International Journal of Green Economics (11 papers in press)

Regular Issues

• Two decades of International Journal of Green Economics: a bibliometric analysis  
  by Anisha Arora, Prashant Kumar Siddhey 
  Abstract: The International Journal of Green Economics (IJGE) promotes economic transformation and advances green economics through peer-reviewed scholarly contributions. Offering essential ideas, strategies, tools, and measures to alter present economic models for the benefit of people and the environment, IJGE has been an industry leader since its founding in 2006. IJGE works to promote social justice with a particular emphasis on resource management and the effects of global trends on society. Scholars apply bibliometric techniques, with the aid of programs such as VOSviewer and R Studio, to analyse the impact of IJGE, pinpoint major themes, and emphasise leading writers. This research highlights the interrelated networks of academics, institutions, and research themes, offering insights into IJGEs ongoing contributions to the field of green economics.
  Keywords: green economics; sustainability; sustainable development; bibliometrics; International Journal of Green Economics; IJGE.
  DOI: 10.1504/IJGE.2026.10077846
   
  
• Unlocking financial inclusion: understanding mobile money adoption among formerly unbanked individuals  
  by Saad Ur Rehman, Shahid Hussain, A.B.M. Asadullah, Hassan Shafique, Muhammad Adnan Raza 
  Abstract: Many formerly unbanked people now have mobile phone access to banking services thanks to advancements in financial technology. Although advancements in Fintech have been heralded as game-changers for expanding access to financial services, their widespread adoption and use has lagged behind. This research contends that more financial inclusion can be achieved by elucidating the conditions under which Fintech ideas are actually adopted. This investigation applies the unified theory of acceptance and use of technology 2 (UTAUT2) and the prospect theory to the emerging financial technology of mobile money. This research utilises the method of partial least squares structural equation modelling to analyse data from a survey taken by 670 participants. The results indicate that performance and effort expectations are significantly related to the likelihood of using mobile money services.
  Keywords: FinTech; financial inclusion; mobile money; survey analysis; unbanked populations; technology acceptance; financial services; advancements in technology.
  DOI: 10.1504/IJGE.2026.10078269
   
  
• Measuring the income effect of energy efficiency in reducing the mortgage probability of default  
  by Bálint Várgedő, Balázs Sárvári, Csaba Kandrács 
  Abstract: We analysed the impact of energy-efficient households increased disposable income on mortgage probability of defaults (PD) in Hungary. We estimated the PD reduction for different residential building types and income classes and two energy efficiency criteria. Our estimation uses a novel methodology consisting of a calculation of heating cost savings and a logistic regression model of mortgage PD. According to our results the PD reduction due to the disposable income effect for houses achieving CC energy label are twice as high, as for houses achieving only 30% energy reduction from the typical energy usage. Additionally, we found that higher-income classes obtain lower PD reduction while the PD impact is the highest for households living in single-family homes.
  Keywords: Central Bank; energy efficiency; housing; income effect; mortgage probability default.
  DOI: 10.1504/IJGE.2026.10078568
   
  
• The demand dilemma: capitalisms structural obstacle to sustainability  
  by Alireza Zandieh 
  Abstract: This paper examines how the structure of economic demand in capitalist economies constrains environmental sustainability. Rather than focusing solely on production processes or technological efficiency, it advances a demand-centred critique that treats consumption as a structural mechanism sustaining growth-dependent economic systems. Drawing on green economics and post-growth perspectives, the paper argues that expanding demand beyond basic human needs is a systemic requirement of capitalism that reinforces resource-intensive production and consumption incompatible with ecological limits. Using a conceptual interdisciplinary approach, the analysis synthesises insights from environmental economics, political ecology, and green economics to examine how demand is socially produced, institutionally reinforced, and politically protected. Building on contributions from Scott Cato and Kennet et al. as well as demand-side frameworks such as avoidshiftimprove, the paper identifies demand expansion as an underexamined barrier to sustainability. It concludes that achieving sustainability requires reorienting economic systems toward sufficiency, equity, and collective well-being within planetary boundaries.
  Keywords: capitalism; sustainability; environment; environmental impact of consumption; green economics.
  DOI: 10.1504/IJGE.2026.10078621
   
