A Review of Construction Program Delivery Attributes: Bibliometric Analysis of Two Decades
Abstract
:1. Introduction
2. Research Significance and Methodologies
3. Bibliometric Findings
3.1. Findings
3.2. Bibliometric Synopsis
- Three leading journals are the International Journal of Project Management, Journal of Management in Engineering, and Journal of Construction Engineering and Management, and four dominant countries, Australia, the USA, the UK, and China, have published research on the context of CPDs.
- Even though there are extensive collaborations among countries in CPD research, the Australia–China, Australia–UK, China–USA, and UK–Nigeria relationships are considered to be more meaningful.
- Scholars have focused primarily on management paradigms such as using institutional framework, risk assessment, procurement, CSFs, and performance factors concerning the CPD.
- Some delivery strategies like Building–Operate–Transfer and DB are gradually supplanted chronologically in the research context by other delivery frameworks such as PPP and Integrated Project Delivery (IPD).
- A recent trend in research has been to look at how social values such as collaboration and corporate responsibility affect the delivery of infrastructure projects.
- Even though program management has now found a trend in CPD research, conventional project management is still the current research nucleus.
- As evidenced by a triadic interrelation of preeminent authors, focal domains, and national affiliations shown in Figure 3, transportation emerges as the predominant sector of scholarly inquiry in CPD, eclipsing other infrastructure categories like ports and Olympic complexes.
- Regarding delivery system selection methods in research, multi-attribute decision-making models, including fuzzy logic approaches, are preferable to other methods, such as guidance and knowledge/experience based [21].
4. Construction Program Delivery Attributes
4.1. Contextual Framework
4.2. Analysis
4.3. Discussion
5. Conclusions, Limitations and Future Research
- Due to the limitations of the Bibliometrix software concerning data input characters, only peer-reviewed journal publications conducted in the recent century were considered in this review. Reviews conducted over a long period as well as other resources like conference papers, can provide further analysis and interpretation.
- This study aims to better understand delivery attributes by providing an auxiliary tool for analysing them, so only papers concerning CPD were analysed.
- This study was a systematic review of delivery attributes for construction programs; therefore, this study did not focus on a specific type. The findings of this study could be used as a basis for further quantitative or qualitative research.
- The review examined the current delivery attributes and considerations affecting the delivery planning process. It is highly probable that regulatory, cultural, and standardisation norm changes due to cultural shifts or environmental concerns, for example, will alter the list.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Tanaka, H. Toward Project and Program Management Paradigm in the Space of Complexity: A Case Study of Mega and Complex Oil and Gas Development and Infrastructure Projects. Procedia-Soc. Behav. Sci. 2014, 119, 65–74. [Google Scholar] [CrossRef]
- Davies, A.; Mackenzie, I. Project complexity and systems integration: Constructing the London 2012 Olympics and Paralympics Games. Int. J. Proj. Manag. 2014, 32, 773–790. [Google Scholar] [CrossRef]
- Martin, H.; Lewis, T.M.; Petersen, A. Factors affecting the choice of construction project delivery in developing oil and gas economies. Arch. Eng. Des. Manag. 2016, 12, 170–188. [Google Scholar] [CrossRef]
- Flyvbjerg, B.; Rothengatter, W.; Bruzelius, N. Megaprojects and Risk: An Anatomy of Ambition; Cambridge University Press: New York, NY, USA, 2003. [Google Scholar]
- Jia, G.; Chen, Y.; Xue, X.; Chen, J.; Cao, J.; Tang, K. Program management organization maturity integrated model for mega construction programs in China. Int. J. Proj. Manag. 2011, 29, 834–845. [Google Scholar] [CrossRef]
