Share:


Scientometric review of construction project schedule studies: trends, gaps and potential research areas

    Gebrehana Derbe Affiliation
    ; Yashuai Li Affiliation
    ; Di Wu Affiliation
    ; Qiuhong Zhao   Affiliation

Abstract

Scheduling plays a fundamental role in construction projects’ success and thus has drawn attention from both academic researchers and industry practitioners. A large number of research articles tend to solve emerging challenges in construction project schedule (CPS). Therefore, there is a strong need of systematic review on existing studies. In this study, a total of 332 articles were retrieved from Scopus database using title, abstract and keywords with respect to CPS and filtered by document type, language type and abstract content. In particular, science mapping approach was adopted to analyse selected journal articles. These articles were examined using three sequential processes, including bibliometric search, scientometric analysis, and in-depth qualitative discussion. It could demonstrate the most influential journals, researchers, published articles, and active countries/regions in this area. In addition, major CPS knowledge areas were identified and summarized as CPS constructability, applications of variety of CPS methods, CPS optimization models and algorithms, identification and quantification of schedule risks and uncertainties, CPS performance management, and adopting new emerging CPS technologies and methods. Furthermore, knowledge gaps and future potential research directions were also discussed in detail. Finally, a comprehensive CPS framework was proposed as a sound reference in future research.

Keyword : construction project schedule (CPS), scheduling methods, schedule uncertainties, resource-constrained scheduling, schedule optimization, scientometric analysis, bibliometric

How to Cite
Derbe, G., Li, Y., Wu, D., & Zhao, Q. (2020). Scientometric review of construction project schedule studies: trends, gaps and potential research areas. Journal of Civil Engineering and Management, 26(4), 343-363. https://doi.org/10.3846/jcem.2020.12317
Published in Issue
Apr 9, 2020
Abstract Views
4119
PDF Downloads
2187
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abbondati, F., Lamberti, R., & Capaldo, F. S. (2016). Linear scheduling analysis toolkit for road and airports construction projects. ARPN Journal of Engineering and Applied Sciences, 11(11), 6863–6874.

Abd El Razek, R. H., Diab, A. M., Hafez, S. M., & Aziz, R. F. (2010). Time-cost-quality trade-off software by using simplified Genetic algorithm for typical-repetitive construction projects. World Academy of Science, Engineering and Technology, 61, 312–321.

Abdirad, H., & Pishdad-Bozorgi, P. (2014). Trends of assessing BIM implementation in construction research. In 2014 International Conference on Computing in Civil and Building Engineering (pp. 496–503). Orlando, Florida, United States. https://doi.org/10.1061/9780784413616.062

Abou-Ibrahim, H., Hamzeh, F., Zankoul, E., Munch Lindhard, S., & Rizk, L. (2019). Understanding the planner’s role in lookahead construction planning. Production Planning and Control, 30(4), 271–284. https://doi.org/10.1080/09537287.2018.1524163

Acemoglu, D., & Restrepo, P. (2019). The wrong kind of AI? Artificial intelligence and the future of labor demand. Cambridge Journal of Regions, Economy and Society. https://doi.org/10.1093/cjres/rsz022

Agarwal, R., Chandrasekaran, S., & Sridhar, M. (2016). Imagining construction’s digital future. McKinsey Productivity Sciences Center. https://www.mckinsey.com/industries/capitalprojects-and-infrastructure/our-insights/imagining-constructions-digital-future

Aghaei Chadegani, A., Salehi, H., Yunus, M., Farhadi, H., Fooladi, M., Farhadi, M., & Ale Ebrahim, N. (2013). A comparison between two main academic literature collections: Web of Science and Scopus databases. Asian Social Science, 9(5), 18–26. https://doi.org/10.5539/ass.v9n5p18

Akinci, B., Fischer, M., & Kunz, J. (2002). Automated generation of work spaces required by construction activities. Journal of Construction Engineering and Management, 128(4), 306–315. https://doi.org/10.1061/(ASCE)0733-9364(2002)128:4(306)

Al Haj, R. A., & El-Sayegh, S. M. (2015). Time-cost optimization model considering float-consumption impact. Journal of Construction Engineering and Management, 141(5), 04015001. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000966

Al Nasseri, H., & Aulin, R. (2016). Enablers and barriers to project planning and scheduling based on construction projects in Oman. Journal of Construction in Developing Countries, 21(2), 1–20. https://doi.org/10.21315/jcdc2016.21.2.1

Al Nasseri, H., Widen, K., & Aulin, R. (2016). A taxonomy of planning and scheduling methods to support their more efficient use in construction project management. Journal of Engineering, Design and Technology, 14(3), 580–601. https://doi.org/10.1108/JEDT-11-2013-0078

