Toward an understanding of loyalty: the moderating role of trust.
Loyalty is about building and sustaining a relationship with your customers. Recently, businesses are again focusing on the benefits of building customer loyalty. If the Eighties rewarded widespread improvements in product quality, the Nineties will compensate the cultivation and coddling of the customer. Says Bob Wayland, a vice president with Mercer Management Consulting: "The paradigm has shifted. Products come and go. The unit of value today is the customer relationship" (Jacob, 1994: 215). Regular customers are also easier to serve; they understand your modus operandi and make fewer demands on employee time. Furthermore, managers are-coming to the realization that measuring improvements in product attributes, quality, and service is not enough. A recent study by the Juran Institute found that fewer than 30 percent of the 200 respondents surveyed believed their customer satisfaction "management" efforts added economic value to their bottom line, and fewer than 2 percent were able to measure a bottom-line improvement as a result of increased customer satisfaction levels (Hepworth and Mateus, 1994). The conclusion is that it doesn't pay to have satisfied customers; it pays to have loyal ones.
A number of authors suggest that the construct of trust is an important element of long-term buyer-seller relationships in a business environment (Anderson and Narus, 1990; Dwyer et al., 1987). Trust is viewed as an important feeling because of its ability to moderate risk in the buying process. As such, trust permits the buyer to make commitments to a single source whose prior behavior has been satisfactory with the confidence that this supplier will continue to perform in a similar manner. Ganesan (1994) finds that trust and dependence play key roles in determining the longterm orientation of firms in a relationship and both are related to environmental uncertainty, transaction-specific investments, reputation, and satisfaction in a buyer-seller relationship. Morgan and Hunt (1994) found that trust was the key mediating variable in relational exchange between automobile fire retailers and their suppliers. While one might argue that trust is not important for a single transaction in which future performance is not a consideration, the importance of trust becomes evident as a moderator of risk when buyers move away from buying systems based on a single transaction to one of repeat purchasers. Here, alliances are often formed between buyers and sellers to share technologies and skills, and to perform required tasks as cost effectively as possible in order to meet competitive threats. The goal is to secure valued resources of selected suppliers without the costs associated with vertical integration due to resource limitations or managerial constraints. From the supplier's side, improvements in loyalty even in the absence of strategic alliances improves profits through higher revenues and more effective marketing expenditures. Furthermore, it can cost the seller many times more to "conquer" a new customer as it takes to keep an existing customer.
In order to safeguard against disruptions in supply, buyers often attempt to reduce risk by using elaborate heuristics such as maintenance of multiple sources, vendor rating, insistence on safety stocks, and purchase contracts. However, implementing these safeguards is an expensive and time consuming process. A more cost effective strategy may be to form relationships with only a limited number of suppliers (Landeros and Monczka, 1989). Perhaps the ultimate goal in some buyer-seller relationships is the "Just-In-Time Exchange Relationship" in which both parties in the exchange commit resources to both the product and delivery systems in order to improve the overall system efficiency (Frazier et al., 1988). Over the past decade, there is growing evidence that to be competitive, manufacturing firms are moving away from a traditional approach of adversarial relationships with many vendors to one of longer-term relationships with few select sup, pliers. Firms such as Xerox, Motorola, General Electric, Ford, and others are reducing their supplier base and looking to a few select suppliers to help them achieve a stronger competitive position (Emshwiller, 1991). The net result is greater dependence between buyers and sellers with many firms conducting business with each other over decades (Williamson, 1985).
Does trust lead to loyalty on the part of buyers? What is the relative importance of trust when compared to product attributes such as quality and terms of delivery, which are often used as a predictor of behavior, in determining loyalty? Resolving these issues should have a significant impact on how marketing managers for business products evaluate customers, determine strategies, and allocate resources. For example, if trust has a larger impact than product evaluations on customer behavior, quality improvements must focus on aspects of the buyer-seller relationship that enhance trust, and training programs will need to include developing skills on trust building activities. The a pt/or/assumption that relational exchange is a surrogate for loyalty has yet to be verified. Morgan and Hunt (1994) asserted that commitment was similar to loyalty and acknowledged that traditional measures of last product purchased was not sufficient to capture loyalty. Our intent is to adopt a specific and more sophisticated measure of purchasing loyalty and verify that trust does indeed have a causal impact on this variable.
Previous research in both psychological and business situations which attempt to measure trust have been problematic. Some of these problems include issues of multi-dimensionality and a lack of reliability (Corazinni, 1977). Furthermore, attempts to adapt psychological measures of trust to business research have proven less than successful (e.g., Dwyer and Oh, 1987). Despite this measurement issue, a consensus is emerging in the literature that defines trust as "an expectancy held by an individual that the words, promise, verbal or written statement of another individual or group can be relied on" (Rotter, 1967: 651). This definition is also consistent with Pruitt (1981) in the context of negotiation and Williamson (1985) in the development of relationships. For buyers in a business purchasing decision, two "types" of trust immediately come to mind - trust in the company (Griffin, 1967) and trust in the salesperson (Schurr and Ozanne, 1985), since they are often the primary communication link between the buyer and the selling company. Dwyer, Schurr, and Oh (1987) argue that a buyer interacts with two primary entities outside of the buying firm in the purchase of products - the seller and his or her organization. We, therefore, propose to (1) measure trust held by a buyer toward both the selling company and the salesperson in a business environment; (2) introduce attitude toward the product (which also includes augmentations such as support and delivery) along with these measures of trust in a model of buyer behavior; and (3) examine their impact on the loyalty intentions and the loyal behavior of the buyer.
