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The AIC Research Group at the University of Salford has been involved in a government‐funded project that has resulted in the development of an integrated multi‐user distributed construction project database through the implementation of next‐generation Internet technology together with Product Data Technology ‐ WISPER. The objective of the project was to develop a working system capable of demonstrating the future direction of information integration with the project partners' businesses. This paper presents the development of the specification application that aims to demonstrate the potential for such technologies to enhance the specification process, enabling design elements to be specified directly from a building product database Web site.

In features based design systems that are underpinned by solid models, buildings are designed by applying features to the design domain. A feature may be translated and/or rotated in order to position it in the desired place. Contradiction between the applied features and resulting features may occur due to the features interaction, wrong positioning, or inadequate parameters supplied by the user during the product definition. Moreover, the application of other features may cause some features to degenerate to further features. Therefore, verification of the resulting features must be performed against the applied features to establish whether the resulting features conform to the underlying geometry. Current feature‐based design systems employ a mechanism of tagging feature labels onto geometry. This approach does not guarantee the geometric correctness of the resultant feature and knowledge of the topology of the resulting feature and a geometric analysis is necessary to correctly identify the validity of the resultant feature. The research reported in this paper proposes an alternative approach which uses a product model that permits all geometrical and technological information associated with the design and construction stages to be represented. Individual features can be extracted from the product model and analysed to determine their accessibility. Methods which use the product description and other construction data to determine feature validity, accessibility and machinability are used. Each volumetric feature corresponds to a solid that can be added by one or more construction process or removed by one or more machining operations; as a consequence of applying volumetric features, surface features are generated. These surface features provide enough information to enable the accessibility, and machinability of the individual features to be determined and establish the possible routes in which the feature can be accessed if any.

This paper discusses an approach for constructing product models in terms of features. In particular, the work focused on features verification and their accessibility using the solid model representation of the design. The research was motivated by the inadequacy of the current geometric modellers to perform verification and accessibility analyses, resulting in possible contradictions between the intended and the resultant features. Consequently, the wrong data are passed to the applications that use the data. The paper describes an alternative approach that considers the geometry, topology of the design and other construction and engineering information of the product rather than the simplistic approach, which is implemented in many geometric modellers; and is based on tagging feature labels on geometry. Individual features are extracted from the product model, where all the information about the product is held, for analyses. Each volumetric feature corresponds to a solid. As a consequence of applying volumetric features to the design model, surface features are generated. These surface features provide enough information to enable the validity and accessibility of the individual features to be determined and establish the possible routes in which the feature can be accessed, if any. The algorithms that are used to determine the validity and accessibility of features will be discussed.

The purpose of this paper is to investigate the effect of motivation to share, interpersonal trust, job involvement, job satisfaction and continuance commitment on knowledge sharing behavior of academics in higher education institutes.

Data were conveniently collected through a self-administered questionnaire from 369 academics working in six public sector universities of Pakistan. Correlation and incremental regression analyses were run to draw the results.

Results reveal that 24 percent of the variation in KSB is due to the changes in all the independent variables – intrinsic motivation, extrinsic motivation, interpersonal trust, job involvement, job satisfaction and continuance commitment. The study also identifies job involvement and continuance commitment as strong determinants of knowledge sharing behavior among academics.

To facilitate knowledge sharing behavior among academics, management of the universities must provide the ways for improving the levels of job involvement, continuance commitment and job satisfaction.

This is the first study that investigated the combined effect of intrinsic motivation, extrinsic motivation to share, interpersonal trust, job involvement, job satisfaction and continuance commitment on knowledge sharing behavior of teachers in public sector universities in Pakistan.

This paper aims to explore the relationship between knowledge sharing factors, emotional intelligence and team conflict on the team performance during the inter-institutionalized collaboration work process.

This study was conducted in South Sulawesi and Central Sulawesi Province’s hospitals. The study lasted for six months in 2017. The sampling was done by using cluster method and stratified random sampling, which was based on Hospital Type, level of Health Officers. These characteristics were considered to have represented quite heterogeneous information about the characteristics of health workers. Data analysis approach used in this study was partial least square (PLS) using WarpPLS software.

Based on the results of data analysis, it can be concluded that there is a significant direct influence between emotional intelligence to knowledge management, emotional intelligence to team conflict, and emotional intelligence to team performance.

Some previous research studies that have been done are by Hasanyl et al. (2015), Othman (2010), Sathitsemakul (2005), Nóra. Obermayer-Kovács (2014), Troth (2009), Leung (2010) and Luca and Tarricone (2001). The novelty of this research is on the effort to see the mediation of knowledge sharing, team conflict and structure mechanism to other variables developed in the research model.