A review of policies concerning development of big data industry in Pakistan: Subtitle: Development of big data industry in Pakistan

Latif, Zahid; Tunio, Muhammad Zahid; Pathan, Zulfiqar Hussain; Zeng, Jianqiu; Liu, Ximei; Sadozai, Sehrish Khan

doi:10.1109/icomet.2018.8346315

Cited by 14 publications

(16 citation statements)

References 8 publications

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“…Technology refers to the combination of various supportive activities to perform such tasks (i.e., computers, software, and others). Prior studies by Benford, D' Ambra and Khan et al [50,75] described the various dimensions of tasks (e.g., nonroutines, interdependence, data access, and quantitative data analysis), which were related to several technical aspects that fulfilled individuals' needs. Task and technology both have significant impacts on the ability of TTF to estimate users' performances from several perspectives [76].…”

Section: Task-technology Fitmentioning

confidence: 99%

“…Despite the fame of BDA, insufficient empirical research has investigated factors that can influence BDA adoption in healthcare [21,49]. 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.…”

mentioning

confidence: 97%

“…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.…”

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confidence: 99%

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Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change

et al. 2019

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IntroductionBig 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 [3,4]. 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 [5,6]. Using BDA in the healthcare sector will help inform each physician of the medical histories of individuals and the population and enable appropriate Abstract Big data analytics is gaining substantial attention due to its innovative contribution to decision making and strategic development across the healthcare field. Therefore, this study explored the adoption mechanism of big data analytics in healthcare organizations to inspect elements correlated to behavioral intention using the technology acceptance model and task-technology fit paradigm. Using a survey questionnaire, we analyzed 224 valid responses in AMOS v21 to test the hypotheses. Our results posit that the credentials of the technology acceptance model together with task-technology fit contribute substantially to the enhancement of behavioral intentions to use the big data analytics system in healthcare, ultimately leading towards actual use. Meanwhile, trust in and security of the information system also positively influenced the behavioral intention for use. Employee resistance to change is a key factor underlying failure of the innovative system in organizations and has been proven in this study to negatively moderate the relationship between intention to use and actual use of big data analytics in healthcare. Our results can be implemented by healthcare organizations to develop an understanding of the implementation of big data analytics and to promote psychological empowerment of employees to accept this innovative system. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Section: Task-technology Fitmentioning

confidence: 99%

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confidence: 97%

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confidence: 99%

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Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change

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“…computers, applications, etc.). Latif, Tunio, Pathan, Jianqiu, Ximei and Sadozai's (2018) finding contribute to a variety of technological criteria that meet the individual's needs (e.g. non-routines, coexistence, data access, and quantitative data analytics).…”

Section: Hypothesismentioning

confidence: 99%

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Sahid

Sani

Noordin

et al. 2021

JIEM

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Purpose: This research objective was to analyze factors affecting IT practitioners’ behavioral intentions in adopting (BDA) using a combination of Initial Trust Model (ITM), Unified Theory Of Acceptance And Use Of Technology (UTAUT) AND Task-Technology Fit (TTF) Model acceptance models.Design/methodology/approach: Using a cross sectional survey, empirical data were collected. A total of 200 questionnaires were obtained and screened. 14 insufficient answers were subsequently discarded leaving 186 valid structured data review questionnaires. Data was analizad using the Partial Least Square Modeling of Structural Equations due to one of the best software for verifying structured data on structural equations modeling (SEM).Findings: Our findings show that two key factors determine behavioral intention to adopt BDA in government agencies. Firstly, the assumption that the technology is going to produce great results raises the expectation of performance. TTF was the second determinant factor. Surprisingly, Initial trust, on the other hand, had not been considered to be a key determinant of behavioural intention and was found to be adversely related to the BDA intentionResearch limitations/implications: These findings identify the crucial model, that would be useful to IT officers in public agencies in making investment choices and designing non-adopter-friendly outreach strategies because they have more barriers to acceptance than adopters and lead adopters in the reward ladder.Practical implications: The findings suggest significant recommendations and consequences for BDA systems practitioners and application developers, which could coincide with the successful implementation of BDA systems. This research gives practitioners an initial way to incorporate and endorse BDA activities in their organization to make the most of the advantages of revolutionary technology, particularly within public agencies.Originality/value: This study's model is helpful and promotes a theory for further BDA research. By utilizing the model, existing public agencies can know their own BDA capability, centered around activities with specifically tailored outcomes, organization dynamics, resources, skills and potential services.

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“…The deployment of the femtocell is the main issue. There are some positions, which need to be clarified before mass deployment of Femtocells in rural and urban areas [17] [18].…”

Section: G Femtocell Users Mobility Managementmentioning

confidence: 99%

Optimization and Deployment of Femtocell: Operator’s Perspectives

Iqbal¹,

Bhutto²,

Latif³

et al. 2019

ijacsa

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This study examines the deployment issues of Femtocell, which require the satisfaction level of users on available bandwidth. Femtocells are small Base Stations installed in Homes for the improvement of coverage and capacity of Cellular Networks. Femtocells are connected over traditional DSL, FTTH (fiber to the home) to the Network. Optimization of Cellular Network is required for efficient utilization of available bandwidth and resources. In this paper, we present deployments issues, optimizations of Femtocell, Operator perspective survey results, and Service level agreement (SLA) between cellular operators, which achieve the user's desires and support in the deployment of Femtocell Network.

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A review of policies concerning development of big data industry in Pakistan: Subtitle: Development of big data industry in Pakistan

Cited by 14 publications

References 8 publications

Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change

Investigating the adoption of big data analytics in healthcare: the moderating role of resistance to change

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Optimization and Deployment of Femtocell: Operator’s Perspectives

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