International Journal of Information Management最新文献_第10页

Exploring the role of information systems-induced depletion, boreout syndrome, social media use on quiet quitting among digital cohorts 探索信息系统导致的耗竭、无聊综合症、社交媒体使用在数字人群中安静戒烟的作用

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-05-05 DOI: 10.1016/j.ijinfomgt.2025.102911

A. Mohammed Abubakar , Ömer Turunç , Mohammad Soliman , Alexandre Sukhov

This research explores the socio-technical factors behind employees’ quiet quitting by investigating how social factors (boreout syndrome and digital cohorts) and technical factors (IS-induced depletion and social media usage) interact to encourage this behavior. A two-wave design across two independent studies was used with an expanded analytical approach. Study 1 used a symmetric variable-based analysis to identify IS-induced depletion, boreout, low social media usage, and digital immigrant status as key predictors of quiet quitting. In Study 2, boreout, social media usage, and digital immigrant status emerged as significant predictors. An asymmetric case-based analysis further demonstrated that quiet quitting results from combinations of conditions: in Study 1, IS-induced depletion and boreout were prevalent among digital immigrants with low social media usage. Similarly, in Study 2, IS-induced depletion and boreout occurred among digital natives or individuals with low social media usage. Contrary to the assumption that digital natives are more prone to quiet quitting, the findings indicate that digital immigrants are, in fact, more susceptible to this behavior when exposed to these stressors.

本研究通过调查社会因素（无聊综合症和数字队列）和技术因素（is诱导的耗竭和社交媒体使用）如何相互作用来鼓励员工的这种行为，探讨了员工安静辞职背后的社会技术因素。两项独立研究采用两波设计，并采用扩展分析方法。研究1使用对称的基于变量的分析来确定is引起的耗竭、无聊、低社交媒体使用率和数字移民身份是安静戒烟的关键预测因素。在研究2中，无聊、社交媒体使用和数字移民身份成为重要的预测因素。一项不对称的基于案例的分析进一步表明，安静的戒烟是多种条件组合的结果：在研究1中，在社交媒体使用率较低的数字移民中，is引起的枯竭和厌倦很普遍。同样，在研究2中，is引起的耗竭和厌倦发生在数字原生代或社交媒体使用率较低的个体中。与数字原生代更倾向于安静戒烟的假设相反，研究结果表明，事实上，当暴露于这些压力源时，数字移民更容易产生这种行为。

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引用次数: 0

Designing AI to elicit positive word-of-mouth in service recovery: The role of stress, anthropomorphism, and personal resources 设计人工智能以在服务恢复中获得积极的口碑：压力、拟人化和个人资源的作用

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-05-05 DOI: 10.1016/j.ijinfomgt.2025.102916

Byron W. Keating , Rory Mulcahy , Aimee Riedel , Amanda Beatson , Kate Letheren

Service organizations are increasingly deploying generative AI (GenAI) chatbots to handle service failures, yet there is a critical gap in understanding how anthropomorphic AI design can improve service recovery outcomes. This study addresses that gap by investigating whether making AI agents more human-like can mitigate customers’ stress during service recovery and foster positive word-of-mouth (PWOM). Grounded in the Transactional Model of Stress and Coping, we propose that anthropomorphic cues in AI interactions reduce customers’ stress appraisals of service failures. A multi-study experimental design was employed, including a pilot study and three scenario-based experiments that manipulated AI anthropomorphism and service failure severity. The results show that anthropomorphized AI significantly lowers customer stress levels and, in turn, increases PWOM, with stress appraisals mediating the relationship between AI anthropomorphism and positive word-of-mouth. Notably, these benefits emerged mainly for low-severity service failures, and the stress-reduction effect of an anthropomorphic AI agent was most pronounced for customers with limited personal coping resources. These findings provide actionable insights for service managers and AI designers: incorporating human-like warmth and competence into AI service agents can enhance recovery experiences by alleviating customer stress, thereby encouraging PWOM and improving overall service recovery effectiveness.

