publications | Kevin Y. Hong

2024

When the clock strikes: A multimethod investigation of on-the-hour effects in online learning

Ni Huang, Lingli Wang, Yili Hong, Lihui Lin, Xunhua Guo, and 1 more author

Information Systems Research, 2024

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Online learners often experience a lack of sustained motivation given the self-paced nature of online learning, resulting in inefficiency and a high dropout rate. Therefore, it is important to explore options that help users optimize their learning behavior and improve their learning performance. This study proposes that on-the-hour time points as external temporal cues can significantly influence online learning outcomes. Using a multimethod approach (i.e., archival data analysis, laboratory experiments, and framed field experiments), we show that (a) starting learning sessions at on-the-hour time points activates users’ implemental mindset, which supports them in building greater learning persistence and achieving better learning performance, and (b) social presence significantly attenuates the effects of on-the-hour time points in online learning. Our findings add to the literature on the design of online learning systems by clarifying the effects of temporal cues in user-system interactions, which provides implications for notification and reminder strategies that can be implemented to further enhance the effectiveness of online learning.
@article{huang2024clock, title = {When the clock strikes: A multimethod investigation of on-the-hour effects in online learning}, author = {Huang, Ni and Wang, Lingli and Hong, Yili and Lin, Lihui and Guo, Xunhua and Chen, Guoqing}, journal = {Information Systems Research}, volume = {35}, number = {2}, pages = {766--782}, year = {2024}, doi = {https://doi.org/10.1287/isre.2023.1234}, publisher = {Informs} }
Monitoring and the cold start problem in digital platforms: Theory and evidence from online labor markets

Chen Liang, Yili Hong, and Bin Gu

Information Systems Research, 2024

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Many online labor platforms employ reputation systems and monitoring systems to mitigate moral hazard. Whereas reputation systems have the potential to reduce moral hazard, they suffer from the cold-start problem, in which new entrants without an established reputation face a high entry barrier as employers predominantly select workers based on their existing reputation. Monitoring systems, providing employers with direct oversight of workers’ actions, offer a different approach. By tracking and reporting workers’ effort levels, monitoring systems reduce ex post information asymmetry and, thus, lower employers’ expected moral hazard risk from workers. However, unlike reputation systems, monitoring systems do not directly address ex ante information asymmetry, failing to assist employers in identifying the right workers. This inherent limitation raises questions about their effectiveness in resolving the cold-start problem. In this paper, we first propose a stylized theoretical model that characterizes worker entry in the presence of reputation and monitoring systems. Based on a unique data set from a leading online labor platform, we then empirically investigate the effect of monitoring systems on the entry barriers by examining the change in workers’ entry behaviors after the introduction of the monitoring system along with associated project outcomes, which include employers’ hiring preferences, hiring prices, and project performance. We exploit the differential availability of the monitoring system across two project types: time-based projects, for which the monitoring system is accessible, and fixed-price projects, for which it is not. Employing a difference-in-differences estimation with a sample including 9,344 fixed-price projects and 3,118 time-based projects, we report that the introduction of the monitoring system increases the number of bids on time-based projects by 27.8%, and the incremental bids predominantly originate from inexperienced workers who lack platform reputation. We further find that, following the introduction of the monitoring system, employers’ preference for experienced workers diminishes, accompanied by an average reduction of 19.5% in labor costs, whereas we observe no significant decrease in project completion and review rating. Our results collectively suggest that monitoring systems alleviate the cold-start problem in online platforms.
@article{liang2024monitoring, title = {Monitoring and the cold start problem in digital platforms: Theory and evidence from online labor markets}, author = {Liang, Chen and Hong, Yili and Gu, Bin}, journal = {Information Systems Research}, year = {2024}, doi = {https://doi.org/10.1287/isre.2021.0146}, publisher = {INFORMS} }
Enhancing user privacy through ephemeral sharing design: Experimental evidence from online dating

Yumei He, Xingchen Xu, Ni Huang, Yili Hong, and De Liu

Information Systems Research, 2024

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Users on online dating platforms tend to encounter a cold-start problem, with limited user engagement in the initial stages of the matching process; this is partially due to privacy concerns. In this study, we propose ephemeral sharing as a privacy-enhancing design to strike a balance between users’ privacy concerns and the need for voluntary information disclosure. Ephemeral sharing refers to a digital design in which the information shared (e.g., a personal photo) becomes invisible and irretraceable to the receiver shortly after the receipt of such information. In partnership with an online dating platform, we report a large-scale randomized field experiment with more than 70,000 users to understand how ephemeral sharing influences users’ disclosure of personal photos, match outcome, and receiver engagement. The experiment features a treatment group in which subjects can upload an ephemeral photo along with their matching request and a control group in which subjects can instead upload a persistent photo. We find that users in the treatment group send more personal photos (and ones with human faces) compared with users in the control group. Additionally, the ephemeral sharing treatment leads to a higher number of matches and a higher level of receiver engagement. Further analyses suggest that the treatment effects are more salient for privacy-sensitive senders. Moreover, we find that the treatment effects on match outcome and receiver engagement can be explained by increases in the disclosure of personal photos. Last, through an online experiment, we show that ephemeral sharing increases disclosure intention by reducing privacy concerns related to data collection, dissemination, and identity abuse. Our study contributes to the literature and practice on privacy-enhancing designs for online matching platforms.
@article{he2024enhancing, title = {Enhancing user privacy through ephemeral sharing design: Experimental evidence from online dating}, author = {He, Yumei and Xu, Xingchen and Huang, Ni and Hong, Yili and Liu, De}, journal = {Information Systems Research}, year = {2024}, doi = {https://doi.org/10.1287/isre.2021.0379}, publisher = {INFORMS} }
Monitoring and home bias in global hiring: Evidence from an online labor platform

Chen Liang, Yili Hong, and Bin Gu

Information Systems Research, 2024

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The increasing prevalence of remote work has accelerated the adoption of monitoring systems to keep track of worker behavior, especially on online labor platforms. In contrast to the existing literature that predominantly focuses on the effect of monitoring on productivity, this study investigates the impact of monitoring from the perspective of contractual governance. In principle, by enabling the detailed real-time observation of worker progress, the deployment of monitoring systems has the potential to improve contractual control and coordination, thereby reducing employers’ preferences for domestic workers (home bias). Leveraging the exogenous introduction of a monitoring system for time-based projects on a leading online labor platform, we employ a difference-in-differences model to estimate the impact of monitoring systems in reducing home bias. Our findings reveal that following the monitoring system’s introduction, the bias against foreign workers becomes substantially weaker and statistically insignificant, highlighting the overlooked role of monitoring systems in fostering a more level playing field for global workers. Our further analysis indicates that monitoring leads to a notable 15% increase in the hiring of foreign workers. Moreover, the decrease in home bias is more pronounced in high-routine projects or when employers lack prior positive experiences with foreign workers, two scenarios characterized by low external uncertainty and high internal uncertainty, respectively. Additionally, employers no longer exhibit a stronger home bias when workers have higher ratings, where the expected moral hazard risk is lower, nor when workers reside in the same time zone, where expected coordination costs are lower. These findings lend support to the effectiveness of monitoring systems in mitigating employers’ home bias through enhancing contractual control and coordination. Our findings provide important managerial implications for the design of online labor platforms.
@article{liang2024monitorinh, title = {Monitoring and home bias in global hiring: Evidence from an online labor platform}, author = {Liang, Chen and Hong, Yili and Gu, Bin}, journal = {Information Systems Research}, year = {2024}, doi = {https://doi.org/10.1287/isre.2021.0526}, publisher = {INFORMS} }
Platform governance with algorithm-based content moderation: An empirical study on Reddit

