Quantifying Critical Success Factors (CSFs) in Management of Investment-Construction Projects: Insights from Bayesian Model Averaging

Abstract

The problem with evaluating investment projects is that there are many factors that determine the degree of their successful conclusion. Consequently, there has been an active debate for years as to which critical success factors (CSFs) contribute most to the performance of construction projects. This is because the practice of empirical research is based on two steps: first, researchers choose a particular model from the space of all possible models, and second, they act as if the chosen model is the only one that fits the data and describes the phenomenon under study. Hence, there are many CSF lists that can be found in the literature, owing to the uncertainty at the model selection stage, which is usually ignored. Alternatively, model averaging accounts for this model uncertainty. In this study, the Bayesian model averaging and data from a survey of Polish construction managers were used to investigate the potential of 28 factors describing a diverse set of characteristics in explaining the performance of construction projects in Poland. Determinants of successful completion of investment projects are categorized by their level of evidential strength, which is derived from posterior inclusion probabilities (PIPs), i.e., providing strong, medium and weak evidence.

Project Risk in the Context of Construction Schedules—Combined Monte Carlo Simulation and Time at Risk (TaR) Approach: Insights from the Fort Bema Housing Estate Complex

“…Time uncertainty is ubiquitous in all disciplines of project planning and scheduling, yet in the construction industry it is of particular importance [1][2][3][4][5][6]. In particular, the uncertainty and risk associated with scheduling is an important aspect of large and complex construction projects [7][8][9][10].…”

“…In particular, the uncertainty and risk associated with scheduling is an important aspect of large and complex construction projects [7][8][9][10]. In fact, successful project completion is mainly the result of a variety of multidirectional and comprehensive activities in the area of the creation of companies' intellectual capital, preparation of flexible plans and schedules, and their posterior implementation [3]. The analysis of completion times for individual activity tasks as well as entire phases/stages of the construction process should help project managers understand the factors that influence the final estimate of project duration [1,10].…”

“…These include Bayesian networks [34,35], decision trees and Bayesian classification algorithms [36], Naïve Bayesian (machine learning models) [36], Bayesian Belief Network [37], logistic regression [38], Markov Dynamic PERT Model [39] and Correlated Schedule Risk Analysis (CSRA) [20]. It should be noted here that understanding schedules is an important thing that often determines project success [2,3,40], therefore the more tools and research findings to help understanding in the area of project scheduling, the better.…”

Correlation of Construction Performance Indicators and Project Success in a Portfolio of Building Projects

“…Pace [3] recognized that project success factors are important to the overall successful outcome of a project, examining a number of studies in an attempt to correlate reported project success with the chosen project management methodology, but recognizing only a weak correlation at best. Determining project success is dependent on the stakeholder's role in the project [4][5][6][7][8][9][10][11][12][13][14][15][16]. Pinto and Slevin [10] discussed the criteria for a project consisting of the following characteristics: a specified time for completion (schedule), a limited or defined budget (budget), performance expectations and a series of activities (performance), and issues dealing with the client (client satisfaction).…”

“…The defined characteristics of a project become the criteria evaluated to determine success, and if the characteristics are incomplete, a determination of project success may be incomplete or inaccurate. Critical success factors (CSFs) can help quantify the success of a project, but which CSFs contribute the most to performance and if they apply equally to all stakeholders continues to be an ongoing debate [12]. Atkinson [5] goes on to state that success must be defined beyond the simplistic "iron triangle" of cost, schedule, and quality, and should include the criteria of the information system, organizational benefits, and stakeholder community benefits.…”