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Information transparency is an important factor in enhancing trust and promoting interfirm cooperation. By combining transaction cost theory and institutional theory, this study aims to examines whether host-country firms’ information transparency prompt multinational enterprises’ (MNEs) to choose the joint venture entry mode for outward foreign direct investment (OFDI).

Using Heckman two-stage estimation method, this study examines Chinese listed manufacturing firms for the period 2014–2019.

The findings indicate that the higher the information transparency of host-country firms, the higher the possibility of MNEs choosing the joint venture entry mode for OFDI. This study further finds that the positive relationship between host country firms’ information transparency and the possibility of choosing the joint venture entry mode is enhanced by institutional distance, but weakened by MNEs’ host-country experience.

How to choose the appropriate entry mode of OFDI in the internationalization strategy is an important issue for MNEs to consider. As the postpandemic world is characterized by increased global risks, decoupling of economies, disruption of global value chains and the retreat of globalization (Contractor and Cantwell, 2022), how to further strengthen cooperation, reduce the cost and risk of MNEs and truly realize common construction and sharing is one of the hot issues in both practice and research.

This paper investigates the mediating role of organizational prosocial behavior (OPB) in the relationship between spiritual leadership (SL) and knowledge-sharing (KS) from the intrinsic motivation perspective.

A survey was used to gather data from middle and executive management employees at industrial firms in Sahab Industrial City in Jordan. The study applied quantitative exploratory methods. The study used a self-reported questionnaire to gather data, with 268 valid responses being used to conduct the analysis. The analysis of data proceeded with the aid of SEM-PLS using SmartPLS 4.

The results advocate the positive link between SL and KS routing through the mediator (OPB). The mediating role of OPB was found to be partial.

This study offers practical implications for organizations that wish to optimize KS among employees. It emphasizes the crucial role of SL in determining employee OPB and proposes that managers strive to engender organization-wide transcendental values.

This study furthers the understanding of KS by testing the relationship between SL and KS using OPB as a mediator, which has not been investigated theoretically or empirically.

This paper aims to empirically investigate the dynamic interlinkages among globalization, digitalization and economic development in the top 75 most globalized countries from 2000 to 2019. The selection of the 75 most globalized developing countries is based on the overall scores of the KOF Globalization Index (2021).

The research design is based on secondary data collected from the World Bank (2021), the International Telecommunication Union (2021) and the KOF Globalization Index (2021). The study uses panel unit root tests followed by the panel cointegration techniques. Further, the estimation uses panel fully modified ordinary least squares and panel dynamic ordinary least squares methods.

The empirical results reveal that the effect of globalization on economic development is sensitive to different estimation procedures; in some cases, but not in every case, the effect is positive and significant. However, the positive and significant effect of digitalization on economic development is robust across all estimated models. Long-run equilibrium relationships and bidirectional causalities strongly affirm the nexus among globalization, digitalization and economic development, substantiating the interconnectedness among 75 developing economies.

The study reinstates that the forces of globalization and digitalization will be instrumental in shaping the selected most globalized economies in the long run. Adopting various econometric methodologies takes care of the time-specific and cross-sectional dynamics, as evident in the panel framework considered in this study. The empirical findings truly ascertain the theoretical synergy among the forces of globalization leading to more digitalization and economic development. This makes the empirical interplay highly conducive to framing long-term policies to expand the information communication network in terms of its access and reach.

We live in a data-driven world where success relies on the accuracy of information and data quality assurance (QA). This chapter delves into the intricacies of establishing a robust data QA framework, empowering you to navigate the ever-evolving data landscape with confidence. This chapter starts with a discussion on consequences of poor data quality and then explains what is data quality and how defining data standards, mapping of data, implementation of validation and error checking, conducting audits, and cleansing and leveraging visualization tools can help one to construct data quality within his managerial ecosystems. This chapter underscores cultivation of a data-driven culture through stakeholder involvements, training, continuous improvements, and emphasizing ownership and responsibility. In the end, this chapter provides the reader with an outlook for the future of data QA discussing emerging technologies like artificial intelligence (AI)-powered data cleansing and blockchain-based security. This chapter will help the readers in ensuring data quality and unlock the door to a future of informed decisions, exceptional customer experiences, and lasting competitive advantage.

