Digital transformation dimensions for evaluating SMEs' readiness for big data analytics and artificial intelligence: A review

Author:

Motjolopane IgnitiaORCID,Chanza MartinORCID

Abstract

Assessing the readiness and maturity of small and medium enterprises (SMEs) is a foundation for implementing emerging technologies like big data analytics and artificial intelligence to drive their digital transformation endeavours. This study emphasises that readiness and maturity dimensions offer descriptive and prescriptive guidelines for gauging the current and desired levels of preparedness and maturity required to achieve desired digital transformation outcomes. However, prevailing readiness and maturity models overlook the diverse stages of advancement in big data analytics and artificial intelligence. This research explores the dimensions essential for assessing SMEs' readiness to adopt big data analytics and artificial intelligence. This paper identifies the key dimensions for evaluating SMEs' readiness and maturity across different categories of big data analytics and artificial intelligence by conducting a systematic literature review and employing cluster analysis. The study's principal findings underscore that SMEs' readiness for maturity is influenced prominently by strategic leadership and organisational culture, closely trailed by information technology, security, and business model transformation. Additionally, three pivotal dimensions encompass data analytics and governance, cost-benefit and risk management, and environmental factors. Consequently, proposing that evaluating digital readiness and maturity for SMEs should encompass these six dimensions, thoughtfully considering various prerequisites related to analytics and artificial intelligence.

Publisher

Center for Strategic Studies in Business and Finance SSBFNET

Subject

General Earth and Planetary Sciences,General Environmental Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Applicability of blockchain technology in improving efficiency in supply chain operations in public procurement in Tanzania;International Journal of Research in Business and Social Science (2147- 4478);2023-12-18

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