THE ROLE OF PERCEIVED RISK IN
NEW PRODUCT ALLIANCES
By
“RUBY” PUI-WAN LEE
A dissertation submitted in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
WASHINGTON STATE UNIVERSITY College of Business and Economics
MAY 2003
© Copyright by “RUBY” PUI-WAN LEE, 2003 All Rights Reserved
To the Faculty of Washington State University:
The members of the Committee appointed to examine the dissertation of “RUBY” PUI-
WAN LEE find it satisfactory and recommend that it be accepted.
____________________________ Co-chair
____________________________ Co-chair
____________________________
ii
ACKNOWLEDGEMENT
I would like to acknowledge several important people for their contribution to my
academic development. First of all, I would like to thank Dr. Jean Johnson for her consistent
faith in my ability. I am grateful that she gave me an opportunity to pursue my doctorate and
walked me through the entire program. She never gave up hope on me even when there were
several moments that I had doubts on myself.
I am deeply indebted to Dr. Rajdeep Grewal who has inspired me to develop my research
interests and skills earlier in my career life. I have learned much through his wealth of ideas and
many words of encouragement.
I would also like to thank Dr. John Cullen. Dr. Cullen is Professor at the Department of
Management. His depth and width of knowledge in organizational research stimulated me to
think outside a narrow paradigm.
I am fortunate to meet many other faculty and friends within and outside the Department
of Marketing during my doctoral life. They have been very supportive. My dissertation cannot
be completed without the financial support from the Department of Marketing, Dr. Jean Johnson,
Dr. Donald Stem, and Amit Saini, and research assistance from Brittney, Jodie, and Dr. Kathleen
Warren of the College of Engineering and Architecture. I have very much appreciated their help
with my dissertation.
I am deeply indebted to my family. My two-year-old boy, Leon, has a terrific sense of
humor despite his age. He and baby Hayden have been a tremendous source of great joy. My
husband, Kenny, has been very accommodating and has made personal sacrifice.
iii
THE ROLE OF PERCEIVED RISK IN
NEW PRODUCT ALLIANCES
Abstract
By “Ruby” Pui-Wan Lee, Ph.D. Washington State University
May 2003
Co-chairs: Jean L. Johnson and Rajdeep Grewal This study investigated the relationship between perceived risk types and governance
attributes in new product alliances. The typology of perceived risk including default
(performance and implementation) risk, knowledge leaking risk, relational risk, and reputation
risk was developed. It was suggested that a firm’s different types of risk perception had effects
on the use of governance attributes (contract explicitness and relational components) and that
such governance attributes would influence new product success. Organizational distance, the
dissimilarity between two firms, was believed to moderate the impact of perceived risk types on
governance attributes. Hypotheses were developed on the basis of past studies and field
interviews. Data collected through mail survey of top management executives in high-tech firms
were used to test the hypotheses.
Results from 107 firms suggested that the hypotheses were partially supported. The tests
of hypotheses indicated that firms in new product alliance activities faced various types of risk.
In particular, default risk, relational risk, and reputation risk were found to have direct effects on
the levels of contract explicitness. The use of relational attributes (flexibility and mutuality) was
found to be associated with default risk only. Organizational distance was found to have no
iv
moderating effect on the relationship between risk types and governance attributes. Further,
results suggested that high levels of contract explicitness and relational attributes had positive
effects on new product success.
v
TABLE OF CONTENTS
Page
ACKNOWLEDGEMENT ………………………………………………………………… iii
ABSTRACT ………………………………………………………………………………. iv
LIST OF TABLES ………………………………………………………………………… ix
LIST OF FIGURES ……………………………………………………………………….. xi
CHAPTER
1. INTRODUCTION ………………………………………………………………... 1
The Role Perceived Risk Types ………………………………………………. 1
Purpose of Study and Research Goals ………………………………………… 4
Organization of The Dissertation ……………………………………………… 6
2. LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK ……………….. 7
Conceptual Foundations of Perceived Risk Types ……………………………. 7
Literature Review on Governance Mechanisms and Contracts ……………….. 21
Conceptual Model and Hypotheses ……………………………………………. 30
Effects of Perceived Risk Types on Governance Attributes ...………………… 32
The Moderating Role of Organizational Distance in Risk-Governance
Attributes Relationships ..…………………………………………………. 38
Effects of Governance Attributes on New Product Success …………..………. 42
Summary ………………………………………………………………………. 44
vi
3. RESEARCH METHOD ……………………………………………………………. 46
Research Context ……………………………………………………………… 46
Preliminary Fieldwork ………………………………………………………… 47
Instrument Development Procedures and Measures ………………………….. 49
Sample Frame and Procedures ………………………………………………… 57
Pilot Study …………………………………………………………………….. 60
Main Study …………………………………………………………………….. 66
Response Bias and Validity Checks …………………………………………… 69
Summary ………………………………………………………………………. 72
4. DATA ANALYSIS AND RESULTS …………………………………..………….. 73
Respondent Characteristics and Descriptive Statistics ………………………... 73
Measure Validation ……………………………………………………………. 76
Hypothesis Testing and Results ……………………………………………….. 85
5. DISCUSSION AND CONCLUSION ……………………………………………… 93
Implications ..…………………………………………………………………... 93
Contributions …………………………………………………………………... 95
Limitations and Future Research Directions .………………………………….. 99
BIBLIOGRAPHY …………………………………………………………………………. 102
vii
APPENDIX
A. Prenotification Letters and Cover Letter for Pilot Study …………………………. 116
B. Summary of Indepth Interviews …………………………………………………… 121
C. Original Scale Items ……………………………………………………………….. 124
D. Cover Letters and Questionnaire for the Main Study ...…………………………… 129
viii
LIST OF TABLES
Page
1. Classification Schemas and Definitions of Governance Structure Used in Marketing .. 24
2. Summary of Hypothesized Relationships …………………………………………...… 45
3. Constructs and Definitions …………………………………………………………….. 51
4. Item Factor Loadings and Reliability Analyses ……………………………………….. 64
5. Correlation Matrix of Variables after Purification …………………………………….. 66
6. Sampling Frames and Response Rates ………………………………………………… 68
7. Comparison of Early Respondents to Late Respondents ……………………………… 69
8. Comparison of Respondents to Non-Respondents ……………………………………. 70
9. Comparison of Pilot to Main Responses ……………………………………………… 71
10. Characteristics of Firms and Key Informants …………………………………………. 74
11. Composition of Partner Firms …………………………………………………………. 75
12. Characteristics of Partner Firms ……………………………………………………….. 76
13. First-order and Second-order Loadings of Performance Risk and Implementation Risk 78
14. First-order and Second-order Loadings of Flexibility and Mutuality ………………… 80
15. Results for Confirmatory Factor Analysis Models ……………………………………. 81
16a. Confidence Intervals, Average Variance Extracted, and Construct Reliability – Risk
Types ………………………………………………………………………………… 83
16b. Confidence Intervals, Average Variance Extracted, and Construct Reliability –
Governance Attributes ..……………………………………………………………… 83
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16c. Confidence Intervals, Average Variance Extracted, and Construct Reliability – New
Product Success, Organizational Distance, and Alliance Experience ...……………… 84
17. Correlation Matrix and Summary Statistics ……. …………………………….………. 85
18. Hierarchical Regression Models ………………………………………………………. 89
19. Regression Model Results ……………………………………………………………... 91
20. Regression Models for Testing Mediating Effects ..…………………………………... 92
x
LIST OF FIGURES
Page
1. Full Conceptual Model ………………………………………………………………… 31
2. Effects of Risk Perceptions on Governance Attributes ……………………………...… 32
3. The Moderating Role of Organizational Culture …..………………………………….. 39
4. Effects of Governance Attributes on New Product Success .………………………….. 43
5. Respondent Identification Procedures and Results ...………………………………….. 58
6. Revised Model (Main Effects and Moderating Effects) ………………………………. 86
7. Revised Model (Effects of Governance Attributes on New Product Success) ..………. 90
xi
Dedication
This dissertation is dedicated to my parents, my brothers and sisters, and my parents-in-law
who provided both emotional and financial support
xii
CHAPTER ONE
INTRODUCTION
If I ask why you believe any particular matter of fact…, you must tell me some reason; and this reason will be some other fact, connected with it. But as you cannot proceed after this manner, in infinitum, you must at last terminate in some fact, which is present to your memory or senses; or must allow that your belief is entirely without foundation.
Hume 1748, p. 46
THE ROLE OF PERCEIVED RISK TYPES
Risk is a central notion in strategy literature (Aaker and Jacobson 1990) and the role of
risk has been implicitly explicated in interfirm research. For example, Mishra, Heide, and Cort
(1998, p.277) suggest that “customers are faced with both adverse selection and moral hazard
problems that involve, respectively, uncertainty about supplier characteristics and the risk of
quality cheating”. Similarly, Houston and Johnson (2000, p. 4) observe that Hercules
Corporation “feared customers would steal its know-how, while important customers grew
increasingly concerned over their dependence on Hercules” and they further propose that
asymmetric information cause “buyers to fear that a supplier’s product performance claims may
be exaggerated”. Although these studies express how the role of risk plays out in interfirm
research, do not explicitly include it in their conceptual frameworks.
It is believed that more attention should be given to the role of risk in interfirm
relationships. To illustrate, consider the following examples. In some cases, the focal firm may
have more information than its partner on the products it sells. Asymmetric information between
the focal firm and the partner firm makes the former think of being opportunistically exploited
by the latter (Mishra et al. 1998). In other situations, strategic partners are not willing to share
1
information or knowledge because the social ties embedded in the relationship are weak
(Granovetter 1973; Rindfleisch and Moorman 2001). In either of the above situations, the
perception of risk plays a critical role. Revisit the first scenario. The focal firm may not really
exploit its partner even though it has the information to do so. However, the partner firm might
feel as though exploitation is a very real possibility. Thus, it is what the partner firm perceives
about the risk of being exploited opportunistically that matters. That is what drives its actions
and decision-making. In the second example, the weak social ties may create risk in executing a
plan perceived by partners. These examples suggest that risk, apart from other widely researched
areas such as opportunism, is a distinctive concept that influences ways a firm makes its
decisions. Hence, knowing what risk is and how it relates to decisions made within interfirm
relationships is crucial.
This dissertation examines the role of perceived risk in a setting of new product alliances
(NPA). In high-tech industries and other sectors, a growing number of firms enter into different
forms of interfirm relationships, such as alliances, partnerships, or joint ventures, to develop new
products (Rindfleisch and Moorman 2001; Robertson and Gatignon 1998). Among these types
of interfirm relationships, the use of alliances is increasingly common (Reuer et al. 2002).
An alliance is an “ongoing, formal, business relationship between two or more
independent organizations to achieve common goals” (Sheth and Parvatiyar 1992, p. 72).
Forming alliances to create new products, in fact, is very important and is said to help access to
resources, reduce risks, and shorten innovation time, among others in today’s competitive
environments (Varadarajan and Cunningham 1995).
New product alliances are different from any other forms of alliance activities (e.g., joint
ventures) in that NPAs involve the acquisition and utilization of information and resources
2
between alliance partners that is related to research and development and product innovations
(Rindfleisch and Moorman 2001). Since NPAs involve close interactions and information
sharing between alliance partners, firms are exposed to different types of risk and a lack of
understanding of these risks results in alliance failures or premature termination of alliance
relationships (Das and Teng 1996). As a result, it is important to uncover the relationship
between risk perceptions and what kind of mechanisms can be used to handle the risk
perceptions. The use of a contract is one way to manage risk. A large body of research (e.g.,
Lusch and Brown 1996) suggests that various contractual components are critical in governing
interfirm relationships. Specifically, explicitness, flexibility, and mutuality are three key
attributes examined in interorganizational research (e.g., Lusch and Brown 1996). These
governance attributes are suggested to have effects on performance outcomes (Cannon et al.
2000). Following extant research on contracting, this study also examines the effect of various
governance attributes on new product success which aims at providing insights for practitioners
in the use of various components in their contracts.
In addition, organizational distance, defined as the dissimilarity between firms (Simonin
1999), was included in this study. Specifically, organizational distance relates to the degree of
dissimilarity between alliance partners in terms of their management styles, philosophies, and
business practices (Simonin 1999; Tyebjee 1988). When the organizational distance between
two alliance partners is close, it implies that their business practices, for example, are likely to be
similar resulting in reduced conflicts and misunderstanding (Mosakowski 1997; Pangarkar and
Klein 2001). Thus, knowing the impact of organizational distance is critical in strategic alliances
(Simonin 1999).
3
PURPOSE OF STUDY AND RESEARCH GOALS
The purpose of this dissertation is two-fold. First is to relax the assumption of risk
neutrality proposed in transaction cost economics (Williamson 1975). Specifically,
Williamson’s (1975) transaction cost analysis rests on three behavioral assumptions,
opportunism, bounded rationality, and risk neutrality, to predict the choice of relationship
governance relationships. Throughout the last two and a half decades, most researchers focus on
the assumptions of opportunism and bounded rationality to predict the alternative governance
structures, while the assumption of risk neutrality remains silence (c.f. Rindfleisch and Heide
1997). As Chiles and McMackin (1996, p. 75) observe, “the assumption of risk neutrality has
gone virtually unnoticed.” Since risk is such an important factor in making decisions (Kohli
1989), it is critical to understand the role of risk and how risk is going to affect the choice of
attributes in a contract between firms.
The second purpose is to uncover the different dimensions of risk in interfirm
relationships. Risk has been acknowledged as a multi-dimensional construct elsewhere in the
marketing literature (e.g., Bauer 1967; Dowling 1986). However, its multiple facets have not
been examined in interfirm research. It is particularly important to understand the various types
of risk in interfirm settings since past research indicates that the concept of risk is comprised of
various aspects. Ignoring anyone of them will lead to incorrect conclusions (Kohli 1989). Thus,
there is a need to understand the nature of risk and its role in interfirm alliances.
Toward this end, this dissertation follows the framework from consumer behavior
research (e.g., Bauer 1967) and builds on theories from multiple disciplines to delineate a set of
perceived risk types (performance, implementation, knowledge leaking, relational, and
4
reputation risk) that is pertinent to alliances. I suspect that certain types of perceived risk are
more salient than others in various specific circumstances. Thus, to test the effects of perceived
risk types, this study focuses the influence of risk types on the use of governance attributes in
new product development alliances.
Different types of perceived risk play a critical role in a situation where the focal firm has
to decide how explicit and how normative (levels of flexibility and mutuality) its contract is
going to be in order to maintain and develop successful NPAs. An explicit contract is a written
agreement detailing the extent to which a firm is going to manage various situations if they
happen. In contrast, a flexible contract describes how much adaptation and changes a firm will
make for its partner whereas mutuality of a contract depicts the extent to which a firm shares
support and stands for its partners to handle different future contingencies. The primary
difference between an explicit contract and a normative contract is that the former one
emphasizes its formal presentation and legal bindings, whereas the latter one addresses the
relational components between parties (Macneil 1980). For example, when the focal firm
perceives a high risk in damaging its performance, it may contract with its partner in the most
explicit ways so that all contingencies are accounted for so as to avoid losses in the future. In
addition, extant research suggests that the design of contracts plays an important role in firm
performance (e.g., Lusch and Brown 1996). The following research, thus, attempts to examine
the relationship between governance attributes and firm performance (in terms of new product
success).
Accordingly, the first objective of this research is to identify various types of perceived
risk which are pertinent to NPAs. The second objective is to empirically examine the
consequences of perceived risk types on the design of contracts and the moderating role of
5
organizational distance on the relationship between perceived risk types and governance
attributes. The third purpose is to study the outcome of different governance attributes on new
product success. Taken together, this dissertation attempts to address the following questions:
1. What types of perceived risk can be found in NPAs and what are their theoretical
underpinnings?
2. Which types of perceived risk result in the use of which attributes in a contract to maintain or
govern an alliance for new product development?
3. What is the moderating effect of organizational distance on the relationship between risk
perceptions and governance attributes?
4. What are the performance implications (i.e., new product success) of various governance
attributes?
ORGANIZATION OF THE DISSERTATION
This dissertation is structured as follows:
Chapter 1 provides an overview of the study. Chapter 2 reviews the literature pertaining
to the major constructs in this dissertation and details the conceptual model and the development
of hypotheses. Chapter 3 outlines the research method including the operationalization of
concepts, the sample design, the development of survey instrument, and the data collection
procedures. Chapter 4 presents data analysis procedures and the findings of this study. Chapter
5 provides discussion, conclusion, and recommendations.
6
CHAPTER TWO
LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK
The view that the precision of science and of scientific language depends upon the precision of its terms is certainly very plausible, but it is none the less, I believe, a mere prejudice.
Popper 1945
The role of risk is critical yet has not been understood in interfirm research. It is believed
that more attention should be given into this area. In this chapter, I draw on various disciplines
to review the concept of risk. My discussion throughout the dissertation focuses primarily on the
perception of risk rather than the risk itself. Since perceived risk has been acknowledged as a
multidimensional construct, a set of perceived risk types is identified on the basis of different
theoretical underpinnings. It has also been suggested that perceived risk plays a critical role in
the design of contracts. Organizational distance is proposed to moderate such relationship. In
the second section of the chapter, literature reviews on the two major sets of constructs,
governance structures and contracts, will be provided. The final section outlines the conceptual
model and details the development of hypotheses including the discussion of organizational
distance for this research.
CONCEPTUAL FOUNDATIONS OF PERCEIVED RISK TYPES
The Meaning of Risk
In the past decades, risk has been defined in many different ways which affect the
theoretical development of risk both in marketing and management strategy. According to
Random House Webster’s College Dictionary (2000), risk means the chance of loss. Within
financial literature, risk is associated with default, bankruptcy, or ruin (Horrigan 1966) and is
7
described largely by variability of returns (Libby and Fishburn 1977) or capital asset pricing
model (Sharpe 1964). Risk has also been studied in the management literature (March and
Shapria 1987) where risk is interpreted as the probability of uncertainty associated with the
outcome of a decision. Similar to financial studies, return variance and capital asset pricing
model are the most popular measures to capture the meaning of risk (e.g., Robins and Schachter
1994). Within marketing, particularly in the consumer behavior literature, risk is defined as a
subjective assessment of negative outcomes of a decision (Bauer 1967).
The wide range of views and definitions of risk corresponds to two somewhat
contradictory perspectives. From a decision theoretical perspective, an individual is assumed to
know all possible alternatives and risk is subsumed in his/her choice among the alternatives.
Since the set of alternatives is known, the individual can assign probability to each alternative
and rank them according to their levels of risk (Pollatsek and Tversky 1970). In addition, risk is
concerned with potential outcomes that can be negative, positive, or both in association with
related situations. From a behavioral perspective, in contrast, scholars (e.g., Bauer 1967) argue
that there is no way an individual can know all the possible choice situations, assigning
probability to each situation is therefore impossible. Further, different from the decision
theoretical perspective, risk is viewed primarily as the perception or subjective assessment of a
negative consequence of a decision made (Das and Teng 1996).
My dissertation adopts the latter view of risk. I argue that often times, managers in a firm
do not know all possible consequences and therefore they are not able to assign probabilities to
the negative outcomes accordingly. My assertion stems from what has been acknowledged in
transaction cost economics as the behavioral assumption of bounded rationality, which refers to
human behavior that is “intendedly rational, but only limitedly so” (Simon 1961, p. xxiv). In
8
other words, managers in a firm are “limited in knowledge, foresight, skill, and time” rather than
being lightning calculators (Simon 1957, p. 199). If the managers were the calculators, they
would have identified exactly what they needed and would have assessed all possible situations
they would have to face. Incomplete information and knowledge are the source of uncertainty
causing the managers to perceive risks associated with alternative situations and the decisions
made in those situations (Richardson 1960).
Although some researchers argue that risk is the other side of trust (e.g, Boon and
Holmes 1991), other scholars maintain that risk is different from trust (e.g., Das and Teng 1996).
Das and Teng (2001) contend that trust becomes irrelevant when risk does not exist, however,
risk remains even though trust appears. The authors further suggest that trust such as goodwill
trust and competence trust is a mechanism to reduce risk (Das and Teng 2001). I concur with the
notion that trust is different from risk in which trust involves positive expectations and is
interrelated to commitment (Morgan and Hunt 1994). When trust exists, performance risk can be
eliminated to a large extent. However, trust is not a panacea of risk. Other types of risk such as
reputation risk may still appear even if trust exists (Das and Teng 1996).
It is also important to demonstrate clearly the difference between risk and perceived risk.
