Technological and Economic Development of Economy
Technological and Economic Development of Economy is a peer reviewed journal that publishes original research, review articles and book reviews on all areas of sustainable economic development including political, economic and technological economic strategies. The journal provides insights and original research on topics of importance to economists and original research on topics of importance to economists and policy makers. More information ...
Copyright © 2021 The Author(s). Published by Vilnius Gediminas Technical University. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Exploring the social and economic consequences of the metaverse: a multi-criteria approach to the SDGs
This study explores the social implications of the Metaverse, a transformative digital ecosystem, through the lens of the United Nations Sustainable Development Goals (SDGs). The research identifies fourteen key concerns associated with the adoption of Metaverse technologies and assesses their societal impact. A two-stage methodology was employed: an expert panel utilized Grey Step-wise Weight Assessment Ratio Analysis (SWARA) and Grey Combined Compromise Solution (CoCoSo) to assign relative weights and to rank these concerns, reflecting their significance in societal contexts. Following this, an international survey was conducted to quantitatively gauge public perspectives across diverse demographics. Key findings highlight substantial psychological impacts linked to immersive experiences, such as addiction and mental health challenges, which pose a threat to SDG 3 (Good Health and Well-being). The environmental sustainability of Metaverse technologies is also critically examined, stressing the urgent need for green practices to mitigate carbon emissions and reduce energy consumption. Furthermore, ethical issues, particularly surrounding data privacy and user consent, are discussed, emphasizing the importance of robust regulatory frameworks to ensure safe and equitable user experiences. The study reveals the Metaverse’s potential to both foster global connectivity and exacerbate existing social inequalities, advocating for balanced, inclusive approaches to ensure equitable access. By integrating expert insights with broad public opinions, this research provides a comprehensive analysis of the complex relationship between digital technology and societal well-being, offering a foundation for future exploration of the responsible evolution of the Metaverse. Please view the correction statement: Corrigendum: Exploring the social and economic consequences of the metaverse: A multi-criteria approach to the SDGs
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
The impact of industrialization and self-renewing energy utilization on carbon discharges in the country economics
Industrialization has been pivotal in driving economic development. The research problem is the negative impact of industrialization to global warming and climate change. The relevance – enabling the use of renewable energy and green solutions to decrease CO₂ emissions. This research aims to evaluate the impact of short and long-term of industrialization, consumption of renewable energy, trade openness and economic growth on carbon emissions per capita in Indonesia. This research analyses [2000–2023] data, applying econometric ARDL approach and diagnostic tools. The Breusch-Godfrey Serial Correlation (BGSC) results revealed no consistent correlations, when Breusch-Pagan-Godfrey (BPG) test heteroscedasticity was confirmed. Ramsey RESET test (RRT) showed that the model is perfectly specified and significant; CUSUMSQ and CUSUM tools proved the stability of the model, when the VIF multicollinearity results indicated that no multicollinearity exists between the variables. Research findings show: trade openness and the consumption of renewable energy demonstrate a favourable effect for carbon output per capita in Indonesia as outcomes of economic progress, while industrialization has an adverse relationship with emissions of carbon per capita. The research originality – complex evaluation of the relationship between mentioned variables interplay. This publication provides recommendations for policymakers to improve the quality of environment.
Corrigendum: Exploring the social and economic consequences of the metaverse: a multi-criteria approach to the SDGs
Fatemeh Ghasemzadeh, Babak Ghahremannasab, Jurgita Antuchevičienė, Violeta Šniokienė, authors of the article “Exploring the social and economic consequences of the metaverse: a multi-criteria approach to the SDGs”, published in Technological and Economic Development of Economy, 31(5), 1619–1643, https://doi.org/10.3846/tede.2025.24858 inform that the first author's last name is misspelt and we would like to make the following correction to the authorship: Fatemeh GHASEMZADEH, Babak GHAHREMANNASAB, Jurgita ANTUCHEVIČIENĖ, Violeta ŠNIOKIENĖ The authors regret the error.
Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)
Addressing regional disparities while pursuing sustainable development has become a critical policy challenge. This study develops a meta parallel two-stage dynamic range directional measure (RDM) directional distance function (DDF) data envelopment analysis (DEA) model to evaluate the efficiency of poverty reduction (SDG 1) and decent work and economic growth (SDG 8) across 30 provinces in China. Given uneven regional development, the provinces are grouped into eastern, central, and western regions, and kernel density estimation is employed to examine the spatial and temporal evolution of efficiency. The results indicate that: (1) The overall efficiency is moderate, with an average score of 0.67, highest in the eastern region, followed by the western, and lowest in the central region. (2) The efficiency of SDG 8 (0.93) significantly exceeds that of SDG 1 (0.87), while the regional ranking remains consistent with the overall efficiency. (3) The technology gap among the three regions shows dynamic changes: the western region has overtaken the eastern region to become the most advanced. In contrast, the central region continues to lag, and its gap with the other regions is steadily widening. First pubished online 29 October 2025
Climate change as a socio-economic challenge for the tourism sector: an econometric analysis of countries with the highest economic losses
The issue of climate change, and in particular the economic losses caused by natural disasters, is a significant problem for the tourism sector and its development. The research conducted aims to address the following research question: Does climate change, quantified by the economic losses attributed to extreme weather events, influence the development of the tourism sector, as measured by tourism’s contribution to GDP? Furthermore, the study explores the role of insurance as a financial instrument for mitigating the effects of climate change on tourism. An important part of the research is an in-depth regional analysis of climate change losses. It was carried out both on a continental level and for the countries studied. Statistical and econometric techniques were employed to investigate the research question. The analysis focused on a selection of countries identified by the Swiss Re Institute as having experienced the highest economic losses due to climate change. Thirteen countries were surveyed, ensuring representation for each continent. The research period spans the years 2014–2023, and the data analysis was conducted using Statistica 13 and Gretl software. The findings indicate that economic losses resulting from natural disasters show an increasing trend, both in absolute terms and as a percentage of national GDP. These losses represent a significant constraint on economic growth, particularly limiting the development of tourism. Furthermore, the survey shows that the negative effects of climate change are more challenging for less economically developed countries. These countries are in addition to being more exposed to climate-related damages because of their natural conditions, but also struggle with underdeveloped insurance sectors. Reduced access to insurance compounds the disruptive impact of climate change on tourism. An analysis of the relationship between the weather damage load on a country’s economy and the insurance gap identifies three countries – the USA and China – as being especially at risk. Investigating the impact of the effects of natural disasters on the development of the tourism sector in countries with the greatest economic losses from climate change fills a research gap in this area and contributes to the development of knowledge on the effects of climate change on the competitiveness and sustainability of tourism. The research should be considered original in its subject coverage. No studies of this scope have been found in the literature. Investigating the impact of insurance on climate change mitigation for the tourism sector should also be considered innovative. The results of the research can be used to shape tourism policy in the countries studied, as well as globally.
Refreshing the design of a regional economic growth model in the context of the new digital decade
The digital economy is a significant objective of future development of the European space and is included alongside other strategic objectives in the 2030 and 2050 Agenda of the European Union. According to the European Union’s Digital Economy and Society Index (DESI), the Nordic countries (Finland, Denmark, the Netherlands, and Sweden) are the top performers of the European Union. In the same time, Romania ranks last in the 2022 ranking. Current research analyses the four areas of the digital economy (human capital, digital technology integration, connectivity, and digital public services) in a mix that is correlated with regional indicators of sustainable development to design a regional model of digital economy growth. The methods of study include restructuring the DESI rankings and regional reclassification based on the criteria of correlative ranking of digital economy indicators in correlation with sustainable development indicators and the design of structural equations. The study results will form the basis of a public policy proposal to accelerate digital development for disadvantaged European regions. First published online 24 September 2025
How does green innovation determine corporate physical investment? New empirical evidence
