Current construction engineering management suffers numerous challenges in terms of the trust, information sharing, and process automation. Blockchain which is a decentralised transaction and data management technology, has attracted increasing interests from both academic and industrial aspects since 2008. However, most of the existing research and practices are focused on the blockchain itself (i.e. technical challenges and limitations) or its applications in the finance service sector (i.e. Bitcoin). This paper aims to investigate the potential of applying blockchain technology in the construction sector. Three types of blockchain-enabled applications are proposed to improve the current processes of contract management, supply chain management, and equipment leasing, respectively. Challenges of blockchain implementation are also discussed in this paper.
Blockchain, a peer-to-peer, controlled, distributed database structure, has the potential to profoundly affect current business transactions in the construction industry through smart contracts, cryptocurrencies, and reliable asset tracking. The construction industry is often criticized for being slow in embracing emerging techno-logies and not effectively diffusing them through its supply chains. Often, the extensive fragmentation, traditional procurement structures, destructive competition, lack of collaboration and transparency, low-profit margins, and human resources are shown as the main culprits for this. As blockchain technology makes its presence felt strongly in many other industries like finance and banking, this study investigates the preparation of construction supply chains for blockchain technology through an explorative analysis. Empirical data for the study were collected through semi-structured interviews with 17 subject experts. Alongside presenting a strengths, weaknesses, opportunities, and threats analysis (SWOT), the study exhibits the requirements for and steps toward a construction supply structure facilitated by blockchain technology.
Lack of trust has been an ongoing issue for decades in construction quality management, hindering the improvement of quality performance. The development of mutual trust depends on immutable, traceable, and transparent construction quality information records. However, current information technologies cannot meet the requirements. To address the challenge, this study explores a blockchain-based framework for construction quality information management, which extends applications of blockchain in the domain of construction quality management. A consortium blockchain system is designed to support construction quality management in which participants’ information permissions and lifecycle are discussed. Additionally, this study presents in detail the consensus process that aims to address the problem of information fraud. The automated compliance checking based on smart contracts is presented as well, aiming to assure that construction products meet regulation requirements. Finally, an example of the consortium blockchain network is visualized to validate the feasibility of blockchain-based construction quality information management. The research shows that blockchain can facilitate mutual trust in construction quality management by providing distributed, encrypted, and secure information records and supporting automated compliance checking of construction quality.
Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries. Motivated by the major development strategies and needs of industrial intellectualization in China, this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization, as well as their application to smart industrial engineering. First, this study describes a general methodology for the fusion of data analytics and optimization. Then, it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing. Finally, it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization. The framework uses data analytics to perceive and analyze industrial production and logistics processes. It also demonstrates the intelligent capability of planning, scheduling, operation optimization, and optimal control. Data analytics and system optimization tech-nologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing, resources and materials, energy, and logistics systems, such as high energy consumption, high costs, low energy efficiency, low resource utilization, and serious environmental pollution. The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency. Therefore, industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.
Partial least squares structural equation modeling (PLS-SEM) is a modern multivariate analysis technique with a demonstrated ability to estimate theoretically established cause-effect relationship models. This technique has been increasingly adopted in construction management research over the last two decades. Accordingly, a critical review of studies adopting PLS-SEM appears to be a timely and valuable endeavor. This paper offers a critical review of 139 articles that applied PLS-SEM from 2002 to 2019. Results show that the misuse of PLS-SEM can be avoided. Critical issues related to the application of PLS-SEM, research design, model development, and model evaluation are discussed in detail. This paper is the first to highlight the use and misuse of PLS-SEM in the construction management area and provides recommendations to facilitate the future application of PLS-SEM in this field.
The quality traceability of precast components has largely affected the widespread adoption of prefabricated buildings. Blockchain technology provides an effective solution to change the centralized storage mode of traditional traceability system and its related disadvantages. In this paper, we propose a framework of quality traceability system for precast components based on blockchain technology. The system framework adopts a hybrid blockchain architecture and dual storage mode, defines three types of smart contracts, and creates an interactive and efficient source tracing query method, which could effectively achieve the goals of decentralization, openness, and non-tamperability, as well as efficient traceability.
