Big data analytics (BDA) is a course of action to examine large and complex data sets (i.e., big data) and select veiled information that can help organizations with efficient decision making [1
]. The volume of data related to healthcare organizations has grown dramatically in past years and is expected to increase in coming years due to the use of innovative technologies [2
]. Meanwhile, healthcare reimbursement methods are changing, and pay for performance is an emerging factor in the current healthcare environment. Recently, healthcare organizations have only focused on profit and have neglected to acquire the essential tools, infrastructure, and technologies for effective control of big data to ensure citizens’ health care [3
]. Big data incorporates features such as variety, velocity, and veracity. BDA techniques can be applied to the massive amount of prevailing patient-related medical information to analyze outcomes for improvement of the healthcare sector [5
]. Using BDA in the healthcare sector will help inform each physician of the medical histories of individuals and the population and enable appropriate decision-making regarding treatment of a particular patient [4
]. However, compared with the banking and retailing industries, healthcare organizations have lagged behind in the sophisticated use of BDA [7
]. The healthcare industry also strives to make internal developments in BDA implementation based on their quality and data performance, which provides timely feedback to interested parties [8
]. Therefore, describing the crucial factors that are required for understanding is important prior to creating a strategy for the acceptance of BDA in the healthcare industry, particularly in developing countries such as Pakistan, where the industry requires filling the gap of BDA adoption. Furthermore, data (i.e., big data) related to healthcare are generated at a very high pace [9
], and existing systems are unable to store and analyze the huge volume, velocity and variety of data [10
]. Therefore, a need exists for a system with the ability to store and analyze data with high volumes, velocities, and variety, all of which are provided by BDA systems [9
]. BDA is in the initial adoption phase, and many healthcare organizations want to implement BDA to obtain its benefits [11
]. Thus, a comprehensive adoption model related to BDA is needed to fulfill the existing gap in the literature and help healthcare organizations replace traditional systems incapable of competing with BDA systems.
Few studies have described the importance of BDA in healthcare [4
], although studies have investigated the technological aspects and required qualifications for big data in healthcare [14
]. Previous studies focused on technological and policy issues and not on adoption factors, such as security, trust, and fitness of technology for the tasks required to manage BDA in healthcare [13
]. According to Dishaw [19
], the technology acceptance model (TAM) and task-technology fit (TTF) provide better outputs than either TAM or TTF alone in the adoption of information technology systems. The prior literature tries to explain BDA adoption through perceptions of technology, such as perceived ease of use and perceived usefulness [20
]. However, emphasizing only the end user’s perception of technology may not be sufficient. According to Goodhue and Thompson [25
], the TTF model claims that the user will adopt the system when the characteristics of the technology fit the task requirements. Adoption will also occur when the user perceives the technology as useful, easy and advanced, but the technology may not be adopted if a mismatch exists with his required tasks and the technology cannot enhance his job performance [26
]. Therefore, not only should the user have the perception that the technology is useful and easy but also the technology characteristics should match with the required job tasks. Furthermore, the previous literature showed that perceived security of information [30
] and perceived trust [33
] were the biggest hurdles for users adopting innovative information systems. Security of information is the main reason for the slow pace of BDA adoption [36
]. Perceived trust is a major concern in the BDA acceptance procedure, and thus organizations should generate more trust in BDA adoption [38
]. Prior studies by Malaka, Shin, and Sivarajah [23
] also highlighted that perceived security and perceived trust were the biggest challenges and hurdles for BDA acceptance. Resistance to change (RTC) from employees is also a key factor that affects the adoption of different innovative systems, especially in developing countries [41
]. In previous literature concerning electronic health record system adoption, RTC from physicians was repeatedly reported as a key barrier for system adoption [44
], and RTC of employees mitigated the willingness of those who wanted to adopt the system [46
]. RTC also resists or slow down the pace of information system acceptance in the health sector [47
]. The study considers RTC a key factor in the adoption of BDA in the healthcare sector, which has never been discussed in this scenario.
Despite the fame of BDA, insufficient empirical research has investigated factors that can influence BDA adoption in healthcare [21
]. Empirical evidence from Pakistan’s healthcare organizations represents a big gap in the literature from both dimensions (i.e., knowledge about BDA and adoption of BDA) [50
]. This study summarizes real facts from Pakistan for the healthcare BDA literature. The gap between the potential pros of BDA and the slow and low geared adoption represents a superior opportunity for scholars to realize how BDA can be adopted in the healthcare industry. BDA is in the initial adoption phase in Pakistan, and the government should develop a clear policy and mechanism for the acceptance of BDA in government and the private sector [50
]. Therefore, to bridge this gap in the literature, the major focus of this paper is to provide comprehensive research insights into the adoption of BDA in healthcare. To fulfill said gap, the study has two main objectives. The first objective is to help government and private healthcare organizations determine the important factors that play key roles in the adoption of BDA in healthcare in developing countries, such as Pakistan. The second objective is to cover the on-hand gap in the literature concerning the influence of RTC from employees for BDA adoption. To achieve the above-mentioned objectives, this study incorporated both TAM and TTF models to explain BDA adoption in the healthcare sector from both viewpoints (the user’s perception of technology and the task-technology fitness) with the most important and substantial factors involved in the adoption of information systems (i.e., perceived security and perceived trust). The study also considers RTC as a moderator in the proposed model to address the most important hurdle for developing countries, such as Pakistan [33
]. The results justified the use of a composite of both TAM and TTF with security and trust as significant predictors of behavioral intentions (BIs) to adopt BDA, whereas RTC negatively moderated the relationship between BIs and actual use of BDA.
