Privacy Regulation and Its Unintended Consequence on Consumption Behaviors: Evidence From CCPA

2023 | International Conference on Information Systems | Citations: 0

Authors: Bae, Donghwa; Mayya, Raveesh; Nian, Tingting

Abstract: This study explores the unintended consequences of data protection regulations ... Expand

Abstract: This study explores the unintended consequences of data protection regulations on consumer behavior. Specifically, we examine the California Consumer Privacy Act, which restricts companies from collecting Californians' personal information. Privacy regulations may limit firms' ability to suggest products aligned with consumers' taste predicted from data, potentially influencing subsequent consumer behavior. These regulations especially pose a challenge to digital platforms, as their success hinges on seamless data flow between firms and consumers. Using a difference-in-differences approach with transaction data, we find that post-CCPA, Californians reduce purchase by 4.1%, increase returns by 2.9%. Moreover, we find that Californians spend more time online and visit more webpages, potentially indicating increased search efforts. Mechanism analysis suggests that firms under CCPA proactively alter their data collection strategy to reduce the liability. These results reveal the complex interplay between privacy regulation and consumer behavior, highlighting the need for a nuanced understanding of the trade-offs between privacy protection and economic outcomes. Collapse

Topics: information privacy law legal context consumer behavior advertising management website

Methods: experimental group longitudinal research natural experiment archival research difference in differences

Optimizing Substance Use Treatment Selection Using Reinforcement Learning

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Baucum, Matt; Khojandi, Anahita; Myers, Carole; Kessler, Larry

Abstract: Substance use disorder (SUD) exacts a substantial economic and social cost in th ... Expand

Abstract: Substance use disorder (SUD) exacts a substantial economic and social cost in the United States, and it is crucial for SUD treatment providers to match patients with feasible, effective, and affordable treatment plans. The availability of large SUD patient datasets allows for machine learning techniques to predict patient-level SUD outcomes, yet there has been almost no research on whether machine learning can be used to optimize or personalize which treatment plans SUD patients receive. We use contextual bandits (a reinforcement learning technique) to optimally map patients to SUD treatment plans, based on dozens of patient-level and geographic covariates. We also use near-optimal policies to incorporate treatments’ time-intensiveness and cost into our recommendations, to aid treatment providers and policymakers in allocating treatment resources. Our personalized treatment recommendation policies are estimated to yield higher remission rates than observed in our original dataset, and they suggest clinical insights to inform future research on data-driven SUD treatment matching. Collapse

Topics: electronic health record individual characteristic healthcare data missing data

Methods: hazard function machine learning random forest classification descriptive statistic propensity score method

Attention to Digital Innovation: Exploring the Impact of a Chief Information Officer in the Top Management Team

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Bendig, David; Wagner, Robin; Piening, Erk; Foege, Johann

Abstract: We draw on the attention-based view of the firm to examine whether and when the ... Expand

Abstract: We draw on the attention-based view of the firm to examine whether and when the presence of a CIO in the TMT has a positive effect on both firms' ideated digital innovation (IDI) (i.e., the intensity of firms' digital patenting activity) and commercialized digital innovation (CDI) (i.e., the digital sophistication of firms' new products). Building on the idea that attention processes are context dependent, we also explore the moderating roles of CEO characteristics (IT background and role tenure) as well as environmental characteristics (the industry's IT attention). We analyze data from a cross-industry panel of U.S. S&P 500 firms over eight years that includes up to 2,852 firm-year observations. The results indicate that CIO presence in the TMT is positively related to a firm's IDI and CDI. Furthermore, they show that the organizational context related to CEO characteristics moderates the CIO-CDI relationship and that the environmental context related to the industry's IT attention moderates the CIO-IDI relationship. Our research contributes to the information systems literature by providing robust evidence that CIO presence in the TMT positively influences a firm's digital innovation outcomes, showing how internal and external boundary conditions affect the work of CIOs, and elaborating the role of managerial attention as an underlying mechanism explaining digital innovation. Collapse

Topics: Chief Information Officer innovation management digital innovation research and development IT investment

Methods: regression analysis method theory development instrumental variables estimation Compustat descriptive statistic

Save Our Souls: Study of Twitter Use during India’s COVID-19 Pandemic

2023 | International Conference on Information Systems | Citations: 0

Authors: Bhattacharyya, Samadrita; Mojumder, Probal

Abstract: Twitter is a commonly used social platform for communication during disasters. ... Expand

