International Journal of Information Management最新文献

Seeking help from AI: Understanding patient use of intelligent guidance applications 向AI寻求帮助：了解患者对智能引导应用程序的使用情况

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-06-01 Epub Date: 2026-01-15 DOI: 10.1016/j.ijinfomgt.2026.103032

Tailai Wu , Ruihan Li , Zhaohua Deng , Lulu Zhou , Lingfei Lu

Intelligent guidance applications (IGAs) have emerged with a profound impact on the patient’s experience of using healthcare services in and out of hospitals. However, the implementation of IGAs faces challenges, including low popularity and acceptance as well as uneven use of hospitals in different regions. Meanwhile, little research has examined the factors of IGAs use. To promote patient use of IGAs, this study focuses on identifying the factors of patient use of IGAs. A research model was developed to examine the factors and articulate their relationships with IGAs use based on the help-seeking model. We validated our research model through a two-stage survey and analyzed the collected data using a multi-analytical approach, including structural equation modeling (SEM) and artificial neural network (ANN). The SEM analysis results indicate that accuracy, personalization, anthropomorphism, and openness all significantly impact patients’ use intention and behavior of IGAs through distress. Self-concealment not only affects the above four attributes but also influences distress and attitudes to IGAs. Meanwhile, the impacts of both distress and attitudes to IGAs on intention to use IGAs are moderated by health consciousness. Besides, the ANN analysis results show that intention to use is the strongest predictor of IGAs use, while distress is the strongest predictor of intention to use IGAs. These findings not only provide a solid theoretical understanding of the factors of IGAs use but also have several managerial implications for hospitals and managers of IGAs to help them make effective decisions about using IGAs.

智能引导应用程序（IGAs）的出现对患者在医院内外使用医疗保健服务的体验产生了深远的影响。然而，IGAs的实施面临着挑战，包括普及程度和接受度低，以及不同地区医院的使用不平衡。与此同时，很少有研究调查iga使用的因素。为了促进患者对IGAs的使用，本研究侧重于确定患者使用IGAs的因素。开发了一个研究模型来检查这些因素，并根据求助模型阐明它们与iga使用的关系。我们通过两阶段的调查验证了我们的研究模型，并使用结构方程模型（SEM）和人工神经网络（ANN）等多分析方法分析了收集到的数据。扫描电镜分析结果表明，准确性、个性化、拟人化和开放性均显著影响患者通过痛苦使用iga的意愿和行为。自我隐藏不仅影响上述四个属性，还影响对IGAs的痛苦和态度。同时，健康意识调节了心理压力和对iga的态度对iga使用意向的影响。此外，人工神经网络分析结果表明，使用意向是使用iga的最强预测因子，而痛苦是使用iga的最强预测因子。这些发现不仅为IGAs使用的因素提供了坚实的理论理解，而且还为医院和IGAs管理人员提供了一些管理意义，以帮助他们做出关于使用IGAs的有效决策。

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引用次数: 0

Configuring trust in AI-augmented healthcare: The role of AI interpretability and data privacy in patient adoption of AI-assisted diagnosis 在人工智能增强医疗保健中配置信任：人工智能可解释性和数据隐私在患者采用人工智能辅助诊断中的作用

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-06-01 Epub Date: 2026-01-27 DOI: 10.1016/j.ijinfomgt.2026.103039

Xiangyu Bian , Yitong Chen , Aobo Yang

The integration of artificial intelligence (AI) into healthcare is transforming traditional patient-physician relationships, particularly in online healthcare platforms. This study investigates how patients integrate AI-assisted diagnosis into their healthcare decision-making alongside traditional physician consultation. Drawing on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Information Systems Success Model, an integrated theoretical framework is developed to examine how digital health literacy and digital service propensity influence AI-assisted diagnosis adoption through AI interpretability and perceived data privacy. A sequential mixed-methods approach combining qualitative interviews (n = 30) and quantitative survey data (n = 753) from Chinese online healthcare platform users is used to validate the proposed model and identify disease type as a significant contextual moderator. Findings reveal that AI interpretability and perceived data privacy are associated with mediating relationships between user characteristics and adoption intentions, with these relationships being significantly stronger in chronic disease contexts compared to acute conditions. This study advances theoretical understanding of healthcare AI adoption by integrating individual differences, system characteristics, and contextual factors into a comprehensive framework. Findings provide actionable insights for platform developers to implement context-specific design strategies, for healthcare providers to develop tailored AI introduction programs, and for policymakers to establish differentiated regulatory guidelines based on disease contexts. These contributions help bridge the "trust gap" in AI-assisted healthcare decision-making.

人工智能（AI）与医疗保健的整合正在改变传统的医患关系，特别是在在线医疗保健平台中。本研究调查了患者如何将人工智能辅助诊断与传统的医生咨询结合到他们的医疗保健决策中。利用技术接受和使用统一理论2 （UTAUT2）和信息系统成功模型，开发了一个综合理论框架，以研究数字健康素养和数字服务倾向如何通过人工智能可解释性和感知数据隐私影响人工智能辅助诊断的采用。采用顺序混合方法，结合中国在线医疗平台用户的定性访谈（n = 30）和定量调查数据（n = 753）来验证所提出的模型，并确定疾病类型是一个重要的语境调节因子。研究结果显示，人工智能的可解释性和感知到的数据隐私与用户特征和采用意图之间的中介关系相关，与急性疾病相比，慢性疾病背景下这些关系明显更强。本研究通过将个体差异、系统特征和背景因素整合到一个综合框架中，推进了对医疗保健人工智能采用的理论理解。研究结果为平台开发人员实施特定环境的设计策略，为医疗保健提供者开发量身定制的人工智能引入计划，以及为政策制定者根据疾病环境建立差异化的监管指南提供了可操作的见解。这些贡献有助于弥合人工智能辅助医疗保健决策中的“信任鸿沟”。

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引用次数: 0

The impact of enterprise and public social media use on guanxi formation and task performance 企业和公众使用社交媒体对关系形成和任务绩效的影响

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-06-01 Epub Date: 2026-01-13 DOI: 10.1016/j.ijinfomgt.2026.103030

Evelyn Ng , Robert M. Davison , Louie Wong , Barney Tan , Jingzhu Hong

This study examines the differential impacts of enterprise social media (ESM) and public social media (PSM) on guanxi formation and task performance in the Chinese workplace. Guanxi, a key cultural concept in Chinese society, encompasses interpersonal relationships that significantly influence organizational dynamics. Using a sample of 214 employees from a Guangzhou branch of a global logistics firm, we explored how ESM and PSM contribute to guanxi development, and how guanxi, in turn, affects extra-role behavior (ERB) and team identification, ultimately impacting task performance. The study found that ESM is more effective for work-related communications, fostering initial guanxi development, while PSM plays a crucial role in deepening social guanxi. These findings, further validated with analysis of a supplementary dataset comprised of 683 valid responses from employees of a China-based IT service provider, suggest that organizations should consider the distinct roles of ESM and PSM in workplace communication strategies, particularly in contexts where guanxi is pivotal. Furthermore, the research demonstrates that guanxi, developed through both enterprise and public social media interactions, plays an important role in fostering ERB and team identification, which collectively enhance task performance. The study offers theoretical contributions to the understanding of guanxi in digital environments and practical implications for managing social media use in Chinese organizations.

本研究考察了企业社交媒体（ESM）和公共社交媒体（PSM）对中国职场关系形成和任务绩效的差异影响。关系是中国社会的一个重要文化概念，它包含了对组织动态有重大影响的人际关系。我们以一家跨国物流公司广州分公司的214名员工为样本，探讨了ESM和PSM如何促进关系发展，以及关系如何反过来影响角色外行为（ERB）和团队认同，最终影响任务绩效。研究发现，ESM在与工作相关的沟通中更有效，有助于建立初步的关系，而PSM在加深社会关系方面起着至关重要的作用。通过对中国IT服务提供商员工的683份有效回复的补充数据集的分析，进一步验证了这些发现，表明组织应该考虑ESM和PSM在工作场所沟通策略中的不同角色，特别是在关系至关重要的情况下。此外，研究还表明，通过企业和公众社交媒体互动而形成的关系在促进ERB和团队认同方面发挥着重要作用，两者共同提升了任务绩效。该研究为理解数字环境中的关系提供了理论贡献，并为管理中国组织的社交媒体使用提供了实践意义。

