Management Decision
Identifying the Configurational Conditions for Marketing
Analytics Use in UK SME
Journal:
Management Decision
Manuscript ID
MD-07-2020-0945.R1
Manuscript Type:
Original Article
Keywords:
marketing analytics, configurations, small to medium-sized enterprises,
fsQCA, conditions
Management Decision
Management Decision
ABSTRACT:
While marketing analytics can be used to improve organizational decision-making and performance
significantly, little research exists to examine how the configurations of multiple conditions affect
marketing analytics use. This study draws on configuration theory to investigate marketing analytics
use in small and medium-sized enterprises (SMEs).
This research employs fuzzy set qualitative comparative analysis using data collected from a survey
of 187 managers in UK SMEs.
The key findings show that (1) configurations of multiple conditions provide alternative pathways to
marketing analytics use; and (2) the configurations for small firms are different from those for
medium-sized firms.
The research results are based on several key configurational factors and a single key-informant
method to collect subjective data from UK SME managers.
The study helps SMEs to understand that marketing analytics use is influenced by the interaction of
multiple conditions, that there are alternative pathways to marketing analytics use, and that SMEs
should choose the configuration that fits best with their organizational contexts.
CUST_SOCIAL_IMPLICATIONS_(LIMIT_100_WORDS) :No data available.
The study contributes to the literature by addressing an important yet under-researched area, i.e.
marketing analytics use in SMEs, applying a configurational approach to the research phenomenon.
It highlights different pathways to marketing analytics use in SMEs. The findings provide empirical
evidence on the possibility and implication of marketing analytics use being asymmetrical and
different between small and medium-sized firms.
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Identifying the Configurational Conditions for Marketing
Analytics Use in UK SMEs
Abstract
Purpose – While marketing analytics can be used to improve organizational decision-making
and performance significantly, little research exists to examine how the configurations of
multiple conditions affect marketing analytics use. This study draws on configuration theory
to investigate marketing analytics use in small and medium-sized enterprises (SMEs).
Design/methodology/approach – This research employs fuzzy set qualitative comparative
analysis using data collected from a survey of 187 managers in UK SMEs.
Findings – The key findings show that (1) configurations of multiple conditions provide
alternative pathways to marketing analytics use; and (2) the configurations for small firms are
different from those for medium-sized firms.
Research limitations/implications – The research results are based on several key
configurational factors and a single key-informant method to collect subjective data from UK
SME managers.
Practical implications – The study helps SMEs to understand that marketing analytics use is
influenced by the interaction of multiple conditions, that there are alternative pathways to
marketing analytics use, and that SMEs should choose the configuration that fits best with their
organizational contexts.
Originality/value – The study contributes to the literature by addressing an important yet under-
researched area, i.e. marketing analytics use in SMEs, applying a configurational approach to
the research phenomenon. It highlights different pathways to marketing analytics use in SMEs.
The findings provide empirical evidence on the possibility and implication of marketing
analytics use being asymmetrical and different between small and medium-sized firms.
Keywords: marketing analytics, conditions, configurations, small to medium-sized enterprises,
fsQCA
Introduction
Marketing analytics is a subset of business or big data analytics. It pertains to the collection,
management, and analysis of data to extract useful insights to support marketing decision-
making (Wedel and Kannan, 2016, Cao et al., 2019). Extant empirical research indicates that
firms can use marketing analytics to improve marketing decision-making and firm
competitiveness significantly, inter alia (e.g., Dremel et al., 2020, Cao et al., 2019). However,
although firms are increasingly utilizing analytics for data-driven insights, and there has been
a substantial amount of academic research into business analytics and its impact on
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Management Decision
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organizations, understanding the conditions required for utilizing business analytics remains
an important gap in the literature (Trieu, 2017, Mikalef et al., 2020) and deserves further
investigation (Ghasemaghaei, 2019).
In particular, while there is indication that some SMEs (fewer than 250 employees) are
benefiting from their analytics investment, there is a dearth of empirical research examining
the use of business analytics and its effect on the performance of SMEs (e.g., Maroufkhani et
al., 2020, Liu et al., 2020, Wang et al., 2018), despite the fact that SMEs are the backbone of
national economies such as the UK, where SMEs account for more than 99.7% of all enterprises
and employ 54% of the workforce (Papadopoulos et al., 2020).
Hence, this research aims to address this gap and advance our understanding of
marketing analytics use in SMEs by examining two research questions: What configurations
of multiple conditions are likely to lead to marketing analytics use? and Do configurations of
multiple conditions that lead to marketing analytics use differ between small and medium-sized
firms?
This study addresses these two questions using a research design that is conceptually
underpinned by configuration theory (Woodside, 2013, Fiss, 2011) and methodologically
based on fuzzy-set qualitative comparative analysis (fsQCA) (Ragin and Davey, 2016). Most
studies examining the factors that affect analytics use have employed conventional statistical
methods to test causality, but Woodside (2013) argues that these methods are often less
proficient at handling multi-faceted interdependencies between variables because these
methods are typically based upon linear and symmetric relationships between variables of
interest. This research argues that an outcome of interest, that is, marketing analytic use, seldom
has a single cause but is best explained through multi-causality conditions; and that causes are
interdependent rather than operating in isolation. Thus, configurational approach is seen to
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offer the possibilities of understanding how the multiple conditions combine into
configurations to lead to equifinal pathways to marketing analytics use.
Drawing on configuration theory and analytics studies that adopted configurational
approach (e.g., Park et al., 2017, WangKung et al., 2019), this study develops and tests a
research model linking the configurations of multiple conditions to marketing analytics use.
Built on prior studies, the conditions included in this study are those that are seen to be
important antecedents to analytics applications, including managerial perception (Kearns and
Sabherwal, 2007), managerial support (Chen et al., 2015, Liang et al., 2007), data availability
(Gupta and George, 2016), competitive pressure (Liang et al., 2007), and organizational
readiness (Iacovou et al., 1995, Chen et al., 2015).
Accordingly, this paper adopts fsQCA to handle the complex interdependencies
between variables (Fiss, 2007, Woodside, 2013). Additionally, to extend the idea that firm size
impacts information system (IS) investment and adoption patterns (e.g. Gillon et al., 2014,
Thong et al., 1996, Dong and Yang, 2020), this study argues that small (fewer than 50
employees) and medium-sized firms (50 to 249 employees) may each have distinctive
configurations of causal conditions, thereby affecting their marketing analytics use.
This study thus contributes to the under-researched marketing analytics use in SMEs.
By suggesting that marketing analytics use is affected by the configurations of multiple
conditions, this study applies configuration theory with marketing analytics research to develop
a better understanding of marketing analytics use in SMEs. Moreover, by showing that the
configurations for small firms are different from those for medium-sized firms, this research
challenges the traditional way of examining SMEs as one homogeneous group, and suggests
that it might be more pertinent to investigate small and medium-sized firms as heterogeneous
clusters to understand their adoption patterns of marketing analytics.
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