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This research aims to clarify the relationship between organizational identification and employees’ unethical pro-organizational behavior, which has been a topic of mixed findings in previous empirical studies. To address this issue, a meta-analytic review was conducted, focusing on the influence of key individual differences such as gender, age and organizational tenure on the relationship between organizational identification and unethical pro-organizational behavior.

The study utilizes large scholarly databases including Google Scholar, PsycINFO, Business Source Premier and ProQuest Dissertations to identify relevant studies. A total of 31 independent samples with a combined sample size of 8,861 participants were included in the analysis.

The results showed that the estimated average correlation between organizational identification and unethical pro-organizational behavior after corrected for measurement unreliability was 0.188 (p < 0.001, 95% [CI: 0.125, 0.251]). Gender demonstrated a significant moderating effect (estimate = 0.004, p < 0.05, 95% [CI: 0.000, 0.007]), suggesting that there is stronger association between organizational identification and unethical pro-organizational behavior among male participants. Neither age nor organizational tenure had significant effect on organizational identification-unethical pro-organizational behavior relations.

This study revealed that the organizational identification-unethical pro-organizational behavior link was positive, and the relationship was stronger among male participants than their female counterparts. Age and organizational tenure show no significant impact on unethical pro-organizational behavior. These contribute to The authors' understanding of organizational identification-unethical pro-organizational behavior relationship, as well as identifying its boundary conditions. The study suggests directions for future research and implications for managers and practitioners.

The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.

This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier.

The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO₂ emissions.

To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.

This study aims to collect distributed knowledge organization systems (KOSs) from various domains, enrich each with meta information and link them to the multilingual KOS registry, facilitating integrated search alongside KOSs from various languages and regions.

This research involved collecting and organizing KOS information through three primary steps. The initial phase involved finding KOSs from Web search results, supplemented by the Korea ON-line E-Procurement System (KONEPS) and the National R&D Integrated Notification Service. After obtaining these KOSs, they were enriched by structuring contextual meta information using Basic Register of Thesauri, Ontologies and Classification (BARTOC) metadata elements and established dedicated media wiki pages for each. Finally, the KOSs were linked to the multilingual KOS registry, BARTOC, ensuring seamless integration with KOSs from various languages and regions and creating connections between each registry entry and its associated KOS wiki page.

The research findings revealed several insights, as follows: (1) importance of a stable source for collecting KOS: no national body currently oversees KOS registration, underscoring the need for a systematic approach to collect dispersed KOSs. For Korean KOSs (K-KOSs), KONEPS and National R&D Integrated Notification Service are effective data sources. (2) Importance of enhanced metadata: merely collecting KOSs were not enough. Enhanced metadata bridges access gaps and dedicated wiki pages aid user identification and understanding. (3) Observations from multilingual registry uploads: When adding KOSs to a multilingual registry, similarities were observed across languages and regions. Recognizing this, the K-KOSs were linked with their international counterparts, fostering potential global collaboration.

Due to the absence of a dedicated KOS registry agency, the study might have missed KOSs from certain fields or potentially over-collected from others. Furthermore, this study primarily focused on K-KOSs and their integration into the BARTOC registry, which might influence the methods and perspectives on collecting and establishing links among analogous KOSs in the registry.

This research pursued a stable method to detect KOS development and revisions across various fields. To facilitate this, we used the integrated e-procurement and R&D notification system and added meta information to aid in the identification and understanding of KOSs, which includes media wiki pages. Furthermore, link information was provided between the BARTOC registry and the Korean KOS websites and media wiki pages.

Upon the realization of the need for guideline in cross-organizational data integration, in an exploratory manner, this study developed a public data governance framework, specifically, the governance for integrated public data (GIPD) framework and identified the influential factors of its successful implementation. This framework was then subjected to an analysis of a real data integration case in the South Korean public sector to test its efficacy.

To develop the GIPD framework, the authors conducted an extensive meta study, focus group interviews and the analytic hierarchy process involving field experts. Further, the authors performed topic modeling on documents from Korean research and development data integration projects, and compared the extracted factors to those of the GIPD to illustrate the latter's usefulness in a real case.

