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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.

The study aims to investigate the effects of intellectual capital and its constituents on the performance of listed companies operating in China's construction sector. The study also intends to examine the moderating role of digital transformation.

Hypotheses will be tested using Modified Value-Added Intellectual Capital (MVAIC). The sample will be comprised of 93 Shenzhen and Shanghai A-share listed companies within the construction industry from the period of 2015–2021. Multiple regression analysis was employed to investigate the influence of intellectual capital, its components and digital transformation on the performance of construction firms.

The study's results reveal that the performance of construction firms greatly depends on intellectual capital and its components. Furthermore, digital transformation plays a vital moderating role between intellectual capital and its components and construction firm performance.

This study addresses a critical inquiry on how construction managers can employ intellectual capital to enhance the performance of firms during digital transformation. Additionally, this research bridges this gap by guiding construction managers to concentrate on their external surroundings when examining firm performance.

By focusing on the predictors influencing construction firms' performance, this study contributes to the existing corpus of knowledge. This study employs resource orchestration theory (ROT) to determine how the different components of intellectual capital impact the performance of construction firms, with digital transformation acting as a moderating variable. This research will be valuable to researchers, construction industry professionals and policymakers.

The architectural profession faces an increasingly complex ethical landscape. In recent decades, the ethical foundations for architecture – formally defined in professional codes of conduct and reflected in regulatory frameworks – have expanded to incorporate imperatives derived from environmental and social responsibilities. The present research examines how these expanding ethical expectations are reflected in, and supported by, recent research about architectural ethics.

Analysis is based on a systematic review of recent research (2002–2023) focussing on ethical values and associated behaviours in the architectural profession. The review identifies 37 research articles (from a starting set of 2,483 articles), which are analysed empirically and then qualitatively to draw out views around three types of ethical behaviour. The paper then discusses how these findings align thematically with the evolving ethical needs of architectural practitioners (as defined in the professional codes of ethics and conduct of the RIBA in the UK, AIA in Australia and the AIA in the USA).

While business ethics remains the focus of past research, there has been a rise in research about ethics and social and environmental factors. The content of professional codes reflects this shift, setting the conditions for architects to aspire to increased expectations of environmental and social responsibility.

This article undertakes the first systematic review of recent research about architectural ethics and its alignment with the content of contemporary professional codes. Organised thematically, recent research about ethical values and associated behaviours can offer guidance for the evolving ethical needs of architects.

Facility management gained profound importance due to the increasing complexity of different systems and the cost of operation and maintenance. However, due to the increasing complexity of different systems, facility managers may suffer from a lack of information. The purpose of this paper is to propose a new facility management approach that links segmented assets to the vital data required for managing facilities.

Automatic point cloud segmentation is one of the most crucial processes required for modelling building facilities. In this research, laser scanning is used for point cloud acquisition. The research utilises region growing algorithm, colour-based region-growing algorithm and Euclidean cluster algorithm.

A case study is worked out to test the accuracy of the considered point cloud segmentation algorithms utilising metrics precision, recall and F-score. The results indicate that Euclidean cluster extraction and region growing algorithm revealed high accuracy for segmentation.

The research presents a comparative approach for selecting the most appropriate segmentation approach required for accurate modelling. As such, the segmented assets can be linked easily with the data required for facility management.

Providing improved access to nature within educational settings can promote stronger child–nature connections and is conditional on making evidence-based decisions for the planning, design and refurbishment of school architecture. The study offers insight into ways of reconnecting children with nature by examining the distribution and classification of diverse natural elements for enhancing children's visual and non-visual experiences of educational environments.

This study combines quantitative and qualitative analysis of data gathered through measurement and observation at three schools in Glasgow, with a total of 75 students, to identify key issues influencing child–nature multi-sensorial connections within indoor and outdoor environments and on building envelopes and layouts. It applies children's open-questions and diagrams to investigate children's discovery of nature, their feelings around natural attributes and their environmental preferences within school contexts.

This study's findings reveal that architectural features and landscape settings have significant influence on the quantitative and qualitative degrees of children's natural exploration through visual and non-visual sensorial modalities and environmental preferences.

The limitations of this study are that the data was gathered in the Spring season and with different groups of children from The Glasgow Academy who received the same educational curriculum. Thus, there is a need for further investigation on children's experiences of nature based on temporal and contextual differences, and varying educational-socio-cultural and economic factors.

The findings suggest that applications of natural diversity, accessible and flexible pathways and indoor natural settings, are potential approaches to connect children with nature within their study and play environments.

The authors provide a deeper understanding of how nature-based settings, including indoor and outdoor environments, constructively benefit children's multi-sensorial experiences, knowledge and biophilic feelings toward nature.

Early termination of public–private partnerships (PPPs) in China is caused by various risk factors, resulting in significant losses. This study aimed to clarify the key factors and identify the causal relationships among these factors.

Social network analysis (SNA) was used to analyze 37 risk factors that were summarized from 97 early terminated PPP cases and to identify the relationships among these key risk factors. Interpretive structural modeling (ISM) was conducted to explore the causal relationships. Data were collected from case documents, questionnaires and interviews.

A total of 17 key risk factors were identified and distributed in a hierarchical structure with six tiers. Among these key risk factors, the root causes affecting the early termination of PPP projects were government oversight in decision-making, local government transition, policy and law changes and force majeure. The direct cause was insufficient returns. Furthermore, local government and private sector defaults were essential mediating factors. Local government transition and the low willingness of the private sector were highlighted as potential key risks.

The cases and experts were all from China, and outcomes in other countries or cultures may differ from those of this study. Therefore, further studies are required.

This research provides knowledge regarding the key risk factors leading to the early termination of PPP projects and guidance on avoiding these factors and blocking the factors' transmission in the project lifecycle.

This study contributes to the knowledge of risk management by emphasizing the importance of local government transition, the low willingness of the private sector and project cooperation and operation, whose significance is ignored in the existing literature. The proposed ISM clarifies the role of risk factors in causing early termination and explains their transmission patterns.

As the number of web applications is increasing day by day web mining acts as an important tool to extract useful information from weblogs and analyse them according to the attributes and predict the usage of a website. The main aim of this paper is to inspect how process mining can be used to predict the web usability of hotel booking sites based on the number of users on each page, and the time of stay of each user. Through this paper, the authors analyse the web usability of a website through process mining by finding the web usability metrics. This work proposes an approach to finding the usage of a website using the attributes available in the weblog which predicts the actual footfall on a website.

PROM (Process Mining tool) is used for the analysis of the event log of a hotel booking site. In this work, authors have used a case study to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.

This article first provided an overview of process mining, then focused on web mining and later discussed process mining techniques. It also described different target languages: system nets (i.e. Petri nets with an initial and a final state), inductive miner and heuristic miner, graphs showing the change in behaviour of the dataset and predicting the outcome, that is the webpage having the maximum number of hits.

In this work, a case study has been used to apply the PROM (process mining tool) to pre-process the event log dataset for analysis to discover better-structured process maps than without pre-processing.