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In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data. The purpose of this paper is to design a robot system compatible with ultra high frequency (UHF) band passive and active RFID applications and to propose a new anti-collision protocol to improve identification efficiency for active tag data collection.

A new UHF RFID robot system based on a cloud platform is designed and verified. For the active RFID system, a grouping reservation–based anti-collision algorithm is proposed in which an inventory round is divided into reservation period and polling period. The reservation period is divided into multiple sub-slots. Grouped tags complete sub-slot by randomly transmitting a short reservation frame. Then, in the polling period, the reader accesses each tag by polling. When tags’ reply collision occurs, the reader tries to re-query collided tags once, and the pre-reply tags avoid collisions through random back-off and channel activity detection.

The proposed algorithm achieves a maximum theoretical system throughput of about 0.94, and very few tag data frame transmissions overhead. The capture effect and channel activity detection in physical layer can effectively improve system throughput and reduce tag data transmission.

In this paper, the authors design and verify the UHF band passive and active hybrid RFID robot architecture based on cloud collaboration. And, the proposed anti-collision algorithm would improve active tag data collection speed and reduce tag transmission overhead in complex manufacturing environments.

The purpose of this paper is to study how to improve the performance of RFID robot system by anti-collision algorithms. For radio frequency identification (RFID) robots operating in mobile scenes, effective anti-collision algorithm not only reduces missed reading but also enhances the speed of RFID robots movement.

An effective anti-collision algorithm is proposed to accelerate tag identification in RFID robots systems in this paper. The tag collisions in the current time slot are detected by a new method, and then further resolve each small tag collision to improve system throughput, rather than the total tags number estimation. After the reader detected the collision, three different collision resolution methods were described and studied, and the situation of missing tag caused by reader moving is also discussed.

The proposed algorithm achieves theoretical system throughput of about 0.48, 0.50 and 0.61 and simulates to show that the proposed algorithm performance is significantly improved compared with the existing ALOHA-based algorithm.

The proposed RFID anti-collision algorithm is beneficial to improve the moving speed and identification reliability of the RFID robots in complex environments.

This research aims to develop an approach to assess the reliability of integrated construction supply chains via an integrated model of building information modelling (BIM) and the lean supply chain (LSC). It reflects the synergistic workflow between BIM and LSC as a novel approach to improve the reliability of construction projects.

This research evaluates the reliability of the BIM-LSC approach through a combination of entropy theory, set pair analysis (SPA), and Markov chains (EESM). An exploratory survey was conducted to collect data from 316 industry professionals experienced in BIM and LSC. Subsequently, multiple cycles of calculations were performed with indirect data inputs. Finally, a reliability evaluation index is established for the BIM-LSC approach and potential applications are identified.

The results show that the EESM model of BIM-LSC developed in this study can handle not only supply chain reliability evaluation at a given state but also the prediction of reliability in supply chain state transitions due to changing project conditions. This is particularly relevant to the current environment of the construction project, which is characterised by an increasing level of complexity in terms of labour, technology, and resource interactions.

Future research could consider the accuracy and validity of the proposed model in real-life scenarios with by considering both quantitative and qualitative data across the entire lifecycle of projects.

The research offers a model to evaluate the reliability of the BIM-LSC approach. The accuracy of BIM supply chain reliability analysis and prediction in an uncertain environment is improved.

The BIM-LSC reliability evaluation and prediction presented in this study provides a theoretical foundation to enhance understanding of the BIM-LSC in the construction project context.

Healthcare employs informatics to offer its services through information technology where the social network can aid virtual medical learning. Since the usage of the internet and other electronic tools for medical services delivery is at the initial stage, it is essential to examine the factors that condition patients and medical elements in a virtual environment can develop relationship models on the health services. So, the authors have systematically reviewed virtual medical learning and offered some suggestions for the upcoming works. The authors have also discovered gaps in the state-of-the-art papers and provided solutions for them.

Numerous novel advancements have changed the old exercise of therapeutic and analytic learning. Virtual spaces have quickly turned into a section of the learning technology vision. Given the importance of its achievements and endless low-cost expansion of the educational system, virtual education has been considered as one of the issues raised by the information communities. Medicine and health are some of the most important fields in virtual technologies. Hence, in this paper, we have used a systematic literature review to deeply examine virtual medical learning. After establishing exclusion and inclusion criteria, an independent systematic search in Google Scholar, ACM, Scopus, Eric, Science Direct, Springer link, Emerald, Global ProQuest and IEEE for relevant studies have been performed, and 21 papers have been analyzed. Detailed data have been mined out of the papers.

