161
Views
0
CrossRef citations to date
0
Altmetric
Articles

Understanding the slow diffusion of alternative delivery systems using interpretive structural modelling

ORCID Icon, , , &
Pages 459-476 | Received 24 Mar 2021, Accepted 20 May 2022, Published online: 09 Jun 2022

References

  • Aldossari, K.M., et al., 2020. Best practices of organizational change for adopting alternative project delivery methods in the AEC industry. Engineering, construction and architectural management, 28(4), 1060–1082.
  • Aldossari, K.M., et al., 2021. Employee reactions to adoption of alternative project delivery methods within the AEC industry. International journal of construction education and research. https://doi.org/https://doi.org/10.1080/15578771.2021.1900463.
  • Alhazmi, T. and McCaffer, R., 2000. Project procurement system selection model. Journal of construction engineering and management, 126 (3), 176–184.
  • Al-Sinan, F.M. and Hancher, D.E., 1988. Facility project delivery selection model. Journal of management in engineering, 4 (3), 244–259.
  • Antoine, A.L.C., Alleman, D., and Molenaar, K.R., 2019. Examination of project duration, project intensity, and timing of cost certainty in highway project delivery methods. Journal of management in engineering, 35 (1), 04018049.
  • Babatunde, S.O., et al., 2015. Barriers to public private partnership projects in developing countries A case of Nigeria. Engineering, construction and architectural management, 22 (6), 669–691.
  • Birner, R. and Wittmer, H., 2006. Better public sector governance through partnership with the private sector and civil society: the case of Guatemala’s forest administration. International review of administrative sciences, 72 (4), 459–472.
  • Cao, D., et al., 2016. Linking the motivations and practices of design organizations to implement building information modeling in construction projects: empirical study in China. Journal of management in engineering, 32(6), 04016013.
  • Cao, D.P., Li, H., and Wang, G.B., 2014. Impacts of isomorphic pressures on BIM adoption in construction projects. Journal of construction engineering and management, 140(12), 04014056.
  • Chan, A.P., et al., 2009. Drivers for adopting public private partnerships—empirical comparison between China and Hong Kong special administrative region. Journal of construction engineering and management, 135 (11), 1115–1124.
  • Chen, Y.Q., et al., 2011. Project delivery system selection of construction projects in China. Expert systems with applications, 38 (5), 5456–5462.
  • Chou, J.-S. and Pramudawardhani, D., 2015. Cross-country comparisons of key drivers, critical success factors and risk allocation for public-private partnership projects. International journal of project management, 33 (5), 1136–1150.
  • Daniel, E.I., Pasquire, C., and Dickens, G., 2019. Development of approach to support construction stakeholders in implementation of the last planner system. Journal of management in engineering, 35 (5), 04019018.
  • Dou, Y., et al., 2019. Factors influence China’s off-site construction technology innovation diffusion. Sustainability, 11(7), 1849.
  • Duperrin, J. and Godet, M., 1973. Methode de hierarchisation des elements d’un systeme. Journal of rapport economique du CEA, Paris, 45–51.
  • Edirisinghe, R., et al., 2017. Building information modelling for facility management: are we there yet? Engineering, construction and architectural management, 24 (6), 1119–1154.
  • Faisal, M.N. and Talib, F., 2016. Implementing traceability in Indian food-supply chains: an interpretive structural modeling approach. Journal of foodservice business research, 19 (2), 171–196.
  • Fernandez-Solis, J.L., et al., 2013. Survey of motivations, benefits, and implementation challenges of last planner system users. Journal of construction engineering and management, 139 (4), 354–360.
  • Franz, B.W. and Leicht, R.M., 2016. An alternative classification of project delivery methods used in the United States building construction industry. Construction management and economics, 34 (3), 160–173.
  • Gambatese, J.A. and Hallowell, M., 2011. Factors that influence the development and diffusion of technical innovations in the construction industry. Construction management and economics, 29 (5), 507–517.
  • Gan, X., et al., 2018. Barriers to the transition towards off-site construction in China: An Interpretive structural modeling approach. Journal of cleaner production, 197, 8–18.
