Communication Patterns in Construction at Construction Manager Level

The procurement process of construction projects has been affected by developments in the field of Information Technology, as well as by the need to cope with growing technological challenges stemming from the integration of multiple building systems into tall and complex buildings. Furthermore, since the procurement phases are undertaken simultaneously, project complexity is increased, and increased integration among them is therefore required. These constraints have made the management of complex construction projects less of an architectural and engineering issue and more of a managerial one. In turn, this has led to an increasing use of the “construction management” concept in the procurement process. This study focused on communications in construction management procurement of building and residential projects in Israel. Communications between the construction manager and the design team were found to be vital in ensuring adherence to project objectives. Communication means were classified as “formal”—written technical information, and as “informal”—verbal communications. Construction managers in Israel still use informal communications in 50% of their interactions with their project counterparts. The study concludes that design capabilities should be one of the essential qualifications required of a construction management firm. In addition to the more traditional responsibilities, such as planning, scheduling, and coordination, the scope of the construction manager’s professional duties should emphasize the aspect of quality management.     

Competency-Based Model for Predicting Construction Project Managers’ Performance

Using behavioral competencies to influence human resource management decisions is gaining popularity in business organizations. This study identifies the core competencies associated with the construction management role and, further, develops a predictive model to inform human resource selection and development decisions within large construction organizations. A range of construction managers took part in behavioral event interviews where staff were asked to recount critical management incidents, decisions, and actions from which their key competencies could be identified. By delineating the sample according to their levels of performance measured against a range of role-specific performance criteria, the competencies defining superior management performance could be determined. These were then used to construct a logistic regression model from which a project manager’s performance can be predicated. The validated results reveal that “self-control” and “team leadership” are the most predictive behaviors of effective project management performance within the framework of the model. The paper explores the potential role and application of the framework to underpin human resource management decision making with regards to recruitment, performance management, succession planning, and resource allocation.     

Neurofuzzy Genetic System for Selection of Construction Project Managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions.     

Computer-mediated communication: problems and potentials of argumentation support systems

Argumentation support systems have both advantages and disadvantages. For the individual, there is an increased power to express herself and to gain recognition and reward for the extra effort and frankness required, but at the cost of slowing down work, making the user constantly explain herself, and putting her statements at risk of being taken out of context. For the organisation, there is a gain in increased information sharing — the bane of current computer-mediated communication (CMC) systems — as the user is motivated to present relevant and convincing evidence to back up her statements, but at the cost of undermining ‘traditional' organisational structures and hierarchies.