In recent times, scholars have stressed how big data hold the power to revolutionize traditional ways of doing business. As a proof, McAfee and Brynjolfsson (2012) seminal paper has defined big data as the next great managerial revolution. Building on these premises, pertinent literature focused on observing how organizational big data analytics (BDA) capabilities - which are a set of organizational capabilities deriving from BDA infrastructure flexibility, BDA management capabilities and BDA personnel capabilities - may affect performance. This phenomenon was particularly observed in large organizations. Yet, the most of scholars explored the phenomenon either from a theoretical standpoint or did not consider potential factors influencing this relationship. In this perspective, the present study builds on dynamic capabilities to propose and empirically test a conceptual model exploring whether organizational ambidexterity and agility mediate the relationship between BDA capabilities and organizational performance. Additionally, the moderating role of organizational resistance to information system (IS) implementation and IS-organizational fit will be explored. A total of 259 surveys were collected from managers of European large organizations. The proposed model was tested using structural equation modelling (SEM). Findings emphasize how organizational BDA capabilities influence ambidexterity, agility and, in turn, performance. Several theoretical implications for scholars and practical suggestions for managers seeking to develop organizational BDA capabilities are provided.

Rialti, R., Zollo, L., Ferraris, A., Alon, I. (2019). Big Data Analytics Capabilities, Ambidexterity and Performance: Empirical Evidences from European Large Organizations. In Global Innovation and Knowledge (pp.1-28). GIKA.

Big Data Analytics Capabilities, Ambidexterity and Performance: Empirical Evidences from European Large Organizations

Riccardo Rialti;
2019-01-01

Abstract

In recent times, scholars have stressed how big data hold the power to revolutionize traditional ways of doing business. As a proof, McAfee and Brynjolfsson (2012) seminal paper has defined big data as the next great managerial revolution. Building on these premises, pertinent literature focused on observing how organizational big data analytics (BDA) capabilities - which are a set of organizational capabilities deriving from BDA infrastructure flexibility, BDA management capabilities and BDA personnel capabilities - may affect performance. This phenomenon was particularly observed in large organizations. Yet, the most of scholars explored the phenomenon either from a theoretical standpoint or did not consider potential factors influencing this relationship. In this perspective, the present study builds on dynamic capabilities to propose and empirically test a conceptual model exploring whether organizational ambidexterity and agility mediate the relationship between BDA capabilities and organizational performance. Additionally, the moderating role of organizational resistance to information system (IS) implementation and IS-organizational fit will be explored. A total of 259 surveys were collected from managers of European large organizations. The proposed model was tested using structural equation modelling (SEM). Findings emphasize how organizational BDA capabilities influence ambidexterity, agility and, in turn, performance. Several theoretical implications for scholars and practical suggestions for managers seeking to develop organizational BDA capabilities are provided.
2019
9788409110605
Rialti, R., Zollo, L., Ferraris, A., Alon, I. (2019). Big Data Analytics Capabilities, Ambidexterity and Performance: Empirical Evidences from European Large Organizations. In Global Innovation and Knowledge (pp.1-28). GIKA.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1277233
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo