Knowledge Sharing within IT Projects

Even though today’s corporations recognize that they need to understand modern project management techniques (Schwalbe, 2002, p2), many researchers continue to provide evidence of poor IT project success. With Kotnour, (2000) finding that project performance is positively associated with project knowledge, a better understanding of how to effectively manage knowledge in IT projects should have considerable practical significance for increasing the chances of project success. Using a combined qualitative/quantitative method of data collection in multiple case studies spanning four continents, and comprising a variety of organizational types, the focus of this current research centered on the question of why individuals working within IT project teams might be motivated towards, or inhibited from, sharing their knowledge and experience in their activities, procedures, and processes. The research concluded with the development of a new theoretical model of knowledge sharing behavior, ‘The Alignment Model of Motivational Focus’. This model suggests that an individual’s propensity to share knowledge and experience is a function of perceived personal benefits and costs associated with the activity, balanced against the individual’s alignment to a group of ‘institutional’ factors. These factors are identified as alignments to the project team, to the organization, and dependent on the circumstances, to either the professional discipline or community of practice, to which the individual belongs.

Identifying the knowledge management structures in enterprise systems projects

Enterprise System (ES) implementation and management are knowledge intensive tasks that inevitably draw upon the experience of a wide range of people with diverse knowledge capabilities. Knowledge Management (KM) has been identified as a critical success factor in ES projects. Despite the recognized importance of managing knowledge for ES benefits realization, systematic attempts to conceptualize KM-structures have been few. Where the adequacy of KM-structures is assessed, the process and measures are typically idiosyncratic and lack credibility. Using the ‘KM-process’, itself based in sociology of knowledge, this paper conceptualizes four main constructs to measure the adequacy of KM-structures. The SEM model is tested using 310 responses gathered from 27 ES installations that had implemented SAP R/3. The findings reveal six constructs for KM-structure. Furthermore, the paper demonstrates the application of KM-structures in the context of ES using the Adaptive Structuration Theory. The results demonstrate that having adequate KM-structures in place, while necessary, is not sufficient. These rules and resources must be appropriated to have greater positive influence on the Enterprise System. Furthermore, the study provides empirical support for knowledge-based theory by illustrating the importance of knowledge use/re-use (vs. knowledge creation) as the most important driver in the process of KM.

Knowledge management for ERP success

The business value of Enterprise Resource Planning (ERP) systems and in general large software implementations has been extensively debated in both popular press and academic literature for over three decades. Despite the positive motives for adoption, various organizations have reported negative impacts from these large investments. This ‘disconnect’ between large IS investments and firms’ organizational performance may be attributable to the economic transition from an era of competitive advantage based on information to one that is based on Knowledge. This paper discusses the initial findings of a two-phased study that focuses on empirically assessing the impact of knowledge management on the success of Enterprise Resource Planning systems. The research study uses information gathered from twenty-seven public sector organizations in Queensland, Australia. Validation of the a priori model constructs through factor analysis identified two dimensions of knowledge management. Further analysis assessed the comparative differences in perceptions of knowledge management in ERP, across four employment cohorts.