A MODEL OF BUYER LOYALTY
The key question in this research is whether trust has a significant impact on purchasing strategies of a business and whether this impact is greater than a traditional compensatory measure of preference: attitude toward the product. Since the activities required to build trust are very different than those used to create favorable evaluations of the product or service offered, resolving this question should provide an understanding so that managers might better allocate resources within the firm. For example, trust building activities include sales force training in communication skills and product knowledge, while product evaluation activities would include improvements in product quality and additions of product features. Trust is a feeling toward the primary entities with whom a buyer interacts in the purchasing process - the salesperson and the marketing firm. Trust is a willingness to rely on an exchange partner in whom one has confidence. An important aspect is that trust can be seen as a belief, sentiment, or expectation about a partner that results from a partner's expertise, reliability, or past behavior. In turn, a buyer's trust in a vendor may then affect his or her buying behavior. Therefore, trust is both an antecedent and consequence of the buyer-seller relationship.
Most marketers would prefer their customers become more loyal since it leads to greater sales and revenue, better prediction of sales, requires minimal marketing efforts, and creates customers who are less sensitive to the marketing efforts of competitors (Jarvis and Wilcox, 1977). From the standpoint of the buyer, loyalty serves as a purchasing strategy that reduces risk inherent in using multiple vendors, reduces switching costs, and gains the customer access to new technologies faster than nonloyal buyers (Puto et al., 1985). Loyalty can be viewed as a "(1) biased (i.e., nonrandom), (2) behavioral response (i.e., purchase), (3) expressed over time, (4) by some decision making unit, (5) with respect to one or more alternative brands out of a set of such brands, and (6) is a function of psychological (decision-making evaluative) process" (Jacoby and Kyner, 1973: 2).
Assessment of loyal behavior is often based on prior purchases. For example, Segal (1989) defines a buyer as loyal if a large percentage (90 or greater) of purchases are given to a single supplier (see also Fader and Lattin, 1993). However, repurchase is not sufficient evidence of buyer loyalty, and such measures may include spurious loyalty due to limited availability or contractual agreements. Jarvis and Wilcox (1977) argue that to understand buyer loyalty, one must consider the behavior both in terms of prior purchases and some component which verifies that the prior purchasing practice is the result of an intentional strategy. With this consideration, we propose two components of loyalty: one reflecting the intentions of the buyer (Loyalty Intentions) and one reflecting the behavior of the firm(Loyal Behavior).
Psychological literature indicates that a linkage exists between trust and loyalty (Butler and Cantrell, 1984), and, while marketing literature acknowledges the importance of trust in buyer-seller relationships, little consideration has been given toward its impact on buyer loyalty. Dwyer, Schurr, and Oh (1987) suggest that trust is a key determinant of commitment in a relationship. Morgan and Hunt (1994) theorize that trust and commitment lead directly to cooperative behaviors which in turn promote efficiency, productivity, and effectiveness for both parties. This enduring desire to maintain a valued relationship should, in turn, impact loyalty. Manufacturers see loyalty as key to superior performance and make efforts to build it through superior product benefits, promoting the firm's values, and establishing an image as a trustworthy supplier.
We suggest that examining the plausible link between trust and loyalty is of importance to both researchers and practitioners. Given our ability to measure the dual focus of trust, we propose to examine how a buyer's trust in the salesperson affects trust in the company and, subsequently, loyalty. Our reasoning for this structure is that, in personal selling situations, the salesperson represents the company to the buyer. Therefore, trust in the salesperson is a necessary, antecedent to trust in the company. We anticipate that trust in the salesperson should have an indirect effect through trust in the company, which, in turn, should have a direct effect on buyer loyalty. We should note that trust in the company in many cases provides the initial source credibility for the salesperson. However, in our study, only existing and ongoing relationships between buyers and their suppliers were considered.
An outcome of trust felt by a buyer is his or her intention to be open in the communications process. When buyers exhibit a high level of trust toward a salesperson, they are more likely to engage in communications behavior which is open and free flowing. Schurr and Ozanne (1985) have classified such behavior as integrative since it focuses on finding methods of satisfying and integrating the needs of both the buyer and the seller in the exchange process. Low trust tends to create what is termed distributive behavior since it represents a separation between buyers and sellers and is typified by high levels of conflict and a tendency for the parties to exhibit "evasive, compliant, or aggressive communications which conceal true attitudes" (Mellinger, 1956: 304). We hypothesize a construct of "Communication Openness," which measures the nature of verbal interaction between the buyer and the salesperson. While recent research has indicated that this construct may be viewed as an input variable to trust (Anderson and Narus, 1990), a well established stream of literature from both psychology and marketing view open communications as an outcome of trusting relationships (e.g., Anderson and Weitz, 1989; Schurr and Ozanne, 1985; Zand, 1972). Given the nature of our sample, we adopt the latter position in our modeling approach, and acknowledge that these inconsistencies may likely result from nonrecursire models which attempt to capture a recursive phenomenon.
We also examine the causal link between Communication Openness and Loyal Behavior to determine if there is a behavioral outcome in terms of customer loyalty as a result of how a buyer communicates with a salesperson. If there is no link, we must question the value of including Communication Openness as a consideration in the management of buyer-seller relationships. Anderson and Weitz (1989) verified the importance of communications in buyer-seller relationships. However, the focus of that work was on the volume of communications; whereas, in this research, we are interested in the nature of those communications. This is a key difference since it is quite conceivable that adversary nonloyal relationships might involve a greater amount of communications than in cooperative loyal relationships.
