Presentation paper for the 2017 International Conference on Knowledge Management. This paper examines the knowledge management practices of the Dallas-Fort Worth (DFW) Schizophrenia Study Team, a group of interdisciplinary informatics researchers comprised of faculty, staff, and students from eight academic units at Texas Woman’s University.

Paper describes the constitutive mechanisms of Learning Governance (GovLearn) from an organizational perspective.

Presentation for the 2017 International Conference on Knowledge Management. This presentation describes interdisciplinary research by a team of informatics researchers representing five academic disciplines at Texas Woman's University.

This book chapter describes the efforts of University of North Texas Libraries to organize data relevant for assessing subject-based collections.

The ever-increasing market turbulence has turned today’s corporate landscape more competitive and complex. Particularly during the last two decades, the increased utilization of ICT systems and technologies globally transformed the services sector in terms of ease of business processes and improved client service delivery. However, in the current knowledge-based era, ICT-enabled systems and tools would only be meaningful if these are appropriately utilized by the knowledgeable and skilled workforce. However, leveraging these necessitates a knowledge-enabled work culture and recognizing that people are crucial to building a robust Intellectual Capital (IC) that is central to achieving long-term market competitiveness. IC comprising of intangible assets and knowledge resources is central to value creation for the firm as evident from the growth of the knowledge-based industries. Nevertheless, the true potential of IC for deriving value advantage for diverse organizational stakeholders has not been fully utilized. Hence, by conducting 12 face2face interviews with the senior executives within Australian Professional Service Firms (PSFs), this study offers renewed approach to IC valuation by introducing ‘Triple Value Bottom-line’ perspective in PSFs. The results highlight that the IC offers enormous potential towards deriving broader value outcomes for multiple organizational stakeholders.

Building predictive models for companies often relies on inference using historical data of companies in the same industry sector. However, companies are similar across a variety of dimensions that should be leveraged in relevant prediction problems. This is particularly true for large, complex organizations which may not be well defined by a single industry and have no clear peers. To enable prediction using company information across a variety of dimensions, we create an embedding of company stocks, Stock2Vec, which can be easily added to any prediction model that applies to companies with associated stock prices. We describe the process of creating this rich vector representation from stock price fluctuations and characterize what the dimensions represent. We then conduct comprehensive experiments to evaluate this embedding in applied machine learning problems in various business contexts. Our experiment results demonstrate that the four features in the Stock2Vec embedding can readily augment existing cross-company models and enhance cross-company predictions.

This is the final program for the 2017 International Conference on Knowledge Management.

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. The conference was among the first post-pandemic face to face conferences, and the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency.