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A model of channel member performance, dependence, and satisfaction.

A Model of Channel Member Performance, Dependence, and Satisfaction

Unlike channel member satisfaction, performance and dependence have

not been subjected to much empirical scrutiny even though they are

variables of critical concern to channel managers. This paper presents

a model of the interrelationship of these three constructs and reports the

findings of a test of the model in a franchise system. The study showed

that financial dependence influences the degree to which franchisees

meet performance goals prescribed by the franchisor. In addition, it

showed that performance leads to satisfaction with the franchisor's

performance and yields positive consequences for the relationship.

Satisfaction, however, is moderated by the amount of credit or blame

franchisees assign to the franchisor for the franchisees' performance.


Channel member dependence and performance are two constructs of critical concern to channel managers. Performance is certainly the variable of utmost concern to managers, and dependence is an important determinant of one firm's ability to influence its channel partner's performance (Frazier et al. 1989). Although the rationale commonly given for many channel studies is management's desire to influence a channel partner's perceptions, decisions and performance, most studies have not included performance (Gaski 1984). Instead, empirical research has addressed behavioral variables like power and conflict without evaluating the relationship between these variables and performance. Similarly, dependence has not been the subject of many channel studies (Frazier et al. 1989).

Channel member satisfaction, however, has provided the focus for many studies; often in tandem with power and conflict (Gaski 1984). Given the economic basis for channel relationships and the interdependence of the parties involved, however, it seems unlikely that practitioners harbor much concern with satisfaction except as it relates to performance, dependence, and other key variables. Even so, no empirical studies have been reported that investigate the interrelationship between these three variables. The purpose of this research, therefore, is to empirically test a model of the relationships among channel member performance, dependence, and satisfaction.


In a channels context, dependence refers to one firm's need to maintain a relationship with another firm in order to achieve desired goals. Dependence has been widely recognized as the inverse of power. That is, if firm A is highly dependent on firm B, then presumably firm B has a great deal of power over A (Aldrich 1979; Emerson 1962; Frazier 1983a). Power has been defined as the ability to influence another to do something they otherwise would not do (see Gaski 1984 for a complete review). Frazier and Summers (1984) draw a distinction between two forms of influence--an attempt to influence and achieved influence. The ultimate manifestation of achieved influence is that the target firm performs up to standards devised by the source firm (Frazier 1983a; Gaski 1984).

Several studies have found a positive relationship between intermediary dependence and perceptions of the source firm's influence (Anderson and Narus 1990; Kale 1986; Skinner and Guiltinan 1985). Additionally, a study by Anderson et al. (1987) showed a weak relationship between intermediary dependence and the time allocated to the source firm in a conventional channel. This last finding suggests that independence leads to greater achieved influence but does not directly address the issue of performance.

This notwithstanding, there is considerable theoretical support for the notion that a firm's dependence on another firm in the channel encourages it to perform at a higher level than if such dependence were lacking (Frazier 1983a; Homans 1974; Robicheaux and El-Ansary 1975). High dependence upon the relationship encourages high performance for two reasons. First, the need for a dependent participant's self-preservation leads to higher performance in order to maintain the economic status already achieved from the channel relationship. Financial dependence is based on the percentage of assets invested in, and the income derived from the business. High financial dependence essentially means that an organization (or individual owner, which is typically the case in a franchise system) may depend on the partnership for its very survival. There is no need more basic than survival. Thus, it is logical to posit that high financial dependence motivates an intermediary to work very hard to achieve top performance. Because channel participants perform complementary roles, a firm's success depends on its own performance and its partner's performance. A high level of performance, therefore, is crucial to preserve each firm's financial well being.

But organizations or individual owners do not join channel systems in order to survive. They enter into the relationship because they expect to reap economic gains. Therefore, the second reason that a high level of financial dependence leads to high performance is self-enrichment. Firms join together in channel relationships for mutual economic gain. The gain derives from each participant shouldering responsibility for specific tasks that facilitate efficient movement and exchange of product. Thus, a high performance level serves to enlarge a channel participant's gains from the relationship (Stern and El-Ansary 1977).

Empirical findings may, however, be determined by the type of channel system under investigation (Kale 1986). Sociological, organizational behavior, and marketing research suggests that context or situation is likely to have a significant impact on the existence and/or functioning of exchange relationships (Frazier et al. 1989). These findings make it important for channel researchers to develop theory with a particular channel context in mind. The relationship between dependence and performance suggested herein is particularly applicable to a franchise system.

Indeed, the basic motivation for entering into franchise agreements is to reduce the risk of failure and/or increase the financial rewards associated with owning a business (Bernstein 1968-1969). Well-defined roles and an acknowledged leader are characteristic of a franchise system with significant legitimate authority vested in the franchisor. In return for the use of a franchisor's trademark and business format, a franchisee accepts some level of financial dependence and is legally bound to meet certain performance obligations established by the franchisor. These obligations extend to both financial and nonfinancial performance, often encompassing operations, personnel, marketing decisions, and profitability. Also, knowledge of a franchisor's ability to police franchisee performance and to terminate the contract of nonperforming franchisees, further motivates franchisees to perform. The franchisee is motivated to meet these performance obligations both to preserve its present status and to improve upon it (Walker and Cross 1988).

