Financing risk remains one of the significant challenges in clean energy projects due to heavy investment requirements, limited financing, unpredictability of future revenues and market instability. Against this backdrop, the present work is an effort to offer further insights into the relationship between industries’ financial constraints and energy efficiency by incorporating the moderating role of research and development. To investigate this relationship, we use industry-level data for twenty-two manufacturing sectors in seven European countries. Our findings from the High-dimensional fixed effect model reveal that energy intensity (energy efficiency) increases (decreases) with the increasing share of financially constrained firms in an industry. Moreover, increasing R&D intensity in an industry lessens the adverse impact of FCs on energy efficiency. The results remain robust under other specifications employing alternative measures of financial constraints. These findings emphasise the innovation funding programs like Horizon Europe to enhance energy efficiency, especially for financially constrained firms.

This study conducts a systematic literature review (SLR) to identify and synthesize the drivers and barriers influencing rooftop solar (RTS) adoption in the hospitality sector, with a focus on hotels. Using PRISMA guidelines, 390 peer-reviewed articles published between 2012 and 2024 were analyzed through both descriptive and thematic analysis, covering economic, environmental, personal, social, demographic, technical, market-related, and regulatory factors. Findings reveal that while financial savings, policy incentives, environmental awareness, and vendor trust serve as strong adoption drivers, high upfront costs, technical limitations, policy inconsistencies, and limited awareness remain critical barriers. The review also applies the Capability–Opportunity–Motivation–Behavior (COM-B) framework to map these factors, providing a holistic understanding of adoption behavior. Results highlight research gaps, particularly in hospitality-specific and developing-country contexts, and recommend innovative financing models, stronger vendor engagement, and policy streamlining to accelerate RTS adoption.

This study examines the role of female leadership and female ownership in the adoption of green investment at the firm level using the data from the World Bank Enterprise Survey (WBES) for Central, Eastern and Southeastern European (CESEE) countries. We classify firms' green investment practices (GIPs) into capital- and noncapital-intensive categories. Furthermore, using the negative binomial and zero-inflated Poisson regression models, we find that female leaders in noninnovative firms are less likely to adopt GIPs than their male counterparts. This is owing to the risk aversion among female leaders towards the strategic actions turning more salient in the absence of innovation and dynamic capabilities. Similarly, a negative association of female ownership is also reported with all types of GIPs for noninnovative firms. However, with innovative firms, female leadership's negative effect is reversed, signifying the dominance of their socially responsible decision-making trait. This is partly due to enhanced capabilities and resilience to internal financial constraints within innovative firms, as is also demonstrated through a higher likelihood of innovative firms adopting GIPs. Overall, these results suggest the presence of gender gaps, indicating that female leaders' connection to sustainability performance is contingent on firms' resource availability and organizational capabilities. The findings suggest that efforts to improve gender diversity should be coupled with enhancing the innovative environment along with addressing credit market frictions to promote sustainable practices in corporates.

The hospitality industry faces the challenge of balancing growth with environmental responsibility. This study conducts a bibliometric analysis of sustainable practices in green hotels by reviewing 394 scholarly publications from 2014 to 2024. It systematically maps major trends and themes in sustainable hotel research. Using the Bibliometric R package and VOS viewer, the analysis reveals a 17.04

This analysis aims to estimate the savings potential through energy efficiency and explore the effects of innovation and exporting. We consider data from 85 firms in the Indian chemical industry for the period from 2003 to 04 to 2019-20. Widely used stochastic frontier analysis has been used to estimate production function-based Energy Efficiency (EE). Overall, the EE estimate has a median of 78 per cent, showcasing significant potential for energy savings in the industry. Firm-level total factor energy efficiency (TFEE) ranges from 55 to 82 per cent, with considerable variation. Our analysis reveals that firms with greater accumulated innovative capabilities tend to achieve higher energy efficiency. Additionally, factors such as firm age, financial performance and exporting are positively associated with better TFEE. Whereas firms with geographically dispersed production facilities and higher energy prices lead to lower energy efficiency. The results underscore the vital role of exporting, regional disparities, and technological gaps when designing EE strategies at the firm level. Our study offers valuable insights for policymakers.

This study aims to measure energy efficiency levels and the impact of technological innovation and regional heterogeneity on energy efficiency. Hence, we use Indian chemical industry data covering 85 firms from 2003–04 to 2018–19. First, we employ the stochastic frontier analysis (SFA) to measure total factor energy efficiency (TFEE). Second, we use truncated regression to assess the effect of innovation and other factors. Our time-varying TFEE has a mean level of 0.84. Most firms can improve their energy efficiency by 15 %. Hence, a substantial energy-saving opportunity exists in the case of the chemical industry in India. Our second-stage results suggest that firms' innovative capability accumulates over time, enabling them to achieve higher energy efficiency. Additionally, older firms perform better than younger ones in terms of TFEE. However, having facilities at different locations reduces energy efficiency, while the number of products produced does not significantly impact energy efficiency. Our study emphasises the need to consider regional heterogeneity and technological gaps when developing strategies to enhance energy efficiency at the firm level. The findings have significant implications for regulating the manufacturing sector, providing insights for policymakers and industry practitioners to design effective strategies to promote energy efficiency.

Fertilizer is a resource-intensive, hard-to-abate industry that provides crucial support to sustain agricultural production. This study estimates the technical efficiency (TE) of the Indian fertilizer-producing firms over the years 2009 to 2019. We use the input distance function under the production function farmwork to find potential input reduction to produce a certain output level. We further examine potential determinants of TE, such as age, ownership, and innovation. We use Greene’s (2005) ‘true fixed effect’ and ‘true random effect’ to isolate inefficiency effectively from fixed effects. The results demonstrate a notable scope for improvement in TE, with a potential increase of up to 30% for half of the firms. There are substantial differences across firms where the bottom 25 percent of samples have less than 60 percent TE. TE slightly declined, particularly in the case of state-owned firms (SOEs), whereas privately owned firms have greater TE than SOEs. Better financial performance and R&D activity positively influence TE, while experienced firms have better TE. Hence, the results support resource-based theory, which argues that firms with better resources and capabilities achieve greater efficiency. Effective government policies should be implemented to boost firms’ capacity for innovation and TE to meet the country’s future fertilizer needs.

Indian states are immensely heterogeneous in terms of their socioeconomic activities. The economic structure of India is consequently bifurcated too. This study examines, under given heterogeneities, whether credit accessibility among states converges over time, particularly in industrial and agricultural lending. We employ the concept of club convergence and find that substantial heterogeneities and multiple transition paths exist for industrial credit convergence across states, while agriculture credit is relatively less heterogeneous as compared with industry. Therefore, more attention is required to reduce access to banking credit for industries in poorer states.

Poor people in a developing country like India face energy poverty and are deprived of clean cooking fuel. Clean cooking fuels are costlier and require more willingness to pay (WTP) from the consumer. Therefore, this is a descriptive study aims to analyze factors associated with differences in cooking fuel expenses at the household level in Uttar Pradesh, India. For this purpose, panel data from the Consumer Pyramids Household Survey of CMIE from 2014 to 2019 has been considered. The study uses fixed-effect panel data model to control individual-specific effects. Cooking fuel expenses show positive elasticity concerning per capita income. However, this elasticity is lower for the higher-income group than the bottom-income group. Less educational attainments of households are associated with lower spending on cooking fuel. Moreover, households with better access to electricity are willing to spend more on cooking fuel expenditure. Hence, improved access to electricity nudges households towards more WTP for cooking fuel. It is further confirmed by finding a positive association between electricity-using household appliances and cooking fuel expenses. Therefore, improved access to electricity may increase the WTP for cooking fuel and adopt clean cooking fuel in different ways. This suggests positive spillover effects of modern energy services on clean cooking fuel.

PurposeThe present study empirically examines the impact of coronavirus disease 2019 (COVID-19) and policy uncertainty on stock prices in India during the COVID-19 pandemic.Design/methodology/approachTo this end, the authors use the daily data by applying the autoregressive distributed lag (ARDL) model, which tests the short- and long-run relationship between stock price and its covariates.FindingsThe study finds that increased uncertainty has adverse short- and long-run effects on stock prices, while the vaccine index has favorable effects on stock market recovery.Practical implicationsFrom investors' perspectives, volatility in the Indian stock market has negative repercussions. Therefore, to protect investors' sentiments, policymakers should be concerned about the uncertainty induced by the COVID-19 pandemic and similar other uncertainty prevailing in the financial markets.Originality/valueThis study used the news-based COVID-19 index and vaccine index to measure recent pandemic-induced uncertainty. The result carries some policy implications for an emerging economy like India.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0244

Access to electricity plays a crucial role in reducing energy poverty. This analysis examines energy affordability based on electricity expenditures. Hence, panel data from the consumer pyramids household survey has been consolidated. Fixed-effect models have been applied at the household level to control unobservable heterogeneity. The results show that better income leads to more electricity expenses non-linearly. Lower-income group households have a higher income elasticity of electricity expenditure than higher-income group households. Whereas moderately educated households have higher expenditure on electricity. The quality of electricity access matters to households for higher electricity usage.

Although much has been discussed about the link between renewable energy, globalisation and carbon dioxide (CO2) emissions, yet the impact of total factor productivity (TFP) on CO2 emissions is less known in the existing literature. Therefore, the present study considers TFP as one of the determinants of CO2 as it is believed that technological enhancement plays an essential role in improving the environmental quality by raising efficiency in energy use and pollution treatment. In contrast, it may also have unfavourable impacts. In particular, this study analyses how TFP along with renewable energy and globalisation affect the aggregate and source of CO2 emissions (oil, coal and gas) in the case of top ten carbon emitters from the developing economies over the period 1980–2018. To achieve the above objective, we use the second-generation panel unit root, cointegration and causality tests. We also implement a cross-sectional autoregressive distributed lag model (CS-ARDL) to find the long-run and short-run coefficients. Findings from panel cointegration tests show that there exists a significant long-run relationship between renewable energy, non-renewable energy, globalisation, total factor productivity and CO2. Moreover, findings show that renewable energy consumption has a negative and significant impact on CO2 emissions while non-renewable energy consumption significantly increases the CO2 at aggregate and disaggregated levels. Further, our results confirm that TFP increases the CO2 emissions whereas globalisation decreases CO2. From the policy point of view, TFP growth needs to be accelerated to a higher level so that it enables low carbon growth. The slower TFP growth may enhance output which requires more energy and produces more emissions. Thus, there should be a promotion of emissions’ reducing technology along with better TFP growth. Also, our findings recommend that CO2 in sample countries can be reduced through promoting low carbon technology, and globalisation.

Unsurprisingly, many studies consider CO 2 emissions to capture the environment quality needed for testing the augmented environmental Kuznets curve (EKC) hypothesis. However, this is a major limitation of the existing literature because CO 2 alone cannot account for environmental pollution. By employing a more comprehensive proxy ecological footprint, this study aims to examine EKC in G20 economies during 1991–2016. To achieve the objective, a second-generation panel data model was implemented, which accounted for the heterogeneity and cross-sectional dependence. The findings reveal that environmental degradation has an inverted N-shaped linkage with economic growth in the selected countries. It is further observed that globalization, renewable energy consumption, and urbanization improve the environmental quality, whereas non-renewable energy consumption mitigates the quality of environment in G20 countries. With these conclusions, it is suggested that policymakers from these countries should emphasize on more renewable energy usage.

This study examines time-varying correlations between clean energy stocks, technology stocks, oil prices, and COVID-19 sentiment. The results confirm a weaker positive relation between oil prices and clean energy stocks. Correlations between COVID-19 sentiment and clean energy and technology stocks vary from low and negative during the peak period to positive and relatively high during the post-peak period. The results show the relatively better position of clean and technology stocks during the post-peak period.