Risk is the probability of loss while perceived risk is a manager’s subjective assessment
regarding the probability of loss due to a decision or an action. Thus, risk may not arise when a
firm does not perceive so. For instance, the focal firm does not feel the risk even though its
partner is, in fact, exploiting it. In other words, it is the risk perceived by the focal firm, rather
than the risk itself, that influences its assessment of alternatives and its decision making in
managing interfirm relationships (Sitkin and Weingart 1995). Throughout the dissertation, I
focus on perceived risk as opposed to risk. The actual probabilities of loss are irrelevant to a
9
firm’s reaction to risk because that is not what drives it to make decisions (Das and Teng 2001).
Instead, my view is that the firm only reacts to the risk it perceives, i.e., subjective interpretations
of that risk (Cunningham 1967; Stone and Gronhaug 1993).
So, what is really meant by perceived risk? A review of literature reveals that defining
perceived risk is fraught with controversy and confusion even within the same discipline such as
in marketing (Stone and Gronhaug 1993). Some researchers (e.g., Bauer 1967; Cunningham
1967) define it in terms of uncertainty and consequences. Other researchers (e.g., Bettman 1973;
Dowling 1986) refer to it as levels of importance of a decision and the chance of negative
consequences associated with the decision. For the purpose of this dissertation, the latter view
provides a more appropriate reflection of perceived risk for two reasons. First, chance already
underlines the notion of uncertainty. Because of cognitive limitations and lacking full
information, a firm is not certain about a situation such that it can only estimate the chance or
probability of experiencing a negative outcome. Second, importance is another critical
component of perceived risk. A decision that a firm has to make must have a significant impact
on its well-being (Dutton and Duncan 1987). Only when the decision is crucial to the firm, the
possible negative outcomes associated with it become influential (Lounamaa and March 1987).
In light of this literature, the definition of perceived risk adopted here is the focal firm’s
subjective assessment of levels of uncertainty and magnitude of negative consequences
associated with its partner firm.
The Multiple Types (Dimensions) of Perceived Risk
Extant research in marketing has indicated that perceived risk is one of the important
elements in consumer buying decisions (e.g., Bauer 1967; Dowling 1986; Stem et al. 1977).
10
Nevertheless, even though many studies (e.g., Kohli 1989; Sitkin and Weingart 1995) have
considered the effect of perceived risk elsewhere, it has been treated as a single dimensional
construct rather than a multidimensional construct suggested in the consumer behavior literature
(e.g., Kaplan et al. 1974; Kim and Lennon 2000).
Campbell and Goodstein (2001, p. 440) give an example of wine purchase to demonstrate
the multiple dimensions of perceived risk, “if a consumer is considering buying an unfamiliar
bottle of wine for a dinner party, the perceived risk associated with the purchase could arise
because she does not know how the wine will taste (performance risk) and is worried that her
guests will think poorly of her if it is not a good wine (image risk).” The example illustrates that
at least two types of perceived risk including performance risk and social (or image) risk are
embedded in a buying decision.
Ignoring the multiple dimensions of perceived risk is problematic (c.f., Dowling 1986;
Stone and Gronhaug 1993). For example, in his study, Kohli (1989) proposes that an
organizational decision will be made contingent upon several categories of factors including
buyer characteristics, individual behavior, and situational characteristics such as perceived risk
and time pressure. In this manner, perceived risk is treated as a conditional factor determining
the impact of an individual’s resources on buying decisions. Nevertheless, the author does not
find that perceived risk plays a moderating role in organizational decisions. Regarding the
surprising result, Kohli (1989, p. 60) suggests “the measurement of perceived risk may have
been too global to capture its moderating effect. In future studies, it may be useful to … ask
more directly about the specific nature of the uncertainty faced by the members.”
While critical, the role of perceived risk is still not understood in interfirm research and
the concern regarding the effect of various aspects of perceived risk remains (Kohli 1989).
11
Following the framework in consumer behavior research (Dowling 1986), I examine the role of
perceived risk and propose a set of perceived risk types that derives from and within the
exchange relationship between two firms in the subsequent sections.
Risk Typology
It has been suggested that perceived risk is more than a unidimensional construct (c.f.,
Jacoby and Kaplan 1978; Stone and Gronhaug 1993). Here specifically, it involves various
facets that affect the focal firm’s relationship with its partners. The risk perceived by the focal
firm in association with its reputation is different from a risk in relation to its performance, for
instance. As such, it is critical to separate the possible types of perceived risk and identify
components relating to them. My field interviews and exhaustive review of interorganizational
studies and other literatures including research on implementation, organizational culture,
identity, image, and reputation suggests that five types of perceived risk can be observed in
interfirm alliances. They involve performance, implementation, knowledge leaking, relational,
and reputation risk. Each of them is examined in greater detail in the following sections.
Perceived Performance Risk. Perceived performance risk has been defined in the
marketing literature as the probability that a product purchased results in failure to function as
expected (Jacoby and Kaplan 1978). Recently, a similar notion of perceived performance risk
has also been examined in the management literature. Das and Teng (1999, p. 51) define it as
“the probability that an alliance may fail even when partner firms commit themselves fully to the
alliances.” Perceived performance risk in their sense involves “the prospect of achieving the
strategic goals of the alliance, given full compliance by all partners” (Das and Teng 1996, p.
829). For the purpose of the dissertation, I follow the definition of perceived performance risk
12
that has been recognized in marketing literature (e.g., Bauer 1967; Bettman 1973) with an
emphasis on interfirm relationships. That is, perceived performance risk is defined as the focal
firm’s extent of uncertainty that the products/services or activities provided by its partner firm
fails to function as expected and the negative consequences associated with the failure.
Performance risk lies in the heart of Williamson’s (1975) transaction cost economics.
Transaction cost analysis suggests that firm managers are bounded rational meaning that they
may not have complete information to make rational decisions. In new product alliances, the
focal firm may not have complete information or knowledge about its partner, and therefore may
perceive a risk embedded in a situation where the partner may not deliver what is needed to
achieve the strategic goals predefined in the relationship. Thus, outcomes, i.e., strategic goals,
become a critical denominator of performance risk. Often time, however, it is not easy for a
firm to specify performance outcomes or when the outcomes are too ambiguous that the firm
cannot quantify and measure them (Heide and Miner 1992; Ouchi 1980) and is referred to as
“performance ambiguity” (Heide and John 1990). Under conditions of high task
interdependence between two firms, intangibility of strategic goals and invisibility of a firm’s
contributions to the final outcomes are rendered ambiguous (Jones 1987). Heide and John
(1990) also found that performance ambiguity requires a firm to pay more effort to verify the
ability of its partner.
The theoretical roots of performance risk can also be traced back to social exchange
theories (e.g., Emerson 1976). Social exchange theorists (e.g., Emerson 1976) suggest that a
firm’s past history is a powerful determinant of its present performance. It reflects how a firm
performs and functions in the past and future. If a partner firm’s products and services function
as expected every time, it encourages the focal firm to repeat purchase and the consumption of
13
umbrella brands since using the same partner firm’s products and services reduces the focal
firm’s perceived performance risk (e.g., Erdem 1998; Montgomery and Wernerfelt 1992). Thus,
when the past record of a partner firm is reliable, positive, or favorable, it reduces the risk
perceived by the focal firm in association with its performance.
In addition, perceived performance risk is theoretically grounded in competence
literatures. Competence, in general, indicates the ability or fitness to perform. The performance
outcome of a new product, for example, can be in jeopardy if a partner firm is not as competent
as expected or unable to deliver services according to the focal firm’s predetermined schedule.
All these can make the focal firm perceive a risk associated with its partner’s performance.
Perceived Implementation Risk. Implementation risk corresponds to the level of
uncertainty and negative consequences associated with the interruption of strategic execution
processes when the focal firm’s partner does not implement as expected. The term,
implementation, relates to the coordination between firms on projects, strategies, or information
processing (Cespedes 1991; Kotler 1997; Wind and Robertson 1983). In practice, the focal firm
may require its partner to coordinate with it to establish joint promotions, work out pricing
strategies (Levy and Weitz 2001), develop new products (Bucklin and Sengupta 1993), and carry
out total quality management (Cannon and Perreault 1999). Thus, it is critical for the focal firm
to pair up with a partner firm that can implement as expected.
Process is a distinctive component in implementation. Implementation risk involves the
processes when the focal firm has to coordinate with its partner firm to achieve goals or complete
projects. Implementation risk is different from performance risk in which the latter relates to the
outcomes (i.e., strategic goals or objectives) predetermined between two parties which are
specified explicitly in their relationship. An ideal outcome can be high quality products or
14
services provided by a partner firm in a purchasing relationship. Yet, the partner firm fails to
deliver the products or services as expected by the focal firm. In this case, products or services
are outcomes that induce performance risk rather than processes a partner firm offers to the focal
firm.
Consider the case of an automobile manufacturer and an automobile dealer. The dealer
believes it should be able to make decisions regarding hours of operation, retail pricing, and
employee recruitment. The dealer does not follow the manufacturer’s decision to discount its
products when it believes that there is no other competitor in the same area. However, the
manufacturer believes that the dealer should consult it before making any decisions. As a result,
there exists implementation risk in the auto manufacturer-dealer relationship. The manufacturer
may fear that the dealer does not execute any of its plans and projects. Nevertheless,
performance risk may not arise in this situation since the dealer delivers quality services and
products to customers and keeps making profit as expected by the manufacturer. This example
underlines the importance of implementation processes.
Perceived Knowledge Leaking Risk. Knowledge leaking risk is referred to as the focal
firm’s subjective assessment of the probability that the relationship with a partner firm results in
disclosing sensitive and proprietary knowledge and the negative consequences associated with
such disclosure. Knowledge, in particular, tacit knowledge, embedded in a firm’s procedures,
norms, rules, and forms (March 1991), is a central notion in organizational learning (Grant
1991). Tacit knowledge is difficult to be expressed and codified and yet it must be experienced
and observed (Nonaka 1994). Knowledge facilitates a firm’ recognition, assimilation, and
application of new information that in turn enables it to develop capabilities, a critical resource to
achieve a competitive advantage (Day 1994).
15
Perceived knowledge leaking risk is theoretically grounded in capabilities and resources
and learning literatures. According to resource-based view of the firm, knowledge or
information-based capability represents a firm’s strategic asset if it is unique, valuable, difficult
to imitate and substitute, and is appropriable by the firm (Amit and Schoemaker 1993; Grant
1991). Firms do recognize the strategic value of knowledge and therefore fear that if their
knowledge will be disclosed to outsiders such as partners and competitors. Further, because a
firm’s unique knowledge contributes to distinguish itself from competitors, it has to protect its
knowledge from leaking to outsiders, including partners (Beamish and Banks 1987; Contractor
and Lorange 1986; Hamel 1991).
Leakage, sometimes, is unavoidable, however. Within a firm, leakage occurs when an
employee uses the knowledge acquired in its position to establish a competing firm (Beamish
and Banks 1987). Between firms, leakage appears when technical know-how or knowledge has
to transfer from one firm to another in order to develop new products, for example (Contractor
and Lorange 1986). Specifically, when two firms are engaged in an exchange relationship, how
can the focal firm be sure that sharing its information and knowledge with its partner will not
have any negative effect on its performance and even its survival? If the focal firm’s knowledge,
skills, and abilities can be appropriated by its partner easily, the focal firm is exposing itself in
knowledge leaking risk since it is difficult, if not impossible, to “own” its partner, making it
problematic to secure its proprietary knowledge. Most of the time, the partner firm can just walk
away with the knowledge obtained from the focal firm (Bettis et al. 1992). Therefore, the ability
of the focal firm to prevent knowledge leaking is critical.
To reduce a firm’s perception of risk associated with knowledge leaking in a new product
development alliance it involves an ability to prevent knowledge erosion and retain added value
16
for a firm’s own benefit (Hamel 1991; Kay 1993). To avoid knowledge erosion, Reed and
DeFillippi (1990) suggest that the focal firm can generate knowledge characterized by tacitness,
complexity, and specificity. In an exchange relationship, the focal firm may fear that its partner
will dissolve the relationship after the partner acquires its knowledge (Beamish and Banks 1987).
Hence, when the focal firm’s knowledge is too ambiguous for its partner to understand and
identify its causality, owning such knowledge gives no advantages to the partner firm since it is
not certain how these knowledge can apply to its situations (Peteraf 1993). As a consequence,
leaking a focal firm’s specific knowledge to its partner becomes unimportant.
Perceived knowledge leaking risk is also grounded in transaction cost economics
literatures (Williamson 1991). For example, if a partner firm that is believed to be opportunistic,
it will by some means cheat and confuse its counterpart. If the focal firm thinks that its partner
will steal its proprietary knowledge to develop new products or serve the existing market for the
partner firm’s own benefits, perceived knowledge leaking risk thus arises (Beamish and Banks
1987). So, it is how opportunistic the focal firm believes its partner is influences its perception
of knowledge leaking risk.
Perceived Relational Risk. Relationship implies long-term orientation (Noordewiser et
al. 1990) and mutual commitment between firms (Anderson and Weitz 1992). The notion of
perceived relational risk has been developed in management literature (Das and Teng 1996).
Das and Teng (1996, p. 831) define perceived relational risk as “the probability and consequence
that the partners in inter-firm alliances do not fully commit themselves to joint efforts.” I
suggest that the concept of perceived relational risk can go beyond the scope of alliances and can
be applied to any form of interfirm relationships. For the purpose of the dissertation, perceived
17
relational risk is defined as the focal firm’s levels of uncertainty and the negative consequences
that its partner firm fails to commit as expected in the relationship.
Perceived relational risk can appear on both sides of an exchange relationship (Das and
Teng 1996). The focal firm can behave opportunistic when it has “greater ability to hold up the
[partner] in future contracting” (Houston and Johnson 2000, p. 4). On the other hand, when the
focal firm has already made specific investments in a particular partner firm, and when these
investments are difficult to produce for other customers, the partner firm can take advantage over
its counterpart.
The theoretical roots of perceived relational risk can be traced back to transaction cost
economics (Das and Teng 1996; Morgan and Hunt 1994; Nooteboom et al. 1997; Williamson
1981). Trust is a primary factor leading to perceived relational risk (Das and Teng 1996). Trust
refers to “a willingness to rely on an exchange partner in whom one has confidence” (Moorman
et al. 1993, p. 82). Confidence allows the focal firm to believe its partner to behave truthfully
and be willing to rely on it. As suggested by Ring and Van de Ven (1992), trust reduces the
concern about opportunistic behavior, and therefore suppresses the relational risk perceived by
the focal firm. When trust disappears, the focal firm will monitor its partner in order to reduce
its perceived relational risk (Williamson 1975). In contrast, when the focal firm holds belief in
its partner, the focal firm may not acknowledge or perceive any risk in their new product alliance
activities (Chiles and McMackin 1996). Trust, therefore, influences the perception of risk in a
relationship (Ring and Ven 1992; Zand 1972).
Additionally, a partner’s opportunistic intention is another factor influencing the focal
firm’s perceived relational risk. Opportunism is defined as “self-interest seeking with guile” in
transaction cost economics (Williamson 1975, p. 6). It implies that the partner firm seeks by all
18
means to cheat, mislead, and confuse the focal firm in order to obtain advantages (Williamson
1985). In a recent study, Dahlstrom and Nygaard (1999) propose that opportunism promotes
bargaining, monitoring, and maladaption costs. Nevertheless, some of their findings do not
support their hypotheses. It may be suggested that opportunism does not induce transaction costs
directly. Rather, such hypothetical link can be established only if a firm acknowledges a risk
embedded in an exchange relationship. That is, when the focal firm believes that its partner
engages in opportunistic behavior, such belief will induce a fear that leads to a stronger
perception of relational risk. Consequently, transaction costs are involved to reduce the
perceived relational risk. In contrast, if the focal firm does not perceive a risk in relation with its
partner, it will not consider paying for monitoring and renegotiation. To conclude, perceived
relational risk may be the missing link between transactional costs and opportunism.
Lastly, asset specificity or idiosyncratic assets may be another important factor inducing
perceived relational risk. Asset specificity indicates the extent to which a firm can transfer or
apply its assets to other situations (Williamson 1985). Idiosyncratic assets create sunk costs to a
firm since the assets it invests in a particular relation are no longer valuable beyond that relation.
Thus, the amount of specific assets invested by the focal firm relative to its partner influences
how it perceives the risk embedded in the relation. In a situation where the focal firm invests
idiosyncratic assets more than its partner, according to the equity theory of motivation (Adams
1963), there exists a sense of inequity whenever firms believe that their ratio of outcome to
inputs is different from those of others. As a result, if the focal firm invests more than its
counterpart, it is expected that the focal firm would have a sense of inequity to engender the
perception of relational risk. Even though the focal firm invests less than its partner in the
relation, the sense of inequity triggers the focal firm to concern the partner (Das and Teng 1996).
19
Perceived reputation risk. Reputation risk relates to the extent of uncertainty that society
or relevant constituents (e.g., shareholders, competitors, suppliers, employees, and customers)
will disapprove of a firm’s relationship with another organization and the negative consequences
associated with such disapproval. A reputation is important and serves to distinguish a firm from
others. Some researchers (e.g., Houston and Johnson 2000) suggest that reputation represents a
firm’s public self. Other scholars (e.g., Dutton and Dukerich 1991) suggest that reputation
indicates how a firm believes outsiders see it and therefore is a self assessed image rather than an
image estimated by the public. Nevertheless, a large body of research suggests that both image
and reputation reflect external appraisals of an organization (Berg 1985; Fombrun 1996; Gioia et
al. 2000). This dissertation, following most studies, views both reputation and organizational
image through a similar lens. That is, both reflect the public self of an organization.
Perceived reputation risk is grounded in the literature of social legitimacy (DiMaggio and
Powell 1983). Legitimacy relates to societal evaluations and approvals of organizational goals.
If the focal firm has to engage in an interfirm alliance, it is believed that it will partner with an
organization which image is socially acceptable at least within the same network (Anderson et al.
1994).
Recently, going on-line is highly regarded by customers in today’s competitive markets
(Frazier 1999; Geyskens et al. 2002) and associating with information technological (IT) savvy
firms is considered socially desirable. Thus, many brick-and-mortar firms (e.g., Toys “R” Us
and Wal-Mart) obtain IT services from giant IT firms (e.g., Microsoft Inc. and American Online
Inc.) rather from other small IT providers to prevent from risking their reputation (Bromley
1993). Despite the fact that partnering with legitimate firms may sometimes reduce the focal
firm’s efficiency (Kogut 1988), the primary purpose of doing so allows the focal firm to gain or
20
at least maintain its reputation among other organizations within a network (Anderson et al.
1994; Scott and Lane 2000). As a result, it suppresses the reputation risk perceived by the focal
firm in association with its partner.
Risk varies from situations to situations and has been found playing a critical role in new
product alliances. In the following section, I will turn to review the literatures on contracting
which is considered to be a tool to manage risk perceptions.
LITERATURE REVIEW ON GOVERNANCE MECHANISMS AND CONTRACTS
Since Williamson’s (1975) governance structure of organizations, i.e., markets and
hierarchies, various classifications of governance mechanisms have been suggested in the
marketing literatures over the last two decades (c.f. Rindfleisch and Heide 1997). Most studies
in the 80s and early 90s, following the domain of Williamson’ work, focus on vertical and
horizontal integrations as two primarily types of governance structure (e.g., Gatignon and
Anderson 1988; Klein 1989; Klein et al. 1990). Researchers view transaction costs as the major
concern in the development of governance mechanisms.
While the transaction cost analysis framework is critical, researchers have recently
switched their attention primarily from transaction costs to social exchange components, such as
organizational ties (Granovetter 1973; Hansen 1999) and dependency (Pfeffer and Salancik
1978), and used these social elements to develop types of governance mechanisms or
relationships (e.g., Cannon and Perreault 1999). Some researchers suggest that governance
mechanisms can take a variety of types, including, but not limited to, market governance,
nonmarket governance, formalization, interfirm cooperation, information exchange, and legal
bonds (Cannon and Perreault 1999; Dahlstrom and Nygaard 1999; Heide 1994).
21
The theoretical roots of these studies can be traced back to Macneil’s (1980) and
Williamson’s (1985) seminal work. Specifically, Williamson proposes three types of contracts
which include classical contracts, neoclassical contracts, and relational contracts. Classical
contract, based on full legal protection for the focal firm’s expectation or bargain interest, can be
expressed completely all the future rights and obligations of each party. The emphasis of a
classical contract is on legal rules, formal documents, and self-liquidating transactions.
