Determinants of cloud ERP adoption in Jordan: an exploratory study

Full text

204
I
nt. J. Business Information Systems, Vol. 34, No. 2, 2020
Copyright © 2020 Inderscience Enterprises Ltd.
Determinants of cloud ERP adoption in Jordan:
an exploratory study
Mannam Zamzeer*, Yazan Alshamaileh,
Hamad Iqab Alsawalqah, Malak Al-Hassan,
Esraa Jalal Abu Fannas and
Sara Sameer Almubideen
King Abdullah II School of Information Technology,
The University of Jordan,
P.O Box 11942, Amman, Jordan
Email: mzamzeer@ju.edu.jo
Email: y.shamaileh@ju.edu.jo
Email: h.sawalqah@ju.edu.jo
Email: m_alhassan@ju.edu.jo
Email: esraa_abufannas@outlook.com
Email: sara_almubideen@hotmail.com
*Corresponding author
Abstract: Enterprise resource planning (ERP) systems are usually adopted
through two major options: cloud computing or on-premise infrastructure. The
issues related to hardware, servers, implementation costs, and facilities, which
are necessary to run on-premise ERP systems, are rather great for small and
mid-sized enterprises (SMEs). The purpose of this research is to highlight the
factors influencing cloud ERP adoption among SMEs. The technological,
organisational, and environmental (TOE) model will be used as a theoretical
base. This qualitative, exploratory study gathers data from 13 different SMEs
and cloud ERP service providers through semi-structured interviews, focusing
on SMEs in Jordan. According to our results, support from both service
providers and top management within the company play an important role in
whether a firm adopts cloud ERP services, in addition to a number of other
factors at varying rates. Research findings can be used by service providers and
business owners to enhance their approach to cloud ERP by showing the
reasons why some SMEs chose to adopt this technology and others did not.
Cloud ERP providers need to intensify their efforts to build a progressive
environment for their services that will eliminate any ambiguity regarding this
type of technology.
Keywords: cloud; enterprise resource planning; ERP; TOE framework; Jordan;
small and mid-sized enterprises; SMEs; information and communication
technologies; ICT.
Reference to this paper should be made as follows: Zamzeer, M.,
Alshamaileh, Y., Alsawalqah, H.I., Al-Hassan, M., Fannas, E.J.A. and
Almubideen, S.S. (2020) ‘Determinants of cloud ERP adoption in Jordan: an
exploratory study’, Int. J. Business Information Systems, Vol. 34, No. 2,
pp.204–228.

Determinants of cloud ERP adoption in Jordan 205
Biographical notes: Mannam Zamzeer is an Associate Professor in Computer
Integrated Manufacturing. KASIT College, The University of Jordan. He is
holding a PhD in the field of Manufacturing Computerisation. He wrote many
books in this field and published a number of papers in reputable journals.
Yazan Alshamaileh is an Assistant Professor at the King Abdullah II School for
Information Technology, The University of Jordan. He received his BSc in
Computer Information Systems from the Mu’tah University, Jordan, followed
by MSc in Business Information Technology from the Northumbria University,
England. In 2013, he has been awarded his PhD in e-Business from the
University of Newcastle, UK. He specialises in cloud computing, and consumer
behaviour, as well as Information and communication technology innovation
adoption in the small and medium sized enterprises.
Hamad Iqab Alsawalqah is currently working as an Assistant Professor at the
Department of Computer Information Systems, The University of Jordan,
Amman, Jordan. He received his BS in Computer Information Systems from
the University of Jordan, in spring 2004. He received his MA in Management
Information Systems from the Amman Arab University for Graduate Studies,
Jordan, in spring 2006. In summer 2008, he received his second MA in
Software Engineering from the Korea Advanced Institute of Science and
Technology (KAIST). From August 2006, he was a member of Global IT
Technology program at KAIST until August 2008. He received his PhD in
Information and Communications Engineering, Software Engineering from the
KAIST in 2014. His research interests are in software product lines, product
management, project management and bug prediction.
Malak Al-Hassan is currently working as an Assistant Professor at the
Department of Business of Information Technology, the University of Jordan,
Amman, Jordan. She received her Bachelor’s and Master’s of Computer
Science from the Yarmouk University and Jordan University of Science and
Technology, respectively. She was a Lecturer in the Hashemite University,
Jordan from 2006–2007. She completed her PhD in Computer Information
Systems at the University of Technology, Sydney Australia in 2014. She was a
member of the Decision Systems and e-Service Intelligence Lab in the Centre
for Quantum Computation and Intelligent Systems, University of Technology,
Sydney, from 2009–2014. Her research interest includes intelligent e-services,
e-government services, web personalisation, recommendation systems,
semantic web and ontology.
Esraa Jalal Abu Fannas is currently a graduate student in the University of
Jordan. She received her BSc in Business Information Technology at the
University of Jordan in 2016. She was working as a Research Assistant in the
Department of Business Information Technology, in the University of Jordan
after her graduation. Her current research interests include real-time embedded
systems, programming languages and pattern recognition.
Sara Sameer Almubideen is currently a graduate student in the University of
Jordan. She received her BSc in Business Information Technology at the
University of Jordan in 2016. She was working as a Research Assistant in the
Department of Business Information Technology, in the University of Jordan
after her graduation. Her main interests are in software management and
could-based systems.

206
M
.
Z
amzee
r
et al.
1 Introduction
The use of information and communication technologies (ICTs) is widespread among
businesses of all sizes. Due to the fast development of ICTs, integrating traditional
enterprise resources planning (ERP) systems with cloud services has become a topic of
emerging importance. Cloud ERP is a blend of standard ERP services with the flexibility
and low cost of cloud services. The flexibility of cloud-based services has played a main
role in shifting ERP system solutions into cloud platforms (Gupta et al., 2018). Cloud
ERP is a breakthrough in enterprise service because it is considered to be scalable,
adaptable, cost-effective, and efficient (Raihana, 2012; Sharma and Keswani, 2014).
Mohammadkazem et al. (2016) believe that ERP systems can help small and mid-sized
enterprises (SMEs) overcome their limitations. The low costs and availability of new
functions provided by cloud ERP increase user satisfaction as well as their willingness to
continue using it (Chauhan and Jaiswal, 2015). ERP implementation affects the
organisation on several levels, including processes, people, and culture; thus, some
challenges may be encountered when adopting this system (Ranjan et al., 2016). Cloud
computing in Jordanian SMEs became a necessary and applicable step in the evolution of
information technology (IT). Jordan is developing strong ICTs with the vision of
becoming a knowledge-based country and a territorial IT centre (Al-Hujran and
Al-Dalahmeh, 2011). Previous research showed that educated and innovative Jordanians
in small businesses are early adopters of the internet and new innovations, which
indicates the new generation’s willingness to adopt new technology (Al-Jaghoub and
Westrup, 2013). The aim of this research is to explore the cloud ERP adoption process by
SMEs in Jordan. Our research questions are intended to define the factors that affect the
decision-making of Jordanian SMEs concerning the adoption of cloud ERP.
2 Background
2.1 ERP systems
ERP systems are enterprise-wide information system packages that contain a
comprehensive set of software modules that aim to integrate all key business processes
across various functional departments of an organisation by using a single data repository
(Bernroider and Koch, 2001). ERP systems contain different functional modules that
reflect the divisional structure of a company (e.g., accounting, procurement, sales,
production, warehousing, and human resources (Staehr, 2010). They are often modified
for a particular industry or vertical solution through significant customisations to fulfil
the unique requirements of each company as well as integration with other packages
(Schubert and Adisa, 2011). Based on the information perspective, ERP system adoption
can improve the interaction between business functions by making information more
accessible (Shaul and Tauber, 2012). Douglas et al. (2016) state that technological
advancements enable SMEs to purchase a plug-and-play model for traditional ERP
solutions. Research such as Utzig et al. (2013) and FossoWamba et al. (2016) view ERP
solutions as more effective for SMEs than large enterprises. FossoWamba et al. (2016)
believe that SMEs can benefit from ERP privileges without the need to install IT
hardware.

