Pub Date : 2023-12-11DOI: 10.1080/07421222.2023.2267317
Elena Revilla, Maria Jesus Saenz, Matthias Seifter, Ye Ma
This study investigates the role of human intervention in artificial intelligence/machine learning (AIML)-driven predictions. By doing so, we distinguish between three different types of human-AIML...
{"title":"Human–Artificial Intelligence Collaboration in Prediction: A Field Experiment in the Retail Industry","authors":"Elena Revilla, Maria Jesus Saenz, Matthias Seifter, Ye Ma","doi":"10.1080/07421222.2023.2267317","DOIUrl":"https://doi.org/10.1080/07421222.2023.2267317","url":null,"abstract":"This study investigates the role of human intervention in artificial intelligence/machine learning (AIML)-driven predictions. By doing so, we distinguish between three different types of human-AIML...","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"13 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138564974","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}
Human managers are increasingly challenged by artificial intelligence (AI) technologies in performing managerial functions. We undertook a field experiment that used AI vis-à-vis human managers to ...
{"title":"Perceived Fairness of Human Managers Compared with Artificial Intelligence in Employee Performance Evaluation","authors":"Shaojun (Marco) Qin, Nan Jia, Xueming Luo, Chengcheng Liao, Ziyao Huang","doi":"10.1080/07421222.2023.2267316","DOIUrl":"https://doi.org/10.1080/07421222.2023.2267316","url":null,"abstract":"Human managers are increasingly challenged by artificial intelligence (AI) technologies in performing managerial functions. We undertook a field experiment that used AI vis-à-vis human managers to ...","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"112 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138564940","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}
Social technologies on online review platforms enable social interactions among users, such as establishing following relationships and commenting on others’ posts. Although it is well recognized t...
{"title":"Impacts of Social Interactions and Peer Evaluations on Online Review Platforms","authors":"Yinan Yu, Warut Khern-am-nuai, Alain Pinsonneault, Zaiyan Wei","doi":"10.1080/07421222.2023.2267323","DOIUrl":"https://doi.org/10.1080/07421222.2023.2267323","url":null,"abstract":"Social technologies on online review platforms enable social interactions among users, such as establishing following relationships and commenting on others’ posts. Although it is well recognized t...","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"54 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138564918","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 : 2023-12-11DOI: 10.1080/07421222.2023.2267312
Vladimir Zwass
Published in Journal of Management Information Systems (Vol. 40, No. 4, 2023)
发表于《管理信息系统期刊》（第 40 卷第 4 期，2023 年）
{"title":"Editorial Introduction","authors":"Vladimir Zwass","doi":"10.1080/07421222.2023.2267312","DOIUrl":"https://doi.org/10.1080/07421222.2023.2267312","url":null,"abstract":"Published in Journal of Management Information Systems (Vol. 40, No. 4, 2023)","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"67 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138564928","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 : 2023-12-11DOI: 10.1080/07421222.2023.2267322
Mariia Petryk, Liangfei Qiu, Praveen Pathak
Although the prices of cryptocurrencies remained volatile for the past decade, the factors that impact the price dynamics of the new type of investment instrument have not been fully identified yet...
尽管加密货币的价格在过去十年中持续波动，但影响这种新型投资工具价格动态的因素尚未完全确定...
{"title":"Impact of Open-Source Community on Cryptocurrency Market Price: An Empirical Investigation","authors":"Mariia Petryk, Liangfei Qiu, Praveen Pathak","doi":"10.1080/07421222.2023.2267322","DOIUrl":"https://doi.org/10.1080/07421222.2023.2267322","url":null,"abstract":"Although the prices of cryptocurrencies remained volatile for the past decade, the factors that impact the price dynamics of the new type of investment instrument have not been fully identified yet...","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"112 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138564973","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 : 2023-10-02DOI: 10.1080/07421222.2023.2267318
Paul Benjamin Lowry, Gregory D. Moody, Srikanth Parameswaran, Nicholas James Brown
ABSTRACT Most of the information security management research involving fear appeals is guided by either protection motivation theory or the extended parallel processing model. Over time, extant research has extended these theories, as well as their derivative theories, in a variety of ways, leading to several theoretical and empirical inconsistencies. The large body of fragmented, and sometimes conflicting, research has muddied the broader understanding of what drives protection- and defensive motivation. We provide guidance to the security discourse by offering the first study in the literature to employ two-stage meta-analytic structural equation modeling (TSSEM), which combines covariance-based structural equation modeling and meta-analysis. Information systems (IS) researchers have traditionally used meta-analysis for structural equation modeling for such purposes—an approach that has several serious statistical flaws. Using 341 systematically selected empirical security articles (representing 383 unique studies) and TSSEM, we pool a large series of five datasets to test six models, from which we examine the effects of constructs and paths in the security fear-appeals literature. We compare and test six versions of models inspired by issues in the broader fear-appeals literature. We confirm the importance of both the threat- and coping-appraisal processes; establish the central role of fear and that it has greater importance than threat; show that efficacy is a stronger predictor of protection motivation than is threat; demonstrate that response costs as currently measured are ineffective but that maladaptive rewards have a strong negative effect on protection motivation and a positive effect on defensive motivation; and provide evidence that dual models of danger control and fear control should be used.
