Determinants of big data analytics adoption in small and medium-sized enterprises (SMEs)
| DOI | https://doi.org/10.1108/IMDS-11-2021-0695 |
| Published date | 23 February 2022 |
| Date | 23 February 2022 |
| Pages | 278-301 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Parisa Maroufkhani,Mohammad Iranmanesh,Morteza Ghobakhloo |
Determinants of big data analytics
adoption in small and medium-
sized enterprises (SMEs)
Parisa Maroufkhani
Zhejiang University City College, The University of Waikato Joint Institute,
Hangzhou, China
Mohammad Iranmanesh
School of Business and Law, Edith Cowan University, Joondalup, Australia, and
Morteza Ghobakhloo
School of Economics and Business, Kaunas University of Technology,
Kaunas, Lithuania and
Graduate School of Business, Universiti Sains Malaysia, Penang, Malaysia
Abstract
Purpose –The study challenges the assumption of independence among Technological, Organizational and
Environmental (TOE) factors and investigates the influence of TOE factors on Big Data Analytics (BDA)
adoption among Smalland Medium Enterprises(SMEs). Top management support was proposed as a mediator
between technological and organizational factors and BDA adoption. Furthermore, the moderating effect of
environmental factors on the association between relative advantage, compatibility, competitiveness,
organizational readiness and BDA adoption was evaluated.
Design/methodology/approach –Data were collected from 171 SME manufacturing firms and analyzed
using the partial least squares technique.
Findings –The findings confirmed the interrelationshipsamong the TOE factors. The effects of compatibility,
competitiveness and organizational readiness on BDA adoption were mediated by top management support.
Furthermore, environmental factors moderate the influences of compatibility and organizational readiness on
top management support.
Originality/value –The findings contribute to the TOE model by challenging the assumption of
independence among TOE factors, and future studies should use this model with more caution and consider the
potential relationships between TOE factors.
Keywords TOE model, Big data analytics, Technology adoption, Environmental factors, Top management
support, Small and medium enterprises
Paper type Research paper
1. Introduction
In the recent digital age, Small and Medium-sized Enterprises (SMEs) use disrupting
technologies to nurture their businesses and progress their operational activities (Akpan
et al., 2020). The need for implementing digital technologies by SMEs has been intensified by
the digitalization race pushed by the fourth industrial revolution (Ghobakhloo and
Iranmanesh, 2021;Gupta et al., 2020). Digitalization delivers great chances and prospects
for enterprisers who lead and run SMEs to make a difference in the market and thereby
develop their business (Ching et al., 2022;Ghoabkhloo et al., 2021). There is a robust demand
to embrace emerging technologies in order to flourish faster and stay competitive with limited
monetary and non-monetary resources (El-Haddadeh et al., 2021;Pappas et al., 2021). Under
the Industry 4.0 phenomenon, emerging technologies, especially Big Data Analytics (BDA),
are flooring the SMEs’path by making them able to be more optimized (Liu et al., 2020;
Mangla et al., 2021;Sun et al., 2020). In particular, BDA can enable SMEs to move toward
servitization and adopt innovative business models. Currently, the revenue from BDA
IMDS
123,1
278
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 15 November 2021
Revised 19 January 2022
Accepted 30 January 2022
Industrial Management & Data
Systems
Vol. 123 No. 1, 2023
pp. 278-301
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-11-2021-0695
worldwide is estimated to be 215 billion USD and is expected to grow to over 270 billion USD
in 2022 (Statista, 2021). As an evolving technology that possibly increases operational,
strategic and other firms’performances, BDA is yet to recognize substantial rates of adoption
within the companies across different sectors and industries, particularly SMEs (Mikalef
et al., 2020). While the substantial function and applicability of BDA in SMEs and the vital
role of SMEs in the constant development of national economies have been shown by scholars
(Coleman et al., 2016;Liu et al., 2020), the adoption of such disruptive technology is practically
missing by SMEs (Liu et al., 2020;Maroufkhani et al., 2020). Recently, a few studies have been
evolved to empirically investigate the adoption of BDA within SMEs (Liu et al., 2020;Mangla
et al., 2021;Maroufkhani et al., 2020;Saleem et al., 2020). However, there is still a need for more
investigation on the role of emerging technologies (Youssef et al., 2022) and, particularly,
BDA on SMEs (Liu et al., 2020).
As such,this study precisely focuseson SMEs and their potentialprovocations foradopting
BDA as this is claimed that it is more remarkable for SMEs than for large organizations to
adopt and take advantage of BDAadoption (Dong and Yang, 2020). Apart from the need for
BDA implementation among SMEs, identifying the possible factors that may influence its
adoptionis a prerequisite for the valuedelivery of BDA usage (Maroufkhaniet al., 2020). Given
that, the Technological-Organizational-Environmental (TOE) modelhas gained more attention
from scholarsto explain the antecedents of technology adoption. TheTOE model argues that
TOE conditions play a critical role in shaping firms’decisions to adopt technology and that
each factoris independent of the other.This questionable assumptionmay have influenced the
findings of the previous studies on the determinants of BDA adoption among SMEs, which
leads to underestimating the role of factorsin technology adoption.
In this line, Chen et al. (2015) found that top management support mediates the effect of
competitive pressure and organizational readiness on BDA adoption. Top management
support as an independent variable takes the direct impact of organizational readiness and
competitive pressure on BDA adoption and may lead to biased findings. The insignificant
effect of competitive pressure and low impact of organizational readiness in the study of
Maroufkhani et al. (2020) on BDA adoption can be the consequence of considering top
management support as an independent variable. El-Haddadeh et al. (2021) confirmed the
effect of organizational and environmental aspects on top management support. In another
study, Lai (2018) found that environmental factors moderate the impacts of organizational
and technological factors on BDA adoption. Oliveira et al. (2019) found support for the
moderating effect of environmental factors in their study on Software-as-a-Service (SaaS)
adoption.
Against this backdrop, the present study challenges the assumption of independence
among TOE factors. This study proposes that the TOE factors should not be considered as
independent predictors of BDA adoption. The authors propose top management support
mediates the influences of technological and organizational factors on BDA adoption.
Further, the authors contend that environmental factors act as a moderator on the impacts of
technological and organizational factors on top management support. It is essential to
mention that within the present study, the BDA adoption level demonstrates the BDA usage
intensity. In summary, this study aims to address two objectives:
(1) To examine the mediating role of top management support in the relationship
between technological and organizational factors and BDA adoption.
(2) To investigate the moderating role of environmental factors on the effects of
technological and organizational factors on top management support.
The outcome of this research contributes to the literature on the TOE model by challenging
the assumption of independence among TOE factors. By testing the mediating impact of top
Determinants
of BDA
adoption in
SME
279
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