Determinants of cloud ERP adoption in Jordan 207
Zouaghi and Laghouag (2016) offer in their paper an overview of the main factors
that can help with successful ERP implementation as well as a framework analysis for
these factors based on implementation strategies. Some research such as Chakravorty
et al. (2016) pinpointed escalation of commitment as one of the main reasons for ERP
implementation failure. In their paper, Schubert and Adisa (2011) say that ERP systems
are complex; implementing a system can be a difficult, time-consuming, and expensive
project for a company. To better tackle these obstacles, cloud ERP has been introduced as
a new technology by big cloud providers. The cloud enables companies to surpass all
obstacles related to data exchange, especially with interorganisational systems. SMEs
only have to download a software application onto a computer to start receiving a cloud
ERP service from a provider. But first, SMEs must have a strong network so they can use
cloud ERP systems efficiently (Albar and Hoque, 2015). Although the use of cloud ERP
is becoming common in developed countries, it is still rather unknown in the Middle East
(AlBar and Hoque, 2015). Using cloud ERP is an essential and logical upgrade for
businesses. Cloud ERP is considered to be a major advancement for firms, because it
enables organisations to expand easily, reduce costs, and avoid unnecessary staff hiring
(Raihana, 2012). Some SMEs already have ERP systems on their premises, but they
chose to use hybrid solutions in which only certain parts are used on the cloud (AlBar and
Hoque, 2015). Pareek (2014) has compared almost all aspects of traditional ERP systems
with cloud ERP systems. He found that the cost of traditional ERP implementation is
higher than cloud ERP implementation, and the flexibility of cloud ERP assures
competitive advantages to certain SMEs. Weng and Hung (2014) specify the following
reasons why SMEs choose to adopt cloud ERP systems:
• The cost of purchasing servers and hiring IT specialists can be avoided.
• Cloud ERP is less complicated than on-premise ERP or legacy systems.
• Organisations that have complicated ERP systems want easier and more cost-
effective technology.
• Top managers do not want to pay for ERP systems.
Even though cloud ERP systems reduce costs and make smarter use of scarce IT
resources to promote a focus on driving innovation (Weng and Hung, 2014), the number
of SMEs that have adopted cloud ERP is still low, potentially because of the limited
resource concerns (Salim, 2015). Moreover, Saeed et al. (2012) pointed out the
challenges of cloud ERP implementation, such as anticipated benefits, integration,
customisation, and system performance in the organisational background.
2.2 Theoretical foundations: the TOE framework
Depietro et al. (1990) established the technological, organisational, and environmental
(TOE) framework. The authors divide the factors that influence organisations’ decisions
to adopt new technologies into three context groups: TOE. The technological aspect is
defined as the technologies available to an organisation and the current state of
technology in the organisation (Low et al., 2011); it also refers to the technological
characteristics that precede any adoption decisions: relative advantage, complexity,
compatibility, observability, and trialability (Low et al., 2011). The organisational aspect
describes the characteristics of an organisation, such as firm size and scope,

208
M
.
Z
amzee
r
et al.
centralisation, formalisation, complexity of managerial structure, and the quality of
human resources (Low et al., 2011). The environmental context refers to the external
environment of the organisation, such as the industry, competitors, and government
policies or intentions (Low et al., 2011). The comprehensiveness of this theory makes it
viable for widespread use in analysing the factors affecting the adoption of IT
innovations such as cloud computing, electronic business, and ERP (Palacios-Marqués
et al., 2015). These factors play a pivotal role when considering adopting any
technological innovation and can act either as a constraint or opportunity for
organisations (Depietro et al., 1990). The TOE factors that affect cloud ERP adoption are
explained in the following section. Definitions of the TOE framework are shown in
Table 1.
Table 1 Definitions of the TOE framework abbreviations and acronyms
Organisational
Firm size Refers to the number of employees in the company.
Top
management
support
Refers to ‘devoting time to the [IS] program in proportion to its cost
and potential, reviewing plans, following up on results and facilitating
the management problems involved with integrating ICT with the
management process of the business’ [Young and Jordan, (2008), p.3]
Innovativeness Refers to ‘the tendency or orientation, either innate or acquired, to
adopt innovations’ [Marcati et al., (2008), p.2]
Cost Refers to the financial benefit received such as and effect in CAPEX
and OPEX (Bernroider and Koch, 2001).
Prior IT
experience
Refers to the degree of experience an individual has with technology
resembling the one being adopted and experience in the field (Heide
and Weiss, 1995; Lippert and Forman, 2005).
Environmental
Competitive
pressure
Refers to ‘the degree of pressure felt by the firm from competitors
within the industry’ (Oliveira and Martins, 2010).
Industry Refers to ‘the sector to which an organisation belonged’ (Zhu et al.,
2003).
Market scope Refers to ‘the horizontal extent of a firm’s operations’ (Zhu et al.,
2003).
Supplier efforts Refers to a supplier’s efforts to communicate.
Technological
Relative
advantage
Refers to ‘the degree to which an innovation is perceived as being
better than the idea it supersedes’ (Rogers, 2010).
Uncertainty Refers to ‘the degree to which the clients are uncertain about the
clouds’ privacy, security, and efficiency’ (Rogers, 2010).
Compatibility Refers to ‘the degree to which an innovation is perceived as consistent
with the existing values, past experiences, and needs of potential
adopters’ (Rogers, 2010).
Complexity Refers to ‘the degree to which an innovation is perceived as relatively
difficult to understand and use’ (Rogers, 2010).
Trialability Refers to ‘the degree of training provided to enable effective and
efficient software usage’ (Rogers, 2010).
2.2.1 Technological context
The technological part of the TOE structure depicts both the inward and outside
significant advancements to the firm (Oliveira and Martins, 2011; Rui, 2007). Premkumar

Determinants of cloud ERP adoption in Jordan 209
(2003) has made it clear that an insufficient number of studies have examined the effect
of technological attributes on the adoption of IT innovation. We will examine the impact
of the TOE factors using Rogers’ creation. As indicated by Stuart (2001), Rogers’
hypothesis is popular in the field of innovation dissemination.
Technological factors are considered the primary and most influential elements that
affect the adoption of IT innovations (Aboelmaged, 2014). The elements related to the
technological aspect are briefly explained below.
• Relative advantage
Relative advantage is considered a key factor in the adoption of new IT innovations.
It has been proven that when businesses perceive a relative advantage in an
innovation, they are likely to adopt that innovation (Lee, 2014; Thong, 1999; Thong
et al., 1994). Organisations can achieve relative advantages by using IT to improve
information flow across the organisation, reduce costs, streamline business
processes, offer product variety, open communication channels with suppliers, and
reduce response time (Beheshti, 2006). Cloud computing can enhance capacity,
reliability, and flexibility (Miller, 2008).
• Uncertainty
Uncertainty refers to a lack of knowledge about a certain innovation, which can
generate doubts regarding any alleged results (Alshamaila et al., 2013). Uncertainty
is usually high regarding innovations with relatively short lifespans (Alshamaila
et al., 2013). Security and privacy are considered common concerns businesses have
when considering cloud computing adoption (Aziz, 2010). In their research, Dwivedi
and Sharma (2016) conclude that some companies have concerns about the
ambiguity of outsourcing ERP services over the cloud while others are worried about
safety issues. They also are focused on the risks that come with moving to the cloud.
These uncertainties can act as barriers to SMEs’ decision to adopt cloud services
until they are resolved (Alshamaila et al., 2013). Companies must ensure high-level
security for the storage and processing of data, whether they decide to adopt ERP on
a cloud or maintain the system on their premises.
• Compatibility
Many studies have discussed the importance of compatibility and have considered it
a key determinant for adopting new IT (Ching and Ellis, 2004; Daylami et al., 2005;
Premkumar, 2003; Premkumar and Roberts, 1999; Rogers, 2010; Teo et al., 1997;
Zhu et al., 2006). Compatibility issues may negatively affect businesses’ IT use
(McKenzie, 2001; Sherry, 1997). Organisations should consider adopting new
technologies when they find them compatible with their existing work application
systems. When they find the technologies significantly incompatible, major
adjustments in their processes, which involve considerable retraining, are required
(Rohani, 2015).
• Complexity
Cloud ERP complexity is defined as ‘the degree to which an innovation is perceived
as relatively difficult to understand and use’ (Rogers, 2010). Rogers (2010) also
stated that hard-to-use innovations are adopted less frequently than those that are

210
M
.
Z
amzee
r
et al.
easier to use. Sometimes it takes time for users to adapt to new systems; thus, the
complexity of the new technology can be viewed as an obstacle in innovation
implementation (Premkumar and King, 1994). To increase the adoption rate,
innovations must be friendly and easy to use (Parisot, 1995; Sahin, 2006). Moreover,
studies have shown that complexity is a key factor in adoption decisions (Chaudhury
and Bharati, 2008; Harindranath et al., 2008; Tiwana and Bush, 2007). It has been
negatively linked with adoption probability (Alshamaila et al., 2013).
• Trialability
Trialability is one of the most significant factors in the process of innovation
adoption (Ramdani and Kawalek, 2007a). The trial period allows potential adopters
to experience the technology and understand how they can use it in their firm. As a
result, it will have an impact on their decision to adopt the system (Salim, 2015).
Users’ understanding of the capabilities of information telecommunication
technologies is increased through education and training, which facilitates the
adoption of these technologies (Premkumar and Roberts, 1999). Mohamad Hsbollah
et al. (2009) emphasised that online education can be a significant factor affecting
the adoption of new internet-based technologies. Kleintop et al. (1994) found that
high levels of acceptance, perceptions of ease of use, and perceptions of the
usefulness of IT systems can be achieved by focusing on end users’ practice with the
new IT system before its implementation.
2.2.2 Organisational context
The following sections explain all elements and definitions related to the organisational
context.
• Size
Organisation size can influence the adoption of cloud technology (Rohani, 2015).
However, the relationship between organisation size and adoption is debated and
based on empirical data (Alshamaila et al., 2013). Some studies have found a
positive correlation between them (Belso-Martinez, 2010; Kamal, 2006; Ramdani
and Kawalek, 2007a); they suggest that larger firms are better able to survive failures
than smaller firms because of greater resources, skills, and expertise (Alshamaila
et al., 2013). In contrast, other studies showed a negative correlation (Goode and
Stevens, 2000; Utterback, 1974), arguing that small firms are better able to adapt
their work to the rapid changes in their medium and, as a result, can be more
innovative than larger firms, whose decision-making processes are slowed by
multiple levels of management (Damanpour, 1992; Jambekar and Pelc, 2002;
Oliveira and Martins, 2011).
• Top management support
Studies have shown a positive correlation between support from top management
and the adoption of innovations (Premkumar and Roberts, 1999). Management’s
vision, support, and commitment are crucial to creating a positive environment for
new technologies (Lee and Kim, 2007). Moreover, top management can spread
awareness of the importance of new technology across the organisation (Low et al.,
2011; Thong, 1999; Wang et al., 2010). Jeyaraj et al. (2006) argued that top

