Moshi, Albert and Sife, Alfred and Matto, George (2024) The Effect of Awareness on Big Data Adoption Readiness in Public Sector Auditing in Tanzania: Assessing TAM Model. Asian Journal of Economics, Business and Accounting, 24 (7). pp. 341-354. ISSN 2456-639X
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Abstract
Big data plays a pivotal role in auditing by unlocking unprecedented opportunities to extract meaningful insights from vast volumes of data. However, the usage of big data in public sector auditing in Tanzania is still limited, highlighting the need to explore the factors that influence its adoption readiness. This study explores the effect of awareness on auditors’ perception towards big data adoption readiness in public sector auditing. Specifically, it focuses on two key Technology acceptance model (TAM) factors, which are perceived ease of use and perceived usefulness. Data were collected from a sample of 221 auditors by using random sampling technique. Confirmatory factor analysis using Partial least square structural equation modelling performed the analysis. The findings revealed that awareness on big data adoption readiness plays a crucial role in shaping the perceived ease of use and perceived usefulness of big data technology. Higher levels of awareness are associated with increased perceived usefulness and perceived ease of use and consequently perceived usefulness was found as a major predictor of big data adoption readiness. The study concludes that empowering auditors with a deeper understanding of big data and its practical applications in public sector auditing could significantly increase their adoption readiness. Specifically, the findings suggest that providing targeted training programs, workshops, and seminars to enhance auditors' awareness and knowledge of big data technologies and their potential benefits would be an effective strategy to promote the readiness for big data adoption.
Item Type: | Article |
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Subjects: | Eurolib Press > Social Sciences and Humanities |
Depositing User: | Managing Editor |
Date Deposited: | 05 Jul 2024 08:15 |
Last Modified: | 05 Jul 2024 08:15 |
URI: | http://info.submit4journal.com/id/eprint/3693 |