Neoclassical contract, on the other hand, involves longer-term contracts where all future
contingencies cannot be identified and where appropriate adaptations may not be evident until
the contingency arises. Formal and legal forms of contracts become less relevant while the
presence of a range of processes designed to create flexibility is critical. Similar to classical
contract, however, neoclassical contract considers arbitration procedures when disputes or
conflicts arise.
Not all transactions will fit into either classical or neoclassical contracting, however. In
some cases, contracts or agreements are designed without arbitration procedures, details of
presentation, or remedies. Williamson (1985) refers to this as relational contracting. A
relational contract develops through mutual understanding between firms. Different from
classical contracting, the presentation, formality, and legal status of relational contracting
becomes irrelevant. More important in relational contracting is the need for flexibility in the
legal enforcement of contractual obligations (Campbell and Harris 1993).
Williamson’s three forms of contracting provide the foundations for the development of
contractual forms in the marketing strategy literature. Extant studies expand from both
Macneil’s (1980) and Williamson’s (1985) work and use different means to derive a framework
of contractual use. Table 1 summarizes the classifications of governance relationships and their
22
definitions as they appeared in the marketing literature in the last decade. A closer examination
on the underlying characteristics of these different classifications found in Table 1, however, are
similar. For example, Heide (1994) is one of the earliest scholars to systematically examine and
develop a typology of governance structure. On the basis of transaction cost analysis, resource
dependence perspective, and relational contracting theory, Heide (1994) proposes three forms of
governance structure, namely, market, unilateral/hierarchical non-market, and bilateral
governance. The author defines market governance as discrete exchange which implies no long-
term exchange intentions (Dwyer et al. 1987). In contrast, non-market governance, be it
unilateral or bilateral, relies on the ability of an exchange partner over another to execute rules
and instructions (Bradach and Eccles 1989).
Though Hiede (1994) attempted to develop a typology of governance form in marketing
channels, his focus was on how specific interfirm processes are carried out in each form of
governance rather than what types of governance structure a firm should adopt. Lusch and
Brown (1996) build on social contract perspectives (Macneil 1980) to develop two types of
contracts in marketing channels. They suggest that explicit or hard contracts and normative or
soft contracts are the two major forms of contracts to govern the relationships between buyers
and suppliers. Dahlstrom and Nygaard (1999), on the other hand, differentiate control structures
into two types: formalization and interfirm cooperation. Formalization relates to the extent to
which interorganizational partners use rules and procedures to govern a relationship, while
interfirm cooperation is the extent to which partners coordinate to each other.
23
TABLE 1
Classification Schemas and Definitions of Governance Structure Used in Marketing
Authors Classification / Levels Definition Heide (1994) Governance typology
(form)
1. Market governance
“synonymous with the concept of discrete exchange” (p. 74)
2. Unilateral/Hierarchical nonmarket governance
“an authority structure that provides one exchange partner with the ability to develop rules, give instructions, and in effect impose decisions on the other” (p. 74)
3. Bilateral nonmarket governance
“the parties jointly develop policies directed toward the achievement of certain goals” (p. 74)
Lusch and Brown (1996)
Channel contracting
1. Explicit (hard) contract
“the extent to which an explicit contract attempts to see into the future and explicitly state today (i.e., in the present) how various situations that might occur in the future would be handled if they were to occur” (p. 20)
2. Normative (soft) contract
“when a mutual understanding exists between parties as to how they will interact and deal with each other, including the handling of future contingencies” (p. 20)
Dahlstrom and Nygaard (1999)
Control structures
1. Interfirm cooperation
“the extent to which the principal and agent coordinate strategies” (p. 162)
2. Formalization “the extent to which rules and procedures govern
relationship between interorganizational partners” (p. 162)
24
TABLE 1 (CONTINUED)
Authors Classification / Levels Definition Cannon and Perreault (1999)
Buyer-seller relationships
1. Information exchange
“expectations of open sharing of information that may be useful to both parties” (p. 441)
2. Operational linkages “the degree to which the systems, procedures, and routines of the buying and selling organizations have been linked to facilitate operations” (p. 442)
3. Legal bonds “detailed and binding contractual agreements
that specify the obligations and roles of both parties in the relationship” (p. 443)
4. Cooperative norms
“expectations the two exchange parties have about working together to achieve mutual and individual goals jointly” (p. 443)
5. Adaptations by sellers
“investments in adaptations to process, product, or procedures specific to the needs or capabilities of an exchange partner” (p. 443)
6. Adaptations by buyers
“investments in adaptations to process, product, or procedures specific to the needs or capabilities of an exchange partner” (p. 443)
Cannon et al. (2000)
Governance forms
1. Legal bonds (legal contracts)
“the extent to which detailed and binding contractual agreements are used to specify the roles and obligations of the parties” (p. 182)
2. Cooperative norms (social norms)
“shared expectations regarding behavior” (p. 183)
3. Plural form (both legal bonds and cooperative norms)
“combinations of market, social, or authority-based mechanisms than on any one category exclusively” (p. 184)
Houston and Johnson (2000)
Relationship structure
1. Buyer-supplier contracts
“a buyer-supplier agreement with no explicit promises of relational continuity (implicit expectations may exist)” (p. 2)
2. Joint ventures “a jointly funded entity … in which partners
agree to a formula for sharing risks and rewards” (p. 2)
25
Cannon and Perreault (1999) integrate literatures from various disciplines and use
clustering approaches to segment buyer-seller relationships into six categories: information
exchange, operational linkages, legal bonds, cooperative norms, relationship-specific adaptations
by sellers, and relationship-specific adaptations by buyers. Cannon and his colleagues (2000)
later empirically test the effect of two relationship types, legal bonds and cooperative norms, on
performance.
Most recently, Houston and Johnson (2000) base on the dichotomy of buyer-supplier
contracts versus joint ventures to examine the choice of relationship structure on performance.
The review of current literature reveals, however, that the use of dichotomy of market vs.
nonmarket or contracts vs. joint ventures appears to be oversimplified (c.f., Das and Teng 2001).
Other factors, such as relational ties, levels of dependency, and environmental dynamisms,
dictate the choice of governance or relationship types (e.g., Cannon and Perreault 1999; Lusch
and Brown 1996; Rindfleisch and Moorman 2001).
Despite the fact that there are various forms of governance mechanisms or contractual
types, a closer examination of their definitions suggests that they are quite similar in nature. For
example, the concept of legal bonds proposed by Cannon and his colleagues’ (2000) is parallel to
the meaning of explicit contracts found in Lusch and Brown (1996) in that both of the legal
bonds and the explicit contracts highlight the importance of presentation or explicitness. In
essence, although various classifications exist in the literature, the common thread lie in their
similarity of shared attributes.
Contracts, as governance mechanisms, vary in how they are written, i.e., what attributes
or contractual arrangements are included. Lusch and Brown (1996, p. 20) suggest that two
different forms of contracts can coexist since “explicit and normative contracts are not opposite
26
ends of a continuum.” It is possible for a firm to simultaneously employ a highly explicit
contract and a contract which is secured by social consensus and mutually understood between
organizations. Cannon, Achrol, and Gundlach (2000) likewise propose that plural forms are
possible when a firm adopts both legal bonds and cooperative norms in its contracts. These
examples point to the conclusion that different contractual arrangements including explicitness
and normative attributes (e.g., flexibility, solidarity, and mutuality) can be observed in a contract
(Macneil 1980; Williamson 1985).
Governance Attributes
A governance attribute is defined as any feature or characteristic that comprises a
contract. The nature or attributes of a contract has long been discussed in extant literature (e.g.,
Dwyer et al. 1987; Macneil 1980). Some researchers have empirically investigated the use of
contracts, more precisely, the governance attributes in interfirm relationships (e.g., Cannon et al.
2000; Lusch and Brown 1996). These researchers have recognized that a contract can be in
different forms including various attributes. For example, Lusch and Brown (1996) identify two
specific natures of contractual arrangements, i.e., explicitness and normativeness. They note that
some contracts are written more explicit than others while some are more normative or even
more in both, suggesting that these two attributes are not mutually exclusive with each other.
Cannon, Achrol, and Gundlach (2000) likewise propose two forms of contractual arrangements,
i.e., legal bonds and cooperative norms. They also argue that a contract can be a combination of
plural forms in order to govern an exchange relationship.
Although there is no consensus on which attributes or contractual arrangements comprise
a contract, extant research suggests that explicitness and cooperative norms are the critical
27
components set in the contract to govern a relationship between the focal firm and its partner
(c.f., Macneil 1980). The notion of explicitness is well defined in the literature (Lusch and
Brown 1996; Macneil 1980). The construct, cooperative norms or normative contracts, although
pertinent, is loosely developed in the marketing literature. Norms should go beyond mutual
understanding and include components such as flexibility, adaptability, relational-base, and
solidarity (Macneil 1980). Thus, I see governance attributes as encompassing one legal attribute:
explicitness and two relational attributes: flexibility and mutuality.
Consistent with extant studies (e.g., Cannon et al. 2000), this dissertation focuses on
governance attributes from the focal firm’s perspective. Two major reasons pertain to the
emphasis from the focal firm’s viewpoint. First, when entering into an agreement with a partner,
it is how the focal firm perceives risks in association with its partner that matters. Second, the
use of various attributes in a contract is a tool that the focal firm can manipulate to suppress its
risk perceptions.
Contract explicitness is a legal arrangement that the focal firm can use in a contract.
Explicitness implies the levels of presentiation (Macneil 1980), which is defined as “the extent to
which an explicit contract attempts to see into the future and explicitly state today how various
situations that might occur in the future would be handled if they were to occur” (Lusch and
Brown 1996, p. 20). It reflects how much detail the focal firm’s contract or agreement is written
to specify its roles and obligations in relation to its partner (Cannon et al. 2000).
Relational attributes are governed by social norms rather than legal forces. The degree of
normative attributes relies upon contractual types or contractual relations. Contractual relations
reflect the spectrum between discrete and relational transactions (Macneil 1980). Discrete
contract, at one end of the continuum, suggests that the relationship between the focal firm and
28
its partner is simply transactional. In reality, most transactions, however, “involve relations apart
from the exchange of goods itself. Thus every contract is necessarily partially a relational
contract, that is, one involving relations other than a discrete exchange” (Macneil 1980, p. 10).
To use a relational contract, the focal firm is hoping that it can create more rooms for it to
develop long-term orientations and obligations, and enhance future cooperation with its partner.
Thus, including different degrees of normative attributes: flexibility and mutuality in addition to
explicitness in a contract with its partner is critical (for details see Macneil 1980) and is
consistent to extant research (e.g., Cannon et al. 2000; Heide and John 1992; Lusch and Brown
1996).
Flexibility refers to the extent that a firm can modify itself above and beyond what has
been stated in a contract for its partner (Macneil 1980). It is a mutual expectation that two firms
in an interfirm relationship will make changes for each other (Heide and John 1992).
Researchers find that flexibility is a critical component in social norms which helps resolve
conflicts, create options, and increase adaptability (Dant and Schul 1992; Lusch and Brown
1996).
Mutuality is a key for keeping firms to continue their exchange relationship. It reflects
the expectations of joint efforts to create positive outcomes and is the degree that two firms stand
by one another and cooperate wholeheartedly when facing difficulties. Mutuality impedes both
firms to use power over their partners which in a way facilitates mutual accommodation and
understanding (Macneil 1980).
Contracts are an important form of governance structures. They provide a means to
manage interfirm relationships. In the remaining sections of this chapter, I will propose a
conceptual model on the basis of the risk typology and contracts discussed in the previous
29
sections. In addition, as mentioned earlier, organizational distance is crucial in determining the
effect of risk perceptions on the use of governance attributes. The conceptual model developed
below will also include a detail discussion on the concept of organizational distance. Further, it
is believed that new product success derives from how firms use governance attributes to manage
their partners. As such, it is interesting to examine the effects of governance attributes on new
product success. I am now turning to the conceptual model and hypothesis development.
CONCEPTUAL MODEL AND HYPOTHESES
The conceptual model proposed here includes three components. As shown in Figure 1,
the first component is the main effect of perceived risk types on the design of contracts to
maintain or govern in a new product alliance. Although it seems clear that direct relationships
do exist between perceived risk types and governance attributes, to date, we still do not know
which facets of perceived risk are more salient than others in the design of a contract to maintain
an alliance relationship.
The second component relates to the organizational distance between two partner firms.
Researchers (e.g., Bucklin and Sengupta 1993) suggest that domain and goal similarity is critical
to the creation of alliances and affects governance mechanisms (Williamson 1981). The role of
organizational distance in affecting the use of contract has not been examined, however. On the
basis of my field interviews, it is suggested that organizational distance plays a significant role
between risk perception and governance mechanisms. Thus, this dissertation proposes to
examine its moderating effect.
The third component is the impact of governance attributes on new product success.
Extant research suggests that the appropriate design of contracts leads to enhanced performance
30
(e.g., Lusch and Brown 1996). This study adds on this stream of research to examine such
relationship in the presence of risk perception on new product success. In short, this study
attempts to answer three questions: (1) which dimensions of perceived risk are critical and what
are the combinatory properties of perceived risk regarding the design of contracts, (2) what is the
moderating role of organizational distance, and (3) what are the performance implications of
different governance attributes?
FIGURE 1
Full Conceptual Model
Implementation
Governance Attributes
H7Relational Attributes
Contract Explicitness
New Product
Knowledge
- Flexibility - MutualitySuccess
RelationalPerformance
Perceived Risk
Reputation
H1-5
H6
Organizational Distance
31
EFFECTS OF PERCEIVED RISK TYPES ON GOVERNANCE ATTRIBUTES
Researchers have theorized that perceived risk is a critical element in organizational
buying decisions (Johnston and Lewin 1996; Kohli 1989; Peters and Venkatesan 1973). Puto,
Patton, and King (1985) suggest that gathering information, playing odds, and spreading risk are
three primary strategies to reduce perceived risk. Here, relying on contracting theoretical
perspectives (Macneil 1980; Williamson 1985), I propose that the design of contractual
arrangements is an alternative strategy to handle perceived risk. Since evidence shows that
focusing on a global nature of risk is insufficient (Kohli 1989) and some researchers also
theorize that specific types of risks dictate the governance of structure in an alliance (Das and
Teng 1996), I hypothesize that performance, implementation, knowledge leaking, relational, and
reputation risk perceptions have direct effects on governance attributes as shown in Figure 2.
FIGURE 2
Effects of Perceived Risk Types on Governance Attributes
Reputation Risk
Relational Risk
Knowledge Leaking Risk
Implementation Risk
H1-5Relational Attributes - Flexibility - Mutuality
Governance Attributes
Contract Explicitness
Perceived Risk Types
Performance Risk
32
Although the assumption of risk neutrality has been neglected in the majority of
marketing (c.f., Rindfleisch and Heide 1997), literatures in law and economics (e.g., Allen and
Lueck 1999) suggest that the idea of risk is increasingly important. In fact, risk is such an
important factor that helps predict the choice of governance structure and well as the
arrangement of a contract. For example, in conditions where the focal firm believes that its
partner perceives high levels of risks on it, the firm will most likely design an exhaustive
contract for performance relief, dispute resolution, among others to maintain stability of the
contract with its partner. Similarly, Otsuka, Chuma, and Hayami (1992, p. 2012), in their study
of agricultural economies, found that the exposure of risk “provides the most consistent
explanation for the existence of a share contract.”
The dominance of this risk explanation in economics is promising, yet the empirical
evidence to support its implications is not only scant, but also mixed. Prendergast (1999, p. 21),
an agricultural economist, alludes that “there is some evidence that contracts are designed to
optimally trade off risk against incentives. However, the evidence is hardly overwhelming, with
some studies showing the effect of noise on piece rates while others show little.” In interfirm
research, studies on risk and the use of contracts are inadequate. Since risk has been
acknowledged as a critical component in contracting (Allen and Lueck 1999), I explore the
impact of specific types of perceived risks on governance attributes as shown in Figure 2.
Effects of Perceived Performance Risk
When perceived performance risk is high, which means that the chance that the final
products or services offered by a partner firm cannot function as expected by the focal firm and
33
when the negative consequences associated with unsatisfactory products is significant, the focal
firm may want to design a contract which details all possible future events in order to avoid any
loss. Performance risk perception does arise very likely as the focal firm cannot always observe
the partner firm’s outputs perfectly. Some products or services are simply difficult to measure
their performance accurately (Heide and Miner 1992). For instance, it may be difficult to
ascertain whether a grain supplier provides its buyer the best quality of flour. Thus, when
performance ambiguity exists, the focal firm is exposed to risks (Heide and John 1992).
Imperfect observation of outputs seems to be relevant in most situations. When
Williamson’s (1985) assumption of risk neutrality is abandoned, the imperfect observation of the
output leads to critical consequences on a contract (Lawarrée and Audenrode 1996). Thus, to
mitigate the negative consequences associated with a partner firm’s performance outcomes, the
level of explicitness stated in a contract can be regarded as a means for the focal firm to attenuate
its fear.
In addition, when perceived performance risk arises, the focal firm should develop a
contract with an emphasis on both flexibility and mutuality. Mutuality promotes cooperation. It
means that a firm will put efforts to produce benefits for each other (Macneil 1980). Flexibility
allows the focal firm to make changes if necessary. Thus, when the focal firm perceives high
performance risk on its partner, a contract that includes the components of mutuality and
flexibility will become a useful mechanism to reinforce or encourage win-win situations
(Lawarrée and Audenrode 1996).
H1: The focal firm’s performance risk perception is positively related to the levels of (a)
explicitness, (b) mutuality, and (c) flexibility in a contract.
34
Effects of Perceived Implementation Risk
Implementation risk occurs when the focal firm believes that its partner does not
coordinate and execute projects and plans as expected in their new product alliance. In this case,
the focal firm may fear that its plans will be interrupted if the partner does not carry out its
responsibilities. When the focal firm believes that its partner fears to break down in
implementation processes, it implies that the focal firm should clearly specify the requirements
and conditions in a contract. High levels of explicitness in a contract become very important as a
highly explicit contract implies that all procedures, steps, communications, and other behaviors
or actions that will be taken place are specified in the contract (Williamson 1983).
To reduce a firm’s risk perception associated with implementation breakdown, other
normative attributes in a contract may be necessary (Cannon et al. 2000). As Cannon, Achrol,
and Gundlach (2000, p. 184) allude, normative attributes “involve expectations rather than rigid
requirements of behavior, they create as cooperative as opposed to a confrontational environment
for negotiating adaptations, thus promoting continuity in exchange.” Likewise, Lusch and
Brown (1996) argue that flexible norms allow a partner firm to adapt to changes required by the
focal firm. Since implementation can break down easily when mutual understanding is
inadequate, the attribute of flexibility included in a contract by the focal firm provides such a
means for it to make changes. Flexibility is also regarded as an important normative attribute
against any of deviant behavior during implementation processes. As a result, if the focal firm is
believed to have high implementation risk perception on its partner, it should include flexibility
component in the contract. Similar to the situation when perceived performance risk is high,
mutuality also promotes the beliefs that the partner firm will cooperate and create win-win
35
situations by sharing information about production and marketing schedules, timing, and other
implementation processes with the focal firm (Macneil 1980).
H2: The focal firm’s implementation risk perception is positively related to (a)
explicitness, (b) mutuality, and (c) flexibility in a contract.
Effects of Perceived Knowledge Leaking Risk
Knowledge leaking risk is the risk that a firm may fear that its knowledge will disclose to
other organizations and thereby losing its competitive advantage. Extant research has also
proved that knowledge leaking to a partner firm is detrimental (e.g., Beamish and Banks 1987;
Hamel 1991). In an NPA setting, sometimes, it is unavoidable for a firm to release information,
data, or technical know-how to its partner when joint activities such as new product
developments are taken place. Such fear is understandable. To reduce the potential for
downside informational losses that the focal firm may come across, providing an explicit
contract for hard bargaining may be a useful catalyst (Gundlach et al. 1995). An explicit
contract helps secure the focal firm to have the right to enforce penalties.
In addition, when perceived knowledge leading risk is high, strong mutuality and
flexibility in a contract may serve to suppress such fear. Mutuality projects an image that a focal
firm is willing to work with its partner toward the goal of positive outcomes. It further promotes
the beliefs that both parties will cooperate and create win-win situations by sharing information
on production schedules and shipping information, among others to each other (Macneil 1980).
Flexibility attenuates the feeling that the partner firm will take advantages of the focal firm and it
therefore should positively relate to perceived knowledge leaking risk.
