Search results

The construction site operates under a hazardous environment that requires a high level of understanding in building systems to minimise accidents. However, the current building education generally adopts paper-based learning approaches that lack hands-on experiences. Furthermore, to achieve Industrial Revolution 4.0 in line with any unforeseen pandemic, the most optimum solution is to transition from physical to technological-based building education. This paper aims to address the problems by proposing a game-based virtual reality (GBVR) for building utility inspection training.

The feasibility of the GBVR for building the utility inspection training approach is validated on a sample of undergraduate engineering students through user experience (survey) and performance-based comparisons against traditional paper-based training method.

The results show that the developed GBVR training has higher system usability in terms of visual output and knowledge retention than paper-based training due to visualisation technologies. The GBVR training method has also higher user-friendliness because of the higher motivational and engagement factors through the adoption of virtual reality and game-based learning.

GBVR training required a longer training duration and achieved a lower performance score (effectiveness) but can be improved by transitioning into hands-on tasks. This study has the potentials to be extended to vocational training platforms for competency development in the construction workforce by using cutting-edge extended reality technologies.

This paper portrays the benefits of integrating virtual reality technology in building education to overcome the low practicality and engagement of paper-based training.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

This chapter proposes a multiobjective model to design a Closed Loop Supply Chain (CLSC) network. The first objective is to minimize the total cost of the network, while the second objective is to minimize the carbon emission resulting from production, transportation, and disposal processes using carbon cap and carbon tax regularity policies. In the third objective, we maximize the service level of retailers by using maximum covering location as a measure of service level. To model the proposed problem, a physical programming approach is developed. This work contributes to the literature in designing an optimum CLSC network considering the service level objective and product substitution.

The purpose of this research is to propose and empirically validate a theoretical framework to investigate the willingness of the elderly to disclose personal health information (PHI) to improve the operational efficiency of AI-integrated caregiver robots.

Drawing upon Privacy Calculus Theory (PCT) and the Technology Acceptance Model (TAM), 274 usable responses were collected through an online survey.

Empirical results reveal that trust, privacy concerns, and social isolation have a direct impact on the willingness to disclose PHI. Perceived ease of use (PEOU), perceived usefulness (PU), social isolation, and recognized benefits significantly influence user trust. Conversely, elderly individuals with pronounced privacy concerns are less inclined to disclose PHI when using AI-enabled caregiver robots.

Given the pressing need for AI-enabled caregiver robots due to the aging population and a decrease in professional human caregivers, understanding factors that influence the elderly's disclosure of PHI can guide design considerations and policymaking.

Considering the increased demand for accurate and comprehensive elder services, this is the first time that information disclosure and AI-enabled caregiver robot technologies have been combined in the field of healthcare management. This study bridges the gap between the necessity for technological improvement in caregiver robots and the importance of transparent operational information by disclosing the elderly's willingness to share PHI.

A circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.

In this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.

The proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.

This study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.

The main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

The wood construction industry has been described as slow in adapting efficiency-increasing activities in its operations and supply chain. The industry is still facing challenges related to digitalization, such as fragmentation, poor traceability and lack of real-time information. This study evaluates the status of digitalization in construction supply chains by thematically analyzing the existing literature and mapping research trends.

A review of the key literature from 2016 to 2021 was performed. The results highlight various technologies and their applications within supply chains and identify research gaps, especially between theoretical frameworks and actual implementation using a scientometric-thematic analysis.

This paper provides a conceptual framework to further aid researchers in exploring the current trends in Supply Chain 4.0 and its applications in the wood construction industry compared to other more advanced industries. Suggested directions for future research in the wood construction Supply Chain 4.0 are outlined.

The existing literature still lacks a comprehensive review of the potential of a digitalized supply chain, especially in the construction industry. This framework is pivotal to continue explaining and observing the best ways to accelerate and implement Supply Chain 4.0 practices for digitalized supply chain management (SCM) while focusing specifically on the wood construction industry. The literature review results will help develop a comprehensive framework for future research direction to create a clearer vision of the current state of digitalization in supply chains and focus on the wood construction supply chain, thus, fully achieving the benefits of Supply Chain 4.0 in the wood construction industry.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

This study research contributes in fulfilling the gap by carrying out a systematic literature review (SLR) of contemporary research studies in closed-loop supply chain (CLSC). To the best of the author’s knowledge, an SLR rooted in bibliometric analysis has not been carried focusing on advent developments in CLSC. SLR employs scientific methodologies to select papers from standard databases. The SLR using advanced bibliometric and network analysis enables unveiling the key features of the contemporary literature.

The author has analyzed over 333 documents published from 2008 and onward. Using the contemporary tools from bibliometric analysis tools, the author presented an exploratory analysis. A network analysis is utilized to visualize literature and create clusters for the cocited research studies, keywords and publication sources. A detailed multivariate analysis of most influential works published based top 100 articles via a cocitation matrix is done. The multivariate analysis used k-means clustering in which optimal number of clusters are estimated. The analysis is further extended by using a factor analysis, which enables determining the most influential clusters in the k-means clustering analysis.

The SLR using a bibliometric and network analysis enables unveiling the key features of the contemporary literature in CLSC. The author examined published research for influential authors, sources, region, among other key aspects. Network analysis enabled visualizing the clusters of cocited research studies, cowords and publication sources. Cluster analysis of cocited research studies is further explored using k-means clustering. Factor analysis extends findings by identifying most contributing grouping of research areas within CLSC research. Each clustering technique disclosed a unique grouping structure.

CLSC has received considerable attention, and its core areas start with focusing on reverse logistics concepts relating reuse, recycling, remanufacturing, among others. Contemporarily, the studies have enhanced reverse logistics core functionalities interfaced with the other interesting avenues related to CO₂ emission reduction, greening and environmental protection, sustainability, product design and governmental policies. Earlier studies have presented a literature review of CLSC; however, these reviews are commonly conducted in the traditional manner where the authors select papers based on their area of expertise, interest and experience. As such these reviews fall short in utilizing the advanced tools from bibliometric analysis.

Supply chain (SC) research has boomed over the past two decades. Significant contributions have been made to the field from various analytical and decision-making perspectives. This paper, a comprehensive bibliometric study, aims to identify the key research contributors, institutions and themes.

A comprehensive knowledge domain visualization of over 1,000 articles, published between 2000 and 2022, is carried out to construct a bird’s eye view of the field in terms of research production, key authors, main publication outlets, geographic disparity of the contributions and emerging research trends. Additionally, collaboration patterns among researchers and institutions are mapped to highlight the communication networks underlying research initiatives.

Results show an explosive growth in the number of articles tackling supply chain optimization (SCO) issues with a significant concentration of the contributions in a relatively small cluster of authors, journals, institutions and countries. Among the many important findings, our analysis indicates that mixed-integer linear programming is the most commonly used model, while robust optimization is the method of choice for handling uncertainty. Furthermore, most SC models are developed at only one level of the organizational hierarchy and consider only one planning horizon. The importance of developing integrated SCO systems is key for future research.

The study fills the optimization techniques gap that exists in SC management bibliometric studies and presents a thematic map for the SCO research highlighting the various research foci.