Strategies to improve productivity in construction
A systematic literature review
DOI:
https://doi.org/10.46421/entac.v20i1.5927Keywords:
Management, Productivity, Civil constructionAbstract
Productivity management remains a challenge in the building sector, prompting companies to adopt various strategies for improvement. Therefore, this paper aims to identify these strategies through a systematic literature review of 45 studies retrieved from the Web of Science. Nine strategies were identified, with emphasis on digital technologies such as machine learning, artificial intelligence, and augmented reality. Additionally, the strategies highlight BIM, Lean Construction, People-Centred Management, and Modular Construction. The study concludes that the goal of improving productivity remains a hot topic, requiring multiple strategies that encompass various dimensions such as technical (construction methods), technological (applications to support project execution and design), and social (human factors). Therefore, the main contribution of the study lies in helping to delineate current research in this field, permitting a critical reflection on the theme.
References
LEE, T. Y.; AHMAD, F.; SARIJARI, M. A. Current status and future research trends of construction labor productivity monitoring: a
Bibliometric Review. Buildings, v. 13, n. 6, p. 1479, 2023.
HWANG, B.-G. et al. Prioritizing critical management strategies to improving construction productivity: empirical research in
Singapore. Sustainability, v. 12, n. 22, p. 9349, 2020.
BARBOSA, F.; WOETZEL, J.; MISCHKE, J. Reinventing construction: A route of higher productivity. McKinsey Global Institute, 2017.
DE SOUZA, U. E. L. Como aumentar a eficiência da mão-de-obra. 2006.
ALMEIDA, E. L. G. DE et al. Study of delays in constructions: A managerial point of view of private companies in Brasilia, Brazil.
Gestão e Produção, v. 28, n. 3, 2021.
SAMBASIVAN, M. et al. Analysis of delays in Tanzanian construction industry: transaction cost economics (TCE) and structural
equation modelling (SEM) approach. Engineering, Construction and Architectural Management, v. 24, n. 2, p. 308–325, 2017.
VILES, E.; RUDELI, N. C.; SANTILLI, A. Causes of delay in construction projects: a quantitative analysis. Engineering, Construction
and Architectural Management, v. 27, n. 4, p. 917–935, 2020.
CHANGALI, S.; MOHAMMAD, A.; NIEUWLAND, M. VAN. The construction productivity imperative. McKinsey Quarterly, p. 1–10,
CÂMARA BRASILEIRA DA INDÚSTRIA DA CONSTRUÇÃO. Manual Básico de Indicadores de Produtividade na Construção Civil – Vol.
Brasilia: CBIC, 2017.
SINK, D. S.; TUTTLE, T. C. Planejamento e medição para performance. Rio de Janeiro, RJ: Qualitymark, 1993.
THOMAS, H. R. et al. Modeling construction labor productivity. Journal of Construction Engineering and Management, v. 116, n. 4,
p. 705–726, 1990.
SHEHATA, M. E.; EL-GOHARY, K. M. Towards improving construction labor productivity and projects’ performance. Alexandria
Engineering Journal, v. 50, n. 4, p. 321–330, 2011.
SONG, L.; ABOURIZK, S. M. Measuring and Modeling Labor Productivity Using Historical Data. Journal of Construction Engineering
and Management, v. 134, n. 10, p. 786–794, 2008.
EL-MASHALEH, M. S.; MINCHIN JR, R. E.; O’BRIEN, W. J. Management of Construction Firm Performance Using Benchmarking.
Journal of Management in Engineering, v. 23, n. 1, p. 10–17, 2007.
THOMAS, H. R. Benchmarking Construction Labor Productivity. Practice Periodical on Structural Design and Construction, v. 20, n.
, p. 1–10, 2015.
THOMAS, H. R.; YIAKOUMIS, I. Factor Model of Construction Productivity. Journal of Construction Engineering and Management, v.
, n. 4, p. 623–639, 1987.
