On fit uncertainty-reducing interventions in retail supply chains

Doctoral thesis, 2021

Fit uncertainty is used in this doctoral thesis to describe the customer’s experience of uncertainty about the physical fit of a product when shopping for experience goods. Experience goods are products whose attributes are difficult to ascertain without physical examination. In online retailing, the ability to provide experiential fit information is limited, which poses product flow and inventory challenges for supply chains, including product returns, lost sales, and obsolescence. Thus, product fitting is a critical pre-sales activity for customers to successfully purchase fit-dependent products, and retailers must facilitate the fitting activity in order to reduce unnecessary product handling. To foster improved performance for retail supply chains of experience goods subject to fit uncertainty, this doctoral thesis sets out to explore the effects of fit uncertainty and fit uncertainty-reducing interventions on retail supply chain performance.

Fit uncertainty-reducing interventions consist of existing digital product fitting and recommendation technologies. The research designs are included in the five appended research papers. Paper I uses a case survey of retail practices to develop a maturity model of digitalization of product fitting, and it proposes supply chain effects for each of the three maturity levels. Paper II uses three cases, design science, and interventionist research to conceptualize digital product fitting as an intervention that improves product flow and reduces lost sales in retail supply chains for experience goods. Paper III uses case research, quantitative analysis of return transactions, test of an intervention, and mathematical modeling to calculate product return costs associated with fit uncertainty in online retailing. Paper IV uses order and return transactions to investigate how online customers shopping for experience goods seek to mitigate fit uncertainty through different order-placing behaviors, and it assesses the cost implications of the behaviors. Paper V uses order and return transactions to explore the effects of an online apparel-fitting intervention on order performance outcomes and fit uncertainty-mitigating ordering tactics.

This thesis theorizes fit uncertainty-reducing interventions. The use of these interventions to facilitate the product-fitting activity can reduce fit uncertainty, leading to many benefits for the retail supply chain in terms of product flow, such as fewer returns and more sales. This thesis contributes to previous research on end-customer behaviors by focusing on order and return behaviors associated with fit uncertainty. The quantification of existent order and return behaviors is an important theoretical contribution to our understanding of the direct effects of fit uncertainty on retail supply chain performance. This thesis theoretically contributes to returns management and to inventory and assortment planning management; its practical contribution supports retail supply chains of experience goods that are reconsidering how they handle fit uncertainty and the unwanted effects thereof. This thesis provides hands-on knowledge on how the interventions work in real life and how they improve retail supply chain performance. Studying the link between fit uncertainty and retail supply chain performance is important for retailers and manufacturers' understanding of end-customer behavior and for improving product development and assortment planning to ensure availability of products that fit.