Pub Date : 2023-12-01DOI: 10.25300/misq/2022/17037
Jürgen Neumann, Dominik Gutt, Dennis Kundisch
Drawing on construal level theory, prior literature has found a positivity bias in online ratings when consumers evaluate an experience from a psychological distance, whether spatial or temporal. Self-distancing theory posits that psychological distance enables individuals to reflect on psychologically distant negative experiences more genuinely, in a less biased way. This raises the question of whether the positivity bias in ratings due to psychological distance persists for negative experiences. To address this question, we collected data from a large review platform that enables the identification of reviewers’ spatial and temporal distance. The negativity of an experience was operationalized via review text sentiment. We introduced spatial and temporal distance as moderators between sentiment negativity and ratings and found a negative moderation by spatial distance and a positive moderation by temporal distance. Our findings indicate that the relationship between sentiment negativity and rating grows stronger under spatial distance and gets weaker under temporal distance. Text mining confirmed self-distancing as the driver behind the spatial moderation and construal levels as the driver behind the temporal moderation. We attribute the asymmetric moderations to differences in the tangibility of spatial distance (more tangible) and temporal distance (less tangible). These results improve our understanding of reviewing behavior and can help platforms de-bias ratings.
{"title":"Reviewing from a Distance: Uncovering Asymmetric Moderations of Spatial and Temporal Distance between Sentiment Negativity and Rating","authors":"Jürgen Neumann, Dominik Gutt, Dennis Kundisch","doi":"10.25300/misq/2022/17037","DOIUrl":"https://doi.org/10.25300/misq/2022/17037","url":null,"abstract":"<style>#html-body [data-pb-style=RMLPEB9]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>Drawing on construal level theory, prior literature has found a positivity bias in online ratings when consumers evaluate an experience from a psychological distance, whether spatial or temporal. Self-distancing theory posits that psychological distance enables individuals to reflect on psychologically distant negative experiences more genuinely, in a less biased way. This raises the question of whether the positivity bias in ratings due to psychological distance persists for negative experiences. To address this question, we collected data from a large review platform that enables the identification of reviewers’ spatial and temporal distance. The negativity of an experience was operationalized via review text sentiment. We introduced spatial and temporal distance as moderators between sentiment negativity and ratings and found a negative moderation by spatial distance and a positive moderation by temporal distance. Our findings indicate that the relationship between sentiment negativity and rating grows stronger under spatial distance and gets weaker under temporal distance. Text mining confirmed self-distancing as the driver behind the spatial moderation and construal levels as the driver behind the temporal moderation. We attribute the asymmetric moderations to differences in the tangibility of spatial distance (more tangible) and temporal distance (less tangible). These results improve our understanding of reviewing behavior and can help platforms de-bias ratings.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 13","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2022/17556
May Truong, Alok Gupta, Wolfgang Ketter, Eric van Heck
Although multichannel sales strategies have become common due to the use of advanced information technologies, how one trading mechanism can influence the outcome of another, especially in the B2B market, remains largely underexplored. This paper investigates the effect of price and quantity information from an online posted-price presales channel on the performance of the century-old sequential Dutch auction system. Sellers can control the price paid and make a proportion of their stock available in auction presales. Anything left after presales is sold via auctions. Our analysis of nearly 1.5 million flower lots reveals a positive effect with higher auction prices and total revenue for lots listed in presales than for lots that are not. The result holds even for lots with no actual sales in the presales, indicating that buyers pay close attention to the additional information from the posted-price presales channel. By teasing out the information effect of presales prices and presales quantity on auction prices, we evaluate a number of pricing strategies. The results suggest that selling at a high price in presales is still more beneficial than selling more by discounting prices.