Determinants of cloud ERP adoption in Jordan 211
management support is the main link between individual and organisational ICT
innovation adoption. In addition, owner involvement ensures that sufficient resources
are allocated to adopt new technologies (Premkumar and Potter, 1995; Vahtera,
2008). Consequently, top management support is thought to have an impact on ICT
innovation adoption (Daylami et al., 2005; Thong, 1999; Wilson et al., 2008).
• Innovativeness
Innovativeness is a human characteristic of the decision-maker that reflects the
individual’s willingness to adopt new ideas, try new solutions, and pursue new
techniques and manners that are risky and have not been thoroughly tested
(Alshamaila et al., 2013; Marcati et al., 2008; Thong and Yap, 1995). Innovative
managers tend to be more receptive towards adopting new technologies to aid in
information processing, decision-making, and problem-solving (Kirton, 2004;
Marcati et al., 2008).
• Cost
Financial resources are a performance requirement and critical success factor for ICT
adoption, especially for SMEs (Rangone, 1999). In general, most SMEs have limited
financial resources, and the owner’s personal assets are usually invested in the
business (Fuller-Love, 2006). This limitation forces SMEs to be more aware of their
investments and capital spending (Ghobakhloo et al., 2011). Ambiguous IT
investment decisions can lead to negative financial consequences and may even
result in insolvency and economic failure (Sarosa and Zowghi, 2003). Implementing
new technologies and their components is a long-term investment, and the high cost
of IT infrastructure means that such an investment is only feasible for SMEs with
adequate financial resources (Nguyen, 2009; Thong and Yap, 1995; Walczuch et al.,
2000). Cloud computing services offer small businesses a huge range of benefits by
using a pay-as-you-go model. SMEs only pay for the resources needed, offering
them a good return on investment for the limited resources (Alshamaila et al., 2013),
which gives the company a chance to focus on core business activities. Dwivedi and
Sharma (2016) state that the implementation of technologies such as ERP over the
cloud will reduce the cost in comparison with the traditional method, which takes a
long time to be implemented and will cost a lot even for large companies.
• Prior technological experience
Thong and Yap (1995) demonstrate that CEOs of small businesses who have more
knowledge of IT are more willing to adopt new technologies than those without such
knowledge. General experience accumulation and IT knowledge reduce uncertainty
issues and lower the risks of adopting new IT (Thong, 1999). Additionally, a study
conducted by Lippert and Forman (2005) found that for SMEs, this factor may play a
facilitative role in the ICT implementation decision.
2.2.3 Environmental context
The following sections describe the elements contained within the environmental context.
• Competitive pressure

212
M
.
Z
amzee
r
et al.
Competitive pressure refers to the level of pressure firms experience from
competitors; it is considered an external stimulus that pushes businesses towards
adopting new technologies to avoid competitive decline (Zhu et al., 2003). Firms can
benefit greatly by adopting cloud computing, which gives them a better view of the
market, better operational competence, and a competitive advantage (Misra and
Mondal, 2011). Businesses that mostly work in a competitive medium are the most
likely to adopt cloud computing (Rohani, 2015).
• Industry
The industry in which a firm operates can affect IT innovation adoption (Levenburg
et al., 2006). Moreover, businesses in different industries have different information
processing requirements, which might affect individual firms’ adoption of new
technologies (Goode and Stevens, 2000; Yap, 1990). Many recent statistics on cloud
computing use the industry as an indicator for adoption, illustrating how certain
sectors are adopting cloud computing services more than others and how the industry
sector could potentially be a significant factor in new technology adoption. However,
there are also studies that suggest that the firm’s sector does not play a pivotal role in
the adoption of new ICT innovations (Levy et al., 2001).
• Market scope
Market scope is the horizontal extent of a company’s operations (Zhu et al., 2003).
The wide availability of ICT innovations can aid small firms in reaching markets
locally, nationally, and internationally (Alshamaila et al., 2013). Moreover,
innovations may help businesses to offer lower prices, thus increasing their market
share (Levenburg et al., 2006).
• Supplier computing support
Marketing providers’ actions can significantly affect adoption decisions and the
spreading process of certain innovations (Alshamaila et al., 2013). Their support
includes marketing, training, customer service, technical support, and
troubleshooting provided by cloud providers (Frambach et al., 1998; Hultink et al.,
1997; Woodside and Biemans, 2005). Frambach and Schillewaert (2002) studied the
connection between firms’ adoption decisions and supplier marketing efforts. To
reduce the expected risks for the potential customer, the importance of service
providers activities such as targeting and communication should be highlighted.
• Data centre location
Cloud services’ external costs to SMEs are expected to decrease, which will make
cloud services more widely available. When selecting a site, SMEs should take three
criteria into consideration: environmental conditions (i.e., the region’s climate and
history of natural hazards), wide area network (i.e., the availability and cost of fibre
and communications infrastructure), and power (i.e., the availability and cost of
electrical power infrastructure; INTEL, 2014).
• Political situation
The political situation refers to government actions that affect the operations of a
company or business. These actions may be on a local, regional, national, or
international level. Business owners and managers should pay close attention to the

Determinants of cloud ERP adoption in Jordan 213
political environment to gauge how government actions will affect their companies
(WebFinance, 2016).
3 Research methodology
3.1 Research design
Cloud computing is one of the key technologies used worldwide. However, few studies
have been conducted concerning the adoption of cloud ERP services in Jordan. As a
result, this study was conducted to focus on cloud ERP services. This study is exploratory
in nature, and a case study is considered a suitable approach for this type of research
project (Marshall and Rossman, 1989; Yin, 2013). Case studies are one of the five types
of qualitative research, which are intensive in both analyses and description (Hancock
and Algozzine, 2016). Case studies help when exploring areas in which knowledge is
limited (Eisenhardt, 1989) and offer valuable understanding in the context of a certain
case (Yin, 2013). Thirteen companies taking part in the study are referred to as F1–13.
3.2 Sampling
Using Rogers’s classification of the basis of innovativeness (Rogers, 2010), we
categorised 13 cases into four groups: service providers (i.e., F1, F2, F3, and F4), which
are referred to as group 1; SMEs that adopted cloud ERP (i.e., F5, F6, and F7), referred to
as group 2; SMEs thinking of adopting cloud ERP, also known as ‘prospectors’ (i.e., F8,
F9, and F10), or group 3; and SMEs that do not intend to adopt cloud ERP (i.e., F11, F12,
and F13), referred to as group 4 (see Table 2). The purpose of using these four groups is
to get diverse views on the topic. SMEs that adopted cloud ERP computing provide their
experience with the system and the future challenges they might have. SMEs considering
adopting cloud ERP provide us with information regarding their approaches towards
adoption, whereas SMEs that refuse to adopt cloud ERP inform us of the obstacles and
drawbacks of adopting such technologies. We classified these groups carefully to
overcome any bias and to gather a wide variety of information. Table 2 shows group
classifications and contain information about each group such as the firm’s name,
industry, and the interviewee’s position.
3.3 Data collection and analysis
Data collection took place between February and April 2016 in the form of
semi-structured interviews, most of which were conducted face to face; this technique is
well-suited to exploratory research such as this because it provides the possibility of
highlighting important factors (Yin, 2013). While studies that adopt the TOE model can
be criticised due to the way they pick and choose from a list of attributes that have been
empirically tested on other ICT innovations (Ramdani and Kawalek, 2007b). We had the
chance to talk to the interviewees and debate the factors they think are significant to their
own cases instead of talking through the TOE frame to avoid bias. The researchers
carefully chose and studied the questions before conducting the main interviews as shown
in the interview script outline in Appendix 1, which is partly adopted from Ramdani
(2008). The interviewees varied from senior managers with considerable experience in

