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LeeAnn Kung

Researcher at Auburn University

Publications -  26
Citations -  1720

LeeAnn Kung is an academic researcher from Auburn University. The author has contributed to research in topics: Big data & Health care. The author has an hindex of 12, co-authored 26 publications receiving 1251 citations. Previous affiliations of LeeAnn Kung include Georgia Southern University & National Taiwan University.

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Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations

TL;DR: The historical development, architectural design and component functionalities of big data analytics, including analytical capability for patterns of care, unstructured data analytical capability, decision support capability, predictive capability and traceability are examined.
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An integrated big data analytics-enabled transformation model: Application to health care

TL;DR: A big data analytics-enabled transformation model based on practice-based view is developed, which reveals the causal relationships among big data Analytics capabilities, IT-enabled Transformation practices, benefit dimensions, and business values and provides practical insights for managers.
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Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations: A Configurational Perspective

TL;DR: The findings suggest that BDA, when given alone, is not sufficient in achieving the outcome, but is a synergy effect in which BDA capabilities and analytical personnel's skills together with organizational resources and capabilities as supportive role can improve average excess readmission rates and patient satisfaction in healthcare organizations.
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Influences of cross-functional collaboration and knowledge creation on technology commercialization: Evidence from high-tech industries

TL;DR: In this paper, a survey of 203 marketing and R&D managers and employees in Taiwanese high-tech companies indicated that cross-function collaboration reveals fresh opportunities for creating knowledge and commercializing technologies.
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An integrated environmental perspective on software as a service adoption in manufacturing and retail firms

TL;DR: The results provide support for the assertion that there are both significant direct and interaction effects that influence a firm’s SaaS adoption intention and suggest that the complex relationships proposed by institutional theory and diffusion of innovation help to describe how environmental pressures and perceived technology complexity combine to affect intention to adopt an emerging technology.