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Mobile Push vs. Pull Targeting and Geo-Conquesting Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-13 Dominik Molitor, Martin Spann, Anindya Ghose, Philipp Reichhart
Firms have two distinct options when delivering content to consumers’ mobile devices: mobile push and mobile pull. Mobile push delivers firm-initiated (ad) content directly to consumers, while mobile pull requires consumers to initiate requests for (ad) content. This study tests the impact of mobile push and mobile pull on consumers’ coupon redemption behavior in a large-scale randomized field experiment
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Mr. Right or Mr. Best: The Role of Information Under Preference Mismatch in Online Dating Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-13 Hongchuan Shen, Chu (Ivy) Dang, Xiaoquan (Michael) Zhang
The rise of two-sided matching platforms such as Uber, Airbnb, Upwork, and Tinder has changed the way we commute, travel, work, and even date. The success of these platforms depends on the role of information: What information and how much information should be provided? In this study, we focus on a defining characteristic of two-sided matching markets—that is, a match depends on the possibly different
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Integrated Decision Support for Disaster Risk Management: Aiding Preparedness and Response Decisions in Wildfire Management Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-12 Daniel Suarez, Camilo Gomez, Andrés L. Medaglia, Raha Akhavan-Tabatabaei, Sthefania Grajales
A central challenge in disaster risk management (DRM) is that there are key dependencies and uncertainty between the decisions made at the mitigation, preparedness, response, and recovery stages. Decision support systems for disaster management require information systems that allow timely and reliable integration of data sources from different domains, including information on hazards and vulnerabilities
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Enhancing User Privacy Through Ephemeral Sharing Design: Experimental Evidence from Online Dating Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-11 Yumei He, Xingchen Xu, Ni Huang, Yili Hong, De Liu
In the dynamic world of online dating, a key challenge faced by platforms is the cold-start problem, where newly matched users are hesitant to engage due to privacy concerns. Our solution, ephemeral sharing, addresses this by balancing privacy with the need for personal information sharing. This feature allows personal photos to disappear and become untraceable soon after being viewed, reassuring users
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Monitoring and the Cold Start Problem in Digital Platforms: Theory and Evidence from Online Labor Markets Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-06 Chen Liang, Yili Hong, Bin Gu
In the realm of online labor platforms, addressing moral hazard is crucial. Reputation systems have been the conventional solution, yet they pose a cold-start problem for newcomers. Alternatively, monitoring systems provide real-time oversight to employers, directly tackling moral hazard. This study combines theory and empirical analysis using data from a leading online labor platform. We find that
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Understanding Volunteer Crowdsourcing from a Multiplex Perspective Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-04 Yifan Yu, Xue (Jane) Tan, Yong Tan
Our study delves into the understudied realm of volunteer crowdsourcing activities. Analyzing 827,260 volunteers’ participation in 183,445 projects initiated by 74,556 nonprofit organizations over nine years, the study unlocks insights into volunteers’ collaboration relationships and their behaviors, vital for increasing nonpaid labor supply and enhancing platform performance. We introduce a multiplex
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How Recommendation Affects Customer Search: A Field Experiment Inform. Sys. Res. (IF 5.49) Pub Date : 2024-03-04 Zhe Yuan, AJ Yuan Chen, Yitong Wang, Tianshu Sun
The findings of this study have important implications for digital platform designers, managers, and regulators. First, the large-scale field experiment provides valuable insights into the relationship between product recommendation and consumer search under different scenarios. It highlights the importance of understanding consumer demand states and previous interests. Platforms can use these findings
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A Nudge to Credible Information as a Countermeasure to Misinformation: Evidence from Twitter Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-28 Elina H. Hwang, Stephanie Lee
As people increasingly rely on social media to obtain healthcare information, misinformation, such as myths, rumors, and false information on healthcare, is posing a grave threat to public health. This paper investigates a potential remedy for such infodemic by examining a unique countermeasure that Twitter implemented. Instead of resorting to outright censorship, Twitter has taken a more nuanced approach:
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Regulating Powerful Platforms: Evidence from Commission Fee Caps Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-28 Zhuoxin Li, Gang Wang
