heterogeneous industry,
while entry barriers isolate industry participants from prospective entrants. The argument
here is that if there are strong mobility barriers, ﬁrms are able to achieve competitive
advantage even if the ﬁrms within a group are homogeneous. The resource-based view
does not reﬁite mobility barriers; however, it suggests that these barriers only become
sources of sustained competitive advantage if current and potentially competing ﬁrms are
heterogeneous in terms of the strategically relevant resources they control and if these
resources are not perfectly mobile (Barney 1991).

Resource heterogeneity implies that ﬁrms of varying assets and capabilities are
able to implement a value-creating strategy not being implemented by rivals and compete
successfully in the marketplace (Peteraf 1993). Resource immobility implies that
resources cannot be traded in the marketplace. Because most assets and capabilities are
not freely traded (Dierickx and C001 1989) or are less valuable to other users for several
reasons, such as geographical immobility, imperfect information, ﬁrm speciﬁcity,

cospecialized assets, and tacitness of capabilities (Amit and Schoemaker 1993; Barney

16

1991; Grant 1991; Nelson and Winter 1982; Teece 1986; Williamson 1985), they remain
in the ﬁrm and are available for long term-use.

To preserve the durability of heterogeneity, ex post limits to competition must
exist (Peteraf 1993). The resource-based view of the ﬁrm has underlined imperfect
substitutability and imperfect imitability as the sources of sustainable competitive
advantage (e.g., Amit and Schoemaker 1993; Barney 1991; Grant 1991). Porter’s (1980)
ﬁve competitive forces include substitutability as well. Imperfect substitutability implies
that the potential of resources to sustain value is enhanced if competitors do not possess
similar resources that enable them to conceive of and implement the same strategies, or
do not hold resources that are strategically equivalent.

Imperfect imitability has been addressed in the forms of “causal ambiguity”
(Lippman and Rumelt 1982; Reed and DeFillippi 1990), “isolating mechanisms” (Rumelt
1984), and “replicability” (Grant 1991; Teece, Pisano, and Shuen 1997). A competitive
advantage is sustained if it continues to exist after efforts to imitate that advantage have
ceased (Lippman and Rumelt I982; Rumelt 1984). The theory of “uncertain imitability "
addresses both the origins of interﬁrrn differences and the mechanisms that impede their
elimination through competition and entry (Lippman and Rumelt 1982). Because
competitors fail to understand the link between ﬁrm performance and its resource
attributes, causal ambiguity creates barriers to imitation (Lippman and Rumelt 1982).
Rumelt (1984) extended “uncertain imitability” and used the term “isolating
mechanisms” to refer to phenomena that make competitive positions stable and
defensible. Isolating mechanisms are described as an analog of Caves and Porter’s (1977)

mobility barriers. The isolating mechanisms consist not only of causal ambiguity but also

17

other elements such as specialized assets, unique resources, patents and trademarks,
reputation and image, buyer switching costs, consumer or producer learning, and special
information.

Finally, there also must be ex ante limits to competition for a ﬁrm to enjoy
sustained above-normal returns (Peteraf 1993). This implies that before a ﬁrm establishes
a superior resource position, there must be limited competition for that position (Peteraf
1993). The general attractiveness of a resource is only a necessary but not a sufficient
condition to support a resource position barrier. Wemerfelt (1984, p. 175) argues that
“ﬁrms need to ﬁnd those resources which can sustain a resource position barrier, but in
which no one has currently one.” The limits to ex ante competition keep costs from
offsetting the rents.

2.3 The Competence-Based Approach to Strategy

Similar to the resource-based theory, the competence-based approach to strategy
also focuses on the “internal factors” in explaining ﬁrms’ performance differentials. The
term “distinctive competence” ﬁrst introduced by Selznick (1957) refers to those things
that an organization does especially well in comparison to its competitors. The
intellectual roots of competence-based theory can be found in the works of Snow and
Hrebiniak (1980), Nelson and Winter (1982), Hitt and Ireland (1985), and Prahalad and
Hamel (1990). In fact, Wemerfelt (1995, p. 171), one of the founders of the resource-
based theory, credits Prahalad and Hamel’s (1990) work as “single-handedly responsible
for diffusion of the resource-based view into practice.” Further, works that have
stimulated the advancement of the competence-based theory can be found in the

conceptual and empirical articles of: Lado, Boyd, and Wright (1992), Leonard-Barton

18

(1992), Day (1994), Henderson and Cockburn (1994), Aaker (1995), Teece, Pisano, and
Shuen (1997), Sanchez, Heene, and Thomas (1996), Sanchez and Heene (1996, 1997), Li
and Calantone (1998), and Eisenhardt and Martin (2000) representing both management
and marketing domains.

Resource-based theory and the competence-based approach are complementary.
While for the resource-based theory a ﬁrm is a portfolio of resources (e.g., physical,
human, and organizational) (Barney 1991), for the competence-based approach a ﬁrm is
both a collection of products or SBUs and a collection of competences (Prahalad and
Hamel 1990). The competence-based approach appears to be a more actionable version
of the resource-based theory, with more emphasis on the sources of competitive
advantage within the ﬁrm.

In contrast to Porter’s (1980, I985) “outside-in” and deterministic view of
strategy as ﬁt, Hamel and Prahalad’s (1989) view of strategy as stretch is voluntaristic
and “inside-out.” To compete for the future, Hamel and Prahalad’s (1994) view of
strategy requires industry foresight and competence leveraging as depicted in Figure 3.
Industry foresight implies that managers should develop a long-term strategic intent by
questioning what new types of beneﬁts should be provided to customers and what new
assets and capabilities should be developed to offer those beneﬁts to customers.
Competence leveraging is then the coordinated use of an organization’s assets and
capabilities in creating customer value. The competitive advantage, in the long run, is
derived from an ability to build and leverage competences at lower cost and more

speedily than competitors (Prahalad and Hamel 1990). Further, their view stresses the

19

dynamic nature of competences suggesting that competences should be nurtured and
protected.

Figure 3: Hamel and Prahalad’s (1994) Competence-Based Framework
Industry Foresight :> Competence Leveraging :> Value to Customers

2.4 Resources

Resources are deﬁned as the tangible or intangible “factors” owned or controlled
by the ﬁrm (Amit and Schoemaker 1993; Black and Boal 1994; Hall 1992), which enable
the ﬁrm to produce efﬁciently and/or effectively marketing offerings that have value for
some market segments (Barney 1991; Hunt and Morgan 1995). In order to have a set of
heterogeneous and valuable resources, a ﬁrm must either acquire them or develop them.
In examining the ﬁrm’s resources, this dissertation focuses on intangible resources that
are speciﬁc to marketing. Intangible resources can be classiﬁed as assets and capabilities
including skills, knowledge, managerial capabilities, and reputation (Barney 1991; Hall
1992). As summarized in Table 1, the identiﬁed intangible resources that are critical for a
ﬁrm’s market knowledge management include relational assets and market orientation

culture.

20

Table 1: Resources

 

 

Resources: Deﬁnition:
' Strategic Relational assets include retailer/distributor equity and supplier
assets equity, which are the outcomes of the strategic relationships between

a ﬁrm and key retailers/distributors and suppliers (Hunt and Morgan
1995; Srivastava, Shervani, and Fahey 1998).

 

 

' Capability Market orientation culture is the organization-wide shared values
and beliefs that ( 1) put the customer’s interest ﬁrst, while not
excluding those of all other stakeholders, and (2) place a high degree
of value on the market analysis for creating superior customer value
(Slater and Narver 1995).

 

 

Strategic assets refer to the factors that are acquired, developed, and leveraged for
marketplace purposes (Amit and Schoemaker 1993; Dierickx and C001 1989; Srivastava,
Shervani, and F ahey 1998). These intangible resources are primarily external to the ﬁrm
and gain their value in the marketplace. Strategic assets are owned by the ﬁrm, but do not
appear on the balance sheet. Yet stocks of these assets can be developed, nurtured,
leveraged, and valued. They may include patents, trademarks, reputation, brand equity, or
channel equity. The strategic value of marketing relationships to the ﬁrm’s market
knowledge activities has been recognized by marketers (Hunt and Morgan 1994;
Sawhney and Zabin 2002; Srivastava, Shervani, and F ahey 1998). In the current context,
retailers/distributors and suppliers are viewed as primary partners for the development
and maintenance of marketing channel relationships. Thus, retailer/distributor and
supplier equity are classiﬁed as strategic assets, which possess the characteristic of
“belongingness” (Hall 1992).

Another important intangible resource identiﬁed in this dissertation is market

orientation culture, which is classiﬁed as an organizational capability (Barney 1986; Hunt

21

 

 

and Morgan 1995; F iol 1991). The essence of organizational capability is the integration
of the specialized knowledge of a number of individuals to create value based upon unity
between organizational members implying stability, proximity, and social relationships
(Grant 1996). Cultural capability consisting of cognitive processes applies to the
organization as a whole and incorporates the values and beliefs diffused among
employees that build up the organization (Hall 1992). In marketing, market orientation
has been recognized as a primary cultural capability in achieving a competitive advantage
in the marketplace (Day 1994; Deshpandé and Webster 1989; Slater and Narver 1995).
Because the ﬁrm’s market orientation culture is embedded in organizational routines
(Nelson and Winter 1982), it holds the characteristics of speciﬁcity, complexity, and
tacitness, and thus it is hard to imitate (Reed and DeFillippi 1990). This implies that the
market orientation culture is built and controlled by the ﬁrm rather than bought in the
factor markets and differentiates it from other ﬁrms. The market orientation culture
determines which market knowledge activities are deﬁned as central, distinctive, and
enduring to the ﬁrm. Thus, it can be a source of competitive advantage if it enables the
ﬁrm to effectively and efﬁciently conduct activities associated with its marketing strategy
formulation and implementation.
Relational Assets

Relational assets arise from the ﬁrm’s interactive relationships with key
marketing channel partners (e. g., distributors, retailers, suppliers, and other strategic
partners) (Hunt and Morgan 1995; Srivastava, Shervani, and Fahey 1998). They are
intangible and, hence they cannot be inventoried or divided physically into speciﬁc parts.

In contrast to tangible assets (e.g., plant, equipment), the value of these intangible assets

22

to a ﬁrm is harder to measure and less visible (Srivastava, Shervani, and F ahey 1998).
Relational assets do not appear on a ﬁrm’s balance sheet, rather their value is derived
from their use by the ﬁrm.

Speciﬁcally, relational assets are identiﬁed as retailer/distributor equity and
supplier equity (Hunt and Morgan 1995; Sawhney and Zabin 2002; Srivastava, Shervani,
and Fahey 1998). Equity is deﬁned as the value of the invested resources (Dorsch et a1.
2001). The resources that are speciﬁc to marketing channel relationships can take
different forms including trust, commitment, status, and knowledge (Foa and Foa 1980).
Here, resources are deﬁned as the knowledge provided by a ﬁrrn’s marketing channel
partners to support its products and services. Accordingly, the ﬁrm’s retailer/distributor
and supplier equity refer to the perceived value of knowledge created by and transferred
from retailers/distributors and suppliers, respectively.

It has been noted that the creation and transfer of valuable knowledge requires
extensive and dedicated coordination between the ﬁrm and key marketing channel
partners for sustained periods of time (Galbraith 1990). In addition, well-grounded
communication patterns and trust between the ﬁrm and its marketing channel partners
ﬁrrther contribute to the value of knowledge (Larson 1992; Levinthal and Fichman 1988).
Thus, relational assets are the outcomes of a ﬁrm’s strategic relationships developed and
maintained for the purpose of knowledge acquisition from retailers/distributors and
suppliers.

To hold the potential of sustained competitive advantage, the knowledge provided
by retailers/distributors and suppliers must satisfy a speciﬁc set of characteristics.

Following Amit and Schoemaker’s (1993) framework, which expanded upon Bamey’s

23

(1992) VRIO base characteristics (i.e., valuable, rare, inimitable, and organizational
orientation), the desired attributes of retailer/distributor and supplier knowledge are
identiﬁed as follows: complementarity, overlap with strategic industry factors (SIFs), low
tradeability, scarcity, inimitability, limited substitutability, durability, and appropriability.

The characteristics for valuable were expanded to include “complementarity” and
“overlap with SIFs.” The asset is considered to be complementary when the strategic
value of its relative magnitude increases with an increase in the relative magnitude of
other assets within the firm (Amit and Schoemaker 1993). The complementarity of
knowledge does matter because such knowledge is typically an intermediate good and
needs to be integrated with a ﬁrm’s business processes to yield value, implying a bilateral
dependence in application (Teece 1986, 1998). SIFs are the outcomes of complex
interactions among competitors, customers, marketing channel partners, and
environmental factors. The set of SlFs speciﬁc to industry represents the ex ante limits to
competition and is subject to change (Peteraf 1993). Because knowledge grows and
becomes obsolete as reality changes, the value of knowledge changes as the relevant set
of SIFs changes. Then, the task of management is to assess, ex ante, the possible sets of
SlFs (Amit and Schoemaker 1993).

The characteristics for rare were expanded to include “low tradeability” and
“scarcity.” Tradeability is the potential that the knowledge can be easily bought, sold, or
transferred in factor markets. If competitors can acquire the factors to imitate the ﬁrm’s
knowledge, then the competitive advantage of a ﬁrm will be short-lived (Black and Boal
1994; Grant 1991). For example, knowledge acquired from key marketing channel

partners cannot be easily traded in the marketplace since such ﬁrm-speciﬁc knowledge

24

accumulates slowly over a period and is deeply rooted in the ﬁrm’s history (Itami and
Roehl 1987). Knowledge is scarce if few other ﬁrms have knowledge that is in high
demand and difﬁcult to imitate. That is, the ﬁrm’s knowledge acquired from key
marketing channel partners is valuable, because fewer ﬁrms will pursue marketing
strategies based on those knowledge assets, which are costly and time-consuming for
others to develop.

The characteristics for inimitability were split into “inimitability” and “limited
substitutability.” Knowledge is imperfectly imitable because the link between knowledge
and the sustained competitive advantage is causally ambiguous due to a combination of
three factors (Lippman and Rumelt 1982; Reed and deFillippi 1990). First, knowledge is
tacit because it is accumulated through key marketing channel partners’ experience with
the ﬁrm and reﬁned by practice (Polanyi 1967). Second, knowledge may be very
complex, because it involves a large number of organizational processes, and the causes
of successes or failures are often difﬁcult to determine. And third, knowledge can be
highly speciﬁc because it is developed in line with a ﬁrm’s products and services.
Though it may not be possible for another ﬁrm to imitate the ﬁrm’s knowledge, another
ﬁrm may be able to substitute a similar asset that enables it to conceive of and implement
the same strategies. For example, a ﬁrm may not be able to imitate the same knowledge
of suppliers but may develop its own knowledge that is strategically equivalent. On the
other hand, very different ﬁrm assets can be strategic substitutes (Barney 1991). Thus,
knowledge should be both imperfectly imitable and substitutable.

The characteristics for organizational orientation represent “durability” and

“appropriability.” Durability refers to the rate at which knowledge depreciates or

25

becomes obsolete (Grant 1991). Thus, the creation and transfer of knowledge requires
continuous investments assigned by a ﬁrm’s key marketing channel partners. In addition,
knowledge can be a source of competitive advantage only if it is “sticky” or is supported
by a regime of strong appropriability concerning the allocation of rents where ownership
is ambiguous (Teece 1998).

In view of the previous discussion, relational assets do not assure a sustainable
competitive advantage if knowledge acquired from key marketing channel partners can
be easily bought or sold in the factor markets for the development and implementation of
marketing strategy (Dierickx and C001 1989). Further, competitive advantage and the
returns associated with it are subject to erosion through the depreciation of knowledge
(Grant 1991). Because the value of knowledge perceived by the ﬁrm is based primarily
on the relationships with key marketing channel partners, those relationships should be
nurtured continually.

Market Orientation Culture

Shapiro (1988) deﬁnes market orientation as “the effort involved dispersing
information about customers, potential customers, and competitors throughout the
organization; spreading strategic and tactical decision-making so that all key divisions
participated; and instilling a shared sense of commitment toward ﬂawless service of the
company’s markets.” Accordingly, market orientation is not exclusively a concern of the
marketing ﬁmction; rather, it requires the participation of a variety of departments.
Though later market orientation research studies have introduced different aspects of
market orientation, the common focus of market orientation is the creation of superior

customer value based on knowledge derived from customer and competitor analysis.

26

There are different views of the conceptualization of market orientation. Thus, the result
has been the emergence of two camps of market orientation research: behavioral and
cultural (Homburg and Pﬂesser 2000; Hurley and Hult 1998).

From a behavioral perspective, Kohli and J aworski (1990) conceptualize and
measure market orientation in terms of organizational behaviors that include generating
market intelligence pertaining to current and future customer needs, disseminating it
across departments, and taking actions in response to it. In contrast, several scholars
describe market orientation as an organizational culture. Deshpandé and his colleagues
(Deshpandé and Webster 1989; Deshpandé, Farley, and Webster 1993) view customer
orientation as a fundamental part of corporate culture and deﬁne it as the set of beliefs
that put customers’ interests ﬁrst, while not excluding those of all other stakeholders (i.e.,
owners, managers, and employees) in developing a long-term proﬁtable enterprise.
Similarly, Narver and Slater (1990, p. 21) characterize market orientation as an
organization culture that most effectively and efﬁciently creates the necessary behaviors
for the creation of superior value for customers, and thus continuous superior
performance for the business. They model it as a construct composed of customer
orientation, competitor orientation, and interfunctional coordination. However, this
cultural perspective provides measures of market orientation consisting of a set of
behaviors and processes rather than a set of cultural values and beliefs. The basic
assumption behind this approach is that these behaviors are the manifestations of an
underlying organizational culture (N arver and Slater 1990; Slater and Narver 1995).

As a result, three market orientation scales are introduced by three separate

groups of researchers representing both camps of market orientation research

27

(Deshpandé, Farley, and Webster 1993; Jaworski and Kohli 1990; Narver and Slater
1990). In addition, Deshpandé and Farley (1998a, p. 213) offered a single market
orientation scale derived from these three market orientation measures and emphasized
the behavioral perspective that deﬁned market orientation “as the set of cross-functional
processes and activities directed at creating and satisfying customers through continuous
needs-assessment.” Finally, a recent study by Homburg and Pﬂesser (2000) has
conceptualized and developed measures of market-oriented organizational culture
composed of organization-wide shared values, norms, artifacts, and behaviors. Homburg
and Pﬂesser (2000) model market-oriented organizational culture as a process, in which
values, norms, artifacts, and behaviors follow a sequential path. Though there is no
agreement upon what constitutes market orientation (a speciﬁc set of cultural values and
beliefs, a speciﬁc set of behaviors or both), the relationship between the ﬁrm’s cultural
values and its market-based learning behaviors has been articulated by market orientation
researchers (Deshpandé and Farley 1998b; Homburg and Pﬂesser 2000; Slater and
Narver 1995). As noted by Slater and Narver (1995, p. 67), “market orientation is the
principal cultural foundation of the learning organization.”

The cognitive orientation to organization, which focuses on the mind of
managers, suggests that values and beliefs affect ﬁrm actions (March and Simon 195 8)
and views organizations as analogous to cognitive enterprises (Argyris and Schon 1978)
or knowledge and belief systems (Rossi and O’Higgins 1980). The research on cognitive
structure and processes characterizes organizations as a network of shared values and
beliefs, shared cognitions, and unique ways in which organization members perceive and

organize their world (Rossi and O’Higgins 1980; Shrivastava and Mitroff 1982).

28

Cognitive processes represent values and beliefs in use that explain “why things happen
the way they do” (Deshpandé and Webster 1989). Because organizations are considered
as systems of thought, values and beliefs deﬁne the rules by which organization members
achieve coordinated action in order to diagnose and intervene in their marketplace

(Smircich 1983). These values and beliefs are referred to as cultures that can differentiate

 

an organization from its surroundings, engender commitment to its purpose. or provide a T
rationale for its actions (Sproull 1981). I
Accordingly, this dissertation emphasizes the culture perspective of market
orientation and classiﬁes it as an organizational cultural capability (Fiol 1991; Hall
5.

1992), which should be developed, rewarded, and managed in order to implement and
sustain activities associated with a ﬁrm’s marketing strategy. Because market orientation
culture dictates what information is to be collected, what types of market information are
important, who gets access to the market information, how it is to be interpreted and used
(Day 1994; Slater and Narver 1995), understanding values and beliefs supporting market ‘
orientation culture and their relationship to its marketing strategy formulation and
implementation are important. Further, market orientation culture affects the ﬁrm’s
perception of its markets and supports not only market knowledge activities but also its
strategic marketing actions. The next discussion relates to the components of market
orientation culture.

