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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.

In light of climate change, the design and construction of buildings needs to shift from conventional to lower-carbon practices to maximise carbon reduction. Over the past few years, the zero carbon buildings (ZCBs) approach has been promoted worldwide as an effective way to reduce environmental impacts and mitigate climate change. Although zero-carbon policies, technologies, processes and products are widely available in the construction market, construction stakeholders play an important part in adopting relevant strategies to implement ZCBs successfully. This study investigates the knowledge of construction stakeholders involved in the design and construction of buildings regarding zero carbon initiatives in New Zealand.

The research was conducted using a literature review and an online questionnaire survey with various New Zealand's construction stakeholders.

The findings indicate a low level of knowledge regarding the design and construction of ZCBs. To successfully deliver ZCBs, the study suggests that construction stakeholders must have their self-awareness increased, especially in improving knowledge of whole-of-life embodied carbon reduction. The governments and construction sectors should devote more effort to establishing training programmes and knowledge-sharing platforms to improve stakeholder knowledge in carbon literacy, building assessment methods, energy modelling and life cycle assessment.

The research implications may assist the real-world uptake of the ZCBs approach by offering academics and practitioners an insight into the ZCBs knowledge gaps.

Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.

Appropriate thermal properties of walls can lead to the improvement of the indoor environment of buildings especially in countries with low energy availability such as Burkina Faso. In order to benefit from these advantages, the thermal properties must be properly characterized. This paper investigates the impact of the design of single- and double-layer walls based on compressed Earth blocks (CEB) on the risk of indoor overheating.

First a building has been used as a tool to measure climate data. Then, a software program was used to define an accurate thermal model. Two indices were defined: weighted exceedance hour (WEH) related to the risk of overheating and cyclic thickness (ξ) related to the thermal properties of the walls. The aim is to define the appropriate values of ξ which minimized the WEH. The study also assesses the sensitivity of these thermal properties to occupancy profiles.

The results indicate the arrangements of the thermal properties that can promote comfortable environments. In single-layer wall buildings, ξ = 2.43 and ξ = 3.93 are the most suitable values to minimize WEH for the room occupied during the day and night, respectively. If a double-layer wall is used, ξ = 1.42 and CEB layer inside is the most suitable for the room occupied during the day, while ξ = 2.43 and CEB outside should be preferred in the case of a room with night occupancy profile.

The findings indicate that occupation patterns at room scale should be systematically considered when dealing with wall design in order to improve the thermal comfort.

The development of circular construction supply chains (CCSCs) is impeded by various barriers, but the current literature overlooks the interrelationships among these barriers and the varying nature of associated countermeasures with the growth of circular economy (CE). This paper aims to develop new perspectives about the transition to CCSCs through the lens of supply-push (SP)/demand-pull (DP) strategies and related underpinning theories.

A systematic literature review including 136 journal articles was undertaken to identify barriers to CCSCs and associated countermeasures that are analysed for their relevance to SP/DP. The interplay between SP/DP approaches was discussed using the “technology acceptance” and “innovation chain” models.

(1) Thirty-five barriers were identified and organised into nine main barrier factors; (2) the predominant factors are knowledge and awareness, policy and regulations, technological capabilities, and incentives; (3) CCSCs transition is SP-configured primarily driven by actors above the project network; (4) “push” measures are devised to gradually create a “pull” environment and can be revoked when demand for circularity is created, suggesting a new “push-to-pull” perspective of CCSCs; and (5) a complex adaptative system is witnessed in relationships between barriers and countermeasures, and interactions among actors at all levels.

The findings offer practitioners countermeasures to barriers encountered in CE initiatives. It also informs policymakers of adjusting policies to accommodate the SP-DP movement in steering the circular transition.

This study uses theoretical models to interpret the dynamics in CCSCs transition and proposes a new definition of CCSCs highlighting their complex and dual transitional/transformational nature.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

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.

The purpose of this paper is to provide small and medium-sized enterprises (SMEs) in emerging markets with an updated Purchasing Portfolio Matrix (PPM) specifically for international sourcing. This data-driven PPM matrix is designed to provide a dynamic and process perspective that can help SMEs survive the disruptions caused by emergency situations such as the global COVID-19 pandemic.

This research reports on qualitative interviews with experienced informants from 15 SMEs in the manufacturing industry. The authors follow process-based research using a combination of retrospective and real-time case study approaches to gradually unveil the dynamics in segmentation and sourcing strategies in the international sourcing context during the COVID-19 pandemic.

The findings reveal the dynamics of segmentation and international sourcing strategies during global disruptions and unpack the underlying logic behind the dynamics that is specific to SMEs in emerging economies.

Existing literature on PPM predominantly focuses on static and normal sourcing circumstances. This paper addresses this gap by adopting a dynamic approach to study how sourcing strategies of SMEs from emerging economies evolve in a highly volatile environment from an international sourcing perspective.

The demand for healthcare innovation is increasing, and not much is known about how entrepreneurial firms search for and sell to customers in the highly regulated and complex healthcare market. Drawing on effectuation perspectives, we explore how entrepreneurial digital healthcare firms with disruptive innovations search for early customers in the healthcare sector.

This study uses a qualitative, longitudinal multiple-case design of four entrepreneurial Nordic telehealth firms. In-depth interviews were conducted with founders and senior managers over a period of 27 months.

We find that when customer buying conditions are highly flexible, case firms use effectual logic to generate customer demand for disruptive innovations. However, under constrained buying conditions firms adopt a more causal approach to customer search.

Managers need to gain a deep understanding of target buying environments when searching for customers. In healthcare sector markets, the degree of flexibility customers have over buying can constrain them from engaging in demand co-creation. In particular, healthcare customer access to funding streams can be a key determinant of customer flexibility.

We contribute to effectuation literature by illustrating how customer buying conditions influence decision-making logics of entrepreneurial firms searching for customers in the healthcare sector. We contribute to entrepreneurial resource search literature by illustrating how entrepreneurial firms search for customers beyond their networks in the institutionally complex healthcare sector.