Customers' intention towards O2O food delivery service under the different characteristic of customer group-a case study of Suzhou Industrial Park

Abstract

Two research questions are identified and discussed. Relevant factors that influence the customer preferences were selected as research objects, data collection was based on 348 valid questionnaires, SPSS software was used for data analysis by the means of the multivariate logistic research model. Customer intentions include delivery payment, delivery time, food quality and brand trust. Customer reviews are related to customer preferences. The delivery payment is the most important factor when customers use food delivery service, but different groups of people have different tendency compared with their counterparts. All variables are designed based on baseline categories; the outcome of the model is only significant while comparing two groups of variables. Multivariate logistic research model is used to find customer preferences under the different characteristic of customer groups based on questionnaires and tries to forecast the possibility of the tendency of one targeting customer group in Suzhou Industrial Park. This research conduct a questionnaire on the Suzhou industry park, the respondents are mainly students and white collars customers, the characteristics of respondents are typical in this area.

Publication DOI: https://doi.org/10.1504/IJEBR.2020.107494
Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
Additional Information: Copyright © 2020 Inderscience Enterprises Ltd.
Uncontrolled Keywords: Customer preference,Targeting customer group,The multivariate logistic research model,Business, Management and Accounting(all),Economics, Econometrics and Finance(all)
Publication ISSN: 1756-9869
Last Modified: 26 Feb 2024 08:44
Date Deposited: 10 Jun 2022 14:44
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.ind ... EBR.2020.107494 (Publisher URL)
PURE Output Type: Article
Published Date: 2020-04-27
Authors: Chang, Victor (ORCID Profile 0000-0002-8012-5852)
Zheng, Nanjun
Shi, Yujie

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