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The purpose of this paper is to put forth maximum difference scaling to more accurately identify importance scores for customer requirements, which will also allow need‐based segments to be recognized and utilized within the QFD process.

An overview of research methods to explore customer requirements are discussed, followed by survey data analysis of customer requirements which compares and contrasts stated importance ratings to maximum difference scaling results.

The results from this study suggest that maximum difference scaling offers some advantages compared to traditional stated importance ratings, as well as other traditional methods for determining importance ratings. Providing significantly more discriminating power among customer requirements, maximum difference scaling allows researchers to have a more accurate and valid view of the relative importance of customer requirements as well as the ability to form need‐based segments.

Limitations of all research methods are discussed, including those limitations of maximum difference scaling.

The method put forth in this article provides practitioners with an improved methodology for determining the importance of customer requirements.

While maximum difference scaling has been proposed and tested in other fields, this is the first article of maximum difference scaling being applied to a QFD project.

Traditional methods of capturing and determining logistics attribute importance have serious research limitations. The purpose of this paper is to introduce maximum difference (MD) scaling as a new research methodology that will improve validity in measuring logistics attribute importance, overcoming many of the limitations associated with traditional methods. In addition, this new research method will allow logistics researchers to identify meaningful need‐based segments, an important goal of logistics research.

This paper provides an overview of MD scaling along with important research advantages, limitations, and practical applications. Additionally, a detailed research process is put forth so that this technique can be implemented by logistics researchers. Finally, an application of this technique is presented to illustrate the research method.

The importance of truck driver satisfaction attributes was analyzed using bivariate correlation analysis as well as MD scaling analysis. The two sets of results are compared and contrasted. The resulting rank order of attributes is very different and MD scaling results are shown to possess important advantages. As a result of this analysis, MD scaling analysis allows for meaningful, need‐based segmentation analysis, resulting in two unique need‐based driver segments.

From a practitioner viewpoint, knowing which attributes are most important will help in investing scarce resources to improve decision making and raise a firm's ROI. Although a number of relevant applications exist, the most important may include examining: the importance of customer service attributes; the importance of logistics service quality attributes; and the importance of customer satisfaction attributes.

MD scaling is a relatively new research technique, a technique that has yet to be utilized or even explored in existing logistics and supply chain literature. Yet, evidence is mounting in other fields that suggest this technique has many important and unique advantages. This paper is the first overview, discussion, and application of this technique for logistics and supply chain management and creates a strong foundation for implementing MD scaling in future logistics and supply chain management research.

The purpose of this study is to develop and formulate marketing strategies by utilizing the importance‐performance analysis (IPA) which is an easy‐to‐use analytical technique that offers prescriptions for the management of customer satisfaction.

Based on a survey from 400 direct sales channel customers, the findings suggest that the ratings and rankings of attributes were largely determined by the methods utilized to measure the attributes' importance.

The results of IPA presented by the current investigation reflect that the matrix is sensitive to the importance measure used.

This paper focuses on the Malaysian direct sales industry and concentrates only on application of importance‐performance analysis (IPA) to formulate customer satisfaction strategies.

The results have important implications for future research directions and business strategy practice.

This study is perhaps the first that concentrates on the application of IPA to formulate customer satisfaction strategies in Malaysia.

The purpose of this paper is to apply the proposed methodology to develop the product as per customer’s requirements (CRs) and increase customer satisfaction (CS).

The companies are using different methods to identify CRs and translate these requirements into new products. The Kano model is used to identify CRs. The result of the Kano model is used in quality function deployment (QFD) to decide the priority for improvements of CRs and the technical requirements.

The integration of the Kano model and QFD is applied on the mobile phone. The Kano model helps to find out the CRs which affect the CS, such as attractive (A) attribute, one (O)-dimensional attribute and must be (M) attribute. The QFD method helps to translate the CRs into technical requirements so that the designer can decide priority of requirements for improvement or new product development.

The proposed methodology can be applied to different consumers as well as industrial products.

The Kano model has been used in manufacturing as well as service sector. This work explores its usefulness and applicability for consumer and industrial products.

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.

Knowing which services are essential to tenants gives the housing associations the background to set priorities in maintenance policy and purchasing. The purpose of this paper is to explore residents' perceived importance of various maintenance services.

The research question is explored through a large‐scale survey of more than 6,000 tenants of Dutch housing associations. Priorities were studied in three different ways: respondents were asked to provide direct importance ratings, importance weights were derived from regression analyses, and, an importance‐performance analysis (IPA) was performed.

The results with regard to the priorities differ somewhat according to which method is used. However, the methods agree in that maintenance of heating and water systems and maintenance of hinges and locks of windows and external doors should get priority. If the goal is to increase customer satisfaction, the maintenance of exterior paintwork and bathrooms should also get appropriate attention. According to the IPA, the maintenance of ventilation systems should be taken good care of.

