Pub Date : 2025-10-27DOI: 10.1016/j.ijinfomgt.2025.102988
Xianhao Xu , Fan Wu , Chung-Yean Chiang , Xingwei Lu
This study investigates the influence of firms’ structural embeddedness (accessibility and interconnectedness) within supply chain network (SCN) on firm resilience. Additionally, it examines how three artificial intelligence (AI) capabilities (data analytics, interaction, and application) moderate this relationship. The research develops a conceptual model anchored in Network Embeddedness Theory (NET). We analyze panel data from Chinese listed firms collected from the China Stock Market & Accounting Research (CSMAR) Database and corporate annual reports to empirically tested conceptual model. Our analysis reveals that structural embeddedness significantly influences firm resilience. Specifically, AI data analytics capability moderates the relationship between accessibility and resilience, while AI application capability moderates the relationships between both accessibility and interconnectedness with resilience. However, AI interaction capability demonstrates no significant moderating effect. This study extends resilience analysis to the network level. By disaggregating AI capabilities into three dimensions and examining their heterogeneity effect, we offer nuanced insights into how firms can strategically leverage their network positions and technological capacities to enhance resilience within increasingly complex and uncertain supply chain environments.
{"title":"Fortifying firm resilience: The interplay of network embeddedness and AI capabilities","authors":"Xianhao Xu , Fan Wu , Chung-Yean Chiang , Xingwei Lu","doi":"10.1016/j.ijinfomgt.2025.102988","DOIUrl":"10.1016/j.ijinfomgt.2025.102988","url":null,"abstract":"<div><div>This study investigates the influence of firms’ structural embeddedness (accessibility and interconnectedness) within supply chain network (SCN) on firm resilience. Additionally, it examines how three artificial intelligence (AI) capabilities (data analytics, interaction, and application) moderate this relationship. The research develops a conceptual model anchored in Network Embeddedness Theory (NET). We analyze panel data from Chinese listed firms collected from the China Stock Market & Accounting Research (CSMAR) Database and corporate annual reports to empirically tested conceptual model. Our analysis reveals that structural embeddedness significantly influences firm resilience. Specifically, AI data analytics capability moderates the relationship between accessibility and resilience, while AI application capability moderates the relationships between both accessibility and interconnectedness with resilience. However, AI interaction capability demonstrates no significant moderating effect. This study extends resilience analysis to the network level. By disaggregating AI capabilities into three dimensions and examining their heterogeneity effect, we offer nuanced insights into how firms can strategically leverage their network positions and technological capacities to enhance resilience within increasingly complex and uncertain supply chain environments.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102988"},"PeriodicalIF":27.0,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-15DOI: 10.1016/j.ijinfomgt.2025.102987
Wei Wang , Haiwang Liu , Xiaohui Zheng , Yuan Qin , Yenchun Jim Wu
Creating types of rewards that align with the motivational inclinations of investors is posited as an essential precondition of successful crowdfunding. However, the relationship among entrepreneurial narratives, the types of rewards, and financing performance is often overlooked. Based on self-determination theory (SDT), we use 256,633 crowdfunding projects from Kickstarter to examine this relationship. Text mining is employed to identify four types of rewards: emotional support, participation opportunity, virtual product, and physical product rewards. The first two have intrinsic incentives, whereas the second two have extrinsic incentives. By econometric models, the results suggest that intrinsically driven rewards are more attractive than extrinsically driven rewards. The participation opportunity reward is the most effective, while the virtual product reward is the least effective. Further, the cognitive load of reward narratives enhances the effect of the reward. Moreover, entrepreneur narcissism enhances the effect of the reward, but the influence is not consistent among the four types of rewards. In addition, the effect of the type of reward depends on a project’s characteristics. This study refines the application of SDT regarding online entrepreneurship, deepens understanding of informational mechanisms that motivate investor participation, and offers actionable guidelines for information management regarding the rewards and narrative content.
