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This study investigates how enhancing slum dwellers' capabilities influences their entrepreneurship development and contributes to urban poverty reduction, providing insights for social policy design.

A quantitative research design is adopted applying structural equation modeling to survey data from 585 beneficiaries of social welfare schemes across Indian slums.

Educational, economic and sociocultural capabilities positively impact quantitative and qualitative dimensions of slum entrepreneurship development, which reduces urban poverty, supporting the hypothesized relationships grounded in the Capability Approach.

The cross-sectional data limits causal inference. Wider sampling can improve generalizability. Capability antecedents of entrepreneurship merit further investigation across contexts.

Integrated policy initiatives focused on education, skill building, access to finance and markets can leverage entrepreneurship for sustainable urban poverty alleviation.

Enhancing slum dweller capabilities fosters entrepreneurship and empowerment, enabling people to shape their own destinies and reduce deprivations.

The research provides timely empirical validation of the Capability Approach and evidence-based insights to inform social policy aiming to alleviate urban poverty via entrepreneurship in developing countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0514.

This study aims to reconstruct how smallholder farmers implement livelihood adaptation strategies to survive and escape poverty, thereby mitigating or eliminating potential livelihood risks by utilizing their available assets.

This research employed a qualitative approach. For the collection of primary data, the researcher conducted observations and in-depth interviews and engaged with the lives of smallholder farmers during the data collection period.

Among the various livelihood adaptation strategies, only migration and profit-sharing strategies enable smallholder farmers to escape poverty. However, migration is an unsustainable adaptation strategy. When farmers move to new locations, they often resort to slash-and-burn methods for clearing land, which can lead to forest degradation and deforestation. Profit sharing is a sustainable livelihood adaptation strategy that falls into a different category. This approach can lift farmers out of poverty, increase their income and have no negative environmental impact. Other adaptation strategies include adjustments to traditional agriculture, both on and off-farm diversification, involving the family in income generation, reducing farming costs, practicing frugality in post-harvest processes, converting land from coffee cultivation to other crops and borrowing money and selling owned assets. Smallholder farmers implement these strategies to survive the existing economic conditions.

The profit-sharing strategy was a novel livelihood adaptation approach that previous studies had yet to uncover at the research site. In this strategy, farmers assume the roles of both managers and laborers simultaneously during farming, while toke (the capital owners) play the role of farming funders. The generated profit is then shared between farmers and toke based on the agreement established at the outset of their collaboration.

Globally, information and communication technology (ICT) is regarded as a reliable tool that facilitates economic development and propels sustainable development. However, little empirical work exists on the specific effects of ICT access and usage on economic and sustainable development. This paper aims to investigate the nexus between ICTs, economic and sustainable development at the global level.

This paper presents ICT for Development (ICT4D) value chain empirical evidence on the linkages between ICTs, economic development and sustainable development goals (SDGs). The research model based on the capability approach is validated by using archival data from 130 global countries and partial least squares–structural equation modelling.

The findings reveal that ICT access and usage significantly influence a country’s attainment of the SDGs. Whilst ICT access plays a crucial role in promoting economic development, ICT usage does not. Also, findings show that economic development significantly mediated the nexus between ICT access and SDGs but not between ICT usage and SDGs. This calls for countries to ensure that access to ICTs is accompanied by a low cost of usage to achieve the full benefits of economic and sustainable development.

Using the ICT4D value chain, this paper empirically shows how ICT readiness and availability in the form of ICT access and ICT uptake (individual ICT use) promote economic development and SDGs (impact). Furthermore, with many studies conducted on SDGs at the country level, this study provides a broader understanding of the roles of ICT access and use on SDGs at the global level. This allows for easy generalisability and reproducibility of results.

This study aims to develop a comprehensive framework for Islamic social entrepreneurship (ISE) by synthesizing Islamic principles and social entrepreneurship concepts, bridging the gap between theory and practice.

Using a systematic literature review, this study focuses on scholarly works published from 1992 to 2023, uses thematic analysis and engages with subject experts to craft a framework for ISE.

