This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International licence Newcastle University ePrints-eprint.ncl.ac.uk Wang Y, Kung K, Byrd TA. Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations.

No 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.

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.

To date, the health care industry has paid little attention to the potential benefits to be gained from big data. While most pioneering big data studies have adopted technological perspectives, a better understanding of the strategic implications of big data is urgently needed. To address this lack, this study examines the development, architecture and component functionalities of big data, and identifies its capabilities, including traceability, the analysis of unstructured data and patterns of care, and its predictive capacity to support healthcare managers seeking to formulate more effective big-data-based strategies. Our findings will help healthcare organizations respond strategically to the challenges they face in today's highly competitive healthcare market.