Assessing the readiness of micro-businesses in the Cape Mmetropolitan to adopt data analytics software
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Date
2024
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University of the Western Cape
Abstract
Small and Medium Enterprises (SMEs) particularly, micro-businesses, have access to an increasing volume of data generated through their daily operations. However, their low rate of
adoption and integration of data analytics software into business operations hinders their ability to make effective data-driven decisions. This limits their potential for growth and success
because of not maximising the potential of their data. Additionally, they also have limited knowledge and understanding of the factors that determine to their readiness to adopt and
integrate data analytics software. Without a means to assess their readiness, many SMEs, specifically micro-businesses will continue to hold the misconception that they are incapable
of incorporating data analytics software into their business processes. This study therefore developed an assessment instrument to help micro-businesses evaluate
their readiness for adopting and integrating data analytics software into their businesses. The study drew on four models and frameworks namely the Technology-Organization-
Environment (TOE), Resource-Based View (RBV), Diffusion of Innovation (DOI) and the Unified Theory of Acceptance and Use of Technology (UTAUT) to develop the key criteria of
this instrument. The data for this study was collected through face- to-face, semi-structured interviews with a sample of 21 micro-businesses. This approach allowed for an in-depth analysis of each sub- criterion based on their daily real world business conditions, the ease of answering the questions within the proposed instrument, and participants understanding of the key concepts surrounding data analytics software adoption. The response helped. assess and determine the applicability of the proposed data analytics software assessment instrument. Thereafter, the data was analysed using qualitative content analysis to code and synthesise the responses of micro-business which provided significant insights into the identified dimensions and its sub- criterion. This led to a further refinement of the draft instrument. The findings revealed that Data accessibility, data availability, data quality, cybersecurity awareness, skilled personnel, organisational training, hardware, software, finance, infrastructure, relative advantage, performance expectancy, effort expectancy, complexity and social influence were relevant for inclusion in the assessment instrument. A final evaluation of the practical utility of the instrument was undertaken by applying it among
three micro-enterprises. During this exercise it was found that the questions in the final data analytics software readiness assessment instrument were understandable and easily answered by all three micro-businesses which allowed them, to successfully assess their level of readiness to adopt and integrate the data analytics software.
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Keywords
SMEs, Micro-businesses, Technology, Data, Data analytics