This dissertation conceptualizes market orientation culture as organization-wide
shared values and beliefs that should (I) put the customer’s interests ﬁrst, while not
excluding those of all other stakeholders, and (2) emphasize the value and necessity of

thorough market analysis directed at creating competitive advantage (Day 1994; Slater

29

and Narver 1995). Accordingly, market orientation culture supports learning from and
monitoring customers, competitors, and retailers/distributors. Because these stakeholders
possess or create knowledge contributing to the competitive advantage, or are threats to
the competitive advantage (Slater and Narver 1995), the scope of market orientation
culture should include customer orientation, competitor orientation, and
retailer/distributor orientation. Previous market orientation studies have used the term
“customer” to include both end-consumers and retailers/distributors. Though the
distinction between customers (end-consumers) and retailers/distributors is not explicit in
the market orientation literature, the emphasis on learning from customers and
retailers/distributors has been noted in the works of Kohli and Jaworski (1990); Narver
and Slater (1990); and Deshpandé, Farley, and Webster (1993). In managing market
knowledge activities, it is important for ﬁrms to know which customers are worth the
effort and resources (Davenport, Harris, and Kohli 2001). For example, Procter &
Gamble, which had been spending most of its effort on end-consumer research, recently
shifted its focus to its key retailer chains because of their growing concentration and
power. Because retailers/distributors also play an important role in creating superior
customer value, this dissertation explicitly makes a distinction between customers and
retailers/distributors and broadens the concept of market orientation culture, including
customer orientation, competitor orientation, and retailer/distributor orientation.
Customer orientation is associated with the values and beliefs that emphasize the
understanding of a ﬁrm’s target buyers to be able to create superior value for them
continuously. This implies that customer needs and requirements have primacy for the

ﬁrm. Competitor orientation means that a ﬁrm understands the short—term strengths and

30

weaknesses and the long-term capabilities of both the key current and the key potential
competitors. The third of the three culture components is retailer/distributor orientation.
Similarly, retailer/distributor orientation emphasizes information regarding the strengths
and weaknesses of the key current and potential retailers/distributors. Further, it values
the feedback on the ﬁrm’s products and/or services acquired from these marketing
channel partners.

In determining the content of market analysis, it is important for a ﬁrm to include
negative knowledge (Teece 1998). This implies that market orientation culture should
emphasize information regarding the ﬁrm’s failures or unsuccessful experiences
associated with customers, competitors, and/or retailers/distributors, aside from successes
in its market,

2.5 Market Knowledge Activities

To achieve competitive advantage in the marketplace, and thereby superior ﬁrm
performance, ﬁrms should identify, seek, develop, maintain, and leverage competences.
Market knowledge competence has been recognized as a source of competitive advantage
and described as a “core competence” (Hamel and Prahalad 1994), “distinctive
knowledge” (Day 1994), “higher-order resource” (Hunt and Morgan 1995), and “strategic
asset” (Glazer 1991; Srivastava, Shervani, and Fahey 1998). Further, market orientation
scholars have emphasized the role of market knowledge in marketing strategy
formulation and implementation, and proposed that ﬁrms should acquire information
about customers and competitors and use it in a coordinated way across departments to
guide strategy recognition, understanding, creation, selection, implementation, and

modiﬁcation (Kohli and Jaworski 1990; Narver and Slater 1990).

31

Day (1994, p. 38) views competences as “complex bundles of skills and collective
learning exercised through organizational business processes.” Competence building is
deﬁned as a process by which a ﬁrm attains qualitative changes to its stock of existing
assets and capabilities to achieve competitive advantages (Sanchez, Heene, and Thomas
1996). To identify competences, the sets of process activities in which competences are
employed should be described, since competences and organizational processes are
closely entwined. Li and Calantone (1998) deﬁne market knowledge competence as a
series of processes that generate and integrate market knowledge. In their study, market
knowledge is treated as a stock, whereas market knowledge competence is characterized
as a process that follows a series of activities (Li and Calantone 1998).

Consistent with organizational learning theory (Huber 1991; Moorman 1995;
Sinkula 1994), this study deﬁnes market knowledge competence as composed of market
knowledge generation and utilization processes. Here, market knowledge is deﬁned as
organized and structured information about the market pertaining to customers,
competition, marketing channel partners, and market trends and events (Glazer 1991; Li
and Calantone 1998). Accordingly, market knowledge competence consists of four
market knowledge process activities: market scanning, market information transmission,
market information interpretation, and market knowledge utilization (see Table 2). That
is, market knowledge competence arises from collecting market information, sharing it
among organizational members, and developing a shared understanding of markets,
followed by the application of market knowledge to marketing strategy formulation and
implementation. It can also be referred to as systematic and collective organizational

learning about the market. The intensity of each market knowledge process activity

32

inﬂuences the level of market knowledge competence. Consequently, market knowledge
competence, in the context of marketing strategy formulation and implementation, (1)
provides access to a wide variety of markets; (2) contributes to customers’ perceptions of
beneﬁts; and (3) is difﬁcult for rivals to imitate.

Table 2: Market Knowledge Activities

 

Activities: Definition:

 

. Market scanning The scanning activity consists of information acquiring and
gathering that involves both formal and informal search about
the marketplace (Aguilar 1967; Hambrick 1982; Kiesler and
Sproull 1982; Miller and Friesen 1982; Starbuck 1976).

 

 

I Market The transmission activity involves information diffusion among
information relevant users within a ﬁrm (Beyer and Trice 1982; Jaworski
transmission and Kohli 1993; Moorman 1995).

' Market The interpretation activity consists of translating market events,
information developing frameworks for understanding the marketplace,
interpretation bringing out meaning, and assembling conceptual schemes

among key managers (Daft and Weick 1984).

 

 

' Market The utilization activity involves the application of market
knowledge knowledge to a ﬁrm’s marketing strategy-related actions
utilization (Menon and Varadarajan 1992; Moorman 1995).

 

 

Market Scanning

The ﬁrst key activity is market scanning (Daft and Weick 1984; Hambrick 1982;
Huber 1991). Managers can only transmit, interpret, and utilize market information that is
brought into the boundary of the organization from the marketplace. Hence, market
scanning is deﬁned as an information acquiring and gathering activity that involves both
formal and informal search about the marketplace (Aguilar I967; Hambrick 1982;

Kiesler and Sproull 1982; Miller and Friesen 1982; Starbuck 1976). The market scanning

33

 

behavior may vary according to the breadth/narrowness and formal/informal acquisition
of information about the marketplace (Aguilar 1967; Daft and Weick 1984).

First, the breadth of market scanning varies with information sources in the
marketplace. F inns differ in their abilities to design and implement marketing strategies
due to their varying levels of market memories, which consist of knowledge and skills
associated with the key players in the marketplace (e.g., customers, competitors,
marketing channel partners) (Hambrick 1982; Jaworski and Kohli 1993). Managers need
to improve their understanding of events and trends in their business environment to
respond to changes. Often, a knowledge gap occurs when knowledge is not sufﬁcient for
what the manager intends to know. Hence, market scanning will be initiated by the desire
to close the gap and the organization will continuously search for new information
necessary for realizing the intended marketing strategy. Even though market scanning
primarily pertains to customer needs and wants, it should also include exogenous factors
such as competitors, retailers, distributors, suppliers, technology, demography, economy,
and other environmental forces that may affect ﬁrm performance (Day 1994; Kohli and
Jaworski 1990; Sinkula 1994; Slater and Narver 1995).

Second, the extent of formality of mechanisms for acquiring market information
and the regularity of acquisition are distinguishing factors of market scanning (Daft and
Weick 1984). Market scanning may be conducted through a variety of formal as well as
informal mechanisms for collecting primary or secondary information from
organizational stakeholders (e.g., customers, competitors, marketing channel partners)
(Kohli and Jaworski 1990). The formal collection of information may include

mechanisms such as market research surveys, competitive intelligence activities,

34

customer satisfaction studies, or sales response in test markets; whereas the informal
means may consist of collecting information from competitors who share information at
industry association meetings or at meetings and discussions with customers and trade
partners (Kohli and Jaworski 1990; Moorman 1995).

Market Information Transmission

An important component of organizational level information activity is sharing,
which is realized through transmission of information among organizational members
(Simon 1991). The role of market information transmission activity in creating
competitive advantage has been emphasized by marketing scholars (Jaworski and Kohli
1993; Maltz and Kohli 1996; Sinkula 1994; Sinkula, Baker, and Noordewier 1997; Slater
and Narver 1995). Market information transmission is deﬁned as the extent to which
market information is diffused among relevant users within a given organization (Beyer
and Trice 1982; Jaworski and Kohli 1993; Moorman 1995). Since the focal point of
transmission, in this study, is the entire SBU, the transmission activity encompasses both
vertical and horizontal channels (Van de Ven, Delbecq, and Koenig 1976). Further, the
range of transmitted information changes across customers, competitors,
retailers/distributors, suppliers, and market trends.

Once market information is acquired and brought into the boundary of the
organization, it must be transmitted within and among the organizational functions for the
occurrence and a breadth of market-based organizational learning (Huber 1991). In
traditional organizations, market information transmission is activated when a need for
information emerges (Glazer 1998). Accordingly, information processing structures are

sequential and information is localized. However, this is not appropriate in the

35

information age. For emergent adaptation to high velocity markets “more speedily” than
competitors, the transmission processes should be parallel and cognitively mindful
instead of being linear and mindless. That is, market information should be broadly
shared within the organization and continuously made available to anyone in the
organization who might potentially use it (Day 1994; Huber 1991).

Firms may have mechanisms (e.g., databases, computer systems) for storing and F
retrieving hard information (e.g., sales data, advertising expenditures). However,
problems may occur when they want to obtain a certain piece of information, because

locating that information calls for knowing by whom, where, when, why, or how that

 

certain piece of information was collected, stored, or used. When information is widely
transmitted in an organization, more varied storage places are created for that information
and individuals are more easily able to retrieve it. As a result, broader market-based
organizational learning occurs in the organization (Huber 1991).

Furthermore, the direction of information transmission is important for the extent
of organizational learning. Firms should encourage vertical as well as horizontal
information ﬂows. Thus, effective transmission enables the development of new
information by assembling together the bits of information obtained from other functions
(Huber 1991; Slater and Narver 1995). The value of information is then mutually
appreciated since it can be seen in its broader context. In addition, organizational
functions with potentially synergistic information are not aware of where such
information could serve, and they do not direct it to appropriate destinations (Huber
1991). Assembling information from different functions enables the coupling of those

who need information and those who possess information (Huber 1991). So, those

36

functions determine where else it could be beneﬁcially used (Day 1994; Glazer 1998;
Slater and Narver 1995). This leads not only to new information but also to new
understanding, which underscores the role of transmission as an antecedent to the market
information interpretation activity.
Market Information Interpretation

The distinctive feature of the interpretation activity is the conversion of F:
information into knowledge and the creation of shared understanding among managers

(Weick and Roberts 1993). Originating from the verb “informare ” (lat. in=in,

 

form=form, are=doing), the meaning of information is “to put data inform” (von Krogh,
R005, and Slocum 1994, p. 59). That is, information is a process of interpretation. In this
context, it is important to distinguish among data, information, and knowledge. Data
represent individual facts and alone are meaningless. Data become information when the
receiver decides whether data are really information or just noise, based on relevancy to a
work at hand and capacity to fulﬁll a goal. In order to change data into information and
derive meaning from data, the receiver condenses, contextualizes, categorizes, calculates,
and corrects data. The actionable information is knowledge, which refers to the “relevant
information being available in the right place at the right time, in the right context, and in
the right way so anyone can bring it to bear on decisions being made every minute”
(Tiwana 2000, p. 57). Knowledge is obtained arising from the interaction between
information and experience.

In the context of marketing, market information interpretation involves translating
market events, developing frameworks for understanding the marketplace, bringing out

meaning, and assembling conceptual schemes among key managers. Consequently,

37

market knowledge is obtained as a result of systematic processing, and is endowed with
useful meaning (Glazer 1991; Li and Calantone 1998). When market information is not
directly applicable to a problem or relevant to a particular marketing project or period in
time, it is more likely to be used conceptually. The conceptual use of information is
simply information interpretation that provides “general. enlightenment” (Beyer and Trice
1982, p. 598) in developing the managerial knowledge base (Menon and Varadarajan
1992; Moorman 1995).

Interpretation can be viewed as a multiple stage process (Isabella 1990; White,
Varadarajan, and Dacin 2003). First, managers bring together bits of market information
into a coherent and cogent frame of reference. Then, events are conﬁrmed by recalling
the common responses to the particular type of market event that is occurring or by
making comparisons to past similar market events (Isabella 1990). Finally, managers
attach meanings to market information, reconstruct their mental models, and develop
more complete understanding of the markets as more of the organization’s functions
understand the nature of interpretations held by other ﬁinctions (Daﬁ and Weick 1984;
Huber 1991).

Meanings are attached to market information as a result of sensemaking in the
organization (Thomas, Clark, and Gioia 1993). They are characterized by both the
content and framing of communications. The content of communication referring to what
is expressed is reﬂected in categories and labels (Dutton and Jackson 1987). To form
categories, objects, events, people, and strategic issues are clustered with similar
perceived attributes. Then, labels are attached to describe a given event. Two strategic

event labels that are commonly used by managers are “threat” and “opportunity.” The

38

 

assumptions of managers about the events are embedded in these labels, implying their
perceptions of an event as negative or positive and uncontrollable or controllable (Dutton
and Jackson 1987; White, Varadarajan, and Dacin 2003). Further, meaning resides in the
framing of communications, which reﬂects how managers construct their views about a
given event (Bartunek 1984). The breadth and rigidity of managers’ framing of their
views are positively related to the effectiveness and ﬂexibility of decision-making,
respectively (Fiol 1994).

The role of information processing at the organizational level is to bridge
diversity and disagreement (Daft and Lengel 1986) and enable convergence on a similar
interpretation. To achieve organized action, it is important for ﬁrms to be able to manage
uniﬁed diversity (Fiol 1994), since managers may pursue different priorities and goals,
and thus may be in conﬂict with respect to market information interpretation or its
signiﬁcance for goal attainment. Consequently, reaching convergence among managers
characterizes the change in the range of potential behaviors related to the ﬁrm’s strategic
marketing actions (Weick 1979; Weick and Roberts 1993).

Market Knowledge Utilization

Market knowledge utilization, which implies action-oriented use (Menon and
Varadarajan 1992), refers to the extent to which an organization directly applies market
knowledge to inﬂuence marketing strategy-related actions (Moorman 1995). Market
knowledge utilization is demonstrated by changes in the ﬁrm’s marketing strategy-related
activities, whereas market information interpretation is subtle and indirect, and therefore

managers may not be able to identify speciﬁc effects or observe the changes (Menon and

Varadaraj an 1992).

39

Market knowledge can be utilized in decision-making, implementation, and
evaluation of marketing decisions (Moorman 1995). “Decision-making” refers to
processes of solving a policy problem and selecting among strategy problems.
Knowledge utilization in implementation provides directions about the enactment of
marketing decisions, strategies, and tactics, and thereby facilitating the implementation
stage. Finally, “evaluation” refers to the processes of identifying positive and negative
performance outcomes and the reasons for those outcomes (Zaltman and Moorman

1989).

40

CHAPTER [11
MODEL DEVELOPMENT AND RESEARCH HYPOTHESES

Chapter III presents a hypothesized model based on the theoretical and conceptual
discussions in Chapter II and the research questions previously stated in Chapter I. An
overview of the hypothesized model developed and tested in this dissertation is provided
in Figure 4. First, the hypothesized model examines the effects of a ﬁrm’s relational
assets and market orientation culture on its market knowledge competence. Then, the
impact of market knowledge competence on ﬁrm performance is investigated. In
assessing the performance consequences of market knowledge competence, the balanced
scorecard frame is implemented. The balanced scorecard frame considers four
dimensions of performance: customer performance, ﬁnancial performance, marketing
strategy formulation and implementation speed, and marketing learning performance.
Finally, the interplay among the four components of ﬁrm performance is explored. The
hypothesized relationships are summarized in Table 3. The focal prediction is that the
ﬁrm’s relational assets and market orientation culture will have important effects on its
market knowledge competence, and thus the ﬁrm’s market knowledge competence will

create superior ﬁrm performance.

41

 

mean—Eaten— Ecr—

8588.20;
3655...

 

  

   

     

89.583—

.mcoamoEE 338:2 3m; $28505 £98» 32935 of. £9865 03355..

85.53.. cute—320— «8.32

mm 392$ $2935 32 85 £98m 320-288 Em ecemgﬁoo emnﬂsosx $qu 28 3328 2625223 $qu 35 8865 8:: 3:8 2; "3oz

    

  

2330
sous—610
$th

   

conﬂuence“:—

 
 

coca—Ecru“—
wEEwoq
wEBxEE

   

I
I s
s x
\
MI

  
  

8:209:00
032305—
8x32

 

     

3on
53855038.
4% 5:232:3—
38g”).

  
  

 

oocwgotom
hOEOHsz

  

 

3:83:80 $3.325— .exeaz me .352 twine—.25»: 2:. "v 95$.”—

  

 

 

  

 

    

bScm
85“:me
Fined

 
 

staccato

Sangria
3:83.

     
     

  

:ozﬂcoto
cozuanoU

     

:o_§:ot0
85330

N: .03ch
cozaasm

  

   
 

   
 

42

Table 3: Summary of the Hypotheses

 

I Relational Assets -) Market Knowledge Competence

Hypothesis 1: The degree of a ﬁrm’s retailer/distributor equity is
positively associated with the degree of its market
knowledge competence.

Hypothesis 2: The degree ofa ﬁrm’s supplier equity is positively
associated with the degree of its market knowledge

_ competence.
I Market Orientation Culture -) Market Knowledge Competence

Hypothesis 3: The degree of a ﬁrm’s market orientation culture is
positively associated with the degree of its market
knor-rledge competence.

I Firm Performance Outcomes

Hypothesis 4: The degree of a ﬁrm’s market knowledge competence is
positively associated with the degree of its customer
performance.

Hypothesis 5: The degree of a ﬁrm’s market knowledge competence is
positively associated with the degree of its marketing
strt‘ttegv/ormulation and implementation speed.

Hypothesis 6: The degree of a ﬁrm’s market knowledge competence is
positively associated with the degree of its marketing
learning performance.

Hypothesis 7: The degree of a ﬁrm’s marketing strategy formulation and
implementation speed is positively associated with the
degree of its customer performance.

Hypothesis 8: The degree of a ﬁrm’s marketing strategy formulation and
implementation speed is positively associated with the
degree of its financial performance.

Hypothesis 9: The degree of a ﬁrm’s marketing strategy formulation and
implementation speed is positively associated with the
degree of its marketing learning performance.

Hypothesis 10: The degree of a ﬁrm’s customer performance is positively
associated with the degree of itsﬁnancial performance.

Hypothesis 1]: The degree of a ﬁrm’s marketing learning performance is
positively associated with the degree of its ﬁnancial
performance.

 

 

 

 

 

To examine the conceptual framework divided into resources, market knowledge
activities. and ﬁrm performance, this chapter is separated into three sections: (1)

relational assets and market knowledge competence. (2) market orientation culture and

43

 

market knowledge competence, and (3) ﬁrm performance outcomes. In addressing the
hypothesized relationships among the study constructs, the model integrates research
from several streams of literature including the resource-based theory of strategy, the
competence-based approach to strategy, organizational learning, and market orientation.
3.1 Relational Assets and Market Knowledge Competence

Glazer (1991) suggests that the ﬁrm’s entire “value-chain” process provides
knowledge from every transaction between the point of purchase, the distributor, the
ﬁrm, and the ﬁrm’s suppliers. Developing strong marketing channel relationships thus
ensures that knowledge is processed and utilized by the ﬁrm. In examining the role of the
ﬁrm’s marketing channel relationships in market knowledge activities, this dissertation
identiﬁes retailers/distributors and suppliers as important knowledge sources. While
retailer/distributor knowledge may be related to sales, customer needs, competitive tactics
and strategies, and market trends and developments that enable the ﬁrm to compete
effectively in the marketplace, supplier knowledge is associated with production and may
involve new products, technological advances, and process innovations.
Retailer/distributor and supplier equity are strategic assets because knowledge provided
by the marketing channel partners is valuable, hard to imitate, hard to substitute, and rare
(Amit and Schoemaker 1993; Barney 1991; Grant 1991). Thus, strategic assets are much
more important than other assets and serve as a powerful mechanism for differentiation
(Barney 1991).

