| Summary: | Purpose: This paper aims to explore the extent of open data actualization for start-up entrepreneurs based on affordance theory. The principal interest of the study revolves around the possible actions or actualization of open data for innovation and entrepreneurial benefits. Design/methodology/approach: The author used a qualitative case study as the research design. The author consulted the central public agency that manages open data implementations in Malaysia regarding the research topic. By doing so, the author recognized and interviewed start-up entrepreneurs who actualize open data in businesses. From that exercise, the author conducted a snowball sampling technique to recruit more informants for the research. Start-up entrepreneurs selected for the study must be active in an entrepreneurial project and have at least one year of experience using open data for innovation and entrepreneurship. The author conducted 30 online semistructured interviews with start-up entrepreneurs, representatives from open data providers and a start-up association for triangulation purposes. The author adopted affordance theory as a lens of understanding. Qualitative analysis software was used to generate research findings. Findings: In this study, start-up entrepreneurs actualize open data in three principal areas: product building with open data, value creation with existing products and open data for business research and strategies. The study came across distinct narratives of local start-ups that build open data products named “a property start-up,” “mechanics on the go” and “peer-to-peer digital charity movement.” Also, the study discovered three unanticipated findings about the research topic. First, the study uncovered two start-ups that used open data to enhance algorithm designs. Second, the study revealed a unique narrative of a start-up that pivoted business ideas based on open data during the Covid-19 pandemic. Third, the study learned about a start-up that initiated strategic partnerships with an agricultural association and smallholder farmers inspired by open data. These findings extend the literature on how start-up entrepreneurs actualize open data for entrepreneurial gains in a developing economy. What is also unique about this study is that there might be an open data misconception among start-up entrepreneurs. The findings advocate that some start-up entrepreneurs believed all data should be shared or opened upon request based on the generic understanding of open data. Clearly, this is a fallacy, and better awareness is required among start-up entrepreneurs regarding open data principles and implementations. Practical implications: Data providers need to build a credible image of open data as a foundation to drive actualization. This can be achieved through capacity building, awareness campaigns and strategic engagements with start-up entrepreneurs. Open data institutions need to initiate flagship projects with start-up associations in highly valuable sectors to demonstrate commercial applications of open data in certain fields. Originality/value: Previous research provides limited empirical studies on the commercial application of open data for start-up entrepreneurs. Hence, the novelty of this study lies in understanding how start-up entrepreneurs actualize open data to create value in their respective fields. © 2024, Emerald Publishing Limited.
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