System reliability optimization problems have been widely discussed to maximize system reliability with resource constraints. Birnbaum importance is a well-known method for evaluating the effect of component reliability on system reliability. Many importance measures (IMs) are extended for binary, multistate, and continuous systems from different aspects based on the Birnbaum importance. Recently, these IMs have been applied in allocating limited resources to the component to maximize system performance. Therefore, the significance of Birnbaum importance is illustrated from the perspective of probability principle and gradient geometrical sense. Furthermore, the equations of various extended IMs are provided subsequently. The rules for simple optimization problems are summarized to enhance system reliability by using ranking or heuristic methods based on IMs. The importance-based optimization algorithms for complex or large-scale systems are generalized to obtain remarkable solutions by using IM-based local search or simplification methods. Furthermore, a general framework driven by IM is developed to solve optimization problems. Finally, some challenges in system reliability optimization that need to be solved in the future are presented.
Blockchain has attracted much attention in recent years with the development of cryptocurrency and digital assets. As the underlying technology of cryptocurrency, blockchain has numerous benefits, such as de-centralization, collective maintenance, tamper-resistance, traceability, and anonymity. The potential of the blockchain technology (BT) is widely recognized in the financial field. Although some scholars have proposed the combination of blockchain and supply chain finance (SCF), the details of this combination is rarely mentioned. This study first analyzes the coupling between SCF and blockchain technology. Second, the conceptual framework of blockchain-driven SCF platform (BcSCFP) is presented. Third, the operation process of three SCF models on the BcSCFP is proposed. Finally, a case study combined with actual events is conducted. This paper has a positive practical significance in the operation and management of banks and loan enterprises.
While in the EU alone 80 million citizens are suffering from excessive environmental noise, the conventional approach, i.e., reduction of ‘sound level’, does not always deliver the required improvements in quality of life. The growing field of ‘soundscape studies’ is addressing this gap by considering the sound environment as perceived, in context, with an interdisciplinary approach. However, soundscapes are hugely complex, and measuring them as a basis for environmental design requires a step change to the discipline. This paper explores the need for developing ‘soundscape indices’, in the movement from noise control to soundscape creation, adequately reflecting levels of human comfort, the impact of which will be reminiscent of that of the Decibel scale created by Bell Systems a century ago. By analysing the soundscape design of urban open public spaces, the coherent steps for achieving this are also discussed, including characterising soundscapes by capturing soundscapes and establishing a comprehensive database; determining key factors and their influence on soundscape quality based on the database; developing, testing and validating soundscape indices; and demonstrating the applicability of the soundscape indices in the management of our sound environment.
The global collaboration and integration of online and offline channels have brought new challenges to the logistics industry. Thus, smart logistics has become a promising solution for handling the increasing complexity and volume of logistics operations. Technologies, such as the Internet of Things, information communication technology, and artificial intelligence, enable more efficient functions into logistics operations. However, they also change the narrative of logistics management. Scholars in the areas of engineering, logistics, transportation, and management are attracted by this revolution. Operations management research on smart logistics mainly concerns the application of underlying technologies, business logic, operation framework, related management system, and optimization problems under specific scenarios. To explore these studies, the related literature has been systematically reviewed in this work. On the basis of the research gaps and the needs of industrial practices, future research directions in this field are also proposed.
China is now in an era of large-scale metro construction. This paper reviews the nature of Chinese metro engineering with a specific focus on its organization and market mode, cost structure, safety control and schedule management. Then, an examination on recent research in metro engineering of the National Natural Science Foundation of China (NSFC) is also conducted, which indicates that information and automation based technologies are increasingly used in practice.
Seru production is regarded as a new production mode and derived from the production site of Japanese electronics industry. This production mode is proposed to overcome the low flexibility of the assembly line. Seru production has been successfully implemented in Japanese electronics industry, such as Canon and Sony. Benefits from Seru production include rapid response, good flexibility, and high productivity. Seru production has received extensive attention in academic research and production practice. This study reviews the background, characteristics, types, and operation of seru production. The advantages and applicable scenes of seru production are summarized from the perspective of business practice. We compare seru production and famous production modes, i.e., assembly line, cellular manufacturing, and Toyota Production System. The literature on seru production is surveyed and classified. Furthermore, future research directions are provided.
