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Evaluation of eTail Services Quality: AHP Approach

Author

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  • Chetan A. Jhaveri
  • Jitendra M. Nenavani

Abstract

The purpose of this research study is to create comparative evaluation model to compare eTail firms across several eTail service quality dimensions. This research paper employs Analytical Hierarchy Process (AHP) for analysing decision problem into several stages which include objective, criteria and the alternatives to evaluate eTail service organizations. Non-probabilistic method of sampling was used to collect the responses. This study validated the formal e-Tailing quality scale eTailQ, with an alteration which resulted into its suitability in the Indian context. After validating the scale, four variables were taken for pair-wise comparison, namely website design, fulfilment/ reliability, security/ privacy and customer services. Results of this study imparts a better understanding of consumer preferences among different eTail service quality dimensions. This research would be helpful to practitioners in eTail industry to measure the quality of their services in comparison to their competitors. Since many eTail organizations have attained scale and volumes but are struggling to reach at sustainable stage, this research may be helpful to bring those organizations at sustainability by knowing which factor should be given more focus. The analysis of best alternative with given criteria by deploying AHP technique is first-ever done on e-Tail scale in India.

Suggested Citation

  • Chetan A. Jhaveri & Jitendra M. Nenavani, 2020. "Evaluation of eTail Services Quality: AHP Approach," Vision, , vol. 24(3), pages 310-319, September.
    • Handle: RePEc:sae:vision:v:24:y:2020:i:3:p:310-319
    DOI: 10.1177/0972262919898093
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    References listed on IDEAS

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    1. Marko Šostar & Vladimir Ristanović, 2023. "An Assessment of the Impact of the COVID-19 Pandemic on Consumer Behavior Using the Analytic Hierarchy Process Model," Sustainability, MDPI, vol. 15(20), pages 1-31, October.
    2. Jingsong Zhang & Hai Yang & Xinguo Xu, 2023. "Research on Service Design of Garbage Classification Driven by Artificial Intelligence," Sustainability, MDPI, vol. 15(23), pages 1-16, November.

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