Understanding cloud computing success and its impact on firm performance: an integrated approach
| Date | 29 March 2020 |
| Pages | 963-985 |
| Published date | 29 March 2020 |
| DOI | https://doi.org/10.1108/IMDS-06-2019-0327 |
| Author | Abul Khayer,Yukun Bao,Bang Nguyen |
| 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 |
Understanding cloud computing
success and its impact on firm
performance: an
integrated approach
Abul Khayer and Yukun Bao
Center for Modern Information Management, School of Management,
Huazhong University of Science and Technology, Wuhan, China, and
Bang Nguyen
Department of Entrepreneurship and Relationship Management,
University of Southern Denmark, Odense, Denmark
Abstract
Purpose –This study aims to investigate the determinants of successful implementation of cloud computing
and, further, examines how cloud computing success influences firm performance.
Design/methodology/approach –The authors developed a con ceptual framework bas ed on the
integration of severa l strands of literature in business studies and in formation systems. To te st the
proposed model, data we re collected from 300 Chi nese firms which have ado pted cloud computing . To
analyze the data, partial least squares structural equation modeling (PLS-SEM) was used. An importance-
performance map anal ysis (IPMA) was also co nducted to identify t he critical factors t hat exhibit high
importance but low perf ormance.
Findings –The results of the study revealed that end-user satisfaction, information quality, system quality,
managerial information technology (IT) capability and technical IT capability significantly affect cloud
computing success. Additionally, cloud computing success has a strong and positive impact on firm
performance. IPMA further confirms that managers need to concentrate more on system quality, information
quality, user satisfaction and technical IT capability.
Originality/value –This paper is one of the few attempts to integrate several theoretical frameworks (i.e. IT
capabilities andresource-based view, expectation-confirmation theory, and information system success theory)
to develop a comprehensive model for understanding the key determinants of cloud computing success and its
impact on firm performance. This study makes a useful contribution to the conventional information systems
(IS) literature and IT management practice.
Keywords Cloud computing, Cloud success, Firm performance, Expectation- confirmation model (ECM),
Information system success model, IT capability, Resource-based view (RBV)
Paper type Research paper
1. Introduction
Cloud computing is a deep revolution in delivering information technology based services
using the ideas of distributed and parallel computing (Naseri and Jafari Navimipour, 2019). It
offers a remotely accessible environment for sharing and accessing various computing
resources such as remote servers, storage spaces and network service applications with high
reliability, dynamicity and scalability (Ebadi and Jafari Navimipour, 2019;Park and Ryoo,
2013). In general, cloud computing offers four service types, namely Software as a Service
(SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and Expert as a Service
(EaaS) on a rental basis (Asghari and Navimipour, 2018). Cloud computing offers
organizations and users convenient access to powerful computing through the network at
minimal cost (Marston et al., 2011;Sheikholeslami and Navimipour, 2017). The proper
Understanding
cloud
computing
success
963
This work was supported by the National Natural Science Foundation of China [71810107003].
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 20 June 2019
Revised 21 September 2019
15 February 2020
Accepted 25 February 2020
Industrial Management & Data
Systems
Vol. 120 No. 5, 2020
pp. 963-985
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-06-2019-0327
deployment of cloud computing adds value in both strategic (e.g. increasing annual revenue)
and operational (e.g. minimizing operational cost) levels of an organization (Carcary et al.,
2014). Cloud computing can help converge information technology (IT) efficiency and
business agility of firms (Oliveira et al., 2014). The means of achieving IT efficiency include
utilizing scalable IT resources (Marston et al., 2011), improving efficiency in work (Low et al.,
2011) and ensuring high availability of services (Armbrust et al., 2010). On the other hand, the
business agility associated with cloud computing includes the capacity of deploying mass
computing technology quickly, minimizing capital cost directly and responding rapidly to
market changes (Oliveira et al., 2014). Therefore, cloud computing has been widely adopted
among firms that desire to deploy IT resources which can be purchased as a service.
Realizing the potentials of cloud technology, information systems (IS) scholars have
started to explore the adoption and usage behavior of cloud computing by applying various
models/theories such as the technology acceptance model (TAM), innovation diffusion theory
(IDT), the technology-organization-environment (TOE) framework and the unified theory of
acceptance and use of technology (UTAUT) model (Alkhater et al., 2018;Low et al., 2011;
Oliveira et al., 2014). It has been argued that these theories are valuable to understand
preliminary adoption of an IS, but may not be effective for examining the post-adoption
success of an IS (Hasan et al., 2019;Veeramootoo et al., 2018). For example, Garrison et al.
(2012) argued that initial adoption and successful deployment of cloud computing are two
theoretically distinct concepts and are affected by diverse sets of determinants. Garrison et al.
(2015) measured the impact of IT capability on firm performance according to different cloud
delivery models. However, that study can be criticized for not using a comprehensive model.
Those authors only examined the internal IT capability dimension, failing to consider other
factors which could impact on the success of cloud implementation. The successful
implementation and deployment of any information system depends on the quality of the
system, organizational IT capability and positive feedback from end-users. Moreover, despite
confirmation of the positive relationship between IS success and firm performance in the
existing literature, assessments of the effects of cloud computing success on performance are
lacking (Nagpal and Lyytinen, 2010). Thus, it is a worthy agenda for contemporary research
to investigate the critical factors affecting the successful implementation of cloud computing.
Therefore, this study attempts to bridge the gap in the literature by proposing an
integrated model that combines factors from technology quality (IS success model), IT
capabilities (resource-based theory) and user experience (expectation-confirmation model).
This study aims to answer the following research questions:
RQ1. What are the determinants of cloud computing success?
RQ2. What is the impact of cloud computing success on firm performance?
RQ3. What are the most critical factors that need special managerial attention to improve
their performance?
To test the research model, data were collected from 300 Chine sefir ms which have adopted cloud
services. The first two questions were examined w ith the use of structural equation modeling
(SEM), and the third question was assessed by using importance-performance map analysis
(IPMA). The research findings will assist managers and practitioners in developing or adjusting
their strategies pursuant of optimizing the i mplementation and deployment of cloud computing.
2. Theoretical foundations
2.1 IT capabilities and resource-based view (RBV)
The resource-based view (RBV) is a theory which conceptualizes firms as an assortment of
resources and capabilities essential for product or market competition that can be used to
IMDS
120,5
964
To continue reading
Request your trial