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This study aims to investigate the causal relationships within an experimental culture of improvisation capability and firm performance, following the logic of “culture-capability-performance” and building on informal institution theory and dynamic capability theory.

Data was mainly collected via on-site questionnaires from firm managers, and 196 valid questionnaires were analyzed using structural equation modeling to test the relationship among experimental culture, improvisation capability and firms’ performance.

Trust and support had a positive impact on firm spontaneity, while the effect of action promotion and error tolerance was not significant. Action promotion, trust and support demonstrate substantial positive effects on the creativity of a firm. Both dimensions of improvisation capability positively and significantly influence a firm’s performance.

The research respondents were firm managers. Cross-sectional data were used to analyze the model, which may cause common method variance. The research context was limited to China, and the generalizability of the results needs to be considered.

Firms can cultivate a culture of trust and support to enhance their spontaneity and improvisation capability. They can encourage cross-departmental communication, empower employees with autonomy in decision-making, provide appropriate resource support for employees’ decisions and use praise and reward incentives to spur further innovation achievements.

This study addresses the gaps in a firm’s improvisation capability within a Chinese market context by theoretically and empirically examining the role of experimental culture and assessing the relationship among each of the dimensions of improvisation capability in relation to firm performance identified in this study.

The purpose of this paper is to build theory concerning the role of discourse in strategic renewal and green knowledge management.

The approach entails an application of discourse theory to the strategy process literature, a review of the knowledge management (KM) literature and examination of examples in the context of organizations' sustainability initiatives.

A discourse-based model of green knowledge management, with associated research propositions that address each element of strategy renewal, is developed.

The model and propositions in this paper may help to spur future management research that draws on a variety of discourse analytic tools, and advances our understanding of KM focused on environmental sustainability.

A discursive perspective on green knowledge management allows for a broader and more dynamic view of strategy process. This paper foregrounds the dynamic nature of strategy process in exploring the nature of discourse, and suggests that green knowledge management addresses a key megatrend that may form a foundation for strategic renewal.

Existing research on collaborative innovation mechanisms from the perspective of global operation is very limited. This paper aims to address the research gap by studying the factors influencing globally distributed teams’ innovation performance, especially how effective knowledge sharing between distributed teams promotes collaborative team innovation.

This research proposes a model to investigate how collaborative knowledge sharing affects global operations [team dispersion, task orientation, information and communication technology (ICT) usage] and innovation performance based on the data collected from 167 managers in 40 local Chinese IT and offshoring firms. Using the theory of Cognitive Diversity and Innovation Diffusion and Synergy, separate hierarchical regression analysis was used to test the proposed model.

The findings of this study demonstrate that effective collaborative knowledge sharing plays a crucial role in enhancing innovation performance in a global operation. Specifically, innovation capacity can be improved by task orientation, ICT usage and team dispersion.

This research study contributes to the development of global distributed operations and innovation among distributed teams in multinational corporations.

This paper aims to investigate investors' willingness to use robo-advisors from customers' perspectives and analyzes the factors that drive them to use robo-advisors, including perceived usefulness and emotional response.

The authors extend the Cognition-Affect-Conation (CAC) framework to the behavioral domain of robo-advisor users on financial technology platforms and conduct an empirical study based on 248 valid questionnaires.

The authors find two types of factors driving the willingness to use robo-advisors: perceived usefulness, trust and perceived risk as external driving forces and investor sentiment as an internal driving force. Trust has a significant positive effect on willingness to use, and arousal in emotional response plays a mediating role between perceived usefulness and willingness to use.

This research provides valuable insights for financial institutions to engage in robo-advisor innovation from customers' perspectives.

This study aims to provide a comprehensive analysis of the current privacy concerns in the tourism industry by uncovering the key factors leading to such concerns (i.e. smart public services, cyber security issues, consumer behaviour and governance). Using papers from multiple sources, the relationship between technology advancements and tourist’s privacy concerns has been established.

