Istanbul Esenyurt University, Faculty of Business and Management Sciences, Istanbul, Türkiye
Abstract
The aim of this research is to analyze the effects of big data usage on the product and process innovation performance of businesses. The survey used to collect data consisted of three parts: the first part included demographic questions, the second part a "Big Data Usage Scale," the third part a "Product Innovation Scale," and the fourth part a "Process Innovation Scale." The "Simple Random Sampling Method," where everyone in the population had an equal chance of being selected, was used to determine the survey participants. The sample consisted of 564 employees from 2640 businesses operating in the Dudullu Organized Industrial Zone in Istanbul. The regression analysis results showed that data size supported product innovation while negatively impacting process innovation; the validation variable showed different effects on product and process innovation. These results indicate that simply collecting large amounts of data is not enough for businesses; the ability to generate meaningful value from data and manage it effectively plays a critical role in improving innovation performance. Utilizing digital technologies is vital for businesses to enhance innovation performance. Failure to adopt new technologies in businesses can reduce business performance, leading to decreased productivity and profitability. Therefore, integrating new technologies, automation, artificial intelligence applications, and big data into business processes can facilitate innovation, provide a competitive advantage, ensure business continuity, and consequently contribute to economic growth. In conclusion, it is believed that scientific studies in this area can make significant contributions to researchers, businesses, public institutions, and other interested parties.
Sahin, Z. (2026). The relationship between big data usage and product and process innovation: The case of Istanbul Dudullu Organized Industrial Zone. International Journal of Eurasia Social Sciences, 17(65), 1182–1207. https://doi.org/10.70736/ijoess.1758
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