The perceived value of retailer/distributor and supplier knowledge by the ﬁrm
tends to be high if it is highly ﬁrm-speciﬁc, complementary to its existing market

knowledge, and/or relevant to its strategic marketing actions. Previous research has

44

“Isl-la

 

suggested a positive relationship between the perceived value of market knowledge (e.g.,
marketing research, marketing information, and research information) and its use by the
ﬁrm (Deshpandé and Zaltman 1984; Low and Mohr 2001; Maltz and Kohli 1996).
Managers appear to accept and utilize knowledge in making decisions or evaluating
performance if they view it useful for the purpose at hand. In view of this, it is believed
that retailer/distributor and supplier equity should positively inﬂuence market knowledge
competence, because the degree to which retailer/distributor knowledge and/or supplier
knowledge has value to the ﬁrm determines the intensity of market knowledge activities.
This implies that the ﬁrm’s market knowledge competence will be enhanced because ( 1)
the intensity of activities geared to the acquisition of retailer/distributor or supplier
knowledge and its transmission among relevant users will increase to the extent it is
perceived as meaningful and useful for marketing strategy making; (2) the intensity of
activities for interpreting retailer/distributor or supplier knowledge through various
analytical procedures and creating a shared understanding of it will increase to the extent
its value is recognized for decision making, and (3) the intensity of activities geared to
making, implementing, and evaluating marketing decisions will increase to the extent the
retailer/distributor or supplier knowledge is related and applicable to the tasks facing the
managers. Collectively, it is believed that retailer/distributor and supplier equity should
enhance market knowledge competence. Hence:
Hypothesis 1: The degree of a ﬁrm’s retailer/distributor equity is positively
associated with the degree of its market knowledge competence.

Hypothesis 2: The degree of a ﬁrrn’s supplier equity is positively associated
with the degree of its market knowledge competence.

3.2 Market Orientation Culture and Market Knowledge Competence

45

The distinction between market orientation culture and ﬁrm activities associated
with learning about the market has been widely emphasized by marketing scholars
(Deshpandé, Farley, and Webster 1993; Hurley and Hult 1998; Moorman 1995; Sinkula,
Baker, and Noordewier 1997; Slater and Narver 1995). In their article, Slater and Narver
(1995, p. 63) note that “for a business to maximize its ability to learn about markets,
creating a market orientation is only a start.” That is, market orientation as a culture F
supports the value of thorough market knowledge generation and utilization and holds
only the potential for market knowledge creation (Day 1994; Slater and Narver 1995).

Speciﬁcally, this dissertation examines the impact of a market orientation culture

 

on market knowledge competence. Market orientation culture is characterized as
organization-wide shared values and beliefs that emphasize learning from and monitoring
customers, competitors, and retailers/distributors because these entities (I) possess or are
able to create valuable knowledge that has the potential to create superior customer value
or (2) are threats to competitive advantage (Slater and Narver 1995). Consequently,
market orientation culture arises from customer orientation, competitor orientation, and
retailer/distributor orientation.

To maximize market knowledge competence, market knowledge activities should
be connected with an underlying system of values and beliefs (Narver and Slater 1990;
Sinkula, Baker, and Noordewier 1997). Because collectively held values and beliefs are
the manifestations of how a ﬁrm perceives, thinks, and feels about customers,
competitors, and retailers/distributors (Walsh and Ungson 1991), market orientation
culture plays an action guidance role in market knowledge generation and utilization

process and promotes collective learning. In other words, market orientation culture

46

guides and facilitates the search for, acquisition of, and interpretation of market
information, and the utilization of market knowledge (Day and Nedungadi 1994;
Deshpandé and Webster 1989; Weick 1979). As a result, market orientation culture
enhances market knowledge competence by motivating the ﬁrm to pursue those market
knowledge activities.

Previous research has provided empirical support for the relationship between 5-
market orientation culture and market knowledge processing. Studies by J aworski and
Kohli (1993) and Li and Calantone (1998) have provided empirical support for the

positive relationship between market knowledge processing and the amount of emphasis

 

top management places on market knowledge. Further, a study by Homburg and Pﬂesser
(2000) has found a signiﬁcant, positive relationship between artifacts of market
orientation and market oriented behaviors. Drawing from these studies, market
orientation culture is expected to increase market knowledge competence. Hence:

Hypothesis 3: The degree of a ﬁrm’s market orientation culture is positively

associated with the degree of its market knowledge competence.

3.3 Firm Performance Outcomes

To examine ﬁrm performance, the balanced scorecard approach is employed
(Kaplan and Norton 1993, 2005). Given the objective of assessing the value that results
from effective market knowledge management, the balance scorecard approach is
appropriate for including both ﬁnancial and non-ﬁnancial measures. The balanced
scorecard framework complements traditional ﬁnancial indicators with measures of
performance for customers, internal processes, and learning and growth activities. In

addition, the scorecard’s measures are grounded in an organization’s strategic objectives

47

and competitive demands, and thus the balanced scorecard provides information not only
about the ﬁrm’s current success but also direction for future success (Kaplan and Norton
1993). The four building blocks of a balanced scorecard designed for this dissertation are:
(1) customer performance, (2) a ﬁrm’s marketing strategy formulation and
implementation speed, (3) marketing learning performance, and (4) ﬁnancial
performance. The represented measures assess the efﬁciency and effectiveness of a ﬁrm’s
market knowledge competence on its performance.
Customer Performance

Many companies today state that their mission is to be number one in delivering
superior customer value. The balanced scorecard demands that managers translate their
company mission on customer service into speciﬁc measures (Kaplan and Norton 2005).
That is, customer performance should indicate how well a ﬁrm is performing in
delivering the products and services demanded by its customers. It is the effectiveness of
a ﬁrm’s products and programs in relation to those of its competitors in the market
(Walker and Ruekert 1987). Accordingly, typical customer-related goals include
customer satisfaction, market share, and growth in comparison with that of competitors
(Homburg and Pﬂesser 2000).
Marketing Strategy Formulation and Implementation Speed

As suggested by Kaplan and Norton (2005), customer-based measures must be
translated into measures of what the company must do internally to meet its customers’
expectations. The internal process measures should be derived from the business
processes that have the greatest impact on customer performance. Because this

dissertation explores the role of market knowledge competence in marketing strategy

48

making, the internal business processes encompass marketing strategy formulation and
implementation. Hence, marketing strategy formulation and implementation speed assess
the ﬁrm’s internal process performance.
Marketing Learning Performance

Customer and internal process performance measures are determined based on the
parameters that are considered to be important for the ﬁrm’s competitive success.
However, because success factors in the market keep changing, ﬁrms should
continuously make improvements to their existing marketing strategies and business
plans to create more value to customers. A ﬁrm’s ability to learn and improve may create
operating efﬁciencies and can be directly linked to the company’s value. In this context,
marketing learning performance refers to the development of marketing skills in the
ﬁrm’s employees and the understanding of the product market in which the ﬁrm operates
(Menon et al. 1999).
Financial Performance

Financial parameters indicate whether the ﬁrm’s marketing strategy,
implementation, and execution contribute to bottom-line improvement (Kaplan and
Norton 2005). Measures of customer performance, marketing strategy formulation and
implementation speed, and marketing learning performance are derived from a
company’s perspective on key success factors, whereas ﬁnancial measures provide
information on the efﬁciency of a ﬁrm’s operational functions. A ﬁrm should learn how
to link its operational functions to its ﬁnancial performance, and identify ﬁnancial
parameters. A failure to convert improved operational performance into ﬁnancial

performance implies that managers should rethink the ﬁrm’s marketing strategy or its

49

implementation plans (Kaplan and Norton 2005). A well-designed ﬁnancial control
system enables managers to examine whether a ﬁrm’s marketing strategies are proﬁtable
strategies. Typical ﬁnancial parameters are associated with sales, investments, assets, and
proﬁt margin in comparison with those of competitors (Ketehen, Thomas, and Snow
1993)
3.3.1 Outcomes of Market Knowledge Competence

Research from several domains points to the positive, direct effects of market-
based learning on ﬁrm performance (Homburg and Pﬂesser 2000; Jaworski and Kohli
1993; Moorman 1995). Speciﬁcally, it is posited that the ﬁrm’s market knowledge
competence should positively affect its customer performance on four grounds. First,
market scanning assists ﬁrms in identifying trends, developments, opportunities, and
threats in the ﬁrm’s market and facilitates effective strategy formulation. For example,
ﬁrms that continuously track customer needs and preferences can better satisfy customers
than competitors and, hence achieve higher levels of customer performance. Second,
transmission of market information across functions discourages. “Compartmentalized
thinking” within the ﬁrm (Adams, Day, and Dougherty 1998, p. 406) and enables
managers to develop a more complete understanding of marketing problems. That is, the
effective distribution of information permits managers to access and assemble pieces of
information about customers, competitors, retailers/distributors, suppliers, and so forth.
Third, market information interpretation enables managers to build a shared
understanding of how their markets will react to their marketing actions, and promotes a
shared vision of marketing strategy formulation and implementation. And fourth, market

knowledge utilization affects customer performance by inﬂuencing the effectiveness of

50

marketing strategy formulation and implementation. In summary, ﬁrms that continuously
scan the market, transmit and interpret market information, and utilize market knowledge
tend to serve customers successfully and achieve higher customer performance. Hence:

Hypothesis 4: The degree of a ﬁrm’s market knowledge competence is

positively associated with the degree of its customer
performance.

Although there are conﬂicting results on the effects of market knowledge
competence, its role in creating process efﬁciencies is being recognized by marketing
scholars. For example, a study by Hult et a1. (2000) found that purchasing knowledge
processing that involves knowledge acquisition and dissemination activities is negatively
associated with purchasing cycle time. In contrast, Moorman (1995) found no association
between market knowledge acquisition and dissemination activities and new product
timeliness, but she found support for the positive effects of market knowledge
interpretation and utilization activities. In view of these studies, market knowledge
competence is expected to facilitate the process of marketing strategy formulation and
implementation due to four reasons. First, market scanning enables the ﬁrm to sense
signals of market changes, and thus allows it to generate actions quickly (Kiesler and
Sproull 1982). Next, market information transmission speeds the process of strategy
making by ensuring that relevant information crucial to strategic decisions is shared by
all parties involved (Smith et al. 1991). Third, market information interpretation
accelerates marketing strategy making because assumptions about the market are broadly
shared (Daft and Weick 1984). Finally, market knowledge utilization mobilizes feedback
about the market as a result of concerted efforts geared to decision-making, evaluation,

and implementation, and thus facilitates marketing strategy making (Corner, Kinicki, and

51

 

Keats 1994). Thus, market knowledge competence that has important effects on the
ﬁrm’s capacity to act is proposed to increase marketing strategy formulation and
implementation speed. Hence:

Hypothesis 5: The degree of a ﬁrm’s market knowledge competence is

positively associated with the degree of its marketing strategy
formulation and implementation speed.

 

Following Bell, Whitwell, and Lukas’s (2002) distinction between organizational P
learning as a verb and organizational learning as a noun, marketing learning performance
(as a noun) refers to what has been retained by the organization as a result of market
knowledge generation and utilization. While some organizational learning scholars k

believe that behavioral change is required for learning (Huber 1991; Levitt and March
1988), some suggest change need not be visibly behavioral (Friedlander 1983).
Accordingly, it is believed that new and signiﬁcant awareness about the market and skill
development are essential for marketing learning. In this context, marketing learning
performance refers to the improvements in the marketing skills of ﬁrm employees and
their understanding of the market. Here, understanding implies that a ﬁrm both learns
new market knowledge and discards obsolete market knowledge, where “discarding”
refers to the ﬁrm’s unleaming about the market (Hedberg 1981).

In view of this, it is posited that marketing learning performance is positively
inﬂuenced by market knowledge competence. Firms develop a better understanding of
how marketing ﬁinctions or what the market is as the intensity of market knowledge
generation and utilization activities increases. As a result, the ﬁrm’s rules and routines
associated with its marketing functioning will be modiﬁed and improved in accordance

with the marketplace. That is, market knowledge competence positively inﬂuences the

52

ﬁrm’s learning of marketing skills that involve pricing, advertising and promotion, and
distribution and its understanding about the market. Hence:

Hypothesis 6: The degree of a ﬁrm’s market knowledge competence is
positively associated with the degree of its marketing learning
performance.

3.3.2 Outcomes of Marketing Strategy Formulation and Implementation Speed

The impact of strategy formulation and implementation speed on ﬁrm
performance has been noted in the strategic management literature. The studies by
Eisenhardt (1989) and Judge and Miller (1991) suggest a signiﬁcant, positive link
between strategic decision speed and performance (e.g., sales, proﬁtability) for ﬁrms
operating in dynamic environments (e.g., high-tech industry, biotechnology industry).
Eisenhardt (1989) reports that the decision-making process in the most successful
companies is fast and comprehensive. In contrast, the study by Forbes (2001) ﬁnds no
relationship. In addition, the research study by Baum and Wally (2003) examines the
impact of strategic decision speed on ﬁrm performance in terms of growth and proﬁt.
Their ﬁndings suggest a positive, direct relationship between decision speed and growth,
only.

Marketing scholars have also recognized the importance of marketing strategy
formulation and implementation speed (e.g., responsiveness) in ﬁrm performance
(Jaworski and Kohli 1993; Walker and Ruekert 1987). Previous research has noted the
role of speed in ﬁrm performance by linking the order of market entry (Kerin,
Varadarajan, and Peterson 1992; Szymanski, Troy, and Bharadwaj 1995) or order
timeliness (Mentzer, Flint, and Hult 2001) with such performance outcomes as market

share, sales growth, and customer satisfaction.

53

In view of these studies, ﬁrms are expected to achieve competitive advantages as
a result of fast marketing strategy formulation and implementation for several reasons
(Prahalad and Hamel 1990). Fast strategy making may lead to early adoption of new
product or process innovations that provide competitive advantages. For example, ﬁrms
may decrease order delivery time by implementing efﬁcient process technologies, and
thus increase customer satisfaction. Moreover, fast strategy making may lead to early
market entry. Studies focusing on the order of market entry provide evidence for the
positive effects of market pioneering on market share and sales growth arising from cost
advantages, consumer information advantages, and/or product differentiation advantages
(Robinson and Fomell 1985). Collectively, it is believed that marketing strategy
formulation and implementation speed is important in a ﬁrm’s success and should be
linked with customer and ﬁnancial performance. Hence:

Hypothesis 7: The degree of a ﬁrm’s marketing strategy formulation and
implementation speed is positively associated with the degree of
its customer performance.

Hypothesis 8: The degree of a ﬁrm’s marketing strategy formulation and
implementation speed is positively associated with the degree of
its ﬁnancial performance.

In addition, marketing strategy formulation and implementation speed is expected
to inﬂuence marketing learning performance. Argyris and Schbn (1978) view
organizational learning as a process of detecting and correcting errors geared to
improving the effectiveness of employee behavior in organizations. Firms modify their
actions based on the feedback they receive from the market. The feedback based on the

ﬁrm’s actions in the market may be in the form of customer’s reactions, competitors’

actions, or retailers’ responses, and plays a key role in motivating the ﬁrm to actively

54

improve its ability to learn (Kim 1984; Kleinmuntz and Thomas 1987). Because faster
marketing strategy making produces more frequent feedback loops within a particular
time frame (Meyer 1993; Thomas, Gioia, and Ketchen 1997), the marketing strategy

making speed of a ﬁrm is related to its learning of marketing skills and understanding
about the market (Eisenhardt 1989; Menon and Lukas 2004). For example, a study by
Menon and Lukas (2004) provides empirical support for the positive effects of faster I,
product development process on organizational learning, suggesting that frequent

feedback will enhance the ﬁrm’s ability to learn as a result of extensive information

sharing across departments. Here, the argument is that if managers receive information

 

sooner, they can sense problems sooner, and thus correct them faster (Mintzberg 1973). '
Accordingly, fast marketing strategy formulation and implementation is expected to yield
higher levels of marketing learning. Hence:

Hypothesis 9: The degree of a ﬁrm’s marketing strategy formulation and
implementation speed is positively associated with the degree of
its marketing learning performance.

3.3.3 Customer Performance and Financial Performance

Previous research has widely supported the positive effects of a ﬁrm’s customer
performance on ﬁnancial performance encompassing its cost position, sales growth, and
proﬁtability (Homburg and Pﬂesser 2000; Szymanski, Bharadwaj, and Varadarajan
1993). It is believed that a ﬁrm will be ﬁnancially successful if it performs well in
carrying out marketing activities. Market share appears to be a valid goal that is capable
of being translated into high proﬁtability. The studies on performance implications of
market share and customer satisfaction provide evidence that these components of

customer performance are positively related to ﬁnancial performance (Prescott, Kohli,

and Venkatraman 1986; Spanos and Lioukas 2001; Szymanski, Bharadwaj, and
Varadarajan 1993). In addition, the ﬁndings of PIMS studies have noted that
product/service quality and market share are the most important factors that inﬂuence the
percentage of return on sales (Buzzell and Gale 1987, p. 45). Hence:

Hypothesis 10: The degree of a ﬁrm’s customer performance is positively

associated with the degree of its financial performance.

3.3.4 Marketing Learning Performance and Financial Performance

Marketing learning is an important source of competitive advantage (Day 1994;
Grant 1996; Leonard-Barton 1992). Previous research has noted the positive effects of
marketing skills on ﬁrm performance (Hitt and Ireland 1985; McKee et a1. 1992). In a
study by McKee et al. (1992), ﬁrms with comprehensive marketing skills were found to
achieve the highest ﬁnancial performance. Because higher levels of learning regarding
improvements in marketing skills and understanding about the market imply higher levels
of marketing management experience and active marketing orientation, marketing
learning increases ﬁnancial performance as a result of attaining operational efﬁciencies.
For example, ﬁrms may achieve higher levels of ﬁnancial performance by developing
effective product policies or by improving marketing channels. Moreover, effective
pricing programs and cost controls may also generate returns from marketing skills
(McKee et a1. 1992). Accordingly, it is expected that marketing learning performance
will be positively related to ﬁnancial performance. Hence:

Hypothesis 11: The degree of a ﬁrm’s marketing learning performance is

positively associated with the degree of its ﬁnancial
performance.

56

CHAPTER IV
RESEARCH DESIGN AND METHODOLOGY

Chapter IV presents the research design and the methodology used to gather and
analyze the primary data. First, the sampling frame is described. Next, the data collection
process is illustrated. Finally, the constructs and the development procedures for
measures used to operationalize the study constructs are provided. R-
4.1 Sampling Frame

The sampling frame for this study was drawn from the manufacturing and service

companies operating in the United States. The directory was obtained from a commercial

 

list provider. A range of industries from both sectors was covered in the sample frame.
An important issue in designing the empirical study is to obtain appropriate
informants. The objective of this research is to investigate the relationships among
resources speciﬁc to marketing, market knowledge activities, and ﬁrm performance. A
ﬁrst implication of this is that the respondent should have knowledge of the ﬁrm,
familiarity with its environment, and access to strategic and ﬁnancial information. Thus,
the targeted informants included marketing managers, sales managers, or product
managers (Aguilar 1967). A second implication is that, regarding the focus on the
generation and utilization of knowledge for marketing strategy related actions, the study
was conducted at the strategic business unit (SBU) level. Further, as Deshpandé and
Webster (1989) propose, the SBU level was more appropriate than the corporate level for
studying organizational culture represented by the ﬁrm’s market orientation culture.
Another important issue is to decide on the number of informants. Data was

collected by the key informant method. It has been suggested that the single respondent

57

design curbs the generalizability of results (John and Reve 1982; Kumar, Stern, and
Achrol 1992). To minimize the limitation imposed by the single informant, the most
appropriate respondent was identiﬁed by evaluating the competence of the key informant
to answer the survey (Homburg and Pﬂesser 2000; Menon et a1. 1999).

4.2 Data Collection Process

The data collection process of this study was divided into two stages: (1) pretest

 

l“
and (2) test of the model with a senior executive sample. i
Stage one involved a pretest of the draft version of the questionnaire. A pretest
was in the form of in-depth telephone and on-site interviews with ﬁve marketing and/or
1L

sales managers to ensure that the scale items accurately address the domain of the
construct as deﬁned conceptually. The executives that participated in this initial
exploratory research were identiﬁed from the directory of the total sample. These
identiﬁed executives were contacted and informed about the study, and an interview was
requested. A brief summary of the research project and the interview protocol was faxed
or e-mailed to them in advance. Five interviews lasting an average of one hour were
conducted following a semi-structured format.

Further, several academics with acknowledged expertise in the subject matter of
this study assessed the scale measures and the questionnaire layout. The questionnaire
was modiﬁed on the basis of comments from these expert judges to ensure the face
validity of the scale items by eliminating items that may potentially contaminate a
measure (Schwab 1999). Finally, it was ensured that the questionnaire was in a readable

and easily understood format.

