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This study aims to compare and evaluate the application of commonly used machine learning (ML) algorithms used to develop models for assessing energy efficiency of buildings.

This study foremostly combined building energy efficiency ratings from several data sources and used them to create predictive models using a variety of ML methods. Secondly, to test the hypothesis of ensemble techniques, this study designed a hybrid stacking ensemble approach based on the best performing bagging and boosting ensemble methods generated from its predictive analytics.

Based on performance evaluation metrics scores, the extra trees model was shown to be the best predictive model. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method. Finally, it was discovered that stacking is a superior ensemble approach for analysing building energy efficiency than bagging and boosting.

While the proposed contemporary method of analysis is assumed to be applicable in assessing energy efficiency of buildings within the sector, the unique data transformation used in this study may not, as typical of any data driven model, be transferable to the data from other regions other than the UK.

This study aids in the initial selection of appropriate and high-performing ML algorithms for future analysis. This study also assists building managers, residents, government agencies and other stakeholders in better understanding contributing factors and making better decisions about building energy performance. Furthermore, this study will assist the general public in proactively identifying buildings with high energy demands, potentially lowering energy costs by promoting avoidance behaviour and assisting government agencies in making informed decisions about energy tariffs when this novel model is integrated into an energy monitoring system.

This study fills a gap in the lack of a reason for selecting appropriate ML algorithms for assessing building energy efficiency. More importantly, this study demonstrated that the cumulative result of ensemble ML algorithms is usually always better in terms of predicted accuracy than a single method.

The aim of this paper is to discuss a selection of policy strategies, regional initiatives and market approaches to uncover the realities of twenty-first-century building energy performance. A position that market-based approaches, human influence and policy interventions are part of an ecosystem of building energy performance is presented.

An exploratory search of secondary sources spanning the last three decades was conducted. Both peer-reviewed and grey literature were included to capture a broader understanding of the discourse in literature. Research questions guided the literature search, and a data extraction tool was designed to categorise the literature. The primary limitation of this study is that only a few applications could be discussed in a condensed format.

Several challenges about the current status quo of building energy performance were identified and summarised as follows. (1) Inconsistencies in measurement and verification protocols, (2) Impacts of market approaches, (3) National policy priorities that are at variance with regional targets and (4) Ambiguous reporting on environmental impacts of energy efficiency (EE) technologies.

The practical implications of the findings in this paper for practice and research are that as part of the building energy performance ecosystem, national responses through government interventions must become adaptive to keep up with the fast-paced energy sector and social trends. Simultaneously, before market-based approaches overcome the messiness of socio-economic dynamics, institutional conditions and cultural nuances, they ought to transparently address environmental impacts and the infringement of several SDGs before they can become viable solutions to building energy performance.

This paper presents building energy performance as an ecosystem comprising human influence, market-based approaches and policy interventions which form interdependent parts of the whole. However, evidence in the literature shows that these aspects are usually investigated separately. By presenting them as an ecosystem, this paper contributes to the discourse by advocating the need to re-align building energy performance to socio-economic-political dynamics and contextually viable solutions.

Extant studies have discussed numerous carbon reduction drivers, but there is a dearth of holistic review and understanding of the dynamic interrelationships between the drivers from a system perspective. Thus, this study aims to bridge that gap.

The study conducted a review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses and adopted interpretive structural modelling (ISM) to analyse and prioritise the drivers.

Eighteen drivers were identified and grouped into five, namely, policy instruments, bid-related, cost and risk, education and training, and reward and penalty drivers. The ISM revealed two hierarchical levels of the drivers with only higher cost of electricity/fuel on the higher level, making it the most important driver that could influence others.

The study presents an overview of decarbonisation drivers in the literature and would be of benefit to the government and stakeholders towards achieving net zero emissions in the construction industry.

The findings of the study present drivers of carbon reduction and prioritise and categorise them for tailored interventions within the construction sector. Also, it could serve as foundational knowledge for further study in the construction process decarbonisation research area.

This study aims to investigate the intricate relationships between a community energy system, water resources and biodiversity conservation, with a specific focus on augmenting community energy resilience in Bondo. The primary objective is to gain an in-depth understanding of how community members perceive and experience the challenges related to balancing the often-conflicting demands of energy, water and biodiversity conservation within this context.

The research uses a qualitative approach to unravel the multifaceted dynamics of community energy systems, water resources and biodiversity conservation in Bondo. Data were collected through focus groups and direct observations, enabling a nuanced exploration of community perspectives and lived experiences. The subsequent analysis of this qualitative data follows established thematic analysis procedures.

The study's findings shed light on the formidable barriers that impede rural communities in Malawi from accessing electricity effectively. Even in communities fortunate enough to have electricity connections, the lack of knowledge regarding productive electricity use results in community energy systems operating at significantly reduced load factors. Furthermore, the intricate challenge of managing a biodiversity hotspot persists, exacerbated by the densely populated peripheral communities' continued reliance on forest, land and water resources. These activities, in turn, contribute to ecosystem degradation.

