LeeAnn Kung

Bio: LeeAnn Kung is an academic researcher from Auburn University. The author has contributed to research in topics: Big data & Information technology. 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.

Leveraging Big Data Analytics to Improve Quality of Care in Healthcare Organizations: A Configurational Perspective

Abstract: Big data analytics (BDA) is beneficial for organizations, yet implementing BDA to leverage profitability is fundamental challenge confronting practitioners. Although prior research has explored the impact that BDA has on business growth, there is a lack of research that explains the full complexity of BDA implementations. Examination of how and under what conditions BDA achieves organizational performance from a holistic perspective is absent from the existing literature. Extending the theoretical perspective from the traditional views (e.g. resource-based theory) to configuration theory, the authors have developed a conceptual model of BDA success that aims to investigate how BDA capabilities interact with complementary organizational resources and organizational capabilities in multiple configuration solutions leading to higher quality of care in healthcare organizations. To test this model, the authors use fuzzy-set qualitative comparative analysis to analyse multi-source data acquired from a survey and databases maintained by the Centres for Medicare & Medicaid Services. 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.

An integrated environmental perspective on software as a service adoption in manufacturing and retail firms

Abstract: In this study, we examine the influence of a firm’s environmental factors on its intention to adopt software as a service (SaaS). We operationalized our assessment of a firm’s environmental pressures as mimetic, coercive and normative pressures and examined the moderating role of perceived technology complexity. Mimetic forces are pressures to copy or emulate other organizations’ activities, systems or structures. Coercive pressures are formal or informal pressures exerted on organizations by other organizations upon which they are dependent. Normative forces describe the effect of professional standards and the influence of professional communities on an organization. We empirically tested our research model using data from 289 valid survey responses. The results provide support for the assertion that there are both significant direct and interaction effects that influence a firm’s SaaS adoption intention. Most important was the significant interaction effects between mimetic pressure and perceived technology complexity. This suggests 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. The theoretical contributions of this study are (i) we integrated, tested and validated mature theories in today’s supply chain era with a new but rapidly diffusing technology, (ii) and we answered the call to include practical technology artifacts in information systems studies. From a practical perspective, through this work managers may develop a better understanding regarding environmental factors and whether or not they should consider these issues for their firm when formulating an intention to adopt SaaS.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Abstract: How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Abstract: What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

Fuzzy-Set Social Science

Abstract: In this innovative approach to the practice of social science, Charles Ragin explores the use of fuzzy sets to bridge the divide between quantitative and qualitative methods. Paradoxically, the fuzzy set is a powerful tool because it replaces an unwieldy, "fuzzy" instrument—the variable, which establishes only the positions of cases relative to each other, with a precise one—degree of membership in a well-defined set. Ragin argues that fuzzy sets allow a far richer dialogue between ideas and evidence in social research than previously possible. They let quantitative researchers abandon "homogenizing assumptions" about cases and causes, they extend diversity-oriented research strategies, and they provide a powerful connection between theory and data analysis. Most important, fuzzy sets can be carefully tailored to fit evolving theoretical concepts, sharpening quantitative tools with in-depth knowledge gained through qualitative, case-oriented inquiry. This book will revolutionize research methods not only in sociology, political science, and anthropology but in any field of inquiry dealing with complex patterns of causation.