In the next section, we describe the theoretical background and develop a research model for this study to analyze the predictors linked to BDA adoption. The research methods are discussed in section three, and section four provides results from our data analysis using structural equation modeling and discussions. “Conclusion
” section concludes the overall findings. In addition to the research limitations, our study also has theoretical and practical implications, as discussed in “Conclusion
” section. References are given in “Reference” section.
The adoption of BDA is in the initial stage, in which many healthcare organizations are thinking about adopting BDA systems. The present is an optimal time to adopt/implement BDA systems, especially in healthcare organizations, with an aim of providing better healthcare facilities by maintaining patients’ health records and formulating better strategies. This study contributes to the literature by showing the main factors that are important when adopting the BDA system. This study results are also imperative for strategy makers who want to implement a BDA system by demonstrating factors that are important initially. In contrast to existing studies, this study also expressed the huge positive combined effect of the TTF and TAM theories on behavioral intentions to adopt BDA. Combining TAM and TTF gives more effective results than use of TAM or TTF individually [19
]. The prior literature demonstrates use of the TAM model alone in the adoption of a BDA system. The current study also incorporated important concerns from users regarding adoption of any innovative system, such as perceived security and perceived trust. These factors provide an additional significant aspect to the literature regarding BDA. Our sampling territory is Pakistan, which is a developing country. RTC is the largest barrier in the adoption of innovative systems, particularly in developing countries but also in developed countries. According to our best information, this study is the first to enrich the literature by linking resistance to change of employees with BDA adoption as a moderator. This moderation result will help implementers control this factor at the time of adopting the BDA system.
This study contributes noteworthy research insights into BDA system implementation. The study fills the main gap in the literature concerning the empirical evidence for BDA in Pakistani healthcare organizations for the first time. Second, the majority of previous studies only highlighted the importance, challenges, and opportunities of BDA, because BDA was in the initial stage of adoption and was a comparatively new topic. Second, few researchers have investigated the adoption of BDA, and the existing studies have focused on a specific perspective (i.e., an economic or financial perspective) or have simply emphasized TAM theory. This study is probably the first on BDA adoption to propose a model that combines the TAM and TTF theories as predictors of behavioral intentions to use BDA. Thus, integration and implementation of the TAM theory with the TTF theory for BDA adoption is a new perspective that enhances the literature. Second, to switch from the previous healthcare system to a BDA system, the literature needs a strong theoretical basis for further research and a broad and general research model that is not specific to one aspect of the business. This study model will be helpful and will advance a theory for future BDA research. Furthermore, the study included security and trust aspects of information in the model to elucidate their impacts on BI. Our results will contribute to the security and trust perspectives in the technology acceptance literature and provide security and trust grounds for further research. In addition, the results obtained for resistance to change represent an immense theoretical contribution for researchers, because the current study has highlighted this important barrier in the implementation of BDA. This investigation can be used as a reference for future research and to increase understanding of the adoption of BDA research.
The study also contributed practically in several ways similar to its theoretical contributions. The findings of the study propose salient guidelines and important implications for practitioners and implementers of BDA systems that can assist with successful adoption of BDA systems. First, connecting system functions with the required tasks of the organization as well as the PU and PEOU of the system are important. This approach will provide results that are more fruitful for practitioners when implementing BDA systems. Second, the findings of the study also indicate that perceived security and perceived trust are the key predictors of intentions regarding acceptance of a BDA system. Third, this study explores the moderating effect of RTC, which reduces the adoption of BDA systems in developing countries. This study will provide broad insights for implementers of BDA systems in developing countries and allow the design of strategies to ultimately reduce employees’ resistance levels. Finally, this study provides an initial platform for practitioners for adoption and promotion of BDA practices within the organization to obtain maximum advantages of innovative technology, especially in developing countries.
Limitations and future directions
The authors acknowledge some limitations of the current study. First, the focus of this study is on healthcare organizations in Pakistan regarding adoption of a BDA system. The impact of organizational culture was ignored by this study, which might have an effect on the level of adoption of this system. Future researchers may test the same research model in other organizations considering different cultural setups, because the organizational setup and culture vary from industry to industry; therefore, the findings of this study may vary when applied to different sector organizations. This study provided understanding of BDA system adoption in developing countries in particular and developed countries in general. Thus, future researchers can test this model in developed countries to increase the generalization of the study, because the severity of resistance to change from employees is greater in developing than in developed countries [41
]. The research model can be tested in different cultural settings with a focus on adoption of BDA systems. This study was aimed to investigate the user adoption factors of BDA, which neglect the other side of system implementation. Therefore, future researchers can identify the developers/architects intentions for development and implementation of BDA system. Finally, this study was based on cross-sectional settings, which restricted measurement of the consistency in respondent behavior; this gap should be tested in a longitudinal setup to improve the significant contribution to knowledge.
MS conceptualized the idea, prepared the literature and build theory, designed research framework and collect data, analyzed results, drafted and proof-read the manuscript, GCY and ZL provided supervision and guide throughout the process. FS and YH contribute in analysis and results writing. All authors read and approved the final manuscript.
This study has been supported by “National Natural Science Foundation of China (NSFC)” Grant Numbers: 71774044, 71672050, and 71272191.
The authors declare that they have no competing interests.
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