Bridging the gap: factors driving retail analytics adoption in traditional retail businesses

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dc.contributor.advisorBudree, Adheesh
dc.contributor.authorMoloi, Shaun
dc.date.accessioned2025-12-19T11:56:11Z
dc.date.available2025-12-19T11:56:11Z
dc.date.issued2025
dc.date.updated2025-12-19T11:53:33Z
dc.description.abstractThis thesis investigates how South Africa's traditional retail sector adopts advanced analytics amid infrastructural, cultural, and economic constraints. Guided by the Technology Organisation-Environment (TOE) framework and Diffusion of Innovations (DOI) theory, it addresses a critical gap in understanding the interplay of legacy systems, limited IT resources, and stringent regulatory demands on data-driven decision-making. A multi-case qualitative study of three large and mid-tier traditional retail chains in South Africa was conducted, involving 15 participants including store managers, IT directors, data analysts, marketing executives, and senior decision-makers. Findings highlight how outdated point-of sale infrastructure, patchy internet connectivity, and frequent power outages impede real-time analytics. At the organisational level, siloed structures and staff concerns over job displacement slow adoption, despite growing leadership support for pilot projects and training programmes. External forces, particularly the Protection of Personal Information Act (POPIA), socio economic pressures such as high unemployment, and intense competition, further complicate large-scale analytics initiatives. Even promising solutions like loyalty cards and semi automated storefronts have yielded uneven returns when confronted by crime risks, transient consumer behaviour, or landlord restrictions. Nonetheless, incremental deployments (e.g., “mobile-first” analytics and phased cloud migrations) emerge as viable stopgaps to overcome resource and connectivity challenges. Findings underscore the importance of executive sponsorship, cross-functional collaboration, and targeted upskilling in fostering a data-centric culture. They also reveal that retailers can simultaneously advance sustainability goals, such as cutting waste and optimising energy usage, by harnessing predictive models that align with cost-saving strategies. Ultimately, this thesis argues that successful analytics adoption in emerging markets hinges on aligning technological ambitions with infrastructural realities and social imperatives. By integrating global best practices with localised approaches, retailers can enhance competitiveness, improve operational efficiencies, and contribute to inclusive, data-driven growth across South Africa's evolving retail landscape
dc.identifier.apacitationMoloi, S. (2025). <i>Bridging the gap: factors driving retail analytics adoption in traditional retail businesses</i>. (). University of Cape Town ,Faculty of Commerce ,Department of Information Systems. Retrieved from http://hdl.handle.net/11427/42467en_ZA
dc.identifier.chicagocitationMoloi, Shaun. <i>"Bridging the gap: factors driving retail analytics adoption in traditional retail businesses."</i> ., University of Cape Town ,Faculty of Commerce ,Department of Information Systems, 2025. http://hdl.handle.net/11427/42467en_ZA
dc.identifier.citationMoloi, S. 2025. Bridging the gap: factors driving retail analytics adoption in traditional retail businesses. . University of Cape Town ,Faculty of Commerce ,Department of Information Systems. http://hdl.handle.net/11427/42467en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Moloi, Shaun AB - This thesis investigates how South Africa's traditional retail sector adopts advanced analytics amid infrastructural, cultural, and economic constraints. Guided by the Technology Organisation-Environment (TOE) framework and Diffusion of Innovations (DOI) theory, it addresses a critical gap in understanding the interplay of legacy systems, limited IT resources, and stringent regulatory demands on data-driven decision-making. A multi-case qualitative study of three large and mid-tier traditional retail chains in South Africa was conducted, involving 15 participants including store managers, IT directors, data analysts, marketing executives, and senior decision-makers. Findings highlight how outdated point-of sale infrastructure, patchy internet connectivity, and frequent power outages impede real-time analytics. At the organisational level, siloed structures and staff concerns over job displacement slow adoption, despite growing leadership support for pilot projects and training programmes. External forces, particularly the Protection of Personal Information Act (POPIA), socio economic pressures such as high unemployment, and intense competition, further complicate large-scale analytics initiatives. Even promising solutions like loyalty cards and semi automated storefronts have yielded uneven returns when confronted by crime risks, transient consumer behaviour, or landlord restrictions. Nonetheless, incremental deployments (e.g., “mobile-first” analytics and phased cloud migrations) emerge as viable stopgaps to overcome resource and connectivity challenges. Findings underscore the importance of executive sponsorship, cross-functional collaboration, and targeted upskilling in fostering a data-centric culture. They also reveal that retailers can simultaneously advance sustainability goals, such as cutting waste and optimising energy usage, by harnessing predictive models that align with cost-saving strategies. Ultimately, this thesis argues that successful analytics adoption in emerging markets hinges on aligning technological ambitions with infrastructural realities and social imperatives. By integrating global best practices with localised approaches, retailers can enhance competitiveness, improve operational efficiencies, and contribute to inclusive, data-driven growth across South Africa's evolving retail landscape DA - 2025 DB - OpenUCT DP - University of Cape Town KW - retail analytics KW - adoption barriers KW - technology-organization-environment framework KW - diffusion of innovation KW - traditional retail KW - data-driven culture KW - South Africa LK - https://open.uct.ac.za PB - University of Cape Town PY - 2025 T1 - Bridging the gap: factors driving retail analytics adoption in traditional retail businesses TI - Bridging the gap: factors driving retail analytics adoption in traditional retail businesses UR - http://hdl.handle.net/11427/42467 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/42467
dc.identifier.vancouvercitationMoloi S. Bridging the gap: factors driving retail analytics adoption in traditional retail businesses. []. University of Cape Town ,Faculty of Commerce ,Department of Information Systems, 2025 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/42467en_ZA
dc.language.isoen
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Information Systems
dc.publisher.facultyFaculty of Commerce
dc.publisher.institutionUniversity of Cape Town
dc.subjectretail analytics
dc.subjectadoption barriers
dc.subjecttechnology-organization-environment framework
dc.subjectdiffusion of innovation
dc.subjecttraditional retail
dc.subjectdata-driven culture
dc.subjectSouth Africa
dc.titleBridging the gap: factors driving retail analytics adoption in traditional retail businesses
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMCom
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