Purpose: This study contributes to the literature on intellectual capital (IC) in light of the emerging paradigm of Big Data. Through a literature review, this paper provides momentum for researchers and scholars to explore the emerging trends and implications of the Big Data movement in the field of IC. Design/methodology/approach: A literature review highlights novel and emerging issues in IC and Big Data research, focussing on: IC for organisational value, the staged evolution of IC research, and Big Data research from the technological to the managerial paradigm. It is expected that identifying these contributions will help establish future research directions. Findings: A conceptual multi-level framework demonstrates how Big Data validates the need to shift the focus of IC research from organisations to ecosystems. The framework is organised into four sections: ‘why’ – the managerial reasons for incorporating Big Data into IC; ‘what’ – the Big Data typologies that enhance IC practice; ‘who’ – the stakeholders involved in and impacted by Big Data IC value creation; and ‘how’ ¬– the Big Data processes suitable for IC management. Originality/value: This paper investigates the effects and implications Big Data offers for IC management, in support of the fourth stage of IC research. Additionally, it provides an original interpretation of IC research through the lens of Big Data. Research implications: The paper provides many avenues for future research in this emerging area of investigation. The key research questions posed aim to advance the contribution of Big Data to research on IC approaches. Practical implications: The paper outlines the socio-economic value of Big Data generated by and about organisational ecosystems. It identifies opportunities for existing companies to renew their value propositions through Big Data, and discusses new tools for managing Big Data to support disclosing IC value drivers and creating new intangible assets.

Intellectual capital in the age of Big Data: establishing a research agenda

SECUNDO, Giustina;DEL VECCHIO, PASQUALE;PASSIANTE, Giuseppina
2017-01-01

Abstract

Purpose: This study contributes to the literature on intellectual capital (IC) in light of the emerging paradigm of Big Data. Through a literature review, this paper provides momentum for researchers and scholars to explore the emerging trends and implications of the Big Data movement in the field of IC. Design/methodology/approach: A literature review highlights novel and emerging issues in IC and Big Data research, focussing on: IC for organisational value, the staged evolution of IC research, and Big Data research from the technological to the managerial paradigm. It is expected that identifying these contributions will help establish future research directions. Findings: A conceptual multi-level framework demonstrates how Big Data validates the need to shift the focus of IC research from organisations to ecosystems. The framework is organised into four sections: ‘why’ – the managerial reasons for incorporating Big Data into IC; ‘what’ – the Big Data typologies that enhance IC practice; ‘who’ – the stakeholders involved in and impacted by Big Data IC value creation; and ‘how’ ¬– the Big Data processes suitable for IC management. Originality/value: This paper investigates the effects and implications Big Data offers for IC management, in support of the fourth stage of IC research. Additionally, it provides an original interpretation of IC research through the lens of Big Data. Research implications: The paper provides many avenues for future research in this emerging area of investigation. The key research questions posed aim to advance the contribution of Big Data to research on IC approaches. Practical implications: The paper outlines the socio-economic value of Big Data generated by and about organisational ecosystems. It identifies opportunities for existing companies to renew their value propositions through Big Data, and discusses new tools for managing Big Data to support disclosing IC value drivers and creating new intangible assets.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/415201
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