Founded in 2001. Transformations in Business and Economics is an international journal of scholarly papers that publishes original scholarly articles devoted to the most important problems in the field of Economics and Management. Registered in Scopus (Q2) from 2007 and Web of Science (Q3) from 2005.
Vilniaus universiteto leidykla / Vilnius University Press
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Reviewed book: Dalia STREIMIKIENE (Ed.) (2025), Societal Challenges and Opportunities of Low-Carbon Energy Transformations, CRC Press, 400 p.
Authors: Dalia STREIMIKIENE (Ed.) Authors’ Affiliation: Kaunas faculty Vilnius University, Lithuania Title: SOCIETAL CHALLENGES AND OPPORTUNITIES OF LOW-CARBON ENERGY TRANSFORMATIONS Subtitle: Monograph Year: 2025 Publisher: CRC Press Volume: 400 pages Type of publication: e-book Language: English ISBN: 9781003517481 For more information contact: dalia.streimikiene@khf.vu.lt
Copyright (c) 2025 Author https://creativecommons.org/licenses/by/4.0
Inquiry of Suicide Rates and their Liaison with Sociocultural and Socioeconomic Indicators in Spain
In Spain, the suicide rate has been on the rise for the past few years. Research shows that people between the ages of 51 and 64 are at the greatest risk of an increased rate of suicide. The number of people committing suicide has also increased among older in recent years. The goal of this paper is an exploratory analysis of the relationship between four social dimensions and the suicide rates in different regions in Spain, without considering people diagnosed with psychological problems or mental disorders. Results showed some areas with the highest number of suicides. Remarkable Canaries region presented huge suicide rates among its population, with suicide being among the upper incidence causes of death in the region. We can highlight slight associations between leisure/social relations and satisfaction with life with the number of suicides in men, which could be contrasted with differences between the autonomous states of Spain.
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Analysis of Tourist Behaviour and Tourism Image in Hainan Province
With the development of tourism, theoretical research on tourist behaviour and tourist destinations is becoming more and more important, but currently, for the specific micro-tourism in Hainan Province, Theoretical research on context is still lacking. Therefore, this study takes tourists to Hainan, where they have published relevant travel notes as research objects. It also uses Python and other technologies to analyse the crawled network. The travel notes were systematically studied, focusing on exploring the behavioral characteristics of tourists in Hainan Province through the three dimensions of “regional relevance of tourist flow, travel motivation, and stay time” and the three dimensions of “cognitive image, emotional image, and conative image”. The research conclusion is: (1) The regional correlation of tourist flows in Hainan Province focuses on Sanya City. The four major bays of Hainan radiate outward; (2) The primary travel motivation of tourists coming to Hainan is the outdoor project experience, followed by duty-free shopping; (3) Although tourists coming to Hainan show a discrete distribution in terms of stay time, the average performance is 5-6-day multi-day stay experience type; (4) Among the six cognitive image categories of “tourist core attractions, tourist accommodation, tourist transportation, tourist entertainment, tourist shopping, and tourist food”, tourists visiting Hainan Province have the perception of core tourism attractions such as “climate and natural scenery” in tourist destinations as the strongest, and the perception of tourism products is the lowest; (5) The perception of the emotional image of tourist destinations in Hainan Province is mostly positive-oriented. Relatively speaking, there are relatively few negative perceptions, which are mainly concentrated on the three aspects of “accommodation, transportation, and integrity”; (6) Hainan Province’s tourist destinations. Conative image perception is mainly reflected in tourists’ strong recommendation intention.
Influence of the Economy on Political Decisions: The Case of Lula Da Silva’s Inaugural Speech in 2023
The main objective of this paper is to analyze how political discourse, with a strong economics and transformational approach, reaches different audiences. Specifically, we study Luiz Inácio Lula da Silva's speech at the National Congress on January 1, 2023, marking his inauguration as president of Brazil. The audiovisual content of the speech is used to investigate, through a codebook, the reality of the market environment in Brazil. The purpose is not only to analyze the competitiveness of political and economic discourse in an international context saturated with diverse messages but also to assess its contributions to the development of Brazilian society. The conclusions of this work confirm the research questions. On the one hand, Lula's discourse resonates more strongly with ideologically aligned audiences. On the other hand, he employs both verbal and nonverbal variables that help him reach the audience more efficiently.