{"title":"Reward-based crowdfunding strategies: Aligning the types of rewards for crowdfunding projects with entrepreneurial narratives","authors":"Wei Wang , Haiwang Liu , Xiaohui Zheng , Yuan Qin , Yenchun Jim Wu","doi":"10.1016/j.ijinfomgt.2025.102987","DOIUrl":"10.1016/j.ijinfomgt.2025.102987","url":null,"abstract":"<div><div>Creating types of rewards that align with the motivational inclinations of investors is posited as an essential precondition of successful crowdfunding. However, the relationship among entrepreneurial narratives, the types of rewards, and financing performance is often overlooked. Based on self-determination theory (SDT), we use 256,633 crowdfunding projects from Kickstarter to examine this relationship. Text mining is employed to identify four types of rewards: emotional support, participation opportunity, virtual product, and physical product rewards. The first two have intrinsic incentives, whereas the second two have extrinsic incentives. By econometric models, the results suggest that intrinsically driven rewards are more attractive than extrinsically driven rewards. The participation opportunity reward is the most effective, while the virtual product reward is the least effective. Further, the cognitive load of reward narratives enhances the effect of the reward. Moreover, entrepreneur narcissism enhances the effect of the reward, but the influence is not consistent among the four types of rewards. In addition, the effect of the type of reward depends on a project’s characteristics. This study refines the application of SDT regarding online entrepreneurship, deepens understanding of informational mechanisms that motivate investor participation, and offers actionable guidelines for information management regarding the rewards and narrative content.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102987"},"PeriodicalIF":27.0,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145332613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-10DOI: 10.1016/j.ijinfomgt.2025.102982
Laurie Hughes , Fern Davies , Keyao Li , Senali Madugoda Gunaratnege , Tegwen Malik , Yogesh K Dwivedi
It is widely accepted that the impact of Generative Artificial Intelligence (GenAI) has been nothing short of transformational, with tangible impacts on industry, education, healthcare and government. But beyond the headlines, how are organisations actually using GenAI, what are the key challenges experienced by decision makers and has the reality on the ground matched the hype? This study adopts a mixed-methods approach, utilising the Technology-Organisation-Environment (TOE) framework to reveal greater insights to how organisations are adopting GenAI, the drivers that affect decision making and the key challenges associated with greater use of the technology. This research adopts a mixed method approach incorporating an explorative qualitative step with industry participants followed by a survey of 304 (three hundred and four) decision makers from a cross section of industry sectors from around the world including: North America, Europe, Africa, Australia and Asia, to gain further insight to the underlying factors that drive GenAI adoption. The research model was validated using Structural Equation Modelling (SEM) and reveals the intricate and inherent complexities related to greater levels of GenAI adoption. The analysis highlights the critical role of change capacity of the organisation in moderating complexity and staff skills. This research provides valuable and timely insights for senior management and policy makers that are attempting to better understand the interdependencies and perspectives on the key challenges facing organisations looking to deliver greater impact on organisational performance through GenAI.
{"title":"Beyond the hype: Organisational adoption of Generative AI through the lens of the TOE framework–A mixed methods perspective","authors":"Laurie Hughes , Fern Davies , Keyao Li , Senali Madugoda Gunaratnege , Tegwen Malik , Yogesh K Dwivedi","doi":"10.1016/j.ijinfomgt.2025.102982","DOIUrl":"10.1016/j.ijinfomgt.2025.102982","url":null,"abstract":"<div><div>It is widely accepted that the impact of Generative Artificial Intelligence (GenAI) has been nothing short of transformational, with tangible impacts on industry, education, healthcare and government. But beyond the headlines, how are organisations actually using GenAI, what are the key challenges experienced by decision makers and has the reality on the ground matched the hype? This study adopts a mixed-methods approach, utilising the Technology-Organisation-Environment (TOE) framework to reveal greater insights to how organisations are adopting GenAI, the drivers that affect decision making and the key challenges associated with greater use of the technology. This research adopts a mixed method approach incorporating an explorative qualitative step with industry participants followed by a survey of 304 (three hundred and four) decision makers from a cross section of industry sectors from around the world including: North America, Europe, Africa, Australia and Asia, to gain further insight to the underlying factors that drive GenAI adoption. The research model was validated using Structural Equation Modelling (SEM) and reveals the intricate and inherent complexities related to greater levels of GenAI adoption. The analysis highlights the critical role of change capacity of the organisation in moderating complexity and staff skills. This research provides valuable and timely insights for senior management and policy makers that are attempting to better understand the interdependencies and perspectives on the key challenges facing organisations looking to deliver greater impact on organisational performance through GenAI.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102982"},"PeriodicalIF":27.0,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-09DOI: 10.1016/j.ijinfomgt.2025.102984