Qinglai He, Yili Hong, and TS Raghu

Information Systems Research, 2024

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With increasing volumes of participation in social media and online communities, content moderation has become an integral component of platform governance. Volunteer (human) moderators have thus far been the essential workforce for content moderation. Because volunteer-based content moderation faces challenges in achieving scalable, desirable, and sustainable moderation, many online platforms have recently started to adopt algorithm-based content moderation tools (bots). When bots are introduced into platform governance, it is unclear how volunteer moderators react in terms of their community-policing and -nurturing efforts. To understand the impacts of these increasingly popular bot moderators, we conduct an empirical study with data collected from 156 communities (subreddits) on Reddit. Based on a series of econometric analyses, we find that bots augment volunteer moderators by stimulating them to moderate a larger quantity of posts, and such effects are pronounced in larger communities. Specifically, volunteer moderators perform 20.9% more community policing, particularly over subjective rules. Moreover, in communities with larger sizes, volunteers also exert increased efforts in offering more explanations and suggestions after their community adopted bots. Notably, increases in activities are primarily driven by the increased need for nurturing efforts to accompany growth in subjective policing. Moreover, introducing bots to content moderation also improves the retention of volunteer moderators. Overall, we show that introducing algorithm-based content moderation into platform governance is beneficial for sustaining digital communities.
@article{he2024platform, title = {Platform governance with algorithm-based content moderation: An empirical study on Reddit}, author = {He, Qinglai and Hong, Yili and Raghu, TS}, journal = {Information Systems Research}, year = {2024}, doi = {https://doi.org/10.1287/isre.2021.0036}, publisher = {INFORMS} }

2023

Voice-based AI in call center customer service: A natural field experiment

Lingli Wang, Ni Huang, Yili Hong, Luning Liu, Xunhua Guo, and 1 more author

Production and Operations Management, 2023

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Voice‐based artificial intelligence (AI) systems have been recently deployed to replace traditional interactive voice response (IVR) systems in call center customer service. However, there is little evidence that sheds light on how the implementation of AI systems impacts customer behavior, as well as AI systems’ effects on call center customer service performance. By leveraging the proprietary data obtained from a natural field experiment in a large telecommunication company, we examine how the introduction of a voice‐based AI system affects call length, customers’ demand for human service, and customer complaints in call center customer service. We find that the implementation of the AI system temporarily increases the duration of machine service and customers’ demand for human service; however, it persistently reduces customer complaints. Furthermore, our results reveal interesting heterogeneity in the effectiveness of the voice‐based AI system. For relatively simple service requests, the AI system reduces customer complaints for both experienced and inexperienced customers. However, for complex requests, customers appear to learn from the prior experience of interacting with the AI system, which leads to fewer complaints. Moreover, the AI‐based system has a significantly larger effect on reducing customer complaints for older and female customers as well as for customers who have had extensive experience using the IVR system. Finally, we find that speech‐recognition failures in customer‐AI interactions lead to increases in customers’ demand for human service and customer complaints. The results from this study provide implications for the implementation of an AI system in call center operations.
@article{wang2023voice, title = {Voice-based AI in call center customer service: A natural field experiment}, author = {Wang, Lingli and Huang, Ni and Hong, Yili and Liu, Luning and Guo, Xunhua and Chen, Guoqing}, journal = {Production and Operations Management}, volume = {32}, number = {4}, pages = {1002--1018}, year = {2023}, doi = {https://doi.org/10.1111/poms.13953}, publisher = {SAGE Publications Sage CA: Los Angeles, CA} }
The hidden costs and benefits of monitoring in the gig economy

Chen Liang, Jing Peng, Yili Hong, and Bin Gu

Information Systems Research, 2023

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Monitoring, a digital surveillance technology that allows employers to track the activities of workers, is ubiquitous in the gig economy wherein the workforce is geographically dispersed. However, workers are often reluctant to be monitored because of privacy concerns, resulting in a hidden economic cost for employers as workers tend to demand higher wages for monitored jobs. To help employers make informed decisions on whether they should adopt monitoring and how to design monitoring policies, we investigate how three common dimensions of monitoring affect workers’ willingness to accept monitored jobs as well as the underlying mechanisms through online experiments on two gig economy platforms (Amazon Mechanical Turk (AMT) and Prolific). The three dimensions of monitoring are intensity (how much information is collected), transparency (whether the monitoring policy is disclosed to workers), and control (whether workers can remove sensitive information). We find that, as the monitoring intensity increases, workers become less willing to accept monitoring because of elevated privacy concerns. Furthermore, we find that being transparent about the monitoring policy increases workers’ willingness to accept monitoring only when the monitoring intensity is low. Transparent disclosure does not reduce privacy concerns over high-intensity monitoring. Interestingly, providing control over high-intensity monitoring does not significantly reduce workers’ privacy concerns either, rendering this well-intentioned policy ineffective. Finally, females are more willing to accept monitored jobs than males as they perceive higher payment protection from monitoring and have lower privacy concerns. On average, we estimate that the compensations required for workers to accept monitoring are 1.8/hour for AMT workers and 1.6/hour for Prolific workers, which translate to roughly 37.5% and 28.6% of their average hourly wages, respectively.
@article{liang2023hidden, title = {The hidden costs and benefits of monitoring in the gig economy}, author = {Liang, Chen and Peng, Jing and Hong, Yili and Gu, Bin}, journal = {Information Systems Research}, volume = {34}, number = {1}, pages = {297--318}, year = {2023}, doi = {https://doi.org/10.1287/isre.2022.1130}, publisher = {INFORMS} }
Putting religious bias in context: How offline and online contexts shape religious bias in online prosocial lending