服务组织越来越多地部署生成式人工智能（GenAI）聊天机器人来处理服务故障，但在理解拟人化人工智能设计如何改善服务恢复结果方面存在关键差距。本研究通过调查使人工智能代理更像人类是否可以减轻客户在服务恢复期间的压力并促进积极的口碑（pom）来解决这一差距。基于压力和应对的交易模型，我们提出人工智能交互中的拟人化提示可以降低客户对服务失败的压力评估。采用多研究实验设计，包括一个先导研究和三个基于场景的实验，操纵人工智能拟人化和服务故障严重程度。结果表明，人格化人工智能显著降低了客户压力水平，进而增加了pom，压力评估中介了人工智能人格化与积极口碑之间的关系。值得注意的是，这些好处主要出现在低严重性的服务故障中，拟人化人工智能代理的减压效果对于个人应对资源有限的客户最为明显。这些发现为服务经理和人工智能设计师提供了可操作的见解：将人类的温暖和能力融入人工智能服务代理中，可以通过减轻客户压力来增强恢复体验，从而鼓励poms并提高整体服务恢复效率。

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引用次数: 0

Towards explaining the effects of the human-technology dynamic on human agency in digital transformations 解释人-技术动态对数字化转型中人的能动性的影响

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-30 DOI: 10.1016/j.ijinfomgt.2025.102915

Mohsin Malik , Amir Andargoli , Kerem Pala , Guilherme Luz Tortorella

The extant theorising of digital transformation has seldom focused on the human agency and how the human agency is affected by the dynamic of human-technology that entails social conflicts. To address this, we provide a complementary explanation of digital transformations grounded in socio-cognitive and role theories. We suggest that employees’ cognitions and behaviours influence digital transformations, but this relationship is dampened by conflicts arising from the dynamic of human-technology. Survey data from 256 participants involved in digital transformations in Australia was used to test the suggested relationships. The statistical findings confirm that employees’ cognitive trust is the driving mechanism that affects digital transformation both directly and indirectly through the innovative behaviour of employees. Role conflict was found to weaken the relationships between trust and innovative behaviour and trust and digital transformation. The empirical validation of the integrative socio-cognitive and role theorising of digital transformations—highlighting the potential social conflicts arising from the human technology interactions—has important theoretical and managerial implications for the strategic decision-making governing digital transformations.

现有的数字化转型理论很少关注人的能动性，以及人的能动性如何受到涉及社会冲突的人类技术动态的影响。为了解决这个问题，我们提供了一个基于社会认知和角色理论的数字转型的补充解释。我们认为，员工的认知和行为影响数字化转型，但这种关系被人与技术动态所产生的冲突所抑制。来自澳大利亚参与数字化转型的256名参与者的调查数据被用来测试所建议的关系。统计结果证实，员工的认知信任是通过员工创新行为直接或间接影响数字化转型的驱动机制。角色冲突削弱了信任与创新行为、信任与数字化转型之间的关系。数字化转型的综合社会认知和角色理论化的实证验证——突出了人类技术互动产生的潜在社会冲突——对数字化转型的战略决策具有重要的理论和管理意义。

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引用次数: 0

Workplace cyberbullying: A multidisciplinary review and agenda for future research in the era of artificial intelligence 工作场所网络欺凌：人工智能时代的多学科回顾和未来研究议程

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-26 DOI: 10.1016/j.ijinfomgt.2025.102910

Jie Yan , Dorothy E. Leidner , Puzant Balozian , Villacis Calderon Eduardo , Ramona Ionescu

Workplace cyberbullying (WCB) is a pervasive issue that adversely impacts individuals and organizations, fueled by technological advancements and the ubiquity of digital communication tools. This study conducts a multidisciplinary review of existing WCB research. By analyzing 83 articles, we synthesized key themes, including the attributes of WCB, its technological enablers, emotional drivers, environmental factors, and organizational control mechanisms. We highlight gaps in detecting, preventing, and addressing WCB, with a particular emphasis on leveraging artificial intelligence (AI) technologies. We propose a research agenda exploring how AI can mitigate WCB through multimodal detection, emotional intervention mechanisms, and pattern recognition. Our study underscores the importance of interdisciplinary approaches in addressing WCB and offers actionable insights for future research and organizational practices, aiming to enhance employee well-being and workplace culture.

