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 for cybersecurity research, within online hack forums. More importantly, this study uniquely examines the chilling effect stemming from users’ fear of legal harm. Drawing on decision-making theories related to choice under uncertainty, we derive new insights into how legal enforcement can suppress lawful acts and reveal the dynamics of social categorization online. Our research offers valuable insights for policymakers and forum administrators. Policymakers can use our findings to mitigate unnecessary uncertainty in legal enforcement such as CMA. This includes developing legal cases to prevent false prosecutions, implementing tailored communication strategies for inexperienced individuals, and considering supplementary measures like licensing and community recognition. A transparent mechanism involving a neutral panel can also be established to ensure legal interpretations align with community norms. Forum administrators, on the other hand, can provide additional information and guidelines, foster responsible online environments, and align resources with professional standards to navigate the uncertain legal landscape and mitigate the chilling effect on knowledge-sharing.
{"title":"Chilling Effect of the Enforcement of Computer Misuse Act: Evidence from Publicly Accessible Hack Forums","authors":"Qiu-Hong Wang, Ruibin Geng, Seung Hyun Kim","doi":"10.1287/isre.2019.0346","DOIUrl":"https://doi.org/10.1287/isre.2019.0346","url":null,"abstract":"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 for cybersecurity research, within online hack forums. More importantly, this study uniquely examines the chilling effect stemming from users’ fear of legal harm. Drawing on decision-making theories related to choice under uncertainty, we derive new insights into how legal enforcement can suppress lawful acts and reveal the dynamics of social categorization online. Our research offers valuable insights for policymakers and forum administrators. Policymakers can use our findings to mitigate unnecessary uncertainty in legal enforcement such as CMA. This includes developing legal cases to prevent false prosecutions, implementing tailored communication strategies for inexperienced individuals, and considering supplementary measures like licensing and community recognition. A transparent mechanism involving a neutral panel can also be established to ensure legal interpretations align with community norms. Forum administrators, on the other hand, can provide additional information and guidelines, foster responsible online environments, and align resources with professional standards to navigate the uncertain legal landscape and mitigate the chilling effect on knowledge-sharing.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135013991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 mindset switching and cognitive strain, thus hurting user engagements. We also reveal a novel crowding-out effect, viz., the integration heightened concerns that posting informal social posts would dilute the contributor’s professional image, thus inhibiting user contributions. Our findings hold important practical implications for all platforms that host (or are considering hosting) diverse types of user-generated content (UGC). Additional content curation tools can potentially enhance user engagement and retention, but their effectiveness hinges on a foundational and crucial element—the presentation format of heterogeneous content types. Essentially, the value of curating informal social posts in a knowledge-sharing platform would diminish when those content intrudes upon and conflict with the professional domain. This insight underscores that any UGC platforms, when adopting a diversity-oriented strategy, should pay close attention to heterogeneity between different content types for the purpose of optimizing user experiences and promoting user contributions.
{"title":"Consequences of Information Feed Integration on User Engagement and Contribution: A Natural Experiment in an Online Knowledge-Sharing Community","authors":"Zike Cao, Yingpeng Zhu, Gen Li, Liangfei Qiu","doi":"10.1287/isre.2022.0043","DOIUrl":"https://doi.org/10.1287/isre.2022.0043","url":null,"abstract":"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 mindset switching and cognitive strain, thus hurting user engagements. We also reveal a novel crowding-out effect, viz., the integration heightened concerns that posting informal social posts would dilute the contributor’s professional image, thus inhibiting user contributions. Our findings hold important practical implications for all platforms that host (or are considering hosting) diverse types of user-generated content (UGC). Additional content curation tools can potentially enhance user engagement and retention, but their effectiveness hinges on a foundational and crucial element—the presentation format of heterogeneous content types. Essentially, the value of curating informal social posts in a knowledge-sharing platform would diminish when those content intrudes upon and conflict with the professional domain. This insight underscores that any UGC platforms, when adopting a diversity-oriented strategy, should pay close attention to heterogeneity between different content types for the purpose of optimizing user experiences and promoting user contributions.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134912289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 this gamification system, the firm effectively monitors user efforts, categorizing them as winners or quitters based on clocking-in completion. In this paper, we examine how a firm should set the optimal time window for its course and how the time window is affected by context-specific factors. We identify two opposing effects associated with extending the time window on users’ quitting time: the psychological disutility increasing effect (negative) and the effort cost decreasing effect (positive). Our results indicate that, as quitters’ positive word-of-mouth effects increase, there are cases in which the firm should opt for shortening the time window. Additionally, we find that, as the marginal content creation cost rises, the firm may find it more advantageous to raise the difficulty level by shortening the time window. Our findings provide valuable insights that online learning firms can utilize to enhance their design of the CIC mechanism.