Amin Sabzehzar, Gordon Burtch, Yili Hong, and TS Raghu

MIS Quarterly, 2023

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Biases on online platforms pose a threat to social inclusion. We examine the influence of a novel source of bias in online philanthropic lending, namely that associated with religious differences. We first propose religion distance as a probabilistic measure of differences between pairs of individuals residing in different countries. We then incorporate this measure into a gravity model of trade to explain variation in country-to-country lending volumes. We further propose a set of contextual moderators that characterize individuals’ offline (local) and online social contexts, which we argue combine to determine the influence of religion distance on lending activity. We empirically estimate our gravity model using data from Kiva.org, reflecting all lending actions that took place between 2006 and 2017. We demonstrate the negative and significant effect of religion distance on lending activity, over and above other established factors in the literature. Further, we demonstrate the moderating role of lenders’ offline social context (diversity, social hostilities, and governmental favoritism of religion) on the aforementioned relationship to online lending behavior. Finally, we offer empirical evidence of the parallel role of online contextual factors, namely those related to community features offered by the Kiva platform (lending teams), which appear to amplify the role of religious bias. In particular, we show that religious team membership is a double-edged sword that has both favorable and unfavorable consequences, increasing lending in general but skewing said lending toward religiously similar borrowers. Our findings speak to the important frictions associated with religious differences in individual philanthropy; they point to the role of governmental policy vis-à-vis religious tolerance as a determinant of citizens’ global philanthropic behavior, and they highlight design implications for online platforms with an eye toward managing religious bias.
@article{sabzehzar2023putting, title = {Putting religious bias in context: How offline and online contexts shape religious bias in online prosocial lending}, author = {Sabzehzar, Amin and Burtch, Gordon and Hong, Yili and Raghu, TS}, journal = {MIS Quarterly}, volume = {47}, number = {1}, pages = {33--62}, year = {2023}, }
Direct and indirect spillovers from content providers’ switching: Evidence from online livestreaming

Keran Zhao, Yingda Lu, Yuheng Hu, and Yili Hong

Information Systems Research, 2023

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Content providers in online social media platforms, particularly livestreaming, often switch content categories. Despite its uniqueness and importance, there is a dearth of academic research examining the unintended effects of providers’ content switching. We study the direct and indirect spillover effects of content switching for livestreamers—individuals who broadcast content through livestreaming platforms. We propose a framework based on theories related to viewer flow and network effects to conceptualize the direct and indirect spillover effects of entrant streamers’ content switching on the incumbent streamers. Contrary to conventional wisdom, which concerns the negative effects on the incumbent’s viewership, we propose two positive spillover effects that are unique to the social media platform setting: (a) the entrant streamers do not just increase competition among streamers, but they also bring their own viewers to the new category, which benefits the incumbent streamers because of a streaming flow effect (direct spillover), and (b) the entrant streamers influence incumbent streamers’ viewer size by boosting category visibility through indirect network effects (indirect spillover). We also propose that the two spillover effects are contingent on the size of the entrant streamers’ follower base. Based on a unique observational data set from the leading livestreaming platform (Twitch.tv), particularly with viewer flow data at the streamer–session level, we first estimate that average content switching is associated with a 1.3% net increase in direct net viewer flow from the entrant to an incumbent. And this direct spillover effect is attenuated by the size of the entrant streamers’ follower base. We also estimate that average content switching is associated with a 2.6% net increase in (indirect) net viewer flow from outside categories to an incumbent streamer. And this indirect spillover effect is reinforced by the entrant streamers’ follower base size. This study contributes to the emerging literature on the dynamics of content creation on social media platforms in the emerging context of livestreaming. We discuss the managerial implications of this study for streaming strategies and platform management.
@article{zhao2023direct, title = {Direct and indirect spillovers from content providers’ switching: Evidence from online livestreaming}, author = {Zhao, Keran and Lu, Yingda and Hu, Yuheng and Hong, Yili}, journal = {Information Systems Research}, volume = {34}, number = {3}, pages = {847--866}, year = {2023}, doi = {https://doi.org/10.1287/isre.2022.1160}, publisher = {INFORMS} }
Differential effects of multidimensional review evaluations on product sales for mainstream vs. niche products

Xin Zheng, Jisu Cao, Yili Hong, Sha Yang, and Xingyao Ren

MIS Quarterly, 2023

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Despite a large body of literature on online reviews, none have considered the nuanced impacts of how multidimensional reviews affect product sales differently for mainstream vs. niche products. This study seeks to fill this knowledge gap by conducting complementary studies in two product categories (i.e., automobiles and laptops) with different methods (a field study and three lab experiments). Our paper reveals three key insights into the emerging literature and phenomenon on multidimensional review systems: (1) the interdimensional rating variance is more negatively related to product sales for mainstream products than for niche products in the same category, (2) the intradimensional rating valence on the dominant dimension of a product is more positively related to product sales for niche products than for mainstream products, and (3) the intradimensional rating variance on the dominant dimension of a product is more negatively related to product sales for niche products than for mainstream products. Our research provides important managerial implications for both product providers and review platforms.
@article{zheng2023differential, title = {Differential effects of multidimensional review evaluations on product sales for mainstream vs. niche products}, author = {Zheng, Xin and Cao, Jisu and Hong, Yili and Yang, Sha and Ren, Xingyao}, journal = {MIS Quarterly}, volume = {47}, number = {2}, pages = {833--856}, year = {2023} }

Some thoughts on reviewing for Information Systems Research and other leading information systems journals

Suprateek Sarker, Edgar A Whitley, Khim-Yong Goh, Yili Hong, Magnus Mähring, and 6 more authors

Information Systems Research, 2023

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@article{sarker2023some,
  title = {Some thoughts on reviewing for Information Systems Research and other leading information systems journals},
  author = {Sarker, Suprateek and Whitley, Edgar A and Goh, Khim-Yong and Hong, Yili and M{\"a}hring, Magnus and Sanyal, Pallab and Su, Ning and Xu, Heng and Xu, Jingjun David and Zhang, Jingjing and others},
  journal = {Information Systems Research},
  volume = {34},
  number = {4},
  pages = {1321--1338},
  year = {2023},
  doi = {https://doi.org/10.1287/isre.2023.editorial.v34.n4},
  publisher = {INFORMS}
}

2022

SHEDR: an end-to-end deep neural event detection and recommendation framework for hyperlocal news using social media

Yuheng Hu, and Yili Hong

INFORMS Journal on Computing, 2022

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Residents often rely on newspapers and television to gather hyperlocal news for community awareness and engagement. More recently, social media have emerged as an increasingly important source of hyperlocal news. Thus far, the literature on using social media to create desirable societal benefits, such as civic awareness and engagement, is still in its infancy. One key challenge in this research stream is to timely and accurately distill information from noisy social media data streams to community members. In this work, we develop SHEDR (social media–based hyperlocal event detection and recommendation), an end-to-end neural event detection and recommendation framework with a particular use case for Twitter to facilitate residents’ information seeking of hyperlocal events. The key model innovation in SHEDR lies in the design of the hyperlocal event detector and the event recommender. First, we harness the power of two popular deep neural network models, the convolutional neural network (CNN) and long short-term memory (LSTM), in a novel joint CNN-LSTM model to characterize spatiotemporal dependencies for capturing unusualness in a region of interest, which is classified as a hyperlocal event. Next, we develop a neural pairwise ranking algorithm for recommending detected hyperlocal events to residents based on their interests. To alleviate the sparsity issue and improve personalization, our algorithm incorporates several types of contextual information covering topic, social, and geographical proximities. We perform comprehensive evaluations based on two large-scale data sets comprising geotagged tweets covering Seattle and Chicago. We demonstrate the effectiveness of our framework in comparison with several state-of-the-art approaches. We show that our hyperlocal event detection and recommendation models consistently and significantly outperform other approaches in terms of precision, recall, and F-1 scores.
@article{hu2022shedr, title = {SHEDR: an end-to-end deep neural event detection and recommendation framework for hyperlocal news using social media}, author = {Hu, Yuheng and Hong, Yili}, journal = {INFORMS Journal on Computing}, volume = {34}, number = {2}, pages = {790--806}, year = {2022}, doi = {https://doi.org/10.1287/ijoc.2021.1112}, publisher = {INFORMS} }
How do on-demand ridesharing services affect traffic congestion? The moderating role of urban compactness