Transformation towards a Warm and Competent Leadership
Competence and warmth, the two essential dimensions of social judgment postulated by the Stereotype Content Model (SCM), are considered to be features of leadership. A hypothesis is posed that warm and competent leaders generate more committed and loyal employees. To test our hypotheses, a cross-sectional study was performed, examining the shop workers (N = 792) of a low-cost fashion retailer. The results show that warmth has almost three times more influence on employee experience than competence. Beyond salary and other perks, employees need to feel valued by their organisations and leaders via significant interactions ―albeit not necessarily in person― and not only in terms of transactions. By failing to understand what their employees are fleeing from and how to connect with them, company leaders are putting their businesses at risk. Leaders must be humble and show interest in people; it is also necessary to implement strategies destined to develop employee talent.
Beyond Diversity Management: A Constructive Perspective on Inclusive Workplaces
Drawing on the needs identified in academic discourse, this study aims to address the theoretical and methodological gaps by conceptualising inclusion in the workplace and examining fundamental organisational processes that facilitate the management of an inclusive workplace. Additionally, it evaluates the limitations of previous research models on inclusion and proposes a new model for an inclusive workplace. The authors used the grounded theory method to conduct interviews with a total of 14 respondents. The findings conceptualise the multifaceted nature of inclusion and unfold the process of managing an inclusive workplace in Pakistan. Furthermore, the findings led to the development of a model of inclusive workplaces, which aims to enhance inclusivity at the workplace and address the challenges associated with a diverse workforce. The current study enriches the theoretical understanding of inclusion by improving the concept’s generalisability based on data, enhancing the theoretical knowledge of inclusion from a new perspective.
Synergistic Effects of Content Structure and Sensory Elements: Exploring the Impact Mechanism of Tourism Short Videos on Travel Intention
Tourism short videos have become pivotal tools that influence tourists’ decision-making amid the rapid development of digital marketing. Existing studies inadequately address the mechanisms through which short video content shapes travel intentions. To explore the relationship between content structure and sensory elements, the interaction mechanisms between content structure and sensory elements in tourism short videos and their impacts on travel intention were unravelled by employing narrative communication theory and information processing fluency theory through two scenario-based experiments. The synergistic effects of video content structures (narrative vs. non-narrative) and sensory elements (visual–content matching, background music tempo) in consumer decision-making processes were examined. Results reveal that narrative short videos significantly enhance travel intentions by evoking emotional resonance through plot development and character portrayal. The visual–content matching effect plays a critical role. Slow-tempo compositions intensify emotional immersion in narrative videos, while fast-tempo tracks amplify visual salience and instantaneous attentional capture in non-narrative formats. These conclusions elucidate the interaction mechanisms underlying content–sensory synergy in tourism short videos, thus providing theoretical foundations for video dissemination strategies and practical guidance for content creation in destination marketing.
Cultural Values and Knowledge through Hofstede’s Framework: A Bibliometric and Bipartite Network Study of Cooperatives
This study explores how cultural values, based on Hofstede’s dimensions, are applied to the study of cooperatives, identifying dominant themes, key academic contributions, and regional patterns in the literature. Understanding how cooperatives, as democratic and member-driven organisations, operate within different cultural contexts offers new insights into the intersection of culture, governance, and the social economy. A bibliometric analysis is conducted to classify, categorise, and identify relationships among academic publications on cooperatives and cultural values. The study employs VOSviewer to map intellectual structures, key thematic clusters, and regional trends. Additionally, a bipartite network co-occurrence analysis using Python is used to examine the intersection of Hofstede’s cultural dimensions, regional influences, and thematic keywords, thereby providing a structured framework for understanding cooperative governance. The results indicate that Hofstede’s framework can provide valuable insights into cooperative governance, as its dimensions align well with the democratic and member-driven nature of these organisations. Based on the results, the influence of cultural factors in cooperatives varies according to regional contexts and the specific purposes or industries in which they operate. This variability underscores the importance of considering local cultural nuances when evaluating cooperative practices. The study identifies key thematic areas to correctly explore culture on cooperatives based on Hofstede’s dimensions. The present study provides a systematic examination of the intersection between cultural dimensions and cooperatives, an approach to cooperatives culture study as it has been marginal so far. By mapping out the structure of the research area and analysing regional and keyword trends, this study contributes to a deeper understanding of how cultural values influence cooperative governance and decision-making across diverse socio-economic contexts proposing a research agenda from the perspective of Hofstede’s ideas.
