Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression

被引:177
|
作者
Mehrolia, Sangeeta [1 ]
Alagarsamy, Subburaj [1 ]
Solaikutty, Vijay Mallikraj [2 ]
机构
[1] Christ Univ, Sch Business & Management, Bangalore, Karnataka, India
[2] Amer Coll, Madurai, Tamil Nadu, India
关键词
binary logistic regression; COVID-19; health belief model; online food delivery services; purchase decision; HEALTH BELIEF MODEL; ACUTE RESPIRATORY SYNDROME; BOVINE GROWTH-HORMONE; PRODUCT INVOLVEMENT; PURCHASE INTENTION; PLANNED BEHAVIOR; RISK PERCEPTION; PERCEIVED RISK; ATTITUDES; PREVENT;
D O I
10.1111/ijcs.12630
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study aims to empirically measure the distinctive characteristics of customers who did and did not order food through Online Food Delivery services (OFDs) during the COVID-19 outbreak in India. Data are collected from 462 OFDs customers. Binary logistic regression is used to examine the respondents' characteristics, such as age, patronage frequency before the lockdown, affective and instrumental beliefs, product involvement and the perceived threat, to examine the significant differences between the two categories of OFDs customers. The binary logistic regression concludes that respondents exhibiting high-perceived threat, less product involvement, less perceived benefit on OFDs and less frequency of online food orders are less likely to order food through OFDs. This study provides specific guidelines to create crisis management strategies.
引用
收藏
页码:396 / 408
页数:13
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