Įkurtas 2001 m. „Transformations in Business and Economics“ yra tarptautinis mokslo žurnalas, publikuojantis originalius mokslinius straipsnius, skirtus svarbiausioms ekonomikos ir vadybos srities problemoms. Nuo 2007 m. indeksuojamas „Scopus“ (Q2), nuo 2005 m. – „Web of Science“ (Q3).
Vilniaus universiteto leidykla / Vilnius University Press
Susipažinkite su autorių teisėmis žurnalo politikoje skiltyje Autorių teisės.
Autorių teisės (c) 2025 Author https://creativecommons.org/licenses/by/4.0
Evolution of economic sustainability terminology in EU legislation: a descriptive and quantitative perspective
Within the realm of governmental activity, the alignment of verbal expressions with diverse theoretical or ideological frameworks gives rise to distinct manifestations of the „social construction of reality “within public opinion. This study aims to scrutinize the discourse characteristics employed by the legislative superstructure of the European Union (EU). Rather than seeking causal explanations based on hypotheses, the research confines itself to elucidating the phenomenon as it exists, deducing its constituent elements deductively from a pre-established conceptual framework. To achieve this, the widely utilized ATLAS.ti tool for applied semantic studies is employed. Discourse trends appear to revolve around the social impact of development economics, the pivotal role assigned to future generations, the significance of target-oriented plans and programs, and the equilibrium among social, environmental, and economic dimensions. The temporal constraints warrant a more extensive investigation into the evolution of the EU's legislative discourses that contribute to the construction of reality.
The impact of China’s delayed retirement policy on household allocation of risky financial assets
The delayed retirement policy extends households’ expected income periods and reduces precautionary savings, sparking growing academic interest in its broader implications. However, existing literature lacks theoretical insights into how this policy reshapes households’ allocation of risky financial assets. To explore the relationship between delayed retirement policies and households’ allocation of risky financial assets, drawing on the life cycle theory, using the data from the China Household Finance Survey (2011, 2013, 2015, and 2017) and a difference-in-differences model, the impact of China’s delayed retirement policy announcement on household financial asset allocation was analysed. Results reveal that: (1) within the life cycle theory framework, the policy announcement significantly promotes risky financial asset allocation among households in the formation and rearing stages; (2) the policy encourages households with stronger social networks to increase risky asset investments. Risk aversion amplifies the policy’s effect during the formation stage but inhibits it during the rearing stage; (3) the positive impact is more pronounced among urban households, those in eastern China, and highly educated families. This study provides novel insights into implementing progressive delayed retirement policies. Conclusions bridge the theoretical gap regarding how retirement policies shape household risk asset allocation and provide evidence for optimizing policy design through heterogeneity analysis.
Promoting Scientific Events & National and International Scientific Networks
Reviewed book: Ona RAKAUSKIENE, Dalia STREIMIKIENE, Lina VOLODZKIENE (2025), Strengthening Human and Societal Resilience in Uncertain Times, Routledge, 352 p.
The Innovation Paradox of Registration Reform: Inefficient Investment Mediation Effects and Heterogeneous Firm Responses
Registration system reform aims to optimize resource allocation and stimulate market dynamics. Many countries have adopted it as a key institutional innovation in their capital markets. However, whether such reform effectively promotes corporate innovation—especially across different enterprise types—remains unclear. To explore the innovation paradox of registration reform, drawing on information asymmetry and investor behavior theories, and using data from the Chinese A-share Growth Enterprise Market (GEM) and Main Board firms covering the period from 2018 to 2022, the impact of the reform, the underlying mechanisms, and the heterogeneous effects on innovation were analyzed with a difference-in-differences (DID) approach. Results show that the registration system reform does not promote corporate innovation as expected. Although the reform has led to an increase in overall enterprise investment, much of this additional investment is inefficient. As a result, the overall innovation capacity of firms has declined. This finding confirms that inefficient investment acts as a mediating factor through which reform weakens corporate innovation. Further analysis reveals significant differences in the impact of the reform. The negative effects are most pronounced for non-manufacturing enterprises, firms located in the eastern region, and companies with low price‒earnings ratios. For other firm types, the impact is not significant. This study highlights the unintended consequences of reforming the registration system for corporate innovation, particularly when investment efficiency does not improve. The conclusions obtained from this study contribute to the theoretical understanding of innovation and offer practical insights for optimizing future reform policies.
