Testing tOrganizatio

Outcome

Faculty & Research

he Life-Cycle Theory of Inter-nal Relations: Do Performance s 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 *** John H. Loudon Chaired Professor of Goizueta Business School International Management and Professor Emory University of Marketing 1300 Clifton Road INSEAD Atlanta, GA 30324 Boulevard de Constance USA 77305 Fontainebleau Cedex, FRANCE sandy_jap@bus.emory.edu erin.anderson@insead.edu 404-727-7056 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-of-

development 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

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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.

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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 postage-

paid 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

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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 supplier-

specific 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 = �1 + �8 Move + �9 Build-up + �10 Maturity + �11 Decline + ����RepTrust

19

Exploration: SAT = �3 + �20 Restart + �21 Reconsider + �22 RepTrust Build-up: SAT = �5 + �31 Save + �32 Renewal + �33 RepTrust Maturity: SAT = �7 + �41 Save + �42 RepTrust Decline: SAT = �9 + �52 Exp_Dec + �53 Build_Dec + �54 Matur_Dec + �55 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 inter-

organizational 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

Movement Through Phases• Restart • Save• Reconsider • Decline• Renewal

Relationship History

Reseller Trustin the Salesrep

IndividualSalesrep

Overall Satisfaction with the

Relationship

Relationship Outcome

Current Phase• Exploration • Maturity• Buildup • Decline

Relationship Phase

Movement Through Phases• Restart • Save• Reconsider • Decline• Renewal

Relationship History

Movement Through Phases• Restart • Save• Reconsider • Decline• Renewal

Relationship History

Reseller Trustin the Salesrep

IndividualSalesrep

Overall Satisfaction with the

Relationship

Relationship Outcome

Overall Satisfaction with the

Relationship

Relationship Outcome

Current Phase• Exploration • Maturity• Buildup • Decline

Relationship Phase

Current Phase• Exploration • Maturity• Buildup • Decline

Relationship Phase

29

Figure 2 Premature Peaks

3.00

3.50

4.00

4.50

5.00

5.50

Explor

ation

Buildu

p

Maturity

Declin

e

Goal Congruence

Information ExchangeNorms

Satisfaction withManufacturerProducts

30

Figure 3 Plateau Effects

2.50

3.50

4.50

5.50

6.50

7.50

Explorat

ion

Buildu

p

Maturity

Decline

RelationshipHarmony

Overall Dependence

Bilateral IdiosyncraticInvestments

Reseller's Trust in theManufacturer

Willingness to takeRisks

Satisfaction withFinancial Returns

Outcomes GivenComparison Level ofAlternatives

31

Figure 4 Investments and Alternatives

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

Explor

ation

Buildu

p

Maturity

Declin

e

Idiosyncratic TimeInvestments*

IdiosyncraticAdaptationInvestmentsNumber of SeriouslyConsideredAlternatives

32

Table 1 Movement Across Relationship Phases

Exploration Build-up Maturity Decline Total (A) (B) (C)

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 71 Exploration to Maturity 30 Build-up to Maturity 268 Decline from Exploration (D) 31 Decline from Build-up (E) 143 Decline from Maturity (F) 173 Total 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 SD Min Max 1 2 3 4 5 6 7 8 9 10 11 12 13 141 Goal Congruence 4.36 1.34 1 7 1.002 Relationship Harmony 4.76 1.54 1 7 0.69 1.003 Information Exchange Norms 4.84 1.03 1 7 0.55 0.48 1.004 Overall Dependence 7.23 1.96 2 12.8 0.24 0.15 0.25 1.005 Bilateral Idiosyncratic Investments 4.41 1.11 1 7 0.47 0.35 0.58 0.43 1.006 Idiosyncratic Time Investments 4.27 1.32 1 7 0.23 0.11 0.29 0.25 0.52 1.007 Idiosyncratic Adaptation Investments 3.64 1.39 1 7 0.20 0.09 0.24 0.30 0.49 0.69 1.008 Reseller's Trust in the Manufacturer 4.37 1.24 1 7 0.73 0.72 0.55 0.26 0.43 0.16 0.12 1.009 Reseller's Trust in the Salesrep 5.12 1.25 1 7 0.59 0.56 0.58 0.24 0.46 0.20 0.16 0.66 1.0010 Willingness to Take Risks 3.82 1.43 1 7 0.47 0.36 0.47 0.30 0.58 0.34 0.34 0.44 0.39 1.0011 Satisfaction with Financial Returns 3.51 1.31 1 7 0.63 0.58 0.36 0.11 0.27 0.06 0.03 0.61 0.42 0.30 1.0012 Satisfaction with Manufacturer Products 4.13 1.13 1 7 0.58 0.55 0.46 0.48 0.51 0.27 0.24 0.61 0.48 0.45 0.49 1.0013 Outcomes Given Comparison Level of Alternatives 4.08 1.34 1 7 -0.57 -0.53 -0.44 -0.27 -0.41 -0.22 -0.20 -0.58 -0.51 -0.39 -0.53 -0.55 1.0014 Number of Seriously Considered Alternatives 2.15 1.76 0 20 -0.18 -0.21 -0.16 -0.14 -0.14 -0.04 -0.04 -0.22 -0.21 -0.12 -0.15 -0.22 0.22 1.00