- Bruzelius, N.; Flyvbjerg, B.; Rothengatter, W. Big decisions, big risks. Improving accountability in mega projects. Transp. Policy 2002, 9, 143–154. [Google Scholar] [CrossRef]
- Sun, J.; Zhang, P. Owner organization design for mega industrial construction projects. Int. J. Proj. Manag. 2011, 29, 828–833. [Google Scholar] [CrossRef]
- van Marrewijk, A.; Clegg, S.R.; Pitsis, T.S.; Veenswijk, M. Managing public–private megaprojects: Paradoxes, complexity, and project design. Int. J. Proj. Manag. 2008, 26, 591–600. [Google Scholar] [CrossRef]
- Locatelli, G.; Mancini, M.; Ishimwe, A. How can System Engineering Improve Supplier Management in Megaprojects? Procedia-Soc. Behav. Sci. 2014, 119, 510–518. [Google Scholar] [CrossRef]
- Brooks, N. Delivering European Megaprojects: A Guide for Policy Makers and Practitioners; University of Leeds: Leeds, UK, 2015. [Google Scholar]
- Scott, W.R.; Levitt, R.E.; Orr, R.J. Global Projects: Institutional and Political Challenges; Cambridge University Press: New York, NY, USA, 2011. [Google Scholar]
- Mišić, S.; Radujković, M. Critical drivers of megaprojects success and failure. Procedia Eng. 2015, 122, 71–80. [Google Scholar] [CrossRef]
- Flyvbjerg, B.; Stewart, A.; Budzier, A. The Oxford Olympics Study 2016: Cost and cost overrun at the games. arXiv 2016, arXiv:1607.04484. [Google Scholar] [CrossRef]
- Chang, A.; Chih, Y.-Y.; Chew, E.; Pisarski, A. Reconceptualising mega project success in Australian Defence: Recognising the importance of value co-creation. Int. J. Proj. Manag. 2013, 31, 1139–1153. [Google Scholar] [CrossRef]
- Pellegrinelli, S. Programme management: Organising project-based change. Int. J. Proj. Manag. 1997, 15, 141–149. [Google Scholar] [CrossRef]
- Gray, R.J. Alternative approaches to programme management. Int. J. Proj. Manag. 1997, 15, 5–9. [Google Scholar] [CrossRef]
- Ashurst, C.; Doherty, N.F.; Peppard, J. Improving the impact of IT development projects: The benefits realization capability model. Eur. J. Inf. Syst. 2008, 17, 352–370. [Google Scholar] [CrossRef]
- Al Nahyan, M.T.; Hawas, Y.E.; Raza, M.; Aljassmi, H.; Maraqa, M.A.; Basheerudeen, B.; Mohammad, M.S. A fuzzy-based decision support system for ranking the delivery methods of mega projects. Int. J. Manag. Proj. Bus. 2018, 11, 122–143. [Google Scholar] [CrossRef]
- Al Khalil, M.I. Selecting the appropriate project delivery method using AHP. Int. J. Proj. Manag. 2002, 20, 469–474. [Google Scholar] [CrossRef]
- Alhazmi, T.; McCaffer, R. Project procurement system selection model. J. Constr. Eng. Manag. 2000, 126, 176–184. [Google Scholar] [CrossRef]
- Ibbs, W.; Chih, Y.Y. Alternative methods for choosing an appropriate project delivery system (PDS). Facilities 2011, 29, 527–541. [Google Scholar] [CrossRef]
- Khanzadi, M.; Nasirzadeh, F.; Hassani, S.H.; Mohtashemi, N.N. An integrated fuzzy multi-criteria group decision making approach for project delivery system selection. Sci. Iran. Trans. A Civ. Eng. 2016, 23, 802. [Google Scholar] [CrossRef]
- Kumaraswamy, M.M.; Dissanayaka, S.M. Developing a decision support system for building project procurement. Build. Environ. 2001, 36, 337–349. [Google Scholar] [CrossRef]
- Li, H.; Qin, K.; Li, P. Selection of project delivery approach with unascertained model. Kybernetes 2015, 44, 238–252. [Google Scholar] [CrossRef]
- Luu, D.T.; Ng, S.T.; Chen, S.E. Formulating procurement selection criteria through case-based reasoning approach. J. Comput. Civ. Eng. 2005, 19, 269–276. [Google Scholar] [CrossRef]
- Mafakheri, F.; Dai, L.; Slezak, D.; Nasiri, F. Project delivery system selection under uncertainty: Multicriteria multilevel decision aid model. J. Manag. Eng. 2007, 23, 200–206. [Google Scholar] [CrossRef]
- Mostafavi, A.; Karamouz, M. Selecting appropriate project delivery system: Fuzzy approach with risk analysis. J. Constr. Eng. Manag. 2010, 136, 923–930. [Google Scholar] [CrossRef]