In a context where government-led management of forest reserves and game reserves has not yielded the expected results due to a multitude of factors, there arises a compelling need for innovative approaches. One such innovation involves fostering partnerships between the government and experienced trusts as lead organisations, providing a fresh perspective on addressing the complex interplay between community energy systems, water resources and biodiversity conservation. This novel approach opens doors to explore alternative pathways for achieving the delicate balance between human energy needs and the preservation of vital ecosystems.

The Gulf Cooperation Council (GCC) of countries has some of the highest electricity consumptions and carbon dioxide emissions per capita in the world. This poses a direct challenge to the GCC government’s ability to meet their CO₂ reduction targets. In this review paper the current household electricity consumption situation in the GCC is reviewed.

Three scenarios for reducing energy consumption and CO₂ emissions are proposed and evaluated using strengths, weaknesses, opportunities and threats (SWOT) as well as the political, economic, social, technical, legal and environmental (PESTLE) frameworks.

The first scenario found that using solar Photovoltaic (PV) or hybrid solar PV and wind system to power household lighting could save significant amounts of energy, based on lighting making up between 8% to 30% of electricity consumption in GCC households. The second scenario considers replacement of conventional appliances with energy-efficient ones that use around 20% less energy. The third scenario looks at influencing consumer behavior towards sustainable energy consumption.

Pilot trials of these scenarios are recommended for a number of households. Then the results and feedback could be used to launch the schemes GCC-wide.

The proposed scenarios are designed to encourage responsible electricity consumption and production within households (SDG12).

All three proposals are found viable for policymakers to implement. However, to ensure successful implementation GCC Governments are recommended to review all the opportunities and challenges associated with these schemes as laid out in this paper.

This paper aims to focus on the assessment of a domestic property's energy performance status by a domestic energy assessor (DEA), to ascertain the possible underlying reasons for variability in the results of Energy Performance Certificates (EPCs). By variability, the authors mean discrepancies in assessment between different DEAs on similar properties. This is important because the uses for the EPC have been extended beyond their original function as an asset rating system, to include themes encompassing building policy decisions, building performance and the distribution of incentives and grants. Consequently, inaccuracies in EPC reporting will have a greater impact than may have been the case at the outset.

A case study approach involving the conducting of semi-structured interviews with 20 practicing DEAs was carried out, with transcribed recordings of the interview material subjected to thematic analysis. This formed part of a wider mixed methods study.

The results identify a wide range of underlying reasons for variability driven by issues in both practice and process, including conflicts of interests, the EPC auditing process, the default inputting of missing data by RdSAP where information may not be available/discoverable by the DEA, the quality and perception of EPCs and DEA training and experience.

The sample size of 20 is by definition limiting, and it is possible that different results would have been obtained from a different sample. Although thematic saturation from the analysis of the responses on the key question of whether EPCs are considered variable does mitigate this. The respondents were all in possession of five years or more experience and of carrying out EPCs for different purposes. Less experienced DEAs may inevitably have responded to questions differently. The thematic analysis gives the researcher control over the presentation of the results, and it is noted that this creates a potential for bias. The researcher is immersed in the world of construction and property, with regular contact with DEAs and EPCs, which may influence the perspective of the results.

The research identifies risks to the accuracy of EPCs. To this end, and with the specific research findings in mind, this research may be of interest to construction professionals with respect to EPC practice and procurement, to the Accrediting Bodies who audit EPCs, to the creators of RdSAP with respect to automated EPC inputs, to academics either at face value or for use in further research and to policy makers who may wish to consider RdSAP data in future with qualifiers or margins of error, or may even look to review the EPC as the instrument of choice for some applications.

There is much literature analysing the shortcomings and nuances of RdSAP results, and the software model that generates the EPC, but only very limited literature extending the discussion about RdSAP to its operator: the DEA. At the time of writing, there is no literature focusing directly on the DEA and its role within the EPC production process. Their role is more important now, given the expanding use of EPCs, and increased reliance on EPC data.

This study aims to assess the readiness of both citizens and the government for digital participatory planning (DDP) as a contribution to the undergoing transformative shift toward smart and sustainable cities to address the challenges posed by rapid urbanization. While much attention has been devoted to leveraging technology to mitigate these challenges, there has been a relative lack of emphasis on engaging stakeholders in the planning process in a smart and inclusive manner. DPP stands as a cornerstone for the development of sustainable and smart cities. However, before DPP can be effectively implemented on the ground, it is crucial to assess the city readiness for DPP to ensure its success. This assessment is undertaken as part of Oman's broader initiative to transition into sustainable smart cities in alignment with the goals outlined in Oman Vision 2040.

A generic evaluation framework was identified, validated and customized to the local context by experts using the pile sorting technique based on the social constructivism theory. Then, the revised framework was used to evaluate the readiness of a sample of local citizens and government officials in Oman for the DPP concept.