Ali, M. M., & Elazouni, A. (2009). Finance-based CPM/LOB scheduling of projects with repetitive non-serial activities. Construction Management and Economics, 27(9), 839–856. https://doi.org/10.1080/01446190903191764

Alias, S. E., & Ismail, N. (2012). The usage of critical path method software in Malaysian construction. International Journal of Knowledge, Culture and Change Management, 11(5), 77–88. https://doi.org/10.18848/1447-9524/CGP/v11i05/50198

Aliverdi, R., Moslemi Naeni, L., & Salehipour, A. (2013). Monitoring project duration and cost in a construction project by applying statistical quality control charts. International Journal of Project Management, 31(3), 411–423. https://doi.org/10.1016/j.ijproman.2012.08.005

AlNasseri, H., & Aulin, R. (2015). Assessing understanding of planning and scheduling theory and practice on construction projects. EMJ – Engineering Management Journal, 27(2), 58–72. https://doi.org/10.1080/10429247.2015.1035963

Alsehaimi, A. O., Fazenda, P. T., & Koskela, L. (2014). Improving construction management practice with the Last Planner System: A case study. Engineering, Construction and Architectural Management, 21(1), 51–64. https://doi.org/10.1108/ECAM-03-2012-0032

Amiri, M. J. T., Haghighi, F., Eshtehardian, E., Hematian, M., & Kordi, H. (2017). Optimization of time and cost in critical chain project scheduling problem using genetic algorithm. Journal of Engineering and Applied Sciences, 12(4), 871–876.

Anderson, K., Kim, H., Lee, S., & Hildreth, J. (2013). Generating construction schedules through automatic data extraction using open BIM (building information modeling) technology. Automation in Construction, 35, 285–295. https://doi.org/10.1016/j.autcon.2013.05.020

Ashuri, B., & Tavakolan, M. (2012). Fuzzy enabled hybrid genetic algorithm-particle swarm optimization approach to solve TCRO problems in construction project planning. Journal of Construction Engineering and Management, 138(9), 1065–1074. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000513

Bakkalbasi, N., Bauer, K., Glover, J., & Wang, L. (2006). Three options for citation tracking: Google Scholar, Scopus and Web of Science. Biomedical Digital Libraries, 3(1), 7. https://doi.org/10.1186/1742-5581-3-7

Bakry, I., Moselhi, O., & Zayed, T. (2016). Optimized scheduling and buffering of repetitive construction projects under uncertainty. Engineering, Construction and Architectural Management, 23(6), 782–800. https://doi.org/10.1108/ECAM-05-2014-0069

Ballesteros-Pérez, P., Elamrousy, K. M., & González-Cruz, M. C. (2019). Non-linear time-cost trade-off models of activity crashing: Application to construction scheduling and project compression with fast-tracking. Automation in Construction, 97, 229–240. https://doi.org/10.1016/j.autcon.2018.11.001

Băncescu, M. (2016). Controlling project schedule progress, using control charts. Cybernetics and Systems, 47(7), 602–615. https://doi.org/10.1080/01969722.2016.1211883

Bankar, R. S., & Lihitkar, S. R. (2019). Science mapping and visualization tools used for bibliometric and scientometric studies: A comparative study. Journal of Advancements in Library Sciences, 6(1), 382–394.

Bansal, V. K., & Pal, M. (2009). Construction schedule review in GIS with a navigable 3D animation of project activities. International Journal of Project Management, 27(5), 532–542. https://doi.org/10.1016/j.ijproman.2008.07.004

Baqerin, M. H., Shafahi, Y., & Kashani, H. (2016). Application of Weibull analysis to evaluate and forecast schedule performance in repetitive projects. Journal of Construction Engineering and Management, 142(2), 04015058. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001040

Bilal, M., Oyedele, L. O., Qadir, J., Munir, K., Ajayi, S. O., Akinade, O. O., Owolabi, H. A., Alaka, H. A., & Pasha, M. (2016). Big Data in the construction industry: A review of present status, opportunities, and future trends. Advanced Engineering Informatics, 30(3), 500–521. https://doi.org/10.1016/j.aei.2016.07.001

Bonnal, P., Baudin, M., & De Jonghe, J. (2013). Merging PDM, RSM and LSM scheduling approaches: Into a single construction project scheduling system. Journal of Modern Project Management, 1(2), 6–17.

Bragadin, M. A., & Kähkönen, K. (2016). Schedule health assessment of construction projects. Construction Management and Economics, 34(12), 875–897. https://doi.org/10.1080/01446193.2016.1205751

Castro-Lacouture, D., Süer, G. A., Gonzalez-Joaqui, J., & Yates, J. K. (2009). Construction project scheduling with time, cost, and material restrictions using fuzzy mathematical models and critical path method. Journal of Construction Engineering and Management, 135(10), 1096–1104. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:10(1096)

Chan, G., Li, H., Skitmore, M., & Huang, T. (2015). A 4D automatic simulation tool for construction resource planning: A case study. Engineering, Construction and Architectural Management, 22(5), 536–550. https://doi.org/10.1108/ECAM-07-2014-0093

Chang, K., & Chen, H. (2015). A cloud-based system framework for storage and analysis on Big Data of massive BIMs. In Proceedings of the International Symposium on Automation and Robotics in Construction (ISARC 2015). Oulu, Finland. https://doi.org/10.22260/ISARC2015/0001

Chen, Y., Feng, C., Wang, Y., & Wu, H. (2011). Using bim model and genetic algorithms to optimize the crew assignment for construction project planning. International Journal of Technology, 2(3), 179–188.

Cheng, M. Y., Prayogo, D., & Tran, D. H. (2016). Optimizing multiple-resources leveling in multiple projects using discrete symbiotic organisms search. Journal of Computing in Civil Engineering, 30(3), 04015036. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000512

Chevallier, N., & Russell, A. D. (1998). Automated schedule generation. Canadian Journal of Civil Engineering, 25(6), 1059–1077. https://doi.org/10.1139/l98-029

Choudhry, R. M., Aslam, M. A., & Arain, F. M. (2014). Cost and schedule risk analysis of bridge construction in Pakistan: Establishing risk guidelines. Journal of Construction Engineering and Management, 140(7), 04014020. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000857

Christodoulou, S. E. (2010). Scheduling resource-constrained projects with ant colony optimization artificial agents. Journal of Computing in Civil Engineering, 24(1), 45–55. https://doi.org/10.1061/(ASCE)0887-3801(2010)24:1(45)

Christodoulou, S. E., Tezias, E. S., & Galaras, K. A. (2012). Resource-constrained scheduling of construction projects and simulation of the entropy impact on a project’s duration and cost. International Journal of Project Organisation and Management, 4(4), 322–338. https://doi.org/10.1504/IJPOM.2012.050328

Cobo, M. J., López-Herrera, A. G., Herrera‐Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. https://doi.org/10.1002/asi.21525

Daniel, E. I., Pasquire, C., Dickens, G., & Ballard, H. G. (2017). The relationship between the last planner® System and collaborative planning practice in UK construction. Engineering, Construction and Architectural Management, 24(3), 407–425. https://doi.org/10.1108/ECAM-07-2015-0109

Ding, L., Zhou, Y., Wang, X., Truijens, M., & Luo, H. (2015). Applicability of 4D modeling for resource allocation in mega liquefied natural gas plant construction. Automation in Construction, 50(C), 50–63. https://doi.org/10.1016/j.autcon.2014.10.016

Dochy, F. (2006). A guide for writing scholarly articles or reviews for the Educational Research Review. Educational Research Review, 4.

El-Abbasy, M. S., Elazouni, A., & Zayed, T. (2016). MOSCOPEA: Multi-objective construction scheduling optimization using elitist non-dominated sorting genetic algorithm. Automation in Construction, 71(Part 2), 153–170. https://doi.org/10.1016/j.autcon.2016.08.038

El-Rayes, K., & Jun, D. H. (2009). Optimizing resource leveling in construction projects. Journal of Construction Engineering and Management, 135(11), 1172–1180. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000097

Elbeltagi, E., Ammar, M., Sanad, H., & Kassab, M. (2016). Overall multiobjective optimization of construction projects scheduling using particle swarm. Engineering, Construction and Architectural Management, 23(3), 265–282. https://doi.org/10.1108/ECAM-11-2014-0135

Eleftheriadis, S., Mumovic, D., & Greening, P. (2017). Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities. Renewable and Sustainable Energy Reviews, 67, 811–825. https://doi.org/10.1016/j.rser.2016.09.028

Eshtehardian, E., Afshar, A., & Abbasnia, R. (2009). Fuzzy-based MOGA approach to stochastic time-cost trade-off problem. Automation in Construction, 18(5), 692–701. https://doi.org/10.1016/j.autcon.2009.02.001

Ezeldin, A. S., & Soliman, A. (2009). Hybrid time-cost optimization of nonserial repetitive construction projects. Journal of Construction Engineering and Management, 135(1), 42–55. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:1(42)