- Mahdi, I.M.; Alreshaid, K. Decision support system for selecting the proper project delivery method using analytical hierarchy process (AHP). Int. J. Proj. Manag. 2005, 23, 564–572. [Google Scholar] [CrossRef]
- Pellegrinelli, S.; Murray-Webster, R.; Turner, N. Facilitating organizational ambidexterity through the complementary use of projects and programs. Int. J. Proj. Manag. 2015, 33, 153–164. [Google Scholar] [CrossRef]
- Pellegrinelli, S.; Partington, D.; Hemingway, C.; Mohdzain, Z.; Shah, M. The importance of context in programme management: An empirical review of programme practices. Int. J. Proj. Manag. 2007, 25, 41–55. [Google Scholar] [CrossRef]
- Miterev, M.; Engwall, M.; Jerbrant, A. Exploring program management competences for various program types. Int. J. Proj. Manag. 2016, 34, 545–557. [Google Scholar] [CrossRef]
- Shehu, Z.; Akintoye, A. Construction programme management theory and practice: Contextual and pragmatic approach. Int. J. Proj. Manag. 2009, 27, 703–716. [Google Scholar] [CrossRef]
- Rijke, J.; van Herk, S.; Zevenbergen, C.; Ashley, R.; Hertogh, M.; ten Heuvelhof, E. Adaptive programme management through a balanced performance/strategy oriented focus. Int. J. Proj. Manag. 2014, 32, 1197–1209. [Google Scholar] [CrossRef]
- Chaw, A.P.C.; Yung, E.H.K.; Lam, P.T.I.; Tam, C.M.; Cheung, S.O. Application of Delphi method in selection of procurement systems for construction projects. Constr. Manag. Econ. 2001, 19, 699–718. [Google Scholar] [CrossRef]
- Chen, Y.Q.; Liu, J.Y.; Li, B.; Lin, B. Project delivery system selection of construction projects in China. Expert Syst. Appl. 2011, 38, 5456–5462. [Google Scholar] [CrossRef]
- Hope, A.J.; Moehler, R. Balancing Projects with Society and the Environment: A Project, Programme and Portfolio Approach. Procedia-Soc. Behav. Sci. 2014, 119, 358–367. [Google Scholar] [CrossRef]
- Pellegrinelli, S. What’s in a name: Project or programme? Int. J. Proj. Manag. 2011, 29, 232–240. [Google Scholar] [CrossRef]
- Project Management Institute. The Standard for Program Management, 4th ed.; Project Management Institute: Newtown Square, PA, USA, 2017. [Google Scholar]
- Blismas, N.G.; Thorpe, A.; Sher, W.D.; Baldwin, A.N. Factors influencing project delivery within construction clients’ multi-project environments. Eng. Constr. Arch. Manag. 2004, 11, 113–125. [Google Scholar] [CrossRef]
- Luu, D.T.; Ng, S.T.; Chen, S.E. Parameters governing the selection of procurement system—An empirical survey. Eng. Constr. Arch. Manag. 2003, 10, 209–218. [Google Scholar]
- Touran, A.; Gransberg, D.D.; Molenaar, K.R.; Ghavamifar, K. Selection of project delivery method in transit: Drivers and objectives. J. Manag. Eng. 2011, 27, 21–27. [Google Scholar] [CrossRef]
- Qiang, M.; Wen, Q.; Jiang, H.; Yuan, S. Factors governing construction project delivery selection: A content analysis. Int. J. Proj. Manag. 2015, 33, 1780–1794. [Google Scholar] [CrossRef]
- Chan, C.T. Fuzzy procurement selection model for construction projects. Constr. Manag. Econ. 2007, 25, 611–618. [Google Scholar] [CrossRef]
- Chang, C.-Y.; Ive, G. Rethinking the multi-attribute utility approach based procurement route selection technique. Constr. Manag. Econ. 2002, 20, 275–284. [Google Scholar] [CrossRef]
- Liu, J.-W.; Huang, L.-C. Detecting and visualizing emerging trends and transient patterns in fuel cell scientific literature. In Proceedings of the 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing, Dalian, China, 12–17 October 2008; pp. 1–4. [Google Scholar]
- Van Eck, N.J.; Waltman, L. Visualizing bibliometric networks. In Measuring Scholarly Impact: Methods and Practice; Springer: Cham, Switzerland, 2014; pp. 285–320. [Google Scholar]
- Synnestvedt, M.B.; Chen, C.; Holmes, J.H. CiteSpace II: Visualization and knowledge discovery in bibliographic databases. In Proceedings of the AMIA Annual Symposium Proceedings, Bethesda, WA, USA, 22–25 October 2005. [Google Scholar]
- Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017, 11, 959–975. [Google Scholar] [CrossRef]