Ziru Li, Chen Liang, Yili Hong, and Zhongju Zhang

Production and Operations Management, 2022

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The role of information technology (IT) in managing operations that support environmentally sustainable growth has been emphasized a lot in operations management and information systems research. In this paper, we study the impact of the IT‐based on‐demand ridesharing platforms on an important aspect of sustainability—traffic congestion. Our theoretical prediction suggests two countervailing effects from the entry of ridesharing platforms to urban areas: the efficiency‐enhancing effect that reduces traffic congestion and the demand‐inducing effect that increases traffic congestion. We propose that the impacts of ridesharing services on traffic congestion should vary with urban spatial features. Given the theoretical tension, we investigate the impact of Uber entry on traffic congestion in urban areas of the United States with a focus on the moderating role of urban compactness. Based on a unique dataset that combines multiple archival sources, we empirically examine whether the entry of Uber’s on‐demand ridesharing service affects traffic congestion by using a difference‐in‐differences framework. Our empirical evidence indicates that ridesharing services significantly increase traffic congestion in compact areas. Meanwhile, we find some marginal evidence that ridesharing services decrease traffic congestion in sprawling urban areas. The results are robust to a series of additional analyses, including the use of alternative measures, relative time model, entry exogeneity test, and placebo tests. We conclude that the efficiency‐enhancing and demand‐inducing effects shape traffic congestion and that the net effect varies according to different levels of urban compactness. We provide circumstantial evidence for the underlying mechanisms by analyzing public transit and commuting characteristic data.
@article{li2022demand, title = {How do on-demand ridesharing services affect traffic congestion? The moderating role of urban compactness}, author = {Li, Ziru and Liang, Chen and Hong, Yili and Zhang, Zhongju}, journal = {Production and Operations Management}, volume = {31}, number = {1}, pages = {239--258}, year = {2022}, doi = {https://doi.org/10.1111/poms.13530}, publisher = {SAGE Publications Sage CA: Los Angeles, CA} }
How do peer awards motivate creative content? Experimental evidence from Reddit

Gordon Burtch, Qinglai He, Yili Hong, and Dokyun Lee

Management Science, 2022

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We theorize peer awards’ effects on the volume and novelty of creative user-generated content (UGC) produced at online platform communities. We then test our hypotheses via a randomized field experiment on Reddit, wherein we randomly and anonymously assigned Reddit’s Gold Award to 905 users’ posts over a two-month period. We find that peer awards induced recipients to make longer, more frequent posts and that these effects were particularly pronounced among newer community members. Further, we show that recipients were causally influenced to engage in greater (lesser) exploitation (exploration) behavior, producing content that exhibited significantly greater textual similarity to their own past (awarded) content. However, because the effects were most pronounced among new community members, who also produce content that, in general, is systematically more novel than that of established members to begin with, this process yields a desirable outcome: larger volumes of generally novel UGC for the community.
@article{burtch2022peer, title = {How do peer awards motivate creative content? Experimental evidence from Reddit}, author = {Burtch, Gordon and He, Qinglai and Hong, Yili and Lee, Dokyun}, journal = {Management Science}, volume = {68}, number = {5}, pages = {3488--3506}, year = {2022}, doi = {https://doi.org/10.1287/mnsc.2021.4040}, publisher = {INFORMS}, }
The screening role of design parameters for service procurement auctions in online service outsourcing platforms

Chen Liang, Yili Hong, Pei-Yu Chen, and Benjamin BM Shao

Information Systems Research, 2022

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This paper provides a novel theoretical angle and robust empirical evidence demonstrating that the auction duration and item description length are two essential auction design parameters that can function as a screening mechanism for bidder quality on online service outsourcing platforms. These outsourcing platforms use buyer-determined reverse auctions to find providers of services (primarily IT services). Using data from a major online outsourcing platform that connects buyers with bidders, we examine the effects of the auction duration and the item description length on both bidder entry (i.e., the number of bids and bidder quality) and contract outcomes (i.e., whether a project is contracted and the buyer’s expected utility from the winning bid) based upon not only project-level, but also bidder-level analyses. Our results show that auctions with longer durations and item descriptions attract more bids (i.e., higher quantity of bidders), and they also attract disproportionately more bidders with lower completion rates (i.e., lower quality of bidders), creating a double whammy of higher evaluation costs and adverse selection for buyers. This, in turn, leads to contracting inefficiency in terms of less successful contracting as well as lower buyer utility. Our research shows strong support for the screening role of the auction duration and the item description length for buyers on online outsourcing platforms for service procurement: by shortening auction durations and item descriptions, buyers can expect higher quality bidders, increase contracting probability, and enhance utility.
@article{liang2022screening, title = {The screening role of design parameters for service procurement auctions in online service outsourcing platforms}, author = {Liang, Chen and Hong, Yili and Chen, Pei-Yu and Shao, Benjamin BM}, journal = {Information Systems Research}, volume = {33}, number = {4}, pages = {1324--1343}, year = {2022}, doi = {https://doi.org/10.1287/isre.2022.1168}, publisher = {INFORMS} }
Managing congestion in a matching market via demand information disclosure

Ni Huang, Gordon Burtch, Yumei He, and Yili Hong

Information Systems Research, 2022

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Congestion is a common issue in digital platform markets, wherein users tend to focus their attention on a subset of popular peers. We examine this issue in the context of online dating, considering the potential efficacy of an informational intervention, namely, the disclosure of peers’ recent demand. In doing so, we first note that the benefits of disclosing demand information are not altogether clear in this context, a priori, because dating platforms are distinct from other platforms in several important respects. On the one hand, dating platforms facilitate social relationships, rather than trade in goods and services. Therefore, they operate on different norms and typically lack common levers that platform operators employ to balance supply and demand, such as pricing mechanisms and reputation systems. Dating app users may therefore pay greater attention to the quality implications of peer demand information, worsening congestion. On the other hand, demand information disclosure may be atypically effective at mitigating congestion in a dating context because, in addition to opportunity costs of time and effort, daters also bear fears of social rejection, leading them to shy away from in-demand peers. We evaluate our treatment’s efficacy in mitigating congestion and improving matching efficiency, conducting a randomized field experiment at a large mobile dating platform. Our results show that the intervention is particularly effective at improving matching efficiency when presented in tandem with a textual message-framing cue that highlights the capacity implications of the peer demand information. Heterogeneity analyses further indicate that these effects are driven primarily by those users who most contend with congestion in the form of competition, namely, male users and those who rely more heavily upon outbound messages for matches.
@article{huang2022managing, title = {Managing congestion in a matching market via demand information disclosure}, author = {Huang, Ni and Burtch, Gordon and He, Yumei and Hong, Yili}, journal = {Information Systems Research}, volume = {33}, number = {4}, pages = {1196--1220}, year = {2022}, doi = {https://doi.org/10.1287/isre.2022.1148}, publisher = {INFORMS}, }