The aim of this paper was to delve into the underlying mechanism of the relationship between environmental knowledge and green purchase intentions, using an extended model based on the knowledge-attitude-behaviour (KAB) theory.

The parallel and serial mediation effects of environmental concern, green perceived value and green attitude were examined using PROCESS macro (Models 4 and 6). Data were collected from 395 youth in three different cities in India using a purposive sampling method.

The study’s findings revealed that environmental concern, green perceived value and green attitude act as parallel and sequential mediators between environmental knowledge and green purchase intentions. However, the direct impact of environmental knowledge on green purchase intentions was deemed insignificant. In essence, environmental knowledge, along with environmental concern and green perceived value, significantly contributes to the formation of attitudes conducive to green purchase intentions.

The present study theoretically contributes to green behaviour research by proposing and testing an extended model of KAB theory with parallel and serial mediations in the Indian context. The model explores the underlying mechanism of the relationship between environmental knowledge and green purchase intentions in detail.

The emergence of virtual reality (VR) has the potential to revolutionize various industries, including tourism, as it delivers a simulated environment that closely emulates real-life experiences. Therefore, this study aims to explore how the factors, i.e. enjoyment, emotional involvement, flow state, perceived privacy risk, physical risk and cost, influence the customers’ intention to use VR for tourism.

This study integrates the technology acceptance model, hedonic consumption theory with other factors, including cognitive response, authenticity, perceived privacy risk, perceived physical risk, perceived cost and perceived presence. Partial least squares structural equation modelling approach was used to test the proposed research model.

The finding based on the sample of 252 respondents revealed that authenticity is the most influential factor impacting behavior intention followed by perceived cost, attitude, cognitive response and enjoyment. Also, the study supported the moderating impact of personal innovativeness between attitude and behavioral intention to use VR for tourism.

The findings of the study offers practical implications for service providers, site managers, destination marketers, tourist organizations and policymaker to develop more effective strategies for offering VR services for tourism.

This study enriches the current understanding of VR adoption in context of tourism with empirical evidences.

虚拟现实的出现有可能彻底改变包括旅游在内的多个行业, 因为它提供了一个模拟环境, 密切模拟真实生活体验。因此, 本研究旨在探讨愉悦、情感投入、流体状态、感知隐私风险、身体风险和成本等因素如何影响顾客使用虚拟现实进行旅游的意愿。

本研究将TAM模型、享乐消费理论与其他因素相结合, 包括认知反应、真实性、感知隐私风险、感知身体风险、感知成本和感知存在。 PLS SEM 方法用于测试所提出的研究模型。

基于 252 名受访者样本的研究结果表明, 真实性是影响行为意图的最大因素, 其次是感知成本、态度、认知反应和享受。此外, 该研究还支持个人创新性对使用虚拟现实进行旅游的态度和行为意图之间的调节影响。

该研究的结果为服务提供商、站点管理者、目的地营销人员、旅游组织和政策制定者制定更有效的策略来为旅游业提供 VR 服务提供了实际意义。

本研究通过实证证据丰富了当前对旅游背景下虚拟现实采用的理解。

La aparición de la realidad virtual tiene el potencial de revolucionar diversas industrias, incluyendo el turismo, ya que proporciona un entorno simulado que emula de cerca las experiencias de la vida real. Por lo tanto, este estudio tiene como objetivo explorar cómo los factores, como la diversión, la participación emocional, el estado de flujo, el riesgo percibido de privacidad, el riesgo físico y el costo, influyen en la intención de los clientes de utilizar la realidad virtual para el turismo.

Este estudiointegra el modelo TAM, la teoría del consumohedónico con otrosfactores que incluyen la respuestacognitiva, la autenticidad, el riesgo de privacidadpercibido, el riesgofísicopercibido, el costopercibido y la presenciapercibida. Se utilizó el enfoque PLS SEM para probar el modelo de investigaciónpropuesto.