{"title":"The Effect of Posted Prices on Auction Prices: An Empirical Investigation of a Multichannel B2B Market","authors":"May Truong, Alok Gupta, Wolfgang Ketter, Eric van Heck","doi":"10.25300/misq/2022/17556","DOIUrl":"https://doi.org/10.25300/misq/2022/17556","url":null,"abstract":"<style>#html-body [data-pb-style=LKQQ207]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>Although multichannel sales strategies have become common due to the use of advanced information technologies, how one trading mechanism can influence the outcome of another, especially in the B2B market, remains largely underexplored. This paper investigates the effect of price and quantity information from an online posted-price presales channel on the performance of the century-old sequential Dutch auction system. Sellers can control the price paid and make a proportion of their stock available in auction presales. Anything left after presales is sold via auctions. Our analysis of nearly 1.5 million flower lots reveals a positive effect with higher auction prices and total revenue for lots listed in presales than for lots that are not. The result holds even for lots with no actual sales in the presales, indicating that buyers pay close attention to the additional information from the posted-price presales channel. By teasing out the information effect of presales prices and presales quantity on auction prices, we evaluate a number of pricing strategies. The results suggest that selling at a high price in presales is still more beneficial than selling more by discounting prices.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":" 731","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138475762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2023/17152
David Bendig, Robin Wagner, Erk P. Piening, Johann Nils Foege
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.
{"title":"Attention to Digital Innovation: Exploring the Impact of a Chief Information Officer in the Top Management Team","authors":"David Bendig, Robin Wagner, Erk P. Piening, Johann Nils Foege","doi":"10.25300/misq/2023/17152","DOIUrl":"https://doi.org/10.25300/misq/2023/17152","url":null,"abstract":"<style>#html-body [data-pb-style=TSCEF4Q]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>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.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"115 13","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2023/17085
Christiane Lehrer, Ioanna Constantiou. Christian Matt, Thomas Hess
User engagement, a key factor in the success of social media platforms, has long been based on permanent content. A recent paradigm shift in platform design has led large social media providers to implement ephemerality features that by default make shared content disappear after a certain amount of time. However, very little is known about how ephemerality features affect user engagement and behavior in social media. Drawing upon the technology affordance perspective, we conducted a qualitative multimethod study involving individual interviews and focus groups. Our findings show that the affordances arising from features with varying degrees of ephemerality (i.e., snaps and stories) differ from those of permanent content features in terms of self-presentation, browsing others’ content, and communication. Adopting a multidimensional conceptualization of user engagement, we show the positive (e.g., more content sharing) and negative (e.g., cognitive burden from context loss) effects for snaps and stories that should be cautiously considered by social media platforms aiming to introduce such features. Finally, we reveal new user behaviors that relate to sharing snapshots of fleeting value as snaps or experiences of transient value as stories.
{"title":"How Ephemerality Features Affect User Engagement with Social Media Platforms","authors":"Christiane Lehrer, Ioanna Constantiou. Christian Matt, Thomas Hess","doi":"10.25300/misq/2023/17085","DOIUrl":"https://doi.org/10.25300/misq/2023/17085","url":null,"abstract":"<style>#html-body [data-pb-style=ISK3K72]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>User engagement, a key factor in the success of social media platforms, has long been based on permanent content. A recent paradigm shift in platform design has led large social media providers to implement ephemerality features that by default make shared content disappear after a certain amount of time. However, very little is known about how ephemerality features affect user engagement and behavior in social media. Drawing upon the technology affordance perspective, we conducted a qualitative multimethod study involving individual interviews and focus groups. Our findings show that the affordances arising from features with varying degrees of ephemerality (i.e., snaps and stories) differ from those of permanent content features in terms of self-presentation, browsing others’ content, and communication. Adopting a multidimensional conceptualization of user engagement, we show the positive (e.g., more content sharing) and negative (e.g., cognitive burden from context loss) effects for snaps and stories that should be cautiously considered by social media platforms aiming to introduce such features. Finally, we reveal new user behaviors that relate to sharing snapshots of fleeting value as snaps or experiences of transient value as stories.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":" 733","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138475760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2023/16216
Lianlian (Dorothy) Jiang, T. Ravichandran, Jason Kuruzovich
This paper empirically investigates how review moderation transparency affects the volume, length, and negativity of reviews. A change to the Yelp platform in 2010, introducing review moderation and displaying filtered reviews, created a natural experiment. We used a panel dataset of online reviews from the same set of restaurants on both the Yelp and TripAdvisor platforms in a difference-in-differences (DID) model to test how review moderation transparency affected our outcome variables. We found that increasing review moderation transparency negatively affects review volume but positively affects review negativity. The results also indicate that providing review moderation transparency reduces review length, especially for reviews with positive sentiment. Our findings suggest that providing review moderation transparency induces users to invest less effort in review contributions, especially when they are submitting positive reviews. We discuss the theoretical and practical implications of these results as they relate to the design and use of online review platforms.
