EconLit

Over the last decades, environmental, social, and governance (ESG) factors become pivotal in organizations' strategy formations and investment decisions. These factors are essential in evaluating business sustainability and its impact on society. Increasing regulatory requirements, investors' expectations, and consumer awareness are driving companies to adopt sustainability principles, but the impact of ESG on companies' financial performance is still a widely debated topic. This article analyses whether disclosure of ESG data affects the profitability of the European and the United States of America (USA) industrial sector companies. By employing a robust linear regression model, the authors aim to identify if information disclosure of ESG's pillars (environment, social, and governance) affects companies' profitability, as assessed by EBIT (Earnings before interest and taxes). The analysis covers 2015-2022 data of the 58 USA corporations and the 124 European companies in the industrial sector. The research findings show different results for industrial sector companies in Europe and the USA. Although a positive and statistically significant relationship is observed for both regions when analyzing the environmental ESG pillar, the results of the social and governance pillar relationship with EBIT show opposite results. The article is expected to contribute to understanding how ESG (environmental, social, and governance) data disclosure impacts companies' financial performance in the European and USA industrial sectors. A key contribution to this research is the indication of region-specific effects within the model, suggesting that further investigation of regional differences and their ESG-related policies would be valuable.

The integration of Artificial Intelligence (AI) into the creative economy, together with its potential transformative effects on creative industries, represents a burgeoning and rapidly evolving area of research. This article aims at contributing to the ongoing debate by analyzing the latest and most relevant literature and providing fresh insights from experts in the field of creative industries. Semi-structured interviews were conducted with five Lithuanian experts selected through purposive sampling based on their engagement in public discussions on AI-related risks and opportunities. This study draws on expert interviews in order to identify problems and opportunities, provide suggestions, and build a theoretical framework for future research on the impact of AI on the creative economy. The findings reveal the significant role of AI in creative industries such as music, advertising, journalism, and design: experts agree that while AI expands creative possibilities, it also raises concerns about originality, quality, and market dynamics. Experts further highlight the potential of AI to globalize local creative industries but warn of risks like job displacement, declining artistic uniqueness, and ethical challenges in authorship and copyright. The economic value of AI-generated works remains open to debate, particularly due to unresolved copyright issues, extending to whether AI prompters should be recognized as authors. Regulatory frameworks, especially within the EU, are still evolving, with experts emphasizing the need for clearer guidelines and transparency regarding AI-generated content. Finally, this study underscores the necessity of balanced regulations, ethical considerations, and adaptive strategies.

With the swift pace of urbanization and industrialization, air pollution has emerged as a critical issue, severely impacting public health and impeding the progress toward sustainable development. This study delves into the nexus between Financial Inclusion (FI) and Air Pollution Reduction (APR), employing a balanced panel dataset that encompasses 255 Chinese prefecture‐level cities from 2011 to 2022. Through the application of econometric models and a series of robustness tests, we uncover an inverse U‐shaped dynamic between the advancement of FI and APR. Our findings indicate that during the nascent stages of FI, there is a positive impact on APR. However, this beneficial effect plateaus and potentially reverses when FI progresses beyond an optimal threshold. Further analysis elucidates three primary economic channels through which FI may influence APR: alleviation of energy poverty, stimulation of innovation, and household consumption. Notably, these mechanisms exhibit distinct patterns of influence across cities with varying levels of economic development and geographical locations. The findings hold significant implications for policy‐making, suggesting that the Chinese government must balance the acceleration of FI with a keen awareness of its regional impacts. Tailored environmental policies and innovative financial instruments can foster green growth and sustainable development.

This paper explores the climate change performance of the Baltic States—Estonia, Latvia, and Lithuania—through the lens of global climate indices, with particular emphasis on the Climate Change Performance Index (CCPI). As EU member states, the Baltic countries are subject to increasingly ambitious climate and energy policies driven by the European Green Deal and the Fit for 55 package. Based on analysis of climate performance indicators and other composite indexes, this study assesses the methodological approaches to climate change performance measurement and applies these tools to evaluate the Baltic States. Comparative analysis with indices such as the CCPI, the Environmental Performance Index (EPI), the Transition Performance Index (TPI), Climate Risk Index (CRI), and the European Extreme Events Climate Index (E3CI) offers a multidimensional view of both climate change mitigation policy effectiveness and climate vulnerability. The findings highlight the region’s relatively favorable climate policy performance, driven by proactive renewable energy and GHG emissions reduction strategies, while underscoring the need for ongoing adaptation measures.

Sustainable development has become a strategic objective for contemporary businesses. It aims to ensure long-term economic growth by creating innovative products and services, efficient resource management, environmental preservation, and promoting social welfare. The interplay between client communication and the development of sustainable innovation has emerged as a critical area of study, intersecting theories of sustainability, innovation management, and communication science. This study aimed to investigate how communication facilitates customer engagement in sustainability initiatives and to explore the creation of sustainable innovations in the Lithuanian business context. The research employed qualitative content analysis to examine the web pages of the largest Lithuanian business organisations. The primary objective was to identify the communication strategies used by these organisations to involve clients in sustainable innovation processes. One hundred publicly available organisational websites were analysed, alongside documents related to their sustainability activities (e.g., sustainability reports, corporate social responsibility reports). The research results indicate that strategic communication of sustainability efforts is essential for promoting client participation in sustainable development processes. Moreover, client involvement is a critical factor in achieving the desired outcomes of sustainability initiatives, particularly in the context of sustainable innovation within Lithuanian businesses.