How Multidimensional Proximity Affects Collaborative Innovation Performance in New Energy Vehicles
The collaborative innovation performance in new energy vehicles (NEVs) is significantly affected by such factors as geographical proximity, technological proximity, and organizational proximity among innovation subjects, but the dynamic influence of multidimensional proximity on collaborative innovation performance has been scarcely investigated. To identify the influence of proximal cooperative relationships on the innovation performance in NEVs, this study employed the cooperative patent data of NEVs in China from 2005 to 2022 and applied the social network analysis method and quadratic assignment procedure （QAP）analysis method to verify the influence of multidimensional proximity on collaborative innovation in NEVs in different periods on the basis of transaction cost theory and resource dependence theory. Results show that proximity is an important influencing factor of cooperative relationships, and proximity factors affect cooperation differently in diverse development periods of the NEV industry. Specifically, technological proximity plays a significant positive role in promoting collaborative innovation, while geographical proximity and organizational proximity have a reduced effect on collaborative innovation. The obtained conclusions reveal the influence mechanism of multidimensional proximity on the collaborative innovation in NEVs to some extent, which can provide decision-making references for the deep integration of NEV industry–university–research.
Innovation Potential and Tourism Development in the EU: The Impact of Digitalisation and Research Investment on Tourism Performance
This paper examines the relationship between the innovation potential of the economy and tourism development in European Union countries, using data from indices such as the European Innovation Scoreboard (EIS), the Tourism and Travel Development Index (TTDI), the Digital Economy and Society Index (DESI), and statistics from UNWTO and Eurostat. Spearman’s correlation coefficient measures the strength and direction of the relationships, revealing moderate to strong correlations between innovation potential and tourism performance. The results show that investment in research and development (GERD) and digitalisation (DESI) significantly enhance the development of the innovation potential of tourism. Countries with higher digitalisation and innovation investments outperform in tourism, while the use of European funds (ERDF/CF) shows weaker or negative correlations. The findings underline the importance of supporting innovation strategies that focus on digital technologies, research and sustainable tourism development, while collaboration between the public and private sectors can be key to maximising innovation opportunities.
The Quantum Leap of Computing: Catalyzing a Paradigm Shift in Industrial Robot Adoption within Firms
With the establishment of supercomputing centers in various regions and countries, the leap in computational power has become a reality. As a typical sign of firms’ move towards intelligence and digitalization, firms’ application of industrial robots holds significant importance in firm development. To explore the logic of industrial robot applications and the role of supply chain finance in them, utilizing the OLS fixed-effect model and drawing on the theories of technological innovation and resource-based view, and using the data of Chinese A-share listed companies from 2007 to 2023, the impacts of computational power leap on the application of industrial robots in firms were examined. Results indicate that the leap in computational power significantly enhances the application level of industrial robots in firms. Further analysis reveals that the leap in computational power can significantly boost firms’ intelligence levels, thereby promoting the application of industrial robots. Additionally, effective supply chain finance support can further strengthen the positive relationship between computational power leaps and the application of industrial robots in firms. The conclusions not only enrich the studies on firm intelligence development but also provide important empirical evidence for fully leveraging the value effect of computational power leaps and accelerating the intelligent process of firms.
