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Personal remittance and ready-made garments (RMG) export incomes have emerged as the largest source of foreign income for Bangladesh's economy. The study investigates their impact on income inequality and gross domestic product (GDP) as a control variable, using time-series yearly data from 1983 to 2018.

It employs the Autoregressive Distributed Lag (ARDL) estimation and the Toda-Yamamoto (T-Y) causality approach. The ARDL estimation outcomes confirm a long-run association among the above variables and validate the autoregressive characteristic of the model.

Personal remittances positively contribute to reducing the income gap among the people of the society and declining income inequality. In contrast, RMG export income and economic growth contribute to further income inequality. The T-Y causality analysis follows the ARDL estimation outcomes and authenticates their robustness. It reveals a feedback relationship between remittance inflow and the Gini coefficient, unidirectional causalities from RMG export income to income inequality and economic growth to income inequality.

The finding has important policy implications to limit the income gaps between low and high-income groups by channeling incremental income to the lower-income group people. The policymakers may facilitate further international migration to attract further remittances and may upgrade the minimum wage of the RMG workers.

The study is original. As far as the authors' knowledge goes, this is a maiden attempt to investigate the impact of personal remittances and RMG export income on income disparity in the case of Bangladesh.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

This paper will identify and further explore the ideals versus realities of learning poverty and the consequential effects on our moral obligations and responsibilities. The wealthy nations are now under further pressure to recognise and realise their moral obligations to enabling social justice in the context of access, and distribution, of vaccines for the poorer nations. Learning poverty has always been a feature of our global economic, and institutional order, and has become an increasingly important factor in achieving justice.

The study focusses on a human rights approach to learning poverty and the ideals versus the realities of what we are beginning to see in the times of a global pandemic. The major challenges to justice is inherent to the recognition that wealthy nations continue to have a pivotal role in the reduction of poverty. The identified major challenges in the context of learning poverty are: “nation states and the global pandemic”, “international interactions and learning poverty” and “global institutions and learning inequalities”. In particular, the authors explore the concept of ideals versus realities through three “challenges”, which continues to challenge any semblance of justice in the current global vaccine distribution. Nation states and borders, international interactions and global institutions remain barriers in overcoming what is becoming a reality of learning poverty.

This paper seeks to look beyond the economics of vaccine trade and seek a way to accept a moral claim of justice for all. The authors consider how wealthy nations are active participants in the emergence of learning poverty for many nations.

By exploring the ideals versus realities of learning poverty, and human rights, the authors highlight some of the challenges, and wealthy nations moral obligations, through the emergence of a new dimensional indicator of poverty, learning poverty.

This study examines the effect of digitalization on poverty and income inequality in developing countries. The study answers the question of whether digitalization is a way for developing countries to get out of poverty and income inequality.

The study uses data from 17 developing countries with data from 2005 to 2021. The study employs fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS), with an augmented mean group (AMG) for robustness. Digitalization, as the variable of interest, is proxied by the digitalization index (DI), constructed using principal component analysis (PCA). The dependent variables are poverty and income inequality, which are used in different models.

The evidence indicates that digitalization decreases poverty and income inequality in developing countries. These findings are justified when we use the AMG estimator, but the strength of the coefficients and significance levels are higher in the FMOLS and DOLS estimators. The results of the control variables also show that human development (LHDI), CO2 emissions and foreign direct investment (FDI) have decreasing effects on poverty and income inequality. Thus, digitalization is a good option for developing countries to get out of poverty and income inequality to achieve sustainable development goals (1&10).

This study provides rigorous empirical evidence on the effect of digitalization on poverty and income inequality in developing countries. Unlike the previous studies on developing countries, this study used a DI to proxy digitalization. In addition, the authors use FMOLS and DOLS estimators, with an AMG estimator for robustness, to provide long-run coefficients.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2023-0586

This study aims to examine the effects of vocational training programs for people with disabilities on their income.

It conducted a multinomial regression analysis of 10,469 survey responses from 31 provincial administrative areas in mainland China.

It finds the following antecedents all influence the trainees’ self-reported income, including their perception of the quality of the program, the training subject, the degree of consistency between their current job and this subject, their employment sector, their motivation and access to training resources and the geographical location of the program.

The findings are not representative of people with disabilities across mainland China because the respondents were not randomly sampled.

