Interpretive structural modelling and fuzzy MICMAC approaches for customer centric beef supply chain: application of a big data technique

Mishra, Nishikant; Singh, Akshit; Rana, Nripendra P.; Dwivedi, Yogesh K.

Abstract

The food retailers have to make their supply chains more customer driven to sustain in modern competitive environment. It is essential for them to assimilate consumer’s perception to improve their market share. The firms usually utilise customer’s opinion in the form of structured data collected from various means such as conducting market survey, customer interviews and market research to explore the interrelationships among factors influencing consumer purchasing behaviour and associated supply chain. However, there is abundance of unstructured consumer’s opinion available on social media (Twitter). Usually, retailers struggle to employ unstructured data in above decision-making process. In this paper, firstly, by the help of literature and social media Big Data, factors influencing consumer’s beef purchasing decisions are identified. Thereafter, interrelationships between these factors are established using big data supplemented with ISM and Fuzzy MICMAC analysis. Factors are divided as per their dependence and driving power. The proposed frameworks enable to enforce decree on the intricacy of the factors. Finally, recommendations are prescribed. The proposed approach will assist retailers to design consumer centric supply chain.

Citation

Mishra, N., Singh, A., Rana, N. P., & Dwivedi, Y. K. (2017). Interpretive structural modelling and fuzzy MICMAC approaches for customer centric beef supply chain: application of a big data technique. Production planning & control, 28(11-12), 945-963. https://doi.org/10.1080/09537287.2017.1336789

• Acceptance Date: May 15, 2017
• Online Publication Date: Jul 11, 2017
• Publication Date: Sep 10, 2017
• Deposit Date: Jun 27, 2017
• Publicly Available Date: Jun 27, 2017
• Journal: Production planning & control
• Print ISSN: 0953-7287
• Electronic ISSN: 1366-5871
• Publisher: Taylor and Francis
• Peer Reviewed: Peer Reviewed
• Volume: 28
• Issue: 11-12
• Pages: 945-963
• DOI: https://doi.org/10.1080/09537287.2017.1336789
• Keywords: Big data; Interpretive structural modelling; Fuzzy MICMAC; Beef supply chain; Twitter; ISM
• Public URL: https://hull-repository.worktribe.com/output/452869
• Publisher URL: http://www.tandfonline.com/doi/full/10.1080/09537287.2017.1336789
• Additional Information: This is the accepted manuscript of an article published in Production planning & control, 2017. The version of record is available at the DOI link in this record.