Purpose – Big Data has been heralded as a key agent of the third industrial revolution, and currently represents a promising area for value creation and frontier research. The potential to extract actionable insights from Big Data has gained increasing attention of both academics and practitioners operating in several industrial sectors. However, the adoption of Big Data solutions does not always generate effective value for the adopters. Therefore, the gap existing between the potential of value creation embedded in the Big Data paradigm and the current limited exploitation of this value represents an area of investigation that this paper aims to explore. In particular the present study aims at investigating the following research question: “Which are the multiple value directions that the Big Data paradigm can generate for organizations?”. In this vein, the article presents the result of a systematic literature review aimed at defining a framework that identifies the possible dimensions of value creation for an organization that may decide to adopt the Big Data paradigm. Design/methodology/approach – The research methodology adopted in this study is based on a Systematic Literature Review, and consists in four key steps such as search, selection, analysis, and synthesis. The result of the search process was a list of 481 resources. Then, by adopting the exclusion criteria, a subset of 91 resources was obtained. The analysis allowed to highlight the different types of value created through the adoption of Big Data paradigm within the organizations. Through the synthesis step, 12 value directions were defined and grouped into 5 key value dimensions. Originality/value – This paper introduces and describes a framework highlighting the possible value creation dimensions associated to the adoption of the Big Data paradigm by the organizations. By adopting a systematic literature review, the framework leverages and extends a previous contribution of Wamba et al. (2015) on the same topic. A further element of originality is related to the introduction of a further phase in the analysis, consisting in the application of text mining algorithms to analyse the selected resources, in the final aim to highlight possible terms and concepts remained hidden or latent in the human-led analysis. Practical implications – From a research perspective, the proposed framework aims at providing a twofold contribution: the more general one consists in the development of the debate on how organization can generate value by adopting the Big Data paradigm; the more specific one refers to the extension of the framework previously proposed by Wamba et al. (2015) on the same topic. From a practitioner point of view, the proposed framework may support managers and executives to understand better and define the strategic perspective of innovative projects based on the Big Data paradigm, which can be promoted and sponsored by the organizations.
Creating Value for organizations through Big Data: a Framework based on a systematic literature review
Gianluca Elia;Gianluca Solazzo;Giuseppina Passiante
2018-01-01
Abstract
Purpose – Big Data has been heralded as a key agent of the third industrial revolution, and currently represents a promising area for value creation and frontier research. The potential to extract actionable insights from Big Data has gained increasing attention of both academics and practitioners operating in several industrial sectors. However, the adoption of Big Data solutions does not always generate effective value for the adopters. Therefore, the gap existing between the potential of value creation embedded in the Big Data paradigm and the current limited exploitation of this value represents an area of investigation that this paper aims to explore. In particular the present study aims at investigating the following research question: “Which are the multiple value directions that the Big Data paradigm can generate for organizations?”. In this vein, the article presents the result of a systematic literature review aimed at defining a framework that identifies the possible dimensions of value creation for an organization that may decide to adopt the Big Data paradigm. Design/methodology/approach – The research methodology adopted in this study is based on a Systematic Literature Review, and consists in four key steps such as search, selection, analysis, and synthesis. The result of the search process was a list of 481 resources. Then, by adopting the exclusion criteria, a subset of 91 resources was obtained. The analysis allowed to highlight the different types of value created through the adoption of Big Data paradigm within the organizations. Through the synthesis step, 12 value directions were defined and grouped into 5 key value dimensions. Originality/value – This paper introduces and describes a framework highlighting the possible value creation dimensions associated to the adoption of the Big Data paradigm by the organizations. By adopting a systematic literature review, the framework leverages and extends a previous contribution of Wamba et al. (2015) on the same topic. A further element of originality is related to the introduction of a further phase in the analysis, consisting in the application of text mining algorithms to analyse the selected resources, in the final aim to highlight possible terms and concepts remained hidden or latent in the human-led analysis. Practical implications – From a research perspective, the proposed framework aims at providing a twofold contribution: the more general one consists in the development of the debate on how organization can generate value by adopting the Big Data paradigm; the more specific one refers to the extension of the framework previously proposed by Wamba et al. (2015) on the same topic. From a practitioner point of view, the proposed framework may support managers and executives to understand better and define the strategic perspective of innovative projects based on the Big Data paradigm, which can be promoted and sponsored by the organizations.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.