The findings suggest that to increase the income of people with disabilities, the training can be designed according to the needs of employers by teaching subjects relevant to the needs of the labor market, reaching out to motivated trainees and enhancing the quality of training. Training institutions, employers and governments are recommended to work together to integrate class-based learning with workplace-based learning and practices. More training resources can be devoted to the self-employed people with disabilities or those who operate in the informal sector and are in less-developed areas.

The improvement of employment opportunities and income of people with disabilities supports the safeguarding of their social economic rights and the building of an inclusive society.

Few studies have empirically explored and explained the effects of vocational training programs on people with disabilities’ income. This article fills this gap by assessing the performance of China's vocational training programs funded by the Federation of Disabled Persons at all levels.

This study aims to analyze the concept of Zakat as an instrument to increase the economy and poverty eradication in Indonesia.

This study used a qualitative method based on library research sourced from books, financial reports and another previous research.

The results show that the empowerment programs conducted by Zakat institutions in Indonesia are based on the scale of priorities and the potential of Mustahik. Zakat management considers the level of productivity and long-term impacts that improve Mustahik Economy. Thus, the empowerment programs lead to the reduction of Mustahik living below poverty line.

This study contributes in two ways: first, it analyzes a model to identify the Mustahik’s potential for the Zakat institution in Indonesia. Second, it encourages the awareness of Muzakki and Mustahik regarding the role of Zakat in the Indonesian economy. This is expected to prompt their level of participation in optimizing the potential of Zakat in Indonesia.

Given the scarce literature that provide qualitative and critical reviews of the implementation Zakat empowerment programs to alleviate poverty conducted by the Zakat institutions in Indonesia, this research can act as a bridge for future research in performing empirical studies regarding the impact of a Zakat empowerment program on society.

This study examines the non-linear impact of financial development on income inequality and analyses the mediators through which financial development affects income inequality.

The study uses a dynamic panel threshold method with an endogeneous threshold variable on a comprehensive sample of 85 countries over the period of 1996-2015.

The author finds that financial development activities increase income inequality in developed countries. However, financial development promotes income equality in developing countries. Further, the study finds that education and institutional quality are the channels through which financial development has non-linear impacts on income inequality.

The study explores relatively new method to examine the nonlinear impact of financial development and also considers new dataset for the main explanatory variable.

The COVID-19 pandemic has significantly impacted global tourism, with international travel bearing the burden of restrictions. Domestic tourism has also faced substantial challenges. This paper aims to analyse the impact of the COVID-19 pandemic on domestic tourism in Spain, focusing on travel from Madrid (the country’s capital) to other tourist destinations.

Mobile phone data has been used to study the evolution of tourist trips over the summers of 2019, 2020 and 2021. Regression models are used to explain the number of visitors at destinations.

The pandemic not only caused a drastic drop in tourist flows but also disrupted the overall pattern of the domestic flow system. Winning destinations were typically areas in proximity to Madrid and less densely populated destinations, while urban destinations were major losers. The preferences of domestic tourists varied notably by income group, but the decrease in trip volumes showed only marginal differences.

The paper demonstrates the potential of mobile phone data analysis to study the uneven impact of external shocks, such as the COVID-19 pandemic, on tourist destinations. This approach considers spatial resilience heterogeneity within regions or provinces. By incorporating income information, the analysis introduces a social dimension to highly detailed spatial data, surpassing traditional studies conducted at the regional or national levels.

COVID-19大流行对全球旅游业产生了重大影响，国际旅行受到了限制的影响最为严重。国内旅游也面临着重大挑战。本文分析了COVID-19大流行对西班牙国内旅游的影响，重点关注从马德里（该国首都）到其他旅游目的地的旅行。

本研究使用移动电话数据研究了2019年、2020年和2021年夏季旅游出行的演变。采用回归模型解释了各目的地游客数量。

大流行不仅导致了旅游流量急剧下降，还扰乱了国内流动系统的总体模式。获胜的目的地通常是马德里附近的地区和人口较稀少的目的地，而城市目的地是主要的输家。国内游客的偏好在收入群体之间有明显差异，但旅行量的减少只显示出边际差异。

本文展示了使用移动电话数据分析研究外部冲击（如COVID-19大流行）对旅游目的地的不均匀影响的潜力。该方法考虑了区域或省份内的空间弹性异质性。通过整合收入信息，该分析为高度详细的空间数据引入了社会维度，超越了传统在区域或国家水平进行的研究。