رابطه بین سرمایه انسانی و مدت زمان عملکرد در مدیریت پروژه: تجزیه و تحلیل مسیر

This paper uses a causal path model to measure the relationship between project management human capital (PMHC) and project time performance. Human capital is an established branch of economic theory concerned with the value embodied in the firm’s human resources. Project managers’ knowledge and experience are considered important in determining project outcomes and these facets are assessed using a human capital framework. The path analysis confirms the central research hypothesis that performance will improve with increased investment in human capital. The results are significant because they confirm that the education and training of project managers is important in influencing the time delivery of construction projects.

What makes project delivery successful is a topic of much academic debate. It is generally agreed that to be considered successful, a project must be fit for purpose and it must have achieved its delivery targets. Though project management (PM) literature often considers wider objectives [1] and [2], the central PM delivery targets remain time, cost and quality. In view of this, the PM discipline has three key responsibilities. First, to ensure that the project mission is appropriately defined [2]. Second, to quantify appropriate targets for the mission. Third, to organise and mobilise resources to accomplish the specified mission, within the quantified targets. PM has a poor track record considering these responsibilities [1], [3] and [4]. Adams and Brown [4] concluded that PM failed to deliver added value. The recent inquiry surrounding the Scottish Parliament project adds currency to this issue [5]. Nevertheless, we still expect that PM should deliver projects successfully. The tools and the body of knowledge that support PM are extensive. Moreover, PM has proved itself in industries other than construction (for example, the Boeing 777 project in the aviation industry [6]). This suggests that PM can be successful and that the problem in construction may be one of implementation. There are many issues in implementation; however, of central importance is capability. Capability can be viewed as a function of education and experience. If these are deficient, there is a high probability that a project mission will be inappropriately specified from the outset, with the result that time, cost and quality targets will be compromised from the beginning. If this is the case, it is highly improbable that the resource base will be organised and mobilised to deliver time, cost and quality targets successfully. This paper examines capability, measured in human capital (HC) terms, and it evaluates the relative importance of HC as a causal factor influencing time performance. The paper is structured as follows. First we address the issue of capability and HC in a PM context and we develop a theoretical framework for evaluation. We operationalise this framework using a path model to interrogate a dataset drawn from the UK and the Saudi Arabian construction industries. The reasons for selecting the UK and Saudi Industries for the sample are explained and the data is subsequently presented and analysed and the findings are discussed.

The analysis undertaken in this paper verifies the main research hypothesis presented. Relationships between HC and performance have been verified in other industries and this research confirms the existence of a similar positive relationship in the case of PM and project performance. The results presented here suggest that investment in PMHC by way of education and specific PM experience will produce a return in terms of improved performance. The results suggest that experience of the construction industry without specific PM education and experience will reduce the initial potential for successful performance and conversely that individuals educated and trained specifically in the subject of PM will deliver better performance. However, there are some important limitations in this work and the findings presented. First, we have considered performance only in terms of time. As we acknowledge, time is one of three interlinked project performance criteria. The other two, cost and quality, are not assessed here. Because time, cost and quality are interlinked, some inference may be drawn insofar as we may expect better time performance to benefit performance in the other areas. However, this is dangerous because it has previously been demonstrated that although PM was associated with a positive influence on time performance, it was simultaneously associated with a negative influence on quality and no influence on cost [4]. In other words, time targets can be delivered at the expense of cost targets and quality targets. It is possible that the very strong relationship between PMHC and time performance identified in this study, may be less meaningful if cost and quality data were also modelled. For this reason, future work will examine the relationship between PMHC and cost and quality performance. Second, the acquired dataset is small in statistical terms. Though we believe the quality of the data acquired to be suitable for the research, the small sample size is an area of weakness and this should be remembered when interpreting the results. Third, there are some measurement limitations that need to be considered, most specifically in connection with the assessment of PMHC. As explained we believe that project manager’s can be categorised into different HC profiles based upon the career path followed. This has been used in the assessment of PMHC and we consider its use legitimate, however, there is an alternative possible explanation for the strong positive relationship between PMHC and TE that has been identified. This alternative explanation arises because of the way PMHC was measured. This relates to the concept of ‘leverage’. Leverage represents the beneficial effects that accrue to a trainee by working with senior professionals within their chosen discipline. As mentioned earlier, individuals learn by observing their peers. We must acknowledge that projects are not managed by individuals, but by teams. It is likely that profile D project managers receive better PM support (leverage) from their firms than will the profile A project manager’s. This is simply because profile D project managers are more likely to be employed by large PM practices than profiles A–C profile project manager’s who are more likely to be employed by multidisciplinary or surveying practices or even self-employed. What this means is the model may in fact be measuring the human capital embodied in the PM (or other) firm than the individual. The results remain encouraging for the project management discipline, however, it is the case that the PMHC measurement system may be disadvantaging profile A–C project managers who do not receive the same level of support from their employers as do profile D project manager’s. These limitations should be remembered in interpreting the results. It is recommended that future research in this area investigates relationships between PMHC and cost and quality performance and that the effect of ‘leverage’ be assessed. Therefore, the findings of this research are presented as preliminary rather than conclusive. Determining a conclusive assessment of PMHC upon project performance remains a subject for future research.