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This study aims to present a research model to investigate the potential impact of human capital, structural capital and social capital on e-banking proactiveness. In addition, it reveals the potential impact of e-banking proactiveness on competitive intelligence and competitive agility. Also, it aims to explore the impact of competitive intelligence on competitive advantage and competitive agility. Finally, the impact of competitive agility on competitive advantage will be examined.

In order to gather data, a questionnaire was prepared and administered to 211 respondents in Jordan. The research model and hypotheses were then assessed using Structural Equation Modeling – Partial Least Squares (SEM-PLS).

The study demonstrated a significant impact of human capital, structural capital and social capital on e-banking proactiveness. The findings confirm that e-banking proactiveness significantly impacts competitive intelligence and achieving competition. Moreover, the findings confirm that competitive intelligence significantly impacts competitive agility. Also, the findings revealed a substantial relationship between competitive intelligence and competitive advantage. Finally, the results discovered that competitive agility significantly impacts competitive advantage.

The research gives valuable insights into the elements that drive e-banking proactiveness, which can beautify the proactiveness literature is well-known. By uncovering the position of intellectual capital in fostering proactiveness, this examination contributes to deeper information on the way financial institutions can successfully respond to market modifications, patron needs and technological advancements. Future scholars can build upon these findings to discover proactiveness in different sectors and industries, thereby broadening the understanding of proactive behaviors throughout numerous contexts.

This study examines the impact of digital corporate social responsibility (CSR) on social entrepreneurship, organizational resilience and competitive intelligence during the coronavirus disease 2019 (COVID-19) crisis. It also examines the impact of competitive intelligence on social entrepreneurship and organizational resilience.

Data were collected from telecommunication companies in Jordan with a sample of 223 managers, using Smart-PLS for analysis and testing the research model and hypotheses.

The results reveal a significant impact of digital CSR on social entrepreneurship. They show that digital CSR significantly impacts organizational resilience. The findings also indicate a significant role of digital CSR in competitive intelligence. This study shows that social entrepreneurship significantly impacts organizational resilience. The results also confirm the impact of competitive intelligence on social entrepreneurship. Finally, the results confirm that competitive intelligence significantly impacts organizational resilience.

This study provides valuable academic and practical insights into digital CSR practices, social entrepreneurship and how to support organizational resilience during crises.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

This paper aims to bring these areas closer by exploring the relationship between the dimensions of strategic intelligence (SI) for leadership and the proactive work behaviours (PWBs) of Upper Egypt universities' employees. Therefore, the research question revolves around: is there a relationship between SI and PWB?

The study relied on a descriptive analytical approach and a stratified random sample. The paper opts for a descriptive study using the survey lists that depends on three scales: strategic leadership intelligence. The sampling unit is represented by the individuals working in Upper Egypt Universities, distributed on a sample of 364 Upper Egypt universities' employees.

The results indicate a significant relationship between dimensions of SI for leadership and the PWBs.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further. This paper is the first to examine, to the authors' knowledge the relationship between intelligence for leadership and the PWBs.

Recognizing women’s potential and directing their talents to realize these potentials can be of great benefit. Accordingly, this paper aims to identify the characteristics of entrepreneurial intelligence in female entrepreneurs, drawing on a national-level study and the international literature on this topic.

The present paper conducted two studies. First, 15 female entrepreneurs in the Guilan province of Iran, who were selected using purposive sampling, were interviewed to identify the characteristics of entrepreneurial intelligence nationally. The data gathered by interviews were analyzed using inductive content analysis. Then, their validity was tested using qualitative validation and analyzed using Shannon entropy. In the second study, the characteristics of female entrepreneurial intelligence were identified through a qualitative metasynthesis. The results of the two studies were compared together.

This categorized entrepreneurial intelligence into six categories, namely, entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. Ultimately the characteristics of women’s entrepreneurial intelligence in each category were compared according to the national-level study and the international literature.

This study has the potential to discover credible and robust approaches for further examining the contextualization of women’s entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various dimensions of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women’s entrepreneurship, this paper challenges the assumption that the characteristics of women’s entrepreneurial intelligence are uniform across the world.

The current work sought to investigate the mediating effect of supply chain ambidexterity on the relationship between Industry 4.0 capabilities and operational performance of manufacturing firms in Jordan.

Data collection was carried out through a survey with 253 respondents from manufacturing firms in Jordan through the first quarter in 2023. The quantitative approach and structural equation modeling (SEM) were applied to analyze the collected data. Dynamic capabilities view (DCV) theory was the adopted theoretical lens for this work.