2021

On factors that moderate the effect of buyer-supplier experience on e-procurement platforms

Yili Hong, and Benjamin BM Shao

Production and Operations Management, 2021

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E‐procurement platforms facilitate transactions between suppliers and buyers from all over the world. Over time, suppliers and buyers may develop familiarity from prior experience with earlier transactions. The literature has established that prior experience leads to better project performance. In this study, we examine the effectiveness of prior experience between buyers and suppliers in e‐procurement platforms with a focus on the moderating roles of temporal distance and language difference between the buyer and the supplier as well as routine tasks in the project (termed “task routinization”). Using a unique observational data set from a large e‐procurement platform, we first find that buyers’ prior experience with a supplier positively affects project outcomes, and temporal distance and language difference both negatively affect project outcomes. More interestingly, we find that the effectiveness of prior experience is constrained by both temporal distance and language difference, such that if a greater temporal distance separates the buyer and supplier or if the two speak different languages, prior experience is less likely to be helpful. In addition, while task routinization does not directly affect a project’s success, it has a positive interaction effect with prior experience, suggesting that buyers’ prior experience with a supplier is more effective in enhancing project outcomes when a project comprises routine tasks. Our findings on prior experience, temporal distance, language difference, and task routinization contribute to a better understanding of the e‐procurement platform for global outsourcing and procurement. Limitations are discussed and topics are identified for future research.
@article{hong2021factors, title = {On factors that moderate the effect of buyer-supplier experience on e-procurement platforms}, author = {Hong, Yili and Shao, Benjamin BM}, journal = {Production and Operations Management}, volume = {30}, number = {4}, pages = {1034--1051}, year = {2021}, doi = {https://doi.org/10.1111/poms.13291}, publisher = {SAGE Publications Sage CA: Los Angeles, CA} }
Measuring product type and purchase uncertainty with online product ratings: A theoretical model and empirical application

Peiyu Chen, Lorin M Hitt, Yili Hong, and Shinyi Wu

Information Systems Research, 2021

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Building on the distinction between search and experience goods, as well as vertical and horizontal differentiation, we propose a set of theory-grounded, data-driven measures that allow us to measure not only product type (search vs. experience, horizontal vs. vertical differentiation) but also sources of uncertainty and to what extent consumer reviews help resolve uncertainty. The proposed measures have two advantages over prior methods: (1) unlike prior categorization schemes that classified goods as either search or experience goods, our measure is continuous, allowing us to rank-order the degree of search versus experience and horizontal versus vertical differentiation among products or categories. (2) Our approach is easier to implement than prior methods, because it relies solely on consumer ratings information (as opposed to expert judgment) and can be employed at multiple levels (attributes, products, or product categories). We illustrate empirical applications of our proposed measures using product rating data from Amazon.com. Our data-driven measures reveal the relative importance of fit in driving product utility and the importance of search for determining fit for each product category at Amazon. Our results also show that, while ratings based on verified purchasers are informative of objective product values, the current Amazon review system appears to have limited ability to resolve fit uncertainty. Our method and findings could facilitate further research on product review systems and enable quantitative measurement of product positioning to support marketing strategy for retailers and manufacturers, covering an expanded group of products.
@article{chen2021measuring, title = {Measuring product type and purchase uncertainty with online product ratings: A theoretical model and empirical application}, author = {Chen, Peiyu and Hitt, Lorin M and Hong, Yili and Wu, Shinyi}, journal = {Information Systems Research}, volume = {32}, number = {4}, pages = {1470--1489}, year = {2021}, doi = {https://doi.org/10.1287/isre.2021.1041}, publisher = {INFORMS} }
When does dispute resolution substitute for a reputation system? Empirical evidence from a service procurement platform

Gordon Burtch, Yili Hong, and Senthil Kumar

Production and Operations Management, 2021

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We consider the role of online dispute resolution (ex‐post guarantees of supplier quality) when introduced in the presence of an online reputation system (an ex‐ante informational mechanism), in the context of online service procurement platforms. We argue that dispute resolution will reduce buyers’ reliance on reputation systems in their hiring decisions to varying extents, depending on the nature of the work required. We assess these predictions using proprietary data capturing projects, service providers, bids, and hiring decisions around a natural experiment: the introduction of a new dispute resolution system at a major online service procurement platform. We provide evidence consistent with our expectations; introducing a dispute resolution system led buyers to reduce their consideration of service provider rating volumes in hiring decisions, particularly for projects where service provider performance could be evaluated objectively by a third party (e.g., data entry, as opposed to more subjective, creative work, like logo design). We also report a variety of additional analyses, which demonstrate the robustness of our findings to alternative measures, dynamics of the effects depending on buyers’ experience with the dispute process, and the impact of the dispute service on buyers’ propensity to enter ratings of service providers. These findings provide empirical evidence that dispute resolution can be an effective, alternative means of mitigating supplier quality risks in online service procurement markets in place of ex‐ante signals of provider quality. However, this is particularly true in settings where the output of work contracted can be objectively evaluated by a third party.
@article{burtch2021does, title = {When does dispute resolution substitute for a reputation system? Empirical evidence from a service procurement platform}, author = {Burtch, Gordon and Hong, Yili and Kumar, Senthil}, journal = {Production and Operations Management}, volume = {30}, number = {6}, pages = {1565--1582}, year = {2021}, doi = {https://doi.org/10.1111/poms.13341}, publisher = {SAGE Publications Sage CA: Los Angeles, CA} }
Just DM me (politely): Direct messaging, politeness, and hiring outcomes in online labor markets

Yili Hong, Jing Peng, Gordon Burtch, and Ni Huang

Information Systems Research, 2021

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This study examines the role of text-based direct messaging systems in online labor markets, which provide a communication channel between workers and employers, adding a personal touch to the exchange of online labor. We propose the effect of workers’ use of the direct messaging system on employers’ hiring decisions and conceptualize the information role of direct messaging. To empirically evaluate the information role of the direct messaging system, we leverage data on the direct messaging activities between workers and employers across more than 470,000 job applications on a leading online labor market. We report evidence that direct messaging with a prospective employer increases a worker’s probability of being hired by 8.9%. However, the degree to which workers benefit from direct messaging is heterogeneous, and the effect amplifies for workers approaching employers from a position of disadvantage (lacking tenure or fit with the job) and attenuates as more workers attempt to message the same prospective employer. The effects also depend on message content. In particular, we find that the benefits of direct messaging for workers depend a great deal on the politeness of the workers, and this “politeness effect” depends on several contextual factors. The beneficial effects are amplified for lower-status workers (i.e., workers lacking tenure and job fit) and workers who share a common language with the employer. At the same time, the beneficial effects weaken in the presence of typographical errors. These findings provide important insights into when and what to message to achieve favorable hiring outcomes in online employment settings.
@article{hong2021just, title = {Just DM me (politely): Direct messaging, politeness, and hiring outcomes in online labor markets}, author = {Hong, Yili and Peng, Jing and Burtch, Gordon and Huang, Ni}, journal = {Information Systems Research}, volume = {32}, number = {3}, pages = {786--800}, year = {2021}, doi = {https://doi.org/10.1287/isre.2021.1003}, publisher = {INFORMS} }