H3: The focal firm’s knowledge leaking perception risk is positively related to (a)
explicitness, (b) mutuality, and (c) flexibility.
36
Effects of Perceived Relational Risk
Relational risk is the risk that a partner firm does not commit to the focal firm (Das and
Teng 1996). To ensure against the feeling that the partner firm will not commit to the
relationship, the focal can design a complete contract to include all future contingencies
(Williamson 1985). Some researchers, for example, Maher (1997), in his study of vertical
integrations and hold-up problems, suggests that a firm should clearly state the terms and
conditions each party would undertake to reduce conflicts when another firm does not commit
itself to the relationship. In contrast, some researchers (e.g., Lyons and Mehta 1997) contend
that a too conscientious contract simply creates negative feeling and induces bad faith that a firm
may see in its partner. I concur with the latter point of view and believe that a detailed contract
only provokes the opportunistic behavior and thereby increases relational risk perception.
Explicitness is not a panacea in all situations and other normative arrangements in a
contract are necessary (Williamson 1993). Heide and his colleagues (1990; 1992) suggest that
the use of relational attributes can cultivate the expectation of long-term commitment which is a
critical suppressor of relational risk perception. To attenuate such risk perception, the focal firm
should include both mutuality and flexibility components in a contract. Mutuality reinforces the
notion of continuance of a relation whereas solidarity maintains that both parties will stand by
each other in case problems occurred. Flexibility reduces the chances that the partner firm will
take opportunities from the focal firm. Thus, high levels of mutuality and flexibility discount the
focal firm’s negative feeling on the partner. .
H4: The focal firm’s relational risk perception is (a) negatively related to the level of
explicitness but (b) positively related to mutuality and (c) flexibility in a contract.
37
Effects of Perceived Reputation Risk
Reputation relates to the extent that a firm is regarded by outsiders (Weiss et al. 1999).
Perceived reputation risk arises when the focal firm fears that the affiliation with its new product
alliance partner will influence its organizational reputation in the eyes of stakeholders (e.g.,
shareholders, customers, competitors, employees, and other partner firms). “Reflected glory and
guilt by association” suggested by Bromley (1993) is an excellent illustration. A firm’s
reputation is tied to its partner through ‘guilt by association’ or ‘reflected glory.’ Evidence also
suggests that firms do watch their reputations and are concerned about managing their
reputations through different means such as the use of sales representatives (Weiss et al. 1999).
This indicates that a firm will detail all possible contingencies. In case the firm’s partner is
involved in some affairs that may affect the focal firm’s reputation, it can terminate the
relationship as specified in a contract.
H5: The focal firm’s reputation risk perception is positively related to the level of
explicitness in a contract.
THE MODERATING ROLE OF ORGANIZATIONAL DISTANCE IN RISK-
GOVERNANCE ATTRIBUTES RELATIONSHIPS
The second component of my conceptual model deals with the moderator, i.e.,
organizational distance. As shown in Figure 3, organizational distance influences the
relationship between risk perceptions and governance attributes. Organizational distance has
been found in extant research that have effects on the formation and management of strategic
alliance partners (Simonin 1999).
38
FIGURE 3
The Moderating Role of Organizational Culture
Perceived Risk Types
Performance Risk Contract Attributes
Contract Explicitness
Reputation Risk
Relational Risk
Knowledge Leaking Risk
Implementation Risk
H6
Organizational Dis
39
Relational Attributes- Flexibility - Mutuality
tance
Organizational distance represents the extent to which two alliance firms are dissimilar to
each other (Simonin 1999). Each firm has its own organizational culture and can be dramatically
different from its partner. Organizational culture denotes “the shared beliefs which pertain to
dominant organizational attributes, leadership styles, organizational bonding mechanisms, and
overall strategic emphasis” (Deshpandé et al. 1993). It has been proposed to have effects on
various marketing practices. For example, Moorman (1995) examined the impact of culture on
the use of marketing information and new product development processes. Likewise, Hewett,
Money, and Sharma (2002) found that internally focused corporate cultures have stronger
association with the positive relationship between relationship quality and buyers’ repurchase
intentions than externally focused corporate cultures. While organizational culture has been
explored in extant studies (e.g., Balakrishnan and Wernerfelt 1986; Hewett et al. 2002), a core
issue of how far apart the organizational culture between the focal firm and its partner has
seldom been examined (for exceptions, see Simonin 1999).
Knowing the organizational distance between two alliance firms, i.e., how far the focal
firm’s organizational culture is different from its partner, is critical (Tyebjee 1988). As Achrol,
Scheer, and Stern (1990) observe, difference in perceived position or status among the
managerial levels at which interaction occurs between firms could lead to cultural and political
conflict. Likewise, Johnson and her colleagues (1996) find that firms sharing similar
organizational structures and business practices are more likely to become successful in their
joint venture. Consistent with their study, I propose that organizational distance which is defined
as the gap between two partner firms in terms of their company philosophy, management style,
40
and other business practices is important and is believed to affect the relationship between risk
perceptions and governance attributes (Figure 3).
When the focal firm’s organizational distance is close to its partner firm, the links
between risk perceptions and levels of explicitness in a contract should be weakened while the
links between risk perceptions and levels of flexibility and mutuality should be strengthened.
The reason is that a small organizational distance between two firms implies that they have
similar philosophies, business practices, and risk taking orientation and thereby requires a less
explicit contract to govern the relationship (Williamson 1975). In line with this argument,
Bucklin and Sengupta (1993) find that domain and goal similarity is important in the creation of
alliances and such organizational compatibility allows a firm to develop positive feelings on its
partner. However, when both of their organizational cultures are different from each other, the
focal firm may see its partner more difficult to communicate (Mosakowski 1997) inducing
stronger risk perceptions. As a result, the focal firm may have a higher level of explicitness in a
contract (Williamson 1981).
To conclude, organizational distance can be regarded as a moderator changing the
relationship between risk perceptions and the use of governance attributes. The closer the
organizational distance between two firms, the relationship between risk perceptions and levels
of explicitness would be weakened while the association between risk perceptions and levels of
flexibility and mutuality would be strengthened. The above discussion leads to the following
hypotheses.
H6a: The positive relationship between risk perceptions and levels of explicitness is
stronger when the organizational distance between the focal firm and its partner is
wide.
41
H6b: The positive relationship between risk perceptions and levels of (a) flexibility and
(b) mutuality is stronger when the organizational distance between the focal firm
and its partner is narrow.
EFFECTS OF GOVERNANCE ATTRIBUTES ON NEW PRODUCT SUCCESS
The third component included in the conceptual model relates to the outcomes of
governance attributes on new product success. Although studies on the impact of governance
attributes on new product development are inadequate, extant research suggests that governance
attributes do affect firm performance (e.g., Cannon et al. 2000; Lusch and Brown 1996). In this
research, I propose that governance attributes are crucial in determining new product success.
Such hypothetical relationships will be examined in the following sections.
Developing new products with other firms is increasingly important and has been
suggested to provide strategic value to the focal organization (Sivadas and Dwyer 2000). A
review of the current literature further suggests that the choice of governance modes is critical to
new product success (e.g. Rindfleisch and Moorman 2001; Robertson and Gatignon 1998).
Forming alliances to develop new products seem to be promising. However, Gates (1993) found
that most alliances are unstable and many of them fail even before their ultimate goals are
fulfilled. By some estimation, the failure rate is as high as about 70% of total alliances (c.f.
Sivadas and Dwyer 2000). I contend that the choice of governance modes is important, yet the
attributes included in contracting with partner firms is even more critical. That is, what
components incorporated in a contract determine the success of an alliance relationship,
specifically, new product outcomes.
42
Both legal (explicitness) and relational (flexibility and mutuality) attributes are expected
to have positive effects on new product outcomes as illustrated in Figure 4. Specifically, using
explicit contracts to specify a firm’s responsibilities and obligations reduces role ambiguities
(Lusch and Brown 1996), suppresses its risks and uncertainties (Cannon et al. 2000), and is
believed to enhance new product success. For example, Cannon, Achrol, and Gundlach (2000, p.
183) find that a clearly specified and detailed contract helps both suppliers and buyers to
“visualize potential contingencies and devise appropriate safeguards” resulting in enhanced
performance. Thus, levels of explicitness should positively relate to new product success. When
a contract is written in a high level of explicitness, it implies that all possible details such as time
of response and enforcement are included. By having the partner firm to follow the explicit
details in a contract, the focal firm should be able to deliver its new product within a planned
time schedule.
FIGURE 4
The Effects of Governance Attributes on New Product Success
H7
New Product Success
Governance Attributes
Contract Explicitness
I
circums
contract
Relational Attributes - Flexibility - Mutuality
n addition, a high level of flexibility in a contract allows firms to adapt to changed
tances. It therefore should have a positive effect on new product success. A flexible
means the ease of changing organizational decision processes and structures (Harris et
43
al. 1998) and reacting to new demands (Li and Kouvelis 1999). A flexible contract can also
speed up the development of new products (Clark and Fujimoto 1991; Eisenhardt and Tabrizi
1995).
Mutuality indicates that two firms in a contract must stand by each other to become
successful (Macneil 1980). The importance of mutuality is that it encourages firms to create
mutual benefits and share information when their partner firms need so. It is suggested that
mutuality should enhance new product success. Such expectation can be explained in terms of
social ties and relational embeddedness suggested elsewhere in interfirm studies (e.g., Hansen
1999; Moorman et al. 1992; Rindfleisch and Moorman 2001; Uzzi 1999). For example, Hansen
(1999) finds that lacking mutuality or weak ties among team members hinders the transfer of
knowledge in new product development activities resulting in longer project completion time.
Without mutuality, new product development activities may suffer (Uzzi 1999).
H7: There is a positive relationship between (a) explicitness, (b) mutuality, and (c)
flexibility and new product success.
SUMMARY
This chapter has detailed the theoretical framework and has proposed a set of testable
hypotheses. Table 2 presents a summary of the relationships between risk perceptions and
governance attributes and how governance attributes in turn affect new product success and the
moderating role of organizational distance.
44
TABLE 2
Summary of Hypothesized Relationships
H1: The focal firm’s performance risk perception is positively related to the levels of (a)
explicitness, (b) mutuality, and (c) flexibility in a contract.
H2: The focal firm’s implementation risk perception is positively related to the levels of (a)
explicitness, (b) mutuality, and (c) flexibility in a contract.
H3: The focal firm’s knowledge leaking perception is positively related to the levels of (a)
explicitness, (b) mutuality, and (c) flexibility in a contract.
H4: The focal firm’s relational risk perception is (a) negatively related to the level of
explicitness but positively related to (b) mutuality and (c) flexibility in a contract.
H5: The focal firm’s reputation risk perception is positively related to the level of explicitness in
a contract.
H6: The positive relationship between risk perceptions and levels of explicitness is stronger
when the organizational distance between the focal firm and its partner is wide.
H6b: The positive relationship between risk perceptions and levels of (a) mutuality and (b)
flexibility is stronger when the organizational distance between the focal firm and its
partner is narrow.
H7: There is a positive relationship between (a) explicitness, (b) mutuality, and (c) flexibility
and new product success.
45
CHAPTER THREE
RESEARCH METHOD
To the people who see the possibilities, and who, sometimes with courage, sometimes with faith and hope – but always with effort, perseverance, and energy – strive to make the possible become reality.
Mohr 2001
This chapter presents the research procedures including the sampling frame, data collection,
operationalization of constructs, scale development, questionnaire design, and analysis plan. The
proposed research procedures are employed to investigate the following areas:
1. The effects of perceived risk types on governance attributes.
2. The moderating role of organizational distance on the relationship between risk
perceptions and governance attributes.
3. Performance implications (i.e., new product success) of governance attributes.
RESEARCH CONTEXT
High technology industries are known to be full of complexity and volatility, which is the
source of risk perception created on both manufacturers and their partners (Heide and Weiss
1995; Krishnan and Bhattacharya 2002; Ruyter et al. 2001). Specifically, firms in high
technology industries must cope with the fact that they are exposed to different types of risk
when they develop new products with other organizations. In this dissertation, I chose to study
electronics industries including computers, facilities, materials, and equipments,
telecommunications, and transportation in the US. These industries are characterized by rapid
technological changes (Mohr 2001), which provide an excellent research context to examine
perceived risk types and the design of contracts.
46
PRELIMINARY FIELDWORK
Before conceptualizing the model for this dissertation, extensive preliminary fieldwork
was conducted to (1) uncover various types of risk in interfirm relationships and (2) identify an
appropriate research context. Ten telephone interviews with senior executives were conducted
between February and March 2002. These managers represented different industries such as
electronics, software, textile and clothing, and pharmaceuticals and were knowledgeable about
inter-organizational relationships.
The interviews were conducted in an unstructured manner. Managers were asked to
describe some of the situations they had come across in reality when dealing with their partners,
be they suppliers, customers, or partners.
To demonstrate perceived performance risk, consider what a merchandising manager at a
large trading company said to me:
“Sometimes, we are thinking of switching to another supplier who can
produce the same products at a lower price. But we never make it happen
because we are not sure whether the product quality of a new supplier is as
good as reliable as our current supplier.”
To illustrate perceived implementation risk, a merchandising manager of a sports good
company with $5 million in sales describes his experience:
“Every time when I go to a trade fair, I am looking for potential suppliers
who can replace some of the current suppliers. I am not quite happy with them
because I always have to spend a whole lot of time to email or fax to them to ask
for a production status, samples, or shipping schedules. They never get back to
47
me in time. I just find very difficult to implement my own plans when I really need
their samples to show to my clients.”
A senior merchandiser at a backpack trading and manufacturing company shares her
experience of perceived relational risk with me:
“Our company has contracted out our production to another factory in
China. We provide them materials that they need for production. Those
materials such as fabrics are imported from Korea and Japan and are very
expensive. We pay for the production materials. But then we were told that they
have been stealing the materials to make money out of extra production.
Although we don’t have any proof, we really think that the factory is not fully
committed to us.”
An owner of a small manufacturer summarizes what we learned about perceived
reputation risk.
“We lost about 10,000 dollars to Wal-Mart in our last shipment. We
really want to terminate our relationship with Wal-Mart. However, we just
cannot afford to do so because we are afraid of losing other customers. Some
customers, they probably may think that we cannot meet the order or we may do
something wrong and therefore Wal-Mart terminates its relationship with us.”
To conclude, these examples drawn from the preliminary field interviews which provide
a base for the development of risk typology. It is believed that one type of risk perception can
be more salient than others depending upon the situations a firm is facing. However, various
types of risk perceptions can coexist in any interfirm relationships.
48
INSTRUMENT DEVELOPMENT PROCEDURES AND MEASURES
Multiple indicators were used to represent unobservable constructs to increase their
validity (Bagozzi et al. 1991; Churchill 1979). Wherever possible, existing scales were used in
this study. Risk perceptions, however, are new and require extensive work to develop an
instrument for each of the risk types. For new constructs (e.g., perceived implementation risk
and perceived reputation risk), I followed recommended procedures (Churchill 1979; Gerbing
and Anderson 1988) to develop multi-item measures.
An initial pool of new scale items was generated based on the review of literatures and
discussions with academic experts in this area. Subsequently, another wave of qualitative
fieldwork was conducted. Six interviews were set up initially with the assistance from the
College of Engineering and Architecture at Washington State University. The College of
Engineering and Architecture has extensive business connections with high tech firms. Finally,
four interviews out of six were conducted with senior executives to verify the
comprehensiveness of the perceived risk typology, to assess the clarity of scale items, and to
improve the overall flow of the research instrument. Appendix A summarizes each of the
indepth interviews.
Respondents were asked to fill out a questionnaire and give comments and feedback on
the questionnaire. Based on the comments received from the field interviews, questions were
restructured and the layout of the survey was modified in the following manners. First, the
instruction of asking key informants to identify a new product alliance partner as a reference was
moved from the cover page to the beginning of the questions. Managers commented that they
normally did not pay attention on the cover page. Second, four demographic-type questions
were moved from the end to the beginning of the questionnaire. The purpose is to get
49
respondents involved in the alliance partner they have chosen to make references to for this
study. Third, a sentence, “Please be sure to keep focusing on the partner firm you have
identified,” was used wherever appropriate to remind respondents to continually make references
to the partner firm they had selected at the beginning of the study. Fourth, the ownership of new
product brands and technology seems to be critical in affecting respondents’ risk perceptions. As
such, four questions, i.e., “With regard to the brand of the new product, what kind of
arrangement has been made?,” “ Who owns the new product brand?,” “Who owns the
technology?,” and “Who will be responsible for introducing and marketing this new product?,”
were added in the second section of the questionnaire. Finally, some items were removed or
modified after receiving the feedback from the managers and extensive discussions with
academic experts.
Measures
The measure development procedures involve developing multiple items for each
construct in the proposed model. The following sections describe each of the measures.
Perceived Risk Types
Following the framework developed in consumer behavior research (e.g., Bettman 1973)
and organizational studies (e.g., Das and Teng 1996), five different types of risk perceptions
were investigated. Perceived performance risk relates to the technology, services, or
components provided by a firm that will cause its partner firm to lose. A total of six completely
new items were created. Sample items to capture the domain of perceived performance risk
include, “we feel uncertain whether our partner firm can contribute to our new product
development,” “we are worried about the adequacy of technology offered by our partner firm,”
50
and “the chance that our new products will fail in the market is high if the partner firm does not
deliver required technology.” Table 3 provides the sample items and construct definitions.
TABLE 3
Constructs and Definitions
Construct Definition and Sample Questions and Items Scale Development
Independent Variables Perceived Performance Risk
The extent of uncertainty associated with jointly developed products and services failing to function as expected and the negative consequences associated with the failure. We feel uncertain whether our partner firm
can contribute to our new product development.
We are worried about the adequacy of technology offered by our partner firm.
New scale, anchored on a seven-point Likert scale
Perceived Implementation Risk
The level of uncertainty and negative consequences associated with the interruption of strategic execution processes when the focal firm’s partner does not implement as expected. We feel uncertain whether we can effectively
coordinate with the partner in developing new products.
We are afraid that we cannot get the partner firm to buy into what needs to be done in developing new products.
New scale, anchored on a seven-point Likert scale
Perceived Knowledge Leaking Risk
The extent to which the focal firm’s proprietary knowledge will be disclosed to other organizations through the development of new products with its partner firm and the negative consequences associated with such disclosure. We fear that too much proprietary
knowledge may be disclosed to this partner firm.
We could suffer a loss if our new product specifications and designs are released to this partner.
New scale, anchored on a seven-point Likert scale
51
TABLE 3 (CONTINUED)
Constructs and Definitions
Construct Definition and Sample Questions and Items Scale Development
Perceived Relational Risk
The extent to which the focal firm is uncertain about its partner firm’s commitment and the negative outcomes when the partner firm is not committed fully to the new product development alliance. We are afraid that this partner firm is not as
dedicated as they should be to make our joint new product development work.
Our firm is at risk if we break up with this partner firm and have to find a new partner
New scale, anchored on a seven-point Likert scale
Perceived Reputation Risk
The extent to which the society or relevant constitutes will disapprove of a firm’s relationship with another organization and the negative consequences associated with such disapproval. If our partner firm does not have a good
reputation, there is some chance our reputation will suffer also.
Our partner’s reputation is so strong and positive, associating with them could only increase our own reputation.
New scale, anchored on a seven-point Likert scale
Moderator Organizational Distance
The extent to which the focal firm’s domain, philosophy, and business practices is different from or similar to its partner. Company culture Operating philosophies
Adapted from Johnson et al. (1996), anchored on a seven-point scale
Mediators
Explicitness The extent to which a contract is presented to its partner In dealing with this partner, your contract or agreement precisely defines The role of each party. How disagreements will be resolved.
Adapted from Lusch and Brown (1996), anchored on a seven-point Likert scale
52
TABLE 3 (CONTINUED)
Constructs and Definitions
Construct Definition and Sample Questions and Items Scale Development
Flexibility The extent to which a firm can adapt to changed circumstances Your agreement with the partner firm allows both of your company and your partner to Make changes when necessary. Make adjustments in the ongoing
relationship with the partner to cope with changing circumstances.
Heide and John (1992), anchored on a seven-point Likert scale
Mutuality The extent to which a firm can adapt to changed circumstances Your agreement with the partner firm allows both of your company and your partner to Work together to be successful. Access information each of us need.
Heide and John (1992), anchored on a seven-point Likert scale
Outcome Variable
New Product Success
The extent to which the new product developed jointly with the partner is successful The overall performance of our new product
program has met our objectives. From an overall profitability standpoint, our
new product development program has been successful.
