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Despite the widespread recognition of the significance of entrepreneurial innovations in driving financial success and building firms' competitive advantage, there is a lack of empirical investigation into their impact on organizations. This research paper aims to address this gap by exploring how entrepreneurial innovations can contribute to firms' competitive advantage and the mediating role of entrepreneurial thinking in this relationship. To answer these research questions, this paper utilizes the resource-based view (RBV) of the firm and the dynamic capabilities view (DCV).

The study employed a quantitative research design, and survey data were collected from 102 chief executive officers (CEOs) of Jordanian manufacturing companies in various industries. Structural equation modeling was used to test the hypothesized relationships.

The findings of this study suggest that there is a positive and significant impact of entrepreneurial innovation and thinking on the competitive advantage of firms. The authors also found that entrepreneurial thinking positively mediates this relationship. This study’s results support the RBV and DCV perspectives, which suggest that firms need to leverage unique resources and capabilities and develop dynamic capabilities to achieve a sustained competitive advantage.

The significance of this study lies in its contribution to the literature on the relationship between entrepreneurial innovation, thinking and competitive advantage. While previous research has explored these concepts separately, this study integrates them into a comprehensive framework that highlights the mediating role of entrepreneurial thinking in the relationship between entrepreneurial innovation and competitive advantage.

In today’s competitive business landscape, organizations are increasingly recognizing the strategic advantage of implementing sustainable practices to gain a competitive edge. This study aims to investigate the effect of green artificial intelligence (AI) on achieving a green competitive advantage, examining the mediating roles of green organizational learning, green product innovation and green process innovation. Additionally, the research explores the moderating role of perceived green climate in the relationship between green AI and these mediating factors.

This research examined companies in Isfahan, Iran, that have varying levels of artificial intelligence adoption within their business processes. The target population consisted of 148 senior managers from these companies. This study uses structural equation modeling to examine the proposed model.

Green AI positively impacted green organizational learning and green process innovation but not green product innovation. In addition, the results showed that green organizational learning, green product innovation and green process innovation had positive effects on green competitive advantage. Finally, the results showed that the perceived green climate did not play a moderating role in the relationship between green AI and these mediating factors.

Organizations should prioritize green AI initiatives, foster a culture of green learning and invest in green innovation to achieve sustainable growth and outpace competitors in the environmentally conscious marketplace.

This study positions itself at the forefront of research on green AI and green competitive advantage. It offers a unique framework by examining the combined effects of green AI, green learning and both product and process innovation on achieving a sustainable competitive advantage.

This study investigates the impact of big data analytics capabilities on export performance. Moreover, it assesses the mediating effect of the supply chain innovation and moderating effect of supply chain agility.

This study is based on primary data that were collected from the manufacturing sector operating in Jordan. A total of 327 responses were used for the final data analysis. Data analysis was performed via a partial least square structural equation modeling (PLS-SEM) approach.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the export performance as well as a mediating effect of supply chain innovation. It was confirmed that supply chain agility moderated the relationship of supply chain innovation and export performance.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, export performance, supply chain innovation and supply chain agility. This study offers new theoretical and managerial contributions that add value to the supply chain management literature by testing the moderated-mediated model of these constructs in the manufacturing sector in Jordan.

Given the remarkable increase in entrepreneurial activities initiated by women in the Egyptian context in addition to the scarcity of empirical studies on digital self-employment there, the authors of the present paper aim to identify what motivates women to engage in digital entrepreneurship, and to identify how those women establish their digital entrepreneurial activities.

The authors employed a qualitative research method through semi-structured interviews with 30 women entrepreneurs who own and manage digital businesses. Thematic analysis was subsequently used to determine the main ideas in the transcripts.

The authors have found that enjoying absolute independence, securing more time for family, guaranteeing an independent source of income in addition to the ease of accessing extensive online markets are the main motives behind the engagement of women in the Egyptian context in digital entrepreneurship activities. Moreover, the authors have also asserted that the minimal training and government support stimulate women entrepreneurs there to start and continue their digital business activities informally.

This paper contributes by filling a gap in entrepreneurship studies in which empirical studies on establishing and managing digital entrepreneurship among women in developing economies has been limited so far.

The aim of this paper is to discuss a selection of policy strategies, regional initiatives and market approaches to uncover the realities of twenty-first-century building energy performance. A position that market-based approaches, human influence and policy interventions are part of an ecosystem of building energy performance is presented.