Due to the escalating issue of global warming and other environmental concerns, green innovation has garnered significant attention. However, there is a dearth of literature addressing the impact of green innovation on industrial investment. Therefore, the present study aims to investigate how green innovation affects corporate physical investment. We utilize a wide array of financial data from a panel comprising 11 Asian economies and employ the system GMM (generalized method of moments) to test the underlying hypothesis. The empirical findings reveal a positive and statistically significant effect of all proxies for green innovation, including patent registrations, the development of environmental technologies, innovation intensity, and green growth innovation, on corporate physical investment. The empirical analysis yields a crucial policy implication, emphasizing the importance of prioritizing green innovation and the adoption of modern technology. These initiatives not only boost investment volumes but also contribute to achieving environmental sustainability. By exploring the intricate relationship between green innovation and corporate physical investment, the current study introduces innovative insights to the literature on financial and environmental economics. First published online 03 September 2025
development in environmental technologies
The efficiency of sustainable development goals 4 and 8 in China: impact of low fertility
China’s declining birth rate is gradually eroding the demographic dividend, potentially affecting education, employment, and the economy. This study constructs a meta two-stage dynamic Directional Distance Function (DDF) Data Envelopment Analysis (DEA) model under exogenous variable. It considers the birth rate as an exogenous variable to assess the efficiency of 30 Chinese provinces in achieving SDGs 4 and 8. Key findings include: (1) Integrating the birth rate into the analytical framework has enhanced overall efficiency in most provinces, particularly in the central region. The average efficiency across 30 provinces was 0.8, with minimal regional disparities. (2) The birth rate positively influences both SDG 4 and SDG 8, notably boosting SDG 4 efficiency. (3) Efficiency varies by province: 17 exhibit high efficiency in both SDG 4 and SDG 8, one shows low SDG 4 but high SDG 8 efficiency, two have high SDG 4 but low SDG 8 efficiency, and ten are inefficient in both goals. (4) Hebei, Shandong, and Guangdong have significant redundancy in education and social security investments. Hebei, Henan, and Shanxi show considerable deficiency in economic growth and employment, while Xinjiang and Inner Mongolia require further enhancements in energy efficiency. First published online 23 September 2025
meta two-stage dynamic DDF DEA model under exogenous variable
The dynamics of the FDI-productivity nexus in BRICS: a wavelet coherence study
The current study investigates the interrelationship between FDI inflows and total factor productivity (TFP) in BRICS economies comprising Brazil, Russia, India, China, and South Africa, along with newly added members Egypt, Ethiopia, Iran, Saudi Arabia, and the UAE. Previous research has often overlooked the country-specific factors that influence how productivity impacts FDI inflows. To address this gap, the study introduces methodological innovation by employing the Method of Moments Quantile Regression (MM-QR) with fixed effects, using annual data from 2012 to 2022. This method accounts for unobserved heterogeneity, allowing for a detailed analysis of how TFP affects FDI across different countries and quantiles. The study adds novelty by utilising wavelet coherence analysis to explore co-movements and causal relationships between FDI and key macroeconomic variables at different time scales. The results show that FDI inflows have a positive and significant relationship with GDP and trade openness while exhibiting a negative association with TFP. Over the long term (16–32 weeks), coherence remains relatively weak, but TFP demonstrates a more consistent impact on FDI inflows compared to the other variables. The study recommends that BRICS nations should enhance FDI’s impact by improving trade integration and regional cooperation to attract high-value investments and foster sustainable growth. First published online 24 September 2025
Method of Moments Quantile Regression (MM-QR)
The role of education and digitalization in tourism development: evidence for the European Union
The investigation of the relationship between tourism, digitalization, education, and economic growth is increasingly significant in the context of sustainable development and technological transformation. This study examines the long run and short run impacts of digitalization (measured through internet usage and broadband subscriptions), education (reflected in tertiary enrollment and public expenditure), and macroeconomic factors (including GDP per capita, employment in services, and urbanization) on international tourism performance, as indicated by arrivals and receipts across clusters of European Union countries. Methodologically, the study adopts a two-stage approach. Hierarchical cluster analysis is first applied to classify European Union countries according to key tourism characteristics, followed by the estimation of panel ARDL models for each resulting cluster to examine both long-run equilibrium relationships and short-run dynamics. Employing panel ARDL models applied to four distinct groups of countries, the analysis highlights differentiated dynamics, strong long-run effects in high-income tourism economies and more pronounced short-run responsiveness in structurally varied countries. Cointegration tests affirm the existence of long-run relationships in most clusters, reinforcing the validity of an error correction framework. Therefore, the empirical findings indicate that digitalization exerts a consistently positive influence on tourism performance in the long-run, while the effects of education are more heterogeneous across clusters. In the short-run, the impact of macroeconomic variables and digital infrastructure is more pronounced, underscoring the relevance of structural and contextual factors in shaping tourism dynamics. The findings emphasize the importance of aligning digital and educational policies with tourism development strategies while considering the structural differences among regions. This research provides a comparative framework that enhances the understanding of tourism as both an economic and social phenomenon.
