Search Results (1,163)

Systematic risk plays a central role in company valuation, enterprise risk management, and sustainable investment. However, conventional approaches primarily rely on historical beta estimates and provide limited insight into the factors associated with future changes in systematic risk. This study develops an AI-supported framework for identifying the determinants of one-year-ahead industry beta coefficients for the US economy by combining macroeconomic variables with risk indicators derived from global news analytics. Annual industry betas published by Damodaran are transformed into monthly observations to align with lagged explanatory variables. The analysis combines macroeconomic indicators with twenty-two artificial intelligence-supported risk categories extracted from the GDELT database, collectively representing Dynamic Sustainability Risk. The empirical results show that historical beta persistence alone does not fully explain future industry beta coefficients. Sustainability-related factors—including ESG, supply-chain, technological, strategic, and labor-market risks—consistently appear among the significant determinants across industries, complementing traditional macroeconomic variables. Furthermore, forward-looking systematic risk is associated with interactions between macroeconomic conditions and dynamic sustainability-related risks rather than with historical financial information alone. Rather than developing a forecasting model, the proposed framework provides an interpretable approach for identifying the macroeconomic and sustainability-related determinants associated with future industry beta coefficients, thereby supporting company valuation, enterprise risk management, and sustainable financial decision-making. Full article

Purpose: This study aims to examine the effects of intellectual capital (IC), environmental, social, and governance (ESG), and competitive advantage (CA) on firm value (FV), with board gender diversity (BGD) as a moderating variable. Methodology/Design/Approach: The population comprises companies in the Asian region from 2015 to 2023. Companies were based on specific criteria, resulting in 637 companies with 5733 observations. The study used multiple regressions and moderated multiple regressions in data analysis. Finding/Result: The findings indicate that IC has a negative and significant effect on FV. ESG performance has a positive and insignificant effect on FV, while CA has a positive and significant effect on FV. BGD moderates the relationship between IC, ESG, and CA on FV. It strengthens the effect of CA on FV and weakens the relationship between IC and ESG on FV. Practical Implications: Companies must pay attention to IC, CA and BGD, these variables influence investor’s reactions in determining investments. The government should monitor ESG-related corporate activities to ensure alignment with sustainable business strategies. Institutions related to sustainability issues develop standardized ESG disclosure. Originality/Value: The results contribute to signaling theory and resource-based theory. Limited prior research utilizes BGD as a moderating variable, highlighting the novelty of this study. Full article

Corporate resilience has become a critical capability for firms to cope with increasing environmental uncertainties and external shocks. Against the backdrop of the rapid development of the digital economy, this study examines whether digital transformation enhances corporate resilience and further investigates whether environmental, social, and governance (ESG) performance serves as a complementary transmission mechanism in this relationship. Drawing on resource orchestration theory, this study uses panel data of Chinese A-share listed companies from 2016 to 2024 and estimates a series of firm fixed-effects models. The results indicate that digital transformation significantly enhances corporate resilience, and the findings remain robust after a series of robustness checks and endogeneity tests are conducted. Further analysis reveals that ESG performance partially mediates the relationship between digital transformation and corporate resilience, suggesting that responsible business practices complement the resilience-enhancing effect of digital transformation. The results of the heterogeneity analysis further indicate that the positive effect of digital transformation is significantly stronger for high-tech firms. In addition, firms exhibit substantial variation in the consistency between digital transformation communication and actual digital investment. Further analysis suggests that greater alignment between digital transformation communication and substantive implementation is associated with stronger resilience outcomes, providing supplementary evidence on the implementation process of digital transformation. This study contributes to the literature on digital transformation and corporate resilience by revealing the resource orchestration process through which digital transformation creates organizational value and identifying ESG performance as a complementary transmission mechanism. The findings also have practical implications for firms seeking to strengthen their resilience and achieve sustainable development in an increasingly uncertain environment. Full article

