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.
Environmental, social, and governance practices and reporting readiness in small and medium-sized enterprises
Following the European Sustainability Reporting Standards (ESRS), in 2026, the non-financial reporting obligation will be extended to small and medium-sized enterprises listed on the regulated market and meet employment and financial criteria. The obligation will also affect their contractors, suppliers, customers, and all stakeholders that influence a company’s overall Environmental, Social, and Governance (ESG) performance. The study aims to identify the Small and Medium-sized Enterprises’ (SME) practices in the field of ESG and recognise whether they are ready to report on their ESG activities. A quantitative method was used to obtain a general picture of the approach to ESG practices. The study was conducted among 300 Polish companies. The study results show that about half of the surveyed small and medium-sized enterprises conduct ESG activities and monitor ESG indicators. More than half demonstrate basic or good readiness for ESG reporting following the adopted criterion. This study’s contribution is twofold. First, it enriches the current state of knowledge by adding original insights into the ESG practices of SMEs, while most existing studies focus on the ESG activities of large enterprises. Second, the study’s novelty is its attempt to assess the readiness for ESG reporting at the corporate and country levels.
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
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
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)
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 technology innovation paradox in Asia’s leading innovative economies: the importance of renewable energy and green financing
The present study investigates the influence of green energy, technological innovation, financial development, natural resources, trade, and economic growth on environmental quality in four technologically innovative economies in Asia using data from 1990 to 2021. By adopting a holistic approach, it addresses gaps in the literature that often focus on isolated factors or regions. The findings provide actionable insights for policymakers to reconcile economic growth with ecological sustainability, offering a blueprint for sustainable development in Asia’s technological hubs. The Panel ARDL approach is used to evaluate the impacts in both the long and short term. Furthermore, we performed robustness tests using panel least squares, panel FMOLS, and panel DOLS techniques. The study’s findings indicate that technological innovation, financial development, and trade all have a long-term positive impact on environmental quality in Asia’s technologically innovative economies. However, green energy, natural resources, and economic progress had a negative impact on CO2 emissions. The findings from panel least squares, panel FMOLS, and DOLS also showed that technological innovation, financial development, and trade enhance the environmental quality. This investigation aims to assist policymakers in creating comprehensive plan that promotes environmental sustainability via technological improvements and renewable energy sources, with an emphasis on economic growth. First publihed online 05 June 2025
Trade liberalization, price transmission and household welfare: evidence from China
This paper estimates the welfare effect of trade through the price channel by jointly considering the consumption and income effect. The consumer price data and household survey data of China are used to conduct the empirical analysis. For assessing the consumption effect, the quadratic almost ideal demand system (QUAIDS) model is used to capture the substitution effect of price changes. We find that every household of China is better off due to the reduction of import tariffs, but there is a strongly pro-poor bias. More importantly, ignoring the substitution effect on the consumption side not only underestimates the absolute value of welfare changes but also distorts the distribution of welfare changes. Our results imply the importance of the consumption effect in estimating the welfare gain of households from trade liberalization. Our framework can also be extended to assess consequences of the opening policies of other economies. First published online 05 June 2025
Assessing the risks of fintech development: the case of online illegal capital raising
This study examines the impact of financial technology (FinTech) on online illegal capital raising (ICR) in China. Using a large dataset of court judgments from China Judgment Online from 2014 to 2019, we observe a steady increase in the number and proportion of defendants involved in online ICR cases. Our empirical analysis shows that FinTech contributes significantly to the increase in online ICR, particularly in regions with low opportunity costs of crime and limited access to traditional financial services. The findings remain robust to different FinTech proxies, sample adjustments, and considerations of potential endogeneity. Weak regulatory oversight and higher potential criminal returns are key channels through which FinTech promotes online ICR. These findings highlight the need for stronger financial regulation, especially in high-risk regions, alongside efforts to improve public awareness of online investment risks. Strengthening regulation while promoting the positive role of FinTech in financial development is critical to mitigating emerging financial risks. First published online 15 April 2025
