How big data analytics use improves supply chain performance: considering the role of supply chain and information system strategies

• DOI: https://doi.org/10.1108/IJLM-06-2020-0255
• Published date: 14 March 2022
• Date: 14 March 2022
• Pages: 620-643
• Subject Matter: Management science & operations,Logistics
• Author: Shaobo Wei,Jinmei Yin,Wei Chen

How big data analytics use

improves supply chain

performance: considering the role

of supply chain and information

system strategies

Shaobo Wei

School of Management, Hefei University of Technology, Hefei, China

Jinmei Yin

College of Economics and Management,

Nanjing University of Aeronautics and Astronautics, Nanjing, China, and

Wei Chen

University of Science and Technology of China, Hefei, China

Abstract

Purpose –Drawing on the dynamic capabilities theory, this paper proposes that supply chain (SC) strategies

(i.e. the lean SC and agile SC strategies) will mediate the relationship between big data analytics (BDA) and SC

performance. Furthermore, from the perspective of strategic alignment, this study hypothesizes that the effect

of the SC strategyon SC performance is differently moderated by the information system (IS) strategy (i.e. the IS

innovator and IS conservative strategies).

Design/methodology/approach –This study used 159 match-paired questionnaires collected from Chinese

firms to empirically test the hypotheses.

Findings –Results show the positive direct and indirect impact of BDA on SC performance. Specifically, the

lean and agile SC strategies mediate the relationship between BDA and SC performance. Furthermore, the

results indicate that the IS innovator and IS conservative strategies differentiallymoderate the effect of the lean

and agile SC strategies on SC performance. Specifically, the IS innovator strategy positively moderates the

effect of the agile SC strategy on SC performance. By contrast, the IS conservative strategy positively

moderates the effect of the lean SC strategy on SC performance but negatively moderates the effect of the agile

SC strategy on SC performance.

Originality/value –This study provides a comprehensive understanding of how SC and IS strategies can

help firms leverage BDA to improve SC performance.

Keywords Big data analytics, Supply chain performance, Lean supply chain strategy, Agile supply chain

strategy, IS innovator Strategy, IS conservative Strategy

Paper type Research paper

1. Introduction

In the past decade, big data gradually became an important factor for firms to gain a

competitive advantage and transform their business operations (Agarwal and Dhar, 2014;

Akter et al.,2016;M€

uller et al.,2018). Big data analytics (BDA)is defined as the use of advanced

technology to analyze big data to obtain useful information that can help firms predict and

make correct decisions across operational processes among internal and external partners

IJLM

33,2

620

This study was funded by the grants from the National Natural Science Foundation of China (72071190

and 71701194), High Level Personnel Project of Jiangsu Province (JSSCBS20210187), and the

Fundamental Research Funds for the Central Universities (2021CDJSKJC08). Shaobo Wei and Jinmei

Yin contributed equally to this manuscript.

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

https://www.emerald.com/insight/0957-4093.htm

Received 22 June 2020

Revised 15 April 2021

28 August 2021

26 November 2021

Accepted 11 February 2022

The International Journal of

Logistics Management

Vol. 33 No. 2, 2022

pp. 620-643

© Emerald Publishing Limited

0957-4093

DOI 10.1108/IJLM-06-2020-0255

(Chen et al.,2015;Mikalef et al.,2020). Over the years, scholarsrealized the importance of BDA,

and studies confirmed its impact on organization performance (Akter et al.,2016). However,

understandingof and empiricalresearch on the specificmechanisms that BDA can provideis in

the elementary stage (Mikalef et al.,2020). Particularly with the accelerating process of

globalization,firms are in a prominent position in the supplychain (SC), and SC management

(SCM) attracted the increasing attention of scholars and practitioners (Huo et al., 2014).

Moreover, information system (IS) scholars gradually shifted their attention to SCM (Akter

et al.,2016;Ghasemaghaei et al., 2018).In the current digital age, Chen et al. (2015) stated that

“SCM can also be conceptualized as a collection of digitally enabled inter-firm processes.”

Nevertheless,research exploring theimpact of BDA on SC performanceis scant (Gunasekaran

et al., 2017). Thus, revealing the underlying mechanism of how BDA can help firms attain

superior SC performance is necessary.

Furthermore, despite the first-mover advantage provided by the use of big data, a

previous industry survey showed that a sizeable number of firms are in a wait-and-see state

in terms of developing big data (Chen et al., 2015), as a majority of firms fail to stand out from

their competitors by using big data (Marr, 2016). A recent survey of 1,000 firms by Fortune

indicated that despite firms’enthusiastic use of big data, the final results varied considerably

(Bean, 2017). The results emphasized that the challenge for a firm using BDA to gain a

competitive advantage is not directly related to information technology (IT) but relevant to

the organizational nature, such as how to leverage BDA to support and shape strategies (Jeble

et al., 2018;Mikalef et al., 2020;Vidgen et al., 2017). Prior studies found that SC strategies play

an important role in improving SC performance (Qi et al., 2011;Tarafdar and Qrunfleh, 2017).

Previous research identified two major SC strategies, namely, the lean SC (LSC) strategy and

agile SC (ASC) strategy (Christopher and Towill, 2000;Yusuf et al., 2004). The difference

between the two strategies is that the LSC strategy emphasizesbalanced production planning

and cost reduction, whereas the ASC strategy focuses on rapid response and reconfiguration

(Qi et al., 2011). Thus, exploring whether BDA can be used to support and shape different SC

strategies to improve SC performance in SCM would be worthwhile. The use of BDA is a

process for deploying and integrating firm resources, and dynamic capabilities theory can

explain this dynamic process well (Gupta and George, 2016). Drawing on dynamic

capabilities theory, BDA can be regarded as a firm’s dynamic capability, which can optimize

SC processes and promote process coordination in SCM (Jeble et al., 2018;Dubey et al., 2018).

Therefore, extending existing studies, the present study argues that SC strategies may be an

important intermediate mechanism between BDA and SC performance from the perspective

of dynamic capabilities theory.

In addition, a group of scholars recognized the importance of IT strategies for gaining a

competitive advantage when developing business strategies (Kearns and Sabherwal, 2006;

Sabherwal and Chan, 2001). Previous studies highlighted the value of considering the

alignment of different strategies, such as IT and business strategies (Wade and Hulland,

2004). For most firms, the main purpose of investing in IT resources is to effectively support

the firm’s business strategies (Chen, 2012). Specifically, Tan and Gallupe (2006) stated that

the alignment of business and IS strategies can enable firms to maximize their IS investments

and achieve coordination with business strategies, thereby leading to improved profitability

and enhanced competitive advantages. Moreover, considering the necessity of IT for efficient

and effective knowledge management in the SC process, research investigating the strategic

alignment of the IS and SC level in the context of BDA is lacking (Liu et al., 2013). Thus, we

argue that exploring the moderating role of the IS strategy in the relationship between the SC

strategy and SC performance from the perspective of strategic alignment is necessary.

To this end, our research mainly seeks to answer three research questions. (1) How does

BDA improveSC performance? (2) How does theSC strategy mediate the relationship between

BDA and SC performance? (3) How doesthe IS strategy moderate therelationship between the

Role of big data

analytics

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