Intellectual Structure of the Research on Corporate Foresight and Innovation: Thinking inside the Box
The aim of this study is to identify the scholarly works that have had the greatest impact on the research on corporate foresight (CF) and innovation and to analyze the intellectual structure of the knowledge base of the research developed in this field. The methodology is based on the bibliometric techniques of citation and co-citation analysis, which are applied to a total of 129 articles published between 2006 and 2023* (database consultation date: January 3, 2024). Clarivate Analytics' Web of Science™ (WoS) database is used in this study. We chose bibliometric analysis over other traditional methods like systematic literature review (SLR) as bibliometric techniques are replicable, objective, unbiased, and rigorous, and thus superior to other techniques for conducting literature reviews.
Influence of AI on Business Strategies of Music Culture Communication Companies
The rise of AI has reshaped corporate strategies across different industries, including music culture communication companies (MCCCs) that specialise in generating, curating, and delivering music culture content. Using multivariate multiple linear regression (MMLR) analysis, this paper explores the impact of artificial intelligence (data analytics, machine learning algorithms, natural language processing, and automated production workflows) on the business strategies adopted by music culture communications companies in China, including music content creation, content curation, operational efficiency, audience engagement, and consumer personalisation. The study findings indicate that various AI tools have a significant impact on a wide range of business strategies of MCCCs. This research contributes to the extant studies by offering a nuanced understanding of how AI can be strategically incorporated within the MCCCs. The insights derived from this study provide the best practices for practitioners and researcher to guide them in improving corporate strategies to effectively navigate the complex digital domain. This study emphasises the significance of integrating AI to complement the sustainable growth of business strategies in MCCCs.
Pathways Analysis of Different Types Platform Enterprises’ Digital Innovation: from the Perspective of Digital Capability and Ambidextrous Learning
Digital innovation is crucial for platform enterprises to gain a competitive advantage in their digital transformation. In order to identify the necessary factors and differentiated paths for platform enterprises to achieve high-level digital innovation, this study employs organisational learning theory and digital capability theory，utilises Necessary Condition Analysis (NCA) and Fuzzy-Set Qualitative Comparative Analysis (FsQCA) to examine the impact of platform type, digital capability, ambidextrous learning approaches, and their matching mechanisms on digital innovation among 139 enterprises. The NCA results showed that neither a single learning style nor digital capability alone constituted a necessary condition for achieving high-level digital innovation. The FsQCA results identified five paths to achieving high-level digital innovation. Specifically, for producer-led platforms, their digital infrastructure and platform capability are generally strong. If executives also have strong digital leadership capabilities, they can collaborate with low-level exploratory learning. If the digital leadership capabilities of executives are weak, it can be combined with low-level exploratory learning and high-level exploitative learning. For buyer-led platforms, the digital platform capability of enterprises and the digital leadership capabilities of executives are generally strong, but the digital infrastructure is weak and needs to be combined with high-level exploratory learning and high-level exploitative learning. For bidirectional platforms, high-level digital innovation requires high level of executive digital leadership capabilities and the adoption of both high-level exploratory learning and high-level exploitative learning. When different types of platform enterprises pursue high-level digital innovation, they must base themselves on their digital capabilities and choose appropriate ambidextrous learning methods.
Is Green Technological Innovation Promoted? Policy Effect of Green Finance Reform Innovation Pilot Zones
The implementation effect of green financial policies has always been widely concerned by scholars, and abundant research results have been achieved. However, systematic research is lacking on whether green financial policies can promote green technological innovation of enterprises and what mechanism exists at the micro level. To clarify the relationship between green financial policies and enterprises’ green technological innovation, the Green Finance Reform Innovation Pilot Zones (GFRIZs) in China were utilized as a quasi-natural experiment. Drawing on the innovation-driven theory, resource-based theory, and environmental regulation theory, the influencing effect and mechanisms of GFRIZs on enterprises’ green technological innovation were systematically investigated using the annual data from Chinese A-share listed companies from 2012 to 2023, and a multiperiod difference-in-differences method. Results show that GFRIZs can significantly promote enterprises’ green technological innovation, which is mainly achieved by relaxing financing constraints and strengthening environmental regulations. However, this effect is heterogeneous due to the differences in property rights, industry types, and pollution levels of enterprises. The conclusion provides theoretical support and empirical evidence for the government to scientifically evaluate the policy effect of GFRIZs. It also helps the government improve enterprises' green technological innovation ability by enhancing the green financial policy system, reducing the financing constraints on enterprises, and giving full play to environmental regulations.