The authors have found that virtual medical learning improves and expands the knowledge core and meaningfully affects the exercise. Virtual learning (VL) has been used in many therapeutic zones, like therapeutic learning, surgery, diagnosing, combining and regularizing processes. It has presented a fundamental access point and a referral mechanism for all of a course's component communities. It can also simplify communicative education, allowing learners to get abilities before applying them in a real-world situation. Also, the communicative characteristics of different VL programs can somehow be like direct teaching.

Some excellent work may be removed owing to applying the filters to select the primary papers. Surveying all the documents on the topic of virtual medical learning is impossible, too. Nevertheless, the authors have tried to present a perfect survey of virtual medical learning. The results will be helpful for scholars to propose better virtual medical learning techniques.

E-learning has become an indispensable additional learning tool in medical education. The introduction of new learning technologies, the exponential growth of Internet usage and the advent of the World Wide Web can change the face of higher education. The results will be helpful for scholars for the upcoming works. The application of a literature review of partial least squares theory was useful for offering comprehensive literary coverage and completing the knowledge development analysis. The authors have backed scholars and experts for better understanding the development of virtual medical learning systems via presenting comparative data and scrutinizing the present advances.

The paper enhances intellectual knowledge by improving the conception of virtual medical learning. It informs the development, use of virtual medical learning and the upcoming works. The lack of comprehensive papers in this field has increased the importance of this paper. The present paper can handle the pace of publications.

Digital technologies, such as big data and artificial intelligence, significantly impact entrepreneurial activities worldwide. However, research on entrepreneurial activities enabled by digital technologies is fragmented, divergent and delayed. This study aims to provide a structured review of digital entrepreneurship (DE) to identify status, hotspots, knowledge structure, dynamic trends and future developments in this field.

The bibliometric analysis was applied to offer a technological review on DE. In total 704 publications and their 34,083 references from Web of Science were retrieved as the sample set. Basic characteristics of publications, including the most influential documents, authors, journals and countries, were obtained. Then, co-citation and co-occurrence analyses were conducted to sketch the contours of the structure and evolution of DE.

DE has attracted increasing attention in the past three decades, especially after 2013. There are dozens of countries, hundreds of journals and more than 1,000 authors that have contributed to this field. Based on keyword co-occurrence clustering and co-citation clustering, the authors proposed a 3E (empower, evolution and ecosystem) framework of DE to facilitate an interdisciplinary dialogue for evidence-based policymaking and practice. In the future, researchers need to pay more attention to theoretical research and study DE from a holistic and dynamic perspective with consideration to the negative impact of digital technology on entrepreneurial activities.

This study draws an outline of the global advance on DE research. It presents an opportunity to comprehensively understand the contemporary achievements, the march of knowledge and the logical venation underlying academic developments as well as foundations for policymaking.

Embracing big data has been at the forefront of research for project management. Although there is a consensus that the adoption of big data has significantly positive impact on project performance, far less is known about how this innovative information technology becomes an effective driver of construction project quality improvement. This study aims to better understand the mechanism and conditions under which big data can effectively improve project quality performance.

Adopting Chinese construction enterprises as samples, the theoretical framework proposed in this paper is verified by the empirical results of the two-level hierarchical linear model. The moderated mediation analysis is also conducted to test the hypotheses. Finally, the empirical findings are validated by a comparative case study.

The results show that big data facilitates the development of technology capability, which further produces remarkable quality performance. That is, a project team's technology capability acts as a mediator in the relationship between organizational adaptability of big data and predictive analytics and project quality performance. It is also observed that two types of project team interdependence (goal and task interdependence) positively moderate the mediation effect.

The questionnaire study from China only represents the relationship within a short time interval in the current context. Future studies should apply longitudinal designs to properly test the causality and use multiple data sources to ensure the validity and robustness of the conclusions.

The value of big data in terms of quality improvement could not be determined in a vacuum; it also depends on the internal capability development and elaborate design of project governance.

This study provides an extension of the existing big data studies and fuels the ongoing debate on its actual outcomes in project management. It not only clarifies the direct effect of big data on project quality improvement but also identifies the mechanism and conditions under which the adoption of big data can play an effective role.

This study assessed the key construction technology trends and tracked the impact of these developments on labor influencing factors in an effort to alleviate the limitations posed by skilled labor scarcity in offsite construction (OSC).

