Intelligent customer complaint handling utilising principal component and data envelopment analysis (PDA)

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Faed, Alireza
Chang, Elizabeth
Saberi, Morteza
Hussain, Omar Khadeer
Azadeh, Ali
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2016
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Abstract

In this study, we consider customer to be a company's crucial asset. In order to have a fast, efficient decision-making process, it is vital that a customer relationship management (CRM) decision-maker condenses and abstracts the existing information. A questionnaire survey was conducted among respondents in order to obtain the required data. The questionnaire contains nine categories of satisfaction variables. To perform the analysis, we used principal component analysis (PCA) and data envelopment analysis (DEA). PDA has been utilised as an abbreviation for the integration of these two methods. To effectively analyse the procedure, PCA was utilised to assign a number to each category of questions related to each satisfaction variable. To achieve optimal precision, DEA was applied to the three categories of customers (‘most important’, ‘important’ and ‘ordinary’ customers) in order to determine the strengths and weaknesses of customer services from these customers’ perspectives. Customers were clustered and then DEA was used to determine their viewpoints. Using DEA, we have optimised our recognition of customers’ complaints and then provided recommendations and remedial actions to resolve the current issues in logistics and transport industry in general, and at Fremantle port in particular.

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Applied Soft Computing

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47

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Artificial intelligence

Numerical and computational mathematics

Science & Technology

Technology

Computer Science, Artificial Intelligence

Computer Science, Interdisciplinary Applications

Computer Science

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Faed, A; Chang, E; Saberi, M; Hussain, OK; Azadeh, A, Intelligent customer complaint handling utilising principal component and data envelopment analysis (PDA), Applied Soft Computing, 2016, 47, pp. 614-630

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