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.
Enhancing economic resilience through digital innovation: the role of financial inclusion and infrastructure in urban China
The digital revolution has redefined financial inclusion, significantly enhancing the capacity of urban economies to withstand and recover from economic shocks. Using panel data from 285 Chinese cities between 2011 and 2020, this study examines the role of digital innovation in promoting economic Resilience, drawing on econometric models and Martin and Sunley’s conceptual framework of Resilience. Our findings reveal that the Digital Innovation Framework (DIF) enhances economic Resilience by driving financial inclusion, technological adoption, and infrastructure development. However, regional disparities persist, with the eastern and central regions benefiting more than the western and southern regions, which have lower economic scales. The quality of corporate operations and the stability of financial markets further amplify the positive effects of digital finance on Resilience. Mediating factors, including the adoption of digital technologies and household expenditure levels, significantly strengthen the impact of DIF on urban Resilience. This study highlights the dual role of digital finance as both a catalyst for innovation and a tool for promoting equitable economic growth. The findings underscore the importance of region-specific policies in bridging development gaps, particularly in less developed areas. Policymakers are encouraged to promote inclusive digital strategies that foster fairer growth while leveraging the transformative potential of DIF.
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Advancing environmental quality through innovation and green entreprenuership
This study investigates the relationships among green entrepreneurial activities, Green Techno-Environmental Innovations (GTEI) and environmental quality. Economic development and renewable energy consumption (CRE) are used as control variables to explore the phenomenon more comprehensively. Data are collected from 40 Organization for Economic Cooperation and Development (OECD) economies and analyzed using ordinary least squares regression models. The findings indicate that green entrepreneurship, GTEI and CRE enhance climate sustainability, whereas economic development leads to a deterioration in environmental quality. This study replaces GTEI with green technologies related to energy generation and production and the disposal of greenhouse gases individually and finds similar results, except for clean technologies in the production of goods. Green innovations linked to production processes which do not show a significant impact on environmental quality. This result arises because production processes lead to harmful emissions, which, in turn, lead to a deterioration in climate quality. This study provides crucial insights and policy implications for enhancing green entrepreneurial activities within OECD economies.
Corrigendum: Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)
Li Ji, Shigui Tao, Tai-Yu Lin, Yanan Sun, Mingle Chen, Yung-ho Chiu, Wesley Hu, authors of the article “Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)”, published in Technological and Economic Development of Economy, 32(2), 485–507, https://doi.org/10.3846/tede.2025.24894 inform that the following note below Table 5 in page 493 should be added. Note: Due to the unavailability of relevant data, the study sample does not include Xizang, Hong Kong, Macao, and Taiwan; therefore, the analysis focuses only on 30 provincial-level regions in China. The correction does not affect the data, empirical results, or conclusions of the article. The authors regret the errors.
Corrigendum: The efficiency of sustainable development goals 4 and 8 in China: impact of low fertility
Li Ji, Shigui Tao, Jiawei Liu, Yanan Sun, Jingjing Geng, Yung-ho Chiu, authors of the article “The efficiency of sustainable development goals 4 and 8 in China: impact of low fertility”, published in Technological and Economic Development of Economy, 32(1), 206–232, https://doi.org/10.3846/tede.2025.24427 inform that several details in Figures 5 and 11 need to be corrected. Figure 5 (p. 219): “No data” should be used to indicate that the white areas are not included in the study sample, and the inset map has been updated. The note has been added. Figure 11 (p. 229), the inset map has been updated. The corrections have no impact on the data, methodology, results, conclusions, or scientific findings of the paper. The authors regret the errors.
