IS Atlas
ms·2019년 2월 20일

Collusion by Algorithm: Does Better Demand Prediction Facilitate Coordination Between Sellers?

Jeanine Miklós‐Thal, Catherine E. Tucker

Management Science

151
피인용
16.5
FWCI
14
IS/마케팅/OM 탑저널 피인용
18
IS/마케팅/OM 탑저널 참고문헌
01Abstract

We build a game-theoretic model to examine how better demand forecasting resulting from algorithms, machine learning, and artificial intelligence affects the sustainability of collusion in an industry. We find that, although better forecasting allows colluding firms to better tailor prices to demand conditions, it also increases each firm’s temptation to deviate to a lower price in time periods of high predicted demand. Overall, our research suggests that, despite concerns expressed by policy makers, better forecasting and algorithms can lead to lower prices and higher consumer surplus. This paper was accepted by Joshua Gans, business strategy.

02연구 흐름

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03비슷한 논문

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04이후 연구

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05선행 연구

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06서지 정보