Analysis of online food purchasing behavior: a study of Sri Lankan consumers

Piyumi Wijesinghe, Shashika D. Rathnayaka, Niranga Bandara, Dinesh D. Jayasena* (Corresponding Author), Jung Min Heo* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Online shopping has been undergoing significant developments in the South Asian region in the last decade. Using a representative sample of Sri Lankan consumers, this study explored online food purchasing behavior in Sri Lanka, a developing nation and island in South Asia. Data were collected from 562 respondents from all nine provinces in Sri Lanka using an online survey. Consumer attitudes were evaluated using factor analysis, and factor scores were
added as explanatory variables to the final model. An ordered logistic regression model was used to examine the impact of consumer demographics, economic variables, and consumer attitudes on online food purchases. Online food purchasing intensity was categorized into four groups that suited ordinal rankings: zero for never, low for rarely, medium for occasionally, and high for regularly. Results indicated that age, income, education, and living in urban
areas affect the online food purchasing behavior of Sri Lankan consumers. In addition, trust, convenience, and attitudes toward price were powerful drivers of online food purchasing. The findings have a number of significant managerial ramifications for creating strategies to promote online food purchases in developing South Asian nations like Sri Lanka. Moreover, promoting online shopping could be a potential solution for traffic congestion, ultimately helping to mitigate the negative externalities associated with it, such as carbon emissions and air pollution.
Original languageEnglish
Pages (from-to)927-940
Number of pages14
JournalKorean Journal of Agricultural Science
Volume50
Issue number4
DOIs
Publication statusPublished - 1 Dec 2023

Keywords

  • e-commerce
  • factor analysis
  • online food shopping
  • ordered logistic regression

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