工作场所网络欺凌（WCB）是一个普遍存在的问题，对个人和组织产生了不利影响，这是由技术进步和无处不在的数字通信工具推动的。本研究对现有的WCB研究进行了多学科综述。通过对83篇文章的分析，我们综合了WCB的属性、技术驱动因素、情感驱动因素、环境因素和组织控制机制等关键主题。我们强调在检测、预防和解决WCB方面的差距，特别强调利用人工智能（AI）技术。我们提出了一个研究议程，探讨人工智能如何通过多模态检测、情绪干预机制和模式识别来减轻WCB。我们的研究强调了跨学科方法在解决WCB问题中的重要性，并为未来的研究和组织实践提供了可操作的见解，旨在提高员工幸福感和工作场所文化。

引用次数: 0

Managing online small-group learning: Effects of facilitation style and type of group reward 管理在线小组学习：促进方式和小组奖励类型的影响

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-18 DOI: 10.1016/j.ijinfomgt.2025.102909

Ron Chi-Wai Kwok , Surinder S. Kahai , Jin-Xing Hao

The theory of community of inquiry (COI) is widely used to explain students’ experiences in online learning. However, it is rarely used to develop structured, evidence-based teaching strategies for managing communities of inquiry. To extend COI theory, this study proposes a dual-element construct of teaching presence and a problem-driven online small-group learning model. The study aims to understand the effects of teaching presence (combining facilitation and group reward) on social presence (peer interactions) and cognitive presence (cognitive learning outcomes). It incorporates leadership style in facilitation (transformational vs. transactional) and individual accountability in group reward to define strategies for the dual-element approach to teaching presence. A controlled experiment with a 2 × 2 factorial design was conducted on a text-based platform to observe the effects of facilitation style and individual accountability in group reward. Results showed that both the transformational (vs. transactional) facilitation style and individual accountability in group reward promoted peer interaction and cognitive learning outcomes. They also interacted positively to enhance peer interaction and cognitive learning outcomes. The nuanced effects of the different elements of the dual-element approach to teaching presence are discussed, along with theoretical and practical implications.

探究共同体（COI）理论被广泛用于解释学生的在线学习体验。然而，它很少用于开发结构化的、基于证据的教学策略来管理探究社区。为了扩展COI理论，本研究提出了教学存在的双要素建构和问题驱动的在线小组学习模型。本研究旨在了解教学在场（结合促进和群体奖励）对社会在场（同伴互动）和认知在场（认知学习结果）的影响。它结合了促进中的领导风格（转型与交易）和团体奖励中的个人责任，以定义双要素教学存在方法的策略。采用2 × 2因子设计，在基于文本的平台上进行对照实验，观察诱导方式和个人问责制对群体奖励的影响。结果表明，群体奖励中的转换型（相对于交易型）促进方式和个人问责制均促进同伴互动和认知学习结果。他们还积极互动，以加强同伴互动和认知学习成果。本文讨论了双要素教学存在的不同要素的微妙影响，以及理论和实践意义。

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引用次数: 0

Dynamics of user engagement: AI mastery goal and the paradox mindset in AI–employee collaboration 用户参与的动态：人工智能掌握目标和人工智能员工协作中的悖论心态

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-14 DOI: 10.1016/j.ijinfomgt.2025.102908