How does city group risk-taking affect climate-friendly technology innovation in cities? Evidence from China
Climate-friendly technology innovation, which always comes with risk, is becoming an essential tool for Chinese cities to cope with climate change. As a macro variable, how does city group risk-taking affect climate-friendly innovation in cities? This study conducts a qualitative analysis on the basis of the theory of planned behaviour. Then, Chinese city data from 2008 to 2020 are employed to study the impact of city group risk-taking on climate-friendly technology innovation with city and year two-way fixed effects models. The results show: first, city group risk-taking promotes climate-friendly technology innovation in cities; for every one standard deviation increase in the level of city group risk-taking, the level of climate-friendly technology innovation in cities increases by 0.1294 standard deviations. Second, city group risk-taking improves a city’s market vitality and promotes the city’s governmental technology investments, both of which are conducive to climate-friendly technology innovation in cities. Third, the role of city group risk-taking in promoting climate-friendly technological innovation in cities is heterogeneous and is greater in cities with high enthusiasm for financial technology innovation, in cities with high population density and in cities with high environmental penalties. First published online 15 April 2025
From uncertainty to opportunity: financial development as bridge to green innovation under economic policy uncertainty
Green innovation (GI) is increasingly recognized as an essential strategy for tackling urgent environmental issues, such as climate change, resource depletion, and pollution. While research is expanding on how economic policy uncertainty (EPU) affects GI, the influence of financial sector development (FSD) as a moderator in this context remains under-examined. To address this gap, we conduct an empirical analysis utilizing two decades of data (2000–2019) from five major emerging economies (BRICS). The study employs FMOLS and DOLS models to scrutinize the data. The findings indicate that EPU has a considerable adverse effect on GI, suggesting that uncertainty in economic policies can obstruct environmentally sustainable progress. In contrast, FSD demonstrates a notable positive association with green innovation, indicating that a robust financial sector can support and bolster these initiatives. Furthermore, the study identifies that FSD serves a crucial intermediary function in the EPU-GI connection. The policy implications of this study are significant, indicating that decision-makers should prioritize enhancing financial sector institutions to foster GI, particularly in times of heightened economic volatility. By providing new evidence regarding the dynamics between EPU, FSD, and GI, this investigation offers valuable insights for developing policies that harmonize economic stability with environmental sustainability. First published online 1 April 2025
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 role of ICT in shaping international trade dynamics: a G20 perspective
This research examines the influence of Information and Communication Technology (ICT) on economic expansion and commerce within G20 nations. Findings reveal that the digital revolution and advancements in artificial intelligence have significantly bolstered the global digital economy, fostering enhanced productivity, innovation, and trade. Utilizing panel data analysis, the study demonstrates that progress in ICT technology contributed approximately 0.33% to economic growth. Additionally, it facilitated an expansion of about 0.12% in product trade and 0.14% in service trade. The research also uncovered a “Diminishing Marginal Returns of ICT on Trade” effect, where trade volume increases with ICT development, but at a decelerating rate over time. To maximize trade growth potential, the study proposes increased governmental investment in ICT technology development and innovation, coupled with the establishment of digital trade standards. These measures could position digital trade as a catalyst for future economic expansion. While the research acknowledges limitations such as a restricted sample size and reliance on panel data, its conclusions offer valuable insights for policymakers and enterprises in emerging economies. First published online 2 July 2025
Assessing SME credit rating in supply chain finance with multi-phase QFD-based MULTIMOORA under uncertainty
Presently, financial institutions have tentatively utilized supply chain finance as a means of assessing small and medium-sized enterprise (SME) credit rating. However, traditional techniques cannot satisfy the requirements of such assessments because financial institutions need to assess SME credit rating from the perspective of the supply chain and core enterprise rather than only from the perspective of SME. In this study, a hybrid technique with quantitative and qualitative criteria called multi-phase quality function deployment (QFD)-based MULTIMOORA under interval type-2 fuzzy set (IT2FS) is proposed to overcome the defects of traditional techniques. First, the quantitative values were converted into IT2FSs using the developed formulas. Second, a multi-phase QFD model is proposed to obtain the SME credit rating matrix by integrating the core enterprise credit rating matrix and the criterion relationship matrices among SME, core enterprises and supply chains. Third, IT2FS-MULTIMOORA is enhanced by considering the improved Borda Rule and extended reference point simultaneously to derive the final rankings; therefore, a weight-determining technique is presented based on the correlation coefficients. Finally, the proposed technique was applied to the SME credit rating assessment problem. Comparisons with other techniques and the sensitivity analysis results provide suggestions for financial institutions to provide loans to SMEs. First published online 31 March 2025
