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The purpose of this study is to examine households’ behavior towards dirty cooking energy utilisation in an environment where relatively higher accessibility to clean energy is noted. Although the low utilisation rate of clean energy can partly be attributed to utility gains anticipated in dirty energy mixes (DEMs) arising out of accessibility constraints, affordances and enablers, it is still unclear on the extend at which each of these contributes towards DEMs manifestation among the seemingly well-to-do households with higher levels of clean energy mixes (CEM) access. This study, therefore, hinges on scrutinising on this lower utilisation patterns despite a seemingly higher accessibility of CEMs, specifically liquified petroleum gases (LPG).

The study is based on a household’s survey that was carried out in 2018, reaching a sample of 393 households using questionnaires in four wards of the Kigamboni district in Tanzania. Subsequent analyses were descriptive as well as inferential based on binary logistic regression analysis where utilisation of DEMs was predicted for both the high and low social economic status (SES) households by incorporating accessibility constraints, affordances and enablers.

The results show, first, if one assumes energy stacking is not an issue, as households become more constrained towards CEMs utilisation, they shift towards DEMs suggesting that the overall effect is a substitution, and second, the complementarity effect ultimately outweighs the substitution effect as households do not shift from DEMs to CEMs rather stack multiple energy. DEMs flourish in this case study area because those with high income are among those in the lowest SES, and some of those with the highest SES are from among the lowest income category, and all of them end up with more DEMs because shifting towards CEMs require income to complement SES.

Policy-wise, removing hurdles in accessing CEMs such as LPG subsidy programme, gas stove provision to the poor, and enhanced LPG awareness will most likely benefits only those who do not stack energy in cooking while strategies targeting those at the lowest SES such as higher education attainment, empower women as a family decision maker, encourage co-occupancy to enlarge the household size and contain urban growth within certain perimeter will have a significant impact only if they raise both incomes and SES.

Despite of the dominance of DEMs for cooking such as charcoal and firewood in Tanzania, CEMs such as LPG, have emerged as complements or alternatives in the household energy basket. The utilisation of such CEMs is, however, still very low despite the accessibility, cost, environmental and health advantages they offer. Accessibility is not the only factor fuelling CEMs; a complementarity must exist between SES and income for the positive transition towards CEMs to be realised.

Renewable energy alternatives and nanoscale materials have gained huge attention in recent years due to the problems associated with fossil fuels. The recyclable battery is one of the recent developments to address the energy requirement issues. In this work, the development of nanoscale materials is focused on using green synthesis methods to address the energy requirements of hybrid electric vehicles.

The current research focuses on developing metal oxide nanoscale materials (NANO-SMs). The Zno-Aloe vera NANO-SM is prepared using the green synthesis method. The developed nanoscale materials are characterized using analysis methods like FESEM, TEM, XRD and FTIR.

The average size of ZnO-Aloe vera mono-crystalline was recorded as 60–70 nm/Hexagonal shape. The nanoscale materials are used for the detection of LPG gases. The sensitivity observed was 48%. The response time and recovery time were recorded as 8–10 s and 230–250 s, respectively. The average size of SnO₂-green papaya leaves poly-crystalline was recorded as 10–20 nm/powder form.

Nanoscale materials are developed using green synthesis methods for hybrid vehicle applications. The nanoscale materials are used for the detection of harmful gases in hybrid vehicles.

This paper aims to assess the relationship between energy poverty and the well-being of people using Amartya Sen’s capability approach to development as theoretical underpinning.

The study uses household-level energy access data collected by the Harvard Dataverse in 2015 and 2018. The authors use multidimensional indices to measure energy poverty and well-being. Further, the authors apply quantile regression approach to measure the relationship between energy poverty and well-being.

The study’s findings reveal that energy poverty and well-being are negatively related. India has made progress in reducing energy poverty and improving well-being during the study period. However, progress in reducing energy poverty is largely due to improved access to electricity and improvement in well-being due to income and financial inclusion. Using modern cooking fuel has a greater negative impact on well-being compared to lighting using electricity. Further, households spending a greater proportion of their income on modern energy fuels leads to a lower quality of life as it precludes them from using it for other purposes. The study records wide variations in the observed relationship between energy poverty and well-being across various socioeconomic groups.

This calls for improvement in the production and distribution of modern energy resources, which have substantial welfare implications.

This is the first study to measure the relationship between energy poverty and quality of life using multidimensional indices. The findings of this paper have policy implications for the pricing of energy resources and energy access measures.

