The paper addresses the improvement of innovation project (IP) risk identification by applying the RBS (Risk Breakdown Structure) method, and represents a follow-up analysis of the subject (a case of IP before and after applying the method). The activities of risk identification are an initial phase in most of risk management processes and classifications. High-level risk-taking is one of the key characteristics of IPs, due to the fact that this type of projects is related to implementation of new ideas. An example illustrates the combination of RBS/WBS for evaluating the risk concentration, called Risk Breakdown Matrix. This research has proven that implementation of the presented approach in the context of the Serbian market can improve efficiency of all phases of the project, especially those related to planning phase.

The purpose of this paper is to introduce recent research on correlation between project managers’ emotional intelligence and their professional success. The implications of this research are important to both project managers who wish to improve their performance and success rate and organizations in their human resource policy. Theoreti- cal considerations discussed potential impact of emotional intelligence on project managers’ success through review on concept and dimensions of emotional intelligence, findings of numbered empirical studies and leadership theories. Complementing these theoretical considerations with research study showed significant correlation between project managers’ emotional intelligence and professional success. Research was conducted on representative sample consi- sted of 75 project managers from top 10 Serbian companies. Data collection instrument was questionnaire consisted of self-descriptive emotional intelligence test and data on respondent's position in organizational hierarchy and edu- cational level. The empirical research reveals that there is a very high positive correlation between emotional intelli- gence and professional success and these findings should have a number of implications for project managers’ pra- ctice. Firstly, project managers should be aware of the concept, their level and way of improving different dimensions of emotional intelligence. Further, the human resource management departments of project oriented organizations should consider concept of emotional intelligence when recruiting staff to the position of project managers but also when deciding on human resources development programs. In order to help good project managers to become excel- lent there is a need for further investigations on methods for development of emotional intelligence competencies

The main objective of this paper is to present the advantages of using Cost-Benefit analysis in energy efficiency projects implemented in public buildings, and to prove the hypothesis that Cost-Benefit analysis boosts the effectiveness and efficiency of the said type of projects. The paper offers theoretical and practical explanation of the implementation of Cost-Benefit analysis in the relevant area. Since energy efficiency projects in public buildings usually represent a part of a broader portfolio of similar projects and their implementation demands allocation of substantial financial resources, communities are often be interested in achieving maximal economic and non-economic benefits. This paper aims to demonstrate that Cost-Benefit analysis can represent an excellent contribution when attempting to select the projects for implementation within a broader portfolio of energy efficiency projects in public buildings. This hypothesis was demonstrated by putting a greater emphasis on non-economic benefits and the costs arising from implementation of the aforementioned types of projects. In addition, a practical test of this hypothesis was performed through the implementation of an energy efficiency portfolio in public buildings, worth several tens of millions of dollars - the Serbian Energy Efficiency Project. The paper concludes that the use of Cost-Benefit analysis can help us to effectively evaluate and manage projects of this type aimed at achieving maximum benefits for the community in question.

The authors discuss why the current conceptual base of project management research and practice continues to attract criticism since it does not adequately address the complexity that leads to software-project failure. To do so, the study explores systems thinking and artificial neural networks to shed light on complexity in software-project behavior using nonlinear functional relationships between critical success factors and project success to utilize their connectedness as an approach in order to create project-outcome prediction models. The artificial neural networks were used to create two project-outcome prediction models: one for a binary classification task to discriminate failed from successful projects using a multi-input-single-output configuration and one for a multi-task binary classification to discriminate success from failure in multiple project-success dimensions using a multi-input multi-output configuration. The results yielded high-performance values for a binary classification task, performed to predict overall project success, and slightly lower performance values for the multi-task binary classification, which was also performed to predict success in project-success dimensions. It was found that the nonlinear behavior of critical success factors may be used to create prediction models, by embedding equifinality and connectedness constructs that prove to be useful to understand projects as complex, multi-loop, and nonlinear systems. Further research is needed to investigate the causality between critical success factors in order to explore the possible propagation of critical success factors within a project system network and its implications on project success.