One limitation of the study is that residents have provided their preferences in maintenance service delivery without noticing the costs that are included with the several options. Furthermore, the priorities between service aspects, i.e. the aspects that determine the service quality of the maintenance service delivery were not measured.

This paper provides insight into resident's priorities with regard to maintenance services. This can be of use for companies, such as housing associations. Furthermore, it contributes to scientific knowledge with regard to the impact of different measurement methods.

Different applied methods for measuring priorities lead to different results. Both practitioners and researchers should take this into account when measuring priorities. The goal of the research should determine the choice of which method to use.

The purpose of this paper is to implement a multi-criteria preference disaggregation approach to measure logistics service quality (LSQ) of manufacturing companies’ supply chains.

A total 216 Greek manufacturing companies took part in a survey with the use of a dedicated questionnaire. They were asked to assess the LSQ of their primary supplier regarding a predefined set of criteria and sub-criteria. The data were analysed with the multi-criteria satisfaction analysis method, which represents an ordinal regression based approach used for customer satisfaction measurement.

Weak points of the suppliers as well as dimensions that drive satisfaction were identified. Furthermore, the competitive advantages of the suppliers as well as their priorities for improvement were spotted.

The sampling framework, including only the manufacturing companies operating in a specific area of Greece, does not ensure the full generalisation of the results. A larger sample of manufacturing companies from all over Greece would be useful to obtain more reliable results and would enable the comparison of LSQ for different manufacturing sectors.

The method used to assess LSQ of manufacturing companies can be installed as a permanent customer satisfaction barometer to measure, control and improve the LSQ provided to manufacturing companies as well as to other business sectors.

This paper proposes a method to explore the relationships between LSQ and industrial customers’ satisfaction to prioritise strategic plans of companies in the supply chains.

The purpose of this paper is to illuminate concerned companies to develop a better understanding of customer needs through reference of Kano model.

This paper facilitates decision-making process for the productive use of strategy management through a case study approach for corrugated industries in India. A hybrid approach is employed by calculating coefficients of satisfaction with S-CR (customer requirements and customer satisfaction (CS)) relationship functions and self-stated importance evaluation.

Kano’s model provides an effective approach for both industries and academic research in classifying different customer requirements into different categories based on their impact on CS. It empowers to obtain competitive and factual information about customer needs.

This study is limited in terms of sample size, domain of the study and the coverage of participants.

This paper suggests a valuable Kano approach for concerned organizations and practitioners, to correctly identify customer requirements and channelize their resources in right direction. Fulfilling customer requirements by providing them satisfaction and delight timely is only golden rule for sustaining in this competitive world.

The purpose of this paper is to examine the impact of internal control opinions on individuals' judgments about investments.

The approach used is a behavioral experiment where risk assessments and judgments about investments are made for four internal control opinion scenarios.

The results indicate that the type of internal control opinion made no difference for either risk assessments or investment decisions.

Participants are provided with data sets that do not contain all of the information they may acquire when they make actual investment decisions. Also, there is a lack of real consequences for making good or poor investment decisions.

The type of internal control opinion has no effect on risk assessments or investing intentions. Thus, other considerations apparently dominate internal control opinions when making judgments about investments.

This is the first paper to examine whether intentions to invest might be affected by internal control opinions.

The paper provides a step-by-step guide in the guise of a roadmap for service improvement initiatives using importance performance map analysis (IPMA).

To empirically illustrate how IPMA can be applied to any service industry, three sectors are considered; sports and fitness (study A), hospitality (study B) and higher education (study C). Following the proper selection of measuring instruments and their evaluation using structural equation modeling-partial least squares (Smart-PLS), IPMA is applied to identify those attributes having strong total effects (high importance) over the targeted construct (satisfaction) but which also have low average latent variable scores (low performance).

For sports and fitness (study A), the physical aspects and programme quality require managerial attention. For the hospitability sector (study B), it is service commitment, interaction quality and internal sense of happiness. Whereas for higher education (study C), it is administrative quality as well as the element of transformative quality, namely the university’s role in adding to its students’ emotional stability, which needs the attention of the top management.

This study provides researchers and practitioners with a roadmap for applying PLS-SEM and IPMA for continuous service quality improvement. The roadmap extends upon Ringle and Sarstedt’s (2016) work. It highlights critical decisions that need to be considered in the pre-analytical stages of the IPMA application, i.e. at the research design phase in selecting the most appropriate service quality measurement model specifications. It not only contributes to the existing body of knowledge by providing empirical evidence to advance theory development in the quality management field but also has implications for the practitioners in any service sector on where to focus their attention for an effective service improvement.