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This study aims to examine whether and how corporate sustainability capability influences energy efficiency through competitive intensity and slack resource availability.

The authors applied a two-wave research design and administered a survey questionnaire to senior-level managers of 78 ISO-14001 and ISO-50001 certified manufacturing companies. The authors use a multi-method approach for data analysis. AMOS 23 software was applied for covariance-based structural equation modeling. In addition, SPSS 25 software was applied for hierarchical regression analysis to examine the causal relationships in the model.

The finding reveals that corporate sustainability capabilities, which include energy-saving opportunities, seizing energy-saving opportunities and resource reconfiguration, significantly improve firms’ energy efficiency. In addition, competitive intensity and slack resource availability positively moderated the relationship between corporate sustainability capability and energy efficiency.

To the best of the authors’ knowledge, this study is the first to examine the link between corporate sustainability capability and energy efficiency in developing countries such as Pakistan. Although the influence of various corporate sustainability capabilities on sustainable performance has been widely examined in the literature, the role of corporate sustainability capability has been limitedly explored with energy efficiency. This study extends the literature by adding to the knowledge of corporate sustainability capability that enhances boundary conditions in developing countries.

Because of growing energy consumption and increasing absolute CO₂ emissions, the recent calibrations about the environmental sustainability across the globe have mandated to achieve the minimal energy consumption through employing energy-efficient technology. This study aims to estimate linkage between simple measure of energy efficiency indicator that is reciprocal of energy intensity and total factor productivity (TFP) in case of Indian paper industry for 21 major states. In addition, the study incorporates the other control variables like labour productivity, capital utilization and structure of paper industry to scrutinize their likely impact on energy efficiency performance of the industry.

To derive the plausible estimates of TFP, the study applies the much celebrated Levinsohn and Petrin (2003) methodology. Using the regional level data for the period 2001-2013, the study employs instrumental variable-generalized method of moments (GMM-IV) technique to examine the nature of relationship among the variables involved in the analysis.

An elementary examination of energy intensity shows that not all states are equally energy intensive. States like Goa, Rajasthan, Jharkhand and Tamil Nadu are less energy intensive, whereas Uttar Pradesh, Kerala, Chhattisgarh, Assam and Punjab are most energy-intensive states on the basis of their state averages over the whole study period. The results estimated through GMM-IV show that increasing level of TFP is associated with lower level of energy per unit of output. Along this better skills and capacity utilization are also found to have positive impact on energy efficiency performance of industry. However, the potential heterogeneity within the structure of industry itself is found responsible for its higher energy intensity.

States should ensure and undertake substantial investment projects in the research and development of energy-efficient technology and that targeted allocations could be reinforced for more fruitful results. Factors aiming at improving the labour productivity should be given extra emphasis together with capital deepening and widening, needed for energy conservation and environmental sustainability. Given the dependence of structure of paper industry on the multitude of factors like regional inequality, economic growth, industrial structure and the resource endowment together with the issues of fragmented sizes, poor infrastructure and availability and affordability of raw materials etc., states should actively promote the coordination and cooperation among themselves to reap the benefits of technological advancements through technological spill overs. In addition, owing to their respective state autonomies, state governments should set their own energy saving targets by taking into account the respective potentials and opportunities for the different industries. Despite the requirement of energy-efficient innovations, however, the cons of technological advancements and the legal frameworks on the employment structure and distributional status should be taken care of before their adoption and execution.

To the best of our knowledge, this is the first study that empirically examines the linkage between energy efficiency and TFP in case of Indian paper industry. The application of improved methods like Levinsohn and Petrin (2003) to derive the TFP measure and the use of GMM-IV to account for potential econometric problems like that of endogeneity will again add to the novelty of study.

How do energy consumption, efficiency and economic performance vary between small enterprises belonging to two different product clusters whose production process and technologies differ?

The objectives are analyzed based on empirical data gathered from a field survey of small enterprises with reference to auto ancillaries in Shimoga and brick‐making enterprises in Malur of Karnataka State in India. Simple averages, correlation and multiple‐regression techniques are used for the analysis.

The study brought out that higher energy intensity results in higher share of energy cost in total variable cost. Energy intensity had a negative relationship with value of output. Energy makes a statistically significant contribution to returns to scale. The classification of small enterprises into two groups based on above average energy intensity and below average energy intensity, and the subsequent regression analysis brought out that energy intensity had a positive influence on returns to scale in auto ancillaries whereas a negative influence on returns to scale in bricks enterprises.