  
• Navigating the uncertainties: perceived risks and their impact on buying refurbished products  
  by Sridevi Periaiya, Sathish Thamburasa, Subhashree Prabhakaran 
  Abstract: This study addresses a gap in the existing literature by examining the influence of perceived risks on cognitive conflict and purchase intention in the context of refurbished products. Circular economy and closed-loop supply chain (CLSC), both of which offer sustainable solutions to issues like raw material scarcity and environmental degradation, this research aims to demystify consumer perceptions of risk associated with refurbished products. By using the Theory of perceived risk, the study uncovers how risk perceptions affect consumers willingness to purchase refurbished products. The findings reveal that many risk factors do not significantly influence purchase intention, except illegitimate risk and isolation risk. However, a majority of these risk factors do contribute significantly to cognitive conflict. This study also finds a significant relationship between cognitive conflict and purchase intention. These insights offer valuable implications for refurbished product manufacturers and sellers. It helps in improving the sustainable purchasing behaviour of refurbished products.
  Keywords: closed-loop supply chain; circular economy; purchase intention; perceived risk; cognitive conflict; refurbished products.
  DOI: 10.1504/IJGE.2026.10078939
   
  
• Green governance, institutional dynamics, disclosure, and stock performance: evidence from Indonesian non-financial firms (2016-2024)  
  by Tasya Aspiranti, Qaisar Ali, Ima Amaliah, Nunung Nurhayati 
  Abstract: This study investigates whether green governance benefits capital markets in emerging economies. Drawing on upper echelons and signalling theories, chief sustainability officers (CSOs) are conceptualised as guardians of green governance and sustainability reporting as the mediator of financial benefits. Panel data between 2016 and 2024 and a generalised method of moments (GMM) regression analysis are used to investigate the impact of CSOs on sustainability reporting and the stock performance of listed non-financial Indonesian firms. The empirical results show that CSOs significantly improve sustainability disclosure but coincide with lower stock performance. An insignificant mediating influence of sustainability reporting highlights a critical transparency and market valuation gap, suggesting that green governance often produces symbolic rather than economic outcomes in institutions of developing markets. These findings enhance sustainability governance theory by challenging the presumed financial benefits of governance-driven disclosure and offering practical guidance for firms and policymakers in comparable emerging economies.
  Keywords: green governance; chief sustainability officers; CSOs; sustainability reporting; stock performance; emerging markets.
  DOI: 10.1504/IJGE.2026.10078940
   
  
• Green finance, foreign and domestic capital with economic development: a dynamic panel data analysis  
  by Somnath Das, Tarak Nath Sahu 
  Abstract: While the existing theoretical and empirical literature is unable to cover the relationship between green finance, domestic and foreign investment with the economic development of Asian nations during the period 1998 to 2022 (25 years), the present study is devoted to disclosing this relationship by using static and dynamic panel data analysis on annual secondary relevant data of 45 Asian nations. The economic development is measured through GDP, green finance is reflected by renewable energy consumption, domestic capital is represented by using gross capital formation (GCF), and FDI is considered as foreign capital. The result reveals the robust form of relationship among variables which helps the policymakers to emphasise these forms of investments for the economic development of nations.
  Keywords: green finance; FDI; economic development; Asian country; panel data.
  DOI: 10.1504/IJGE.2026.10079351
   
  
• Impact of green supply chain management practices on environmental and operational performance in the Indian manufacturing sector  
  by Tohid Kachwala 
  Abstract: This survey-based empirical study is establishing a framework to promote knowledge of GSCM techniques, highlighting the cost and efficiency advantages for companies, and examining the impact of GSCM on the environmental performance and operational performance in the Indian manufacturing sector. In this article, senior managers in Indian manufacturing factories participated in interviews and comprehensive primary data collection to study the two constructs used to evaluate operating performance. Gujarat, Goa, and Maharashtra Manufacturing facilities made up the sample data from June 2020 to July 2022. Using SPSS AMOS, we examined the structural models path coefficients throughout the entire model. Managers can thoroughly grasp GSCM techniques, their application, and the expected results from this study. Future research, however, should expand the sample size and include adequate samples from diverse sectors to encompass multiple sectors within a manufacturing organisation.
  Keywords: structural equation modelling; environmental performance; operational performance; green supply chain management; GSCM; manufacturing.
  DOI: 10.1504/IJGE.2026.10079382
   