Faghihi, V., Nejat, A., Reinschmidt, K. F., & Kang, J. H. (2015). Automation in construction scheduling: a review of the literature. International Journal of Advanced Manufacturing Technology, 81(9–12), 1845–1856. https://doi.org/10.1007/s00170-015-7339-0

Faghihi, V., Reinschmidt, K. F., & Kang, J. H. (2014). Construction scheduling using Genetic Algorithm based on Building Information Model. Expert Systems with Applications, 41(16), 7565–7578. https://doi.org/10.1016/j.eswa.2014.05.047

Falagas, M. E., Pitsouni, E. I., Malietzis, G. A., & Pappas, G. (2008). Comparison of PubMed, Scopus, Web of Science, and Google scholar: strengths and weaknesses. The FASEB Journal, 22(2), 338–342. https://doi.org/10.1096/fj.07-9492LSF

Faniran, O., Love, P., & Smith, J. (2000). Effective front-end project management – a key element in achieving project success in developing countries. In Proceedings of Construction Development Conference.

Gannon, T., Feng, P., & Sitzabee, W. (2012). Reliable schedule forecasting in federal design-build facility procurement. Lean Construction Journal, 1–14.

García-Nieves, J. D., Ponz-Tienda, J. L., Salcedo-Bernal, A., & Pellicer, E. (2018). The multimode resource-constrained project scheduling problem for repetitive activities in construction projects. Computer-Aided Civil and Infrastructure Engineering, 33(8), 655–671. https://doi.org/10.1111/mice.12356

Gebrehiwet, T., & Luo, H. (2019). Risk level evaluation on construction project lifecycle using fuzzy comprehensive evaluation and TOPSIS. Symmetry, 11(1), 12. https://doi.org/10.3390/sym11010012

Ghoddousi, P., Ansari, R., & Makui, A. (2017). An improved robust buffer allocation method for the project scheduling problem. Engineering Optimization, 49(4), 718–731. https://doi.org/10.1080/0305215X.2016.1206534

Giran, O., Temur, R., & Bekdaş, G. (2017). Resource constrained project scheduling by harmony search algorithm. KSCE Journal of Civil Engineering, 21(2), 479–487. https://doi.org/10.1007/s12205-017-1363-6

González, V., Alarcón, L. F., & Molenaar, K. (2009). Multiobjective design of Work-In-Process buffer for scheduling repetitive building projects. Automation in Construction, 18(2), 95–108. https://doi.org/10.1016/j.autcon.2008.05.005

Gwak, H. S., Son, S. H., Park, Y. J., & Lee, D. E. (2016). Exact time-cost tradeoff analysis in concurrency-based scheduling. Journal of Construction Engineering and Management, 142(10), 04016054. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001164

Hamzeh, F., Ballard, G., & Tommelein, I. D. (2012). Rethinking lookahead planning to optimize construction workflow. Lean Construction Journal, 15–34.

Han, K. K., & Golparvar-Fard, M. (2017). Potential of big visual data and building information modeling for construction performance analytics: An exploratory study. Automation in Construction, 73, 184–198. https://doi.org/10.1016/j.autcon.2016.11.004

Hanagodimath, A. V., Rajashekarswamy, H. M., & Parate, H. R. (2016). Project performance in real time construction industry – A case study. International Journal of Civil Engineering and Technology, 7(5), 93–102.

Hardin, B., & McCool, D. (2015). BIM and construction management: proven tools, methods, and workflows. John Wiley & Sons.

Harty, C., Goodier, C. I., Soetanto, R., Austin, S., Dainty, A. R., & Price, A. D. (2007). The futures of construction: a critical review of construction future studies. Construction Management and Economics, 25(5), 477–493. https://doi.org/10.1080/01446190600879117

He, Q., Wang, G., Luo, L., Shi, Q., Xie, J., & Meng, X. (2017). Mapping the managerial areas of Building Information Modeling (BIM) using scientometric analysis. International Journal of Project Management, 35(4), 670–685. https://doi.org/10.1016/j.ijproman.2016.08.001

Hosseini, M. R., Martek, I., Zavadskas, E. K., Aibinu, A. A., Arashpour, M., & Chileshe, N. (2018). Critical evaluation of offsite construction research: A Scientometric analysis. Automation in Construction, 87, 235–247. https://doi.org/10.1016/j.autcon.2017.12.002

Hsiau, H. J., & Lin, C. W. R. (2009). A fuzzy pert approach to evaluate plant construction project scheduling risk under uncertain resources capacity. Journal of Industrial Engineering and Management, 2(1), 31–47. https://doi.org/10.3926/jiem.2009.v2n1.p31-47

