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Abstract

The purpose of this research is to develop an integrative framework for identifying and prioritising process improvement opportunities in a multi-stage service operation with the objective of improving quality perception. The proposed framework identifies important perceptual elements in the process and links the abstract nature of service quality perception with the operational measures (e.g., delivery time) of actual process performance. The proposed framework looks beyond customer SQ perception scores and analyses the actual performance of the process alongside customer perception in a multi-stage service process. The framework recommends that the customer perception of service quality and process performance are to be measured and analysed simultaneously for any process improvements. The applicability of the framework is verified by using a real-life case on customer service request and the service delivery process. Ordinal logistic regression is used to determine the process improvement priorities. The case study findings provide evidence and critical insight into the linkage of customer perception of service quality with operational measures of actual process performance.

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... Traditional charts are also applied to multi-stage service operations in some papers. For example, Ning, Shang, and Tsung (2009) provided an application of multi-stage procedures in a call center presented in Figure 1; for other studies see Sulek, Marucheck, and Lind (2006), and Roy and Mukherjee (2015). ...
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This paper develops control charts for monitoring the service times at the different stages of a congested system that provides a multi-stage service to its customers. A simulation-based optimization procedure is used to simulate the whole service process and determine the chart parameters that minimize the average time a customer spends in the system. Statistical constraints are also considered to enhance the statistical properties of the control chart. The proposed socio-statistical method may be of interest for a variety of applications. The method is applied to a fast food restaurant with two waiting stages.
... Quality control tools, total quality management, lean, Six Sigma and the integrated version of lean Six Sigma have found applications in diverse areas of manufacturing, service, healthcare, government and logistics. Roy and Mukherjee (2015) put forward a framework for quality enhancement in multiple stage processes. However, these procedures have not been implemented to analyse failure of components in the distribution unit. ...
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... Quality control tools, total quality management, lean, Six Sigma and the integrated version of lean Six Sigma have found applications in diverse areas of manufacturing, service, healthcare, government and logistics. Roy and Mukherjee (2015) put forward a framework for quality enhancement in multiple stage processes. However, these procedures have not been implemented to analyse failure of components in the distribution unit. ...
Article
The spares distribution centre is an important member of a manufacturing supply chain where the automobile components are packaged and distributed to customers and retail units. Though the components do not undergo processing in a spare parts centre, various other operations are performed during distribution that contributes to component failures. The Six Sigma DMAIC framework is used for the analysis of the failures effectively. The different causes of rejections are generated using the cause and effect diagram and each of these causes are validated with the help of experiments and other tools. The root cause of this problem arising in the distribution centre is identified to be the packing method. An economic solution to the existing cause of the problem is implemented with minor variations in the current packing method and the results are discussed. A structured follow up plan for continuous improvement is also suggested
Structured Abstract Purpose: To develop a tool, ‘The Excellence Grid’, to categorize attributes on the basis of their ability to impact customer perception of ‘excellence’ in service compared to perception of ‘good’ service. In addition, provide a 3-D model for Excellence-Performance Analysis, which can aid managers in formalizing the strategies for building perceptions of excellence about the service. Approach: The positive zone of performance is analyzed through a two-function modeling technique of ordinal logistic regression with the non-proportional odds to categorize attributes on grid. The tool is applied to two case studies to validate and establish the asymmetric impact of attributes on perceptions of ‘good service’ and ‘excellent service’. Findings: Similar to the Kano model for impact of attributes on positive and negative performances, findings from cases confirm the asymmetric impact of attributes in the positive zone of performance and establish ‘Excellence Grid’ as a means to categorize attributes as drivers of excellence. Practical implications: The ‘Excellence Grid’ tool is expected to empower managers to focus on strategies directed towards the goal of ‘service excellence’ and recommends that managers should not only strive for process improvement but also sharpen the external communication of service excellence. Contribution: The ‘Excellence Grid’ and the ‘3-D Excellence-Performance model’, proposed in this research, are expected to enrich the body of knowledge on operational tools to achieve service excellence. Using parameter estimates of the two-function model of ordinal logistic regression for service quality has not yet been reported in open literature.
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The relationship between attribute-level performance, overall satisfaction, and repurchase intentions is of critical importance to managers and generally has been conceptualized as linear and symmetric. The authors investigate the asymmetric and nonlinear nature of the relationship among these constructs. Predictions are developed and tested empirically using survey data from two different contexts: a service (health care, n = 4517) and a product (automobile, n = 9359 and n = 13,759). Results show that (1) negative performance on an attribute has a greater impact on overall satisfaction and repurchase intentions than positive performance has on that same attribute, and (2) overall satisfaction displays diminishing sensitivity to attribute-level performance. Surprisingly, results show that attribute performance has a direct impact on repurchase intentions in addition to its effect through satisfaction.