{"title":"Examining the Differential Effectiveness of Fear Appeals in Information Security Management Using Two-Stage Meta-Analysis","authors":"Paul Benjamin Lowry, Gregory D. Moody, Srikanth Parameswaran, Nicholas James Brown","doi":"10.1080/07421222.2023.2267318","DOIUrl":"https://doi.org/10.1080/07421222.2023.2267318","url":null,"abstract":"ABSTRACT Most of the information security management research involving fear appeals is guided by either protection motivation theory or the extended parallel processing model. Over time, extant research has extended these theories, as well as their derivative theories, in a variety of ways, leading to several theoretical and empirical inconsistencies. The large body of fragmented, and sometimes conflicting, research has muddied the broader understanding of what drives protection- and defensive motivation. We provide guidance to the security discourse by offering the first study in the literature to employ two-stage meta-analytic structural equation modeling (TSSEM), which combines covariance-based structural equation modeling and meta-analysis. Information systems (IS) researchers have traditionally used meta-analysis for structural equation modeling for such purposes—an approach that has several serious statistical flaws. Using 341 systematically selected empirical security articles (representing 383 unique studies) and TSSEM, we pool a large series of five datasets to test six models, from which we examine the effects of constructs and paths in the security fear-appeals literature. We compare and test six versions of models inspired by issues in the broader fear-appeals literature. We confirm the importance of both the threat- and coping-appraisal processes; establish the central role of fear and that it has greater importance than threat; show that efficacy is a stronger predictor of protection motivation than is threat; demonstrate that response costs as currently measured are ineffective but that maladaptive rewards have a strong negative effect on protection motivation and a positive effect on defensive motivation; and provide evidence that dual models of danger control and fear control should be used.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"25 1","pages":"1099 - 1138"},"PeriodicalIF":7.7,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138582883","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 : 2023-09-30DOI: 10.1080/07421222.2023.2258673
Published in Journal of Management Information Systems (Ahead of Print, 2023)
发表于Journal of Management Information Systems(提前印刷，2023)
{"title":"Correction","authors":"","doi":"10.1080/07421222.2023.2258673","DOIUrl":"https://doi.org/10.1080/07421222.2023.2258673","url":null,"abstract":"Published in Journal of Management Information Systems (Ahead of Print, 2023)","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"44 9","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49696094","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 : 2023-08-23DOI: 10.1080/07421222.2023.2229121
Robert J. Kauffman, Atanu Lahiri
Published in Journal of Management Information Systems (Vol. 40, No. 3, 2023)
发表于《管理信息系统学报》(Vol. 40, No. 3, 2023)
{"title":"Special Section: Digital Strategies for Business Readiness","authors":"Robert J. Kauffman, Atanu Lahiri","doi":"10.1080/07421222.2023.2229121","DOIUrl":"https://doi.org/10.1080/07421222.2023.2229121","url":null,"abstract":"Published in Journal of Management Information Systems (Vol. 40, No. 3, 2023)","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"40 12","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49695924","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 : 2023-08-23DOI: 10.1080/07421222.2023.2229116
Vladimir Zwass
Published in Journal of Management Information Systems (Vol. 40, No. 3, 2023)
发表于《管理信息系统学报》(Vol. 40, No. 3, 2023)
{"title":"Editorial Introduction","authors":"Vladimir Zwass","doi":"10.1080/07421222.2023.2229116","DOIUrl":"https://doi.org/10.1080/07421222.2023.2229116","url":null,"abstract":"Published in Journal of Management Information Systems (Vol. 40, No. 3, 2023)","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"41 1","pages":""},"PeriodicalIF":7.7,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49695923","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 : 2023-07-03DOI: 10.1080/07421222.2023.2229124
F. Delkhosh, R. Gopal, Raymond A. Patterson, Niam Yaraghi
ABSTRACT Incentivized blockchain-based online social media (BOSM), where creators and curators of popular content are paid in cryptocurrency, have recently emerged. Traditional social media ecosystems have experienced significant bot involvement in their platforms, which has often had a negative impact on both users and platforms. BOSM can provide additional direct financial incentives as motivation for both bots’ and human users’ engagement. Using the panel vector autoregression and regression discontinuity in time framework, we analyze two distinct data sets from Steemit, the largest and most popular BOSM, to study the impact of bot engagement on human users and the impact of changes in financial reward on user engagement. Interestingly, our findings demonstrate that while increased engagement by bots is positively associated with engagement by human users, the association between bot engagement and human user engagement decreases as the number of votes for a post increases. We also find that shifts in economic incentives significantly influence the behavior of both human users and bots. This research provides significant insights on how social media platforms can leverage economic incentives to influence user behavior and, more importantly, leverage bots’ activity to increase the engagement of their human users.
{"title":"Impact of Bot Involvement in an Incentivized Blockchain-Based Online Social Media Platform","authors":"F. Delkhosh, R. Gopal, Raymond A. Patterson, Niam Yaraghi","doi":"10.1080/07421222.2023.2229124","DOIUrl":"https://doi.org/10.1080/07421222.2023.2229124","url":null,"abstract":"ABSTRACT Incentivized blockchain-based online social media (BOSM), where creators and curators of popular content are paid in cryptocurrency, have recently emerged. Traditional social media ecosystems have experienced significant bot involvement in their platforms, which has often had a negative impact on both users and platforms. BOSM can provide additional direct financial incentives as motivation for both bots’ and human users’ engagement. Using the panel vector autoregression and regression discontinuity in time framework, we analyze two distinct data sets from Steemit, the largest and most popular BOSM, to study the impact of bot engagement on human users and the impact of changes in financial reward on user engagement. Interestingly, our findings demonstrate that while increased engagement by bots is positively associated with engagement by human users, the association between bot engagement and human user engagement decreases as the number of votes for a post increases. We also find that shifts in economic incentives significantly influence the behavior of both human users and bots. This research provides significant insights on how social media platforms can leverage economic incentives to influence user behavior and, more importantly, leverage bots’ activity to increase the engagement of their human users.","PeriodicalId":50154,"journal":{"name":"Journal of Management Information Systems","volume":"40 1","pages":"778 - 806"},"PeriodicalIF":7.7,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43387819","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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