Adapted from Sivadas and Dwyer (2000) and Song, Sounder, Dyer (1997), anchored on a seven-point Likert scale
Perceived implementation risk reflects the level of uncertainty and negative consequences
associated with the interruption of strategic execution processes when the focal firm’s partner
does not implement as expected (McDermott and Boyer 1999). Extant literature (e.g., Noble and
Mokwa 1999) suggests that implementation relates to the coordination between firms. On this
basis, seven items were developed to measure perceived implementation risk. Sample items
include: “we feel uncertain whether we can effectively coordinate with the partner in developing
53
new products,” “we are afraid that we cannot get the partner firm to buy into what needs to be
done in developing new products,” and “we stand to lose our competitive advantage if our
partner does not execute and implement according to requirements” (Table 3).
Perceived knowledge leaking risk is described as the extent to which the focal firm’s
proprietary knowledge will be disclosed to other organizations through the development of new
products with its partner firm and the negative consequences associated with such disclosure.
Following the literature on organizational learning and interfirm relationships (Beamish and
Banks 1987; Hamel 1991) and field interviews, seven new items were developed. For instances,
“we fear that too much proprietary knowledge may be disclosed to this partner firm,” “we could
suffer a loss if our new product specifications and designs are released to this partner,” and “we
fear that we will lose our competitive advantage if our proprietary product knowledge is
disclosed to our partner firm.”
Perceived relational risk has been discussed in the management literature (Das and Teng
1996). Using related literature in management (Das and Teng 1999) as a guide and with a
specific emphasis on the context of new product alliances, seven new items were created.
Sample items illustrated in Table 3 include: “we are afraid that this partner firm is not as
dedicated as they should be to make our joint new product development work,” “our firm is at
risk if we break up with this partner firm and have to find a new partner/ally,” and “our firm has
taken a risk in trusting and committing to the relationship with this partner.”
Perceived reputation risk relates to the extent to which the society or relevant constitutes
will disapprove of a firm’s relationship with another organization and the negative consequences
associated with such disapproval. Drawing from the literature on organizational image and
reputation (Gioia et al. 2000; Houston and Johnson 2000), seven new items were developed.
54
Sample items include: “if our partner firm does not have a good reputation, there is some chance
that our reputation will suffer also,” “our partner’s reputation is so strong and positive,
associating with it could only increase our own reputation,” and “it is risky for us to develop new
products with this firm because it seems that their reputation with our customers is not all that
good.”
Organizational Distance
It is defined as the extent to which the focal firm’s domain, philosophy, orientation, and
business practices is different from or similar to its partner firm. The measure was modified on
the basis of Johnson et al. (1996) with emphases on new product development. Respondents
were asked to what extent their companies were different from or similar to their partner firms on
the following items: “risk taking,” “innovativeness,” and “new product development processes,”
for instances. All items were anchored on a seven-point scale in which 1 represents very similar
to partner firm and 7 represents very different from partner firm.
Governance Attributes
Explicitness, flexibility, and mutuality are included in this research. The measure of
explicitness is adapted from Lusch and Brown (1996). Since this research focuses on new
product alliances, a specific component relating to intellectual property was added. Respondents
were asked the extent to which their contracts were presented to their partners. Items include
“the role of each party,” “what intellectual property remains with each partner,” and “the
responsibilities of each party” and are anchored on a seven-point Likert scale. Flexibility and
mutuality are two governance attributes borrowed from Heide and John (1992). Items to capture
55
flexibility include “make changes when necessary,” “make adjustments in the ongoing
relationship,” “apply rules and policies loosely,” and “grant exceptions to meet special requests.”
Items for mutuality include “work together to be successful,” “access information each of us
need,” and “create mutual benefits.” All items are anchored on a seven-point Likert scale.
Outcome Variable
This research views new product success as the focal outcome variable. The measure
was adapted from Sivadas and Dwyer (2000) and Song, Sounder, and Dyer (1997). Sample
items include “the overall performance of this new product alliance program has met our
objectives” and “from an overall profitability standpoint, our new product alliance development
program has been successful. Again, the items are anchored on a seven-point Likert scale.
Control Variables
The primary focus of this research is to examine the impact of risk perceptions on the use
of governance attributes and how different nature of these governance attributes influence new
product alliance outcomes. As a result, two variables were included to control for individual
firm differences that might have effects on the proposed relationships.
Relationship age corresponds to the length of business relationships between the focal
firm and its partner. Past studies demonstrate that relationship age influences interfirm
cooperation (Morgan and Hunt 1994; Smith and Barclay 1997). To assess the relationship age,
respondents were asked to specify the number of business experience with their partner firm.
Alliance experience relates to the past experience or history of a firm involving in other
alliance activities. Extant research suggests that past experience has a strong effect on risk
56
perceptions (Sitkin and Weingart 1995). To my best knowledge, alliance experience has never
been studied. However, its effect on the relationship between risk perceptions and governance
attributes is likely. To assess alliance experience, five new items anchored on a seven-point
Likert scale were developed. They include: “our company has been involved in other alliances,”
“we are experienced in managing alliance partners,” “we are familiar with the practice of
forming alliances,” “this is our first time working with other firms to develop new products,” and
“we are very new at figuring out how alliances work.”
SAMPLE FRAME AND PROCEDURES
The sample frame for this research is firms that have recently participated in new product
development alliance activities. Firms in electronic industries such as semiconductors, software,
telecommunications, and medical equipments are included (Mohr 2001). As a sampling base, all
firms that had been involved in any form of alliance activities and such activities were publicized
(e.g., Wall Street Journal, Business Week) between 1999 and 2003 were included. A total of
1,252 firms were identified. Figure 5 outlines the sampling procedures.
57
FIGURE 5
Respondent Identification Procedures and Results
Prescreen and qualify informants through
telephone Qualified Respondents = 404 firms
Pilot (N=50)
Main – 1st Wave(N = 252)
Main – 2nd Wave(N = 102)a
Identify firms that have NPAs and their addresses
N = 801 firms
Identify publicized alliance activities from secondary sources N = 1,252 firms
Note: a Only mailing addresses were verified
58
As shown in Figure 5, identifying key informants involves the following three steps.
Step 1: Identifying firms that had alliance activities between 1999 and 2003
This step involves an extensive review of secondary sources listed on ProQuest
database. 1,252 firms were found to have alliance activities between 1999 and 2003. These
firms could be involved in various sorts of alliance activities not limited to new product
development. In other words, not all alliance activities involved in this stage had new product
alliances.
Step 2: Identifying company contact information
This step is to go to the website of each of the companies identified in Step 2 and to
obtain their telephone numbers and mailing addresses. 801 firms out of 1,252 were found to
have individual company website and contact information.
Step 3: Prescreening and qualifying key informants
This study is primarily interested in new product alliances. With this objective in mind,
only firms that had new product development activities with other companies would be selected.
In this stage, two research assistants were involved in qualifying and prescreening key
informants. Prescreening was conducted in early February through early March. As mentioned
before, not all firms that had alliance activities between 1999 and 2003 dealt with new product
development. Thus, the purpose of prescreening is to identify firms that have new product
alliances. In addition to it, precontacting each key informant by telephone can (1) assess the key
informant’s ability to serve as a key informant by asking if he or she was knowledgeable about
the alliance in question, (2) obtain cooperation, and (3) verify his/her mailing address. The
procedures of prescreening and qualifying gave this study 302 firms that met the above three
59
criteria and 102 firms which met the third criterion only. Key informants were mostly holding
key positions such as chief executive office, president or vice president of engineering or
marketing.
PILOT STUDY
Sample and Procedures
Thirty-four firms were randomly selected from the sampling frame and a list of 16 firms
was provided by the College of Engineering and Architecture at Washington State University.
The College of Engineering and Architecture has an extensive connection with companies in
high-tech industries and places students regularly in those companies. Consequently, a total of
50 firms were included in the pilot study. The purpose of conducting the pilot study is to
examine the validity and reliability of each of the measures employed in the questionnaire and to
assess the nomological net.
A packet of survey materials was sent to each key informant. As detailed by Campbell
(1955), the key informant approach enables researchers to obtain information about a firm by
collecting data from selected people within that organization who are highly knowledgeable
about the phenomena under study. This approach has been used by many other researchers in a
similar type of research (e.g., Lusch and Brown 1996; Morgan and Hunt 1994; Rindfleisch and
Moorman 2001). A senior executive (e.g., vice president, chief officer) in the area of
engineering, research and development, new product development, marketing, and/or operations
is appropriate for this study. Respondents were asked to identify the most recent partner firm
with whom they have jointly developed a new product(s). Questions focus on the attributes they
60
used in contracting with their partners, their risk perceptions of the partners, the organizational
distance from their partners, and new product outcomes.
Prenotification letters were sent on February 11. A week after sending the prenotification
letters, each informant was mailed a packet including a cover letter, a survey, and a postage-paid
reply envelope. A sample of the prenotification letter and cover letter can be found in Appendix
B.
All survey packets were serialized for tracking purposes. There are two reasons to
include a tracking number on each of the survey packets: (1) perspective respondents who have
not responded to the initial mailing can be identified and (2) responses from key informants can
be verified through secondary data resulting in attenuating common method variances found in
many firm-level research. The tracking number was printed on a return-mailing label. Given
that all packets were serialized, informants who did not reply within two weeks could be
identified and were mailed a second set of survey materials (Dillman 1978). This time, a
handwritten Post-it Note and a one-dollar financial incentive were attached on to a cover letter.
The handwritten note is a plea to request that informants to help me with my dissertation.
As a result, four firms replied that they were not appropriate to participate in the survey at
that point in time mainly because their alliance activities were still on going and two firms did
not have time for this research. This left an effective sampling frame of 44 firms. Ten responses
were received from the first mailing and 16 from the follow-up mailing. In total, twenty-six
firms were returned with complete information, for a 59% response rate for the pilot study.
61
Measure Purification and Construct Validation
The pilot sample responses were used to purify measures and provide evidence of the
validity and reliability of both the new and adapted scale items. Following Churchill’s (1979)
recommendations, all measures were purified using the data collected from the pilot study.
Exploratory factor analysis is useful at the earliest stage to assess the validity in particular of new
measures (Anderson and Gerbing 1988; Nunnally 1978). Any items in a construct having a cross
factor loading above .4 would be removed. In other words, if an item with high factor loadings
across factors, the unidimensionality of a construct would be a concern (Churchill 1979).
After purification, all the scales were examined for internal consistency and
unidimensionality. To maintain the unidimensionality of a construct, a clean factor structure is
expected to obtain from exploratory factor analyses. As a result, any items that had a loading
below .4 were removed. Table 4 shows the factor loadings and the reliability of each construct
after eliminating items with low factor loadings. Measures of explicitness, flexibility, and
mutuality were developed on the basis of Lusch and Brown’s (1996) study and all of them
perform reasonably well. Factor loadings of explicitness range from .76 to .94. Both flexibility
and mutuality measures also perform as expected with factor loadings range from .56 to .73 and
.66 to .89 respectively. The measure of new product success was drawn from both Sivadas and
Dwyer’s (2000) and Song, Sounder, and Dyer’s (1997) work. The reliability of this scale is as
high as .89 and the factor loadings are above .6.
Wherever possible, existing measures are used for this study. However, as the scales for
perceived risk types (i.e., performance risk, implementation risk, knowledge leaking risk,
relational risk, and reputation risk) and organizational distance are new and do not have
62
precedence in the literature, these new scales may not perform as well as expected. Six items
were included in the original scale of perceived performance risk. Two of them had factor
loadings less than the acceptable cut-off point of .4 and were removed. After eliminating the two
items, the remaining four items loaded nicely together and the reliability is above .83 which is
higher than the acceptable level of .6 for a new scale (Vogt 1999). Similar to performance risk,
two items out of seven on the implementation risk scale were removed due to their low factor
loadings. The remaining five items loaded reasonably well. Two items of knowledge leaking
risk scale were dropped due to low factor loadings. The remaining items have factor loadings
between .84 and .97. With respect to relational risk, the factor loadings range from .59 to .92
after three items out of seven were dropped. Reputation risk was the most problematic scale.
Only three items out of seven were retained. Although the factor loading of the first item is as
low as .31, I decided to keep it on the scale following Bagozzi and Yi’s (1988) recommendation
of 3 to 5 items.
The scales were modified after all constructs except for perceived reputation risk showed
reliabilities over the minimum recommended level, .7. Perceived reputation risk is a new
measure and the reliability is .62 after four items were removed. Original items are provided in
Appendix C.
63
TABLE 4
Item Factor Loadings and Reliability Analysesa
Construct Items Factor Loading Reliability (Alpha) Explicitness EX1
EX3 EX4
.76
.94
.84
.88
Flexibility FLEX1 FLEX2 FLEX4
.56
.66
.73
.78
Mutuality MUTUAL1 MUTUAL2 MUTUAL3
.66
.87
.89
.83
Organizational Distance DIST1 DIST2 DIST3 DIST4 DIST5
.72
.63
.89
.75
.56
.84
Perceived Performance Risk PERF_R3 PERF_R4 PERF_R5 PERF_R6
.61
.81
.91
.70
.83
Perceived Implementation Risk IMP_R3 IMP_R4 IMP_R5 IMP_R6 IMP_R7
.46
.59
.50
.57
.69
.88
Perceived Knowledge Leaking Risk KNOW_R1 KNOW_R2 KNOW_R3 KNOW_R4
.85
.84
.87
.97
.93
Perceived Relational Risk REL_R1 REL_R3 REL_R4 REL_R7
.59
.92
.87
.64
.84
Perceived Reputation Risk REPU_R1 REPU_R5 REPU_R7
.31
.92
.85
.62
New Product Success NPS1 NPS2 NPS4 NPS5
.66
.90
.75
.93
.89
an = 26
64
Nomological Net and Discriminant Validity
Nomological net involves demonstrating that the pattern of correlations with other
measures of other constructs adheres to theoretical expectations. Table 5 shows the correlation
matrix for all the focal measures used in this study. The correlations between the constructs
provide a strong support for the specified nomological network, thereby establishing
nomological validity of the constructs. In addition, examining the correlation matrix can also
assess the constructs’ discriminant validity. Zero order correlations between variables indicate a
high level of discriminant validity. However, as shown in Table 5, the correlations among
perceived risk types can be as high as .53. Discriminant validity may be a concern among some
of the perceived risk types. Similarly, the correlation between flexibility and mutuality reaches
.57. Such high correlation is not unexpected. As Gundlach and his colleagues (1995) comment
on the literature of social contracting, flexibility and mutuality are two components which are
closely related to each other.
65
TABLE 5
Correlation Matrix of Variables after Purification 1 2 3 4 5 6 7 8 9 10 1. Explicitness 1.00 2. Flexibility .22 1.00 3. Mutuality .39* .57** 1.00 4. Performance Risk .33 .30 .30 1.00
5. Implementation Risk .05 -.08 .07 .53** 1.00
6. Knowledge Leaking Risk .03 -.21 -.28 -.35 .02 1.00
7. Relational Risk -.08 -.22 -.20 -.04 .51** .43* 1.00 8. Reputation Risk .01 .19 -.25 .24 .12 .12 .11 1.00 9. Organizational Distance .33 -.16 .19 .04 .13 .53** .20 -.01 1.00
10. New Product Success .19 .48* .70** .27 -.06 -.33 -.35 -.48* .06 1.00
Mean 5.38 4.98 5.69 4.61 4.46 3.41 3.57 2.85 3.99 5.35 Standard Deviation 1.13 1.04 1.08 1.46 1.24 1.81 1.35 1.03 1.26 1.22
n=26 *correlation is significant at the .05 level. ** correlation is significant at the .01 level.
MAIN STUDY
The main study consisted of two waves. For the first wave, 252 packets of survey
materials were sent on March 10. Unlike the pilot study where a prenotification letter was sent
to each individual firm, no prenotification letters were sent to the respondents of the main study.
The major reason is that respondents were precontacted through telephone and were notified that
they would receive a survey packet shortly. So, the prenotification step was unnecessary.
Similar to the pilot study, a packet including a cover letter, a postage return envelope, and
the survey, was sent to each firm. A sample of cover letter and the survey instrument can be
66
found in Appendix D. In addition, a handwritten plea was attached on the cover to ask
informants to help with this research. Also, as an incentive to participate, informants were told
that they would be provided with an executive summary report of the research findings.
Out of 252 firms, 10 replied that they neither had NPAs nor enough knowledge to
participate in this study. Data from thirty-three firms were received. Three of which were not
completed. Thus, the effective response rate for the major survey was 12.6% (=30/239). Given
that the effective response rate for the pilot study was 59.1%, the effective response rate for the
first wave of the main study was far below my expectation.
Two approaches were adopted in an attempt to increase the response rate and the total
number of responses. First, a follow-up survey was mailed on April 2. Following Dillman’s
(1978) recommendations, a follow-up letter with a questionnaire was sent to the respondents as a
reminder three weeks after the initial mailing. A one-dollar-incentive together with a hand-
written plea for help with this research was attached onto a cover letter. Four were returned
indicating that they did not have NPAs. Thirty-four completed questionnaires were received.
Together with the 30 usable responses received from the initial mailing, the effective response
rate for the first wave of the main study was 27%.
Second, as described previously, an additional 102 firms were identified to have NPAs.
However, the research assistants were not able to contact the key informants in person after
calling three times in different time periods. Despite the fact that no consent was received from
this list of respondents, a packet including a cover letter, a postage return envelope, and the
survey was sent to each firm. It was believed that these firms had new product alliance activities
and were therefore eligible for this study. Four were returned because of incorrect addresses.
Another three indicated that they did not have enough knowledge. A total of twelve completed
67
survey was received. Similar to the first wave of the main study, a follow-up survey was
conducted. Again, following Dillman’s (1978) recommendations, a follow-up letter with a
questionnaire was sent to the respondents as a reminder two weeks after the initial mailing. This
time, in addition to a hand-written plea for help with this research, a one-dollar-incentive was
attached onto a cover letter. Five usable questionnaires were received. In total, 17 completed
questionnaires were received from the second wave, giving a 17.9% response rate. Given that no
commitment was obtained from the respondents of this wave, the response rate was comparable
to other recent studies to this population (e.g., Isobe et al. 2000). The study was terminated on
April 22. A total of 107 usable questionnaires were received, for a 28.5% response rate. Table 6
summarizes the response rates for both the pilot and the main studies.
TABLE 6
Sampling Frames and Response Rates
Study Sampling Frame Effective Sampling Frame
Usable Responses
Effective Response Rate
Pilot (Initial) 50 44 10
Pilot (Follow-up) 34 33 16 59.1%
Main – 1st Wave (Initial) 252 239 30
Main – 1st Wave (Follow-up) 209 205 34
27%
Main – 2nd Wave (Initial) 102 95 12
Main – 2nd Wave (Follow-up) 83 83 5
17.9%
Total 404 376 107 28.5%
68
RESPONSE BIAS AND VALIDITY CHECKS
Following Armstrong and Overton’s (1977) recommendations, potential nonresponse
bias was assessed through a series of t-tests to compare early with late respondents in terms of all
key constructs. In this study, responses from the initial mailing were used to compare with the
responses received from the follow-up mailing. A series of t-test on key constructs were
performed. The results in Table 7 suggest that there is no significant difference between early
and late respondents in terms of key variables.
TABLE 7
Comparison of Early Respondents to Late Respondents
Construct t-value Significance Level
Perceived Performance Risk 1.38 .17
Perceived Implementation Risk 1.50 .14
Perceived Knowledge Leaking Risk .99 .34
Perceived Relational Risk .34 .73
Perceived Reputation Risk 1.57 .12
Explicitness .04 .97
Flexibility 1.53 .13
Mutuality 1.62 .11
New Product Success .93 .36
In addition, potential nonresponse bias was assessed by comparing nonresponding firms
with responding firms in terms of their demographics. Since a majority of the firms in this study
69
are the members of the American Electronics Association (AeA), their demographic information
such as annual sales, number of employees, and years of establishment can be found on the AeA
website (www.aea.org). If not available, other means such as individual company websites were
used to identify the required information. The results illustrated in Table 8 further suggest that
there is no significant difference between respondent firms and non-respondent firms in terms of
their age, revenues, and number of employees. This provides evidence that the responding firms
were comparable to the sample, and any findings in this study had sufficient external validity to
be generalizable across firms within the same high-tech industries.
