Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/6658
Title: Artificial Intelligence (AI), Machine Learning (ML) and Big Data Analytics' Impact on Frugal Digital Marketing Firms
Authors: Brighton Nyagadza
Abu Bashar
Neo Ligaraba
Theo Tsokota
Colletor Tendeukai Chipfumbu
Lovemore Chikazhe
Hamilton Tamburayi Katsvairo
Tawanda Taurai Maradze
Charlene Muswaka
York St John University, UK
University of Bahrain, Bahrain
University of the Witwatersrand, South Africa
Midlands State University (MSU), Zimbabwe
Midlands State University (MSU), Zimbabwe
Chinhoyi University of Technology (CUT), Zimbabwe
Marondera University of Agricultural Sciences and Technology (MUAST), Zimbabwe
Marondera University of Agricultural Sciences and Technology (MUAST), Zimbabwe
Marondera University of Agricultural Sciences and Technology (MUAST), Zimbabwe
Keywords: Disruptive technologies
Digital technologies
Issue Date: 2025
Publisher: Emerald Publishing Limited
Abstract: Disruptive technologies have changed the way that firms model their business approach. The aim of this study is to analyse the influence of novel digital technologies (artificial intelligence [AI] and machine learning [ML]) and big data analytics on the digital transformation of digital marketing firms. This research study is based on a review of the extant literature, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Gaps in the extant research literature were identified and emerged that are directly linked with the impact of AI, ML and big data analytics on digital transformation for digital marketing firms. Potential opportunities for digital transformation in digital firms were also unlocked, as well as related challenges. The research informs practice and policy for the current trends and provides future research directions. The study was limited to the application of the PRISMA methodology, which is incapable of fully providing testable results for a given study. Complementary cross-sectional research studies using the same methodology in different areas of study with the same topic can be applied to check for relevancy and applicability. This study contributes to digital marketing, information communication technologies, information systems practice and theory building. In addition, it provides researchers with an agenda for future digital transformation research directions.
URI: https://cris.library.msu.ac.zw//handle/11408/6658
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