Moderating Effects of Gender and Resistance to Change on the Adoption of Big Data Analytics in Healthcare

Abstract

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.

Teachers’ technological competence and success in online teaching during the COVID-19 crisis: the moderating role of resistance to change

“…This finding is consistent with previous studies, which suggest that readiness to accept change is crucial to individuals' success in adapting to new ways of working or behaving (e.g. Shahbaz et al, 2020).…”

“…Likewise, resistance to change was found to moderate the association between different cognitive and behavioral variables and the adoption of new technology (Huang, 2015). For example, Shahbaz et al (2020) studied employees' intentions to use big data analytics in health-care organizations and found that the higher their resistance to change, the weaker the association was between intention to adopt change and the adoption of actual change. Therefore, although previous work has addressed the relation between resistance to change and the adoption of new technology, no research to date has examined the effect of resistance to change on success in online teaching.…”

Investigating the Impact of Big Data Analytics on Perceived Sales Performance: The Mediating Role of Customer Relationship Management Capabilities

“…In the present era of big data, input data from all available sources, such as social media (e.g., social, electronic, and mobile commerce websites), sales forums, competitor data, and other stakeholder data, are mandatory for ensuring the efficient output of analyzed information [21][22][23][24]. In the management of organizational sales performance, BDA can store and analyze big data of massive amounts, variety, and velocity from all possible resources, including social commerce sites, electronic commerce sites, mobile commerce sites, competitors, substitute products or service organizations, and decision-making [25][26][27][28]. erefore, BDA may solve the existing sales force problems, especially in pharmaceutical organizations.…”

A mini-review of machine learning in big data analytics: Applications, challenges, and prospects

“…(5) Even though BDA has seen rapid growth in recent years (see Fig. 6), the study by Shahbaz et al [129] revealed no gender balance in the adaptation of BDA in most industries. That is, males, as compared with females, are dominant towards the positive intent to use BDA.…”