Registration System Reform and Analyst Forecast Accuracy: Evidence from China
The registration system reform (RSR) in China’s capital market has gradually become the focus of academic discussion and attention. However, the existing literature has not yet offered systematic theoretical insights into how RSR influences analyst forecasts. To explore the impact of RSR on analyst forecasts, drawing on information spillover effect theory and limited attention theory, using the data from Chinese A-share companies that are listed under the approval system in 2015-2021 and a staggered difference-in-differences model, the spillover effect of the RSR on analyst forecast accuracy from the analysts’ perspective was examined. The results show that the RSR has a positive spillover effect on analyst forecast accuracy. After the RSR, the analyst forecast accuracy for peer companies under the approval system has significantly improved. This spillover effect intensifies with the improvement of industry information that has been provided by companies under the registration system. The RSR induces a “catfish effect” on the disclosure quality of peers under the approval system, which compels them to elevate their information disclosure and enhances analyst forecast accuracy. The impact of the RSR on improving analyst forecast accuracy becomes pronounced when the same analyst follows companies under the registration system and peers under the approval system and when these peers are located in regions with superior institutional environments and with high internal control quality. The conclusions provide empirical evidence that supports the government’s active promotion of the RSR and the optimization of the information environment in the capital market.
When Financial Stress and Monetary Policy Interplay with Economic Dynamics in the Eurozone: Multiple Shocks Effects
The aim of this paper is to examine the relationship between financial stress, as measured by the Composite Indicator of Systemic Stress (CISS), and macroeconomic variables, including GDP, inflation, unemployment and the ECB’s monetary tools. Using a vector autoregression (VAR) model, we analyse euro area data over the period 1999 to 2023 to assess the dynamic influences and their relative strength. The study estimates impulse response functions (IRFs) and forecast error variance decomposition (FEVD) to interpret the effects of multiple shocks, including multiple shocks from 2020 onwards caused by the COVID-19 pandemic, the war in Ukraine, and the energy crisis. Our findings suggest that increased financial stress undermines the effectiveness of traditional ECB instruments such as the main refinancing operations, negatively impacts GDP and increases unemployment. The FEVD results indicate that financial stress accounts for a significant part of the variability in unemployment, suggesting that financial stress indirectly affects labour demand and investment. In addition, GDP shocks explain a large share of unemployment variability across the ten observation periods. The results underline the need for flexible monetary responses in times of crisis and provide deeper insights into how monetary policy, financial shocks, and economic determinants interact to optimise policy decisions. The paper fills a gap in empirical research by analysing financial stress over a longer period, during which several crises and multiple shocks have occurred since 2020, highlighting the importance of observing the interactions of selected variables in each period of the business cycle, especially in the period of multiple shocks.
Effects of Employees’ Attitudes towards Digital Transformation Factors on SMEs’ Sustainability and Financial Performance
Digital transformation is the most frequently analysed from the technological perspective. The following research investigates the social elements of organisational digital transformation, by placing employees in SMEs in focus. After extensive literature review the research questions and related hypotheses were defined. To test the proposed hypotheses, a questionnaire was developed, and 635 responses were received from individual owners, managers, and employees in organizations from Serbia, Bulgaria, and Visegrad Four countries (V4). A structural equation model has been used to explore the mediating effect on the relationship between the employee’s attitudes and their perceived opinions on the organisations’ sustainability and financial performance. All relationships within stated hypotheses were confirmed. It was revealed that employees’ positive attitude towards digitalisation is improving their self-efficacy in the digitalized work.
Exploring Investment Behaviour: the Role of Personality, Risk Preferences, Financial Literacy, and Demographics
This study explores the impact of personality traits, risk preferences, financial literacy, and demographics on investment behaviour in Romania, addressing a gap in understanding how these factors interact in an emerging market context. Using survey data from 1,171 respondents, it applies multinomial logistic regression to analyse preferences for stocks, cryptocurrencies, real estate, and banking products. The study is original in its integration of psychological traits and socio-economic factors with a focus on high-risk assets like cryptocurrencies, a topic underexplored in existing research. Results show openness and extraversion significantly influence preferences for innovative and tangible assets, while financial literacy plays a key role in promoting informed investment decisions. Urban and younger investors lean toward innovative investments, while older and risk-averse individuals prefer traditional options. Policy implications suggest prioritising targeted financial education to improve literacy and fostering inclusive investment opportunities to reduce disparities across demographic groups.