The study identified 39 sub-dimensions grouped into 13 core dimensions. These findings highlight the multifaceted impact on ISE, emphasizing its commitment to ethical, socially responsible practices and achieving lasting social impact through collaborative, innovative approaches guided by Islamic principles.

Limitations include regional focus, lack of longitudinal data and absence of quantitative testing for the framework. Future research should expand scope, use quantitative analysis and explore gender dynamics, policy implications and standardized impact metrics to enhance the framework’s robustness.

The study’s comprehensive framework aids ISE practitioners in aligning their ventures with Islamic ethics and social impact. As interest in ISE grows, particularly in Muslim-majority contexts, this research facilitates the integration of Islamic values into social entrepreneurship, addressing pressing societal challenges.

This study contributes to the field of ISE by proposing a meticulously crafted framework that synthesizes Islamic principles and social entrepreneurship concepts. It stands out as a unique endeavor that bridges the gap between theory and practice in ISE, offering practical guidance while enriching the scholarly discourse on the subject.

Persons with disabilities (PwD) are generally less likely to be employed than the general population. The paper aims to investigate whether access to assistive technologies (AT) impacts labour force participation in the disabled population.

The study utilises the nationally representative survey on disability in India conducted in 2018 through multi-stage sampling by the Ministry of Statistics and Programme Implementation (MOSPI), Government of India. The instrumental variable (IV) approach has been employed to infer causality between AT and labour market participation.

The study found that the labour force participation rate (LFPR) in India amongst the disabled population was 29% in the age group of 15–65 years in 2017–2018, as compared to 52% in the general population. Around two-thirds of the PwD respondents who were advised to acquire aid appliances acquired them, implying limited access to AT. The probability of LFPR in disabled population increases by 26.6% with access to AT particularly in urban areas.

Persistent issues such as lack of adequate amenities, poor literacy and a lack of vocational skills need to be addressed to improve labour market outcomes for the disabled population in rural areas.

Despite its role in promoting distributive justice and inclusive development, research on equity gaps in access to AT and its impact on labour market outcomes is scant. This is the first paper that provides empirical evidence on the impact of access to AT on LFPR in the context of low- and middle-income countries.

The paper seeks to introduce the “critical open access literacy” construct as a holistic approach to confront the challenges in open access (OA) as a dimension of scholarly communication.

The paper first introduces the concepts of information literacy (IL) and OA in the context of transformations in the scholarly information environment. Via a theoretical-analytical exercise on the basis of a literature review of the intersections between the two concepts and of the criticisms of OA, the paper discusses the role of critical IL in addressing the challenges in OA and lays the theoretical-conceptual groundwork for the critical OA literacy construct.

The structural nature of the challenges and transformations in the scholarly information environment require new foci and pedagogical practices in library and information studies. A more holistic, critical and integrative approach to OA is warranted, which could effectively be achieved through the re-conceptualization of IL.

The paper specifies the avenues for putting the theoretical conceptualizations of critical OA literacy into practice by identifying possible foci for IL instruction alongside a transformed role for librarians.

The paper extends deliberations on the role of critical IL for scholarly communication and attempts to advance the research fields of the two domains by proposing a new construct situated at the junction of OA and IL.

The main aim of this study is to explore the role of multi-dimensional human capital on the economic growth of the Indian economy.

The study used the methodology given by World Bank, 2018) in calculating the human capital index (HCI). The HCI has been constructed at a regional level for all 28 Indian states and 8 Union Territories (UTs) for the period of 2015–2016. The study explored the linkages between HCI and per capita gross state domestic product (PGSDP). The study further employed OLS (Ordinary Least Square) for overall significance and Spearmen’s Rank correlation coefficient test for establishing the linkage between HCI and PGSDP.

The results indicate that quality education, expected year of schooling, and infant mortality rate play a significant role in the improvement of HCI which further impacts the productivity rate of the upcoming generation and the inclusive growth of the country. The findings show that Mizoram, Chandigarh and Kerala are better performing states while the Bihar and Uttar Pradesh are the worst performers. The results also show that there is a positive and statistically significant correlation between PGSDP and HCI and its components. Further, the results show that public expenditure on health and education has significant effect on HCI.