Even when franchisees have the legal right to make their own decisions, they often defer to the franchisor. A study of the decision-control process in a franchise system showed that franchisees often expect greater success if they depend on the franchisor's decisions than if they retain decision control (Anand and Stern 1985). These authors report that when franchisees have higher performance expectancies for the franchisor, they expect greater success if they rely on the franchisor's decisions. Franchisees expect good performance to pay off because they understand that their performance obligations, shaped by the franchisor's business knowledge and experience, are designed to yield mutual benefits. Of course, it should be noted that if a franchisee meets its goals through good performance its dependence may increase, especially if it lacks other attractive business opportunities. Even so, it is clear that the franchisee's dependence provides a strong motivation to perform.

Dependence should also influence a franchisee's decision to reinvest funds in the business. Periodic investments are required in any business to replace aging or obsolete assets and to help the business grow. Although other factors may come into play, a high level of financial dependence on the relationship would motivate additional investments, if only to preserve and protect the franchisee's existing income stream and assets. But asymmetrical power characterizes most franchise systems and provides the franchisor with the means to engage in opportunistic behavior--defined as "self-interest seeking with guile" (Williamson 1981).

Franchisees may engage in dependence-balancing behaviors whereby they limit subsequent investment in the franchise and take other steps to reduce their dependence on the relationship. In this way, franchisees are seen to help safeguard against opportunism by the franchisor (Heide and John 1988). Even so, the presumption is that franchisees would make some periodic investments in the business largely as a way to protect their considerable existing interest in the franchise. Such periodic investments in the business would then reinforce a franchisee's desire to perform at a high level.

Additional investments in the business would directly influence performance because the franchisee believes that good performance will enable them to earn a larger return on these investments. Thus, the size of these investments would directly affect a franchisee's motivation to perform at a high level. Additionally, reinvestment exerts an indirect influence on performance because, cumulatively, these incremental investments increase the franchisee's dependence on the relationship.

The propositions presented in the preceding section can be formally stated as the following hypotheses:

[H.sub.1]: A franchisee's level of dependence on the franchisor directly

influences the franchisee's performance.

[H.sub.1]: A franchisee's level of dependence on the franchiso directly

influences the franchisee's reinvestment in the business.

[H.sub.3]: A franchisee's level of reinvestment in the business directly

influences the franchisee's performance.

Channel member satisfaction has been widely recognized as an important influence on channel management, one that is closely related to performance (Ruekart and Churchill 1984). No empirical support has been found, however, for the hypothesis that satisfaction leads to performance (Gaski and Nevin 1985). This finding seems logical since a dissatisfied franchisee that chooses to perform at a low level erodes its own rewards.

Robicheaux and El-Ansary (1975) developed a model of channel member behavior in which they posited that a member's performance outcomes would influence the member's satisfaction with their channel partner. Frazier (1983a) conceptualized the relationship between these two variables in a similar way. Given the interdependencies inherent in a channel relationship it is logical to assume that a participant's satisfaction with its own performance influences its satisfaction with its partner's role performance. This should especially hold true for franchisees, because the franchisor is responsible for devising the franchisee's performance criteria.

It is unlikely, however, that the relationship between channel member performance and satisfaction is direct; this is because perception plays a critical role in channel relationships (Gaski 1984). Satisfaction with one's partner would depend upon the perceived contribution to the member's performance outcomes (Anand and Stern 1985; Frazier 1983a; Kelley and Michela 1980; Ruekart and Churchill 1984; Schul, Pride, and Little 1985). In a study of a convenience store franchise system, Anand and Stern (1985) found that franchisees chose the decision control option that maximized expected-performance outcomes. Often, decision control was freely given to the franchisor because the franchisees tended to associate successful outcomes with the franchisor and failure with themselves. Research in social psychology provides further empirical support for this lack of an egocentric bias in situations where mutual interests exist (Kelley and Michela 1980).

It is logical, then, to assume that franchisees will attribute some responsibility for their performance outcomes to the franchisor. Thus, a franchisee's satisfaction with the franchisor would be moderated by the amount of credit (or blame) the franchisee assigns to the franchisor. If a franchisee is satisfied with its performance outcomes, then some credit will be assigned to the franchisor. Satisfaction with and trust in the franchisor would increase as the amount of credit assigned to the franchisor increases (Kelley and Michela 1980). In contrast, if the franchisee blames the franchisor for poor performance outcomes, satisfaction with the franchisor decreases. Satisfaction, therefore, is influenced by performance outcomes but moderated by the extent to which the franchisee assigns responsibility for its performance to the franchisor. Two additional hypotheses can be suggested based on the preceding discussion:

[H.sub.4]: A franchisee's performance outcome directly influences the amount

of credit or blame the franchisee assigns to the franchisor.

