Faculty & Research
Testing the Life-Cycle Theory of InterOrganizational Relations: Do Performance
Outcomes Depend on the Path Taken?
by
S. Jap
and
E. Anderson
2003/17/MKT
Working Paper Series
Testing the Life-Cycle Theory of Inter-Organizational Relations:
Do Performance Outcomes Depend on the Path Taken?*
Sandy D. Jap**
Erin Anderson***
February 2003
* This study was supported by a grant from the Integrated Supply Chain Management
Program in the Center for Transportation Studies, Massachusetts Institute of Technology.
Special thanks to the participating supplier firm for data access and funding and to Nirmalya
Kumar for comments on previous versions of the manuscript.
** Associate Professor of Marketing
Goizueta Business School
Emory University
1300 Clifton Road
Atlanta, GA 30324
USA
[email protected]
404-727-7056
*** John H. Loudon Chaired Professor of
International Management and Professor
of Marketing
INSEAD
Boulevard de Constance
77305 Fontainebleau Cedex, FRANCE
[email protected]
33-1-60-72-44-48
Testing the Life-Cycle Theory of Inter-Organizational Relations:
Do Performance Outcomes Depend on the Path Taken?
Abstract
This research provides an empirical test of the Dwyer, Schurr & Oh (1987) lifecycle
theory of relationships and considers the role of path dependence in achieving overall
satisfaction during each phase. Using survey data of over 1300 channel resellers, we find
general support for the notion that relationship properties (e.g., goal congruence, investments,
satisfaction) first increase and then decrease over the course of the relationship lifecycle,
including a significant drop in the decline phase relative to all other phases. Contrary to the
theory’s predictions, however, minimal empirical differences among these properties do exist
in the build-up and maturity phase. We also explore whether relationships that followed the
expected lifecycle path outperform relationships that followed aberrant (backward) patterns.
We find that movement through regressive patterns can exert detrimental effects on overall
satisfaction. Moreover, the scars from such movements can last for an extended period of
time, which can prove particularly detrimental during the decline phase. Evidence also
reinforces the critical role of the individual sales representative in promoting the creation of
successful long-term inter-organizational relationships.
Testing the Life-Cycle Theory of Inter-Organizational Relations:
Do Performance Outcomes Depend on the Path Taken?
Introduction
An influential article by Dwyer, Schurr, and Oh (1987) posits that ongoing, stable
buyer-seller relationships develop according to a predictable series of events occurring in a
fixed order. This life-cycle theory posits that inter-organizational relationships begin with a
phase of awareness, followed by acceleration of the relationship through succeeding phases of
first exploration, then expansion (build-up), and finally commitment (maturity).
Some
relationships then enter a phase of decline, perhaps ending in dissolution. This phases-ofdevelopment approach blends elements of economic sociology and transaction-cost analysis
in order to arrive at a description rich with normative implications and often cited. Curiously,
little empirical validation of this theory exists, and no one has considered how progression (or
regression) through the various phases may affect the ultimate performance of the
relationship. This research addresses this gap.
We test the descriptive validity of the life-cycle theory itself. This endeavor leads to a
series of propositions that certain relationship properties will be highest during maturity,
somewhat lower during expansion, lower still during exploration, and lowest during decline.
For the most part, we find supportive evidence. However, while clear evidence still supports
these differences from exploration to maturity and on to decline, it proves somewhat difficult
to distinguish empirically between the two intermediate phases of expansion (build-up) and
maturity.
We also examine the performance implications of the life-cycle theory of
relationships.
The customer’s perception of relationship performance is modelled as a
function of both the phase of the relationship at present and the path by which the relationship
arrived at its current phase. Relationships that appear to have progressed according to the
phase-by-phase development theory to reach their current phase are compared to relationships
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that appear to have regressed to their current phase (aberrant in the theory). For example, a
relationship in expansion (or build-up) may have progressed to this phase by passing through
the prior phase of exploration (expected), or it may have regressed to this phase by falling
back from having once hit the committed phase (aberrant). We ask whether the path leading
to the current phase of the relationship life cycle helps to explain several facets of B2B
relationship performance.
We find evidence that path dependence produces a substantial impact on relationship
performance: the buyer-supplier relationships that generate better results for customers appear
to do so as a function of how they came to their current phase of development. Notably,
relationships with an apparent history of setbacks, even outright failures, perform differently
from relationships emerging from a path of less friction. Hence, it appears that the path by
which the dyad arrives at its current phase generates different effects on the level of
satisfaction received from the relationship, and this difference will vary systematically across
the phases of the lifecycle. We also find evidence that a sales representative, acting as a
relationship builder and key liaison between the organizations, exerts an important influence
over the customer’s view of the relationship.
This study tests the phases-of-development theory and its performance implications
empirically, using a large data set: over thirteen hundred customers of an industrial chemicals
supplier, all of whom report on the relationship properties and performance of their
relationships from their own perspective. Customers also report on the current relationship
phase and on the phase of the relationship five years earlier.
This data provides an
approximate indicator of the path by which the relationship came to its current phase of
development.
The setting (one supplier, one industry) enhances the comparability of
observations, while the size and scope of the data set insures considerable variation.
We begin with a review of Dwyer, Schurr, and Oh’s (1987) life-cycle theory, drawing
testable implications as to the current state of affairs in each phase of a buyer-supplier
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relationship. We then examine how the path taken might flout expectations arising from this
description, and how path dependence could influence how well a given relationship
functions, above and beyond the influence of the current phase of development. We then
describe the data assembly and test the influence of the current phase on the properties of the
relationship. We also test how the path taken to reach this phase influences relationship
performance from the customer's standpoint.
This analysis -- necessarily exploratory --
suggests implications for both research and practice.
The Theory of Life Cycles in B2B Relationships
A substantial body of literature tests the premise that close relationships differ
systematically from more distant relationships and describes the differences between discrete
and relational exchange.
This literature, also known as relationship management, has
become one of the most active fields in marketing in recent years (Stewart 2002). Dwyer,
Schurr, and Oh’s (1987), hereafter DSO, seminal contribution to this literature is the notion
that understanding how relationships develop can offer a critical vantage point for relationship
management strategy. This central idea has been and continues to be cited frequently by
scholars in many disciplines (Leigh, Pullins, and Comer 2001).
DSO posits that buyer-seller relationships develop according to a predictable, stable
series of events occurring in a fixed order. Marketplace relationships are said to begin with a
phase of awareness, followed by acceleration of the relationship through succeeding phases of
exploration, expansion, and finally commitment. Some then enter a phase of decline, perhaps
ending in dissolution. DSO acknowledges that not all transactions move through these phases
to develop into relational exchanges. In the DSO view, transactions that are not relational will
be discrete -- that is, classic arm’s-length market contracting, one deal at a time, with no joint
efforts and no future time horizon. Discrete contracting is more likely when the customer is
the final buyer. However, resellers differ; they put their reputation behind what they sell.
Channels of distribution are interdependent systems in which the seller and buyer share a
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common interest in cultivating a market. Resellers can and do operate one deal at a time, with
no joint efforts and no future, but the gains to cooperation in channels are potentially very
large (Coughlan et al. 2001). Hence, the DSO phases theory becomes particularly appropriate
when the customer is a reseller, the setting we examine.
The DSO approach unites many seemingly disparate approaches to the function and
performance of buyer-supplier relationships, including ideas from political economy,
sociology of organizations, transaction cost analysis, marketing exchange, social exchange,
bargaining and conflict theory, and relational governance. Macneil's (1980) relational theory
of contract, with its emphasis on the development of norms, figures prominently, as do
variants of social exchange theory.