Attitudinal Links to Loyalty
Attitude has long been considered to be a relevant predictor of future purchases of a product and there is considerable support as to the validity and reliability of linear compensatory models of attitude. Customers satisfied with a company's products are likely to form or reinforce positive brand attitudes which would lead to more frequent purchases, purchases in greater volume, and purchases of other goods and services offered by the firm (Howard, 1994). Favorable attitude toward the product should enhance the overall reputation of the firm, and in turn aid in establishing and maintaining relationships with key suppliers, distributors, and potential allies (Anderson and Weitz, 1989). We therefore hypothesize that attitude should be an antecedent to both Loyalty Intentions and Communication Openness.
The Impact of Company Size
Finally, company size has long been considered a key variable in determining how individuals in a buying organization interact with suppliers and their salespeople (Lilien and Wong, 1984). Griffin and Hauser (1993) discuss the possibility of a negative relationship between customer satisfaction and market share. They argue that whereas a small market-share firm may serve a niche market quite well, a large market-share firm must serve a more diverse and heterogeneous set of customers. Company size may also play a role in the perception of equity of future outcomes. Equitable outcomes provide confidence that neither party is seeking an unfair advantage, and that both parties are concerned with the other's welfare in the relationship. A buyer who perceives inequity in a relationship will be dissatisfied and likely to view the vendor as exploitative. Though the buyer still could continue such a relationship, there is likely to be a reduced level of loyalty toward the vendor. We, therefore, have included the exogenous variable of company size in the causal structure, expecting it to impact both the purchasing agent's purchase intentions and the purchasing outcome. For purposes of this study, company size was measured by the number of employees.
A Conceptual Model of Buyer-Seller Relationships
The relationships between the six theoretical variables and size of company are represented in Figure I. All the hypothesized directions of causal relationships are assumed to be positive with the exception of size, which is assumed to be negative. That is, as the buying company becomes larger, we expect the buyers to exhibit less loyal purchase intentions and the firm's buying behavior to be less loyal. The three theoretical constructs - trust in company, trust in salesperson, and attitude toward the product - are assumed to influence purchasing behavior indirectly through the purchasing strategies of the buyer.
Data were collected with a mail questionnaire sent to 297 buyers of electronic circuit boards in seven different industries in Massachusetts. Circuit boards were selected as the product of focus for three primary reasons. First, buyers of circuit boards are diverse in nature, using them in a wide range of products from low technology (e.g., industrial controls) to high technology (e.g., high frequency communications equipment). Second, the technology of the boards themselves varies from low to high (i.e., rigid to multi-layer boards). Finally, the configurations that buyers purchase vary from simple to complex (i.e., basic substrate to fully assembled and tested boards). Hence, this product category captured a rich range of product types and applications.
Respondents were contacted by telephone and qualified based on whether they were responsible for the purchasing of circuit boards, and then asked to participate in the survey. In all cases, we were able to verify that the decision to purchase circuit boards rested with a single individual, even in the large firms. From this, we conclude that issues related to buying center complexity are minimized in this research. The cover letter included a $1.00 incentive and identified the research as being conducted by a large university for noncommercial reasons. A follow-up postcard was sent to each respondent one week after the original mailing. A total of 155 complete questionnaires were returned (response rate of 52%). Since there were no significant differences between the means of a sample of attitudinal belief measures for the first thirty and the final thirty respondents, we conclude that threats of a nonresponse bias are minimized (Armstrong and Overton, 1977). Furthermore, a random group of nonrespondents were contacted by telephone and asked to respond to a limited set of items concerning trust. No significant differences between the means of their answers and those of the study respondents were found.
Trust Measures. "Trust," as a construct, can be thought of as the level of expectation or degree of certainty in the reliability and truth or honesty of a person or thing (in this situation, the salesperson and the selling company). Two types of trust measures concerning the primary vendor are obtained: trust in the salesperson and trust in the company. A representative set of possible items were assembled which had been used in past studies to measure trust (cf. Hockreich and Rotter, 1970; University of Michigan, 1979) and given to a panel of five expert judges who rated how well the items in this set corresponded to our definition of trust. The results were totaled across all five judges and the top items served as the basis for developing the final two constructs of trust. Each item was reworded slightly to capture the focus of trust (salesperson or company). The three items, measured on a 5-point Likert scale anchored from "strongly disagree" to "strongly agree," concerning trust in the salesperson are:
S1: Generally speaking, you can't be too careful in dealing with him/her.
S2: Anyone who completely trusts him/her is asking for trouble.
S3: Despite what s/he says, s/he will try to take advantage of me.
The three items concerning trust in the company are:
C1: This company can't be trusted, it's just too busy looking out for itself.
C2: I have found that I can rely on this company to keep the promises that it makes.
C3: This company is basically honest.
The negative wording for all three items for trust in the salesperson is not uncommon for scales concerning salespeople (Saxe and Weitz, 1982). Such wordings make it easier to give negative responses.
Attitude Toward the Product. The attitude toward the product (supplied by the primary vendor) is a multidimensional model often called an adequacy-importance measure:
(1) A-BRAND [summation of] [P.sub.j][I.sub.j] where j = 1 to n
where A-BRAND is the buyer's attitude toward the brand from the primary vendor, [P.sub.j] is his/her rating of how well the brand performs on the attribute or benefit j, and [I.sub.j] is the buyer's evaluation of the degree of importance of benefit j. A total of n = 16 benefits were evaluated. The benefits were: "Quality as Promised," "Keeps Pricing Competitive," "On Time Delivery," "Competence of Technical Support," "Responsive Customer Service," "Quality of Products Received," "Salesperson Customer Orientation," "Company Customer Orientation," "Salesperson Product Expertise," "Company Product Expertise," "Salesperson Industry Expertise," "Company Industry Expertise," "Salesperson Reliability," "Company Reliability," "Salesperson Listens to My Problems," and "Company Listens to My Problems." Each benefit's performance was rated on a 5-point scale from "poor" to "excellent," and each benefit's importance was evaluated on a 5-point scale from "not important" to "extremely important."
