Complexity Measurement in Engineering Projects Using Factor Analysis and the Single Multi-Attribute Rating Technique Exploiting Ranks (SMARTER)
American Journal of Management Science and Engineering
Volume 1, Issue 2, November 2016, Pages: 36-43
Received: Sep. 8, 2016;
Accepted: Sep. 22, 2016;
Published: Oct. 15, 2016
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Odysseas Manoliadis, Democritus University of Thrace, Department Civil Engineering, Xanthi, Greece
Emmanouil Vasilakis, Hellenic Open University, Management in Technical Projects, Patra, Greece
A lot of problems that emanate from complexity could have been mitigated or even avoided, if the factors that render a project complex and the risks that they induce, were fully comprehensible in order for a more appropriate management process to be established. The aim of this study is the comprehension of the meaning of complexity in engineering projects through the identification of the factors that affects it based on which a project complexity measurement model is proposed. To that end an extensive literature review has been conducted in order to detect as many factors already identified by previous researchers as possible and to categorize them in a way that can integrate the existing theoretical and empirical approaches. Through that study, 21 factors that contribute to the complexity of engineering projects were distinguished. Afterwards, following the results of a questionnaire survey that was carried out and upon implementing factor analysis on its data, 7 key factors were discerned as the main components of the complexity variables. Finally, using a simplified method of multiple-criteria decision analysis, namely Single Multi Attribute Rating Technique Exploiting Ranking – SMARTER, a practical and approachable model of complexity measurement has been introduced, named Complexity Level Indicator – CLI.
Complexity Measurement in Engineering Projects Using Factor Analysis and the Single Multi-Attribute Rating Technique Exploiting Ranks (SMARTER), American Journal of Management Science and Engineering.
Vol. 1, No. 2,
2016, pp. 36-43.
Vidal, L.-A., & Marle, F. (2008). Understanding project complexity: implications on project management. 37 (8), 1094-1110.
Baccarini, D. (1996). The concept of project complexity, a review. International Journal of Project Management, 14 (4), 201-204.
Masood, A., & Mini, J. (2007). Complexity in Projects. Practitioners' understanding complexity in relation to existing theoretical models. Master Thesis.
Geraldi, J. (2009). What complexity assessments can tell us about projects: dialogue between conception and perception. Technology Analysis & Strategic Management, 21 (5), 665-678.
Austin, S., Newton, A., Steele, J., & Waskett, P. (2002). Modelling and managing project complexity. International Journal of Project Management, 20, 191-198.
Edmonds, B. (1999). Syntactic measures of complexity. Thesis for the degree of doctor of philosophy in the faculty of arts, University of Manchester.
Marle, F. (2002). Modele d'informations et methodes pour aider a la prise de decision en management de projets. Thesis, Genie Industriel de l'Ecole Centrale, Paris.
Docker, T., & Vincent, G. (2009). CITI CofEe Club. Accessed 11 14, 2015, www.eciti.co.uk/cofee
Snowden, D., & Boone, M. (2007, November). A leader's framework for decision making. Harvard Business Review. Accessed 4 12, 2016, https://hbr.org/2007/11/a-leaders-framework-for-decision-making
Geraldi, J., Maylor, H., & Williams, T. (2011). Now, let's make it really complex (complicated). International Journal of Operations & Production Management, 31 (9), 966-990.
Bosch-Rekveldt, M., Jongkind, Y., Mooi, H., Bakker, H., & Verbraeck, A. (2011). Grasping project complexity in large engineering projects: the TOE (Technical, Organizational and Environmental) framework. International Journal of Project Management, 29 (6), 728-739.
Hass, K. B. (2008, 10 2). Introducing the New Project Complexity Model. Accessed 2 13, 2016, https://www.projecttimes.com/articles/introducing-the-new-project-complexity-model-part-i.html
Page, S. (2008). Uncertainty, difficulty, and complexity. Journal of Theoritical Politics, 20 (2), 115-149
Bosch-Rekveldt, M. (2011). Managing project complexity - A study into adapting early project phases to improve project performance in large engineering projects. The Hague, The Netherlands: Delft Centre for Project Management.
Vidal, L.-A., Marle, G., & Bocquet, J.-C. (2011). Using a Delphi process and the Analytic Hierarchy Process (AHP) to evaluate the complexity of projects. Expert Systems with Applications, 38 (5), 5388-5405.
Xia, B., & Chan, A. P. (2012). Measuring complexity for building projects: A Delphi study. Engineering, Construction and Architectural Management, 19 (1), 7-24.
Olson, D. (1996). Decision Aids for Selection Problems. Springer Series in Operations Research.
Sinha, S., Kumar, B., & Thomson, A. (2006). Measuring project complexity: a project manager's tool. Architecture Engineering and Design Management, 2, 187-202.
Gidado, K. (1996). Project complexity: the focal point of construction production planning. Construction Management and Economics, 14 (3), 213-225.
Remington, K., Zolin, R., & Turner, R. (2009). A model of project complexity: distinguish dimensions of complexity from severity. Proceedings of the 9th International Research Network of Project Management Conference. Berlin.
Roberts, R., & Goodwin, P. (2002). Weights approximations in multi-attribute decision models. Journal of Multi-Criteria Decision Analysis, 11, 291-303.
Barron, F., & Barrett, B. (1996). The efficacy of SMARTER - Simple Multi-Attribute Rating Technique Extended to Ranking. Acta Psychologica, 93, 23-36.
Edwards, W., & Barron, F. (1994). SMARTS and SMARTER: Improved simple methods for multiattribute utility. Organizational Behavior and Human Decision Processes, 60, 306-325.