214
M
.
Z
amzee
r
et al.
assessing new technologies to managers who are new to assessing technologies. This
study aims to examine the factors that affect cloud ERP adoption in Jordan; accordingly,
three sets of questions were designed. The first set of questions was designed to identify
the characteristics of the enterprises that took part in the interview.
Table 2 Data sources for the study
Interviewee’s position Industry Firm’s name Group #
Partner sales executive Technology F1 Group 1
Vendors
Account technology strategist
Channel manager Computer technology F2
Manager of education and health
department
IT solutions F3
Sales manager/key Business solutions F4
Accounts
Project manager Education and training F5 Group 2
Adopted
cloud ERP
Centre
IT manager Retailer F6
Head manager IT solutions F7
General manager Business solutions F8 Group 3
Prospectors
Head of information technology
unit
Geotechnical engineering F9
Technical administrator Education F10
Sales and business development
manager
IT solutions F11 Group 4
Do not
intend to
adopt
Operations manager Entertainment F12
IT manager Education F13
The second set of questions was about the level of Information systems innovation
adoption and its use in the firm. The last set of questions was about the impact of the
TOE factors on cloud computing adoption. At the end of each interview, we immediately
recorded the session notes, with the permission of the interviewees. We analysed the data
according to the process suggested by Miles and Huberman (1994). Our process of
analysis consisted of three simultaneous flows of activities: data reduction, data display,
and drawing and verifying conclusions. Our intention was to compress the data so it
could be summarised and simplified (Saunders and Thornhiel, 2003; Saunders et al.,
2007). We also combined and organised information to be displayed in the most useful
way, which ultimately enabled us to reach our conclusions (Miles and Huberman, 1994).
4 Findings and discussion
This section presents the findings of the study and examines which factors and to what
extent each of these factors influences the cloud ERP adoption decision made by SMEs in
Jordan.

Determinants of cloud ERP adoption in Jordan 215
4.1 Technological factors
4.1.1 Relative advantage
Some organisations believe that adopting cloud ERP will give them an important relative
advantage over their competitors (F1, F3, F4, F5, F6, F7, F9, F10, and F11). Additional
benefits over the competitors are necessary to adopt the cloud solutions (Gangwar et al.,
2015). They are tempted to adopt cloud ERP to improve accessibility, facilitate market
reach, and enhance productivity and efficiency (F5, F7, and F9). They believe cloud ERP
will offer them transaction traceability (F9), mobility, and work completion (F6 and F11).
Some firms believe that adopting cloud ERP would offer the chance to obtain the latest
updates (F1 and F4) and compete with larger firms (F3).
However, SMEs must have proper internet bandwidth to enable full utilisation of
cloud benefits (F5). In contrast, other organisations explain their reasons for not adopting
cloud ERP by saying that it would not necessarily give them a relative advantage over
their competitors (F2, F8, F12, and F13). They also state that their current work methods
already satisfy the work requirements (F12) and that cloud ERP was not necessary; it
could be replaced by an on-premise ERP system (F2).
4.1.2 Uncertainty
All service providers in this study agree that companies are resistant to the idea of cloud
computing and that, in general, it is important to ensure data are protected from
unauthorised parties. According to Saa et al. (2017), SMEs gain benefits from cloud ERP,
and they do not have any issues related to security, whereas large companies have their
own concerns about moving to the cloud. However, some firms raise questions regarding
the cloud’s security because cloud-based information is not kept within the firm’s
boundaries (F1, F2, F3, and F4). Moreover, service providers must maintain trust with
clients to help them overcome security and privacy concerns as mentioned by F5, F6, F7,
F10, and F11. F1, F2, F3, F4, and F8 state that uncertainty is an important factor for
moving to cloud services. Connectivity loss and data latency are also major worries
(F12), and firms are fearful of relinquishing their data (F13). While F7 states that cloud
ERP vendors cannot afford any issues in this area because such issues would affect their
reputation and force them to pay compensation to their customers, as stated in their
contracts, F8 expresses fear because rules and regulations regarding data security are not
mature enough in Jordan. Other companies believe that the risk in cloud ERP is low
because authorities are distributed more clearly (F9 and F10).
4.1.3 Compatibility
Most of the sampled SMEs consider compatibility an insignificant factor (F1, F2, F3, F4,
F5, F6, F7, F9, F10, and F11). F1, F3, F4, and F11 state that there is no need to buy
servers and manage software. F2 and F9 explain that companies can easily integrate on-
premise ERP systems with the cloud because the cloud environment is almost unified.
The only infrastructure needed for cloud ERP is a trusted, high-qualitative internet
connection (F3, F4, and F11). F10 illustrates that cloud ERP allows high efficiency and
availability without requiring huge infrastructure and redundant components. For some
businesses, compatibility is an issue because they already have a legacy system and

216
M
.
Z
amzee
r
et al.
servers on their premises, and they can neither relinquish existing infrastructure nor
throw it away. The integration between the old and new systems would not be that easy
(F12 and F13).
4.1.4 Complexity
The more complex the software is, the more companies are encouraged to adopt the
software as a cloud service (F1, F6, F7, F8, F10, and F11). To adopt new technologies,
they must be easy and user-friendly (Sahin, 2006). This is consistent with the results of
this study. In general, all vendors (F1–F4) mentioned that the cloud ERP environment is
user-friendly, and clients should face no problems when using it. F3, F5, and F9 state that
complexity is not a crucial factor. For instance, F5 previously had an on-premise ERP
system, so it feels that dealing with the cloud is not difficult. Other firms, like F13, have
extremely basic software that meets their requirements, so they do not feel the need to
adopt cloud services, especially because they are not fully aware of the concept of cloud
computing. F12 states that it is comfortable with its existing on-premise ERP system,
knows how to handle it, and feels that the maintenance is affordable.
4.1.5 Trialability
Regarding system trialability, most vendors provide firms with a free trial period so they
can understand the concepts related to cloud ERP, which allows clients to feel less
reluctant about this technology (F1, F2, and F4). Most firms find that training does not
affect their adoption decisions (F5, F6, F7, F8, F9 and F12). Cloud ERP is easy to use
and does not need much IT infrastructure (Gupta et al., 2017). In that context, all vendors
(F1–F4) mention that the cloud ERP environment is user-friendly and online help is
always available, but training is always conducted for licensing accounts, system
administration, and information updates. F10 says that training for software on the cloud
is much easier than training for on-premise ERP because it does not require technical
skills to maintain servers and solve issues in the system. F12 believes that training is not
necessary, especially if staff is proficient in IT matters. Summary of the results about
technological factors presented in Table 3.
Table 3 Summary – technological factors
Technological factors Supported Not supported
Relative advantage 1, 3–7, 9–11 2, 8, 12, 13
Uncertainty 1–8, 11–13 9–10
Compatibility 12–13 1–11
Complexity 1, 6–8, 10, 11 3, 5, 9, 12, 13.
Trialability 1–4, 10 5–9, 12
4.2 Organisational factors
4.2.1 Firm size
Previous studies are divided into three schools of thought. First, some studies believe that
the size factor of firms has a positive impact on the adoption of new technologies such as

Determinants of cloud ERP adoption in Jordan 217
Oliveira and Martins (2011). This result is in line with the results of this study. According
to F1, F2, F3, F4, F6, F11, and F12, organisation size is an important factor in adoption.
They all agree on the fact that the smaller the firm, the greater the need to adopt cloud
ERP. F1 and F2 say that large enterprises are less cost-sensitive than SMEs. Mabert et al.
(2003) state that all firms of different sizes can benefit from the implementation of ERP.
In this regard, F5, F7, F8, F9, F10, and F13 believe that cloud ERP systems can be
implemented in firms of all sizes, meaning company size is not a critical factor. However,
F5, F7, and F9 believe that organisations in rural areas can obtain huge benefits from
such technology.
4.2.2 Top management support
Top management support has a strong influence on both the decision to adopt and the
success of the adoption (Wilson et al., 2008). All firms believe that commitment and
support from top management play a key role in the adoption decision (F1–F13) because
top management usually has a broad view of organisations and their needs (F6 and F8).
When the firms’ managers understand the benefits of adopting new technology, this will
boost the adoption process (Wilson et al., 2008). Managers tend to approve adoption
when they feel cloud ERP is financially beneficial, time saving (F1), and has the ability
to track transactions and operations efficiently (F5); however, managers tend to be more
reluctant to adopt cloud ERP when firms already have an on-premise system, including
infrastructure that could not be used if cloud ERP was adopted (F2 and F12). Some
managers may be against adopting such technologies because they feel the benefits
offered by the cloud do not add value to the business (F7, F12, and F13). In general, most
participants agreed on the importance of top management support for technology
adoption.
4.2.3 Innovativeness
Many firms find that innovativeness is an important factor. Marcati et al. (2008) found
that entrepreneurs with creative minds are more eager to adopt and take risks regarding
new technologies. This characteristic is especially prominent in young managers because
they are usually more aware of emerging technologies (F1, F2, F3, F4, F5, F6, F7, F9,
and F11). Some companies consider adopting new technologies as key performance
indicators (KPI) to improve their technology indices (F1). In contrast, F8, F10, F12, and
F13 believe that business rather than concern for innovativeness needs to drive adoption
decisions.
4.2.4 Cost
By adopting cloud ERP, some related to the financial and human resources needed in the
process of installing and maintaining the ERP systems will be solved and the cost will be
low (Peng and Gala, 2014). This result is consistent with our findings. Most firms stress
that the cost reduction of adopting cloud ERP, especially in capital expenditures, is an
important factor in the adoption decision (F1, F2, F3, F4, F6, F7, F9, and F11); the firms
justified this by saying that adopting cloud ERP is cheaper than buying and maintaining a
server and licensing an on-premise system. ‘The more acceptable the price is, the more
SMEs choose to adopt cloud ERP’ (F3). However, other firms do not consider cost to be

