The Lithuanian laser industry is considered one of the country’s most appreciated manufacturing sectors due to its high value-added output, growing potential significance, and the wide range of future applications of laser technologies. Despite considerable global potential and increasing export volumes, the laser industry faces challenges such as intensifying global competition, short product life cycles, high production costs, demand for highly skilled employees, dependence on global supply chains, standards, and regulations. The core aim of the research is to identify the main economic and non-economic determinants of laser export development in Lithuania in the context of rapid technological progress and geopolitical uncertainty. To empirically assess the impact of selected factors on the export results of the Lithuanian laser industry, correlation analysis, the Granger causality test, regression model, and the autoregressive distributed lag (ARDL) model were used. The results indicate that the export performance of the Lithuanian laser industry is positively affected by investment in patents and licenses. However, after controlling for other selected factors, interest rates, the number of military conflicts, and R&D expenditure were found to have a negative effect. Strategic support for intellectual property acquisition and mitigation of external economic risks are key insights for policymakers and stakeholders.

As artificial intelligence technology rapidly develops, enterprises pursuing intelligent transformation may face innovation resource allocation dilemmas. On one hand, the construction and maintenance of AI systems require substantial financial investment, and this high-cost pressure may crowd out resources traditionally allocated to innovation activities. On the other hand, excessive dependence on AI may lead enterprises to neglect talent cultivation and equipment updates, resulting in technological path lock-in. Based on resource allocation theory, principal-agent theory, and path dependence theory, this paper uses Chinese A-share listed companies from 2013-2023 as research samples and employs text analysis methods to construct an enterprise AI application intensity index to explore the impact of AI on enterprise innovation behavior and its mechanisms. The research finds that: (1) AI application has a significant crowding-out effect on enterprise innovation; (2) this crowding-out effect is primarily realized through two channels: reducing innovation talent investment intensity and cutting professional technical equipment configuration; (3) heterogeneity analysis shows that characteristics such as state ownership, high market competition, low financing constraints, high technology intensity, and high management shareholding can effectively mitigate AI's inhibitory effect on innovation. This research not only deepens theoretical understanding of the relationship between AI and enterprise innovation but also provides practical guidance for optimizing innovation resource allocation during enterprise digital transformation.

The high incidence of financial fraud in listed companies in recent years has raised more concerns about the quality of financial reporting (FRQ) for sound development purposes. Although auditing is used to ensure FRQ for listed companies, more and more companies are subject to financial and regulatory penalties for financial fraud or non-compliance even after receiving standard unqualified audit opinions. Recent new government regulations in China make it more difficult to change auditors, so companies now tend to use audit fee as a proxy to influence audit opinions. Therefore, it is crucial to investigate the relationship between audit fees and FRQ in the Chinese context. This research takes this perspective to measure and discuss FRQ of listed companies in China using the proxy audit fee. In this research, 25,482 A-share listed companies in China are selected to empirically investigate the relationship between audit fee and FRQ, and the authors innovatively divide the audit fee into abnormal audit fee and reasonable audit fee, and use the proportion method to calculate whether the audit fee is abnormal. The research finds that there is a positive relationship between reasonable audit fee and FRQ, while the relationship between abnormal audit fee and FRQ is negative. The results show that the division and measurement of audit fee is a good proxy to measure FRQ, which will contribute to the healthy development of listed companies and the capital market as a whole.

This study conducts a systematic literature review on supply chain management (SCM) strategies and their influence on Small- and Medium-sized Enterprise (SME) performance in emerging economies. Covering 241 Scopus-indexed articles from 2001 to 2024, the analysis utilizes bibliometric and content analysis with tools such as RStudio, VOSviewer, and Microsoft Excel. Three main themes emerged from the analysis: (1) SCM strategies’ impact on SME performance, (2) integration and collaboration for enhanced performance, and (3) technology adoption for competitive advantage. Findings reveal notable trends, such as the growing interest in green SCM and supply chain resilience, with the UK and India leading in contributions. This research offers SMEs actionable insights for integrating supply chain strategies, enhancing collaborative planning, and refining supply chain management capabilities. Additionally, the study provides a roadmap for future research into sustainable practices, regulatory compliance, and technology driven SCM strategies to support SMEs in addressing complex market challenges.

Investments in research and development (R&D) and human capital affect economic growth by influencing total factor productivity (TFP) and competitiveness (exports). The determinants of this influence were analysed on a cointegrated panel of seven large countries and separately on five medium-sized or small countries. The results show that TFP and exports per unit of R&D or per unit of human capital mainly depend on the interconnection of these two factors, but also on capital per employee, the control of inflation, the foreign trade share in GDP, oil prices, digitalisation, electrification, the concentration of development activity related to the share of military expenditures in GDP, energy efficiency and ecological protection in the national economy. In medium-sized or small countries, the influence of regulation is greater, while the effect of development activities related to military expenditures is much smaller than in the large countries.

