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A recipe for big data value creation

A recipe for big data value creation The purpose of this paper is to present a process-theory-based model of big data value creation in a business context. The authors approach the topic from the viewpoint of a single firm.Design/methodology/approachThe authors reflect current big data literature in two widely used value creation frameworks and arrange the results according to a process theory perspective.FindingsThe model, consisting of four probabilistic processes, provides a “recipe” for converting big data investments into firm performance. The provided recipe helps practitioners to understand the ingredients and complexities that may promote or demote the performance impact of big data in a business context.Practical implicationsThe model acts as a framework which helps to understand the necessary conditions and their relationships in the conversion process. This helps to focus on success factors which promote positive performance.Originality/valueUsing well-established frameworks and process components, the authors synthetize big data value creation-related papers into a holistic model which explains how big data investments translate into economic performance, and why the conversion sometimes fails. While the authors rely on existing theories and frameworks, the authors claim that the arrangement and application of the elements to the big data context is novel. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Business Process Management Journal Emerald Publishing

A recipe for big data value creation

Business Process Management Journal , Volume 25 (5): 16 – Aug 19, 2019

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1463-7154
DOI
10.1108/bpmj-03-2018-0082
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to present a process-theory-based model of big data value creation in a business context. The authors approach the topic from the viewpoint of a single firm.Design/methodology/approachThe authors reflect current big data literature in two widely used value creation frameworks and arrange the results according to a process theory perspective.FindingsThe model, consisting of four probabilistic processes, provides a “recipe” for converting big data investments into firm performance. The provided recipe helps practitioners to understand the ingredients and complexities that may promote or demote the performance impact of big data in a business context.Practical implicationsThe model acts as a framework which helps to understand the necessary conditions and their relationships in the conversion process. This helps to focus on success factors which promote positive performance.Originality/valueUsing well-established frameworks and process components, the authors synthetize big data value creation-related papers into a holistic model which explains how big data investments translate into economic performance, and why the conversion sometimes fails. While the authors rely on existing theories and frameworks, the authors claim that the arrangement and application of the elements to the big data context is novel.

Journal

Business Process Management JournalEmerald Publishing

Published: Aug 19, 2019

Keywords: Big data; Business value; Capabilities; Data assets; Digital transformation; Process theory

References