Abstract: Twitter is a commonly used social platform for communication during disasters. Tweets by citizens during disasters to share information, seek, and offer help create a body of spontaneous, decentralized, emergent social media communication. Users' exploit Twitter's reach-enabling technological functionalities (hashtags (#), mentions (@), and 'reply-to') to draw attention to the messages. Set in context of the second wave of COVID-19 in India, that saw a surge in citizen-driven tweets seeking healthcare resources from fellow citizens and officials (i.e., SOS tweets), our paper empirically analyses the effects of Twitter's reach-enabling functionalities on online responses (i.e., retweets and replies) to these SOS tweets. We investigate the effects of inclusion of hashtags, mentions, and 'reply to' SOS tweets. We also examine the moderating effect of how the effects of the reach-enabling functionalities change as the social platform gets crowded with SOS tweets. The study offers various academic and practical implications. Collapse

Topics: Twitter pandemic social media Python societal evaluation criteria

Methods: propensity score method machine learning propensity score matching econometric modeling robustness check

Let Artificial Intelligence Be Your Shelf Watchdog: The Impact of Intelligent Image Processing-Powered Shelf Monitoring on Product Sales

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Deng, Yipu; Zheng, Jinyang; Huang, Liqiang; Kannan, Karthik

Abstract: We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer t ... Expand

Abstract: We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer to investigate how intelligent image processing (IIP)-based shelf monitoring aids manufacturers' shelf management by using data from a quasi-experiment and a field experiment. We discovered that such artificial intelligence (AI) assistance significantly and consistently improves product sales. Several underlying mechanisms were revealed by our quantitative and qualitative analysis. First, retailers are more likely to comply due to the greater monitoring effectiveness enabled by AI assistance. Second, the positive effect of IIP-based shelf monitoring partially persists after it is terminated, implying that human learning takes place. Third, the value of IIP-based shelf monitoring can be attributed to independent retailers rather than chain retailers. Since the degree of contract heterogeneity is the major difference between these retailers in terms of monitoring, this finding further suggests that AI is relatively more scalable when coping with more heterogeneous instances. Apart from these great benefits, we demonstrate the low marginal costs of implementing IIP-powered shelf monitoring, which indicates its long-term applicability and potential to generate incremental value. Our research contributes to several literature streams and provides managerial insights for practitioners who consider AI-assisted operational models. Collapse

Topics: artificial intelligence organizational value cost benefit analysis mobile application human AI collaboration

Methods: experimental group field experiment qualitative interview experiment quasi experiment

When Reward Meets Donation: A Paradoxical Dilemma

2023 | International Conference on Information Systems | Citations: 0

Authors: Deng, Yipu; Zheng, Jinyang; Li, Guoxin; Kannan, Karthik

Abstract: Reward-based crowdfunding platforms are increasingly incorporating donation opt ... Expand

Abstract: Reward-based crowdfunding platforms are increasingly incorporating donation options, allowing backers to financially support campaigns without receiving any tangible rewards in return. Although this option seems to create a novel fundraising channel, our quasi-natural experimental study highlights the potential negative impacts of individual donation occurrences, which ultimately lead to reduced total raised funds, as substantiated by robust empirical evidence. We explore two primary mechanisms responsible for the adverse effect. First, the bystander effect, where prior donations discourage potential backers from supporting the campaign, causing them to either forgo reward purchases or decrease their contribution amounts. Second, the social conformity effect, in which prior donations shape backers' perceptions of social norms and consequently lower their support levels. By offering a comprehensive understanding of behavioral dynamics in crowdfunding, our study enriches the literature on the design and management of crowdfunding platforms and provides valuable insights for industry practitioners. Collapse

Topics: crowdfunding crowdsourcing social norm logistics management willingness to pay

Methods: experimental group propensity score method descriptive statistic quasi experiment experiment

Theories: social influence theory

Economic Impacts of Platform-Endorsed Quality Certification: Evidence from Airbnb

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Dewan, Sanjeev; Kim, Jooho; Nian, Tingting

Abstract: We contribute to the emerging literature on quality certification by digital pl ... Expand

Abstract: We contribute to the emerging literature on quality certification by digital platforms by studying the launch of the Airbnb Plus service, wherein the platform inspects properties and provides a badge that presumably signals the quality of the property and the reliability of the host. Our identification strategy relies on the fact that the Airbnb Plus service was launched in different cities at different times, and listings within the cities received the certification at different times. Using a staggered difference-in-differences estimation strategy in conjunction with suitable matching methods, we found that the Airbnb Plus certification increased the weekly booking rate of Plus listings by about 6.8% on average (direct effect). We also found some evidence that non-Plus listings saw a temporary decline in booking rate when one or more nearby properties received a Plus certification (externality effect). The net impact of the Airbnb Plus service on the platform itself was an annual increase in revenue of about $37,500 for the average 2-kilometer zone in a U.S. city that included one or more Plus listings, as compared to matched zones without any Plus listings (local platform effect). We performed additional analyses, including a randomized experiment, to demonstrate the robustness of our findings. Overall, our results suggest that platform-endorsed quality certification has significant economic impacts-not just on the listings that receive the certification but on other listings on the platform as well as on the platform itself. Collapse