Reza Marvi , Pantea Foroudi , Naja AmirDadbar

Given the scarcity of previous studies on employee–AI collaboration and its impact on employee behavior and user engagement, we investigated its potential to drive user engagement using a mixed-method approach. Grounded in qualitative findings from 27 participants in a healthcare setting, we propose a robust model that emphasizes the impact of AI–employee collaboration on AI mastery goal, user engagement, and a paradox mindset, as well as the moderating role of AI empathy and technological frames. Using a quantitative method, we collected data from 452 participants in a healthcare setting across two studies. Our findings showed that AI–employee collaboration can drive AI mastery goal and a paradox mindset. We also found empirical evidence that both AI mastery goal and the paradox mindset can mediate the relationship between employee–AI collaboration and user engagement. Moreover, our findings revealed interesting moderating results across two studies. In Study 1, significant effects were found for both employee–AI collaboration and AI mastery goal at low AI empathy, but not at high levels. In Study 2, while the interaction between employee–AI collaboration and AI empathy was not significant, the influence of AI mastery goal became significant at high empathy levels, and the paradox mindset showed a significant effect only at high levels of AI empathy. These findings provide managers with valuable insights into the essential operations dynamic of employee–AI collaboration, underscoring its important role in enhancing user engagement.

鉴于之前关于员工与人工智能协作及其对员工行为和用户参与度影响的研究缺乏，我们使用混合方法研究了其推动用户参与度的潜力。基于医疗保健环境中27名参与者的定性研究结果，我们提出了一个强大的模型，强调人工智能员工协作对人工智能掌握目标、用户参与度和悖论心态的影响，以及人工智能移情和技术框架的调节作用。使用定量方法，我们收集了两项研究中来自医疗保健机构的452名参与者的数据。我们的研究结果表明，人工智能员工协作可以推动人工智能掌握目标和悖论心态。我们还发现经验证据表明，人工智能精通目标和悖论心态都可以调节员工-人工智能协作和用户参与度之间的关系。此外，我们的发现在两项研究中揭示了有趣的调节结果。在研究1中，低人工智能同理心对员工-人工智能协作和人工智能掌握目标都有显著影响，而高人工智能同理心对员工-人工智能协作和人工智能掌握目标没有显著影响。在研究2中，员工-人工智能协作与人工智能共情的交互作用不显著，而人工智能掌握目标的影响在高共情水平下变得显著，悖论心态仅在高共情水平下才有显著影响。这些发现为管理人员提供了有关员工与人工智能协作的基本运营动态的宝贵见解，强调了其在提高用户参与度方面的重要作用。

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引用次数: 0

Navigating remote host management and strategic information disclosure in Airbnb: A dual-theory perspective Airbnb的远程主机管理与战略信息披露：双重理论视角

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-09 DOI: 10.1016/j.ijinfomgt.2025.102906

Long Xia

Airbnb, a prominent sharing economy platform, has experienced significant global expansion, offering lucrative investment opportunities irrespective of investors' geographical locations. Despite the rising trend of using Airbnb for remote investments, this phenomenon has received limited research attention. This study employs a dual-theory lens, integrating social exchange and social penetration theories, to propose a unified theoretical framework for examining the dynamics of remote host management and information disclosure. Using a mixed-method approach—combining deep learning-based text classification to extract nuanced information aspects from host self-disclosures and econometric modeling on an extensive panel dataset—we reveal that while remote management exhibits lower performance than locally managed counterparts, strategic information disclosure can effectively mitigate such impacts. As a groundbreaking exploration of remote host management, this study contributes theoretically to the sharing economy, social exchange and social penetration theories, and information disclosure literature, while providing practical implications to support remote management and strategic information disclosure decision-making.

著名的共享经济平台Airbnb经历了重大的全球扩张，无论投资者的地理位置如何，都能提供利润丰厚的投资机会。尽管使用Airbnb进行远程投资的趋势正在上升，但这一现象得到的研究关注有限。本研究采用双理论视角，整合社会交换理论和社会渗透理论，提出了一个统一的理论框架来考察远程主机管理和信息披露的动态。使用混合方法方法-结合基于深度学习的文本分类从主机自我披露和广泛面板数据上的计量经济建模中提取细微信息方面-我们发现，尽管远程管理表现出比本地管理的同行更低的性能，但战略信息披露可以有效减轻这种影响。作为远程主机管理的开创性探索，本研究在理论上为共享经济、社会交换与社会渗透理论、信息披露文献提供了理论支持，同时为远程管理和战略性信息披露决策提供了实践意义。

