Improving Agility Using Big Data Analytics: The Role of Democratization Culture

Youyung Hyun, Taro Kamioka, Ryuichi Hosoya

Abstract


Background: Big data analytics (BDA) is considered an enabler of organizational agility because it helps firms to sense market-based changes and improve decision making in a more informed and timely manner. However, in reality, only a handful of firms have achieved improvement in their outcomes by using BDA. To address this inconsistency, our study explores the conditions under which BDA use translates into agility. We particularly focus on organizational culture because in the pursuit of agility, culture is emphasized as a source of stability that allows firms to successfully adapt to the changing environment. Therefore, by assuming organizational culture as a contextual factor, this study examines the moderating effect of organizational culture on the link between BDA use and agility.

Method: We employ a concept from data democratization called “democratization culture,” which values the willingness to share information and the acceptance of diversity. We also adopt collectivistic culture for comparison with democratization culture. Further, BDA use is decomposed into advanced and basic use based on the functions and BDA types. A model is proposed and empirically validated through survey data collected from 304 senior-level managers.

Results: Our findings suggest that the moderating effects of democratization culture on agility are different depending on whether it is combined with advanced or basic BDA use.

Conclusions: This study provides initial empirical evidence that contributes to the scarce research on the role of organizational culture in the link between BDA use and agility.

Keywords


Big data analytics (BDA); organizational agility; organizational culture; democratization culture; collectivistic culture

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Citation: Hyun, Y., Kamioka, T., & Hosoya, R. (2020). Improving Agility Using Big Data Analytics: The Role of Democratization Culture. Pacific Asia Journal of the Association for Information Systems, 12(2), 34-62. https://doi.org/10.17705/1pais.12202