[H.sub.5]: The amount of credit or blame assigned to the franchisor directly
             influences the franchisee's satisfaction with the franchisor's role

Finally, a franchisee's level of satisfaction with the franchisor's role performance should yield positive consequences for the relationship. Given the mutuality of their interests, satisfied franchisees may be more likely to perceive the franchisor as an expert, to trust the franchisor, and to cooperate with future requests (Kelley and Michela 1980). Two previous studies have provided empirical evidence that the franchisee's satisfaction with the franchisor's performance of a variety of services influences both the franchisee's overall assessment of the franchisor's role performance and the franchisee's belief that joining the system was a good decision. In a mail survey of 567 automobile dealers, Lusch (1977) found that the franchisor's performance of a set of services was an important determinant of the franchisee's overall satisfaction with the franchisor's performance. Hunt and Nevin (1974) conducted a study of 815 fast-food franchisees and reported that satisfaction with the franchisor's role performance of a set of services influences the franchisee's level of satisfaction with their initial decision to join the franchise system. Based on these findings, one might posit that a franchisee's overall assessment of the franchisor's role performance should directly influence the franchisee's assessment of its initial decision to join the franchise organization. Three additional hypotheses were formulated so that these relationships could be empirically evaluated:

[H.sub.6]: Satisfaction with the franchisor's performance of specific services

leads to overall satisfaction with the franchisor.

[H.sub.7]: Satisfaction with the franchisor's performance of specific services
             reinforces the franchisee's initial decision to join the franchise

[H.sub.8]: The franchisee's overall satisfaction with the franchisor reinforces

the franchisee's initial decision to join the franchise system.

A model of the interrelationships among channel member performance, dependence, and satisfaction proposed in these hypotheses are depicted in Figure 1.


It is customary in channels research to investigate the characteristics of a single channel system; this is because the participants in multiple channels would be likely to interpret the measures differently (El-Ansary and Stern 1972; Etgar 1976a,b; Frazier and Summers 1984; Hunt and Nevin 1974; Gaski and Nevin 1985; Lusch 197a,b, 1977; Lusch and Brown 1982; Rosenberg and Stern 1971; Ruekert and Churchill 1984; Wilkinson 1974, 1981). The data for this study were collected from a single fast-food franchise system. The firm had 229 franchises and most were owned and operated by a single individual. The franchisees varied regarding such characteristics as: number of years with the system; number of stores operated; geographical location; and education. Finally, the franchisees' contracts did not prevent them from having other businesses or jobs, and a significant number did own other businesses or had other jobs.

The content validity of many of the measures used in previous studies of channel member satisfaction, performance, and dependence was questionable. For that reason, the researchers engaged in extensive discussions with key managers in the franchisor's organization as well as with industry experts. This was done to (1) identify the business functions performed by the franchisor; (2) revise or add questions useful in measuring the constructs of interest; and (3) identify key demographics that may be useful in explaining differences in satisfaction, performance, and dependence among respondents.

In-depth interviews lasting from two to five hours were conducted with fifteen franchisees that represented a cross section of the total franchise population. These franchisees varied considerably regarding key demographics such as years with the franchise system, number of stores operated, age, education, and geographical location. The interviews were necessary for four reasons: (1) to gain knowledge about the industry and the franchise system; (2) to add, delete, and/or revise items to ensure that the list was comprehensive and meaningful to the franchisees (to provide content validity); (3) to revise the list of franchisee demographics to reflect the franchisees' input; and (4) to modify the instructions contained in the questionnaire to ensure that respondents would interpret them in the same way. The questionnaire format and layout were reviewed to confirm that the franchisees understood the interrelationships of certain tasks and to reduce the time and effort needed to complete the questionnaire. The interviews enabled the researchers to adapt items and demographic information from previous studies to the unique nuances of this channel.

The in-depth interviews resulted in five iterations of the questionnaire. Each revision reflected the findings of successive in-depth interviews. A brief description of the measures employed in the study follows.

Performance. The franchisor had a formal performance evaluation system and each franchisee was evaluated annually. Performance was evaluated in four key areas: operations, organization, financial, and upgrades/development. The franchisor assigned a performance rating to each franchisee and provided the researchers with these scores (PERFM).

Dependence. Franchisees were asked to report the percentage of their total annual income derived from the franchise (DEP$$).

Reinvestment. A single item measure of reinvestment was used. The respondents reported the percentage of profits they had reinvested for the current year (RNV$T).

Credit. Respondents were asked to distribute 100 points among three factors that may have contributed to their performance: (1) their own performance; (2) the franchisor's performance; and (3) other situational factors such as economic conditions. The factor believed to have been most instrumental in the franchisee's performance was assigned the highest number of points. The credit variable was operationalized by using the number of points assigned to the franchisor (CREDIT)--which ranged from 5 to 70 points.

