An uncertain product demand in online retailing leads to loss of opportunity cost and customer dissatisfaction due to instances of product unavailability. On the other hand, when e-retailers store excessive inventory of durable goods to fulfill uncertain demand, it results in significant inventory holding and obsolescence cost. In view of such overstocking/understocking situations, this study attempts to mitigate online demand risk by exploring novel e-retailing approaches considering the trade-offs between opportunity cost/customer dissatisfaction and inventory holding/obsolescence cost.
Four e-retailing approaches are introduced to mitigate uncertain demand and minimize the economic losses to e-retailer. Using three months of purchased history data of online consumers for durable goods, four proposed approaches are tested by developing product attribute based algorithm to calculate the economic loss to the e-retailer.
Mixed e-retailing method of selling unavailable products from collaborative e-retail partner and alternative product's suggestion from own e-retailing method is found to be best for mitigating uncertain demand as well as limiting customer dissatisfaction.
Limited numbers of risk factor have been considered in this study. In the future, others risk factors like fraudulent order of high demand products, long delivery time window risk, damage and return risk of popular products can be incorporated and handled to reduce the economic loss.
The analysis can minimize the economic losses to an e-retailer and also can maximize the profit of collaborative e-retailing partner.
The study proposes a retailer to retailer collaboration approach without sharing the forecasted products' demand information.