Communication Openness. "Communication Openness" was evaluated based on how open the buyer was in discussing business issues with the salesperson. Items concerning approaches to communications with the salesperson were measured on a 5-point Likert scale anchored from "strongly agree" to "strongly disagree." The three items concerning Communication Openness are:
GS1: In discussing matters with him/her, I tend to be completely open.
GS2: It is important that I don't reveal everything in discussing business with him/her, I never know where it will end up.
GS3: I don't have to worry, about what we discuss, s/he is discreet about not telling others.
Loyalty Intentions. Loyalty Intentions were assessed on a continuum of nonloyal to loyal purchasing intentions. Respondents were asked about their approach toward the purchase of circuit boards by characterizing their purchasing intentions as one of four possible approaches representing differing levels of intended buyer loyalty. The variable, LOYALI, was the respondent's selection of one of the following four levels:
1. I try to stay loyal to a single supplier.
2. I stay loyal to a single major supplier and a limited number of secondary suppliers.
3. I try to stay loyal to several suppliers.
4. I spread the business around to all qualified suppliers.
Loyal Behavior. Self-reported purchasing behavior was elicited from each respondent. Our measure of the outcome variable, LOYALB, in our model is constructed by subtracting the percentage of sales given to the second vendor from the percentage of sales given to the first (primary) vendor, conditioned on the type of circuit board. In the exploratory phase of the research, a number of companies expressed an intentional strategy of staying loyal to a primary supplier, but also had a desire to have a secondary (backup) supplier available for safety stock. Since most buyers had a secondary vendor, the difference between the purchases from the primary and secondary suppliers rather than the absolute level given to the primary supplier is believed to reflect the true nature of loyalty in this industry. For example, if the primary vendor received 60% of a firm's business, then whether the secondary vendor received 10% or 40% is an important distinction.
To examine the effects of trust on buyer-seller relationships, this research was conducted in two stages. In the first stage, we use structural equation methodology to evaluate the hypothesis that, in our buying situation, trust is multidimensional in nature. Specifically, we analyze the reliability of several items of the two aspects of trust and assess their convergent and discriminant validity. Our goal is to determine whether purported measures of seller and company trust covary as expected and can be distinguished from each other. In the second stage, we use causal modelling analyses to establish the relationships between our trust constructs and behavior - purchasing strategies and buying decisions. Specifically, we examine the theoretical relationships, as depicted in Figure I, between two types of trust and four other constructs with which they are theoretically related. Of special interest is the effect of trust on purchasing strategies when attitude towards the product is a covariate. Table I presents the correlation matrix of our measures. Items worded negatively were reversed coded.
Convergent Assessment. Convergent validity is reflected by the degree to which several presumed measures of the same construct empirically "converge" as indicators of that construct. To support inferences of convergent validity, the three measures of trust in the salesperson (TRUST-S) must be sufficiently correlated with one another, and the three measures of trust in the company (TRUST-C) must be sufficiently correlated. To test for convergence, we use a causal modelling methodology which uses a maximum-likelihood ratio test to determine whether convergent validity is achieved. Figure II presents the causal model we used to test for convergence. In this model, we hypothesize that the three purported measures of TRUST-S (S1, S2, and S3) converge. We also posit that the three purported measures of TRUST-C (C1, C2, and C3) converge.
The hypothesized set of relationships shown in Figure II are tested using confirmatory factor analysis (LISREL VII) developed by Joreskog and Sorbom (1989). Factor loadings of measures, which are theoretically unrelated to the hypothesized constructs, are fixed at 0 and the measurement errors [Delta] = ([[Delta].sub.1], [[Delta].sub.2], [[Delta].sub.3], [[Delta].sub.4], [[Delta].sub.5], [[Delta].sub.6])[prime] are assumed to be uncorrelated, that is, they have a diagonal correlation matrix. The degree of correspondence between measure and construct is reflected through the parameter, [Lambda], which varies from 0 (no correspondence) to 1 (perfect correspondence), and [Phi] is the intercorrelation among the two theoretical constructs, TRUST-S and TRUST-C.
[TABULAR DATA FOR TABLE I OMITTED]
The analysis shows that the TRUSTS and TRUST-C measures converge to indicate single constructs, respectively. We assess convergence by examining the goodness of fit of the proposed model. The model is estimated yielding a goodness-of-fit index (GFI) of .95 and an adjusted goodness-of-fit index (AGFI) of .88. The root mean square residual (RMSR) is .03, and each t-value for the estimated parameters is significant. In contrast, the chi-square value is [[Chi].sup.2](8) = 22.52, p [less than] .01, indicating an inadequate fit. However, the chi-square statistic is a function of sample size and therefore must be interpreted accordingly. Moreover, since all normalized residuals were less than 2.0, we conclude that no better specification exists than the one provided. That is, since no large residuals were found, any alternative model specification could not, because of error variance, ensure a better fit with respect to the chi-square statistic. Figure II presents the estimated parameters for the hypothesis of convergence. In summary, the data indicate strong evidence of convergence.