- Caputo, A.; Kargina, M. A user-friendly method to merge Scopus and Web of Science data during bibliometric analysis. J. Mark. Anal. 2022, 10, 82–88. [Google Scholar] [CrossRef]
- Martins, M.; Sganzerla, W.G.; Forster-Carneiro, T.; Goldbeck, R. Recent advances in xylo-oligosaccharides production and applications: A comprehensive review and bibliometric analysis. Biocatal. Agric. Biotechnol. 2023, 47, 102608. [Google Scholar] [CrossRef]
- Igarashi, M.; de Boer, L.; Fet, A.M. What is required for greener supplier selection? A literature review and conceptual model development. J. Purch. Supply Manag. 2013, 19, 247–263. [Google Scholar] [CrossRef]
- Chong, H.-Y.; Preece, C.N. Improving construction procurement systems using organizational strategies. Acta Polytech. Hung. 2014, 11, 5–20. [Google Scholar]
- Chen, Y.Q.; Zhang, Y.B.; Liu, J.Y.; Mo, P. Interrelationships among critical success factors of construction projects based on the structural equation model. J. Manag. Eng. 2012, 28, 243–251. [Google Scholar] [CrossRef]
- Yang, L.; Sandanayake, M.; Jayasuriya, S.; Vu, H.; Zhang, G. Chinese Public-Private Partnership (PPP) Project Development Characteristics: An Interview Study. In International Symposium on Advancement of Construction Management and Real; Estate Singapore: Singapore, 2019; pp. 879–895. [Google Scholar]
- Biesenthal, C.; Wilden, R. Multi-level project governance: Trends and opportunities. Int. J. Proj. Manag. 2014, 32, 1291–1308. [Google Scholar] [CrossRef]
- Yong, Y.C.; Mustaffa, N.E. Critical success factors for Malaysian construction projects: An empirical assessment. Constr. Manag. Econ. 2013, 31, 959–978. [Google Scholar] [CrossRef]
- Nguyen, L.D.; Ogunlana, S.O. A study on project success factors in large construction projects in Vietnam. Eng. Constr. Arch. Manag. 2004, 11, 404–413. [Google Scholar] [CrossRef]
- Berssaneti, F.T.; Carvalho, M.M. Identification of variables that impact project success in Brazilian companies. Int. J. Proj. Manag. 2015, 33, 638–649. [Google Scholar] [CrossRef]
- Yu, J.-H.; Kwon, H.-R. Critical success factors for urban regeneration projects in Korea. Int. J. Proj. Manag. 2011, 29, 889–899. [Google Scholar] [CrossRef]
- Sandanayake, M.; Bouras, Y.; Haigh, R.; Vrcelj, Z. Current Sustainable Trends of Using Waste Materials in Concrete—A Decade Review. Sustainability 2020, 12, 9622. [Google Scholar] [CrossRef]
- Landhuis, E. Scientific literature: Information overload. Nature 2016, 535, 457–458. [Google Scholar] [CrossRef] [PubMed]
- Waltman, L. A review of the literature on citation impact indicators. J. Informetr. 2016, 10, 365–391. [Google Scholar] [CrossRef]
- Rothengatter, W. 81Risk Management for Megaprojects. In The Governance of Infrastructure; Wegrich, K., Kostka, G., Hammerschmid, G., Eds.; Oxford University Press: Oxford, UK, 2017; pp. 81–102. [Google Scholar]
- Fathi, M.; Shrestha, P.P. Public–Private Partnership Project Performance Analysis Compared to Design-Build in Highway Projects. J. Constr. Eng. Manag. 2022, 148, 04022118. [Google Scholar] [CrossRef]
- Ogunsanmi, O.E. Stakeholders’ perception of key performance indicators (KPIs) of publicprivate partnership (PPP) projects. Int. J. Constr. Supply Chain Manag. 2013, 3, 27–38. [Google Scholar]
- Lycett, M.; Rassau, A.; Danson, J. Programme management: A critical review. Int. J. Proj. Manag. 2004, 22, 289–299. [Google Scholar] [CrossRef]
- Koppenjan, J.F.M. The Formation of Public-Private Partnerships: Lessons from Nine Transport Infrastructure Projects in The Netherlands. Public Adm. 2005, 83, 135–157. [Google Scholar] [CrossRef]
- Al Nahyan, M.T.; Sherif, M.; Hawas, Y.E.; Basheerudeen, B. A Fuzzy-Based Decision-Support System for the Analysis of Suitability of Megaproject Delivery Methods. J. Mod. Proj. Manag. 2019, 7, 120–137. [Google Scholar] [CrossRef]
- Nguyen, A.T.; Nguyen, L.D.; Le-Hoai, L.; Dang, C.N. Quantifying the complexity of transportation projects using the fuzzy analytic hierarchy process. Int. J. Proj. Manag. 2015, 33, 1364–1376. [Google Scholar] [CrossRef]