This study unveils the question of how renewable energy, non-renewable energy, globalisation, and total factor productivity affect the carbon dioxide (CO 2 ) at the aggregate and disaggregate levels (CO 2 from oil, coal and gas) in case of top ten carbon emitters developing economies over the period 1991–2016. To achieve the above objective, we apply various panel unit, cointegration and causality tests. We also implement a Pooled Mean Group estimator technique to find the long-term coefficients. Findings from panel cointegration tests show that there exists a significant long-run relationship between renewable energy, non-renewable energy, globalisation, total factor productivity and CO 2 . Moreover, findings derived from PMG infers that renewable energy consumption has a negative and significant impact on CO 2 while non-renewable energy consumption significantly increases the CO 2 at aggregate and disaggregate level. Further, our results show that total factor productivity increases the CO 2 emissions whereas globalisation decreases it. From the policy point of view, our findings recommend that CO 2 in sample countries can be reduced through promoting low carbon technology, and globalisation. Moreover, our findings propose to encourage renewable energy installation and drafting comprehensive policies.

This study has picked up an essential question for the Indian pharmaceutical industry, whether innovation and internationalisation follow a two-way relationship during the product patent regime. This study analyzes the role of product, process and variety of innovation on exporting activities of 168 pharmaceutical firms from 2006 to 2013. For this purpose, this study applies two-stage least square probit and tobit model on innovation and export equation separately. The results show the feedback relation between export and innovative performance while there is a differential effect of product and process innovation on exporting. The results strongly support the learning-by-exporting and product-life cycle hypothesis. European origin firms are more likely to be innovative and export-oriented, while U.S. origin firms influence the firms' innovative performance. Business strategy should take account of benefits from the dynamic interaction of innovative and exporting activities and make their strategic decisions carefully.

Although several studies explored the issue of CO2/Ecological footprint convergence across the countries, study on biomass material footprint (BMF) convergence is scant. This study bridges this research gap by examining the “BMF convergence hypothesis” across 172 countries for the period from 1990 to 2017. To attain our objective, we use the novel Phillips and Sul (J Appl Econom 24(7):1153–1185, 2007a; Econometrica 75:1771–1855, 2007b) approach. We find that there is no evidence of convergence, while 172 countries are taken together. This implies that all the countries together are having different transition paths. Thus, Phillips and Sul test implements the clustering algorithms to identify the club convergence. Our results show the existence of six different steady-state (or club convergence) equilibriums for BMF. Thus, our findings show that climate change policies are required to be designed as per the existing clubs of the sample countries.

This paper aims to estimate energy efficiency and quantify the energy-saving potential of Indian iron and steel firms. Further, we explore the influence of different innovative capability channels that can enhance energy efficiency. Firm-level data of 82 Indian iron and steel firms over the period of 2003–2017 has been taken to investigate the issues. Bayesian stochastic frontier analysis (SFA) has been adopted to measure underlying energy efficiency. The results show that most of the firms can reduce half of their energy consumption, while substantial heterogeneity exists in terms of energy efficiency. The Bayesian SFA outperforms classical SFA and documents slightly declining evidence of energy efficiency over time. The analysis also depicts that investing in R&D expenditure, patenting activity, and disembodied technology flow enables firms to achieve higher stage energy efficiency. ISO 14001 certified firms do not perform better than non-certified firms, and there is no significant effect of embodied technology on the firms' energy efficiency.

Mechanical Engineers (IEs) approved effectiveness standards in the plan and improvement of assembly frameworks. The lean idea of the Toyota Production System broadened traditional business design cycles as a device for eliminating waste in an assembly climate. As frameworks are the mastermind, IE Expert's extraordinary capabilities and tools will expand their waste disposal to incorporate the item's overall lifestyle. The IE Capabilities Group is important to assist in economical design practices in planning and investigating items and cycles. The reason for this paper is to examine the importance of incorporating management standards and practices into IE advanced education.

This article aims at estimating the energy efficiency of the iron and steel industry in production theoretic approach. Taking a regional perspective, we have done a meta-frontier analysis combined with the slack-based measure of data envelopment analysis (DEA). The results depict huge energy efficiency gap exists across four regions. The northern region is the best performer under group frontier than meta-frontier DEA. South and west regions are relatively well-performed under meta-frontier than group frontier while the eastern region performs moderately well under both frontiers. The results show the significant energy efficiency improvement opportunities available across regions can be realised through technological advancement and energy management.