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引用次数: 0

Knowledge workers’ trust and reception of generative AI’s advice in complex tasks 知识工作者在复杂任务中对生成式人工智能建议的信任和接受

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-06-01 Epub Date: 2026-01-12 DOI: 10.1016/j.ijinfomgt.2026.103031

Alireza Amrollahi , Jiaqi Yang , Syed Muhammad Fazal-e-Hasan , Basma Badreddine

Building on the prior literature that suggests knowledge workers are generally averse to algorithmic advice, this study explores the differences in reception of and trust in generative AI (GAI) advice compared to human advice, particularly among various reception groups engaged in complex and professional tasks, such as software development. Studies 1 and 2 explore preferences between human and GAI advice sources and assess the impact of users’ reception to GAI. The findings reveal that programmers appreciate GAI advice more than the equivalent advice from human experts. Furthermore, the reception type significantly influences advice-taking behaviour; programmers with a dominant reception of GAI exhibit greater acceptance, while those with an oppositional reception show less acceptance. In Study 3, we develop a nomological model through survey data to verify the complex relationships among technological innovativeness, various forms of trust in GAI, and advice-taking behaviour, noting variations among the different reception groups. We also conduct a complementary configurational analysis to examine how users’ trust in GAI is influenced by factors outside the main domain of study, such as task complexity, perceived security risks, and past exposure to GAI. Our research challenges the widely held belief of algorithm aversion among knowledge workers and contributes to information systems literature by highlighting the impact of the critical factors such as individual reception, past exposure, and innovativeness on knowledge workers’ advice-taking from GAI. Practically, it offers insights for organisations to develop human-centric GAI implementation strategies that embrace individual differences.

在先前的文献表明知识工作者普遍反对算法建议的基础上，本研究探讨了与人类建议相比，对生成式人工智能（GAI）建议的接受和信任的差异，特别是在从事复杂和专业任务（如软件开发）的各种接受群体中。研究1和2探讨了人类和GAI建议来源之间的偏好，并评估了用户接受GAI的影响。研究结果表明，程序员更欣赏GAI的建议，而不是来自人类专家的同等建议。此外，接受类型显著影响建议采纳行为；接受GAI的占主导地位的程序员表现出更高的接受度，而接受GAI的持反对意见的程序员则表现出更低的接受度。在研究3中，我们通过调查数据建立了一个规律模型，以验证技术创新、GAI中各种形式的信任和建议采纳行为之间的复杂关系，并注意到不同接受群体之间的差异。我们还进行了补充的配置分析，以检查用户对GAI的信任如何受到主要研究领域之外的因素的影响，例如任务复杂性、感知的安全风险和过去对GAI的暴露。我们的研究挑战了知识工作者对算法厌恶的普遍看法，并通过强调个人接受、过去接触和创新等关键因素对知识工作者从GAI中获得建议的影响，为信息系统文献做出了贡献。实际上，它为组织开发以人为中心的GAI实施策略提供了见解，这些策略包含了个体差异。

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引用次数: 0

Enhancing supply chain resilience: A fit mechanism between key core technology innovations and digital technology applications 增强供应链弹性：关键核心技术创新与数字技术应用的契合机制

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-06-01 Epub Date: 2026-01-31 DOI: 10.1016/j.ijinfomgt.2026.103040

