This study uses dynamic capability theory and a resource-based view to examine whether intellectual capital (human, relational, and structural capital) mediates entrepreneurial leadership and innovation success. Drawing on data from 422 senior-level employees working in Peruvian I.T. companies, the proposed relationships were analyzed using SmartPLS 4. Entrepreneurial leadership was found to foster employees’ innovative performance through the mediating role of human capital, relational capital, and structural capital. Practically, businesses often rely on innovation for survival and growth, so they should consider entrepreneurial leadership to create intellectual capital (human capital, relational capital and structural capital) for innovation performance. Businesses should provide entrepreneurial training that emphasizes role modeling intellectual capital and encourages employees to recognize and pursue entrepreneurial opportunities. With significantly limited research, the study contributes by investigating the interrelationship of entrepreneurial leadership, intellectual capital, and innovation performance. The study contributes to the Resource Based View and Dynamic Capability Theory by demonstrating how entrepreneurial leadership contributes to innovation performance through human capital, relational capital, and structural capital.

In light of the metaverse’s vast expansion, it’s a crucial intellectual platform that’s transforming the video game industry and spurring creative innovation and technological advancement. Considering the distinctive niche that Taiwan occupies within the realm of the video game industry, this study uses a total of 11 video game companies in Taiwan as samples. The study spans a period of 16 years, from 2007 to 2022, and utilizes the random effect regression model for analysis. The study results illustrate that intellectual capital efficiency exerts varying contributions to the creation of value across different corporate value indicators within the video game industry. Among the factors, HCE, SCE, and CEE demonstrate the highest explanatory power for ROE, reaching up to 82.23%. Following this, they account for 73.57% of the variance in market share, but only a meager 13.67% for Tobin’s Q. This study is the empirical evidence that different methods of measuring intellectual capital and various definitions of value creation in an industry may lead to divergent results and managerial implications in intellectual capital research. Hence, it is worthwhile for subsequent studies to continue clarifying and delving deeper into these aspects.

Purpose: This study empirically investigates the effect of big data analytics (BDA) on project success (PS). Additionally, in this study, the investigation includes an examination of how intellectual capital (IC) and (KS) act as mediators in the correlation between BDA and KS. Lastly, a connection between entrepreneurial leadership (EL) and BDA is also explored. Design/Methodology- Using a sample of 422 senior-level employees from the IT sector in Peru. The partial least squares structural equation modeling technique tested the hypothesized relationships. Findings- According to the findings, the relationship between BDA and PS is mediated by structural capital (SC) and relational capital (RC), and BDA demonstrates a positive and noteworthy correlation with PS. Furthermore, EL is positively associated with BDA in a significant manner. Practical implications- The finding of this study reinforce the corporate experience of BDA and suggest how senior levels of the IT sector can promote SC, RC, and EL. Originality/Value- This study is one of the first to consider big data analytics as an important antecedent of project success. With little or no research on the interrelationship of big data analytics, intellectual capital and knowledge sharing the study contributes by investigating the mediating role of intellectual capital and knowledge sharing on the relationship between big data analytics and project success.

The use of infrastructure as a catalyst for Indonesia’s economic growth faces significant challenges. One example is the construction projects, which have not reached the intended goal and have led to an increase in investment cost compared to the original plan. Additionally, the interaction between the government and companies involved in toll-road construction projects under the public-private partnerships (PPP) mechanism has yet to produce good quality project governance and expected project performance. This study aimed to find empirical data on the determination of project intellectual capital and project ownership structure through good project governance on toll-road project performance in Indonesia. This study adopted a quantitative approach that involved data collected through a survey conducted among toll-road projects from 2015 to 2019. The data was analyzed with Structural Equation Modeling Partial Least Square (SEM-PLS). The results showed that project intellectual capital and project ownership structure significantly affected good project governance. Good project governance Practices significantly affected project performance. Project intellectual capital and project ownership structure influenced project performance through the mediation of good project governance. Conversely, two hypotheses were not supported by the data, i.e., the effect of project intellectual capital and project ownership structure on project performance. The findings of this research contributed to the literature regarding the implementation of collaborative governance in PPPs toll road development projects in Indonesia by providing a framework and assessment tools, which could be valuable for researchers and policymakers in analyzing and evaluating the governance and performance of toll road construction PPP projects.

This study aims to investigate the alignment of emerging skills and competencies with Continuous Professional Development (CPD) programs in the accounting and auditing professions. The research focuses on enhancing the intellectual capital within these sectors, as dictated by the demands of the modern knowledge economy. Employing the World Economic Forum’s (WEF) framework of emerging skills for professional services, a comprehensive content analysis is conducted. This involves reviewing 1009 learning outcomes across 248 CPD courses offered by the global professional accounting body. The analysis reveals that while the existing courses cover all WEF-identified skills, there is an unaddressed requirement for a specialized focus on specific competencies. The study also notes gaps in clearly articulated learning outcomes, highlighting the need for more explicit statements to facilitate effective skills development and knowledge transfer. This research contributes to the ongoing discourse on intellectual capital management strategies, providing actionable recommendations for professional organizations. It fills a critical gap in understanding how CPD offerings can be optimized to better prepare accounting and auditing professionals for the evolving knowledge economy.

The use of artificial intelligence (AI) is related to the dynamic development of digital skills. This article focuses on the impact of AI on the work of non-profit organizations that aim to help those around them. Based on 10 semi-structured interviews, it is presented here how it is possible to work with AI and in which areas it can be used—in social marketing, project management, routine bureaucracy. At the same time, workers and volunteers need to be educated in critical and logical thinking more than ever before. These days, AI is becoming more and more present in almost all the activities, bringing several benefits to those making use of it. On the one hand, by using AI in the day-to-day activities, the entities are able to substantially decrease their costs and have the advantage of being able to have, in most cases, a better and faster job done. On the other hand, those individuals that are more creative and more innovative in their line of work should not feel threatened by those situations in which organizations decide to use more AI technologies rather than human beings for the routine activities, since they will get the opportunity to perform tasks that truly require their intellectual capital and decision making abilities.