58

In the second stage, a random sample of 1,350 SBUs was drawn from a
commercial mailing list. Of these, 750 SBUs were drawn from Fortune 1000 companies.
Thus, mailings were made to the senior executives in these 1,350 ﬁrms. The respondents
were requested to ﬁll out the questionnaire with respect to the strategic business unit with
which they are most familiar. A copy of the questionnaire, along with a cover letter and
instructions explaining the purpose of the research, and a return envelope were mailed.

All respondents were assured anonymity of their responses, but they were r;
informed that a code included on each questionnaire was used to verify their responses to

the survey. In addition, participating ﬁrms were promised an executive summary report

 

of the study if they returned their business cards with the completed questionnaire.
Multiple follow-up methods were used extensively. Two weeks following the ﬁrst
mailing, nonrespondents were telephoned to verify the contact name and the
appropriateness of the ﬁrm for participation in the study, reminded of the questionnaire,
and encouraged to complete and return it. A replacement copy of the questionnaire along
with a follow-up letter was mailed to nonrespondents one month after the ﬁrst mailing. It
was determined that at least 281 mailings were nondeliverable due to several factors
(e.g., incorrect address, respondent no longer with the company), 93 respondents reported
a corporate policy of not responding to academic surveys, and 5 respondents reported that
the company was closing. The ﬁnal sampling frame consisted of 971 companies. Thus,
the total of 124 (122 usable) returned questionnaires represented a response rate of
12.77%. It should be noted that the actual number of ﬁrms that did not participate in this
study may be higher; however, it could not be determined due to time and ﬁnancial

constraints.

59

4.3 Constructs and Measure Development Procedures

A structured survey was developed to test the proposed hypotheses. Measurement
of the constructs was accomplished via the use of both established and original scales.
Accordingly, appropriate scale development and testing procedures were followed (e.g.,
Anderson and Gerbing 1988; Churchill 1979; F omell and Larcker 1981). In the ﬁrst
phase of the questionnaire development, a comprehensive review of the literature was
performed. In the second phase, valid measurement scales were borrowed or adapted
when possible for the purposes of the present study. To maintain the integrity of the
established scales, modiﬁcations were kept to the minimum necessary to address the
constructs as they are conceptualized. Given the scarcity of prior empirical research and
the novelty of some constructs, new scales had to be deﬁned and developed. New scales '
were generated by the guidance obtained from the literature review and the content
analysis. Other scales were adopted, modiﬁed from existing scales, or driven by the
conceptualization of study constructs in the literature. All perceptual measures were
conducted with a seven-point rating scale with anchors I = “strongly disagree” and 7 =
“strongly agree,” or 1 = “much worse” and 7 = “much better,” or 1 = “very poor” and 7 =
“excellent.”

Two types of measures were used in the survey: reﬂective multi-item measures
and formative multi-item measures. A reﬂective measurement model was appropriate in
cases where observed variables were manifestations of underlying constructs (Bagozzi
and Baumgartner 1994). If a construct was a summary index of observed variables, a

formative measurement model was employed (Bollen and Lennox 1991; Diamantopoulos

and Winklhofer 2001 ).

60

Construct measurements are presented below in three categories. First, resources
are discussed. Second, activities that represent the facets of market knowledge
competence are presented. Third, the components of ﬁrm performance are examined
based on the balanced scorecard approach.

4.3.1 Resources

Based on the theoretical discussion in Chapter 11, resources consist of strategic
assets and capabilities. While relational assets represent strategic assets, the market
orientation culture refers to capabilities.
4.3.1.1 Relational Assets

Relational assets refer to the extent to which a ﬁrm has developed valuable
strategic assets that are speciﬁc to business relationships with key marketing channel
partners (Hunt and Morgan 1995; Srivastava, Shervani, and Fahey 1998). Two types of
relational assets were identiﬁed as: (l) retailer/distributor equity and (2) supplier equity.
N0 scales for equity constructs were available in the literature. Subsequently, scales for
retailer/distributor and supplier equity incorporated the characteristics of Bamey’s (1992)
VRIO characteristics and were developed based on Amit and Schoemaker’s (1993)
conceptualization of valuable assets (characterized by complementarity, overlap with
SIFs, low tradeability, inimitability, limited substitutability, durability). The scales for

relational assets were implemented as follows:

61

Retailer/Distributor Equity

Please rate the extent of your agreement or disagreement with each of thefollowing
statements that relate to your ﬁrm ’3 partners in the value chain.

Strongly Strongly
Disagree Agree

1. If the relationship with this channel partner were 1 2 3 4 5 6 7
to end, it would be difﬁcult for us to ﬁnd
another partner that has shared unique
knowledge in our relationship.

2. If this channel partner switched to a competitor, 1
they would be wasting a lot of knowledge that is
tailored to our relationship.

3. This channel partner shares knowledge aligned l 2 3 4 5 6 7
with the needs of our markets.

4. We each have separate knowledge that, when l 2 3 4 5 6 7
combined, enables us to achieve goals beyond
our individual reach.

10
b)
.5
kl]
O5
\I

5. It would be difﬁcult for other ﬁrms to imitate l 2 3 4 5 6 7
the knowledge of this channel partner.

6. This channel partner does much to provide a 1 2 3 4 5 6 7
stable knowledge stream as part of our
relationship.

62

Supplier Equity

Please rate the extent of your agreement or disagreement with each of the following
statements that relate to your ﬁrm ’s partners in the value chain.

Strongly Strongly
Disagree Agree
1. If the relationship with this supplier were to end, 1 2 3 4 5 6 7
it would be difﬁcult for us to ﬁnd another
supplier that has shared unique knowledge in
our relationship.
2. If this supplier switched to a competitor, they 1 2 3 4 5 6 7
would be wasting a lot of knowledge that is
tailored to our relationship.
3. This supplier shares knowledge aligned with the l 2 3 4 5 6 7
needs of our markets.
4. We each have separate knowledge that, when l 2 3 4 5 6 7
combined, enables us to achieve goals beyond
our individual reach.

5. It would be difficult for other ﬁrms to imitate l 2 3 4 5 6 7
the knowledge of this supplier.

6. This channel partner does much to provide a l 2 3 4 5 6 7
stable knowledge stream as part of our
relationship.

4.3.1.2 Market Orientation Culture

The market orientation culture is deﬁned as the organization-wide shared values
and beliefs, which (1) put the customer’s interest ﬁrst, while not excluding those of all
other stakeholders, and (2) place a high degree of value on market analysis for creating
superior customer value. Because the scope of market orientation culture should include
key stakeholders in the market that possess or create knowledge, three subscales were
used to measure the market orientation culture construct: customer orientation,
competitor orientation, and retailer/distributor orientation. Consistent with how such
formative measures are interpreted (Bollen and Lennox 1991; Diamantopoulos and

Winklhofer 2001), it is posited that ﬁrms have higher levels of market orientation culture

63

because they are customer, competitor, and/0r retailer/distributor oriented. Thus, market
orientation culture is conceptualized as a formative second-order construct composed of
these three subscales. That is, market orientation culture is a second-order factor that has
three ﬁrst-order factors as formative indicators and the three ﬁrst-order factors
themselves have reﬂective indicators.
Customer Orientation

Customer orientation assesses the extent to which a ﬁrm has developed
organization-wide shared values and beliefs that support learning from and monitoring
customers. The customer orientation subscale is a reﬂective measure, which includes six
items. The construct was measured by scales that were modiﬁed versions of the items
used by Deshpandé, Farley. and Webster (1993) and other items used by Narver and

Slater (1990).

64

Please indicate the extent to which you agree or disagree with each of the following
statements that relate to your firm ’s values and beliefs with respect to customers.

Strongly Strongly
Disagree Agree
1. We place great value on our commitment to the 1 2 3 4 5 6 7
highest standards of integrity and ethics when
serving our customers.
2. We believe our business exists primarily to 1 2 3 4 5 6 7
serve customers.
3. We believe that understanding the needs of our 1 2 3 4 5 6 7
customers is necessary to achieve a competitive
advantage.
4. We believe that how our customers value our 1 2 3 4 5 6 7
products drives our business strategies.
5. We believe it is important to constantly monitor 1 2 3 4 5 6 7
our level of customer service in our business
operations.
6. We believe that frequently measuring customer 1 2 3 4 5 6 7
satisfaction is necessary to achieve a competitive
advantage.

Competitor Orientation

Competitor orientation assesses the extent to which a ﬁrm has developed
organization-wide shared values and beliefs that support learning from and monitoring
competitors. The competitor orientation subscale is a reﬂective measure, which consists
of six items. The construct was measured by new scales driven by Jaworski and Kohli’s

(1993) intelligence generation and intelligence dissemination constructs and Narver and

Slater’s (1990) competitor orientation construct.

65

Please indicate the extent to which you agree or disagree with each of the following
statements that relate to your ﬁrm ’s values and beliefs with respect to competitors.

Strongly Strongly
Disagree Agree
1. We believe that it is necessary to constantly 1 2 3 4 5 6 7
monitor competitor activities in our business
environment.
2. We believe it is necessary to evaluate the l 2 3 4 5 6 7
strengths and weaknesses of competitors.
3. We believe that it is important to closely l 2 3 4 5 6 7

monitor the strategic moves of our key and
potential competitors.
4. We value information about the performance of l 2 3 4 5 6 7
competitors.
5. We place great value on information about 1 2 3 4 5 6 7
competitor success and/or failure.
6. We place great value on information about new 1 2 3 4 5 6 7
product introductions by competitors.
Retailer/Distributor Orientation
Retailer/distributor orientation assesses the extent to which a ﬁrm has developed
organization-wide shared values and beliefs that support learning from and monitoring
retailers/distributors. The retailer/distributor orientation subscale is a reﬂective measure
composed of ﬁve items. The construct was measured by new scales driven by Jaworski

and Kohli’s (1993) intelligence generation and intelligence dissemination constructs and

Narver and Slater’s (1990) customer orientation and competitor orientation constructs.

66

Please rate the extent of your agreement or disagreement with each of thefollowing
statements that relate to your ﬁrm 's partners in the value chain.

Strongly Strongly
Disagree Agree
1. We believe that it is necessary to constantly 1 2 3 4 5 6 7
monitor the activities of our channel partners.
2. We believe it is necessary to evaluate the 1 2 3 4 5 6 7
strengths and weaknesses of our channel
partners.
3. We believe it is important to closely monitor 1 2 3 4 5 6 7

changes in key and potential channel partners in

our business environment.
4. We value information on the performance of l 2 3 4 5 6 7

products and services offered by our channel

partners (e.g., cost, quality, speed, ﬂexibility).
5. We place great value on lessons learned from 1 2 3 4 5 6 7

successful and/or unsuccessful experiences with

our channel partners.
4.3.2 Market Knowledge Competence

The activities that represent the facets of market knowledge competence include

market scanning, market information transmission, market information interpretation, and
market knowledge utilization (Huber 1991; Moorman 1995). This dissertation
conceptualizes market knowledge competence as a formative second-order construct
composed of four market knowledge activities. It is posited that a ﬁrrn’s market
knowledge competence enhances when its market scanning, transmission of market
information, interpretation of market information, and/or utilization of market knowledge
increases. Accordingly, market knowledge competence is a second-order factor that has
four ﬁrst-order factors as formative indicators and the four ﬁrst-order factors themselves

have reﬂective indicators.

Market Scanning

67

Market scanning refers to an information acquiring and gathering activity, which
involves both formal and informal search about the marketplace (Aguilar 1967; Day
1994; Hambrick 1982; Kiesler and Sproull 1982; Miller and Friesen 1982; Starbuck
1976) and is operationalized as the extent of effort dedicated toward market scanning
devices and the comprehensiveness of the market scanning process (Barringer and
Bluedom 1999). It is a reﬂective measure composed of nine items. The construct was
measured by scales of scanning devices adapted from Miller and Friesen (1982) and
scales adapted from Barringer and Bluedom’s (1999) scanning comprehensiveness

construct.

68

Please indicate the extent to which you agree or disagree with each of the following items
that relate to your ﬁrm ’3 collection of market information.

Strongly Strongly
Disagree Agree
1. We use routine gathering of opinions from 1 2 3 4 5 6 7
customers to obtain information about the
marketplace.
2. We frequently use explicit tracking of 1 2 3 4 5 6 7

competitor policies and tactics to obtain
information about the marketplace.

3. We frequently make use of certain mechanisms 1 2 3 4 5 6 7
to gather marketplace information from partners
in the value chain (e.g., suppliers, distributors,
retailers).

4. We frequently make use of forecasting l 2 3 4 5 6 7
techniques (e.g., sales, customer preferences,
technology) to understand the dynamics of the
marketplace better.

5. We frequently make use of marketing research 1 2 3 4 5 6 7
studies to obtain information about the
marketplace.

6. We frequently collect information about market 1 2 3 4 5 6 7
trends and developments to remain abreast of
changes in our marketplace (e.g., economic,
technological, and/or demographic trends).

7. We frequently collect information about 1 2 3 4 5 6 7
customer needs and preferences to remain
abreast of changes in our marketplace.

8. We frequently collect information about I 2 3 4 5 6 7
competitor operations to remain abreast of
changes in our marketplace.

9. We frequently collect information about the l 2 3 4 5 6 7
operations of partners in the value chain to
remain abreast of changes in our marketplace
(e.g., suppliers, distributors, retailers).

Market Information Transmission
Market information transmission captures the extent to which market information
is diffused among relevant users within a given organization (Beyer and Trice 1982;

Jaworski and Kohli 1993; Moorman 1995). Transmission of information related to

69

customers, competitors, and market trends encompasses both vertical and horizontal
channels (Van de Ven, Delbecq and Koenig 1976). Market information transmission is a
reﬂective measure composed of a six-item scale. The construct was measured by scales
adapted from Jaworski and Kohli’s (1993) intelligence dissemination construct, Slater
and Narver’s (1994) coordination construct, and Matsuno and Mentzer’s (2000)
intelligence dissemination construct.

Please indicate the extent to which you agree or disagree with each of the following items
that relate to your ﬁrm ’s transmission of market information.

Strongly Strongly
Disagree Agree
1. Marketing personnel in our ﬁrm spend time 1 2 3 4 5 6 7

discussing customer future needs with other
functional departments.

2. When something important happens to a major I 2 3 4 5 6 7
customer in our business market, the whole ﬁrm
knows about it within a short period.

3. In our ﬁrm, information about our successful 1 2 3 4 5 6 7
and unsuccessful customer experiences is
transmitted at all levels on a regular basis.

4. When one department ﬁnds out something 1 2 3 4 5 6 7
important about competitors, it is fast to alert
other departments.

5. We have interdepartmental meetings at least 1 2 3 4 5 6 7

once a quarter to discuss market trends and

developments (e.g., economic, technological,

and/or demographic trends).
6. Market information spreads quickly through all 1 2 3 4 5 6 7

levels in this ﬁrm.
Market Information Interpretation

Market information interpretation refers to the managerial activity that involves

translating market events, developing frameworks for understanding the marketplace,

bringing out meaning, and assembling conceptual schemes among key managers (Daft

and Weick 1984). It is a reﬂective measure composed of a six-item scale. The construct

70

was measured by new scales driven by Isabella’s (1990) conceptualization of information
interpretation.

Please indicate the extent to which you agree or disagree with each of the following items
that relate to your firm ’5 understanding of market information.

To reach a shared understanding, we Strongly Strongly

frequently. . . Disagree Agree

1. assemble pieces of market information into a l 2 3 4 5 6 7
coherent and logical format.

2. summarize market information to reduce its 1 2 3 4 5 6 7
complexity.

3. generate explanations for the given market 1 2 3 4 5 6 7
information.

4. refer to past similar events to frame new market 1 2 3 4 5 6 7
information in a consistent format.

5. challenge each other’s opinions on the given 1 2 3 4 5 6 7
market information.

6. reconstruct our understanding about the l 2 3 4 5 6 7
marketplace as new market information is
obtained.

Market Knowledge Utilization

Market knowledge utilization captures the extent to which an organization
directly applies market knowledge to the marketing strategy related actions (Menon and
Varadarajan 1992; Moorman 1995). It is a reﬂective measure composed of a six-item
scale. The scales for market knowledge utilization were adapted from Moorrnan’s (1995)
instrumental utilization construct and driven by Day’s (1984) conceptualization of the

marketing strategy development process.

71

Please indicate the extent to which you agree or disagree with each of thefollowing items
that relate to yourﬁrm ’s use of market knowledge.

Strongly Strongly

We rely heavily on market knowledge Disagree Agree

1. to carefully evaluate various marketing strategy 1 2 3 4 5 6 7
alternatives.

2. to strategically plan our marketing activities 1 2 3 4 5 6 7
(e.g., planning, goal setting. budgeting).

3. to make strategic decisions related to our 1 2 3 4 5 6 7
marketing activities.

4. to formally evaluate the effectiveness of our 1 2 3 4 5 6 7
marketing activities.

5. to guide and direct our marketing efforts. 1 2 3 4 5 6 7

6. to provide clear direction to all functions 1 2 3 4 5 6 7

regarding their role in implementation.

4.3.3 Firm Performance

The balanced scorecard approach was adopted to measure ﬁrm performance. The
four building blocks of the balanced scorecard are customer performance, marketing
strategy formulation and implementation speed, marketing learning performance, and
ﬁnancial performance. Although objective measures may have been more ideal for
customer and ﬁnancial performance, recent research points out that managerial
assessments of these performance outcomes are widely used and that there are high
correlations between subjective and objective performance measures (c.f. Dess and
Robinson 1984; Menon et a1. 1999; Song et a1. 2005). Accordingly, the subjective
measures were utilized for assessing customer and ﬁnancial performance.
Customer Performance

Customer performance is deﬁned as the effectiveness of a ﬁrm’s marketing

strategy representing how well a ﬁrm performs with respect to its customers. The scales

72

for customer performance were adapted from Homburg and Pﬂesser’s (2000) market
performance construct.

Please rate the extent to which your ﬁrm has achieved thefollowing customer outcomes
relative to major competitors over the past year.

 

hduch Aduch

Worse Better
1. Achieved customer satisfaction. 1 2 3 4 5 6 7
2. Kept current customers. 1 2 3 4 5 6 7
3. Attracted new customers. 1 2 3 4 5 6 7
4. Attained desired growth. 1 2 3 4 5 6 7
5. Attained desired market share. 1 2 3 4 5 6 7

Marketing Strategy Formulation and Implementation Speed

No scale for the ﬁrm’s marketing strategy formulation and implementation speed
was available in the literature. The construct was measured by new scales driven by the
cycle time construct developed by Hult and his colleagues (Hult 1998; Hult, Ketchen, and
Nicholas 2002). Scales for marketing strategy formulation and implementation speed
were developed and implemented as follows:

Please rate the extent to which your ﬁrm has achieved thefollowing development and
implementation outcomes over the past year.

 

Strongly Strongly
Disagree Agree
1. Our marketing strategy was developed in a short 1 2 3 4 5 6 7
time period.
2. We have seen an improvement in the l 2 3 4 5 6 7

development time of our marketing strategy.
3. We were very quick to develop our marketing 1 2 3 4 5 6 7
strategy.

4. We are satisﬁed with the speediness of the l 2 3 4 5 6 7
implementation of our marketing strategy.

5. The length of the implementation of our 1 2 3 4 5 6 7
marketing strategy could not have been much
shorter.

6. We were very quick to implement our marketing 1 2 3 4 5 6 7
strategy.

73

Marketing Learning Performance

Marketing learning performance refers to the development of marketing skills of
the ﬁrm’s employees and the improvement in their understanding about the market
(Menon et a1. 1999). No scale for marketing learning performance was available in the
literature. The construct was measured by new scales driven by Menon et al.’s (1999)
organizational learning construct.

Please rate the extent of your agreement or disagreement with each of thefollowing
marketing learning outcomes over the past year.

Strongly Strongly
Disagree Agree
1. We have a larger proportion of skilled marketing 1 2 3 4 5 6 7
employees this year than last year.
2. We have a larger proportion of marketing 1 2 3 4 5 6 7
employees learning new managerial skills this
year than last year.
3. We have a larger proportion of marketing 1 2 3 4 5 6 7
employees who have improved their
understanding about our marketplace this year
than last year.

Financial Performance

Financial performance is deﬁned as the extent to which a ﬁrm’s marketing
strategy and its implementation contribute to bottom-line improvement (Kaplan and
Norton 2005). Financial performance was measured by adapting scales pertaining to the
return on sales (Lewis and Thomas 1990), return on investment (Boeker 1991; Lawless

and Finch 1989), return on assets (Dess and Davis 1984), and average proﬁt margin

(Kumar 1990).

74

Please rate the extent to which your ﬁrm has achieved thefollowing ﬁnancial outcomes

compared to their stated objectives over the past year.