How Can Capital Investment Improve the Development Level of University Informatization? A Moderated Chain Mediation Model
Under the background of the digital transformation of education, increasing capital investment to promote the construction of university informatization is an important measure to boost the high-quality development of higher education. However, there is no systematic explanation and demonstration of the internal mechanism, logic, and conditions through which funds affect the development of university informatization. Because of this, this paper attempts to build a moderated chain mediation model based on literature review. Using official data from 95 universities in Zhejiang province to evaluate the informatization development level, descriptive statistics, correlation analysis, regression analysis, and mediation and moderation effects were conducted using SPSS 26 and Process V3.5 plugins to explore the impact of capital investment on the informatization development level of universities. The results show that capital investment in college informatization construction can significantly and positively affect the level of informatization development. Information leadership and human resource investment in colleges and universities play an intermediary role in the relationship between capital in-vestment and information development level. The mechanism of university informatization construction positively regulates the relationship between human resource investment and informatization development level. Additionally, the mechanism of university informatization construction positively regulates the indirect effect of capital investment on the level of informatization development. The research results reveal the internal mechanism and function path of "how the capital investment affects the development level of university informatization” and pro-vide beneficial enlightenment for universities to make full use of informatization funds to conduct construction practices.
Investigating the Impact of Perceived Elements of Social Media Marketing on Consumer Brand Interaction and Brand Knowledge in the Fashion Industry
In the digital economy of today, social media has transformed marketing functions in most consumer-oriented businesses, such as fashion. This research examines the impact of the leading social media marketing features – “entertainment”, “customization”, “electronic word of mouth” (EWoM), and “trendiness” – on “consumer brand engagement” and “brand awareness” in the fashion industry. Based on a systematic survey conducted among 384 active social media users, the study uses partial least squares structural equation modeling (PLS-SEM) to analyze the interrelatedness of the variables. The study reveals that “consumer engagement” with brands is highly influenced by EWoM, interactivity, and “fashion trends”, which consequently increase “brand awareness” and “brand image”. However, the influence of “entertainment” and “customization” on consumer participation was statistically insignificant. Through offering a strict examination of the determinants of “brand knowledge” in social media contexts, this research provides fresh insights into digital marketing strategies and offers pragmatic implications for practitioners who wish to maximize consumer participation in fashion-based brand communities.
Influence of Customer’s Self-comments Versus Others’ Comments on the Customer’s Subsequent Repurchase Behaviour
User-generated content (UGC) is an important type of customer feedback that provides reference for a future customer’s purchase decision and acts as a guideline for corporate marketing strategies. This research verifies the influence of a customer’s previous self-comments and others’ comments on the former’s future repurchasing behavior. To obtain observations on customers’ real purchases, we cooperate with one company that sells its product through the Amazon platform to get transaction data and collect comments and ratings directly from the platform. Excluding missing data, in the first round of data collection there are 1,366 transactions from this company’s focal products during the years 2019 to 2022. After following up on any repeat purchase behavior from those customers in the next year, final repurchase orders make up 139 repeat transactions. This research uses the Large Language Model (LLM) to transform customers’ text comments by natural language processing (NLP) into a score. Empirical results reveal that customers are both concerned about their own previous experiences and others’ comments and focus more on the text content rather than the title of the comments. For the moderating effect of product types, the more negative the contents of others’ comments and previous comments on utilitarian products are, the less a customer will repurchase from the brand. One interesting finding is that when making repurchase decisions, others’ comments outweigh a customer’s self-comments.
