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There is a pressing need for practitioners to adopt viable analytic procedures that may help them optimize resource allocation to strengthen customer satisfaction. This paper reviews a range of procedures used for measuring customer satisfaction that are identified in the literature and tests which procedures might be more useful to practitioners.

Customer satisfaction measurement procedures developed in the literature are reviewed to assess the non‐linear and asymmetric relationship between attribute performance and overall satisfaction. A convergent validity test between the two measurement procedures that the review suggests are the most suitable for application in practice is then conducted to discover the relative merits of each. The test is based on an empirical investigation carried out in the mobile communication industry.

Two measurement procedures were identified as the most appropriate to practitioners, “regression with dummy variables” and the “Importance Grid”. These were compared using a convergent validity test, which revealed a lack convergent validity between the two. Discussion about the reliability of the two procedures and the implications for practice is provided. On balance, the regression with dummy variables was identified as the better approach.

The paper highlights the importance that recognition is given to the non‐linear and asymmetric response of customer satisfaction to the performance of different product/service attributes if appropriate decisions are to be made for allocating marketing resources. While research on customer satisfaction has emphasized the need to account for the non‐linear and asymmetric relationship between attribute performance and overall satisfaction, no effort has been made to disseminate these insights fully among practitioners. Since understanding the relationship between attribute performance and overall satisfaction is paramount if resource allocation to improve attribute performance is to be prioritized correctly, there is a pressing concern to move customer satisfaction programs closer to the theory predictions. A range of measurement procedures is reviewed and compared. Through this work, academics and practitioners may gain further insight into procedures for measuring customer satisfaction and an understanding of the relative benefits and limitations of the procedures that may be adopted.

To investigate the theoretical foundations of price as a multi‐dimensional component of value and to examine the nature of the relationship between price‐attribute perception and overall price evaluation.

The economic theory of the distribution of surplus across customers and the equity theory are used to develop the hypotheses about the multi‐dimensional nature of the price construct. Prospect theory is used to predict the relationship between price‐attribute performance and overall price evaluation. Data were collected through a structured questionnaire regarding mobile communications operators in Italy. After carrying out a principal factor analysis, several regression models were run to test the hypotheses.

The results confirm that price is a multi‐dimensional construct (i.e. made up of cheapness, fairness and variety), yet they do not fully support the prospect theory predictions.

Multi‐item price measurement scales need to be further developed and validated. The theoretical framework needs to be further validated in other industries to assess the external validity of these findings.

Different dimensions of price represent different “evaluation categories”, all related to importance, yet vastly different in how one ought to respond to each of them. For price dimensions showing an asymmetric relationship with overall price evaluation, relative importance is a function of performance.

This paper extends the price conceptualization from a uni‐dimensional to a multi‐dimensional construct and suggests an integration of prospect theory. It offers a contribution for research on evaluation measurement procedures as well as on price and value management.