An exploratory search of secondary sources spanning the last three decades was conducted. Both peer-reviewed and grey literature were included to capture a broader understanding of the discourse in literature. Research questions guided the literature search, and a data extraction tool was designed to categorise the literature. The primary limitation of this study is that only a few applications could be discussed in a condensed format.

Several challenges about the current status quo of building energy performance were identified and summarised as follows. (1) Inconsistencies in measurement and verification protocols, (2) Impacts of market approaches, (3) National policy priorities that are at variance with regional targets and (4) Ambiguous reporting on environmental impacts of energy efficiency (EE) technologies.

The practical implications of the findings in this paper for practice and research are that as part of the building energy performance ecosystem, national responses through government interventions must become adaptive to keep up with the fast-paced energy sector and social trends. Simultaneously, before market-based approaches overcome the messiness of socio-economic dynamics, institutional conditions and cultural nuances, they ought to transparently address environmental impacts and the infringement of several SDGs before they can become viable solutions to building energy performance.

This paper presents building energy performance as an ecosystem comprising human influence, market-based approaches and policy interventions which form interdependent parts of the whole. However, evidence in the literature shows that these aspects are usually investigated separately. By presenting them as an ecosystem, this paper contributes to the discourse by advocating the need to re-align building energy performance to socio-economic-political dynamics and contextually viable solutions.

This study aims to empirically examine the influence of transformational leadership on job satisfaction in Jordanian commercial banks through knowledge sharing as a mediator. The data were collected from 232 employees and then analyzed through regression analysis using SPSS. The results revealed that there is a significant influence of transformational leadership on job satisfaction, as well as a significant influence of knowledge sharing on this relationship. These findings imply that if managers adopt transformational leadership, their subordinates can be satisfied with their jobs, specifically if they facilitate knowledge sharing. This study sheds light on improving organizational performance and employee engagement in a specific context and provides excellent direction for future contributions.

Despite some academic recognition that leadership is particularly significant in reshaping the oil and gas industry’s contributions to global economic development and the sustainability of global energy supplies at affordable prices (Sharma et al., 2022), the attendant problem of how the industry’s leadership contributes towards the preservation of global environment and the maintenance of ecosystems’ balance, among other sustainability challenges, remains an academic lag. This calls for the urgent need for oil and gas companies to practice effective sustainable leadership approach at multiple organisational levels to address global environmental, economic and social challenges.

This paper adopts an interpretivist/constructivist philosophical stance, where findings have been extracted from in-depth thick descriptive qualitative research in Bahrain oil and gas industry. Companies operating within Bahrain oil and gas industry were identified as the unit of analysis. Empirical data are gathered through semi-structured interviews from senior management and analysed using thematic analysis. This paper is structured as follows: introduction, contextualisation of the UNSDGs in the oil and gas industry, literature on network leadership, research methods used to gather and analyse data from Bahrain oil and gas industry findings, contributions, limitations and trajectories for further studies.

The study’s participants argued that the emergence of transformational and Sustainable Network Leadership is essential to successfully and sustainably implementing the UN SDGs. In other words, the Sustainable Network Leadership is a contribution to the single, leadership competences approach of previous scholarship (Weber et al., 2022; Kumalo and Scheepers, 2021) partly because it evolves around the notion of positioning different network and change actors based on their capacity to lead, exchange their knowledge, effectively communicate the need to comply with SDGs and the skills to establish high density within a complex network of actors.

This study recognises its limitations in the sense that it is based on the single context of Bahrain oil and gas, and data were collected from senior management and executives only. Gathering data from a broader swathe of employees may have provided greater levels of leadership and organisational member nuances in both single and collective differences of leadership attributes.

Transformational and Sustainable Network Leadership provides a new construct in the perception (the “what”), instrumentalisation (the “how”) and theoretical re-conceptualisation of leadership within organisational change settings needing radical rethink for sustainable and successful change. The practical implications of transformational and Sustainable Network Leadership expose the way a variety of highly challenged organisational change contexts are interconnected to highlight not only their different sets of challenges but also their opportunities and the resolution mechanisms they present for organisational leaders and staff alike.

This paper identified the single, leadership competence approach as the dominant discourse in organisational change, leadership studies and presented an alternative collective set of leaders’ attributes. The less utilised network leadership concept was drawn upon to contribute network leadership attributes as a way of addressing the challenges faced by Bahraini oil and gas company leaders. Therefore, this study contributes to both network leadership, transformational leadership by expanding both domains to include organisational transformation and the leadership-of-risky change. This was done by identifying attributes and characteristics of Sustainable Network Leadership, then showing their significance as an approach to successfully and sustainably implementing the UNSDGs.