Hanfei Xue , Jiayu Wang , Szeman Chong , Woojin Choi , Chung-Wha (Chloe) Ki , Christina W.Y. Wong
Despite ongoing debates about the benefits and challenges of AI in retail, advances in AI continue to drive the evolution of virtual assistants (VAs). Initially limited to simple, formless chatbots, VAs have progressively incorporated visual representations and, more recently, hyper-realistic, human-like digital personas enabled by AI. While these innovations have significantly enhanced the form and realism of VAs, their true impact remains underexplored, with mixed evidence on how such visual improvements influence consumer perception and, ultimately, VA service quality. Complicating this issue is a persistent theoretical bias in the existing literature, which predominantly depends on technology-, social-, and cognitive-centered frameworks. Although technology-based theories were useful in early VA adoption, their explanatory power declines as consumer familiarity grows. Moreover, the online retail context—where VAs primarily operate—limits the relevance of traditional social and cognitive theories. Unlike goal-driven, socially interactive in-store shopping, online retail is often solitary, self-paced, and hedonic. Online consumers browse not only to fulfill functional or cognitive needs but also to seek leisure, escape from daily routines (liberation), and indulge in immersive pleasure (hedonic engagement), treating shopping as a source of fun and stress relief. Given these dynamics, VA research must move beyond traditional frameworks to better capture the hedonic nature of modern online retail. To address these gaps, we examine how VA form and realism influence consumer evaluations of VA services, focusing on the mediating roles of liberation, hedonic engagement, and fun, as outlined in consumer fun theory. Using VA stimuli generated by AI tools, we conducted three experimental studies. Study 1 found that simply adding a visual form to VA (compared to no form) significantly improved consumer evaluations, mediated by liberation, hedonic engagement, and fun. Study 2 showed that increasing VA form realism (high vs. low) further amplified service evaluations through the same mediation pathways. Study 3 confirmed these effects and revealed that recreation-oriented shoppers experienced stronger mediation effects than task-oriented shoppers. Together, these findings offer fresh theoretical and practical insights for enhancing VA design and deployment in online retail environments.
{"title":"Fun by Design: Visual Form, Realism, and the Hedonic Appeal of AI-Powered Virtual Assistants","authors":"Hanfei Xue , Jiayu Wang , Szeman Chong , Woojin Choi , Chung-Wha (Chloe) Ki , Christina W.Y. Wong","doi":"10.1016/j.ijinfomgt.2025.102984","DOIUrl":"10.1016/j.ijinfomgt.2025.102984","url":null,"abstract":"<div><div>Despite ongoing debates about the benefits and challenges of AI in retail, advances in AI continue to drive the evolution of virtual assistants (VAs). Initially limited to simple, formless chatbots, VAs have progressively incorporated visual representations and, more recently, hyper-realistic, human-like digital personas enabled by AI. While these innovations have significantly enhanced the form and realism of VAs, their true impact remains underexplored, with mixed evidence on how such visual improvements influence consumer perception and, ultimately, VA service quality. Complicating this issue is a persistent theoretical bias in the existing literature, which predominantly depends on technology-, social-, and cognitive-centered frameworks. Although technology-based theories were useful in early VA adoption, their explanatory power declines as consumer familiarity grows. Moreover, the online retail context—where VAs primarily operate—limits the relevance of traditional social and cognitive theories. Unlike goal-driven, socially interactive in-store shopping, online retail is often solitary, self-paced, and hedonic. Online consumers browse not only to fulfill functional or cognitive needs but also to seek leisure, escape from daily routines (liberation), and indulge in immersive pleasure (hedonic engagement), treating shopping as a source of fun and stress relief. Given these dynamics, VA research must move beyond traditional frameworks to better capture the hedonic nature of modern online retail. To address these gaps, we examine how VA form and realism