TABLE 8
Comparison of Respondents to Non-Respondents
Indicator t-value Significance Level
Age .94 .32
Sales .56 .61
Number of Employees .44 .59
Responses obtained from the pilot study were compared to responses from the main
study. As demonstrated in Table 9, results indicate that there is no significant difference these
two groups of responses in terms of the key constructs. Data were therefore combined to test the
hypotheses.
70
TABLE 9
Comparison of Pilot to Main Responses
Construct t-value Significance Level
Perceived Performance Risk .11 .92
Perceived Implementation Risk .3 .76
Perceived Knowledge Leaking Risk .46 .65
Perceived Relational Risk .01 .99
Perceived Reputation Risk .77 .44
Explicitness 1.08 .28
Flexibility .36 .72
Mutuality 1.18 .24
New Product Success .21 .83
Validity Check
As a validity check, respondents were asked to provide their information regarding their
positions, the number of years they had worked for their firm, and their level of involvement and
influence in alliance activities. Results suggest that respondents had worked for their company
for an average of 9 years. About 90% respondents were presidents, vice presidents, or senior
executives who were highly involved in their alliances (5.8 on a seven-point scale) and did have
significant influence on new product development alliances (5.9 on a seven-point scale). The
findings provide evidence that the sampling approach was successful in identifying key
informants.
71
SUMMARY
In this chapter, a comprehensive discussion of research method was provided.
Specifically, it detailed the measurement development and the sampling procedures. The next
chapter presents the results of this research including the respondent characteristics and
hypothesis testing results.
72
CHAPTER FOUR
DATA ANALYSIS AND RESULTS
A nice adaptation of conditions will make almost any hypothesis agree with the phenomena. This will please the imagination but does not advance our knowledge.
J. Black 1803, p. 193.
Chapter 4 presents the analyses of the survey data and the results of hypothesis testing.
This chapter is organized into three major sections. The first section presents respondent
characteristics and the patterns of alliance activities. The second section relates to measure
validation. The final section presents the hypothesis testing procedures and the results.
RESPONDENT CHARACTERISTICS AND DESCRIPTIVE STATISTICS
From the responses received, respondents represented four industries including
computers and office equipments, semiconductors, software, and medical devices with a range in
size by revenues of $300 thousand to $60 billion and size by number of employees ranged from
5 to 30,000. All respondents in the sample were high-tech firms and informants for each firm
were at the senior vice president level or higher with the majority holding the chief executive
position (90% of total respondents). These respondents have been employed at their firms
approximately 9 years on average (Table 10).
73
TABLE 10
Characteristics of Firms and Key Informants
Respondent/Firm Characteristics Minimum Maximum Mean
Respondent’s Length of Employment with Firm (years) 1 30 9
Firm Age (years) 1 87 25
Firm Size (number of employees) 5 30,000 124
Alliance Patterns
Seventy percent of the firms have alliance partners located in the US. About 30% of
firms, however, have international alliance partners in Canada, Germany, India, China, or Japan,
among others. It is not surprising as forming alliances across borders increased dramatically in
the last two decades (Johansson 1995).
Among 107 firms, 70 of them have partners, be they suppliers or customers, in the same
industry. As illustrated in Table 11, forming alliances with competitors in the same industry is
uncommon. Only four firms said that they partnered with their competitors to produce new
products. An interesting observation found in here is that 12 responding firms had an alliance
partner with multiple identities, i.e., supplier, customer, and/or competitor.
74
TABLE 11
Composition of Partner Firms
Different Industry
Same Industry
Competitor 0 4
Customer 15 20
Supplier 18 32
Multiple Forms 2 10
Others (e.g., industry friends, L-T joint ventures) 2 4
Total 37 70
Table 12 summarizes the characteristics of partner firms. The average size of partner
firms by number of employees was 7,277 (range from 2 to 100,000) and by sales was $13 billion
(range from 1 to 500,000 million). In general, the partner firms had been in business for 22.5
years (range from 1 to 137 years) and the responding firms had been involved doing business
with their partner firms for an average of 5.3 years (range from 1 to 40).
75
TABLE 12
Characteristics of Partner Firms
Characteristics Minimum Maximum Mean
Firm Age (years) 1 137 22.5
Firm Size (sales in million) 1 500,000 12,655
Firm Size (no. of employees) 2 100,000 7,277
Length of Relationship (years) 1 40 5.29
MEASURE VALIDATION
On the basis of the results from the pilot study, measures were modified (results can be
found in Chapter 3). Here, as recommended by Churchill (1979) and Gerbing and Anderson
(1988), unidimensionality and discriminant validity were both examined by means of a series of
confirmatory factor analysis models using LISREL 8 (Jöreskog and Sörbom 1993). Given that
the sample size of this study is small (n=107), relevant constructs were split into subsets of
theoretically related variables in order not to violate recommended minimal sample size to
parameter estimate ratios (Bentler and Chou 1988). Splitting relevant constructs into subsets of
variables allows me to test for construct convergence within maximally similar sets of variables
and have been used in past research (e.g., Grewal and Tansuhaj 2001; Moorman and Miner
1997).
In the following, I will lay out the measure validation procedure.
76
Domain Examination
All the key constructs in this study are of multiple items. For the multi-item scales, each
set of items was initially subjected to an examination of item-to-total correlations to identify
items that did not belong to the specific domain. None of the items was found to be a concern.
High-Order Factor Examination
In most cases, constructing high-order factors must be guided by theories. However,
there exist certain situations when no empirical work has been done in the same area. In this
research, both performance risk and implementation risk have never been studied in the past.
Although my field interviews suggested that performance risk was different from
implementation risk in that the latter focused on implementation processes while the former
emphasized outcomes, an examination of their correlation suggests that they are correlated at .91,
which indicates that the two variables are highly correlated with each other. Such high
correlation indicates that a second-order factor may exist. Conceptually, these two variables
should be correlated since implementation processes should influence performance outcomes.
Thus, to examine whether a single second-order factor is superior than a two first-order factors, I
followed the procedures which have been used in extant research (e.g., Heide and John 1992).
The proposed factor structure and its parameter estimates can be found in Table 13. The
fit indices for the model indicate a satisfactory fit to the data (χ2 (64) = 156.77, p = .00, GFI =
.88, RMSR = .08, Bentler and Bonnett’s index ∆ = .82, Bentler’s comparative fit index = .84).
Although Bentler and Bonnett’s index does not exceed the ideal point of .90 and Bentler’s
comparative fit index is also below .90, the relevant first- and second-order factor loadings are
large and statistically significant (Table 13). In particular, the factor loadings of the two first-
order factors, performance risk and implementation risk, are .96 and .93 respectively.
77
TABLE 13
First-Order and Second-Order Loadings of Performance Risk and Implementation Risk
First-Order Loadingsa
Indicator Performance Risk (PER) Implementation Risk (IMP)
PERF_R3 .52
PERF_R4 .82
PERF_R5 .85
PERF_R6 .91
IMPL_R3 .71
IMPL_R4 .80
IMPL_R5 .71
IMPL_R6 .66
IMPL_R7 .80
Second-Order Loadingsa
First-Order Factor Default Risk (DEFAULT)
PER .96
IMP .93 aAll factor loadings are significant at p < .05
Given the high factor loadings, the assertion that a second-order factor structure underlies
the factors of performance and implementation risk was supported. Further, for the sake of
simplicity, both performance risk and implementation risk were combined into an equally
78
weighted composite score representing the high order factor of default risk for the hypothesis
tests.
The constructs of mutuality and flexibility were examined for two reasons. First,
theoretically speaking, mutuality and flexibility have been proposed to underline different
conceptual meanings (Macneil 1980). Macneil (1978) has made a very compelling argument
suggesting that mutuality corresponds to the mutual understanding between partners while
flexibility implies how a firm adapts to environmental changes. Empirically speaking, however,
some researchers argue that mutuality and flexibility are essentially two similar factors
underlying the notion of relational norms (Heide and John 1992), normative (soft) contracts
(Lusch and Brown 1996), interfirm coordination (Dahlstrom and Nygaard 1999), and
cooperative norms (Cannon and Perreault 1999). Given that past studies have proposed a
second-order factor structure, an effort was made to examine whether mutuality and flexibility
comprise a high-order factor.
The proposed factor structure and its parameter estimates can be found in Table 14. The
fit indices for the model indicates a satisfactory fit to the data (χ2 (3) = 8.8, p = .00, GFI = .85,
RMSR = .08, Bentler and Bonnett’s index ∆ = .80, Bentler’s comparative fit index = .81).
Although Bentler and Bonnett’s index does not exceed the ideal point of .90 and Bentler’s
comparative fit index is also below .90, the relevant first- and second-order factor loadings are
large and statistically significant (Table 14). In particular, the factor loadings of the two first-
order factors, flexibility and mutuality, are .71 and .75 respectively.
79
TABLE 14
First-Order and Second-Order Loadings of Flexibility and Mutuality
First-Order Loadingsa
Indicator Flexibility (FLEX) Mutuality (MUT)
FLEX1 .78
FLEX2 .80
FLEX4 .58
MUTUAL1 .73
MUTUAL2 .74
MUTUAL3 .79
Second-Order Loadingsa
First-Order Factor Default Risk (DEFAULT)
FLEX .71
MUT .75
aAll factor loadings are significant at p < .05
Given the high factor loadings, the assertion that a second-order factor structure underlies
the notion of flexibility and mutuality was supported. It should be noted that despite the fact that
Macneil’s (1980) argument is theoretically compelling, the assessment of high-order constructs
appears in Table 14 is consistent to past empirical studies (e.g., Heide and John 1992). As a
result, for the sake of simplicity, both flexibility and mutuality were combined into an equally
weighted composite score representing relational attributes for the hypothesis tests.
80
Confirmatory Factor Analyses
After constructing the two high-order constructs, confirmatory factor analyses as
suggested by Gerbing and Anderson (1988) were used to assess the convergent and discriminant
validity for three measurement models: (1) perceived risk types including default risk (i.e.,
performance risk and implementation risk), knowledge leaking risk, relational risk, and
reputationrisk, (2) governance attributes including explicitness and relational components (i.e.,
mutuality and flexibility), (3) new product success, organizational distance, and alliance
experience.
Table 15 shows the results from confirmatory factor analysis models. Results indicate
that a reasonably good fit for each measurement model. All factor loadings are greater than the
.4 cutoff (Nunnally and Bernstein 1994) and are statistically significant.
TABLE 15
Results from Confirmatory Factor Analysis Models
Measurement Model
Range of Standardized
Factor Loadings
NNFI CFI RMSEA χ2 (d.f., p-value)
1. Governance Attributes .76 - .89 .81 .86 .11 81.54 (26, p = .12)
2. Risk Types .49 - .94 .86 .88 .09 294.71 (146, p = .00)
3. New Product Success, Organizational Distance, Alliance Experience
.43 - .95 .87 .89 .09 172.72 (74, p = .00)
81
With respect to discriminant validity, two approaches are commonly used to assess it
(Anderson and Gerbing 1988). The first approach is to examine the 95% confidence intervals (+
or –1.96 standard errors) around all possible pairwise factor correlations. The phi coefficient (Φ)
plus and minus the standard error of Φ should not include 1 to establish discriminant validity
between any two variables. The second approach is to conduct a series of two-factor
confirmatory factor analysis models for each of all possible pairs of constructs. Specifically, the
phi coefficient (Φ) is constrained to unity for the first model of each pair of constructs and in the
second model, the (Φ) is freed. A chi-square test is then performed to compare the first model to
the second model. If the second model is found to be superior, it then provides an evidence of
discriminant validity. In this research, the former approach was adopted. As Bentler and Chou
(Bentler and Chou 1988) suggest, the assessment of discriminant validity based on an inspection
of confidence intervals is entirely complementary to the latter approach. The matrix described in
Tables 16a – 16c show that none of the confidence intervals encompasses +/-1 suggesting that
discriminant validity is established.
82
TABLE 16a
Confidence Intervals, Average Construct Variance Extracted, and Construct Reliability –
Risk Types
Confidence Intervals
1 2 3
Average Variance Extracted
Construct Reliability
1. Default Risk .54 .91
2. Knowledge Leaking Risk
-.05 – -.03 .68 .89
3. Relational Risk .31 – .33 .43 – .45 .59 .84
4. Reputation Risk .11 – .13 .51 – .53 .34 – .36 .68 .81
TABLE 16b
Confidence Intervals, Average Construct Variance Extracted, and Construct Reliability –
Governance Attributes
Confidence Intervals
2
Average Variance Extracted
Construct Reliability
1. Explicitness .26 – .28 .71 .88
2. Relational Attributes .43 .82
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TABLE 16c
Confidence Intervals, Average Construct Variance Extracted, and Construct Reliability –
New Product Success, Organizational Distance, Alliance Experiences
Confidence Intervals
1 2
Average Variance Extracted
Construct Reliabilities
1. New Product Success .66 .89
2. Alliance Experiences .17 – .19 .78 .95
3. Organizational Distance -.09 – -.11 -.13 – -.11 .36 .73
Reliability
Reliability is the correlation between a measure and itself. If the correlation is high, then
most of the variance in a measure would be thought to be systematic (Nunnally 1978). Hence,
reliability indicates the degree to which measures are free from random error.
Coefficient alpha is the basic statistic used to determine the reliability of a measure based
on internal consistency. Coefficient alpha, however, does not adequately estimate errors caused
by factors external to an instrument such as differences in testing situations and respondents over
time. In this research, two indicators, average variance extracted and construct reliability, were
used to assess reliability (Bagozzi and Yi 1988). The average variance extracted indicates the
reliability of a set of measures of a latent variable and the values greater than .5 are considered
adequate (Bagozzi and Yi 1988). Tables 16a-c suggest that except for relational attributes and
organizational distance, the measures of average variance extracted suggested satisfactory
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reliabilities. Construct reliability further supports that the measures are internally consistent.
None of the measures has reliability below .7 (Bagozzi and Yi 1988).
HYPOTHESIS TESTING AND RESULTS
Before testing hypotheses, the construct scales were formed by summing and averaging
the resultant values for all items in a scale. All scales had multiple indicators with a minimum of
three items per scale. Using multi-item scales can make relatively fine distinctions among
respondents and specificity of items can be averaged out with an increase in reliability as the
measurement error is reduced. In other words, several items were combined for the purpose of
averaging out random errors in this study (Nunnally 1978). Table 17 provides the correlation
matrix and summary statistics.
TABLE 17
Correlation Matrix and Summary Statistics
1 2 3 4 5 6 7 8
1. EXPLICIT 1.00
2. REL_ATT .26* 1.00
3. DEFAULT .10 .10 1.00
4. KNOWRISK .03 .05 -.04 1.00
5. RELRISK -.014 -.05 .33* .42* 1.00
6. REPRISK .12 .12 .15 .33* .24* 1.00
7. DIST .01 -.12 -.03 .02 .11 -.04 1.00
8. NPS .33* .44* -.01 -.24* -.43* -.27* -.04 1.00
Mean 5.46 5.45 4.42 3.16 3.52 2.05 4.12 5.35 Standard Deviation 1.19 .89 1.30 1.63 1.31 1.23 1.11 1.02
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Hierarchical regression analyses were employed to test the first two components of the
model, i.e., (1) the direct effects of risk perception on governance attributes and (2) the
moderating effect of organizational distance as shown in Figure 6. Interaction terms between the
measure of organizational distance and each of the perceived risk types were generated. Before
creating interaction terms, all variables were mean-centered to avoid the problem of
multicollinearity (Aiken and West 1991; Mason and Perreault 1991). The first model, i.e., the
restricted model, includes control variables only. The second model includes both control
variables and the hypothesized direct effects of perceived risk types. The final model is a full
model encompassing all variables in the second model and the interaction terms.
FIGURE 6
Revised Model (Main Effects and Moderating Effects)
Contract Explicitness
Relational Attributes (Mutuality and
Flexibility
H6
Organizational Distance
H1-H5
Governance Attributes
Reputation Risk – H5
Relational Risk – H4
Knowledge Leaking Risk – H3
Default Risk (Performance and Implementation Risk) – H1-H2
Perceived Risk Types
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Table 18 shows the results of the hierarchical regression models used to test Hypotheses
1-6. Specifically, Model 1 includes two control variables, alliance experiences and years of
business relationship with partner firms. Alliance experience (ALLYEX) was expected to have
direct positive effects on levels of explicitness was supported (b=.19, p<.01). Number of
relationship years (R_AGE) was also proposed to have direct positive effects. Unexpectedly, the
results indicate a negative relationship between the number of relationship years and explicitness
(b=.-.04, p<.05). Similarly, both alliance experience and relationship age were expected to have
positive effects on relational attributes. None of the assertion was supported.
In Model 2, all main effects were included in the hierarchical regression analysis. The R-
square changed significantly (∆R2 = .10, p<.05) indicating the existence of main effects on
explicitness. However, the R-square did not have a significant change (∆R2 = .04, p>.1) with
respect to the main effect of risk types on relational attributes. The following sections detail the
main effect hypothesis testing results.
Hypotheses 1 and 2
H1a and H2a proposed that there is a positive relationship between perceived default risk
(i.e., performance risk and implementation risk) (DEFAULT) and explicitness (EXPLICIT). The
coefficient associated with default risk is positive and significant (b=.16, p<.05) providing
support for the hypotheses. Also, H1b and H2b suggested a positive relationship between
perceived default risk and relational attributes (i.e., flexibility and mutuality). As expected, the
results lend support to the hypotheses (b=.10, p<.1).
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Hypothesis 3
H3a suggested that perceived knowledge leaking risk (KNOWRISK) is positively related
to explicitness. No empirical support was found for this hypothesis (b=.02, p>.1). Results also
did not support H3b which proposed a positive relationship between knowledge leaking risk and
relational attributes (b=.05, p>.1).
Hypothesis 4
H4a contended that perceived relational risk (RELRISK) was negatively associated with
explicitness. The results in Table 18 lend support to this hypothesis (b=-.27, p<.01). In contrast,
findings did not provide evidence to support H4b. Perceived relational risk was found to have a
negative effect on relational attributes (b=-.10, p>.1) which was in contrast to the hypothesis.
Hypothesis 5
H5 suggested that perceived reputation risk (REPRISK) is positively related to
explicitness. This hypothesis is supported as the results indicate that the coefficient is positive
and statistically significant (b=.18, p<.05).
Hypothesis 6
To examine the second component of the model, i.e., the moderating role of
organizational distance, all variables in the second model and the interaction terms were included
in the final model. The R-square did not change significantly (∆R2 = .03, p>.10 for explicitness
and ∆R2 = .04, p>.10 for relational attributes) indicating an absence of moderating effects.
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TABLE 18
Hierarchical Regression Modelsa
Model 1 Model 2 Model 3
EXPLICIT REL_AT EXPLICIT REL_AT EXPLICIT REL_AT
Model Summary
R2 = .11*** ∆R2 = .11***
F = 6.49
R2 = .02 ∆R2 = .02 F = 1.08
R2 = .19*** ∆R2 = .10**
F = 3.67
R2 = .06 ∆R2 = .04 F = .99
R2 = .22 ∆R2 = .03 F = 2.48
R2 = .09 ∆R2 = .04 F = .96
ALLYEX .19*** .04 .21*** .02 .22*** .03
R_AGE -.04** -.02* -.04*** -.02* -.05*** -.02*
DEFAULT .16* .10* .13* .11*
KNOWRISK .02 .05 .03 .03
RELRISK -.27*** -.10 -.29*** -.08
REPRISK .18** - .18* -
DIST*DEFAULT -.01 -.01
DIST*KNOWRISK -.07 .01
DIST*RELRISK -.06 -.09
DIST*REPRISK -.12 -
Note: One-tail tests, *p < .1, **p<.05, ***p<.01. For simplicity, constant terms and organizational distance were not included in the table.
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Ordinary least square regression was used to test the final component of the model as
illustrated in Figure 7. In other words, the hypothesis of having positive relationships between
governance attributes and new product success was examined.
FIGURE 7
Revised Model (Effects of Governance Attributes on New Product Success)
H7 New Product Success
Relational Attributes (Flexibility and
Mutuality)
Contract Explicitness
Governance Attributes
Hypothesis 7
Results in Table 18 show that the positive relationship between explicitness (EXPLICIT)
and new product success (NPS) was established (b=.20, p<.01). As expected, relational
attributes (REL_AT) were also found to have direct positive effects on new product success
(b=.43, p<.01).