- Oyetunji, A.A.; Anderson, S.D. Relative effectiveness of project delivery and contract strategies. J. Constr. Eng. Manag. 2006, 132, 3–13. [Google Scholar] [CrossRef]
- Kandil, A.; Hastak, M.; Dunston, P. The relationship between delivery processes and transportation projects’ performance. Bridges 2014, 10. [Google Scholar] [CrossRef]
- Liu, B.; Meng, J.; Xue, B.; Huo, T.; Yang, Z.; Shen, Q. Which owner characteristics are key factors affecting project delivery system decision making? empirical analysis based on the rough set theory. J. Manag. Eng. 2015, 31, 05014018. [Google Scholar] [CrossRef]
- Cheung, S.-O.; Lam, T.-I.; Wan, Y.-W.; Lam, K.-C. Improving objectivity in procurement selection. J. Manag. Eng. 2001, 17, 132–139. [Google Scholar] [CrossRef]
- Luu, D.T.; Ng, S.T.; Chen, S.E. A case-based procurement advisory system for construction. Adv. Eng. Softw. 2003, 34, 429–438. [Google Scholar] [CrossRef]
- Minchin Jr, R.E.; Henriquez, N.R.; King, A.M.; Lewis, D.W. Owners respond: Preferences for task performance, delivery systems, and quality management. J. Constr. Eng. Manag. 2010, 136, 283–293. [Google Scholar] [CrossRef]
- Rwelamila, P.D.; Edries, R. Project procurement competence and knowledge base of civil engineering consultants: An empirical study. J. Manag. Eng. 2007, 23, 182–192. [Google Scholar] [CrossRef]
- Wang, Z.; Wang, D.; Yang, G.; Ding, J. Selection of construction project delivery method based on value-added analysis: A theoretical framework. In ICCREM 2013: Construction and Operation in the Context of Sustainability; American Society of Civil Engineers: New York, NY, USA, 2013; pp. 403–414. [Google Scholar]
- Xiao-mei, G.; Xiao-jun, L. Application of entropy measurement in risk assessment of the engineering project of construction-agent system. Syst. Eng. Procedia 2011, 1, 244–249. [Google Scholar] [CrossRef]
- Erkul, M.; Yitmen, I.; Çelik, T. Stakeholder Engagement in Mega Transport Infrastructure Projects. Procedia Eng. 2016, 161, 704–710. [Google Scholar] [CrossRef]
- Marzouk, M.; Elmesteckawi, L. Analyzing procurement route selection for electric power plants projects using SMART. J. Civ. Eng. Manag. 2015, 21, 912–922. [Google Scholar] [CrossRef]
- Zhong, Q.; Tang, H.; Chen, C.; Igor, M. A Comprehensive Appraisal of the Factors Impacting Construction Project Delivery Method Selection: A Systematic Analysis. J. Asian Arch. Build. Eng. 2022, 22, 802–820. [Google Scholar] [CrossRef]
- Youssef, M.; Mohamed, M.S.E.; Balah, A.A.S. Fuzzy model for Libyan construction projects delivery system selection. Int. J. Constr. Manag. 2022, 1, 1–8. [Google Scholar] [CrossRef]
- Buertey, J.T.; Dadadzogbor, E.; Atsrim, F. Procurement path influencing factors in Ghana: Managing the challenge of cultural shift. Int. J. Constr. Manag. 2021, 21, 78–92. [Google Scholar] [CrossRef]
- Chen, P.; Qiang, M.; Wang, J.N. Project management in the Chinese construction industry: Six-case study. J. Constr. Eng. Manag. 2009, 135, 1016–1026. [Google Scholar] [CrossRef]
- Feghaly, J.; El Asmar, M.; Ariaratnam, S.; Bearup, W. Selecting project delivery methods for water treatment plants. Eng. Constr. Arch. Manag. 2020, 27, 936–951. [Google Scholar] [CrossRef]
- Demetracopoulou, V.; O’Brien, W.J.; Khwaja, N. Lessons Learned from Selection of Project Delivery Methods in Highway Projects: The Texas Experience. J. Leg. Aff. Disput. Resolut. Eng. Constr. 2020, 12, 04519040. [Google Scholar] [CrossRef]
- Khwaja, N.; O’Brien, W.J.; Martinez, M.; Sankaran, B.; O’Connor, J.T.; “Bill” Hale, W. Innovations in project delivery method selection approach in the Texas Department of Transportation. J. Manag. Eng. 2018, 34, 05018010. [Google Scholar] [CrossRef]
- Mogerman, A.; Mendis, D.; Hewage, K.N. Project delivery and contracting strategies for district energy projects in Canada. Can. J. Civ. Eng. 2016, 43, 461–471. [Google Scholar] [CrossRef]
- Khoso, A.R.; Memon, N.A.; Siddiqui, F.; Memon, A.H. Decision preferences of procurement delivery method in public sector construction projects using TOPSIS. Int. J. Procure. Manag. 2023, 16, 234–251. [Google Scholar] [CrossRef]