More than 40% of Indian households still rely on unclean cooking fuels, exposing particularly women and children to adverse health effects. This paper explores the factors determining a household’s cooking fuel choice in India.

The study used the fifth round of the National Family Health Survey (2019-21) dataset. A chi-square test and a logistic regression were used for empirical analysis. Cooking fuel was categorized as “clean” and “unclean” cooking fuel.

The result shows that around 47% of the households are still using unclean cooking fuel in India. Households with a better-educated or female head, those with smaller family sizes, those with a higher level of wealth and those located in urban areas are more likely to use clean cooking fuel. Similarly, households headed by younger individuals and Muslim households are linked to more usage of clean cooking fuels. However, Scheduled Tribe (ST) and Other Backward Classes (OBC) households and those headed by older individuals are less likely to use clean cooking fuels.

The cross-sectional nature of data enables us to draw only associations between the variables and not causal relationships between them. The findings of this study have important implications for household energy policies in India and other developing nations. There is a need for policymakers to seriously consider socioeconomic factors in addressing issues and challenges associated with household energy consumption.

The study extends the empirical literature on determinants of household cooking fuel choice using the latest round of National Family Health Survey data from India.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2023-0988

In the process of industrial growth, when existing industries go for technology upgradation and new modernised industries emerge, both capital intensity and energy demand of overall industry tend to rise steadily. This poses a serious challenge for sustainable development objectives. Towards this end, enhancing energy efficiency of individual industries is the only remedy. Against this backdrop, the study aims to probe the trends in capital intensities and energy efficiencies of individual industries in India.

This study uses panel data regression analysis on data of two-digit industries from 1980/1981–2016/2017. The statistical analysis includes relevant macroeconomic variables derived from the literature to ascertain the drivers of energy efficiency in industries.

The results brought out that capital deepening due to technology upgradation and modernisation and capital productivity growth are the decisive determinants of energy efficiency growth. Furthermore, the ever-increasing fuel price motivated industries to conserve energy on a steady basis, supplemented by energy conservation-specific policy interventions.

This study recommends policy initiatives to ascertain and address technology gaps industry-wise, so that its subsequent efficient capital utilisation, and energy conservation measures of industries would result in energy efficiency growth in industry. The policy must focus on energy-efficient capital intensification in fabricated metals, leather, textile and wood industries that are found less-energy-efficient despite being less-capital-intensive.

This study empirically explores the capital efficiency of industries by investigating the interaction between capital intensity and energy efficiency at a two-digit industry level. It explores the determinants of energy efficiency and proposes industry-specific policies for energy-efficiency-enhancement of the overall industry.

The continuous increase of energy demands is a critical worldwide matter. Jordan’s household sector accounts for 44% of overall electricity usage annually. This study aims to use artificial neural networks (ANNs) to assess and forecast electricity usage and demands in Jordan’s residential sector.

Four parameters are evaluated throughout the analysis, namely, population (P), income level (IL), electricity unit price (E$) and fuel unit price (F$). Data on electricity usage and independent factors are gathered from government and literature sources from 1985 to 2020. Several networks are analyzed and optimized for the ANN in terms of root mean square error, mean absolute percentage error and coefficient of determination (R²).

The predictions of this model are validated and compared with literature-reported models. The results of this investigation showed that the electricity demand of the Jordanian household sector is mainly driven by the population and the fuel price. Finally, time series analysis approach is incorporated to forecast the electricity demands in Jordan’s residential sector for the next decade.

The paper provides useful recommendations and suggestions for the decision-makers in the country for dynamic planning for future resource policies in the household sector.

India’s manufacturing sector employs about 12% of the labour force and contributes to about 17% of the nation’s GDP. The Indian government intends to implement several initiatives under the “Make in India” and Atma Nirbhar Bharat banners to increase the manufacturing sector’s share of the nation’s GDP to 25% by 2025. Applying lean manufacturing, green manufacturing and Six Sigma is crucial to ensure that India’s manufacturing sectors grow sustainably in international markets. This study aims to identify sustainability indicators and ascertain their respective weights to evaluate the sustainability performance of the Indian manufacturing industry.

This research identifies 25 sustainability indicators and classifies them into the triple bottom line of sustainability based on an evaluative literature review and expert opinion. The Best Worst Method was utilised to determine the weights of the sustainability indicators. The sustainability index was developed to evaluate economic, social and environmental sustainability.

The sustainability performance of a foundry in a significant Western Indian State city was assessed by applying the developed sustainability index. After the adoption of integrated lean, green and Six Sigma (LG&SS) strategies and related practices in the foundry, there has been a notable improvement of 68.03% in the economic index, 61.62% in the social index and 13.24% in the environmental index.