Reliability. Given the demonstration of convergence, it is appropriate to examine the reliability of measures of TRUSTS and TRUST-C. Based on classical test score theory, we refer to the reliability of an individual measurement as the squared correlation between the observed score and true score. Specifically, the reliability of the individual measurements is computed as (Werts et al., 1974):
(2) [[Rho].sub.i] = ([[[Lambda].sub.[Iota]].sup.2] var A)/([[[Lambda].sub.[Iota]].sup.2] var A + [[Psi].sub.i])
where [[Rho].sub.i] is the reliability of measurement i, [[Lambda].sub.[Iota]] is the factor loading relating measurement i to its respective construct A, and [[Psi].sub.[Iota]] is the error variance of measurement i. Similarly, the composite reliability of [n.sup.*] measures of construct A can be calculated as:
(3) [[Rho].sub.c] = [([summation of] [[Lambda].sub.i] where i = 1 to [n.sup.*]).sup.2] var A/[[([summation of] [[Lambda].sub.i] where i = 1 to [n.sup.*]).sup.2] var A + [summation of] [[Psi].sub.i] where i = 1 to [n.sup.*]]
where [[Rho].sub.c] is the composite reliability.
We use equation (2) to compute individual reliabilities for the measures of TRUST-S and TRUST-C. All the individual score reliabilities are quite good. The individual reliabilities for the TRUST-S measures are .83 (S1), .55 (S2), and .67 (S3). The reliabilities for the TRUST-C measures are .52 (C1), .61 (C2), and .66 (C3). Furthermore, the reliabilities of both composite measures are high (TRUST-S = .87; TRUST-C = .81).
Discriminant Assessment. Discriminant validity is the extent to which measures of constructs exhibit uniqueness. For example, we would expect that TRUST-S and TRUST-C would be related, but have different relative impacts on the resulting variables. The computer program, LISREL VII, provides a formal means to test these implications through the confidence interval for [[Phi].sub.12] (Joreskog and Sorbom, 1989). Referring to Figure II, discriminant validity is indicated when the separate measures of TRUST-S and TRUST-C exhibit convergence within their respective latent variables and uniqueness between them. To assess the degree of discrimination, we examine [[Phi].sub.12] in a model providing an acceptable fit. If the latent variables are unique, then [[Phi].sub.12] must be sufficiently less than unity. Referring to Figure II, the estimate for this correlation is .71, and this parameter is significantly below unity (N.B., a .95 percent confidence interval for [[Phi].sub.12] is [.59,.83], which does not contain unity).
The Effects of Trust on Behavior
In this stage of the research, we examine the effects of trust on Loyalty Intentions and Loyal Behavior. To explore fully the effect of trust on loyalty, we introduce a construct that represents an alternative theoretical explanation. We expect that TRUST-C should predict Loyalty Intentions and that TRUST-S should predict Communication Openness since the items concerning Communications Openness focused on communications with the salesperson. Furthermore, TRUST-S is hypothesized to have a positive effect on TRUST-C, and both types of trust should affect attitude toward the product in a positive manner. To assess the effects of trust, we examined the relationships between the constructs using the causal model shown in Figure I. The analysis is conducted using LISREL VII. The parameter estimates are presented in Table II. The estimated model yielded a GFI of .95, an AGFI of .92, and the RMSR is .04. In addition, each t value for the estimated parameters is significant (except for the four regression weights noted below), and all normalized residuals were less than 2.0. Finally, the chi-square value is [[Chi].sup.2](58) = 54.62, p [congruent] .60, indicating a good fit.
A number of findings in Table II are of interest. First, as expected, TRUST-C has a strong positive impact on LOYALI. We observe that TRUSTS has a stronger relationship with Communication Openness than TRUST-C has with LOYALI as reflected by the estimated regression weights. The reasons are twofold. First, Communication Openness, as we measure it, evaluates the buyer's interaction with the sales force and we would, therefore, expect that trust in that salesperson would have a strong influence on such interactions. Second, with 86% of the variance unexplained, there are a number of other antecedents to LOYALI that still need to be identified and were beyond the scope of this research, and the measurement of LOYALI, while better than prior measures, could still be improved.
Table II Maximum-Likelihood Parameter Estimates for the Model of Figure I Construct Variable [Lambda] SE Company Trust C1 .88 .10 residual var = .32 C2 .95 .10 C3 1.00 0(*) Attitude Toward Product A-BRAND 1.00 0(*) residual var = .88 Communication Openness CO1 .83 .12 residual var = .28 CO2 1.00 0(*) CO3 1.00 .13 Loyalty Intentions LOYALI 1.00 0(*) residual var = .86 Loyalty Behavior LOYALB 1.00 0(*) residual var = .59 Salesperson Trust S1 .89 .07 S2 .76 .07 S3 .83 .07 Size of Company SIZE 1.00 0(*) Causal Paths Variable Coefficient SE [[Beta].sub.1] .36 .17 [[Beta].sub.2] .29 .11 [[Beta].sub.3] .09 .06 [[Beta].sub.4] -.05 .08 [[Beta].sub.5] .12 .09 [[Beta].sub.6] .48 .07 [[Lambda].sub.1] .59 .07 [[Lambda].sub.2] .08 .14 [[Gamma].sub.3] .51 .08 [[Gamma].sub.4] -.29 .08 [[Gamma].sub.5] -.27 .07 * Constrained parameter.
As expected, the effect of TRUSTS on TRUST-C is strong and positive. Four of the regressions weights were found to be nonsignificant. They are (1) TRUST-S on A-BRAND, (2) Communication Openness on LOYALB and (5) A-BRAND on both LOYALI and (4) Communication Openness. The t values for these regression weights are .58, 1.34, -.57, and 1.44, respectively. We find that TRUST-C has a strong, positive impact on the overall attitude that a buyer holds for a company and its products, ABRAND, while the effect of TRUST-S on A-BRAND does not. That is, after accounting for the effect of TRUST-C on A-BRAND, the impact of TRUST-S on A-BRAND is not significant. While Communications Openness does not have an impact on our measure of Loyal Behavior, the estimated regression weight between LOYALI and LOYALB is positive, significant, and large. That is, after accounting for the effect of LOYALI on LOYALB, the impact of Communication Openness is not significant. This is not to imply that Communication Openness is not important, as we discuss in the next section. The most surprising result is that, after accounting for the effect of trust (TRUST-C and TRUST-S) on LOYALI and Communication Openness, the impact of A-BRAND on both is not significant. Finally, the size of a buying company affects both LOYALI and LOYALB. As we hypothesized, this association is negative, implying that as buying companies get larger, they tend to become less loyal in terms of both purchasing strategy and behavior.
