Judgmental adjustments through supply integration for strategic partnerships in food chains

Can Eksoz,S Afshin Mansouri,Michael Bourlakis,Dilek Önkal

doi:10.1016/j.omega.2018.11.007

Abstract

Despite significant attention to strategic partnerships among members of supply chains, there has been limited research in food supply chains where such partnerships can provide a competitive advantage through forecasting practices of time-sensitive food items in volatile business environments. The current paper aims to close this gap by examining manufacturers’ strategic partnerships with retailers, with a special emphasis on information sharing, integration, and collaborative forecasting of time-sensitive products in food supply chains. Through Partial Least Square (PLS) analysis of survey data collected from 105 food manufacturers in Europe and North America, this research reveals the importance of strategic partnerships for satisfaction from forecasts generated for perishable, seasonal, promotional and newly-launched products in the food industry. Group forecasting and manufacturers’ external integration with retailers are found to be significant for strategic partnerships. In addition, our findings show that manufacturers’ internal integration is positively associated with group forecasting, external integration and judgmental adjustments. Our findings also reveal that information sharing with retailers facilitates consensus forecasts in group forecasting. These results provide unique insights to researchers and practitioners of human judgment in supply chain forecasting towards enhancing strategic partnerships in food supply chains.

Highlights

The Food Supply Chain (FSC) distinguishes itself from other supply chains due to its complicated, dynamic and fragile profile, where the quality and availability of products are critical and the primary goal is to “guarantee the provision of safe and healthy products that are fully traceable from farm to fork” ([7], p.2)
Given the complexity of the model and relatively small sample size, the Partial Least Square (PLS)-SEM technique seems to be appropriate for data analysis while the other option was Structural Equation Modeling (SEM), which is “a statistical methodology that takes a confirmatory approach to the analysis of a structural theory bearing on some phenomenon” ([10], p.3)
There are an abundance of studies which employed the confirmation oriented SEM technique (e.g. He et al [44], Ramanathan and Muylderman [81] and Ramanathan and Gunasekaran [80]) while others relied upon the exploratory technique of Partial Least Squares Structural Equation Modeling (PLS-SEM) (e.g. Braunscheidel and Suresh [8], Perols et al [77], Oh et al [71] and Sawhney [88])

Summary

Introduction

The Food Supply Chain (FSC) distinguishes itself from other supply chains due to its complicated, dynamic and fragile profile, where the quality and availability of products are critical and the primary goal is to “guarantee the provision of safe and healthy products that are fully traceable from farm to fork” ([7], p.2). The shelf life of products and price variability emerge as significant concerns [2], while information sharing between partners are vital for forecasts due to the heterogeneous structure of FSC [122], in addition to the supportive role of IT for the integration of partners [19]. This necessitates chain members’ strategic integration, that is “the degree to which a manufacturer strategically collaborates with supply chain partners and collaboratively manages intra- and inter-. Manufacturers and retailers face considerable barriers in their efforts to foresee the demand for perishable, seasonal, promotional and newly-launched products in such partnerships [27,66]

Methods

Results

Conclusion