大数据的哪些“V”支持企业的激进创新和渐进式创新?

IF 10.9 1区 管理学 Q1 ENGINEERING, INDUSTRIAL
Giulio Ferrigno, Saverio Barabuffi, Enrico Marcazzan, Andrea Piccaluga
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引用次数: 0

摘要

尽管学术界和实践者都相当关注大数据对企业创新绩效的影响,但在理解大数据如何影响不同类型的创新(即激进创新和渐进式创新)方面,仍存在明显的研究空白。许多研究都认识到,大数据可以成为创新的宝贵来源,因为它使公司能够收集和整合来自客户、合作伙伴、供应商和其他利益相关者的见解。然而,以往的研究很少从微观角度考察这种关系,未能区分大数据对激进创新和渐进式创新的具体影响。关注企业利用大数据引入突破性和渐进式创新的意图,我们采用基于知识的观点和大数据的四个众所周知的维度(即体积、速度、多样性和准确性)来探索大数据是否以及何时成为突破性和渐进式创新的知识来源。通过对155家意大利企业样本的OLS回归分析,我们发现大数据的多样性和准确性对企业的激进创新和渐进式创新都有积极影响。这些发现提供了关于大数据可以改善企业创新流程的条件的见解,有助于对大数据在企业产品、服务和流程创新背景下带来的机会进行更全面的理论理解。此外,我们的研究结果为管理人员在利用大数据进行新产品开发的复杂性方面提供了有价值的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Technovation
Technovation 管理科学-工程:工业
CiteScore
15.10
自引率
11.20%
发文量
208
审稿时长
91 days
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.
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