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.
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.
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
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.
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 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.
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.
Psychic distance and other determinants of the EU new member states’ outward foreign direct investment
Research on outward Foreign Direct Investment (OFDI) has so far been focused on developed countries. However, the significance of emerging and transition economies is increasing. The literature review shows the gap in research on determinants of the EU NMS (European Union New Member States) OFDI, in particular regarding Psychic Distance (PD). The paper motivates theoretically and uses a gravity model to investigate the drivers behind OFDI from NMS. We apply Hausman-Taylor (HT), Poisson Pseudo-Maximum Likelihood (PPML), and Gamma Pseudo-Maximum Likelihood (GPML) estimators. These are the characteristics of the destination country that exert more significant influence than the origin, which raises scepticism about OFDI being stimulated by policy measures in the case of the NMS. A tax-avoiding motive strongly drives their OFDI. We contribute to the literature by showing that PD affects OFDI from the NMS and is an alternative to distance in kilometres, which is traditionally used in gravity models. Socioeconomic and psychic distances are robust alternatives, while other single-dimensional ones (language, industrial, democratic, or religious) are not. Our findings confirm that NMS’s OFDI strongly depends on the Inward Foreign Direct Investment (IFDI) from the counterpart economies.
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
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
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
Copyright (c) 2025 The Author(s). Published by Vilnius Gediminas Technical University. http://creativecommons.org/licenses/by/4.0
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
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
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.
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.
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
Investigating effects of ICT infrastructure on economic growth: data flow perspective based on China’s evidence
This study employs a mediating effect model and the Generalized Method of Moments (GMM) approach to examine the direct effect of ICT on the economy and the mediating role of data flow in the ICT – economic growth nexus. The results indicate that ICT significantly enhances data flow intensity, which in turn promotes economic growth. Moreover, both the direct effect of ICT and the mediating role of data flow are more pronounced in developed regions compared to underdeveloped areas. Further analysis shows that with the implementation of the policy, the mediating effect of data flow shifted from being insignificant (2006–2010) to significant (2011–2019). This study contributes to the understanding of the digital divide, highlighting potential drivers such as disparities in ICT infrastructure and data flow inequality. The government should develop tailored ICT development policies based on the region’s economic level to fully harness the benefits of digitalization. First published online 18 May 2026
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.
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.
Digital exclusion and the implementation of selected sustainable development goals in EU countries
Dynamic development of digital technologies and the Internet in the 1990s. and the beginning of the 21st century significantly influenced the directions of social, economic and cultural development of societies in all countries of the world. A negative consequence of this process is the phenomenon of digital exclusion. The aim of this work is to measure this phenomenon in EU countries in 2023 and assess it in the context of the sustainable development goals. For this purpose, synthetic taxonomic measures were constructed using the TOPSIS method. The source of data was the Eurostat database, from which selected information from the ICT (Information and Communication Technologies) study and indicators describing the level of sustainable development. The research results show that EU countries were clearly differentiated in terms of the level of digital exclusion. This also had an impact on their implementation of selected sustainable development goals. First published online 4 June 2026
Roy Bahl's implementation rules for fiscal decentralization: theoretical insights and empirical evidence from OECD countries
The paper refers to the twelve principles of fiscal decentralization, proposed by Roy Bahl (Bahl’s Rules for Fiscal Decentralization – BRfd), with special emphasis on the first Bahl’s rule (regarding the comprehensiveness of the fiscal decentralization, CSfd). The purpose of the research was to estimate the level of CSfd in OECD countries. Thus, the objective was to construct a synthetic measure of the first Bahl’s rule (CSfd) which constitutes the value added of this research. The goal was also to rank countries as the main idea was to advance empirical assessment in the field of fiscal federalism and to provide practical guidance for shaping public finance policy including policies on the collection of public revenues and the allocation of public expenditure. This directly corresponds to the research problem of the very limited number of tools available for measuring fiscal decentralization. Based on Hellwig’s method of linear ordering two rankings were developed using the Euclidean metric and the Mahalanobis metric. The results indicate that the most comprehensive fiscal decentralisation systems in 2022 were found in the Slovak Republic, Switzerland and Canada (ranking based on the Mahalanobis metric). When the Euclidean metric is used, Switzerland emerges as the leader, followed by Spain and Austria. First published online 4 June 2026
Bahl’s rules for fiscal decentralization
Empowering migrant worker households: digital finance for inclusive growth
