Impact of project procurement systems on performance of Rwandan building construction projects

This section presents a review of the previous studies that have dealt with the influence of project procurement systems on the key project constraints and their indicators in various countries.

It is widely accepted view that, at a minimum, key constraints of construction project performance are time, cost and quality (Barkley and Saylor 1994). However, Yates and Eskander (2002) remarked that four key criteria must be used in measuring project performance; and according to the view expounded in their study, a successful project has to be completed within the scheduled time, within budget and within scope, and should satisfy the relevant quality requirements. Since these requirements are needed to be simultaneously satisfied, with the effort made towards the fulfilment of one of these not impeding the achievement of any of the others, they constitute the primary paradox of project management (Caccamese and Bragantini 2012). Therefore, based on the previous studies, this study also adopted four attributes – namely, time, cost, quality and scope – as the project performance criteria.

Oladinrin et al. (2013) assessed the effects of selected procurement systems – namely, CM, DB, management contracting and traditional procurement system – on the project’s cost and quality in 76 building projects in Nigeria. The measurement indicators used for cost were delay costs, claims costs, contingencies costs, cost related to environmental issues, cost related to insurance, legal costs, managerial cost, variation between contract sum and final account, variation in design/change orders, retention and rework; and the indicators used for quality were adherence and compliance with specification, competence of contractor and his team, inconsistency of variation and change orders, insistence on specification, major variation between original design and the actual completed work, material test, number of rework, number of variation, and supervision of works. The results revealed that the traditional procurement system was the most-employed option in executing projects in Nigeria. Thus, the DB system performed better in terms of cost, while the CM system was identified as the most suitable system whenever quality was the most prioritised objective. Based on these results, it was discovered that none of the selected procurement systems is the best for all the performance assessment criteria; instead, one can be better than the other against a specific performance criteria. This is in agreement with Abdul Rashid et al. (2016), who stated that each procurement system possesses its own peculiarity that will provide a different impact on the critical parameters of project performance, i.e. time, cost and quality.

A study by Ling et al. (2001) compared the performance of DB and DBB procurement systems in Singapore and Australia. The criteria to gauge the performance were: aesthetic quality, workmanship quality, physical construction time, total development time, timeliness of completion, and costs. The results of the Analysis of variance (ANOVA) showed that DB project time and cost performance in the two countries were not significantly different. Also, Singapore and Australian architects revealed the aesthetic quality and workmanship quality of DB projects to be lower than those of DBB projects. This is consistent with the studies of Hogg and Morledge (1995) and Smith et al. (1992), which revealed that the nature of DB projects resulted in a failure to achieve high quality. Therefore, the DB system is used to simultaneously meet the owner’s requirements and reduce the contractor’s cost. Under this system, since they are motivated to submit the lowest bid, the contractors are incentivised to lower quality, which would enable them to achieve more savings in costs together with completion of the defined scope of the work. Thus, financial pressure would take the precedence over the project’s quality standards.

Through a survey research, Sanvido et al. (1997) evaluated the cost, schedule and quality performance of US building projects that used CM at risk, DB and DBB project delivery systems. The metrics used for schedule performance were construction speed, delivery speed and schedule growth, while cost metrics were cost unit, cost growth and intensity; and quality metrics were start up; call backs; operation and maintenance; envelope, roof, structure and foundation; interior space and layout environment; and process equipment and layout. According to the results, the DB project delivery system achieved significantly improved cost and schedule advantages. Also, it was indicated that usage of this system yielded a better-quality performance than DBB projects and CM at risk.

Alhazmi and McCaffer (2000) conducted a survey on the performance of a project procurement system selection model in Saudi Arabia and it was revealed that Saudi public clients selected DB as the most appropriate procurement system for their project with an overall priority of 0.496. The model assisted in choosing the procurement system that would ideally fulfil their needs, and it consisted of various key criteria including cost, time and quality. Metrics used to measure cost were capital cost, maintenance cost, prequalification cost, cost overrun and reduction of financial risk. Metrics used to measure time were construction time, the early start of construction activity, planning and designing time, rapid response to new client needs, minimisation of activities interference, speed of construction, and time overruns. Metrics used to measure quality were design reliability and durability, design innovation, building systems guarantees, suitability of the intended uses, flexibility, and aesthetic appearance of the building.