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TABLE 19
Regression Model Results
Independent Variable Dependent Measure: NPS
Constant 1.90***
EXPLICIT .20***
REL_AT .43***
R-Square .24***
Two-tailed tests: *p < .1, **p<.05, ***p<.01
Finally, to examine whether there exists a mediating effect of governance attributes on
the relationship between risk perceptions and new product success, I followed the procedures
established by Baron and Kenny (1986). A mediator represents the generative mechanism
through which an independent variable is able to influence a dependent variable of interest. It
speaks to how or why such effects occur. In this research, governance attributes were proposed
to mediate the effects of risk perceptions on new product success. To establish the fact that
governance attributes do play a mediating role, according to Baron and Kenny (1986), they
should have the following two properties: (1) governance attributes are correlated with both
perceived risk types and new product success and (2) the relationship between perceived risk
types and new product success approaches zero if governance attributes are held constant.
Again, following Baron and Kenny’s (1986) recommendations, three regression
equations were included: (1) regressing governance attributes on perceived risk types; (2)
regressing new product success on perceived risk types; (3) regressing new product success on
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both governance attributes and perceived risk types. Given the moderating effects of
organizational distance were not supported (Table 18), organizational distance was not included
to test mediating effects. Coefficients were compared to see if there existed any mediating
effects. Results in Table 20 show that explicitness does play a mediating role. Explicitness was
found to have mediating effects in that the beta of explicitness on equation 3 is smaller than that
on equation 2 (b = .18 < b = .20). In particular, levels of explicitness mediate the effects of (1)
default risk, (2) relational risk, and (3) reputation risk on new product success. In contrast,
relational attributes were found to have no mediating effect of risk perceptions on new product
success. Specifically, the beta of relational attributes (REL_AT) on equation 3 is greater than the
beta of REL_AT on equation 2 (b = .45 > b = .43) indicating that no mediating effects.
TABLE 20
Regression Models for Testing Mediating Effects
Equation 1 Equation 2 Equation 3
EXPLICIT REL_ATT NPS NPS
DEFAULT .16** .11* - .06
KNOWRISK .08 .07 - -.03
RELRISK -.25*** -.10* - -.25***
REPRISK .13 - - -.24***
EXPLICIT - - .20*** .18***
REL_AT - - .43*** .45*** Two-tailed tests: *p<.1, **p<.05, ***p<.01
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CHAPTER FIVE
DISCUSSION AND CONCLUSION
This dissertation provides a first step in the direction toward understanding the roles of
perceived risk, organizational distance, and governance attributes in new product alliances. A
typology of perceived risk in interfirm relationships was developed and used to investigate its
effect on the use of governance attributes in new product alliance activities. More important, the
moderating role of organizational distance has seldom been explored in the marketing literatures.
This research studied how organizational distance influenced the effect of perceived risk on
governance attributes. Further, some researchers (e.g, Lusch and Brown 1996) have called for an
attention to the impact of governance attributes on firm performance. To answer this call, the
outcome of governance attributes on new product success was examined.
In the subsequent sections, I will turn to highlight the key implications of the findings of
this study, discuss the limitations, and identify future research directions.
IMPLICATIONS
The basic conclusion that can be drawn from this study is that risk perceptions are
multidimensional and yet their impact on the use of attributes in a contract are critical.
Governance attributes were found to have significant impact on new product success and the
effect of relational attributes is even stronger than contract explicitness on new product success.
Specifically, the empirical findings presented in this support the contention that firms’
perceptions of risk influence the way they design a contract, i.e., what components should be
included in a contract per se. Default risk (performance and implementation risk) was found to
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have direct impact on the level of explicitness. The stronger the default risk, the higher is the
level of explicitness in a contract used to govern a partner firm. Relational risk, as expected, was
found to negatively influence the level of explicitness. The findings, however, do not support the
hypothesis that knowledge leaking risk is positively related to explicitness. Knowledge leaking
is a tricky question. The insignificant result may suggest that the respondent firms are able to
protect their proprietary knowledge from disclosing to their partners. Alternatively, as suggested
by Reed and DeFillipi (1990), firms may believe that their partners are unable to identify their
proprietary knowledge components as a result of causal ambiguity. As a result, contract
explicitness becomes irrelevant when a firm believes that its partner cannot acquire its
knowledge easily.
The hypotheses of direct relationships between risk types and relational attributes (i.e.,
mutuality and flexibility) were found mostly unsupported. With an exception of default risk,
none of the risk types has any influence on the use of relational attributes in a contract. The
reason may be due to the fact that relational attributes are socially embedded and the use of such
attributes relies on a social context. In this research, 70% of the respondents have domestic
partners while 30% of the respondents have international alliance partners in countries such as
Germany, France, India, Japan, China, Taiwan, and Hong Kong. Prior research suggests that
international alliances may be systematically different from domestic alliances (e.g, Gulati 1995;
Harrigan 1985; Kogut and Singh 1988). As a consequence, firms that have alliance partners in
the US vs. China, for example, may have different considerations in the use of relational
attributes.
Organizational distance has seldom been investigated in the marketing literature. In this
research, organizational distance was proposed to play a moderating role between risk
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perceptions and governance attributes. However, no moderating effect was found. Perhaps, the
conceptualization and the measures of organizational distance are as problematic as cultural
distance. Shenkar (2001, p. 520) comments that “the appeal of the CD construct is,
unfortunately, illusory. It masks serious problems in conceptualization and measurement, from
unsupported hidden assumptions to questionable methodological properties, undermining the
validity of the construct and challenging its theoretical role and application.”
Both explicitness and relational attributes were found to have positive effects on new
product success. Thus, firms can effectively manage their alliance partners if they include
explicitness and well as relational attributes in their contracts. Finally, although governance
attributes were not hypothesized to have mediating effects in this study. The conceptual model,
in fact, suggested that governance attributes are critical. An effort was made to examine such
relationship and the findings lend support to the assertion that levels of explicitness but not
relational attributes intervene the effects of perceived risk on new product success. Perhaps, the
results explain why so many alliances fail in a year. Many alliances are established with or
without formal contractual agreements. As such, having an explicit contract may be the key to
the success of alliance activities.
CONTRIBUTIONS
Theoretical Contributions To Existing Literature
The theoretical contributions lie in the examination of risk neutrality assumption in
interfirm relationships concerning new product alliances (NPA) that is embedded in transaction
cost analyses. Prior research has mostly focused on the assumptions of opportunism and
bounded rationality to predict the choice of governance structures, while overlooking the
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assumption of risk neutrality which is an important component in Williamson’s (1975)
transaction cost economics (Chiles and McMackin 1996; Rindfleisch and Heide 1997). The
notion of risk has been studied in other areas such as consumer behavior (e.g., Bauer 1967;
Campbell and Goodstein 2001) and strategy (e.g., Kohli 1989), and yet has not been empirically
examined in NPA research (for exceptions, see Kotabe and Swan 1995; Rindfleisch and
Moorman 2001; Robertson and Gatignon 1998; Sivadas and Dwyer 2000). This dissertation
takes the first step to empirically study the notion of risk in NPA.
Further, this research contributes to the development of risk typology in NPA which is
generalizable to other interfirm relationships. In strategy literature, the preponderance of
research on risk perceptions has focused on its broad-based definition. In this stream of research
(e.g., Forlani and Mullins 2000; Kohli 1989; Sitkin and Weingart 1995), risk perception is
viewed as a global concept involving all sorts of risk characteristics. The primary problem of
this perspective is that it overlooks specific dimensions of risk perceptions that may contribute
differently at different situations. As Kohli (1989, p. 60) noted, “the measurement of perceived
risk may have been too global to capture its moderating effect. In future studies, it may be useful
to … ask more directly about the specific nature of the uncertainty faced by the members.”
Recently, some strategy researchers have suggested an alternative perspective on risk perceptions
(e.g., Das and Teng 1996). For example, Das and Teng (1996), in concert with Kohli’s (1989)
assertion, propose that risk perceptions should consist of two dimensions, i.e., performance and
relational, and suggest that these two dimensions are interwoven with one another in strategic
alliances. I contend that risk that appears in NPA should involve more than two dimensions. On
the basis of my in-depth interviews with senior managers and my comprehensive review of
literatures (e.g., management, decision science, psychology, and consumer behavior), a set of
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risk types including default risk (performance and implementation risk), knowledge-leaking risk,
relational risk, and reputation risk is developed. It is believed that the risk typology can enhance
our understanding of risk in interfirm research.
In addition, some researchers have called for examining the impact of contracts on
performance (e.g., Lusch and Brown 1996). This research building upon previous studies on
contracting issues (e.g., Cannon et al. 2000) found that both relational attributes and explicitness
(one form of legal attributes) have strong and positive effects on new product success.
Practical Contributions
Any organizational decision must involve some kind of risk, which is likely to be
perceived by a decision-maker. Risk is a concept as important as other constructs such as
resources and capabilities. Knowing how to reduce risk can help firms create and maintain
sustainable competitive advantage (Chatterjee et al. 2003). As noted by Wang, Barney, and
Reuer (2003, p. 58), “risk management should be incorporated into the company’s strategic
planning.” Thus, it is believed that the examination of perceived risk is particularly relevant to
practitioners, academia, and researchers. My focus is on perceived risk rather than objective risk
suggested elsewhere in finance or decision science literature (for detailed discussion, see Das and
Teng 1996). Although objective risk, such as the measure of return variance and excessive
returns, provides insights on an estimation of a decision outcome, it does not explain how
decision behavior, such as evaluation of alternatives, is made (Pablo et al. 1996). I believe that
understanding risk perception is important since it dictates how managers process and interpret
information (Tyler and Steensma 1998) and thereby shape their decision-making behavior (e.g.,
Kohli 1989; Sitkin and Weingart 1995).
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In addition, this study focuses particularly on alliances, since using this form of interfirm
relationship to develop new products is increasingly popular. Alliances provides a means for a
firm to access resources they lack and also facilitate them to achieve various objectives
(Varadarajan and Jayachandran 1999). For example, Hwelett-Packard and Microsoft have
teamed up to create a new modular communications station (CRN 2002). Likewise, Nokia and
Trend Micro formed an alliance to produce a corporate e-mail security appliance (Network
World 2002). However, not all alliance activities are successful. Results indicate that about 70
percent alliances fail or terminate prematurely (c.f., Sivadas and Dwyer 2000). Such high failure
rates may be due to the fact that alliances are “inherent instability arising from uncertainty
regarding a partner’s future behavior and the absence of a high authority to ensure compliance”
(Parkhe 1993, p. 794). Such “inherent instability arising from uncertainty” is the tenet of risk
perceptions.
My emphasis on NPAs is crucial to managers because different types of risk perceptions
can arise out of concerns about knowledge sharing between partners, cultural differences, among
others. Specifically, in a NPA, partners may have to integrate their own technology to create a
product novel to the marketplace. However, as reflected in my field interviews, the alliance
firms may feel uncertain whether the technology provided by their alliance partners can perform
as expected. Further, developing new products jointly with an alliance partner involves sharing
of knowledge. In such cases firms may fear that their proprietary knowledge maybe disclosed to
their partners, who can act opportunistically. In other situations, the status of a firm’s alliance
partner may also cause risk to the firm. Nike is a case in point. Nike has been accused of
partnering with factories that employ child labors. Having alliance relationships with such
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factories will definitely hurt Nike’s brand image, especially when the factories are not well
accepted by Nike’s stakeholders resulting in social disapproval or rejection (Arminas 2001).
As a practitioner, it is therefore important to understand the nature of risk and its various
dimensions in NPAs. Risk varies, so does the use of contracts (e.g., soft vs. hard) and
governance modes (e.g., joint ventures vs. partnerships). In Nike’s case, in order to reduce the
risk in association with sweatshops, using an explicit contract may be a means to deal with such
situation. In short, a practitioner should be aware of what types of risk can arise and what means
s/he can use in order to mitigate different risk types that s/he encounters in collaborating with
other organizations and what kind of outcomes (i.e., new product success) can be expected by
using a specific combination of governance attributes.
LIMITATIONS AND FUTURE RESEARCH DIRECTIONS
Limitations
This research, similar to extant organizational research (e.g., Rindfleisch and Moorman
2001), employs a key informant approach (Campbell 1955). Although using a single informant
to represent a firm has long been debatable (Phillips 1981), it is believed that this approach is
valid and appropriate for the current research. Campbell (1955) alludes to that if a key informant
is knowledgeable about the subject in questions and is carefully identified, using a key informant
should be appropriate. In fact, results of validity checks on key informants in terms of their
levels of influence on and involvement in new product alliances and their positions and work
experience suggest that these informants “are surprisingly robust” (Griffin 1993, p. 120).
Another potential limitation of the study is that it is cross-sectional and, thus, cannot
capture the dynamic aspects of a firm’s decision process. This study only examines the direct
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effect of perceived risk on governance attributes. However, how different types of risk
perceptions arise or are structured are not considered in this study.
Further, the overall effect size in terms of variance explained by risk perceptions on
governance attributes is relatively small. Except default risk, none of the effects of risk
perceptions on relational attributes was found significant. Since this research is the first study to
develop the typology of risk perceptions in interfirm relationships and empirically test its impact
on governance attributes, it is not surprising that the hypothetical relationships are not
established. Insufficient empirical support for the hypotheses may be the primary constraint or
limitation of the study.
The final limitation goes to measurement issues. Insignificant findings may be due to the
fact that risk measures are new and yet unable to capture the domain comprehensively. Further,
risk measures are problematic and researchers have not had consensus even on the
conceptualization of and the definition of risk For example, in Kohli’s (1989) study, perceived
risk is measured by the negative outcomes and the level of importance of a decision. The
product term of negative consequences and importance of a decision reflect perceived risk.
Similarly, relational attributes were found to underline various domains in past research and the
conceptualization varies from studies to studies (e.g., Cannon, Gundlach, and Archol 2000;
Heide and John 1992; Lusch and Brown 1996). Organizational distance is another construct that
needs further examination. None of the moderating effects was found in this research. The
major reason may be due to the fact that the domain of the construct has not been captured.
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Future Research Directions
This dissertation takes an important step to develop the typology of risk perceptions in
interfirm relationships. Future research is encouraged to use the typology to investigate its
impact on other aspects in interfirm settings. For instance, risk perceptions may influence
relationship quality, entry mode decisions, partner selections, among others. One type of risk
perceptions may be more salient than others depending upon situations or research contexts. As
such, it may be interesting to explore a particular type of risk perceptions in a specific setting.
One of the significant findings of this study is that governance attributes are positively
related to new product success. Future research may follow this line to develop a list of
governance attributes and examine which attributes are critical to the success of new product
development and other performance outcomes. In addition, since the mediating role of relational
attributes was not established in this study, it may suggest that the effects of perceived risk types
on new product success may be moderated instead of mediated by relational attributes. Although
my field interviews suggested that relational attributes played a mediating role, future studies
may look into the moderating role of relational attributes on performance (Brown et al. 2000).
Finally, as Gulati (1995) suggests, international alliances are different from domestic
alliances. Future studies may make an effort to investigate into international alliance settings
which may provide results different than this research.
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APPENDICE
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APPENDIX A
Summary of Indepth Interviews
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Interview #1 Date: 2/12/2003 Time: 11:00am – 12:00 noon Location: Penn State (telephone interview) Informant: Mr. K, Senior Manager of Engineering Department The informant is a manager in a large software company on the east coast. Forming alliances to produce new products is not very common within the software industry but is very common between industries. Horizontal alliances are hardly found because new programs developed by a firm can be easily appropriated by its partners. “When we want to have the new platforms developed by other firms, the only way our company does is through acquisition. There are many small firms which are very smart. We will just buy the whole firms if we want to have their new platforms,” the senior manager said. Vertical alliances are more common in the software industry. The company works with its customers to develop a platform which is unique to them. The company normally owns the technology while its customers own the final products. The company does not have any particular concerns when working with its customers to develop new products. However, developing new products with other software firms is unlikely to happen in this company. Knowledge leaking is a real concern. Besides, small software firms may steal away customers from the company if they know which customers the company is going to sell to. Profits from selling a new platform to a customer are not much but the money from providing maintenance services to the customer is significant. That is the major reason the company does not ally with other software companies to develop new products.
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Interview #2
First telephone interview – Date: 2/12/2003 Time: 12:40pm – 1:15pm Second telephone interview – Date: 2/17/2003 Time: 11:00am – 11:20am Informant: Ms. Y, Product Development Manager The informant is a product development manager of a business equipment manufacturer in Oregon. Developing new products with alliance partners happens fairly often in this firm. Partners are difficult to identify, however. Past experiences with the company’s partners are critical. The company only chose to develop new products with other firms whom it had extensive business relationships. “We don’t have to worry about their technology. We know how well they do,” Ms. Y said.
The informant said that the contents of contracts the company had been used to manage its partners varied from one firm to another. It is difficult to say which kind of contracts is more effective. It depends upon the partners. If the partners are new to the firm, more comprehensive contracts will be employed. Meanwhile, the most important thing in a contract is to clearly define the ownership of the new product in terms of its patent, technology, and brand. There are many situations in which the firm owns a new product’s technology while its partner owns the patent.
The success of a new product really relies on a partner’s cooperation. The primary
concern of the informant in any of the alliance activities she has come across is whether a partner can implement as expected. “Formal and frequent meetings are necessary to keep control over our partner … meeting frequently is the only way to ensure success,” she concluded.
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Interview #3
Date: February 14, 2003 Time: 2:00pm – 3:00pm Location: Washington State Informant: Mr. T, President of a computer chip company The third interview is with a small computer chip company. The company has been in business since 1988. Forming alliances to product new products is fairly often in this company. Some of its alliance partners are large firms including Sony, Xerox, Konica, and HP. The company chose to ally with large firms as Mr. T believed that it was the most effective way to create a right product to the market. Depending upon the needs of its alliance partners, the company will customize solutions for them. It normally takes the company several months to develop a new chip with its alliance partner. Occasionally, the company will partner with small firms since it is more efficient and a lot easier to work with than large firms. However, it is more profitable and less risky to ally with large companies to create new products. Working with big names such as Sony can enhance the company’s self image.
Risks do exist when developing new products with other firms. When the company is looking for an alliance partner, it tries not to disclose its new technology to its prospective partners. The only thing the company does is to convince its prospective alliance partners how well the new technology can help improve their products’ speed, efficiency, and an overall performance. Also, the company will develop an algorithm which Mr. T would believe having a high market potential and then search alliance partners. A new algorithm developed by the company is always unique to the market and is under protections by patents. The company will also ask its alliance partners to sign a non-disclosure agreement (NDA) to prevent its new technology from being stolen by the partners.
The company has come across with a situation that its alliance partners had an intention
to steal its technology. Forming alliances must really have to be careful. Before the company is engaged with its partner, a comprehensive contract is needed. The typical length of a contract is 25 pages which details all possible contingencies.
Further, creating new products with other firms is a very common business practice in
this industry. However, the informant estimated that at least nine out of ten alliance relationships fail. There are two major reasons causing alliance failure. First, according to the informant, the new products developed with his partners must be the first to the market. If the new products are not the pioneer but the second to the marketplace, the company will lose its competitive advantage and there is no point to keep the alliance partners. Second, uncertainties in technological environments are a real concern. When the technology provided by a partner is no longer needed by customers, alliance relationships are dissolved.
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Interview #4
Date: 2/20/2003 Time: 10:30am – 12:15pm Location: Washington State Interviewee: Mr. C, a vice president of an investment company, a business consultant, and a chief operation officer of a manufacturing company According to the informant, alliance activities usually start when firms recognize that they need external resources and capabilities to help finance or materialize their new product ideas. Many firms are very entrepreneurial. They are innovative but they lack marketing sense. These companies can invest all their personal savings to develop a product which does not have a market. Thus, alliances are formed after a firm has gone through the following three stages: (1) recognizing it hurts, (2) having an urge to fix a problem, and (3) willing and able to buy in other firm’s resources and capabilities. Many firms do not recognize that the market is not large enough for their new product ideas. They just believe what they believed. Many of these firms are technology-based and do not have any marketing knowledge. As a result, the primary thing the company does is to educate and re-educate its prospective partners that knowing their customers’ needs and their customers’ customers’ needs is critical to the success of new products.
Building a trustful relationship with a prospective partner is important to the success of new product alliances. Without trust, a prospective partner will never share its new product ideas or technologies with the company. Many partner firms are technological-based and always afraid that their new “babies” (i.e., new ideas) will be stolen. In order to gain a trust from a prospective partner, as mentioned earlier, the prospective partner must recognize it hurts, want to fix it, and be willing and able to search help.