Digital platforms have become increasingly dominant in many industries, bringing the concerns of adverse economic and societal effects (e.g., monopolies and social inequality). Regulators are actively seeking diverse strategies to regulate these powerful platforms. However, the lack of empirical studies hinders the progress toward evidence-based policymaking. This research investigates the regulatory
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Strategic Expectation Setting of Delivery Time on Marketplaces Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-23 Si Xie, Siddhartha Sharma, Amit Mehra, Arslan Aziz
Delivery speed is an essential component of the service provided by online delivery platforms. Because improving actual delivery speed is expensive, platforms can instead create a perception of faster delivery by showing a conservative estimate of the delivery duration when a customer places an order. We use detailed transaction-level data from a major food delivery marketplace to examine the effects
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The Impact of Process- vs. Outcome-Oriented Reviews on the Sales of Healthcare Services Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-22 Hongfei Li, Jing Peng, Gang Wang, Xue Bai
With the rise of digital health platforms, consumers increasingly rely on online reviews when choosing healthcare services. Understanding how these reviews shape consumer decisions is crucial for both platforms and healthcare providers. To explore this, we analyzed a comprehensive data set from a leading online cosmetic surgery platform to understand how process-oriented (focusing on the recovery experience)
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Strategic Content Generation and Monetization in Financial Social Media Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-20 Ding Li, Khim-Yong Goh, Cheng-Suang Heng
Strategic Content Generation and Monetization in Financial Social MediaAbstractFinancial social media, which relies on social media analysts (SMAs) to contribute content to investors, is a crucial channel for investors to gain financial information and for SMAs to monetize their content. The interactive nature of financial social media has given SMAs the opportunity to gain access to the investor preferences
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Mispricing and Algorithm Trading Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-19 Lihong Zhang, Xiaoquan (Michael) Zhang
This study relaxes the efficient market hypothesis by introducing a model that accounts for initial mispricing and explores the effects of algorithmic trading. The research finds that algorithmic strategies can cause significant market volatility and affect financial stability, particularly when they amplify overpricing, leading to bubbles and crashes. Key insights include: Initial mispricing is crucial
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Making Lemonade from Lemons: A Transaction Cost Economics Perspective on Third-Party Disruptions in a Multivendor Information Technology Service Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-13 Haoyuan Liu, Wen Wen, Anitesh Barua, Andrew B. Whinston
In modern enterprise computing environments, multiple information technology (IT) services from first and third parties are often integrated to form coherent solutions for enterprise customers. In this study, 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
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A Smart Ad Display System Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-09 Li Xiao, D. J. Wu, Min Ding
This paper proposes a smart ad display system to provide personalized delivery of video ads. The proposed system records consumers’ facial expression and eye gaze stream data as they watch an ad and analyzes data at the frame level. The recognized facial expression and detected eye gaze are matched to the corresponding frame of the video ad, thereby linking facial expressions to specific visual objects
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Operation Dumbo Drop: To Airdrop or Not to Airdrop for Initial Coin Offering Success? Inform. Sys. Res. (IF 5.49) Pub Date : 2024-02-08 Jian Li, Xiang (Shawn) Wan, Hsing Kenneth Cheng, Xi Zhao
Practice AbstractInitial Coin Offerings (ICOs) have become a new and popular fundraising approach for blockchain start-ups. To motivate blockchain individuals to invest in the subsequent ICO, a growing number of blockchain-based project founders employ the airdrop campaign, through which they distribute a specific amount of free official tokens or promotional tokens to potential investors on the blockchain
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Background Music Recommendation on Short Video Sharing Platforms Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-31 Jiawei Chen, Luo He, Hongyan Liu, Yinghui (Catherine) Yang, Xuan Bi
On short video sharing platforms, users often choose background music for their videos. In this paper, we study the problem of background music recommendation for short videos on short video sharing platforms. In our recommendation setting, the item (music) is not recommended directly to the user, but to the video created by the user. When making music recommendations for videos, we consider three
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Encouraging Eco-driving with Post-trip Visualized Storytelling: An Experiment Combining Eye-Tracking and a Driving Simulator Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-31 Zhiyin Li, Ben C. F. Choi