Satisfaction with Multiple Dimensions of Role Performance. The multi-item, multi-dimensional measure of channel member satisfaction reflected satisfaction with the franchisor's performance of a variety of activities (SATMD). The franchisor's role performance was evaluated by using a seven-point scale ranging from 1 (Poor Performance) through 7 (Excellent Performance). Role performance was evaluated by using 117 items distributed among eight business functions as follows:
  * Product                                  26
  * Physical Distribution/Customer Service   25
  * Operations                               19
  * Promotion                                14
  * Real Estate and Construction             13
  * Pricing                                   9
  * Personnel                                 7
  * Training                                  4

Overall Satisfaction with Role Performance. Respondents were asked to mark a point on a line that best expressed their level of overall satisfaction with the franchisor's performance. The line was anchored by the words "poor" (1) and "excellent" (100). A midpoint was placed on the line to correspond to satisfactory performance (SATRL).

Satisfaction with Business Decision. A single item measure was used to assess how satisfied franchisees were with their initial decision to join the franchise system (AGAIN). Respondents indicated whether they "would do it again" by circling a number on a scale from 1 (Strongly Disagree) through 5 (Strongly Agree).

The survey instrument was a detailed 12-page questionnaire that was sent to 204 of the firm's 229 franchisees. The list was reduced to 204 as a result of duplicate listings of the same name, multiple owners of the same franchise and retirements, sales, or deaths. A total of 107 completed surveys were returned for a response rate of 52 percent. In comparison to similar studies, this was an excellent response rate and may be attributed to pre- and post-mailing phone calls. Early and late respondents were compared and no statistically significant differences (p < .05) were found. Therefore, nonresponse bias did not appear to be a problem (Armstrong and Overton 1977).

Data Analysis

Oblique centroid multiple groups analysis (MPRG), a limited information estimation procedure, was used to respecify the measurement model. Multiple groups analysis provides a confirmatory factor analysis complementary to the maximum likelihood estimates (MLE) provided by LISREL (Anderson and Gerbing 1982). As a final step, the structural model was evaluated using LISREL VI (Joreskog and Sorbom 1984). According to Bagozzi (1980), the two-step procedure "keeps the interpretation of the theoretical variables constant in the analysis and makes for a more accurate estimation of the relationships between the theoretical variables."

The measurement model was evaluated by a five-step process as follows: (1) establish content validity; (2) respecify the scales and assessed external consistency; (3) evaluate the internal consistency of the scales; (4) identify multi-dimensional constructs; and (5) create a correlation matrix of the constructs. The purpose of step one was to establish the content validity of the items that comprise the scales used in this research. The process used to establish content validity was presented earlier so this section describes the remaining four steps in the process.

Step two was undertaken to respecify the scales and to assess the external consistency of the items. The multiple groups analysis (MPRG) program in PACKAGE (Hunter and Cohen 1969; Hunter et al. 1980) was used to develop the scales. Anderson and Gerbing (1982) suggested that MPRG be employed for this purpose because it produces similarity coefficients that offer some advantages over correlation coefficients:

The problem with correlation coefficients is that they are too

general. Any two variables related by a linear transformation

correlate perfectly; but proportionality is described only by

those linear transformations with an intercept of zero. Thus an

index is needed "that does not reduce the data to deviation

scores" (Hunter 1973). The result is the similarity coefficient.

The square of this coefficient is called the "index of

proportionality" by Tryon and Bailey (1970). The value of this

index ranges from -- 1 to 1, with these extreme values

representing perfect internal and external consistency.

The usefulness of this coefficient for exploratory analysis of multiple indicator measurement models is outlined by Hunter (1973):

A matrix of indicator correlation coefficients can be

transformed into a matrix of similarity coefficients and then ordered

according to the following criterion. The first variable has the

highest sum of squared coefficients with the remaining

variables. The second variable has the highest coefficient with the

first, the third has the highest coefficient with the second, etc.

The result is an ordering of the variables with relatively large

drops in adjacent similarity coefficients indicating the cluster


All items retained for further analysis had a similarity coefficient of at least .80 with alternative items of their respective constructs. A cut-off point of .80 is the criterion suggested by Anderson and Gerbing (1982) as a useful guide when purifying measurements. The matrix of similarity coefficients also was examined to assess the parallelism or external consistency of the scale items. When the similarity coefficients for two items equals -1 or +1 the two items are perfectly parallel. Additionally, all items comprising a specific scale should exhibit similar patterns of correlations with items making up other scales (Hunter and Gerbing 1982).

In step three, the scales were subjected to confirmatory factor analysis using the MPRG routine in PACKAGE. Steps two and three were undertaken jointly in an iterative manner until the scales evidenced a high degree of external and internal consistency. Internal consistency was evaluated using the standard score coefficient alpha scores produced by the MPRG routine.

Steps two and three resulted in the identification of ten scales, one each related to channel member performance, dependence, reinvestment, franchisor credit, overall satisfaction with role performance, satisfaction with the initial business decision, and four scales representing different dimensions of the satisfaction with multiple dimensions of role performance measure. Table 1 summarizes the findings relative to the scales.