This paper assesses the impact of uncertainty for investors on the economic valuation of medical innovation projects for orphan drugs or rare diseases. Conventionally, investor evaluation uses the deterministic discounted cash flow (DCF) method with an appropriate sensitivity analysis that captures some level of uncertainty. In healthcare, and particularly for rare diseases, the levels of uncertainty in financial outcomes (return on investment and net present value (NPV)) are broader than the ones normally captured by the DCF formula. Uncertainties include R&D costs, the approval process (level and timing) for obtaining reimbursement, sales, the production cost, and the failure probabilities of the clinical trial phases, to name a few. Additionally, there is not only one type of investor to consider, but different investors exposed to different levels of risk management of their investment. Our analysis tried to capture those two dilemmas (higher levels of uncertainty and different investor types) in two ways. One way was to identify a better method to enhance the different levels of uncertainty. The real option method of evaluation was proposed instead of DCF. For instance, the real option method better captures the uncertainty of the different phases of product development. The other way is to differentiate the investor types through their level of risk assessment perspectives. Small investors and start-up companies may see more benefit in applying the real option methodology to estimate their NPVs at different time points during product development. In summary, our evaluation identified various types of uncertainty when assessing an investment, along with methods to manage their effect on the economic/financial outcomes of medical innovations. Given the high uncertainty associated with early-stage drug development, such as orphan drugs for rare diseases, the real options approach is preferable to traditional DCF models. The analysis also showed that there is not just a single investor perspective to consider but specific perspectives that enhance the prime use of the real option methodology. Full article

The objective of this paper is to examine the United Arab Emirates (UAE) as a test case of Gulf energy transition finance by analyzing how a hydrocarbon-dependent economy is constructing the financial, regulatory, and institutional architecture required to move from net-zero pledges to climate finance flows. Rather than treating climate finance as a set of isolated instruments, the paper conceptualizes the UAE’s approach as a state-led transition-finance model shaped by Gulf state capitalism, sovereign wealth accumulation, national oil company strategy, financial regulation, and post-COP28 climate diplomacy. Using a qualitative policy and institutional review, the paper maps the UAE’s transition-finance architecture across three interrelated dimensions: institutions and governance, financial instruments, and policy alignment. It examines the role of federal strategies such as Net Zero 2050 and the UAE Energy Strategy 2050, regulatory actors including the Central Bank of the UAE, the Securities and Commodities Authority (SCA), Abu Dhabi Global Market (ADGM), and Dubai Financial Services Authority (DFSA), and key financial mechanisms including green bonds and sukuk, sustainability-linked finance, sovereign wealth fund investments, national oil company decarbonization strategies, blended-finance platforms, and carbon-market mechanisms. The analysis finds that the UAE has developed a distinctive state-led, finance-centric model for financing the energy transition. This model enables rapid capital mobilization, de-risking of private investment, and strong international positioning, particularly following COP28 and the launch of ALTÉRRA. However, its effectiveness is constrained by unresolved tensions between net-zero ambition and hydrocarbon expansion, fragmented sustainable-finance regulation, limited carbon-pricing signals, uneven disclosure practices, underdeveloped domestic green capital markets, and restricted access to green finance for SMEs. The paper argues that the UAE’s climate-finance architecture is best understood neither as simple green diversification nor as symbolic climate positioning, but as an emerging Gulf model of transition finance: well-capitalized, and institutionally coordinated, yet structurally shaped by the same hydrocarbon rents and state-led governance logics it seeks to transform. By positioning the UAE as a benchmark, the paper contributes to debates on climate finance, state capitalism, and transition governance in hydrocarbon-dependent economies, while identifying the coherence gaps to be addressed for climate finance to support economy-wide decarbonization. Full article

Enhancing supply chain resilience has become crucial for sustainable manufacturing development as firms face repeated disruptions from pandemics, geopolitical shocks, logistics bottlenecks, and climate-related uncertainty. As digital finance alleviates corporate financing constraints and improves information transmission across supply chains, it may strengthen supply chain resilience, thereby supporting the sustainable development of manufacturing firms. Accordingly, this paper examines this effect using panel data consisting of 21,060 firm-year observations of Chinese A-share listed manufacturing firms spanning the period 2011–2023. It combines the proxy of digital finance, which is the city-level Baidu search index for digital finance, with the entropy-weighted and firm-level supply chain resilience index to assess its sustainability. Based on the fixed-effects model, digital finance positively affects the resilience of manufacturing companies’ supply chains and, by extension, promotes the sustainable development of manufacturing supply chains. We also find that digital finance improves manufacturing supply chain resilience by enhancing information transparency, resolving maturity mismatches between investment and financing, and mitigating financial risks. This impact is larger in poorly developed traditional financial regions, firms with poor governance, and in growing companies. Policy recommendations center on advancing digital supply chain finance, strengthening data governance, and improving risk management systems to reinforce supply chain resilience and promote the long-term sustainable development of manufacturing firms. Full article

