Toward an Understanding of Government Cloud Acceptance

A Quantitative Study of G-Cloud Acceptance by Saudi Government Agencies using

Extended UTAUT

Maha A. Al Rashed and Mutlaq B. Alotaibi

Department of Computer and Information Sciences, Al-Imam Muhammad Ibn Saud University, Riyadh, Saudi Arabia

Keywords: Cloud Computing, Government Cloud, Technology Acceptance, Unified Theory of Acceptance and Use of

Technology (UTAUT), Trust.

Abstract: With today’s rapid advances in Information and Communication Technologies (ICT), an increasing number

of governments worldwide are seeking solutions to enhance their IT infrastructures and services, and

reshape their e-government systems to meet public needs of providing easily accessible, cost-effective, high

quality, and reliable e-services. In recent years, government cloud (G-Cloud) has emerged as a new and

innovative computing paradigm with a promising opportunity for many governments to rationalize the way

they manage their services and resources. Government cloud’s potential benefits has been recognized by

many governments around the world. This paper will study the acceptance of cloud computing technologies

and services in Saudi government agencies by investigating the significant and influential factors that affect

the behavioral intentions to use G-Cloud. Moreover, in light of the rising concerns over trust issues in cloud

computing which have been reported to be one of the major barriers to the adoption of the cloud, the study

proposes an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model by

incorporating trust as a key factor in the acceptance of G-Cloud.

1 INTRODUCTION

Over the last decade, the adoption of ICT solutions

in the public sector has been recognized as a

strategic tool to enable governmental reforms

(Charalabidis et al., 2010). E-government systems

and applications are now increasingly leveraging

new technological developments and this trend

seems to continue at a great pace in the future. It has

been noted that e-government initiatives are aimed

beyond providing citizens with government

information and services into providing permanent

access with transparency in government activities

and services (Kurdi et al., 2011). Furthermore, there

is a need for e-government systems to be redesigned

and revised to meet public needs and governments’

own demands. It is mainly due to the inflation of the

data in e-government systems, complexity in

operation flows, and difficulties in business

collaboration (Liang, 2012). With regard to this

issue, cloud computing has emerged at the right time

to solve these challenges by promoting economies of

scale to increase business agility and lower IT costs.

To this extent, governments are considering the real

value of incorporating the cloud into their practices

and making full use of cloud computing potentials

for higher working efficiency and better public

services (Liang, 2012). This new initiative involves

applying cloud computing model to the business

processes of e-government and building government

cloud (G-Cloud) (Zhang and Chen, 2010).

The Government of Saudi Arabia has recognized

the tremendous potentials of the cloud and accorded

it a considerable amount of attention. According to

the Communications and Information Technology

Commission (CITC), the spending on cloud services

in Saudi Arabia has been increased enormously

between 2011and 2014 by 373%. Moreover, it is

expected that cloud services market will expand at a

CAGR of 36.6% through 2019, surpassing SAR 898

million; making the cloud one of the fastest growing

segments in the Saudi ICT market (CITC, 2015).

This paper aims to study the acceptance of G-

Cloud among government agencies. Specifically, it

will examine the acceptance of cloud computing

technologies and services in Saudi government

agencies by studying the key factors that influence

the behavioral intention to use G-Cloud which, in

turn, affect the actual use.

Rashed, M. and Alotaibi, M.

Toward an Understanding of Government Cloud Acceptance - A Quantitative Study of G-Cloud Acceptance by Saudi Government Agencies using Extended UTAUT.

In Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016) - Volume 1, pages 239-244

ISBN: 978-989-758-182-3

239

A relatively extensive amount of research has

been done to study the factors that influence

organizations’ decisions to adopt cloud computing

technologies. However, there is a limited research on

cloud adoption and usage in the context of e-

government. Moreover, as governmental operations

involve sensitive and critical data, and as cloud

computing implies risky conditions and uncertainty

about data security and safety due to the lack of

control and confidence in entrusting sensitive

information to cloud service providers, trust has

been reported to be a major concern (Kanwal et al.,

2013). Indeed, scholars agree that lack of users’ trust

is a key inhibitor to the adoption of cloud services

especially in domains where confidential and

sensitive information is involved (Ko, Lee and

Pearson, 2011). To the best of our knowledge there

is limited research on the acceptance of government

cloud, and no studies have considered trust as a key

factor when investigating G-Cloud acceptance

among government agencies. While the focal point

of the majority of studies in the relevant literature

was on the benefits and concerns of G-Cloud, other

studies focused on finding approaches and models to

build trust in the cloud. This issue presents a gap in

the research field which this study is addressing by

proposing an extended UTAUT model to account for

trust as a main construct.