Consistent with conventional logic, we have confirmed that the trust held by a buyer toward a seller is an important antecedent of loyalty, for at least some buying situations in a business environment. Of more importance is that we find that measures of trust surpass an attribute-based compensatory measure in their impact on both loyal purchasing strategy and, subsequently, on loyal buying behavior. While this may be an expected conclusion in a purchasing environment where the switching costs are high, our findings were drawn from an environment where there were a number of available suppliers and switching costs are considered low. The implications seem to be that buyer loyalty can exist in the absence of high switching costs and may, in fact, be a function of the risk of failure in the acquisition process rather than the relative cost of moving to alternative suppliers.
Certain concerns should be addressed before discussing the implications of this research. First, our measure of Loyalty Intentions is a four-point scale that may fail to capture a full range of possible strategies. This may also account for the amount of unexplained variance in this measure. Second, our measure of Loyal Behavior assumes a unidimensional purchasing strategy; we suspect that the process is far more complex. And, while measuring both intentions and strategy, as suggested by Jarvis and Wilcox (1977), represent an improvement over prior measures of loyalty, we believe that the decision-making process is more complex than modelled here. Third, Loyalty Intentions and Loyal Behavior are single measures, and so the technique of path analysis could also be considered. However, the variables of trust are multiple measures. And while their covariability could be, in theory, explained by a correlated error structure, the resulting path model would solve for the effect of the different aspects of trust, rather than the effect of the construct of trust. Future research should strive to create and test multiple measures of both loyalty dimensions. Finally, we have made some plausible assumptions as to the risk and switching costs associated with the products studied. Those assumptions need to be evaluated with more rigor in subsequent studies (e.g., in a variety of industries and with a variety of products) in a recursive model.
Loyalty and the Allocation of Risk
Previous researchers have advocated (Jackson, 1985) that the best way to develop loyal customers is to build physical switching costs, thus making it more difficult and expensive for customers to move their purchases to alternate suppliers. While this is a reasonable approach for complex systems where both the risk of failure and the cost of changing suppliers is high, our research suggests that loyalty can be achieved when the risk of failure is high but the switching costs are low and products are in some cases viewed as commodities. Verbatims from buyers were quite consistent on this issue. Even for the more commodity-like rigid circuit boards, buyers recognized that, while the cost of switching might be quite low, the risk of failure factored by the implications of failure is what drove their loyalty. One buyer told us that while she may be able to save 10% or more on the cost of a $1 board substrate by putting it out to bid, when that board was etched and drilled, it was worth $10. When it was "stuffed" with electronic components, it was worth $100. If it failed in a product before shipment, it was worth $1,000 and if it failed in the field it could cost the firm as much as $10,000 to repair. She referred to this as her "Rule of Tens" and indicated that it just wasn't worth the risk to try a lower priced circuit board.
Another important confirmation is that the size of the buying firm has a negative effect on both Loyalty Intentions and Loyal Behavior. Small customers do not have the resources for extensive specification and testing of incoming components and must rely on their suppliers to deliver products that will perform as required; nor do small customers have the resources to maintain large stores of inventory, to safeguard against disruptions in supply. Instead, they must trust their suppliers to reliably meet their present and future needs with quality products. In the end, small customers must trust their suppliers in order to survive, regardless of the physical switching costs. These suppliers, in turn, must provide the necessary support systems, such as customer and technical services, that encourage that trust and loyalty.
Conversely, large firms possess the expertise to develop the necessary in-house systems to check incoming component quality and safeguard against disruptions in supply by maintaining back-up inventories or alternate supply sources. Because of their size, large firms can afford these systems and assume the risk of product failure. For large customers, there are two benefits to such expenditures. The first is the apparent economic advantage gained from achieving lower prices on larger volumes of purchases. The second is their ability to control their suppliers and maximize the return on individual transactions. The net result is that trust in the supplier becomes of limited value as large buyers adopt a short planning horizon, evaluating alternative vendors based on a limited number of product attributes such as price and availability.
Clearly, suppliers cannot expect their customers to be loyal based on a large volume of business. A supplier who expends resources in anticipation of more loyal purchasing behavior from large customers should make sure that there are clear indications that the buying company intends to become more loyal. Some of these signals might be: loyal behavior in prior transactions, sole source supply policies for critical components or policies which limit participation from other suppliers, and specific discussion with members of the buying center which specify intended loyal behavior toward suppliers who invest in partnering technologies. Conversely, small-volume buyers have an inherent need to be loyal, and sellers who provide the necessary support services can accrue the benefits of that loyalty. Further, these sellers are able to spread those investments over a larger base of customers and reduce the risk of any single customer not being loyal. Unfortunately, as sellers pursue dual distribution strategies - selling directly to large customers and through distributors to small customers - they relinquish the customers more likely to be loyal to intermediaries who can reap the benefits of that loyalty.
Further, as large companies move toward just-in-time inventory management systems, where they do not hold inventory and expect suppliers to test quality prior to shipping, their prior lack of loyalty may inhibit suppliers from being willing to invest in the resources necessary to provide these services. Buyers who attempt to forge such alliances with their suppliers must recognize that many of their present practices signal that they are not loyal customers. A key aspect of moving towards a strategic alliance is, therefore, to change the way they do business by making commitments to a limited number of suppliers, treating them as a valued partner in how they do business.