Measurement Model
                       Number     Similarity    Coefficient
Scale                 of Items   Coefficients     Alpha
PERFM                      1             --        --
DEP$$                      2            .90        .84
RNV$T                      1             --         --
CREDT                      1             --         --
AGAIN                      1             --         --
SATRL                      1             --         --
CLIMATE/INTERACTION       12        .92-.98        .92
MARKETING                 20        .92-.98        .95
PRODUCT/ACCESS            15        .93-.98        .93
OPERATION/PERSONNEL        9        .93-.98        .90

The dimensionality of the scales was the focus of step four and was evaluated by creating a matrix of the similarity coefficients of the scales. If two scales exhibited a similarity coefficient of .80 or greater, they were judged to be different dimensions of the same construct. As anticipated, the climate/interaction, marketing, product/access, and operations/personnel scales dimensions of the multi-dimensional satisfaction construct. All four scales had similarity coefficients of .80 or greater as shown in Table 2. Subsequently, the four scales were summed to form one scale and the revised set of scales was subjected to confirmatory factor analysis using the MPRG routine in PACKAGE. The MPRG routinne provided an alpha coefficient for the newly formed scale that indicated a high degree of internal consistency (alpha = .97).

The fifth step in developing the measurement model was to produce a correlation matrix of the constructs. The correlation matrix is depicted in Table 3.


Correlations Between Constructs*
SATMD     100     56      49      27       6      -6      -12
AGAIN      56    100      43      21      12     5         8
SATRL      49     43     100      34       3      -5      -1
CREDT      27     21      34     100      18      18      9
PERFM       6     12       3      18     100      28       7
DEP$$      -6      5      -5      18      28     100      15
RNV$T     -12      8      -1       9       7      15     100

*Decimals are omitted.


Before testing the structural model using LISREL VI, it was evaluated with the ordinary least squares routine in PACKAGE. Chi-squared was used to test the overall fit of the model. The customary alpha level of .10 was employed. Thus, p > .90 was interpreted as an indication of a good fit (Bagozzi 1980; Fornell and Larker 1981). The model fit the data quite well (p > 99.5). All of the path coefficients had the predicted sign and with the exception of one, the path coefficients were substantially different than zero. The path coefficient from RNV$T to PERFM was only .03. But PACKAGE does not include a test to evaluate the statistical significance of path coefficients.

As shown in Table 4, the model fit quite well when evaluated with LISREL VI. The chi-squared was 18.20 (d.f. = 13), p = .15. Other indices of fit for the theoretical model were GFI = .955, AGFI = .955, and RMR = .063. As predicted by [H.sub.1], the channel member's financial dependence had a positive impact on performance ([Gamma.sub.1] = .276, t = 2.911). The relationship between financial dependence and reinvestment, however, was direct ([Gamma.sub.2] = .150) but insignificant (not different from zero), with t = 1.555; so [H.sub.2] was rejected.


Key Parameter Estimates of the Model
                Standardized              LISREL
                  LISREL               Goodness-of-Fit
Parameter        Estimate     t-value    Measures
[Beta.sub.1]        .029       .302    [X.sup.2] = 18.20
[Beta.sub.2]        .180       1.875           p = 00.15
[Beta.sub.3]        .270       2.873       d.f.  = 13.00
[Beta.sub.4]        .490       5.760
[Beta.sub.5]        .460       5.075         GFI  = .955
[Beta.sub.6]        .205       2.261        AGFI  = .903
[Gamma.sub.1]       .276      2.911        RMSR   = .063
[Gamma.sub.2]       .150       1.555

There are several plausible explanations for this result. One explanation is that factors other than level-of-dependence affect a franchisee's decision to reinvest in the franchise. The availability of other investment opportunities would be one such factor. Franchisees may limit additional investment in the business to a level needed to protect their existing interests if more attractive investments are available. Also, because franchises are typically owned by a single individual, s/he may forgo additional investment in the business in order to satisfy personal obligations or wants, despite a high level of dependence.

Another possible explanation is that franchisees, who are often highly dependent on the franchisor, would generally be expected to engage in dependence balancing behavior. That is, a franchisee may choose not to make additional investments in the business even when reinvestment provides the best available return. This enables the franchisee to limit the potential for the franchisor to take advantage of them (Heide and John 1988). This reasoning is supported by the finding that one-third of the franchisees in this study had other jobs or businesses.

The decision to take steps to offset high dependence, however, may be based on perceived dependence rather than objective dependence. Two franchisees with the same objectively measured level of dependence may differ in their perceived dependence due to differences in such things as experience, local market conditions, personal characteristics, and circumstances. Thus, future studies that employ a measure of perceived dependence may yield more insight into the relationship between dependence and reinvestment.