Very

Poor Excellent
1. Sales (revenue). 1 2 3 4 5 6 7
2. Average proﬁt margin. 1 2 3 4 5 6 7
3. Return on investment. I 2 3 4 5 6 7
4. Return on assets. 1 2 3 4 5 6 7
5. Return on sales. 1 2 3 4 5 6 7

75

 

CHAPTER V
ANALYSIS AND FINDINGS

Chapter V details the various steps undertaken to analyze the data collected by the
survey methodology. First, the evaluation of data quality is discussed. Second,
measurement issues are examined and bootstrapping is illustrated. Third, the hypothesis
testing is provided.
5.] Evaluation of Data Quality

A total of 122 questionnaires were usable. Table 4 contains the sample
characteristics. Sixty-six percent of the respondents had senior management titles,
twenty-seven percent of the respondents had middle-level management titles, and seven
percent of the respondents did not report their position in the company. Moreover, the
respondents’ experience was used as a proxy for knowledge. On average, the respondents
had 12.5 years of experience with the ﬁrm and approximately 20.8 years of industry
experience. These levels are comparable to other samples of top management informants
(c.f. Menon, Bharadwaj, and Howell 1996; Menon et a1. 1999). Table 4 presents a
breakdown of respondents by their experience with the ﬁrm and industry. The

respondents belonged to manufacturing (41.8%) and service sectors (58.2%).

76

Table 4: Sample Characteristics

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Characteristics Specifics Frequency Percent

CEO / President 9 7%

Vice President 32 26%

C MO 2 2%

RCSPOHde‘S Executive Vice l4 1 1%

T1110 President
Director / 24 20%
Senior Director

Managers 33 27%

__ Not Reported 8 7%
Respondent’s Exp 3 5 40 32.8%
Experience 5 < Exp g 10 27 22.1%
with the Firm 10 < Exp S 15 15 12.3%
, (Exp) 4 15 < Exp 3 25 24 19.7%
[m Years] Exp > 25 16 13.1%

F Respondent’s 1nd 3 5 l l 9%
Experience 5 < Ind g 10 18 14.8%
with the 10 < Ind S 15 32 11.40/0
Industry (1nd) ‘5 < 1nd S 25 33 30.4%
1‘“ Years] Ind > 25 26 34.49..

 

Subsequently, non-response bias was assessed by grouping responses into two

77

groups: early responses vs. late responses (Armstrong and Overton 1977). The
questionnaires received in the ﬁrst mailing were divided into two groups based on the
date on which they were received. There were twenty-six responses in the ﬁrst group and
thirty-one late responses. The two groups were then compared on annual sales volume.
number ofemployees. and length oftime in the industry (Menon et al. 1999). Among
early responses. 23 out of 26 respondents reported the annual sales ﬁgure, 25 out of 31
respondents reported number of employees, and 25 out of 26 respondents reported the
length of time in the industry. Among late responses, 28 out of 31 respondents reported
the annual sales ﬁgure, 29 out of 31 respondents reported number of employees, and all

31 respondents reported the length of time in the industry. Based on a comparison of the

 

averages ofannual sales, number of employees, and length of time in the industry there
was no signiﬁcant non-response bias present in the dataset (Armstrong and Overton
1977). Table 5 presents the results of the t-test for selected variables.

Table 5: Non-Response Bias

 

 

 

 

 

Early Late 2-tail
Variable Respondents Respondents t-value Signiﬁcance
Mean (11) Mean (11) Level
Annual Sales 3551 3580 .018 .986
[in $ Million]
Number of 12050.80 14781.03 .460 .647
Employees
Length of Time 53.81 56.13 .216 .83
in Industry

 

 

 

 

 

 

5.2 Measurement Model

As suggested by F ornell and Larcker (1981, p. 45), “before testing for a
significant relationship in the structural model, one must demonstrate that the
measurement model has a satisfactory level of validity and reliability.” Accordingly,
conlirmatory factory analysis (C FA) is carried out to investigate the validity of each
construct using EQS for Windows 6.1 (Bentler 1995) before proceeding to conduct data
analyses to test the hypotheses embedded in the theoretical model. The C FA model
included thirteen constructs: (a)_/ive resource constructs including two strategic asset
constructs (retailer/distributor equity and supplier equity) and three capability constructs
(customer orientation, competitor orientation, and retailer/distributor orientation); (b)‘four
market knowledge activity constructs (market scanning, market information transmission.
market infomiation interpretation, and market knowledge utilziation); and (c) four
performance constructs (customer performance, marketing strategy formulation and

implementation speed. marketing learning performance, and ﬁnancial performance).

78

 

The scales were evaluated using a CF A that involved raw data as input since CF A
is a more rigorous method for assessing unidimensionality than coefﬁcient alpha,
exploratory factor analysis, and item-total correlations (Anderson and Gerbing 1988).
Accordingly, measures were subjected to a puriﬁcation process involving
unidimensionality, reliability, and convergent and discriminant validity assessments
(Bagozzi and Phillips 1982; Bollen 1989; Churchill 1979; Gerbing and Anderson 1988).
In the puriﬁcation process of items in the measurement model, the items that were
weakly loaded (e.g., < .5) on their respective constructs were eliminated due to problems
with convergent validity (Bagozzi and Yi 1988). Furthermore, items that are cross-linked
to multiple constructs weakening discriminant validity were examined and deleted if
necessary for the item level discriminant validity based on the multivariate Lagrange
Multiplier (LM) test (Bentler 1995).

After the items for each construct were delineated, the procedure recommended
by Bagozzi and Yi (1988) was used to evaluate the ﬁt of the measurement model. First,
the univariate and multivariate statistics of the input variables were screened and no
apparent outlier was detected. Second, the EQS output was examined but no anomalies or
no special problems in the minimization process were found. In addition, the variance
estimates were all signiﬁcantly greater than zero. These ﬁndings suggest that the
estimation process converged properly for the measurement model.

Third, the CFA model was evaluated using the comparative ﬁt index (CFI), the
non-normed ﬁt index (NNFI), and the root mean square error of approximation
(RMSEA). As presented in Table 6, the results of the CFA model yielded good ﬁt lndices

including Chi-square of 929.50 on 699 degrees of freedom, CF I of .93. NNFI of .92, and

79

 

R MSl'iA of .05. indicating that the measurement model has a very good ﬁt with the

covariances provided by the sample.

Table 6: Results of the Measurement Model Analysis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Construct and Measurement Items Standardized t-valueb
Average variance extracted Loading'
Highest shared variance
Composite reliability
RESOURCES

RETEQ: Retailer/Distributor
Equity RETEQ. .63 7.05
RETEQ4 .71 8.20
RETEQt, .83 9.79
Average variance extracted 53%
Highest shared variance 32%
Composite reliability .77
SUPEQ: Supplier Equity
SUPEQ. .68 7.79
SUPEQ4 .83 10.00
SUPEQO .77 9.00
Average variance extracted 58%
Highest shared variance 24%

__ Composite reliability .80

Market Orientation Culture

CUSTO: Customer Orientation
CUSTO3 .83 9.51
C USTO4 .73 8.27
C UST05 .62 6.79
Average variance extracted 53.7%
Highest shared variance 19%

ﬁComposite reliability .77
COMPO: Competitor Orientation
COMPO. .88 11.93
COMPO3 .90 12.44
COMPO4 .84 11.10
COMPO(, .79 10.19
Average variance extracted 72.5%
Highest shared variance 18%
Composite reliability .91

 

80

 

Table 6 (cont’d): Results of the Measurement Model Analysis

 

RETRO: Retailer/Distributor
Orientation

 

 

 

 

 

 

 

 

RETRO3 .83 10.91
RETRO4 .86 11.57
RETR05 .94 13.21
Average variance extracted 76.7%
Highest shared variance 32%
Composite reliability .91

Market KnowledggCompetence
MSCAN: Market Scanning
MSCAN3 .62 6.62
MSCAN4 .68 7.34
MSCAN6 .78 8.55
Average variance extracted 48%
Highest shared variance 30%
Composite reliability .73
ITRAN: Market Information
Transmission
ITRAN3 .87 11.61
ITRAN4 .79 10.17
ITRANb .92 12.80
Average variance extracted 74.1%
Highest shared variance 44%
Composite reliability .90
IINTP: Market Information
Interpretation
llNTP; .91 12.78
llNTPg .91 12.80
IINTP3 .89 12.46
Average variance extracted 81.6%
Highest shared variance 62%
Composite reliability .93
MUTIL: Market Knowledge
Utilization
MUTIL1 .86 11.67
MUTIL; .96 14.12
MUTIL3 .94 13.82
Average variance extracted 84.5%
Highest shared variance 62%
Composite reliability .94

 

 

 

 

81

 

 

‘F‘! 1 "z-l a"
"P
a

Table 6 (cont’d): Results of the Measurement Model Analysis

 

FIRM PERFORMANCE

 

 

 

 

 

 

 

CUSPR: Customer Performance
C USPR3 .74 9.27
CUSPR4 .96 13.46
CUSPR5 .83 10.88
Average variance extracted 72%
Highest shared variance 22%
Composite reliability .88
SPEED: Strategy Formulation
and Implementation Speed
SPEED. .61 6.60
SPEED; .94 10.29
SPEED, .61 6.58
Average variance extracted 54.1%
Highest shared variance 10%
Composite reliability .77
LRNPR: Marketing Learning
Performance
LRN PR1 .84 10.98
LRNPR; .88 l 1.76
LRNPR3 .83 10.80
Average variance extracted 72.9%
Highest shared variance 9%
Composite reliability .89
FINPR: Financial Performance
FINPR; .85 11.48
FINPR3 .97 14.44
FINPR4 .95 13.93
FINPR5 .89 12.61
Average variance extracted 83.6%
Highest shared variance 22%
Composite reliability .95
CFA Model Goodness-of-F it lndices:
Chi—square statistic of the model 929.50
(Degrees of freedom) (699)
Bentler-Bonett nonnonned ﬁt index (NNFI) .92
Comparative ﬁt index (C Fl) .93
Root mean square error of approximation (RMSEA) .05
90% Conﬁdence Interval RMSEA (.04 - .06)

 

F“ All standardized loadings are signiﬁcant at p < .05.
" The t-values from the unstandardized solution.

 

 

 

 

Fourth, convergent validity and discriminant validity were examined as a part of a
unidimensionality assessment of each construct. For convergent validity, the standardized
loading of each item must be greater than .5 (Bagozzi and Yi 1988; Bagozzi, Yi, and
Phillips 1991). As shown in Table 6, items loaded on each hypothesized construct
signiﬁcantly as expected (p < 0.01; two-tailed) and no standardized loading was less than
.5. That is, there is an adequate level of convergent validity established for each
construct.

Moreover, the discriminant validity was established by calculating the shared
variance between all possible pairs of constructs and verifying that they were lower than
the average variance extracted for the individual constructs (Fomell and Larcker 1981).
The shared variance was calculated as y2 = 1 - ‘1’, where y2 = shared variance between
constructs and the diagonal element of ‘1’ indicates the amount of unexplained variance.
Because 11 and s are standardized, 72 is equal to the r2 between the two constructs. The
average variance extracted was calculated as Vn = EM? / (22?qu2 + 280, where Vn =
average variance extracted for n, Mi = standardized loading for scale item Yr, and Si =
measurement error for scale item Yi- As shown in Table 6, the shared variances between
pairs of all possible scale combinations ranged from a low of 9% to a high of 62%
between the various scale combinations. The average variances extracted ranged between
48% and 84.5%, all having higher average variances extracted than the shared variances
among all applicable pairs of scales. To assess discriminant validity further, following
Bagozzi and Phillips (1982), pairs of scales were assessed in a series of two-factor
conﬁrmatory models using EQS for Windows 6.1. Accordingly, each model was

performed twice — once constraining the phi coefﬁcient ((1)) to unity and once freeing the

83

parameter. Then, a )6 test was used to test for differences between models. In all cases.
the x2 results were higher in the constrained models, thereby indicating discriminant
validity between the constructs.

As a ﬁnal step to assess the unidimensionality of each construct (Churchill 1979;
Fomell and Larcker 1981; Gerbing and Anderson 1988), composite reliability for each
construct was calculated using the following formula suggested by Fomell and Larcker
(1981): CRn = (21702 / [QM/02 + (2a)], where CRn = composite reliability for scale 11,
Mi = standardized loading for scale item 1’1. and Si = measurement error for scale item 7i.
Composite reliability represents the shared variance among a set of observed variables
that measure an underlying construct (Fomell and Larcker 1981). As shown in Table 6,
all composite reliabilities are above .7, indicating acceptable levels of reliability for the
constructs. The Appendix shows that there were at least three puriﬁed items for each
construct that remained in the measurement model after ensuring the unidimensionality
of the multiple-item constructs and eliminating unreliable items from them.

5.3 Measurement Model Validation via Bootstrapping

Because the total number of items utilized to measure the study constructs was
high relative to the sample size, bootstrapping, in this dissertation, was performed for
assessing the measurement model through the evaluation of parameters and model ﬁt
using EQS for Windows 6.1 (Bentler 1995). The discussion will now turn to the
illustration of the bootstrap method. Then, the results of the bootstrapped measurement

model will be provided.

84

5.3.1 Bootstrap Method

Bootstrapping is a method for “calculating approximated biases, standard
deviations, and conﬁdence intervals and so forth, in almost any nonparametric estimation
problem” (Efron 1982, 1987). The bootstrap method determines a sampling distribution
of a parameter estimate whose theoretical sampling distribution is unknown (Bone,
Sharma, and Shimp 1989). The procedure consists of four basic steps. First, the effective
original sample (N = 122) is designated to act as the population for sampling purposes.
The bootstrap method treats a random sample of data as a substitute for the population
and resamples it a speciﬁed number of times to generate bootstrap estimates and standard
errors. In the second step, the original data is resampled with replacement until a
bootstrap sample of appropriate sample size (n = 122) is obtained. The resampling
procedure is then repeated 100 times to generate a large number of new samples, each a
random subset of the original sample. It is suggested that 100 replications are sufﬁcient
for estimating standard error (Efron and Tibshirani 1986). In the third step, parameters
from these 100 bootstrap samples are then serially estimated using EQS for Windows 6.1.
Only parameter estimates from the converged bootstrap samples are saved for further
statistical testing. Bootstrap samples with non-converged or improper solutions are
deleted. In the last step, these sample bootstrap estimates and standard errors are
averaged and used to obtain a conﬁdence interval around the average of the bootstrap
estimates. This average is termed a bootstrap estimator. The bootstrap estimator and
associated conﬁdence interval are used to determine how stable the sample statistic is as

an estimate of the population parameter.

85

For evaluating model ﬁt, the bootstrap method involves separation of errors into
sampling versus nonsampling errors (such as errors including model misspeciﬁcations or
the presence of method factors, demand characteristics, correlated errors, and other
possible sources of error). The procedure starts with estimating model parameters from
the original sample data and obtaining the reported ﬁt indices. Any less-than-perfect ﬁts
obtained from the model analysis are due to both sampling and nonsampling errors.

To obtain only the sampling error, the average of ﬁt indices must be obtained
from a model analysis of bootstrap samples (0). Any less-than-perfect ﬁt indices reported
from the bootstrap method represent only sampling errors. Once the sampling error of the
data is obtained, the nonsampling error can be calculated, since the value of less-than-
perfect ﬁt due to nonsampling error equals the average of ﬁt indices obtained from model
analysis of bootstrap samples (0) minus the value of the ﬁt index for the original sample
data (0,), as illustrated in Figure 5.

Figure 5: Sampling Error versus Nonsampling Error for GFI and AGFI

 

 

 

 

 

 

Nonsampling Sampling Error
Enor
0 0, = 0 = 1
Original Average Perfect
sample model ﬁt indices ﬁt

To assess whether the sampling error is signiﬁcantly different from total error,
the bootstrap-t value (BST-value) is calculated. As suggested by Bone, Sharma, and
Shimp (1989), the BST-value equals (0 - 09/89, where 0 and So are the values of the

average and standard errors of ﬁt indices obtained from model analyses of bootstrap

86

 

samples, and 95 is the value of the ﬁt index from the original sample data. Again, 0

represents only sampling error, whereas 08 includes both sampling and nonsampling
errors. If the BST-value is statistically signiﬁcant, it means that the less-than-perfect ﬁt of
the model is signiﬁcantly less than what would be expected due to sampling error alone.
In other words, the less-than-perfect ﬁt of the model is also due to nonsampling error
when BST-value is signiﬁcant.

Following Bone, Sharma, and Shimp (1989), the absolute ﬁt indices (OF I and
AGFI) were chosen for evaluating model ﬁt because the absolute ﬁt indices directly
assess how well an a priori model reproduces the sample data (Hu and Bentler 1995).
That is, the absolute ﬁt indices compare the hypothesized model with no prespeciﬁed
model at all (Byrne 1998). In addition to absolute ﬁt indices, this dissertation also
provides an incremental ﬁt index (CFI) that measures how much better the model ﬁts in
comparison to the baseline model. Because the use of CFI for the bootstrapping model
evaluation was not considered by Bone, Sharma, and Shimp (1989), it is presented in this
dissertation only to provide additional information and will not be used to evaluate the
model ﬁt.

The ﬁnal index for assessing the model ﬁt in bootstrapping is the normed ﬁt
index, which is calculated as the ratio of ﬁt indices estimated from the original data (05)
to average ﬁt indices from the bootstrapping procedure (0) (Bone, Sharma, and Shimp
1989). The higher the NF], the less severe the lack of model ﬁt due to nonsampling error.
While there is no objective cutoff value for NFI, Bone, Sharma, and Shimp (1989)

suggested that, for practical purposes, NFl above 0.80 indicates a signiﬁcant model ﬁt.

87

5.3.2 Bootstrapping Measurement Model

Having conducted a C FA analysis for the theoretical model, the original effective
sample was bootstrapped and the measurement model was assessed through examining
the convergent and discriminant validity of the proposed constructs, and evaluating the
model ﬁt. As presented in Table 7, all average loadings from the bootstrap procedure
were highly signiﬁcant (p < .01; two-tailed) with unstandardized loadings ranging from
.67 to 1.55, demonstrating good convergent validity. The conﬁdence interval around the
mean of the bootstrap sample correlation between any two latent constructs did not
contain one, showing good discriminant validity. Furthermore, all the unstandardized
loadings obtained from the original sample did fall within their corresponding ninety-ﬁve

percentile bootstrap conﬁdence intervals.

88

Table 7: Results of the Bootstrapped Measurement Model Analysis

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Construct and Measurement Items Average 95% Conﬁdence
Unstandardized Interval
LoadingII
RESOURCES
RETEQ: Retailer/Distributor
Equity RETEQI .85 .63 - 1.07
RETEQ4 .94 .61 - 1.22
RETEQb 1.07 .82 - 1.31
SUPEQ: Supplier Equity
SUPEQ. .97 .77 - 1.17
SUPEQ4 1.17 .98 - 1.41
SUPEQ6 .92 .73 - 1.10
Market Orientation Culture
CUSTO: Customer Orientation
CUSTO; .70 .44 - .94
CUSTO4 .76 .56 - .96
CUSTOS .67 .44 - .87
COMPO: Competitor Orientation
COMPO. .98 .83 - 1.12
COMP03 1.03 .87 - 1.16
COMPO4 .89 .74 - 1.08
COMPO(, .90 .74 - 1.06
RETRO: Retailer/Distributor
Orientation
RETRO3 .89 .66 - 1.09
RETRO4 1.04 .87 - 1.22
RETR05 1.11 .94 - 1.28
Market Knowledge Competence
MSCAN: Market Scanning
MSCAN3 .79 .53 - 1.06
MSCAN4 .98 .60 - 1.28
MSCAN6 1.04 .78 - 1.32
ITRAN: Market Information
Transmission
ITRAN3 1.25 1.09 - 1.39
1TRAN4 1.16 .99 - 1.33
ITRAN6 1.43 1.28 - 1.61

 

 

 

89

 

Table 7 (cont’d): Results of the Bootstrapped Measurement Model Analysis

 

 

 

 

IINTP: Market Information

Interpretation

llNTP. 1.47 1.32 - 1.63
llNTPz 1.39 1.25 - 1.51
IINTP:. 1.30 1.17 - 1.46
MKUSE: Market Knowledge

Utilization

MUTIL. 1.20 1.07 - 1.33
MUTIL; 1.31 1.17 - 1.44
MUTIL3 1.20 1.07 - 1.33

 

FIRM PERFORMANCE

 

 

 

 

C USPR: Customer Performance

CUSPR3 .84 .72 - .95
CUSPR4 1.33 1.20 - 1.49
CUSPR:; 1.16 1.00 -1.31
SPEED: Strategy Formulation

and Implementation Speed

SPEED. .95 .71 - 1.17
SPEED3 1.23 1.02 - 1.41
SPEED, .78 .60 - .94
LRNPR: Marketing Learning

Performance

LRNPR. 1.55 1.36 - 1.75
LRNPRZ 1.52 1.33 - 1.68
LRNPR3 1.25 1.03 - 1.45
F INPR: Financial Performance

FINPR2 1.16 1.01 -1.28
FINPR3 1.37 1.23 - 1.50
FINPR4 1.33 1.18-1.47
FINPR5 1.23 1.09 - 1.36

 

 

 

" All average unstandardized loadings are signiﬁcant at p < .05.