Hsie, M., Chang, C. J., Yang, I. T., & Huang, C. Y. (2009). Resource-constrained scheduling for continuous repetitive projects with time-based production units. Automation in Construction, 18(7), 942–949. https://doi.org/10.1016/j.autcon.2009.04.006

Huang, K. M., Yang, B., Lee, C. H., & Chiu, C. T. (2014). Incorporating lost productivity calculation into delay analysis for construction projects. KSCE Journal of Civil Engineering, 18(2), 380–388. https://doi.org/10.1007/s12205-014-0128-8

Indhu, B., & Farhan, M. (2015). Analysis of probabilistic times in a construction project using Monte Carlo simulation technique. International Journal of Applied Engineering Research, 10(10), 26463–26474.

Jacsó, P. (2005). Google Scholar: the pros and the cons. Online Information Review, 29(2), 208–214. https://doi.org/10.1108/14684520510598066

Jaskowski, P., & Biruk, S. (2018). Reducing renewable resource demand fluctuation using soft precedence relations in project scheduling. Journal of Civil Engineering and Management, 24(4), 355–363. https://doi.org/10.3846/jcem.2018.3043

Jha, K. N., & Chockalingam, C. T. (2011). Prediction of schedule performance of Indian construction projects using an artificial neural network. Construction Management and Economics, 29(9), 901–911. https://doi.org/10.1080/01446193.2011.608691

Jin, R., Yuan, H., & Chen, Q. (2019a). Science mapping approach to assisting the review of construction and demolition waste management research published between 2009 and 2018. Resources, Conservation and Recycling, 140, 175–188. https://doi.org/10.1016/j.resconrec.2018.09.029

Jin, R., Zou, P. X., Piroozfar, P., Wood, H., Yang, Y., Yan, L., & Han, Y. (2019b). A science mapping approach based review of construction safety research. Safety Science, 113, 285–297. https://doi.org/10.1016/j.ssci.2018.12.006

Kasravi, M., Mahmoudi, A., & Feylizadeh, M. R. (2019). A novel algorithm for solving resource-constrained project scheduling problems: a case study. Journal of Advances in Management Research, 16(2), 194–215. https://doi.org/10.1108/JAMR-03-2018-0033

Kastor, A., & Sirakoulis, K. (2009). The effectiveness of resource levelling tools for resource constraint project scheduling problem. International Journal of Project Management, 27(5), 493–500. https://doi.org/10.1016/j.ijproman.2008.08.006

Kavuma, A., Ock, J., & Jang, H. (2019). Factors influencing time and cost overruns on freeform construction projects. KSCE Journal of Civil Engineering, 23(4), 1442–1450. https://doi.org/10.1007/s12205-019-0447-x

Khanzadi, M., Movahedian, A., & Bagherpour, M. (2016). Finding optimum resource allocation to optimizing construction project Time/Cost through combination of artificial agents CPM and GA. Periodica Polytechnica Civil Engineering, 60(2), 169–180. https://doi.org/10.3311/PPci.7883

Kim, S. G. (2012). CPM schedule summarizing function of the beeline diagramming method. Journal of Asian Architecture and Building Engineering, 11(2), 367–374. https://doi.org/10.3130/jaabe.11.367

Kovvuri, P. R. R., Sawhney, A., Ahuja, R., & Sreekumar, A. (2016). Efficient project delivery using lean principles – An Indian case study. Journal of The Institution of Engineers (India): Series A, 97(1), 19–26. https://doi.org/10.1007/s40030-016-0142-6

Larsen, J. K., Shen, G. Q., Lindhard, S. M., & Brunoe, T. D. (2016). Factors affecting schedule delay, cost overrun, and quality level in public construction projects. Journal of Management in Engineering, 32(1), 04015032. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000391

Larsen, J. K., Lindhard, S. M., Brunoe, T. D., & Jensen, K. N. (2018). The relation between pre-planning, commissioning and enhanced project performance. Construction Economics and Building, 18(2), 1–14. https://doi.org/10.5130/AJCEB.v18i2.5762

Lekshmi, S. A., & Unnikrishnan, V. (2018). Planning and delay analysis of a residential complex: A case study. International Journal of Civil Engineering and Technology, 9(6), 1191–1201.

Li, H., & Zhang, H. (2013). Ant colony optimization-based multi-mode scheduling under renewable and nonrenewable resource constraints. Automation in Construction, 35, 431–438. https://doi.org/10.1016/j.autcon.2013.05.030

Li, H., Zhang, J., Ren, L., & Shi, Z. (2013). Scheduling optimization in construction project based on ant colony genetic algorithm. Journal of Theoretical and Applied Information Technology, 48(3), 1540–1545.