- Crosby, P. Shaping complex mega-projects: Practical steps for success. Aust. J. Civ. Eng. 2017, 15, 1–19. [Google Scholar] [CrossRef]
- Tabish, S.Z.S.; Jha, K.N. Identification and evaluation of success factors for public construction projects. Constr. Manag. Econ. 2011, 29, 809–823. [Google Scholar] [CrossRef]
- Amora, V.C.M.; Juanzon, J.B.P. A Framework of Critical Success Factors and Success Criteria for Structural Works of a Mixed-Use Building Construction Project. Civ. Eng. Arch. 2022, 10, 267–279. [Google Scholar] [CrossRef]
- Tran, D.Q.; Molenaar, K.R. Exploring critical delivery selection risk factors for transportation design and construction projects. Eng. Constr. Arch. Manag. 2014, 21, 631–647. [Google Scholar] [CrossRef]
- Tran, D.Q.; Molenaar, K.R.; Alarcön, L.F. A hybrid cross-impact approach to predicting cost variance of project delivery decisions for highways. J. Infrastruct. Syst. 2016, 22, 04015017. [Google Scholar] [CrossRef]
- Phua, F.T. Modelling the determinants of multi-firm project success: A grounded exploration of differing participant perspectives. Constr. Manag. Econ. 2004, 22, 451–459. [Google Scholar] [CrossRef]
- Vu, H.; Sandanayake, M.; Zhang, G. Factors Affecting the Readiness of User-Pay Public–Private Partnership Procurement for Infrastructure Projects: A Comparison between Developed and Emerging Economies. Knowledge 2023, 3, 384–400. [Google Scholar] [CrossRef]
- Tran, D.Q.; Harper, C.M.; Molenaar, K.R.; Haddad, N.F.; Scholfield, M.M. Project delivery selection matrix for highway design and construction. Transp. Res. Rec. 2013, 2347, 3–10. [Google Scholar] [CrossRef]
- Liu, B.; Huo, T.; Liang, Y.; Sun, Y.; Hu, X. Key Factors of Project Characteristics Affecting Project Delivery System Decision Making in the Chinese Construction Industry: Case Study Using Chinese Data Based on Rough Set Theory. J. Prof. Issues Eng. Educ. Pr. 2016, 142, 05016003. [Google Scholar] [CrossRef]
- Yoon, Y.; Jung, J.; Hyun, C. Decision-making support systems using case-based reasoning for construction project delivery method selection: Focused on the road construction projects in Korea. Open Civ. Eng. J. 2016, 10, 500–512. [Google Scholar] [CrossRef]
- Tran, D.Q.; Molenaar, K.R. Risk-Based Project Delivery Selection Model for Highway Design and Construction. J. Constr. Eng. Manag. 2015, 141, 04015041. [Google Scholar] [CrossRef]
- Hosseini, A.; Lædre, O.; Andersen, B.; Torp, O.; Olsson, N.; Lohne, J. Selection criteria for delivery methods for infrastructure projects. Procedia-Soc. Behav. Sci. 2016, 226, 260–268. [Google Scholar] [CrossRef]
- Ameyaw, E.E.; Edwards, D.J.; Kumar, B.; Thurairajah, N.; Owusu-Manu, D.G.; Oppong, G.D. Critical Factors Influencing Adoption of Blockchain-Enabled Smart Contracts in Construction Projects. J. Constr. Eng. Manag. 2023, 149, 04023003. [Google Scholar] [CrossRef]
- An, X.; Wang, Z.; Li, H.; Ding, J. Project delivery system selection with interval-valued intuitionistic fuzzy set group decision-making method. Group Decis. Negot. 2018, 27, 689–707. [Google Scholar] [CrossRef]
- Nguyen, P.H.; Tran, D.; Lines, B.C. Fuzzy set theory approach to classify highway project characteristics for delivery selection. J. Constr. Eng. Manag. 2020, 146, 04020044. [Google Scholar] [CrossRef]
- Ajibike, W.A.; Adeleke, A.Q.; Muuka, G.N.; Bamgbade, J.A.; Darun, M.R.; Moshood, T.D. Impacts of Oil and Gas Internal Risk Factors on Project Success: Moderating Role of Government Support. Constr. Econ. Build. 2022, 22, 47–69. [Google Scholar] [CrossRef]
- Locatelli, G.; Brookes, N.; Mikic, M.; Kovacevic, M.; Ivanisevic, N. The Successful Delivery of Megaprojects: A Novel Research Method. Proj. Manag. J. 2017, 48, 78–94. [Google Scholar] [CrossRef]
- Ogunlana, S.O. Critical COMs of success in large-scale construction projects: Evidence from Thailand construction industry. Int. J. Proj. Manag. 2008, 26, 420–430. [Google Scholar]