Fuzzy Technique for Order Preference by Similarity to Ideal Solution Approach for Financial Efficiency Measurement of the Private Banks
In India, the banking industry has been one of the most rapid growing industries after the government’s demonetisation move in 2016. Private banks are doing exceptionally well in terms of their customer relations and financial services compared to the public banks. The main component of a bank is undoubtedly its financial performance. In today’s increasingly more competitive market, an appropriate and accurate measurement of financial performance is of great importance for a bank that aims to successfully maintain its market position. The main objectives of this study are to identify the best private bank and to rank the private banks in India. This research paper attempts to propose a Multi-Criteria Decision-Making (MCDM) model to evaluate and compare the financial performance of ten private banks enlisted on the National Stock Exchange (NSE) NIFTY as of 2 September 2023. These ten private banks are evaluated to gain a financial performance score and a ranking by applying a Fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) methodology, which is based on Euclidean Distance. The results show that the HDFC Bank is the most financially efficient one followed by ICICI Bank and Axis bank.
Mapping the Green Path: A Comprehensive Bibliometric Analysis of Green Tourism Research Trends
Environmental protection and business development are priorities for the European Union, and the successful implementation of Green Pact policies will be of great importance to all parties involved. The primary objective is to perform a comprehensive examination of scientific results by using bibliometric analysis in order to understand the existing structure of studies and potential directions for research connected to business environment improvements through green economy implementation. Business and sustainable development will be an engine as we transition to a more resource-efficient and green economy, one in which economic growth, equitable distribution of resources, and human development interact with environmental security. The transition to an environmentally friendly green economy will generate substantial financial advantages. Greening the economy is a new economic engine, an incubator for sustainable jobs, and an essential instrument for eliminating poverty. The bibliometric investigation found 1643 documents that appeared on the Web of Science database between 1991 and 2023. The VOSviewer programme has been used to analyse its scientific content.
Empirical Analysis of the Interplay between Municipal Waste Generation, Living Standards, and Innovation in the European Union
The paper examines global interlinkages among the level of municipal waste generation and the representative socio-economic, technological, and innovation factors at the level of the European Union countries. Further, we realize a hierarchical clustering of the European Union member states according to similar characteristics regarding the level of municipal waste generation, jointly with these representative socio-economic and technological factors, in order to propose adequate solutions for lower-performing states. The data covers the 2006-2021 lapse of time, and the research methodology is based on two advanced methods, namely network analysis performed through Gaussian graphical models and cluster analysis performed by the Ward method. The results highlight that the analysis only of municipal waste generation level, without other socio-economic benchmarks, would not be conclusive, as there are developed states with high levels of municipal waste generation, as well as developing countries with waste generation above the EU.
Emerging Sustainable Energy Technologies to Combat Climate Change: Evidence using Non-linear ARDL Estimation
Economies, either developed or developing, face problems in the form of climatic issues as they fail to restrict greenhouse gas emissions. The challenge increases as these emissions are due to high levels of consumption of non-renewable energy. Thus, in order to mitigate emissions, especially CO2, it is imperative to enhance the green energy share of the energy supply. Interestingly, scholars agree that public sector investment to raise renewable energy is significant, hence they hypothesize that investment is crucial for the technological advancement needed to increase sustainable energy production and supply. The circumstantial role of sustainable technology cannot be overlooked, as it boosts green energy supply and protects the environment. Because of climate complexities and rapid urbanization, a zero-carbon economy is not easy to achieve. To address the issues, countries must find effective ways to restrict carbon emissions, which is only possible if they are aware of the potential determinants of carbon emissions. Based on refined indicators, this study presents a comprehensive model to quantify the role of sustainable energy technologies in climate change in the context of China between 1991 and 2020. Through autoregressive distributed lag estimations, it reveals that renewable energy consumption and production, along with advanced technologies, are blessings for an economy trying to reduce carbon emissions. However, economic activity, rapid urbanization and industrial structures are responsible for high emissions. The findings suggest that certain target policies must be implemented to reduce carbon emissions. Also, there should be a proper platform to promote green technology at a regional level along with effective urban development strategies.