influence consumer evaluations of VA services, focusing on the mediating roles of liberation, hedonic engagement, and fun, as outlined in consumer fun theory. Using VA stimuli generated by AI tools, we conducted three experimental studies. Study 1 found that simply adding a visual form to VA (compared to no form) significantly improved consumer evaluations, mediated by liberation, hedonic engagement, and fun. Study 2 showed that increasing VA form realism (high vs. low) further amplified service evaluations through the same mediation pathways. Study 3 confirmed these effects and revealed that recreation-oriented shoppers experienced stronger mediation effects than task-oriented shoppers. Together, these findings offer fresh theoretical and practical insights for enhancing VA design and deployment in online retail environments.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102984"},"PeriodicalIF":27.0,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-07DOI: 10.1016/j.ijinfomgt.2025.102985
Györgyi Danó, Stefan Kovács, Vivien Surman
Artificial intelligence (AI)-based tools, such as virtual assistants (VAs), are increasingly used in marketing research, offering both task automation and interactive capabilities. This study examines virtual interviewers (VIs), AI-driven systems designed to conduct surveys as an alternative to human interviewers, addressing a key research gap on demographic and regional differences in VI adoption. Using two independent datasets (N = 1077 for a national sample, N = 1161 for Budapest), we tested three hypotheses related to Chatbot usage, willingness to engage with VIs, and regional differences. The findings reveal significant urban-rural disparities in AI acceptance. Urban respondents, particularly in Budapest, showed greater openness to Chatbot adoption, driven by curiosity and a desire for novelty. In contrast, rural participants exhibited heightened privacy concerns, acting as a barrier to adoption. Across both groups, openness to innovation and positive AI attitudes facilitated adoption, whereas privacy apprehensions and a preference for human interaction posed challenges. Beyond individual preferences, the study highlights ethical concerns, including AI replacing human interviewers and biases in AI algorithms. These findings underscore the need for tailored AI strategies that address regional and demographic differences while mitigating privacy concerns and building trust. This study advances knowledge on demographic and attitudinal factors influencing AI acceptance in research, with implications for optimizing AI-human hybrid models and ensuring ethical, inclusive AI adoption in marketing research and beyond.
{"title":"AI meets marketing research: Virtual interviewers and the challenges of regional and demographic adoption","authors":"Györgyi Danó, Stefan Kovács, Vivien Surman","doi":"10.1016/j.ijinfomgt.2025.102985","DOIUrl":"10.1016/j.ijinfomgt.2025.102985","url":null,"abstract":"<div><div>Artificial intelligence (AI)-based tools, such as virtual assistants (VAs), are increasingly used in marketing research, offering both task automation and interactive capabilities. This study examines virtual interviewers (VIs), AI-driven systems designed to conduct surveys as an alternative to human interviewers, addressing a key research gap on demographic and regional differences in VI adoption. Using two independent datasets (N = 1077 for a national sample, N = 1161 for Budapest), we tested three hypotheses related to Chatbot usage, willingness to engage with VIs, and regional differences. The findings reveal significant urban-rural disparities in AI acceptance. Urban respondents, particularly in Budapest, showed greater openness to Chatbot adoption, driven by curiosity and a desire for novelty. In contrast, rural participants exhibited heightened privacy concerns, acting as a barrier to adoption. Across both groups, openness to innovation and positive AI attitudes facilitated adoption, whereas privacy apprehensions and a preference for human interaction posed challenges. Beyond individual preferences, the study highlights ethical concerns, including AI replacing human interviewers and biases in AI algorithms. These findings underscore the need for tailored AI strategies that address regional and demographic differences while mitigating privacy concerns and building trust. This study advances knowledge on demographic and attitudinal factors influencing AI acceptance in research, with implications for optimizing AI-human hybrid models and ensuring ethical, inclusive AI adoption in marketing research and beyond.