Topics: Airbnb website sharing platform peer-to-peer model Google+

Methods: experimental group experiment propensity score method product review robustness check

“Maybe You Should Talk to Someone”: The Role of Online Communities on Mental Healthcare

2023 | International Conference on Information Systems | Citations: 0

Authors: Ghosh, Soham; Chakraborty, Soumyakanti; Sharma, Megha; Susarla, Anjana

Abstract: Online Health Communities like YouTube offer mental health patients an alternat ... Expand

Abstract: Online Health Communities like YouTube offer mental health patients an alternative channel to learn about mental illnesses, the treatment path to follow, and to share their experiences. For many patients who are reluctant to seek professional help, a video on mental health uploaded by a content creator may serve as a substitute for a counsellor. Our work aims to develop an understanding of the relationship between language formality and social support and provide normative guidelines for content creators on social media platforms. Using two transformer-based deep learning classification models, we determine the degree of language formality or informality present in the content, and three dimensions of social support in the comments. We then utilize propensity score estimation to establish the causal effect of (in)formality on the dimensions of social support for 994 videos and 3,10,157 comments. Our findings indicate that informal speech increases emotional support, leading to better health outcomes. Collapse

Topics: YouTube social media electronic mail blog

Methods: deep learning RoBERTa BERT propensity score matching propensity score method

Theories: speech act theory

Software-Vendor Diversification: A Source of Organizational Rigidity in Adversity?

2023 | Journal of Management Information Systems | Citations: 0

Authors: Gong, Jing; Liang, Yi; Ramasubbu, Narayan

Abstract: Firms often assemble digital infrastructures using continuously evolving softwar ... Expand

Abstract: Firms often assemble digital infrastructures using continuously evolving software applications sourced from a multitude of vendors. Using the theoretical lens of the threat-rigidity thesis, we raise the possibility that during adverse environmental conditions, software-vendor diversification can be a source of organizational rigidity that may dampen firm performance. Empirical analysis using data on 918 large public U.S. firms operating during two severe environmental shocks, the global financial crisis and the burst of the dot-com bubble, lends strong support to our thesis. Results indicate that a variety of firm performance indicators (e.g., stock return and operating income measures) are negatively associated with software-vendor diversification during crisis periods. Mediation analysis highlights the role of IT-related material weakness in firms' internal controls in transmitting threat-rigidity effects that decrease performance. These results underscore the importance of software portfolio optimization for countering the dysfunctional effects of software-vendor diversification during adverse environmental shocks. Collapse

Topics: organizational productivity accounting computer hardware information technology infrastructure database system

Methods: mediation analysis structural equation modeling cross sectional research propensity score method longitudinal research

When Images Backfire: The Effect of Customer-Generated Images on Product Rating Dynamics

2023 | Information Systems Research | Citations: 0

Authors: Guan, Yue; Tan, Yong; Wei, Qiang; Chen, Guoqing

Abstract: Customer-generated images (CGIs) on e-commerce platforms have been widely adopte ... Expand

Abstract: Customer-generated images (CGIs) on e-commerce platforms have been widely adopted as a promotional tool to persuade customers into purchases. Despite their prevalent applications, the effect of CGIs on customer postpurchase satisfaction has not been extensively examined. This study postulates that CGIs could cause expectation disconfirmation and reduce product uncertainty for customers, therefore making their effect on subsequent product ratings complex. We leverage multiple methods and data sets to gain a better understanding of this problem and underlying mechanisms. We employ a difference-in-differences model to empirically test our hypotheses and find that CGIs lead to a decline in subsequent ratings compared with product ratings not exposed to CGIs. Further heterogeneity analyses demonstrate that high CGI review rating and high aesthetic quality exacerbate the negative effect, whereas reviewer face disclosure could alleviate the negative effect. Through cross-product analyses, we find that the negative effect is more prominent for experience goods (e.g., women’s dresses) than for search goods (e.g., lightning cables). Finally, the underlying mechanism is further validated through a laboratory experiment that shows participants experience significantly higher expectation and more negative disconfirmation in the CGI group with high review ratings, whereas uncertainty reduction effect is insignificant, which collectively explains the decline of subsequent product ratings. These findings suggest that platforms and retailers should be aware of the potential negative effect of CGIs on the rating dynamics and take appropriate measures to circumvent it. History: Ravi Bapna, Senior Editor; Gordon Burtch, Associate Editor. Funding: This work was supported in part by National Science Foundation of China [Grants 72202220, 72172070, and 71729001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1201. Collapse

Topics: online review experience good electronic commerce data breach digital good

Methods: experiment experimental group laboratory experiment computational algorithm product review