Conceptualizing big data practices

• Pages: 205-222
• Published date: 26 February 2020
• DOI: https://doi.org/10.1108/IJAIM-12-2018-0154
• Date: 26 February 2020
• Author: Canchu Lin,Anand S. Kunnathur,Long Li
• Subject Matter: Accounting & Finance,Accounting/accountancy,Accounting methods/systems

Conceptualizing big data practices

Canchu Lin

Carroll University, Waukesha, Wisconsin, USA

Anand S. Kunnathur

University of Toledo, Toledo, Ohio, USA, and

Long Li

University of Louisiana at Alexandria, Alexandria, Louisiana, USA

Abstract

Purpose –The purpose of this paper is to provide a conceptual understanding of Big Data practices in

organizations, which will enable exploring the operational andstrategic roles of Big Data in organizational

performance.

Design/methodology/approach –Both academic andnon-academic literature studies on Big Data were

reviewed so as to capture what wasknown about Big Data practices. Qualitative interviews were conducted

with firm executives about Big Data practices in their organizations. Both literature review and interview

resultswere analyzed based on the dynamic capabilities perspective.

Findings –The analysis of the results suggeststhat Big Data capability develops when the resources parts

of Big Data and the skill and competencyparts are integrated and then grow into a dynamic capability.

Research limitations/implications –This study contributes to the literaturewith the concept of Big

Data capability thatbest characterizes Big Data practices in organizations.Validity of this concept should be

tested in empiricalstudies.

Originality/value –The development of the concept of Big Data capability helps to fill a gap in the

research literature that theoreticalunderstanding of big data practices is lacking or needs to be updated. It

motivatespractitioners to develop this capability so as to create and maintain theirstrategic advantage.

Keywords Big Data, Big Data capability, Thematic analysis, Organizational capabilities,

Dynamic capabilities, Knowledge management

Paper type Research paper

Introduction

In recent years, Big Data has become a buzzword. The power of Big Data in creating

business value was well documented in the popular and business press (Barton and Court,

2012;Carr, 2013;McAfee and Brynjolfsson,2012;Sanders, 2016). There is already a sizable

literature documenting how Big Data, in a technical sense, leads to efficient and effective

operations in business firms (Gunther et al.,2017). However, it remains less explored how

Big Data strategically works to enable thesepayoffs. This relates to a major concern in the

information systems (IS) strategy literature about our understanding of strategy in IS use

and implementation (Arvidsson et al.,2014;Henfridsson and Lind, 2014;Yeow et al.,2018).

To address this gap, an initial stepis to gain a deep understanding of Big Data practices and

then capture its strategicimplications conceptually.

In the strategy literature, a theoretical perspective explicating the interplayof resources

(for example, data in the case of Big Data), competencies (Big Data analytics)

(Ghasemaghaei et al.,2018), activities and processes (organizationalroutines in handling Big

Data) and its impact on performance is the theory of organizational capabilities.

Organizational successor failure can be attributed to their capabilities (Prahaladand Hamel,

Big data

practices

205

Received30 December 2018

Revised1 March 2019

Accepted26 March 2019

InternationalJournal of

Accounting& Information

Management

Vol.28 No. 2, 2020

pp. 205-222

© Emerald Publishing Limited

1834-7649

DOI 10.1108/IJAIM-12-2018-0154

The current issue and full text archive of this journal is available on Emerald Insight at:

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1990). In the case of Big Data initiatives, despite those success stories, there are reported

cases of disappointments (Nair and Narayana, 2012). Given these observations, the

organizational capabilities perspective can arguably provide direction for conceptualizing

Big Data. Indeed this perspective was used to investigate Big Data analytics as a dynamic

capability (Chen et al.,2015), but analytics is just the competency part of Big Data

(Ghasemaghaei et al.,2018). Besides analytics, other aspects of Big Data have also been

captured in the literature, such as new data characteristics(McAfee and Brynjolfsson, 2012;

Pigni et al.,2016), high tech (Esteves and Curto, 2013), an emerging profession (Davenport

and Patil, 2012) and data culture (Ross et al.,2013), among others. In IS research, it is viewed

as a breakthrough technological development (Fichman et al.,2014). Thus, the

conceptualizationof Big Data as a dynamic capability must cover all these identified aspects

as well. Moreover, considering this multiplicity, we tend to use the concept of dynamic

capability to cover all these aspects of Big Datathat may have already been well integrated

in organizationalpractices.

Conceptualizing Big Data as an organizational capability would also help to address

another gap existing in theorganizational capabilities literature. Prior researchprovided an

assortment of definitions and conceptual clarifications for organizational capabilities

(Fortune and Mitchell, 2012;Peteraf et al.,2013), explored their values and benefits

(Bingham et al.,2015;Collins, 1994;Drnevich and Kriauciunas, 2011) and, most importantly,

conceptually distinguished dynamic from operational capabilities (Drnevich and

Kriauciunas, 2011;Helfatand Winter, 2011). Yet, these studies only examined organizational

capabilities generally and thus mainly helped us to understand them conceptually. There

were rare cases of developing concepts of organizational capabilities from empirical

evidence in the literature,especially ones emerging from analysis of qualitative data.

To explore Big Data as an organizationalcapability based on empirical evidence can help

to fill these two gaps. Toward this goal, this study investigates Big Data practices in some

US firms across different industries.More specifically, we will interview business executives

about their perceptions, understandings and practices with regard to Big Data in their

organizations. This grounded theory inquiry will yield initial knowledge about

practitioners’understandings of and, more importantly, practicesof Big Data. Then, we will

connect this emergent knowledge to theory in an attempt to conceptualize Big Data

practices. This study will contribute to the literaturein two ways. First, it will help to gain

some theoretical understanding of Big Data by integrating its various aspects into a

unifying concept. Such a conceptaims to explain why some firms are successful in their Big

Data initiatives and why others experience failures. More extensively, it will help to renew

our understanding of IS strategy (Henfridsson and Lind, 2014).Second, it will contribute to

the organizational capabilities literature in that the newly developed concept of Big Data

practices that emerges from the analysis of first-hand interview data will help to test and

possibly extend currenttheoretical knowledge about organizational capabilities.

The rest of the paper is structured as follows. First, we will outline Big Data’s

contribution to organizationalperformance, review the theoretical literature of strategy and

connect it to Big Data. Then, we will detail the methodologyof gathering interview data and

present a thematic analysis of such data.Next, we will discuss the thematic analysis results

with regard to strategy theory and develop the concept of Big Data capability. Finally, we

will discuss its theoreticalimplications and future researchdirections.

Big Data and organizational effectiveness

In recent years, Big Data has represented a high point in the advancement of information

technology (IT). Its noted power has attracted attention from the popular press. The New

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