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Modelling the distribution performance in dairy industry: a predictive analysis

Mor Rahul S., Bhardwaj Arvind, Singh Sarbjit, Khan Syed Abdul Rehman

LogForum

2021

Vol. 17, no. 3

425--440

Background: Predictive analysis is a vital element to operations management as it facilitates real-time decision making and advanced planning on both strategy and performance. This paper identifies predictors to measure distribution performance in the dairy industry and to establish their importance. Methods: A distribution model is developed through exploratory structural equation modelling (SEM) techniques. The key performance predictors are marketing and distribution management, quality management, supply chain coordination, and brand management, which account for 71.5% of the variability in distribution performance. Results and conclusion: The predictors help improving the distribution performance, specifically in quality, order fill rate, and food safety. The outcomes of this research can help dairy professionals in managing their distribution channels, improving traceability, on-time delivery, and shipment accuracy. Consequently, these factors can improve distribution performance. Four predictors are elicited from the data to estimate the distribution performance and the relative importance of predictors is also established.