The accidental release of hazardous energy is one of the causes of construction site accidents. This risk is considerably increased during petrochemical plant construction because the project itself is complex in terms of process, equipment, and environment. In addition, a general construction safety barrier hardly isolates and controls site hazardous energy effectively. Thus, this study proposes an Internet of Things (IoT) sensor-based building information modeling (BIM) system, which can be regarded as a new smart barrier design method for hazardous energy in petrochemical construction. In this system, BIM is used to support the identification of on-site hazardous energy, whereas IoT is used to collect the location of on-site personnel in real time. A hazardous energy isolation rule is defined to enable the system to generate a smart barrier on the web terminal window, thereby ensuring the safety of on-site person. This system has been applied to a large-scale construction project in Sinopec for one year and accumulated substantial practical data, which supported the idea about the application of sensor and BIM technology in construction. The related effects of the system on hazardous energy management are also presented in this work.

The rapid development of economics requires highly efficient and environment-friendly urban transportation systems. Such requirement presents challenges in sustainable urban transportation. The analysis and understanding of transportation-related behaviors provide one approach to dealing with complicated transportation activities. In this study, the management of traffic systems is divided into four levels with a structural and systematic perspective. Then, several special cases from the perspective of behavior, including purchasing behaviors toward new energy vehicles, choice behaviors toward green travel, and behavioral reactions toward transportation demand management policies, are investigated. Several management suggestions are proposed for transportation authorities to improve sustainable traffic management.

E-commerce, new retail, and other changes have highlighted the requirement of high efficiency and accuracy in the logistics service. As an important section in logistics and supply chain management, warehouses need to respond positively to the increasing requirement. The “smart warehouse” system, which is equipped with emerging warehousing technologies, is increasingly attracting the attention of industry and technology giants as an efficient solution for the future of warehouse development. This study provides a holistic view of operations management problems within the context of smart warehouses. We provide a framework to review smart warehouse operations management based on the characteristics of smart warehouses, including the perspectives of information interconnection, equipment automation, process integration, and environmental sustainability. A comprehensive review of relevant literature is then carried out based on the framework with four perspectives. This study could provide future research directions on smart warehouses for academia and industry practitioners.

Today’s supply chain is becoming complex and fragile. Hence, supply chain managers need to create and unlock the value of the smart supply chain. A smart supply chain requires connectivity, visibility, and agility, and it needs be integrated and intelligent. The digital twin (DT) concept satisfies these requirements. Therefore, we propose creating a DT-driven supply chain (DTSC) as an innovative and integrated solution for the smart supply chain. We provide background information to explain the DT concept and to demonstrate the method for building a DTSC by using the DT concept. We discuss three research opportunities in building a DTSC, including supply chain modeling, real-time supply chain optimization, and data usage in supply chain collaboration. Finally, we highlight a motivating case from JD.COM, China’s largest retailer by revenue, in applying the DTSC platform to address supply chain network reconfiguration challenges during the COVID-19 pandemic.

This study presents a systematic review of the literature on service-oriented manufacturing (SOM). Specifically, we focus on the impact of SOM on firm operating decisions, which distinguishes this work from previous reviews. This study proposes a classification framework for SOM research based on product flow, from its design to its final disposal. Although SOM has been studied for many years, most related research remains conceptual. Our criterion for choosing papers is that they must be relevant to practical problems. This review aims to provide readers a guide that will facilitate their search for papers in their field of interest. More importantly, we hope that this review can provide insightful managerial implications for SOM.

The purpose of this paper is to delineate the research challenges of human–machine collaboration in risky decision-making. Technological advances in machine intelligence have enabled a growing number of applications in human–machine collaborative decision-making. Therefore, it is desirable to achieve superior performance by fully leveraging human and machine capabilities. In risky decision-making, a human decision-maker is vulnerable to cognitive biases when judging the possible outcomes of a risky event, whereas a machine decision-maker cannot handle new and dynamic contexts with incomplete information well. We first summarize features of risky decision-making and possible biases of human decision-makers therein. Then, we argue the necessity and urgency of advancing human–machine collaboration in risky decision-making. Afterward, we review the literature on human–machine collaboration in a general decision context, from the perspectives of human–machine organization, relationship, and collaboration. Lastly, we propose challenges of enhancing human–machine communication and teamwork in risky decision-making, followed by future research avenues.

Synchronous collaboration sessions within the context of 4D BIM position construction professionals into a complex socio–technical system. This system includes hardware, software, people, and broader community aspects. This article strictly focuses on the ontology representation of synchronous collaboration sessions with collocated collective decision-making. The model is designed by considering various 4D BIM model uses while a digital multiuser touch table facilitates the collaboration between actors. The outlined ontological model aims to improve interoperability and to move toward a knowledge-driven, smart-built environment paradigm. A knowledge engineering methodology is outlined, by virtue of which the semantics of the presented model are defined and discussed. Concepts from nearby knowledge fields, especially from the Industry Foundation Classes, are reused. Several examples on querying the knowledge base according to the project meeting requirements are outlined to demonstrate the benefits of using the model. Although 4D BIM model data can be imported by using standard formats, capturing data about the social context remains a challenge in the future. This is expected to change the ontology model structure by considering user ergonomics, data modeling requirements, as well as technical implementation constraints.

Grand infrastructure projects, such as dam, power plant, petroleum, and gas industry projects, have several contractors working on them in several independent sub-projects. The concern of reducing the duration of these projects is one of the important issues among various aspects; thus, our aim is to fulfill the requirements by using the game theory approach. In this study, a mixed-integer programming model consisting of game theory and project scheduling is developed to reduce the duration of projects with a minimum increase in costs. In this model, two contractors in successive periods are entered into a step-by-step competition by the employer during dynamic games, considering an exchange in their limited resources. The optimum solution of the game in each stage are selected as the strategy, and the resources during the game are considered to be renewable and limited. The strategy of each contractor can be described as follows: 1) share their resources with the other contractor and 2) not share the resources with the other contractor. This model can act dynamically in all circumstances during project implementation. If a player chooses a non-optimum strategy, then this strategy can immediately update itself at the succeeding time period. The proposed model is solved using the exact Benders decomposition method, which is coded in GAMS software. The results suggest the implementation of four step-by-step games between the contractors. Then, the results of our model are compared with those of the conventional models. The projects’ duration in our model is reduced by 22.2%. The nominal revenue of both contractors has also reached a significant value of 46078 units compared with the relative value of zero units in the original model. Moreover, we observed in both projects the decreases of 19.5%, 20.9%, and 19.7% in the total stagnation of resources of types 1, 2, and 3, respectively.

The management of resources has been claimed to be as important as scheduling methods. Inefficiency in managing resources may bring about severe delays and cost overruns caused by resource shortages in some cases and/or idle resources in others. Therefore, resources should be utilized efficiently to prevent project failures. Resource leveling is one of the approaches that are used for the management of resources. It aims to minimize fluctuations, peaks, and valleys in resource utilization without changing the completion time of a project and the number of resources required. Although the main principle behind traditional resource leveling is achieving an even flow of resources while the original project duration remains unchanged, the literature supports the need to develop an efficient model that discriminates among the activities that are selected for participation in resource leveling. For this purpose, this study has developed a model that considers the float consumption rates of activities in resource leveling. The float consumption rate is the percentage that is set to determine the maximum amount of float which will be consumed to shift the start time of the activity. The proposed model allows a scheduler to assign float consumption rates to each activity that can be used during the resource leveling procedure. When the required information is inputted, the proposed model automatically changes the required daily resources as it shifts the noncritical activities along their available total float times. The proposed model is expected to minimize the likelihood of severe delays and cost overruns. The model is demonstrated by constructing a network and its resource utilization histograms.

Given the European Public Procurement Directive 2014/24/EU, policymakers have ordered the inclusion of various criteria, such as the price, life-cycle costs, environmental, and social aspects, in the evaluation of tenders for public construction projects. Consequently, the relevance of non-monetary award criteria has gained significant value. However, the established evaluation formulas, which are used to obtain the best value for money procurement, have resulted in legal disputes. The existing evaluation formulas exhibit mathematical weaknesses, wherein scoring indices do not express economic efficiency adequately. Thus, a conflict is observed between the political requirement of non-monetary award criteria and their evaluation by contracting authorities. To overcome such dilemma, an extensive literature review is conducted. Specifically, this study explores the essential problems of existing evaluation formulas and develops a more reliable method. The technique from the field of efficiency analysis, i.e., Data Envelopment Analysis (DEA), is adopted in this study. For contract awarding, the DEA is extended by introducing a decision theoretical framework. For public procurement, the proposed method combines two advantages. First, the proposed method ensures the derivation of a robust tender ranking given that with respect to clients’ preferences, irrelevant and insufficiently tailored tenders do not influence the scoring. Second, the proposed method supports the intention of policy makers to promote public goals, such as sustainable aspects. By disclosing the strengths and weaknesses of bidders with respect to their competitors, all bidders can obtain a precise overview of their performance regarding the award criteria. In sum, the proposed method allows a targeted improvement of certain criteria values in future tenders and consequently leads to an enhancement of public goals.