SOUZA, U. E. L. de. Método para a previsão da produtividade da mão-de-obra e do consumo unitário de materiais para os serviços
de fôrmas, armação, concretagem, alvenaria, revestimentos com argamassa, contrapiso, revestimentos com gesso e
revestimentos cerâmicos. [s.l.] 357f. Tese (Livre docência) – Escola politécnica, Universidade de São Paulo. São Paulo, 2002.
CAMARA BRASILEIRA DA INDÚSTRIA DA CONSTRUÇÃO. Manual básico de indicadores de produtividade na construção civil
completo. Brasília: CBIC, 2017b.
CÂNDIDO, L. F.; LIMA, S. H. DE O.; BARROS NETO, J. DE P. Medição e gestão de desempenho em empresas construtoras. Ambiente
Construído, v. 20, n. 1, p. 195–214, mar. 2020.
DRESCH, A.; LACERDA, D. P.; ANTUNES JÚNIOR, J. A. V. Design Science research: método de pesquisa para avanço da ciência e
tecnologia. Porto Alegre: Bookman, 2015.
HEIGERMOSER, D. et al. BIM-based Last Planner System tool for improving construction project management. Automation in
Construction, v. 104, p. 246–254, ago. 2019.
JAHANGER, Q. K.; TREJO, D.; LOUIS, J. Evaluation of field labor and management productivity in the USA construction industry.
Engineering, Construction and Architectural Management, 20 jul. 2023.
VIGNESHWAR, R. V. K.; SHANMUGAPRIYA, S. Investigating the factors affecting construction site productivity – a case of India.
Engineering, Construction and Architectural Management, v. 30, n. 2, p. 963–985, 14 mar. 2023.
PANERU, S.; JEELANI, I. Computer vision applications in construction: Current state, opportunities & challenges. Automation
in Construction, v. 132, p. 103940, dez. 2021.
HASAN, A. et al. Empirical Study on Implications of Mobile ICT Use for Construction Project Management. Journal of Management
in Engineering, v. 35, n. 6, nov. 2019.
LI, J. et al. Evaluating the Work Productivity of Assembling Reinforcement through the Objects Detected by Deep Learning.
Sensors, v. 21, n. 16, p. 5598, 19 ago. 2021.
CALVETTI, D. et al. Worker 4.0: The Future of Sensored Construction Sites. Buildings, v. 10, n. 10, p. 169, 23 set. 2020.
SADATNYA, A. et al. Machine learning for construction crew productivity prediction using daily work reports. Automation in
Construction, v. 152, p. 104891, ago. 2023.
ZULU, S. L.; SAAD, A. M.; OMOTAYO, T. The Mediators of the Relationship between Digitalisation and Construction Productivity: A
Systematic Literature Review. Buildings, v. 13, n. 4, p. 839, 23 mar. 2023.
RATAJCZAK, J.; RIEDL, M.; MATT, D. BIM-based and AR Application Combined with Location-Based Management System for the
Improvement of the Construction Performance. Buildings, v. 9, n. 5, p. 118, 9 maio 2019.
AKANMU, A. A.; ANUMBA, C. J.; OGUNSEIJU, O. O. Towards next generation cyber-physical systems and digital twins for
construction. Journal of Information Technology in Construction, v. 26, p. 505–525, Hwang, 26 jul. 2021.
FATHI, SAHAND; FATHI, SOHEIL; BALALI, V. Time–Space Conflict Management in Construction Sites Using Discrete Event
Simulation (DES) and Path Planning in Unity. Applied Sciences, v. 13, n. 14, p. 8128, 12 jul. 2023.
TURNER, C. J. et al. Utilizing Industry 4.0 on the Construction Site: Challenges and Opportunities. IEEE Transactions on Industrial
Informatics, v. 17, n. 2, p. 746–756, fev. 2021.
YU, Y. et al. Automatic Biomechanical Workload Estimation for Construction Workers by Computer Vision and Smart Insoles.
Journal of Computing in Civil Engineering, v. 33, n. 3, maio 2019.
MESA FERNÁNDEZ, J. M. et al. Bibliometric Analysis of the Application of Artificial Intelligence Techniques to the Management of
Innovation Projects. Applied Sciences, v. 12, n. 22, p. 11743, 18 nov. 2022.