This study aims to identify and evaluate the impact of operational and organizational activities on reducing energy consumption in selected stages of agricultural transport equipment component production. The research focused on manufacturing companies from the agricultural machinery sector, characterized by high energy intensity and operational complexity. The empirical study was conducted among 121 experts representing manufacturing enterprises. The results indicate that enterprises achieve the highest level of implementation in organizational and Lean Manufacturing-related activities, particularly in reducing downtime, optimizing production scheduling, limiting empty transport runs, and eliminating overproduction. In contrast, technological and investment-intensive solutions, such as heat recovery systems, advanced energy monitoring, and digital simulation tools, remain implemented to a significantly lower extent. The findings also reveal a moderate level of maturity in energy management practices and limited integration of energy-related data into strategic decision-making processes. The study confirms the multidimensional nature of energy efficiency and highlights the importance of integrating Lean Manufacturing principles with digital technologies and systemic energy management. The proposed research model may serve as a practical diagnostic tool supporting the identification of key improvement areas for sustainable production development in manufacturing enterprises. This study aims to identify and evaluate the impact of operational and organizational activities on reducing energy consumption at selected stages of agricultural transport equipment component manufacturing. The research focused on manufacturing companies operating in the agricultural machinery sector, which is characterized by high energy intensity and operational complexity. The empirical study involved 121 experts representing manufacturing enterprises. The results indicate that organizational and Lean Manufacturing-related practices exhibit the highest levels of implementation, particularly those aimed at reducing downtime, optimizing production scheduling, limiting empty transport runs, and eliminating overproduction. In contrast, technology-intensive and capital-intensive solutions, such as heat recovery systems, advanced energy monitoring, and digital simulation tools, show substantially lower implementation levels. The findings also reveal a moderate level of maturity in energy management practices and limited integration of energy-related data into strategic decision-making processes. The findings confirm the multidimensional nature of industrial energy efficiency and highlight the importance of integrating Lean Manufacturing principles with digital technologies and systematic energy management. The proposed research model may serve as a practical diagnostic tool for identifying key areas for improvement in the development of sustainable manufacturing. Full article

Global angel investment and venture capital are key financial drivers supporting the long-term growth of technology companies, and they play a vital role in improving the global science and technology innovation financial system and advancing green and sustainable transformation. This paper uses data on technology-sector companies listed on the A-share market from 2017 to 2025 to construct a multi-period DID model. It empirically examines the impact of angel investment and venture capital on the sustainable development of technology companies and investigates the moderating effect of ESG performance. The study finds that angel investment can significantly enhance the level of sustainable development in technology firms. Mechanism tests indicate that angel investment indirectly empowers sustainable development by attracting and introducing venture capital. The moderating effect shows that strong ESG performance positively reinforces the promotional role of angel investment and venture capital in the sustainable development of technology firms. Heterogeneity analysis reveals that these enhancement and moderating effects are more pronounced in high-tech industries, private enterprises, and asset-light technology firms. These findings provide empirical evidence and policy guidance for governments worldwide to direct venture capital toward supporting science and technology enterprises, help technology firms improve their ESG governance systems, and achieve long-term sustainable operations. Full article

