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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.

The purpose of this paper is to propose a novel approach of fuzzy importance‐performance analysis (FIPA) to replace conventional importance‐performance analysis (IPA) for determining critical service attributes those really need to improve for achieving superior customer satisfaction.

First, referring numerous studies, conventional IPA has some erroneous assumptions, the customer satisfaction of attribute performance has the characteristic of three‐factor theory and the novel approach which integrates natural logarithmic transformation and partial correlation analysis is feasible for acquiring the implicitly derived importance of attributes. Second, according the fact and nature of fuzziness in human perception, this study applies fuzzy set theory to revise conventional IPA. Finally, the FIPA is proposed and subsequently implemented in a Taiwanese hot spring hotel case study.

The implementation of FIPA shows the determined critical service attributes are almost completely different from those attributes acquired by conventional IPA. Hence, the application of conventional IPA may cause practitioners make incorrect decisions of improvement priorities for service attributes and direct unsuitable quality‐based marketing strategies.

The proposed FIPA which integrates fuzzy set theory, three‐factor theory, partial correlation analysis and natural logarithmic transformation avoids the erroneous assumptions of conventional IPA, considers the nature of fuzziness in human perception and includes the actual importance of service attributes. Therefore, the proposed FIPA can effectively assist business managers in determining critical service attributes to improve service quality or customer satisfaction and to achieve competitive advantage.

This paper aims to present and compare a new method, improvement gap analysis (IGA), with two different versions of importance-performance analysis (IPA) – original IPA and diagonal IPA – focusing on how each method evaluates the possible impact of incremental innovations on customer satisfaction.

Two studies were carried out, one with users of mobile phones and another with users of a fitness centre. Mobile phone users answered questions about 24 attributes, of which six were incremental innovations at the time of the research. Users of the fitness centre answered questions about 16 attributes, of which three were incremental innovations.

Both case studies show that diagonal IPA overcomes two limitations of original IPA, in terms of IPA's failure to address: the high correlation between stated importance and customer satisfaction and the non-linear relationship between attribute performance and customers’ satisfaction. However, diagonal IPA is unable to identify the possible impact of incremental innovations on customer satisfaction. Thus, IGA is formulated to overcome both the problems with original IPA and the limitation of diagonal IPA.

The new method, IGA, uses expected customer dissatisfaction as a measure of attribute relevance. Its relationship with other methods used to evaluate attribute importance should be studied in the future.

The paper presents a new method (IGA) that is able to overcome problems of original and diagonal IPA methods and is also able to identify the possible impact of incremental innovations on customer satisfaction.

The purpose of this paper is to present the improvement gap analysis (IGA), a simple method to direct improvement opportunities in services that overcomes limitations of the traditional IPA regarding excitement and basic attributes.

The proposed method is theoretically developed and simulated. The theoretical simulation explains why IGA overcomes limitations of the traditional importance performance analysis (IPA) and how it could identify the impact of excitement innovative attributes. A case study with 287 customers of supermarkets was used to empirically test IGA and compare it to IPA.

The case study confirmed that the traditional IPA may lead to wrong improvement decisions for basic and excitement attributes. It happens because IPA is based on current attributes' performance and considers the relationship between attribute performance and customer satisfaction as a linear one. Also, it cannot identify the impact of excitement innovative attributes on customer satisfaction. Using only information about the company's customers, IGA could differentiate neutral from excitement attributes in the case study and, differently from IPA, it correctly identified improvement decisions for basic and excitement attributes.

Although IGA can theoretically distinguish between excitement innovative and neutral attributes, the case study presented in the paper did not test any innovative attribute. All attributes were already experimented or known by the subjects. Future research should empirically test IGA's real capability to identify excitement innovative attributes.

Managers should be aware that IPA may lead to wrong improvement decisions. It may leave excitement attributes unnoticed or direct the company to the improvement of basic attributes that already have adequate performance. IGA can be a good substitute for IPA with the additional advantage that it does not need information about competitors in the analysis. Also, since service quality evaluation depends heavily on customer perception, IGA is particularly suitable to this industry, but it could also be used for product improvement.

The literature presents several papers discussing IPA's problems. Some papers present the possible decision errors of IPA when dealing with excitement and basic attributes. Fewer have tried to propose methods to overcome these problems. This paper confirms the problems of IPA and presents a simple method that overcomes these limitations, distinguishing between excitement and neutral attributes. Also, because it does not use information about competitors, it can be easily used by companies that have difficulties in gathering such information.

Customer relationship management (CRM) strategies rely heavily on the importance and performance of the attributes that define a service. The aim of this paper is first to investigate the asymmetric relationship between performance of service attributes and customer satisfaction, and second, through a case study in the mobile telecommunication industry to prove that the importance of a service attribute is a function of the performance of that attribute.

An empirical study using questionnaires with a focus on service enquiring about the performance of service key attributes and overall customer satisfaction was conducted. The data were fed into the Kano customer satisfaction model and the importance‐performance analysis (IPA) method for analysis and comparison.

The results indicate that there is a dynamic relationship between service attributes and overall customer satisfaction. Service attributes have a different impact on customer satisfaction regardless of their classification. The importance of service attributes can be derived from their performance and this can be proved in the Mobile Telecommunication sector. Also this research concludes that the major weaknesses in the Mobile Telecommunication industry that cause the highest customer dissatisfaction are the range of phones, the accuracy of billing and payment, and the service plans, whereas the major strengths as a source of customer satisfaction are customer service quality, value for money and network performance.

