Effects of components of satisfaction on overall satisfaction in industrial markets.

ABSTRACT

High levels of customer satisfaction are important to marketers as both offensive and defensive tools and are capable of creating a lasting competitive advantage. The effects of four components of satisfaction, satisfaction with the product, interpersonal satisfaction, satisfaction with

price, and satisfaction with vendor performance, on overall satisfaction among industrial buyers are investigated. Results show that the component of satisfaction experiencing the largest level of negative (positive) disconfirmation serves as a lower (upper) bound on the level of overall satisfaction reported by the respondent.

1. INTRODUCTION

Satisfied customers represent "an indispensable means of creating a sustainable advantage in the competitive environment of the 1990s" (Patterson, Johnson and Spreng, 1997). Highly satisfied customers spread positive word-of-mouth, demonstrate readier acceptance of other products in the product line, and exhibit brand loyalty or increased intentions to repurchase (Rogers, Peyton and Bed, 1992; Grewal and Sharma, 1991). Patterson, Johnson, and Spreng (1997) find a strong link between customer satisfaction and repurchase intention, with customer satisfaction explaining 78% of the variance in repurchase intention. Thus, the investigation of overall customer satisfaction has important managerial implications.

The purpose of this study is to examine some of the systematic consequences of customer satisfaction and dissatisfaction among industrial buyers. Industrial customers' judgments of components of satisfaction are modeled as influencing overall satisfaction. Empirical results test the relationships that are proposed.

2. LITERATURE REVIEW

Overall customer satisfaction is generally considered to be a multi-attribute model (Woodruff, Cadotte and Jenkins, 1983). Components of overall satisfaction (SAT_OVERALL) that have been examined include product satisfaction (e.g., Oliver 1993; Homburg and Rudolph 2001), interpersonal satisfaction (e.g., Lele and Sheth 1988; Manning and Reece 2001), satisfaction with the price of the offering (e.g., Anderson 1996), and satisfaction with vendor performance (e.g., Sheth 1973).

Researchers have sought greater understanding of the overall satisfaction construct in industrial markets by examining the phenomenon in different situations. In a study of consumer markets, Mittal, Ross, and Baldasare (1998) show a consumer can be simultaneously satisfied with one or more components of satisfaction related to a specific offering while being dissatisfied with other components of satisfaction for that same offering. Thus, while experiencing relatively high overall satisfaction, a customer might be extremely dissatisfied with one or more aspects of that offering.

Extensive research into the factors influencing customer satisfaction has been conducted in consumer markets (e.g., Spreng, et al. 1996; Swan and Oliver 1991; Oliver and Swan 1989; Churchill and Surprenant 1982), but relatively little such research has been conducted in industrial markets. In spite of this dearth of research, Patterson, Johnson, and Spreng (1997) find that industrial buyers, like consumers, consider multiple attributes when evaluating overall satisfaction. While industrial buyers weight their judgments differently than consumers, the disconfirmation paradigm is applicable in B2B markets (Patterson, Johnson and Spreng, 1997). In the expectancy-disconfirmation model of customer satisfaction, the most widely accepted and studied model (Patterson, Johnson and Spreng, 1997), customers compare their perceptions of performance (not objective actual performance) with their pre-purchase expectations to form judgments about the experience (Olshavsky and Spreng, 1989). When expectations are met, i.e., when perceived performance is close to expectations, little conscious thought is given to the process. However, when perceived performance is higher (lower) than the expected level of performance, expectations are said to be disconfirmed. When expectations are lower (higher) than perceived performance, satisfaction (dissatisfaction) is experienced.

3. PROPOSITIONS

Satisfaction with the product, interpersonal satisfaction, satisfaction with the price of the offering, and satisfaction with vendor performance are independent variables that have direct effects on overall satisfaction.