This study adopted a machine learning-based systematic literature review approach to find out the clusters. The study analysed 68 papers using the topic modelling approach. A four-cluster solution was considered to be most representative of the extant literature identified using bibliographic coupling. Finally, content analysis of the selected literature has been performed.

This study identified four factors majorly leading to privacy concerns amid increasing technological advancements. Moreover, these factors were found to have a dyadic relationship with technological advancements. To everyone’s amazement, sustainable tourism was also found to have led to privacy concerns among tourists along with a lack of governance and cyber security issues. Furthermore, cluster-wise future research directions are provided based on the content analysis.

This study contributes to the literature by systematically reviewing and identifying the four dimensions leading to privacy concerns. To the best of the authors’ knowledge, the study done is the only attempt to synthesize the extant literature on tourists’ privacy concerns using an unbiased scientific approach.

本研究对旅游业当前的隐私问题进行了全面分析, 以揭示导致此类担忧的关键因素（即智能公共服务、网络安全问题、消费者行为和治理）。 通过考察来自多方渠道的现有文献, 本研究确立了技术进步与游客隐私问题之间的关系。

本研究采用基于机器学习的系统文献综述方法来找出聚类。 该研究使用主题建模方法分析了 68 篇文章。四聚类解决方案是现有文献中最具代表的 文献分类方法。最后, 本研究对所选文献进行了内容分析。

这项研究确定了在技术进步不断增加的情况下主要导致隐私问题的四个因素。 此外, 这些因素被发现与技术进步有二元关系。 本研究还发现可持续旅游业引发了游客对隐私的担忧以及缺乏治理和网络安全问题。 此外, 通过基于内容的分析, 本研究提供了未来的聚类研究方向。

本研究对现有文献的贡献在于通过系统地文献综述和分析以确定导致隐私问题的四个维度。该研究是基于公正的科学方法综合现有游客隐私问题文献的首度尝试。

Este estudio proporciona un análisis exhaustivo de la actual preocupación por la privacidad en el sector turístico, poniendo al descubierto los factores clave que la generan (los servicios públicos inteligentes, los problemas de ciberseguridad, el comportamiento de los consumidores y la gobernanza). Gracias al uso de artículos de múltiples fuentes, se ha establecido la relación entre los avances tecnológicos y la preocupación de los turistas por la privacidad.

Este estudio adoptó un enfoque de revisión sistemática de la literatura basado en el aprendizaje automático para descubrir los conglomerados. El estudio analizó sesenta y ocho artículos utilizando el enfoque de modelización de temas. Se consideró que una solución de cuatro conglomerados era la más representativa de la literatura existente identificada mediante el acoplamiento bibliográfico. Por último, se realizó un análisis de contenido de la bibliografía seleccionada.

En este estudio se identificaron cuatro factores principales que suscitan inquietud por la privacidad en medio de los crecientes avances tecnológicos. Además, se descubrió que estos factores tienen una relación diádica con dichos avances. Para sorpresa de todos, se halló que el turismo sostenible, junto con la falta de gobernanza y los problemas de ciberseguridad, también suscitan entre los turistas preocupaciones por su privacidad. Finalmente, el análisis de contenido ofrece orientaciones para futuras investigaciones.

Este estudio contribuye a la literatura haciendo una revisión sistemática e identificando las cuatro dimensiones que conducen a la preocupación por la privacidad. Este estudio es el único intento de sintetizar la bibliografía existente sobre la preocupación de los turistas por su privacidad utilizando un enfoque científico imparcial.

While the idea of the resilience of information systems security exists, there is a lack of research that conceptualizes, defines and specifies a way to measure it as a dynamic capability. Drawing on relevant cybersecurity and dynamic capabilities literature, this study aims to define Information Systems Security Resilience (ISSR) as a “dynamic capability of a firm to respond to, and recover from, a security attack” and test it as a new construct.