Hui Sun , Yun Song , Ruiqiu Zhang

In the increasingly complex VUCA global environment, supply chain disruptions are becoming more frequent, making the enhancement of supply chain resilience a critical issue for both academia and practice. Grounded in the task-technology fit (TTF) theory and the fit-based perspective, this study empirically examines the impact of key core technology innovations on supply chain resilience, using a sample of 372 Chinese A-share listed companies from three industries over the period 2012–2023. This study explores the complementing fit and balancing fit mechanisms between key core technology innovations and digital technology applications, while also examining the mediating role of supply base concentration. The results indicate that: (1) Key core technology innovations have a significant positive impact on supply chain resilience. (2) The complementing fit shows that the digital technology application depth significantly strengthens the relationship between key core technology innovations and supply chain resilience, while the application breadth does not exhibit a significant moderating effect. (3) The balancing fit demonstrates a nonlinear impact: high balance maximizes resilience, early-stage imbalance can have compensatory effects, and severe imbalance weakens resilience. The negative impact of the “low key core technology innovations - high digital technology applications” combination is notable. (4) Supply base concentration mediates the relationship between the two fits and resilience, and fits help manage risks associated with high concentration. This study challenges the traditional “efficiency-resilience” paradox, extends TTF theory at the strategic level, and provides insights for firms seeking to build highly resilient supply chains through technological synergy.

在日益复杂的VUCA全球环境中，供应链中断变得越来越频繁，使供应链弹性的增强成为学术界和实践中的关键问题。本研究基于任务-技术契合度理论和契合度视角，以2012-2023年三个行业的372家中国a股上市公司为样本，实证检验了关键核心技术创新对供应链弹性的影响。本研究探讨了关键核心技术创新与数字技术应用之间的互补匹配和平衡匹配机制，并考察了供应基地集中度的中介作用。结果表明：(1)关键核心技术创新对供应链弹性具有显著的正向影响。(2)互补拟合表明，数字技术应用深度显著增强了关键核心技术创新与供应链弹性之间的关系，而应用广度不表现出显著的调节作用。(3)平衡拟合呈现非线性影响，高平衡最大化弹性，早期不平衡具有补偿作用，严重不平衡削弱弹性。“低核心技术创新-高数字技术应用”组合的负面影响是显著的。(4)供应基地集中度在两者契合度与弹性之间起中介作用，契合度有助于管理集中度高的风险。本研究挑战了传统的“效率-弹性”悖论，在战略层面扩展了TTF理论，并为寻求通过技术协同建立高弹性供应链的企业提供了见解。

{"title":"Enhancing supply chain resilience: A fit mechanism between key core technology innovations and digital technology applications","authors":"Hui Sun , Yun Song , Ruiqiu Zhang","doi":"10.1016/j.ijinfomgt.2026.103040","DOIUrl":"10.1016/j.ijinfomgt.2026.103040","url":null,"abstract":"<div><div>In the increasingly complex VUCA global environment, supply chain disruptions are becoming more frequent, making the enhancement of supply chain resilience a critical issue for both academia and practice. Grounded in the task-technology fit (TTF) theory and the fit-based perspective, this study empirically examines the impact of key core technology innovations on supply chain resilience, using a sample of 372 Chinese A-share listed companies from three industries over the period 2012–2023. This study explores the complementing fit and balancing fit mechanisms between key core technology innovations and digital technology applications, while also examining the mediating role of supply base concentration. The results indicate that: (1) Key core technology innovations have a significant positive impact on supply chain resilience. (2) The complementing fit shows that the digital technology application depth significantly strengthens the relationship between key core technology innovations and supply chain resilience, while the application breadth does not exhibit a significant moderating effect. (3) The balancing fit demonstrates a nonlinear impact: high balance maximizes resilience, early-stage imbalance can have compensatory effects, and severe imbalance weakens resilience. The negative impact of the “low key core technology innovations - high digital technology applications” combination is notable. (4) Supply base concentration mediates the relationship between the two fits and resilience, and fits help manage risks associated with high concentration. This study challenges the traditional “efficiency-resilience” paradox, extends TTF theory at the strategic level, and provides insights for firms seeking to build highly resilient supply chains through technological synergy.</div></div>","PeriodicalId":48422,"journal":{"name":"International Journal of Information Management","volume":"88 ","pages":"Article 103040"},"PeriodicalIF":27.0,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079444","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}

引用次数: 0

Artificial intelligence in healthcare IT: Enhancing work productivity through techno-eustress 医疗保健IT中的人工智能：通过技术压力提高工作效率

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-04-01 Epub Date: 2025-11-26 DOI: 10.1016/j.ijinfomgt.2025.103004

Shameem Shagirbasha , Naman Agarwal , Angelin Vilma G.