A grey-based hybrid decision support framework for assessing the Environmental, Social, and Governance (ESG) sustainable performance: a case study of BIST-listed banks
The present research has been designed to address two significant gaps in the existing literature pertaining to the banking industry. Firstly, it presents a set of criteria derived from the Refinitiv database for the evaluation of ESG sustainability performance. Secondly, it puts forward a novel methodological framework that is both novel and noteworthy in the MCGDM field. This framework employs a grey-based multi-criteria group decision-making (MCGDM) technique with Bonferroni aggregation to comparatively analyze banks’ ESG sustainable performance. The developed methodology uses extended versions of three very recent methods, like the Modified Standard Deviation (MSD), Symmetry Point of Criterion (SPC), and Simple Ranking Process (SRP), based on the utilization of interval grey numbers. The Bonferroni aggregation operator is utilized for the aggregation of the experts’ evaluations concerning the alternatives based on the selected criteria. A real-life case study on seven publicly traded banks in the Borsa Istanbul Sustainability Index is conducted with the aid of five experts. The research results imply that among the three main ESG dimensions, environmental management practices emerged as the most important factor influencing banks’ sustainable performance. This finding also signals that banks that adopt sound environmental management practices into their business models may gain a competitive edge over their competitors in terms of environmental regulations, resilience to environmental risks, and achieving high performance and stability. Finally, the model’s validity is checked via comparison and sensitivity assessments. The outcomes of the two-stage validation analysis corroborate the robustness and dependability of the suggested grey MCGDM model.
Environmental, Social, and Governance (ESG)
Bivariate grid scale based multiple attribute evaluation technique (GAMETE) with incomplete information on weights
In this paper, we have devised a novel Multiple Attribute Decision Making (MADM) method referred to as the bivariate Grid Scale based Multiple Attribute Evaluation Technique (GAMETE) method to deal with MADM decision problems involving tangible and intangible attributes under incomplete weight information. The proposed method innovatively incorporates an Attractiveness GRID Scale (AGRIDS) to evaluate intangible attributes, grounded in cognitive psychological principles – particularly the separability and independence of positive and negative aspects in human judgement. Additionally, a new bidimensional positional advantage operator (bi-pao) is introduced to compute the intangible attractiveness index. Further, linear programming models are formulated in order to construct the pairwise dominance matrix. Afterwards, we rank alternatives using a dominance intensity measure and the Boolean matrix. Furthermore, the proposed method is illustrated through a logistics center location problem. We also perform a comparison with several state-of-the-art linguistic Intuitionistic Fuzzy Sets (LIFS) and linguistic Pythagorean Fuzzy Sets (LPFS) based MADMs with the aim of showing the applicability and feasibility of the method suggested. Notably, GAMETE provides a multidimensional decision-making framework suitable for addressing complex technological and economic challenges where both quantitative and qualitative factors coexist. Its flexibility and interpretability make it a promising tool for real-world strategic decision scenarios.
Does government digitization contribute to economic growth? Empirical evidence from 109 countries
In the digital age, governments worldwide are increasingly turning to digitization to enhance efficiency and foster economic growth. This study investigates the impact of government digitization on economic growth, addressing the pressing issue of how digital transformations within the public sector can drive economic growth. First, we empirically estimate panel data from 2002 to 2021 across 109 countries using multiple statistical methods, consistently supporting that government digitization can significantly promote economic growth. Subsequently, mechanism tests are conducted using two fixed effect models containing interaction terms, revealing that government digitization can foster economic growth by curbing corruption and reducing the time businesses need to access public services. Furthermore, heterogeneity analysis confirms the moderating effects of telecommunications infrastructure, basic education popularization, natural resource abundance, government efficiency, democracy, and ruling party ideology on the relationship between government digitization and economic growth. Lastly, quantile regression reveals a nuanced pattern, indicating that as a country’s economic development level increases, the promoting effect of government digitization on economic growth initially rises before declining. These findings provide new insights for governments worldwide seeking economic growth. First published online 04 July 2025
Innovation spillovers as a driver of economic development: evidence from regions located in Central and Eastern European Union countries
Innovation has been a core element in the economic development of countries worldwide. Although innovation often has a global impact, it is created in a particular location. This research focuses on regions from Central and Eastern European Union (EU) countries as they are in the process of catching up with more developed Western EU economies. This paper aims to explore the link between innovation level and economic development in Central and Eastern EU countries from a regional perspective as well as to examine the impact of innovation spread between these regions. The analysis applies spatio-temporal models for data on the regional innovation index and gross domestic product per capita from 2016 to 2022. The results of this research show that southeastern regions had, on average, a lower level of both innovation and economic growth than western and northern ones. The analysis also confirms the positive relationship between innovation and economic development in these regions. Finally, this research proves the existence of spatial innovation spillovers: the strongest effect in Polish (near its capital city’s region) and Romanian regions while the weakest one in Slovenia, Bulgaria, and further from the capitals of Romania, Poland, and the Czech Republic. First published online 16 July 2025
Digitalization and configurational effects on regional income inequality: analysis of panel data from 134 economies