El hallazgobasadoen la muestra de 252 encuestadosreveló que la autenticidades el factor másinfluyente que afecta la intención de comportamiento, seguido del costopercibido, la actitud, la respuestacognitiva y el disfrute. Además, el estudioapoyó el impactomoderador de la innovación personal entre la actitud y la intención de comportamiento al utilizar la realidad virtual para el turismo.

Los hallazgos del estudioofrecenimplicacionesprácticas para que losproveedores de servicios, administradores de sitios, comercializadores de destinos, organizacionesturísticas y formuladores de políticasdesarrollenestrategiasmásefectivas para ofrecerservicios de realidad virtual para el turismo.

Este estudioenriquece la comprensión actual de la adopción de la realidad virtual en el contexto del turismo con evidenciasempíricas.

This study aims to understand the research data management (RDM) services offered by academic libraries in South Asian and Southeast Asian countries. This study aims to evaluate the library and information science professionals’ required RDM skills and the challenges faced with providing RDM services.

The research methodology for this study used a survey method with purposive sampling. Data were collected through online structured questionnaires, which were used to examine the current state of RDM services offered in academic libraries in South Asia and Southeast Asia.

South Asian and Southeast Asian region major types of RDM services provided were data repository, data management training, maintaining Web resources, data study and analysis, and promoting awareness of reusable data sources. Little attention was given to advisory services on data analysis/mining/visualization and supporting reproducibility and workflow transparency. The results indicated that most respondents agreed that metadata standards and data management planning skills were required for RDM services in South Asia and Southeast Asia.

This study is significant because it offers a comprehensive assessment of ongoing RDM services in academic libraries of South Asia and Southeast Asia. Most current literature focuses on best practices in developed nations. This study highlights the need for more competent and dedicated academic staff for effective RDM services. Library professionals can use this study to identify the gaps in RDM services and suggest formative measures to overcome such challenges.

This study aims to propose mindfulness as a key factor in merchants’ adoption of mobile payments through the trust and perceived value pathways in an unorganized sector.

Data were collected physically via a structured questionnaire from a random sample of 350 merchants from the unorganized retail sector in India. Partial least squares-based structural equation modeling was used to analyze the data.

Mindfulness plays a key role in the formation of trust and perceived value, which further influences merchants’ intentions to adopt mobile payments. Furthermore, moderating effects of technology anxiety and skepticism were also observed.

To the best of the authors’ knowledge, this study is the first to illustrate mindfulness in merchants of the unorganized sector in adopting mobile payments to influence the adoption intentions of mobile payments in emerging markets.

Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques in predicting the financial performance of microfinance institutions (MFIs).

This study gathered 9,059 firm-year observations spanning from 2003 to 2018 from the World Bank's Mix Market database. To predict the financial performance of MFIs, the authors applied a range of machine learning regression approaches to both training and testing data sets. These included linear regression, partial least squares, linear regression with stepwise selection, elastic net, random forest, quantile random forest, Bayesian ridge regression, K-Nearest Neighbors and support vector regression. All models were implemented using Python.

The findings revealed the random forest model as the most suitable choice, outperforming the other models considered. The effectiveness of the random forest model varied depending on specific scenarios, particularly the balance between training and testing data set proportions. More importantly, the results identified operational self-sufficiency as the most critical factor influencing the financial performance of MFIs.

This study leveraged machine learning on a well-defined data set to identify the factors predicting the financial performance of MFIs. These insights offer valuable guidance for MFIs aiming to predict their long-term financial sustainability. Investors and donors can also use these findings to make informed decisions when selecting their potential recipients. Furthermore, practitioners and policymakers can use these findings to identify potential financial performance vulnerabilities.

This study stands out by using a global data set to investigate the best model for predicting the financial performance of MFIs, a relatively scarce subject in the existing microfinance literature. Moreover, it uses advanced machine learning techniques to gain a deeper understanding of the factors affecting the financial performance of MFIs.