A This study examines the interplay between environmental, social, and governance (ESG) practices, artificial intelligence (AI) adoption, and financial performance within Saudi Arabia’s financial sector. It investigates whether AI adoption moderates the ESG–performance relationship, reflecting the sector’s ongoing digital transformation under Vision 2030. Drawing on 224 firm-year observations across banks, diversified financials, real estate investment trusts (REITs), and insurance companies, the study employs content analysis of annual reports to identify AI implementation. Panel regression models are used to test the effects of ESG practices on both accounting-based (ROE) and market-based (Tobin’s Q) performance measures, while examining AI’s moderating role. The results reveal that ESG practices significantly enhance accounting-based performance, particularly return on equity, while board size exerts a positive and board independence a negative influence. However, ESG does not significantly affect market-based valuation (Tobin’s Q). Notably, AI adoption negatively moderates the ESG–financial performance link, suggesting short-term challenges in integrating digital transformation with sustainability strategies. This study contributes to literature in three key ways. First, it provides new evidence from financial institutions in a developing economy—Saudi Arabia—where ESG and AI integration remains underexplored. Second, unlike previous research that proxies AI adoption through R&D expenditure, this study captures actual deployment of AI tools in operational activities. Third, it extends the ESG–performance debate by introducing AI adoption as a novel moderating factor. The findings offer actionable insights for managers and policymakers in emerging markets, underscoring the importance of developing organizational capabilities that harmonize AI-driven innovation with ESG principles to foster sustainable long-term value creation. Full article

This article examines the persistent gap between the formal recognition of work–life balance (WLB) policies and their effective implementation in Italy, within the broader European framework of gender equality. It adopts a multi-level approach that integrates the analysis of EU policy developments—particularly Directive (EU) 2019/1158—with pandemic-related dynamics and organizational practices The study is based on a combined methodology, including policy analysis, recent statistical evidence, and an original empirical dataset on corporate initiatives, focusing on the Code of Corporate Self-Regulation on Maternity. The findings indicate that, despite significant regulatory advances, structural, cultural, and institutional constraints continue to limit the accessibility and uptake of WLB measures in Italy. These shortcomings were further exacerbated during the pandemic, which intensified unpaid care burdens and reinforced traditional gender roles. Company initiatives show uneven levels of engagement and are often driven by organizational capacity rather than a substantive commitment to gender equality. Overall, the study highlights that the effectiveness of WLB policies depends on the interaction between institutional capacity, cultural norms, and governance arrangements. It concludes that bridging the gap between formal rights and everyday practices requires a shift toward integrated strategies based on social investment, coordinated governance, and shared responsibility. Full article

Corporate sustainability reporting has become a central component of corporate governance under the European Sustainability Reporting Standards (ESRS); yet organizations continue to face challenges in integrating sustainability data into decision-making processes. This study addresses this gap by developing a system dynamics (SD) model for analyzing corporate sustainability performance based on ESG indicators. The proposed framework integrates environmental, social, and governance variables into a unified dynamic structure, capturing feedback loops, time delays, and interdependencies among sustainability dimensions. The model is empirically tested using a ten-year dataset from a fuel retail company, enabling both historical validation and scenario-based analysis. The results demonstrate that the model successfully reproduces observed trends in resource efficiency, safety performance, and social indicators while highlighting trade-offs associated with business growth, particularly in energy consumption and CO₂ emissions. Sensitivity analysis demonstrates that the sustainability index remains stable under uncertainty in normalized ESG indicator values. Scenario simulations indicate that several sustainability targets for 2030 are achievable under current development trajectories; however, maintaining progress requires continuous investment and organizational commitment. The study contributes to sustainability research by integrating ESRS-based indicators into a dynamic modeling framework and provides a practical decision-support tool for corporate sustainability management, enabling more informed planning, performance evaluation, and strategic alignment with long-term sustainability goals. Full article