  • Geddes, R.R. and Reeves, E., 2017. The favourability of U.S. PPP enabling legislation and private investment in transportation infrastructure. Utilities policy, 48, 157–165.
  • Gholizadeh, P., Esmaeili, B., and Goodrum, P., 2018. Diffusion of building information modeling functions in the construction industry. Journal of management in engineering, 34 (2), 04017060.
  • Gledson, B.J. and Greenwood, D., 2017. The adoption of 4D BIM in the UK construction industry: an innovation diffusion approach. Engineering, construction and architectural management, 24 (6), 950–967.
  • Gunhan, S., 2019. Analyzing sustainable building construction project delivery practices: builders perspective. Practice periodical on structural design and construction, 24 (1), 05018003.
  • Hale, D.R., et al., 2009. Empirical comparison of design/build and design/bid/build project delivery methods. Journal of construction engineering and management, 135 (7), 579–587.
  • Hawthorne, R.W. and Sage, A.P., 1975. On applications of interpretive structural modeling to higher education program planning. Socio-economic planning sciences, 9 (1), 31–43.
  • Hosseini, M.R., et al., 2016. BIM adoption within Australian small and medium-sized enterprises (SMEs): an innovation diffusion model. Construction economics and building, 16 (3), 71–86.
  • Ismail, S. and Harris, F.A., 2014. Challenges in implementing public private partnership (PPP) in Malaysia. Procedia - social and behavioral sciences, 164, 5–10.
  • Iyer, K.C. and Sagheer, M., 2010. Hierarchical structuring of PPP risks using interpretative structural modeling. Journal of construction engineering and management, 136 (2), 151–159.
  • Kale, S. and Arditi, D., 2010. Innovation diffusion modeling in the construction industry. Journal of construction engineering and management, 136 (3), 329–340.
  • Kang, S., et al., 2019. Public-private partnerships in developing countries: factors for successful adoption and implementation. International journal of public sector management, 32 (4), 334–351.
  • Kaufmann, D., Kraay, A., and Mastruzzi, M., 2011. The worldwide governance indicators: methodology and analytical issues. Hague journal on the rule of law, 3 (2), 220–246.
  • Kyriazos, T.A., 2018. Applied psychometrics: sample size and sample power considerations in factor analysis (EFA, CFA) and SEM in general. Psychology, 9 (08), 2207.
  • Lahdenperä, P., 2012. Making sense of the multi-party contractual arrangements of project partnering, project alliancing and integrated project delivery. Construction management and economics, 30 (1), 57–79.
  • Li, Y.Y., et al., 2011. Critical project management factors of AEC firms for delivering green building projects in Singapore. Journal of construction engineering and management, 137 (12), 1153–1163.
  • Lindgren, J. and Emmitt, S., 2017. Diffusion of a systemic innovation: a longitudinal case study of a Swedish multi-storey timber housebuilding system. Construction innovation-England, 17 (1), 25–44.
  • Liu, B., et al., 2015. Which owner characteristics are key factors affecting project delivery system decision making? Empirical analysis based on the rough set theory. Journal of management in engineering, 31 (4), 05014018.
  • Liu, B., et al., 2016a. Identification of key contractor characteristic factors that affect project success under different project delivery systems: empirical analysis based on a group of data from China. Journal of management in engineering, 32 (1), 05015003.
  • Liu, B., et al., 2016b. 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. Journal of professional issues in engineering education and practice, 142 (4), 05016003.
  • Lundberg, M., Engstrom, S., and Lidelow, H., 2019. Diffusion of innovation in a contractor company: the impact of the social system structure on the implementation process. Construction innovation-England, 19 (4), 629–652.
  • Luu, D.T., Ng, S.T., and Chen, S.E., 2005. Formulating procurement selection criteria through case-based reasoning approach. Journal of computing in civil engineering, 19 (3), 269–276.
  • Maali, O., Kepple, N., and Lines, B., 2022. Strategies to achieve high adoption of organizational change initiatives within the AEC industry. Journal of management in engineering, 38 (4), 04022021.
