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This paper aims to investigate whether all the dimensions of institutional pressures matter for energy management (EM) of manufacturing small and medium enterprises using evidence from Uganda.

This study used a cross-sectional design using evidence from 195 manufacturing small and medium enterprises in Uganda. The study was conducted by administering a questionnaire to obtain quantitative data which were analyzed using Smart Partial Least Square Structural Equation Modeling.

The findings revealed that two dimensions of institutional pressures (coercive and mimetic) positively and significantly predict EM, unlike normative pressures. Notable is that coercive pressures contribute more to EM than mimetic pressures.

This study uses a quantitative design; thus, future studies through interviews would offer more knowledge on EM. The government should reinforce regulations to achieve sustainable energy for all communities. Additionally, governments and industry associations should pay attention to the critical pressures (coercive and mimetic) to step up EM. Moreso, enterprise managers should comprehend government regulations and peers’ actions for effective EM.

This study contributes to EM literature by using institutional theory to examine the contribution of individual dimensions of institutional pressures to EM from the context.

This study aims to examine the challenges in the implementation of energy management systems in residential buildings to lower the running cost and achieve a better energy-efficient building.

This study adopted a mixed research method. Quantitative data was gathered by issuing a research questionnaire to 20 Delphi experts, while qualitative data was acquired through a Systematic Literature Review. Data received was analyzed using the descriptive analysis method.

The findings revealed that the main barriers to incorporating energy management systems (EMSs) in residential buildings consist of a lack of awareness of energy management systems, lack of management commitment to energy management, lack of knowledge about energy management systems, lack of funds for energy management systems, resistance to energy management technology by the property owners and property managers, distrust and resistance to energy management technology by the property owners, high initial cost of energy management technologies, shortage of technicians for energy management technologies, the nonexistence of local manufacturers of energy management equipment, lack of incentives for efficient energy management and high repair costs of energy management technologies.

The specific focus on residential buildings may limit the applicability of findings to commercial or industrial sectors. Further research is warranted to accommodate other energy-consuming sectors.

People’s perceptions, either wrong or correct, affect their ability to make an informed decision to adopt energy management systems, denying them the opportunity to reap the associated benefits. Therefore, there is an urgent need for the residential industry stakeholders and the government to increase educational opportunities for property owners, managers and property tenants on the importance of energy management systems.

This research presents the potential obstacles and problematic areas that residents may encounter while using these energy management systems. Consequently, they will be able to make a well-informed choice when installing energy management systems. Moreover, the research elucidates the identification of novel perspectives and also unexamined obstacles that impede the widespread use of energy management systems in residential buildings.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

This paper addresses the challenges associated with forecasting electricity consumption using limited data without making prior assumptions on normality. The study aims to enhance the predictive performance of grey models by proposing a novel grey multivariate convolution model incorporating residual modification and residual genetic programming sign estimation.

The research begins by constructing a novel grey multivariate convolution model and demonstrates the utilization of genetic programming to enhance prediction accuracy by exploiting the signs of forecast residuals. Various statistical criteria are employed to assess the predictive performance of the proposed model. The validation process involves applying the model to real datasets spanning from 2001 to 2019 for forecasting annual electricity consumption in Cameroon.

The novel hybrid model outperforms both grey and non-grey models in forecasting annual electricity consumption. The model's performance is evaluated using MAE, MSD, RMSE, and R², yielding values of 0.014, 101.01, 10.05, and 99% respectively. Results from validation cases and real-world scenarios demonstrate the feasibility and effectiveness of the proposed model. The combination of genetic programming and grey convolution model offers a significant improvement over competing models. Notably, the dynamic adaptability of genetic programming enhances the model's accuracy by mimicking expert systems' knowledge and decision-making, allowing for the identification of subtle changes in electricity demand patterns.

This paper introduces a novel grey multivariate convolution model that incorporates residual modification and genetic programming sign estimation. The application of genetic programming to enhance prediction accuracy by leveraging forecast residuals represents a unique approach. The study showcases the superiority of the proposed model over existing grey and non-grey models, emphasizing its adaptability and expert-like ability to learn and refine forecasting rules dynamically. The potential extension of the model to other forecasting fields is also highlighted, indicating its versatility and applicability beyond electricity consumption prediction in Cameroon.