2020

Unemployment and worker participation in the gig economy: Evidence from an online labor market

Ni Huang, Gordon Burtch, Yili Hong, and Paul A Pavlou

Information Systems Research, 2020

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The gig economy has low barriers to entry, enabling flexible work arrangements and allowing workers to engage in contingent employment, whenever, and in some cases, such as online labor markets, wherever, workers desire. The growth of the gig economy has been partly attributed to technological advancements that enable flexible work environments. In this study, we consider the role of an alternative driver, economic downturns, and associated financial stressors in the offline economy, for example, unemployment. As the exact nature of the relationship between online labor supply and offline unemployment is not immediately clear, in this work, we seek to quantify the relationship, exploring heterogeneity across a variety of county-specific characteristics. We study these relationships in the context of a leading online labor market, combining data on the participation of workers residing in counties across the United States with county-level data on unemployment from the Bureau of Labor Statistics. Our results demonstrate a positive and significant association between local (county) unemployment in the traditional offline labor market and the supply of online workers residing in the same county, as well as significantly larger volumes of online project bidding activity from workers in the same county. Specifically, we estimate that a 1% increase in county unemployment is associated with a 21.8% increase in the volume of county residents actively working online at the platform. Furthermore, our results suggest significant heterogeneity in the relationship, such that a significantly larger supply of online labor manifests when unemployment occurs in counties characterized by better internet access, younger and more educated populations, and populations whose social ties are dispersed over a wider geographic area. We discuss the theoretical and practical implications for workers, online labor markets, and policy makers.
@article{huang2020unemployment, title = {Unemployment and worker participation in the gig economy: Evidence from an online labor market}, author = {Huang, Ni and Burtch, Gordon and Hong, Yili and Pavlou, Paul A}, journal = {Information Systems Research}, volume = {31}, number = {2}, pages = {431--448}, year = {2020}, doi = {https://doi.org/10.1287/isre.2019.0896}, publisher = {INFORMS} }

2019

Motivating user-generated content with performance feedback: Evidence from randomized field experiments

Ni Huang, Gordon Burtch, Bin Gu, Yili Hong, Chen Liang, and 3 more authors

Management Science, 2019

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We design a series of online performance feedback interventions that aim to motivate the production of user-generated content (UGC). Drawing on social value orientation (SVO) theory, we develop a novel set of alternative feedback message framings, aligned with cooperation (e.g., your content benefited others), individualism (e.g., your content was of high quality), and competition (e.g., your content was better than others). We hypothesize how gender (a proxy for SVO) moderates response to each framing, and we report on two randomized experiments, one in partnership with a mobile-app–based recipe crowdsourcing platform, and a follow-up experiment on Amazon Mechanical Turk involving an ideation task. We find evidence that cooperatively framed feedback is most effective for motivating female subjects, whereas competitively framed feedback is most effective at motivating male subjects. Our work contributes to the literatures on performance feedback and UGC production by introducing cooperative performance feedback as a theoretically motivated, novel intervention that speaks directly to users’ altruistic intent in a variety of task settings. Our work also contributes to the message-framing literature in considering competition as a novel addition to the altruism–egoism dichotomy oft explored in public good settings.
@article{huang2019motivating, title = {Motivating user-generated content with performance feedback: Evidence from randomized field experiments}, author = {Huang, Ni and Burtch, Gordon and Gu, Bin and Hong, Yili and Liang, Chen and Wang, Kanliang and Fu, Dongpu and Yang, Bo}, journal = {Management Science}, volume = {65}, number = {1}, pages = {327--345}, year = {2019}, doi = {https://doi.org/10.1287/mnsc.2017.2944}, publisher = {INFORMS} }

2018

Stimulating online reviews by combining financial incentives and social norms

Gordon Burtch, Yili Hong, Ravi Bapna, and Vladas Griskevicius

Management Science, 2018

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In hopes of motivating consumers to provide larger volumes of useful reviews, many retailers offer financial incentives. Here, we explore an alternative approach, social norms. We inform individuals about the volume of reviews authored by peers. We test the effectiveness of using financial incentives, social norms, and a combination of both strategies in motivating consumers. In two randomized experiments, one in the field conducted in partnership with a large online clothing retailer based in China and a second on Amazon Mechanical Turk, we compare the effectiveness of each strategy in stimulating online reviews in larger numbers and of greater length. We find that financial incentives are more effective at inducing larger volumes of reviews, but the reviews that result are not particularly lengthy, whereas social norms have a greater effect on the length of reviews. Importantly, we show that the combination of financial incentives and social norms yields the greatest overall benefit by motivating reviews in greater numbers and of greater length. We further assess treatment-induced self-selection and sentiment bias by triangulating the experimental results with findings from an observational study.
@article{burtch2018stimulating, title = {Stimulating online reviews by combining financial incentives and social norms}, author = {Burtch, Gordon and Hong, Yili and Bapna, Ravi and Griskevicius, Vladas}, journal = {Management Science}, volume = {64}, number = {5}, pages = {2065--2082}, year = {2018}, doi = {https://doi.org/10.1287/mnsc.2016.2715}, publisher = {INFORMS} }
Embeddedness, prosociality, and social influence: Evidence from online crowdfunding

Yili Hong, Yuheng Hu, and Gordon Burtch

MIS Quarterly, 2018

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This paper examines how (1) a crowdfunding campaign’s prosociality (the production of a public versus private good), (2) the social network structure (embeddedness) among individuals advocating for the campaign on social media, and (3) the volume of social media activity around a campaign jointly determine fundraising from the crowd. Integrating the emerging literature on social media and crowdfunding with the literature on social networks and public goods, we theorize that prosocially, public-oriented crowdfunding campaigns will benefit disproportionately from social media activity when advocates’ social media networks exhibit greater levels of embeddedness. Drawing on a panel dataset that combines campaign fundraising activity associated with more than 1,000 campaigns on Kickstarter with campaign-related social media activity on Twitter, we construct network-level measures of embeddedness between and amongst individuals initiating the latter, in terms of transitivity and topological overlap. We demonstrate that Twitter activity drives a disproportionate increase in fundraising for prosocially oriented crowdfunding campaigns when posting users’ networks exhibit greater embeddedness. We discuss the theoretical implications of our findings, highlighting how our work extends prior research on the role of embeddedness in peer influence by demonstrating the joint roles of message features and network structure in the peer influence process. Our work suggests that when a transmitter’s message is prosocial or cause-oriented, embeddedness will play a stronger role in determining influence. We also discuss the broader theoretical implications for the literatures on social media, crowdfunding, crowdsourcing, and private contributions to public goods. Finally, we highlight the practical implications for marketers, campaign organizers, and crowdfunding platform operators.
@article{hong2018embeddedness, title = {Embeddedness, prosociality, and social influence: Evidence from online crowdfunding}, author = {Hong, Yili and Hu, Yuheng and Burtch, Gordon}, journal = {MIS Quarterly}, volume = {42}, number = {4}, pages = {1211--1224}, year = {2018}, }
The value of multidimensional rating systems: Evidence from a natural experiment and randomized experiments