The objective of this study is to develop a methodological approach to the integral assessment of the investment attractiveness of metallurgical enterprises to improve the efficiency of investment activities and the implementation of projects and ensure sustainable development. The metallurgy industry faces the challenge of balancing efficiency goals and sustainable objectives (ESG) and risks. Our approach takes into account the relationship between investment potential, realized opportunities, and the level of risk. Based on a systematic analysis of theoretical approaches, an integral investment attractiveness index is proposed that aggregates investment potential (consisting of seven sub-potentials), an assessment of the results of project implementation, and an aggregated risk index. Assessing investment attractiveness is important for ensuring the sustainable implementation of effective projects and determining their priority. A panel dataset was constructed using data from two metallurgy companies. The relationship between investment attractiveness and classical indicators (ROIC, EVA, MVA, Tobin’s Q, and P/BV) is examined through panel regression with fixed effects, cross-correlation analysis of the temporal structure of relationships, a CUSUM test for model stability, and decomposition of investment attractiveness changes. Decomposition of investment attractiveness changes makes it possible to quantify the contribution of potential, opportunities, and risk to the dynamics of investment attractiveness across various periods, including crisis and post-crisis ones describing the specifics of the metallurgic industry. The presented methodology is relevant for increasing the efficiency of project implementation within the framework of an integral company policy and contributes to the acceleration of industrial implementation of sustainable projects in the metallurgy sector. Full article

Artificial intelligence (AI) is increasingly viewed as a key driver of sustainable development, yet evidence on its role in corporate sustainable green innovation remains limited. Drawing on Resource Orchestration Theory and Signaling Theory, this study examines the impact of AI capability on sustainable green innovation using panel data from Chinese A-share listed companies during 2014–2023. The results show that stronger AI capability significantly promotes sustainable green innovation. AI investment serves as a mediating mechanism. However, the estimated indirect effect is negative, suggesting that the process of AI implementation may involve resource reallocation and organizational adjustment costs before innovation benefits can be fully realized. Environmental investment strengthens the positive impact of AI capability, whereas digital transformation weakens it. Robustness tests confirm the reliability of the findings. Further analyses indicate that the positive effect of AI capability is more pronounced in non-state-owned enterprises, low-technology firms, and firms in the growth stage. By revealing the mechanisms and boundary conditions through which AI capability influences sustainable green innovation, this study enriches the literature on AI-enabled sustainability and offers practical insights for firms pursuing long-term sustainable development. Full article

In this article we examine the real and financial effects of public credit guarantees issued to SMEs in different regions in Croatia. Credit guarantee schemes are aimed at increasing lending to SMEs and are widely spread around the world. However, the evaluation of their efficiency is lagging behind and existing empirical evidence on the impact of state guarantees and other forms of government interventions in the credit market is mixed. Hence in this article we are investigating the impact of public credit guarantees on company development. Analysis is conducted using data on credit guarantees that the Croatian Agency for SMEs, Innovations and Investments (HAMAG-BICRO) gives to the SME sector, as well as data on company financials and demographics. Results show that companies that received public credit guarantees indeed have better performance than similar companies that did not get guarantees. Still, the difference in performance is not visible immediately, but only after several years (depending on the indicator used). Full article

The construction sector continues to experience elevated levels of insolvency, driven by an interplay of structural vulnerabilities and macroeconomic pressures, including supply chain disruptions and cost inflation. These challenges have been particularly prominent in Australia, especially among micro and small construction firms, which account for over 90% of reported insolvency cases. In 2024, the Australian construction sector contributed nearly one-quarter of all company insolvencies nationally. This study undertakes a comprehensive review of construction insolvency research, synthesising key themes, causes, early warning indicators, and mitigation strategies, while contextualising global insights using empirical evidence from the Australian construction sector. The methodology integrated systematic literature screening, scientometric analysis, and critical thematic synthesis with a descriptive and selective statistical examination of the Australian Securities and Investments Commission (ASIC) data, complemented by practice-informed insights. The review identified dominant research trajectories, centred on financial risk management, insolvency prediction models, project-level cost and governance risks, and emerging data-driven approaches. Empirical analysis revealed that inadequate cash flow (~16–20%), poor strategic management (~12–18%), and weak financial controls (~11–15%) consistently rank among the leading causes of construction firm failure over the last decade. Indicators such as non-payment of statutory obligations and deteriorating working capital are observed in over half of insolvency cases, highlighting persistent structural fragility. Although global strategic focus areas emphasised financial monitoring and early warning systems, practice-informed findings indicated that effective mitigation requires their operationalisation through capability development, early intervention tools, regulatory oversight, and stakeholder-informed support mechanisms. The study shows how global insolvency risk concepts align with Australian regulatory evidence and highlights the need to translate early-warning approaches into accessible tools and support mechanisms for micro and small construction firms. Full article