Legislation, policy goals and strategies, operation organization, decision-making council, financial support size and objective, system development and operation, data integration, data generation, system/data standardization and master data management were derived as the 10 important factors in implementing the GIPD framework. The illustrative case of Korea revealed that decision-making council, financial support size and objective, legislation, data generation and data integration were insufficient.

Although this study reveals important findings, it has a few limitations. First, the potential factors for data governance might vary depending on the attribute of the “interviewee” (such as their career or experience period) and the goal and area of GIPD framework building. Second, the inherent limitation of topic modeling in determining topics from groups of extracted keywords means that topics may be interpreted in various ways, depending on the perspective of the expert.

This study is highly significant in that it provides a starting point for discussions on the issue of data integration among public institutions. Therefore, although this study examined public data governance based on R&D data, it will contribute to providing a sufficient guideline for any type of inter-institutional data governance framework, what to discuss and how to discuss between institutions.

The findings are expected to provide a roadmap to formulate practical guidelines on inter-institutional data cooperation and a diagnostic matrix to improve the existing data governance system, especially in the public sector, from the existing practice of empirical analysis using a mixed methodology approach.

The purpose of this study is to analyze the nonlinear effects of corporate philanthropy on the responses of both internal and external stakeholders as well as its impact on corporate financial performance.

Based on the stakeholder theory, the authors developed a conceptual model to examine the nonlinear effects of corporate philanthropy on company performance. For the empirical analysis, data from 397 company-years was analyzed using a using a Heckman two-stage model. The robustness of the findings was also confirmed through panel regression analysis.

The study revealed a linear relationship between corporate reputation and corporate philanthropy, whereas job satisfaction exhibited a nonlinear relationship with corporate philanthropy.

This research bridges the gap in extant literature by scrutinizing the nonlinear associations between corporate philanthropy and financial performance. Additionally, it addresses an emerging scholarly demand to uncover the “dark side” of corporate philanthropy through an investigation into its adverse impacts on employee satisfaction. Moreover, the study augments existing understandings of stakeholder theory and corporate philanthropy, positing that the influence of corporate philanthropy, as conceptualized through stakeholder theory, hinges on perceived fairness in multilateral relationships.

Building on upper echelons theory, the authors advance the literature on the influence of diversity on innovation by studying the link between top management team (TMT) gender diversity and innovation performance and the link's boundary conditions.

The authors analyze survey data from 390 manufacturing establishments in Germany and India through an ordinary least square (OLS) regression analysis.

TMT gender diversity is positively related to innovation performance. The influence of gender diversity on innovation performance is not strengthened by team level attributes, including cognitive proficiency and openness to external information. In contrast, TMT gender diversity enhances innovation performance more strongly in Germany than in India, indicating the relevance of country-level cultural norms for leveraging gender diversity.

The authors' study is built on data from two countries only, based on TMTs in the manufacturing sector and cross-sectional. Future studies may address these limitations by considering more countries, examining TMTs in the service sector and applying experimental or longitudinal research designs.

Executives should establish gender diverse TMTs to enhance innovation performance and leverage diverse views of male and female managers effectively. Managers located in countries with strongly hierarchical cultural norms should promote egalitarian values at the organizational level to increase the effectiveness of gender diverse TMTs.

This is the first study which examines the moderating effect of country-level cultural norms on the relationship between TMT gender diversity and innovation performance.

This study comprehensively aims to review the key influential and intellectual aspects of spillovers between Islamic and conventional financial markets.

The study uses the bibliometric and content analysis methods using the VOSviewer software to analyse 52 academic documents derived from the Web of Sciences (WoS) between 2015 and June 2022.

The results demonstrate the influential aspects of spillovers between Islamic and conventional financial markets, including the leading authors, journals, countries and institutions and the intellectual aspects of literature. These aspects are synthesised into four main streams: research between stock indexes; studies between stock indexes, oil and precious metal; works between Sukuk, bond and indexes; and empirical studies review. The authors also propose future research directions in spillovers between Islamic and conventional financial markets.

