Big data in accountancy firms
Creators: name: Hussain, Rafaqat
Publisher: name: Zenodo
Year: 2024

description: Despite the growing number of researchers in the field of big data and big data analytics (BDA), the success rate of these deployments and the strategic value provided are unclear. The majority of big data and big data analytics literature focuses on how they can be utilised to improve tactical organisational skills, but there are few studies that look at how they might improve organisational value. Moreover, the researcher believes that there is a lack of understanding of how big data and big data analytics may add strategic value to organisations, particularly small accounting firms in the United Kingdom. After all, the ultimate success of any big data and big data analytics implementation is the realisation of strategic business value, which provides businesses with a competitive advantage. Therefore, this thesis seeks to survey the perceived experiences on big data implementation as well as any challenges that have emerged within the SME’s of the accounting firms in UK. The focus is on identifying the critical factors that will determine the effective incorporation of big data technology in accounting firms, as well as analysing the benefits and risks connected with this innovation. Based on empirical evidence, it will identify the variables within accounting firms that can lead to these opportunities being exploited.Prior research has established the advantages of big data and big data analytics, as well as their characteristics. With the expansion of technology and information systems, and also the global meltdown, the subject of big data and big data analytics is now popular in many industries, including corporate, industry, public sector, and also educational institutes. Which results in, fundamental shifts in how big data and big data analytics are perceived, sustained and developed are required to comprehend the evolving environment's complexity. In contrast, the development of such big data and big data analytics has gotten less scholarly attention, especially in the UK's small accounting business.To address these issues within the small accounting firms in the UK, the present study is undertaken and identified the critical factors relating to the big data and big data analytics. This study, with a sample of 80 participants across small accounting firms; 8 partners’ from small accounting firms’ and 7 managers from small accounting firms’; first revealed that a clear business strategy with respect to big data and big data analytics is needed from the senior management to successfully drive the implementation across the firms. Furthermore, the study also disclosed the critical factors of strategy, information systems, analytics, culture and architecture are important for the small accounting firms with the guidance of using the big data maturity model.Because of the big data maturity model's ability to guider the firm, as organisations may be at different stages and require different measures, and it may also be dependent on financialstructure, cultural adoption, and the digital divide. The study also shown that equally important, are expertise, skillful and knowledgeable people in field of big data and big data analytics anticipate that often models are hard to understand practically and much of the organisational resources may be used. Subsequently, the study also revealed that small accounting firms are lacking within the information systems and recent technology advancement however, this is mainly due to the lacking in the capital invest.In conclusion, this thesis provides empirical support for big data and big data analytics centeredon small accounting businesses' perceptions in the United Kingdom. It also develops new theories in order to advance these fields of study. As a result, the thesis contributes to a deeper understanding of the creation of effective and efficient big data and big data analytics implementation for small accounting firms. It identifies crucial research directions for the potential of big data and big data analytics.