直观模糊数下购物中心吸引力参数的提取与优先排序

Alireza Bakhshizadeh, Abdolreza Yazdani-Chamzini, Masoumeh Latifi Benmaran, Jonas Šaparauskas, Zenonas Turskis
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摘要

购物中心在分销系统和营销方面发挥着重要作用。这些购物中心为顾客提供适宜的氛围,使顾客在短时间内获得最佳服务。然而,为了吸引更多顾客以增加利润,购物中心之间的竞争十分激烈。因此,一个功能强大的模型可以帮助有关部门确定关键的竞争方面,并引导其努力提高业绩。然而,为了确定最相关的组成部分,已经开发出了许多策略。直觉模糊环境下的德尔菲技术,即直觉模糊德尔菲法(IFDM)研究,是一种基于群体的技术,可以简单地表述决策圈施加的不确定性。另一方面,多标准决策(MCDM)方法,如分析网络过程(ANP),是一种考虑相互关系的数学工具,用于对多个标准进行排序。然而,ANP 无法解释决策过程中的不确定性。同样,直觉模糊集(IFS)可以利用给定的尺度来表达模糊性和不确定性。由于 IFS 在处理复杂性和模糊性方面非常稳健,因此 IFS-GANP(群体决策下 IFS 和 ANP 方法的集成模型)可以对情况进行更具体的描述。因此,IFS-GANP 方法优于传统 ANP 和模糊 ANP。为了证明该模型的可行性,我们展示了一个案例研究,对影响零售中心吸引力的重要因素进行了评级。结果表明,因子 C31(位置)的值为 0.202,在吸引顾客方面发挥了最大作用。
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EXTRACTING AND PRIORITIZING THE ATTRACTIVENESS PARAMETERS OF SHOPPING CENTERS UNDER INTUITIONISTIC FUZZY NUMBERS
Shopping center plays an important role in distribution system and marketing. These canters provide an appropriate atmosphere for customers; so that, the customers achieve the best service within a short time. However, there is an intense competition among shopping centers to attract more customers for increasing the profit. Therefore, a powerful model assists authorities in identifying the critical competitive aspects and directing their efforts toward performance improvement. However, a number of strategies have been developed to identify the most relevant components. The Delphi technique under intuitionistic fuzzy environment, called intuitionistic fuzzy Delphi method (IFDM) study, is a group-based technique that can simply formulate the uncertainty imposed by decision making circle. On the other hand, multi criteria decision making (MCDM) method such as analytical network process (ANP) is a mathematical tool for taking into account mutual relationships in order to rank a number of criteria. Nonetheless, the ANP is unable to account for the uncertainty involved in the decision-making process. Similarly, the intuitionistic fuzzy set (IFS) can express ambiguity and vagueness by utilizing the given scale. Because the IFS is robust in dealing with complexity and ambiguity, the IFS-GANP (an integrated model of the IFS and ANP methods under group decision) can result in a more specific description of the situation. As a result, the IFS-GANP approach outperforms both conventional ANP and fuzzy ANP. To demonstrate the model’s feasibility, a case study rating the essential aspects impacting the attractiveness of retail centers is shown. The result demonstrates factor C31 (Location) with value of 0.202 plays the greatest role in attracting customers.
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