 

 

 

The results of model fit, assessed using the bootstrap method and listed in Table
8. demonstrated that the lack of ﬁt is due to sampling error only. The negative BST-

values show that the less-than-perfect ﬁt is not signiﬁcantly due to nonsampling error.

90

Table 8: Evaluation of Fit lndices for Measurement Model

 

 

 

 

 

 

 

 

Fit
lndices Average Fit
From lndices (0) Less-than- Less-than-
Original From perfect Fit perfect Fit
Sample Bootstrapping Due to Due to
Fit Model (Standard Confidence Sampling Nonsampling
lndices (0,) Error) Interval BST Error Error NF I
(0.605 —
GFI 0.767 0.636 (0.019) 0.669) -6.895 0.364 -0.131 1.206
(0.514 —
AGFI 0.713 0.552 (0.024) 0.592) -6.708 0.448 -0.l61 l 292
(0.708 —
CFI 0.933 0.750 (0.025) 0.784) -7.320 0.250 -0.183 1.244

 

 

 

 

 

5.4 Ilypothesis Testing

Having satisﬁed the requirement arising from the measurement issues, the

hypothesized structural relationships were tested using EQS path analysis (Bentler 1995).

To obtain a more favorable relationship between sample size and the number of

parameters to be estimated. the path model was preferred. The const.ucts in the path

model were represented with summated scores using equally weighted scales. Because

the summary-item constructs method yields an acceptable variable-to-sample size ratio

and reduces the model's complexity. it has been commonly employed by marketing

researchers (c.f. C alantone. Schmidt, and Song 1996; Calantone and Zhao 2001; Cavusgil

and 7.ou 1994; Li and C alantone 1998).

As illustrated in Figure 6. the path model included eight constructs;

retailer/distributor equity. supplier equity. market orientation culture. market knowledge

competence. customer performance. marketing strategy formulation and implementation

speed. marketing learning performance. and ﬁnancial performance. The market

orientation culture was a composite of three capabilities that required a second-order

91

 

formative measure (Jarvis, MacKenzie and Podsakoff 2003). Accordingly, summated
scores for customer, competitor, and retailer/distributor orientation were computed ﬁrst.
Next, the overall mean score of these three capabilities was used to measure the market
orientation culture. Market knowledge competence was conceptualized as a second-order
formative construct, as well. The same procedure was followed to represent market
knowledge competence, which is composed of market scanning, market information
transmission, market information interpretation, and market knowledge utilization. The
summated scores for these four activities were averaged to measure market knowledge

competence.

92

g. v a.
2. v 9..
~60 V Qua...

v2.

 

 

oocaEcottom
wEEmoq
wccoxcﬂz

 

 

 

oucmccofom
RESET.—

 

 

 

 

A
E.

G!

 

 

 

 

3on
53958295
£ cote—2E0“—
388%

   

8. "Ems;—

2: "Eu

2: “E22

.2. E .3 2.2 "2.3325

 

23—30
=o_§:otO
8me

 

 

 

 

 

 

 

 

oozmscotom
EEEmzu

 

 

 

 

 

00:8an00
omen—>55.
5x32

bra—um
Lozmmsm

 

 

 

 

 

 

bEcm
5:33:55
tozﬁom

 

 

 

3:53— amoh £85233 6 0.53...—

93

Figure 6 presents the hypothesized relationships embedded in the theoretical
model and Table 9 summarizes the hypothesis testing results of this dissertation. The
results revealed a very good ﬁt between the theoretical model and the empirical
covariances provided by the sample with a Chi-square of 13.17 on 14 degrees of freedom,
CFI of 1.00, NNFI of 1.00, and RMSEA of .00, as shown in Table 9. These goodness-of-
ﬁt indices are well above acceptable levels, and thus it can be concluded that the
hypothesis testing based on this model is reliable.

Also, shown in Table 9 are standardized path coefﬁcients and t-values for each
parameter. According to the results, Hypothesis 1, which states that retailer/distributor
equity has a positive direct impact on market knowledge competence, is supported with a
standardized coefﬁcient of .146 (p < .10). However, Hypothesis 2, which postulates that
supplier equity has a positive direct impact on market knowledge competence, is not
supported. Hypothesis 3, which claims that the market orientation culture positively
inﬂuences market knowledge competence, is supported; the standardized coefﬁcient is
.297 (p < .01).

The market knowledge competence is expected to affect three constructs.
Hypothesis 4 states that market knowledge competence has a positive impact on customer
performance and is supported; the standardized coefﬁcient is .281 (p < .01). Hypothesis
5, which states that market knowledge competence has a positive impact on marketing
strategy formulation and implementation speed, is supported with a standardized
coefﬁcient of .117 (p < .10). Finally, market knowledge competence is expected to
positively inﬂuence marketing learning performance, according to Hypothesis 6, which is

supported; the standardized coefﬁcient is .199 (p < .05).

94

Marketing strategy formulation and implementation speed is linked with three
performance constructs. Hypothesis 7, which claims that fast marketing strategy
formulation and implementation has a positive impact on customer performance, is
supported; the standardized coefﬁcient is .197 (p < .05). Hypothesis 8 postulates that fast
marketing strategy formulation and implementation increases ﬁnancial performance and
is supported; the standardized coefﬁcient is .137 (p < .05). In addition, fast marketing
strategy formulation and implementation is expected to positively inﬂuence marketing
learning performance, according to Hypothesis 9, which is supported with a standardized
coefﬁcient of .153 (p < .05).

Hypothesis 10, which deals with the positive effects of customer performance on
ﬁnancial performance, is supported; the standardized coefﬁcient is .413 (p < .01 ).

Also, Hypothesis 11, which states that marketing learning performance has a

positive impact on ﬁnancial performance, is supported with a standardized coefﬁcient of

.194 (p < .05).

95

Table 9: Results of the Path Model Analysis

 

Ilypothesis

Standardized
Path
Coefficient

t-value

Conclusion

 

H.: The degree ofa ﬁrm‘s
retailer/distributor equity is positively
associated with the degree of its market
knowledge competence.

.146

1.556.

Supported

 

112: The degree of a ﬁrm’s supplier
equity is positively associated with the
degree of its market knowledge
competence.

.031

.330115.

Not
supported

 

H31 The degree of a ﬁrm’s market
orientation culture is positively
associated with the degree of its market
knowledge competence.

.297

Supported

 

H4: The degree of a ﬁrm’s market
knowledge competence is positively
associated with the degree of its
customer performance.

.281

3.292'"

Supponed

 

115: The degree ofa ﬁrm’s market
knowledge competence is positively
associated with the degree of its strategy
formulation and implementation speed.

.117

1.301‘

Supported

 

Ho: The degree of a ﬁrm‘s market
knowledge competence is positively
associated with its marketing learning
performance.

.199

2.249”

Supported

 

H7: The degree ofa ﬁrm’s marketing
strategy formulation and
implementation speed is positively
associated with the degree of its
customer performance.

.197

2.314"

Supported

 

Hg: The degree of a ﬁrm’s marketing
strategy formulation and
implementation speed is positively
associated with the degree of its
ﬁnancial performance.

.137

1.710"

Supported

 

 

Hg: The degree of a ﬁrm’s marketing
strategy formulation and
implementation speed is positively
associated with the degree of its

_ marketing leamin_g performance.

.153

 

 

1.728"

 

Supported

 

96

 

Table 9 (cont’d): Results of the Path Model Analysis

 

11m: The degree of a ﬁrm‘s customer

 

performance is positively associated .413 5.192". Supported
with the degree ofits ﬁnancial

performance.

11; I: The degree ofa ﬁrm‘s marketing

learning performance is positively .194 2.469M Supported

associated with the degree of its
ﬁnancial performance.

 

 

 

 

Path Model Goodness-of—Fit lndices:
C hi-square statistic of the model
(Degrees of freedom)
Bentler-Bonett nonnormcd ﬁt index (NNFI)
Comparative ﬁt index (CFl)
Root mean square error of approximation (RMSEA)
90% Conﬁdence Interval RMSEA

13.17
(14)

1.00

1.00

.00

(.00 - .08)

 

 

mp <4 .01; "p 41.05: 'p < .1 (l-tailed test): "5' Not signiﬁcant.

 

97

 

CHAPTER VI
CONTRIBUTIONS TO THEORY AND MANAGEMENT

Chapter 6 discusses the results from Chapter 5, presents theoretical and
managerial contributions of the study, and provides its limitations and future research
directions. This chapter is organized as follows. Section 6.1 is divided into two parts.
Section 6.1.1 discusses the effects of relational assets on market knowledge competence.
Section 6.1.2 discusses the relationship between market orientation culture and market
knowledge competence. Then, section 6.1.3 discusses the ﬁrm performance outcomes.
Sections 6.2 and 6.3 discuss the contributions of this dissertation to theory and
management, respectively. Finally, section 6.4 discusses the limitations of the dissertation
and additional directions for future research, and section 6.5 presents the conclusions.
6.1 Discussion of the Results
6.1.1 Relational Assets and Market Knowledge Competence

As predicted, the ﬁnding that retailer/distributor equity has a signiﬁcant effect on
market knowledge competence suggests that the perceived value of retailer/distributor
knowledge drives market knowledge competence. For example, knowledge of customers’
buying criteria provided by retailers may have value to the ﬁrm’s decisions related to its
product strategy. The lack of direct effect of supplier equity on market knowledge
competence was surprising but not unexplainable. From this ﬁnding, it can be speculated
that supplier knowledge is less directly applicable to a ﬁrm’s marketing strategy making.
It can be concluded that retailer/distributor equity has important implications for market
knowledge competence and ﬁrms should nurture relationships with key

retailers/distributors.

98

6.1.2 Market Orientation Culture and Market Knowledge Competence

The impact of market orientation culture on market knowledge activities is an
important ﬁnding of this study. As is evident from the results, a market orientation
culture signiﬁcantly inﬂuences market knowledge competence. The strong support for
this relationship provides empirical evidence for Deshpandé and Webster’s (1989)
assertion that organizational culture is central to marketing function. This is also
consistent with the organizational memory perspective suggesting that collectively held
values and beliefs stored in the organizational memory shape the ﬁrm’s future behaviors.
6.1.3 Firm Performance Outcomes

To evaluate ﬁrm performance, a balanced scorecard framework was developed
that provides information on performance outcomes of a ﬁrm including customer
performance, marketing strategy formulation and implementation speed, marketing
learning performance, and ﬁnancial performance. Because the balanced scorecard
includes ﬁnancial as well as nonﬁnancial measures, it provides a comprehensive
framework for assessing the effects of market knowledge competence in the context of
marketing strategy making on ﬁrm performance.

As is evident from the results, market knowledge competence is found to
signiﬁcantly improve customer performance, marketing strategy formulation and
implementation speed, and marketing learning performance. Consistent with the research
on market orientation from a behavioral perspective (Jaworski and Kohli 1993), market
knowledge competence helps ﬁrms satisfy customer needs and wants, and thus they

achieve superior customer performance in relation to their competitors. Further, market

99

knowledge competence facilitates the process of marketing strategy formulation and
implementation. Finally, marketing learning performance appears to be improved by
market knowledge competence. Consistent with organizational learning theory,
systematic and collective learning within the organization results in improved marketing
skills of employees and their understanding about the market.

Further, the interrelationships among the four performance outcomes is
1 investigated. The ﬁnding that marketing strategy formulation and implementation speed
have a signiﬁcant positive effect on customer performance suggests that early strategic
decisions may enable the ﬁrm to access opportunities in the market sooner, and thus
improve the effectiveness of marketing strategy. Also as predicted, marketing strategy
formulation and implementation speed have a signiﬁcant positive effect on ﬁnancial
performance by creating efﬁciencies. Finally, the ﬁnding that marketing strategy
formulation and implementation speed have a signiﬁcant positive effect on marketing
learning performance suggests that the ﬁrm gets feedback on its responses to the market
sooner as it makes faster decisions. Thus, higher amounts of feedback loops enable it to
learn about its markets faster and adjust its marketing skills faster within a given period
of time.

Also as predicted, customer performance positively inﬂuences ﬁnancial
performance. Thus, customer related goals appear to be valid goals that are capable of
being translated into high ﬁnancial performance.

Finally, the ﬁnding that marketing learning performance has a signiﬁcant direct
effect on ﬁnancial performance suggests that organizational learning plays a key role in

creating competitive advantage. This is consistent with the competence-based approach

100

suggesting that marketing skills and knowledge create barriers to imitation and have the
highest potential for sustaining competitive advantage (Day 1994; Reed and deFilippi
1990; Teece, Pisano, and Shuen 1997).

6.2 Contributions to Theory

The discussion of the contributions to research and theory is centered around the
three research questions presented in Chapter 1.

How are ﬁrm-speciﬁc marketing resources leveraged through market
knowledge activities? Are there meaningful distinctions among strategic assets,
capabilities, and activities that are speciﬁc to marketing?

The incorporation of ﬁrm-speciﬁc marketing resources and market knowledge
activities in a single model affords the opportunity to examine how resources are
leveraged through activities. Moreover, resources are identiﬁed as composed of strategic
assets and capabilities. The conceptual and empirical distinction among strategic assets,
capabilities, and activities contributes to the resource-based theory and the competence-
based approach. According to the resource-based theory, a ﬁrm is characterized as a
bundle of resources. In examining the effects of resources on activities, the identiﬁcation
of types of resources adds precision to the research.

Prior research has examined the direct effects as well as the moderating effects of
resource deployments on ﬁrm performance (Capron and Hulland 1999; Slotegraaf,
Moorman, and Inman 2003). This study extends prior research by linking resources to
market knowledge activities, which, in turn, will increase ﬁrm performance. The

alignment of resources, activities, and ﬁrm performance contributes to our understanding

101

of how the ﬁrms’ resources and activities are interrelated to enable them to attain and
sustain competitive advantage.

What kind of organizational culture encourages market knowledge
competence? Are there speciﬁc values and beliefs associated with customers,
competitors, and retailers/distributors?

This dissertation contributes to the market orientation literature by
conceptualizing and operationalizing market orientation from a culture perspective. Slater
and Narver (1995, p. 67) suggest that “market orientation is the principal cultural
foundation of the learning organization.” Day (1994), who draws on the process view of
market knowledge generation and utilization, takes the opposite view on the causality and
proposes that market driven culture can only emerge if knowledge processes are
examined in a way that enables ﬁrms to learn about markets. Moreover, organizational
culture has been recognized as an important factor in motivating the ﬁrm’s knowledge
processing activities by researchers from several domains including marketing,
organizational learning, and knowledge management (Cook and Yanow 1993; Schein
1996; Sinkula, Baker, and Noordewier 1997; Weick 1979). This study provides empirical
support for Slater and Narver’s (1995) assertion by measuring market orientation as
culture, as well as testing its effects on market knowledge competence. The ﬁndings of
this study are consistent with Li and Calantone’s (1998) study that suggests a positive
relationship between the perceived importance of knowledge and customer knowledge
processing, competitor knowledge processing, and R&D integration. In sum, this study

advances our understanding of market orientation as culture and explores its effects on

102

market knowledge competence by identifying the culture components that motivate
managers to conduct market knowledge activities.

Does market knowledge competence inﬂuence competitive advantage? What
market knowledge activities contribute to market knowledge competence?

This study notes the value of market knowledge competence in gaining and
sustaining competitive advantage. The ﬁndings suggest that the four components of
market knowledge competence are market scanning, market information transmission,
market information interpretation, and market knowledge utilization. This is consistent
with the organizational learning theory (Huber 1991; Sinkula 1994). Further, this study
extends the market knowledge competence study by Li and Calantone (1998). While their
study deﬁnes market knowledge competence based on the types of information, this
study focuses on the types of market knowledge activities. Further, though they
conceptualize market knowledge competence as a series of processes, the contribution of
each process to market knowledge competence is not empirically examined. This
dissertation proposes that the intensity level of each activity has an impact on market
knowledge competence. That is, market knowledge competence increases with (1) the
amount of information acquired from the market, (2) the level of information shared by
the organization’s components, (3) the extent of varied interpretations, and (4) the
amount of knowledge applied to strategic marketing actions.

6.3 Contributions to Management

This study offers several guidelines for managers to develop market knowledge

competence. Further, it offers critical insights into the identiﬁcation of ﬁrm-speciﬁc

resources that inﬂuence market knowledge competence. Finally, it provides a balanced

103

scorecard framework that might help managers in selecting measures for assessing ﬁrm
performance.

The ﬁndings show that market knowledge competence is a multidimensional
construct that is composed of four behavioral activities. These market knowledge
generation and utilization activities include market scanning, market information
transmission, market information interpretation, and market knowledge utilization.
Understanding the nature of market knowledge competence advances the ability of
managers to direct their efforts in managing and conducting these activities.
Differentiation at the activity level can guide managers in developing rules and
procedures to improve the efﬁciency and effectiveness of each activity. Furthermore,
activity differentiation enables managers to identify what activities are important for
market knowledge generation and utilization.

The ﬁndings pertaining to ﬁrm-speciﬁc resources suggest that market orientation
culture is critical to market knowledge competence. Thus, this study provides managers
with a complete understanding of some of the components of market orientation culture,
including customer orientation, competitor orientation, and retailer/distributor orientation.
Accordingly, managers should recognize the value of understanding the target market and
the long-run capabilities of present and potential competitors and retailers/distributors.

This study also offers critical insights into the ﬁrm’s management of marketing
channel relationships. Relationships with retailers/distributors appear to provide valuable
knowledge for the ﬁrm and to drive the market knowledge generation and utilization
process. Therefore, it is beneﬁcial for ﬁrms to develop, maintain, and nurture

relationships with retailers/distributors.

104

Finally, the balanced scorecard developed for assessing market knowledge
competence provides both internal and external measures. From a managerial
perspective, it might be a useful guideline for managers in achieving a balance between
performance outcomes in internal and external environments.

6.4 Limitations and Additional Future Research Directions

The primary purpose of this dissertation is to link ﬁrm-speciﬁc marketing
resources to market knowledge activities, which, in turn, inﬂuence performance. The
ﬁndings of this study advance our understanding of how resources are leveraged through
activities to create competitive advantage. Nevertheless, some limitations should be
noted. In the following discussion, potential limitations are discussed, followed by the
suggestions for various avenues for future research.

Many of the concerns that apply generally to cross-sectional, survey based
research designs are in evidence here. Scholars might explore through longitudinal
studies how changes in the resource conﬁguration and activities may affect ﬁrm
performance as the ﬁrm evolves organically.

A second limitation relates to the perceptual nature of the performance data.
Performance implications would be stronger if the results can be duplicated using
archival performance data. Accordingly, the archival ﬁnancial data on the ﬁrms in the
sample could be obtained, and the convergence of the perceptual and archival
performance data could be conﬁrmed. Another limitation of this study is the use of a
single respondent in each SBU. Thus, informant bias, which may be present in the
context of abstract constructs (i.e., market orientation culture, retailer/distributor and

supplier equity, etc.), cannot be assessed. For example, research examining market

105

orientation culture should collect data from multiple informants, which has been done by
Kohli, Jaworski, and Kumar (1993).

In addition, the data collection of this study was limited by resource constraints.
The effective response rate is 12.8 percent. It could have been improved by more follow-
up phone calls and personal contact. A sampling frame of well-qualiﬁed potential
respondents could have been helpful. While the problem of getting senior executives to
contribute to survey studies is well documented, a larger sample size would increase the
power of the tests, and thus provide a more solid ground for the ﬁndings and implications
of the study. However, it was not feasible for the current study to thoroughly reﬁne the
list used, due to time and ﬁnancial constraints. It is certain that future researchers will be
able to conﬁrm all the ﬁndings of this study with an even better response rate using a
reﬁned list.

Several more speciﬁc limitations associated with the current study also exist.
First, this study included only three resources that are speciﬁc to marketing. It is
important to consider marketing and non-marketing resources. For example, information
technology is an important resource that plays a key role in market knowledge
management. Information technology increases the integration of knowledge sharing
between a ﬁrm and its marketing channel members, and thus may enable the ﬁrm to have
access to a variety of information sources. Studying such non-marketing resources could
provide a better understanding of what drives market knowledge competence, as well.

A second issue is related to the marketing strategy formulation and
implementation process. This study does not differentiate between marketing-mix

decisions (i.e., pricing, promotion, distribution, and product). Future research might

106

investigate the impact of market knowledge competence on different types of marketing
actions.

