Quality dominant logic in big data analytics and firm performance

Samuel Fosso Wamba (Department of Information, Operations and Management Sciences, Toulouse Business School, Toulouse, France)
Shahriar Akter (Sydney Business School, University of Wollongong, Sydney, Australia)
Marc de Bourmont (NEOMA Business School, Mont-Saint-Aignan, France)

Business Process Management Journal

ISSN: 1463-7154

Publication date: 27 June 2019

Abstract

Purpose

Big data analytics (BDA) gets all the attention these days, but as important—and perhaps even more important—is big data analytics quality (BDAQ). Although many companies realize a full return from BDA, others clearly struggle. It appears that quality dynamics and their holistic impact on firm performance are unresolved in data economy. The purpose of this paper is to draw on the resource-based view and information systems quality to develop a BDAQ model and measure its impact on firm performance.

Design/methodology/approach

The study uses an online survey to collect data from 150 panel members in France from a leading market research firm. The participants in the study were business analysts and IT managers with analytics experience.

Findings

The study confirms that perceived technology, talent and information quality are significant determinants of BDAQ. It also identifies that alignment between analytics quality and firm strategy moderates the relationship between BDAQ and firm performance.

Practical implications

The findings inform practitioners that BDAQ is a hierarchical, multi-dimensional and context-specific model.

Originality/value

The study advances theoretical understanding of the relationship between BDAQ and firm performance under the influence of firm strategy alignment.

Keywords

Citation

Fosso Wamba, S., Akter, S. and de Bourmont, M. (2019), "Quality dominant logic in big data analytics and firm performance", Business Process Management Journal, Vol. 25 No. 3, pp. 512-532. https://doi.org/10.1108/BPMJ-08-2017-0218

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Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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