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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.

Organic food has additional quality attributes compared to those found in conventional food, such as environmental responsibility and health benefits. Information about these attributes is scarce and complex, the assortment of organic foods is deficient and there are fewer places that sell this kind of food. These factors increase the uncertainty and the transaction costs (TCs) for potential organic fresh fruit and vegetable (FFV) consumers. This paper aims to show the influence of these costs on the intensity of organic FFV consumption, particularly among high-income consumers.

The empirical strategy was based on a survey, and data were collected by administering a structured online questionnaire among residents of the Brazilian Federal District. Organic food consumption was decomposed into three different intensity categories. Data analysis was based on two logistic models, a multinomial regression and an ordered regression, where perceived economic value and different dimensions of TCs were the main independent variables, and the intensity of organic food consumption was the dependent variable.

The results show that organic food consumers are not a homogeneous group, and that perceived economic value and the TCs associated with searching for marketplaces, inadequate product assortment and distrust in health benefits and in organic authenticity are important inhibitors of organic FFV consumption and help explain the intensity of consumption.

This study innovates, as it takes a post-purchase approach, examines different groups based on the intensity of their consumption of organic FFV and focuses on perceived economic value and TCs as important explanations of the intensity of organic FFV consumption.

The calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type, there is currently no model that considers the time factor to accurately calculate the CFP of hospital building throughout their life cycle. This paper aims to establish a CFP calculation model that covers the life cycle of hospital building and considers time factor.

On the basis of field and literature research, the basic framework is built using dynamic life cycle assessment (DLCA), and the gray prediction model is used to predict the future value. Finally, a CFP model covering the whole life cycle has been constructed and applied to a hospital building in China.

The results applied to the case show that the CO₂ emission in the operation stage of the hospital building is much higher than that in other stages, and the total CO₂ emission in the dynamic and static analysis operation stage accounts for 83.66% and 79.03%, respectively; the difference of annual average emission of CO₂ reached 28.33%. The research results show that DLCA is more accurate than traditional static life cycle assessment (LCA) when measuring long-term objects such as carbon emissions in the whole life cycle of hospital building.

This research established a carbon emission calculation model that covers the life cycle of hospital building and considered time factor, which enriches the research on carbon emission of hospital building, a special and extensive public building, and dynamically quantifies the resource consumption of hospital building in the life cycle. This paper provided a certain reference for the green design, energy saving, emission reduction and efficient use of hospital building, obviously, the limitation is that this model is only applicable to hospital building.

This paper presents a cross‐cultural study of organic food consumption. Relationships between health and diet concern, environmental concern, confidence in the conventional food industry, demographic characteristics, and intensity of organic food consumption of consumers from Denmark (mature organic industry) and New Zealand (novice organic food industry) are investigated. The authors evaluate the adequacy of deficit value and market development conceptual frameworks to predict priority of these concerns related to the level of organic market development.

The quest for economic development has brought adverse effects on the environment through the release of greenhouse gases, such as carbon dioxide (CO₂₎. This will counter the efforts to achieve the Sustainable Development Goals (SDGs) by 2030. This study, therefore, investigates the effect of electricity consumption and urbanization on CO₂ emissions in Ghana. Electricity consumption and urbanization are among the factors that can be used to reduce CO₂ emissions.

Following the STIRPAT framework with the Hansen (2000) least squares threshold estimation strategy, the study employed annual time series data from 1971 to 2019.

The study revealed a single threshold effect of both electricity consumption and urbanization on CO₂ emissions. Electricity consumption intensity reduces CO₂ emission when electricity consumption is below the threshold (6287GWh) but increases when consumption passes the threshold. However, urbanization exerts a positive influence on CO₂ emissions regardless the level of urbanization (either before or after the threshold point). Again, the empirical results revealed that the urbanization threshold moderates the effect of electricity consumption on CO₂ emissions.

Policymakers have to consider redesigning the current urbanization mode to include some new-type urbanization elements.

The threshold effect of electricity consumption and urbanization on CO₂ emissions in Ghana is examined using the Hansen (2000) least square method.

On the basis of corporate wholesale and hypermarket stores, this study aims to investigate the relationship between energy consumption, physical building characteristics and operational sales performance and the impact of energy management on the corporate environmental performance.

A very unique dataset of METRO GROUP over 19 European countries is analyzed in a sophisticated econometric approach for the timeframe from January 2011 until December 2014. Multiple regression models are applied for the panel, to explain the electricity consumption of the corporate assets on a monthly basis and the total energy consumption on an annual basis. Using Generalized Additive Models, to model nonlinear covariate effects, the authors decompose the response variables into the implicit contribution of building characteristics, operational sales performance and energy management attributes, under control of the outdoor weather conditions and spatial–temporal effects.

METRO GROUP’s wholesale and hypermarket stores prove significant reductions in electricity and total energy consumption over the analyzed timeframe. Due to the implemented energy consumption and carbon emission reduction targets, the influence of the energy management measures, such as the identification of stores associated with the lowest energy performance, was found to contribute toward a more efficient corporate environmental performance.