{"title":"Clocking in or Not? Optimal Design of a Novel Gamified Business Model in Online Learning","authors":"Yi Gao, Subodha Kumar, Dengpan Liu","doi":"10.1287/isre.2021.0138","DOIUrl":"https://doi.org/10.1287/isre.2021.0138","url":null,"abstract":"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 this gamification system, the firm effectively monitors user efforts, categorizing them as winners or quitters based on clocking-in completion. In this paper, we examine how a firm should set the optimal time window for its course and how the time window is affected by context-specific factors. We identify two opposing effects associated with extending the time window on users’ quitting time: the psychological disutility increasing effect (negative) and the effort cost decreasing effect (positive). Our results indicate that, as quitters’ positive word-of-mouth effects increase, there are cases in which the firm should opt for shortening the time window. Additionally, we find that, as the marginal content creation cost rises, the firm may find it more advantageous to raise the difficulty level by shortening the time window. Our findings provide valuable insights that online learning firms can utilize to enhance their design of the CIC mechanism.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135938451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 should be thought of as a portfolio of two types of products: customized and omni-channel. Customized products are priced in such a way that they are targeted toward customers who prefer to shop from the channel the products are sold through. In contrast, omni-channel products are priced attractively so that all customers consider buying them. The relative mix of these products depends on how flexible customers are in shopping from the channel they do not prefer and the number of customers who prefer each channel. Additionally, we investigate whether the conventional wisdom of selling niche products through the online channel is always optimal. We find that this suggestion may be sub-optimal when the online channel has greater cost of including a product in the assortment and fewer preferring customers compared with the brick-and-mortar channel.
{"title":"Optimal Joint Assortment for an Omni-Channel Retailer","authors":"A. Sapra, Subodha Kumar","doi":"10.1287/isre.2021.0596","DOIUrl":"https://doi.org/10.1287/isre.2021.0596","url":null,"abstract":"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 should be thought of as a portfolio of two types of products: customized and omni-channel. Customized products are priced in such a way that they are targeted toward customers who prefer to shop from the channel the products are sold through. In contrast, omni-channel products are priced attractively so that all customers consider buying them. The relative mix of these products depends on how flexible customers are in shopping from the channel they do not prefer and the number of customers who prefer each channel. Additionally, we investigate whether the conventional wisdom of selling niche products through the online channel is always optimal. We find that this suggestion may be sub-optimal when the online channel has greater cost of including a product in the assortment and fewer preferring customers compared with the brick-and-mortar channel.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44583058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 utilizes a method that combines deep learning and temporal point process for predicting irregularly spaced future demands, and then, it formulates the resource allocation problem faced with randomly arrived demands as a stochastic optimization model. The superiority of this approach over existing resource allocation methods is demonstrated using both real-world data and simulated scenarios. The findings highlight the need for a shift from reactive to proactive strategies. Moreover, the research emphasizes the potential of advanced techniques, such as deep learning and stochastic optimization, in disaster management. These techniques can provide valuable tools for policy makers and practitioners in the field, enabling them to make more informed and effective decisions. Policies that encourage the adoption of such optimized resource allocation strategies could lead to more effective disaster response operations.
