Abushaikha, Ismail, Bwaliez, Omar, Yaseen, Marwa, Hamadneh, Samer and Tamer, Darwish ORCID: https://orcid.org/0000-0003-1815-9338
(2025)
Leveraging animal feed supply chain capabilities through big data analytics: a qualitative study.
International Journal of Quality & Reliability Management.
(In Press)
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Text (Peer-reviewed version)
14987 Darwish (2025) Leveraging animal feed supply chain capabilities.pdf - Accepted Version Restricted to Repository staff only until 17 October 2025. (Publisher Embargo). Available under License Creative Commons Attribution Non-commercial 4.0. Download (415kB) |
Abstract
Purpose – Although big data analytics (BDA) has gained widespread interest in supply chain management (SCM) literature in recent years, our understanding of how it contributes to improved animal feed supply chains (SCs) is still underexplored. This study provides a greater understanding of the role of BDA in improving animal feed SC capabilities. Design/methodology/approach – A qualitative approach was used in this study. Data were collected through 32 semi-structured interviews from several actors involved in the production and supply of animal feed concentrates. Findings – This study provides rich in-description evidence of how BDA enhances performance in animal feed supply chain through improved logistics capabilities, quality control and information visibility. Our findings also suggest that organizational culture contributes to leveraging BDA capabilities in the feed processing SCs. Practical implications – The research provides an in-depth qualitative investigation of implementing big data in the feed processing SCs. The study provides practical implications for SC managers in the agrifood sector. Originality/value – The study contributes to the growing body of knowledge by providing field evidence of the relevance of BDA to animal feed SCs. This study adds to existing literature by providing an understanding of the role of internal culture of the organization in leveraging BDA capabilities in the SC. Keywords: Animal feed supply chain; Big data analytics; Sustainable supply chain, Qualitative research, Logistics capabilities. Paper type: Research paper.
Item Type: | Article |
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Article Type: | Article |
Uncontrolled Keywords: | Animal feed supply chain; Big data analytics; Sustainable supply chain, Qualitative research, Logistics capabilities |
Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HF Commerce > HF5001 Business > HF5410 Marketing Q Science > QA Mathematics > QA76 Computer software > QA76.9 Other topics > QA76.9.B45 Big data |
Divisions: | Schools and Research Institutes > School of Business, Computing and Social Sciences |
Depositing User: | Tamer Darwish |
Date Deposited: | 22 Apr 2025 09:12 |
Last Modified: | 22 Apr 2025 09:15 |
URI: | https://eprints.glos.ac.uk/id/eprint/14987 |
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