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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).
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).
- Type: Journal Article
- Keywords:
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001759
- Abstract:
Technological advancements focusing on effective and efficient information modeling, visualization, resource tracking, and collaboration have gained substantial traction in the architectural, engineering, construction, and facility management (AEC/FM) industry in the last 10 years. The use of advanced technologies has resulted in safer jobsites hosting more productive project teams building more sustainable and resilient facilities and infrastructure. Recently, the innovative use of data and analytical approaches has had a major positive effect on a variety of businesses by incorporating data-driven applications and approaches. However, the AEC/FM industry is still lagging behind many other industries in leveraging the true power of data. Data analytics concepts and tools integrated with emerging construction trends such as building information modeling (BIM) have a high potential to revolutionize industry practices. This paper consolidates the record of current efforts in the AEC/FM body of knowledge (BOK) and body of practice (BOP) that incorporate the use of Data Analytics with common Technology Trends in various Application Areas. Identifying common subsections of each category, a three dimensional evidenced taxonomy was developed that maps (1) Data Analytics concepts such as cloud computing and machine learning onto, (2) AEC/FM emerging trends such as BIM and automation, and (3) existing and potential AEC/FM applications such as safety and progress monitoring. To further expand the validity of the results and explore opportunities and potential, a survey with the same categorization was developed and distributed among industry experts. Comparing the results of the exploration of the BOK and the survey illustrated the popularity of BIM among industry practitioners and in academic research. Also, process efficiency and productivity improvement were the two Application Areas that demonstrated the most potential to benefit from the integration of Data Analytics and Technology Trends. Analysis of the survey results indicated that, with a 95% confidence level, there is no statistically significant difference among the Technology Trends or Application Areas, as identified in the literature, that can benefit from Data Analytics. The results presented in this study demonstrate evidence of the revolutionizing power of Data Analytics in the AEC/FM industry.
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).