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The paper presents the results of an extensive study on the determinants of customer satisfaction for a retail bank. In doing so, it uses a revised version of the traditional analyses based on derived measures of attribute importance. The need for a revised methodology is prompted by the insights of the two- and three-factor theories of customer satisfaction, such as Kano's framework. Indeed, the evidence from 5000 customers of a prominent Italian bank confirms a non-linear and asymmetric relationship between attribute performances and overall customer satisfaction. The results from both a traditional and our revised approach are compared. While this approach can be applied across different industries, it should not be assumed that the numerical results presented in the paper apply to contexts with substantially different underlying characteristics. General trends and implications for banking services are reported in the conclusions.
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Many multistage service operations exhibit the cascade property, where performance at one stage is statistically correlated with performance at the preceding stage. Prior research on multistage services has analyzed each process stage independently or in an additive manner. Increased emphasis on Six Sigma initiatives in services has rekindled interest in the use of control charts to monitor and control service processes. This study examines the cause selecting control chart as a methodology to monitor and identify potential problem areas in an actual cascade service process and compares the diagnostic capability of the cause selecting chart to that of a traditional Shewhart chart. A grocery store whose parent company was implementing efficient consumer response (ECR) serves as the research context. This study models the grocery store as a two-stage cascade process and uses operating data from the store to construct a cause selecting chart and a traditional Shewhart chart for the front-end operation. Analysis of the two charts reveals that the cause selecting chart outperforms the traditional control chart as tool for signaling unusual variation in performance at the front-end stage. The analysis demonstrates that service managers can receive misleading or erroneous information from traditional control charts if the service process being monitored is a cascade process.
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Prior studies of how service quality evolves during the service delivery process either have used aggregate case data or have not obtained objective measurements of the actual dimensions of the service encounter on an individual basis. Reports on a study of a service delivery process in a hotel. Its conference day guests rated the delivery process based on four distinct service encounters: arrival, coffee break, lunch and conference room. The aim was to investigate how quality factors were related to their respective encounters and how cumulative satisfaction levels impact on each other and over time. Average satisfaction levels for each of the four encounters were found to be significantly different. Moreover, there was a clear trend in the cumulative satisfaction results. Arrival resulted in high satisfaction, the coffee break was not as satisfying and lunch rated the worst. Satisfaction rose again after the conference room experience. A factor analysis of all the questions, for a hypothesized four-factor solution, explained 72 per cent of the variation. All four encounters loaded highly and collectively on four distinct factors. Finally, a logistic regression model was used to rank the importance of the quality factors on their respective encounters. This information can be used to assist with the quality improvement of each encounter.
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The manufacturing of a product has been changing from a single geographical location to multi-locations due to the impact of information technology. The quality of the product manufactured is affected since gaps, such as a perception gap, an understanding gap, a design gap, a process gap and an operations gap, are widened due to business process outsourcing (BPO) activities. The lack of understanding of customer needs between various groups of people is one of the reasons why the quality of the end-product is not as expected. In order to overcome this situation a web-enabled model is proposed in this paper for integrating the voice of the end customer (VOC) in the product supply chain. A case study has been conducted in a heater manufacturing company and the continuous improvement possibly is put in place of product supply chain by integrating the VOC at all levels using quality function deployment (QFD).
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The experience of waiting for service is often the first direct interaction between customers and most service delivery processes. The literature on satisfaction with waiting has paralleled the literature on general service satisfaction, in which the relative importance of actual performance, perceived performance, and the disconfirmation between expected performance and perceived performance has been the subject of much debate. This paper presents an empirical study of satisfaction with waiting for service in a fast food environment. The study demonstrates that actual waiting time, perceived waiting time, and the disconfirmation between expected waiting time and perceived waiting time are all related to satisfaction with the waiting experience. It further demonstrates that the relative importance of each of these variables in predicting satisfaction depends on the differences in the needs of the customers. The implications for both theory and practice are significant: the importance of the perception of the experience increases as the importance of the satisfaction measure increases. More specifically, for customers who are concerned about time, the perception of the time spent waiting is a better predictor of satisfaction than the actual waiting time.
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Purpose – Over many years there has been an emergence of a large‐scale, worldwide academic movement concerned with the management of services. This paper, originally published in 1999, aims to chart the role and impact of operations management (OM) on this movement and to propose that the key focus for service academics should be with the application of frameworks and techniques. Design/methodology/approach – A conceptual discussion and approach are taken. Findings – Suggests that as the service movement has grown, with increasing overlap between the subjects of operations, marketing and HRM for example, there is a need to “return to roots”. Contends that service academics, in their bid to develop cross‐functional service management material, may have lost, or inadvertently ignored, the strength of their core disciplines. Refocusing on the traditional strengths of OM, such as performance quality, design, and operational improvement, might help provide a greater rigour to the developing subject of service management. Originality/value – Discusses nine areas for service operations research and suggests specific research questions.
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Describes a service design technique that allows managers to systematically analyse the quality of their service processes at a detailed, or transaction level, from a customer’s perspective. Following a review of alternative approaches the author argues for an approach which combines four critical elements; the service concept, the service process, transaction quality assessment, and messages - the customer’s interpretation of the service. Two case studies are used to illustrate the simplicity yet power of the technique. The key benefits of this technique are that it instils a “customer orientation” in managers and staff and encourages managers to “engineer” their service processes by identifying the root causes of transactions which do not accord with the organisation’s intentions.