The sample‐size formulation could not be done on a scientific basis due to the absence of comprehensive data on all small enterprises operating in the respective clusters and therefore, the findings may not be generalized.

Industry specific characteristics must be taken into account while introducing “energy efficiency improvement” programmes as a means of enhancing competitiveness in “energy intensive” small enterprises.

The paper illustrates the scope for energy conservation and efficiency improvement in Indian small enterprises.

The need to improve energy efficiency as an essential factor for achieving the Sustainable Development Goals (SDGs) through green financing is one of the most important issues worldwide. It is even more important for ASEAN (Association of Southeast Asian Nations) countries because of their potential for economic growth and the challenge of their environmental problems. This paper therefore addresses the question of whether and how green finance (with the proxy of issued green bonds [GBs]) promotes energy efficiency (with the proxy of energy intensity) in the ASEAN member countries.

The paper runs a two-stage generalized method of moments (GMM) system model for the quarterly data over the period 2017–2020. It also uses a linear interaction model to explore how the pandemic may affect the relationship between green finance and energy efficiency in this region.

The main results only demonstrate the short-term negative impact of GBs on energy intensity. Furthermore, per capita income, economic integration and renewable energy supply can be used as potential variables to reduce energy intensity, while modernization in ASEAN increases energy intensity. Establishment of digital green finance, long-term planning of a green finance market, trade liberalization and policies to mitigate the negative impacts of COVID-19 are recommended as golden policy implications.

The present study has several limitations. First, it accounts for explanatory variables by following a number of previous studies. This may lead to omissions or errors. Second, the empirical estimates were conducted for 160 observations due to the repositioning of GBs in ASEAN, which is not bad but not good for an empirical study.

To the best of authors' knowledge, there has not been any in-depth study focusing on the relationship between energy efficiency and green financing for the case of ASEAN economies.

This paper aims to measure the state-level energy efficiency in Indian paper industry and simultaneously explain inter-state variation in efficiency by inefficiency effect model. Three variables, labor productivity, capital intensity and structure of paper industry, are included in inefficiency effect model to assess the likely impact on energy efficiency.

Sub-vector input distance function is derived through neo-classical production function which provides measures to estimate energy efficiency. Assuming a translog production function specification, energy efficiency is estimated by using Battese and Coelli (1995) stochastic frontier analysis (SFA). The authors also estimated four other SFA models, and energy efficiency from all the models is compared for robustness checking.

The results show the existence of a vast potential to improve energy efficiency. Inefficiency effect model reported a positive impact of structure of the industry and capital intensity on energy efficiency performance, while labor productivity does not have any significant impact on energy efficiency. There exists considerable energy efficiency variation among states. Uttarakhand, Punjab and Orissa are the best performing states while Rajasthan, Jharkhand and Goa have worst energy efficiency performance based on average efficiency. The ranks assigned to states according to inefficiency effects model are found contrary to the simple measure of energy efficiency, i.e. energy intensity. Thus, energy intensity may not always be a good proxy for underlying energy efficiency and need to be compared with a comprehensive possible measure.

To the best of the authors’ knowledge, this is the first study which measures energy efficiency of Indian paper industry through stochastic frontier model using region-level data. Instead of relying on traditional energy efficiency indicators (energy-output ratio), total-factor energy efficiency approach is used to conduct the empirical exercise. Deviations from the frontier because of factors beyond the scope of producers are also incorporated into analysis to portray the magnitude of random factors in influencing the efficiency performance.

This study aims to identify and analyse energy intensity in Indonesia’s manufacturing industry based on industrial sub-sector, island region, technology intensity, firm size, type of ownership and exporter status to determine which of these characteristics have the highest potential to decrease energy intensity.

Using firm characteristics data from statistics of large and medium industries in Indonesia, this study decomposed energy consumption of Indonesian firms into economic activity, economic structure and energy intensity for the period 2010–2014 through the logarithmic mean Divisia index (LMDI).

The results showed the decomposed energy intensity based on the six sub-categories. From the sub-categories, several characteristics which induced the most increases in energy intensity are highlighted. Several industrial sub-sectors were classified as highly energy-consuming, including rubber and plastic products, glass and non-metal mineral products, food, electrical machinery and apparatus, chemical, paper, motor vehicles and trailers and tobacco. Results from other sub-categories indicated that firms with high energy intensity were located in the Java--Bali region, had medium technology intensity and were exporters. Meanwhile, firm size and ownership type sub-categories did not show clear differences in energy intensity.

This study provides more focused policy recommendations for related policymakers and stakeholders to emphasise the most energy-inefficient and energy-intensive firm based on the results from each sub-category and hence policy priorities to reduce energy consumption can be well-targeted.