Matching if an alternative means to increase the chance of alliance and new product
success. Matching works out in a way similar to an arranged marriage. It means to collaborate two companies’ core competencies to develop new products. The informant will first identify two firms on the basis of his experiences with each of them and then arrange a meeting for these two firms to meet with each other. Sometimes, if the informant sees a high potential in an alliance venture, an investment will be made in it. An example given by the informant is that his firm has invested in an alliance venture which is located in Xiamen, China. It is his first project in China.
There are various concerns and uncertainties in an alliance venture. In order to overcome
those concerns, the informant said that he would design a contract that could allow him to make changes over time.
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APPENDIX B
Prenotification Letters and Cover Letter for Pilot Study
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Date: Dear:
Here in the Department of Marketing at Washington State University we are conducting a
study on New Product Development (NPD) in high tech settings. We have identified your firm as one who might be interested and willing to participate in this important study.
The goal of the study is to understand the business practices between NPD alliance
partners. At some time, a company like yours may have joined with another firm(s) to develop a new product(s). Forming alliances to create new products not only provides access to valuable resources, but also reduces costs. However, reports indicate that many alliance activities fail. Through this study, we are attempting to find out the concerns of the firms in participating into NPD alliances and how they handle those concerns. In order to get a comprehensive picture, we will contact as many firms as possible in North America that have NPD alliance activities.
A few days from now you will receive in the mail a request to fill out a brief questionnaire for an important research project. I am writing in advance because we have found many executives like to know ahead of time that they will be contacted.
We expect the findings of this research to be extremely useful to managers, and therefore we would like to make them available to you. We will provide a space in the questionnaire for you to indicate whether or not you would like to receive an executive summary of the results. In addition, should you decide to help us by completing the survey, I want to assure you of complete confidentiality. Our concern is with information aggregated over a large number of firms, not with any individual firm or manager. Neither the identity of the firms nor managers participating in the study will be disclosed in any form at any point. We will use the information in summary form only.
Thank you for your time. We very much hope that you agree with us about the potential value of this project and that you will help us with it by completing the survey. Sincerely, Jean L. Johnson Associate Professor of Marketing
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Date Dear:
Recently we contacted you by phone about our research project and that time you kindly agreed to participate. A few days ago we sent you a letter further explaining the study and letting you know that the questionnaire would soon be sent to you. As you may recall, our project involves the business practices between new product development (NDP) alliance partners. By filling out and mailing in the questionnaire included in this packet, you can help us understand how firms can make effective NPD alliances.
We expect the findings of this research to be extremely useful to managers, and therefore we would like to make them available to you. We will provide a space in the questionnaire for you to indicate whether or not you would like to receive an executive summary of the results. In addition, should you decide to help us by completing the survey, I want to assure you of complete confidentiality. Our concern is with information aggregated over a large number of firms, not with any individual firm or manager. Neither the identity of the firms nor managers participating in the study will be disclosed in any form at any point. We will use the information in summary form only.
Thank you for your time. We very much hope that you agree with us about the potential value of this project and that you will help us with it by completing the survey. We have included a postage paid return envelope for your convenience. If you think you are not in the right position to participate in our study, please forward the enclosed questionnaire to someone you think may be appropriate. If you have questions with respect to this survey, please do not hesitate to contact me at 509-335-1877 or email [email protected].
Sincerely, Jean L. Johnson Associate Professor of Marketing
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APPENDIX C
Original Items and Removed Items after Purification
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Original and Removed Items in Scales after Purification Construct/ Acronym Items
Explicitness
EX1 The role of each party
EX2* What intellectual property remains with each partner
EX3 The responsibilities of each party
EX4 How each party is to perform
Flexibility
FLEX1 Make changes when necessary
FLEX2 Make adjustments in the ongoing relationship with the partner to cope with changing circumstances
FLEX3* Apply rules and policies loosely
FLEX4 Grant exceptions to meet special requests
Performance Risk
PERF_R1* We feel uncertain whether our partner firm can contribute to our new product development.
PERF_R2* We are worried about the adequacy of technology offered by our partner firm.
PERF_R3 Our partner firm’s technology is important to the success of our new products.
PERF_R4 We are at risk if our partner firm does not perform according to requirements.
PERF_R5 We would take a big loss if our partner firm were not reliable in delivering required technology.
PERF_R6 The chance that our new products will fail in the market is high if the partner firm does not deliver required technology.
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Implementation Risk
IMP_R1* We feel uncertain whether we can effectively coordinate with our partner in developing new products.
IMP_R2* We are afraid that we cannot get our partner firm to buy into what needs to be done in developing new products.
IMP_R3 We are worried about interruptions in our new product development plans if our partner firm does not cooperate with us.
IMP_R4 We are at risk if our partner firm does not execute and implement what is required.
IMP_R5
We are afraid that there would be serious problems if
our partner firm does not follow our instructions in this
new product development project.
IMP_R6 We are not sure we can be successful in developing this new product if our partner does not implement as required.
IMP_R7 We stand to lose our competitive advantage if our partner does not execute and implement according to requirements.
Knowledge Leaking Risk
KNOW_R1 We fear that too much proprietary knowledge may be disclosed to this partner firm.
KNOW_R2 We could suffer a loss if our new product specifications and designs are released to this partner.
KNOW_R3 It is risky for our company to disclose too much proprietary product knowledge to this partner firm.
KNOW_R4 It is important to keep our new product knowledge inside the company and away from our partner.
KNOW_R5* The chance that our proprietary knowledge will be disclosed to our partner firm is high.
KNOW_R6* Our company has a lot at stake in leveraging our product knowledge to our partner firm.
KNOW_R7* We fear that we will lose our competitive advantage if our proprietary product knowledge is disclosed to our partner firm.
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Relational Risk
REL_R1 We are afraid that this partner firm is not as dedicated as they should be to make our joint new product development work.
REL_R2* Our firm is at risk if we break up with this partner firm
and have to find a new partner/ally.
REL_R3 We worry whether our partner firm has any true sense of obligation to us and our new product development project with them.
REL_R4 It is risky for us to commit totally to this partner firm when we are not sure of their commitment to us.
REL_R5* Our firm could stand to lose a lot if our partner firm is not fully committed to their relationship with us.
REL_R6 We stand to lose if our partner firm decides to be opportunistic in their relationship with us.
REL_R7 Our firm has taken a risk in trusting and committing to the relationship with this partner.
Reputation Risk
REP_R1 If our partner firm does not have a good reputation, there is some chance our reputation will suffer also.
REP_R2* Our partner’s reputation is so strong and positive, associating with them could only increase our own reputation.
REP_R3* We stand to lose if our partner does anything at all that reflects badly on our image and good name.
REP_R4* We believe it is important to develop new products with only allies that have a strong positive image with the public.
REP_R5 Ever since we began the association with this partner, we have had to worry about the damage to our reputation.
REP_R6* Our company could end up looking bad if our partner firm did something irresponsible and in some way harmful to the public.
REP_R7 It is risky for us to develop new products with this firm because it seems that their reputation with our customers is not all that good.
Organizational Distance
DIST1 Technologies
DIST2 New product strategies
DIST3 Innovativeness
DIST4 Risk taking
DIST5 New product development processes
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New Product Success
NPS1 The overall performance of this new product alliance program has met our objectives.
NPS2 From an overall profitability standpoint, our new product alliance development program has been successful.
NPS3 Compared with our major competitors, our overall new product alliance program is far more successful.
Alliance Experience
ALLYEX1 Our company has been involved in other alliances ALLYEX2 We are experienced in managing alliance partners ALLYEX3 We are familiar with the practice of forming alliances ALLYEX4 The is our first time working with other firms to develop new products
(reverse coded) ALLYEX5 We are very new at figuring out how alliances work (reverse coded) *Items removed after purification
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APPENDIX D
Cover Letters and Questionnaire for the Main Study
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Date: Dear:
We want to take this opportunity to thank you for your interest in our research study. The study, being conducted here in the Department of Marketing at Washington State University, involves New Product Development (NPD) in high tech settings. In particular, we hope to better understand the business practices between NPD alliance partners.
More and more often, companies like yours join with other firm(s) to develop new
products. Forming alliances to create new products not only provides access to valuable resources, but also reduces costs. However, reports indicate that many alliance activities fail. Through this study, we are attempting to understand the problems that firms have in NPD alliances and how they handle those problems to make the alliances more effective. To get a comprehensive picture, we are contacting firms like yours that have NPD alliance activities.
We expect the findings of this research to be extremely useful to managers, and therefore
we would like to make them available to you. We will provide a space in the questionnaire for you to indicate whether or not you would like to receive an executive summary of the results. In addition, should you decide to help us by completing the survey, we want to assure you of complete confidentiality. Our concern is with information aggregated over a large number of firms, not with any individual firm or manager. Neither the identity of any firm nor any manager participating in the study will be disclosed in any form at any point. We will use the information in summary form only.
Thank you for your time. We very much hope that you agree with us about the potential value of this project and that you will help us with it by completing the survey. We have included a postage paid return envelope for your convenience. If you think you are not in the right position to participate in our study, please forward the enclosed questionnaire to someone you think may be appropriate. If you have questions with respect to this survey, please do not hesitate to contact Dr. Jean Johnson at 509-335-1877 or email [email protected].
Sincerely, Sincerely, Jean L. Johnson, Ruby Lee, Associate Professor of Marketing Ph.D. Student
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New Product Development Alliances*
*Thank you for taking time to complete this questionnaire. We assure you of complete confidentiality on all of your responses.
World Class. Face to Face.
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SURVEY OF NEW PRODUCT DEVELOPMENT ALLIANCES
Thank you for participating in our study. This questionnaire should take about 10 minutes to complete. The information you provide will be used in summary form only. Neither the identity of the firms nor managers participating in the study will be disclosed in any form at any point. SECTION 1 – General Business Practices with New Product Development Partners/Allies At some time, your company may have joined with another firm(s) to develop a new product(s). We are interested in your business practices with your new product alliance partner. If you have more than one alliance partner, please identify one that came to your mind most recently. In which country is your partner firm located? ______________ Is your partner firm in the same industry as you are? Yes / No Is your partner firm your
1. Competitor 2. Customer 3. Supplier 4. Other; please specify _________________
Does your company have any equity in this alliance venture?
No _____ Yes _____. If yes, approximate _______ %
In dealing with this partner, your contract or agreement precisely defines (please circle your response) ……..
Your contract or agreement with the partner firm allows both of your company and your partner to (please circle your response) ……
Strongly Disagree Strongly
Agree the role of each party. 1 2 3 4 5 6 7 what intellectual property remains with each partner. 1 2 3 4 5 6 7 the responsibilities of each party. 1 2 3 4 5 6 7 how each party is to perform. 1 2 3 4 5 6 7 the legal remedies for failure to perform. 1 2 3 4 5 6 7 what will happen in the case of events occurring that were not planned. 1 2 3 4 5 6 7 how disagreements will be resolved. 1 2 3 4 5 6 7 the time of response. 1 2 3 4 5 6 7
Strongly Disagree Strongly
Agree make changes when necessary. 1 2 3 4 5 6 7 make adjustments in the ongoing relationship with the partner to cope with changing circumstances. 1 2 3 4 5 6 7
apply rules and policies loosely. 1 2 3 4 5 6 7
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Strongly Disagree Strongly
Agree grant exceptions to meet special requests. 1 2 3 4 5 6 7 work together to be successful. 1 2 3 4 5 6 7 access information each of us need. 1 2 3 4 5 6 7 create mutual benefits. 1 2 3 4 5 6 7 Please circle a number to indicate your response on each of the following statements.
Strongly Disagree Strongly
AgreeOur technology development is enhanced because we are always reworking and reviewing specifications with our partner firm. 1 2 3 4 5 6 7
Working with this partner firm enhances our capacity to learn. 1 2 3 4 5 6 7
We are able to deploy the skills and knowledge that we learn from this partner firm in developing new products. 1 2 3 4 5 6 7
Through the association with this partner/ally, we learn better ways to develop new products. 1 2 3 4 5 6 7
In the process of this joint product development, we have absorbed significant amounts of knowledge from our partner. 1 2 3 4 5 6 7
Our ability to advance and upgrade our technologies has greatly increased because of what we have learned in this joint new product development. 1 2 3 4 5 6 7
We look for ways to internalize and retain skills and capabilities from our partners. 1 2 3 4 5 6 7
We actively engage with our partner in order to understand and assimilate the knowledge to develop new products. 1 2 3 4 5 6 7
The joint new product activities improved as we learned with our partner in the product development process. 1 2 3 4 5 6 7
Together, we and our partner firm have made huge strides in our understanding of the technologies involved in this new product. 1 2 3 4 5 6 7
Please use the following scale and write down your response on the space provided.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree
Our relationship with this partner is a big factor in achieving our strategic objectives. Our firm’s long-term product development strategy depends on maintaining a good, healthy
relationship with this partner. A strong cooperative relationship must be maintained between our company and the ally for
us to remain competitive in our industry. When developing our firm’s new product development strategy, we depend on the
participation of our partner/ally. We do not think about our own firm’s long-term strategy when we make plans with our
partner. If our partner went out of business, our firm would immediately have to change our
competitive strategy.
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To what extent is your company different from or similar to your partner on the following? Please circle your response.
Very similar to partner firm
Very different from partner
firm Company culture 1 2 3 4 5 6 7 Goals regarding growth 1 2 3 4 5 6 7 Operating philosophies 1 2 3 4 5 6 7 Organizational structure 1 2 3 4 5 6 7 Management style 1 2 3 4 5 6 7 Resources 1 2 3 4 5 6 7 Technologies 1 2 3 4 5 6 7 New product strategies 1 2 3 4 5 6 7 Innovativeness 1 2 3 4 5 6 7 Risk taking 1 2 3 4 5 6 7 New product development processes 1 2 3 4 5 6 7
Please be sure to keep focusing on the partner firm you have identified. Use the following scale and write down your response on the space provided.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree We feel uncertain whether our partner firm can contribute to our new product development. We are worried about the adequacy of technology offered by our partner firm. Our partner firm’s technology is important to the success of our new products. We are at risk if our partner firm does not perform according to requirements. We would take a big loss if our partner firm were not reliable in delivering required technology. The chance that our new products will fail in the market is high if the partner firm does not
deliver required technology.
Please circle your response on each of the following statements
Strongly Disagree Strongly
Agree We feel uncertain whether we can effectively coordinate with our partner in developing new products. 1 2 3 4 5 6 7
We are afraid that we cannot get our partner firm to buy into what needs to be done in developing new products. 1 2 3 4 5 6 7
We are worried about interruptions in our new product development plans if our partner firm does not cooperate with us. 1 2 3 4 5 6 7
We are at risk if our partner firm does not execute and implement what is required. 1 2 3 4 5 6 7
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Strongly Disagree Strongly
Agree We are afraid that there would be serious problems if our partner firm does not follow our instructions in this new product development project.
1 2 3 4 5 6 7
We are not sure we can be successful in developing this new product if our partner does not implement as required. 1 2 3 4 5 6 7
We stand to lose our competitive advantage if our partner does not execute and implement according to requirements. 1 2 3 4 5 6 7
Please use the following scale and write down your response on the space provided.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree We fear that too much proprietary knowledge may be disclosed to this partner firm. We could suffer a loss if our new product specifications and designs are released to this
partner. It is risky for our company to disclose too much proprietary product knowledge to this partner
firm. It is important to keep our new product knowledge inside the company and away from our
partner. The chance that our proprietary knowledge will be disclosed to our partner firm is high. Our company has a lot at stake in leveraging our product knowledge to our partner firm. We fear that we will lose our competitive advantage if our proprietary product knowledge is
disclosed to our partner firm. Please be sure to keep focusing on the partner firm you have identified and circle your response on each of the following statements.
Strongly Disagree Strongly
Agree We are afraid that this partner firm is not as dedicated as they should be to make our joint new product development work. 1 2 3 4 5 6 7
Our firm is at risk if we break up with this partner firm and have to find a new partner/ally. 1 2 3 4 5 6 7
We worry whether our partner firm has any true sense of obligation to us and our new product development project with them. 1 2 3 4 5 6 7
It is risky for us to commit totally to this partner firm when we are not sure of their commitment to us. 1 2 3 4 5 6 7
Our firm could stand to lose a lot if our partner firm is not fully committed to their relationship with us. 1 2 3 4 5 6 7
We stand to lose if our partner firm decides to be opportunistic in their relationship with us. 1 2 3 4 5 6 7
Our firm has taken a risk in trusting and committing to the relationship with this partner. 1 2 3 4 5 6 7
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Use the following scale and write down your response on the space provided.
Strongly Disagree 1 2 3 4 5 6 7 Strongly Agree If our partner firm does not have a good reputation, there is some chance our reputation will
suffer also. Our partner’s reputation is so strong and positive, associating with them could only increase
our own reputation. We stand to lose if our partner does anything at all that reflects badly on our image and good
name. We believe it is important to develop new products with only allies that have a strong positive
image with the public. Ever since we began the association with this partner, we have had to worry about the damage
to our reputation. Our company could end up looking bad if our partner firm did something irresponsible and in
some way harmful to the public. It is risky for us to develop new products with this firm because it seems that their reputation
with our customers is not all that good. In this section, we are interested in the outcomes brought by this alliance relationship. Please circle your response.
Strongly Disagree Strongly
Agree The alliance is characterized by a strong and harmonious relationship between the alliance partners. 1 2 3 4 5 6 7
We have achieved our primary objective(s) in forming this alliance. 1 2 3 4 5 6 7 We have been successful in learning some critical skill(s) or capabilities from this alliance partner. 1 2 3 4 5 6 7
The overall assessment of this alliance is satisfactory. 1 2 3 4 5 6 7 The overall performance of this new product alliance program has met our objectives. 1 2 3 4 5 6 7
From an overall profitability standpoint, our new product alliance development program has been successful. 1 2 3 4 5 6 7
Compared with our major competitors, our overall new product alliance program is far more successful. 1 2 3 4 5 6 7
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The following questions relate to your firm’s alliance experiences. Please circle your response. Strongly
Disagree Strongly
Agree Our company has been involved in other alliances. 1 2 3 4 5 6 7 We are experienced in managing alliance partners. 1 2 3 4 5 6 7 We are familiar with the practice of forming alliances. 1 2 3 4 5 6 7 This is our first time working with other firms to develop new products. 1 2 3 4 5 6 7 We are very new at figuring out how alliances work. 1 2 3 4 5 6 7
In terms of your firm’s external environment …….
Strongly Disagree Strongly
Agree The technology in our industry is changing rapidly. 1 2 3 4 5 6 7 It is very difficult to forecast where the technology in this industry will be in the next five years. 1 2 3 4 5 6 7
Rapid technology changes in our industry necessities frequent product modifications. 1 2 3 4 5 6 7
Technological developments in our industry are frequent. 1 2 3 4 5 6 7 Technological changes in our industry provide major opportunities. 1 2 3 4 5 6 7 SECTION 2 – Facts about Your Company and Your Partner Firm How long has your partner firm been in business? ____________ years What is the approximate size of your partner firm?
_____________ (in number of employees) _____________ (last year’s sales volume)
How many years have you been doing business with this partner? ________ years How did you know this partner? Please check the appropriate box.
□ We were introduced to this partner through another firm (e.g., consultancy). □ We identified this partner by ourselves □ Other, please specify _______________________
With regard to the brand of the new product, what kind of arrangement has been made? Please check the appropriate box.
□ A new brand was created that was not connected or associated with either partners. □ The new product’s brand was associated with our firm. □ The new product’s brand was associated with the partner firm. □ Other; please specify ________________
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Who owns the new product brand? Please check the appropriate box.
□ Both partners jointly □ Our firm
□ Partner firm □ Other; please specify ________________
Who owns the technology? Please check the appropriate box.
□ Both partners jointly □ Our firm
□ Partner firm □ Other; please specify ________________
Who will be responsible for introducing and marketing this new product? Please check the appropriate box.
□ Both partners jointly □ Our firm □ Partner firm □ Other; please specify ________________
How long have you been with this company? __________ years
How much involvement do you have in this new product development alliance?
Not at all 1 2 3 4 5 6 7 Very much How much influence do you think you have in this new product development alliance?
Not at all 1 2 3 4 5 6 7 Very much
Thank you for your time and we appreciate your effort.
If you want to get a report summarizing the findings of this research, please provide us with your name and address OR attach a business card with your response. Company Name ___________________________________________ Address __________________________________________________ Telephone ________________________________________________ Fax ______________________________________________________ E-mail address _____________________________________________ Respondent Name and Position ________________________________
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