With the accelerated urbanization in China, passenger demand has dramatically increased in large cities, and traffic congestion has become serious in recent years. Developing public urban rail transit systems is an indispensable approach to overcome these problems. However, the high energy consumption of daily operations is an emerging issue due to increased rail transit networks and passenger demands. Thus, reducing the energy consumption and operational cost by using advanced optimization methodologies is an urgent task for operation managers. This work systematically introduces energy-saving approaches for urban rail transit systems in three aspects, namely, train speed profile optimization, utilization of regenerative energy, and integrated optimization of train timetable and speed profile. Future research directions in this field are also proposed to meet increasing passenger demands and network-based urban rail transit systems.
Due to the characteristics of hesitant fuzzy sets (HFSs), one hesitant fuzzy element (HFE), which is the basic component of HFSs, can express the evaluation values of multiple decision makers (DMs) on the same alternative under a certain attribute. Thus, the HFS has its unique advantages in group decision making (GDM). Based on which, many scholars have conducted in-depth research on the applications of HFSs in GDM. We have viewed lots of relevant literature and divided the existing studies into three categories: theory, support and methods. In this paper, we elaborate on hesitant fuzzy GDM from these three aspects. The first aspect is mainly about the introduction of HFSs, HFPRs and some hesitant fuzzy aggregation operators. The second aspect describes the consensus process under hesitant fuzzy environment, which is an important support for a complete decision-making process. In the third aspect, we introduce seven hesitant fuzzy GDM approaches, which can be applied in GDM under different decision-making conditions. Finally, we summarize the research status of hesitant fuzzy GDM and put forward some directions of future research.
Global ports and maritime shipping networks are important carriers for global supply chain networks, but they are also the main sources of energy consumption and pollution. To limit ship emissions in ports and offshore areas, the International Maritime Organization, as well as some countries, has issued a series of policies. This study highlights the importance and necessity of investigating emergent research problems in the operation management of green ports and maritime shipping networks. Considerable literature related to this topic is reviewed and discussed. Moreover, a comprehensive research framework on green port and shipping operation management is proposed for future research opportunities. The framework mainly comprises four research areas related to emission control and grading policies. This review may provide new ideas to the academia and industry practitioners for improving the performance and efficiency of the operation management of green ports and maritime shipping networks.
This review aims to gain insight into the current research and application of operational management in the area of intelligent agriculture based on the Internet of Things (IoT), and consequently, identify existing shortcomings and potential issues. First, we use the Java application CiteSpace to analyze co-citation networks in the literature related to the operational management of IoT-based intelligent agriculture. From the literature analysis results, we identify three major fields: (1) the development of agricultural IoT (Agri-IoT) technology, (2) the precision management of agricultural production, and (3) the traceability management of agricultural products. Second, we review research in the three fields separately in detail. Third, on the basis of the research gaps identified in the review and from the perspective of integrating and upgrading the entire agricultural industry chain, additional research directions are recommended from the following aspects: The operational management of agricultural production, product processing, and product sale and after-sale service based on Agri-IoT. The theoretical research and practical application of combining operational management theories and IoT-based intelligent agriculture will provide informed decision support for stakeholders and drive the further development of the entire agriculture industry chain.
Against the background of addressing global climate change and carbon emission reduction, corporate carbon information disclosure (CID) has become an important measure to achieve carbon emission reduction worldwide and a research hotspot closely investigated by the academia. This study provides a systematic overview of literature on CID, including its research trend, theoretical basis, disclosing features, influencing factors, and consequences. Results indicate that, first, CID has been increasing in recent years, but the content and quality of the disclosure still need to be improved. Second, the main influencing factors of CID include company features, corporate governance, environmental performance, institutional characteristics, and stakeholders. Third, the consequences of CID are based mainly on company performance, ecological environment, and investors’ decision-making. Lastly, most studies have confirmed the positive effect of CID on company performance and investors’ decision-making, but the nexus of environmental performance and corporate CID remains to be investigated. Several important future research directions are also proposed based on these results.
