The perks and perils of artificial intelligence use in lateral exchange markets

Cinthia B. Satornino; Dhruv Grewal; Abhijit Guha; Elisa B. Schweiger; Ronald C. Goodstein

doi:10.1016/j.jbusres.2022.113580

The perks and perils of artificial intelligence use in lateral exchange markets

Cinthia B. Satornino, Dhruv Grewal, Abhijit Guha, Elisa B. Schweiger, Ronald C. Goodstein

Research output: Contribution to journal › Article › peer-review

8 Citations (SciVal)

Abstract

Artificial intelligence (AI) clearly can benefit standard business models, in which firms sell products to buyers. But the outcomes of greater reliance on AI in peer-to-peer marketplaces, also known as lateral exchange markets (LEMs), might differ. Deploying AI likely improves outcomes for buyers and sellers (separately), as well as the effectiveness of their matching. In contrast, contingencies related to the power of the LEM and the presence and interaction of buyers and sellers (consociality) may evoke a dark side of AI. Guided by literature on LEMs, AI, and agency theory, the current work establishes buy- and sell-side tensions that arise when LEMs deploy AI. With a unique focus on buyers and sellers (cf. platforms) in LEMs and careful attention to the dark side, as well as the bright side, of AI, this article offers novel perspectives and implications for research and practice.

Original language	English
Article number	113580
Journal	Journal of Business Research
Volume	158
Early online date	10 Jan 2023
DOIs	https://doi.org/10.1016/j.jbusres.2022.113580
Publication status	Published - 31 Mar 2023

Funding

Elisa B Schweiger is a Lecturer (Assistant Professor) of Marketing at King's Business School. Her research centers around retailing, focusing on technology and AI in retailing, multi-sensory marketing, and pricing. Elisa's background is in psychology and marketing, and she holds a PhD from the University in Bath in consumer psychology. She employs a multi-method approach of behavioral experiments, field studies and text mining. Her work has appeared in various scientific outlets such as the Journal of Retailing and Risk Analysis. She serves on the editorial review board of the Journal of Business Research. Also, she acts as an ad-hoc reviewer for the Academy of Marketing Science, the Journal of Retailing, and the European Journal of Marketing. Her research is supported through numerous awards, including the Future Leader Award, Santander Mobility Awards, and multiple scholarships. She has received awards for her teaching and doctoral dissertation.

Keywords

Artificial intelligence
Lateral exchange markets
Peer-to-peer markets
Platform economics
Sharing economy

ASJC Scopus subject areas

Marketing

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10.1016/j.jbusres.2022.113580

Cite this

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title = "The perks and perils of artificial intelligence use in lateral exchange markets",

abstract = "Artificial intelligence (AI) clearly can benefit standard business models, in which firms sell products to buyers. But the outcomes of greater reliance on AI in peer-to-peer marketplaces, also known as lateral exchange markets (LEMs), might differ. Deploying AI likely improves outcomes for buyers and sellers (separately), as well as the effectiveness of their matching. In contrast, contingencies related to the power of the LEM and the presence and interaction of buyers and sellers (consociality) may evoke a dark side of AI. Guided by literature on LEMs, AI, and agency theory, the current work establishes buy- and sell-side tensions that arise when LEMs deploy AI. With a unique focus on buyers and sellers (cf. platforms) in LEMs and careful attention to the dark side, as well as the bright side, of AI, this article offers novel perspectives and implications for research and practice.",

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AU - Goodstein, Ronald C.

PY - 2023/3/31

Y1 - 2023/3/31

N2 - Artificial intelligence (AI) clearly can benefit standard business models, in which firms sell products to buyers. But the outcomes of greater reliance on AI in peer-to-peer marketplaces, also known as lateral exchange markets (LEMs), might differ. Deploying AI likely improves outcomes for buyers and sellers (separately), as well as the effectiveness of their matching. In contrast, contingencies related to the power of the LEM and the presence and interaction of buyers and sellers (consociality) may evoke a dark side of AI. Guided by literature on LEMs, AI, and agency theory, the current work establishes buy- and sell-side tensions that arise when LEMs deploy AI. With a unique focus on buyers and sellers (cf. platforms) in LEMs and careful attention to the dark side, as well as the bright side, of AI, this article offers novel perspectives and implications for research and practice.

AB - Artificial intelligence (AI) clearly can benefit standard business models, in which firms sell products to buyers. But the outcomes of greater reliance on AI in peer-to-peer marketplaces, also known as lateral exchange markets (LEMs), might differ. Deploying AI likely improves outcomes for buyers and sellers (separately), as well as the effectiveness of their matching. In contrast, contingencies related to the power of the LEM and the presence and interaction of buyers and sellers (consociality) may evoke a dark side of AI. Guided by literature on LEMs, AI, and agency theory, the current work establishes buy- and sell-side tensions that arise when LEMs deploy AI. With a unique focus on buyers and sellers (cf. platforms) in LEMs and careful attention to the dark side, as well as the bright side, of AI, this article offers novel perspectives and implications for research and practice.

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The perks and perils of artificial intelligence use in lateral exchange markets

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Keywords

ASJC Scopus subject areas

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