The number of construction dispute cases has maintained a high growth trend in recent years. The effective exploration and management of construction contract risk can directly promote the overall performance of the project life cycle. The miss of clauses may result in a failure to match with standard contracts. If the contract, modified by the owner, omits key clauses, potential disputes may lead to contractors paying substantial compensation. Therefore, the identification of construction project contract missing clauses has heavily relied on the manual review technique, which is inefficient and highly restricted by personnel experience. The existing intelligent means only work for the contract query and storage. It is urgent to raise the level of intelligence for contract clause management. Therefore, this paper aims to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology.

A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts are pre-processed and converted from unstructured natural language into structured digital vector form. Following the initial categorization, a multi-label classification of long text construction contract clauses is designed to preliminary identify whether the clause labels are missing. After the multi-label clause missing detection, the authors implement a clause similarity algorithm by creatively integrating the image detection thought, MatchPyramid model, with BERT to identify missing substantial content in the contract clauses.

1,322 construction project contracts were tested. Results showed that the accuracy of multi-label classification could reach 93%, the accuracy of similarity matching can reach 83%, and the recall rate and F1 mean of both can reach more than 0.7. The experimental results verify the feasibility of intelligently detecting contract risk through the NLP-based method to some extent.

NLP is adept at recognizing textual content and has shown promising results in some contract processing applications. However, the mostly used approaches of its utilization for risk detection in construction contract clauses predominantly are rule-based, which encounter challenges when handling intricate and lengthy engineering contracts. This paper introduces an NLP technique based on deep learning which reduces manual intervention and can autonomously identify and tag types of contractual deficiencies, aligning with the evolving complexities anticipated in future construction contracts. Moreover, this method achieves the recognition of extended contract clause texts. Ultimately, this approach boasts versatility; users simply need to adjust parameters such as segmentation based on language categories to detect omissions in contract clauses of diverse languages.

This study aims to analyse the existing literature on factors motivating higher education institutions to disclose their Sustainability Development Goals initiatives.

This study used an interdisciplinary systematic review to develop a review protocol for Sustainability Development Goals and higher education institutions-related literature. Thematic analysis was performed using NVivo Release 1.4 to generate the theme related to the motivating factors of disclosure and further analysed using content analysis.

The study identified five clusters relating to Sustainability Development Goals and higher education institutions. The main subcategory consists solely of motivating factors as the main child note. The four main factors that motivate Higher Education Institutions to disclose their Sustainability Development Goals practices are the curriculum, research activities, human resource management and collaborations in research and operations.

This paper provides an overview of factors that contribute to Sustainable Development Goals disclosure among higher education institutions with regard to their primary functions of pioneering research, providing education, exercising governance and providing external leadership. Several implications in light of multiple stakeholders are provided in the paper.

This study is among the few studies that develop a review protocol for Sustainability Development Goals and higher education institutions-related literature. The review provides international overview of the current academic debate on the topic of Sustainability Development Goals disclosure.

This study aims to explore how institutional quality impacts private capital participation in large-scale infrastructure development, particularly in public–private partnership (PPP) projects, aiming to enhance incentives for private sector involvement.

Building on new institutional theory, a triangular theoretical framework was constructed to analyze the high participation of private capital in PPP projects, focusing on seven key institutional factors. Data from 1,319 PPP projects across 36 Belt and Road Initiative (BRI) countries from 2015 to 2020 were then analyzed using a combination of necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis (fsQCA) to evaluate the combined impact and interactions of these factors.

Results indicate that high private capital participation does not hinge on a single institutional quality factor but results from the synergistic influence of multiple factors. The paths leading to high private capital participation can be categorized as regulatory-led, normative-cognitive synergistic, regulatory-normative synergistic and institutional failure-led. Among these, regulatory quality plays a central role in the regulatory-led; the synergy between political stability and voice and accountability is pivotal in the normative-cognitive synergistic, and the rule of law, in combination with voice and accountability, is essential to the regulatory-normative synergistic.

This research systematically examines the multidimensional impact of institutional quality, revealing how different institutional factors interact to influence private capital’s willingness to participate and behavior. It enriches applied research in institutional economics within PPP projects and provides a new theoretical perspective and methodological framework to the scholarly community.