{"title":"Review Moderation Transparency and Online Reviews: Evidence from a Natural Experiment","authors":"Lianlian (Dorothy) Jiang, T. Ravichandran, Jason Kuruzovich","doi":"10.25300/misq/2023/16216","DOIUrl":"https://doi.org/10.25300/misq/2023/16216","url":null,"abstract":"<style>#html-body [data-pb-style=J7RWQHP]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>This paper empirically investigates how review moderation transparency affects the volume, length, and negativity of reviews. A change to the Yelp platform in 2010, introducing review moderation and displaying filtered reviews, created a natural experiment. We used a panel dataset of online reviews from the same set of restaurants on both the Yelp and TripAdvisor platforms in a difference-in-differences (DID) model to test how review moderation transparency affected our outcome variables. We found that increasing review moderation transparency negatively affects review volume but positively affects review negativity. The results also indicate that providing review moderation transparency reduces review length, especially for reviews with positive sentiment. Our findings suggest that providing review moderation transparency induces users to invest less effort in review contributions, especially when they are submitting positive reviews. We discuss the theoretical and practical implications of these results as they relate to the design and use of online review platforms.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 12","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2022/16422
Chao Ding, Wael Jabr, Hong Guo
Social media—and, in particular, social media influencers—are playing an increasingly central role in shaping public opinion on a variety of issues. The political sphere is no exception. In response to the impact that social media influencers have on citizens’ political views and voting behaviors, political parties adapt their messages and policies during election campaigns. Media outlets, too, faced with competition for readership from social media, are adjusting their news coverage. To analyze the nature and extent of the impact of social media on parties’ policies, media outlets’ news reports, and citizens’ opinions, we used a game theoretical model of electoral competition involving four key stakeholders—citizens, political parties, media outlets, and social media influencers. Our results show that with social media, parties’ policy positions become more moderate while media outlets’ editorial positions become more extreme. We also show that citizens’ opinions may become more polarized when the influencers’ true editorial positions are more homogeneous as a result of increased information distortion.
{"title":"Electoral Competition in the Age of Social Media: The Role of Social Media Influencers","authors":"Chao Ding, Wael Jabr, Hong Guo","doi":"10.25300/misq/2022/16422","DOIUrl":"https://doi.org/10.25300/misq/2022/16422","url":null,"abstract":"<style>#html-body [data-pb-style=VOLJORF]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>Social media—and, in particular, social media influencers—are playing an increasingly central role in shaping public opinion on a variety of issues. The political sphere is no exception. In response to the impact that social media influencers have on citizens’ political views and voting behaviors, political parties adapt their messages and policies during election campaigns. Media outlets, too, faced with competition for readership from social media, are adjusting their news coverage. To analyze the nature and extent of the impact of social media on parties’ policies, media outlets’ news reports, and citizens’ opinions, we used a game theoretical model of electoral competition involving four key stakeholders—citizens, political parties, media outlets, and social media influencers. Our results show that with social media, parties’ policy positions become more moderate while media outlets’ editorial positions become more extreme. We also show that citizens’ opinions may become more polarized when the influencers’ true editorial positions are more homogeneous as a result of increased information distortion.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 10","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2022/16764
Kui Du and Hüseyin Tanriverdi
In the U.S., multihospital systems (MHSs) charge significantly higher prices for hospital services than stand-alone hospitals. Rivalry restraint theory suggests that MHS with multimarket contact (MMC) can tacitly collude and mutually forebear from price competition to keep their prices above competitive levels. We posit that the success of such MMC-induced rivalry restraints (the truce) is affected by two conflicting roles of IT at the corporate level and market unit levels, respectively. The corporate parent seeks to standardize IT applications enterprise-wide to coordinate market units as a means of jointly implementing the rivalry restraint strategy and keeping prices high enterprise-wide. However, market units, i.e., the member hospitals of MHS clustered in geographic patient markets, face competitive pressures to reduce their service costs. Market units seek to use differentiated IT applications to achieve cost reductions, which then fuel price competition in local markets, jeopardize the sustainability of the truce, and weaken the enterprise-wide price effects of the corporate parent’s rivalry restraint strategy. In a longitudinal study of 195 multihospital systems in the U.S. in the 2005-2013 time period, we found support for these ideas. The corporate-wide standardization of the operational IT of MHS complements the rivalry restraint strategy to increase enterprise-wide prices. Market units’ use of differentiated analytical IT reduces costs in local markets and weakens the price effects of the rivalry restraint strategy. The study advances IS research and practice by theorizing how the corporate-level and the market unit-level IT of a multi-unit, multimarket (MUMM) organization can have opposing moderating effects on the link between MMC and the average prices charged by the MUMM organization.
