The importance–performance analysis (IPA) is a widely used analytical technique that yields prescriptions for the management of customer satisfaction. IPA is a two-dimensional grid based on customer-perceived importance of quality attributes and attribute performance. Depending on the interplay of these two dimensions, strategies for satisfaction management can be derived. As theoretical and empirical work has shown, the relationship between attribute-level performance and overall satisfaction is asymmetric. These findings call into question the applicability of IPA. In this paper, an empirical study on customer satisfaction with a supplier in the automotive industry was undertaken. Using a regression analysis with dummy variables, the asymmetric relationship between attribute-level performance and overall satisfaction could be confirmed. Furthermore, it is shown empirically that the managerial implications derived from an IPA are misleading. Consequently, the traditional IPA needs to be revised.
Without question, quality and customer satisfaction are key drivers of financial performance. It is argued that satisfaction leads to increased loyalty, reduced price elasticity, increased cross-buying, and positive word of mouth. Numerous empirical studies confirm a positive relationship between customer satisfaction and profitability (e.g., Anderson et al., 1994, Eklöf et al., 1999 and Ittner & Larcker, 1998).
In industrial markets, the importance of assessing and managing customer satisfaction is widely recognized (e.g., Tikkanen, Alajoutsijärvi, & Tähtinen, 2000). It is crucial to identify the critical factors that determine satisfaction and loyalty. Each company, however, is constrained by limitations on the resources they have available. Therefore, it must be decided how scarce resources are best deployed to achieve the highest level of satisfaction. An effective method to set priorities is importance–performance analysis (IPA). It analyses quality attributes on two dimensions: their performance level (satisfaction) and their importance to the customer. Evaluations of attributes on these two dimensions then are combined into a matrix that allows a firm to identify key drivers of satisfaction, to formulate improvement priorities, and to find areas of possible overkill and areas of “acceptable” disadvantages. In practice, IPA is considered a simple but effective tool (e.g., Hansen & Bush, 1999). It is very helpful in deciding how to best allocate scarce resources in order to maximize satisfaction.
Two implicit assumptions underlie the IPA: (1) Attribute performance and attribute importance are two independent variables. (2) The relationship between quality attribute performance and overall performance is linear and symmetric.
Research in customer satisfaction, however, suggests that quality attributes fall into three categories: basic factors, performance factors, and excitement factors Anderson & Mittal, 2000, Gale, 1994, Johnston, 1995, Matzler & Hinterhuber, 1998, Matzler et al., 1996 and Oliver, 1997. In Kano's (1984) model of customer satisfaction, the relationship between performance and importance of a basic and an excitement factors is nonlinear and asymmetric. Furthermore, attribute importance can be interpreted as a function of performance. Basic factors are critical when performance is low. Their influence on overall satisfaction decreases when performance increases. The opposite is true for excitement factors. They become important determinants of satisfaction when performance is high but play an unimportant role when performance is low. Thus, Kano's model of customer satisfaction disconfirms the basic assumptions of IPA and calls into question its managerial implications. The purpose of this paper is twofold. First, using data from a customer satisfaction survey, it is intended to confirm Kano's model of customer satisfaction empirically. A regression analysis with dummy variables is used to assess the asymmetric relationship between attribute-level performance and overall satisfaction. These results then are used to demonstrate that the traditional IPA is misleading and that it needs to be revised.
In the following sections, IPA and Kano's (1984) model of customer satisfaction are described briefly. Then, the results of the empirical study are presented. In the final section of the paper managerial implications of the findings are discussed.
As has been shown in this study, the three-factor theory of customer satisfaction calls into question the applicability of IPA and its managerial recommendations. Managers need to be aware that a change of attribute performance (satisfaction) can be associated with a change of attribute importance. Therefore, it is crucial to estimate the relative impact of each attribute for high and low performance. Attributes need to be classified in basic, excitement, and performance factors.
If the asymmetries are not considered, the impact of the different attributes on overall satisfaction is not correctly assessed. Importance depends on performance (see Fig. 8). The importance of basic factors is underestimated if performance is high, and overestimated if performance is low. If the performance of excitement factors is low, their impact is underestimated and vice versa.
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Fig. 8.
Attribute classification and importance (adapted from Matzler & Sauerwein, 2002).
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In order to set the right priorities in customer satisfaction management, managers need to know into which category product attributes fall. Only then can effective decisions be made. As a rule of thumb, the following implications emerge: fulfil all basic factors, be competitive with regard to performance factors, and stand out from competition regarding excitement factors.
