工商管理学院知识库

摘  要

近年来，随着旅游业的发展，自驾游受到越来越多游客的青睐，游客对自驾游服务质量的要求也越来越高，为游客提供服务的主要是自驾游APP平台，但自驾游APP在游客服务质量上有待于提高，例如在导航、规划行程等方面，因此对自驾游APP服务质量的提升迫在眉睫。已有研究主要侧重于自驾游的概念、综述、服务体系、产品开发与优化、游客行为研究等，但关于自驾游APP以及自驾游APP服务质量评价的研究较为缺乏，因此构建自驾游APP服务质量关键评价指标有重要的理论和现实意义。评价指标根据用户需求收集数据进行研究更具科学性，QFD正是这样一种方法，能将顾客要求转化为产品设计。有部分学者将QFD引入服务质量评价研究，但将QFD引入自驾游APP服务质量评价的研究较为缺乏，因此本文致力于运用QFD构建自驾游APP服务质量关键评价指标，对理论进行补充，同时为实践提供指导。

本文以QFD方法对自驾游APP进行研究，首先发放调查问卷确定游客需求及重要度。其次将游客需求与现有研究成果进行归纳梳理，确定自驾游APP服务质量要素。再根据游客需求-质量要素关联系数构建关联矩阵。最后根据以上分析构建质量屋，确定自驾游APP服务质量要素的重要度，根据重要度选取分数较高的服务质量要素作为评价指标。根据结果，本文将自驾游APP服务质量关键评价指标划分为五大维度：可靠性、安全性、服务效率、智能化、社交性。为了验证所构建指标的合理性，先运用SPSS对爱自驾APP服务质量水平调研问卷所收集的数据进行信效度分析，发现结果与预期基本一致，效果良好；再运用模糊综合评价法对爱自驾APP服务质量进行评分，结果表明爱自驾APP的服务质量处于中等偏上水平。通过以上验证，表明本文所构建的自驾游APP服务质量关键评价指标是合理有效的。本文将QFD引入自驾游APP服务质量评价，构建了自驾游APP服务质量关键评价指标，对理论方法进行补充，同时对实践有一定的指导。

关键词：QFD  自驾游APP  服务质量  关键评价指标

Abstract

In recent years, with the development of tourism, self-driving tour is favored by more and more tourists, tourists have higher and higher requirements for the service quality of self-driving travel. The main service for tourists is self-driving travel app platform, but the service quality of the APP needs to be improved, such as navigation, travel planning and so on. Therefore, it is urgent to improve the service quality of self-driving travel app. Existing researches mainly focus on the concept, overview, service system, product development and optimization, and tourist behavior of self driving tourism. However, there is a lack of research on self-driving APP and its service quality evaluation, so it is of great theoretical and practical significance to build the key evaluation index of self-driving APP service quality. It is more scientific to collect data according to users’ needs. QFD is just such a method, which can transform customers’ requirements into product design. Some scholars introduce QFD into service quality evaluation research, but the research on introducing QFD into self-driving APP service quality evaluation is relatively lack. Therefore, this paper is committed to using QFD to build the key evaluation index of self-driving APP service quality, so as to extend the related theory and provide guidance for practice.

In this paper, the QFD method is used to study the self driving travel app. Firstly, the questionnaire is issued to determine the tourist demand and its importance. Secondly, the tourists’ demand and existing research results are summarized and sorted to determine the service quality elements of self-driving APP. Then the correlation matrix is constructed according to the correlation coefficient of tourist demand and quality factors. Finally, according to the above analysis, the house of quality is constructed to determine the importance degree of service quality elements of self-driving travel APP. According to the importance degree, service quality elements with higher scores are selected as evaluation indexes. According to the results, the key evaluation indicators of service quality of self-driving travel APP are divided into five dimensions: reliability, safety, service efficiency, intelligence and sociality. In order to verify the rationality of the constructed indicators, SPSS is used to conduct reliability and validity of the data collected from questionnaire on the service quality level survey of Love Self-driving APP. It was found that the results are basically consistent with expectations and the effect is good. Then the fuzzy comprehensive evaluation method is used to evaluate the service quality of Love Self-driving APP, and the results show that the service quality of Love Self-driving APP is above the average level. Through the above verification, it shows that the key evaluation index of service quality of self-driving APP constructed in this paper is reasonable and effective. This paper introduces QFD into the service quality evaluation of self-driving travel APP, and the key evaluation indexes of service quality of self-driving travel APP are constructed to extend theoretical methods and provide certain guidance for practice.

Keywords: Quality function deployment; Self-driving travel APP; Service quality; Key evaluation index