Air pollution contributes to global warming and climate change, leading to extreme weather events and rising sea levels. Promoting sustainable practices has become the focus of policy programs and awareness campaigns. In this study, we propose an effective and powerful way to promote eco-driving behaviors by drawing on data storytelling. Our study shows that animated narrative and narrative sequence
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Digital Approaches to Societal Grand Challenges: Toward a Broader Research Agenda on Managing Global-Local Design Tensions Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-29 Satish Nambisan, Gerard George
Policy/Practice-Focused AbstractDespite considerable and continued resource investments, effective solutions to broad-scope problems of social interest or societal grand challenges (GCs) have proven to be elusive in many domains. In multiactor situations that characterize GCs, divergent goals, needs, priorities, and capabilities of global and local actors create organizing design tensions that need
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Calibration of Heterogeneous Treatment Effects in Randomized Experiments Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-12 Yan Leng, Drew Dimmery
Machine learning is commonly used to estimate the heterogeneous treatment effects (HTEs) in randomized experiments. Using large-scale randomized experiments on Facebook and Criteo platforms, we observe substantial discrepancies between machine learning-based treatment effect estimates and difference-in-means estimates directly from the randomized experiment. This paper provides a two-step framework
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Noisebnb: An Empirical Analysis of Home-Sharing Platforms and Residential Noise Complaints Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-11 Gorkem Turgut Ozer, Brad N. Greenwood, Anandasivam Gopal
Practice and Policy-Based AbstractExternalities stemming from digital platforms have had a profound impact on the daily lives of people across the globe. In this work, we examine one such externality that contributes to urban quality of life, the noise stemming from home-sharing platforms, which has been subject to aggressive scrutiny by policymakers and the popular press but has received limited rigorous
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Exploring Contrasting Effects of Trust in Organizational Security Practices and Protective Structures on Employees’ Security-Related Precaution Taking Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-08 Malte Greulich, Sebastian Lins, Daniel Pienta, Jason Bennett Thatcher, Ali Sunyaev
Encouraging employees to take security precautions is a vital strategy that organizations can use to reduce their vulnerability to information security (ISec) threats. This study investigates how the bright- and dark-side effects of trust in organizational information security impact employees’ intention to take security precautions. Employees who trust organizational security practices are more committed
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Content Length Limit: How Does It Matter for a Consumer-to-Consumer Media Platform? Inform. Sys. Res. (IF 5.49) Pub Date : 2024-01-03 Zheyin (Jane) Gu, Xuying Zhao
Our study is inspired by the rapid growth of consumer-to-consumer (C2C) media platforms such as TikTok. There are three key findings. First, we show that when content pieces on the platform are longer, viewers set a higher standard of match value in selecting content to view, leading to a lower click-through rate of contributed content on the platform. This finding suggests that a tight limit on content
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Digital Contact Tracing for Pandemic Response: The Roles of Cultural Worldviews and Technology Awareness Inform. Sys. Res. (IF 5.49) Pub Date : 2023-12-21 Jingguo Wang, Yuan Li
Information technologies have been developed and used by government agencies and public authorities to address societal issues, but their effectiveness often hinges on public support and participation. This is evidenced in the use of digital contact tracing (DCT) technology to contain the spread of the coronavirus. Despite the efforts of public authorities and technology firms to develop and promote
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Managerial Response to Online Positive Reviews: Helpful or Harmful? Inform. Sys. Res. (IF 5.49) Pub Date : 2023-12-20 Chaoqun Deng, T. Ravichandran
Managerial responses to negative reviews could be easily understood as a brand-safeguarding strategy by firms because negative reviews can damage a company’s reputation. However, it is unclear if managers should respond to positive reviews and if so, if such action helps or hurts the firm. We develop a theoretical framework to explicate the mechanisms underlying the effects of managerial responses
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Rethinking Gamification Failure: A Model and Investigation of Gamified System Maladaptive Behaviors Inform. Sys. Res. (IF 5.49) Pub Date : 2023-12-19 Shih-Lun “Allen” Tseng, Heshan Sun, Radhika Santhanam, Shuya Lu, Jason B. Thatcher
Current studies show gamification, the integrating of game design elements into target systems, enhances user engagement and instrumental task outcomes. Despite its potential for improving behavioral outcomes, gamification can also lead to maladaptive behaviors, behaviors directed at misappropriating gamified systems. We conceptualized gamified system maladaptive behaviors (GSMB), which involve technology