{"title":"Does IT Enable Collusion or Competition: Examining the Effects of IT on Service Pricing in Multimarket Multihospital Systems","authors":"Kui Du and Hüseyin Tanriverdi","doi":"10.25300/misq/2022/16764","DOIUrl":"https://doi.org/10.25300/misq/2022/16764","url":null,"abstract":"<style>#html-body [data-pb-style=SJ85VTL]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>In the U.S., multihospital systems (MHSs) charge significantly higher prices for hospital services than stand-alone hospitals. Rivalry restraint theory suggests that MHS with multimarket contact (MMC) can tacitly collude and mutually forebear from price competition to keep their prices above competitive levels. We posit that the success of such MMC-induced rivalry restraints (the truce) is affected by two conflicting roles of IT at the corporate level and market unit levels, respectively. The corporate parent seeks to standardize IT applications enterprise-wide to coordinate market units as a means of jointly implementing the rivalry restraint strategy and keeping prices high enterprise-wide. However, market units, i.e., the member hospitals of MHS clustered in geographic patient markets, face competitive pressures to reduce their service costs. Market units seek to use differentiated IT applications to achieve cost reductions, which then fuel price competition in local markets, jeopardize the sustainability of the truce, and weaken the enterprise-wide price effects of the corporate parent’s rivalry restraint strategy. In a longitudinal study of 195 multihospital systems in the U.S. in the 2005-2013 time period, we found support for these ideas. The corporate-wide standardization of the operational IT of MHS complements the rivalry restraint strategy to increase enterprise-wide prices. Market units’ use of differentiated analytical IT reduces costs in local markets and weakens the price effects of the rivalry restraint strategy. The study advances IS research and practice by theorizing how the corporate-level and the market unit-level IT of a multi-unit, multimarket (MUMM) organization can have opposing moderating effects on the link between MMC and the average prices charged by the MUMM organization.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 9","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2022/16773
Benjamin M. Abdel-Karim, Nicolas Pfeuffer, K. Valerie Carl, Oliver Hinz
This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of ML-based decision support systems and also enriches theories on human-AI augmentation.
{"title":"How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work","authors":"Benjamin M. Abdel-Karim, Nicolas Pfeuffer, K. Valerie Carl, Oliver Hinz","doi":"10.25300/misq/2022/16773","DOIUrl":"https://doi.org/10.25300/misq/2022/16773","url":null,"abstract":"<style>#html-body [data-pb-style=S2AMIW1]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of ML-based decision support systems and also enriches theories on human-AI augmentation.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 7","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2023/17688
Anol Bhattacherjee
Prior research has suggested that corrective fact-checking has inconsistent effects on beliefs about online misinformation claims. This study attempts to explain this inconsistency using three contingent factors—claim-source credibility, fact-checker credibility, and attitude strength—which respectively relate to three key parties in the fact-checking process: the source of a misleading claim, the fact-checker, and the user evaluating the fact-check. I hypothesize the interplay between these factors, which is tested using two online experiments on COVID-19-related misinformation with over 900 participants. Multilevel analysis of pretest-posttest, repeated measures data supports the hypothesized moderating effects and offers additional insights about how these effects vary between earlier versus later phases of misinformation cycles. The paper concludes with a discussion of contributions to research and practice.