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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.
Article
Describes a study performed in Canada to develop a reliable and valid scale for the measurement of the perceived service quality of bank services. A sample of retail banking customers was questioned. The proposed scale is called banking service quality (BSQ) and comprises 31 items which span six dimensions: effectiveness and assurance; access; price; tangibles; services portfolio and reliability.
Article
Purpose – The purpose of this paper is to promote successful application of quality function deployment (QFD) combined with quantitative techniques in service organizations. Design/methodology/approach – The paper assesses advantages and disadvantages of implementing the QFD method in service organizations. It discusses the integration of quantitative techniques with QFD in order to overcome some of the problems that organizations face in its application. The implementation of QFD along with AHP and ANP is studied within the bank sector. With the intention of completing the first House of Quality and thus prioritizing customers' bank selection criteria, a field survey was carried out with customers of a bank. Also, information from interviews with the bank's managers was utilized. Findings – The real world illustration confirms the compatibility between QFD, AHP and ANP and demonstrates the applicability and ease of use of the proposed model. Originality/value – A procedure is presented to help practitioners of this improved QFD framework deal with the challenges of quick response to dynamic shifts in customer needs by automating the House of Quality (HOQ). The paper could be useful to academics and practitioners in developing the integrated QFD‐AHP‐ANP method to design high quality services in various services.
Article
Briefly reviews some of the literature on service quality and in particular the zone of tolerance – the zone of acceptable or expected outcomes in a service experience. Uses the zone of tolerance to explore the relationships between customers' satisfaction with individual transactions, or service encounters, and their satisfaction with the overall service. Provides nine propositions which identify how customers' perceptions of the quality of a service can be influenced and how the thresholds of the zone of tolerance can be adjusted during the process of service delivery. Also considers some of the design implications of the propositions.
Article
Prior studies of how service quality evolves during the service delivery process have used aggregate case data in retrospect or have not obtained objective measures of the actual dimensions of the service encounter on an individual basis. Reports on a study of an actual hotel service delivery process partitioned into five distinct service encounters; check-in, the room, the restaurant, the breakfast and check-out. The aim was to investigate how quality factors were related to their respective encounters and how cumulative satisfaction levels impact on each other and over time. Average satisfaction levels for each of the five encounters were found to be significantly different. Moreover, there was a clear trend in the cumulative satisfaction results. Check-in resulted in high satisfaction, the room was not so satisfying and the restaurant rated the worst. Satisfaction scores rose after the breakfast experience and rose again after check-out. A factor analysis of all the questions, for a hypothesized five-factor solution, explained 78 per cent of the variation. All the first four encounters loaded highly and collectively on four distinct factors. The fifth factor largely comprised correct check-in booking and a correct bill on check-out. Finally, a logistic regression model was used to rank the importance of the quality factors on their respective encounters. This information can be used to assist with the quality improvement of each encounter.
Article
The study addresses the problem of service quality in the banking industry by modifying an importance-satisfaction (I-S) model in order to develop an integrated performance-measurement model for the banking industry, which would enable the priority of items for improvement to be determined. An importance and satisfaction questionnaire has been provided to determine which items do not fall into the appropriate performance-control zone of the performance-control matrix of the model. The performance-control matrix index provided enables the value of certain improvement objectives to be calculated. Finally, quality loss function is then adopted to rank the improvement objectives in terms of priority. A case study of a Taiwanese bank is then presented to demonstrate the applicability of the model in practice. The study thus presents a complete assessment model that helps managers to identify items for improvement, while simultaneously promoting cost and time efficiencies in service processes.
Article
The importance attributed to service sector industries has become more pronounced in the post-globalization era and the trend continues unabated even today. In such industries, direct assessment of the service quality is often not possible and the measurement has to be made in terms of suitable surrogates through various parameters related to delivery, support, cost, billing, access, speed, response to queries, complaint redressal and so on. The SERVQUAL models and their extensions (Parasuraman et al., 1985, 1988, 1994a, 1994b; Zeithamal et al., 1993) have delved into the various facets of measuring service quality and the factors that influence the customer expectations and their perceptions. However, a concrete quantification of the ‘service gaps’ used in such models, is seldom found in the literature. As such, it is very much necessary to quantify the ‘service gaps’ and also to quantify the expectation of the service parameters as perceived by the customers. In the present paper, a prioritization methodology of the service quality parameters has been proposed for a service sector industry based on surveys carried out on both the internal, as well as, external consumers. The responses of the surveys are Ordered Categorical in nature. As such, the conventional statistical techniques based on continuous responses are not suitable or justified. Moreover, it appears that the use of ‘difference scores’ in SERVQUAL or similar instruments, contributes to problems with the reliability, discriminant validity, convergent validity and predictive validity of the measure (Van Dyke et al., 1999). The idea of a gap without constructing difference scores may be conceived by the RIDIT scores, which is a well known technique in Categorical Data Analysis (Bross, 1958; Fleiss, 1973, 1999; Agresti, 1984). The proposed methodology is expected to encompass any service sector industry with well-defined service quality parameters and can be used as an alternative approach to the SERVQUAL instrument.
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