218
M
.
Z
amzee
r
et al.
of great importance and instead prioritise system functionalities (F5, F8, F10, F12, and
F13).
4.2.5 Prior ICT experience
Apart from F6 and F12, who believe that this factor is insignificant, we divided the
remaining firms that find this factor significant into two groups. Group one (F1, F4, F8,
F10, and F11) believes that there is a negative correlation between adopting cloud ERP
services and experience; they argue that experienced managers are more resistant and
reluctant towards cloud technologies in general, and they tend to prefer having their
servers on the premises.
Group two (F2, F3, F5, F7, F9, and F13) thinks that there is a positive correlation;
they argue that experienced managers facilitate the adoption because they can understand
the benefits of cloud ERP and drive the company towards success and operational
efficiency much better than fresh managers. This is in line with the results of Gupta et al.
(2017), who state that having prior experience, such as that found in large companies,
help them in the decision-making process because they are already aware of cloud ERP.
Summary of the results about organisational factors presented in Table 4.
Table 4 Summary – organisational factors
Organisational factors Supported Not supported
Firm size 1–4, 6, 11, 12. 5, 7–10, 13.
Top management support 1–13
Innovativeness 1–7, 9, 11 8, 10, 12, 13.
Cost 1–4, 6–7, 9, 11. 5, 8, 10, 12, 13.
Prior ICT experience 1–5, 7–11, 13 6, 12
4.3 Environmental factors
4.3.1 Competitive pressure
In general, the adoption of new technologies from competitors encourage SMEs to think
about adopting those technologies (Usman et al., 2016). However, in contrast to service
providers (F1, F3, and F4), all firms (F2, F5 – F13) agree that competitive pressure does
not influence their adoption decisions. F1, F3, and F4 argue that companies are
encouraged to adopt cloud ERP when a competitor adopts it because they feel the urge to
be more successful than their competitors. It is interesting that F11 believes that although
businesses consider competitive pressure insignificant, a key motivator for service
providers to start offering cloud ERP services in Jordan is to gain market share.
4.3.2 Industry
The more sensitive the information in the firm is, the less likely the firm is to adopt cloud
ERP services. Most companies (F3–F10) state that cloud ERP adoption is not limited to a
specific sector but rather can be applied in all areas. For example, Ahmad et al. (2015)
stated that the deployment of cloud ERP in the agriculture sector improved farming
practices, according to a study they conducted. F10 adds that it might be difficult to apply

Determinants of cloud ERP adoption in Jordan 219
in the education sector due to the interrelated nature of operations. Governmental circles
are more reluctant to adopt cloud ERP, especially because rules and regulations are not
mature enough in this area. Banks are heading towards adopting cloud ERP services (F1
and F11). In contrast, F3 believes that the more complexity in business functions, the
greater the need for adopting cloud ERP.
4.3.3 Market scope
The interview results show that cloud ERP adoption could improve the quality of services
provided to customers, but it is not as important as the other factors in the adoption
decision (F1, F2, F4, F8, F11, F12, and F13). For instance, F12 believes that extending
market share can be achieved by other technologies, such as virtual networks. However,
F3, F5, F6, F7, F9, and F10 find it to be a key factor because cloud ERP services
facilitate market reach and scalability as well as enabling firms to stop depending on a
physical location.
4.3.4 Supplier computing support
Suppliers must offer support agreements, set up a help centre that is available 24/7, assure
customers they will not experience data loss or availability issues, and provide
continuous system testing and maintenance, according to all the participants in these
interviews (F1–F13). Cloud vendors have the responsibility to follow up on the
maintenance and support issues of the clients (Peng and Gala, 2014). This universal
agreement is an indicator of the importance of this factor. F7 highlights the importance of
service providers clearly explaining cloud benefits to clients. Large vendors continuously
try to attract firms, but their efforts are not sufficient (F12 and F13).
4.3.5 Data centre location
It was noted during the interviews that there was a debate regarding the importance of the
location of the data centre and the political situation in the Middle East. The data centre,
server, and data storage locations are of great importance to many firms (F1, F3, F4, F7,
F8, F10, F11, and F12), due to the rules and regulations that host them, according to F1,
F8, and F12. However, other firms (F7) desire a location near the company in case any
issues arise. Knowing the location of the data centre gives the client a sense of security
(F10). F8 argues that as long as the server location is a matter of discussion, it means the
laws and regulations that govern cloud services are not mature enough, which serves as a
barrier to the adoption of cloud ERP. Nevertheless, many companies do not consider this
factor during their cloud ERP adoption decisions and believe that as long as the service
provider is trustworthy and the geographical location is not far away – to avoid latency
issues – it will not influence their cloud ERP adoption decisions (F2, F5, F6, F9, and
F13).
4.3.6 Political factors
In Jordan and surrounding countries, the impact of the political situation was
demonstrated in the responses of F1, F2, F3, F4, F5, F6, F9, F10, F11, and F12. The
political situation in surrounding areas in the Middle East can be important to firms

220
M
.
Z
amzee
r
et al.
where they either have branches or a dominant market share because data is the main
asset for most firms (F7, F9, F11, and F12).
As explained by F2, ‘The political tension that dominated many Middle Eastern
countries lately has forced many enterprises to move their data to the cloud to ensure its
safety and availability’. Companies tend to adopt cloud services to keep a backup of their
information outside the company (F1 and F8), and they demand the server to be in a
secure area (F3). Moreover, it is an important factor not just because of war; the electrical
continuity in some countries affects on-premise systems and can ruin servers (F6). In
contrast, firms such as F8, F10, and F13 find it is not an important factor because the
political environment is stable in Jordan. Summary of the results about environmental
factors presented in Table 5.
Table 5 Summary – environmental factors
Environmental factors Supported Not supported
Competitiveness pressure 1, 3, 4. 2, 5–13.
Industry 3–10 1, 11.
Market scope 3, 5–7, 9, 10. 1, 2, 4, 8, 11–13.
Suppliers computing support 1–13
Political factor 1–7, 9, 11, 12 8, 10, 13.
5 Discussion
In this section, we discuss the implications of our findings in the context of the three TOE
aspects.
5.1 Technological context
New technologies are expected to add value and advantages to the firm. Relative
advantage is often used as a significant index in ICT innovation literature (Chaudhury
and Bharati, 2008; Gangwar et al., 2015; Lee, 2014; Ramdani and Kawalek, 2007a;
Thong, 1999). In this case study, relative advantage was found to affect adoption
decisions because it adds independence, mobility, and practicality due to the lack of a
physical system location. The complexity factor was supported because it draws attention
towards cloud ERP, which allows for high efficiency and availability without requiring
large infrastructure and redundant components. If SMEs already have an on-premise
ERP, they can integrate it with the cloud by using a hybrid cloud ERP. Likewise,
trialability has a major impact on the adoption decision. SMEs need to be trained to
license their accounts and update their information; additionally, the interface must be
user-friendly. Several studies conclude that cloud ERP reduces the cost for companies
(Jain and Sharma, 2016; Johansson et al., 2015; Weng and Hung, 2014). Interviews have
shown that cost tremendously affects the adoption decision by saving money that would
be used to buy an on-premise ERP, allowing firms to pay as they go for what they need,
rather than paying on an ongoing basis for overflowing capacity (Morgan and Conboy,
2013). It is interesting to note that all SMEs agree that cloud ERP is much easier to work
with than an on-premise ERP and that some SMEs note that the complexity of an