Informal settlements are frequently located in hazardous areas with a high risk of natural disasters. Upgrading informal settlements can be difficult due to the time and expense needed to complete the process. This chapter advocates using a management framework of public services in informal settlements. In doing so, it addresses 17 of the 17 UN sustainable development goals (SDGs). The study reviewed the literature to investigate current ways of managing environmental enterprises in informal settlements in South Africa. Thereafter, the challenges of managing public services were explored, and a conceptual framework for managing public services by social enterprises in such communities was developed. The chapter found that environmental enterprises are classified as ‘green spaces’ and infrastructure, water and sanitation services, energy systems, and recycling initiatives. Essential aspects of sustainable community-based facilities management (SCbFM) for managing public services are maintenance, governance, community project management, environment service delivery, service performance, governance, community project management, environment service delivery, service performance, well-being and health and safety, disaster management, and finance. Some of the problems of managing public services in informal settlements include the limited skills of managers, the focus of government on new projects rather than managing existing projects, not choosing the right indicators to measure service performance, and limited guidelines for the health and safety of managers and disaster management. Thus, a new conceptual framework was needed and developed based on the principles of social capital and capability for managing services in informal settlements in South Africa.

The current movement toward digitisation has promoted the adoption of smart building technology globally. Despite its advantages, its usage in developing countries such as Nigeria is still very low. Therefore, the purpose of this paper is to investigate construction professionals' awareness of smart building concepts (SBCs) in the Nigerian construction industry and identify the parameters by which SBCs can be measured.

A quantitative survey was carried out using a questionnaire to gather relevant data in the study area. This paper was conducted on 363 registered construction professionals in the Nigerian construction industry. The collected data were analysed using descriptive statistics and Kruskal–Wallis H test analysis.

This paper indicated that the majority of Nigerian construction professionals are aware of SBCs. Furthermore, the Kruskal–Wallis H test shows no significant difference between the awareness level of the various construction professionals. This paper further revealed energy management systems, IT network connectivity, safety and security management systems and building automation systems as the most significant parameters in which SBCs can be measured.

This paper identified significant parameters influencing SBCs awareness in the Nigerian construction industry. These parameters can be integrated into the building during the design stage and can be incorporated into the policymaking process of construction firms to promote the awareness of SBCs and encourage practices related to construction sustainability.

This paper provides empirical evidence on the awareness of SBCs among construction professionals and significant parameters influencing awareness in the Nigerian construction industry.

Many industries use non-Newtonian ternary hybrid nanofluids (THNF) because of how well they control rheological and heat transport. This being the case, this paper aims to numerically study the Casson-Williamson THNF flow over a yawed cylinder, considering the effects of several slips and an inclined magnetic field. The THNF comprises Al₂O₃-TiO₂-SiO₂ nanoparticles because they improve heat transmission due to large thermal conductivity.

Applying suitable nonsimilarity variables transforms the coupled highly dimensional nonlinear partial differential equations (PDEs) into a system of nondimensional PDEs. To accomplish the goal of achieving the solution, an implicit finite difference approach is used in conjunction with Quasilinearization. With the assistance of a script written in MATLAB, the numerical results and the graphical representation of those solutions were ascertained.

As the Casson parameter β increases, there is an improvement in the velocity profiles in both chord and span orientations, while the gradients Re1/2Cf, Re1/2C¯f reduce for the same variations of β. The velocities of Casson THNF are greater than those of Casson-Williamson THNF. Approximately, a 202% and a 32% ascension are remarked in the magnitudes of Re1/2Cf and Re1/2C¯f for Casson-Williamson THNF than the Casson THNF only. When velocity slip attribute S1 jumps to 1 from 0.5, magnitude of both F(ξ,η) and Re1/2Cf fell down and it is reflected to be 396% at ξ=1, Wi=1 and β=1. An augmentation in thermal jump results in advanced fluid temperature and lower Re−1/2Nu. In particular, about 159% of down drift is detected when S2 taking 1.

There is no existing research on the effects of Casson-Williamson THNF flow over a yawed cylinder with multiple slips and an angled magnetic field, according to the literature.

The aim of this research is to elucidate the correlation between open innovation, digital strategies and networking in enhancing agricultural enterprises within the new perspective of Agrifood 5.0. As such, it contributes to making businesses more competitive, especially in the Italian agricultural sector, where small and medium-sized enterprises are highly fragmented. Numerous studies have asserted that the competitiveness of actors operating within a specific territory is closely linked to local identity and image enhancement. Agricultural organizations are undergoing a profound transformation, with technological assets emerging as catalysts for new synergies. Advanced technologies such as robotics, the Internet of Things (IoT) and automation (AI) are emerging as differentiating elements capable of further advancing the agricultural sector, transitioning it from Agrifood 4.0 to Agrifood 5.0. The empirical analysis of the research shows a positive correlation between a collaborative attitude and a propensity for innovation. Indeed, the data demonstrated that digital strategies and open innovation positively influence competitiveness in agricultural SMEs.