DSO’s life-cycle theory is rich with normative
implications yet retains a fundamental simplicity: within the relationship, a number of posited
properties remain at a fairly low level in exploration, then increase during expansion, peak
during maturity, and fall when the relationship declines. Although the theory is not explicit,
DSO's emphasis on the pain and cost of decline suggests that the posited properties are lower
in decline than in exploration. Below, we summarize this progression and the states of the
relationship that DSO expects to prevail in each phase.
In the awareness phase, no transactions occur between a potential buyer and supplier,
but at least one actor considers the other a feasible exchange partner. When both actors begin
communication, they pass to the exploration phase. They explore not only market exchange
(in which they might engage) but also the prospect of forging a closer relationship. The key is
to build in a long time horizon or expectation of continuity (Anderson and Weitz 1989).
Players in relationships with a longer "shadow of the future" more likely cooperate (Heide
and Miner 1992), thereby improving prospects for future performance. While neither side
makes significant investments (or takes other risks) in the exploration phase, both sides assess
the attractiveness of closer ties and begin to communicate and negotiate the outlines of the
relationship. Neither side wields significant power over the other, as neither depends on the
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other or feels committed to the arrangement. The exploration phase may be lengthy, as both
sides gauge and test each other, but is easily terminated, as no one has much to lose.
Should exploration prove fruitful, buyer and supplier progress to phase three,
expansion, in which the relationship builds properties not present during discrete contracting.
Each side makes investments and takes risks. Some of these investments are the most
hazardous kind, idiosyncratic to the dyad (and therefore difficult to redeploy to another
exchange partner). For example, a customer may invest time and effort to learn the supplier's
products and processes and to forge relationships with supplier personnel. Or the customer
may make changes in strategies, policies, processes, and physical assets (such as tooling) so
as to adapt to the supplier.
Reciprocity is common: both sides are expected to make
idiosyncratic investments, thereby building barriers to exit and creating incentives to
cooperate.
DSO posits that communication increases significantly and conflict is kept in check.
Norms develop: both parties expect each other to exchange information freely and frankly, to
share goals, and to exhibit commitment to their relationship. Trust presumably blossoms as
interdependence deepens. Increased cooperation should secure the dyad more rewards, which
they are likely to divide fairly, according to a norm of mutuality. Hence, both parties should
be more satisfied in expansion than in exploration.
Should the relationship continue to deepen, it will reach the fourth phase, maturity.
This phase, which DSO labels commitment, yields "an implicit or explicit pledge of relational
continuity between exchange partners" (p. 19). In this phase, the relationship deepens the
processes begun in the expansion phase.
The properties that have built throughout the
expansion phase peak. From here, the relationship is stable; if it changes, it has nowhere to
go but down.
Many relationships eventually pass into phase five, decline. DSO claims that decline
is poorly understood and that it does not merely reverse or unwind earlier phases. The four
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phases prior to decline depend on mutual efforts. In contrast, decline may be unilateral,
reflecting mounting dissatisfaction on one side. Decline typically leads to the final phase, a
negotiated dissolution. DSO suggests that this phase is the end of the story: “neither party
returns to their prerelationship state” (p. 20). DSO explains that the loss of investment and
the difficulty of a “negative transition” or “rollback” can “leave deep sentimental scars that
may block out intermediate relational levels” (DSO p. 22).
These descriptions of the phases lead to a series of propositions positing that certain
relationship properties will be highest during maturity, somewhat lower during expansion,
lower still during exploration, and lowest during decline.
Relationship properties may
include: (a) goal congruence between buyer and seller, (b) harmony (lack of conflict), (c)
norms of frank information exchange, (d) overall dependence (the combined dependence of
both sides), and (e) bilateral investments, as well as the reseller’s time and tangible
idiosyncratic investments.
We expect this same pattern (highest in maturity, then expansion, then exploration,
then decline) to apply to the customer’s attitudes, behaviors, and outcomes vis-à-vis the
manufacturer. The customer should exhibit (f) higher trust in the manufacturer as an entity,
and (g) greater willingness to take risks on behalf of the supplier. These properties reflect
relationship norms, which peak during maturity. Further, the customer’s behavior should
evince (h) greater willingness to increase dependence on the supplier by making idiosyncratic
investments. The customer should be (i) more satisfied with the supplier’s performance on its
behalf and should (j) rate its outcomes more highly in comparison to the next best alternative.
Finally, as the relationship deepens, the customer should (k) develop a strong preference:
operationally, the reseller will consider a smaller set of other suppliers as acceptable
alternatives.
In part one of our two-part analysis, we examine this broad set of DSO predictions in
a unified manner by comparing these relationship properties (a-k) in different phases. We
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contrast each phase from exploration to decline and dissolution, expecting a pattern of
increase, then decrease in relational states and in performance (from the customer's
perspective). We now turn to a second issue: the influence of history.
Path Dependence, Transitions and Performance
Path Dependence
In recent years, organizational scholars have become interested in the phenomenon of
path dependence: the idea that a firm's performance and choices today are strongly influenced
by its performance and choices in the past. The premise that the paths currently open depend
on the path already taken is central to evolutionary theories of the firm (Nelson 1995). This
premise controversially implies that firms do not face the same choice set, cannot freely elect
to follow the "best" path, and are limited in their ability to adapt to an environment.
Assumptions that all firms are path-dependent (that their past conditions their future) imply
that economic selection mechanisms do not operate as strongly as classical economic theory
posits.
Once relegated in most organizational analyses to footnotes, limitation sections, and
discussions of puzzling results (Nelson 1995), path-dependence theory is rapidly gaining
acceptance in multiple literatures.
Grewal and Dharwadkar (2002) offer a review in
marketing, focusing on channels of distribution as a major area of application. One leitmotiv
suggests that the history of a relationship produces a substantial influence on how social
actors 1) perceive relationship dynamics, 2) frame relationship performance, and 3) set the
time horizon of their arrangement. Indeed, Grewal and Dharwadkar (2002) argue that history
determines the relationship’s potential level of performance.
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Transitions
DSO posits that relationship phase influences performance, current and potential;
performance should increase along with relational states through the various phases of the life
cycle, peaking in the commitment phase and tapering off or dropping in the decline and
dissolution phases. Where one starts possibly matters significantly: relationship outcomes
such as performance or time horizon may reflect not only relationship phase but also how the
relationship reached that phase. We focus on two elements of history: direction of movement
and stability.
The thrust of DSO is that "relationships inevitably move toward the commitment
phase or dissolve along the way" (Cannon and Perreault 1999, p. 456). However, DSO
speculates that some phases, such as exploration and expansion, may be compressed. DSO
also argues that firms can remain in a given phase, even exploration, for a long time. Hence,
the DSO framework expects paths of both stability and progression. We contrast these
expected paths with unexpected paths -- namely, relationships that have regressed to their
current phase. DSO does recognize that not every relationship moves to higher phases and
notes the possibility that a relationship can scale back (or “wind down”) from expansion to
exploration, a transition that may not even be dramatic. DSO emphasizes the "scars" incurred
when a relationship dials back from a more advanced phase, such as from commitment to
expansion.
Accordingly, we anticipate that relationships that reached their phase by
regression exhibit lower performance outcomes than do relationships that either progressed to
their current phase or remained stable in that phase for a long time. In short, although the
DSO framework predicts a progression from early to later phase, we consider at least some
departures from this ordering, along with the possibility that relationships may not behave as
expected in each phase.
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Performance
How should we conceptualize performance? We adopt the position of Anderson and
Narus (1990) that satisfaction is the focal consequence of working in partnership. They
contend (p. 46) that "satisfaction, by its nature, is not only a close proxy for concepts such as
perceived effectiveness, but also may be more predictive of future actions by partner firm
managers."
