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2014

GAINING COMPETITIVE ADVANTAGE FROM ANALYTICS THROUGH THE MEDIATION OF DECISION-MAKING EFFECTIVENESS: AN EMPIRICAL STUDY OF UK MANUFACTURING COMPANIES Guangming Cao University of Bedfordshire, Luton, United Kingdom, guangming.cao@beds.ac.uk

Yanqing Duan University of Bedfordshire Luton, United Kingdom, yangqing.duan@beds.ac.uk

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Recommended Citation Cao, Guangming and Duan, Yanqing, "GAINING COMPETITIVE ADVANTAGE FROM ANALYTICS THROUGH THE MEDIATION OF DECISION-MAKING EFFECTIVENESS: AN EMPIRICAL STUDY OF UK MANUFACTURING COMPANIES" (2014). PACIS 2014 Proceedings. 377. http://aisel.aisnet.org/pacis2014/377

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GAINING COMPETITIVE ADVANTAGE FROM ANALYTICS

THROUGH THE MEDIATION OF DECISION-MAKING

EFFECTIVENESS: AN EMPIRICAL STUDY OF UK

MANUFACTURING COMPANIES

Cao, Guangming, University of Bedfordshire, Luton, UK, guangming.cao@beds.ac.uk

Duan, Yanqing, University of Bedfordshire, Luton, UK, yangqing.duan@beds.ac.uk

Abstract

While it is widely believed that analytics capabilities enable a company to identify valuable insights

from big data thereby to improve the effectiveness of decision-making and to gain competitive

advantage, little empirical research has been undertaken to investigate the mechanisms through

which analytics capabilities improve decision-making effectiveness and organisational

competitiveness. This paper aims to reduce this research gap in the literature. Drawing on the

resource-based view (RBV), it develops a research model to specify the interrelationships among

information processing capabilities, resource heterogeneity, decision-making effectiveness, and

competitive advantage. It then empirically tests the proposed model using structural equation

modelling based on 232 responses collected from UK manufacturing companies. This paper has made

several contributions to the research and practice of business analytics and decision-making. First, it

advances the literatures by conceptually developing and empirically testing a path model linking

information processing capabilities to decision-making effectiveness and competitive advantage.

Second, it advances our knowledge by clarifying and testing the mediating role of decision-making

effectiveness in affecting the relationship between information processing capabilities and competitive

advantage. Third, it extends the RBV and decision-making literatures by explicating and testing the

mediating role of resource heterogeneity in affecting the relationship between information processing

capabilities and competitive advantage, and between information processing capabilities and

decision-making effectiveness. Finally, this paper contributes to managers’ and business analytics

practitioners’ knowledge by demonstrating the importance of improving decision-making

effectiveness in gaining competitive advantage.

Keywords: Information processing capability, Decision making effectiveness, Resource heterogeneity,

Competitive advantage, Mediating role, Questionnaire survey

mailto:guangming.cao@beds.ac.uk mailto:yangqing.duan@beds.ac.uk

1 INTRODUCTION

In order to compete successfully in the context of digitalisation, it is essential for contemporary

business organisations to be able to address the unprecedented challenges posed by big data that is

characterised by high volume, high velocity of generation and transmission, and a large variety of data

and file type. While a number of business analytics (BA) studies (Davenport et al. 2001, Davenport et

al. 2010, Davenport 2013, Kiron and Shockley 2011, Kiron et al. 2012, Lavalle et al. 2011) suggested

that companies with advanced analytic capabilities can derive valuable insights from big data, thereby

to make effective decisions and to gain competitive advantage; “many companies are still struggling

to figure out how, where and when to use analytics” (Kiron et al. 2012, p.17), or “unsure how to

proceed” (Barton and Court 2012, p.97), or “struggling to achieve a worthwhile return” (Marchand

and Peppard 2013, p.105).

Since BA is still emerging as an important area of research, there are only a few empirical studies in

the literature. To help business organisations understand the challenges and opportunities associated

with the use of BA, MIT Sloan Management Review conducted three large scale questionnaire surveys

consecutively; two of them were jointly with IBM Institute for Business Value and one with SAA

Institute Inc. (Kiron and Shockley 2011, Kiron et al. 2012, Lavalle et al. 2011). These surveys were

typically based on responses collected from more than 2,500 executives, managers, and analysts

working across more than 30 industries and 100 countries. The finding from the 2010 survey

indicated that there is an emerging performance gap between companies that use BA and those that do

not (Lavalle et al. 2011), and this divide becomes larger and rapidly widening based on the findings of

the 2011 survey (Kiron and Shockley 2011). The findings from the latest survey suggested that

companies using BA to compete and innovate are characterised by believing data being a core asset to

enhance business operations, effective use of data for faster results, and supports for analytics by

senior managers; consequently, they are much more likely to be able to make effective decisions and

create a competitive advantage (Kiron et al. 2012).

These studies have highlighted the importance of using BA to compete and innovate, together with a

number of recommendations made for leveraging analytic capabilities to improve organisational

performance. However, they did not reveal the specific mechanisms through which for example

analytic capabilities are related to effective decision-making and competitive advantage as no

inferential analyse was conducted; nor did other BA studies since little empirical research exists in

this emerging research area based on our literature review.

This paper therefore aims to reduce this research gap by focusing on examining the interrelationships

among analytics capabilities, decision-making effectiveness, and competitive advantage. Drawing on

the resource-based view (RBV) and relevant empirical studies in other research areas, this paper will

develop a path model to specify the links among these variables. It then empirically tests the proposed

path model using structural equation modelling based on data collected from 232 UK manufacturing

companies. The structure of the paper is as follows. The next section presents the conceptual research

model and hypotheses. The subsequent section describes the instrument development and the data

collection processes and reports on the empirical results. The final section discusses the results and

implications.

2 THEORETICAL DEVELOPMENT

2.1 Key Concepts Defined

Before developing our theoretical model, we clarify two key concepts to be used in this research:

information processing capabilities and decision-making effectiveness. Information processing

capabilities/capacities were used by Galbraith (1974) without definition in 1974 to outline the

information processing view of organisational design. These terms were adopted by Tushman and

Nadler (1978, p.614) in 1978 to further develop the information processing view of organisational

design, while information processing was defined as “the gathering, interpreting, and synthesis of

information in the context of organizational decision making”. Building upon the information

processing view (Galbraith 1974), Premkumar et al. (2005, p.266), defined information processing

capability as “the level of IT support for various activities” to refer to similar notions when they

examined the fit between information processing needs and information processing capability and its

effect on performance in an inter-organisational supply chain context