Fuel prices and economic activity: time and frequency analysis for selected European countries
The effects of fuel prices on economic activity are still being investigated, as oil and gas are critical inputs in the production process. This study examines the relationship between fuel prices and macroeconomic aggregates both in the time domain and frequency domain in three selected countries of Germany and Poland as net oil importers and Norway as a net oil exporter for the period 1995Q1–2021Q3. The causal relationships between these macroeconomic variables are first examined using a conventional Granger causality test for the time domain and then the Breiutung–Candelon test based on the vector autoregression model for the frequency domain, which are estimated separately for the long-term, business cycle, and short-term components obtained by applying the boosted Hodrick–Prescott filter. This study demonstrates that the predictability of fuel prices for macroeconomic aggregates differs across various frequencies. Although the patterns of causality differ across countries depending on whether it is oil-importing or oil-exporting and the level of economic development and energy mix, this relationship is found to be important for slowly and fast fluctuating components but to different degrees in each country. First published online 15 April 2025
A hybrid clustering and boosting tree feature selection (CBTFS) method for credit risk assessment with high-dimensionality
To solve the high-dimensional issue in credit risk assessment, a hybrid clustering and boosting tree feature selection method is proposed. In the hybrid methodology, an improved minimum spanning tree model is first used to remove redundant and irrelevant features. Then three embedded feature selection approaches (i.e., Random Forest, XGBoost, and AdaBoost) are used to further enhance the feature-ranking efficiency and obtain better prediction performance by applying the optimal features. For verification purpose, two real-world credit datasets are used to demonstrate the effectiveness of the proposed hybrid clustering and boosting tree feature selection (CBTFS) methodology. Experimental results demonstrated that the proposed method is superior to others classic feature selection methods. This indicates that the proposed hybrid clustering and boosting tree feature selection method can be used as a promising tool for solving high-dimensional issue in credit risk assessment. First published online 12 February 2025
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
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.
Changes in food demand in the EU member states and selected OECD countries: the impact of disposable income, unemployment, and inflation
This study focuses on consumption patterns: as societies get richer, their attitude toward the level and structure of consumption changes. Unemployment and inflation might influence consumption patterns. This paper aims to analyze the impact of unemployment and inflation on the convergence of food demand in households in the EU Member States and selected OECD countries from 1995 to 2019. The analysis of β-conditional convergence proved that the convergence of the share of food expenditure was positively conditioned by the unemployment level and negatively by the disposable income, but with no inflation influence. While in club convergence of more developed economies, with a higher inflation level comes a higher share of disposable income spent on food. First published online 27 November 2025
DEA-based composite index for innovation-integrated human development performance assessment of countries
The Human Development Index (HDI) introduced by United Nations Development Programme (UNDP) offers a unique quantitative measure that encompasses advancements in three fundamental aspects of human development: health, education, and living standards. However, focusing on only three dimensions when evaluating human development performance of countries is not adequate in today’s digital world. This study proposes a data envelopment analysis (DEA)-based composite index to provide an innovation-integrated human development performance assessment tool for countries. The novel two-stage common-weight DEA-based approach proposed in here is applied in a case study examining the performance assessment of European Union (EU) countries. The first stage of the developed methodology consists of solving the novel commonweight DEA-based approach with HDI indicators as the outputs and the Gini coefficient as the input. At the second stage, innovation-based indicators from World Bank database are used to evaluate innovation efficiency of EU countries. The composite index that yields the complete ranking of EU countries in terms of innovation-integrated human development performance is computed as the product of the efficiency scores resulting from these two stages. The rankings produced by the proposed approach are compared with the HDI rankings as well as the results obtained from various common-weight DEA-based models. First published online 27 November 2025
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