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The Anchoring Effect, Algorithmic Fairness, and the Limits of Information Transparency for Emotion Artificial Intelligence Inform. Sys. Res. (IF 5.49) Pub Date : 2023-12-19 Lauren Rhue
Emotion artificial intelligence (AI) is shown to vary systematically in its ability to accurately identify emotions, and this variation creates potential biases. In this paper, we conduct an experiment involving three commercially available emotion AI systems and a group of human labelers tasked with identifying emotions from two image data sets. The study focuses on the alignment between facial expressions
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Can Telework Adjustment Help Reduce Disaster-Induced Gender Inequality in Job Market Outcomes? Inform. Sys. Res. (IF 5.49) Pub Date : 2023-12-11 Jingbo Hou, Chen Liang, Pei-Yu Chen, Bin Gu
This study investigates the role of telework adjustment in addressing gender inequality in the labor market induced by disasters, taking the COVID-19 disaster as an example. Disasters often disrupt labor markets, disproportionately impacting female workers because of traditionally greater domestic responsibilities, thus increasing gender inequality. In such a case, telework adjustment has emerged as
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Do “Likes” in a Brand Community Always Make You Buy More? Inform. Sys. Res. (IF 5.49) Pub Date : 2023-12-07 Chen Liang, Ji Wu, Xinxin Li
Online brand communities often use social plug-in features, such as the Like button, to facilitate social interactions and engage users with the brands. However, whether and how such a community feature affects users’ purchases remain open questions. Analysis of user behavior following the adoption of the Like feature indicates a surprising downturn in purchases, with a 4.1% decrease in orders and
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Crowdworking: Nurturing Expert-Centric Absorptive Capacity Inform. Sys. Res. (IF 5.49) Pub Date : 2023-11-29 Elham Shafiei Gol, Michel Avital, Mari-Klara Stein
Organizations increasingly engage with external communities for value generation through an ever-growing multitude of digital services. Absorptive capacity, or the organizational capability to identify, assimilate, and apply new knowledge for commercial ends, is a key determinant of how organizations successfully generate value from external sources of knowledge and sustain a competitive advantage
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Platform Loophole Exploitation, Recovery Measures, and User Engagement: A Quasi-Natural Experiment in Online Gaming Inform. Sys. Res. (IF 5.49) Pub Date : 2023-11-28 Jianqing Chen, Shu He, Xue Yang
Online platforms often encounter the challenge of system vulnerabilities, such as bugs, which can be exploited by certain users for illicit gains. These platforms face a dilemma when devising countermeasures, particularly in deciding whether to penalize rule breakers. Different countermeasures can lead to varying economic impacts, including subsequent user engagement. In this study, based on unique
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Longitudinal Impact of Preference Biases on Recommender Systems’ Performance Inform. Sys. Res. (IF 5.49) Pub Date : 2023-11-21 Meizi Zhou, Jingjing Zhang, Gediminas Adomavicius
Recommender systems are ubiquitous on various online platforms and provide significant value to the users in helping them find relevant content/items to consume. After item consumption, users can often provide feedback (i.e., their preference ratings for the item) to the system. Research studies have shown that recommender systems’ predictions, observed by users, can cause biases in users’ postconsumption
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When Does Beauty Pay? A Large-Scale Image-Based Appearance Analysis on Career Transitions Inform. Sys. Res. (IF 5.49) Pub Date : 2023-11-08 Nikhil Malik, Param Vir Singh, Kannan Srinivasan
When Does Beauty Pay? A Large-Scale Image Based Appearance Analysis on Career TransitionsIn this study, we collect up to 15 years of career histories for over 40,000 MBA graduates from top 100 MBA programs in the United States. We find that attractive MBA graduates earn at least $2,508 more in yearly salary compared with plain-looking (unattractive) MBA graduates. The attractiveness premium is even
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A Computational Framework for Understanding Firm Communication During Disasters Inform. Sys. Res. (IF 5.49) Pub Date : 2023-11-07 Bei Yan, Feng Mai, Chaojiang Wu, Rui Chen, Xiaolin Li
Firms’ public communication on social media during disasters can benefit both disaster response efficiency and the perception of the corporate image. Despite its importance, limited guidelines are available to inform firms’ disaster communication strategies. The current study examines firms’ communication on social media in various disasters and how it impacts public engagement. We employ a novel natural
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Uncertainty Reduction vs. Reciprocity: Understanding the Effect of a Platform-Initiated Reviewer Incentive Program on Regular Ratings Inform. Sys. Res. (IF 5.49) Pub Date : 2023-11-07 Jingchuan Pu, Young Kwark, Sang Pil Han, Qiang Ye, Bin Gu