The multi-attribute nature of overall satisfaction suggests that consumers are using some combinatory function to reach overall satisfaction judgments based on evaluations of components of satisfaction (Woodruff, Cadotte and Jenkins, 1983; Crosby and Stephens, 1987; Homburg and Rudolph, 2001). The function may be a step-function (Woodruff, Cadotte and Jenkins, 1983), a multi-variable linear function (e.g., Preis and Kellar 2003; Kellar and Preis 2003), or a nonlinear function (e.g., Anderson and Mittal 2000). An underlying question in these findings is whether several negatively (positively) disconfirmed components of satisfaction could harm (advantage) the overall impression of the purchase to the point that an overall satisfaction rating could be lower (higher) than all components of satisfaction. This seems unlikely so the following propositions are written:

P1: For each customer responding to the survey, let [X.sub.max] = max(SAT_PDT, SAT_PRICE, SAT_REL, SAT_PERF) and let Y = SAT_OVERALL. Then, for each individual surveyrespondent, Y [less than or equal to] [X.sub.max]. and

P2: For each customer responding to the survey, let [X.sub.min] = min(SAT_PDT, SAT_PRICE, SAT_REL, SAT_PERF) and let Y = SAT_OVERALL. Then, for each individual surveyrespondent, Y [greater than or equal to] [X.sub.min].

Having developed propositions, we now turn to the methodology for collecting data, analysis of the data, and the results.

4. METHODOLOGY AND RESULTS

A cross-sectional survey was conducted of members of the Institute for Supply Management (ISM), a national organization of purchasing professionals. Using the "URL embedded" design (Bradley, 1999), each member with an e-mail address on file with the organization was sent an e-mail requesting that they use a hot-link to connect to the website hosting the survey instrument. Surveys were completed on line.

Purchasing agents were asked to respond for one offering for which they had decision-making authority and which they had previously purchased. This latter condition assured that all respondents had relevant experience with the offerings on which they were reporting. As recommended by Drolet and Morrison (2001) single items, each using a seven-point, semantic-differential scale, were used to assess each component of satisfaction and to assess overall satisfaction. The scales were anchored at the end-points with the extremes "extremely satisfied" and "extremely dissatisfied." The mid-point was not anchored. Drolet and Morrison (2001) and Miller (1978) find single-measure items in general agreement with multiple-measure items. Single-measure items are commonly used in contemporary satisfaction research (see, for example, Bolton 1998; Rust and Zahorik 1995; Smith and Bolton 2002) and were used in this study, as well.

A total of 15,000 e-mail invitations to participate in the study was sent out. Reminder messages were sent two weeks after the initial messages. Of the messages that were sent, 3,566 (23.8%) were undeliverable. Of those that received messages, 230 (1.5%) did not receive the message in a timely fashion (autoresponses indicated that the recipients were on extended leaves, trips, etc.). A further 460 (3.1%) respondents claimed ineligibility. Thus, 10,744 recipients constituted the sample frame. The data collection was part of a larger study of dyads of industrial buyers who were members of the ISM and salespeople that called on them; responses had to be received from both parties in order to be considered usable. Usable responses were received from 103 dyads, yielding a response rate of 1.0%.

P1 and P2 were tested on a respondent-by respondent basis. It was observed that the highest-rated value of any component of satisfaction was always greater than or equal to the reported value of overall satisfaction. Similarly, it was observed that the lowest-rated value of any component of satisfaction was less than or equal to the reported level of overall satisfaction. This was true for all (100%) of the observations. The inspection was double-checked electronically. Thus propositions P1 and P2 are confirmed.

5. DISCUSSION

Propositions P1 and P2 confirm that levels of overall satisfaction are bounded by the levels of the components of satisfaction. Thus, overall satisfaction is rated neither higher nor lower than the highest and lowest ratings for components of satisfaction, respectively. The implication is that if managers can raise the ratings of the lowest-rated components of satisfaction for their offerings, their overall ratings will rise, as well.

6. MANAGERIAL IMPLICATIONS

The results of this study suggest that marketing managers should survey their customers and work to reduce dissatisfaction on all components of satisfaction. This is so regardless of the weighting given to any individual component of satisfaction, either through a statistical analysis such as multiple linear regression or through surveying customers to determine their perceptions of the importance of various components of satisfaction.

