An integrated big data analytics-enabled transformation model: Application to health care

By Yichuan Wang, LeeAnn Kung, William Yu Chjung Wang, Casey G. Cegielski. Information Manager (The), 2018

407 citations recorded by the source corpus.

Abstract 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. This model was then tested in healthcare setting. By analyzing big data implementation cases, we sought to understand how big data analytics capabilities transform organizational practices, thereby generating potential benefits. In addition to conceptually defining four big data analytics capabilities, the model offers a strategic view of big data analytics. Three significant path-to-value chains were identified for healthcare organizations by applying the model, which provides practical insights for managers.

Subfields: Management Information Systems, Management Science and Operations Research, Medical Laboratory Technology

View Paper: https://www.semanticscholar.org/paper/1b85485dab9ead5e746e07b7eade4d2004bd856a

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In Management Information Systems

In Management Science and Operations Research

Citations in the corpus

The use of Big Data Analytics in healthcare (2022, background): “Big Data Analytics in healthcare can be divided into [33, 73, 74]:”
Big data analytics adoption: Determinants and performances among small to medium-sized enterprises (2020, background): “Although there are many studies on BDA adoption among large firms (Wang & Hajli, 2017; Wang et al., 2018), there is a lack of empirical study on SMEs in this context.”
Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities (2020, background): “Applications of BDACs toward renewal of technological capabilities can be found in a range of industries including healthcare [94,95], manufacturing [96,97], bank and financial institutions [98], energy and communication infrastructure providers [99], as well as in the oil and gas sector amongst oth”