Pub Date : 2026-04-01Epub Date: 2026-01-16DOI: 10.1016/j.im.2026.104306
Tsung-Sheng Chang, Lan-Gui Huang
Artificial intelligence (AI) tools can aid significantly in information system development. However, there has yet to be a comprehensive study on how programmers’ reliance on AI tools affects system development performance. This research, grounded in the theory of technology dominance, introduces the concept of AI reliance and integrates various factors such as task–technology fit, personal task experience, and knowledge integration to develop a model predicting the performance of information system development. This study employs quantitative methods to survey program development employees in Taiwan’s top 500 companies and the software service industry. Partial least squares structural equation modeling is used to evaluate the model, confirming the research hypotheses and the relationships between variables. This research confirms that AI reliance significantly impacts performance in information system development. This finding offers practical implications for information system developers and is an essential reference for enterprises seeking to optimize their strategies for using artificial intelligence tools.
{"title":"The impact of generative artificial intelligence on software development performance: a study based on the theory of technology dominance","authors":"Tsung-Sheng Chang, Lan-Gui Huang","doi":"10.1016/j.im.2026.104306","DOIUrl":"10.1016/j.im.2026.104306","url":null,"abstract":"<div><div>Artificial intelligence (AI) tools can aid significantly in information system development. However, there has yet to be a comprehensive study on how programmers’ reliance on AI tools affects system development performance. This research, grounded in the theory of technology dominance, introduces the concept of AI reliance and integrates various factors such as task–technology fit, personal task experience, and knowledge integration to develop a model predicting the performance of information system development. This study employs quantitative methods to survey program development employees in Taiwan’s top 500 companies and the software service industry. Partial least squares structural equation modeling is used to evaluate the model, confirming the research hypotheses and the relationships between variables. This research confirms that AI reliance significantly impacts performance in information system development. This finding offers practical implications for information system developers and is an essential reference for enterprises seeking to optimize their strategies for using artificial intelligence tools.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"63 3","pages":"Article 104306"},"PeriodicalIF":8.2,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145995809","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 : 2026-03-14DOI: 10.1016/j.im.2026.104344
Xu (Joyce) Cheng, Travis Holt, James Long, Tina Loraas
{"title":"Blockchain Applications: The Impact of a Firm’s Choice of Financial Accounting System on Nonprofessional Investor Judgment and Decision-Making","authors":"Xu (Joyce) Cheng, Travis Holt, James Long, Tina Loraas","doi":"10.1016/j.im.2026.104344","DOIUrl":"https://doi.org/10.1016/j.im.2026.104344","url":null,"abstract":"","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"91 1","pages":""},"PeriodicalIF":9.9,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447299","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 : 2026-03-13DOI: 10.1016/j.im.2026.104345
Sherry L. Fowler, Antonis Stylianou, Dongsong Zhang, Paul Lowry, Reza Mousavi, Shannon Reid
{"title":"Words Matter When Gangs Cyberbang: Predicting Imminent Urban Violence from Gang Members’ Social Media Posts","authors":"Sherry L. Fowler, Antonis Stylianou, Dongsong Zhang, Paul Lowry, Reza Mousavi, Shannon Reid","doi":"10.1016/j.im.2026.104345","DOIUrl":"https://doi.org/10.1016/j.im.2026.104345","url":null,"abstract":"","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"3 1","pages":""},"PeriodicalIF":9.9,"publicationDate":"2026-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447300","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 : 2026-03-12DOI: 10.1016/j.im.2026.104343
Elodie Gentina, Rui Chen, Frantz Rowe
{"title":"The Effect of Online Social Networks on Theory of Mind among Adolescents","authors":"Elodie Gentina, Rui Chen, Frantz Rowe","doi":"10.1016/j.im.2026.104343","DOIUrl":"https://doi.org/10.1016/j.im.2026.104343","url":null,"abstract":"","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"59 1","pages":""},"PeriodicalIF":9.9,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147447301","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 : 2026-03-09DOI: 10.1016/j.im.2026.104341
Bangan Wu, Ben Liu, Xitong Guo
Patient trust in physicians is crucial for healthcare outcomes, particularly for middle-aged and elderly adults who face complex health conditions and greater healthcare utilization. Despite growing research on trust determinants, the role of intergenerational dynamics remains underexplored. This paper investigates how adult children’s Internet use affects their parents’ trust in physicians. Using a sample of adult children from the China Family Panel Studies (CFPS), we find that adult children’s Internet use decreases their parents’ trust in physicians significantly. Using the national average Internet use of 29.0 hours per week (June 2024) as a benchmark for adult children, this level of Internet engagement leads to a 1.53-point decrease in parental trust in physicians on a 0–10 scale. This magnitude represents a substantial intergenerational spillover effect. We then identify two primary mechanisms driving this effect: a behavioral transmission mechanism, whereby children’s Internet use behavior is adopted by parents, and an attitudinal transmission mechanism, whereby children’s diminished physician trust attitudes influence parental perspectives directly through family interactions. Our findings contribute to the literature on Internet welfare effects in healthcare by showing the complex implications of Internet use for medical trust across generations. Furthermore, our study highlights the importance of addressing potential negative intergenerational effects in digital health literacy programs. It provides important policy implications for managing the digital divide across generations.
{"title":"Trust in Physicians across Generations: The Role of Internet Use in Reshaping Physician–Patient Relationships","authors":"Bangan Wu, Ben Liu, Xitong Guo","doi":"10.1016/j.im.2026.104341","DOIUrl":"https://doi.org/10.1016/j.im.2026.104341","url":null,"abstract":"Patient trust in physicians is crucial for healthcare outcomes, particularly for middle-aged and elderly adults who face complex health conditions and greater healthcare utilization. Despite growing research on trust determinants, the role of intergenerational dynamics remains underexplored. This paper investigates how adult children’s Internet use affects their parents’ trust in physicians. Using a sample of adult children from the China Family Panel Studies (CFPS), we find that adult children’s Internet use decreases their parents’ trust in physicians significantly. Using the national average Internet use of 29.0 hours per week (June 2024) as a benchmark for adult children, this level of Internet engagement leads to a 1.53-point decrease in parental trust in physicians on a 0–10 scale. This magnitude represents a substantial intergenerational spillover effect. We then identify two primary mechanisms driving this effect: a behavioral transmission mechanism, whereby children’s Internet use behavior is adopted by parents, and an attitudinal transmission mechanism, whereby children’s diminished physician trust attitudes influence parental perspectives directly through family interactions. Our findings contribute to the literature on Internet welfare effects in healthcare by showing the complex implications of Internet use for medical trust across generations. Furthermore, our study highlights the importance of addressing potential negative intergenerational effects in digital health literacy programs. It provides important policy implications for managing the digital divide across generations.","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"19 1","pages":""},"PeriodicalIF":9.9,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147392975","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 : 2026-03-05DOI: 10.1016/j.im.2026.104326
Nan (Tina) Wang
{"title":"Erratum to ‘MANAGERS’ NOTICING OF NEW ORGANIZATIONAL IT AND INFLUENCES OF IT ATTRIBUTES’","authors":"Nan (Tina) Wang","doi":"10.1016/j.im.2026.104326","DOIUrl":"https://doi.org/10.1016/j.im.2026.104326","url":null,"abstract":"","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"75 1","pages":""},"PeriodicalIF":9.9,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147360421","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 : 2026-03-01Epub Date: 2025-11-24DOI: 10.1016/j.im.2025.104276
Yayuan Liu , Haofeng Jin , Yu Tong
Low user payments have long been a challenge for experts who monetize knowledge on paid question-and-answer (Q&A) platforms. To address this issue, many platforms have introduced a “shared Q&A” service, in which users can pay a nominal fee to access previously generated answers. However, its economic implications for experts remain underexplored. This study proposes that shared Q&As play a dual role in both stimulating and substituting for the demand for paid Q&A services, resulting in an inverted U-shaped relationship between an expert’s shared Q&A volume and paid Q&A demand. Drawing on the theoretical lens of knowledge transfer, we further propose that this relationship is moderated by knowledge complexity, knowledge context dependence, and knowledge tacitness of shared Q&As. Empirical analyses based on a leading paid Q&A platform support most of the hypotheses. Our findings add prominent contribution to the knowledge payment literature and offer valuable insights into how shared Q&As can be used to increase expert revenue.
