Mitigating demand risk of durable goods in online retailing

Date published

2020-11-13

Free to read from

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Emerald

Department

Type

Article

ISSN

0959-0552

Format

Citation

Ghadge A, Bag S, Goswami M, Tiwari MK. (2021) Mitigating demand risk of durable goods in online retailing. International Journal of Retail and Distribution Management, Volume 49, Issue 2, February 2021, pp. 165-186

Abstract

Purpose 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.

Design/methodology/approach 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.

Findings 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.

Research limitations/implications 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.

Practical implications The analysis can minimize the economic losses to an e-retailer and also can maximize the profit of collaborative e-retailing partner.

Originality/value The study proposes a retailer to retailer collaboration approach without sharing the forecasted products' demand information.

Description

Software Description

Software Language

Github

Keywords

Demand risk, Online retailing, Demand management, e-retailing, e-business

DOI

Rights

Attribution-NonCommercial 4.0 International

Relationships

Relationships

Supplements

Funder/s