The proposed sustainability index is applied and evaluated specifically for assessing the sustainability performance of Indian manufacturing SMEs. It can be used to substantiate firm’s sustainability performance and also to assess the improvement in firm’s performance in economic, environmental and social dimensions after implementing various operational excellence practices. However, it cannot serve as a benchmark tool across similar companies or organisations.

The developed sustainable index can be used to analyse the company or organisation’s sustainability performance and see how various strategies have improved things. Practitioners can use this index to assess social, economic and environmental performance and focus on areas that need improvement.

The proposed sustainability index serves as a vital tool for monitoring a firm’s progress in triple bottom line (TBL) dimensions of sustainability, tracking a diverse range of indicators and encouraging sustainable organisational practices.

This study attempts to assess the economic, social and environmental performance of Indian Manufacturing SMEs by proposing a sustainability index.

India is one of the fastest developing economies, but it faces numerous socioeconomic problems, such as hunger, poverty, under- and unemployment, gender inequity and illiteracy. Corporate social responsibility (CSR) funding at the corporate level could tackle these socioeconomic problems, providing support to the nation’s overall development. Mandated CSR expenditures, in alignment with the achievement of the sustainable development goals (SDGs) of the United Nations, would support the nation’s contributions to building a sustainable future. Several questions, however, remain. Thus, this study aims to explore relationships between a company’s gross and net profits and its expenditures for CSR; and mapped the specific CSR activities used to address each of the 17 UN SDGs and then draw implications for human resource development (HRD).

The data were gathered from published annual reports (2019–23) of 60 Fortune 500 Indian companies. A zero-order correlation was used to find the relationship between CSR expenditure and gross, as well as net, profits. Furthermore, the CSR activities of the sample were mapped with the UN SDGs.

There was a positive, moderate to strong correlation between CSR expenditures and gross profit (r = 0.82, p < 0.01), but for net profit, the correlation was strong (r = 0.85, p < 0.01). All CSR activities mapped to at least one of the SDGs.

The alignment of CSR activities and SDGs based on Fortune 500 Indian companies has not yet been explored. Also, no study to date discusses the gaps in the CSR expenditures for specific UN SDGs.

This study attempts to quantify the degree of independence of Central Bank of India from both legal and behavioural contexts over the period 1990–1991 to 2018–2019, a period encompassing major developments in the operation and regulation of Reserve Bank of India (RBI).

We followed Jasmine et al. (2019) to calculate the magnitude of de jure independence of RBI and for de facto independence, “turnover rate (TOR) of CB governor” as proposed by Cukierman et al. (1992) is applied.

The results report that the legal autonomy of RBI increased specifically after the reforms and post formulation of Monetary Policy Committee (MPC). However, the actual independence of RBI remains more or less in line within the critical threshold limit of 0.2.

The study proposes effective implementation of laws and procedures designed to promote the independence of Central Bank of India imperative for an effective monetary operation along with a coordinated fiscal policy.

Targeted study of a particular central bank on its “independence” aspect in general and of the Reserve Bank of India in particular has not been attempted as on date. It is to this end that the present study contributes.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0098.

Bangladesh is one of the leading countries that has been facing serious air pollution issues, with an exponentially higher death rate attributed to it than other environmental pollution. This study aims to identify the sources and dynamics of particulate matter (PM) pollution across different micro-environments in Rajshahi City.

PMs’ concentration data were collected from 60 sampling stations, located across the six micro-environments of the study area, throughout the year using “HT 9600 Particle Counter.” To assess the level of pollution, the air quality index (AQI) was calculated, and different methods, including observation, group discussion, interview and questionnaire survey, were used to identify the pollution sources.

Both PM_2.5 and PM₁₀ exhibit varied concentrations in different micro-environments, and the area covered by different AQI classes differs considerably throughout the year. The monthly average concentration of PM_2.5 and PM₁₀ was highest in January, 200 and 400 µg/m³ and was lowest in September, 46 and 99 µg/m³, respectively. Among the total 1,440 observations, 853 observations (59.24%) exceeded the national standard. Based on the pollution level, different months and micro-environments in the city have been ranked in descending order as January > December > February > March > April > November > October > May > June > July > August > September and traffic > commercial > industrial > residential > green cover > riverine environment.

Although numerous research has been conducted on air pollution in Bangladesh, the authors are certain that no attempt has been made to address the issue from a multi- micro-environmental perspective. This makes the methodology and findings truly unique and significant in the context of air pollution research in Bangladesh.