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引用次数: 0

Agenda-setting effects for covid-19 vaccination: Insights from 10 million textual data from social media and news articles using BERTopic covid-19疫苗接种的议程设置效应：来自社交媒体和新闻文章的1000万文本数据的见解

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-07 DOI: 10.1016/j.ijinfomgt.2025.102907

Hyunsang Son , Young Eun Park

This study investigates the agenda-setting effects of media in the context of the COVID-19 vaccination by leveraging a cutting-edge machine learning framework, BERTopic, to analyze over 10 million textual data points from social media and news articles. The research highlights a significant divergence between public opinion, primarily expressed on Twitter, and the media agenda, challenging traditional agenda-setting theories in public health crises. Specifically, while public discourse centered on vaccination-related concerns and negative sentiments toward vaccination policies, media coverage diversified to include topics such as politics, foreign affairs, and economics. The proposed framework systematically integrates data collection, preprocessing, and advanced topic modeling to enhance interpretability and efficiency. By adopting BERTopic, this study advances beyond traditional Latent Dirichlet Allocation (LDA) models by offering superior clustering and contextual understanding of unstructured text data. The framework demonstrates its utility in identifying actionable insights for public health practitioners, policymakers, and information systems researchers, providing a robust methodology to track and evaluate public sentiment and media narratives during health crises. Ultimately, this study emphasizes the critical need to align media messaging with public concerns to improve vaccination campaigns and public health communication. It contributes to the theoretical understanding of agenda-setting in the digital era while offering practical guidelines for leveraging social big data in multidisciplinary applications.

本研究通过利用尖端机器学习框架BERTopic分析来自社交媒体和新闻文章的1000多万文本数据点，调查了媒体在COVID-19疫苗接种背景下的议程设置效果。该研究强调了主要在Twitter上表达的公众舆论与媒体议程之间的重大分歧，挑战了公共卫生危机中传统的议程设置理论。具体而言，公众话语集中在疫苗接种相关的担忧和对疫苗接种政策的负面情绪上，而媒体报道则多样化，包括政治、外交和经济等话题。该框架系统地集成了数据收集、预处理和高级主题建模，以提高可解释性和效率。通过采用BERTopic，本研究超越了传统的潜在狄利克雷分配（Latent Dirichlet Allocation， LDA）模型，对非结构化文本数据提供了优越的聚类和上下文理解。该框架证明了其在为公共卫生从业人员、政策制定者和信息系统研究人员确定可操作的见解方面的效用，并提供了一种可靠的方法来跟踪和评估卫生危机期间的公众情绪和媒体叙述。最后，本研究强调，迫切需要将媒体信息与公众关注的问题结合起来，以改善疫苗接种运动和公共卫生沟通。它有助于从理论上理解数字时代的议程设置，并为在多学科应用中利用社会大数据提供实践指导。

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引用次数: 0

The dark side of employee-generative AI collaboration in the workplace: An investigation on work alienation and employee expediency 工作场所员工生成人工智能协作的阴暗面：对工作异化和员工权宜之计的调查

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-04-03 DOI: 10.1016/j.ijinfomgt.2025.102905

Shenyang Hai , Tianyi Long , Andreawan Honora , Arnold Japutra , Tengfei Guo

Generative AI (GenAI) has emerged as a powerful tool in the modern workplace, delivering significant benefits to both employees and organizations. As its adoption gains momentum, understanding the potential risks associated with employee-GenAI collaboration becomes increasingly important. While much of the existing research emphasizes the challenges GenAI presents to employees as individuals, this study shifts the focus to explore broader organizational risks, particularly unethical workplace behaviors. Drawing on human-AI collaboration research and the job demands-resources model, we develop and empirically test a novel model to explain how and when employee-GenAI collaboration may lead to employees’ unethical behavioral outcomes in daily organizational contexts. Using an experience sampling approach with longitudinal data from 229 service industry employees, encompassing 1050 matched daily observations, our findings reveal that employee-GenAI collaboration increases work alienation—a sense of disconnection from work—which, in turn, drives employee expediency that compromises work standards. Furthermore, we demonstrate that this effect is pronounced under high digital job demands. By highlighting this unintended consequence, our study contributes to theoretical advancements in understanding the darker side of employee-GenAI collaboration and provides practical insights to help organizations harness the benefits of GenAI while mitigating its potential ethical pitfalls.