The third issue is related to marketing strategy formulation and implementation
speed. In this study, the proposed relationships between marketing strategy formulation
and implementation speed, and customer and ﬁnancial performance, are supported.
Subsequently, it can be speculated that ﬁrms might be achieving ﬁrst-mover advantages
as a result of fast strategy making. However, it might be interesting to investigate the
direct effects of market knowledge competence on the order of market entry.

The last issue is related to market knowledge activities. This study includes four
activities suggested by organizational learning scholars. Future research might consider
other market knowledge management activities such as knowledge protection, knowledge
storage, and so forth.

6.5 Conclusion

This dissertation has explored how resources are leveraged through market
knowledge activities in order to increase ﬁrm performance. Using the two streams of
literature in strategic management, namely resource-based theory and the competence-
based approach, this research tested a number of hypotheses and found support for most.

The ﬁndings of this dissertation indicate which resources speciﬁc to marketing
are important for market knowledge competence. Among the numerous implications and
contributions of this study, the central ﬁndings are that retailer equity and market
orientation culture play distinctive roles in enhancing a ﬁrm’s market knowledge
competence. For managing marketing channel relationships, ﬁrms may prefer to invest in

relationships with key retailers/distributors since the perceived value of knowledge

107

provided by these channel partners tends to be high. Further, this study accounts for a
link between market orientation culture and ﬁrm behavior. Therefore, ﬁrms should have a
particular way of thinking about customers, competitors, and retailers/distributors to
manage their market knowledge activities.

Then, this study explores the effect of market knowledge competence on ﬁrm
performance in several ways. Market knowledge competence enhances customer
performance, the speed of marketing strategy formulation and implementation, and
marketing learning performance. Further, the speed of marketing strategy formulation
and implementation has important implications for customer performance, ﬁnancial
performance, and marketing learning performance. Finally, customer and marketing
learning performance increase ﬁnancial performance.

This study, thus, highlights how a ﬁrm’s resources are leveraged through market
knowledge activities to create superior ﬁrm performance. Firms should identify strategic
resources that are important for market knowledge competence, which, in turn, produces

positive returns to the ﬁrm.

108

APPENDICES

109

Appendix: Final Measurement Items

 

Constructs and Measurement Items

 

Retailer/Distributor Equity New scale

1.

If the relationship with this channel partner were to end, it would be difﬁcult for us

to ﬁnd another partner that has shared unique knowledge in our relationship.
(RETEQ:)

 

 

 

 

 

2. We each have separate knowledge that, when combined, enable us to achieve
goals beyond our individual reach. (RETEQ4)

3. This channel partner does much to provide a stable knowledge stream as part of
our relationship. (RETEQ6)

Supplier Equity New scale

1. If the relationship with this supplier were to end, it would be difﬁcult for us to ﬁnd
another supplier that has shared unique knowledge in our relationship. (SUPEQI)

2. We each have separate knowledge that, when combined, enable us to achieve
goals beyond our individual reach. (SUPEQ4)

3. This supplier does much to provide a stable knowledge stream as part of our
relationship. (SUPEQ6)

Customer Orientation New scale

1. We believe that understanding the needs of our customers is necessary to achieve a
competitive advantage. (CUSTO3)

2. We believe that how our customers value our products drives our business
strategies. (CUSTO4)

3. We believe it is important to constantly monitor our level of customer service in
our business operations. (CUSTOS)

Competitor Orientation New scale

1. We believe that it is necessary to constantly monitor competitor activities in our
business environment. (COMPO.)

2. We believe that it is important to closely monitor the strategic moves of our key.
and potential competitors. (COMPO3)

3. We value information about the performance of competitors. (COMPO4)

4. We place great value on information about new product introductions by
competitors. (COMPO6)

Retailer/Distributor Orientation New scale

1. We believe it is important to closely monitor changes in key and potential channel
partners in our business environment. (RETRO3)

2. We value information on the performance of products and services offered by our
channel partners (e.g., cost, quality, speed, ﬂexibility). (RETRO4)

3. We place great value on lessons learned from successful and/or unsuccessful

experiences with our channel partners. (RETROs)

 

110

 

Appendix (cont’d): Final Measurement Items

 

Market Scanning Adapted

1. We frequently make use of certain mechanisms to gather marketplace information
from partners in the value chain (e.g., suppliers, distributors, retailers). (MSCAN3)

2. We frequently make use of forecasting techniques (e.g., sales, customer
preferences, technology) to understand the dynamics of the marketplace better.
(MSCAN4)

3. We frequently collect information about market trends and developments to
remain abreast of changes in our marketplace (e.g., economic, technological,
and/or demographic trends). (MSCAN6)

 

Market Information Transmission Adapted

1. In our ﬁrm, information about our successful and unsuccessful customer
experiences is transmitted at all levels on a regular basis. (ITRAN3)

2. When one department ﬁnds out something important about competitors, it is fast to
alert other departments. (ITRAN4)

3. Market information spreads quickly through all levels in this ﬁrm. (ITRANb)

 

Market Information Interpretation New scale

To reach a shared understanding, we frequently

1. assemble pieces of market information into a coherent and logical format. ONT.)
2. summarize market information to reduce its complexity. (llNTz)

3. generate explanations for the given market information. (11NT3)

 

Market Knowledge Utilization Adapted

We rely heavily on market knowledge

l. to carefully evaluate various marketing strategy alternatives. (MUTILI)

2. to strategically plan our marketing activities (e.g., planning, goal setting,
budgeting). (MUTILZ)

3. to make strategic decisions related to our marketing activities. (MUTIL3)

 

Customer Performance Adapted
1. Attracted new customers. (CUSPR3)

2. Attained desired growth. (CUSPR4)

3. Attained desired market share. (CUSPRs)

 

 

Strategy Formulation and Implementation Speed New scale

1. Our marketing strategy was developed in a short time period. (SPEEDI)
2. We were very quick to develop our marketing strategy. (SPEED3)

3. We were very quick to implement our marketing strategy. (SPEED6)

 

lll

 

Appendix (cont’d): Final Measurement Items

 

Marketing Learning Performance Adapted

l.

2.

3.

We have a larger proportion of skilled marketing employees this year than last
year. (LRNPRt)

We have a larger proportion of marketing employees learning new managerial
skills this year than last year. (LRNPRz)

We have a larger proportion of marketing employees who have improved their
understanding about our marketplace this year than last year. (LRNPR3)

 

 

Financial Performance Adapted

l

2.
3.
4.

Average proﬁt margin. (FlNPRz)
Return on investment. (FINPR3)
Return on assets. (FINPR4)
Return on sales. (FINPRS)

 

112

 

BIBLIOGRAPHY

113

Adams, Marjorie E., George S. Day, and Deborah Dougherty (1998), “Enhancing New
Product Development Performance: An Organizational Learning Perspective,” Journal of
Product Innovation Management, 15 (5), 403-22.

Aguilar, F. J. (1967), Scanning the Business Environment. New York: Macmillan.

Amit, Raphael and Paul J. H. Schoemaker (1993), “Strategic Assets and Organizational
Rent,” Strategic Management Journal, 14 (1), 33-46.

Andrews, Kenneth R. (1980), The Concept of Corporate Strategy. Richard D. Irwin, lnc.
Ansoff, H. Igor (1965), Corporate Strategy. New York: McGraw Hill.

Argyris, Chris and Donald A. Schon (1978), Organizational Learning: A Theory of
Action Perspective. Reading, MA: Addison-Wesley Publishing Company.

Armstrong, J. Scott and Terry S. Overton (1977), “Estimating Nonresponse Bias in Mail
Surveys,” Journal of Marketing Research, 14 (3), 396-402.

Bain, J. (1956), Barriers to New Competition. Cambridge, MA: Harvard University
Press.

Bagozzi, Richard P. and Youjae Yi, (1988), “On the Evaluation of Structural Equation
Models,” Journal of the Academy of Marketing Science, 16 (1), 74-94.

----, ----, and Lynn W. Phillips. (1991), “Assessing Construct Validity in Organizational
Research,” Administrative Science Quarterly, 36 (3), 421-58.

---- and Lynn W. Phillips (1982), “Representing and Testing Organizational Theories: A
Holistic Construal,” Administrative Science Quarterly, 27 (3), 459-89.

---- and Hans Baumgartner (1994), “The Evaluation of Structural Equation Models and
Hypothesis Testing,” in Principles of Marketing Research, R. Bagozzi, ed. Cambridge,
386-422.

Barney, Jay B. (1986), “Organizational Culture: Can It Be a Source of Sustained
Competitive Advantage?” Academy of Management Review, 11 (3), 656-65.

---- (1991), “Firm Resources and Sustained Competitive Advantage,” Journal of
Management, 17 (1), 99-120.

Barringer, Bruce R. and Allen C. Bluedom (1999), “The Relationship Between Corporate

Entrepreneurship and Strategic Management,” Strategic Management Journal, 20 (5),
421-44.

114

Bartunek, Jean M. (1984), “Changing Interpretive Schemes and Organizational
Restructuring: The Example of a Religious Order,” Administrative Science Quarterly, 29
(3), 355-72.

Baum, J. Robert and Stefan Wally (2003), “Strategic Decision Speed and Firm
Performance,” Strategic Management Journal, 24 (l 1), 1107-29.

Bell, Simon J ., Gregory J. Whitwell, and Bryan A. Lukas (2002), “Schools of Thought in
Organizational Learning,” Journal of the Academy of Marketing Science, 30 (1), 70-86.

Bentler, Peter M. (1995), EQS Structural Equations Program Manual. Encino, CA:
Multivariate Software, Inc.

Beyer, Janice M. and Harrison M. Trice (1982), “The Utilization Process: A Conceptual
Framework and Synthesis of Empirical Findings,” Administrative Science Quarterly, 27
(4), 591-622.

Black, Janice A. and Kimberly B. Boal (1994), “Strategic Resources: Traits,

Conﬁgurations and Paths to Sustainable Competitive Advantage,” Strategic Management
Journal, 15 (Special Issue), 131-48.

Boeker, Warren (1991), “Organizational Strategy: An Ecological Perspective,” Academy
of Management Journal, 34 (3), 613-35.

Bollen, Kenneth A. (1989), Structural Equations with Latent Variables. New York: John
Wiley & Sons, Inc.

---- and R. Lennox (1991 ), “Conventional Wisdom on Measurement: A Structural
Equation Perspective,” Psychological Bulletin, 110 (2), 305-14.

Bone, Paula Fitzgerald, Subhash Shanna, and Terence A. Shimp (1989), “A Bootstrap
Procedure for Evaluating Goodness-of—F it Indices of Structural Equation and
Conﬁrrnatory Factor Models,” Journal of Marketing Research, 26 (1), 105-11.

Buzzell, Robert D. and Bradley T. Gale (1975), “Market Share--A Key to Proﬁtability,”
Harvard Business Review, 53 (1), 97-106.

Byme, Barbara M. (1998), Structural Equation Modeling with LISREL, PRELIS, and
SIMPLIS: Basic C oncepts, Applications, and Programming. Mahwah, New Jersey:
Lawrence Erlbaum Associates, Inc.

Calantone, Roger J. and C. Anthony di Benedetto (1988), “An Integrative Model of the

New Product Development Process: An Empirical Validation,” The Journal of Product
Innovation Management, 5 (3), 201.

115

----, Jeffrey B. Schmidt, and X. Michael Song (1996), “Controllable Factors of New
Product Success: A Cross-National Comparison,” Marketing Science, 15 (4), 341-58.

---- and Yushan Sam Zhao (2001), “Joint Ventures in China: A Comparative Study of
Japanese Korean, and US. Partners,” Journal of International Marketing, 9 (1), 1-23.

Capron, Laurence and John Hulland (1999), “Redeployment of Brands, Sales Forces, and
General Marketing Management Expertise Following Horizontal Acquisitions: A
Resource-Based View,” Journal of Marketing, 63 (2), 41 -54.

Castanias, Richard P. and Constance E. Helfat (1991), “Managerial Resources and
Rents,” Journal of Management, 17 (1), 155-71.

Caves, R. E. and M. E. Porter (1991), “From Entry Baniers to Mobility Baniers:

Conjectural Decisions and Contrived Deterrence to New Competition,” Quarterly
Journal of Economics, 91 (2), 241-61.

Cavusgil, S. Tamer and Shaoming Zou, “Marketing Strategy-Performance Relationship:
An Investigation of the Empirical Link in Export,” Journal of Marketing, 58 (1), 1-21.

Chandler, Alfred D. (1962), Strategy and Structure. Cambridge: MIT Press.

Chi, Tailan (1994), “Trading in Strategic Resources: Necessary Conditions, Transaction
Cost Problems, and Choice of Exchange Structure,” Strategic Management Journal, 15
(4), 271-90.

Churchill, Gilbert A., Jr. (1979), “A Paradigm for Developing Better Measures of
Marketing Constructs,” Journal of Marketing Research, 16 (1), 64-73.

Conner, Kathleen R. (1991), “Historical Comparison of Resource-Based Theory and Five
Schools of Thought within Industrial Organization Economics: Do We Have a New
Theory of the Firm?” Journal of Management, 17 (1), 121-54.

Cook, Scott D. N. and Dvora Yanow (1993), “Culture and Organizational Learning,”
Journal of Management Inquiry, 2 (4), 373-90.

Corner, Patricia Doyle, Angelo J. Kinicki, and Barbara W. Keats (1994), “Integrating
Organizational and Individual Information Processing Perspectives on Choice,”
Organization Science, 5 (3), 294-308.

Daft. Richard L. and Karl E. Weick, (1984), “ Toward a Model of Organizations as
Interpretation Systems,” Academy Of Management Review, 9 (2), 284-95.

---- and Robert H. Lengel (1986), “Organizational Information Requirements, Media
Richness and Structural Design,” Management Science, 32 (5), 554-71.

116

Davenport, Thomas, Jeanne G. Harris, and Ajay K. Kohli (2001), “How Do They Know
Their Customers So Well?” MIT Sloan Management Review, 42 (2), 63-73.

Day, George S. (1994), “The Capabilities of Market-Driven Organizations,” Journal of
Marketing, 58 (4), 37-52.

---- and Prakash Nedungadi (1994), “Managerial Representations of Competitive
Advantage,” Journal of Marketing, 58 (2), 31-44.

---- and Robin Wensley (1988), “Assessing Advantage: A Framework for Diagnosing
Competitive Superiority,” Journal of Marketing, 52 (2), 1-20.

Deshpandé, Rohit (1982), “Factors Affecting the Use of Market Research Information: A
Path Analysis,” Journal of Marketing Research, 19 (1), 14-31.

---- and Gerald Zaltman (1984), “A Comparison of Factors Affecting Researcher and
Manager Perceptions of Market Research Use,” Journal of Marketing Research, 21 (1),
32-38.

---- and Frederick E. Webster, Jr. (1989), “Organizational Culture and Marketing:
Deﬁning the Research Agenda,” Journal of Marketing, 53 (1), 3-15.

--—-, John U. Farley, and Frederick E. Webster, Jr. (1993), “Corporate Culture, Customer

Orientation, and lnnovativeness in Japanese Firms: A Quadrad Analysis,” Journal of
Marketing, 57 (1), 23-37.

---- and ---- (1998a), “Measuring Market Orientation: Generalization and Synthesis,”
Journal of Market Focused Management, 2, 213-32.

---- and ---- (1998b), “The Market Orientation Construct: Correlations, Culture, and
Comprehensiveness,” Journal of Market Focused Management, 2, 23 7-3 9.

Dess, Gregory G. and Peter S. Davis (1984), “Porter's (1980) Generic Strategies as
Determinants of Strategic Group Membership and Organizational Performance,”
Academy of Management Journal, 27 (3), 467-88.

---- and Richard B. Robinson Jr. (1984), “Measuring Organizational Performance in the
Absence of Objective Measures: The Case of the Privately-Held Firm and Conglomerate
Business Unit,” Strategic Management Journal, 5 (3), 265-73.

Diamantopoulos, Adamantios and Heidi M. Winklhofer (2001), “Index Construction with
Formative Indicators: An Alternative to Scale Development,” Journal of Marketing
Research, 38 (2), 269-77.

Dierickx, Ingemar and Karel C001 (1989), “Asset Stock Accumulation and Sustainability
of Competitive Advantage,” Management Science, 35 (12), 1504-11.

117

Dorsch, Michael J ., Les Carlson, Mary Anne Raymond, and Robert Ranson (2001),
“Customer Equity Management and Strategic Choices for Sales Managers,” Journal of
Personal Selling & Sales Management, 21 (2), P157-66.

Dutton, Jane E. and Susan E. Jackson (1987), “Categorizing Strategic Issues: Links to
Organizational Action,” Academy of Management Review, 12 (1), 76-90.

Efron, Bradley (1982), The Jackknife, the Bootstrap and Other Re-sampling Plans.
Philadelphia: Society for Industrial and Applied Mathematics.

---- (1987), “Better Bootstrap Conﬁdence Interval,” Journal of American Statistical
Association, 82 (March), 171-85.

---- and Robert Tibshirani (1986), “Bootstrap Methods for Standard Errors, Conﬁdence
Intervals, and Other Measures of Statistical Accuracy,” Statistical Science, 1 (1), 54-77.

Eisenhardt, Kathleen M. (1989), “Making Fast Strategic Decisions in High-Velocity
Environments,” Academy of Management Journal, 32 (3), 543-76.

---- and Jeffrey A. Martin (2000), “Dynamic Capabilities: What are They?” Strategic
Management Journal, 21 (10/11), 1105-21.

Fiol, C. Marlene (1991), “Managing Culture as a Competitive Resource: An Identity-
Based View of Sustainable Competitive Advantage,” Journal of Management, 17 (1),
1 91 -21 1 .

---- (1994), “Consensus, Diversity, and Learning in Organizations,” Organization
Science, 5 (3), 403-20.

Foa, Edna B. and Uriel G. Foa (1980), “Resource Theory: Interpersonal Behavior as
Exchange,” in Social Exchange: Advances in Theory and Research, Kenneth J. Gergen,
Martin S. Greenberg, and Richard H. Willis, eds. New York: Plenum Press, 77-94.

Forbes, D. P. (2001), “The Performance Implications of Strategic Decision-Making:
Evidence From a New Venture Context,” Presented at 2001 Academy of Management
Meeting, Washington, DC.

Fomell, Claes and David F. Larcker (1981), “Structural Equation Models with
Unobservable Variables and Measurement Error: Algebra and Statistics,” Journal of

Marketing Research, 18 (3), 382-88.

Foss, Nicolai J. (1997), Resources, Firms, and Strategies. New York: Oxford University
Press, Inc.

118

F riedlander, F. (1983), “Patterns of Individual and Organizational Learning,” in The
Executive Mind: New Insights on Managerial Thought and Action, S. Srivasta and
Associates, eds. San Francisco: Jossey-Baas.

Galbraith, Craig S. (1990), “Transferring Core Manufacturing Technologies in High-
Technology F inns,” California Management Review, 32 (Summer), 56-70.

Gerbing David W. and James C. Anderson (1988), “An Updated Paradigm for Scale
Development Incorporating Unidimensionality and its Assessment,” Journal of
Marketing Research, 25 (2), 186-192.

Glazer, Rashi (1991), “Marketing in an Infonnation-Intensive Environment: Strategic
Implications of Knowledge as an Asset,” Journal of Marketing, 55 (4), 1-19.

---- (1998), “Measuring the Knower: Towards a Theory of Knowledge Equity,”
California Management Review, 40 (3), 175-94.

Grant, Robert M. (1991), “The Resource-Based Theory of Competitive Advantage:
Implications for Strategy Formulation,” California Management Review, 33 (3), 114-35.

---- (1996), “Toward a Knowledge-Based Theory of the F inn,” Strategic Management
Journal, 17(Special Issue), 109-22.

Gray, Brendan, Sheelagh Matear, Christo Boshoff, and Phil Matheson (1998),
“Developing a Better Measure of Market Orientation,” European Journal of Marketing,
32 (9/ 10), 884-903.

Hall, Richard (1992), “The Strategic Analysis of Intangible Resources,” Strategic
Management Journal, 13 (2), 135-44.

Hambrick, Donald C. (1982), “Environmental Scanning and Organizational Strategy,”
Strategic Management Journal, 3 (2), 159-74.

Hamel, Gary and C. K. Prahalad (1989), “Strategic Intent,” Harvard Business Review, 67
(3), 63-76.

---- and -—-- (1994), “Competing for the Future,” Harvard Business Review, 72 (4), 122-
28.

Hedberg, B0 (1981), “How Organizations Learn and Unleam,” in Handbook of
Organizational Design, P. Nystrom and W. Starbuck, eds. Oxford: Oxford University
Press, 3-27.

Henderson, Rebecca and Iain Cockburn (1994), “Measuring Competence? Exploring
Firm Effects in Pharmaceutical Research,” Strategic Management Journal, 15 (8), 63-84.