The Kano model of customer satisfaction needs to be extended to other customer behaviour variables such as customer retention (e.g. purchase intention) and customer loyalty (e.g. word‐of‐mouth, feedback) for improved decision analysis. The paper does not include customer retention and loyalty factors.

The methodology employed here can be easily applied by marketers for evaluating customer behaviours and service quality performance for improved decision making and resource allocation.

There is little evidence that extensive work has been dedicated to studying the relationship between service attributes and customer satisfaction through Kano's model. The paper specifically investigates the applicability of the model and the key factors in the mobile telecommunication industry.

Importance-performance analysis (IPA) is an effective tool for firms to prioritise service quality attributes, but has limitations in evaluating and enhancing service quality within a competitive environment. The purpose of this paper is to present an evolved model of IPA – importance-performance benchmark vectors (IPBV) – as a benchmarking tool and investigate its applicability in the context of hotel service quality.

Empirical studies based on self-completion survey data from 150 customers of two full-service hotels in Taiwan were conducted in to examine the practical utility of IPBV.

Eight key benchmark typologies were identified and expressed as vectors in the IPBV model which are as follows: “sustainable advantage”, “potential strength”, “false advantage or outstanding advantage”, “cease-fire competition”, “false disadvantage or on-hand disadvantage”, “potential weakness”, “dangerous warning” and “head-on competition”.

The paper extends the methodology to more cases, and other service industries to test further the discriminatory power of the model and to explore the descriptors in the IPBV vector model. Alternative seven-point or nine-point Likert scales could be explored to test the discriminant validity using means. The alternative IPA diagonal approach focussing on GAP analysis may reveal alternative interpretations for the IPBV vector model. Other extended models of IPA, which include competitor analysis, should be compared in practice using a data set where both quantitative and qualitative data could be generated.

The paper proposes the two-dimensional IPBV model which retains the advantages of IPA, but also includes competitor or benchmark comparisons which enable organisations to analyse their relative competitive position. The two-part model provides both quantitative information and qualitative interpretation of relativities. The graphical matrix models provide simple quantitative analysis of attributes, whilst the IPBV vector model provides qualitative interpretations of the eight competitive market positions. Vector analysis enables the development of competitive strategies relative to benchmarks, or within a competitive set. Importance is retained and means that organisations can benchmark against a range of competitors prioritising specific attributes for resource allocation.

The interpretive utility of the model should be explored with practitioners and decision makers in the service industries. The model has been designed for practical use in industry to inform operational and strategic decision making, its usefulness in practice should be explored and the attitudes of practitioners to the model should be tested.

Traditional approaches to benchmarking have adopted a one-dimensional approach that does not include a measure of the relative importance of the service quality dimensions in specific markets. This research develops a two-dimensional advanced model of IPA, called IPBV, which is based on vector relationships between key attributes of service quality. These vectors are explored and described in competitive terms and the model is discussed with regard to its implications for industry, practitioners and researchers.

This study aims to compare the customer satisfaction index (CSI) based on two approaches: stated‐importance and derived‐importance approaches. The stated‐importance approach uses both importance and performance scores in constructing the CSI, while the derived‐importance approach uses regression analysis to derive the betas for calculating CSI. The results show that the stated‐importance approach has achieved a higher CSI (79.1 percent) than that of the derived‐importance approach (57.4 percent). Both approaches find that the aspects of rooms and employees are the most important factors in driving customer satisfaction. Strengths and weaknesses of the two approaches are discussed.

This study aims to consider how the consumer ascribes importance to attributes that define a given product or service consumption experience relative to the extent that they contribute to satisfaction. Two separate dimensions of attribute importance are conceptualized, contrary to the more common view that there exists only a single form of importance. A hypothesis of how each type of importance changes throughout a consumption event is constructed in order to illustrate the nature of each importance dimension and how they operate in tandem.

Survey data taken from tourists who were asked to evaluate attributes describing a travel destination are used to illustrate how each type of importance changes.

Changes in each type of attribute importance occurred as predicted. Evidence indicates that the differences between the two types of attribute importance diminish as the consumption experience unfolds.

In addition to validating the theoretical underpinnings of this conceptualization of attribute importance, the study illustrates the usefulness of a framework developed to measure each type of importance.

Importance performance analyses, commonly used by organizations to evaluate and improve product and service performance, should recognize and incorporate these two separate types of attribute importance.

The study provides a new conceptualization of attribute importance.

Describes a method to analyze competitive standing of a product, brand or made‐in label vis‐à‐vis its competitors. Presents the results of an illustrative case study and discusses their implications.

The present work assesses destination and service quality attributes, in terms of exploring the stronger and weaker points within these entities. In addition, it explores the relative effect of holistic experiences of destinations and the service-specific attributes on tourists’ overall satisfaction with destinations. Building on the perception, performance, and service quality literature a survey is carried out at 5 different tourist attractions among 701 tourists from over 15 countries worldwide visiting Northern Norway. The results divulge that many destination attributes are important; however, tourists find that the destination performs correspondingly with the perceived importance of destinations. The service quality attributes are also important, but reveal a perceptual gap between importance and performance. The study finds that Northern Norway as a tourist destination should concentrate on “uniqueness” and “novelty” to enhance tourist satisfaction. Service providers are advised to keep up the good work on “giving a good impression and a nice welcome” to enhance tourist satisfaction.