Finally, the lack of support for the relationship between dependence and reinvestment may be attributable to the measure of reinvestment used. There may be a lag effect when linking dependence and reinvestment because investment opportunities may vary from year to year, and investments may vary in size. One example of a reinvestment is the purchase of an additional franchise outlet, which may require cash accumulation over several years. The level of financial dependence in one period may lead to reinvestment in latter periods. Concurrent levels of financial dependence and reinvestment, therefore, may not be strongly related.

In addition, [H.sub.3] was rejected because even though reinvestment was directly related to performance ([[Beta].sub.1] = .029) it was significant with t = .302. As with the relationship between financial dependence and reinvestment, this finding may be attributable to a measurement or methods artifact. The measure of reinvestment used in this research may be responsible for the lack of support for the relationship between reinvestment and performance, and for the same reasons mentioned above regarding dependence and reinvestment. Finally, this hypothesis may have been rejected because other important factors are not represented in the model.

[H.sub.4] predicted that performance has a positive effect on the assignment of credit or blame to one's partner and had [[Beta].sub.2] = .180 with t = 1.875. This t-value fails the two-tail test of significance (1.96), but meets the significance criterion for the one-tail test (1.645). So it is difficult to reject [H.sub.4] completely. The relationship between the franchisee's performance and the amount of credit assigned to the franchisor deserves further investigation.

Analysis at an aggregate level may obscure the true relationship between these two variables. A high performing franchisee may not attribute much credit to the franchisor, but if performance were low the franchisee may be quick to blame the franchisor. This possibility seems plausible and could be tested by dividing the respondents into two groups, high and low performing franchisees respectively, prior to testing the model. Unfortunately, small sample size prevented the authors from performing this analysis.

The amount of credit or blame assigned to one's partner was hypothesized to have a positive impact on satisfaction and [H.sub.5] was supported ([[Beta].sub.3] = .270, t = 2.873). Here satisfaction was represented by a multidimensional measure. [H.sub.6] and [H.sub.7] predicted that satisfaction with one's partner across a variety of dimensions would directly influence satisfaction with overall role performance and whether one would join this channel system again. Both hypotheses were strongly supported. [H.sub.6] had [[Beta].sub.4] = .490 with t = 5.760 and [H.sub.7] and [[Beta].sub.5] = .460 with t = 5.075. [H.sub.8] hypothesized a direct relationship between satisfaction with overall role performance and whether one would join the channel system again. [H.sub.8] was supported ([[Beta].sub.6] = .205, t = 2.261).


Six of the eight hypothesized relationships tested in this study were supported. Dependence did not appear to influence reinvestment in the hypothesized manner and, similarly, reinvestment did not influence performance. An explanation for these two findings is presented in the results section of the paper. These findings notwithstanding, the research did show that financial dependence is a determinant of performance as prescribed by the franchisor. Performance, in turn, leads to satisfaction with the franchisor's role performance, but not directly. The amount of credit or blame a franchisee attributes to the franchisor for its performance does appear to moderate the relationship between performance and satisfaction. A franchisee's satisfaction with the franchisor's performance across a wide spectrum of services influences the franchisee's overall satisfaction with the franchisor's performance. These two satisfaction variables then act as determinants of a franchisee's satisfaction with the relationship.

The study has several important implications for the franchisor's business strategy. The first implication is that the franchisor needs strategies to encourage financial dependence because dependence influences the franchisee to perform in accordance with the franchisor's objectives. It may be particularly important to attract franchisees who are willing to accept a high level of financial dependence from the onset of the relationship. This is because the franchisee's decision to make subsequent investments in the franchise that might increase the franchisee's dependence appears to be influenced by a number of factors beyond the franchisor's control. The franchisee's assessment of market conditions, other business opportunities, and other personal financial needs all may play a larger role in the decision to reinvest than the franchisee's current level of investment or satisfaction with the franchisor and the relationship. The key, therefore, may be in the selection of franchisees who have most of their assets invested in the business. Such a franchisee has ample incentive to perform at a high level, because the downside risk associated with not performing is so great. One possible strategy for encouraging financial dependence is to offer a more extensive array of support services to those franchisees that agree to invest a larger percentage of their net worth in the business. This strategy would discourage owner-investors who are not interested in participating in the day-to-day operation of the business. Instead, some investors would be encouraged to become owner-operators, due to their large financial stake in the business, while others, not willing to make this commitment, would opt for other investment opportunities.

A second implication of the research findings is that franchisors must devise strategies to maximize the amount of credit they receive from franchisees who perform well. Conversely, franchisors need strategies to limit the amount of blame they receive when franchisees perform poorly. This is because the amount of credit or blame assigned to the franchisor influences the franchisee's satisfaction with the franchisor's role performance and with the relationship itself. Since many of the support services performed by the franchisor may be invisible to the franchisee, it behooves franchisors to make their services as visible and tangible to the franchisee as possible. In addition, every effort should be made to link support services to specific benefits that accrue to the franchisee from receipt of the services. It is essential, however, to make the franchisee's role in bringing about satisfactory outcomes explicit. This will help ensure that the franchisor is appropriately perceived as a facilitator of good performance, albeit an important but secondary factor in the franchisee's performance. Finally, just as manufacturers of such products as Morton's Salt engage in reminder ads, the franchisor's self-promotion efforts should be repeated periodically to counter the "fast forgetting" that tends to occur among franchisees over time.