Over the past decade, electric vehicles (EVs) have been considered in a growing number of models and methods for vehicle routing problems (VRPs). This study presents a comprehensive survey of EV routing problems and their many variants. We only consider the problems in which each vehicle may visit multiple vertices and be recharged during the trip. The related literature can be roughly divided into nine classes: Electric traveling salesman problem, green VRP, electric VRP, mixed electric VRP, electric location routing problem, hybrid electric VRP, electric dial-a-ride problem, electric two-echelon VRP, and electric pickup and delivery problem. For each of these nine classes, we focus on reviewing the settings of problem variants and the algorithms used to obtain their solutions.
The high-end equipment intelligent manufacturing (HEIM) industry is of strategic importance to national and economic security. Engineering management (EM) for HEIM is a complex, innovative process that integrates natural science, technology, management science, social science, and the human spirit. New-generation information technology (IT), including the internet, cloud computing, big data, and artificial intelligence, have made a remarkable influence on HEIM and its engineering management activities, such as product system construction, product life cycle management, manufacturing resources organization, manufacturing model innovation, and reconstruction of the enterprise ecosystem. Engineering management for HEIM is a key topic at the frontier of international academic research. This study systematically reviews the current research on issues pertaining to engineering management for HEIM under the new-generation IT environment. These issues include cross-lifecycle management, network collaboration management, task integration management of innovative development, operation optimization of smart factories, quality and reliability management, information management, and intelligent decision making. The challenges presented by these issues and potential research opportunities are also summarized and discussed.
The construction industry has long faced the challenge of introducing collaborative systems among multiple stakeholders. This challenge creates a high level of rigidity in terms of processing shared information related to different processes, robust holistic regulations, payment actualizations, and resource utilization across different nodes. The need for a digital platform to cross-connect all stakeholders is necessary. A blockchain-based platform is a prime candidate to improve the industry in general and the construction supply chain (CSC) in particular. In this paper, a literature review is presented to establish the main challenges that CSC faces in terms of its effects on productivity and efficiency. In addition, the effect of applying blockchain platforms on a case study is presented and analyzed from performance and security level. The analysis aims to emphasize that blockchain, as presented in this paper, is a viable solution to the challenges in the CSC regardless of the risks associated with the security and robustness of the flow of information and data protection. Moreover, a threat analysis of applying a blockchain model on the CSC industry is introduced. This model indicates potential attacks and possible countermeasures to prevent the attacks. Future work is needed to expand, quantify, and optimize the threat model and conduct simulations considering proposed countermeasures for the different blockchain attacks outlined in this study.
Intelligent construction technology has been widely used in the field of railway engineering. This work first analyzes the connotation, function, and characteristics of intelligent construction of railway engineering (ICRE) and establishes its system structure from three dimensions, namely, life cycle, layers of management, and intelligent function, to deeply understand the development situation of intelligent railway construction in China. Second, seven key technical support systems of ICRE, which include building information modeling (BIM) standard system for China’s railway sector, technology management platform and life cycle management based on BIM+GIS (geography information system), ubiquitous intelligent perception system, intelligent Internet-of-Things (IoT) commu-nication system based on mobile interconnection, construction management platform based on cloud computing and big data, unmanned operation system based on artificial intelligence, intelligent machinery and robot, and intelligent operation and maintenance system based on BIM and PHM (prediction and health management), are established. Third, ICRE is divided into three development stages: primary (perception), intermediate (substitution), and advanced (intelligence). The evaluation index system of each stage is provided from the aspects of technology and function. Finally, this work summarizes and analyzes the application situation of ICRE in the entire railway sector of China, represented by Beijing–Zhangjiakou and Beijing–Xiong’an high-speed railways. Result shows that the technical support systems of the ICRE have emerged in China and are still in the process of deepening basic technology research and preliminary application. In the future, the ICRE of China’s railway sector will develop toward a higher stage.