2 LITERATURE REVIEW

2.1 Government Cloud Computing

Government Cloud (G-Cloud) is an emerging

paradigm, in which cloud computing is utilized to

redesign the business processes of e-government

system for allocation, management, distribution and

maintenance of IT resources of governments via the

internet (Liang, 2012). It has revolutionized how

governments operate; governments are leveraging

the cloud for its flexibility, scalability, accessibility,

elasticity, and substantial cost savings. Thus, this

innovative step of moving to the cloud can lead to

improved government transparency, accountability,

and service value (Zhang and Chen, 2010).

The G-Cloud model can help governments to

dramatically cut costs associated with large and

expensive IT infrastructures required to support

government agencies’ work. It also reduces the

burden of IT administration, maintenance, and

upgrades as it shifts to cloud providers (Khan et al.,

2011). G-Cloud provides government organizations

with greater ability to focus on core business and

mission-critical processes and outsource non-critical

applications to service providers (Wyld, 2010).

Moreover, it supports resource and information

sharing and business collaboration among different

departments and agencies within the government

which has been perceived as one of the biggest

benefits of moving to the cloud (Wyld, 2009).

The cloud movements in the public sector are

spreading all around the world; the literature

highlights many early government cloud computing

initiatives that have been undertaken by

governments in a number of worldwide countries.

The USA, UK, Thailand, China, New Zealand and

Germany have introduced and used cloud computing

in the public sector, and realized budget reductions

and high-efficiency green IT implementation (Shen,

Yang and Keskin, 2012). Australia, Singapore, and

Japan are among the most active countries for

government-led implementation of the cloud model.

These countries are leveraging cloud computing as a

solution for e-government efficiency, business

innovation, IT development, and cost reduction

(Seo, Min and Lee 2014).

2.2 The Unified Theory of Acceptance

and use of Technology (UTAUT)

Several models and theories have been developed

and surfaced over the last three decades to help

explain users’ acceptance and use of IT. Such

models include the Theory of Reasoned Action

(TRA), the Theory of Planned Behavior (TPB), the

Technology Acceptance Model (TAM), and the

Diffusion of Innovation (DOI). Central to this study

is the Unified Theory of Acceptance and Use of

Technology (UTAUT), a comprehensive and widely

accepted framework that had been formulated by

Venkatesh et al. (2003) by integrating the findings

of eight prominent technology acceptance models. It

addresses the limitations and shortcomings identified

in previous models by combining determinants from

various acceptance theories, and thereby providing

superior advantage. Venkatesh et al. (2003) argued

that this model is able to explain variance in IT

behavioral intention and usage behavior better than

the previous ones. The theory holds that four key

constructs: performance expectancy, effort

expectancy, social influence, and facilitating

conditions are direct determinants of usage intention

and behavior; along with four moderating variables

of gender, age, experience, and voluntariness of use

are posited to moderate the impact of the core

constructs on use intention and behavior (Venkatesh

et al., 2003). The UTAUT model validity, reliability

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and comprehensiveness in technology adoption have

been tested and proven on large real world data sets

in various contexts (Im, Hong and Kang, 2011). It

has been featured prominently in studies concerning

IT acceptance such as cloud based e-government

services (Lian, 2015). Accordingly and given the

robust theoretical background of this model and its

suitability for the context of the study, this study

adopt UTAUT as the primary theoretical framework

to examine users’ acceptance of G-Cloud.