In the context of corporate responsibility/sustainability of wholesale, hypermarket and retail corporations, the energy efficiency and reduction of carbon emissions from corporates’ real estate assets is of emerging interest. Besides the insights about the energy efficiency of corporate real estate assets, the role of the energy management, contributing to a more efficient corporate environmental performance, is not yet investigated for a large European wholesale and hypermarket portfolio.

The main purpose of this paper is to empirically investigate the effect of macroeconomic uncertainty on environmental degradation in India over the period 1971–2016. Additionally, this paper considers the role of financial development, energy consumption intensity and economic growth in explaining the variation of environmental degradation in India.

The authors applied the power generalized autoregressive conditional heteroskedasticity model to measure inflation volatility and used it as a proxy for macroeconomic uncertainty. From a methodological perspective, the authors employ the autoregressive distributive lag bound testing model to establish the long-run equilibrium association between the variables. The Toda–Yamamoto causality approach has been used to examine the direction of causality between the variables.

Findings suggest that macroeconomic uncertainty exerts a positive effect on carbon emissions, indicating that higher inflation volatility, as a proxy for macroeconomic uncertainty, hinders India's environmental quality. Financial development, economic growth and energy consumption intensity have also adversely impacted environmental quality.

The negative association between macroeconomic uncertainty and environmental degradation calls for some stringent policy actions. While formulating policies to promote growth and maintain stability, policymakers and government stakeholders should take into account the environmental effects of macroeconomic policies. There is a need to implement more environmental-friendly technologies in the financial sector that could reduce carbon emission.

To the best of the authors' knowledge, this study is the first that considers the role of macroeconomic uncertainty along with financial development and energy intensity in an emerging economy like India.

Growing food insecurity is a leading cause of fatalities, particularly in developing nations like Sub-Saharan Africa and Southeast Asia. However, the rising energy consumption and carbon dioxide (CO2) emissions are mostly associated with food production. Balancing the trade-offs between energy intensity and food security remains a top priority for environmentalists. Despite the critical role of the environment in food security, there is a scarcity of substantial studies that explore the statistical connections among food security, CO2 emissions, energy intensity, foreign direct investment (FDI) and per capita income. Therefore, this study aims to provide more precise and consistent estimates of per capita CO2 emissions by considering the interplay of food security and energy intensity within the context of emerging economies.

To examine the long-term relationships between CO2 emissions, food security, energy efficiency, FDI and economic development in emerging economies, this study employs correlated panel-corrected standard error, regression with Newey–West standard error and regression with Driscoll–Kraay standard error models (XTSCC). The analysis utilizes data spanning from 1980 to 2018 and encompasses 32 emerging economies.

The study reveals that increasing food security in a developing economy has a substantial positive impact on both CO2 emissions and energy intensity. Each model, on average, demonstrates that a 1 percent improvement in food security results in a 32% increase in CO2 levels. Moreover, the data align with the Environmental Kuznets Curve (EKC) theory, as it indicates a positive correlation between gross domestic product (GDP) in developing nations and CO2 emissions. Finally, all experiments consistently demonstrate a robust correlation between the Food Security Index (FSI), energy intensity level (EIL) and exchange rate (EXR) in developing markets and CO2 emissions. This suggests that these factors significantly contribute to environmental performance in these countries.

This study introduces novelty by employing diverse techniques to uncover the mixed findings regarding the relationship between CO2 emissions and economic expansion. Additionally, it integrates energy intensity and food security into a new model. Moreover, the study contributes to the literature by advocating for a sustainable development goal (SDG)-oriented policy framework that considers all variables influencing economic growth.

Purpose – Religion is an important driving force behind many lifestyle decisions. Therefore, it is surprising that research on cultural consumption and stratification has linked religion and religiosity with consumption patterns only to a limited degree. In this chapter, we outline several theoretical directions that can be used for studying the link between religion, religiosity, and cultural consumption and the consequences of this link for cultural stratification.

Design/Methodology/Approach – Our empirical analysis is based on data from the International Social Survey Programme (ISSP), conducted in 2007 and pertaining to samples from 33 countries.

Findings – We present cross-national evidence illustrating that, first, there is a positive correlation between religiosity and cultural consumption in many countries and, second, there is little evidence that religion is significantly linked to cultural consumption. Furthermore, we find that the effect of religiosity on cultural consumption is comparable to that of important socioeconomic factors such as education and socioeconomic status. We offer three possible explanations to the findings. First, that religious individuals tend to be active individuals; therefore, they go more often to religious services and they are active also in cultural participation. Second, a certain level of religiosity affects cultural consumption by setting standards for the intensity of social ties. Third, religiosity plays a central role in marking boundaries of cultural distinction. In the last part of the chapter, we delineate motivations for further research interest in the link between religion and cultural consumption and discuss possible avenues for the development of such research.

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.