The Impact of Entrepreneurial Intention on Marketing Innovation within the Context of Economic Recessions
Since economic crises affect individuals’ attitudes to take actions under the conditions of tough economic conditions, they can also influence individuals’ entrepreneurial intention which in turn lead to changes in marketing innovation activities of businesses. In this regard, the purpose of this study is to investigate the effect of entrepreneurial intention on marketing innovation within the context of economic recessions. While entrepreneurial intention is based on the Theory of Planned Behavior, marketing innovation is a dynamic capability included in Resource-based View. The researchers create an online questionnaire and send it to purposively selected respondents from 1367 enterprises in several European countries. Furthermore, the researchers employ Ordinal Logistic Regression Test for analysis purposes. The results confirm the positive impacts of entrepreneurial intention on enterprises’ marketing innovation during the periods of economic recessions. Financial and moral support of family members and previous failures of executives might be the reasons of these findings.
Exploring the Interplay of Positive Psychological Capital and Career Adaptability in Multinational Corporations
The aim of this study is to investigate how positive psychological capital, employee resilience, career calling, and role overload interact to shape career adaptability among employees in multinational firms in Pakistan. The study investigates the impact of employee resilience as a mediator in the relationship between positive psychological capital and career flexibility, as well as the moderating effects of career calling and role overload. Design/methodology/approach: The study used a cross-sectional design, and data were obtained from 287 employees of multinational firms in Pakistan. Positive psychological capital, employee resilience, professional calling, job overload, and career adaptability were all assessed using self-report questionnaires. PLS-SEM (Partial Least Squares Structural Equation Modelling) was used to examine the data. Findings: The findings demonstrated that positive psychological capital has a substantial influence on job adaptability as well as community and individual employees’ resilience. Furthermore, resilience influenced the association between good psychological capital and job adaptability considerably. The connection between positive psychological capital and career flexibility was considerably reduced by career calling, while role overload had a modest moderating effect. Originality: This study adds to the body of knowledge by providing empirical evidence of the complex relationships between positive psychological variables, employee resilience, and career adaptability. The study expands on positive psychology in the context of careers, emphasising the importance of psychological resources and contextual elements in supporting individuals’ adaptive behaviours and well-being in their careers.
AI Determinants of Organizational Performance of English Training Institutions in China
Using a multivariate multiple linear regression analysis, this study examines the effect of AI adoption measures (organizational AI investment, intelligent tutoring systems, adaptive learning platforms, culturally sensitive AI tools, & faculty training in AI) on the different metrics of organizational performance (student enrollment growth, personalized learning experience, enhanced student engagement, improved teaching efficiency, & organizational revenue growth) of China’s English training institutes. The study findings reveal that AI incorporation significantly improves the organizational performance of English training institutions in China, illuminating the strategic role of investing in AI-driven technologies such as adaptive learning platforms, organizational AI investment, culturally sensitive AI tools, intelligent tutoring systems, and faculty trainings in AI. In specific, intelligence tutoring systems and adaptive learning platforms exhibit the most substantial effect on organizational performance, validating their versatility and effectiveness in supplementing both financial/economic and educational performance. Similarly, culturally sensitive AI tools result in improved student engagement and inclusivity, emphasizing the importance of cultural considerations in AI integrations. Besides this, organizational AI investment and faculty training in AI also play a pivotal role, particularly in fostering personalized learning experience and organizational revenue growth. Thus, the research inferences proposed in this study put forward useful theoretical and practical implications for educators, policymakers, and business managers. AI adoption acts as a strategic tool to address long-run issues associated with enrollment stagnation, cost inefficiencies, business operations, and financial performance. Therefore, institutional managers must perceive AI not merely as a technological upgrade but as an integral element of organizational strategy that supports operational efficiency, financial sustainability, and long-term growth.