The literature on the impact of digitalization on regional income disparities is fragmented and contentious. Drawing on complex systems perspective and configurational theory, this paper analyses the configurational effects of digitalization factors embedded in specific contexts on regional income disparities, using a sample of 134 economies from 2012 to 2021, employing Panel Fuzzy-Set Qualitative Comparative Analysis (Panel fsQCA) and Necessary Condition Analysis (NCA). This paper identifies four context-specific configurational patterns through which digitalization reduces regional income disparities. While no single condition emerges as a strictly necessary condition, digital inclusion and digital finance demonstrate broad positive effects across configurations. Although digital transformation cannot guarantee reduced disparities, severe digital deficiency consistently leads to widening regional income disparities. At the same time, this paper discovers previously unnoticed causal mechanisms and captures the dynamic trends and spatial characteristics of digitalization’s impact. These findings offer diverse,adaptable insights for regional common prosperity. First published online 23 September 2025
Housing price, bank credit, and firm innovation investment: theory and evidence from China
This paper develops a novel theoretical model to explore the impact of housing price appreciation on firm innovation investment and its interaction with bank lending. The predictions of the model are empirically tested using a comprehensive dataset of China’s A-share listed companies and 94 cities over the period 2011–2021. The findings provide robust evidence of a crowding-out effect, where rising housing prices negatively affect firm innovation investment. Moreover, the crowding-out effect is found to be less pronounced for firms with stronger debt repayment capabilities, superior R&D capabilities, or in tighter credit environments, consistent with the theoretical predictions. Further analysis indicates that the crowding-out effect becomes significant only when banks show a stronger preference for providing short-term loans or exhibit lower service efficiency. In terms of firm innovation outcomes, housing price appreciation generally reduces innovation efficiency, and this negative impact is especially pronounced for lower-quality innovation projects. First published online 19 November 2025
Addressing hidden challenges in urban renewable energy integration via a hybrid-decision model
The integration of renewable energy into urban development has some critical legal challenges. However, the literature lacks a systematic framework for prioritizing the most critical obstacles. Existing studies generally address the legal barriers to the integration of renewable energy into urban areas at a general level. Therefore, these studies do not provide a systematic framework to prioritize which barriers are more critical. This deficiency creates some important problems such as increasing investor distrust, delays in projects and increasing costs. This study tries to fill this gap by establishing a novel hybrid decision-making model to evaluate hidden legal challenges in renewable energy integration. The proposed model follows a structured methodology by integrating z-scoring method to ensure expert representativeness, p,q,r-Fractional fuzzy sets to handle uncertainties, entropy method to compute the weights of the identified legal barriers and grey relational analysis to identify the most effective strategy alternatives. The main contribution is that prior investment strategies can be identified to overcome these legal challenges regarding the integration of renewable energy into urban development by creating a novel model. The use of p,q,r-Fractional fuzzy sets in this model provides an important contribution to the literature. With the help of considering these sets, more complex and multi-dimensional uncertainties can be managed more effectively. The findings highlight the significance of financial incentives and streamlined regulatory processes to have the sustainable transformation of urban areas. First published online 23 September 2025
Does fiscal and financial green policy coordination curb corporate “greenwashing”? Evidence from the green loan interest subsidies policy in China
Amidst the push for green development, finding ways to effectively coordinate fiscal and financial policies to curb corporate “greenwashing” has emerged as a crucial issue to investigate. Using data from non-financial listed firms in China from 2011 to 2022, this study employs a multi-period difference-in-differences model, treating the green loan interest subsidies (GLIS) policy as a quasi-natural experiment to examine its impact on “greenwashing”. We find that the GLIS policy significantly suppresses corporate “greenwashing.” GLIS policy not only stimulates bank credit supply and increases the scale of green credit, but also motivates banks to strengthen their risk identification mechanisms, thereby curbing “greenwashing.” The inhibitory effect is more pronounced in firms with high financing constraints, low transparency in environmental management systems, and heavy pollution firms. Moreover, GLIS policy can synergize fiscal and financial policies, addressing the deficiencies of individual policies and enhancing their practical effectiveness in green governance. Overall, our results verify the inhibitory effect of the GLIS policy on “greenwashing,” providing evidence and useful insights for China and other countries or regions to promote coordinated green policies between fiscal and financial sectors. First published online 20 October 2025
Integrated expert model for risk assessment and ensuring the safety of tourist trips: economic and technological aspects
This study aims to develop an integrated expert model for assessing and ensuring the safety of tourist trips, with a particular emphasis on the economic and technological aspects. The model adopts a multi-level approach, spanning from individual perceptions of safety during travel to national assessments of regional tourism security. The economic factors, such as the financial implications of safety measures and their impact on regional tourism development, play a central role in this approach. The methodological foundation includes the theory of fuzzy sets and fuzzy logic, expert evaluations, and knowledge-based intelligent analysis. For the first time, we received: an information model for assessing the safety level of a tourist trip; a fuzzy method for determining the aggregated term risk assessment of one’s safety of a tourist trip; an expert method of assessing the level of the sense of security of the region on the part of the participants of the tourist movement; a hybrid method of determining the degree of risk to the safety of a tourist trip. The model not only provides a quantitative assessment but also highlights the safety risks associated with tourist trips, thereby enabling regional analyses that support decision-making aimed at ensuring tourism safety through both economic and technological means solutions.