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102985"},"PeriodicalIF":27.0,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Generative artificial intelligence (GenAI) has demonstrated remarkable potential in creative domains; however, existing research has yet to fully explore how to optimize human–GenAI synergy or uncover the mechanisms underlying its impact on creativity. This study transcends the view of creativity as a singular process or monolithic outcome and examines how human–GenAI collaboration differentially influences the distinct creative phases of idea generation and idea elaboration. Drawing on creative process theory and goal orientation theory, we propose that human–GenAI collaboration activates phase-specific psychological mechanisms in pursuit of divergent creative goals. Using a multimethod approach, including a qualitative study (N = 20), two lab experiments (N1 = 42; N2 = 44), and an online behavioral experiment (N = 198), we find that human–GenAI collaboration in the idea generation phase (compared with the elaboration phase) enhances creative novelty by increasing cognitive flexibility, whereas human–GenAI collaboration in the idea elaboration phase (compared with the generation phase) improves creative usefulness by reducing cognitive overload. Furthermore, perceived GenAI intelligence moderates the indirect relationship between collaboration phases and usefulness through cognitive overload. By deconstructing the creative process, this research offers a nuanced understanding of the mechanisms and boundary conditions of human–GenAI collaboration, advancing theoretical conversations on AI-assisted creativity and providing actionable guidance for integrating GenAI into creative and organizational workflows.
{"title":"Human–GenAI collaboration across creative phases: Cognitive mechanisms shaping novelty and usefulness","authors":"Shiyingzi Huang , Lirong Long , Yanghao Zhu , Julie N.Y. Zhu","doi":"10.1016/j.ijinfomgt.2025.102986","DOIUrl":"10.1016/j.ijinfomgt.2025.102986","url":null,"abstract":"<div><div>Generative artificial intelligence (GenAI) has demonstrated remarkable potential in creative domains; however, existing research has yet to fully explore how to optimize human–GenAI synergy or uncover the mechanisms underlying its impact on creativity. This study transcends the view of creativity as a singular process or monolithic outcome and examines how human–GenAI collaboration differentially influences the distinct creative phases of idea generation and idea elaboration. Drawing on creative process theory and goal orientation theory, we propose that human–GenAI collaboration activates phase-specific psychological mechanisms in pursuit of divergent creative goals. Using a multimethod approach, including a qualitative study (<em>N</em> = 20), two lab experiments (<em>N</em><sub><em>1</em></sub> = 42; <em>N</em><sub><em>2</em></sub> = 44), and an online behavioral experiment (<em>N</em> = 198), we find that human–GenAI collaboration in the idea generation phase (compared with the elaboration phase) enhances creative novelty by increasing cognitive flexibility, whereas human–GenAI collaboration in the idea elaboration phase (compared with the generation phase) improves creative usefulness by reducing cognitive overload. Furthermore, perceived GenAI intelligence moderates the indirect relationship between collaboration phases and usefulness through cognitive overload. By deconstructing the creative process, this research offers a nuanced understanding of the mechanisms and boundary conditions of human–GenAI collaboration, advancing theoretical conversations on AI-assisted creativity and providing actionable guidance for integrating GenAI into creative and organizational workflows.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102986"},"PeriodicalIF":27.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-03DOI: 10.1016/j.ijinfomgt.2025.102983
Guanghong Xie
Generative AI (Gen AI) shopping assistants have been extensively studied—both theoretically and empirically—for their impact on consumer experiences in developed-country e-commerce platforms. However, cultural, economic, and technological differences may constrain applicability in developing-country contexts. This study examines both the “lights and shadows” of Gen AI shopping assistants in developing countries, focusing on how these assistants shape the consumer motivation–behaviour process. We conduct a review from the perspectives of human–computer interaction (HCI), cognitive psychology, and marketing to assess the current state and challenges of Gen AI shopping assistants. Based on this review, we have developed the Motivation–Expectation Management Model (MEMM) to complete the following cycle: Motivation → HCI → Expectation Confirmation → Satisfaction and Repurchase → (feedback to) Motivation. We then collect data from consumers using the “Taobao Wenwen” Gen AI shopping assistant within the Taobao app in China and employ a mixed-methods approach to test the significance, importance, and necessity of the MEMM. (1) Extrinsic motivation exerts a greater influence on personalzation and UX than intrinsic motivation; (2) Mediation chains linking user experience, expectation confirmation, satisfaction, and repurchase intention are significant, with some relationships supported across significance, importance, and necessity analyses, while others are only partially consistent. In summary, MEMM provides both theoretical and empirical grounding for studying Gen AI shopping assistants in developing-country contexts, helps elucidate the consumer–Gen AI interaction mechanisms at play, and offers strategic guidance for sustaining a continuous cycle of interaction optimisation in e-commerce markets.