119

Hitt, Michael A. and R. Duane Ireland (1985), “Corporate Distinctive Competence,
Strategy, Industry and Performance,” Strategic Management Journal, 6 (3), 273-93.

Homburg Christian and Christian Pﬂesser (2000), “A Multiple-Layer Model of Market-
Oriented Organizational Culture: Measurement Issues and Performance Outcomes,”
Journal of Marketing Research, 37 (4), 449-62.

Hu, Li-Tze and Peter M. Bentler (1995), “Evaluating Model Fit,” in Structural Equation
Modeling: Concepts, Issues and Applications, Rick H. Hoyle, ed. Thousand Oaks, CA:
SAGE Publications, Inc.

Huber, George P. (1991), “Organizational Learning: The Contributing Processes and the
Literatures,” Organization Science, 2 (1), 88-115.

Hult, G. Tomas M. (1998), “Managing the International Strategic Sourcing Process as a
Market-Driven Organizational Learning System,” Decision Sciences, 29 (1), 193-216.

----, Robert F. Hurley, Larry C. Giunipero, and Ernest L. Nichols, Jr. (2000),
“Organizational Learning In Global Purchasing: A Model and Test of Internal Users and
Corporate Buyers,” Decision Sciences, 31 (2), 293-325.

----, David J. Ketchen, Jr., and Ernest L. Nichols, Jr. (2002), “An Examination of Cultural
Competitiveness and Order Fulﬁllment Cycle Time within Supply Chains,” Academy of
Management Journal, 45 (3), 577-86.

Hunt, Shelby D. (2000), A General Theory of Competition. Thousand Oaks, CA: Sage
Publications.

---- and Robert M. Morgan (1995), “The Comparative Advantage Theory of
Competition,” Journal of Marketing, 59 (2), 1-15.

Hurley, Robert F. and G. Tomas M. Hult (1998), “Innovation, Market Orientation, and

Organizational Learning: An Integration and Empirical Examination,” Journal of
Marketing, 62 (3), 42-54.

Isabella, Lynn A. (1990), “Evolving Interpretations as a Change Unfolds: How Managers
Construe Key Organizational Events,” Academy of Management Journal, 33 (1), 7-41.

Itami, Hiroyuki and Thomas W. Roehl (1987), Mobilizing Invisible Assets. Cambridge,
MA: Harvard University Press.

Jarvis, Cheryl Burke, Scott B. Mackenzie, Philip M. Podsakoff, David Glen Mick, and
William O. Bearden (2003), “A Critical Review of Construct Indicators and

Measurement Model Misspeciﬁcation in Marketing and Consumer Research,” Journal of
Consumer Research, 30 (2), 199-218.

120

Jaworski, Bernard J. and Ajay K. Kohli (1993), “Market Orientation: Antecedents and
Consequences,” Journal of Marketing, 57 (3), 53-70.

John, George and Torger Reve (1982), “The Reliability and Validity of Key Informant
Data from Dyadic Relationships in Marketing Channels,” Journal of Marketing
Research, 19 (4), 517-24.

Judge, William Q. and Alex Miller (1991), “Antecedents and Outcomes of Decision

Speed in Different Environmental Context,” Academy of Management Journal, 34 (2),
449-63.

Kaplan, Robert S. and David P. Norton (1993), “Putting the Balanced Scorecard to
Work,” Harvard Business Review, 71 (5), 134-40.

---- and ---- (2005), “The Balanced Scorecard: Measures that Drive Performance,”
Harvard Business Review, 83 (7), 172-80.

Kerin, Roger A., P. Rajan Varadarajan, and Robert A. Peterson (1992), “First-Mover

Advantage: A Synthesis, Conceptual Framework, and Research Propositions,” Journal of
Marketing, 56 (4), 33-52.

Ketchen, David J ., J r., James B. Thomas, and Charles C. Snow (1993), “Organizational
Conﬁgurations and Performance: A Comparison of Theoretical Approaches,” Academy of
Management Journal, 36 (6), 1278-, 36p,

Kiesler, Sara and Lee Sproull (1982), “Managerial Response to Changing Environments:
Perspectives on Problem Sensing from Social Cognition,” Administrative Science
Quarterly, 27 (4), 548-70.

Kim, Jay S. (1984), “Effect of Behavior Plus Outcome Goal Setting and Feedback on
Employee Satisfaction and Performance,” Academy of Management Journal, 27 (1), 139-
49.

Kleinmuntz, Don N. and James B. Thomas (1987), “The Value of Action and Inference

in Dynamic Decision Making,” Organizational Behavior and Human Decision
Processes, 39 (3), 341-64.

Kohli, Ajay K. and Bernard J. Jaworski (1990), “Market Orientation: The Construct,
Research Propositions, and Managerial Implications,” Journal of Marketing, 54 (2), 1-18.

----, Bernard J. Jaworski, and Ajith Kumar (1993), “MARKOR: A Measure of Market
Orientation,” Journal of Marketing Research, 30 (4), 467-77.

Kumar, Nirmalya (1990), “Mobility Barriers and Proﬁtability of Multinational and Local
Enterprieses in Indian Manufacturing,” Journal of Industrial Economics, 38: 449-63.

121

Kumar, Nirmalya, Louis W. Stern, and Ravi S. Achrol (1992), “Assessing Reseller

Performance from the Perspective of the Supplier,” Journal of Marketing Research, 29
(2), 238-53.

Lado, Augustine A., Nancy G. Boyd, and Peter Wright (1992), “A Competency-Based
Model of Sustainable Competitive Advantage: Toward a Conceptual Integration,”
Journal of Management, 18 (1), 77-91.

Larson, Andrea (1992), “Network Dyads in Entrepreneurial Settings: A Study of the

Governance of Exchange Relationships,” Administrative Science Quarterly, 37 (1): 76-
104.

Lawless, Michael W. and Linda K. Finch (1989), “Choice and Detenninism: A Test of
Hrebiniak and Joyce’s Framework on Strategy-Environment Fit,” Strategic Management
Journal, 10: 351-65.

Leonard-Barton, Dorothy (1992), “Core Capabilities and Core Rigidities: A Paradox in

Managing New Product Development,” Strategic Management Journal, 13 (Special
Issue), 111-25. .

Levinthal, Daniel A. and Mark F ichman (1988), “Dynamics of lnterorganizational
Attachments: Auditor-Client Relationships,” Administrative Science Quarterly, 33 (3),
345-69.

Levitt, Barbara and James G. March (1988), “Organizational Learning,” Annual Review
of Sociology, 14, 319-340.

Lewis, Pam and Howard Thomas (1990), “The Linkage Between Strategy, Strategic

Groups, and Performance in the UK. Retail Grocery Industry,” Strategic Management
Journal, 11 (5), 385-97.

Li, Tiger and Roger J. Calantone (1998), “The Impact of Market Knowledge Competence
on New Product Advantage: Conceptualization and Empirical Examination,” Journal of
Marketing, 62 (4), 13-29.

Lippman, SA. and R. P. Rumelt (1982), “Uncertain Imitability: An Analysis of Interﬁnn

Differences in Efﬁciency Under Competition,” Bell Journal of Economics, 13 (2), 418-
38.

Low, George S. and Jakki J. Mohr (2001), “Factors Affecting the Use of Information in
the Evaluation of Marketing Communications Productivity,” Journal of the Academy of

Marketing Science, 29 (1), 70-88.

Mahoney, Joseph T. (1995), “The Management of Resources and the Resource of
Management,” Journal of Business Research, 33 (2), 91-101.

122

-—-- and J. Rajendran Pandian (1992), “The Resource-Based View within the
Conversation of Strategic Management,” Strategic Management Journal, 13 (5), 363-80.

Makadok, Richard (2001), “Toward a Synthesis of the Resource-Based and Dynamic-
Capability Views of Rent Creation,” Strategic Management Journal, 22 (5), 387-401.

Maltz, Elliot and Ajay K. Kohli (1996), “Market Intelligence Dissemination Across
Functional Boundaries,” Journal of Marketing Research, 33 (1), 47-61.

March, James G. and H. A. Simon (1958), Organizations. New York: Wiley.

Mason, E. (1939), “Price and Production Policies of Large Scale Enterprises,” American
Economic Review, 29, 61-74.

 

Matsuno, Ken and John T. Mentzer (2000), “The Effects of Strategy Type on the Market
Orientation-Perfonnance Relationship,” Journal of Marketing, 64 (4), 1-16.

----, ----, and Joseph 0. Rentz (2000), “A Reﬁnement and Validation of the MARKOR
Scale,” Journal of the Academy of Marketing Science, 28 (4), 527-39. _L

 

McKee, Daryl O., Jeffery S. Conant, P. Rajan Varadarajan, and Michael P. Mokwa
(1992), “Success-Producer and F ailure-Preventer Marketing Skills: A Social Learning
Theory Interpretation,” Journal of the Academy of Marketing Science, 20 (1), 17-26.

Menon, Ajay and Bryan A. Lukas (2004), “Antecedents and Outcomes of New Product

Development Speed: A Propositional Inventory Germane to Marketing,” European
Journal of Marketing, 38 (1/2), 209-23.

Menon, Anil and P. Rajan Varadarajan (1992), “A Model of Marketing Knowledge Use
within Firms,” Journal of Marketing, 56 (4), 53-71.

----, Sundar G. Bharadwaj, Phani Tej Adidam, and Steven W. Edison (1999),
“Antecedents and Consequences of Marketing Strategy Making: A Model and a Test,”
Journal of Marketing, 63 (2), 18-40.

----, ----, and Roy Howell (1996), “The Quality and Effectiveness of Marketing Strategy:
Effects of Functional and Dysfunctional Conﬂict in Intraorganizational Relationships,”

Journal of the Academy of Marketing Science, 24 (4), 299-313.

Mentzer, John T., Daniel J. Flint, and G. Tomas M. Hult (2001), “Logistics Service
Quality as a Segment-Customized Process,” Journal of Marketing, 65 (4), 82-104.

Meyer, C. (1993), Fast Cycle Time: How to Align Purpose, Strategy, and Structurefor
Speed. New York, NY: Free Press.

123

Miller, Danny and Jamal Shamsie (1996), “The Resource-Based View of the Firm in
Two Enviroments: The Hollywood Film Studios from 1936 to 1965,” Academy of
Management Journal, 39 (3), 519-43.

---- and Peter H. Friesen (1982), “Innovation in Conservative and Entrepreneurial Firms:
Two Models of Strategic Momentum,” Strategic Management Journal, 3 (1), 1-25.

Mintzberg, Henry (1973), “Strategy-Making in Three Modes,” California Management
Review, 16 (2), 44-53.

Moorman, Christine (1995), “Organizational Market Information Processes: Cultural

Antecedents and New Product Outcomes,” Journal of Marketing Research, 32 (3), 318-
35.

----, Gerald Zaltman, and Rohit Deshpandé (1992), “Relationships Between Providers
and Users of Market Research: The Dynamics of Trust within and Between
Organizations,” Journal of Marketing Research, 29 (3), 314-28.

Narver, John C. and Stanley F. Slater (1990), “The Effect of a Market Orientation on
Business Proﬁtability,” Journal of Marketing, 54 (4), 20-35.

---- and ---- (1998), “Additional Thoughts on the Measurement of Market Orientation: A
Comment on Deshpandé and Farley,” Journal of Market Focused Management, 2, 233-
36.

Nelson, Richard R. and Sidney G. Winter (1982), An Evolutionary Theory of Economic
Change. Cambridge, MA: The Belknap Press of Harvard University Press.

Penrose, Edith (1959), The Theory of the Growth of the Firm. New York, NY: Oxford
University Press.

Peteraf, Margaret A. (1993), “The Comerstones of Competitive Advantage: A Resource-
Based View,” Strategic Management Journal, 14 (3), 179-91.

Polanyi, Michael (1967), The Tacit Dimension. Garden City, New York: Anchor Books.
Porter, Michael E. (1980), Competitive Strategy. New York, NY: The Free Press.

---- (1985), Competitive Advantage: Creating and Sustaining Superior Performance.
New York, NY: The Free Press.

---- (1991), “Towards a Dynamic Theory of Strategy,” Strategic Management Journal, 12
(Winter), 95-117.

Prahalad, C. K. and Gary Hamel (1990), “The Core Competence of the Corporation,”
Harvard Business Review, 68 (3), 79-91 .

124

Prescott, John E., Ajay K. Kohli, and N. Venkatraman (1986), “The Market Share-
Proﬁtability Relationship: An Empirical Assessment of Major Assertions and
Contradictions,” Strategic Management Journal, 7 (4), 377-94.

Reed, Richard and Robert J. DeFillippi (1990), “Causal Ambiguity, Barriers to Imitation,

and Sustainable Competitive Advantage,” Academy of Management Review, 15 (1), 88-
102.

Richardson, G. B. (1972), “The Organisation of Industry,” Economic Journal, 82 (327),
883-96.

Robinson,William T. and Claes Fomell (1985), “Sources of Market Pioneer Advantages
in Consumer Goods Industries,” Journal of Marketing Research, 22 (3), 305-17.

Rossi, Ino and Edwin O’Higgins (1980), “The Development of Theories of Culture,” in
People in Culture, Ino Rossi, ed. New York, NY: Praeger, 31-78.

Rubin, Paul H. (1973), “The Expansion of Firms,” Journal of Political Economy, 81 (4),
936-49.

Rumelt, Richard P. (1984), “Towards a Strategic Theory of the Firm” in Competitive
Strategic Management, R. B. Lamb, ed. Upper Saddle River, NJ: Prentice Hall.

---- (1991), “How Much Does Industry Matter?” Strategic Management Journal, 12 (3),
167-85.

Sanchez, Ron, Aime Heene, and Howard Thomas eds. (1996), Dynamics of C ompetence-
Based Competition: Theory and Practice in the New Strategic Management. Oxford:
Elsevier Pergamon.

---- and ---- (1997), “Managing for an Uncertain Future,” International Studies of
Management & Organization, 27 (2), 21-42.

Sawhney, Mohanbir and Jeff Zabin (2002), “Managing and Measuring Relational Equity
in the Network Economy,” Journal of the Academy of Marketing Science, 30 (4), 313-32.

Schein, Edgar H. (1996), “Three Cultures of Management: The Key to Organizational
Learning,” Sloan Management Review, 38 (1), 9-20.

Schwab, Donald P. (1999), Research Methods for Organizational Studies. New Jersey:
Lawrence Erlbaum Associates, Inc., Publishers.

Selznick, Philip (1957), Leadership in Administration: A Sociological Interpretation.
Harper & Row.

125

Shapiro, Benson P. (1988), “What the Hell is ‘Market Oriented?” Harvard Business
Review, 66(6), 119-25.

Shrivastava, Paul and Ian I. Mitroff (1982), “Frames of Reference Managers Use,” in
Advances in Strategic Management, Vol. 1, Robert Lamb, ed. Greenwich, CT: J AI Press,
Inc., 161-80.

Simon, Herbert A. (1991), “Bounded Rationality and Organizational Learning,”
Organization Science, 2 (1), 125-134.

Sinkula, James M. (1994), “Market Information Processing and Organizational
Learning,” Journal of Marketing, 58 (1), 35-45.

----, William E. Baker, and Thomas Noordewier (1997), “A Framework for Market-
Based Organizational Learning: Linking Values, Knowledge, and Behavior,” Journal of
the Academy of Marketing Science, 25 (4), 305-18.

Slater, Stanley F. and John C. Narver (1995), “Market Orientation and the Learning
Organization,” Journal of Marketing, 59 (3), 63-74.

Slotegraaf, Rebecca J ., Christine Moorman, and J. Jeffrey Inman (2003), “The Role of
Firm Resources in Returns to Market Deployment,” Journal of Marketing Research, 40
(3), 295-309.

Smircich, Linda (1983), “Concepts of Culture and Organizational Analysis,”
Administrative Science Quarterly, 28 (3), 339-58.

Snow, Charles C. and Lawrence G. Hrebiniak (1980), “Strategy, Distinctive Competence,
and Organizational Performance,” Administrative Science Quarterly, 25 (2), 317-36.

Song, Michael, Cornelia Droge, Sangphet Hanvanich, and Roger J. Calantone (2005),
“Marketing and Technology Resource Complementarity: An Analysis of their Interaction
Effect in Two Environmental Contexts,” Strategic Management Journal, 26 (3), 259-76.

Spanos, Yiannis E. and Spyros Lioukas (2001), “An Examination into the Causal Logic
of Rent Generation: Contrasting Porter's Competitive Strategy Framework and the

Resource-Based Perspective,” Strategic Management Journal, 22 (10), 907-34.

Sproull, Lee (1981), “Response to Regulation: An Organizational Process Framework,”
Administration and Society, 12: 447-470.

126

Srivastava, Rajendra K., Liam F ahey, and H. Kurt Christensen (2001), “The Resource-
Based View and Marketing: The Role of Market-Based Assets in Gaining Competitive
Advantage,” Journal of Management, 27 (6), 777-802.

----, Tasadduq A. Shervani, and Liam Fahey (1998), “Market-Based Assets and
Shareholder Value: A Framework for Analysis,” Journal of Marketing, 62 (1), 2-18.

Starbuck, William H. (1976), “Organizations and Their Environments,” in Handbook of

Industrial and Organizational Psychology, Marvin D. Dunnette, ed. Chicago: Rand
McNally, 1069-1123.

Szymanski, David M., Lisa C. Troy, and Sundar G. Bharadwaj (1995), “Order of Entry
and Business Performance: An Empirical Synthesis and Reexamination,” Journal of
Marketing, 59 (4), P17-33.

----, Sundar G. Bharadwaj, and P. Rajan Varadarajan (1993), “An Analysis of Market
Share-Proﬁtability Relationship,” Journal of Marketing, 57 (3), 1-18.

Teece, David J. (1986), “Proﬁting from Technological Innovation,” Research Policy, 15,
285-305.

---- (1998), “Capturing Value from Knowledge Assets: The New Economy, Markets for
Know-How, and Intangible Assets,” California Management Review, 40(3), 55-79.

----, Gary Pisano, and Amy Shuen (1997), “Dynamic Capabilities and Strategic
Management,” Strategic Management Journal, 18 (7), 509-33.

Thomas, James 8., Shawn M. Clark, and Dennis A. Gioia (1993), “Strategic
Sensemaking and Organizational Performance: Linkages among Scanning, Interpretation,
Action, and Outcomes,” Academy of Management Journal, 36 (2), 239-70.

----, Dennis A. Gioia, and David J. Ketchen, Jr. (1997), “Strategic Sensemaking:
Learning Through Scanning, Interpretation, Action, and Performance,” in Advances in
Strategic Management, Vol. 14, James P. Walsh and Anne S. Huff, eds. Greenwich, CT:
JAI Press, Inc., 299- 329.

Tiwana, Amrit (2000), The Knowledge Management Toolkit: Practical. Techniques for
Building a Knowledge Management System. Upper Saddle River, NJ: Prentice-Hall.

Van de Ven, Andrew H., Andre L. Delbecq, and Richard Koenig, Jr. (1976),

“Determinants of Coordination Modes within Organizations,” American Sociological
Review, 41, 322-38.

von Krogh, Georg, Johan R003, and Ken Slocum (1994), “An Essay on Corporate
Epistemology,” Strategic Management Journal, 15 (Special Issue), 53-71.

127

Walker, Orville C., Jr. and Robert W. Ruekert (1987), “Marketing's Role in the
Implementation of Business Strategies: A Critical Review and Conceptual Framework,”
Journal of Marketing, 51 (3), 15-33.

Walsh James P. and Gerardo Rivera Ungson (1991), “Organizational Memory,”
Academy of Management Review, 16 (1), 57-91.

Weick, Karl E. (1979), “Cognitive Processes in Organizations,” Research in
Organizational Behavior, 1, 41 ~74.

---- and Karlene H. Roberts (1993), “Collective Mind in Organizations: Heedful
Interrelating on Flight Decks,” Administrative Science Quarterly, 38 (3), 357-81.

Wemerfelt, Birger (1984), “A Resource-Based View of the Firm,” Strategic Management
Journal, 5 (2), 171-80.

---- (1995), “The Resource-Based View of the Firm: Ten Years After,” Strategic
Management Journal, 16 (3), 171-74.

White, J. Chris, P. Rajan Varadarajan, and Peter A. Dacin (2003), “Market Situation
Interpretation and Response: The Role of Cognitive Style, Organizational Culture, and
Information Use,” Journal of Marketing, 67 (3), 63-79.

Williamson, 0. E. (1985), The Economic Institutions of Capitalism: Firms, Markets,
Relational Contracting. New York, NY: Free Press.

Zaltman, Gerald and Christine Moorman (1989), “The Management and Use of
Advertising Research,” Journal of Advertising Research, 29 (6), 11-18.

128