Navigating Socio-Technical Dynamics of AI-Enabled Traceability Implementation in the Dairy Industry: A Fuzzy-DEMATEL Approach

Mohit Malik; Vijay Kumar Gahlawat; Rahul S Mor; Divya  Shukla; Md Shamimul Islam

doi:10.1007/s13198-026-03324-7

Navigating Socio-Technical Dynamics of AI-Enabled Traceability Implementation in the Dairy Industry: A Fuzzy-DEMATEL Approach

Mohit Malik
, Vijay Kumar Gahlawat^*
, Rahul S Mor^*
, Divya Shukla
, Md Shamimul Islam

^*Corresponding author for this work

School of Professional Business Education

Research output: Contribution to Journal › Article › peer-review

Abstract

Traceability in the dairy supply chain helps ensure high transparency, quality assurance, and regulatory compliance. At the same time, the implementation of traceability in the dairy sector faces several challenges; therefore, this paper examines the factors influencing the implementation of AI-enabled traceability in the Indian dairy industry. The Fuzzy-Decision-Making Trial and Evaluation Laboratory (DEMATEL) method investigated the relationship among identified factors and categorized them into cause-and-effect groups. The analysis highlighted “Lack of Standards and Regulations” and “High Cost of Infrastructure” with D-R values of 1.26 and 1.08 as the most influential causal factors, while “Supply Chain Integration” with a D+R value of 11.52 emerged as the most impacted effect factor. The factors underscore the critical need to develop strategic solutions to address the traceability challenges faced by the dairy industry. The proposed framework enhances socio-technical theory by explicitly outlining the complex interactions required to efficiently implement AI-enabled traceability. The findings provide policymakers, industry stakeholders, and researchers with valuable insights into prioritizing interventions, allocating resources, and fostering collaboration to improve dairy traceability practices.

Original language	English
Pages (from-to)	1-15
Number of pages	15
Journal	International Journal of Systems Assurance Engineering and Management
DOIs	https://doi.org/10.1007/s13198-026-03324-7
Publication status	Published - 14 May 2026

Bibliographical note

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure
SDG 11 Sustainable Cities and Communities
SDG 12 Responsible Consumption and Production
SDG 17 Partnerships for the Goals

Keywords

Artificial Intelligence (AI)
Traceability
Dairy Industry
Fuzzy-DEMATEL approach
Digital Transformation

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10.1007/s13198-026-03324-7

Malik_et_al_2026_Navigating_socio-technical_dynamics_of_AI-enabled_traceability_implementation_in_the_dairy_industry_a_fuzzy-DEMATEL_approach_AAMAccepted author manuscript, 847 KBLicence: CC BY

Cite this

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abstract = "Traceability in the dairy supply chain helps ensure high transparency, quality assurance, and regulatory compliance. At the same time, the implementation of traceability in the dairy sector faces several challenges; therefore, this paper examines the factors influencing the implementation of AI-enabled traceability in the Indian dairy industry. The Fuzzy-Decision-Making Trial and Evaluation Laboratory (DEMATEL) method investigated the relationship among identified factors and categorized them into cause-and-effect groups. The analysis highlighted {\textquotedblleft}Lack of Standards and Regulations{\textquotedblright} and {\textquotedblleft}High Cost of Infrastructure{\textquotedblright} with D-R values of 1.26 and 1.08 as the most influential causal factors, while {\textquotedblleft}Supply Chain Integration{\textquotedblright} with a D+R value of 11.52 emerged as the most impacted effect factor. The factors underscore the critical need to develop strategic solutions to address the traceability challenges faced by the dairy industry. The proposed framework enhances socio-technical theory by explicitly outlining the complex interactions required to efficiently implement AI-enabled traceability. The findings provide policymakers, industry stakeholders, and researchers with valuable insights into prioritizing interventions, allocating resources, and fostering collaboration to improve dairy traceability practices.",

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Navigating Socio-Technical Dynamics of AI-Enabled Traceability Implementation in the Dairy Industry: A Fuzzy-DEMATEL Approach

Abstract

Bibliographical note

UN SDGs

Keywords

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