{"title":"The impact of generative AI shopping assistants on E-commerce consumer motivation and behavior: Consumer-AI interaction design","authors":"Guanghong Xie","doi":"10.1016/j.ijinfomgt.2025.102983","DOIUrl":"10.1016/j.ijinfomgt.2025.102983","url":null,"abstract":"<div><div>Generative AI (Gen AI) shopping assistants have been extensively studied—both theoretically and empirically—for their impact on consumer experiences in developed-country e-commerce platforms. However, cultural, economic, and technological differences may constrain applicability in developing-country contexts. This study examines both the “lights and shadows” of Gen AI shopping assistants in developing countries, focusing on how these assistants shape the consumer motivation–behaviour process. We conduct a review from the perspectives of human–computer interaction (HCI), cognitive psychology, and marketing to assess the current state and challenges of Gen AI shopping assistants. Based on this review, we have developed the Motivation–Expectation Management Model (MEMM) to complete the following cycle: Motivation → HCI → Expectation Confirmation → Satisfaction and Repurchase → (feedback to) Motivation. We then collect data from consumers using the “Taobao Wenwen” Gen AI shopping assistant within the Taobao app in China and employ a mixed-methods approach to test the significance, importance, and necessity of the MEMM. (1) Extrinsic motivation exerts a greater influence on personalzation and UX than intrinsic motivation; (2) Mediation chains linking user experience, expectation confirmation, satisfaction, and repurchase intention are significant, with some relationships supported across significance, importance, and necessity analyses, while others are only partially consistent. In summary, MEMM provides both theoretical and empirical grounding for studying Gen AI shopping assistants in developing-country contexts, helps elucidate the consumer–Gen AI interaction mechanisms at play, and offers strategic guidance for sustaining a continuous cycle of interaction optimisation in e-commerce markets.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102983"},"PeriodicalIF":27.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.ijinfomgt.2025.102980
Bo Yang, Yongqiang Sun, Qinwei Li
Generative artificial intelligence (GAI) can fundamentally disrupt how content is produced and is increasingly integrated into organizational and individual task-performing and decision-making. This study investigates how individuals perceive and process AI-generated content by advancing the understanding of user satisfaction through an extension of dual fit theory. By theoretically grounding our investigation in dual fit theory, we propose that two key information representations (information credibility and creativity) are key drivers of user satisfaction, operating through two distinct mediating mechanisms: cognitive fit, which reflects the alignment of information with task demands, and emotional fit, which captures the match between the interaction experience and user emotions. Our model posits that both credibility and creativity distinctly influence these cognitive and emotional fit pathways. Furthermore, we examine the boundary conditions by exploring the moderating role of task representation (e.g., task routineness and task hedonism). We tested our hypotheses through two 2 × 2 between-subject scenario experiments with 548 and 197 participants. Across both studies, the results consistently show that information credibility positively impacts both cognitive and emotional fit. Information creativity primarily enhances emotional fit, with its effect on cognitive fit emerging under specific task conditions. Both fit dimensions, in turn, positively affect user satisfaction with the outcome and the process. Our results indicate that task routineness is a stronger moderator than task hedonism. A good match between the information and task representations (i.e., aligning credibility with routine tasks and creativity with creative tasks) leads to enhanced cognitive and emotional fit.