The results demonstrated that Industry 4.0 capabilities positively and significantly affect exploration, exploitation and operational performance. In addition, the results confirmed that exploration and exploitation positively and significantly affect operational performance. Further, it is also found that exploration and exploitation in the supply chain positively and significantly mediate the relationship between Industry 4.0 capabilities and operational performance.

This study focuses on this gap to deepen the understanding of operational performance in a recent manufacturing environment under various factors and perspectives (Industry 4.0 capabilities and supply chain ambidexterity).

This paper aims to empirically examine the impact of dynamic capabilities on Industry 4.0 capabilities in small and medium enterprises (SMEs) in Jordan. It also aims to examine the potential impact of industry 4.0 capabilities on technological innovation.

Data were collected from 210 respondents who work and own SMEs in Jordan. SmartPLS software based on the partial least squares-structural equation modeling approach was used to test hypotheses.

The findings reveal the positive effects of the three components of dynamic capabilities, including sensing, seizing and reconfiguring, on Industry 4.0 capabilities. They also confirm the positive effect of Industry 4.0 capabilities on technological innovation.

This study provides valuable practical implications and enriches the literature on the determinants of Industry 4.0 capabilities and its role in developing the dynamic capabilities of SMEs, such as technological innovation.

Emotional intelligence (EI) has a profound effect on the performance of tour guides, though past studies on the subject have neglected to examine the effects of EI on neither the overall nor specific pattern of tour guides' performance. This study examines the overall link between four dimensions of EI (self-emotion appraisal [SEA], others' emotion appraisal [OEA], use of emotions [UOEs] and regulation of emotions [ROEs]) and five dimensions of citizenship performance (helping, self-development, initiative, compliance and adaptability), ultimately identifying the relationship between EI factors and each dimension of tour guides' citizenship performance.

The data from 244 Jordanian tour guides were gathered through a quantitative survey. A confirmatory factor analysis (CFA) and multiple regression analysis were performed to analyze the data.

The results reveal that emotionally intelligent tour guides are more likely to have higher levels of citizenship performance. The most significant factors in determining extra-role behaviors by tour guides are “UOEs” and “others’ emotion appraisal (OEA)”.

This study equips different professional entities in the tour guide industry with useful, contextualized links between EI and citizenship performance. This assists in developing new accreditation policies and business practices to augment tour guides' citizenship professionalism, thereby maximizing their valuable contributions to tourism growth.

This study advances the tourism studies by establishing a new theoretical link between tour guides' EI and citizenship performance. The study also uncovers unique factors of EI that significantly determine tour guides' citizenship behaviors.

As a counterproductive interpersonal work behavior, knowledge hiding inhibits team creativity, hampers collaboration and ultimately has a detrimental impact on organizational performance. Drawing upon the impression management perspective. This study aims to investigate how and when employees’ political skill affects their knowledge-hiding behavior in real work contexts.

The authors tested the hypotheses using data gathered from 266 employees in China using a time-lagged research design.

The results indicate that political skill positively influences knowledge hiding through the supplication strategy. Moreover, the positive effect of political skill on this strategy is stronger under higher levels of competition.

A cross-sectional design and the use of self-report questionnaires are the limitations of this study.

The authors contribute to the literature on the emergence of knowledge hiding by identifying an impression management perspective. The authors also contribute to the literature on political skill by exploring the potential negative effects of political skill in the interpersonal interaction. Moreover, the authors enrich the understanding of the literature in competitive climate by introducing the impression management theory and exploring its influence on knowledge floating.

The authors argue that privacy is integral to the well-being of consumers and an essential component in not only corporate social responsibility (CSR) but what they term uniquely as social media responsibility (SMR). A conceptual framework is proposed that delineates the privacy issues companies should pay attention to in artificial intelligence (AI)-fueled social media environments.

The authors review literature on privacy issues in social media and AI in the academic and practitioner literatures. Based on the review, arguments focus on the need for an SMR framework, proposing responsible use of consumer data that is attentive to consumers' privacy concerns.

Implications from the framework are a path forward for social media companies to treat consumer data more fairly in this new environment. The framework has implications for companies to reduce potential harms to consumers and consider addressing their power and responsibility. With social media and AI transforming consumer behavior so profoundly, there are a variety of short- and long-term social implications.

Since AI tools are becoming integral to social media company activities, this research addresses the changing responsibilities social media companies have in securing consumers' data and enabling consumers the agency to protect their privacy effectively. The authors propose an SMR framework based on CSR research and AI tools employed by social media companies.