Digital infrastructure and education as drivers of entrepreneurship in the European Union
In the context of accelerated digital transformation, understanding the factors that stimulate entrepreneurship at the European level has become a strategic priority. This study investigates the impact of digital infrastructure and human capital on new business density in the European Union, testing the hypothesis that these determinants operate differently depending on countries’ innovation stage. The analysis is grounded in a balanced panel dataset covering 26 EU member states over the period 2010–2023, grouped into four innovation clusters according to the European Innovation Scoreboard. Empirical analysis adopts a dual econometric approach. Static relationships are estimated using a Panel EGLS framework with cross-section SUR weights to capture short-run correlations and cross-country interdependence. Dynamic relationships are examined through a Panel Autoregressive Distributed Lag (ARDL) model estimated via the Pooled Mean Group (PMG) method, allowing for the identification of long-run equilibrium effects and adjustment dynamics while accounting for structural heterogeneity. Results show substantial cross-cluster heterogeneity. For Moderate Innovators, primarily located in Southern and Central Europe, digital infrastructure acts as a clear catalyst for entrepreneurship, exerting positive effects on new business density in both the short and long run. In contrast, for Strong Innovators, digitalization displays a more complex temporal pattern, with short-run effects dominated by implementation and adjustment costs, while long-run benefits materialize as productivity gains. The analysis shows that tertiary education supports entrepreneurial entry in the short run, while its long-run effect becomes negative, reflecting rising opportunity costs and the increasing absorption of skilled labor into corporate employment. While emerging economies benefit directly from investments in digital infrastructure, mature economies require structural interventions to reduce market rigidities and better align human capital with entrepreneurial activity.
Integrated fuzzy model for assessing cultural tourism potential in ethno-villages
This research examines the alignment of ethno-villages with cultural tourism to assess their commitment to preserving cultural values but attracting tourists in order to increase the efficiency of the economy, also. By engaging tourism experts, this research categorizes criteria into distinct groups and uses an integrated fuzzy set approach to assess the cultural tourism potential of these destinations. By combining Improved Fuzzy SWARA (Step-Wise Weight Assessment Ratio Analysis) and fuzzy WASPAS (Weighted Aggregates Sum Product Assessment) methods with the Fuzzy DOMBI operator, the research presents a methodology to address uncertainties in decision-making. The IMF SWARA method determined the criteria’s significance by assigning weights, while the fuzzy WASPAS method introduced uncertainty into the decision-making process through Z-numbers. The findings highlight ethno-villages like Ljubačke Doline and Kotromanjić, demonstrating admirable dedication to cultural immersion in their tourism offerings. These ethno-villages can serve as examples of how culture, tradition, and customs can be smoothly integrated to improve the tourism experience and economic system as a whole.
Driving net-zero and resilient supply chains through industry 5.0: a strategic pathway for sustainable economic development
Industry 5.0 (I5.0) based practices help to reduce supply chain emissions while ensuring resiliency. But the evidence on these practices remains limited. Therefore, this study analyses the practices in the context of I5.0 that can enable net-zero and resilient supply chains. We followed a three-phase framework: (1) identify practices through literature review, (2) map their hierarchical relationships using Interpretive Structural Modeling (ISM), (3) evaluate causal influence using the Decision-making trial and evaluation laboratory approach (DEMATEL). The results indicate four important practices: ESG compliance, Life Cycle Assessment (LCA), human-centric and collaborative systems, and mass personalization. These practices help build net-zero and resilient supply chains. From a theoretical perspective, this study bridges the gap between I5.0 theories and the net-zero and supply chain resiliency concept. From a managerial perspective, this study offers a structured pathway to integrate digital and human capabilities for a resilient future. For policymakers, it highlights the need for incentives and infrastructure to improve I5.0 maturity.