A third implication is that franchisors need to motivate their employees to meet and even exceed franchisees' role performance expectations on a continuing basis. Satisfactory role performance by the franchisor reinforces the franchisee's initial decision to join the franchise system. This may make franchisees more amenable to the franchisor's direction, more likely to make subsequent investments in the business, and less inclined to seek out other business ventures. In any event, satisfaction with the franchisor influences the franchisee to continue the relationship and that benefits both parties.

The findings from this study, however, may not apply to all types of channels. It may be particularly inappropriate to generalize these findings to conventional channels because they differ from franchise systems in several fundamental respects. Franchise systems are vertically administered systems with the characteristics cited previously.

Future research should carefully evaluate the channel contexts or situations where the hypothesized relationships may be relevant. Giving more explicit consideration to the concept of channel context would contribute to richer theories of channel management and improve the managerial usefulness of empirical research. A logical starting point would be to critically assess the traditional bases for distinguishing one type of channel from another.

Finally, two research design issues deserve some discussion. The first issue involves the use of objective and perceptual measures. Objective measures may be relevant to test one relationship involving a particular variable and perceptul measures may be needed to test another relationship involving the same variable. What appears to be a single construct may in fact be two different variables, depending upon whether objective or perceptual measures are used (Frazier et al. 1989). The researcher should consider the role of perception in the theoretical constructions under investigation and choose perceptual or objective measures accordingly.

A closely related research design issue involves the scope of channel studies. Indeed, a major conclusion that can be made on the basis of this study is that channel researchers need to adopt an integrated approach to channel theory and research; several scholars have advanced cogent arguments favoring such an approach (Frazier 1983b; Frazier and Summers 1984; Gaski 1984; and Stern and Reve 1980). This is the first study reported in the literature that investigates the relationship between financial dependence and performance, two key economic variables, and satisfaction, an important behavioral variable. The rationale for investigating both the behavioral and economic characteristics of a channel is simple but quite compelling: studying either dimension alone does not accurately represent a channel's operational dynamics. The findings from this study suggest that the economic variables are key determinants of channel member behavior and, therefore, should be subjected to more scrutiny by channel researchers.

[Table 2 Omitted] [Figure 1 Omitted]