Determinants of cloud ERP adoption in Jordan 221
on-premise ERPs drives them to adopt cloud ERP. This is consistent with previous
studies that state that cloud ERP is easy to use (Gupta et al., 2017; Weng and Hung,
2014). However, most SMEs seem to disregard the uncertainty factor and show no
concern for privacy or security because they trust vendors and the new technology they
provide.
5.2 Organisational context
Firm size is a key factor that influences the adoption decision (Mabert et al., 2003;
Oliveira and Martins, 2011). We found that firm size is a significant factor in cloud ERP
adoption; SMEs (F1, F2, F3, F4, F6, F11, and F12) share the same opinion, which means
that the smaller the firm is, the greater the need to adopt cloud ERP. The most interesting
finding was that all SMEs in the study agree that top management support affects their
adoption decisions because management sees the firm’s big picture and goals better than
anyone else. Another important finding was that innovativeness plays a major role in the
adoption decision. Moreover, new SMEs intend to adopt cloud ERP, which will help
achieve KPI to improve their technology index.
5.3 Environmental context
The most obvious finding to emerge from our analysis is that industry has a tremendous
impact on SMEs’ cloud ERP adoption decisions; most SMEs agreed that each industry
has its own goals and needs, and the more functions SMEs have, the greater their need for
cloud ERP adoption. This supports the choice of industry as one of the organisational
characteristics that was consistently connected with the adoption of technology (Goode
and Stevens, 2000). All participants in the study (F1–F13) believe supplier computing
support is one of the most influential factors because it assures SMEs that they will not
suffer data losses or availability issues and will receive continuous system testing and
maintenance.
Furthermore, the server location causes most of the SMEs to question cloud ERP
adoption because data sovereignty and the rules and regulations of the country that
contain the server are important factors to SMEs. Prospectors (F8, F9, and F10) agree
that they want the server location to be nearby so they can check on it whenever they
want. We also added a new factor – the political situation of the country – which may
prove to be of increasing importance. This could be one of the main factors that affects
cloud ERP adoption in the Middle East overall and in Jordan specifically, as all providers
in the case study note.
6 Conclusions
This paper highlights the factors that affect the adoption of cloud ERP by SMEs in
Jordan. The TOE framework was designed to include the main factors and defined terms
examined by most previous studies. Evidence is drawn by focusing mainly on the impact
of TOE factors on cloud ERP adoption. We found that the most influential factors
affecting cloud ERP adoption in SMEs in Jordan are management support and service
provider support. However, other factors such as relative advantage, compatibility,

222
M
.
Z
amzee
r
et al.
trialability, cost, size, innovativeness, server location, and political situation have
moderate effects. Finally, some factors previously identified as critical success factors
were deemed uninfluential. For example, uncertainty, complexity, prior IT experience,
competitive pressure, and market scope have minimal effects on SMEs’ adoption of
cloud ERP. The findings of this paper have implications for both practitioners and
researchers. Practitioners, including both companies and cloud ERP service providers,
have important views about the influential factors that affect the adoption of cloud ERP
in Jordan. For researchers, the primary implication was that future cloud ERP adoption
research should be intensified. Cloud ERP adoption in SMEs is a field that is drastically
growing yet has a dearth of academic research. This study’s findings offer multiple
possible future research extensions. Further research using a quantitative method is
recommended to complement the findings of this study. More case study research would
enable a deeper understanding of each factor identified in the conceptual framework.
Furthermore, additional case study research could advance the understanding of the
interactions between the identified factors. Finally, empirical research, such as a survey,
could provide insight into the correlation between factors identified in the conceptual
framework and determine the generalisability of this research.
Acknowledgements
This work was supported by the Deanship of Academic Research, The University of
Jordan.
References
Aboelmaged, M.G. (2014) ‘Predicting e-readiness at firm-level: an analysis of technological,
organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing
firms’, International Journal of Information Management, Vol. 34, No. 5, pp.639–651.
Ahmad, T., Ahmad, S. and Jamshed, M. (2015) ‘A knowledge based Indian agriculture: with cloud
ERP arrangement’, in 2015 International Conference on Green Computing and Internet of
Things (ICGCIoT), October, pp.333–340, IEEE.
AlBar, A.M. and Hoque, M.R. (2015) ‘Determinants of cloud ERP adoption in Saudi Arabia: an
empirical study’, in 2015 International Conference on Cloud Computing (ICCC), April,
pp.1–4, IEEE.
Al-Hujran, O. and Al-Dalahmeh, M. (2011) ‘The role of national culture on citizen adoption of
egovernment web sites’, in ECEG2011-Proceedings of the 11th European Conference on
EGovernment: ECEG2011, Academic Conferences Limited, p.17.
Al-Jaghoub, S. and Westrup, C. (2013) ‘Jordan and ICT-led development: towards a competition
state?’, Information Technology & People, Vol. 16, No. 1, pp.93–110.
Alshamaila, Y., Papagiannidis, S. and Li, F. (2013) ‘Cloud computing adoption by SMEs in the
north east of England: a multi-perspective framework’, Journal of Enterprise Information
Management, Vol. 26, No. 3, pp.250–275.
Aziz, N. (2010) ‘French higher education in the Cloud’, Grenoble Ecole de Management.
Beheshti, H.M. (2006) ‘What managers should know about ERP/ERP II’, Management Research
News, Vol. 29, No. 4, pp.184–193.
Belso-Martinez, J.A. (2010) ‘Outsourcing decisions, product innovation and the spatial dimension:
evidence from the Spanish footwear industry’, Urban Studies, Vol. 47, No. 14, pp.3057–3077.

Determinants of cloud ERP adoption in Jordan 223
Bernroider, E. and Koch, S. (2001) ‘ERP selection process in midsize and large organizations’,
Business Process Management Journal, Vol. 7, No. 3, pp.251–257.
Chakravorty, S.S., Dulaney, R.E. and Franza, R.M. (2016) ‘ERP implementation failures: a case
study and analysis’, International Journal of Business Information Systems, Vol. 21, No. 4,
pp.462–476.
Chaudhury, A. and Bharati, P. (2008) ‘IT outsourcing adoption by small and medium enterprises: a
diffusion of innovation approach’, AMCIS 2008 Proceedings, p.390.
Chauhan, S. and Jaiswal, M. (2015) ‘Exploring factors affecting service quality of ERP on cloud: a
revelatory case study’, International Journal of Business Information Systems, Vol. 19, No. 1,
pp.87–102.
Ching, H.L. and Ellis, P. (2004) ‘Marketing in cyberspace: what factors drive e-commerce
adoption?’, Journal of Marketing Management, Vol. 20, Nos. 3–4, pp.409–429.
Damanpour, F. (1992) ‘Organizational size and innovation’, Organization Studies, Vol. 13, No. 3,
pp.375–402.
Daylami, N., Ryan, T., Olfman, L. and Shayo, C. (2005) ‘System sciences’, in Proceedings of the
38th Annual Hawaii International Conference, HICSS ‘05, Island of Hawaii, January, pp.3–6.
Depietro, R., Wiarda, E. and Fleischer, M. (1990) ‘The context for change: organization,
technology and environment’, The Processes of Technological Innovation, Vol. 199, No. 0,
pp.151–175.
Douglas, A.B., Barry, C.W., Jongwoo, K., Balasubramaniam, R. and Pamela, S.R. (2016)
‘Achieving dynamic capabilities with cloud computing: an empirical investigation’, European
Journal of Information Systems, Vol. 25, No. 3, pp.209–230.
Dwivedi, K. and Sharma, M. (2016) ‘Virtual investigation of grouping of on premise and cloud
ERP’, International Journal of Research and Development in Applied Science and
Engineering, Vol. 9, No. 1.
Eisenhardt, K.M. (1989) ‘Building theories from case study research’, Academy of Management
Review, Vol. 14, No. 4, pp.532–550.
FossoWamba, S., Gunasekaran, A., Bhattacharya, M. and Dubey, R. (2016) ‘Determinants of RFID
adoption intention by SMEs: an empirical investigation’, Production Planning & Control,
Vol. 27, No. 12, pp.979–990.
Frambach, R.T. and Schillewaert, N. (2002) ‘Organizational innovation adoption: a multi-level
framework of determinants and opportunities for future research’, Journal of Business
Research, Vol. 55, No. 2, pp.163–176.
Frambach, R.T., Barkema, H.G., Nooteboom, B. and Wedel, M. (1998) ‘Adoption of a service
innovation in the business market: an empirical test of supply-side variables’, Journal of
Business Research, Vol. 41, No. 2, pp.161–174.
Fuller-Love, N. (2006) ‘Management development in small firms’, International Journal of
Management Reviews, Vol. 8, No. 3, pp.175–190.
Gangwar, H., Date, H. and Ramaswamy, R. (2015) ‘Understanding determinants of cloud
computing adoption using an integrated TAM-TOE model’, Journal of Enterprise Information
Management, Vol. 28, No. 1, pp.107–130.
Ghobakhloo, M., Arias-Aranda, D. and Benitez-Amado, J. (2011) ‘Information technology
implementation success within SMEs in developing countries: an interactive model’, POMS
22nd Annual Conference, Reno, USA, 29 April–2 May.
Goode, S. and Stevens, K. (2000) ‘An analysis of the business characteristics of adopters and
non-adopters of world wide web technology’, Information Technology and Management,
Vol. 1, Nos. 1–2, pp.129–154.
Gupta, S., Misra, S.C., Kock, N. and Roubaud, D. (2018) ‘Organizational, technological and
extrinsic factors in the implementation of cloud ERP in SMEs’, Journal of Organizational
Change Management, Vol. 31, No. 1, pp.83–102.