As noted by Geyskens, Steenkamp, and Kumar (1999), satisfaction with
economic and non-economic aspects of the relationship are strongly related. Accordingly, we
cast performance -- from the reseller's standpoint -- as satisfaction with the overall outcomes
achieved within the relationship.
Reseller’s Trust in the Sales Representative
The DSO framework fails to address a critical aspect of inter-organizational
relationships: the role of an individual sales representative in building successful long-term
relationships. Sales representatives can play a critical role in this process; their personal
interactions and ongoing efforts to build and maintain the exchange can be a source of
tremendous value and customer satisfaction (Cravens 1995; Wortruba 1991). By engaging in
actions that demonstrate benevolence toward the customer, honest communications, and
extra-role efforts, the sales representative develops the customer’s trust, which is a primary
means of building customer satisfaction (Geyskens, Steenkamp and Kumar 1998; Jap 2001;
Morgan and Hunt 1994; Smith and Barclay 1997). Hence, the decision to cultivate an
interpersonal relationship with a customer and to develop trust in a sales representative is a
matter of strategic choice.
Reseller trust in the sales representative refers to the customer’s confidence in the
sales representative’s integrity and reliability (Andaleeb 1992; Anderson and Narus 1990;
Moorman, Deshpandé and Zaltman 1993; Morgan and Hunt 1994). This trust develops out of
repeated interactions in which the reseller finds the sales representative consistent, competent,
honest, fair, responsible, and benevolent (Altman and Taylor 1973; Larzelere and Huston
9
1980; Rotter 1971). Thus, the customer views the sales representative’s trustworthiness as
grounded in observable behaviors and specific actions: it is not just a latent trait of the
individual. A trustworthy sales representative can exert considerable influence on a reseller’s
view of the supplier’s reliability and service value and can also affect the reseller’s interest in
continuing the relationship (Biong and Selnes 1996).
In light of these possibilities, we
include the reseller’s trust in the sales representative as a critical covariate in the analysis of
movement from phase to phase.
In order to examine how a relationship’s path dependence affects satisfaction
outcomes, we examine a subset of industrial relationships that have existed at least five years.i
Figure 1 presents our framework for examining the impact of path dependence. We model
performance from the customer’s perspective, operationalizing it as reseller satisfaction with
the relationship.
Methodology
Data Collection
Research setting. Tests of propositions are conducted in the channel base of a leading
chemical manufacturer, whom we offered customized analyses in exchange for its
participation in the research. The manufacturer is one of the top five chemical producers in
the world, with over $7 billion in annual sales. The firm sells herbicides, plant growth
regulators, animal feed supplements, and crop chemicals to thousands of channel resellers,
who in turn sell to hundreds of thousands of growers throughout the U.S. Some of the
manufacturer’s products are patented and in high demand among growers.
Given the
importance of this principal and of the product category, downstream channel members are
unlikely to treat the relationship as a discrete exchange, where each transaction stands on its
own as a deal on its own merits, no joint efforts emerge, and the relationship has no future
orientation. Hence, the DSO stages theory should apply to all relationships.
10
Our informants (see below) indicate that the average number of alternative
manufacturers who could provide the products that this supplier provides is 3 (range: 0 to 30),
while the average number that the channel would seriously consider is 2.1 (range: 0 to 20) and
the average number with which the channel would regularly work is 2.4 (range 0 to 20). This
supplier is not a monopolist. That said, the available set of replacements is not, on average,
large. Furthermore, this supplier has substantial brand equity in some product categories.
Sample. The manufacturer created a stratified random sample of their 15,000 resellers,
producing a sampling frame of 4,033 channel resellers. The sample was stratified to insure
that the sample reflected similar proportions among various types of resellers (e.g.,
independent, national, and cooperative resellers) as the complete channel base. These channel
members purchased an annual average of $3.3 million in goods and services from the
manufacturer (range: less than $100 thousand to $112 million) and had worked with the
manufacturer an average of 17 years (range: 1 to 50 years). The informants at these firms
were the chief point of contact for the supplier; in other words, these managers had the most
regular interaction with the supplier on a range of issues.
Procedure. Questionnaires were mailed to named key informants among the resellers,
along with a cover letter from the researchers explaining the study and guaranteeing
confidentiality, a cover letter from the manufacturer encouraging participation, and a postagepaid return envelope to a university address. As 1,660 surveys were received, the response
rate is 41%.
The informants were told that the study concerned the topic of channel
relationship management and were offered a summary of the aggregate results in exchange for
their participation. They were encouraged to express their firm’s true attitudes toward the
manufacturer (our pretest efforts indicated that they did not hesitate to do so). The informants
had on average, 20.9 years of experience in their position with the reseller (range: 1 to 50) and
had personally worked with this manufacturer an average of 14.8 years (range: 1 to 51),
confirming that they were indeed knowledgeable.
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The unit of analysis is the relationship between this manufacturer and this reseller, as
perceived by the reseller. The questionnaire directed the informant to complete all items with
respect to his/her firm’s relationship with the manufacturer organization; the only exceptions
were the items used to measure the customer’s trust in the individual sales representative.
Because of the tremendous difficulty in collecting longitudinal data on relationship phases
(cf., Anderson 1995), we employ a cross-sectional approach in which each relationship is
classified in a specific relationship phase and a multi-sample analysis is used to understand
specific effects across the various phases.
One might argue that using a single supplier or industry as a reference point might
limit the generalizability of the results or the range of measure. However, this effect is
minimized to some degree. First, the marketing literature suggests that relationships between
a single supplier and multiple resellers may differ markedly due to differences in end-user
characteristics, competition levels, cost of channel functions, and the nature of prior
relationships (Lusch and Brown 1996; Stern, El-Ansary and Coughlan 1996, p. 349; Stump
and Heide 1996). Second, interviews with resellers indicated that each one negotiated a
variety of discount, shipping, packaging, and transportation terms, such that each relationship
reflected specific considerations in its market area. Furthermore, multiple contracts were
often negotiated among different entities of a single organization. For example, coordination
difficulties among offices of national resellers would result in a national contract with the
supplier and additional contracts with regional and territory offices, thus reflecting the
idiosyncratic nature of reselling within the various organizations. This research surveyed all
three levels of these organizations.
To this end, the wide variety of relationship types
represented in the sample of 1500+ resellers is likely to reflect the relationship types that may
occur across a variety of industries.
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Measurement
Relationship stages. Of the six stages, none can fall in the awareness stage, as these
are existing relationships.
Thus, informants classified their relationships with the
manufacturer as being in one of five possible phases: exploration, build-up, maturity, decline,
or deterioration. This measure, from Jap and Ganesan (2000), contains brief descriptions of
each phase: managers check one.
Pretests indicated that informants had no difficulty
understanding the differences across descriptions, felt the five descriptions encompassed all
their relationships, and did not require another choice in order to respond. Key here is that the
description should be brief and should not cue the informant as to all the features that DSO
expect to see as a result of the relationship's stage.
Managers are presented with the statement "Relationships typically evolve through a
number of phases over time. Which of the following best describes your firm's current
relationship with ___________?" For exploration, the description is:
Both firms have are discovering and testing the goal compatibility, integrity, and
performance of the other as well as potential obligations, benefits and burdens
involved with working together on a long-term basis.
For expansion, DSO (p. 18) states "expansion refers to the continual increase in
benefits obtained by exchange partners and to their increasing interdependence."
Accordingly,
Both firms are receiving increasing benefits from the relationship and a level of trust
and satisfaction has been developed such that they are more willing to become
committed to the relationship on a long-term basis.