Many online platforms are now offering free samples to seasoned reviewers, hoping to get feedback. While these reviewers are given free samples to review, they also buy and review products themselves. The regular ratings for the purchased products are the majority. This brings up the question: Does receiving free products make them rate their personal purchases more positively? And if so, why? We explored
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The Open Prison of the Big Data Revolution: False Consciousness, Faustian Bargains, and Digital Entrapment Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-31 Ojelanki Ngwenyama, Frantz Rowe, Stefan Klein, Helle Zinner Henriksen
Although some scholars raise alarm about societal harm emerging from Big Data practices, critical social theory (CST) Information Systems research on the structures and dynamics driving Big Data practices is rare. In this research commentary, we interrogate how tech firms use social practices and platform design to strategically manipulate individuals into accepting datafication and data assetization
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Join Up or Stay Away? Coalition Formation for Critical IT Infrastructure Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-23 Hong Guo, Yipeng Liu, Barrie R. Nault
PRACTICE AND POLICY ABSTRACTWe consider the formation of a coalition when districts invest in critical IT infrastructure that, if disrupted, can cause significant damage to security, the economy, public health, or safety. The benefits from these investments can spill over to other districts. Districts choose whether to participate in a coalition, and the coalition subsequently makes IT infrastructure
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Social Trading, Communication, and Networks Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-20 Jiaying Deng, Mingwen Yang, Matthias Pelster, Yong Tan
Social trading is an emerging market in the sharing economy, allowing investors (followers) to duplicate the trades of other investors (leaders) in real time. We analyze the formation and dissolution of links in a large social trading network. Such networks are characterized by the rapid dissolution of links, increasing the importance of studying network dissolution. We investigate how social communication
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How Does Online Information Influence Offline Transactions? Insights from Digital Real Estate Platforms Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-17 Zhengrui Jiang, Arun Rai, Hua Sun, Cheng Nie, Yuheng Hu
This study highlights the critical function that digital real estate platforms, like Zillow, serve in facilitating effective property transactions. They do this by transmitting vital property information from sellers to buyers, thereby enriching the value of offline deals. Our findings indicate that Zillow, as a source of information, is incredibly valuable for properties that deviate significantly
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Retargeted Versus Generic Product Recommendations: When is it Valuable to Present Retargeted Recommendations? Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-16 Xiang (Shawn) Wan, Anuj Kumar, Xitong Li
Practitioner’s AbstractOnline platforms/retailers widely use collaborative filtering (CF)-based generic product recommendations to improve sales. These systems recommend products to a consumer based on the product co-views and co-purchases by other consumers on the website but do not leverage the consumer’s browsing data. Based on a field study on a U.S. fashion apparel and home goods retailer’s website
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Development Trajectory of Blockchain Platforms: The Role of Multirole Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-13 Tianyi Li, Xiaoquan (Michael) Zhang
Understanding the development trajectory of digital platforms is central to digital platform management. We develop a parametric model that investigates the development trajectories of blockchain platforms, accounting for the feedback between blockchains’ utility change and people’s adoption and abandonment behavior. We consider a typical blockchain participant to simultaneously play three roles on
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Dinner at Your Doorstep: Service Innovation via the Gig Economy on Food Delivery Platforms Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-12 Geng Sun, Yeongin Kim, Yinliang (Ricky) Tan, Geoffrey G. Parker
Despite the rapid growth of online food delivery (OFD) market, the impact of its three-sided nature—encompassing consumers, restaurants, and gig drivers—on incentives and payoffs remains unclear compared to the traditional two-sided model. This study examines how OFD platforms make optimal choices in a competitive environment involving pricing and service quality. The analysis reveals that insights
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Leveraging the Digital Tracing Alert in Virus Fight: The Impact of COVID-19 Cell Broadcast on Population Movement Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-12 Anindya Ghose, Heeseung Andrew Lee, Wonseok Oh, Yoonseock Son
Digital tracing alerts (DTAs) have emerged as effective means to share information with agility in responding to disaster outbreaks. Governments are able to instantaneously coordinate the available information to provide information related to the disaster and promote preventive actions. However, despite the opportunities granted by these innovative technologies in managing disasters, privacy concerns