A multi-valued neutrosophic ARAS model for economic resilience in uncertain olive farming systems
This study proposes the integration of Multi-Valued Neutrosophic Numbers (MVNNs) with the Additive Ratio Assessment (ARAS) method to conduct an economic evaluation of multi-criteria decision-making (MCDM) problems under high uncertainty. MVNNs enhance traditional neutrosophic approaches by allowing multiple degrees of truth, indeterminacy, and falsity, providing a richer representation of the ambiguous and often conflicting economic data prevalent in agricultural planning. The proposed MVN-ARAS framework is presented with formal definitions, aggregation operators, and a step-by-step decision-making procedure tailored for economic assessment. Its effectiveness is demonstrated through an illustrative investment case and a real-world application to prioritize and economically evaluate climate change adaptation strategies for smallholder olive growers in Chile’s Coquimbo Region. Results show that drought-resistant olive cultivars and water-saving irrigation technologies achieve the highest relative utility values, indicating their dominant role in improving economic resilience under prolonged water scarcity. In contrast, diversification-oriented measures – such as value-added olive products and rural ecotourism – rank lower but still contribute to long-term income stability. These findings highlight the ability of the MVN-ARAS framework to deliver a structured economic evaluation, a robust ranking of alternatives based on cost-benefit and risk criteria, and improved handling of conflicting expert opinions, offering decision-makers a transparent and reliable tool for strategic investment and resource allocation to enhance economic resilience.
Ensuring fair treatment of investors: a novel approach for revaluation of liabilities from unissued and unredeemed investment shares in collective investment funds
In the dynamic world of open-ended investment funds, where investors continuously enter and exit, and in funds with multiple classes of investment shares, a critical issue often goes unnoticed: the revaluation of liabilities from unissued and unredeemed shares. These liabilities, typically left unsettled and unrevalued for extended periods, can significantly skew the Net Asset Value per Share (NAVpS), leading to unfair treatment of different groups of investors. In this paper, a novel methodological framework designed to adjust the NAVpS is introduced that not only ensures fair treatment among all groups of investors, but also provides unbiased performance information to potential investors. It also addresses the complexities of non-revalued liabilities in funds with multiple investment classes, which can disrupt class allocation ratios. The practical implications of the framework are profound. The issues of fair allocation across multiple investment classes and mitigating distortions arising from unrevalued liabilities related to unissued and unredeemed shares are addressed. As demonstrated in focused case studies, these distortions can become significant, depending on the size of the liabilities and changes in the value of underlying assets. We believe that our approach contributes to a more transparent investment landscape for all stakeholders.
Determinants of sustainable economic development in the EU: the role of innovation and infrastructure resilience
Technological innovation and infrastructure resilience are key pillars of sustainable economic development in the European Union, directly contributing to the achievement of Sustainable Development Goal 9 (SDG 9). This goal supports the transition to a competitive, climate-neutral and digitized economy by 2050 by strengthening resilient infrastructures, promoting sustainable industrialization and fostering innovation capacity. This study investigates EU Member States’ performance against SDG 9, using a set of indicators provided by Eurostat and applying the Holt-Winters (AAA) forecasting model to project trends through 2030. The analysis covers key areas such as R&D expenditure, patent activity, sustainable mobility and industrial emissions intensity. The results reveal significant progress in strengthening innovation capacity in some Member States; however, considerable regional disparities remain, particularly in transport infrastructure and industrial decarbonization. The study therefore highlights the need for integrated public policies, enhanced trans-national cooperation and targeted financial support to reduce structural gaps and accelerate sustainable convergence at European level. The conclusions emphasize the importance of an adaptive policy framework that harnesses the potential of emerging technologies and strengthens the resilience of industrial and infrastructure systems to meet the EU’s climate and economic objectives.
A study on the impact of global digital economy development on China’s export trade
The rapid development of the global Digital Economy (DE) is profoundly affecting international trade and has emerged as a crucial engine sustaining the steady expansion of China’s export trade (CE). Drawing on panel data covering 146 countries from 2003 to 2023, this study investigates in depth how the development of the global DE influences CE by integrating the level of DE development into an extended gravity model framework, and further examines the threshold effect arising from the DE gap between importing countries and China in this process. The study finds that the development of the global DE has significantly increased CE. The results of heterogeneity analysis indicate that this promoting effect is heterogeneous across countries with different levels of economic development and internet regulation, as well as across different industries. Mechanism analysis shows that this impact is mainly achieved through two channels: reducing trade costs and increasing production capacity. Finally, the empirical results reveal that when the DE gap between China and importing countries is introduced as a threshold variable, the influence of DE development in the importing country on China’s exports exhibits a single-threshold effect. Once the DE gap surpasses this critical point, the positive effect diminishes.