2.3 Trust as an Extension to the

UTAUT Model

As cloud computing involves third parties storing

and processing sensitive data, and it requires

individuals and organizations to transfer some or all

control of their data and computing resources to

cloud service providers, trust-related concerns arise

(Khan and Malluhi, 2010). Indeed, trust is widely

perceived as a key concern for cloud consumers,

whether they are end users or organizations; they are

worried about who have access to their data and how

it will be shared and used (Pearson, 2013). It has

been reported that the fear of loss of control over

data is a major inhibitor to the adoption of the cloud

in Saudi Arabia (CITC, 2015). However, according

to CITC, as Saudi organizations develop trusting

relationships with their service providers, this will

boost adoption and usage.

Scholars from various research disciplines

believe that trust is crucial in enabling relations and

exchanges that involve uncertainty, interdependence,

or fear of opportunism (Bradach and Eccles, 1989).

That is, it is most needed in risky situations (Kim,

Ferrin and Rao, 2008). Mayer, Davis and

Schoorman (1995) define trust as “the willingness of

a party to be vulnerable to the actions of another

party”. Consistent with this conceptualization of

trust and related literature, this study defines trust as

the user’s willingness to accept vulnerability based

on his/her beliefs and positive expectations that the

cloud provider will perform fairly and reasonably as

expected, and that using the cloud will result in

positive outcomes due to the provider’s integrity and

competences.

Scholars believe that the adoption of IT can

involve high levels of uncertainty, especially when

challenged with the emergence of a new technology

(Kirs and Bagchi, 2012). Therewith, trust has been

recognized as a key driver for adoption due to its

relevance to deal with uncertainty and the risk of

vulnerability which are present mostly in online

contexts (Gefen, Karahanna and Straub, 2003). The

abstract and distributed nature of the cloud

technology besides the associated uncertainty pose a

considerable obstacle for the acceptance of cloud

based solutions (Martucci et al., 2012). Thus, this

study has expanded upon the UTAUT model by

incorporating trust as a key factor to better

comprehend the acceptance of G-Cloud.

Extant research that has examined trust in online

environments with respect to consumer–vendor

relationships has suggested a generic model of trust

that, in essence, concerns two targets: the entity or

vendor providing the online service and the

technology itself through which the service is

provided (Schaupp, Carter and McBride, 2010).

Pavlou (2003) argued that when consumers willingly

become vulnerable to online vendors, they consider

both the characteristics of the e-vendors due to

behavioral uncertainty, as well the characteristics of

the related technology due to environmental

uncertainty. Consistent with related scholarly

research, this study defines trust in terms of trust in

Cloud Service Providers (CSPs) as well as trust in

the reliability and integrity of the cloud technology.

In that sense, trust in government cloud can be

viewed as the user’s confidence in using the cloud,

and that the CSPs will fulfill obligations set forth in

an exchange. This conceptualization of trust implies

that users must have a certain level of confidence in

that cloud providers will behave capably

(competence), fairly (benevolence), and ethically

(integrity) (Adjei, 2015). These three dominantly

cited beliefs have been identified as key

characteristics for assessing trustees’ trustworthiness

(Burda and Teuteberg, 2014).

3 RESEARCH MODEL AND

HYPOTHESES

3.1 Research Model

As previous research has proved the validity of the

UTAUT framework in explaining a wide range of IT

acceptance and usage behavior, this study adopt the

UTAUT as the baseline model. However, in this

study, G-Cloud is a specific context that calls for

additional variables to extend the original UTAUT

to better explain variances. Thus, the study proposes

a modified UTAUT model that incorporates other

constructs for a better explanation of G-Cloud

acceptance. Figure 1 shows the research model and

associated hypotheses investigated under this study.

Toward an Understanding of Government Cloud Acceptance - A Quantitative Study of G-Cloud Acceptance by Saudi Government Agencies

using Extended UTAUT

241

Figure 1: Research Model.

3.2 Hypothesis Development

Performance expectancy (PE) has been constantly

found to be a significant predictor, if not the

strongest predictor, of intention to use IT (Venkatesh

et al., 2003). That is, users who perceive the

usefulness of a particular technology will be more

likely to adopt it. Prior cloud adoption studies have

shown the direct and positive effect of perceptions

of usefulness on the behavioral intention toward

using the cloud (Opitz et al., 2012). It has been

argued that increasing the awareness of users

towards the usefulness of using cloud services is

most likely to increase the acceptance of such

technology (Alharbi, 2012). Therefore, this study

has hypothesized that:

H1: Performance expectancy has a significant

positive effect on the behavioral intention to use G-

Cloud.