The aim of the study is to advance the understanding of direct and moderated effect between implemented transformational leadership style and employee innovative work behavior. The mediating role of Leader-member exchange theory and employee voice behavior is tested within the relationship of transformational leadership style and innovative work behavior. Respondents to a survey were 544 employees working in organizations in Serbia. Structural equation modeling was run by using Smart partial least square 3. to test the proposed model. Results suggest that transformational leadership style has significantly influenced employee innovative work behavior directly and through moderators as Leader-member exchange theory and employee voice behavior. This study was the first study in the Serbian business context that reveals a highly effective mediating mechanism like: leader-member exchange theory and voice behavior, which exists with transformational leadership style to increase innovative work behavior of employees. Furthermore, this study reveals additional results, like: transformational leadership style was significantly related to leader-member exchange theory and employees voice behavior, then leader-member exchange theory as well as employee voice behavior were significantly related to employees innovative working behavior.

The academic discourse on stress in the global economy and financial markets has ignited discussions regarding regulatory oversight of pension fund management and investment strategies. This study investigates how pension funds (PF) respond to short-term and long-term risks, as well as their recovery periods following market shocks. To address these inquiries, we classify financial market stress, considering both short-term and long-term risks. Utilizing the change point detection technique and Bayesian average (Zhao et al., 2019), we analyse shifts in the dynamics of PF values managed by SEB and Swedbank from 2004 to 2023. The research explores not only timings and the number of change points but also their likelihood over time. Drawdowns, recovery rates, and timing ratios are particularly insightful for assessing PF performance during crises and market disturbances. These findings contribute to the understanding of PF behaviour in various market conditions and underscore the significance of adaptive investment strategies in navigating financial uncertainties.

Despite the increasing investment opportunities in emerging technologies, strategic alliance and dynamic investment strategy suffer from a limited understanding of the market investment trends and industry convergence. Therefore, this study aims to develop a structured framework to examine the market diversification trend and the industry-to-industry influential degree. The proposed framework utilizes M&A transaction activities from the interests of buyer and target industries from 2009 to 2018 in North America. The M&A network is then examined for the difference in the structural characteristics between the buyer and target industries. This study identifies market irregularity and diversification trends and applies the initial findings as market-level evidence to elucidate industry convergence potentials. Degrees of a specific industry’s influence on other industries are also presented and discussed from the perspectives of buyer and target industries. The findings of this study contribute to the development of industry convergence conceptual model and advances knowledge regarding market diversification, collaboration-driven industry convergence, and investment strategy.

This research study investigates the transformational leadership (TFL) and IT project success nexus via the proactive behavior of employees. It further investigates the moderating impact of psychological empowerment (PE) in the nexus between TFL and proactive behavior (PB). The study also tested a moderated mediation model of the effect of TFL on IT project success mediated and moderated by PB and PE, respectively. The researcher collected data from 340 IT project experts in Pakistan through the purposive sampling technique. For data analysis, a multi-level method comprising CFA and SEM was applied. The findings indicated that TFL is significantly linked to IT project success. In addition, findings also confirmed the mediating effect of PB in the relationship between TFL and IT project success. Moreover, PE significantly moderates the relationship between TFL and PB. The results also revealed that PE moderates the indirect effect of TFL on IT project success through PB. Through the lens of self-determination theory, this study contributed to the understanding of how employee proactive behavior can play a significant role in successfully completing technology-oriented projects. In sum, the current study suggests that transformational leaders will be in a better position to encourage their employees to complete projects successfully using proactive behavior, provided their followers are psychologically empowered. The study offers valuable insights for both researchers and practitioners.

Corporate social responsibility (CSR) entails balancing economic, social, and environmental aspects of business activities. The CSR report, a crucial non-financial disclosure tool, enables firms to effectively communicate their CSR strategies, actions' impacts, achievements, and shortcomings to stakeholders. It plays a pivotal role in shaping corporate reputation and performance. Therefore, enhancing CSR report quality is of great importance. This study examines the relationship between Corporate Social Responsibility Disclosure Approaches (CSRDA) and corporate performance, with consideration of corporate reputation's role in this connection. By drawing from stakeholder theory, signaling theory, and reputational capital theory, we address the gap in understanding CSRDA and corporate reputation (CR) linkage. Using the System-Generalized Method of Moments (SYS-GMM) and bootstrapping techniques, we explore this relationship in a dataset of 943 publicly listed Chinese companies from 2011 to 2019, accounting for incomplete CSR data during the pandemic period from 2020 to 2022. Our results indicate a positive association between CSR disclosure approaches and corporate performance, mediated by corporate reputation.