224
M
.
Z
amzee
r
et al.
Gupta, S., Misra, S.C., Singh, A., Kumar, V. and Kumar, U. (2017) ‘Identification of challenges
and their ranking in the implementation of cloud ERP: a comparative study for SMEs and
large organizations’, International Journal of Quality & Reliability Management, Vol. 34,
No. 7, pp.1056–1072.
Hancock, D.R. and Algozzine, B. (2016) Doing Case Study Research: A Practical Guide for
Beginning Researchers, Teachers College Press, New York, NY.
Harindranath, G., Dyerson, R. and Barnes, D. (2008) ‘ICT in small firms: factors affecting the
adoption and use of ICT in Southeast England SMEs’, in ECIS, June, pp.889–900.
Heide, J.B. and Weiss, A.M. (1995) ‘Vendor consideration and switching behavior for buyers in
high-technology markets’, The Journal of Marketing, Vol. 59, No. 3, pp.30–43.
Hultink, E.J., Griffin, A., Hart, S. and Robben, H.S. (1997) ‘Industrial new product launch
strategies and product development performance’, Journal of Product Innovation
Management, Vol. 14, No. 4, pp.243–257.
INTEL (2014) Selecting a Data Center Site: Intel’s Approach [online] http://www.intel.com/
content/dam/www/public/us/en/documents/white-papers/selecting-a-data-center-site-intels-
approach-paper.pdf (accessed June 2016).
Jain, D. and Sharma, Y. (2016) ‘Cloud computing with ERP-A push business towards higher
efficiency’, Annual Research Journal of SCMS, Vol. 4, pp.140–155, Pune.
Jambekar, A.B. and Pelc, K.I. (2002) ‘Managing a manufacturing company in a wired world’,
International Journal of Information Technology and Management, Vol. 1, No. 1,
pp.131–141.
Jeyaraj, A., Rottman, J.W. and Lacity, M.C. (2006) ‘A review of the predictors, linkages, and
biases in IT innovation adoption research’, Journal of Information Technology, Vol. 21, No. 1,
pp.1–23.
Johansson, B., Alajbegovic, A., Alexopoulo, V. and Desalermos, A. (2015) ‘Cloud ERP adoption
opportunities and concerns: the role of organizational size’, in 2015 48th Hawaii International
Conference on System Sciences (HICSS), January, pp.4211–4219, IEEE.
Kamal, M.M. (2006) ‘IT innovation adoption in the government sector: identifying the critical
success factors’, Journal of Enterprise Information Management, Vol. 19, No. 2, pp.192–222.
Kirton, M.J. (2004) Adaption-Innovation: In the Context of Diversity and Change, Routledge,
New York.
Kleintop, W.A., Blau, G. and Currall, S.C. (1994) ‘Practice makes use: using information
technologies before implementation and the effect on acceptance by end users’, in
Proceedings of the 1994 Computer Personnel Research Conference on Reinventing IS:
Managing Information Technology in Changing Organizations: Managing Information
Technology in Changing Organizations, April, pp.120–132, ACM.
Lee, S. and Kim, K.J. (2007) ‘Factors affecting the implementation success of internet-based
information systems’, Computers in Human Behavior, Vol. 23, No. 4, pp.1853–1880.
Lee, S.Y. (2014) ‘Examining the factors that influence early adopters’ smartphone adoption: the
case of college students’, Telematics and Informatics, Vol. 31, No. 2, pp.308–318.
Levenburg, N., Magal, S.R. and Kosalge, P. (2006) ‘An exploratory investigation of organizational
factors and e-business motivations among SMFOEs in the US’, Electronic Markets, Vol. 16,
No. 1, pp.70–84.
Levy, M., Powell, P. and Yetton, P. (2001) ‘SMEs: aligning IS and the strategic context’, Journal
of Information Technology, Vol. 16, No. 3, pp.133–144.
Lippert, S.K. and Forman, H. (2005) ‘Utilization of information technology: examining cognitive
and experiential factors of post-adoption behavior’, IEEE Transactions on Engineering
Management, Vol. 52, No. 3, pp.363–381.
Low, C., Chen, Y. and Wu, M. (2011) ‘Understanding the determinants of cloud computing
adoption’, Industrial Management & Data Systems, Vol. 111, No. 7, pp.1006–1023.

Determinants of cloud ERP adoption in Jordan 225
Mabert, V.A., Soni, A. and Venkataramanan, M.A. (2003) ‘The impact of organization size on
enterprise resource planning (ERP) implementations in the US manufacturing sector’, Omega,
Vol. 31, No. 3, pp.235–246.
Marcati, A., Guido, G. and Peluso, A.M. (2008) ‘The role of SME entrepreneurs’ innovativeness
and personality in the adoption of innovations’, Research Policy, Vol. 37, No. 9,
pp.1579–1590.
Marshall, C. and Rossman, G. (1989) ‘How to conduct the study: designing the research’,
Designing Qualitative Research, Sage Publications, Maryland.
McKenzie, J. (2001) ‘Head of the class: how teachers learn technology best’, American School
Board Journal, Vol. 188, No. 1, pp.20–23.
Miles, M.B. and Huberman, A.M. (1994) Qualitative Data Analysis: An Expanded Sourcebook,
Sage, Thousand Oaks, CA.
Miller, M. (2008) Cloud Computing: Web-based Applications that Change the Way you Work and
Collaborate Online, 1st ed., Que Publishing.
Misra, S.C. and Mondal, A. (2011) ‘Identification of a company’s suitability for the adoption of
cloud computing and modelling its corresponding return on investment’, Mathematical and
Computer Modelling, Vol. 53, Nos. 3–4, pp.504–521.
Mohamad Hsbollah, H., Kamil and Idris, M. (2009) ‘E-learning adoption: the role of relative
advantages, trialability and academic specialisation’, Campus-Wide Information Systems,
Vol. 26, No. 1, pp.54–70.
Mohammadkazem, M., Shirazi, B. and Aarabi, M. (2016) ‘Presentation of the model for readiness
assessment of ERP implementation in Iranian small and medium enterprises’, International
Journal of Business Information Systems, Vol. 23, No. 4, pp.456–481.
Morgan, L. and Conboy, K. (2013) ‘Factors affecting the adoption of cloud computing: an
exploratory study’, in 21st European Conference on Information Systems, United States.
Nguyen, T.H. (2009) ‘Information technology adoption in SMEs: an integrated framework’,
International Journal of Entrepreneurial Behavior& Research, Vol. 15, No. 2, pp.162–186.
Oliveira, T. and Martins, M.F. (2010) ‘Understanding e-business adoption across industries in
European countries’, Industrial Management & Data Systems, Vol. 110, No. 9, pp.1337–1354.
Oliveira, T. and Martins, M.F. (2011) ‘Literature review of information technology adoption
models at firm level’, The Electronic Journal Information Systems Evaluation, Vol. 14, No. 1,
pp.110–121.
Palacios-Marqués, D., Soto-Acosta, P. and Merigó, J.M. (2015) ‘Analyzing the effects of
technological, organizational and competition factors on web knowledge exchange in SMEs’,
Telematics and Informatics, Vol. 32, No. 1, pp.23–32.
Pareek, R. (2014) ‘Analytical study of cloud ERP and ERP’, International Journal of Engineering
and Computer Science, Vol. 3, No. 10, pp.8710–871.
Parisot, A.H. (1995) Technology and Teaching: The Adoption and Diffusion of Technological
Innovations by a Community College Faculty, Doctoral dissertation, Montana State
University-Bozeman, College of Education, Health & Human Development.
Peng, G.C.A. and Gala, C. (2014) ‘Cloud ERP: a new dilemma to modern organisations?’, Journal
of Computer Information Systems, Vol. 54, No. 4, pp.22–30.
Premkumar, G. (2003) ‘A meta-analysis of research on information technology implementation in
small business’, Journal of Organizational Computing and Electronic Commerce, Vol. 13,
No. 2, pp.91–121.
Premkumar, G. and King, W.R. (1994) ‘Organizational characteristics and information systems
planning: an empirical study’, Information Systems Research, Vol. 5, No. 2, pp.75–109.
Premkumar, G. and Potter, M. (1995) ‘Adoption of computer aided software engineering (CASE)
technology: an innovation adoption perspective’, ACM SIGMIS Database: the DATABASE for
Advances in Information Systems, Vol. 26, Nos. 2–3, pp.105–124.