{"title":"Proactive Resource Request for Disaster Response: A Deep Learning-Based Optimization Model","authors":"Hongzhe Zhang, Xiaohang Zhao, Xiao Fang, Bintong Chen","doi":"10.1287/isre.2022.0125","DOIUrl":"https://doi.org/10.1287/isre.2022.0125","url":null,"abstract":"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 utilizes a method that combines deep learning and temporal point process for predicting irregularly spaced future demands, and then, it formulates the resource allocation problem faced with randomly arrived demands as a stochastic optimization model. The superiority of this approach over existing resource allocation methods is demonstrated using both real-world data and simulated scenarios. The findings highlight the need for a shift from reactive to proactive strategies. Moreover, the research emphasizes the potential of advanced techniques, such as deep learning and stochastic optimization, in disaster management. These techniques can provide valuable tools for policy makers and practitioners in the field, enabling them to make more informed and effective decisions. Policies that encourage the adoption of such optimized resource allocation strategies could lead to more effective disaster response operations.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135150294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As artificial intelligence (AI) solutions are being rapidly deployed, they increasingly compete with human labor. This study examines designers’ strategies in response to the threat from the introduction of an AI system for simple logo designs in a crowdsourcing design platform. We find that, although designers with lower abilities are more likely to exit the platform, designers with higher abilities move away from the locus of threat in the lower-tier contests and switch to more-complex design contests after the introduction of the AI system. More interestingly, we find that, although unsuccessful designers respond to the threat from AI by increasing their participation across multiple contests, successful designers become more focused (i.e., they substantially increase the number of submissions within a contest) and more quality oriented (i.e., they increase emotional content and complexity of their designs) after the AI launch. Our findings show how designers can learn from the behaviors of the more successful designers to differentiate themselves from AI systems by leveraging the more-abstract design attributes. Platform operators would benefit from adopting better segmentations strategies: with AI solutions for simple design tasks, hybrid AI + human solutions for less-complex design tasks, and skilled human designers competing primarily for the more-complex design tasks.
{"title":"Threatened by AI: Analyzing Users’ Responses to the Introduction of AI in a Crowd-Sourcing Platform","authors":"Mikhail Lysyakov, Siva Viswanathan","doi":"10.1287/isre.2022.1184","DOIUrl":"https://doi.org/10.1287/isre.2022.1184","url":null,"abstract":"As artificial intelligence (AI) solutions are being rapidly deployed, they increasingly compete with human labor. This study examines designers’ strategies in response to the threat from the introduction of an AI system for simple logo designs in a crowdsourcing design platform. We find that, although designers with lower abilities are more likely to exit the platform, designers with higher abilities move away from the locus of threat in the lower-tier contests and switch to more-complex design contests after the introduction of the AI system. More interestingly, we find that, although unsuccessful designers respond to the threat from AI by increasing their participation across multiple contests, successful designers become more focused (i.e., they substantially increase the number of submissions within a contest) and more quality oriented (i.e., they increase emotional content and complexity of their designs) after the AI launch. Our findings show how designers can learn from the behaviors of the more successful designers to differentiate themselves from AI systems by leveraging the more-abstract design attributes. Platform operators would benefit from adopting better segmentations strategies: with AI solutions for simple design tasks, hybrid AI + human solutions for less-complex design tasks, and skilled human designers competing primarily for the more-complex design tasks.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135636430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blockbuster projects on crowdfunding platforms are those that have achieved outstanding and exceptional performance. Regarding the impact of blockbuster projects on crowdfunding platforms, there are two plausible yet opposing predictions: they may exhibit both a negative effect by monopolizing backer attention and resources and a positive effect by increasing the activeness of backer side. This tension could be further complicated, considering that blockbusters are inherently heterogeneous. Drawing on the cross-side network effects literature and integrating insights from the unique features of crowdfunding, we develop a theoretical framework highlighting the multidimensional view of blockbuster effects: blockbuster projects have an overall positive effect on the performance of concurrent projects (overall effect), and such positive effect is stronger for related blockbusters (local effect) and blockbusters emerging before the focal project (temporal effect). With data from a leading crowdfunding platform, the empirical analyses largely support our proposed framework. Using off-platform data and backer data, we unveil the mechanism driving the blockbuster effects: blockbusters increase the popularity of the platform, whereby backers participating in the blockbusters tend to develop positive impressions and heightened expectations, so that they are likely to participate in other concurrent projects. Our findings have important implications for project creators and platform operators.