Cities are incorporating smart and green infrastructure components in their urban design policies, adapting existing and new infrastructure systems to integrate technological advances to mitigate extreme weather due to climate change. Research has illustrated that smart green infrastructure (SGI) provides not only climate change resilience but also many health and wellbeing benefits that improve the quality of life of citizens. With the growing demand for smart technology, a series of problems and challenges, including governance, privacy, and security, must be addressed. This paper explores the potential to transition from grey, green, or smart silos to work with nature-based solutions and smart technology to help change cities to achieve considerable environmental and socio-economic benefits. The concepts of grey, green, and smart infrastructure are presented, and the needs, benefits, and applications are investigated. Moreover, the advantages of using integrated smart, green nature-based solutions are discussed. A comprehensive literature review is undertaken with keyword searches, including journal papers, stakeholder and case study reports, and local authority action plans. The methodology adopts multimethod qualitative information review, including literature, case studies, expert interviews, and documentary analysis. Published data and information are analysed to capture the key concepts in implementing SGI systems, such as storm-water control, flood and coastal defense, urban waste management, transportation, recreation, and asset management. The paper investigates the elimination of silo approaches and the alleviation of the destructions caused by extreme weather events using these interdependent SGI systems supported by novel data-driven platforms to provide nature-based solutions to boost the health and wellbeing of the residents.
This multiple case study of a contracting firm contributes to understanding the barriers that organizations face during the implementation of building information modeling (BIM) by providing insights into the impact of these barriers across different organizational levels (i.e., from top management to project teams) and by relating these barriers to different degrees of BIM maturity. First, we observe the dominance of barriers related to the motivation, competence, and time capacity of people across all levels of an organization. Second, the cluster of barriers at the middle-management level highlights the important role of this level in reducing these barriers. Third, only those cases with a low level of BIM maturity have struggled with lack of top management support, thereby highlighting the importance of such support in achieving BIM maturity growth. High BIM maturity situations are more prone to externally oriented barriers in attempting to further leverage the benefits of BIM. Our study provides insights on where to focus BIM implementation measures and how to enhance organizational BIM maturity.
The outbreak of COVID-19 has significantly affected the development of enterprises. In the post-pandemic era, blockchain technology has become one of the important technologies to help enterprises quickly gain market competitiveness. The heavy investment required of supply chain stakeholders to employ blockchain technology has hindered its adoption and application. To tackle this issue, this study aims to facilitate the adoption of blockchain technology in a supply chain consisting of a core enterprise and a small/medium-sized enterprise through an effective supply chain contract. We analyze the performance of a cost-sharing (CS) contract and a revenue-sharing (RS) contract and propose a new hybrid CS-RS contract for better performance. We conduct comparative analyses of the three contracts and find that the hybrid CS-RS contract can more effectively incentivize both parties to reach the highest level of blockchain technology adoption and achieve supply chain coordination.
Through analysis of articles published from 2000 to March 2014 in Automaton in Construction (AUTCON), an international research journal published by Elsevier, this paper summarizes the topics of research and the institutions worldwide where research was conducted in construction safety engineering and management. Seventy-one articles published during this time focused on Information Technology (IT) applications in this field were selected for analysis. The underlying research topics and their related IT implementations are discussed, and research trends in allied specialties are identified.
The field of engineering management usually involves evaluation issues, such as program selection, team performance evaluation, technology selection, and supplier evaluation. The traditional self-evaluation data envelopment analysis (DEA) method usually exaggerates the effects of several inputs or outputs of the evaluated decision-making unit (DMU), resulting in unrealistic results. To address this problem, scholars have proposed the cross-efficiency evaluation (CREE) method. Compared with the DEA method, CREE can rank DMUs more completely by using reasonable weights. With the extensive application of this technique, several problems, such as non-unique weights and non-Pareto optimal results, have arisen in CREE methods. Therefore, the improvement of CREE has attracted the attention of many scholars. This paper reviews the theory and applications of CREE, including the non-uniqueness problem, the aggregation of cross-efficiency data, and applications in engineering management. It also discusses the directions for future research on CREE.
The low carbon energy transition has attracted worldwide attention to mitigate climate change. Renewable energy (RE) is the key to this transition, with significant developments to date, especially in China. This study systematically reviews the literature on RE development to identify a general context from many studies. The goal is to clarify key questions related to RE development from the current academic community. We first identify the forces driving RE development. Thereafter, we analyze methods for modeling RE developments considering the systematic and multiple complexity characteristics of RE. The study concludes with insights into the target selection and RE development roadmap in China.