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

Abstract

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.

Factors Affecting the Acceptance of Big Data Technology in Teaching among Higher Education Educators: An Empirical Investigation Using the UTAUT Model

“…This significant relationship is consistent with previous research (Radovan & Kristl, 2017;Teo & Noyes, 2012), which concluded that performance expectancy is a key factor influencing teachers' intention to adopt new technologies. Other studies (Brünink, 2016;Sahid et al, 2021;Cabrera-Sanchez & Villarejo-Ramos, 2019) also found positive and significant effects of performance expectancy on the intention to use big data technology. This result implies that if educators believe that using big data technology will benefit their careers, they will be more likely to accept it.…”

“…Furthermore, previous big data research has primarily focused on technical attributes (such as machine learning or technical algorithms) with little consideration given to the intention to use big data technologies in practice (Kwon et al, 2019). In addition, although a few studies have focused on the intentions of adopting big data techniques in organizations (Brünink, 2016;Demoulin & Coussement, 2020;Verma et al, 2018;Sahid et al, 2021;Queiroz & Pereira, 2019;Cabrera-Sanchez & Villarejo-Ramos, 2019), identifying the factors that influence educators' intentions to use big data technology in teaching needs more research.…”

Understanding Information Ethics Practice through the PAPA Framework

“…Privacy or anonymity, from some standpoint, refers to the expectation of fairness and control over personal information and the expectation of confidentiality (Sahid et al, 2021). Privacy is also described as the ability of individuals to control the access others have to personal information about them.…”