  • Mafakheri, F., et al., 2007. Project delivery system selection under uncertainty: multicriteria multilevel decision aid model. Journal of management in engineering, 23 (4), 200–206.
  • Migliaccio, G.C., Gibson, G.E., and O'Connor, J.T., 2008. Changing project delivery strategy: an implementation framework. Public works management & policy, 12 (3), 483–502.
  • Minchin, R.E., et al., 2013. Comparison of cost and time performance of design-build and design-bid-build delivery systems in Florida. Journal of construction engineering and management, 139 (10), 04013007.
  • Minchin, R. E., et al., 2014. Design management guide for design-build and construction manager/general contractor projects. Washington DC.: U.S. Department of Transportation.
  • Minchin, R. E., et al., 2016. Alternative contracting research: final report. Tallahassee, Florida: Department of Transportation.
  • Mollaoglu-Korkmaz, S., et al., 2016. Diffusion of green building guidelines as innovation in developing countries. Construction innovation-England, 16 (1), 11–29.
  • Mollaoglu-Korkmaz, S., Riley, D., and Horman, M., 2010. Piloting evaluation metrics for sustainable high-performance building project delivery. Journal of construction engineering and management, 136 (8), 877–885.
  • Mollaoglu-Korkmaz, S., Swarup, L., and Riley, D., 2013. Delivering sustainable, high-performance buildings: influence of project delivery methods on integration and project outcomes. Journal of management in engineering, 29 (1), 71–78.
  • Mostafavi, A. and Karamouz, M., 2010. Selecting appropriate project delivery system: fuzzy approach with risk analysis. Journal of construction engineering and management, 136 (8), 923–930.
  • Ng, S.T., Wong, Y.M.W., and Wong, J.M.W., 2012. Factors influencing the success of PPP at feasibility stage – a tripartite comparison study in Hong Kong. Habitat international, 36 (4), 423–432.
  • Olanipekun, A.O., et al., 2017. Motivation for delivering green building projects. Journal of construction engineering and management, 143 (9), 04017068.
  • Osei-Kyei, R. and Chan, A.P.C., 2015. Review of studies on the critical success factors for public–private partnership (PPP) projects from 1990 to 2013. International journal of project management, 33 (6), 1335–1346.
  • Otairu, A., et al., 2014. Slow adoption of PPPs in developing countries: survey of Nigerian construction professionals. Procedia engineering, 77, 188–195.
  • Park, M., et al., 2009. Strategies for design-build in Korea using system dynamics modeling. Journal of construction engineering and management, 135 (11), 1125–1137.
  • Percoco, M., 2014. Quality of institutions and private participation in transport infrastructure investment: evidence from developing countries. Transportation research part A: policy and practice, 70, 50–58.
  • Prakash, A. and Phadtare, M., 2019. Exploration of logic in project marketing using interpretive structural modeling. Journal of construction engineering and management, 145 (11), 04019066.
  • Ptschelinzew, L., et al., 2020. Relationship management strategies for identifying party discord and misperceptions. Journal of legal affairs and dispute resolution in engineering and construction, 12 (2), 03720002.
  • Raut, R.D., et al., 2018. Analyzing the factors influencing cloud computing adoption using three stage hybrid SEM-ANN-ISM (SEANIS) approach. Technological forecasting social change, 134, 98–123.
  • Ringnér, M., 2008. What is principal component analysis? Nature biotechnology, 26 (3), 303–304.
  • Rogers, E. M., 1995. Diffusion of innovations: modifications of a model for telecommunications. In: M.-W. Stoetzer and A. Mahler, eds. Die Diffusion von Innovationen in der Telekommunikation. Berlin: Springer, 25–38.
  • Sage, A. P., 1977. Interpretive structural modeling: methodology for large-scale systems. New York, NY: McGraw-Hill.
  • Sepasgozar, S.M.E. and Loosemore, M., 2017. The role of customers and vendors in modern construction equipment technology diffusion. Engineering, construction and architectural management, 24 (6), 1203–1221.