{"title":"Winner Takes All? The Blockbuster Effect on Crowdfunding Platforms","authors":"Jingjing Liu, Lusi Yang, Zhiyi Wang, Jungpil Hahn","doi":"10.1287/isre.2022.1154","DOIUrl":"https://doi.org/10.1287/isre.2022.1154","url":null,"abstract":"Blockbuster projects on crowdfunding platforms are those that have achieved outstanding and exceptional performance. Regarding the impact of blockbuster projects on crowdfunding platforms, there are two plausible yet opposing predictions: they may exhibit both a negative effect by monopolizing backer attention and resources and a positive effect by increasing the activeness of backer side. This tension could be further complicated, considering that blockbusters are inherently heterogeneous. Drawing on the cross-side network effects literature and integrating insights from the unique features of crowdfunding, we develop a theoretical framework highlighting the multidimensional view of blockbuster effects: blockbuster projects have an overall positive effect on the performance of concurrent projects (overall effect), and such positive effect is stronger for related blockbusters (local effect) and blockbusters emerging before the focal project (temporal effect). With data from a leading crowdfunding platform, the empirical analyses largely support our proposed framework. Using off-platform data and backer data, we unveil the mechanism driving the blockbuster effects: blockbusters increase the popularity of the platform, whereby backers participating in the blockbusters tend to develop positive impressions and heightened expectations, so that they are likely to participate in other concurrent projects. Our findings have important implications for project creators and platform operators.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135894978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study examines whether and how an online service marketplace can leverage refund options endorsed by different parties (i.e., the platform or sellers) to address the “lemons” problem that is due to the intangibility, variability, and unreturnable nature of the services sought. We show that both platform refund insurance and a seller-guaranteed refund increase service demand, with platform refund insurance as the more effective option and hence having a more effective signaling mechanism, and that sellers with a better reputation or less popularity might benefit less from refund options. An investigation on further use of the more effective refund option, a “having platform refund insurance or being cast out” policy (i.e., retaining platform refund-insured sellers but expelling uninsured ones), reveals the effectiveness of this policy in filtering out low-quality sellers, shown as an improved quality of sellers on the platform due to new sellers’ replacing those who were expelled, yet a cost (i.e., a loss in demand and consumer welfare) for the platform due to the changes in characteristics (e.g., price) of sellers. This cost, however, is lower than the benefit from the improved quality of the sellers, so that the platform’s overall performance improves.
{"title":"Platform Refund Insurance or Being Cast Out: Quantifying the Signaling Effect of Refund Options in the Online Service Marketplace","authors":"Jinyang Zheng, Youwei Wang, Yong Tan","doi":"10.1287/isre.2022.1162","DOIUrl":"https://doi.org/10.1287/isre.2022.1162","url":null,"abstract":"This study examines whether and how an online service marketplace can leverage refund options endorsed by different parties (i.e., the platform or sellers) to address the “lemons” problem that is due to the intangibility, variability, and unreturnable nature of the services sought. We show that both platform refund insurance and a seller-guaranteed refund increase service demand, with platform refund insurance as the more effective option and hence having a more effective signaling mechanism, and that sellers with a better reputation or less popularity might benefit less from refund options. An investigation on further use of the more effective refund option, a “having platform refund insurance or being cast out” policy (i.e., retaining platform refund-insured sellers but expelling uninsured ones), reveals the effectiveness of this policy in filtering out low-quality sellers, shown as an improved quality of sellers on the platform due to new sellers’ replacing those who were expelled, yet a cost (i.e., a loss in demand and consumer welfare) for the platform due to the changes in characteristics (e.g., price) of sellers. This cost, however, is lower than the benefit from the improved quality of the sellers, so that the platform’s overall performance improves.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135686634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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