All correlations greater than .04 are significant at �=.001

Table 2B Construct Means, Standard Deviations, and Correlation Matrix for Movement Analysis

Construct Mean SD Min Max 1 2

1 Reseller Trust in the Salesrep 5.14 1.26 1 7 1.002 Overall Satisfaction 4.22 1.46 1 7 0.63 1.00

34

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

(e)Idiosyncratic Adaptation Investments 3.38 4.00 3.66 3.40

(f) Reseller's Trust in the Manufacturer 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

(k)Number of Seriously Considered Alternatives 2.19 1.94 1.93 2.65

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

Adj Std Coefficient R-Sq Estimate Err ALL PHASES (n=1356) Intercept .59 1.47*** .16 Aberrant movement -.18** .09 Build 1.04*** .11 Mature .90*** .11 Decline -.69*** .12 Reseller Trust in the Rep .46*** .02

EXPLORATION (n=126) Intercept .14 1.60*** .37 Restart -.05 .29 Reconsider .26 .24 Reseller Trust in the Rep .39*** .08

BUILD-UP (n=281) Intercept .30 1.74*** .33 Save -.32*** .13 Renewal -.02 .13 Reseller Trust in the Rep .60*** .06

MATURITY (n=569) Intercept .39 1.32*** .21 Save -.45*** .17 Reseller Trust in the Rep .66*** .04

DECLINE (n=380) Intercept .16 1.10*** .23 Exploration to Decline .23 .25 Build-up to Decline .66*** .20 Maturity to Decline .39** .19 Reseller Trust in the Rep .28*** .04

* ��.10, **���05, ***��.01 Adj R-Sq is the adjusted R-squared for the regression.

36

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) �=.83 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) Reseller Trust in the Supplier (adapted from Jap 1999) �=.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) �=.84 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) Information Exchange Norms (adapted from Heide and John 1992; Dwyer and Oh 1987) �=.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 �=.88 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. Reseller’s Dependence on the Supplier (adapted from Jap and Ganesan 2000) �=.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) �=.69 If we discontinued our relationship with this supplier, they would have difficulty making up the sales volume inour 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) �=.86 Just for this supplier, we have invested time in… developing new information systems. learning their products. learning their procedures. training our employees. Idiosyncratic Adaptation Investments (adapted from Cannon 1992) �=.90 Your firm may have made investments in time, energy and/or money specifically to accommodate this supplierand its products. These investments would be lost if your firm switched to another supplier. Please indicate theextent 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) �=.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 andprocedures. If either company were to switch to a competitive or supplier, they would lose a lot of investments made in thepresent relationship. This supplier has invested a great deal in this relationship. Outcomes Given Comparison Level of Alternatives �=.87 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, howmany do you seriously consider when making a purchase order? Satisfaction with Financial Returns (adapted from Ruekert and Churchill 1984) �=.88 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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Satisfaction with Supplier Products (adapted from Ruekert and Churchill 1984) �=.71 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. Reseller Trust in the Representative (adapted from Jap 2001) �=.95 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.

Reseller's Overall Satisfaction with the Relationship (adapted from Kumar, Stern and Achrol 1992; Ruekert and Churchill 1984) �=.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.

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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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