{"title":"Pay to view or pay to ask? The effect of shared questions-and-answers on paid question-and-answer demand","authors":"Yayuan Liu , Haofeng Jin , Yu Tong","doi":"10.1016/j.im.2025.104276","DOIUrl":"10.1016/j.im.2025.104276","url":null,"abstract":"<div><div>Low user payments have long been a challenge for experts who monetize knowledge on paid question-and-answer (Q&A) platforms. To address this issue, many platforms have introduced a “shared Q&A” service, in which users can pay a nominal fee to access previously generated answers. However, its economic implications for experts remain underexplored. This study proposes that shared Q&As play a dual role in both stimulating and substituting for the demand for paid Q&A services, resulting in an inverted U-shaped relationship between an expert’s shared Q&A volume and paid Q&A demand. Drawing on the theoretical lens of knowledge transfer, we further propose that this relationship is moderated by knowledge complexity, knowledge context dependence, and knowledge tacitness of shared Q&As. Empirical analyses based on a leading paid Q&A platform support most of the hypotheses. Our findings add prominent contribution to the knowledge payment literature and offer valuable insights into how shared Q&As can be used to increase expert revenue.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"63 2","pages":"Article 104276"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145593655","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 : 2026-03-01Epub Date: 2025-12-09DOI: 10.1016/j.im.2025.104289
Mingwei Li , Loo Geok Pee , Shan-Ling Pan , Xiang Xie
As digital platforms evolve, more vendors are participating in multi-vendor loyalty programs (MVLPs), which offer a wide variety of point redemption rewards to enhance customer engagement. However, an increase in redemption options can lead to greater confusion because of the choice overload effect. In this study, we explore how to design customer redemption analytics (CRA) for marketing professionals to effectively manage customer redemption choice overload in MVLPs. Using the design science research approach, we identify three CRA design requirements, which inform the formulation of design principles. We then instantiate these design principles into an operational CRA by embedding analytical algorithms and design features across three development iterations. To test the effectiveness of the artifacts, two summative evaluations are conducted in a real MVLP context. The results of our evaluation suggest the effectiveness of our designed CRA in reducing customer redemption choice overload from the perspectives of customers, vendors, and program managers. Our research contributes to design knowledge concerning CRA development in both the problem space and the solution space.