The inferential statistical analysis revealed that citizens are willing to participate in DPP when trust and transparency with policymakers are enhanced. On the government side, the results showed that there is adequate infrastructure that can enable DPP, and planners have a positive attitude toward DPP provided that trust in citizens' opinions is strengthened. This study concludes with a roadmap for preparation for DPP implementation in smart sustainable cities mandated by Oman Vision 2040. The findings and roadmap can inform policy development, decision-making and urban planning practices toward more inclusive, participatory and technologically enabled urban environments.

The study contributes to the existing body of knowledge by emphasizing the significance of stakeholders' smart involvement in planning processes, social sustainability, evaluating city readiness for DPP and providing practical recommendations for DPP implementation in the context of smart sustainable cities. At a theoretical level, the study contributes a framework for assessing readiness for DPP and emphasizes that mutual trust is not only important for conventional participation practices but it is also essential for smart citizens. This study argues that a building or a city is not sustainable unless it is seen as such by its stakeholders, including the end users. Therefore, effective and smart involvement of the citizens in smart city planning is a precondition for the success of the future cities.

The construction industry and its activities harmfully affect the environment. Hence, adopting green building (GRB) practices can be helpful in achieving sustainable development goals. Therefore, this study aims to identify the factors affecting the intention to adopt GRB practices by extending theory of planned behavior (TPB).

Using non-probability purposive sampling technique, data was gathered from consultant and contractor engineers in the construction industry through a questionnaire. The analysis was done using partial least square-structural equation modeling technique on a useful sample of 290.

Findings revealed that the core constructs of TPB [i.e. attitude (AT), subjective norms (SUBN) and perceived behavioral control (PBC)] significantly affect the intention to adopt GRB practices. Moreover, government support and knowledge of green practices (KNGP) were found to be critical influencing factors on AT, SUBNs and PBC. Lastly, the findings confirmed that environmental concerns (ENC) play as a moderating between SUBN and intention to adopt GRB practices, as well as AT and intention to adopt GRB practices.

This study contributes to existing knowledge on GRB, offering evidence base for policy choices regarding climate change adaptation and mitigation in the construction industry.

This study provides insights from the perspective of a developing economy and confirms the applicability of TPB in the adoption of GRB practices. Moreover, this study confirms the moderation role of ENC in between TPB constructs and intention to GRB that is not tested earlier in the context of GRB. This study also confirms that government sustainable support positively affects PBC, and KNGP significantly affects SUBNs.

The UK Government has committed to achieving net-zero emissions by 2050, being the first major nation to do so. While laudable, it raises the question, “are future built environment professionals (BEPs) equipped for this?” Although studies related to students’ perspectives exist, they broadly focus on sustainability-related pedagogical aspects, with limited studies conducted in the built environment (BE). This study makes the case that it is timely to investigate this from an emerging perspective using the term “low-carbon future” (LCF), given that it is germane to achieving net-zero emissions and is at the forefront of academic and practice discourse. Therefore, this paper aims to investigate the knowledge level of UK BE students’ in higher education institutions (HEIs) specific to the term LCF.

This is a systematic scoping study review of published papers related to sustainability in BE curricula in the UK HEI context.

The findings reveal that LCF remains at a nascent stage, with no study specifically addressing it. It indicates a knowledge gap that could impact the grounding students require to address current and future sustainability challenges.

The review focused on a specific term, which, while relevant, is very niche. A review of other emerging terms, considering LCF as a theme, and/or empirical data from diverse stakeholders in UK HEIs could enrich the results.

This study provides significant insight into the status of sustainability inclusion in the BE curriculum. It would serve as a reference for stakeholders involved in equipping future BEPs with the requisite knowledge and skills to deal with sustainability challenges that will be consequential beyond the UK context. It would also inform future research.

Sustainability-informed and equipped BEPs will be influential in shaping their immediate surroundings and how people engage with them, which will contribute to developing a more equitable and sustainable society.

Beyond contributing to the discourse on sustainability literacy in UK HEI from an emerging concept perspective, this study would be useful as possibly the first of its kind. Therefore, it fills the theoretical gap and proffers recommendations that would be beneficial for curriculum development.

As public–private partnerships (PPPs) have become preferred and veritable approach to deliver affordable housing, the seemingly lack of understanding of the significant factors that impact on success has become a notable setback. This study aims to delineate significant factors that can support decisions in affordable PPP public housing delivery.

Largely, a questionnaire survey was adopted to elicit insights from practitioners, policymakers and experts to develop an evaluative decision support model using an analytical hierarchy process and multi-attribute utility technique approach. Further, an expert illustration was conducted to evaluate and validate the results on the housing typologies.

The results revealed that energy efficiency and low-cost green building materials scored the highest weighting of all the criteria. Furthermore, multi-storey self-contained flats were found to be the most preferred housing typology and were significantly influenced by these factors. From the model evaluation, the scores on the factors of sustainability, affordability, cultural values and accountability were consistent across all typologies of housing whereas that of benchmarking, governance and transparency were varied.

The decision support factors captured varied dimensions of key factors that impact on affordable PPP housing that have not been considered in an integrated manner. These findings offer objective and systematic support to decision-making in affordable PPP housing delivery.