In a labor-intensive sector such as healthcare, the work productivity of frontline healthcare workers (FHWs) is crucial to reducing costs and managing patient volume. This study explores the affordances of Gen AI HITs that enhance FHWs’ work productivity and examines the mechanisms underlying this effect. A sequential mixed-methods design was employed for this study: qualitative interviews with 32 FHWs to identify the affordances that positively influence work productivity, followed by quantitative analyses using the PROCESS macro and structural equation modeling (SEM) to assess mediation by techno-eustress and moderation by job self-efficacy. The qualitative findings indicate that Gen AI HITs’ information, navigation, and interactivity affordances foster work productivity among FHWs, among other affordances identified. The quantitative results highlight that techno-eustress mediates the positive impact of Gen AI HITs’ interactivity and information affordances on FHWs’ work productivity, but not navigation affordance. However, when accounting for FHWs’ job self-efficacy, the mediation effect of techno-eustress becomes significant for all three affordances of Gen AI HIT – information, navigation, and interactivity. Specifically, the indirect positive impact of these affordances on productivity is stronger among FHWs with higher job self-efficacy. These results offer significant contributions to understanding the human–technology interaction in healthcare and provide practical insights for designing Gen AI HITs and training programs that improve adoption while enhancing work performance.

在医疗保健等劳动密集型行业，一线医疗工作者（FHWs）的工作效率对于降低成本和管理患者数量至关重要。本研究探讨了新一代人工智能HITs在提高fhw工作效率方面的优势，并研究了这种影响的潜在机制。本研究采用顺序混合方法设计：对32名外籍家庭佣工进行定性访谈，以确定对工作效率产生积极影响的支持，然后使用PROCESS宏观和结构方程模型（SEM）进行定量分析，以评估技术压力的中介作用和工作自我效能的调节作用。定性研究结果表明，Gen AI HITs的信息、导航和交互性能力提高了fhw的工作效率，以及其他已确定的能力。定量结果强调，技术压力介导了Gen AI HITs的交互性和信息能力对FHWs工作效率的积极影响，但不影响导航能力。然而，当考虑到FHWs的工作自我效能感时，技术压力对Gen AI HIT的信息、导航和交互性三种能力的中介作用都是显著的。具体而言，这些能力支持对工作效率的间接积极影响在工作自我效能感较高的外籍佣工中更为明显。这些结果为理解医疗保健领域的人机交互做出了重大贡献，并为设计Gen AI hit和培训计划提供了实际见解，从而在提高工作绩效的同时提高采用率。

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引用次数: 0

Artificial intelligence and career development: Concerns and insights from first-generation college students 人工智能与职业发展：来自第一代大学生的关注和见解

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-04-01 Epub Date: 2025-11-21 DOI: 10.1016/j.ijinfomgt.2025.103003

Xuefei (Nancy) Deng , Rui Sun

Artificial intelligence (AI) is disrupting workforce and posing an unprecedented threat of job displacement. However, our understanding of AI's role in shaping individual career development is limited. This study provides insights into AI and career development within the context of first-generation college students (FGCSs), a marginalized group that is arguably among the most vulnerable to the career disruption of AI. Employing mixed methods, this exploratory study examines the effects of FGCS status and career anchor on individual concerns about AI’s career impact and the perceptions of FGCSs and non-FGCSs regarding their career development. Using survey data from 70 students at a minority-serving public university in the United States, the quantitative analysis shows that FGCS status is positively associated with individual concern about AI’s career impact, whereas prior ChatGPT experience is negatively associated with this concern. However, we did not find evidence that a student’s career anchor affects their concerns about AI’s career impact. Meanwhile, the qualitative analysis revealed four themes that highlight employed FGCSs’ reliance on college education to change to a professional career or prepare for entrepreneurship. Our follow-up study revealed four types of individual attitudes toward AI’s career impact and suggested that the attitudes are influenced by generational status and career stage. We compare FGCSs and their peers in terms of career stage, career development and attitude toward AI’s impact and propose intervention strategies to help FGCSs mitigate AI-related job replacement risks. The study contributes to research on the AI impact on career development of a marginalized population.