Collaboration Satisfaction in Human–AI Teams: The Dual Roles of Trust and Cognitive Load
With the rapid development of artificial intelligence (AI), organizational collaboration structure and operational logic are being reshaped, and human–AI co-creation is gradually becoming the norm. However, the impact of AI embedding on team collaboration satisfaction remains unclear. To explore how AI embedded in teams affects team collaboration satisfaction, drawing on socio-technical systems theory and information processing theory, utilizing a between-subjects experimental design, 100 participants were recruited via an online platform in April 2025, how AI affects team collaboration satisfaction was investigated through the dual pathways of social and technical subsystems by manipulating team composition (human–human teams vs. human–AI teams). Results indicate that the introduction of AI significantly weakens human members’ team trust while effectively reducing their cognitive load. The opposite effects of these two pathways lead to a canceling indirect effect, which makes the overall impact of AI on collaboration satisfaction neutral. Further analysis reveals that team project experience significantly moderates the above mechanisms. Specifically, experienced members rely more on interpersonal cooperation and are more sensitive to AI’s emotionless collaboration style, thereby reducing trust. However, they perceive less value in AI’s assistance because they have internalized efficient cognitive strategies. The conclusions of this study deepen the present understanding of the human–AI collaborative mechanism in AI technology embedding, reveal the interaction between structural technological change and individual experience, and provide theoretical support for the design and management of future intelligent collaboration systems.
Technology Driven Consumer Protection for the Use of E-Commerce Platforms
In the context of the unprecedented development of online commerce, the need to implement consumer protection strategies while recognising and strengthening their rights is growing. This study aims to highlight the role of consumer protection in online purchasing transactions conducted on different e-commerce platforms using technology based on artificial intelligence (AI) systems and e-advertising. The authors’ approach is to use a conceptual model and argue its relationships. To conduct the research, the authors employed a survey technique involving an online questionnaire distributed to 354 consumers. The analysis of the relations between the constructs of the conceptual model is carried out using structural equations via the lavaan library, version 06-12 of the R software. The research results emphasise that both artificial intelligence-based systems and e-advertising are influenced by the way consumer protection is achieved, and, in turn, influence consumer perception and confidence in online platforms. The paper extends the research on the Technology Acceptance Model by firstly investigating the relationships between constructs such as the commitment of e-commerce platforms and unawareness of consumers’ rights when shopping online, and e-advertising; unawareness of consumers’ rights when shopping online and trust in the chatbots of e-commerce platforms; and the respect of consumers’ rights by e-commerce platforms and the increasing importance of e-advertising.
Autorių teisės (c) 2025 a https://creativecommons.org/licenses/by/4.0
Blockchain and other Determinants of the Financial Attractiveness of Tourism Enterprises at the Regional Level: A Proposal for a Synthetic Fundraising Indicator
This study evaluates the key factors influencing non-traditional financing in the tourism industry as an alternative to traditional bank financing. It explores whether companies using Blockchain technology or integrating it into their processes are more likely to secure investments. Two significant contributions are made: proposing variables that enhance financial attractiveness in tourism and examining whether companies adopting Blockchain attract more investment. Using a sample of 1,327 tourism companies from Crunchbase, this study develops five indicators and constructs a synthetic indicator using the P2 distance method. The results reveal that tourism companies incorporating Blockchain are more likely to secure financing, influencing regional financing capabilities, and enhancing appeal to private investors. The Synthetic Indicator of Fund Raising offers a novel tool for assessing investment potential globally, providing insights into financial attractiveness across regions and highlighting the role of advanced technologies, such as Blockchain, in securing private investments.
The impact of digital technology affordances on radical innovation: moderating effects of industry technological turbulence and regional innovation environment
To explore the mechanisms and conditions through which digital technology impacts radical innovation, this paper uses a sample of 409 firms to integrate digital technology affordances and radical innovation into the same research framework from the technology affordances’ perspective while also assuming the effect of industry technological turbulence and regional innovation environments. The impact of digital technology accumulation affordance, variation affordance, and their comprehensive balance on radical innovation shows an “inverted U-shaped” relationship. Industry technological turbulence and regional innovation environment have a negative moderating impact on the above relationships. From the interaction viewpoint between internal technology and the external environment, this study explains the conditions under which digital technology affects radical innovation, harnessing digital technology for radical innovation.
