Adoption Readiness for Autonomous Vehicle Technologies in Logistics SMEs: Explaining the Capability–Complexity Gap in South Africa
Year: 2026
Type: article
Abstract: Research on advanced technology adoption has traditionally emphasised technology acceptance, behavioural intentions, and determinants of organisational adoption. Less attention has been given to adoption readiness, particularly in contexts where organisations have foundational digital capabilities yet cannot implement technologically complex innovations. This study investigates autonomous vehicle (AV) adoption readiness among logistics small and medium-sized enterprises (SMEs) in South Africa. It examines how operational realities and readiness conditions shape organisational assessments of implementation feasibility. The study uses a sequential explanatory mixed-methods design, combining survey data from 100 respondents representing logistics SMEs with 17 semi-structured interviews with owners, managers, and operational decision-makers. The findings indicate that logistics SMEs generally associate AV technologies with anticipated improvements in efficiency, safety, cost optimisation, operational resilience, and competitiveness. However, financial limitations, skills shortages, infrastructure deficiencies, regulatory uncertainty, security risks, and broader operational pressures still constrain adoption readiness. Existing digital technologies support operational optimisation but do not automatically provide the capabilities required for advanced automation. Readiness depends on aligning process, organisational, environmental, technological, and infrastructure conditions, with sociocultural influences shaping organisational assessments across these domains. The study distinguishes adoption readiness from technology acceptance, provides contextual empirical support for refining the Process–Organisation–Environment–Technology (POET) framework, and identifies the capability–complexity gap as an interpretive explanation for constrained implementation readiness.
Source: Future Transportation
Authors: Mpedi Mary Kumalo, Masike Malatji
Institution: University of South Africa
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W7225662164
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