{"title":"Customer redemption analytics in multi-vendor loyalty programs: a design science research approach","authors":"Mingwei Li , Loo Geok Pee , Shan-Ling Pan , Xiang Xie","doi":"10.1016/j.im.2025.104289","DOIUrl":"10.1016/j.im.2025.104289","url":null,"abstract":"<div><div>As digital platforms evolve, more vendors are participating in multi-vendor loyalty programs (MVLPs), which offer a wide variety of point redemption rewards to enhance customer engagement. However, an increase in redemption options can lead to greater confusion because of the choice overload effect. In this study, we explore how to design customer redemption analytics (CRA) for marketing professionals to effectively manage customer redemption choice overload in MVLPs. Using the design science research approach, we identify three CRA design requirements, which inform the formulation of design principles. We then instantiate these design principles into an operational CRA by embedding analytical algorithms and design features across three development iterations. To test the effectiveness of the artifacts, two summative evaluations are conducted in a real MVLP context. The results of our evaluation suggest the effectiveness of our designed CRA in reducing customer redemption choice overload from the perspectives of customers, vendors, and program managers. Our research contributes to design knowledge concerning CRA development in both the problem space and the solution space.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"63 2","pages":"Article 104289"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790778","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 : 2026-03-01Epub Date: 2025-11-16DOI: 10.1016/j.im.2025.104274
Wei Liu , Xueying Sun , Weiguo Fan , Zhengfa Yang
Online knowledge-sharing platforms (OKSPs) play an important role in enabling the participants to generate and transfer novel knowledge and obtain social support from their peers. To foster knowledge exchange between knowledge contributors and knowledge seekers, OKSPs implement various governance mechanisms, such as platform recommendations. We are interested in whether cross-side network effects (CNEs) exist on OKSPs, and how the OKSPs’ governance mechanisms affect these CNEs. In this study, we theorize knowledge-sharing processes between the contributor-side and the seeker-side, drawing on the dynamic theory of knowledge conversion. Using fine-grained longitudinal data from the Zhihu platform, we propose a vector autoregressive model (VAR) to examine the temporal dynamics of CNEs on OKSPs and the role of platform recommendations in the CNEs empirically. Our findings indicate that there are symmetrical short-run contributor-to-seeker CNEs and seeker-to-contributor CNEs. However, a temporal asymmetry is present between contributor-to-seeker CNEs and seeker-to-contributor CNEs in the long run. Specifically, we find the answers’ quantity and answers’ quality have short-run and long-run impacts on the growth of questions’ quantity, meaning that the contributor side plays a predominant role in driving the growth and evolution of OKSPs. Our findings also reveal that platform recommendations strengthen immediate and persistent growth in the number of questions and answers through the direct contributor-to-seeker and seeker-to-contributor CNEs rather than the indirect CNEs. Our study provides important theoretical implications to enrich knowledge management research from CNEs’ perspective, as well as practical insights for OKSPs in their operations to incorporate network analytics to promote participants’ engagement and knowledge exchange.
{"title":"Asymmetric cross-side network effects on online knowledge-sharing platforms and the role of platform recommendations","authors":"Wei Liu , Xueying Sun , Weiguo Fan , Zhengfa Yang","doi":"10.1016/j.im.2025.104274","DOIUrl":"10.1016/j.im.2025.104274","url":null,"abstract":"<div><div>Online knowledge-sharing platforms (OKSPs) play an important role in enabling the participants to generate and transfer novel knowledge and obtain social support from their peers. To foster knowledge exchange between knowledge contributors and knowledge seekers, OKSPs implement various governance mechanisms, such as platform recommendations. We are interested in whether cross-side network effects (CNEs) exist on OKSPs, and how the OKSPs’ governance mechanisms affect these CNEs. In this study, we theorize knowledge-sharing processes between the contributor-side and the seeker-side, drawing on the dynamic theory of knowledge conversion. Using fine-grained longitudinal data from the Zhihu platform, we propose a vector autoregressive model (VAR) to examine the temporal dynamics of CNEs on OKSPs and the role of platform recommendations in the CNEs empirically. Our findings indicate that there are symmetrical short-run contributor-to-seeker CNEs and seeker-to-contributor CNEs. However, a temporal asymmetry is present between contributor-to-seeker CNEs and seeker-to-contributor CNEs in the long run. Specifically, we find the answers’ quantity and answers’ quality have short-run and long-run impacts on the growth of questions’ quantity, meaning that the contributor side plays a predominant role in driving the growth and evolution of OKSPs. Our findings also reveal that platform recommendations strengthen immediate and persistent growth in the number of questions and answers through the direct contributor-to-seeker and seeker-to-contributor CNEs rather than the indirect CNEs. Our study provides important theoretical implications to enrich knowledge management research from CNEs’ perspective, as well as practical insights for OKSPs in their operations to incorporate network analytics to promote participants’ engagement and knowledge exchange.</div></div>","PeriodicalId":56291,"journal":{"name":"Information & Management","volume":"63 2","pages":"Article 104274"},"PeriodicalIF":8.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145536027","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号