The most advanced stage, maturity, is characterized as:
Both firms have on ongoing, long-term relationship in which both are receiving
acceptable levels of satisfaction and benefits from the relationship.
This phrasing does not cue the informant that DSO expects these ongoing, long-term
relationships to be so close as to approximate vertical integration, nor that DSO expects that
"acceptable levels of satisfaction and benefits" will be very high.
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Decline and then deterioration are described as:
One or both members have begun to experience dissatisfaction and are contemplating
relationship termination, considering alternative manufacturers or customers, and are
beginning to communicate intent to end the relationship.
The firms have begun to negotiate terms for ending the relationship and/or are
currently in the process of dissolving the relationship.
Few relationships fell in the deterioration phase; this scarcity could result from the fact that
deterioration can occur rapidly, relative to other phases.
As a result, we pooled these
responses with those in the decline phase.
Phase by phase relationship properties. The relationship properties constructs a-k are
measured by multiple-item scales, where 1=strongly disagree and 7=strongly agree.
Whenever possible the scales from past research; all other measures are created specifically
for the purposes of this research. The Appendix lists all the scale items used and the sources
of the scales. Table 2A displays the construct means, standard deviations and correlations
among all the latent constructs.
A measurement model consisting of 14 first-order latent
factors, their associated item loadings, measurement errors and intercorrelations using full
information maximum likelihood techniques in LISREL 8.51 (Jöreskog and Sörbom 1993).
The chi-square for this model is 8364.44 (1861 df). The comparative fit index (CFI) and the
incremental fit index (IFI) is .90, while the Tucker-Lewis fit index (TLI) is .89. The root
mean square approximation of error is .049. Collectively, these indices indicate a good fit of
the model to the covariance matrix. All of the factor loadings are significant, indicating
convergent validity of the items with respect to their intended constructs. Discriminant
validity is stringently assessed by comparing the intercorrelations among the latent factors
according to the procedure recommended by Fornell and Larcker (1981). All possible pairs of
factors pass this test.
Movement. To capture the historical movement of the relationship up to the point in
time of data collection, the informant also classified the relationship into the phase prevailing
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five years ago with the same manufacturer.
A review of longitudinal studies in the
management literature indicates that no clearly optimal time frame exists (Williams and
Podsakoff 1989); time frames are typically chosen for convenience, as opposed to theoretical
reasons. The five-year time period was selected in order to insure sufficient variation in
potential movement across the phases, given that relationships take time to evolve.
Informants could also indicate that their firm had no relationship with the
manufacturer five years ago or that he/she personally did not work with the manufacturer five
years ago. For the current relationship phase, 1,540 informants provided responses, which are
used to examine the current properties of the relationships. Of these, 1,356 informants
classified their relationship into one of the relationship phases five years ago; for these
informants, the relationship existed and the informant was working with the supplier, insuring
that the informant was personally knowledgeable). This is the set of relationships used in the
analysis of the effects of path dependence on performance.
Table 1 summarizes the movement implied by the stage five years ago versus the
current stage. Relationships could possibly have moved through additional stages besides the
ones measured over the five-year period: for example, an apparent progression from
exploration to maturity could disguise a complete cycle through decline, followed by a move
toward maturity in a second cycle.
However, relationships tend to develop gradually,
dampening the number of shifts likely to occur during the five years. We treat relationship
movements as if they encompass one cycle, although we acknowledge the possibilities that
some relationships could have undergone more than one cycle to reach the current state from
five years earlier.
As Table 1 shows, each relationship as showing no change (n=417) versus some
movement (n=939) across the five-year period. That 417 of 1356 relationships show no
apparent change in stage supports the idea of relationship inertia.
Most no-change
relationships are in maturity or build-up. Strikingly, 33 relationships are still in decline,
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having avoided deteriorating into dissolution. Of the 939 relationships showing movement,
the bulk of relationships appear to follow a standard DSO progression. This number includes
369 relationships that progress from earlier life-cycle stages to later ones in the sequence of
exploration, then build-up, then maturity, as well as a set of 347 relationships that passed into
decline from earlier stages of exploration, build-up, or maturity. These relationships are
indicated by arrows to the right.
Arrows to the left are considered relatively unlikely in the DSO framework and are
indeed a minority.
Nonetheless, more than a few unexpected relationships are present,
perhaps due to the large sample size. These relationships appear to backtrack from later
stages to earlier ones. One set of 110 relationships reflects improvement from a decline
status.
They may well represent relationships that have been “saved” from a negative
outcome (continuing decline or eventual dissolution). Twenty-eight declining states have
been upgraded to maturity, while 53 declines were saved by entering a build-up phase.
Another 29 declining relationships have effectively re-started over and are now in a state of
exploration.
Another set of 113 relationships has regressed from a posterior to an anterior
stage, by DSO reasoning.
Twenty-five once-mature relations appear to be under
reconsideration and are now in the exploration phase. Another 49 mature relationships seem
to be experiencing a renewal: they have returned to a state of build-up.
Finally, 39
relationships in build-up have reverted to exploration in what may constitute a reconsideration
of the arrangement.
The items used to measure the two latent factors, reseller trust in the sales
representative and overall satisfaction with the relationship, are listed in the Appendix and the
means, standard deviations, and correlation between the two constructs are listed in Table 2B.
A confirmatory factor analysis yields an estimated measurement model with a chi-square of
1004.23 (103 df), with a CFI and IFI of .95 and a TLI of .94. The RMSEA is .089.
Collectively, these indices suggest a good fit of the model to the data. The factor loadings are
16
significant, indicating evidence of convergent validity of the items, and the two constructs
pass the Fornell and Larcker (1981) test of discriminant validity.
Tests of Propositions: Patterns in Current Relationships
Part one of our analysis tests whether states of relationships, taken as a whole, follow
the pattern expected by DSO: rising relationship states through exploration and build-up,
peaking at maturity, and falling in the decline stage.
Table 3 shows the results of a
multivariate analysis of variance (MANOVA) of the full set of 1540 current relationships.
This analysis ignores history, focusing only on the current stage, as identified by their
managers (our informants). Recall that informants were not cued as to what DSO expects in
each stage, beyond the broad statements of momentum, intent, and time horizon that are
defining characteristics of a phase.
For the most part, these results support the idea that relationship states start low
(exploration stage), increase (build-up stage), and then fall (decline stage). This finding
accords with much of the framework. What does occur in the maturity stage is unexpected.
Not once does a mature relationship show the expected peak. Indeed, roughly half the results
show no difference between build-up and maturity. We consider these results in three groups,
each exhibiting systematically different patterns.
Figure 2 depicts the first group, which we have labeled the “premature peak.” This
group includes constructs for which mature relationships appear to operate slightly below
expansion relationships. Here, the lowest states are found in the decline phase. Relationship
states are more favorable in exploration, supporting the idea that decline involves
recrimination and disappointment. Of course, these are different relationships, not the same
relationships at different points in time. And while these differences are small, they are
statistically significant. This pattern of premature peaks occurs for goal congruence, norms of
information exchange, and satisfaction with the manufacturer's products.
Perhaps these
premature peaks in relationship properties reflect the fact that expectations are built in the
17
expansion phase of the relationship. These constructs might also be particularly important for
establishing and building a long-term relationship. It is important to insure that both parties
share congruent goals in regard to sales and profits objectives and the purpose of the
relationship’s existence. Information exchange norms are critical for insuring how parties
will handle issues that arise over the course of the relationship and how they will share critical
information. The reseller must also have a high level of satisfaction with the supplier’s
products before entering into a deeper, long-term relationship. These properties are usefully
established at the start of a relationship and enable the dyad to cope with the risks and
uncertainties (of forming long-term ties) that are characteristic of the expansion phase.