Pei-Yu Chen, Yili Hong, and Ying Liu

Management Science, 2018

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Online product ratings offer information on product quality. Scholars have recently proposed the potential of designing multidimensional rating systems to better convey information on multiple dimensions of products. This study investigates whether and how multidimensional rating systems affect consumer satisfaction (measured by product ratings), based on both observational data and two randomized experiments. Our identification strategy of the observational study hinges on a natural experiment on TripAdvisor when the website started to allow consumers to rate multiple dimensions of the restaurants, as opposed to only providing an overall rating, in January 2009. We further obtain rating data on the same set of restaurants from Yelp, which controls for the unobserved restaurant quality over time and allows us to identify the causal effect using a difference-in-differences approach. Results from the econometric analyses show that ratings in a single-dimensional rating system have a downward trend and a higher dispersion, whereas ratings in a multidimensional rating system are significantly higher and convergent. Findings from two randomized experiments suggest that the multidimensional rating system helps consumers find products that better fit their preferences and increases the confidence of their choices. We also show that the observed results cannot be explained by the priming effect due to rating system interface or a list of other alternative explanations. The combined evidence from the natural experiment and randomized experiments support the view that the multidimensional rating system enhances rating informativeness and provide implications for designing online rating systems that help consumers match their preferences with product attributes.
@article{chen2018value, title = {The value of multidimensional rating systems: Evidence from a natural experiment and randomized experiments}, author = {Chen, Pei-Yu and Hong, Yili and Liu, Ying}, journal = {Management Science}, volume = {64}, number = {10}, pages = {4629--4647}, year = {2018}, doi = {https://doi.org/10.1287/mnsc.2017.2852}, publisher = {INFORMS} }
Surviving in global online labor markets for IT services: A geo-economic analysis

Irfan Kanat, Yili Hong, and TS Raghu

Information Systems Research, 2018

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Global online labor markets (OLMs) lower the barriers to entry and enable global competition for information technology (IT) services from providers around the world. Although the prior OLM literature predominantly found systematic advantages for IT service providers from developed countries because of their higher perceived quality, the reality is that most service providers in OLM are from developing countries. This phenomenon requires a robust analysis of how OLMs are evolving. In this study, we conduct a geo-economic analysis on IT service providers’ survival utilizing a unique longitudinal panel data set from an OLM, which comprises 40,874 IT service providers from different countries over a period of more than four years (2006 to 2010). Based on results from Survival models and a series of robustness checks, we were able to decipher how geo-economic factors (specifically the country development level) and reputation interact to determine service providers’ survival. Our findings provide a different perspective from the prior literature on OLM by showing a systematic advantage for IT service providers from developing countries in terms of survival, especially when providers from developing countries were able to signal their individual quality through reputation. We explain and discuss the mechanisms underlying these effects, and highlight implications for OLMs for IT services.
@article{kanat2018surviving, title = {Surviving in global online labor markets for IT services: A geo-economic analysis}, author = {Kanat, Irfan and Hong, Yili and Raghu, TS}, journal = {Information Systems Research}, volume = {29}, number = {4}, pages = {893--909}, year = {2018}, doi = {https://doi.org/10.1287/isre.2017.0751}, publisher = {INFORMS} }

2017

On the role of fairness and social distance in designing effective social referral systems

Yili Hong, Paul A Pavlou, Nan Shi, and Kanliang Wang

MIS Quarterly, 2017

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Online referral systems help firms attract new customers and expand their customer base by leveraging the social relationships of existing customers. We integrate ultimatum game theory, which focuses on fairness, with motivation theories to investigate the effects of social distance and monetary incentives on the performance of three competing designs for online referral systems: rewarding only or primarily the proposer, rewarding only or primarily the responder, and dividing the reward equally or fairly between the proposer and responder. A set of controlled laboratory and randomized field experiments were conducted to test how the fairness of the split of the reward (equal/fair versus unequal/unfair split of the referral bonus) and social distance (small versus large) between the proposer and the responder jointly affect the performance of online referral systems (the proposer sending an offer and the responder accepting the offer). For a large social distance (acquaintances or weak tie relationships), equally splitting the referral bonus results in the best performance. However, for a small social distance (friends or strong tie relationships), an equal split of the referral reward does not improve referral performance, which suggests that under a small social distance, monetary incentives may not work effectively. Face validity and external validity (generalizability) are ensured using two distinct measures of social distance across several contexts. Through the analysis of the interaction effects of fairness and social distance, our research offers theoretical and practical implications for social commerce by showing that the effectiveness of fairness on the success of online social referrals largely depends on social distance.
@article{hong2017role, title = {On the role of fairness and social distance in designing effective social referral systems}, author = {Hong, Yili and Pavlou, Paul A and Shi, Nan and Wang, Kanliang}, journal = {MIS Quarterly}, volume = {41}, number = {3}, pages = {787--A13}, year = {2017}, publisher = {JSTOR} }
On buyer selection of service providers in online outsourcing platforms for IT services

Yili Hong, and Paul A Pavlou

Information Systems Research, 2017

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The Internet has presumably created a level playing field that allows any service provider across the globe to compete for contracts on online outsourcing platforms for information technology (IT) services. In this paper, we empirically examine (a) how country (language, time zone, cultural) differences and the country’s IT development affect buyers’ selection of service providers in online outsourcing platforms; and (b) how the reputation of service providers moderates the proposed effects of country differences and the country’s IT development. We integrated a unique data set formed by a sample of 11,541 software development projects from an online outsourcing platform matched with archival sources on the language, time zone, culture, and IT development of countries. Since price is typically endogenous in any supply demand system, we used the exogenous variation of the normalized exchange rate of the currency among countries, as a “cost-shifter” type instrumental variable (IV) for econometric identification. Our panel data analyses results (both with and without IV) show that buyers are negatively affected by country differences in terms of language, time zone, and culture, and prefer service providers from countries with higher IT development. Notably, the reputation of service providers attenuates the negative effects of language and cultural (but not time zone) differences, while it substitutes the positive effect of the country’s IT development. We discuss the study’s theoretical and managerial implications for understanding the global dynamics of online outsourcing platforms and better designing these platforms.
@article{hong2017buyer, title = {On buyer selection of service providers in online outsourcing platforms for IT services}, author = {Hong, Yili and Pavlou, Paul A}, journal = {Information Systems Research}, volume = {28}, number = {3}, pages = {547--562}, year = {2017}, doi = {https://doi.org/10.1287/isre.2017.0709}, publisher = {INFORMS} }
On the role of fairness and social distance in designing effective social referral systems

Ni Huang, Yili Hong, and Gordon Burtch

MIS Quarterly, 2017

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This paper is the lead article of this issue of MIS Quarterly.

