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作者：Yu, Yifan; Tan, Xue (Jane); Tan, Yong
作者单位：University of Texas System; University of Texas Austin; Southern Methodist University; University of Washington; University of Washington Seattle
摘要：Crowdsourcing is about leveraging information technologies to outsource tasks to a large group of people, who can either be paid workers or nonpaid workers. Differing from monetarily incentivized workers, nonpaid workers are more likely to be affected by coworking relationships. To explore the link between the network and volunteering behavior, we construct dynamic collaboration networks from 827,260 unique volunteers' participation in 183,445 projects initiated by 74,556 nonprofit organizatio...
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作者：Song, Yicheng; Wang, Wenbo; Yao, Song
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Hong Kong University of Science & Technology; Washington University (WUSTL)
摘要：Effective customer acquisition heavily hinges on sequential targeting to ensure that appropriate marketing messages reach customers. Sequential targeting could guide customers through the acquisition process and thus, optimize long-term revenue for the firm. Toward this goal, reinforcement learning (RL) has demonstrated great potential in facilitating sequential targeting during user acquisition. However, decisions made by RL during this process often lack explainability. We introduce the deep...
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作者：Wambsganss, Thiemo; Janson, Andreas; Soellner, Matthias; Koedinge, Ken; Leimeister, Jan Marco
作者单位：University of St Gallen; Universitat Kassel; Carnegie Mellon University; Universitat Kassel
摘要：Argumentation is an omnipresent rudiment of daily communication and thinking. The ability to form convincing arguments is not only fundamental to persuading an audience of novel ideas but also plays a major role in strategic decision making, negotiation, and constructive, civil discourse. However, humans often struggle to develop argumentation skills, owing to a lack of individual and instant feedback in their learning process, because providing feedback on the individual argumentation skills ...
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作者：Deng, Honglin; Wang, Weiquan; Lim, Kai H.
作者单位：Tongji University; Chinese University of Hong Kong; Hong Kong Polytechnic University
摘要：Sponsored search results (SSRs) that deviate from users' search queries often raise suspicion despite receiving positive evaluations from previous users. Such a suspicion typically prompts users to avoid SSRs. To address this issue, our study focuses on the role of online informational cues, such as product reviews and ratings from user-generated content, in reducing users' suspicion when encountering these SSRs. Drawing on the theoretical perspective of state suspicion, we contextualize the d...
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作者：Molitor, Dominik; Spann, Martin; Ghose, Anindya; Reichhart, Philipp
作者单位：Fordham University; University of Munich; New York University
摘要：This study examines the impact of different mobile content delivery mechanisms on consumers' coupon redemption behavior. Firms have two distinct content delivery options when engaging with consumers' mobile devices: mobile push and mobile pull. Mobile push delivers firm -initiated (ad) content directly to consumers, whereas mobile pull requires consumers to initiate requests for (ad) content. We hypothesize that mobile push delivery increases the likelihood of coupon redemption due to reduced ...
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作者：Zhang, Xin; Yue, Wei Thoo; Zhang, Ran (Alan); Yu, Yugang
作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; City University of Hong Kong; Texas Tech University System; Texas Tech University
摘要：The abundance of consumer data has given rise to a new data broker industry that plays a pivotal role in targeted advertising. Many publishers rely on data brokers to gain (i) individual insights drawn from their own data or (ii) collective insights drawn from both their data and those of their competitors, thus improving their targeting capabilities. As data brokers control large volumes of data, they can govern how data insights are sold to downstream publishers. Despite their importance, pr...
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作者：Bardhan, Indranil; Kohli, Rajiv; Oborn, Eivor; Mishra, Abhay; Tan, Chuan Hoo; Tremblay, Monica Chiarini; Sarkerf, Suprateek
作者单位：University of Texas System; University of Texas Austin; University of Warwick; Iowa State University; National University of Singapore; University of Virginia
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作者：Gopal, Ram D.; Qiao, Xiao; Strub, Moris S.; Yang, Zonghao
作者单位：University of Warwick; City University of Hong Kong
摘要：Although online lending enjoyed explosive growth in the past decade, its market size remains small compared with other financial assets. The risk of losing money, stringent government regulations, and low awareness of the benefits have hampered the realization of the full potential of the online lending market. Because online loans are an emerging asset class, investors may not be aware of the investment performance of online loans compared with other assets, and it remains an open question wh...
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作者：Liu, Haoyuan; Wen, Wen; Barua, Anitesh; Whinston, Andrew B.
作者单位：Nanyang Technological University; University of Texas System; University of Texas Austin
摘要：In modern enterprise computing environments, multiple information technology (IT) services from first and third parties are often integrated to form coherent solutions for business customers. Using transaction cost economics (TCE) as a theoretical foundation, we seek to understand how uncertainties introduced by third -party services shape enterprise customers' use of various IT services in these multivendor service settings. Specifically, we analyze a case of service disruption caused by a th...
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作者：Hu, Yu Jeffrey; Rombouts, Jeroen; Wilms, Ines
作者单位：Purdue University System; Purdue University; ESSEC Business School; Maastricht University
摘要：On -demand service platforms face a challenging problem of forecasting a large collection of high -frequency regional demand data streams that exhibit instabilities. This paper develops a novel forecast framework that is fast and scalable and automatically assesses changing environments without human intervention. We empirically test our framework on a large-scale demand data set from a leading on -demand delivery platform in Europe and find strong performance gains from using our framework ag...
