Exploring artificial intelligence adoption in digital marketing using snowball sampling: A qualitative study of small retail businesses in Cape Town
Steven Lububu · Monique Harris · Michael Twum-Darko
International Journal of Business Ecosystem & Strategy · 2026 · Vol. 8 / Issue 3 · 218-223
Publication metrics
External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.
Dimensions
Live provider badge. If unavailable, use the Dimensions link above.
Observed 21 Oct 2026, 00:14 UTC
Observed 22 Oct 2026 01:56 UTC
Observed 22 Oct 2026 01:56 UTC
OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.
Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.
2017–2026 Annual history last updated:
Citations received
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
View data & coverage
2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.
Abstract
Artificial intelligence (AI) is transforming digital marketing by enabling advanced analytics, automation, and personalised customer engagement. Despite growing adoption, qualitative insights into how small retail enterprises in emerging economies adopt AI remain limited. This study examines AI adoption in digital marketing among small retailers in Cape Town using an interpretivist qualitative case study design. Grounded in an integrated Technology–Organisation–Environment (TOE) and Unified Theory of Acceptance and Use of Technology (UTAUT) framework, data were collected through semi-structured interviews with 18 participants identified via snowball sampling. Thematic analysis shows that AI adoption is driven by competitive pressure, customer expectations, and perceived performance benefits, but is constrained by skills gaps, cost concerns, and data-related challenges. The study extends TOE–UTAUT theory by demonstrating how platform-based AI tools reduce technological barriers while amplifying organisational and capability-related constraints in emerging market contexts. The findings provide actionable insights for policymakers and practitioners aiming to support sustainable digital transformation in small business ecosystems.
Keywords: {'name': 'Artificial Intelligence'}, {'name': 'Digital Marketing'}, {'name': 'TOE–UTAUT'}, {'name': 'Qualitative Case Study'}, {'name': 'snowball sampling'}
Authors & affiliations
Steven Lububu
Cape Peninsula University of Technology
Monique Harris
Cape Peninsula University of Technology
Michael Twum-Darko
Cape Peninsula University of Technology
Deposited references
Supplied references, not a list of publications citing this article.
No reference list supplied.