Halal Purchasing Strategies of MSEs in the Malaysian Food Industry: An Exploratory Study on the Potential Use of CAQDAS in the Qualitative Evaluation of Multiple Case Studies

Nurulfaraiza Ariffin, Veera Pandiyan Kaliani Sundram and Mohd Hafiz Zulfakar

Information Management and Business Review, 2024, vol. 16, issue 3, 164-174

Abstract: This paper explores the potential of computer-assisted qualitative data analysis software (CAQDAS), specifically Nvivo 14, in facilitating the qualitative evaluation of multiple case studies. The focus is on halal purchasing strategies within micro and small enterprises (MSEs) in the food industry, a critical issue from a Shariah perspective that ensures halal integrity from source to consumer. The issue highlights that MSE leaders in Malaysia’s food industry failed to optimize halal purchasing in their management practices, which undermines their ability to increase probability. The objective is to explore the strategies for optimizing halal purchasing performance of MSEs in Malaysia’s food industry, on how these businesses navigate the requirements of halal compliance in their operational practices. Through an exploratory study, 10 MSEs were examined to investigate their halal purchasing structures, involving interviews with key stakeholders such as brand owners, company directors, halal executives, and CEOs. In-depth, semi-structured interviews provided insights into company structures, challenges, and halal purchasing strategies. Thematic analysis was employed, using an inductive pattern coding approach where codes emerged organically from the data and were categorized into themes and sub-themes. Findings revealed a variety of business types, with six individually owned companies and four family-run businesses, highlighting differences in employee numbers, business longevity, and owner demographics. The study also suggests a trend of generational succession in family-owned businesses. This research demonstrates the utility of CAQDAS in managing and analyzing complex qualitative data in case study research.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:rnd:arimbr:v:16:y:2024:i:3:p:164-174

DOI: 10.22610/imbr.v16i3S(I)a.4208

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