Journal of Construction Engineering and Management

The literature acknowledges criminal behavior in the architecture, engineering, and construction (AEC) industry as a problem that needs addressing, but few comprehensive reviews of the research field exist to date. Thus, the purpose of this study is to examine the extent of research carried out in the field. The paper reports on a scoping literature review on crime in the AEC industry and explores how the literature covers crime in construction, and more specifically the topics of materials, organization, and health, safety, and environment (HSE). The results indicate that research in this area has only recently begun to take off. Characteristics of the AEC industry seem to facilitate the embedding of criminal actors, and in turn, activities leading to crime. The research topics are not covered evenly, and some, namely materials and HSE issues, are lagging behind. This study aids practitioners by highlighting the extent of these topics within the AEC industry. It also provides a number of departure points that can be used by academics for further research.

Comprehensive and effective safety risk identification in metro construction has a significant impact on risk management. Although previous studies attempted to obtain a final ranking of the risk factors using various risk identification methods, they did not consider real-time risk identification. To address the complex issues involved, a model was established to identify the possible safety risks among the many potential risk factors in real time, considering the uncertain and complex environment in metro construction adjacent to buildings/structures. The study made decisions regarding the weights of the safety risk criteria at various stages of the construction. The safety risk factors and degrees of closeness were ranked at a specific time using real-time construction data. The model was demonstrated by real-time safety risk identification in a typical case study of metro construction adjacent to buildings/structures. The results are consistent with the reality of safety risks at various stages of such a metro project. The method of real-time risk identification is established to be feasible and effective, and experiments are proposed to identify risks in similar metro projects.

Behavior-based safety (BBS), which contains definition, observation, intervention, and test, is proven to be useful in safety management on-site. Safety training is regarded as an effective method for the BBS intervention. However, existing studies provide little attention to workers’ personal behavior patterns that limit the persistent effectiveness of interventions. This paper proposes a hybrid recommendation approach that can enhance the effectiveness of safety training in the Chinese construction industry. The proposed approach integrates content-based personalized recommendation and MapReduce-based collaborative filtering for personalized recommendation. The personal behavior patterns of workers are automatically analyzed through data that are generated from training. Then, reasonable training materials are recommended for behavior modification. The workers’ behavior modification (WoBeMo) system is designed to implement safety training. A pilot study on metro construction sites showed that the unsafe behavior rate ($S$) of 20 laborers who were engaged in scaffolding work decreased over 70% after intervention, and were reduced over 60% compared with another group of laborers not using the WoBeMo. Application results indicate the feasibility and practicability of the proposed approach on modifying workers’ unsafe behaviors and improving safety performance on construction sites.

Workforce planning in the construction industry too often ignores the symbiotic relationship between employee and employer objectives by overly concentrating on corporate objectives such as maximizing productivity at the expense of construction workers’ career development needs. Overall, the consequence of this approach is suboptimal performance. To address this problem, this paper presents an innovative multiobjective model that enables managers to optimize the relationship between these interdependent corporate priorities. The proposed model was implemented and solved using mixed-integer nonlinear programming on a case study involving the allocation of tasks to employees with different skill levels in a multidisciplinary engineering consulting company. While leading to a small loss of productivity, the results show a significant improvement in the career development of workers compared to conventional productivity-oriented workforce planning models, with on average 8.6% improvement in employees’ closeness to their ideal skill set. Furthermore, the model produced Pareto-optimal points and a Pareto curve that enabled client-model users to select optimum job allocation based on their preferences. This research represents a paradigm shift toward a new class of socially responsible workforce planning models in which the objectives of both employees and employers are optimized.

The representation of the Hispanic construction workforce has substantially increased over the last 15 years, and it continues to increase. Because of this, the Hispanic construction workforce represents a crucial segment of the US construction workforce. Unfortunately, the safety performance of Hispanic workers has been documented as an area requiring special attention due to the higher rates of fatalities and nonfatal injuries among Hispanic workers. Active cultural differences (ACDs) have been identified as one of the causes that negatively influence the performance of diverse construction crews. Therefore, the construction industry strives to adopt novel management techniques to better manage diverse crews. Accordingly, this study illustrates a training module that provides the knowledge to help construction firms overcome the undesirable influences of ACDs and strengthen their desirable effects. The findings strongly suggest that the proposed training is accepted by construction personnel. The proposed training would not only improve the overall safety performance of diverse construction crews but also positively influence other project success factors such as quality, productivity, and crew performance.