  • Shane, J.S., Bogus, S.M., and Molenaar, K.R., 2013. Municipal Water/Wastewater Project Delivery Performance Comparison. Journal of management in engineering, 29 (3), 251–258.
  • Shen, L., et al., 2016. Interpretive structural modeling based factor analysis on the implementation of emission trading system in the Chinese building sector. Journal of cleaner production, 127, 214–227.
  • Sherratt, F., Sherratt, S., and Ivory, C., 2020. Challenging complacency in construction management research: the case of PPPs. Construction management and economics, 38 (12), 1086–1100.
  • Shrestha, A., et al., 2018. Risk allocation inefficiencies in Chinese PPP water projects. Journal of construction engineering and management, 144 (4), 04018013.
  • Shrestha, P.P. and Batista, J.R., 2021. Transition from traditional to alternative project delivery methods in water and wastewater project: executive decision-makers' perspective. Engineering, construction and architectural management. https://doi.org/https://doi.org/10.1108/ECAM-10-2020-0791.
  • Sive, T., 2009.  Integrated project delivery: Reality and promise, a strategist’s guide to understanding and marketing IPD. Washington: Society for Marketing Professional Services Foundation.
  • Song, J., Hu, Y., and Feng, Z., 2018. Factors influencing early termination of PPP projects in China. Journal of management in engineering, 34 (1), 05017008.
  • Thirupathi, R.M. and Vinodh, S., 2016. Application of interpretive structural modelling and structural equation modelling for analysis of sustainable manufacturing factors in Indian automotive component sector. International journal of production research, 54 (22), 6661–6682.
  • Touran, A., et al., 2011. Selection of project delivery method in transit: drivers and objectives. Journal of management in engineering, 27 (1), 21–27.
  • Tran, D.Q., Diraviam, G., and Minchin, R.E., 2018. Performance of highway design-bid-build and design-build projects by work types. Journal of construction engineering and management, 144 (2), 04017112.
  • Tran, D.Q., et al., 2013. Project delivery selection matrix for highway design and construction. Transportation research record: journal of the transportation research board, 2347 (1), 3–10.
  • Venkatesh, V.G., Rathi, S., and Patwa, S., 2015. Analysis on supply chain risks in Indian apparel retail chains and proposal of risk prioritization model using interpretive structural modeling. Journal of retailing and consumer services, 26, 153–167,
  • Wang, H., et al., 2019. The moderating role of governance environment on the relationship between risk allocation and private investment in PPP markets: evidence from developing countries. International journal of project management, 37 (1), 117–130.
  • Wang, W., et al., 2019. An empirical analysis of the factors affecting the adoption and diffusion of GBTS in the construction market. Sustainability, 11 (6), 1795.
  • Watson, R.H., 1978. Interpretive structural modeling—a useful tool for technology assessment? Technological forecasting and social change, 11 (2), 165–185.
  • Wibowo, A. and Alfen, H.W., 2015. Government-led critical success factors in PPP infrastructure development. Built environment project and asset management, 5 (1), 121–134.
  • Xu, H., Feng, J., and Li, S., 2014. Users-orientated evaluation of building information model in the Chinese construction industry. Automation in construction, 39, 32–46.
  • Yang, J., Nisar, T.M., and Prabhakar, G.P., 2017. Critical success factors for build–operate–transfer (BOT) projects in China. The Irish journal of management, 36 (3), 147–161.
  • Yuan, H. and Yang, Y., 2020. BIM adoption under government subsidy: technology diffusion perspective. Journal of construction engineering and management, 146 (1), 04019089.
  • Zhang, Y., 2014. From state to market: private participation in China’s urban infrastructure sectors, 1992–2008. World development, 64, 473–486.
  • Zhang, Y., 2015. The formation of public-private partnerships in China: an institutional perspective. Journal of public policy, 35 (2), 329–354.
  • Zheng, C., et al., 2019. Process-based identification of critical factors for residual value risk in China’s highway PPP projects. Advances in civil engineering, 2019, 1–21.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.