Over recent times, the availability of big data -which are datasets so large that cannot be analyzed using traditional statistical software- and big data analytics (BDA) tools have dramatically revolutionized the ways organizations are managed. In this perspective, managerial literature has determined that the development of BDA capabilities is a must for the most of large organizations collecting enough data whose datasets fall into the definition of big data. Specifically, it emerged how large organizations should acquire flexible BDA infrastructures and invest in the development of managers’ and employees (personnel) BDA skills. Yet, transforming a classical organization in an organization pervaded by the so called “big data culture” is neither easy nor without potential complications. Employees may, as an example, try to resist the implementation of big data architectures and systems amidst the fear of losing their jobs. Anyway, whether managers of an organization will be able to drive the big data-driven digital transition, the organization as a whole organism may obtain several relevant benefits such as better performances, increased capabilities to identify opportunities and threats, increase resilience and adaptability, and increase capability to react to changes. Notwithstanding the existing literature on big data, some research gaps still exist anyway. In particular, there is a need to evaluate whether other factors can influence the relationship between organizational BDA capabilities and performance. As an example, as BDA capabilities may increase both organizational capacities to identify and exploit opportunities and the capacity to adapt to change, ambidexterity and agility may be outcomes of BDA capabilities. Additionally, there is the need to better explore factors preventing BDA to generate effects. Moving from this, the present research focuses on the impact of BDA on large organizations. In particular, building on dynamic capabilities, we will focus on the importance of organizational ambidexterity and agility on the relationship between BDA analytics and performance. Next, building on IS contingency theory, the importance of IS organization fit and organization resistance to IS change will be explored. In this dissertation, the phenomenon will be explored both from three perspectives: theoretical, qualitative, and quantitative. The first one will be explored through a literature analysis. The second one will be explored using a case analysis. The third one will be explored thanks to structural equation modelling (SEM). The data used in this research derive from 259 surveys completed by European large organization managers. Findings stress out the importance of BDA capabilities as antecedents of ambidexterity, agility and performance. At the end of each paper composing the research managerial implications are provided.

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

2019

Abstract

Over recent times, the availability of big data -which are datasets so large that cannot be analyzed using traditional statistical software- and big data analytics (BDA) tools have dramatically revolutionized the ways organizations are managed. In this perspective, managerial literature has determined that the development of BDA capabilities is a must for the most of large organizations collecting enough data whose datasets fall into the definition of big data. Specifically, it emerged how large organizations should acquire flexible BDA infrastructures and invest in the development of managers’ and employees (personnel) BDA skills. Yet, transforming a classical organization in an organization pervaded by the so called “big data culture” is neither easy nor without potential complications. Employees may, as an example, try to resist the implementation of big data architectures and systems amidst the fear of losing their jobs. Anyway, whether managers of an organization will be able to drive the big data-driven digital transition, the organization as a whole organism may obtain several relevant benefits such as better performances, increased capabilities to identify opportunities and threats, increase resilience and adaptability, and increase capability to react to changes. Notwithstanding the existing literature on big data, some research gaps still exist anyway. In particular, there is a need to evaluate whether other factors can influence the relationship between organizational BDA capabilities and performance. As an example, as BDA capabilities may increase both organizational capacities to identify and exploit opportunities and the capacity to adapt to change, ambidexterity and agility may be outcomes of BDA capabilities. Additionally, there is the need to better explore factors preventing BDA to generate effects. Moving from this, the present research focuses on the impact of BDA on large organizations. In particular, building on dynamic capabilities, we will focus on the importance of organizational ambidexterity and agility on the relationship between BDA analytics and performance. Next, building on IS contingency theory, the importance of IS organization fit and organization resistance to IS change will be explored. In this dissertation, the phenomenon will be explored both from three perspectives: theoretical, qualitative, and quantitative. The first one will be explored through a literature analysis. The second one will be explored using a case analysis. The third one will be explored thanks to structural equation modelling (SEM). The data used in this research derive from 259 surveys completed by European large organization managers. Findings stress out the importance of BDA capabilities as antecedents of ambidexterity, agility and performance. At the end of each paper composing the research managerial implications are provided.
5-feb-2019
Italiano
Ciappei, Cristiano
Università degli Studi di Pisa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/134185
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-134185