Technology innovation and carbon efficiency in Africa: what is the role of digitalization and digital inclusive finance?
Improving carbon efficiency and mitigating carbon emissions is fundamental to sustainable development and the well-being of human society. Yet, no study highlighted and identified the drivers of carbon efficiency in Africa. Specifically, an empirical study on the role of technological innovation (GTI), digitalization, and digital inclusive finance (DIF) in improving carbon efficiency (CEE) in Africa is rare. To fill this gap, this study investigates the synergistic impact of green technological innovation (GTI), digitalization, and digital inclusive finance (DIF) on improving carbon efficiency (CEE) from the African perspective. A meta-frontier slack-based environmental polluting technology and mixed integervalued data envelopment analysis (DEA) is framed to gauge the carbon efficiency across oil-endowment and non-oil-endowment African countries from 2010 to 2019. The results indicate that only a few African countries appeared to be operating at efficient production levels. The bootstrapped regression results indicated an invented U-shaped nexus is established between carbon efficiency and African economic development via the extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) framework. Internet usage and mobile cellular subscriptions as components of digitalization positively improve Africa’s carbon efficiency. Mobile money transaction innovation (i.e., active mobile money agents per 1000 km2) as a dimension of digital inclusive finance conserves Africa’s environmental efficiency. Green technological innovations did not drive carbon efficiency significantly in Africa and the two groups. Based on the empirical findings, pragmatic policy strategies are further discussed to boost carbon efficiency and mitigate environmental degradation in Africa.
The dark side of strengthening tax enforcement
Using the staggered adoption of China’s province-level Tax Administration Information System (TAIS) as an exogenous shock, we show that firms compromise employee workplace safety in response to strengthened tax enforcement driven by advances in tax collection technology. This effect is more pronounced in firms with significant prior tax avoidance, those under greater earnings pressure, and those where employees have limited bargaining power. Further analyses reveal that firms reduce employee workplace safety by cutting safety-related investments and increasing employee workloads. Collectively, our study highlights an unintended consequence of intensified tax enforcement on workplace safety.
Adapting to uncertainty: A quantitative investment decision model with investor sentiment and attention analysis
In the face of global uncertainties, including pandemics, economic fluctuations, disruptions in supply chains, major disasters, wars, and impending economic crises, the financial landscape and the impact of investor sentiment on the return of stock index futures can be significantly altered. Understanding the relationship between investor sentiment, attention, and stock index futures returns in the face of these diverse challenges has become particularly critical. However, existing research does not adequately consider the effect of these unexpected events on the market and the shifts in investor attention. Using the COVID-19 pandemic as a case study, this research proposes a dynamic quantitative investment decision-making model that considers the influence of investors’ attention and emotional characteristics, aiming to adapt to the financial market under these global changes and improve the accuracy of quantitative investment forecasting. Initially, the Bidirectional Encoder Representations from Transformers model is employed to analyze investor comment data, extract information on investor attention and emotional characteristics, and construct investor sentiment indicators. Subsequently, a stock index futures forecasting method based on Variational Mode Decomposition algorithm and Support Vector Regression (SVR) model is constructed, and the grey wolf optimization algorithm is introduced to optimize the parameters of the SVR model. Guided by investor sentiment indicators, different market states are further distinguished, and appropriate investment strategies are implemented to effectively enhance the returns of quantitative investment. When compared with models that neglect investor attention and emotional characteristics, the results show that considering investor sentiment indicators not only improves the predictive ability of the model, but also reduces cognitive bias and market risk. First published online 6 December 2024
Copyright (c) 2024 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
The convergence of environmental innovation, stakeholder pressure, open innovation in logistics firms: pathway to renewable energy in the presence of managerial cognition & competitive advantage
