Giulio Ferrigno, Saverio Barabuffi, Enrico Marcazzan, Andrea Piccaluga
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However, prior research has rarely investigated this relationship through a granular lens, failing to distinguish the specific effects of big data on radical and incremental innovation.</div><div>Focusing on firms’ intent of introducing radical and incremental innovation using big data, we employ the Knowledge Based View and the four well-known dimensions of big data (i.e., volume, velocity, variety, and veracity) to explore if and when big data is a source of knowledge for radical and incremental innovation. Performing an OLS regression analysis on a sample of 155 Italian firms, we find that both big data variety and veracity positively affect firms’ radical and incremental innovation. These findings provide insights about the conditions under which big data can improve firms’ innovation processes, contributing to a more comprehensive theoretical understanding of the opportunities big data bring in the context of firms’ product, service and process innovation. Moreover, our findings offer valuable guidance to managers navigating the complexities of leveraging big data for new product development.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103295"},"PeriodicalIF":10.9000,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"What “V” of the big data support firms’ radical and incremental innovation?\",\"authors\":\"Giulio Ferrigno, Saverio Barabuffi, Enrico Marcazzan, Andrea Piccaluga\",\"doi\":\"10.1016/j.technovation.2025.103295\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Despite the considerable attention from both academics and practitioners to the effects of big data on firms’ innovation performance, a noticeable research gap remains in understanding how big data influences different types of innovation—namely, radical and incremental innovation. Many studies recognize that big data can be a valuable source of innovation, as it enables firms to gather and incorporate insights from customers, partners, suppliers, and other stakeholders. However, prior research has rarely investigated this relationship through a granular lens, failing to distinguish the specific effects of big data on radical and incremental innovation.</div><div>Focusing on firms’ intent of introducing radical and incremental innovation using big data, we employ the Knowledge Based View and the four well-known dimensions of big data (i.e., volume, velocity, variety, and veracity) to explore if and when big data is a source of knowledge for radical and incremental innovation. Performing an OLS regression analysis on a sample of 155 Italian firms, we find that both big data variety and veracity positively affect firms’ radical and incremental innovation. These findings provide insights about the conditions under which big data can improve firms’ innovation processes, contributing to a more comprehensive theoretical understanding of the opportunities big data bring in the context of firms’ product, service and process innovation. Moreover, our findings offer valuable guidance to managers navigating the complexities of leveraging big data for new product development.</div></div>\",\"PeriodicalId\":49444,\"journal\":{\"name\":\"Technovation\",\"volume\":\"146 \",\"pages\":\"Article 103295\"},\"PeriodicalIF\":10.9000,\"publicationDate\":\"2025-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technovation\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0166497225001270\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technovation","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0166497225001270","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
What “V” of the big data support firms’ radical and incremental innovation?
Despite the considerable attention from both academics and practitioners to the effects of big data on firms’ innovation performance, a noticeable research gap remains in understanding how big data influences different types of innovation—namely, radical and incremental innovation. Many studies recognize that big data can be a valuable source of innovation, as it enables firms to gather and incorporate insights from customers, partners, suppliers, and other stakeholders. However, prior research has rarely investigated this relationship through a granular lens, failing to distinguish the specific effects of big data on radical and incremental innovation.
Focusing on firms’ intent of introducing radical and incremental innovation using big data, we employ the Knowledge Based View and the four well-known dimensions of big data (i.e., volume, velocity, variety, and veracity) to explore if and when big data is a source of knowledge for radical and incremental innovation. Performing an OLS regression analysis on a sample of 155 Italian firms, we find that both big data variety and veracity positively affect firms’ radical and incremental innovation. These findings provide insights about the conditions under which big data can improve firms’ innovation processes, contributing to a more comprehensive theoretical understanding of the opportunities big data bring in the context of firms’ product, service and process innovation. Moreover, our findings offer valuable guidance to managers navigating the complexities of leveraging big data for new product development.
期刊介绍:
The interdisciplinary journal Technovation covers various aspects of technological innovation, exploring processes, products, and social impacts. It examines innovation in both process and product realms, including social innovations like regulatory frameworks and non-economic benefits. Topics range from emerging trends and capital for development to managing technology-intensive ventures and innovation in organizations of different sizes. It also discusses organizational structures, investment strategies for science and technology enterprises, and the roles of technological innovators. Additionally, it addresses technology transfer between developing countries and innovation across enterprise, political, and economic systems.