The city digital twin is anticipated to accurately reflect and affect the city’s functions and processes to enhance its realization, operability, and management. Although research on the city digital twin is still in its infancy, the advancement of the digital twin technology is growing fast and providing viable contributions to augmenting smart city developments. This study reviews the literature to identify the current and prospective potentials and challenges of digital twin cities. A research agenda is also proposed to guide future research on the city digital twincity digital twin to reach the utmost level of a comprehensive and complete city digital twin. Enhancing the efficiency of data processing, promoting the inclusion of socio-economic components of the city, and developing mutual integration between the two counterparts of the digital twin are proposed to be the future research directions to achieve and utilize a completely mirrored city digital twin.

A construction defect can cause schedule delay, cost overrun and quality deterioration. In order to minimize these negative impacts of construction defects, this paper aims to analyze the causality of construction defects. Specifically, association rule mining (ARM) is used to quantify the interrelationships between defect causes, and social network analysis (SNA) is utilized to find out the most influential causes triggering generation of construction defects. The suggested approach was applied to 2949 defect instances in finishing work. Through this application, it was confirmed that the proposed approach can systematically identify and quantify causality among defect causes.

Decision making at the early stages of a construction project has a significant impact on the project, and various scenarios created based on the owner's requirements should be considered for the decision making. At the early stages of a construction project, the information regarding the project is usually limited and uncertain. As such, it is difficult to plan and manage the project (especially cost planning). Thus, a cost model that could be varied according to the owner's requirements was developed. The cost model that was developed in this study is based on the case‐based reasoning (CBR) methodology. The model suggests cost estimation with the most similar historical case as a basis for the estimation. In this study, the optimization process was also conducted, using genetic algorithms that reflect the changes in the number of project characteristics and in the database of the model according to the owner's decision making. Two optimization parameters were established: (1) the minimum criteria for scoring attribute similarity (MCAS); and (2) the range of attribute weights (RAW). The cost model proposed in this study can help building owners and managers estimate the project budget at the business planning stage. Santruka Sprendimu priemimas ankstyvuoju statybos projekto etapu turi didele itaka projektui ir ivairiems scenarijams, remiantis savininko reikalavimais, kuriu turi būti laikomasi priimant sprendimus. Ankstyvaisiais statybos projekto etapais informacijos apie projekta paprastai yra nedaug ir ji nera patikima. Del to sudetinga planuoti ir taisyti projekta (ypač išlaidu planavima). Todel šio tyrimo metu buvo sukurtas kainos modelis, kuris galetu būti keičiamas atsižvelgiant i savininko poreikius. Kainos modelis, kuris buvo sukurtas šio tyrimo metu, remiasi atveju analize, pagrista argumentu metodika (angl. CBR). Modelis siūlo samatinius skaičiavimus su panašiausiais ankstesniais atvejais, kurie yra skaičiavimo pagrindas. Šio tyrimo metu procesas buvo optimizuotas naudojant genetinius algoritmus, rodančius projektu skaičiaus kitima tam tikro modelio duomenu bazeje pagal savininko priimamus sprendimus. Buvo nustatyti du optimizavimo parametrai: 1) minimalūs kriterijai veiksniu panašumui ivertinti (angl. MCAS); 2) veiksniu svoriu vertinimo intervalas (angl. RAW). Kainos modelis, pasiūlytas šiame tyrime, gali padeti pastatu savininkams ir valdytojams ivertinti projekto biudžeta verslo planavimo etape.

The discourse of disaster governance is focused on the arrangements, relationships, and roles of the various actors involved in disaster governance. However, due to the lack of research on utilizing emerging technologies in disaster governance systems, this paper addresses the prospective benefits of utilizing Internet of Things (IoT) technologies in smart disaster governance systems. The authors employed a conceptual analysis of the previous research on disaster governance and utilizing IoT in disaster management. The basic concepts and constructs were abstracted from the literature to conceptualize a smart disaster governance system and its processes. As a result, six spheres were portrayed to form the characteristics of the smart disaster governance system, and an integrative conceptual framework for smart disaster governance was developed. The conceptual framework encompasses IoT technologies’ capabilities and disaster governance functions, in addition to the foreseen enhancements in disaster coping capacities and an overall rise in disaster resilience. A hypothetical case study was conducted to investigate the conceptual framework’s plausibility, and it showed a probable enhancement of the disaster governance of the 2018 Kerala floods if the smart disaster governance framework was utilized. This research provides a novel conceptualization of smart disaster governance. It can deepen the understanding of prospective benefits of integrating IoT technologies with disaster governance functions, contribute to disaster governance policy formulations, and construct a basis for future research on smart disaster governance for a sustainable society.

The construction industry is one of the most hazardous industries in many countries. Many studies have asserted that industrial accidents could be prevented by eliminating their root causes. However, given that accident occurrence processes are considerably complex and often invisible, it is difficult to identify and eliminate the root causes. Based on this recognition, this paper aims to analyze the causality of construction accidents on the basis of direct causes that are classified into unsafe actions (UA) and unsafe conditions (UC). A logistic regression is applied to examine associations between UAs and UCs and their significances in triggering construction accidents. Then, a Delphi method is applied to determine the relationships between direct and root causes of construction accidents. This study contributes to an improved understanding of the complex causal process of construction accidents, which is a necessary stepping-stone to prevent construction accidents. Meanwhile, only one-to-one combinations of UCs and UAs are considered in this paper. Thus, follow-up studies to examine the impact of one-to-many or many-to-many combinations are needed.

The importance of construction industries has increased significantly in developing countries because of rapid urbanization. Lack of construction management (CM) skills is one of the main risks for project stakeholders in developing countries. Therefore, developing countries need to create training programs and establish laws and regulations to enhance CM skills. As CM has many functions, it is necessary to prioritize them appropriately. In this study, a survey of practitioners in the Cambodian construction industry was conducted to determine their perceptions of CM and the most important CM function. According to the analysis of data from146 surveys, the study found that safety management is the most important CM function. Considering that the problems faced by developing countries with regard to the construction industry are similar, this study can help developing countries prioritize CM functions to develop training programs, laws, and regulations that improve their construction industries.