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Urbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.

We employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.

The results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.

This paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

This paper examines the impact of financial inclusion on poverty through access to mobile money in developing economies.

The authors employ the principal component analysis to construct an index of financial inclusion using demand and supply indicators, including mobile accounts. The authors use the two-step system GMM estimator for the analysis because of its efficiency and robustness in addressing heteroscedasticity and autocorrelation.

The main finding is that financial inclusion generally increased and significantly reduces poverty in the sample period. Furthermore, income inequality worsens poverty.

This study has few limitations. First, the empirical analysis of the study is restricted to macroeconomic factors only because of limited Household Finance Survey data set and time availability. Second, the study is limited to developing countries and the results cannot be generalized.

Financial inclusion is a significant policy tool for poverty reduction. There is the need to enhance strategies that further improve financial inclusion by expanding and improving the use of mobile money accounts.

The paper sheds light on how developing countries can harness financial inclusion to reduce poverty.

The paper differs from the previous studies in two ways. Firstly, mobile money account is included in the computation of financial inclusion index over the sample period. It also determines the impact of financial inclusion on poverty for short-run and long-run periods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2021-0690

This study aims to analyze factors that influence the utilization of remittances by Indonesia Migrant Workers (TKI) and to analyze the role of stakeholders in the implementation of financial inclusion. This research used a mixed method, regression analysis, and Matrix of Alliances and Conflicts: Tactics, Objectives, and Recommendations (MACTOR). This study found that the factors that influence savings are training variables, education, and a dummy variable for widow status. The results when remittance as dependent show that the regional origin, dummy variable for receiving remittances, for training, and for determining the use of remittances by TKI themselves had an effect. The implementation of financial inclusion is needed in the economic development of TKI, and the main actors are migrant workers, assistants, economists, and Bapermas. Actors who have the potential for ambivalence are workers who do not participate in mentoring and do not join BUMDes.

This research aims to develop sustainable development scores at districts level based on weights of thirteen sub-indicators using a spatial information system.

The empirical study was conducted at seven districts in the state of Terengganu Malaysia. The evaluation was implemented using a spatial information system combined with weights of sub-indicators that were computed from the analytic hierarchy process (AHP) method.

In this study the sub-indicators layers overlaid into one raster layer to produce a sustainability development score from 1 to 3 for every district. The one raster layer shows that Marang district received the highest sustainable development score of 2.284. On the other hand, Kemaman district received the poorest sustainable development score of 1.686.

In this study the weights that obtained from the AHP method are verified and validated using a sensitivity analysis. The scores at districts level perhaps may not be accurate due to difficulties in differentiating the variability of indicators and sub-indicators. These are among the unsettled issues that could be explored as future research direction.

The results would have greatly benefited the policy makers and stakeholders, particularly in planning for future development without compromising the significance of environment, social and economic indicators.

Sustainable development is one of the key elements that needs to be considered seriously in assessing development of a country. The assessment may include proposing indices for environment, social, economic indicators and related sub-indicators of sustainable development. Instead of considering specific indices for indicators, this approach departs more formally from the concept of unweighted indices at country level.

This study examines specific budget execution items (as proxies of vulnerability and sustainability) along with political factors to identify earnings management (EM) practices in Greek municipalities.

The study employs a sample of 1,831 financial and budget execution statements for the period 2011–2019. EM is proxied by unsigned discretionary accruals that are assessed through the performance-matched modified-Jones model and the modified-Jones model.

The findings provide evidence that the municipality’s dependence on subsidies (or its self-sufficiency) affects EM, especially during the pre-election year. Municipalities that maintain their financial autonomy engage less in EM in pre-election years. Lastly, it is proven that electoral cycles, weak opposition and other variables exert an effect on the size of EM. Sensitivity analysis confirms the results.

This paper contributes to the literature on EM by analyzing for the first time budget execution items (as proxies of vulnerability and sustainability) and their impact on the size of unsigned discretionary accruals.

The Organization for Economic Cooperation and Development (OECD) countries are facing unprecedented challenges related to climate change and population aging. The purpose of the analysis is to explore the relationship between population aging and environmental degradation, accounting for human capital, using a sample of 19 OECD countries over the period 1980–2019.