ASLAM, M.; GAO, Z.; SMITH, G. Development of Innovative Integrated Last Planner System (ILPS). International Journal of Civil
Engineering, v. 18, n. 6, p. 701–715, 11 jun. 2020.
RYU, J. et al. Automated Action Recognition Using an Accelerometer-Embedded Wristband-Type Activity Tracker. Journal of
Construction Engineering and Management, v. 145, n. 1, jan. 2019.
M. A. AlRushood, F. Rahbar, S. Z. Selim, and F. Dweiri, “Accelerating Use of Drones and Robotics in Post-Pandemic Project Supply
Chain,” Drones, vol. 7, no. 5, p. 313, May 2023, doi: 10.3390/drones7050313.
JAHANGER, Q. K. et al. Potential Influencing Factors Related to Digitalization of Construction-Phase Information Management by
Project Owners. Journal of Management in Engineering, v. 37, n. 3, maio 2021.
PRADHANANGA, P.; ELZOMOR, M.; SANTI KASABDJI, G. Identifying the Challenges to Adopting Robotics in the US Construction
Industry. Journal of Construction Engineering and Management, v. 147, n. 5, p. 622–639, 14 maio 2021.
JIANG, L. et al. Study on the construction workforce management based on lean construction in the context of COVID-19.
Engineering, Construction and Architectural Management, v. 30, n. 8, p. 3310–3329, 1 set. 2023.
LERCHE, J.; ENEVOLDSEN, P.; SEPPÄNEN, O. Application of Takt and Kanban to Modular Wind Turbine Construction. Journal of
Construction Engineering and Management, v. 148, n. 2, fev. 2022.
NOORZAI, E. Evaluating lean techniques to improve success factors in the construction phase. Construction Innovation, v. 23, n. 3,
p. 622–639, 14 abr. 2023.
PÓVOAS SOUTO FILHO, J. A.; CASADO LORDSLEEM JÚNIOR, A.; AQUINO ROCHA, J. H. Construção enxuta em obras de edificações:
avaliação e sugestões. Revista de Gestão e Projetos, v. 13, n. 3, p. 117–148, 9 dez. 2022.
LIMENIH, Z. M.; DEMISSE, B. A.; HAILE, A. T. The Usefulness of Adopting the Last Planner System in the Construction Process of 4
Addis Ababa Road Projects. Advances in Civil Engineering, v. 2022, p. 1–12, 26 fev. 2022.
AHMED, S.; HOSSAIN, M. M.; HAQ, I. Implementation of lean construction in the construction industry in Bangladesh: awareness,
benefits and challenges. International Journal of Building Pathology and Adaptation, v. 39, n. 2, p. 368–406, 31 mar. 2020.
SCHULZE, F.; DALLASEGA, P. Lean and Industry 4.0 mitigating common losses in Engineer-to-Order theory and practice: an
exploratory study. Flexible Services and Manufacturing Journal, 31 jul. 2023.
MESÁROŠ, P.; MANDIČÁK, T.; BEHÚNOVÁ, A. Use of BIM technology and impact on productivity in construction project
management. Wireless Networks, v. 28, n. 2, p. 855–862, 16 fev. 2022.
KIM, SEUNGHO; KIM, SANGYONG; LEE, D.-E. 3D Point Cloud and BIM-Based Reconstruction for Evaluation of Project by As-Planned
and As-Built. Remote Sensing, v. 12, n. 9, p. 1457, 4 maio 2020.
WONG, J.; RASHIDI, A.; ARASHPOUR, M. Evaluating the Impact of Building Information Modeling on the Labor Productivity of
Construction Projects in Malaysia. Buildings, v. 10, n. 4, p. 66, 30 mar. 2020.
CHA, H.; KIM, J. A study on 3D/BIM-based on-site performance measurement system for building construction. Journal of Asian
Architecture and Building Engineering, v. 19, n. 6, p. 574–585, 1 nov. 2020.
SHIN, M.-H.; JUNG, J.-H.; KIM, H.-Y. Quantitative and Qualitative Analysis of Applying Building Information Modeling (BIM) for
Infrastructure Design Process. Buildings, v. 12, n. 9, p. 1476, 17 set. 2022.
ALABOUD, N.; ALSHAHRANI, A. Adoption of Building Information Modelling in the Saudi Construction Industry: An Interpretive
Structural Modelling. Sustainability, v. 15, n. 7, p. 6130, 3 abr. 2023.
MOYO, T.; CRAFFORD, G.; EMUZE, F. People-centred management for improving construction workers’ productivity in Zimbabwe.
Built Environment Project and Asset Management, v. 11, n. 2, p. 350–368, 27 abr. 2021.
BAMFO-AGYEI, E.; THWALA, D. W.; AIGBAVBOA, C. The effect of management control on labour productivity of labour-intensive
works in Ghana. Acta Structilia, v. 29, n. 1, 2022.
GURMU, A. T. Fuzzy synthetic evaluation of human resource management practices influencing construction labour productivity.
International Journal of Productivity and Performance Management, v. 70, n. 2, p. 256–276, 30 mar. 2020b
TAM, N. VAN; WATANABE, T.; HAI, N. L. Measuring Work Autonomy and Its Role in Enhancing Labour Productivity: The Case of the
Vietnamese Construction Industry. Buildings, v. 12, n. 9, p. 1477, 17 set. 2022.
SHAHPARI, M. et al. Assessing the productivity of prefabricated and in-situ construction systems using hybrid multi-criteria
decision making method. Journal of Building Engineering, v. 27, p. 100979, jan. 2020.
ZHAO, J. et al. Using Real-Time Tracking of Materials and Labor for Kit-Based Logistics Management in Construction. Frontiers in
Built Environment, v. 7, 3 set. 2021.
LU, W.; YANG, Z.; KONG, L. Identification of Learning Effects in Modular Construction Manufacturing. Automation in Construction,
v. 154, p. 105010, out. 2023.
SMALL, E. P.; BAKRY, I.; AYYASH, L. Evaluating the effect of TQM on MEP construction productivity and project delivery in Dubai.
International Journal of Construction Management, v. 21, n. 10, p. 1061–1075, 3 out. 2021.
ALAWAG, A. M. et al. The Role of the Total-Quality-Management (TQM) Drivers in Overcoming the Challenges of Implementing
TQM in Industrialized-Building-System (IBS) Projects in Malaysia: Experts’ Perspectives. Sustainability, v. 15, n. 8, p. 6607, 13 abr.
DEMIRDÖĞEN, G. et al. Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC
Industry. Sustainability, v. 13, n. 18, p. 10029, 7 set. 2021.
GURMU, A. T. Construction materials management practices enhancing labour productivity in multi-storey building projects.
International Journal of Construction Management, v. 20, n. 1, p. 77–86, 2 jan. 2020a.
GURMU, A. T. Hybrid Model for Assessing the Influence of Safety Management Practices on Labor Productivity in Multistory
Building Projects. Journal of Construction Engineering and Management, v. 147, n. 11, nov. 2021.
ERNSTSEN, S. N. et al. How Innovation Champions Frame the Future: Three Visions for Digital Transformation of Construction.
Journal of Construction Engineering and Management, v. 147, n. 1, 2021.
BARBOSA, G. et al. Heijunka System to Level Telescopic Forklift Activities Using Tablets in Construction Site (C. T. Formoso & P.
Tzortzopoulos, Eds.)21th Annual Conference of the International Group for Lean Construction. Anais...Civil engineer trainee.
Colmeia Construction Company, Fortaleza, Brazil, 2013. Disponível em: <http://iglc.net/Papers/Details/873/pdf>
SACKS, R.; KOSKELA, L. Interaction of lean and building information modeling in construction. Journal of Construction Engineering
and Management, v. 136, n. 9, p. 968–981, 2010.
ALTAN, E.; IŞIK, Z. Digital twins in lean construction: a neutrosophic AHP – BOCR analysis approach. Engineering, Construction and
Architectural Management, 2023.