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Racial Discrimination and Anti-discrimination: The COVID-19 Pandemic’s Impact on Chinese Restaurants in North America Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-11 Chuang Tang, Shaobo (Kevin) Li, Yi Ding, Ram D. Gopal, Guanglei Zhang
The coronavirus disease 2019 (COVID-19) pandemic has seen a rise in racial discrimination against Asian communities, notably the Chinese population. Despite growing research on various aspects of the pandemic, there is a notable gap in understanding its behavioral impact regarding racial discrimination. This study delves into the manifestations of COVID-19-related racial discrimination and antidiscrimination
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Ontology-Based Intelligent Interface Personalization for Protection Against Phishing Attacks Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-11 Fatemeh Mariam Zahedi, Yan Chen, Huimin Zhao
Millions of users on the Internet have fallen into phishing website traps. Detection tools are designed to warn users against such attacks, but often fail to achieve this purpose. One crucial reason behind this is that users rarely have a chance to interact and build a relationship with a detection tool that stealthily runs at the backend. A warning message on a rarely seen interface from such a tool
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The Impacts of Internet Monitoring on Employees’ Cyberloafing and Organizational Citizenship Behavior: A Longitudinal Field Quasi-Experiment Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-11 Hemin Jiang, Mikko Siponen, Zhenhui (Jack) Jiang, Aggeliki Tsohou
Many organizations have implemented internet monitoring to curb employees’ non-work-related internet activities during work hours, commonly referred to as “cyberloafing.” For managers, two primary considerations emerge: (1) the actual effectiveness of internet monitoring in diminishing cyberloafing and (2) any unintended side effects this monitoring might have on overall employee behavior. From a longitudinal
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Are Neighbors Alike? A Semi-supervised Probabilistic Collaborative Learning Model for Online Review Spammers Detection Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-10 Zhiang Wu, Guannan Liu, Junjie Wu, Yong Tan
Review spammers can harm the trustworthy environment of online platforms by purposefully posting unauthentic ratings and comments for products or online merchants, with the aim of gaining improper benefits. Though a vast majority of methods have been proposed to resolve the spammer detection problem, several challenges such as collusion recognition, label scarcity and biased distributions, etc., are
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An Onto-Epistemological Analysis of Information Privacy Research Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-05 Heng Xu, Nan Zhang
Privacy is one of the most pressing concerns in the continuously evolving landscape of information technology. Despite decades of vigorous and multifaceted exploration in the interdisciplinary field of information privacy, a consensual or unifying theory remains elusive. Moreover, the complexities of issues surrounding privacy are frequently labeled as “too big to understand” in the public press. At
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When Variety Seeking Meets Unexpectedness: Incorporating Variety-Seeking Behaviors into Design of Unexpected Recommender Systems Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-04 Pan Li, Alexander Tuzhilin
In this paper, we study the consumers’ variety-seeking behavior in recommender system applications and propose a comprehensive framework to measure such behavior based on past consumption records. The effectiveness of the proposed framework is validated through user questionnaire studies conducted at Alibaba, where our constructed variety-seeking measures match well with consumers’ self-reported levels
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When Sharing Economy Meets Traditional Business: Coopetition Between Ride-Sharing Platforms and Car-Rental Firms Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-03 Chenglong Zhang, Jianqing Chen, Srinivasan Raghunathan
Coopetition has been a common practice, especially among emerging markets. The coopetition relationship between a ride-sharing platform and a car-rental firm is distinct in that they operate under two different business models. Although the platform controls both its demand and supply by setting rider prices and driver wages, the car-rental firm operates under the traditional model with a fixed supply
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Dynamic Bayesian Network–Based Product Recommendation Considering Consumers’ Multistage Shopping Journeys: A Marketing Funnel Perspective Inform. Sys. Res. (IF 5.49) Pub Date : 2023-10-03 Qiang Wei, Yao Mu, Xunhua Guo, Weijie Jiang, Guoqing Chen
Recommender systems are widely used by platforms/merchants to find the products that are likely to interest consumers. However, existing dynamic methods still face challenges with regard to diverse behaviors, variability in interest shifts, and the identification of psychological dynamics. Premised on the marketing funnel perspective to analyze consumer shopping journeys, this study proposes a novel
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The Performative Production of Trace Data in Knowledge Work Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-20 Aleksi Aaltonen, Marta Stelmaszak