226
M
.
Z
amzee
r
et al.
Premkumar, G. and Roberts, M. (1999) ‘Adoption of new information technologies in rural small
businesses’, Omega, Vol. 27, No. 4, pp.467–484.
Raihana, G.F.H. (2012) ‘Cloud ERP – a solution model’, International Journal of Computer
Science and Information Technology & Security, Vol. 2, No. 1, pp.76–79.
Ramdani, B. (2008) Technological, Organisational and Environmental Factors Influencing SMEs
Adoption of Enterprise Systems: A Study in the Northwest of England, Doctoral dissertation,
The University of Manchester.
Ramdani, B. and Kawalek, P. (2007a) ‘SME adoption of enterprise systems in the Northwest of
England’, in IFIP International Working Conference on Organizational Dynamics of
Technology-Based Innovation, Springer, Boston, MA, June, pp.409–429.
Ramdani, B. and Kawalek, P. (2007b) ‘SMEs & IS innovations adoption: a review & assessment of
previous research’, Academia Revista Latinoamericana de Administración, Vol. 39, No. 1,
pp.47–70.
Rangone, A. (1999) ‘A resource-based approach to strategy analysis in small-medium sized
enterprises’, Small Business Economics, Vol. 12, No. 3, pp.233–248.
Ranjan, S., Jha, V.K. and Pal, P. (2016) ‘Literature review on ERP implementation challenges’,
International Journal of Business Information Systems, Vol. 21, No. 3, pp.388–402.
Rogers, E.M. (2010) Diffusion of Innovations, 5th ed., Simon and Schuster, Free Press, New York.
Rohani, M.B. (2015) ‘An integrated theoretical framework for cloud computing adoption by
Universities Technology Transfer Offices (TTOs)’, Journal of Theoretical and Applied
Information Technology, Vol. 79, No. 3, p.415.
Rui, G. (2007) Information Systems Innovation Adoption among Organizations – A Match-Based
Framework and Empirical Studies, Doctoral dissertation.
Saa, P., Moscoso-Zea, O., Costales, A.C. and Luján-Mora, S. (2017) ‘Data security issues in cloud-
based software-as-a-service ERP’, in 2017 12th Iberian Conference on Information Systems
and Technologies (CISTI), June, pp.1–7, IEEE
Saeed, I., Juell-Skielse, G. and Uppström, E. (2012) ‘Cloud enterprise resource planning adoption:
motives & barriers’, Advances in Enterprise Information Systems II, CRC Press/Balkema,
Leiden, The Netherlands.
Sahin, I. (2006) ‘Detailed review of Rogers’ diffusion of innovations theory and educational
technology-related studies based on Rogers’ theory’, TOJET: The Turkish Online Journal of
Educational Technology, Vol. 5, No. 3, pp.14–23.
Salim, S.A. (2015) Moving from Evaluation to Trial: The Case of cloud ERP Adoption in SMEs,
Doctoral dissertation, Queensland University of Technology.
Sarosa, S. and Zowghi, D. (2003) ‘Strategy for adopting information technology for SMEs:
Experience in adopting email within an Indonesian furniture company’, Electronic Journal of
Information Systems Evaluation (EJISE), Vol. 6, No. 2, pp.165–176.
Saunders, M. and Thornhiel, H. (2003) Research Methods for Business Students, Pearson
Education, Harlow, Essex.
Saunders, M., Lewis, P. and Thornhill, A. (2007) ‘Formulating the research design’, Research
Methods for Business Students, 4th ed., pp.130–161, Pearson Education, England.
Schubert, P. and Adisa, F. (2011) ‘Cloud computing for standard erp systems: reference framework
and research agenda’, Inst. fürWirtschafts-und Verwaltungsinformatik.
Sharma, R. And Keswani, B. (2014) ‘Study of cloud based ERP services for small and medium
enterprises (data is processed by text mining technique)’, Salesian Journal on Information
Systems, Vol. 1, No. 13, pp.2–10.
Shaul, L. and Tauber, D. (2012) ‘CSFs along ERP life-cycle in SMEs: a field study’, Industrial
Management & Data Systems, Vol. 112, No. 3, pp.360–384.
Sherry, L. (1997) ‘The boulder valley internet project: lessons learned’, The Journal Technological
Horizons In Education, Vol. 25, No. 2, p.68.

Determinants of cloud ERP adoption in Jordan 227
Staehr, L. (2010) ‘Understanding the role of managerial agency in achieving business benefits from
ERP systems’, Information Systems Journal, Vol. 20, No. 3, pp.213–238.
Stuart, W.D. (2001) Influence of Sources of Communication, User Characteristics and Innovation
Characteristics on Adoption of a Communication Technology, PhD, The University of Kansas,
UMI No. AAT 9998115.
Teo, T.S., Tan, M. and Buk, W.K. (1997) ‘A contingency model of Internet adoption in Singapore’,
International Journal of Electronic Commerce, Vol. 2, No. 2, pp.95–118.
Thong, J.Y. (1999) ‘An integrated model of information systems adoption in small businesses’,
Journal of Management Information Systems, Vol. 15, No. 4, pp.187–214.
Thong, J.Y. and Yap, C.S. (1995) ‘CEO characteristics, organizational characteristics and
information technology adoption in small businesses’, Omega, Vol. 23, No. 4, pp.429–442.
Thong, J.Y., Yap, C.S. and Raman, K.S. (1994) ‘Engagement of external expertise in information
systems implementation’, Journal of Management Information Systems, Vol. 11, No. 2,
pp.209–231.
Tiwana, A. and Bush, A.A. (2007) ‘A comparison of transaction cost, agency, and
knowledge-based predictors of IT outsourcing decisions: a US-Japan cross-cultural field
study’, Journal of Management Information Systems, Vol. 24, No. 1, pp.259–300.
Usman, U.M.Z., Ahmad, M.N. and Zakariya, N.H. (2016) ‘Factors influencing cloud enterprise
resource planning adoption in SMEs’, in Information Science and Applications (ICISA) 2016,
Springer, Singapore, pp.235–245.
Utterback, J.M. (1974) ‘Innovation in industry and the diffusion of technology’, Science, Vol. 183,
No. 4125, pp.620–626.
Utzig, C., Holland, D., Horvath, M. and Manohar, M. (2013) ‘ERP in the cloud is it ready? Are
you?’, Perspective, pp.1–9.
Vahtera, A.M. (2008) ‘Organisational factors affecting IT innovation adoption in the Finnish early
childhood education’, in ECIS, pp.1106–1116.
Walczuch, R., Van Braven, G. and Lundgren, H. (2000) ‘Internet adoption barriers for small firms
in the Netherlands’, European Management Journal, Vol. 18, No. 5, pp.561–572.
Wang, W.Y., Heng, M.S. and Chau, P.Y. (2010) ‘The adoption behaviour of information
technology industry in increasing business-to-business integration sophistication’, Information
Systems Journal, Vol. 20, No. 1, pp.5–24.
WebFinance (2016) Political Environmental [online] http://www.businessdictionary.com/
definition/political-environmental.html (accessed June 2016).
Weng, F. and Hung, M.C. (2014) ‘Competition and challenge on adopting cloud ERP’,
International Journal of Innovation, Management and Technology, Vol. 5, No. 4, p.309.
Wilson, H., Daniel, E. and Davies, I.A. (2008) ‘The diffusion of e-commerce in UK SMEs’,
Journal of Marketing Management, Vol. 24, Nos. 5–6, pp.489–516.
Woodside, A.G. and Biemans, W.G. (2005) ‘Modeling innovation, manufacturing, diffusion and
adoption/rejection processes’, Journal of Business & Industrial Marketing, Vol. 20, No. 7,
pp.380–393.
Yap, C.S. (1990) ‘Distinguishing characteristics of organizations using computers’, Information &
Management, Vol. 18, No. 2, pp.97–107.
Yin, R.K. (2013) ‘Validity and generalization in future case study evaluations’, Evaluation,
Vol. 19, No. 3, pp.321–332.
Young, R. and Jordan, E. (2008) ‘Top management support: mantra or necessity?’, International
Journal of Project Management, Vol. 26, No. 7, pp.713–725.
Zhu, K., Dong, S., Xu, S.X. and Kraemer, K.L. (2006) ‘Innovation diffusion in global contexts:
determinants of post-adoption digital transformation of European companies’, European
Journal of Information Systems, Vol. 15, No. 6, pp.601–616.

228
M
.
Z
amzee
r
et al.
Zhu, K., Kraemer, K. and Xu, S. (2003) ‘Electronic business adoption by European firms: a
cross-country assessment of the facilitators and inhibitors’, European Journal of Information
Systems, Vol. 12, No. 4, pp.251–268.
Zouaghi, I. and Laghouag, A. (2016) ‘Aligning key success factors to ERP implementation
strategy: learning from a case study’, International Journal of Business Information Systems,
Vol. 22, No. 1, pp.100–115.
Appendix 1
Interview script outline
Firm background:
1 What is your firm’s number of employees (small/medium enterprise) and types of
services provided?
2 What are the main challenges/benefits of running your IT operations on-premises?
3 Why has your firm decided to use/not to use ERP cloud services?
Level of IS innovations adoption and use in the firm:
4 What are the technologies that are currently used in your firm (or think about using)?
(i.e., ERP, email application, CRM, data storage, CPU usage, etc.)?
5 To what extent do you feel your firm is aware of cloud computing?
Impact of TOE Factors on cloud computing adoption:
If we classify these factors into three groups (technological, organisational and
environmental):
6 What technological factors do you think may impact the adoption of ERP cloud in
your firm?
Why?
7 What is the impact of (relative advantage, uncertainty, compatibility, complexity,
and trialability) on the adoption of ERP cloud?
8 What organisational factors do you think may impact the adoption of cloud
computing in your firm?
Why?
9 What is the impact of (firm size, top management support, innovativeness, cost, and
prior IT experience) on the adoption of ERP cloud?
10 What environmental factors do you think may impact the adoption of cloud
computing in your firm? Why?
11 What is the impact of (competitive pressure, industry, market scope, supplier efforts
and external computing support, data centre location, political situation) on the
adoption of ERP cloud?