基于人工神经网络的在线出租车用户感知服务质量与满意度分析

IF 0.7 Q4 TRANSPORTATION
Vishal Devalalikar
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引用次数: 0

摘要

随着在线出租车服务的出现,尤其是在城市部门,印度的旅游业一直在快速增长。对交通服务的高需求和缺乏高质量的公共交通为许多出租车聚合商提供了获得客户的机会。人们选择出租车是因为它提供了理想的舒适、灵活性和隐私。它还有助于避免停车等问题。因此,评估客户/用户在在线打车服务时最需要的方面是很重要的。为了研究服务质量属性与出租车用户总体满意度的关系,我们在蒂鲁奇拉帕利市和浦那市进行了一项基于网络的调查。本文提出利用人工神经网络(ANN)分析网约车用户的感知服务质量,找出用户在网约车服务时考虑的重要属性。建立的模型表明,安全、等待时间、驾驶员行为、舒适性、清洁度和对驾驶员的信任等属性是对总体满意度有较高影响的变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Neural Network for Analyzing the Customer’s Perceived Service Quality and Satisfaction of Online Cab Services
India has been witnessing rapid growth in travel with the occurrence of online cab service especially in urban sector. The high demand for transport service and lack of good quality of public transport has given the opportunity to many cab aggregators to gain customers. People go for cab because it offers desirable comfort, flexibility and privacy. It also helps to avoid problem like parking issues. Hence, it’s important to assess the aspects that the customer/user is looking for the most while hailing an online cab service. To study the relationship of service quality attributes with overall satisfaction of the cab users, a web-based survey was conducted in Tiruchirappalli and Pune city. This paper proposes the use of Artificial Neural Network (ANN) to analyze perceived service quality of online cab users and to find out the attributes of importance a customer consider while hailing an online cab service. Model developed show that the attributes like safety, waiting time, driver behavior, comfort, cleanliness and trust on driver are some of the variables that have relatively higher influence on overall satisfaction.
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CiteScore
2.30
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