  
• The use of digital finance and its influence on economic sustainability: evidence from the tribals’ perspective in India  
  by K. Katini, Kaikho Hriizhiinio, S. Amalanathan 
  Abstract: This research aims to empirically examine the relationships between the use of digital finance and economic sustainability. The Mao-Naga tribe in Northeast India is being surveyed using a cross-sectional survey and structured questionnaires. Primary data is collected using a convenient sampling methodology. This study measures the relationship between the antecedent constructs of using digital finance and economic sustainability using partial least squares structural equation modelling. This empirical analysis was supported by integrating the UTAUT2 and D&M models for testing hypotheses and other statistical powers. The findings show that the usage of digital finance can raise living standards, promote the transition to clean energy consumption, lessen social issues, enhance energy efficiency and create cost awareness of natural resources. The development of innovative financial technology and its application can benefit individual tribals and the markets ability to sustain long-term economic viability.
  Keywords: UTAUT2; D&M model; perceived security; economic sustainability; digital finance usage; Mao-Naga tribal; India.
  DOI: 10.1504/IJGE.2026.10079468
   
  
• Efficiency measures of European railways considering sustainable mobility objectives: a data envelopment analysis approach  
  by Arsen Benga, Manuel Arana-Jiménez, María Jesús Delgado Rodríguez, Sonia De Lucas Santos 
  Abstract: This study evaluates the sustainability performance of 14 major European railway operators over 20112019 using a non-oriented slack-based inefficiency (SBI) data envelopment analysis model that incorporates weak disposability for undesirable outputs. To enhance discrimination among efficient units, we extend the framework with a super-SBI specification. The model jointly considers multiple dimensions of sustainable mobility economic performance, energy efficiency, climate protection, and exhaust emissions using a consistent sectoral dataset. Results show moderate but improving sustainability gaps: average inefficiency declines from roughly 2728% toward the end of the period. Decomposition indicates that climate protection and exhaust emissions are the principal drivers of overall inefficiency, while energy efficiency generally requires the least adjustment. The super-SBI layer yields a unique ranking of efficient operators, thereby identifying best-practice frontiers for benchmarking. These findings highlight priority areas for targeted environmental improvements and offer a transparent basis for performance monitoring as European railways pursue sectoral climate and pollution-reduction commitments.
  Keywords: data envelopment analysis; DEA; slack-based inefficiency; SBI; weak disposability; sustainable mobility; rail transport; benchmarking.
  DOI: 10.1504/IJGE.2026.10080164
   
  
• Exploring the dynamic interplay between green bond prices and financial markets: machine learning evidence from 2018 to 2024  
  by Rim Oueghlissi, Ahmed Derbali 
  Abstract: We investigate the dynamic interplay between green bond prices and major financial markets by employing an explainable machine learning framework to forecast green bond performance. Using daily data from 2018 to 2024? We develop a robust predictive model based on ensemble learning algorithms, incorporating a comprehensive set of macro-financial indicators, including interest rates, exchange rates, equity indices, commodity prices, and macroeconomic conditions such as the Citigroup Economic Surprise Index, and the Economic Policy Uncertainty Index, we develop a robust predictive model based on ensemble learning algorithms. Our findings reveal that US and German sovereign yields dominate green bond price dynamics, together accounting for more than 70% of the models explanatory power, while exchange rate fluctuations, particularly USD/JPY, also play a significant role. By applying Shapley additive explanations (SHAP) values, we enhance model interpretability and identify key drivers with precision. A robustness analysis centred on the Russo-Ukrainian conflict confirms the stability of predictive performance under geopolitical stress and reveals a notable shift in the importance of explanatory variables during crisis periods.
  Keywords: green bonds; financial markets; machine learning; sovereign yields; exchange rates; geopolitical risk.
  DOI: 10.1504/IJGE.2026.10080273