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作者：Feng, Kai; Hong, Han; Tang, Ke; Wang, Jingyuan
作者单位：Tsinghua University; Stanford University; Beihang University
摘要：This paper proposes a statistical framework of using artificial intelligence to improve human decision making. The performance of each human decision maker is benchmarked against that of machine predictions. We replace the diagnoses made by a subset of the decision makers with the recommendation from the machine learning algorithm. We apply both a heuristic frequentist approach and a Bayesian posterior loss function approach to abnormal birth detection using a nationwide data set of doctor dia...
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作者：Baillon, Aurelien; Bleichrodt, Han; Li, Chen; Wakker, Peter P.
作者单位：emlyon business school; Centre National de la Recherche Scientifique (CNRS); Ecole Normale Superieure de Lyon (ENS de LYON); Universite Claude Bernard Lyon 1; Universite Jean Monnet; Universite Lyon 2; Universitat d'Alacant; Erasmus University Rotterdam - Excl Erasmus MC; Erasmus University Rotterdam
摘要：This paper introduces source theory, a new theory for decision under ambiguity (unknown probabilities). It shows how Savage's subjective probabilities, with sourcedependent nonlinear weighting functions, can model Ellsberg's ambiguity. It can do so in Savage's framework of state-contingent assets, permits nonexpected utility for risk, and avoids multistage complications. It is tractable, shows ambiguity attitudes through simple graphs, is empirically realistic, and can be used prescriptively. ...
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作者：de Kok, Ties
作者单位：University of Washington; University of Washington Seattle
摘要：Generative large language models (GLLMs), such as ChatGPT and GPT-4 by OpenAI, are emerging as powerful tools for textual analysis tasks in accounting research. GLLMs can solve any textual analysis task solvable using nongenerative methods as well as tasks previously only solvable using human coding. Whereas GLLMs are new and powerful, they also come with limitations and present new challenges that require care and due diligence. This paper highlights the applications of GLLMs for accounting r...
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作者：Distelhorst, Greg; Stroehle, Judith C.; Yang, Duanyi
作者单位：University of Toronto; University of St Gallen; Cornell University
摘要：Industries and firms have diverse motives for adopting self-regulatory institutions. This research develops and tests propositions about one motive-exploiting opportunities to do business with reputation-sensitive buyers-as distinct from self-regulation to defend against regulatory or activist threats. To study the adoption and effects of selfregulation for reputation-sensitive buyers, we study the SA8000 socially responsible employment certification among large firms in China in the early 200...
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作者：Inderst, Roman; Griem, Fabian; Shaffer, Greg
作者单位：Goethe University Frankfurt
摘要：We show how manufacturers can benefit from contracts that incentivize retailers to purchase multiple products from the same manufacturer. We isolate two effects: first, under standard contractual inefficiencies, which give rise to double marginalization, such contracts can increase channel profits (the improved contractual efficiency effect); second, when a weaker product is tied to a particularly strong must-stock product, such contracts can also reduce a retailer's position and shift rent to...
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作者：Palley, Asa B.; Steffen, Thomas D.; Zhang, Frank
作者单位：Indiana University System; Indiana University Bloomington; Yale University
摘要：Consensus analyst target prices are widely available online at no cost to investors. In this paper, we examine how the amount of dispersion in the individual target prices comprising the consensus affects the predictive association between the consensus target price and future returns. We find that returns implied by consensus target prices and realized future returns are positively correlated when dispersion is low, but they become highly negatively correlated when dispersion is high. Further...
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作者：Bosch-Rosa, Ciril; Gietl, Daniel; Heinemann, Frank
作者单位：Technical University of Berlin
摘要：This paper investigates whether limited liability and moral hazard affect risk taking through motivated beliefs. On the one hand, limited liability encourages investors to take excessive risks. On the other, excessive risk taking makes it hard for investors to maintain a positive self-image when moral hazard is present. Using a novel experimental design, we show that subjects form motivated beliefs to self -justify their excessive risk taking. For the same investment opportunity, subjects inve...
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作者：Chaboud, Alain P.; Dao, Avery; Vega, Clara; Zikes, Filip
作者单位：Federal Reserve System - USA; Federal Reserve System Board of Governors; Federal Reserve System - USA; Federal Reserve System Board of Governors; Federal Reserve System - USA; Federal Reserve System Board of Governors
摘要：We study the impact of two changes in the minimum tick size, a reduction and a subsequent increase, on the trading behavior of fast and slow traders in the spot foreign exchange market. We find that the most notable impact of the tick size reduction is a substantial increase in the liquidity demand of high -frequency traders (HFTs) and not the decrease in their liquidity provision discussed by prior literature. We show that this change in behavior is linked to the higher frequency of price sig...
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作者：Nageswaran, Leela; Hwang, Elina H.; Cho, Soo-Haeng
作者单位：University of Washington; University of Washington Seattle; Carnegie Mellon University
摘要：Online shoppers often prefer to return items to stores (i.e., offline return) rather than mail them back. We study a new business practice, return partnership, wherein online retailers partner with store retailers to offer offline returns. We seek to identify when return partnerships benefit both the store and online retailers. Customers choose between the online and store channels for their purchase and decide whether, and through which channel, to return an online purchase if needed. We find...
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作者：Chen, Xi; Simchi-Levi, David; Wang, Yining
作者单位：New York University; Massachusetts Institute of Technology (MIT); University of Texas System; University of Texas Dallas
摘要：This paper introduces a novel contextual bandit algorithm for personalized pricing under utility fairness constraints in scenarios with uncertain demand, achieving an optimal regret upper bound. Our approach, which incorporates dynamic pricing and demand learning, addresses the critical challenge of fairness in pricing strategies. We first delve into the static full-information setting to formulate an optimal pricing policy as a constrained optimization problem. Here, we propose an approximati...