Figure 3 demonstrates relationship properties with a pattern resembling a plateau
between the expansion and commitment phase, rather than a DSO peak. This pattern holds
for the level of bilateral idiosyncratic investments, willingness to take risks on the supplier's
behalf, the reseller's trust in the supplier, the level of harmony in the dyad, and outcomes
given the comparison level of alternatives. It also holds for a critical performance outcome:
satisfaction with financial returns. These six features significantly influence the function and
performance of the marketing system, as seen by the reseller. In contrast to the constructs in
the premature peak group, these relationship properties are built up over time. A history of
interaction is needed for the dyad to develop trust, a level of harmony, satisfaction with
financial returns, and a willingness to take risks and make joint investments. Without a
history of interaction with the supplier, establishing satisfaction with the financial returns
from the relationships and alternative comparable outcomes proves difficult.
Collectively, the premature peak and plateau groups fit a general pattern of rising and
falling over the course of the relationship, with some exceptions to DSO predictions in the
build-up and maturity phases. It is also worth noting that the relationship properties in the
decline phase are significantly lower than in the build-up phase.
18
Less common are patterns that show decline and exploration to be indistinguishable,
as in Figure 4. The reseller’s idiosyncratic adaptation and time investments in supplierspecific development and learning peak in the build-up phase and drop in the maturity phase,
consistent with the notion of expanding the relationship into the long-term. However, the
levels of these constructs are indistinguishable in the exploration and decline phases. This
pattern may reflect the fact that idiosyncratic investments are difficult to dissolve. The value
of these investments is difficult to transfer to alternative relationships; hence, an incentive
emerges to wring out any possible returns from these investments before permanently
dismantling them. This figure also contains an anomalous result: the number of seriously
considered alternatives.
Unlike the other relationship properties, this construct is
indistinguishable during the exploration, build-up, and maturity phases and then increases
significantly in the decline phase.
Evidently the reseller begins to actively investigate
alternative suppliers only once the relationship has begun to unravel and dissolve.
Tests of Propositions: Path Dependence
We now turn to the effects of history, using the subset of 1356 relationships for which
the path to the current stage can be approximated. To examine the model of Figure 1, the
implied equations are tested via OLS regression within each phase. These equations are
compared to a baseline model estimated across the sample of 1356 relationships. These
equations all possess a common form, in that overall satisfaction is regressed on a dummy
variable indicating the relationship’s movement through phases as well as the reseller’s trust
in the sales representative.
We contrast all relationships that follow the typical relationship life cycle, either by
remaining in the same stage over the five years or progressing in a pattern specified by DSO,
with relationships that exhibit unexpected movement. The specific equations estimated are as
follows (see Table 1 for graphical representation of dummy variables):
All phases: SAT = a1 + b8 Move + b9 Build-up + b10 Maturity + b11 Decline + b12 RepTrust
19
Exploration: SAT = a3 + b20 Restart + b21 Reconsider + b22 RepTrust
Build-up: SAT = a5 + b31 Save + b32 Renewal + b33 RepTrust
Maturity: SAT = a7 + b41 Save + b42 RepTrust
Decline: SAT = a9 + b52 Exp_Dec + b53 Build_Dec + b54 Matur_Dec + b55 RepTrust
Variable Key:
SAT = Reseller’s Overall Satisfaction with the Relationship
Move = dummy for aberrant movement from the DSO framework
Build-up = dummy for relationships currently in the build-up phase
Maturity = dummy for relationships currently in the mature phase
Decline = dummy for relationships currently in the decline phase
RepTrust = Reseller Trust in the sales rep
Restart = dummy for relationships that moved from decline to exploration
Reconsider = dummy for relationships that moved from maturity or build-up to exploration
Save = dummy for relationships that moved from decline to build-up or maturity
Renewal = dummy for relationships that moved from maturity to build-up
Exp_Dec = dummy for relationships that declined from the exploration phase
Build_Dec = dummy for relationships that declined from the build-up phase
Matur_Dec = dummy for relationships that declined from the maturity phase
The all-phases equation provides a baseline model that contrasts unexpected
movement with stability and expected movement through the life cycle. The purpose is to
examine how aberrant movement affects the performance of the relationship. All other
equations decorticate various types of movement within each phase. Their purpose is to
explore the effect of phase-specific forms of unexpected movement and deterioration patterns.
Within each phase, the intercept term always contains all relationships that DSO expects,
namely progression or stability. The dummy variables represent unexpected and exploratory
paths.
We now turn to testing the effects of path dependence. Table 4 displays their
estimated coefficients.
All phases. Fifty-nine percent of overall satisfaction, all phases combined, is partly
explained by the relationship phase, reseller trust in the sales representative, and aberrant
movement. Movement that is aberrant by DSO’s predictions produces a detrimental effect on
overall satisfaction (-.18). Compared to expansion, reseller satisfaction is higher in build-up
and maturity (1.04 and .90), again suggesting the plateau effect of the middle stages. In the
20
decline stage, performance suffers (-.69). With phases controlled, resellers are more satisfied
when they trust the salesperson (.46).
However, aggregation often obscures opposing forces at work.
In particular, it
obscures the impact of aberrant movement on a phase-by-phase basis. When examined in
greater detail, the results below suggest that the nature of the aberrant movement has an
impact and that satisfaction indeed depends on some of the paths the relationships have taken.
We explore these results below.
The path taken to the exploration phase.
In this phase, we consider two forms of
aberrant movement: a restart and a reconsideration. A restart occurs when the dyad moves
from decline to an exploration phase. Reconsideration occurs when the dyad moves to an
exploration phase from either the maturity or build-up phase.
Both forms of aberrant
movement exert no discernible effect on overall satisfaction, relative to stability or the typical
life-cycle movement. However, reseller trust in the sales representative does yield a positive,
significant impact on satisfaction (.39) during this phase.
The path taken to the build-up phase. In this phase, aberrant movement such as a
save, which involves movement from the decline phase to build-up, has a significant negative
effect on overall satisfaction (-.32). However, renewal, which involves movement from
maturity to build-up, produces no significant effect on satisfaction. The reseller’s trust in the
sales representative, controlling for aberrant movement, continues to have a substantial effect
on overall satisfaction (.60).
The path taken to the maturity phase. In the mature phase, we consider another form
of save: movement from the decline phase to maturity. This form of movement exerts a
detrimental impact on overall satisfaction (-.45). Reseller satisfaction is also boosted by trust
in the salesperson (.66).
The path taken to the decline phase. An unexpected right-to-left path is not possible
in decline; the only way to achieve decline is to have done some business five years ago.
21
Hence, the intercept contains all stable cases, of which there are 33. In this phase, history can
play an intriguing role in the level of satisfaction the reseller ekes out of a declining
relationship. Although movement from exploration to decline results in no noticeable impact
on the reseller’s overall satisfaction, movement to the decline phase from build-up (.66) or
maturity (.39) can have a significant impact on reseller satisfaction with the relationship. The
trustworthiness of the supplier sales representative also bolsters satisfaction (.28).
Discussions and Conclusions
These results consistently indicate that mature relationships are not usually the
pinnacle of relationship development. They are relationships, and they do not fit the DSO's
description of discrete contracting. The parties work together, share a time horizon, and think
beyond the current deal. Yet, frequently, maturity in these dyads is no better than build-up
and is often marginally inferior. This finding accords with the general conclusions of Cannon
and Perreault (1999), who also find that domesticated markets (long term relationships) need
not be close in relational terms. As they put it (Cannon and Perreault 1999, p. 456), "if
relationships meet customer needs, they are likely to endure, no matter how closely
connected." They argue that buyers and sellers are rather unlikely to select the optimal type
of relationship for their circumstances. Instead, the actors improvise, and the successful ones
find only vaguely right solutions.