Firms increasingly harness data that are created as by-products of information systems usage to evaluate and manage employees. However, such “trace data” can be a double-edged sword. The data can provide a whole new visibility into work practices but also, make work less transparent if the employees start to change their behavior to shape the data. We study this dilemma in the context of knowledge
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Does Help Help? An Empirical Analysis of Social Desirability Bias in Ratings Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-20 Jinyang Zheng, Guopeng Yin, Yong Tan, Jianing Ding
Review-in-review (RIR) is a feature that allows viewers to generate positive or negative evaluations for primary quality evaluations of a product (e.g., ratings and reviews). This study reveals that it can cause social desirability bias in primary ratings: Reviewers who desire social recognition are driven to adjust their ratings (about 7.4% likelihood) to elicit more helpful responses and avoid unhelpful
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Chilling Effect of the Enforcement of Computer Misuse Act: Evidence from Publicly Accessible Hack Forums Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-19 Qiu-Hong Wang, Ruibin Geng, Seung Hyun Kim
To reduce the availability of hacking tools for use in cybersecurity offenses, many countries have enacted computer misuse acts (CMA) that criminalize the production, distribution, and possession of such tools with criminal intent. Nevertheless, our research illuminates an unintended consequence: the chilling effect of CMA enforcement on legitimate cybersecurity discussions, some of which may be desirable
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Consequences of Information Feed Integration on User Engagement and Contribution: A Natural Experiment in an Online Knowledge-Sharing Community Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-14 Zike Cao, Yingpeng Zhu, Gen Li, Liangfei Qiu
This paper investigates the ramifications of information feed integration on user engagements and contributions in online content-sharing platforms by exploiting a natural experiment occurred in a leading knowledge-sharing platform that integrated informal social posts with professional knowledge content in one feed. Our results show that the juxtaposition of incongruous types of content increased
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Clocking in or Not? Optimal Design of a Novel Gamified Business Model in Online Learning Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-11 Yi Gao, Dengpan Liu, Subodha Kumar
Clocking-in cash-back (CIC), an emerging gamified business model in online learning, has recently garnered significant attention. CIC allows users to secure a full refund of the course fee through consecutive completion of specific tasks within a required time window. These tasks, known as clocking in, encompass activities such as daily assignments and sharing progress updates on social media. By employing
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Optimal Joint Assortment for an Omni-Channel Retailer Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-08 Amar Sapra, Subodha Kumar
With the growing popularity of e-commerce, nearly every prominent retailer is aiming to turn omni-channel. One crucial decision in this pursuit is the identification of the joint assortment. In this study, we contribute by examining joint assortment and product prices for a retailer that sells products through both brick-and-mortar and online channels. Our analysis indicates that the optimal assortment
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Proactive Resource Request for Disaster Response: A Deep Learning-Based Optimization Model Inform. Sys. Res. (IF 5.49) Pub Date : 2023-09-06 Hongzhe Zhang, Xiaohang Zhao, Xiao Fang, Bintong Chen
In the realm of disaster response operations, effective resource management is crucial. This research introduces an innovative approach that proactively determines the optimal quantities of resources that should be requested by local agencies. This determination is based on both current and anticipated demands, thereby ensuring a more efficient and effective response to disasters. The approach first
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Speak with One Voice? Examining Content Coordination and Social Media Engagement During Disasters Inform. Sys. Res. (IF 5.49) Pub Date : 2023-08-31 Changseung Yoo, Eunae Yoo, Lu (Lucy) Yan, Alfonso Pedraza-Martinez
Speak with One Voice? Examining Content Coordination and Social Media Engagement During DisastersPractice- and policy-oriented abstract:Disaster relief organizations (DROs) use social media to share information rapidly and broadly. Many DROs maintain multiple accounts on the same social media platform. Each account represents a different operational entity of a DRO, such as its national headquarters
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The Attention Economy: Measuring the Value of Free Goods on the Internet Inform. Sys. Res. (IF 5.49) Pub Date : 2023-08-31 Erik Brynjolfsson, Seon Tae Kim, Joo Hee Oh
We develop a framework to measure the value of free goods and services available on the internet. The conventional method of measuring consumer surplus based on monetary expenditures is ineffective because these goods’ prices are predominantly zero. As the saying goes, time is money, and thus, our method addresses this challenge by quantifying the value of the time that consumers devote to consuming