The authors employ a methodology including multiple phases to develop and test this construct of ISSR. The authors first interview senior managers from various organizations to establish the face validity of the construct; then develop and analyze a pilot survey for internal validity and reliability; and finally, design and deploy a field survey to test and externally validate the construct.

The authors conceptualize and define the construct of ISSR as a dynamic capability, develop a scale for its measurement and test it in a pilot and field survey. The construct is valid, and the measurement tool works. It demonstrates that resilience is something that is done, rather than had. As a capability, organizations need to track and measure ISSR, which is what this tool provides the ability to do.

This research contributes to the information systems and cybersecurity literature and offers valuable insights for organizations to manage their security effectively.

Sharing knowledge of physicians in hospitals is critical and significant in terms of providing better healthcare services. Despite the significance of knowledge sharing in the healthcare setting, very few studies have empirically investigated knowledge sharing drivers among physicians. Particularly, the process of knowledge sharing through the interplay between individual characteristics, knowledge characteristics, and intention in a healthcare setting has received very little empirical support. In this study, the authors draw upon personality traits and knowledge characteristics theories to develop a theoretical model to empirically examine the effect of individual characteristics and knowledge characteristics on physicians' knowledge sharing behavior.

Based on a sample of 215 physicians from 20 hospitals in Jordan, the authors conducted data analysis using the partial least squares statistical technique.

The study revealed that the personality traits (Extraversion, Neuroticism, Agreeableness and Conscientiousness) significantly influence physician intention to share knowledge. Knowledge characteristic (Situatedness) was also found to affect the intention to share knowledge.

Very little is known about the effect of individual characteristics and knowledge characteristics on knowledge sharing behavior among physicians. The study contributes to the related literature by empirically investigating how individual characteristics and knowledge characteristics influence physicians' knowledge sharing behavior. The findings add to the understanding of the role of personality traits and knowledge characteristics in physicians' intention to share knowledge and give important insights for practice and theory.

This research aims to explore the dark side of mobile applications by investigating the role of apps' technicality and app security in the mechanism of user satisfaction, app intention and customers' continuance tendency to make in-app purchases.

Drawing on attitude-behavior-context (ABC) theory, the study proposed a conceptual framework and examined the framework using a structural equation modeling (SEM) approach based on data collected from app users from New Zealand.

The results reveal the correlation between user satisfaction and in-app purchase with a mediator of app continuance intention (ACI). In particular, the results show that app technicality (AT) has a positive correlation with user satisfaction as an antecedent. App security and hedonic value are positively correlated with user satisfaction.

The research has three critical research implications. First, this research advances the understanding of the dark side of mobile apps by showing how app security influences customers' in-app purchases. Secondly, this study reveals and offers empirical evidence for the mechanism between app security and user satisfaction. Finally, the study provides empirical evidence of AT as a distal antecedent for in-app purchases.

The growth of the global labor force and business analytics has significantly impacted human resource management (HRM). Human resource (HR) analytics is an emerging field that creates value for employees and organizations. By examining the existing studies on HR analytics, the paper systematically reviews the literature to identify active research areas and establish a roadmap for future studies in HR analytics.

A portfolio of 503 articles collected from the Scopus database was reviewed. The study has adopted a Latent Dirichlet allocation (LDA) topic modeling approach to identify significant themes in the literature.

The HR analytics research domain is classified into four categories: HR functions, statistical techniques, organizational outcomes and employee characteristics. The study has also developed a framework for organizations adopting HR analytics. Linking HR with blockchain technology, explainable artificial intelligence and Metaverse are the areas identified for future researchers.

The framework will assist practitioners in identifying statistical techniques for optimizing various HR functions. The paper discovers that by implementing HR analytics, HR managers and business partners can run reports, make dashboards and visualizations and make evidence-based decision-making.

The previous studies have not applied any machine learning techniques to identify the topics in the extant literature. The paper has applied machine learning tools, making the review more robust and providing an exhaustive understanding of the domain.