Sustainable Development Path of Post-Project Evaluation: New Quality Productivity Perspective
The introduction of the concept of new quality productivity in 2023 has precipitated a wave of extensive reforms in various industries. The efficient integration of new quality productivity measures within the context of the new era has become a significant challenge in achieving industry development. Drawing upon the paradigm of new quality productivity, this paper employs the CiteSpace and bibliometric mapping visualisation and analysis methodologies to explore the sustainable development trajectory of post-evaluation of engineering projects. This provides a theoretical foundation and practical recommendations for the sustainable development of engineering projects.
The Role of Forests in Low Carbon Transition: A Systematic Literature Review
The use of a carbon sink mechanism plays an important role in achieving a low-carbon transition. Forest-based carbon sequestration assumes a notable role in the suite of ecosystem services that influence global climate dynamics. The paper aims to conduct a systematic literature review on the role of forests in decarbonising the economy, define the research gap, and develop a future research agenda. The SALSA and PRISMA frameworks and the PSALSAR protocol were used in the systematic literature review. The main findings of the analysis showed that there is a lack of integrated studies addressing the water, land, climate, energy, agriculture, and forests nexus for defining the harmonised climate change mitigation policies targeting specific sectors of the economy linked to natural resources, as decarbonisation can be achieved through various climate change mitigation and carbon sequestration measures in interlinked water-land-climate-food-energy-forests systems.
Green Supply Chain Decision Making and Contract Coordinaion: The Influence of Brand Reputation and Consumer Reference Effects on Low-Carbon Levels
Rapid economic growth leads to severe pollution and excessive resource consumption, which poses challenges to sustainability. To address these issues, green supply chain management was promoted by the government, encouraging firms to enhance their low-carbon reputation and meet the increasing consumer demand for ecofriendly products. This study developed a differential game model for a two-echelon green supply chain that incorporated consumer reference effects on low-carbon levels-a factor that was often overlooked in previous research. By considering retail price, advertising investment, and emission reduction effort as decision variables, the optimal strategies under decentralized and centralized decision making were analyzed. Results show that centralized decision making leads to higher emission reduction, a stronger reputation, and better financial performance, although its efficiency depends on investment intensity. To bridge the gap between decentralized and centralized decision making, we proposed three contract coordination mechanisms: (i) two-way cost-sharing, (ii) revenue-sharing, and (iii) a hybrid contract. Particularly, the hybrid contract best aligns supply chain performance with the centralized optimum, thereby enhancing profitability for manufacturers and retailers. Numerical analysis validated the findings, providing insights for sustainable supply chain management and low-carbon policy formulation.
Emotional Intelligence and Work Engagement: Connected or not? Evidence from the IT&C sector in Romania
Emotional intelligence has been widely accepted as a very important feature of employees, influencing the way of thinking, the behaviour, and the interaction with other people. Traditionally, IT&C professionals are considered to have fewer soft skills than other types of professionals, as their education and work environment require task orientation, autonomy, reduced direct communication, and technical skills (Tang and Yin, 2008). The present research aims at investigating the emotional intelligence and its relationship with the work engagement among 450 Romanian IT&C professionals using a questionnaire-based survey. Two valid and reliable scales, the Wong and Law Emotional Intelligence Scale and Work (Wong and Law, 2002) and the Well-being Survey (UWES) (Schaufeli et al., 2017), were used to assess the concepts. The results of the study show that, contrary to our assumptions, the level of emotional intelligence of respondents is quite high, and that a direct relationship between the two concepts does exist. Our research reveals significant differences in multiple factors linked to Emotional Intelligence and Work Engagement according to various control variables, such as gender, age, residence, and income level.