Lin, C. W. R., & Hsiau, H. J. (2010). A genetic algorithm approach for optimizing chemical towers construction project scheduling with dynamic resources constraints. International Journal of Industrial Engineering: Theory Applications and Practice, 17(2), 128–141.

Lines, B. C., Sullivan, K. T., Hurtado, K. C., & Savicky, J. (2015). Planning in construction: Longitudinal study of pre-contract planning model demonstrates reduction in project cost and schedule growth. International Journal of Construction Education and Research, 11(1), 21–39. https://doi.org/10.1080/15578771.2013.872733

Liu, D., Xuan, P., Li, S., & Huang, P. (2015). Schedule risk analysis for TBM tunneling based on adaptive CYCLONE simulation in a geologic uncertainty-aware context. Journal of Computing in Civil Engineering, 29(6), 04014103. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000441

Long, L. D., & Ohsato, A. (2009). A genetic algorithm-based method for scheduling repetitive construction projects. Automation in Construction, 18(4), 499–511. https://doi.org/10.1016/j.autcon.2008.11.005

Luu, V. T., Kim, S. Y., Tuan, N. V., & Ogunlana, S. O. (2009). Quantifying schedule risk in construction projects using Bayesian belief networks. International Journal of Project Management, 27(1), 39–50. https://doi.org/10.1016/j.ijproman.2008.03.003

Ma, Y., & Xu, J. (2014). A novel multiple decision-maker model for resource-constrained project scheduling problems. Canadian Journal of Civil Engineering, 41(6), 500–511. https://doi.org/10.1139/cjce-2013-0232

Mahalingam, A., Yadav, A. K., & Varaprasad, J. (2015). Investigating the role of lean practices in enabling BIM adoption: Evidence from two Indian cases. Journal of Construction Engineering and Management, 141(7), 05015006. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000982

Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & LópezCózar, E. D. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics, 12(4), 1160–1177. https://doi.org/10.1016/j.joi.2018.09.002

May, I., Pynn, C., & Hill, P. (2018). Arup’s digital future: The path to BIM. In Building Information Modeling (pp. 509–534). Springer. https://doi.org/10.1007/978-3-319-92862-3_31

McCabe, B., AbouRizk, S. M., & Goebel, R. (1998). Belief networks for construction performance diagnostics. Journal of Computing in Civil Engineering, 12(2), 93–100. https://doi.org/10.1061/(ASCE)0887-3801(1998)12:2(93)

Meho, L. I., & Yang, K. (2006). A new era in citation and bibliometric analyses: Web of Science, Scopus, and Google Scholar. Journal of the American Society for Information Science and Technology (accepted for publication).

Mirzaei, A., Nasirzadeh, F., Parchami Jalal, M., & Zamani, Y. (2018). 4D-BIM dynamic time-space conflict detection and quantification system for building construction projects. Journal of Construction Engineering and Management, 144(7), 04018056. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001504

Moselhi, O., & Alshibani, A. (2013). Schedule compression using Fuzzy Set Theory and contractors judgment. Journal of Information Technology in Construction, 18, 64–75.

Müller, V. C., & Bostrom, N. (2016). Future progress in artificial intelligence: A survey of expert opinion. In Fundamental Issues of Artificial Intelligence (pp. 555–572). Springer. https://doi.org/10.1007/978-3-319-26485-1_33

Ökmen, Ö., & Öztaş, A. (2008). Construction project network evaluation with correlated schedule risk analysis model. Journal of Construction Engineering and Management, 134(1), 49–63. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:1(49)

Ökmen, Ö., & Öztaş, A. (2014). A CPM-based scheduling method for construction projects with fuzzy sets and fuzzy operations. Journal of the South African Institution of Civil Engineering, 56(2), 2–8.

Petrochenko, M. V., Velichkin, V. Z., Kazakov, Y. N., & Zavodnova, Y. B. (2018). Reliability assessment of the construction schedule by the critical chain method. Magazine of Civil Engineering, 81(5), 25–31.

Poshdar, M., González, V. A., Raftery, G. M., Orozco, F., & Cabrera-Guerrero, G. G. (2018). A multi-objective probabilistic-based method to determine optimum allocation of time buffer in construction schedules. Automation in Construction, 92, 46–58. https://doi.org/10.1016/j.autcon.2018.03.025

Poshdar, M., González, V. A., Raftery, G. M., Orozco, F., Romeo, J. S., & Forcael, E. (2016). A probabilistic-based method to determine optimum size of project buffer in construction schedules. Journal of Construction Engineering and Management, 142(10), 04016046. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001158

Radziszewska-Zielina, E., Śladowski, G., & Sibielak, M. (2017). Planning the reconstruction of a historical building by using a fuzzy stochastic network. Automation in Construction, 84, 242–257. https://doi.org/10.1016/j.autcon.2017.08.003

Rakhshani, H., Idoumghar, L., Lepagnot, J., & Brevilliers, M. (2019). From feature selection to continues optimization. Accepted for EA2019.