Understanding the factors that influence customer satisfaction can have great value to marketing managers. This value may occur in the form of greater customer loyalty or greater share of wallet. Marketing managers may find the results of this study applicable to many situations and should keep the results in mind when establishing policies and evaluating service levels. For example:

1. Since there is a natural tendency to concentrate on the things they understand or have control over, marketing managers may spend more time and resources "fixing" components of satisfaction that are not troublesome to customers. Managers should guard against this tendency by examining the area that experiences the greatest negative disconfirmation.

2. Marketing managers should periodically survey customers to assess levels of satisfaction. Of course major customers need to be satisfied but to the extent that factors influencing satisfaction differ between large customers and small ones, concentrating on only the components of satisfaction important to large customers will tend to ignore those components important to small buyers, to the extent that they differ.

3. Training should be provided to salespeople, who are often the only face from the supplier that customers see. Salespeople need to recognize signs of dissatisfaction before they run out of control and the salespeople need to be trained to a) probe to find out the basis for the dissatisfaction, and b) report those finding quickly to managers. If salespeople are penalized for reporting "bad news" their tendency will be to hide that news until it can no longer be contained.

The results of this study demonstrate that the component manifesting the lowest level of satisfaction is cause for concern for marketers since it serves as a lower bound for overall satisfaction; decreased overall satisfaction, in turn, is correlated with decreased repurchase intention (Eggert and Ulaga, 2002).

7. LIMITATIONS

The limitations of the study should be kept in mind when interpreting the results. First, while Drolet and Morrison (2001) report that single item measures are commonly used in satisfaction research and are reliable, single item measures may not fully capture the importance or emotion being measured. This study utilized single item measures for all components of satisfaction and for overall satisfaction. Second, four components of satisfaction are analyzed in this analysis; these four components may not represent the full range of components that customers evaluate when making overall satisfaction judgments. Third, the survey was conducted utilizing the embedded URL design involving e-mail and the Internet. Use of the Internet among purchasing professionals is high and increasing, nevertheless, not all organizations or purchasing individuals utilize these tools. Consequently, the results may not be representative of the population of purchasing professionals, in spite of the similarity in the demographics of the sample and the ISM membership. Fourth, this study aggregated responses from many different buying industries for many different commodities. Goods and services are commingled. Preis and Kellar (2003) and Kellar and Preis (2003) demonstrate that differences in the importance attached to components of satisfaction exist when purchasing offerings from industries with different levels of technology. Fifth, the satisfaction scores in this study are highly skewed to the satisfied end of the scale. Peterson and Wilson (1992) show that in studies of satisfaction virtually all results are skewed in this manner. The effects of such skewness on the resulting analyses are unknown. Sixth, the demographics of the sample are very similar to the demographics of the ISM, from which the sample was drawn. Nevertheless, the sample must be considered a convenience sample, with all of the cautions that entails. Seventh, the response rate to the e-mail invitation to participate in the study may indicate a systematic bias in the responses, making them non representative.

8. CONCLUSION

Propositions have been developed and tested to examine the effects of four components of satisfaction, satisfaction with the product, interpersonal satisfaction, satisfaction with the price, and satisfaction with the vendor's performance, on overall satisfaction among industrial buyers. Results demonstrate that the effects of the component of satisfaction manifesting the greatest level of positive (negative) disconfirmation forms an upper (lower) bound on overall satisfaction. This provides a simple method for approximating overall satisfaction.

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Author Profiles:

Dr. Gregory M. Kellar earned his Ph.D. at the University of Tennessee, Knoxville in 1996. Currently he is an assistant professor of business at Penn State University, Delaware County

Dr. Michael W. Preis earned his Ph.D. at The George Washington University in 2000. Currently he is an assistant professor of marketing at the Long Island University/C.W. Post Campus, New York.

Gregory M. Kellar, Penn State University, Delaware County Michael W. Preis, Long Island University/C. W. Post Campus