On the empirical methodology, the analysis uses panel estimators with heterogenous coefficients and an error structure that takes into consideration cross-country heterogeneity and cross-sectional dependence for a panel of 19 OECD countries over the period 1980–2019. To examine the relationship between population aging and environmental degradation, the authors employ two alternative measures of environmental degradation that is energy consumption and CO2 emissions in metric tons per capita. Concerning the regressors, the authors account for two alternative aging indicators, namely the elderly population and the old-age dependency ratios to confirm robustness.

The analysis provides evidence that population aging and human capital development (IHC) lead to lower energy consumption in the OECD sample. Overall, the growing number of elderly people in the OECD seems to act as a mitigating factor for energy consumption. The authors view these results as conveying the message that the evolution of population aging along with channeling government expenditures towards human capital enhancement are important drivers of curbing energy consumption and ensuring environmental sustainability. The authors' research is of great significance for environmental policymakers by illuminating the favorable energy consumption patterns that population aging brings to advanced economies.

The main limitation of this study concerns data availability. Future research, and subject to greater data availability in the future, could dig deeper into understanding the dynamics of this complex nexus by incorporating additional control variables. Similarly, the authors focus on aggregate renewable energy consumption, and the authors do not explicitly model the sources of renewable energy (wind, hydropower, solar power, solid biofuels and other). Additional analysis of the breakdown of renewable energy sources would be insightful – subject to data availability – especially for meeting the recently agreed new target of 42.5% for European Union (EU) countries by 2030. A deep transformation of the European energy system is needed for the EU to meet the target. Finally, extending the model to include a range of non-OECD countries that are also experiencing demographic transformations is a promising avenue for future research.

To the best of the authors' knowledge, this study is the first to examine the effects of population aging and human capital on environmental degradation using a broad set of OECD countries and advanced spectrum estimation methods. Given cross-sectional dependencies and cross-country heterogeneity, the authors' empirical results underline the importance of cross-OECD policy spillovers and knowledge diffusions across the OECD countries. The new “energy culture” calls for concerted policy action even in an aging era.

The aim of this study is to analyze which socioeconomic factors (economic, demographic, and political) most commonly affect the social expenditure of the European Union (EU) and Organization for Economic Co-operation and Development (OECD) countries.

A panel data fixed-effects model is employed for 34 OECD and 23 EU countries between 2000 and 2020.

Results indicate that, in all country groups, economic factors have the most significant influence on social expenditures, with income being the primary determinant, particularly in EU countries. The negative impacts of unemployment and inflation underscore the importance of counter-cyclical measures adopted by countries to maintain stability in their social expenditures. The most influential demographic factor is found as the old-age-dependency ratio. While the rule of law affects social expenditure positively, government effectiveness and female labor force participation affect it negatively. The positive effect of Konjunkturforschungsstelle (KOF) indexes shows the globalization effect, which can be attributable to the compensation hypothesis.

Governments enforce inclusive and sustainable policies to boost economic activities and GDP, thus combating inflation and unemployment and regulating the labor market and socioeconomic problems about aging populations and women’s economic participation to control social expenditures. The rule of law and institutional quality will also boost economic growth.

This study focuses on the effects of social expenditures in a broader view within the framework of the three main factors (economic, demographic, political) and attempts to determine the key factors that account for the differences in social expenditure between the OECD and EU countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0384

Population ageing will bring economic challenges in the future. The purpose of this paper is to examine whether increased educational level could mitigate the consequences of population ageing on economic sustainability, measured as the gap between labour income and consumption.

Using the National Transfer Accounts (NTA) methodology, the authors decompose labour income and consumption by age and educational level (low, medium and high) and compare obtained age profiles with those calculated conventionally. In addition, using the population projections by age and educational level, the authors project both profiles to 2060 for selected EU countries and assess future economic sustainability.

The results show that the highly educated have a significantly higher surplus for a longer period then those with lower and medium education. Therefore, the improved educational level of individuals will have a substantially positive impact on labour income in the future—on average by about 32% by 2060 for all EU countries included. However, as the better educated also consume more, higher production does not fully translate into improved economic sustainability, but the resulting net effect is still positive at about 19%.

The authors present for the first time an NTA by education for 15 EU countries and show the importance of including education in the analysis of the economic life cycle. The authors also show that increased educational level will mitigate the consequences of population ageing on economic sustainability in the future.