人工智能（AI）正在颠覆劳动力市场，并带来前所未有的工作岗位流失威胁。然而，我们对人工智能在塑造个人职业发展中的作用的理解是有限的。这项研究提供了第一代大学生（FGCSs）背景下的人工智能和职业发展的见解，这是一个边缘化群体，可以说是最容易受到人工智能职业中断的影响。采用混合方法，本探索性研究考察了FGCS地位和职业锚对个人对人工智能职业影响的影响，以及FGCS和非FGCS对其职业发展的看法。通过对美国一所少数族裔公立大学70名学生的调查数据，定量分析表明，FGCS状态与个人对人工智能职业影响的担忧呈正相关，而之前的ChatGPT经历与这种担忧呈负相关。然而，我们没有发现证据表明学生的职业锚会影响他们对人工智能职业影响的担忧。与此同时，定性分析揭示了四个主题，突出了在职fgcs对大学教育的依赖，以转向专业职业或为创业做准备。我们的后续研究揭示了个人对人工智能职业影响的四种态度，并表明这种态度受到代际地位和职业阶段的影响。我们比较了fgcs和他们的同龄人在职业阶段、职业发展和对人工智能影响的态度方面的差异，并提出了干预策略来帮助fgcs减轻人工智能相关的工作替代风险。这项研究有助于研究人工智能对边缘人群职业发展的影响。

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引用次数: 0

Exploring information sharing intention of employees through privacy calculus perspective: A mixed-methods approach 基于隐私演算视角的员工信息共享意愿研究：一种混合方法研究

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-04-01 Epub Date: 2026-01-03 DOI: 10.1016/j.ijinfomgt.2025.103028

Abdul Khader V , Sreejith S S

The contemporary business world demands a high volume of data in each of its functional areas, including human resources. Despite the availability of various data extraction options, it is imperative to directly obtain information from employees for making decisions using human resources analytics. We primarily aim to investigate employees’ perspectives on voluntarily sharing their personal information through a respecified privacy calculus model (PCM) to ensure contextual validity and theoretical coherence. We conducted sequential exploratory mixed-methods research, consisting of two stages. The first stage involved qualitative interviews with 23 employees, while the second stage included quantitative survey data collected from 511 employees, aiming to gain a comprehensive understanding of employees’ perceptions of personal information sharing. In the first stage, we identified six influential themes using thematic analysis and developed a conceptual model based on the privacy calculus perspective. In the second stage, we used covariance-based structural equation modeling (CB-SEM) to analyze the survey data to validate the model. Findings confirmed the explanatory power of PCM and respecified it in the context of employee personal information sharing. We offer recommendations to organizations on how to collect and manage HR information, taking into account the perspectives of employees.

当代商业世界在每个功能领域都需要大量的数据，包括人力资源。尽管有各种数据提取选项，但必须直接从员工那里获取信息，以便使用人力资源分析做出决策。本研究的主要目的是通过一个重新定义的隐私演算模型（PCM）来研究员工自愿分享个人信息的观点，以确保语境的有效性和理论的连贯性。我们进行了顺序探索性混合方法研究，包括两个阶段。第一阶段对23名员工进行了定性访谈，第二阶段对511名员工进行了定量调查，旨在全面了解员工对个人信息共享的看法。在第一阶段，我们使用主题分析确定了六个有影响力的主题，并基于隐私微积分的视角建立了一个概念模型。在第二阶段，我们使用基于协方差的结构方程模型（CB-SEM）对调查数据进行分析，以验证模型。研究结果证实了PCM的解释力，并在员工个人信息共享的背景下重新定义了PCM。我们向组织提供关于如何收集和管理人力资源信息的建议，同时考虑到员工的观点。

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引用次数: 0

Gain or loss? The dual effects of dependence on AI on employee’s creativity 得还是失？依赖人工智能对员工创造力的双重影响

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-04-01 Epub Date: 2025-11-19 DOI: 10.1016/j.ijinfomgt.2025.103001