This study examines how social network integration (i.e., integration of online platforms with other social media services, for example, with Facebook or Twitter) can affect the characteristics of user-generated content (volume and linguistic features) in the context of online reviews. Building on the social presence theory, we propose a number of hypotheses on how social network integration affects review volume and linguistic features of review text. We consider two natural experiments at leading online review platforms (Yelp.com and TripAdvisor.com), wherein each implemented a social network integration with Facebook. Constructing a unique panel dataset of online reviews for a matched set of restaurants across the two review sites, we estimate a difference-in-differences (DID) model to assess the impact of social network integration. We find that integration with Facebook increased the production of user-generated content and positive emotion in review text, while simultaneously decreasing cognitive language, negative emotion, and expressions of disagreement (negations) in review text. Our findings demonstrate that social network integration works as a double-edged sword. On the one hand, integration provides benefits in terms of increased review quantity. On the other hand, these benefits appear to come at the cost of reduced review quality, given past research which has found that positive, emotional reviews are perceived by users to be less helpful. We discuss the implications of these results as they relate to the creation of sustainable online social platforms for user content generation.
@article{huang2017social, title = {On the role of fairness and social distance in designing effective social referral systems}, author = {Huang, Ni and Hong, Yili and Burtch, Gordon}, journal = {MIS Quarterly}, volume = {41}, number = {4}, pages = {1035--1058}, year = {2017}, publisher = {JSTOR}, }

2016

Comparing open and sealed bid auctions: Evidence from online labor markets

Yili Hong, Chong Wang, and Paul A Pavlou

Information Systems Research, 2016

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Online labor markets are Web-based platforms that enable buyers to identify and contract for information technology (IT) services with service providers using buyer-determined (BD) auctions. BD auctions in online labor markets either follow an open or a sealed bid format. We compare open and sealed bid auctions in online labor markets to identify which format is superior in terms of obtaining more bids and a higher buyer surplus. Our theoretical analysis suggests that the relative advantage of open versus sealed bid auctions hinges on the role of reducing service providers’ valuation uncertainty (difficulty in assessing the cost to execute a project) and competition uncertainty (difficulty in assessing the intensity of the competition from other service providers), which largely depend on the relative importance of the common value (versus the private value) component of the auctioned IT services, calling for an empirical investigation to compare open and sealed bid auctions. Based on a unique data set of 71,437 open bid auctions and 7,499 sealed bid auctions posted by 21,799 buyers at a leading online labor market, we find that, on average, although sealed bid auctions attract 18.4% more bids, open bid auctions offer buyers $10.87 higher surplus. Furthermore, open bid auctions are 55.3% more likely to result in a buyer’s selection of a certain service provider and 22.1% more likely to reach a contract (conditional on the buyer’s making a selection) with a provider, and they generate higher buyer satisfaction. In contrast to conventional wisdom that “the more bids the better” and industry practice of treating sealed bid auctions as a premium feature, our results suggest that the buyer surplus gained from the reduction in valuation uncertainty enabled by open bid auctions outweighs the buyer surplus gained from the higher competition uncertainty in sealed bid auctions, which renders open bid auctions a superior auction design in online labor markets.
@article{hong2016comparing, title = {Comparing open and sealed bid auctions: Evidence from online labor markets}, author = {Hong, Yili and Wang, Chong and Pavlou, Paul A}, journal = {Information Systems Research}, volume = {27}, number = {1}, pages = {49--69}, year = {2016}, doi = {https://doi.org/10.1287/isre.2015.0606}, publisher = {INFORMS} }

2014

Product fit uncertainty in online markets: Nature, effects, and antecedents

Yili Hong, and Paul A Pavlou

Information Systems Research, 2014

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Product fit uncertainty (defined as the degree to which a consumer cannot assess whether a product’s attributes match her preference) is proposed to be a major impediment to online markets with costly product returns and lack of consumer satisfaction. We conceptualize the nature of product fit uncertainty as an information problem and theorize its distinct effect on product returns and consumer satisfaction (versus product quality uncertainty), particularly for experience (versus search) goods without product familiarity. To reduce product fit uncertainty, we propose two Internet-enabled systems—website media (visualization systems) and online product forums (collaborative shopping systems)—that are hypothesized to attenuate the effect of product type (experience versus search goods) on product fit uncertainty. Hypotheses that link experience goods to product returns through the mediating role of product fit uncertainty are tested with analyses of a unique data set composed of secondary data matched with primary direct data from numerous consumers who had recently participated in buy-it-now auctions. The results show the distinction between product fit uncertainty and quality uncertainty as two distinct dimensions of product uncertainty and interestingly show that, relative to product quality uncertainty, product fit uncertainty has a significantly stronger effect on product returns. Notably, whereas product quality uncertainty is mainly driven by the experience attributes of a product, product fit uncertainty is mainly driven by both experience attributes and lack of product familiarity. The results also suggest that Internet-enabled systems are differentially used to reduce product (fit and quality) uncertainty. Notably, the use of online product forums is shown to moderate the effect of experience goods on product fit uncertainty, and website media are shown to attenuate the effect of experience goods on product quality uncertainty. The results are robust to econometric specifications and estimation methods. The paper concludes by stressing the importance of reducing the increasingly prevalent information problem of product fit uncertainty in online markets with the aid of Internet-enabled systems.
@article{hong2014product, title = {Product fit uncertainty in online markets: Nature, effects, and antecedents}, author = {Hong, Yili and Pavlou, Paul A}, journal = {Information Systems Research}, volume = {25}, number = {2}, pages = {328--344}, year = {2014}, doi = {https://doi.org/10.1287/isre.2014.0520}, publisher = {INFORMS} }

2012

On product uncertainty in online markets: Theory and evidence

Angelika Dimoka, Yili Hong, and Paul A Pavlou

MIS Quarterly, 2012

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Online markets pose a difficulty for evaluating products, particularly experience goods, such as used cars, that cannot be easily described online. This exacerbates product uncertainty, the buyer’s difficulty in evaluating product characteristics, and predicting how a product will perform in the future. However, the IS literature has focused on seller uncertainty and ignored product uncertainty. To address this void, this study conceptualizes product uncertainty and examines its effects and antecedents in online markets for used cars (eBay Motors). Extending the information asymmetry literature from the seller to the product, we first theorize the nature and dimensions (description and performance) of product uncertainty. Second, we propose product uncertainty to be distinct from, yet shaped by, seller uncertainty. Third, we conjecture product uncertainty to negatively affect price premiums in online markets beyond seller uncertainty. Fourth, based on the information signaling literature, we describe how information signals (diagnostic product descriptions and third-party product assurances) reduce product uncertainty. The structural model is validated by a unique dataset comprised of secondary transaction data from used cars on eBay Motors matched with primary data from 331 buyers who bid on these used cars. The results distinguish between product and seller uncertainty, show that product uncertainty has a stronger effect on price premiums than seller uncertainty, and identify the most influential information signals that reduce product uncertainty. The study’s implications for the emerging role of product uncertainty in online markets are discussed.
@article{dimoka2012product, title = {On product uncertainty in online markets: Theory and evidence}, author = {Dimoka, Angelika and Hong, Yili and Pavlou, Paul A}, journal = {MIS Quarterly}, volume = {36}, number = {2}, pages = {395--426}, year = {2012}, doi = {https://doi.org/10.2307/41703461}, publisher = {JSTOR} }