Presenting an innovative business model based on collaborative, online platforms in the era of the fifth industrial revolution
In the framework of the rapid technological evolution that is characteristic of the Fifth Industrial Revolution, digital platforms serve as an indispensable driver for business innovation and sustainable development. This is largely due to their ability to potentially merge human ingenuity with advanced technology. The explosively expanding platform-based sharing economy has fundamentally disrupted traditional economic frameworks and regulatory environments both within nations and globally. The present study employs the meta-synthesis methodology to develop a framework for comprehending platform-centric business operations. This has been conducted via an inductive approach to qualitative meta-synthesis as propounded by Sandelowski and Barroso, integrated with a systematic review process. The researchers extracted the relevant literature from Google Scholar and Web of Science, supplemented by manual searches of relevant journals and their citation networks. Following a thorough review of the 454 source documents, the authors narrowed down to 69 academic articles. The data analysis was a multi-layered process in which the primary coding, axial coding, and selective coding of the research results were conducted. The conclusions that can be made from this work underline the key factors and their relationships, which are critical for successful platform business design. Consequently, they provide valuable guidance for both scholars and practitioners within the digital economic context.
The integration of ERP systems and technologies for process automation: an analysis of the literature
In the context of Industry 4.0, economic entities that want to be successful on the market have to take into consideration the use of various technologies for digitalisation and automation of operational processes. To facilitate work and increase performance, ERP (Enterprise Resource Planning) systems can be integrated with other innovative solutions for automation, such as RPA (Robotic Process Automation). This paper aims to identify the main topics of interest in the field and the correlations between them by using a bibliometric literature analysis. The database included 284 publications extracted from Scopus. The search was carried out using keywords such as ‘ERP’, ‘RPA’, and ‘automation’. Using the VOSviewer software, the answers to the research questions were obtained by analysing keyword co-occurrence network, the evolution of the number of papers published in the period 2015–2024, the papers with the highest number of citations, the representative authors, the sources that include the largest number of publications, and the countries that contributed the most to the field. The results illustrate that there is an increasing interest in the integration of ERP systems with digitalisation and automation technologies. In the analysed papers, automation-based solutions, such as software robots, are mainly chosen. The current research contributes to the literature by exploring the integrated use of ERP solutions with RPA, an aspect that is not much addressed in existing work. An overview of trends takes shape as this study can represent the basis for future research in this particular, continuously evolving field.
Carbon emissions trading pilot policy drives enterprise new quality productivity: the mediating mechanism of green technology innovation
The promotion of global green development strategies has brought significant attention to the structural contradiction between “insufficient quality and efficiency” and “virtually high quantity” of green technology innovation, particularly concerning its role in fostering new quality productivity cultivation of enterprises. However, empirical research specifically examining the influence of a carbon emissions trading pilot policy on enterprise new quality productivity, from the dual perspective of green technology innovation, remains limited. To explore the path to promote enterprise new quality productivity, drawing upon dual theory and using the data of Chinese A-share listed companies during 2012-2023, the internal action mechanism among the carbon emissions trading pilot policy, green technology innovation, and enterprise new quality productivity was analyzed through a Difference-in-Difference method. Results show that the carbon emissions trading pilot policy generates a markedly positive influence on the enterprise’s new quality productivity. In addition, the quality improvement of green technology innovation mediates this relationship. For non-state-owned, small, and high-growth enterprises, the policy exerts a stronger positive effect on new quality productivity. Furthermore, environmental attention from the government, the degree of digital transformation, and managerial performance pressure exerts positive moderating effects, whereas the degree of market competition plays a negative moderating role. These conclusions reveal the influencing mechanism of the carbon emissions trading pilot policy on enterprise new quality productivity, thereby providing a theoretical basis and practical enlightenment for economic green transformation and low-carbon, high-quality development.
The impact of low-carbon pilot policies on enterprise environmental performance
This study seeks to examine the influence of low-carbon pilot policies on the corporate environmental performance of Chinese enterprises. The results reveal that in SOEs, the impact of low-carbon pilot policies is more significant, while in non-SOEs, the effect is relatively small. In heavily polluting enterprises, the influence of the pilot policies is more significant, while in non-heavy polluting enterprises, the impact is relatively small. The mentioned pilot policy provides a variety of mechanisms, including policy incentives, technical support, industry norms, social pressure, and market opportunities, thereby improving their environmental performance. In addition, it effectively alleviates financing constraints and provides financial support for enterprises to implement low-carbon technologies or innovations. Further analysis shows that green innovation and financing constraints have partial mediating effects in the process of improving corporate environmental performance through low-carbon pilot policies. This paper provides corresponding policy recommendations, including increasing policy support, strengthening the effect of policy implementation, and implementing differentiated low-carbon policies for different types of firms and different regions. Simultaneously, the paper also calls on enterprises to actively participate in the pilot policies to achieve sustainable development goals.
