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作者：Yang, Cathy (Liu); Bauer, Kevin; Li, Xitong; Hinz, Oliver
作者单位：Hautes Etudes Commerciales (HEC) Paris; Goethe University Frankfurt
摘要：Amid ongoing policy and managerial debates on keeping humans in the loop of artificial intelligence (AI) decision-making processes, we investigate whether human involvement in AI-based service production benefits downstream consumers. Partnering with a large savings bank in Europe, we produced pure AI and human-AI collaborative investment advice, which we passed to the bank customers and investigated the degree of their advice taking in a field experiment. On the production side, contrary to c...
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作者：Fugener, Andreas; Walzner, Dominik D.; Gupta, Alok
作者单位：University of Cologne; University of Minnesota System; University of Minnesota Twin Cities
摘要：Humans will see significant changes in the future of work as collaboration with artificial intelligence (AI) will become commonplace. This work explores the benefits of AI in the setting of judgment tasks when it replaces humans (automation) and when it works with humans (augmentation). Through an analytical modeling framework, we show that the optimal use of AI for automation or augmentation depends on different types of human-AI complementarity. Our analysis demonstrates that the use of auto...
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作者：Xu, Yuqian; Dai, Hongyan; Yan, Wanfeng
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Central University of Finance & Economics
摘要：Fueled by the widespread adoption of algorithms and artificial intelligence, the use of chatbots has become increasingly popular in various business contexts. In this paper, we study how to effectively and appropriately use voice chatbots, particularly by leveraging the two design features identity disclosure and anthropomorphism, and evaluate their impact on the firm operational performance. In collaboration with a large truck-sharing platform, we conducted a field experiment that randomly as...
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作者：Tambe, Prasanna B.
作者单位：University of Pennsylvania
摘要：This study provides evidence that AI and algorithms act as complements to domain expertise, creating the greatest value when algorithmic literacy is broadly diffused among workers. Unlike earlier business technologies that concentrated expertise in IT specialists, AI and algorithms are most effective when domain experts themselves can interpret and apply them. Using two workforce datasets, I show that demand for algorithmic skills is rising among domain experts, frontier firms diffuse these sk...
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作者：Flicker, Blair
作者单位：University of South Carolina System; University of South Carolina Columbia
摘要：Work is increasingly being completed by humans and algorithms in collaboration. A relative strength of humans in this partnership is their insight: private information that is relevant to the task but not available to computerized systems. I introduce a flexible model of managerial insight that accepts any distribution of demand, an advantage over alternative models, and apply it to the newsvendor setting. The optimal policy in this setting is theoretically straightforward but difficult for ma...
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作者：Yu, Yifan; Xue, Wendao; Jia, Lin; Tan, Yong
作者单位：University of Texas System; University of Texas Austin; Beijing Institute of Technology; Beijing Institute of Technology; University of Washington; University of Washington Seattle
摘要：When organizations adopt artificial intelligence (AI) to recognize individuals' negative emotions and accordingly allocate limited resources, strategic users are incentivized to game the system by misrepresenting their emotions. The value of AI in automating such emotion-driven allocation may be undermined by gaming behavior, algorithmic noise in emotion detection, and the spillover effect of negative emotions. We develop a gametheoretical model to understand emotion AI adoption, particularly ...
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作者：Kormylo, Cameron; Adjerid, Idris; Ball, Sheryl; Dogan, Can
作者单位：University of Notre Dame; Virginia Polytechnic Institute & State University; Virginia Polytechnic Institute & State University; Radford University
摘要：Failing to follow expert advice can have real and dangerous consequences. While any number of factors may lead a decision maker to refuse expert advice, the proliferation of algorithmic experts has further complicated the issue. One potential mechanism that restricts the acceptance of expert advice is betrayal aversion, or the strong dislike for the violation of trust norms. This study explores whether the introduction of expert algorithms in place of human experts can attenuate betrayal avers...
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作者：Zhang, Shunyuan; Narayandas, Das
作者单位：Harvard University
摘要：This article may be used only for the purposes of research, teaching, and/or private study. Commercial use or systematic downloading (by robots or other automatic processes) is prohibited without explicit Publisher approval, unless otherwise noted. For more information, contact permissions@informs.org. The Publisher does not warrant or guarantee the article's accuracy, completeness, merchantability, fitness inclusion of an advertisement in this article, neither constitutes nor implies a guaran...
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作者：Bastani, Hamsa; Bastani, Osbert; Sinchaisri, Wichinpong Park
作者单位：University of Pennsylvania; University of Pennsylvania; University of California System; University of California Berkeley
摘要：Workers spend a significant amount of time learning how to make good decisions. Evaluating the efficacy of a given decision, however, can be complicated-for example, decision outcomes are often long-term and relate to the original decision in complex ways. Surprisingly, even though learning good decision-making strategies is difficult, the strategies can often be expressed in simple and concise forms. Focusing on sequential decision making, we design a novel machine learning algorithm that is ...
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作者：Hillenbrand, Adrian; Hippel, Svenja
作者单位：Leibniz Association; Zentrum fur Europaische Wirtschaftsforschung (ZEW); Helmholtz Association; Karlsruhe Institute of Technology; University of Bonn
摘要：Rapid technological developments in online markets fundamentally change relationship between consumers and sellers. Online platforms can easily gather data consumers' search behavior, allowing for price discrimination. Therefore, product becomes a strategic choice. Consumers face a tradeoff: Search intensely and receive fit at a potentially higher price or restrict search behavior, be strategically inattentive, receive a worse fit but maybe a better deal. We study the resulting strategic buyer...
