Construction projects are characterised by complexity in the technical, organisational and environmental sphere. The organisational complexity of such projects makes it necessary to manage relationships between actors who fulfil various functions. Formal organisational structures that have been developed for this purpose do not always reflect the actual relationships between construction project participants. In literature, scholars more and more often point to the need to identify and monitor such informal relationships and attempt to manage them in order to effectively carry out projects. Structural analysis of so-called self-organising networks of relationships between project participants is carried out on the basis of established structural measures by performing Social Network Analysis (SNA). In a situation when inappropriate communication between project participants relative to management staff expectations is detected, interventions meant to improve communication in such networks are possible. The goal of the article is proposing an optimisation-oriented approach to planning such interventions while taking various constraints, such as communication costs, into consideration. As a part of this optimisation, the authors proposed a method from the heuristic methods group. This solution will support decision-making in terms of intervening within an informal relationship structure. The method was presented on the example of an actual construction project involving the construction of a complex of housing buildings. the self-organising network structure was defined on the basis of a survey carried out among the project's participants and concerned communication between them over a four-week period. As a result of the structural network analysis, abnormalities in communication between project participants were detected. The optimisation method developed by the authors pointed to possibilities of improving communication effectiveness within this network. The effects of the analysis confirmed the application potential of the method that was presented.
Animal behaviour and its underlying causal factors are investigated by numerous behavioural sciences. Ethology, one of the most important classical behavioural sciences, is concerned with the description and quantification of behaviour and the analysis of a wide spectre of its causal factors. Ethology also lays stress on the importance of comparative behavioural research and field research. Specific behaviour paterns were considered by classical ethology as elements of hierarchically organised behavioural systems focused on specific functions. The notion of instinct was, however, far from unequivocal and is no more frequently used in behavioural sciences. We also know that information flow between the levels of organization existing in the nervous system and in living systems in general is multidirectional. The assumption that processes running on higher levels of organization can and should be explained solely in terms of processes running on lower levels becomes thus largely groundless. In behavioural sciences reductionism can manifest itself also as the so called law of parsimony adopted during explanations of observed phenomena (Occam’s razor, Lloyd Morgan’s canon). Since the introduction of Karl Popper’s falisifiability criterion to the methodology of scientific research, reductionistic explanations of observed phenomena are, however, less frequently proposed in behavioural sciences. Instead, an approach currently used involves experimental testing of sets of hypotheses proposing alternative explanations of the observed phenomena, not necessarily the simplest ones. Classical ethology was the so called objectivist science of behaviour: its adherents did not deny the existence of subjective phenomena in animals, however, explanations of mechanisms of investigated phenomena in terms of underlying subjective processes were not considered to be sufficient. Presently we may put forward increasingly daring hypotheses concerning subjective experiences of animals thanks to the development of advanced techniques of neuroimaging such as the functional magnetic resonance imaging (fMRI). Behavioural sciences are constantly progressing and their methods become increasingly sophisticated. We can thus hope that philosophy and behavioural sciences will continue during a long time yet to contribute jointly to achieve new insights enriching our knowledge on factors influencing animal and human behaviour.