- Liu, B.; Xue, B.; Huo, T.; Shen, G.; Fu, M. Project external environmental factors affecting project delivery systems selection. J. Civ. Eng. Manag. 2019, 25, 276–286. [Google Scholar] [CrossRef]
- Gharehbaghi, K.; McManus, K.; Robson, K. Minimizing the environmental impacts of mega infrastructure projects: Australian public transport perspective. J. Eng. Des. Technol. 2019, 17, 736–746. [Google Scholar] [CrossRef]
- Shahbaz, M.S.; Soomro, M.A.; Bhatti, N.U.K.; Soomro, Z.; Jamali, M.Z. The impact of supply chain capabilities on logistic efficiency for the construction projects. Civ. Eng. J. 2019, 5, 1249–1256. [Google Scholar] [CrossRef]
- Lu, Y.; Luo, L.; Wang, H.; Le, Y.; Shi, Q. Measurement model of project complexity for large-scale projects from task and organization perspective. Int. J. Proj. Manag. 2015, 33, 610–622. [Google Scholar] [CrossRef]
- Miller, J.B.; Garvin, M.J. Toward a New Paradigm: Simultaneous Use of Multiple Project Delivery Methods. J. Manag. Eng. 2000, 16, 58. [Google Scholar] [CrossRef]
Description | Results |
---|---|
Main Information about the Data | |
Timespan | 2000:2023 |
Sources (Journals, Books, etc.) | 180 |
Documents | 639 |
Annual Growth Rate % | −2.97 |
Document Average Age | 7.53 |
Average citations per doc | 24.41 |
References | 27,014 |
Document Contents | |
Keywords Plus (ID) | 2117 |
Author’s Keywords (DE) | 1625 |
Authors | |
Authors | 1356 |
Authors of single-authored docs | 61 |
Authors Collaboration | |
Single-authored docs | 66 |
Co-Authors per Doc | 2.97 |
International co-authorships % | 12.68 |
Collaboration Index | 2.25 |
Document Types | |
Article | 624 |
Article; early access | 15 |
Governance and Administration 7.04% | Design Management Approach 10.03% | ||||
---|---|---|---|---|---|
Organisation type and size | [3,24,40,80,81,82,83,84] | 1.20% | Agency control over design | [3,40,42,81,83,85,86,87,88] | 1.35% |
Program organisation maturity | [3,42,56,57,58,82,84,87,89,90,91,92,93] | 1.95% | Level of design completion, detailing, quality, and documentation | [42,57,80,83,86,87,91,92,93,94,95,96,97] | 1.95% |
Top management or agency support | [3,42,57,58,81,84,90,91,92] | 1.35% | Flexibility regarding design | [3,24,81,85,86,91,94,95,97,98,99,100,101] | 1.95% |
Organisational responsibilities assigned to the right-sized capable team | [80,82,84,90,92] | 0.75% | Teams’ capability | [3,42,83,91] | 0.60% |
Construction program innovation features | [39,40,42,57,85,87,92,99,101] | 1.35% | |||
PM approach | [42,58,84,87,90,92,93,96,98] | 1.35% | Sustainability | [80,85,89,102] | 0.60% |
Transparency | [84,92,96] | 0.45% | Constructability | [40,56,81,82,85,96,97,99,101,103,104] | 1.65% |
Risk Allocation 11.53% | |||||
Early contractor engagement in the design Phase | [3,56,89,99] | 0.60% | |||
Schedule risks | [3,24,39,80,85,86,87,88,89,93,96,97,99,101,103,104,105,106] | 2.69% | |||
Technical risk | [3,24,40,42,80,81,83,85,89,92,93,94,96,100,101,103,104,105] | 2.69% | Finance Approach 5.24% | ||
Organisational risk | [24,56,80,85,89,90,92,96,104] | 1.35% | Source of funding capacity | [3,24,39,40,42,57,81,82,85,87,88,90,96,99,103] | 2.25% |
Financial/Cost risks | [3,24,39,80,85,86,87,88,89,93,96,99,101,103,104,105,106] | 2.40% | Funding cycle | [3,42,57,82,88,95,96] | 1.05% |
Management risk | [3,24,42,56,80,85,90,92,93,94,96,97,103,104,105,107] | 2.40% | Stakeholder partnership/shares and credibility | [42,57,87,89,96] | 0.75% |
Cost and time Determinants 11.23% | Cash flow Status | [3,24,57,82,85,89,95,96] | 1.20% | ||
Delivery speed | [3,73,85,86,88,93,94,98,99,101] | 1.50% | Legislative Procedure 5.39% | ||
Contract type | [3,82,84,86,89,94,95,98,99,101,107] | 1.65% | Dispute Resolution/jurisdictional complexities | [56,81,89,94,103] | 0.75% |
Payment time flexibility | [3,80,82] | 0.45% | Engagement of the government | [81,86,90,94] | 0.60% |
Value for money | [3,40,80,82,87] | 0.75% | |||
Tender and contract award approach | [3,57,85,86,87,88,89,98] | 1.20% | Legislative Prerequisite/Regulatory and statutory requirements | [42,80,85,86,90,94,97,103,108] | 1.35% |