The impact of carbon finance, renewable energy, and environmental knowledge on load capacity factor
Load capacity factor is a comprehensive indicator which compares biocapacity and ecological footprint to track an environmental threshold. Scholars observe that, with rising environmental pollution, the load capacity factor decreases. The existing literature empirically measures environmental degradation through over-explored proxies such as ecological footprint, carbon emissions, GHG emissions, and nitrogen emissions. Because of the proxies used, the supply side of environmental problems is often neglected. This study addresses this gap by investigating renewable energy, environmental knowledge, and carbon finance, and their influence on load capacity factor in China. A nonlinear autoregressive distributed lag (NARDL) technique is used to evaluate the associations. The results show that renewable energy output and consumption, environmental knowledge, carbon finance, and population growth have positive relationships with load capacity factor in China. Therefore, the Chinese government must encourage biomass use and investment in renewable energy forms to restrict emissions.
Green HRM and prosocial rule-breaking: role of climate, intentions, and CSR
Drawing on the social exchange theory, this research examines how green HRM encourages prosocial rule-breaking through a green psychological climate and behavioural intentions. A time-lagged survey design was used to collect data from 230 employees across various organisations in Pakistan. Structural equation modelling is used to test the direct and indirect effects of green HRM on prosocial rule-breaking. Results show that green HRM does not directly influence prosocial rule-breaking. Its impact is mediated through green psychological climate and behavioural intentions. Moreover, external CSR negatively affects the relationship between green HRM and the green psychological climate. This challenges the common belief that CSR always plays a supportive role. These findings offer valuable insights for researchers and organisations looking to enhance sustainability-driven innovation and encourage discretionary behaviours. The study provides implications for both researchers and practitioners. Future research direction is offered to strengthen the field of sustainability and green HRM.
How can merchant responses repair potential consumers’ trust after negative online product reviews? An attibution theory perspective
For online merchants, providing clear and appropriate feedback explanations to address negative product reviews is crucial for mitigating consumer trust crises triggered by service failures and ensuring the sustainable growth of e-commerce. However, existing studies on merchant responses predominantly rely on traditional service recovery theories. In actual e-commerce platforms, while conventional remedial measures such as apologies and compensation help potential consumers achieve psychological balance and perceive fairness, they place greater emphasis on merchants’ attributional explanations for transaction failures. To explore how merchants’ feedback attributions influence trust damage and recovery following negative product reviews, drawing on attribution theory, an attribution model for restoring potential consumer trust was constructed, and using scenario-based experiments involving 467 typical young online shoppers, the impact of responsibility locus, controllability, and stability of merchants’ feedback on the trust damage and recovery of potential consumer. Results indicate that: (1) External attributions in causal explanations for negative reviews result in significantly less trust damage compared to internal attributions. (2) For attribute-level explanations, uncontrollable attributions are more effective than controllable attributions in reducing trust damage. (3) Unstable attributions outperform stable attributions in mitigating trust erosion. This study offers a novel perspective on service recovery through merchant feedback, thereby expanding the application scope of attribution theory. The conclusions obtained from this study offer actionable recommendations for operators to strategically employ attributional explanations to counterbalance the adverse effects of negative reviews.