Aldrich, Howard (1979), Organizations and Environments, Englewood Cliffs, NJ; Prentice-Hall, Inc. Anand, Punam, and Louis Stern (1985), "A Sociopsychological Explanation for Why Marketing Channel Members Relinquish Control," Journal of Marketing Research, 22 (November, 365-376. Anderson, Erin, Leonard Lodish, and Barton Weitz (1987), "Resource Allocation Behavior and Conventional Channels," Journal of Marketing Research, 24 (February), 85-97. Anderson, J. C., and D. W. Gerbing (1982), "Some Methods for Respecifying Measurement Models to Obtain Unidimensional Construct Measurement," Journal of Marketing Research, 19 (November), 453-460. Anderson, James, and James Narus (1990), "A Model of Distributor Firm and Manufacturer Firm Working Partnerships," Journal of Marketing, 54 (January), 42-58. Armstrong, S. J., and T. S. Overton (1977), "Estimating Nonresponse Bias in Mail Surveys," Journal of Marketing Research, 14 (August), 396-402. Bagozzi, Richard P. (1980), Causal Models in Marketing, New York, NY: John Wiley & Sons, Inc. Bernstein, Louis M. (1968-69), "Does Franchishing Create a Secure Outlet for the Small Aspiring Entrepreneur?" Journal of Retailing, 44 (Winter), 21-38. El-Ansary, Adel I., and Louis W. Stern (1972), "Power Measurement in the Distribution Channel," Journal of Marketing Research, 9 (February), 47-52. Emerson, Richard (1962), "Power-Depedence Relations," American Sociological Review, 27 (February), 31-41. Etgar, Michael (1976a), "The Effects of Administrative Control of Efficiency of Vertical Marketing Systemss," Journal of Marketing Research, 13 (February), 12-24. -- (1976b), "Channel Domination and Countervailing Power in Distributive Channels," Journal of Marketing Research, 13 (August), 254-262. Fornell, Claus, and David F. Larcker (1981), "Evaluating Structural Equation Models With Unobservable Variables and Measurement Error," Journal of Marketing Research, 18 (February), 39-50. Frazier, Gary L. (1983a), "On the Measurement of Infirm Power in Channels of Distribution," Journal of Marketing Research, 45 (May), 58-66. --(1983b), "Interorganizational Exchange Behavior in Marketing Channels: A Broadened Perspective," Journal of Marketing, 47 (Fall), 68-78. --, and John O. Summers (1984), "Interfirm Influences Strategies and Their Application Within Distribution Channels," Journal of Marketing, 48 (Summer), 43-55. --, James D. Gill, and Sudhir H. Kale (1989), "Dealer Dependence Levels and Reciprocal Actions in a Channel of Distribution in a Developing Country," Journal of Marketing, 53 (January), 50-69. Gaski, John (1984), "The Theory of Power and Conflict in Channels of Distribution," Journal of Marketing, 48 (Summer), 9-29. --, and John Nevin (1985), "The Differential Effects of Exercised and Unexercised Power Sources in a Marketing Channel," Journal of Marketing Research, 22 (May), 130-142. Heide, Jan B., and George John (1988), "The Role of Dependence Balancing in Safeguarding Transaction-Specific Assets in Conventional Channels," Journal of Marketing, 52 (January), 20-35. Homans, George (1974), Social Behavior: Its Elementary Forms, New York, NY: Harcourt, Brace, Jovanovich, Inc., revised edition. Hunt, Shelby D., and John R. Nevin (1974), "Power in a Channel of Distribution: Sources and Consequences," Journal of Marketing Research, 11 (May), 186-193. Hunter, J. E. (1973), "Methods of Reordering the Correlation Matrix to Facilitate Visual Inspection and Preliminary Cluster Analysis," Journal of Educational Measurement, 10 (1), 51-61. --, and S. H. Cohen (1969), "PACKAGE: A System of Computer Routines for the Analysis and Causal Models," in B. M. Staw and L. L. Cummings, (eds.), Research in Organizational Behavior, Greenwich, CT: JAI Press. --, --, S. H. Cohen, and T. Nicol (1980), "PACKAGE 1980: A System of FORTAN Routines for the Analysis of Correlational Data," prepared with the support of Academic Computing Services, Baylor University, Waco, Texas. Joreskog, K. G., and D. Sorbom (1984), LISREL VI: Analysis of Linear Structural Relationships by Maximum Likelihood and Least Squares Methods, Chicago, IL: National Education Resource. Kale, Sudhir (1986), "Dealer Perceptions of Manufacturer Power and Influence Strategies in a Developing Country," Journal of Marketing Research, 23 (November) 387-393. Kelley, H. H., and John Michela (1980), "Attribution Theory and Research," Annual Review of Psychology, 31, 457-501. Lusch, Robert F. (1976a), "Sources of Power. Their Impact on Intrachannel Conflict," Journal of Marketing Research, 13 (November), 382-390. --(1976b), "Channel Conflict: Its Impact on Retailer Operating Performance," Journal of Retailing, 51 (Summer), 3-12, 89-90. --(1977), "Franchisee Satisfaction: Causes and Consequences," International Journal of Physical Distribution, 7 (February), 128-140. --, and James R. Brown (1982), "A Modified Model of Power in the Marketing Channel," Journal of Marketing Research, 19 (August), 312-323. Robicheaux, Robert, and Adel I. El-Ansary (1975), "A General Model for Understanding Channel Member Behavior," Journal of Retailing, 52 (Winter), 13-30. Rosenberg, Larry J., and Louis W. Stern (1971), "Conflict Measurement in the Distribution Channel," Journal of Marketing Research, 8 (November), 437-442. Ruekert, Robert, and Gilbert Churchill (1984), "Reliability and Validity of Alternative Measures of Channel Member Satisfaction," Journal of Marketing Research, 21 (May), 226-234. Schul, Patrick, William Pride, and Taylor Little (1985), "Channel Climate: Its Impact on Channel Members' Satisfaction," Journal of Retailing, 61 (Summer), 9-37. Skinner, Steven, and Joseph Guiltinan (1985), "Perceptions of Channel Control," Journal of Retailing, 61 (Winter), 65-88. Stern, Louis, and Adel I. El-Ansary (1977), Marketing Channels, Englewood Cliffs, NJ: Prentice-Hall, Inc. Stern, Louis W., and Torger Reve (1980), "Distribution Channels as Political Economies: A Framework for Comparative Analysis," Journal of Marketing, 44 (Summer), 52-64. Tyron, R. C., and D. E. Bailey (1970), Cluster Analysis, New York, NY: McGraw-Hill Book Co. Walker, Bruce, and James Cross (1988), "Franchise Failures: More Questions Than Answers," in Robert Dwyer, (ed.), Forging Partnerships For Competitive Advantage, Proceedings of Society of Franchising, Cincinnati, OH: University of Cincinnati. Wilkinson, I. F. (1974), "Researching the Distribution Channels for Consumer and Industrial Goods: The Power Dimension," Journal of the Market Research Society, 16 (1), 12-32. Williamson, Oliver (1981), "The Modern Corporation: Origins, Evolution, Attributes," Journal of Economic Literature, 19 (December), 1537-1568.
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Author:Lewis, M. Christine; Lambert, Douglas M.
Publication:Journal of Retailing
Date:Jun 22, 1991
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