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Agyekum-Mensah, G, Reid, A and Temitope, T A (2020) Methodological Pluralism: Investigation into Construction Engineering and Management Research Methods. Journal of Construction Engineering and Management, 146(03).

Ayhan, B U and Tokdemir, O B (2020) Accident Analysis for Construction Safety Using Latent Class Clustering and Artificial Neural Networks. Journal of Construction Engineering and Management, 146(03).

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001762
  • Abstract:
    Despite many improvements in safety management, the construction industry still has the highest potential for occupational injuries including High Severe (HS) work events, which result in injuries or fatalities, and Low Severe (LS) work events, which cause near misses or nonserious injuries. The analysis of incidents is highly dependent on the quality of records. Problems in recording and the heterogeneity of incident data may create conflicts while analyzing the relationship between attributes. The objective of the study was to develop a novel model to predict the outcomes of construction incidents using Latent Class Clustering Analysis (LCCA) and Artificial Neural Networks (ANNs) and determine necessary preventative actions. ANN has been used for many years to investigate the nonlinear relation between attributes and generate a logic between them. Herein, ANN was used to perform severity analyses of incidents utilizing real data, which were collected from various construction sites anonymously. Many factors affect the performance of ANN, including the size of the input and the heterogeneity of data. LCCA was used to seek out better performance and accuracy in ANN applications by reducing the heterogeneity of the incidents. By applying LCCA, attributes that possess different probabilities were clustered together and put into the ANN model. Then, the study concluded by providing a necessary preventative measure according to the result of incidents forecasted in advance. The research has two significant contributions. First, the hybrid model revealed promising results as the performance of the ANN-based predictive model was enhanced by addressing the heterogeneity of data. Second, the study presented professionals with practical preventative actions to avoid construction incidents according to the results of prediction.

Bowen, P and Zhang, R P (2020) Cross-Boundary Contact, Work-Family Conflict, Antecedents, and Consequences: Testing an Integrated Model for Construction Professionals. Journal of Construction Engineering and Management, 146(03).

Chan, A P C, Nwaogu, J M and Naslund, J A (2020) Mental Ill-Health Risk Factors in the Construction Industry: Systematic Review. Journal of Construction Engineering and Management, 146(03).

Collinge, W (2020) Stakeholder Engagement in Construction: Exploring Corporate Social Responsibility, Ethical Behaviors, and Practices. Journal of Construction Engineering and Management, 146(03).

Dutta, A, Breloff, S P, Dai, F, Sinsel, E W, Warren, C M and Wu, J Z (2020) Identifying Potentially Risky Phases Leading to Knee Musculoskeletal Disorders during Shingle Installation Operations. Journal of Construction Engineering and Management, 146(03).

Farahani, A, Wallbaum, H and Dalenbäck, J (2020) Cost-Optimal Maintenance and Renovation Planning in Multifamily Buildings with Annual Budget Constraints. Journal of Construction Engineering and Management, 146(03).

Gao, Y, González, V A and Yiu, T W (2020) Exploring the Relationship between Construction Workers’ Personality Traits and Safety Behavior. Journal of Construction Engineering and Management, 146(03).

Gunduz, M and Elsherbeny, H A (2020) Operational Framework for Managing Construction-Contract Administration Practitioners’ Perspective through Modified Delphi Method. Journal of Construction Engineering and Management, 146(03).

Gurmu, A T and Ongkowijoyo, C S (2020) Predicting Construction Labor Productivity Based on Implementation Levels of Human Resource Management Practices. Journal of Construction Engineering and Management, 146(03).

Haj Seiyed Taghia, S A, Darvishvand, H R and Ebrahimi, M (2020) Economic Analyses for Low-Strength Concrete Wrapped with CFRP to Improve the Mechanical Properties and Seismic Parameters. Journal of Construction Engineering and Management, 146(03).

Ho Song, M and Fischer, M (2020) Empirical Determination of the Smallest Batch Sizes for Daily Planning. Journal of Construction Engineering and Management, 146(03).

Ji, Y and Leite, F (2020) Optimized Planning Approach for Multiple Tower Cranes and Material Supply Points Using Mixed-Integer Programming. Journal of Construction Engineering and Management, 146(03).

Lee, C, Chong, H, Li, Q and Wang, X (2020) Joint Contract–Function Effects on BIM-Enabled EPC Project Performance. Journal of Construction Engineering and Management, 146(03).

Lee, Y Y R, Samad, H and Miang Goh, Y (2020) Perceived Importance of Authentic Learning Factors in Designing Construction Safety Simulation Game-Based Assignment: Random Forest Approach. Journal of Construction Engineering and Management, 146(03).

Lijauco, F, Gajendran, T, Brewer, G and Rasoolimanesh, S M (2020) Impacts of Culture on Innovation Propensity in Small to Medium Enterprises in Construction. Journal of Construction Engineering and Management, 146(03).

Lyu, H, Sun, W, Shen, S and Zhou, A (2020) Risk Assessment Using a New Consulting Process in Fuzzy AHP. Journal of Construction Engineering and Management, 146(03).

Mansouri, S, Castronovo, F and Akhavian, R (2020) Analysis of the Synergistic Effect of Data Analytics and Technology Trends in the AEC/FM Industry. Journal of Construction Engineering and Management, 146(03).

Shiha, A, Dorra, E M and Nassar, K (2020) Neural Networks Model for Prediction of Construction Material Prices in Egypt Using Macroeconomic Indicators. Journal of Construction Engineering and Management, 146(03).

Votto, R, Lee Ho, L and Berssaneti, F (2020) Applying and Assessing Performance of Earned Duration Management Control Charts for EPC Project Duration Monitoring. Journal of Construction Engineering and Management, 146(03).