The growing frequency of climate-related events underscores the urgent need for effective adaptation strategies alongside mitigation efforts. This study investigates the motivations driving climate adaptation behaviors in Lithuania, a region less immediately affected by climate change impacts. Drawing on survey data from 1,013 respondents, the research applies established theoretical frameworks, including the Theory of Planned Behavior and Value-Belief-Norm Theory, to analyze economic, ecological and social motivators for adaptation actions. Results reveal that financial considerations, such as affordability and incentives, are the strongest drivers, followed by social influences, including interpersonal encouragement and moral satisfaction. Ecological motivations, while impactful, are predominantly linked to actions with visible local environmental benefits. Demographic analyses highlight age-related differences in motivations, with younger respondents displaying higher ecological and economic concerns, and gendered patterns showing females prioritizing social and ecological values. The findings emphasize the importance of localized strategies that align interventions with dominant motivators and demographic preferences, fostering inclusive and effective climate adaptation policies. This study contributes a nuanced understanding of adaptation behaviors in less vulnerable regions, offering insights for targeted communication and policy design.

As industrial organizations use more technology, systems' data production capacities improve. Thus, big data analytics (BDA) is becoming more critical. BDA and supply chain integration (SCI) require IoT technology to gather, transmit, and process enormous amounts of real-time data from multiple sources. Because IoT devices are equipped with sensors and actuators that collect and share data from the physical world, these devices generate large amounts of data regarding product movement within the supply chain, environmental conditions, equipment status, etc. These data serve as a valuable source of information for BDA. Additionally, IoT devices facilitate communication and collaboration between different supply chain components. Suppliers, manufacturers, distributors, and retailers can share real-time data to coordinate operations and respond quickly and efficiently to changes. This affects SCI positively. In this context, this study investigated the impact of manufacturing companies' use of IoT technology on their BDA capacity and SCI. As a result of the structural equation model analysis, it was found that the use of IoT technology positively affects BDA capacity and SCI. It has been determined that BDA capacity has a significant positive effect on SCI. According to the research results, suggestions were made to companies and researchers.

Research background: Increasing CO2 emissions place considerable strain on environmental performance, whereas the digital economy, as a transformative economic paradigm, has been identified as an essential catalyst for mitigating environmental effects. However, the inherent limitations of conventional decomposition models have led previous decomposition analyses to overlook the driving effect of the digital economy on CO2 emissions. Purpose of the article: Examining the impacts of the digital economy within the framework of CO2 emissions disaggregation and subsequently projecting the future pathways of CO2 emis-sions. Ultimately, the research aims to offer scientific insights and recommendations for achieving low-carbon development through digital economic support. Methods: The actual contribution of the digital economy to CO2 emissions is assessed through a novel Generalized Divisia Index (GDI) model. Further, the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model is extended to project the CO2 trajectories across distinct scenarios. Findings & value added: The results unveil that the digital economy plays a weaker driving force in cutting CO2 emissions. Carbon intensity and energy intensity within the digital econ-omy show substantial potential to deliver CO2 emission abatement, especially in the provinces of eastern and western regions. The carbon factor is manifested as the main accelerator of increasing CO2 emissions. Under the low-CO2 scenario, CO2 emissions driven by the digital economy will meet the emission goals ahead of schedule, while reductions will suffer con-straints in the baseline and high-CO2 scenarios. The findings provide an empirical basis and scientific reference at the factor decomposition level for the digital economy to support CO2reduction.

Commodities can be treated as an alternative investment, a hedging strategy, or a diversification opportunity. Various types of commodities, especially metals, usually are not strongly affected by inflation, and the trends of their prices are not correlated with other investment instruments. To participate in the metals area of the commodity market, an investor can buy shares of companies from the basic materials sector. Such companies are involved in discovering, developing, and processing raw materials. However, as not all the companies from the basic materials sector deal with precious metals, it is worth adding gold futures to such a portfolio. The aim of this paper is to compare a portfolio of the basic materials sector stocks against a similar portfolio hedged with gold. Our findings revealed that hedging a commodities’ portfolio with gold minimizes both profits and losses and can be suitable for risk-averse investors. The research results can be applied by individual investors and investment managers to choose the most appropriate investment approach.

The selection of appropriate solution strategies to deal with the disruption in project management has become an essential topic. The evaluation of the ranking of solution strategies for dealing with disruption as a complex multi-criteria decision-making (MCDM) problem includes several alternatives with conflicting criteria in the implementation phase of the project. This paper introduces a new MCDM method by a novel integration of grey relational analysis (GRA) and measurement alternatives and ranking according to the compromise solution (MARCOS) approaches under interval-valued fuzzy sets (IVFSs). The contribution of this paper is not only to extend the MARCOS method with both GRA techniques and IVFSs but also to propose a method for weighting the criteria that considers both the subjective and the objective weight based on entropy in an integrated manner. In this proposed method, the subjective weights assigned by decision makers (DM) and the objective weights are based on interval Shannon’s entropy theory. Subsequently, the proposed method is evaluated through an empirical example, which demonstrates its applicability and validity in prioritising solution strategies for managing project disruption. The paper also provides managerial insights.