Symbiotic development relationship between regional agricultural industry clusters and agricultural logistics
Under the prevailing trend of coordinated industrial development, extending supply chains and strengthening industry linkages have emerged as critical pathways for upgrading modern agriculture. However, research into the dynamic symbiotic evolution mechanisms and optimization strategies of regional agricultural industry clusters and logistics systems remains insufficient, hindering the realization of high‐quality collaborative growth. To advance the co‐development of regional agricultural clusters and logistics, this study constructed a system dynamics model grounded in symbiosis theory. This model was applied to Jiangsu Province, China to investigate the feedback mechanisms and co‐evolutionary trajectories of the cluster–logistics symbiotic system. First, the symbiotic units, environmental factors, and interaction patterns were synthesized to develop causal loop and stock–flow diagrams. Second, scenario simulations were conducted following parameter calibration and validity testing against historical data. Finally, the effects of policy support, labor return, and transportation improvements on system performance were assessed. Results indicate that Jiangsu’s agricultural GDP will reach 1459.53 billion yuan by 2025. Elevating the policy support coefficient to 0.20 can increase cluster output value and logistics employment by approximately 3.92% and 3.50%, respectively. A 2% rise in labor supply yields a 17.44% increase in output value, and enhanced transportation accessibility boosts cluster output value and logistics capacity by 3.19% and 2.19%, respectively. Moreover, persistent rural labor outflow and logistics supply–demand imbalances are identified as principal constraints on collaborative development. These findings not only provide theoretical guidance for optimizing regional factor allocation and enhancing overall symbiotic system performance but also offer novel insights for advancing China’s agricultural modernization through “place‐based, differentiated strategies”.
Privatization Policy with Corporate Social Responsibility in a Mixed Duopoly
This paper constructs a mixed duopoly model considering privatization, the level of corporate social responsibility (CSR), and the cost of state-owned shares. It examines the equilibrium results under the Cournot model and the Stackelberg model and makes comparisons. The results show that CSR and state-owned shares have essential effects on equilibrium results. Faced with different types of competition, stakeholders make various decisions. Under the Cournot model, there is an optimal state-owned share proportion. Full privatization is optimal under the Stackelberg model and the expanded three-stage game. Therefore, state-owned shares, CSR, and competition mode should be considered in the privatization policy.
Taxation of undeclared income in Montenegro: constitutional challenges
In this study, we survey and analyse the system of taxation of ‘undeclared income’, which essentially refers to cross-assessment of the tax base by the tax authority, which is carried out in situations where the reported income is many times smaller than the property and consumption of a certain individual. In these situations, the tax authorities have provisions at their disposal that give them the opportunity to determine the value of taxpayers’ property and consumption, so that if this value is significantly higher than the amount of income they have declared, the authorities have the right to tax the difference. We identify the shortcomings of the subject fiscal mechanism, due to which the competent authority never applied them in practice. A special focus is placed on the issue of the compatibility of these provisions with the Constitution of Montenegro, and the violation of several constitutional principles in the practice of the Constitutional Court of Montenegro will be pointed out. It has been found that the legislator does not properly understand the aim and the role of these fiscal provisions in the overall context of reviewing the origin of property.
The impact of efficiency and market structure on the financial performance: empirical evidence from China’s banking sector
Against the backdrop of structure-conduct-performance (SCP) and efficient-structure (ESH) hypotheses, this research investigates the impact of the market structure on the performance of banks in China from 2015 to 2024. The DEA method is adopted to gauge the efficiency of banks, whereas the concentration ratio is utilised to evaluate the market structure of Chinese banks. Using random regression analysis, both variables (market structure and efficiency of banks) among other independent variables (market share, loan ratio, bank size, and operating expenses) are regressed upon the explained variable, namely the financial performance of Chinese banks represented by ROA. In this study, a trend analysis is also carried out to analyse the performance of the Chinese banking sector. The regression results show that both the market structure and the efficiency of banks exert a noticeable positive influence on the banks’ performance in China, supporting the ESH and rejecting the SCP hypothesis. This implies that banking efficiency and market structure (concentration) significantly affect the profitability performance of Chinese commercial banks. From the structural perspective, the concentration of Chinese banks is on a declining trend, and the Chinese banks are more competitive due to less concentration of the market. In the context of efficiency, DEA analysis shows that banks in China are operating below their efficient capacity. Thus, Chinese banks could lessen the utilisation of their inputs to operate in an efficient manner.