The Moderating Effect of Trust in the Salesperson
We also discovered that trust felt toward the salesperson strongly influences trust felt toward the supplying company and, therefore, has an indirect effect on purchasing strategy and behavior. However, because of the existence of other influences on the buying process, buyers will not become loyal buyers of a company's product purely because they trust the salesperson. Some insights into these other influences are gained from verbatims of the respondents in the research. While a buyer's relationship with a salesperson appeared to be important, in the final analysis, a buyer's ability to trust the supplying company was the critical determinant of Loyalty Intentions. This might be because the salesperson often fulfills only a boundary role in the purchasing process. In the absence of commitment from the selling company that leads to trust, buyers have little control over the process other than negotiating for the lowest price from a number of suppliers. Relationships with salespeople appear to have little to do with altering this strategy.
However, we must be careful in uniformly applying these conclusions to all buying situations. In some cases, trust in the salesperson can be the major determinant in the decision process. A restaurant's customers may not return, regardless of the quality of the food, if they dislike the treatment they received from their waiter. Consultants, attorneys, and advertising account managers can usually count on favored clients following when they move to another firm since those "salespeople" are either providing the primary service or are a major conduit to receiving the service. The key is to assess whether salespeople are also the primary providers of the company's service and, if this is true, then their impact and value must be explicitly recognized.
We also confirmed that buyers communicate more openly with salespeople they trust. However, our analysis found that communication's impact on loyal purchasing behavior of the firm is nonsignificant. This is not to say that open communications between buyers and sellers is not important. When a supplier relies on verbal inputs from the buyer to assess customer needs, developing trust between buyers and salespeople is important in order to maintain the necessary communications to correctly configure the offering. Conversely, companies selling commodity or established products which require limited feedback have less need for their salespeople to develop high levels of trust with their customer since the configuration is already established. For these situations, the need for open and regular personal communication with these customers is less.
Once again, subject verbatims were clear on this issue. Several of the respondents who were classified as loyal buyers did not want to "waste their time" seeing salespeople. Their feeling was that, since the relationship was established and comfortable, there was no real need to have regular meetings with salespeople. In fact, some viewed this aspect of the relationship to be a minor aggravation. When loyal buyers need information, they pick up a telephone and ask for it. Regular meetings do not add value to the existing relationship and, in fact, take time away from more important tasks. Undoubtedly, supplying companies with existing loyal relationships, and those which have a system to handle questions or complaints via the telephone, must assess whether salespeople should make regular sales calls. Therefore, the logic of the commonly employed heuristic of scheduling sales calls based on a customer's value to the firm, such as volume of sales, must be questioned, as well as, traditional measures of relationship quality, such as communication frequency. Further investigations would seem worthwhile.
Toward a New Paradigm for Buying Behavior
A key insight gained from our research is that multi-attribute compensatory models may not be a reasonable representation of how buyers make many business buying decisions. We have confirmed a new paradigm which includes the consideration of trust as a primary determinant of buying behavior in at least some business environments. Researchers attempting to understand the decision process of larger customers purchasing low-risk products may find traditional attribute-based models more predictive, but that assumption is unconfirmed. These models fail to capture the effect of trust and would most likely not predict purchasing behavior of small customers. Further, while our conclusions can only be confirmed for compensatory attribute-based models, questions should be raised as to the value of similar attribute-based approaches (e.g., conjoint analysis). However, we are not saying that product attributes are not important. Rather, customers will only purchase from companies when quality, price and service measure up and, at an emotional level, there is trust. Trust emerged as a critical factor in true consumer loyalty and was influential in the perception of the product, the openness of communications, and the ensuing purchasing behavior of the buyer.
Buyers in long-term relationships seek to use the strengths and skills of the suppliers to their advantage. Buyers in long-term relationships also benefit from improved quality and process performance and continuous cost reductions. However, suppliers must take care when entering a trusting relationship with buyers. The level of investments made by the supplier may far exceed the long-term gains to the supplier. Investing resources in long-term relationships to retain the loyalty of a selected set of customers over the long run often means forgoing maximizing sales or market share in the short term. Suppliers seek to win the loyalty of the targeted customers by improving the overall value of their product offering, either by lowering costs or by increasing functionality. The ultimate goal is to gain a greater volume of business or profit from these firms, either through an increase in the portion of the business they received or an expansion in the scope of the relationships. Finally, as manufacturers move to trim their vendor lists drastically, suppliers that do not focus on their existing customers might lose the entire business to a focused competitor. Because long-term relationships typically have a horizon of five to seven years or more, it means that the suppliers lose the customers for good.
Suppliers can obtain higher sales and earn greater returns from resources invested in maintaining long-term relationships through higher repeat sales and cross-selling opportunities from their current customers compared to resources spent in attracting new customers. Furthermore, existing customers can be sources of new product ideas, test sites for new product development, and also serve as showcase accounts (Jackson, 1985). Salespeople can also use customers in long-term relationships as aides in attracting new business. Kalwani and Narayandas (1995) find that long-term relationships with a few select customers do not seem to lead to a loss in the rate of sales growth over time. Supplier firms in long-term relationships are able to achieve a higher level of sales growth compared to supplier firms that use a transactional approach to servicing customers. Furthermore, they find that these firms increase profitability by reducing their discretionary expenses such as selling, general, and administrative overhead costs to a greater extent than their counterparts.
