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Moderating Effects of Gender and Resistance to Change on the Adoption of Big Data Analytics in Healthcare
المؤلفون المشاركون
Shahbaz, Muhammad
Gao, Changyuan
Zhai, Lili
Shahzad, Fakhar
Arshad, Muhammad Rizwan
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-01-23
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
The big data analytics (BDA) has dragged tremendous attention in healthcare organizations.
Healthcare organizations are investing substantial money and time in big data analytics and want to adopt it to get potential benefits.
Thus, this study proposes a BDA adoption model in healthcare organizations to explore the critical factors that can influence its adoption process.
The study extends the technology acceptance model (TAM) with the self-efficacy as an external factor and also includes gender and resistance to change (RTC) as moderators to strengthen the research model.
The proposed research model has been tested on 283 valid responses which were collected through a structured survey, by applying structural equation modeling.
Our results portray that self-efficacy is a strong predictor of intention to use BDA along with other TAM factors.
Moreover, it is confirmed by the results that RTC dampens the positive relationship between intention to use and actual use of BDA in healthcare organizations.
The outcomes revealed that male employees as compared to female employees are dominant towards the positive intention to use BDA.
Furthermore, females create more RTC than males while adopting BDA in healthcare organizations.
Theoretical and practical implications, limitations, and future research directions also underlined in this study.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Shahbaz, Muhammad& Gao, Changyuan& Zhai, Lili& Shahzad, Fakhar& Arshad, Muhammad Rizwan. 2020. Moderating Effects of Gender and Resistance to Change on the Adoption of Big Data Analytics in Healthcare. Complexity،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1140881
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Shahbaz, Muhammad…[et al.]. Moderating Effects of Gender and Resistance to Change on the Adoption of Big Data Analytics in Healthcare. Complexity No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1140881
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Shahbaz, Muhammad& Gao, Changyuan& Zhai, Lili& Shahzad, Fakhar& Arshad, Muhammad Rizwan. Moderating Effects of Gender and Resistance to Change on the Adoption of Big Data Analytics in Healthcare. Complexity. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1140881
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1140881
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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