Rosłon, J. H., & Kulejewski, J. E. (2019). A hybrid approach for solving multi-mode resource-constrained project scheduling problem in construction. Open Engineering, 9(1), 7–13. https://doi.org/10.1515/eng-2019-0006

Russell, M. M., Howell, G., Hsiang, S. M., & Liu, M. (2013). Application of time buffers to construction project task durations. Journal of Construction Engineering and Management, 139(10), 04013008. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000735

Russell, M. M., Hsiang, S. M., Liu, M., & Wambeke, B. (2014). Causes of time buffer and duration variation in construction project tasks: Comparison of perception to reality. Journal of Construction Engineering and Management, 140(6), 04014016. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000819

Ryall, T., Fitzpatrick, S., Parsloe, R., & Morris, J. (2012). Collaborative planning on the Borough viaduct project, London. In Proceedings of the Institution of Civil Engineers: Civil Engineering, 165(5), 45–49. https://doi.org/10.1680/cien.11.00015

Shen, Q., Xue, F., Li, Z., Luo, L., Xu, X., & Sommer, L. (2017). Schedule risk modeling in prefabrication housing production. Journal of Cleaner Production, 153, 692–706. https://doi.org/10.1016/j.jclepro.2016.11.028

Sigalov, K., & König, M. (2017). Recognition of process patterns for BIM-based construction schedules. Advanced Engineering Informatics, 33, 456–472. https://doi.org/10.1016/j.aei.2016.12.003

Sinesilassie, E. G., Tabish, S. Z. S., & Jha, K. N. (2017). Critical factors affecting schedule performance: A case of Ethiopian public construction projects - Engineers’ perspective. Engineering, Construction and Architectural Management, 24(5), 757–773. https://doi.org/10.1108/ECAM-03-2016-0062

Siu, M., Lu, M., AbouRizk, S., & Tidder, V. (2016). Quantitative assessment of budget sufficiency and resource utilization for resource-constrained project schedules. Journal of Construction Engineering and Management, 142(6), 04016003. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001106

Song, L., Mohamed, Y., & AbouRizk, S. M. (2009). Early contractor involvement in design and its impact on construction schedule performance. Journal of Management in Engineering, 25(1), 12–20. https://doi.org/10.1061/(ASCE)0742-597X(2009)25:1(12)

Sonmez, R., Iranagh, M. A., & Uysal, F. (2016). Critical sequence crashing heuristic for resource-constrained discrete time-cost trade-off problem. Journal of Construction Engineering and Management, 142(3), 04015090. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001077

Soto Ramírez, D., Rivera Cadavid, L., Orobio Quiñones, A., & Cuadros López, A. J. (2018). Evaluation of the impact of schedule risks in a road infrastructure project. Espacios, 39(47).

Subramani, T., & Ammai, A. (2018). Maturing construction management up the BIM model & scheduling using Primavera. International Journal of Engineering and Technology, 7(3). https://doi.org/10.14419/ijet.v7i3.10.15617

Succar, B. (2009). Building information modelling framework: A research and delivery foundation for industry stakeholders. Automation in Construction, 18(3), 357–375. https://doi.org/10.1016/j.autcon.2008.10.003

Suresh, M., Dutta, P., & Jain, K. (2011). Analysis of an EPC project: A solution to the resource constrained project scheduling problem using genetic algorithms. International Journal of Industrial and Systems Engineering, 8(2), 251–269. https://doi.org/10.1504/IJISE.2011.041372

Tang, Y., Liu, R., & Sun, Q. (2014). Schedule control model for linear projects based on linear scheduling method and constraint programming. Automation in Construction, 37, 22–37. https://doi.org/10.1016/j.autcon.2013.09.008

Tesfaye, E., Lemma, T., Berhan, E., & Beshah, B. (2017). Key project planning processes affecting project success. International Journal for Quality Research, 11(1), 159–172.

