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Purpose -Importance-performance analysis (IPA) is a simple marketing tool commonly used to identify the main strengths and weaknesses of a value proposition. The purpose of this paper is to propose a revision of traditional IPA prompted by intuitions arising from the three-factor theory of customer satisfaction. The ultimate goal is to propose a decision support method, which is as simple and intuitive as the original IPA, but more precise and reliable than the solutions proposed thus far. Design/methodology/approach -In order to estimate indirect measures of attribute importance, the study uses the coefficients of a multiple regression with overall satisfaction ratings as the dependent variable. Additional calculations are then introduced in order to manage non-linear effects. Findings -Using empirical data from a survey among 5,209 customers of a European bank, the authors show how the proposed method can be more accurate than other solutions, especially as disregarding non-linear effects can prompt sub-optimal marketing decisions. Research limitations/implications -While the procedure in this study is applicable to any service business, the paper does not claim external validity for the numerical results of the empirical application: the authors acknowledge that only one dataset has been used. The authors' goal is merely to demonstrate a revised approach to IPA. Originality/value -First, the authors assert the need for an explicit distinction between the use of IPA for customer acquisition vs customer retention purposes. These two cases refer to distinct moments in the customer relationship life cycle and thus require separate analyses. The authors then propose a specific method for customer retention IPA. On this basis, they generate two priority charts: one for the purpose of maximizing customer satisfaction and one for the purpose of minimizing customer dissatisfaction.

We explore symbolic determinants of technology acceptance to complement more functional frameworks and better predict decisions to adopt information appliances. Previous research has investigated such variables as "need for uniqueness" and "status gains" to capture relevant aspects of technology acceptance. However, the more we move toward personal and ubiquitous technologies, the more we need to broaden and deepen our understanding of the symbolic aspects of adoption. This study reinterprets the symbolic dimension of adoption by broadening its scope to include the self-concept. Results support a prominent role for self-identity in predicting intentions to adopt mobile TVs. Self-identity is shown to complement the effects of "need for uniqueness" and "status gains" in this regard.

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The study focuses on the multifaceted motives for adopting personal technologies. Specifically, it uses earlier models of technology adoption to develop a model of smartphone acceptance. The model is unique in that it decomposes attitudinal beliefs into three components: functional value, hedonic value, and symbolic value. Latent class analysis facilitates the identification of three user types. The analysis shows that value drivers, control beliefs, and normative beliefs play different roles for determining smartphone acceptance, depending on three different individual characteristics (i.e., playfulness, public self-consciousness, and innovativeness). The paper makes a contribution to the information systems literature by providing an analysis of the drivers of overall value perceptions for multipurpose information appliances and of the role of individual differences among potential users in forming these attitudes.