Completion of estimated (original) budget and schedule | [24,40,42,57,80,81,83,86,87,88,90,92,98,99,101,103,105,106] | 2.69% | Regulatory Feasibility | [3,40,80,91,94,97,101,108] | 1.20% |
Predictability | [3,24,80,81,82,86,87,96,97,98,99,101,103,105,106,107] | 2.54% | Contracting law clarity | [3,42,56,86,89,91,93,94,95,96] | 1.50% |
Change orders frequency | [88,96,101] | 0.45% | |||
Scope Definability 7.63% | Stakeholder Influences/Intervention 5.69% | ||||
Main drivers | [3,24,39,40,56,57,81,82,90,91,100,101,107] | 1.95% | Political stability | [40,74,75,85,86,89,92,93,98,105] | 1.50% |
Goals | [24,39,42,56,85,90,92,93,98,107] | 1.50% | Consensus on rules of governance | [39,56,57,83,84,86,87,88,90,91,93,96] | 1.80% |
Lifecycle expected span | [39,85,90,96,101] | 0.75% | |||
Certain outcomes | [39,42,56,57,81,82,85,87,89,90,93,98,100,101,107] | 2.25% | Dispute resolution and frequency | [80,84,86,87,90,91,98,100,101,108] | 1.50% |
Scope creep | [3,39,42,68,91,94,96,100] | 1.20% | |||
Third-party agreement | [3,40,87,93,94,97] | 0.90% | |||
Technical Clarity 5.24% | Local and environmental preferences 4.94% | ||||
Resource technical competency | [42,57,83,85,89,92,93,96,97,98,103,107] | 1.80% | Local condition of the program site, size and type | [1,39,40,42,74,75,77,79,80,81,86,89,91,95,96,97,98,100,104,105] | 2.99% |
Contractor capability | [3,42,57,80,82,85,91,97,101,108] | 1.50% | Environmental Impact | [40,81,85,88,89,92,93,94,96,97,101,104,108] | 1.95% |
In-house technical capability | [3,40,42,80,82,83,85,86,88,96,99,101,108] | 1.95% | |||
Economic influences 1.50% | Logistics 1.20% | ||||
Stability/Growth | [39,91,95,99,103] | 0.75% | Logistics planning approach | [39,87,109,110] | 0.60% |
Inflation rate | [42,89,93,96,99] | 0.75% | |||
Market Status 4.19% | Proximity to resources | [80] | 0.15% | ||
Market stability/availability | [40,80,81,85,87,93,99,108] | 1.20% | logistics challenges | [80,97,108] | 0.45% |
Market competitiveness | [3,40,80,81,84,85,87,93,99,101,103,108] | 1.80% | Institutional cognitive load 2.54% | ||
Certain GC/subcontractor availability and credibility | [40,42,80,81,91,97,99,101,107] | 1.20% | Status que bias | [83,108] | 0.30% |
Institutional wisdom | [86,91,103] | 0.45% | |||
Resource workload 3.89% | Cultural environment | [3,40,42,57,80,81,84,87,91,92,95,108] | 1.80% | ||
Human resource allocation | [39,40,56,57,80,81,82,84,86,89,90,91,92,93,101,107] | 2.40% | Agency history 4.04% | ||
Other resources allocation | [39,57,80,81,84,90,91,92,93,107] | 1.50% | Familiarity and experience | [3,24,39,40,57,83,86,87,90,91,97,99,103] | 1.95% |
Quality management 5.09% | knowledge retention | [39,57,83,87,90,92,96] | 1.05% | ||
Risk toleration | [3,40,42,83,85,101,103] | 1.05% | |||
Quality performance | [3,24,42,73,80,81,82,85,91,94,98,101,103,104,105] | 2.25% | Teamworking 3.59% | ||
Consensus on quality standards | [56,80,85] | 0.45% | Certain incentives and penalties | [91,95,96] | 45% |
Quality control and safety | [42,80,81,86,87,91,92,94,95,98] | 1.50% | Credibility in commitments | [56,83,91,107] | 0.60% |
Quality assurance | [3,42,56,80,91,94] | 0.90% | Teams’ trust, cooperation and coordination | [40,42,56,81,84,86,87,88,91,92,95,96] | 1.80% |
Program organisation responsibility | [80,82,88,95,96] | 0.75% |
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Taheriboshrouyeh, M.; Sandanayake, M.; Fragomeni, S. A Review of Construction Program Delivery Attributes: Bibliometric Analysis of Two Decades. Buildings 2023, 13, 2664. https://doi.org/10.3390/buildings13102664
Taheriboshrouyeh M, Sandanayake M, Fragomeni S. A Review of Construction Program Delivery Attributes: Bibliometric Analysis of Two Decades. Buildings. 2023; 13(10):2664. https://doi.org/10.3390/buildings13102664
Chicago/Turabian StyleTaheriboshrouyeh, Mehdi, Malindu Sandanayake, and Sam Fragomeni. 2023. "A Review of Construction Program Delivery Attributes: Bibliometric Analysis of Two Decades" Buildings 13, no. 10: 2664. https://doi.org/10.3390/buildings13102664