Our results indicate the surprising adequacy of an
enforcement mechanism that is seldom mentioned in the relational contracting literature: the
exigencies of the customer.
The lack of empirical differences in relationship properties between the build-up and
maturity phase correspond with the viewpoint of Rousseau et. al. (1998), who stress that
much of trust-building in commercial relationships is really re-building from a prior set of
transactions. The boundaries between build-up and maturity may blur, particularly after the
dyad builds a history and develops trust, harmony, a comparison level of alternatives, and a
level of satisfaction. To this end, Rousseau et. al. (1998) simplifies the development of
22
trusting relationships to only three stages: building (forming or re-forming), stability, and
dissolution.
Broadly, this scheme corresponds to exploration, expansion/maturity, and
dissolution/decline.
It is worth emphasizing that the decline of the relationship properties in the premature
peak group and the plateau group is steep, such that relationship properties in decline are
lower than in any other stage. This steep difference may occur because progression in the
relationship (from exploration to build-up to maturity) and decline differ in several important
ways.
Relationship progression requires two parties, each making an effort, while
relationship breakdown only requires one party to provoke deterioration.
Relationship
progression involves the creation of a shared history, while relationship breakdown entails
managing the effects of a shared history. Relationship progression focuses on joint growth
and closeness, while relationship breakdown fosters individual survival and distance.
Relationship progression may involve unambiguous announcements of intention to invest in
and expand the relationship, while relationship breakdown may feature subtle, ambiguous
attempts to undermine the relationship. In short, progression occurs against a backdrop of
joint context and is mutual, effortful, and relatively transparent.
Decline has the opposite
properties; it is a separate phenomenon, unique in its own right, and deserving of more
systematic research and attention.
This study only concerns ongoing relationships, precluding examination of the
awareness phase.
Larson's (1992) case studies of relationships that became close and
successful fill this gap. Larson concludes (p. 100) that "these partnerships cannot and should
not last indefinitely. Instead, a more accurate picture is that of firms moving in and out of
relatively stable networks over time." Her findings concur with the many cases of restart,
reconsideration, or renewal that appear in our data.
Larson also finds a number of
relationships that failed to live up to the lofty expectations of the build-up phase, yet settled
into being solid, strong, enduring relationships. This result coincides with our finding that
23
build-up and maturity, although distinguishable to our informants, differ little in terms of
properties the relationships have actually achieved.
If firms do move in and out of networks over time, can they do so without friction? A
strictly economic analysis would suggest that they should be able to reconfigure freely. If
indeed "business is business," then firms should easily be able to renew relationships that
have fallen into decline as circumstances and calculations of advantage change. Our results
suggest that this is not the case. The reseller is significantly less satisfied with relationships
that had gone into decline and were then pulled back to build-up or maturity. It appears that
these relationships do not enjoy a fresh start. Rather than "wiping the slate clean" and starting
over, the organizations in these once-damaged relationships appear to carry over some of the
negativity of their decline phase. This evidence suggests that the "psychological scars" which
DSO posits are indeed real and enduring. Scars are consistent with the findings of Anderson
and Weitz (1992), who find that organizations doubt their counterpart's current commitment
when the relationship has a conflictual history. A meta analysis by Cohen-Charash and
Spector (2001) suggests a mechanism: organizational actors see procedural and distributive
injustice in troubled relationships. We find that history matters: the outcome of today's
mature or built-up relationship depends on the path taken to reach this phase of development.
This research indicates that declining relationships can linger for long periods, with
neither side terminating the relationship.
Ping (1993) offers insight into how this
phenomenon occurs. Perpetually-in-decline channel relationships are not hostile. Instead, at
least one side simply neglects the other, a passive reaction that Hirschman (1970) labels the
“loyalty” response to a disappointing inter-organizational relationship. Why doesn’t someone
end the relationship? Ping (1993) shows that idiosyncratic investments incite the firms not to
terminate their arrangement. This result is consistent with our finding that idiosyncratic assets
are long lasting and that they remain at high levels during the decline phase. Hibbard, Kumar,
and Stern (2001) show that loyalty is a common channel reaction, even in the face of a
24
destructive act by the supplier. A reseller often tolerates a disappointing relationship if the
supplier has substantial brand equity, which is the case in our setting.
The reseller
compensates by shifting resources to other brands or product categories, rather than by
terminating the supplier.
Negative relationships come at the price of low reseller satisfaction, only partially
offset by the efforts of trusted salespeople. We find that the better performers in declining
relationships are those which have managed to achieve a much more positive state—either
build-up or maturity—five years earlier. Those relationships that had managed to build
something appear to fare better than relationships that have stagnated, staying in decline for a
very long period.
This suggests that successful relationship building creates a positive
momentum that carries forward. Thus, even in decline, organizations extract some additional
satisfaction from those relationships that once were strong. Even in decline, history matters:
the path taken influences the results achieved.
This research also informs our understanding of the role of interpersonal relations in
the development of successful inter-organizational relationships.
In the management
literature, awareness grows of the need to consider both individual and organizational level
factors of inter-organizational relationships (House, Rousseau, and Thomas-Hunt 1995),
although the theoretical basis for combining interpersonal and inter-organizational factors is
still debated. Some scholars contend that the interpersonal relationships formed between
organizational boundary spanners plays a critical role in the development of interorganizational exchange and relationship development (Larson 1992). Others maintain that
organizational relationships and strategies develop independently of the individuals in these
positions (Ogilvy 1995; Williamson 1996).
Our research supports the importance of one individual in a key role.
The
development of interpersonal trust via sales representatives considerably strengthens the
reseller’s overall satisfaction with the relationship throughout the course of the customer life
25
cycle. DSO focuses on the development of relationships involving groups of employees, and
does not single out any one function. But these results suggest that the salesperson is a
particularly important player. The cultivation of trust in the sales representative bolsters
satisfaction, even in the decline stage. The salesperson yields a noteworthy impact even
allowing for the stage of the relationship and the path taken to reach this stage.
The
development of new information technologies, particularly the Internet, has led some
observers to conclude that personal selling will decrease in importance.
These results,
however, show that even stable, well-developed relationships perform substantially better
when a trusted individual represents the supplier.
Limitations
The research is not without its limitations. One limitation might be the reliance on a
common method, the use of a paper survey for measuring the conceptual model. To this end,
respondents were not told the specific purpose and interest of the research, only that it
concerned their relationship with a particular supplier. An effort was also made to intersperse
the items throughout the survey so that it would be impossible for respondents to determine
the precise constructs of interest and their expected relations to each other.
Another limitation might arise from the fact that the lag in the movement analysis was
five years as opposed to a shorter time frame. However, we made an informed selection of
this lag period: pretest efforts indicated that this time period was appropriate for possibly
observing movement from one phase to another. At the time of the data collection, the
industry and the development of reseller relationships within it were relatively stable.
26
Managerial Implications
The notion of a relationship life cycle provides a powerful reminder that relationships
are dynamic phenomena that systematically change in their composition and nature over time.
By recognizing and understanding these changes, managers can better develop relationship
strategies best suited to their phase of development.
