Algorithmic pricing in hospitality and tourism: call for research on ethics, consumer backlash and CSR

Purpose - This viewpoint paper calls for research on the social impact that comes with implementing algorithmic pricing in hospitality and tourism, in particular online price discrimination. It seeks to broaden the literature on consumer backlash and corporate social responsibility (CSR) to include algorithmic pricing. Design/methodology/approach - As algorithmic pricing will become increasingly important in hospitality and tourism, the authors argue that scholarly attention should be directed to two topics. Findings - First, there is a need for research on how algorithmic pricing triggers consumer backlash and online firestorms, and how these can be detected, prevented, and mitigated. Second, the authors need to increase our understanding of how deception, misconduct, dishonesty, and injustice in algorithmic pricing impact CSR performance, especially when differential pricing is enticed by deceptive yet legal algorithmic applications of indirect behavioral self-selection mechanisms. Social implications - Algorithmic price discrimination has been criticized for its potential to harm consumers, and doubt is cast upon the current ability of legal frameworks to set minimum standards of behavior. Originality/value - Algorithmic pricing includes a variety of computerized pricing applications aimed at increasing revenue and minimizing opportunity costs. With early use by airlines decades ago its diffusion has gradually extended to other sectors including hospitality and tourism. While algorithms are expected to increasingly impact pricing decisions, little research can be found on the topic, with the exception of a vigorous debate in the policy literature on its ethical implications and regulatory needs.

Automated summary

This paper calls for research on the social impact of algorithmic pricing in hospitality and tourism, particularly online price discrimination. The authors argue for studying how algorithmic pricing triggers consumer backlash and online firestorms, as well as understanding the impact of deception and injustice in algorithmic pricing on corporate social responsibility performance.