Alaeddin and Nuhu (2016) assess the impact of DBB procurement methods on project performance in Libya and revealed that 11 out of its 12 common selection criteria exhibit a significant contribution to one or more project performance criteria, namely, time, cost and quality. The criteria highlighted as a best measure for one or more criteria were high price completion, clarity of scope definition, complexity of design, high quality level, clear definition for project parties’ responsibilities, client involvement, controllable project variations, cost certainty, organising and reviewing, project planning and project functionality.

Ghulam and Noel (2015) compared the performance evaluations of DB and traditional procurement systems for highway projects in Afghanistan and ascertained that DB was a superior option in terms of time performance, while it performed poorly in cost saving compared to the traditional procurement system. However, both the systems were identified as suitable in terms of quality performance. The quality variables used were in conformity with the applicable standards and specifications, and using these, it was possible to ensure compliance with warranty provisions as well as expectations as to the aesthetic quality of the workmanship, and thereby achieve overall client satisfaction. Cost saving and cost overrun were used as the main measurement metrics for cost, while, similarly, time saving and time overrun were used as the key measurements for time.

Luis et al. (1999) evaluated the improvement of the procurement process used in construction projects, where the potential performance indicators for the procurement process were identified as cycle times, event indicators, management indicators, cost indicators and referential values. For cost indicators, these were number of drops to ground and month, number of days in warehouse and in delivery, number of rules and of possible fiscal credits, number of repairs, number of special transport and time until release of container. The results indicated that the main problem of procurement is related to schedule delays and lack of specified quality for the project.

The study of Ameyaw (2009) evaluated the performance of the traditional DBB and DB procurement methods in Ghana and the findings indicated that, while a sizeable portion of DB projects are completed within their respective estimated durations and budgets, a greater number of DBB projects do incur time and cost overruns due to variation and price fluctuations. On the other hand, there is significant difference between the qualities of completed projects executed under the two project delivery methods.

Ron (2012) studied the changing of construction procurement culture to improve project outcomes and highlighted that construction projects need to be delivered on time, within the budget and in adherence with the applicable quality standard, but also need to meet the client requirement or agreed scope of work. Project Management Institute (2013) revealed the key components of scope management as defined project scope, set manageable requirements, control scope related risks such as scope change and scope creep, and a detailed identification of the scope involved using the trifurcation of scope into flexible, fixed and interfered scope.

Several previous studies have evaluated the influence of project procurement systems on the three key project constrains/performance criteria of time, cost and quality. However, the criteria have to be adjusted to reflect the most current attributes while executing projects in different countries. Accordingly, in this paper, the four project performance criteria of time, cost, quality and scope are utilised, since these have been extensively reported as the key factors determining the success or failure of construction projects (Yates and Eskander 2002). In addition, based on the above literature review, we are able to ascertain that the respective various effects that the choice of procurement system have on the different criteria vary from country to country, probably due to the disparity in the environment of their construction projects. Therefore, a gap emerges in the literature dealing with Rwandan construction projects, calling for the need to evaluate the influence of the various procurement systems on the mentioned key performance criteria: Finally, given the fact that there is a paucity in studies dealing with the evaluation of procurement systems’ effects on the measurement indicators associated with the mentioned key performance criteria, in formulating the list of the indicators corresponding to each criterion (for which an evaluation is proposed to be made), some indicators that are particularly compatible with the Rwandan construction industry were selected from several studies, adequately having the required type of content, that were identified based on a review of the literature and on experts’ opinions, as shown in Table 1.

The sample size was ascertained by employing formula of Taro Yamane (1973), which is utilised in reckoning the sample size when the number of a target population is known.

According to Yamane (1973): 1 n=N[ 1+(Ne2) ] \[n=\frac{N}{\left[ 1+\left( N{{e}^{2}} \right) \right]}\] where n = sample size, N = target population, e = error limit, and the error limit of 0.05 was used based on a 95% confidence level.

Therefore, n = 90/[1 + 90(0.05)²], and thus, n = 73.4.

A sample size of 74 respondents was adopted within an error limit of 5%. Only those participants who had been attending a university with ≥5 years of experience, who are familiar with the construction industry in Rwanda and who are considered reputable professionals were chosen. The participants comprising this study were clients, consultants and contractors having experience concerning various procurement systems, especially in the four most-utilised systems in Rwanda. They were chosen through purposive sampling technique in order to gather the data needed for the study. In order to obtain an appropriate sample size, 100 questionnaires were forwarded to the respondents. Out of the 100 questionnaires that were administered and sent through email, 73 questionnaires were received back as suitable for the analysis, signifying a response rate of 73%.