Sustainable last mile delivery: are e-consumers ready for courier services by electric vehicles?
Driven by the expansion of e-commerce and rising environmental awareness, this study is set within the context of growing market demand for sustainable and low-emission solutions in the courier industry. The aim of the article is to verify the readiness of e-consumers and the determinants to use an eco-innovative method of last-mile delivery by electric vehicles (EVs) in the courier services. A quantitative authors’ conceptual model including Technology Readiness and Technology Acceptance Model was developed and verified. Perceived ease of use significantly impacts perceived usefulness, and both strongly predict adoption intention. The growing shift toward electric fleets among couriers aligns with e-consumers’ readiness, however, the study offers important insights. Technological optimism influences adoption of last-mile deliveries by EV indirectly, e-consumers’ innovation and trust show an unsatisfactory effect. Although environmental awareness improves perceptions of use, it does not directly translate into higher adoption intent. The findings emphasise the importance of a holistic strategy that combines technological functionality, environmental values, and realistic expectations to promote the integration of EVs into courier logistics. Providers should focus on operational improvements and education, presenting EVs above all as efficient and easy to integrate with existing logistics systems, striving for their integration with sustainability and circularity.
Patent activity in the Polish food system and the business cycle. Conclusions from spectral analysis
Invention activity is an important innovation development factor, as it not only imposes changes in economic activity, but also often leads to the completely new structures within sectors. The aim of the paper was to investigate the relationship between macroeconomic and sectorial business cycle, and the patent filings in the food system in Poland in the period 2006–2022 taking advantage of statistics defined in time and frequency domains. Data on patent applications from 34 IPC classification (sub-)classes were analyzed, combined into five groups: food, beverages, tobacco, agricultural chemistry, agricultural machinery and packaging. The results obtained with spectral and cross-spectral analysis tools were compared with results obtained in the time domain. The positive relationship between patents and macroeconomic cycle is the strongest for cycles lasting 3.5–4 years, which dominate in reference to GDP series in the analyzed period. Patent filings are strongly positively correlated also with the agri-food sector output, especially in shorter cycles of 2.5–3 years. Although cycles of patent filings fluctuate much more than both business cycles, they seem to be more similar to the agri-food sector fluctuations. Moreover, patent activity may be treated as an early warning indicator of sectorial economic activity, whereas it’s lagging in reference to the aggregated economic activity.
Value-added manufacturing, growth and inflation: dynamic panel threshold perspective
This study pioneers the exploration of inflation’s nonlinear role in the nexus between value-added manufacturing and economic growth, employing a dynamic panel threshold model for 38 Organisation for Economic Co-Operation and Development (OECD) countries from 1980 to 2023. Unlike prior research, it uniquely identifies an inflation threshold (4.4954%) that alters the manufacturing-growth relationship. Below this threshold, value-added manufacturing significantly boosts economic growth, while above it, growth declines despite manufacturing process, revealing a novel nonlinear dynamic. Utilizing advanced methodologies like System Generalized Method of Momemnts (GMM) and Diallo’s (2020) dynamic panel threshold approach, the study addresses endogeneity and cross-sectional dependence, offering robust insights. These findings highlight inflation’s critical influence on manufacturing’s growth effects, urging policymakers to prioritize price stability to maximize manufacturing’s economic contributions. This research enriches the literature by integrating inflation thresholds into growth models, providing fresh policy implications for sustainable economic strategies in OECD economies. First published online 28 January 2026
Sustainability and carbon footprint evaluation at university: case study of VILNIUS TECH
Because of a societal push towards sustainability a problem emerges of adapting the concept to different sectors of the economy and society. The differing complexities of different fields and social structures make it difficult to create a universal sustainability strategy. Higher education institutions (HEIs) consist of a broad range of people, working in various fields of industry, making it an appropriate cross-section of the nation. Adapting sustainability practices in these institutions would allow to screen for successful policies before implementing them more widely, detecting most effective practices, allowing a faster transition towards achieving the Sustainable Development Goals (SDGs). It is hard to decide where to start, as many sustainable practices exist. This article presents the case study of VILNIUS TECH and conducts a comparison with universities in the region, determining best sustainability practices. The Greenhouse gas (GHG) protocol standard was used to form the emission inventory. The university comparison will help identify effective HEIs carbon footprint minimization practices, as well as other implemented policies as an example of where HEIs should start on their road to a more sustainable institution.