However, there are some serious risks involved to the seller. Customers that are willing to engage in long-term relationships may be the most difficult to service because they are sensitive to and rather intolerant of any sign of inadequacy on the part of the vendors upon whom they depend. These customers demand short-term price concessions while also expecting a long-term orientation from the supplier. Variables such as the level of trust and cooperation, adaptation to uncertainty, and goal congruence in the relationship change in long-term relationships and moderate the degree of their success. Tying up substantial resources could force suppliers to give up opportunities to service other customers. In the case of joint product development, customers expect suppliers not to use the technology developed specific to their relationship in dealings with competitors. In Japanese manufacturing, a supplier to a keiretsu usually is forbidden to do business with firms in other keiretsus.
While progress has been made in developing a better understanding of how trust impacts buyer loyalty, we have a long path in front of us if we are to understand effectively the range and nature of relationships between buyers and sellers in a business environment. Of considerable interest is how trust develops; that is, how does it start, what are its determinants, and what is its reciprocal nature in the evolution of relationships? Associated questions deal with how salespeople and marketing firms develop trust with their buyers as well as other members of the customer buying center.
Additional research should also evaluate how trust felt by some members of the buying center impacts trust felt by, and actions of, other members in the customer organization. This is an essential consideration in products where chains of control pass from Research and Development to Manufacturing and eventually to Purchasing as the buying process becomes more routine. The same set of concerns can be applied to the selling center. How does trust in the salesperson impact trust in technical support or inside sales support personnel, and which trusted relationships impact the ultimate purchasing decision? Future research should also focus on developing a better understanding of the range of company buying strategies employed and identify the determinants of those strategies.
Validations and extensions of our conclusions concerning the importance of trust relative to attribute-based models would include investigating low-risk buying situations for commodity products and high-risk situations for specialty products. The nonsignificant relationship between attitude and loyalty not only raises questions about the validity of attribute-based measures of attitude, it is also plausible that the measure itself is flawed. In particular, sixteen items may be too many for the typical business-to-business purchasing situation. The sixteen items may be measuring attitude toward three different objects: the product, the company, and the salesperson. One possible extension would be to identify the set of truly salient attributes for a particular buying domain through a protocol procedure, free elicitation, or factor analysis. Alternatively, a more systematic approach for analyzing importance and performance data could be considered (cf. Martilla and James, 1977). Such efforts would not only extend our understanding of the range of relationships between buyers and sellers, but aid in the understanding of the relevance of certain attribute-based research techniques and possibly provide more appropriate techniques to model the decision process in business environments.
Finally, we a need better understanding of the causes and implications of customer loyalty. Such research should further investigate issues of physical switching costs, customer size and risk, and develop a better understanding of how these and other factors cause customers to become or not become more loyal. We need to understand more fully how trust impacts both commitments to relationships between buyers and sellers and how commitments are either moderated or enhanced by trust. While conventional wisdom dictates that loyalty is of great value, it is equally conceivable that loyalty may place both buyers and sellers at risk by making them less cognizant of alternate opportunities and by building exit barriers. Therefore, we must also develop a better understanding of the true long-term value of loyalty in buyer-seller relationships in the exchange process. Future research of loyalty must consider the high level of relationship-specific investments and resources that are potentially involved for the partner firms in long-term relationships. This may necessitate tracking performance over time since the impact of long-term relationships can only be seen in the long run. That there is usually no benchmark available to assess the impact of long-term relationships further complicates this issue.
Many firms are attracted by the lure of strategic alliances, and the logic of such relationships is especially compelling when the proposed partner is a supplier. Inherent in any such alliance are the unique benefits and risks to each party. Trust is the necessary component that binds the two parties together, moderates the risk, and implicitly guarantees the future benefits. In order to be competitive, small companies need to trust their suppliers for reliable delivery of quality products. Alternatively, for large buyers, trust can be the element that converts "specification shoppers" to "strategic allies." As more and more manufacturers explore ways to build tight, long-term relationships with suppliers, both need to recognize the importance of instilling trust into the relationship.
Trust is a multifaceted phenomenon, manifested at least in two parts: trust in the salesperson and trust in the company. Trust appears to be based on the expectation that parties involved will honestly and reliably meet each other's future needs. While buyers expect the reliability and quality of continued supply, sellers expect loyal buying behavior in return. Therefore, both must be willing to invest in the development and continuation of the relationship and to use open communications and exhibit loyalty in their respective strategies. Increase customer loyalty and a domino reaction occurs. Powered by repeat sales and referrals, revenues and market share grow. Costs fall because resources allocated to replacing switchers are eliminated. Loyal customers expect a good price, but they desire value most of all. Rather than becoming an enemy, price then becomes a tool to filter out buyers whom will bolt for a penny.
Trust operates in an interactive, interdependent, escalating cycle. At the extreme, trust can cause a relationship to be so tight that economists call it "quasi-vertical integration" (two organizations function like one). However, if buyers commit time and effort to create and reciprocate seller trust, and if they publicly create barriers to their own exit, then they are vulnerable. This is the reality of strategic alliances of any kind. Strong alliances bring substantial benefits but at substantial costs. One of these costs is the lack of flexibility to change the relationship and exit painlessly. Ultimately, then, strategic alliances are based on mutual need. Mutual need, in turn, creates tension, conflict, and expectations for the future. But if a large amount of trust is present, such relationships are the basis for a formidable and durable strategic advantage.
Both authors contributed equally to this article. The authors would like to thank Rajiv Dant for providing many helpful comments on an earlier draft of this paper. Correspondence can be addressed to the second author at: Strategic Pricing Group Inc., 63 Boston Post Road West, Marlborough, MA 01752. Telephone number (508) 481-9775.
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|Author:||Chow, Simeon; Holden, Reed|
|Publication:||Journal of Managerial Issues|
|Date:||Sep 22, 1997|
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