Ascertaining the progress and challenges of implementing data mining technology in the accounting information systems of public sector functions in developing countries

Abstract

Modern technology has made it possible to generate and analyse vast quantities of data. This is because information technology is required in all fields for management to make vital choices. In addition, data has grown into a crucial tool in the modern business environment, and the ability to use this data efficiently has become critical. This research examines the preparedness to integrate data mining technologies inside the accounting information systems of the Malaysian public sector and the degree to which these technologies are used. Few research have examined data mining deployment in Nigeria. This previous research were conducted in the private sector. In the public sector, none have occurred. This research helps to close this knowledge gap by examining the influence of technology, organisational and human resources, and external factors such as political action. Also explored are the characteristics of persons who chose or would be eager to accept this technology, as contrasted to those who do not. Combining information and communication technologies (ICTs), knowledge management (KM), data warehousing (DW), and data mining (DM), a data mining utilisation model is created for use in the Nigerian public sector, and the advantages of adopting such a model are discussed. Using both online surveys and online interviews, the research is triangulated. The online survey had a 68% response rate, and 15 semi-structured interviews were conducted. Issues investigated were respondents' perspectives on the significance and significance of elements in assessing the accounting information system, the degree of knowledge, attitudes, and preparedness to apply data mining technologies in the public sector. SPSS was used for analysis, whereas NVivo was used for interview data. This survey found that thirty of the one hundred and twenty-nine respondents were adopters and had expertise about the adoption of this technology inside their departments. Most respondents were unaware that data mining technologies existed. Moreover, although respondents were generally satisfied with the present accounting information system, they noted enhancements and modifications that would be beneficial. For both current users and non-adopters of data mining technologies, key factors such as technical, organisational, and human resources played a part in the choice to use or not use such technology. Significant reasons cited by non-adopters for not implementing data mining technology were a lack of support from senior management, a lack of accessible funds to build up the required infrastructure, and human resource challenges, including a lack of expertise of the technology. In terms of preparedness to apply data mining technology, the research revealed no difference between gender, job function, or utilisation groups. However, there was a difference in education level and experience working with the AIS. Using this sort of technology was discovered to be correlated with the performance of the AIS. It was determined that the optimal strategy for implementing data mining technologies in the public sector would consist of a centralised data repository connected to a well-managed data warehouse that integrates a few current systems with data mining technology.