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
Multiple Normalization Rating Analysis (MUNRA) and its application to digital supplier selection in the textile industry
The rapid development of digital technologies – such as IoT, AI, blockchain, and digital twins – has transformed supply chains into interconnected ecosystems, making digital supplier selection both critical and complex. For the first time, this study proposes a novel multi-criteria decision-making (MCDM) method, Multiple Normalization Rating Analysis (MUNRA), for ranking alternatives. It integrates linear, vector, and non-linear normalization to improve robustness, reduce rank reversal, and enhance decision accuracy. A case study of digital supplier selection in the textile industry is considered for a real-life application of the method. Results highlight technology integration, flexibility, and technological capability as the most influential criteria for selecting digital suppliers. Moreover, the final ranking of the six digital suppliers is as follows: DS5, DS4, DS2, DS6, DS1, and DS3. Validation through comparative MCDM methods, Spearman correlation, and sensitivity analyses confirms the credibility of the method. It is also shown that it is free from the rank reversal phenomenon. The research presents a computationally efficient and rigorous method for evaluating digital suppliers, offering strategic insights for digital supply chain management. The application of MUNRA to a larger decision-making problem further illustrates its scalability and cross-domain applicability.
Assessment of data quality and validity of composite innovation indicators with a neutrosophic multi-criteria approach
In light of the emphasis on innovation as a driver of economic growth, new tools are needed to measure and compare national innovation systems. Improving methodological approaches to constructing composite innovation indicators also requires exploring issues related to aggregation, weighting, and reviewing the quality and validity of the data. This paper aims to support this debate by assessing the process and outcomes of innovation using fuzzy theory combined with a multicriteria technique to address the uncertainty attached to the underlying data used in constructing the composite indicator. Mainly, we deal with the problems related to the uniformity of the period covered by the indicator and the origin and reliability of the source of information by incorporating degrees of truth, indeterminacy, and falsity into the assessment process by applying neutrosophic numbers. To test the effectiveness of our approach, an empirical analysis is carried out based on the European Innovation Scoreboard and the assessment of the elementary criteria over the period 2020–2023.
Foreign direct investment, financial development, and technological innovation: a new perspective on spatial spillovers
This study used data from cities in the Yangtze River Delta (YRD) in China between 2012 and 2022 to analyze how foreign direct investment (FDI) and financial development impact technological innovation and how these effects spread to nearby areas. We found that (1) FDI significantly boosted technological innovation, and financial development effectively strengthened this effect. (2) The YRD urban agglomeration exhibited clear spatial spillovers in technological innovation, in that geographically adjacent regions showed technological siphoning effects, whereas regions with similar economic development levels demonstrated positive spillovers. (3) The synergistic effects of FDI and financial development varied by region, with positive spillovers in economically linked regions but insignificant effects in geographically adjacent regions. The findings also suggested that late-developing regions exhibited stronger absorptive capacity for FDI technology spillovers. The YRD and Pearl River Delta regions exhibited significantly superior synergistic effects compared to the Beijing-Tianjin-Hebei and Chengdu-Chongqing regions. This study enriches the understanding of the relationship among FDI, financial development, and technological innovation along with their spatial heterogeneity. It also provides valuable innovative insights for formulating regionally differentiated innovation policies, thereby offering practical guidance for fostering coordinated technological innovation across regions.