Thomas, H. R., Maloney, W. F., Horner, R. M. W., Smith, G. R., Handa, V. K., & Sanders, S. R. (1990). Modeling construction labor productivity. Journal of Construction Engineering and Management, 116(4), 705–726. https://doi.org/10.1061/(ASCE)0733-9364(1990)116:4(705)

Tiwari, S., & Johari, S. (2015). Project scheduling by integration of time cost trade-off and constrained resource scheduling. Journal of The Institution of Engineers (India): Series A, 96(1), 37–46. https://doi.org/10.1007/s40030-014-0099-2

Tomar, A., & Bansal, V. K. (2019). Scheduling of repetitive construction projects using geographic information systems: an integration of critical path method and line of balance. Asian Journal of Civil Engineering, 20(4), 549–562. https://doi.org/10.1007/s42107-019-00123-3

Tran, D. H., & Long, L. D. (2018). Project scheduling with time, cost and risk trade-off using adaptive multiple objective differential evolution. Engineering, Construction and Architectural Management, 25(5), 623–638. https://doi.org/10.1108/ECAM-05-2017-0085

Udaipurwala, A., & Russell, A. D. (2002). Computer-assisted construction methods knowledge management and selection. Canadian Journal of Civil Engineering, 29(3), 499–516. https://doi.org/10.1139/l02-030

Van Eck, N. J., & Waltman, L. (2011). Text mining and visualization using VOSviewer. ArXiv 2011.

Van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Measuring Scholarly Impact (pp. 285–320). Springer. https://doi.org/10.1007/978-3-319-10377-8_13

Vidhyasri, R., & Sivagamasundari, R. (2017). A review on factors influencing construction project scheduling. International Journal of Civil Engineering and Technology, 8(3), 146–157.

Vignesh, C. (2017). A case study of implementing last planner system in Tiruchirappalli District of Tamil Nadu - India. International Journal of Civil Engineering and Technology, 8(4), 1918–1927.

Wambeke, B. W., Hsiang, S. M., & Liu, M. (2011). Causes of variation in construction project task starting times and duration. Journal of Construction Engineering and Management, 137(9), 663–677. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000342

Wang, J., & Yuan, H. (2016). System dynamics approach for investigating the risk effects on schedule delay in infrastructure projects. Journal of Management in Engineering, 33(1), 04016029. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000472

Wang, Y.-R., Yu, C.-Y., & Chan, H.-H. (2012). Predicting construction cost and schedule success using artificial neural networks ensemble and support vector machines classification models. International Journal of Project Management, 30(4), 470–478. https://doi.org/10.1016/j.ijproman.2011.09.002

Wang, Z., & Rezazadeh Azar, E. (2019). BIM-based draft schedule generation in reinforced concrete-framed buildings. Construction Innovation, 19(2), 280–294. https://doi.org/10.1108/CI-11-2018-0094

Xu, X., Wang, J., Li, C. Z., Huang, W., & Xia, N. (2018). Schedule risk analysis of infrastructure projects: A hybrid dynamic approach. Automation in Construction, 95, 20–34. https://doi.org/10.1016/j.autcon.2018.07.026

Yahya, M. A., & Mohamad, M. I. (2011). Review on lean principles for rapid construction. Jurnal Teknologi, 54, 1–11. https://doi.org/10.11113/jt.v54.87

Yang, J. (2017). Reviewing construction schedule float management. Open Construction and Building Technology Journal, 11, 1–13. https://doi.org/10.2174/1874836801711010001

Yao, G., Yang, Y., Wang, M., & Zhou, M. (2018). A review of construction schedule optimization with heuristic method. Journal of Advanced Oxidation Technologies, 21(2).

Zareei, S. (2018). Project scheduling for constructing biogas plant using critical path method. Renewable and Sustainable Energy Reviews, 81, 756–759. https://doi.org/10.1016/j.rser.2017.08.025

Zhou, J., Love, P. E. D., Wang, X., Teo, K. L., & Irani, Z. (2013). A review of methods and algorithms for optimizing construction scheduling. Journal of the Operational Research Society, 64(8), 1091–1105. https://doi.org/10.1057/jors.2012.174

Zou, X., Huang, Y., & Zhang, L. (2016). Genetic algorithm-based method for the deadline problem in repetitive construction projects considering soft logic. Journal of Management in Engineering, 32(4), 04016002. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000426

Zou, X., Zhang, L., & Kan, Z. (2014). Improved strategy for resource allocation in repetitive projects considering the learning effect. Journal of Construction Engineering and Management, 140(11), 04014053. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000896

Zou, X., Zhang, L., & Qi, J. (2015). A trade-off between time and cost in scheduling repetitive construction projects. Journal of Industrial and Management Optimization, 11(4), 1423–1434. https://doi.org/10.3934/jimo.2015.11.1423

Zwikael, O. (2009). Critical planning processes in construction projects. Construction Innovation, 9(4), 372–387. https://doi.org/10.1108/14714170910995921