In order to ensure the reliability of the responses obtained for the questionnaire, and to verify the degree up to which these responses are in compliance with the research aim, the survey questionnaire was divided into two main sections. The first section of the questionnaire shows the background information of the respondents (organisation category, respondents’ position and years of experience), the type and size of the projects that are mostly executed, and the level of awareness concerning project procurement systems and their utility. The second section, firstly, dealt with rating the usage of the project procurement system using a 5-point Likert scale (1 – never, 2 – rare, 3 – sometimes, 4 – very often and 5 – always); and secondly, the effect of each procurement system on performance criteria and indicators was evaluated, likewise, using a 5-point Likert scale as follows: 1 – very low effect, 2 – low effect, 3 – medium effect, 4 – high effect and 5 – very high effect.

Cronbach’s α is one of the most-utilised methods for evaluating the inter-correlations among test items, which is known as an internal consistency estimate of the reliability of the test scores. If the Cronbach’s α is >0.9, the internal consistency is considered excellent, while 0.8 < α > 0.9 is good, and 0.7 < α > 0.8 is still acceptable (Tavakol and Dennich 2011). In this study, the Cronbach’s α coefficients of 0.880, 0.928, 0.910, 0.968 and 0.960 were obtained from the data concerning the usage levels of the four most-utilised delivery methods in Rwanda, the effect of ODF on performance criteria and indicators, the effect of DBB on performance criteria and indicators, the effect of DB on performance criteria and indicators, and the effect of CM on performance criteria and indicators, respectively. Therefore, the acceptable reliability was obtained as shown in Table 2. Additionally, a research methodology appropriate to the research aim and objectives was employed in order to achieve valid and reliable results.

Data obtained from the respondents were analysed using Statistical package for the social sciences (SPSS) IBM SPSS Statistics 22 (manufactured by HYPERLINK “https://en.wikipedia.org/wiki/Norman_H._Nie” Norman H. Nie, Dale H. Bent, C. Hadlai Hull, Stanford, USA) after screening for data entry errors in Microsoft Excel. After verifying the reliability of the data, the mean scores (MS) based on the 5-point Likert scale and ranks (R) were calculated to determine the level of influence that the choice of project procurement systems exerted on the project performance. scores (MS).

The first section of the demographic information presented in Table 3 shows the frequency of survey responses from participants according to the years of experience, qualification of the respondents, organisation category, position, the type and size details corresponding to the most-performed project, and awareness of project delivery methods. Only those with >5 years of experience were selected as respondents for the survey, in order to ensure that the chosen individuals would have adequate knowledge-sharing capabilities. The respondents were classified as persons with 5 years, 5–11 years, 10–15 years and >16 years of working experience, and their rates were 60.3%, 31.5%, 6.8% and 1.4%, respectively. In addition, the responses have been gleaned from a variety of organisation categories, such as contractors (37%), consultants (39.7%) and owners (23.3%); and the respondents’ positions were, variously, project manager (13.7%), architect (16.4%), engineer (27.4), quantity surveyor (12.3%) and owner (13.2%). This ensures that the obtained responses represent diverse views from the key construction participants and that it implies a fair distribution of the questionnaire. Particularly, large groups of the respondents, accounting for 39.7% and 58.9% of the survey size, mostly performed residential construction and medium sized projects, respectively. Subsequently, the respondents revealed that from a total of 12 project procurement systems, only four – namely ODF (20.5%), general contractors (32.9%), DB (16.4%) and CM (17.8%) – were identified as forming part of the most popular method. This implies that these four systems are mostly known in Rwanda because they are probably more patronised than others.

From Table 4 that assessed the usage levels of project procurement systems in Rwandan building construction projects, it is ascertained that the general contractor system ranked highest, with a mean score of 4.36. This was followed by the ODF, DB and CM systems, with the MS of 4.03, 3.22 and 1.49, respectively. This means that DBB is the most popular and utilised method, while CM is the least utilised system. This is probably due to the fact that, among the four popular systems for project procurement prevalent in Rwanda, a low awareness level prevails concerning DBB, as can be confirmed from Table 3.

Tables 5–8 show MS and ranks for the influence levels of four selected project procurement systems marked by a higher awareness level than others, namely, ODF, general contractor, DB and CM, on the key project performance criteria such as time, cost, quality and scope and their 36 indicators. Each method was individually assessed under the four performance criteria together with their 36 indicators. The MS were used to measure the influence levels on all four performance criteria and their 36 indicators, and according to the methodology formulated for the analysis, it would be inferred that a system with the highest mean score on a particular criterion or indicator implies that it performs better with respect to that criterion or indicator and vice versa.