Our study is subject to several limitations. Firstly, the authors only used the WoS database. Secondly, the study only includes papers and reviews written in English from the WoS. This study assists academic scholars, practitioners and regulatory bodies in further exploring the suggested issues in future studies and improving and predicting economic and financial stability.

To the best of the authors’ knowledge, no extant empirical studies have been conducted in this area of research interest.

This study develops a comprehensive research model and investigates the significant factors affecting positive marketing outcomes in the Metaverse through perceived social benefits and trust.

The authors propose a new research model based on social exchange theory (SET) and examine the impact of cost and reward factors. Using 327 survey samples collected from current Metaverse users in South Korea, dual-stage analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM) and an artificial neural network (ANN) were employed to test the study’s hypotheses.

The results showed that perceived social benefit and trust had significant mediating effects on marketing outcomes, such as loyalty to the seller, product/service attitude, and purchase intention. All antecedents, except perceived performance risk, had a crucial impact on the two mediators. The most interesting finding of this study is the positive influence of knowledge-seeking efforts on perceived social benefits.

This study is the first empirical research to examine the effectiveness of marketing in the Metaverse. It also proposes a new theoretical model based on SET to investigate users’ behavioral intentions regarding marketing in the Metaverse, and confirms its explanatory power. Moreover, the results of this study also offer suggestions to brands on how to market to consumers in the Metaverse.

Given its growing economic potential and social impact, this study aims to understand the motivations and concerns regarding metaverse usage. It identifies user needs and risks around the metaverse grounded on uses and gratifications theory and perceived risk theory.

The authors analyzed user reviews and rating data from Roblox, a representative modern metaverse platform. They applied BERTopic modeling to extract topics from reviews, identifying key motivations and risk aspects related to metaverse usage. They further constructed an explanatory model to assess how those affect user satisfaction and changes in these effects over time.

This study discovered that gratifications like entertainment, escapism, social interaction and avatar-based self-expression significantly influence user satisfaction in the metaverse. It also highlighted that users find satisfaction in self-expression and self-actualization through creating virtual spaces, items and video content. However, factors such as identity theft, fraud and child safety were identified as potential detriments to satisfaction. These influences fluctuated over time, indicating the dynamic nature of user needs and risk perceptions.

The novelty of this study lies in its dual application of the uses and gratifications theory and perceived risk theory to the metaverse. It provides a novel perspective on user motivations and concerns, shedding light on the distinct elements driving user satisfaction within the metaverse. This study unravels the metaverse’s unique capacity to assimilate features from established digital media while offering a distinctive user-generated experience. This research offers valuable insights for academics and practitioners in digital media and marketing.

This research pioneers the application of both uses and gratifications and perceived risk theories to understand factors influencing metaverse satisfaction. By establishing a comprehensive framework, it explores the metaverse’s unique value as a user-content creation platform, while encompassing existing digital platform characteristics. This study enriches the academic literature on the metaverse and offers invaluable insights for both metaverse platforms and brand marketers.

This study is based on the heuristic-systematic model (HSM) to dynamically examine the effect of review variance on sales and the boundary conditions that mitigate this effect.

Based on the theoretical domain of HSM, a conceptual model is proposed that analyzes the nonlinear relationship between review variance and sales and the interaction and motivation factors that moderate these relationships. Review data from websites targeting the film industry in the USA and South Korea (Korea) were collected to empirically analyze the authors' hypothesis, and panel regression analysis was used for confirmation.

Moderated by interactive and motivational factors, review variance exhibits an inverse-U-shaped relationship with review variance. Specifically, as an interaction factor, review valence and owned social media (OSM) resulted in positive interaction effects, and as a motivation factor, the number of alternatives exhibited a positive interaction effect with review variance. The effect of review variance was less pronounced in the USA than in Korea.

The study outcomes reveal a nonlinear relationship between review variance and sales, thus supporting the contradictory findings of previous studies. This study contributes to the literature by using the HSM as a theoretical framework to verify various HSM mechanisms using online review data. This exploratory study also contributes to the international marketing literature by showing that the effects of review variance vary across cultures.