{"title":"Can Fact-Checking Influence User Beliefs About Misinformation Claims: An Examination of Contingent Effects","authors":"Anol Bhattacherjee","doi":"10.25300/misq/2023/17688","DOIUrl":"https://doi.org/10.25300/misq/2023/17688","url":null,"abstract":"<style>#html-body [data-pb-style=KQ1TQXM]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>Prior research has suggested that corrective fact-checking has inconsistent effects on beliefs about online misinformation claims. This study attempts to explain this inconsistency using three contingent factors—claim-source credibility, fact-checker credibility, and attitude strength—which respectively relate to three key parties in the fact-checking process: the source of a misleading claim, the fact-checker, and the user evaluating the fact-check. I hypothesize the interplay between these factors, which is tested using two online experiments on COVID-19-related misinformation with over 900 participants. Multilevel analysis of pretest-posttest, repeated measures data supports the hypothesized moderating effects and offers additional insights about how these effects vary between earlier versus later phases of misinformation cycles. The paper concludes with a discussion of contributions to research and practice.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 11","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.25300/misq/2022/17491
Zhao Wang, Cuiqing Jiang, Huimin Zhao
With the rapid development of fintech, the need for dynamic credit risk evaluation is becoming increasingly important. While previous studies on credit scoring have mostly focused on single-period loan default prediction, we call for a new avenue—multiperiod default prediction (MPDP)—to depict risk profiles over time. To address the challenges raised by MPDP, such as monotonic default probability prediction and complex relationship accommodation, we propose a novel approach, hybrid and collective scoring (HACS). We design a hybrid modeling strategy to predict whether and when a borrower will default separately through a default discrimination model and a default time estimation model, respectively, and synthesize them through a probabilistic framework. To accommodate various possible patterns of default time and measure the distribution of default probability over successive time intervals, we propose a joint default modeling method to train the default time estimation model. Empirical evaluations at the model (time-to-default prediction performance and discrimination performance) and mechanism (identifiability and discriminability) levels, as well as impact analyses at the application (granting performance and profitability performance) level, show that HACS outperforms the benchmarked survival analysis and multilabel learning methods on all fronts. It can more accurately predict time-to-default and provide financial institutions and investors better decision-support in granting loans and selecting loan portfolios.
{"title":"Depicting Risk Profile over Time: A Novel Multiperiod Loan Default Prediction Approach","authors":"Zhao Wang, Cuiqing Jiang, Huimin Zhao","doi":"10.25300/misq/2022/17491","DOIUrl":"https://doi.org/10.25300/misq/2022/17491","url":null,"abstract":"<style>#html-body [data-pb-style=GHFD705]{justify-content:flex-start;display:flex;flex-direction:column;background-position:left top;background-size:cover;background-repeat:no-repeat;background-attachment:scroll}</style>With the rapid development of fintech, the need for dynamic credit risk evaluation is becoming increasingly important. While previous studies on credit scoring have mostly focused on single-period loan default prediction, we call for a new avenue—multiperiod default prediction (MPDP)—to depict risk profiles over time. To address the challenges raised by MPDP, such as monotonic default probability prediction and complex relationship accommodation, we propose a novel approach, hybrid and collective scoring (HACS). We design a hybrid modeling strategy to predict whether and when a borrower will default separately through a default discrimination model and a default time estimation model, respectively, and synthesize them through a probabilistic framework. To accommodate various possible patterns of default time and measure the distribution of default probability over successive time intervals, we propose a joint default modeling method to train the default time estimation model. Empirical evaluations at the model (time-to-default prediction performance and discrimination performance) and mechanism (identifiability and discriminability) levels, as well as impact analyses at the application (granting performance and profitability performance) level, show that HACS outperforms the benchmarked survival analysis and multilabel learning methods on all fronts. It can more accurately predict time-to-default and provide financial institutions and investors better decision-support in granting loans and selecting loan portfolios.","PeriodicalId":49807,"journal":{"name":"Mis Quarterly","volume":"116 8","pages":""},"PeriodicalIF":7.3,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138455778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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