The research also suggests that how the relationship develops over time is critically
important to performance. Relationships that develop along a typical life cycle will produce
higher levels of satisfaction than those in decline and reconfigured to upgrade to a build-up or
maturity phase. In other words, it is best to prevent entering the decline phase, because the
scars incurred in this phase heal slowly and affect subsequent overall satisfaction in the
relationship. On the other hand, it may be better to dissolve a relationship than allow the
participants to “marinate” in a decline phase for an extended period of time. By recognizing
quickly that the relationship is incompatible or inoperable, it is better for firms to cut the ties
between them and go on to new relationships than to allow an inferior exchange to persist.
Directions for Future Research
Much remains to be explored and understood in regard to relationship dynamics. For
example, one under-explored area involves the drivers that transition the relationship from
one phase to the next. What factors move the relationship from an exploratory phase into
build-up? Similarly, what motivates firms to move from awareness to exploration? Are the
circumstances that drive these changes a function of the internal needs of the firm, the
competitive landscape, or are they dually created between the organizational participants?
Another important research direction is better understanding how firms can manage
the decline phase of the relationship.
Perhaps the psychological scars and acrimonious
interactions that typify this stage can be minimized by building appropriate safeguards and by
better managing expectations in earlier phases. Another research priority in this area includes
better understanding of the dissolution process. What motivates one organization to begin
27
dissolution activities? At what point do these activities become obvious? How does the
counterpart respond to such actions? These are the questions for the future.
The relationship life cycle is a useful metaphor for better understanding how
relationships begin, evolve, and dissolve over time.
On the whole, the DSO theory of
relationship development holds: one or two sentences allow the observer to predict relative
levels of many states of the channel. However, results also indicate that relationships do not
inexorably progress to a state of peak functioning and performance. The expectations of the
partners in the relationship-building process often turn out to be too ambitious. Anticipations
of continuing performance improvement and extremely close relationships appear not to be
realized in many channel relationships.
Furthermore, partners cannot disregard history.
Allowing a relationship to enter decline imposes costs that are realized when the relationship
is "restarted": a negative history exacts its price.
28
Figure 1
Conceptual Overview
RelationshipHistory
Movement Through Phases
• Restart
• Save
• Reconsider • Decline
• Renewal
RelationshipPhase
Relationship Outcome
Current Phase
• Exploration • Maturity
• Buildup
• Decline
Overall Satisfaction
with the
Relationship
Individual Salesrep
Reseller Trust
in the Salesrep
29
Figure 2
Premature Peaks
5.50
Goal Congruence
5.00
Information Exchange
Norms
4.50
4.00
Satisfaction with
Manufacturer
Products
3.50
De
cli
ne
at
ur
it y
M
Bu
il d
up
Ex
plo
ra
t io
n
3.00
30
Figure 3
Plateau Effects
Relationship
Harmony
7.50
Overall Dependence
6.50
Bilateral Idiosyncratic
Investments
5.50
Reseller's Trust in the
Manufacturer
4.50
Willingness to take
Risks
3.50
Satisfaction with
Financial Returns
De
cli
ne
at
ur
it y
M
Bu
ild
up
Ex
pl
o
ra
t io
n
2.50
31
Outcomes Given
Comparison Level of
Alternatives
Figure 4
Investments and Alternatives
5.00
Idiosyncratic Time
Investments*
4.50
4.00
Idiosyncratic
Adaptation
Investments
3.50
3.00
Number of Seriously
Considered
Alternatives
2.50
2.00
De
cli
ne
at
ur
it y
M
Bu
il d
up
Ex
pl
o
ra
t io
n
1.50
32
Table 1
Movement Across Relationship Phases
Exploration Build-up Maturity
(A)
(B)
Decline
(C)
Total
Current relationship phase
126
281
569
380
1356
Relationship phase 5 years ago
165
558
490
143
1356
No change over 5 years
33
108
243
33
417
Movement over 5 years
Followed DSO Pattern
Exploration to Build-up
Exploration to Maturity
Build-up to Maturity
Decline from Exploration (D)
Decline from Build-up (E)
Decline from Maturity (F)
Total
71
30
268
31
143
173
716
Followed Aberrant Pattern (G)
Save (to Maturity) (H)
28
Save (to Build-up) (H)
53
Restart (to Exploration) (I)
29
Reconsider (from Maturity) (J)
25
Reconsider (from Build-up) (J)
39
Renewal (from Maturity) (K)
49
Total
223
- The numbers depict the number of observations in each phase or path of movement.
- The arrows illustrate the apparent path of movement over a five-year period.
- The following terms correspond to dummy variables in the analysis of path
dependence influencing reseller overall satisfaction:
(A)
Build-up
(B)
Maturity
(C)
Decline
(D)
Exp_Dec
(E)
Build_Dec
(F)
Matur_Dec
(G)
Move
(H)
Save
(I)
Restart
(J)
Reconsider
(K)
Renewal
33
Table 2A
Construct Means, Standard Deviations, and Correlation Matrix for Phase Analysis
Construct
Mean
1 Goal Congruence
4.36
2 Relationship Harmony
4.76
3 Information Exchange Norms
4.84
4 Overall Dependence
7.23
5 Bilateral Idiosyncratic Investments
4.41
6 Idiosyncratic Time Investments
4.27
7 Idiosyncratic Adaptation Investments
3.64
8 Reseller's Trust in the Manufacturer
4.37
9 Reseller's Trust in the Salesrep
5.12
10 Willingness to Take Risks
3.82
11 Satisfaction with Financial Returns
3.51
12 Satisfaction with Manufacturer Products
4.13
13 Outcomes Given Comparison Level of Alternatives 4.08
14 Number of Seriously Considered Alternatives
2.15
All correlations greater than .04 are significant at a=.001
SD Min Max 1
2
3
4
5
6
7
8
9
10
1.34 1
7 1.00
1.54 1
7 0.69 1.00
1.03 1
7 0.55 0.48 1.00
1.96 2 12.8 0.24 0.15 0.25 1.00
1.11 1
7 0.47 0.35 0.58 0.43 1.00
1.32 1
7 0.23 0.11 0.29 0.25 0.52 1.00
1.39 1
7 0.20 0.09 0.24 0.30 0.49 0.69 1.00
1.24 1
7 0.73 0.72 0.55 0.26 0.43 0.16 0.12 1.00
1.25 1
7 0.59 0.56 0.58 0.24 0.46 0.20 0.16 0.66 1.00
1.43 1
7 0.47 0.36 0.47 0.30 0.58 0.34 0.34 0.44 0.39 1.00
1.31 1
7 0.63 0.58 0.36 0.11 0.27 0.06 0.03 0.61 0.42 0.30
1.13 1
7 0.58 0.55 0.46 0.48 0.51 0.27 0.24 0.61 0.48 0.45
1.34 1
7 -0.57 -0.53 -0.44 -0.27 -0.41 -0.22 -0.20 -0.58 -0.51 -0.39
1.76 0
20 -0.18 -0.21 -0.16 -0.14 -0.14 -0.04 -0.04 -0.22 -0.21 -0.12
Table 2B
Construct Means, Standard Deviations, and
Correlation Matrix for Movement Analysis
1
2
Construct
Reseller Trust in the Salesrep
Overall Satisfaction
Mean SD Min Max 1
2
5.14 1.26
1
7
1.00
4.22 1.46
1
7
0.63 1.00
34
11
12
13
14
1.00
0.49 1.00
-0.53 -0.55 1.00
-0.15 -0.22 0.22 1.00
Table 3
Means Across Phases
Variable
Exploration
Buildup
Maturity
Decline
(a) Goal Congruence
4.01
5.06
4.82
3.15
(b) Relationship Harmony
4.31
5.52
5.38
3.31
(c) Information Exchange Norms
4.61
5.25
5.07
4.22
(d) Overall Dependence
6.97
7.63
7.49
6.58
(e) Bilateral Idiosyncratic Investments
4.13
4.76
4.62
3.89
(e) Idiosyncratic Time Investments*
4.13
4.55
4.33
3.99
Idiosyncratic Adaptation
(e) Investments
3.38
4.00
3.66
3.40
4.04
4.91
4.86
3.25
(g) Willingness to take Risks
3.61
4.29
4.09
3.09
(h) Satisfaction with Financial Returns
3.09
3.93
3.92
2.66
(i)
Satisfaction with Manufacturer
Products
4.00
4.63
4.45
3.25
(j)
Outcomes Given Comparison Level
of Alternatives
3.57
4.44
4.34
2.94
2.19
1.94
1.93
2.65
(f)
Reseller's Trust in the Manufacturer
Number of Seriously Considered
(k) Alternatives
Row means with no significant differences are indicated by a single or double underscore.