The logistics industry has recently been pressured to adopt sustainable practices due to increasing environmental concerns and regulatory mandates. This study investigates the nexus between ecological innovation, stakeholder pressure, open innovation, and renewable energy adoption in logistics firms, emphasizing the moderating role of managers’ cognition of sustainable opportunities and competitive advantage. In this regard, stakeholder pressure compels organizations to adopt renewable solutions. On the other hand, open innovation and eco-innovation are pivotal in taming firms’ internal limitations and advancing the adoption of renewable technologies. Thereby, analyzing empirical data from China’s logistics firm, the present study demonstrates how open innovation, eco-innovation, and stakeholder pressure affect renewable energy adoption and the firm’s competitive advantage. In addition, the study explicitly outlines the critical role of managers’ cognition of sustainable opportunities and competitive advantage as a moderator. Through SEM, the study reveals a positive and significant relationship between open-innovation, eco-innovation, and stakeholders’ pressures regarding renewable energy adoption. The moderation of managers’ cognition in the case of eco-innovation and open innovation proved significant, whereas, in the case of stakeholder pressure, it is insignificant. Competitive advantage, another moderator, failed to moderate the proposed relationship. Findings explain that managers can realize strategic significance in terms of sustainability. They may shift toward green strategies aligned with market apprehensions and environmental regulations. This cognitive factor enhances the usefulness of open and eco-innovation during renewable adoption. Overall, the study’s findings underscore the significance of managerial insights in leveraging these factors to accelerate the industry toward a sustainable future.
E-commerce policy, market integration and regional economic disparities: evidence from China’s national e-commerce demonstration cities
Using panel data of 284 cities at prefecture level and above in China from 2003 to 2022, this paper takes the National E-commerce Demonstration Cities (NEDC) as a quasi-natural experiment, employs the staggered difference-in-difference (DID) model to examine the impact of the NEDC policy on regional economic disparities (RED), and explores the mediating roles of factor and commodity market integration. The main findings are as follows: First, the NEDC policy significantly narrows RED, which still holds after a series of robustness tests. Second, the mechanism analysis demonstrates that the NEDC policy mitigates RED by fostering both factor and commodity market integration. Third, the inhibitory effect of the NEDC policy on RED is more pronounced in non-eastern cities, southern cities, commercial-based cities, ordinary prefecture-level cities and good business environment cities. Fourth, the NEDC policy exhibits a significant synergistic inhibitory effect on RED within 150 km radius of the demonstration cities. Moreover, the inhibitory effect of the NEDC policy becomes more pronounced at lower quantiles of RED. This study elucidates the role of e-commerce policy in narrowing RED and provides valuable policy insights for achieving coordinated regional economic development in the new era. First published online 16 July 2025
National E-commerce Demonstration Cities (NEDC)
An analysis of the influence and mechanisms of the digital economy on the disparities in urban total factor productivity
The influence of the digital economy (DE) on the coordination of the urban total factor productivity (TFP) gap and its underlying mechanisms were investigated. The significance of this research mainly originates from its contribution to the theoretical understanding of regional coordination mechanisms, offering new insights into how the digital economy internally regulates disparities in regional TFP. Key findings include: (1) The dynamic analysis reveals that during the early stages of DE, the urban TFP gap expands significantly. However, as the digital economy matures, it contributes to reducing this gap. (2) Quantile regression results indicate that the digital economy substantially narrows the TFP gap primarily in regions with the most pronounced disparities (comprising 20% of the sample), while this effect is not evident in the remaining 80% of regions. (3) Enhancing the level of marketization of factors significantly strengthens the digital economy’s ability to reduce the TFP gap, and improvements in resource allocation also contribute to this effect. First published online 06 June 2025
Exploring service improvement through importance-performance analysis considering the reliability of multiple online platforms
Service improvement has emerged as a pivotal task for hoteliers to ensure competitive advantage. This study proposes a service improvement method based on online reviews from multiple platforms considering the reliability of online platforms and different evaluation modes, where the reliability of an online platform is defined based on the number of online reviews on that platform and the degree of review helpfulness. In our method, Latent Dirichlet Allocation model is utilized to extract keywords, and lexicon-based sentiment analysis methods are employed to analyze the sentiment of online reviews on each platform considering different evaluation modes. The importance of attributes on each platform is measured by the TextRank method. A multi-platform-oriented importance-performance analysis model is constructed based on the integrated performance and the importance of attributes, so as to classify attributes and formulate service improvement strategies. A case study about hotel service improvement is implemented to illustrate the effectiveness of the method. Results show that the attributes classification results considering the reliability of multiple platforms is more reasonable compared to the results based on a single platform, providing more effective service improvement strategy and clearer view of attribute status on various platforms for hoteliers.
