Perceptions of status and TMO workgroup cooperation: implications for project governance

Achieving and sustaining the cooperation of individuals with their temporary multi-organization (TMO) workgroups is, arguably, one of the most enduring challenges facing the construction sector. A mediational model connecting pride and self-respect to each of four dimensions of cooperative behaviour-in-role, compliance, extra-role, and deference-is tested in a survey sample of 140 construction professionals in Hong Kong. Bootstrap tests of the indirect effect of pride on cooperative behaviour suggest that self-respect fully mediates the influence of pride on in-role behaviour and compliance behaviour, and partially mediates the influence of pride on extra-role behaviour. The results also suggest that pride has no effect on deference behaviour. While needing corroboration by future research, the findings suggest that viable strategies designed to foster pride and self-respect could engender and sustain cooperation in construction TMO workgroups, and support ongoing efforts to reform construction. The bootstrapping procedures for testing intervening variable models are elaborated in the hope that this will encourage more process analysis research in construction. © 2012 Copyright Taylor and Francis Group, LLC

2009. Semantic Rules for Context-Aware Geographical Information Retrieval

Abstract. Geographical information retrieval (GIR) can benefit from context information to adapt the results to a user’s current situation and personal preferences. In this respect, semantics-based GIR is especially challenging because context information – such as collected from sensors – is often provided through numeric values, which need to be mapped to ontological representations based on nominal symbols. The Web Ontology Language (OWL) lacks mathematical processing capabilities that require free variables, so that even basic comparisons and distance calculations are not possible. Therefore, the context information cannot be interpreted with respect to the task and the current user’s preferences. In this paper, we introduce an approach based on semantic rules that adds these processing capabilities to OWL ontologies. The task of recommending personalized surf spots based on user location and preferences serves as a case study to evaluate the capabilities of semantic rules for context-aware geographical information retrieval. We demonstrate how the Semantic Web Rule Language (SWRL) can be utilized to model user preferences and how execution of the rules successfully retrieves surf spots that match these preferences. While SWRL itself enables free variables, mathematical functions are added via built-ins – external libraries that are dynamically loaded during rule execution. Utilizing the same mechanism, we demonstrate how SWRL built-ins can query the Semantic Sensor Web to enable the consideration of real-time measurements and thus make geographical information retrieval truly context-aware.