Su Cui , Longdong Wang , Weihang Cao , Tongqing Zhu

The distinct advantages of artificial intelligence (AI) in cognitive and creative projects have driven organizations to advocate for and implement AI, which has contributed to a deep and widespread dependence on AI among employees in creative generation. However, why, how, and when the dependence on AI influences employees’ creativity remains understudied. To figure out these issues, this research explored the double-edged effect of employee dependence on AI on their creativity, drawing on the job demands-resources model. Our mixed methods reveal that employee dependence on AI positively and indirectly affects their creativity via creative process engagement, while the indirect effect is stronger when employee cognitive flexibility is higher than lower. In contrast, employee dependence on AI negatively affects their creativity via information overload when cognitive flexibility is low. These findings have several theoretical and managerial implications related to AI-creativity research and practice.

人工智能（AI）在认知和创造性项目中的独特优势促使组织倡导和实施人工智能，这导致了创造性一代员工对人工智能的深刻而广泛的依赖。然而，对人工智能的依赖为何、如何以及何时影响员工的创造力，仍未得到充分研究。为了解决这些问题，本研究利用工作需求-资源模型，探讨了员工对人工智能的依赖对其创造力的双刃剑效应。我们的混合方法发现，员工对人工智能的依赖通过创造性过程投入正向和间接影响其创造力，而当员工认知灵活性高时，间接影响更强。相反，当认知灵活性较低时，员工对人工智能的依赖会通过信息过载对其创造力产生负面影响。这些发现对人工智能创造力的研究和实践具有若干理论和管理意义。

引用次数: 0

Why ride-hailing platform firms are reluctant to share data with governments: Evidence from China 为什么网约车平台公司不愿与政府分享数据：来自中国的证据

IF 27 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2026-04-01 Epub Date: 2025-12-19 DOI: 10.1016/j.ijinfomgt.2025.103019

Guoyin Jiang, Wanqiang Yang, Xingshun Cai

Data sharing between the public and private sectors, such as ride-hailing platform (RHP) firms and the government, aims to generate value. However, the reasons behind the intentions of RHP firms to share data with public entities remain unclear. In this research, a business-to-government (B2G) information-sharing framework is employed, and a mixed study combining structural equation modeling (SEM), with a sample size of 426 and fuzzy-set qualitative comparative analysis (fsQCA), with a sample size of 82 is conducted. The same variables are adopted and assessed through different methods, providing complementary insights into how information and technology, organizational and managerial dynamics, and political and policy considerations affect the intentions of RHP firms to share data with the government. The results of SEM analysis show government-led initiatives related to data infrastructure, data management improvement, robust systems for data security, administrative penalties, and strong government–business political connections collectively decrease the reluctance to share data (RSD) among RHP firms. The platform power (PP) level of RHP firms influences B2G data sharing to varying degrees. The fsQCA analysis identifies four configurations linked to the RSD of RHP firms, and their combinations result in the same outcome. Heterogeneity analysis further yields variations in configurations of reluctance across different PP levels. This research has important implications for governments seeking to address firm reluctance and promote sustainable B2G data-sharing practices.

公共和私营部门之间的数据共享，如叫车平台（RHP）公司和政府之间的数据共享，旨在创造价值。然而，RHP公司与公共实体共享数据的意图背后的原因尚不清楚。本研究采用企业对政府（B2G）信息共享框架，采用结构方程模型（SEM）和模糊集定性比较分析（fsQCA）相结合的混合研究，样本量为426个，样本量为82个。采用相同的变量，并通过不同的方法进行评估，从而对信息和技术、组织和管理动态以及政治和政策考虑因素如何影响RHP公司与政府共享数据的意图提供互补的见解。SEM分析的结果显示，政府主导的与数据基础设施、数据管理改进、强健的数据安全系统、行政处罚以及强大的政府-企业政治关系相关的举措，共同降低了RHP公司之间共享数据的意愿（RSD）。RHP企业的平台权力水平对B2G数据共享有不同程度的影响。fsQCA分析确定了与RHP公司的RSD相关的四种配置，它们的组合导致相同的结果。异质性分析进一步得出了不同PP水平的磁阻构型的变化。这项研究对寻求解决企业不情愿和促进可持续B2G数据共享实践的政府具有重要意义。

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引用次数: 0