Pre‐tender estimates may be inaccurate because they are often prepared within a limited time, when the project scope is not yet fully described. Progressing with an underestimated project can lead to project failure. On the other hand, overestimation of a project at the pre‐tender stage can lead to a viable project being dropped or re‐tendered when there is no bid close enough to permit project award (most especially in the public sector). Using Australia data, Aibinu and Pasco examined the influence of project characteristics on the accuracy of pre‐tender building cost estimates. They also investigated whether or not the accuracy of estimates has improved over time and what firms are doing to improve the accuracy of cost estimates in practice. They have discovered that estimates are more often overestimated than underestimated. Surprisingly, the accuracy of estimates is influenced by project size, such that cost estimates for smaller projects are more biased than cost estimates for larger projects, but estimates of smaller projects are more consistent than estimates for larger projects. The authors also discovered that project estimate bias and consistency today are in the same order of magnitude as they were over the last 10 years. Since financial management, cost engineering processes require knowledge that has developed over time, these findings suggest that that firms do not monitor the performance of their estimates, and that there appears not to be any increase of estimating skill, knowledge and experience over time. The majority of the firms studied often use the estimate of past projects as a basis for estimating new projects. However, there is a low uptake of probability and simulation approaches to cost estimation in the industry. These findings have significant implications for firms. The findings will help quantity surveyors, estimators and cost engineers to be more aware of how project cost estimating has performed over time and where special attention is needed during cost estimation, as well as what practices would be most effective for improving the accuracy of their estimates.
Liu and Fellows review organizational citizenship behaviour (OCB) from a social exchange perspective. Certain organizational cultures support individualistic behaviours while others emphasize the benefits to the collective whole. They examine collectivistic orientation as the cultural dimension of individualism‐collectivism for quantity surveyors in Hong Kong. Generally, more individualistic quantity surveyors are less likely to exhibit organizational citizenship behaviours. The study shows that the correlation of collectivistic norms and OCB is highly significant. People's behaviours are underpinned by norms and expressed through their values and beliefs. The authors have found that values and beliefs are manifested in sportsmanship; and collectivistic norms positively affect civic virtue, sportsmanship, courtesy and conscientiousness. They suggest that organizations may seek to foster collectivistic norms which support OCB through reward systems. Thus, individuals who observe, learn and imitate OCB from leaders, based on the norm of reciprocity, can replicate these behaviours in work group collaborations. Hence, work culture promoting a norm of reciprocity may have a significant influence on level of OCB which will enhance work group performance.
The raison d'etre of bidding models in general, and unbalanced bidding models in particular, is contractors' bid optimization via the maximization of a project's potential profits. Profit maximization is achieved using techniques of applying differentiated mark‐ups to all items of work associated with the project. Cattell, Bowen and Kaka argue that incorporating consideration of a project's item costs is an unnecessary complication, and that unbalanced bidding models can be significantly simplified by maximizing a project's revenue rather than its profit. They propose a simplified unbalanced bidding model for optimizing contractors' bids in competetive tendering environments. The new model, incorporating all three standard effects of item price loading, namely, front‐end loading, individual‐rate loading and back‐end loading, gives effect to determining the optimum pricing for a project's component items.
Resource constraints, including financial constraints, have an enormous impact on the sequencing of tasks, on overall project duration and on project profitability. When bidding for a construction contract, it is important that the contractor considers not only the amount of the bid itself but also the financial constraints, the cashflow and the profit allocation to individual bid items and project activities, as well as the financial risks involved and their impact on the project. A planner should therefore consider not only financial assignments that maximize activity and project profits (classical approach) but also financial assignments that minimize the project's tendency to fall into disarray (entropy‐based approach). Christodoulou presents a novel method for unbalancing bids and optimizing the allocation of overall project profits to individual activities by considering the financial parameters of a project (bid mark‐up and projected cashflow), in conjunction with lowering the exposure to possible financial disorder in the project. The method utilizes the general concept of entropy and a variant of it (termed as “Monetary Entropy”) as measures of a project's perceived level of disorder, in order to distribute the total bid mark‐up to the project activities and minimize this disorder. The entropy method should be of interest to both contractors and project planners, as an alternative method to the traditional net present value approach.
Managing change situations in construction projects can be viewed as a knowledge‐creation activity rather than an information‐processing activity. Senaratne and Sexton explore this knowledge creation process during managing change events. In their study, they use Nonaka and Takeuchi's knowledge creation model as the basis where the key is in externalizing tacit knowledge into explicit knowledge. However, by identifying the process‐based nature of construction, Senaratne and Sexton argue that, in a construction setting, knowledge mainly transfers from socialization to internalization stages and does not necessarily go through a codification stage. They have established this point by conducting two case studies in the UK construction industry. Towards the latter sections in their paper, they offer a new theoretical model that better represents the knowledge creation process that takes place through change events in a construction project setting. They further offer key steps towards a knowledge‐based project change process. In that, Senaratne and Sexton conclude that construction project teams need to balance between “appropriate codification” and “enhanced personalization” strategies in order to successfully resolve and learn through change events.
Highway agencies have long rated construction quality through questionnaire forms completed by project personnel. Most of these questions receive answers that are qualified in nature. Minchin, Hammons and Ahn develop an index for rating the quality of, first a construction project, and then a body of work by a contractor. The model used to deliver the Construction Quality Index is the first ever devised that rates the quality of materials and workmanship on a highway construction project using only quantified numbers, i.e. test results, to render a score, or index, of construction quality.