{"title":"To be credible or to be creative? Understanding the mechanisms driving user satisfaction with AI-generated content from a dual fit perspective","authors":"Bo Yang, Yongqiang Sun, Qinwei Li","doi":"10.1016/j.ijinfomgt.2025.102980","DOIUrl":"10.1016/j.ijinfomgt.2025.102980","url":null,"abstract":"<div><div>Generative artificial intelligence (GAI) can fundamentally disrupt how content is produced and is increasingly integrated into organizational and individual task-performing and decision-making. This study investigates how individuals perceive and process AI-generated content by advancing the understanding of user satisfaction through an extension of dual fit theory. By theoretically grounding our investigation in dual fit theory, we propose that two key information representations (information credibility and creativity) are key drivers of user satisfaction, operating through two distinct mediating mechanisms: cognitive fit, which reflects the alignment of information with task demands, and emotional fit, which captures the match between the interaction experience and user emotions. Our model posits that both credibility and creativity distinctly influence these cognitive and emotional fit pathways. Furthermore, we examine the boundary conditions by exploring the moderating role of task representation (e.g., task routineness and task hedonism). We tested our hypotheses through two 2 × 2 between-subject scenario experiments with 548 and 197 participants. Across both studies, the results consistently show that information credibility positively impacts both cognitive and emotional fit. Information creativity primarily enhances emotional fit, with its effect on cognitive fit emerging under specific task conditions. Both fit dimensions, in turn, positively affect user satisfaction with the outcome and the process. Our results indicate that task routineness is a stronger moderator than task hedonism. A good match between the information and task representations (i.e., aligning credibility with routine tasks and creativity with creative tasks) leads to enhanced cognitive and emotional fit.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102980"},"PeriodicalIF":27.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid adoption of Artificial Intelligence (AI)–powered Customer Relationship Management (CRM) systems has exposed a critical gap: despite substantial investment, many organisations fail to derive meaningful business value from these technologies. Recent surveys show that while AI is a strategic priority for executives, only a fraction report significant returns, with adoption challenges particularly acute in customer-facing functions. This study addresses this gap by conceptualising and empirically examining AI-powered CRM as a higher-order organisational capability. Drawing on the microfoundations of dynamic capability theory, we adopt a three-stage research design. First, a systematic scoping review and in-depth interviews with industry experts identify the core dimensions and subdimensions of AI-powered CRM capability. Second, we operationalise and validate these dimensions within a nomological network. Third, a survey of 205 banking employees in Australia tests the influence of AI-powered CRM capability on marketing ambidexterity and, in turn, on organisational outcomes. The quantitative analysis confirms that AI-powered CRM capabilities positively shape marketing ambidexterity, which subsequently enhances profitability and competitive advantage. Theoretically, the findings advance CRM research by introducing a microfoundational capability model that integrates data management, multi-channel integration, and service offerings. Practically, the study provides actionable guidance for managers seeking to close the “value realisation gap” by cultivating AI-powered CRM systems as dynamic capabilities that balance exploration and exploitation in volatile markets.
{"title":"AI-powered CRM capability model: Advancing marketing ambidexterity, profitability and competitive performance","authors":"Khadija Khamis Alnofeli , Shahriar Akter , Venkata Yanamandram , Umme Hani","doi":"10.1016/j.ijinfomgt.2025.102981","DOIUrl":"10.1016/j.ijinfomgt.2025.102981","url":null,"abstract":"<div><div>The rapid adoption of Artificial Intelligence (AI)–powered Customer Relationship Management (CRM) systems has exposed a critical gap: despite substantial investment, many organisations fail to derive meaningful business value from these technologies. Recent surveys show that while AI is a strategic priority for executives, only a fraction report significant returns, with adoption challenges particularly acute in customer-facing functions. This study addresses this gap by conceptualising and empirically examining AI-powered CRM as a higher-order organisational capability. Drawing on the microfoundations of dynamic capability theory, we adopt a three-stage research design. First, a systematic scoping review and in-depth interviews with industry experts identify the core dimensions and subdimensions of AI-powered CRM capability. Second, we operationalise and validate these dimensions within a nomological network. Third, a survey of 205 banking employees in Australia tests the influence of AI-powered CRM capability on marketing ambidexterity and, in turn, on organisational outcomes. The quantitative analysis confirms that AI-powered CRM capabilities positively shape marketing ambidexterity, which subsequently enhances profitability and competitive advantage. Theoretically, the findings advance CRM research by introducing a microfoundational capability model that integrates data management, multi-channel integration, and service offerings. Practically, the study provides actionable guidance for managers seeking to close the “value realisation gap” by cultivating AI-powered CRM systems as dynamic capabilities that balance exploration and exploitation in volatile markets.