Nyagadza, Brighton ORCID: https://orcid.org/0000-0001-7226-0635, Bashar, Abu ORCID: https://orcid.org/0000-0003-1415-5591, Chuchu, Tinashe ORCID: https://orcid.org/0000-0001-7325-8932, Chipfumbu, Colletor Tendeukai ORCID: https://orcid.org/0000-0001-6933-9246, Durrah, Omar ORCID: https://orcid.org/0000-0002-8923-9450, Alkhalaf, Taher ORCID: https://orcid.org/0000-0002-8765-4538, Takunda Chiwaridzo, Option ORCID: https://orcid.org/0000-0001-9755-9123, Dzingirai, Mufaro ORCID: https://orcid.org/0000-0002-1518-8275, Munyavhi, Archeford ORCID: https://orcid.org/0009-0003-8120-9227, Ahmad, Khalil ORCID: https://orcid.org/0000-0001-8951-2640, Mabuyana, Brian ORCID: https://orcid.org/0000-0002-6773-4565, Mhlanga, David ORCID: https://orcid.org/0000-0002-8512-2124, Mutodi, Knowledge ORCID: https://orcid.org/0009-0003-0162-3445, Chibaro, Munyaradzi ORCID: https://orcid.org/0000-0002-4139-5139, Manyanga, Wilbert ORCID: https://orcid.org/0000-0002-6710-0140, Skandali, Dimitra ORCID: https://orcid.org/0009-0008-1728-2821, Cosmas Jaravaza, Divaries ORCID: https://orcid.org/0000-0002-8930-1242, Ngwu, Akachi ORCID: https://orcid.org/0000-0001-5163-6680, Wilfred Chikwape, Komborerai, Wasiq, Mohammad ORCID: https://orcid.org/0000-0003-0438-039X and Mashapure, Rahabhi ORCID: https://orcid.org/0009-0002-6526-9169 (2026) Artificial Intelligence (AI) and Social Commerce in Digital Business Ecosystems: A Science-Mapping Analysis of Global Research Evolution and Emerging Trends. Strategic Business Research, 2. p. 100227.

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Abstract

The current study presents a comprehensive science-mapping analysis of global research on the intersection of Artificial Intelligence (AI) and social commerce within digital business ecosystems. Through systematic analysis of bibliometric data from the Scopus database between 2000 and February 8, 2026, we identify the intellectual structure, thematic evolution, and emerging trends in this rapidly changing field. Using sequential bibliometric mapping and Latent Dirichlet Allocation (LDA) topic modelling, we reveal five key research clusters that illustrate the ways AI-enabled technologies (machine learning, recommendation systems, natural language processing) are discussed in relation to social commerce practices, including personalization, consumer engagement, and transactional efficiency. The study makes three interconnected contributions. First, it sequentially integrates bibliometric mapping with LDA topic modelling, using bibliometrics to establish the field's intellectual structure (who, where, when) and LDA to uncover its latent thematic content (what). Second, it empirically grounds the Technology-Organization-Environment (TOE) framework in AI-enabled social commerce, demonstrating that the three TOE dimensions are not static adoption factors but deeply interlinked, co-evolving forces. Third, it proposes a conceptually coherent framework derived directly from the five LDA topics, mapping each topic to a TOE dimension and identifying relationships suggested by the temporal patterns in our bibliometric data. These are presented as testable propositions for future research, not as confirmed causal mechanisms. These proposed relationships, drawn from observed patterns in the literature, offer hypotheses for future empirical testing rather than confirmed causal pathways. The study discusses disciplinary and geographic trends, showing rising contributions from Asia and Europe and collaborative interdisciplinary work across business strategy, information systems, and marketing domains. Future research avenues focus on algorithmic fairness, data privacy, and sustainability in AI-enhanced social commerce. This science-mapping analysis provides a holistic perspective on the research landscape, offering academics, practitioners, and pracademics actionable insights into the trajectory of AI and social commerce scholarship within digital business ecosystems.

Item Type:	Article
Status:	Published
DOI:	10.1016/j.sbr.2026.100227
Subjects:	H Social Sciences > HF Commerce Q Science > QA Mathematics > QA76.9.H85 Human-Computer Interaction; Virtual Reality; Mixed Reality; Augmented Reality ; Extended Reality
School/Department:	York Business School
URI:	https://ray.yorksj.ac.uk/id/eprint/15382

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