采购
认证
营销
业务
大流行
消费(社会学)
独创性
排名(信息检索)
2019年冠状病毒病(COVID-19)
广告
定性研究
经济
社会学
计算机科学
医学
社会科学
管理
疾病
病理
机器学习
传染病(医学专业)
作者
Tzong‐Ru Lee,Yong-Shun Lin,Erne Suzila Kassim,Stephanie Sebastian
标识
DOI:10.1108/bfj-10-2022-0926
摘要
Purpose The main objective of this research is to investigate the factors that influence consumer purchase decisions for halal products before and during the COVID-19 pandemic, based on the Engel-Kollat-Blackwell (EKB) theory. Design/methodology/approach The research was conducted as a survey. The influencing factors were determined based on the grey relational analysis (GRA) approach. Findings The findings indicate before the COVID-19 pandemic, consumers mainly purchased halal products based on four key factors: purchasing experience, certification label, Internet searches and past consumption experience. However, during the pandemic, the ranking and factors have changed to six indicators, which are past consumption experience, purchasing experience, certification labels, standardized specifications, Internet searches and halal certification labels. Research limitations/implications The study was limited by the sample size and geographical area. Nevertheless, the findings could be further explored by expanding related theories toward understand human decisions based on spiritual beliefs. Practical implications The findings of this study have important implications for research, practice and society. Understanding the factors influencing halal purchase decisions before and during the pandemic can help businesses, policymakers and halal certification bodies to better cater to consumers' needs and preferences and ensure the continued growth and development of the halal industry. Originality/value This study evaluates halal purchasing decisions between periods of certainty and uncertainty by using the GRA. Changes in halal consumption and purchase decisions in response to COVID-19 pandemic have become an emerging topic of discovery. The study addresses the gap in the literature regarding changes in consumer decision pattern.
科研通智能强力驱动
Strongly Powered by AbleSci AI