Barriers to digital transformation of high and medium high tech global manufacturing enterprises in Poland
The aim of the study is to identify the key barriers to digital transformation and assess the structure of interrelations between these barriers and the selected characteristics of enterprises, their approach to digital transformation, as well as the technological advancement of products in large and very large foreign manufacturing enterprises operating in the high and medium high technology sectors in Poland. The empirical research is based on information from 95 survey respondents. Multidimensional correspondence analysis was applied in the research to simultaneously assess the structure of interrelations between the categories of multiple nominal variables. The conducted research shows that more than 50% of the surveyed enterprises indicated excessive costs of digitalization as the main barrier to its implementation, followed by uncertain market conditions and lack of own financial resources. The most significant difficulties related to the implementation of digitalization were primarily experienced by the enterprises operating in Poland for up to 10 years, free to relocate, not committed to develop innovative products, and presenting negative approach to digital transformation. The research findings provide crucial information useful for businesses, politicians, researchers and technology providers in creating more effective strategies and policies to support the Industry 4.0 development. It can contribute to increased business competitiveness and innovation, thus having a positive impact on the economy in general. The article constitutes an original study based on the authors’ own research. First published online 28 January 2026
high and medium high technology sector enterprises
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.
Assessing the impact of economic variables on Romania's real estate market evolution: risk, uncertainty, and investment dynamics
This study examines Romania’s real estate market (2003–2023), analyzing economic variables’ impact on housing demand and investment trends through PLS-SEM and regression analysis. It addresses housing affordability challenges, particularly for younger generations, highlighting rising prices, increasing costs, and limited mortgage access as key barriers to homeownership. Furthermore, it explores the socio-economic implications of affordability issues, emphasizing their links to inequality and financial vulnerability. This study examines the shift from consumption to investment in the market, emphasizing the rising demand for real estate. It explores the impact of the sharing economy, particularly short-term rental platforms like Airbnb, on housing prices and affordability. Analyzing economic variables within a supply-demand framework, it distinguishes between new and existing housing stock while incorporating a LCC perspective. The research identifies high-growth market segments, providing insights for policy formulation and investment optimization. It contributes to the debate on government interventions in housing, evaluating whether support should target supply or demand for affordability. Using an ECM, the study examines investment impacts, particularly capital gain speculations, on housing demand, assessing interest rate fluctuations and mortgage dynamics. By integrating historical and current housing prices, it improves market analysis and forecasting, clarifying economic variables’ influence on investment behaviour and stability. First published online 28 January 2026
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 Please view the correction statement: Corrigendum: Efficiency and regional divergence in China’s poverty reduction (SDG 1) and decent work and economic growth (SDG 8)
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
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.
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
Striving for carbon neutrality in EU region: examining the role of environmental policy stringency in geopolitical risk and energy transition
Global economic policymakers are facing increasing demands from diverse environmental constituents to prioritize sustainable development through the implementation of strict environmental policies, energy transition strategies, and the reduction of fossil fuel consumption by fostering technological advancement. This study aims to assess the moderating role of environmental Policy Stringency (EPS), among Geopolitical Risks (GPR), Energy Transition (ET), Technological Innovation (INV), and environmental degradation (CO2 emission). This study relies on empirical datasets spanning the years 1990 to 2022 in 13 EU countries and employed an extensive range of econometric techniques., Dynamic Ordinary Least Square (DOLS), Fully modified Ordinary Least Square (FMOLS), Canonical Cointegration Regression (CCR), and Method of Moment Quantile Regression (MMQR) to examine the data. The empirical findings demonstrate that interaction of GPR*EPS, INV*EPS, and ET*EPS plays a crucial role in promoting environmental sustainability and lowering CO2 emissions. Whereas, environmental degradation is attributed to higher geopolitical instability and increased economic activities. Further, Quantile Regression (QR) and Feasible Generalized least square (FGLS) methods are employed to check the robustness empirical findings of the primary techniques. Based on our comprehensive empirical research findings, we can put forth constructive policy recommendations aimed at addressing environmental concerns and achievement of SDGs 7 & 13 in EU region.
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