A customer based supplier selection process that combines quality function deployment, the analytic network process and a Markov chain

Asadabadi, Mehdi Rajabi

doi:10.1016/j.ejor.2017.06.006

Cited by 85 publications

(60 citation statements)

References 95 publications

(124 reference statements)

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“…To deal with the heterogeneity of DMs, AHP (Jia, Liu, Lin, Qiu, & Tan, ), Bodily's updated method (Wang, Fung, Li, & Pu, ), and fuzzy majority‐based method (Yan & Ma, ) have been developed to assign importance weights to each DM. To obtain the basic weights of ECs, objective weighting methods such as MDM (Li & He, ) and entropy‐based method (Li, Du, & Chin, ), subjective weighting methods such as AHP (Haber et al, ), analytic network process (Asadabadi, ), and BWM (Huang et al, ) have been widely used. Moreover, some researchers have viewed prioritizing the final importance ratings of ECs as a form of multicriteria decision‐making (MCDM).…”

Section: Literature Reviewmentioning

confidence: 99%

Group multigranular linguistic QFD for prioritizing service designs with combined weighting method

et al. 2019

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Qualification for the importance degree of service designs (SDs) is an essential stage in promoting accommodation performances to satisfy customers and gain market shares. Although various methods have been applied to derive the priorities of SDs, they do not effectively deal with the vagueness of information and the heterogeneity of decision makers (DMs). This study presents an improved quality function deployment (QFD) for prioritizing SDs. Multigranular unbalanced linguistic term sets are used to capture evaluators' ratings to cope with vague information. The multigranular linguistic information is unified by using a novel uniform method. This kind of information then is represented as linguistic distribution assessments using the concept of random preferences based on possibility interpretations of weight information. A consensus‐based mathematical programming model is established to determine the weights of DMs. Moreover, a combined structure that combines maximizing deviation and best worst methods is used to derive basic weights of SDs. Finally, an illustrative example of island accommodation management in Weizhou Island is provided to demonstrate the applicability and advantages of the proposed QFD framework.

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Section: Literature Reviewmentioning

confidence: 99%

Group multigranular linguistic QFD for prioritizing service designs with combined weighting method

et al. 2019

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“…Asadabadi () introduced a supplier‐oriented supplier selection method, which adopts the analysis of network process, the quality function deployment (QFD), and the Markov chain to solve the problem of supplier selection. Mkpojiogu and Hashim () studied the relationship between the Carnot model customer satisfaction scores and the importance of self‐requirements.…”

Section: Service Demand Analysismentioning

confidence: 99%

Modular configuration of service elements based on the improved K‐means algorithm

Zhang

2018

Expert Systems

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To reduce the vagueness and subjectivity of customer demand in the process of product–service system design, a fuzzy semantic calculation method is proposed to obtain the importance of service demand. In addition, according to the demand of the clustering of service modules, a new clustering method is proposed to analyse discrete data based on the improved K‐means algorithm that is based on the Kruskal algorithm. According to the criterion of the service module division and its weight, the correlation coefficient between any two service activities is judged to form the comprehensive correlation coefficient matrix, and the comprehensive dissimilarity matrix can be obtained by the additive model. Then, this method calculates the minimum cost spanning tree (MCST) using the Kruskal algorithm. The different clusters of service activities with different centres can be found based on the MCST, and the edge values can be calculated by the improved K‐means algorithm. This paper uses 28 service activities of excavators. These activities can be divided into K (K = 4, 5, 6, and 7) clusters by the improved K‐means algorithm. Finally, the service element configuration model is established based on the demand weight, which is optimized by using the maximum customer satisfaction of competition.

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“…This garage is lack of development particularly because of lack of customers. According to Asadabadi (2017), one of the things that affect the number of customers is customer satisfaction. After listening to complaints from several consumers, we find that consumers are less satisfied with the quality of AdiTeknik garage.…”

Section: Introductionmentioning

confidence: 99%

Improving Service of Quality using Quality Function Deployment

Ekasari¹,

Aziza²,

Prasnowo³

et al. 2019

SMBR

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AdiTeknik is one of the garages in Sidoarjo, East Java, Indonesia, engaged in repairing services industry tools. This garage recently has problems in attracting customers. Prior studies suggest that one of the things that affect the number of customers is customer satisfaction. After listening to complaints from several consumers, consumers said that they are less satisfied with the quality of the garage. This phenomenon become the trigger for us to investigate the customer satisfaction especially on the AdiTeknik garage. One method that can be used to help companies to improve the quality according to customer point of view is Quality Function Deployment (QFD). We find that there are twelve attributes of the desires and needs of consumers to improve the quality of garage service of AdiTeknik. Those are the quality of repair, cleanliness and neatness of the garage, complete facilities for customer, employee performance, repair results in accordance with demand, timeliness of completion, the ability to analyze problems, clarity fees and the completion time, warranty repair results, employee friendliness, ease of contacting a workshop, and a willingness to give feedback.

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A customer based supplier selection process that combines quality function deployment, the analytic network process and a Markov chain

Cited by 85 publications

References 95 publications

Group multigranular linguistic QFD for prioritizing service designs with combined weighting method

Group multigranular linguistic QFD for prioritizing service designs with combined weighting method

Modular configuration of service elements based on the improved K‐means algorithm

Improving Service of Quality using Quality Function Deployment

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