引用本文:马遵平, 谢泽氡, 邓天.餐饮业网络点评数量影响因素研究——以成都主城区川菜餐馆为例[J].西南师范大学学报(自然科学版),2019,44(8):86~91
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餐饮业网络点评数量影响因素研究——以成都主城区川菜餐馆为例
马遵平, 谢泽氡, 邓天1,2
1. 绵阳师范学院 旅游发展与规划研究中心, 四川 绵阳 621000;2. 西南财经大学 工商管理学院, 成都 611130
摘要:
网络点评数量是餐饮企业“网络人气”的直接反映,它能引导顾客进行消费决策,促进产品销售.为了解餐饮业点评数量影响因素,通过“大众点评”“百度地图”收集成都主城区1 929家川菜餐馆的相关数据,运用主成分分析进行数据处理,运用(准)泊松回归模型进行变量拟合.结果表明:餐馆的人均消费及团购项目数量对其网络点评数量没有显著影响;餐馆的口味、服务和环境的综合评分对其网络点评数量有显著的正向影响;从市中心乘公交、驾车和骑行到达餐馆的综合可达时间对其网络点评数量有显著的负向影响;综合评分影响程度大于综合可达时间.
关键词:  网络点评数量  川菜餐馆  成都主城区  (准)泊松回归模型
DOI:10.13718/j.cnki.xsxb.2019.08.015
分类号:F592.6;TS972.3
基金项目:四川省川菜发展研究中心项目(CC18G08);绵阳市社科联专项项目(MYSY2017QN05);绵阳师范学院校级科研机构建设项目(075010).
On Influencing Factors of Number of Online Reviews in the Catering Industry——A Case Study of Sichuan Restaurants in Main Urban Area of Chengdu
MA Zun-ping, XIE Ze-dong, DENG Tian1,2
1. Tourism Development and Planning Research Center, Mianyang Teachers'College, Mianyang Sichuan 621000, China;2. School of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China
Abstract:
The number of online reviews represents a restaurant's "online popularity". This datum also provides guidance for customers to make consumption decisions and promotes product sales. However, relevant research on the influencing factors on the number of online reviews in catering industry is still lacking. In this paper, therefore, data of 1929 Sichuan Restaurants in main urban area of Chengdu were collected on online platforms of "https://www.dianping.com/" and "http://map.baidu.com"; such data was processed by PCA, and multivariate fitting was conducted by using quasi-Poisson/Poisson regression model. The results show that 1) the per capita consumption of restaurants and the number of group purchase items have no significant influence on the number of online reviews. 2) the overall rating of food taste, service and environment of the restaurants have a significant positive effect on the number of online reviews. 3) the traffic time from downtown to restaurants by bus, car and bike has a significant negative impact on the number of online reviews. 4) the overall rating has a greater impact on the number of online reviews than the traffic time.
Key words:  the number of online reviews  Sichuan restaurant  main urban area of Chengdu  quasi-Poisson/Poisson regression model
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