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Understanding the antecedents of biomass heating adoption by domestic users is important for both public authorities and businesses because of the impact of this technology on energy consumption. The purpose of this study offers an overview of the predictors of biomass adoption based on the most relevant theories, gleaned from pro-environmental decision-making research.

The proposed model was tested using the partial least squares technique. The study was conducted with a sample of 528 owners of detached houses who did not use biomass technology.

The results showed that intention to adopt this type of heating system is determined by individual values, environmental concerns, attitudes, perceived control, personal and social norms, perceptions of the technology’s attributes, of the benefits of biomass and access to economic aid.

Companies in the biomass heating sector (manufacturers, installers, biomass producers and distributors) and public bodies should take a proactive approach toward the economic and environmental situations they currently face.

Economic aid or subsidies should be made available to influence the adoption intention of potential owners; and the availability of the aid and the requirements that must be met to access, it should be publicized through advertisement campaigns.

This study includes comprehensive academic and managerial implications crucial for the introduction of domestic biomass heating systems.

Energy security is a major concern for India and many rural areas remain un-electrified. Thus, innovations in sustainable technologies to provide energy services are required. Biomass and solar energy in particular are resources that are widely available and underutilised in India. This paper aims to provide an overview of a methodology that was developed for designing and assessing the feasibility of a hybrid solar-biomass power plant in Gujarat.

The methodology described is a combination of engineering and business management studies used to evaluate and design solar thermal collectors for specific applications and locations. For the scenario of a hybrid plant, the methodology involved: the analytical hierarchy process, for solar thermal technology selection; a cost-exergy approach, for design optimisation; quality function deployment, for designing and evaluating a novel collector – termed the elevation linear Fresnel reflector (ELFR); and case study simulations, for analysing alternative hybrid plant configurations.

The paper recommended that for a hybrid plant in Gujarat, a linear Fresnel reflector of 14,000 m2 aperture is integrated with a 3 tonne per hour biomass boiler, generating 815 MWh per annum of electricity for nearby villages and 12,450 tonnes of ice per annum for local fisheries and food industries. However, at the expense of a 0.3 ¢/kWh increase in levelised energy costs, the ELFR can increase savings of biomass (100 t/a) and land (9 ha/a).

The research reviewed in this paper is primarily theoretical and further work will need to be undertaken to specify plant details such as piping layout, pump sizing and structure, and assess plant performance during real operational conditions.

The paper considers the methodology adopted proved to be a powerful tool for integrating technology selection, optimisation, design and evaluation and promotes interdisciplinary methods for improving sustainable engineering design and energy management.

The aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.

Fuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.

Digital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.

This study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

The central suggestion of this paper is that innovation in the concept of entrepreneurship is overdue and that the concept of entrepreneurship needs to be extended to accommodate its often neglected collective or pluralistic dimension, a concept termed “associative entrepreneurship”. It has also been argued that there may be a natural link between sustainability and the co‐operative form. In this paper these themes are drawn together by considering the entrepreneurial potential expressed by the recent creation of mutual businesses in a range of renewable energy sectors in Wales. It is suggested that, at least in the renewable energy sector and perhaps in other sectors too, innovation in the direction of sustainability may require a development of the concept of entrepreneurship in the direction of mutualism.

The paper takes the form of a theoretical discussion focusing around seven preliminary case studies.

As yet only a cluster of community‐based enterprises have been discovered in the renewable energy sector in Wales. The authors propose to study them in detail in the next stage of the research.

This is a developmental paper and many of its suggestions require rigorous testing. The authors would suggest that detailed case studies of the seven examples of associative enterprise in the renewable energy field outlined here, and others which may emerge during the research, would greatly enhance our understanding of what drives entrepreneurs in this field. Further research might also compare these examples with others organised according to more traditional business models.

In view of the urgent need to move towards a low‐carbon economy and the expansion of the renewable energy sector this would require, understanding of the motivations of entrepreneurs in this sector is of great value.

Innovation in the renewable energy sector may be being held back by the limitations of the concept of entrepreneurship.

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.

Municipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.

The findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.

This article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.

This study aims to introduce the results of a research carried out to develop a prototype of a highly energy-efficient modular detached house, called CASA+ CASA means HOUSE in spanish, adapted to the climatic features of central-southern Chile. The project enables a sustainable alternative to facilitate the reconstruction of the residential areas after the impact of the 2010 earthquake.

The methodology is based on an “integrated design process” of a case study that proposes a constructive response that quantitatively and qualitatively improves the initial data of traditional dwellings. The characteristics of the new system have been simulated with specific software to validate the final decisions, considering the cost–benefit ratio.

Simulation tools were used to assess and improve the system’s energy performance with respect to present options and to analyse its economic and construction viability. We obtained several economically competitive housing prototypes that substantially reduced energy consumption and the CO₂ footprint by between 20% and 80%.

The prototype has not been developed, as we are waiting for funding, but all its energy features have been simulated.

Furthermore, this experience also identified similar modifications made to the design of the houses, which revealed general possibilities for improving energy performance.

The origin of this research is a public call for international researchers to improve the quality of the new homes to be built in Chile after the strong earthquake of 2010. The result of the research has been put at the direct service of Chilean society and in other international projects for the construction of low-energy social housing.

These are the result of a long research aimed at establishing a new architectural model that, in addition to improving the architectural quality of the product, obtains significant improvements in energy consumption and CO₂ emissions. The most particular aspect is the practical vocation and its implementation with real construction with the support of construction companies.

The purpose of this paper is to show three principal aims – to highlight the gap in the international energy efficiency and carbon emission targets in relation to existing commercial real estate; to examine the contribution that such legacy stock could make to the various targets; and to provide commentary on some of the measures that are being introduced to support sustainable refurbishment in the legacy stock.

The paper critically reviews recent academic, policy and practitioner publications.

The international sustainability agenda is being driven through via a “top‐down” approach. Targets are largely concentrated on new‐build provision and there is a limited focus on existing stock. The annual rate of replacement of commercial sector stock is minimal. Unless the existing commercial stock is addressed in a meaningful way, other measures used to address anthropogenic climate change will be undermined.

The paper offers an applied examination of the potential of the existing stock of commercial real estate to contribute toward achieving targeted energy efficiency and carbon dioxide reduction targets.

The purpose of this paper is to outline an integrative modelling approach that includes agricultural and forestry process chains in an energy system model, on a regional scale. The main focus is on land use for biomass production, aimed at satisfying the demands for energy, food, and materials.

The described model combines geographic modelling with a linear optimisation approach. The cost‐based optimisation of the energy system includes agricultural and forestry process chains. The system's commodities and processes are identified and these are linked appropriately in the specifications of the reference system. Spatial models provided geographically specific input data for the optimisation; these spatial models were based on publicly available data, regional heat and electricity demands, and regional biomass potentials. The optimisation tool was applied in two case studies.

The optimisation results allow an improved understanding of the interdependencies between regional agricultural and forestry structures and the regional energy system. Future developments of the energy system can be quantified. The application of the model in the case studies has revealed the limits on biomass availability, even in rural areas, and the fossil fuel price sensitivity of an optimal system setup.

Geographic models linked to a forecast model approach and based on publicly available data allow a high spatial resolution by taking into account the region‐specific conditions and mean that the modelling approach is transferrable to other regions. This paper provides an initial insight into the linkage between bottom‐up optimisation and spatial modelling, representing an innovative approach that is yet to be well explored.