The study followed systematic literature review to acquisition initial data sets. The data retrieved form identified databases was then subjected to scientometric analysis. In next stage, disruptive factors were identified to produce a conceptual framework followed by its practical application for an OSC firm.

This study identified seven construction technologies with a potential to disrupt OSC in future. The study also developed a conceptual framework as a benchmark to help establish further frameworks for policy interns in OSC.

The review conducted only takes into account the literature from 2009 to March 2021. Any prior to the date and unpublished studies were not included in study.

A proper utilization of conceptual framework can contribute to technological adoption significantly lowering the need of labor in OSC industry. Moreover, the established discussion on understanding the purpose of deploying latest technology may reduce additional costs, management, time and allocation of labor resources.

This study provides a mechanism to intern OSC policymakers to impartially incorporate the latest technology in OSC.

This study fulfilled an identified need to study latest technological trends in OSC by utilizing bibliometric tools with SLR. The disruptive categories and factors highlighted by the study were not identified in a systematic manner in previous studies, which could further enhance the implementation of latest construction technology in OSC.

The purpose of this paper is to summarize the latest research of BIM adoption in construction engineering and management (CEM) and propose research directions for future scholarly work. During the recent decade, building information modeling (BIM) has gained increasing applications and research interest in the construction industry. Although there have been review-based studies that summarized BIM-based research in the overall architecture, engineering and construction (AEC) area, there is limited review that evaluates the current stage of BIM-based research specifically in the CEM sub-area.

CEM falls into the scope of AEC. It involves construction-related tasks, activities and processes (e.g. scheduling and cost estimates), issues (e.g. constructability), as well as human factors (e.g. collaboration). This study adopted a holistic literature review approach that incorporates bibliometric search and scientometric analysis. A total of 276 articles related to BIM applied in CEM were selected from Scopus as the literature sample for the scientometric analysis.

Some key CEM research areas (e.g. CEM pedagogy, integrated project delivery, lean and off-site construction) were identified and evaluated. Research trends in these areas were identified, and analyses were carried out with regard to how they could be integrated with BIM. For example, BIM, as a data repository for ACE facilities, has substantial potential to be integrated with a variety of other digital technologies, project delivery methods and innovative construction techniques throughout the whole process of CEM.

As BIM is one of the key technologies and digital platforms to improve the construction productivity and collaboration, it is important for industry practitioners to be updated of the latest movement and progress of the academic research. The industry, academics and governmental authorities should work with joint effort to fill the gap by first recognizing the current needs, limitations and trends of applying BIM in the construction industry. For example, it needs more understanding about how to address technical interoperability issues and how to introduce the integrated design and construction delivery approach for BIM implementation under the UK BIM Level 2/3 framework.

This study contributed to the body of knowledge in BIM by proposing a framework leading to research directions including the differences of BIM effects between design-bid-build and other fast-track project delivery methods; the integration of BIM with off-site construction; and BIM pedagogy in CEM. It also addressed the need to investigate the similarities and differences between academia and industry toward perceiving the movement of BIM in construction field work.

This paper studies the critical factors from the perspectives of technological quality, personal compatibility and organisational commitment using the technological adoption framework (TAF). The proposed TAF studies the critical factors that influence the intention to use building information modelling (BIM) taking into consideration of the “Perceived Ease of Use (PEU)” and “Perceive Usefulness (PU).”

The proposed study is a quantitative research study using the TAF model and the statistical analysis using “Partial Least Squares-Structural Equation Modelling (PLS-SEM).” The questionnaires are developed based on the literature review study and disseminated to the stakeholders in the Malaysian construction industry, including consultants, contractors, and clients. The data collected are analysed using PLS-SEM to identify the correlation between the critical factors influencing BIM adoption and the moderation influence of the PEU and PU towards the “Intention to Use (IU)” BIM.

The data collected from 185 construction industry stakeholders in Malaysia was utilised to develop the structural equation model. The measurement model was analysed in terms of composite reliability, discriminant validity, and collinearity issues. Subsequently, the SEM is analysed, and the findings on the hypothesis on the correlation between the critical factors and the intention to use BIM are examined. The study also examines the mediation effects of the PEU and PU towards the BIM adoption in the Malaysian construction industry.

This research conceptual framework, TAF, is derived from the integration of the existing underpinning theories of the technological adoption model and the technology–organisation–environment framework. This new TAF can be used for the study of new technology adoption. This cross-sectional research study is in line with the “Construction 4.0 Strategic Plan” in Malaysia to establish the current BIM adoption scenario and formulate the framework to promote incentives to promote BIM adoption.