This study establishes a Digital Buffer Enhancement framework based on the buffer-stock model to investigate how digital finance affects consumption levels of migrant worker households, with implications for inclusive growth and sustainable development. Utilizing microdata from the 2019 China Household Finance Survey (CHFS) and applying Endogenous Switching Regression (ESR), Instrumental Variable (IV) approach, and quantile regression analysis, the research reveals three key findings. First, digital finance adopters exhibit 13.74% higher consumption levels, while non-adopters could increase consumption by 5.62% via adoption. Intriguingly, the Digital Buffer Enhancement framework identifies three complementary mechanisms: transaction convenience leapfrogging, liquidity constraint mitigation, and income uncertainty reduction, which together reduce precautionary savings thresholds. Second, enhanced marginal effects emerge among elderly households, eastern regions, and low-consumption quantile groups. Third, analysis of consumption structure heterogeneity indicates that developmental consumption elasticity substantially exceeds hedonic and subsistence consumption, with credit functions demonstrating the strongest impact among digital finance types, followed by payment and wealth management services. These findings advance theoretical understanding of technology-driven consumption transformation and provide practical guidance for developing inclusive digital finance policies in emerging economies. First published online 5 June 2026
Vertical specialization and the middle-income trap: an explanation based on global value chains
This paper aims to provide theoretical and empirical evidence to explain the middle-income trap from the perspective of Global value chains (GVCs). GVCs improve vertical specialization in two possible ways: (i) “economies of specialization”, induced by market expansion among developed countries; and (ii) the inequity of factor prices between emerging markets and developed ones (comparative advantages). This paper clarifies the differences between the two channels with a model considering two kinds of labor – technological labor and regular labor – and shows how vertical specialization plays an important role in the socalled “middle-income trap”. We argue that GVCs accelerate global market integration, which makes the labor wage in emerging markets to approach the middle-income level. Through vertical specialization, emerging markets lose their advantage of low labor costs, while the disadvantage in terms of technological production increases. We also explore the differences between vertical specialization patterns in empirical part to check whether the data can verify what we find in the theoretical part. We find that middle-income countries are at a more disadvantaged position than other countries in vertical specialization (they are locked in an unfavorable situation of international division of labor), which provides evidence for what are derived from the theoretical model. First published online 3 April 2026
The leading effect of developing countries’ capital cities in innovation: evidence from Chinese provincial capitals
Motivated by the limited research on the role of capital cities in driving innovation within developing countries, this study used China as a sample to examine the relationship between Provincial Capitals’ Priority Development (PCPD) and Provincial Innovation Capacity (PIC). The findings revealed that PCPD significantly enhances PIC. Quantile regression further demonstrated the varying impact of PCPD at different stages of PIC. A lag effect was also identified, as evidenced by regressing lagged PCPD variables on PIC. Additionally, by incorporating interaction terms in the regression, we verified the positive moderating effects of industrial isomorphism, fiscal support for innovation, and higher education resources on the PCPD–PIC link. Finally, heterogeneity analysis indicated that PCPD initially benefits innovation primarily in provincial capitals; however, over time, its positive impact gradually extends to non-provincial capital cities. These findings offer insights for policymakers in developing countries seeking to foster innovation through the strategic prioritization of capital cities. First published online 14 May 2026
ESG and green transition of enterprises: a perspective from emission reduction and development
Using data from 2009 to 2020 of A-share listed firms in China, this study investigates how ESG (Environmental, social, and governance) impacts corporate green transition (GT) from two perspectives: carbon emission intensity and total factor productivity. Results show that ESG significantly enhances corporate GT. Channel analysis shows that ESG improves the financing environment, optimizes environmental governance strategies, and improves the information environment, thereby promoting corporate GT. After the implementation of the new Environmental Protection Law (EPL) and the Environmental Protection Tax Law (EPTL), the GT with ESG advantages is significantly enhanced compared to those without ESG advantages. Heterogeneity analysis shows that the positive effects of ESG are more pronounced in firms with low availability of green credit and high levels of greenwashing. In addition, social responsibility of ESG has the greatest effect in enhancing GT, and ESG uncertainty can weaken the promotion effect of ESG on GT. The industry spillover effect test found that ESG has an industry emission reduction governance effect, and there is a peer effect of mutual influence on carbon emissions decisions among enterprises. Overall, our results reveal that ESG can promote GT to achieve sustainable development. First published online 26 March 2026
Energy carbon performance curse: an analysis based on the economic restructuring stickiness
Although natural resource’s negative impacts on economic growth have been extensively explored, its curse on energy carbon performance may remain ignored. Combining theoretical analysis, this paper further examines the curse of mineral resource dependence on energy carbon performance and the specific mechanism. In 2019, if optimal production is achieved in all sample cities, China would reduce electricity consumption by 42.941% and carbon emissions by 43.958%. Compared to non-resource-based cities, the potential ratios of energy savings and carbon reduction in resource-based cities are 5.403% and 6.059% higher, respectively. When the mineral resource dependence is less than 0.042%, it contributes to energy carbon performance, but when the mineral resource dependence exceeds 0.042%, higher mineral resource dependence implies more serious energy carbon performance curse, which explains the coexistence of resource blessing and resource curse. Economic restructuring stickiness caused by mineral resource dependence serves as a key mechanism for energy carbon performance curse, and energy, factor and industry restructuring stickiness are specific channels for this mechanism. First published online 4 June 2026
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.
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