The results of this study would be useful for policymakers to identify the determinants and improve the position of Indian states in HCI. The results show that policymakers should focus on quality education and health to improve the productivity of future generation workers for sustainable and inclusive growth.

The study is the pioneering study to analyze the state-wise HCI in India using methods mentioned by the World Bank. Unlike previous studies, variables such as expected year of schooling, under-5 mortality rates and survival rates are constructed more pragmatically.

This study aims to investigate the relationships between the perceived neighborhood walkable environment (PNWE), neighborhood interaction (NI) and residents’ mental health, with a focus on examining differences among residents of different age groups.

Using an electronic survey questionnaire, data on PNWE, NI and mental health were collected from 1,159 residents across 205 communities in Shanghai, China. Our study utilized a structural equation modeling (SEM), employing the maximum likelihood estimation method. The structural equation model was fitted using the MPLUS software.

The mental health of young and middle-aged adults is generally poor, and they are at higher risk of depression than children and older adults. The effects of PNWE and NI on the mental health of residents varied among different age groups. As residents get older, their mental health is more affected by the PNWE. In addition, the influence of the PNWE on children and older adults’ mental health is direct and not mediated by NI. For young and middle-aged adults, the influence of the PNWE on their mental health needs to be mediated by NI.

This study marks the first examination of the relationship between PNWE, NI and mental health among different age groups of residents in China. The findings of this research can assist policymakers in gaining a deeper understanding of the underlying mechanisms by which PNWE affects mental health. Furthermore, it can contribute to the development of more targeted walkable environment designs aimed at enhancing mental health among various age groups.

Designing and developing responsible business practices can create various tensions for service organizations. The purpose of this research is to develop a deeper understanding of the relationship between customer engagement (CE) and responsible business practices (e.g. environmental, social and/or governance [ESG], corporate social responsibility [CSR] and diversity, equity, and inclusion [DEI]) and explore customer engagement tensions that service organizations may face.

This research develops a list of CE-related responsible business practice tensions and empirically explores their relevance through in-depth interviews with nine ESG professionals.

This paper makes three important contributions. First, we find support for nine distinct but related tensions with implications for CE that organizations must navigate when pursuing responsible business practices. Second, interview participants provide some suggestions for tackling these tensions, which we support with relevant theories. Finally, we develop a conceptual framework that may stimulate future service research and inform the implementation of ESG strategies.

To the best of the authors’ knowledge, this research is the first to conceptualize and empirically explore the tensions that emerge between responsible business practices and CE. The authors develop a novel analysis of the CE-related tensions that emerge when pursuing an ESG strategy.

The findings are based on a small sample of ESG professionals. Future research may take a quantitative approach to further evaluate the role that these tensions play in engaging customers.

This research provides a conceptual framework that may guide ESG professionals in understanding, framing and navigating CE-related tensions when pursuing responsible business practices.

A social benefit may be found when service organizations are better able to successfully navigate CE-related tensions when pursuing responsible business practices.

Climate change is a problem that concerns all of us. Despite the information produced by organizations such as the Expert Team on Climate Change Detection and Indices and the United Nations, only a few cities have been planned taking into account the climate changes indices. This paper aims to study climatic variations, how climate conditions might change in the future and how these changes will affect the activities and living conditions in cities, specifically focusing on Mexico city.

In this approach, two distinct machine learning regression models, k-Nearest Neighbors and Support Vector Regression, were used to predict variations in climate change indices within select urban areas of Mexico city. The calculated indices are based on maximum, minimum and average temperature data collected from the National Water Commission in Mexico and the Scientific Research Center of Ensenada. The methodology involves pre-processing temperature data to create a training data set for regression algorithms. It then computes predictions for each temperature parameter and ultimately assesses the performance of these algorithms based on precision metrics scores.

This paper combines a geospatial perspective with computational tools and machine learning algorithms. Among the two regression algorithms used, it was observed that k-Nearest Neighbors produced superior results, achieving an R² score of 0.99, in contrast to Support Vector Regression, which yielded an R² score of 0.74.

The full potential of machine learning algorithms has not been fully harnessed for predicting climate indices. This paper also identifies the strengths and weaknesses of each algorithm and how the generated estimations can then be considered in the decision-making process.