* The thick underscore indicates that the column mean is not significantly different from the
row means with a single or double underscore.
35
Table 4
Summary of Results
OVERALL
SATISFACTION
Coefficient
Adj
R-Sq
Err
Std
Estimate
ALL PHASES (n=1356)
Intercept
.59
1.47***
Aberrant movement
-.18**
Build
1.04***
Mature
.90***
Decline
-.69***
Reseller Trust in the Rep
.46***
EXPLORATION (n=126)
Intercept
.14
1.60***
Restart
-.05
Reconsider
.26
Reseller Trust in the Rep
.39***
BUILD-UP (n=281)
Intercept
.30
1.74***
Save
-.32***
Renewal
-.02
Reseller Trust in the Rep
.60***
MATURITY (n=569)
Intercept
.39
1.32***
Save
-.45***
Reseller Trust in the Rep
.66***
DECLINE (n=380)
Intercept
.16
1.10***
Exploration to Decline
.23
Build-up to Decline
.66***
Maturity to Decline
.39**
Reseller Trust in the Rep
.28***
* a=.10, **a=.05, ***a=.01
Adj R-Sq is the adjusted R-squared for the regression.
36
.16
.09
.11
.11
.12
.02
.37
.29
.24
.08
.33
.13
.13
.06
.21
.17
.04
.23
.25
.20
.19
.04
Appendix
Measures and Reliabilities
All scales are measured using 7-point scales in which 1=strongly disagree and 7=strongly agree.
Relationship Harmony (adapted Kumar, Stern and Achrol 1992)
The relationship between this supplier and us can best be described as tense. (R)
We have significant disagreements in our working relationship with this supplier. (R)
We frequently clash with this supplier on issues relating to how we should conduct our business. (R)
a=.83
Reseller Trust in the Supplier (adapted from Jap 1999)
a=.90
Even when this supplier gives us a rather unlikely explanation, we are confident that they are telling the truth.
This supplier usually keeps the promises they make to our firm.
Whenever this supplier gives us advice on our business operations, we know they are sharing their best judgment.
We believe that this supplier is honest in their dealings with us.
When making important decisions, this supplier is concerned about our welfare.
We trust this supplier to deal fairly with us.
Goal Congruence (adapted from Jap 1999)
We share the same goals in the relationship as this supplier.
Both firms have compatible goals.
We support each other's sales and profits objectives.
Our goals differ from this supplier's goals considerably. (R)
a=.84
Information Exchange Norms (adapted from Heide and John 1992; Dwyer and Oh 1987)
a=.73
In this relationship, it is expected that any information that might help the other party will be provided to them.
Information is informally exchanged in this relationship.
It is expected that we keep each other informed about events or changes that may affect the other party.
Exchange of information in this relationship takes place frequently.
Willingness to Take Risks
We are willing to take risks on behalf of this supplier.
We are willing to take chances on this supplier's behalf.
We are willing to go out on a limb for this supplier.
a=.88
Reseller’s Dependence on the Supplier (adapted from Jap and Ganesan 2000)
a=.84
If our relationship were discontinued with this supplier, we would have difficulty making up the sales volume in
our trading area.
It would be difficult for us to replace this supplier.
We are quite dependent on this supplier.
We do not have a good alternative to this supplier in our trading area.
Supplier’s Dependence on the Reseller (adapted from Jap and Ganesan 2000)
a=.69
If we discontinued our relationship with this supplier, they would have difficulty making up the sales volume in
our trading area.
It would be difficult for this supplier to replace us.
This supplier is quite dependent on us.
This supplier does not have a good alternative to us in our trading area.
Note: Overall Dependence is the sum of Reseller’s Dependence on the Supplier and the Supplier’s Dependence
on the Reseller.
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Idiosyncratic Time Investments (adapted from Cannon 1992)
Just for this supplier, we have invested time in…
developing new information systems.
learning their products.
learning their procedures.
training our employees.
a=.86
Idiosyncratic Adaptation Investments (adapted from Cannon 1992)
a=.90
Your firm may have made investments in time, energy and/or money specifically to accommodate this supplier
and its products. These investments would be lost if your firm switched to another supplier. Please indicate the
extent to which your firm has made investments or changes specifically to accommodate this supplier. (1=none,
7=a great deal)
Just for this supplier, we have changed our…
product requirements.
sales personnel.
inventory and distribution procedures.
merchandising policies.
retailing strategy.
information systems.
capital equipment and tools.
Bilateral Idiosyncratic Investments (adapted from Anderson and Weitz 1992)
a=.78
We have made a substantial investment in personnel dedicated to this supplier's product line.
We have invested a great deal in building up this supplier's business.
If this relationship were to end, we would be wasting a lot of knowledge regarding this supplier's products and
procedures.
If either company were to switch to a competitive or supplier, they would lose a lot of investments made in the
present relationship.
This supplier has invested a great deal in this relationship.
a=.87
Outcomes Given Comparison Level of Alternatives
How attractive is this supplier compared to your next best alternative supplier in terms of: (1=much less attractive,
7=much more attractive).
Generating sales
Generating profits
Providing support and selling services
Number of Seriously Considered Alternatives
Of the alternative suppliers who could provide you with the products and services that this supplier provides, how
many do you seriously consider when making a purchase order?
Satisfaction with Financial Returns (adapted from Ruekert and Churchill 1984)
On an average, the margins on this supplier's products are lower than the industry. (R)
This supplier provides competitive margins on their products.
Some of this supplier's products aren't worth carrying because of their low margins. (R)
We are happy with the margins we receive on this supplier's products.
We are satisfied with the margins on this supplier's products
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a=.88
Satisfaction with Supplier Products (adapted from Ruekert and Churchill 1984)
This supplier's products are in high demand with our customers.
This supplier's products are a good growth opportunity for our firm.
This supplier's products perform much better than the competition.
a=.71
Reseller Trust in the Representative (adapted from Jap 2001)
This representative…
has been frank in dealing with us.
makes reliable promises.
does not make false claims.
is honest about problems that may arise.
has made sacrifices for us in the past.
cares for us.
has gone out on a limb for us in times of shortages.
is like a friend.
has been on our side.
a=.95
Reseller's Overall Satisfaction with the Relationship (adapted from Kumar, Stern and Achrol 1992; Ruekert and
Churchill 1984)
a=.94
Our association with this supplier has been a successful one.
This supplier's performance leaves a lot to be desired from an overall standpoint. (R)
Taking all the different factors into account, this supplier's performance has been excellent.
Overall, the results of our relationship with this supplier have fallen far short of our expectations. (R)
We are satisfied with the relationship we have with this supplier.
We are displeased with our relationship with this supplier. (R)
Our relationship with this supplier has more than fulfilled our expectations.
39
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Endnote
i
Interviews with informants in the research context indicated that a five-year time period was
a typical time frame in which relationships may develop from one phase to another.
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