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.
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.
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
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.
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.
Enhancing strategic flexibility for sustainable agro-industrial enterprises in transition economies: a fuzzy multicriteria approach
The article demonstrates that managing an enterprise’s strategic flexibility effectively is key to its competitiveness and market sustainability. The authors have developed a comprehensive model of strategic flexibility management of an agro-industrial enterprise operating in the Ukrainian agricultural market. This model integrates modern strategic analysis tools with fuzzy set theory, multicriteria evaluation, and fuzzy matrix analysis. Specifically, the Fuzzy PIPRECIA (PIvot Pairwise RElative Criteria Importance Assessment) method is used to prioritize the assessment directions of internal (ISF) and external (ESF) strategic flexibility. The Fuzzy Delphi method is used to harmonize expert opinions. In contrast, the Fuzzy SAW (Simple Additive Weighting) method, incorporating a 7-level term set, triangular fuzzy numbers, and triangular membership functions, calculates the fuzzy values of ISF and ESF levels. Based on the constructed ”ISF – ESF” fuzzy matrix, generalized recommendations for improving and managing the enterprise’s strategic flexibility are proposed. Considering the specifics of the studied agro-industrial enterprise’s activities and expert assessments for each component of its internal and external flexibility, a list of refined proposals, initiatives, and measures to enhance its strategic flexibility has been formulated. First published online 4 March 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.
Does corporate social responsibility of pharmaceutical manufacturing enterprises decrease debt financing costs? Economic implications through a moderated mediation model
In today’s complex economy, debt financing costs play a crucial role in shaping corporate competitiveness and are significantly shaped by stakeholder interests. This study focuses on the pharmaceutical manufacturing industry, exploring how Corporate Social Responsibility (CSR) affects the debt financing costs, with CSR further divided into strategic CSR and altruistic CSR. Drawing on the data of 286 pharmaceutical enterprises publicly traded on China’s A-share market during the 2010–2021 period, we construct a moderated-mediation framework to examine the complex mechanisms by which CSR affects debt financing costs. The findings show that stronger CSR efforts are linked to decreased debt financing costs. Financial performance acts as a mediator in this relationship, while media attention serves as a moderator. Specifically, strategic CSR initiatives, enterprises that are privately-owned, companies positioned in the eastern areas of China, and strong medical regulation witness a more significant reduction in financing costs. Furthermore, we find that compared to other industries, the fulfilment of social responsibility by pharmaceutical manufacturing enterprises plays a more crucial role in the sustainable development of the enterprise. This study examines the mechanisms through which pharmaceutical manufacturing firms reduce debt financing costs by fulfilling Corporate Social Responsibility (CSR), contributing to understanding of CSR’s economic value creation China’s emerging economy context. By incorporating firm-level and regional economic variations, the research addresses a gap in the existing literature and provides insights for pharmaceutical companies to optimize their financing strategies and attain sustainable economic development in emerging economies. First published online 16 March 2026
Does intergenerational economic support reduce the perception of pension risk among ecological migrants? – evidence from China
Understanding the influence of intergenerational economic support on ecological migrants’ perceived pension risks is essential. It provides a basis for designing targeted pension security systems and promoting sustainable livelihoods. Based on survey data from 1,915 ecological migrants in the upper reaches of the Yangtze River, this study employs empirical methods to examine the mechanisms and impacts of intergenerational economic support on their perceived pension risks. The main findings are as follows: (1) Intergenerational economic support significantly reduces ecological migrants’ perceived pension risks. This conclusion remains robust after a series of sensitivity and endogeneity tests, highlighting the crucial role of economic support from children in alleviating elderly migrants’ concerns about future pension security. (2) Individual, family, and community-level characteristics all exert significant effects on perceived pension risks. (3) Mechanism analysis reveals that intergenerational economic support alleviates perceived pension risks primarily through enhanced life satisfaction. Based on these findings, this study provides policy recommendations aimed at mitigating pension risks among ecological migrants in China. First published online 9 March 2026
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
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.
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.
The impact of digital literacy on subjective well-being: evidence from China
With the advancement of digital technology, digital literacy has gained prominence as a key determinant shaping individuals’ subjective well-being; however, it has remained underexplored in academic literature. This research utilizes the POLS method to investigate the impact of digital literacy on individuals’ subjective well-being, using data from the 2017 China General Social Survey (CGSS). To address potential endogeneity, we applied the instrumental variable approach, complemented by the Oprobit model and CMP estimation methods for robustness checks. The results demonstrate that digital literacy boosts both subjective happiness and life satisfaction, particularly among disadvantaged populations, such as women and low-income groups. Furthermore, digital literacy plays a significant role in reducing the well-being disparity between residents of underdeveloped and developed regions, as well as between urban and rural areas. The analysis also shows that digital literacy elevates residents’ subjective well-being mainly by alleviating employment vulnerability, enhancing human and social capital accumulation. By revealing the role of digital literacy in individuals’ subjective well-being, this study strengthens the formation mechanism of individual well-being perceptions in the context of technological advancement. This contributes to narrowing the digital gap and offers empirical support for public policies aimed at enhancing residents’ subjective well-being in the digital era. First published online 5 March 2026
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
Economic and mathematical evaluation of Ukraine’s renewable energy development with consideration of military risks
This article explores the renewable energy development in Ukraine, taking into account military risks through an economic-mathematical assessment of its investment attractiveness. To evaluate the investment priorities of renewable energy in Ukraine, two strategies have been considered – traditional and the one taking into account ESG factors. Using the Fuzzy TOPSIS approach, the main priorities of renewable energy in Ukraine have been determined: solar power plants for the traditional strategy, and for the ESG strategy – biomass power plants. For further evaluation of the investment attractiveness of the identified priorities, a multifactor model for assessing investment attractiveness using the method of integral assessment was constructed. The model is based on four primary indicators: development prospects, return on equity of enterprises, level of inflation stability in industry prices, and industry-specific risks. First published online 3 March 2026
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