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102981"},"PeriodicalIF":27.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With recent advancements in quantum computing technology, companies have begun considering replacing or jointly utilizing their existing classical computing resources with quantum computing. Despite initial research on the examination of the adoption considerations for quantum computing, there is a lack of studies investigating the conditions that influence the adoption of quantum computing technology. Therefore, the purpose of this study is to identify and analyze the key factors that drive or hinder companies' intention to adopt quantum computing technology. Building on the theory of innovation diffusion and integrating insights from the adoption of multiple emerging technologies, this research aims to extend the understanding of quantum computing adoption dynamics. Specifically, drawing on the theory of innovation diffusion and existing literature related to the adoption of multiple emerging technologies, this research proposes the following research questions to identify the factors influencing the adoption intention of quantum computing. The study employed a Sequential Explanatory design, first exploring the topic through literature and interviews with 11 quantum computing experts, then quantifying findings with a questionnaire survey with 250 IT decision-makers within Korean companies, analyzed using PLS-SEM and MGA. Research findings revealed that belief in quantum superiority, quantum advantage, continuous budget allocation, and regulatory support significantly and positively influenced quantum computing adoption, whereas organizational resistance had the most substantial negative impact. Furthermore, firm size and industry significantly moderate these adoption intentions. Interestingly, companies expressed a desire to adopt quantum computing despite uncertainties. Theoretically, this study contributes to innovation diffusion theory by contextualizing its application to the adoption of a highly complex and nascent technology such as quantum computing. Practically, the findings offer actionable implications for policymakers and business leaders by illuminating the key drivers and barriers that must be addressed to promote quantum computing adoption.
{"title":"Factors influencing the adoption intent of quantum computing in enterprises: An innovation adoption process perspective","authors":"Ohbyung Kwon , Seongjun Kwon , Timothy Jung , Saifeddin Alimamy","doi":"10.1016/j.ijinfomgt.2025.102978","DOIUrl":"10.1016/j.ijinfomgt.2025.102978","url":null,"abstract":"<div><div>With recent advancements in quantum computing technology, companies have begun considering replacing or jointly utilizing their existing classical computing resources with quantum computing. Despite initial research on the examination of the adoption considerations for quantum computing, there is a lack of studies investigating the conditions that influence the adoption of quantum computing technology. Therefore, the purpose of this study is to identify and analyze the key factors that drive or hinder companies' intention to adopt quantum computing technology. Building on the theory of innovation diffusion and integrating insights from the adoption of multiple emerging technologies, this research aims to extend the understanding of quantum computing adoption dynamics. Specifically, drawing on the theory of innovation diffusion and existing literature related to the adoption of multiple emerging technologies, this research proposes the following research questions to identify the factors influencing the adoption intention of quantum computing. The study employed a Sequential Explanatory design, first exploring the topic through literature and interviews with 11 quantum computing experts, then quantifying findings with a questionnaire survey with 250 IT decision-makers within Korean companies, analyzed using PLS-SEM and MGA. Research findings revealed that belief in quantum superiority, quantum advantage, continuous budget allocation, and regulatory support significantly and positively influenced quantum computing adoption, whereas organizational resistance had the most substantial negative impact. Furthermore, firm size and industry significantly moderate these adoption intentions. Interestingly, companies expressed a desire to adopt quantum computing despite uncertainties. Theoretically, this study contributes to innovation diffusion theory by contextualizing its application to the adoption of a highly complex and nascent technology such as quantum computing. Practically, the findings offer actionable implications for policymakers and business leaders by illuminating the key drivers and barriers that must be addressed to promote quantum computing adoption.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"86 ","pages":"Article 102978"},"PeriodicalIF":27.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145227140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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