@article{scholars14611,
          volume = {13},
            note = {cited By 34},
          number = {15},
             doi = {10.3390/su13158379},
           title = {The assessment of big data adoption readiness with a technology{\^a}??organization{\^a}??environment framework: A perspective towards healthcare employees},
            year = {2021},
       publisher = {MDPI AG},
         journal = {Sustainability (Switzerland)},
        abstract = {Big data is rapidly being seen as a new frontier for improving organizational performance. However, it is still in its early phases of implementation in developing countries{\^a}?? healthcare organizations. As data-driven insights become critical competitive advantages, it is critical to ascertain which elements influence an organization{\^a}??s decision to adopt big data. The aim of this study is to propose and empirically test a theoretical framework based on technology{\^a}??organization{\^a}??environment (TOE) factors to identify the level of readiness of big data adoption in developing countries{\^a}?? healthcare organizations. The framework empirically tested 302 Malaysian healthcare employees. The structural equation modeling was used to analyze the collected data. The results of the study demonstrated that technology, organization, and environment factors can significantly contribute towards big data adoption in healthcare organizations. However, the complexity of technology factors has shown less support for the notion. For technology practitioners, this study showed how to enhance big data adoption in healthcare organizations through TOE factors. {\^A}{\copyright} 2021 by the authors.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112349294&doi=10.3390\%2fsu13158379&partnerID=40&md5=40903a936c09da730e5b6558df4d6e98},
        keywords = {assessment method; complexity; data set; detection method; developing world; health care; spatiotemporal analysis, Malaysia},
          author = {Ghaleb, E. A. A. and Dominic, P. D. D. and Fati, S. M. and Muneer, A. and Ali, R. F.},
            issn = {20711050}
}