生成式人工智能（GenAI）已经成为现代工作场所的强大工具，为员工和组织带来了巨大的好处。随着采用势头的增强，理解与员工- genai协作相关的潜在风险变得越来越重要。虽然现有的许多研究都强调GenAI给员工个人带来的挑战，但这项研究将重点转移到探索更广泛的组织风险，特别是不道德的工作场所行为。利用人类-人工智能协作研究和工作需求-资源模型，我们开发并实证测试了一个新模型，以解释员工-人工智能协作在日常组织环境中如何以及何时可能导致员工的不道德行为结果。通过对229名服务行业员工的纵向数据进行经验抽样，包括1050个匹配的日常观察，我们的研究结果表明，员工与员工之间的协作增加了工作疏离感——一种与工作脱节的感觉——这反过来又会推动员工的权宜之计，从而损害工作标准。此外，我们证明了这种效应在高数字工作要求下是明显的。通过强调这种意想不到的后果，我们的研究有助于在理解员工与GenAI合作的阴暗面方面取得理论进步，并提供实用的见解，帮助组织利用GenAI的好处，同时减轻其潜在的道德陷阱。

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引用次数: 0

How livestream engagement inspires tourist purchasing behaviour: A multi-study approach 直播互动如何激发游客购买行为：一种多研究方法

IF 20.1 1区管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

International Journal of Information Management

Pub Date : 2025-03-31 DOI: 10.1016/j.ijinfomgt.2025.102903

Hamed Azad Moghddam , Gary Mortimer , Hormoz Ahmadi , Hamid Sharif-Nia

In the rapidly evolving digital landscape, livestream commerce has become a powerful tool for tourism providers. This study underscores the pressing need for businesses within the tourism sector to understand the nuances of this dynamic medium and align their marketing strategies accordingly. In responding to calls, this research utilises a rigorous mixed-methods approach to examine the interactions between streamers, viewers, and the broader online community. Inspiration theory and optimum stimulation level theory are applied in a tourism context to examine how livestream viewers’ individual differences influence their inspiration for impulse buying and cross-buying. Further, sociomateriality is adopted to examine how the interconnectedness of livestreaming has an impact on inspiration and behaviours. Findings from in-depth interviews and an online survey of social media users who had livestreaming commerce experience indicate that impulse buying and cross-buying are driven by antecedents such as two-way communications between streamers and individuals and online communities and individuals, as well as the perception of inspiration. These relationships are moderated by the optimum stimulation level. This study offers directions for further research and insights for managers, suggesting a focus on the dynamics of livestream commerce.

在快速发展的数字环境中，直播商务已成为旅游提供商的强大工具。这项研究强调了旅游业企业迫切需要了解这一动态媒体的细微差别，并相应地调整其营销策略。为了回应这些呼吁，这项研究采用了一种严格的混合方法来研究主播、观众和更广泛的在线社区之间的互动。运用激励理论和最优刺激水平理论，以旅游为研究对象，考察了直播观众的个体差异如何影响其冲动购买和交叉购买的激励。此外，采用社会物质性来研究直播的互联性如何影响灵感和行为。深度访谈和对有直播商业经验的社交媒体用户的在线调查结果表明，冲动购买和交叉购买是由前因驱动的，例如主播与个人、在线社区与个人之间的双向交流，以及对灵感的感知。这些关系受到最佳刺激水平的调节。该研究为管理者提供了进一步研究和见解的方向，建议关注直播商业的动态。

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引用次数: 0