Evaluation of Online Grocery Platform Alternatives Using Fuzzy Z-Numbers

Duygu Sergi, I. Sari
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Abstract

Retail management has evolved into a new business model with the development of online shopping habits. There may be significant differences between onsite service and online service in terms of customer expectations. In this study, companies providing online grocery services in Turkey are evaluated by examining the services they provide from the perspective of customers. Fuzzy Z numbers, which also add the reliability of linguistic assessments to the analysis, are used in order to better describe the uncertainty. Fuzzy Z-analytic hierarchy method (FZ-AHP) is used to weight the decision criteria, and fuzzy Z-Grey relational analysis (FZ-GRA) method is used to find the best online market company. As a result of the analysis, it is revealed that the most important criteria for online grocery shopping are minimum order amount and brand diversity. The results are also compared with ordinary fuzzy methods. The comparison of the methods used in the study shows that although the ranks of the criteria and alternatives are the same, using fuzzy Z linguistic scale results in a wider interval for the weights and the scores of the alternatives which could change the ordering, especially in cases where criterion weights or alternative scores are very close to each other.
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基于模糊z数的在线杂货平台选择评价
随着网上购物习惯的发展,零售管理已经演变成一种新的商业模式。在客户期望方面,现场服务和在线服务可能存在显著差异。在这项研究中,在土耳其提供在线杂货服务的公司通过从客户的角度检查他们提供的服务来评估。为了更好地描述不确定性,使用模糊Z数,它也增加了语言评估分析的可靠性。采用模糊z层次分析法(FZ-AHP)对决策准则进行加权,采用模糊z -灰色关联分析法(FZ-GRA)寻找最佳在线市场公司。分析结果显示,网上杂货购物最重要的标准是最小订单量和品牌多样性。并将结果与普通模糊方法进行了比较。研究中使用的方法的比较表明,虽然标准和备选方案的排名相同,但使用模糊Z语言尺度会导致备选方案的权重和分数的区间更大,这可能会改变排序,特别是在标准权重或备选方案分数非常接近的情况下。
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