The methodology employed in this study is mixed, incorporating both qualitative and quantitative approaches. The quantitative aspect involves analysis of the dataset from the Italian Statistical Institute (ISTAT) through logistic regression, while the qualitative component entails analysis of semi-structured interviews conducted with a sample of 174 agricultural cooperatives in southern Italian regions (Campania). This approach allows for a comprehensive understanding of the research topic, capturing both numerical trends and nuanced insights from interviews.

After analyzing the data from the 7th General Census of Agriculture conducted by ISTAT, a clear understanding of the sector has emerged, revealing several potential research avenues. It is evident that innovation in the agricultural sector is often driven by the largest and best-capitalized production entities, primarily located in Italy. Conversely, smaller agricultural entities can benefit from networking as new technological assets act as catalysts for new synergies, innovation and competitiveness.

Enhancing the relational contribution within the network and humanizing a fragmented sector are crucial elements for promoting open innovation. Network structuring facilitates the transmission of managerial knowledge, contributing to an overall increase in the intellectual and relational capital of the agricultural sector. These factors, combined with open innovation, enhance the competitiveness of individual firms and elevate the brand of the entire sector, creating a conducive environment for transitioning toward Agrifood 5.0. This transition is characterized by increased interconnection, continuous innovation and overall prosperity. Specific studies on this topic are lacking in Italy, particularly in the southern regions. Therefore, this contribution focuses on investigating the Campania region.

The novelty of this study lies in its investigation of the relationship between agricultural enterprises and innovation in the context of enterprises networking strategies (i.e. associationism and/or cooperation), promoting competitiveness. The limitations of this study are related to the dimension of the sample selected and its relationship with other productive sectors.

The Recast Energy Efficiency Directive 2023 has defined the concept of “split incentive,” also known as “tenant-owner dilemma.” This dilemma refers to the situation where neither landlords nor tenants have incentives to invest in energy efficiency upgrades. Although the Energy Efficiency Directive calls Member States to overcome legal barriers to remove split incentives and to encourage retrofits, the list of possible measures is too vague. This paper aims to discuss tenancy law measures designed to increase the energy efficiency of residential housing and to detect which Member States have already addressed this phenomenon.

This paper analyses, from a civil legal perspective, the possible private law barriers arising from the tenant-owner dilemma when performing energy efficiency works in selected countries and proposes legal reforms in tenancy law and related policies to overcome them. To do so, this paper follows a legal-dogmatic and comparative law methodology.

This paper concludes that some tenancy law provisions, such as the possibility to increase the rent after energy efficiency renovations and long-term leases, may challenge the tenant-owner dilemma in private rented markets, thus promoting renovations and retrofitting for energy efficiency purposes. It also proposes other policies intended to increase parties’ willingness to undertake works.

More research on the economic and legal efficiency to regulate some of the civil law measures to challenge the tenant-owner dilemma should be necessary.

The civil law measures included in this paper may help national policymakers meet the energy efficiency targets, according to what is established in the Recast Energy Efficiency Directive 2023.

Based on the economic theory of the tenant-owner dilemma, this paper investigates the elements of tenancy law that may contribute to less energy-efficient homes, proposing policies for those countries interested in addressing the energy-efficiency challenge from a private law point of view.

The purpose of this study is to investigate and analyse the potential of existing buildings in the UK to contribute to the net-zero emissions target. Specifically, it aims to address the significant emissions from building fabrics which pose a threat to achieving these targets if not properly addressed.

The study, based on a literature review and ten (10) case studies, explored five investigative approaches for evaluating building fabric: thermal imaging, in situ U-value testing, airtightness testing, energy assessment and condensation risk analysis. Cross-case analysis was used to evaluate both case studies using each approach. These methodologies were pivotal in assessing buildings’ existing condition and energy consumption and contributing to the UK’s net-zero ambitions.

Findings reveal that incorporating the earlier approaches into the building fabric showed great benefits. Significant temperature regulation issues were identified, energy consumption decreased by 15% after improvements, poor insulation and artistry quality affected the U-values of buildings. Implementing retrofits such as solar panels, air vents, insulation, heat recovery and air-sourced heat pumps significantly improved thermal performance while reducing energy consumption. Pulse technology proved effective in measuring airtightness, even in extremely airtight houses, and high airflow and moisture management were essential in preserving historic building fabric.

The research stresses the need to understand investigative approaches’ strengths, limitations and synergies for cost-effective energy performance strategies. It emphasizes the urgency of eliminating carbon dioxide (CO₂) and greenhouse gas emissions to combat global warming and meet the 1.5° C threshold.