When Will Workers Follow an Algorithm?: A Field Experiment with a Retail Business

69 Pages Posted: 24 Apr 2018 Last revised: 11 Jan 2020

See all articles by Kohei Kawaguchi

Kohei Kawaguchi

Hong Kong University of Science and Technology

Date Written: November 1, 2019


This paper develops a new algorithm for increasing the revenue in a dynamic product assortment problem. Then, it identifies the challenges faced by managers in practice and discusses the conditions under which workers follow the algorithm. To do so, I conducted a field experiment with a beverage vending machine business. The experiment shows that, on average, workers are reluctant to follow the algorithmic advice; however, the workers are more willing to conform once their forecasts are integrated into the algorithm. Analyses using non-experimental variations highlight the importance of taking worker and context heterogeneity into account to maximize the benefit from adopting a new algorithm. Higher worker's regret, sales volatility, and fewer delegations increase the conformity, while they mitigate the effects of integration. Workers avoid high-traffic vending machines and focus on machines with high sales volatility when adopting the algorithm. The effects on the sales are largely similar to the effects on product assortments. The results emphasize the gap between nominal and actual performance of an algorithm and several practical issues to be resolved.

Keywords: Automation; Experimentation; Learning; Product Assortment Problem; Multi-Armed Bandit Problem; Algorithm Aversion; Conflicts of Interest; Productivity; Retail Business; Beverage Vending Machines

JEL Classification: L20; L81; M12; M15; M20

Suggested Citation

Kawaguchi, Kohei, When Will Workers Follow an Algorithm?: A Field Experiment with a Retail Business (November 1, 2019). Available at SSRN: https://ssrn.com/abstract=3157132 or http://dx.doi.org/10.2139/ssrn.3157132

Kohei Kawaguchi (Contact Author)

Hong Kong University of Science and Technology ( email )

6070 LSK Building, HKUST
Clear Water Bay
Hong Kong

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
PlumX Metrics