This study contributes to the field through a more thorough energy intensity analysis based on the classification of Indonesian firm characteristics to provide a more detailed insight on the cause of the ever-increasing energy intensity level in the country.

We examine the effect of firm ownership status on three environmentally relevant variables: energy efficiency, toxic emissions, and spending on pollution abatement. Prior research has demonstrated that public firms invest less than private firms and suggests this difference is due pressure from investors to strongly favor short over long-term earnings. We extend this logic to other firm behavior, examining whether publicly owned facilities invest in energy efficiency and pollution reduction differently than privately owned facilities. Using data from the US Census of Manufactures from 1980 to 2009, information on pollution from the Environmental Protection Agency Toxic Release Inventory (TRI) and pollution abatement spending from the Pollution Abatement Costs and Expenditures survey, we find that facilities switching to public ownership are less energy efficient and spend less on pollution abatement than their privately owned counterparts. However, we also find that facilities switching to public ownership have lower toxic emissions than other facilities. We also examine how different sources of external pressures alter these results and find that increased regulatory scrutiny is correlated with increased energy efficiency, toxic emissions, and abatement spending. More concentrated institutional ownership in public firms is associated with lower energy efficiency as is a greater brand focus. These latter results are broadly consistent with the idea that publicly owned firms respond to pressures from investors with a reduced focus on environmentally relevant variables. However, since facilities switching to public ownership have lower toxic emissions, this suggests that there are two competing pressures in publicly owned facilities: cost pressures, consistent with lowered energy efficiency, and public perceptions, consistent with lower toxic emissions, particularly since TRI data became available. In this sense, the combination of ownership and transparency of information appears to influence how firms prioritize different stakeholders.

This study aims to assess financial development and debt status impact on energy efficiency in Nigeria as a developing economy.

This study combined the autoregressive distributed lag (ARDL), fully modified ordinary least squares and canonical cointegration regression analytical methods to estimate the parameters for energy efficiency policy recommendations. Secondary data between 1990 and 2020 were used for the analysis.

The result confirms the long-run nexus between energy efficiency, financial development and total debt stock. Furthermore, the ARDL estimates for this study’s key variables show that financial development promotes energy efficiency in the short run but hinders long-run energy efficiency. Total debt stock limits energy efficiency in Nigeria in short- and long-run periods.

The limitation of this study is that the scope is limited to Nigeria as a developing economy. The need to support energy efficiency projects is a global call requiring cross-country analysis. Despite this study’s focus on Nigeria, it provides useful insights that can guide energy efficiency policy through the financial sector and debt management.

The financial sector must ensure the availability of long-term credit facilities to clean energy investors. The government must maintain a sustainable debt profile to pave the way for capital expenditure on clean energy projects that promote energy efficiency.

The environmental consequences of energy intensity are being felt globally, with the developing countries most vulnerable. The cheapest way to curb these consequences is to promote energy efficiency to reduce the disastrous effect. Driving energy efficiency requires investment in energy-efficient technology but the challenge for developing economies, i.e. Nigeria’s funding, remains challenging amid a blotted debt profile. This becomes crucial to investigate how financial sector development and debt management can accelerate energy-efficient investments in Nigeria.

Energy efficiency is critical for global sustainability (International Energy Agency, 2019). The purpose of this paper is to examine how agency conflicts arising from pyramidal ownership structures impact the energy intensity (EI) of group-affiliated Indian firms. Group-affiliated firms face unique governance challenges. For instance, parent owners (promoters) may transfer profits from one group-affiliated firm to another firm in which they have greater ownership. The authors hypothesize that such governance issues will lead to underinvestment in energy-saving projects among group firms in which promoters have a low ownership stake, resulting in their greater EI.

The authors measure EI as the ratio of total energy expense to total sales revenue (EI) and as the industry-adjusted version of this ratio. Group-affiliated Indian firms are divided into high- and low-stake firms based on the sample’s median promoter ownership.

Results support the authors’ prediction: group firms in which promoters have low ownership are more energy intensive, consistent with these firms being exposed to greater governance challenges and agency conflicts that result in operating inefficiencies and/or underinvestment in energy-saving projects.

Given energy efficiency will be key in addressing climate change, this study could raise awareness among activists, motivate regulators to consider agency problems among group-affiliated firms in emerging markets and may underscore the importance of environmental-related corporate disclosures.

To the best of the authors’ knowledge, this study is the first to identify the significant impact that firm ownership structure and associated governance challenges have on corporate EI.