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Big data analytics in innovation processes. Which forms of dynamic capabilities should be developed and how to embrace digitization

Caputo, R., Garzella, S., Fiorentino, R. & Giudici, A. ORCID: 0000-0001-6033-1643 (2021). Big data analytics in innovation processes. Which forms of dynamic capabilities should be developed and how to embrace digitization. European Journal of Innovation Management, doi: 10.1108/EJIM-05-2021-0256


Purpose: The purpose of this paper is to analyze, from a dynamic capabilities perspective, the role of big data analytics in supporting firms’ innovation processes.

Design/methodology/approach: Relevant literature is reviewed and critically assessed. An interpretive methodology is used to analyze empirical data from interviews of big data analytics experts at firms within digitally related sectors.

Findings: Our study shows how firms leverage big data to gain "richer” and "deeper” data at the intersections between the digital and physical worlds. We also provide evidence for the importance of counterintuitive strategies aimed at developing innovative products, services, or solutions with characteristics that may initially diverge, even significantly, from established customer/user needs.

Originality: We provide insights into the evolution of scholarly research on innovation directed toward opportunities to create a competitive advantage by offering new products, services or solutions diverging, even significantly, from established customer demand.Practical implications: Our findings offer insights to help practitioners manage innovation processes in the physical world while taking investments in big data analytics into account.

Publication Type: Article
Additional Information: © 2021. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher.
Publisher Keywords: Strategic management, innovation, dynamic capabilities, big data analytics, digitalization
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HF Commerce
Departments: Bayes Business School > Management
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