Unlocking the inverted-U: exploring the threshold impact of population aging on income inequality dynamics
As population aging unfolds at an unprecedented scale worldwide, its impact on income inequality continues to be contentious, with no clear consensus in the literature. Rather than viewing the aging-inequality linkage as solely positive or negative, this paper introduces a modified life cycle with precautionary behavior, indicating that inequality may initially worsen with aging before stabilizing at later stages. The Dynamic Panel Threshold Kink (DPTK) regression method is used to identify the threshold point of aging intensity at which the inequality begins to moderate following a period of intensification. The findings reveal a threshold aging intensity of 1.4%, which supports an inverted-U characterization of the aging-inequality nexus. The results suggest that liberalizing trade and improving government redistribution can assist countries experiencing a rise in inequality. At the same time, the prevalence of precautionary effects due to population aging may offer a natural defense against the detrimental effects of inequality over time. First published online 05 June 2025
The digital economy and city innovation convergence – an empirical research based on the innovation value chain theory
Within China’s strategy for innovation-driven development, digital economy (DE) plays a crucial role, significantly influences city innovation convergence. This study, grounded in the theoretical perspective of the innovation value chain theory (IVCT), divides innovation activities into two major phases: technological research phase and results transformation phase, and uses data from 283 Chinese cities spanning 2011 to 2021, it systematically explores, for the first time, the convergence characteristics of city innovation activities in each phase and delves deeply into the role of DE in this process. The findings reveal that city innovation in China’s cities demonstrates notable convergence characteristics during both technological research and achievements transformation phases. These convergence traits persist in both phases, even when accounting for spatial effects, particularly regarding the engagement of DE. Furthermore, in technological research phase, fiscal pressures faced by local governments diminish the effectiveness of DE in fostering city innovation convergence; but, during achievements transformation phase, such fiscal pressures do not impede DE’s capacity to enhance city innovation convergence. Lastly, the difference of city Innovation and entrepreneurial vitality during both technological research and achievements transformation phases restrict DE’s potential to support city innovation convergence, with a more pronounced diminishing effect observed in technological research phase. This study provides important decision-making support for policymakers and helps further uncover and unleash the potential of DE in promoting city innovation convergence. First published online 05 June 2025
city innovation and entrepreneurial vitality
Decoding tourist satisfaction for sustainable economic development: a multi-method configuration framework using online reviews
Online reviews are crucial to understanding tourist satisfaction (TSA) in the digital tourism era. This study deconstructs the factors leading to high TSA performance in reviews, offering guidance for long-term economic benefits for destinations and businesses. Building on the three-factor theory, we create a framework utilizing text mining, affective distribution computing, and fuzzy-set qualitative comparative analysis (fsQCA) to identify patterns driving high TSA. We employ topic modeling to extract destination attributes from reviews, quantifying their performance through affective distribution computing. An enhanced Kano model classifies tourist needs based on emotional expressions in reviews. We investigate how basic, performance and excitement attributes interact and influence TSA. Additionally, we apply the coupling coordination degree model (CCDM) to analyze attribute interconnections within configurations. Our results show that no single attribute leads to specific outcomes; relatively, high TSA results from a combination of attributes. This study identifies three normative causal recipes and is the first to clarify the complex interactions in satisfaction management within the three-factor theory framework, addressing a significant knowledge gap. Ultimately, our operational guidelines aim to sustain the economic vitality of the tourism industry. First published online 14 July 2025
The impact of digital economy on regional green and high-quality economic development in China
With the rapid advancement of digitization, the duty of the digital economic climate in advertising regional economic growth is ending up being progressively noticeable. Nonetheless, there is relatively little research study on how the digital economic situation specifically impacts regional environment-friendly and high-quality financial growth (RGED). This study utilizes provincial panel data from 2013 to 2020 in China to empirically assess the effect of the digital economic environment and validates its effect with a fixed impacts model. The study has produced four unique and important findings for: firstly, the effect of the digital economic climate on RGED exhibits nonlinear qualities; Second of all, RGED is significantly influenced by the “∩ - formed” effect of the advancement of the digital economic situation and the degree of industrial digitization; Finally, the influence of digital framework and digital industrialization on RGED exhibits a considerable “U-shaped” pattern; Fourth, the digital economic situation indirectly advertises the growth of RGED by enhancing human funding and updating commercial structure. These conclusions offer beneficial plan support for relevant financial entities to achieve RGED. First published online 05 June 2025
green and high-quality economic development (RGED)