Effort expectancy (EE) refers to “the degree of

ease associated with the use of the system”

(Venkatesh et al., 2003). A system that is perceived

to be easier to use is more likely to induce the

behavioral intention of usage. Lian (2015) has found

that effort expectancy significantly affects user’s

behavioral intention toward using a cloud-based e-

government service. Opitz et al. (2012), in their

study on the acceptance of cloud computing by CIOs

and IT managers, have found that both perceptions

of usefulness and ease of use explained 66.4 % of

the variance in the behavioral intention to use cloud

based services. Thus, it is hypothesized that:

H2: Effort expectancy has a significant positive

effect on the behavioral intention to use G-Cloud.

Social influence (SI), in this study, revolved

around users’ beliefs that the behavior (using G-

Cloud services) is accepted, encouraged, and

promoted by their circle of influencers which in turn

tends to affect their behavioral intentions. The effect

of SI on intention to use technology has been shown

to be significant in several previous adoption

studies. Park and Ryoo (2013) have validated the

significant role of SI on users’ intention to use cloud

computing services. Alotaibi (2014) has pointed out

on the need to investigate the effect of social

influence on the intention to use the cloud in Saudi

Arabia as Saudis rely heavily on social models to

make decisions. Therefore, it is hypothesized that:

H3: Social influence has a significant positive

effect on the behavioral intention to use G-Cloud.

Consistent with Venkatesh et al. (2003)

definition, facilitating conditions (FC) refers to the

degree to which users believe that organizational as

well technical infrastructure supports the use of

government cloud and removes barriers to adoption.

The influence of facilitating conditions on IT usage

behavior has been investigated and validated in

several prior adoption studies. AlAwadhi and Morris

(2008) believe that the use of a new system is

expected to increase as users find support in using

the system. Lian (2015) argues that since cloud

based e-government services are relatively new and

innovative, unfamiliarity may hinder usage. Hence,

according to Lian (2015), the better the facilitating

conditions, the more likely people will be to use the

service. Thus, it has hypothesized that:

H4: Facilitating conditions has a significant

positive effect on the behavioral intention to use G-

Cloud.

In light of the inherent risks and uncertainties

surrounding the cloud environment, it is expected

that perceived risk would affect users’ intentions to

use cloud services. This study defines perceived risk

(PR) as the user’s belief of the potential and

uncertain negative outcomes of using the cloud. This

definition covers both forms of PR, behavioral and

environmental uncertainty, that have been identified

in the literature (Pavlou, 2003). According to

Pavlou, (2003), both behavioral and environmental

uncertainty involve privacy risks. In cloud

computing environment, scholars argue that the

cloud raises risks of security and privacy (Chi, Yeh

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242

and Hung, 2012). CITC has suggested that Saudi

organizations are generally reluctant to risks of data

security and privacy which are considered major

concerns and inhibitors to cloud services adoption

(CITC, 2015). Chi, Yeh and Hung (2012), in their

study of the effect of perceived risk on intentions to

use cloud services, has found that perceived risk

significantly and negatively affects usage intentions.

Therefore, it is hypothesized that:

H5: Perceived risk has a significant negative

effect on the behavioral intention to use G-Cloud.

The role of trust on IT adoption has been

investigated in many prior studies that consistently

found trust to exert a positive and direct effect on

behavioral intentions (Burda and Teuteberg, 2014;

Wu and Chen, 2005). Previous cloud adoption

studies have recognized trust to be a key predictor of

behavioral intention to use cloud services (Wu, Lan

and Lee, 2013). Thus, it is hypothesized that:

H6: Trust in G-Cloud has a significant positive

effect on the behavioral intention to use G-Cloud.

Prior empirical adoption studies have shown that

trust exerts an indirect influence on intention to use

via perceived usefulness and perceived risk. Gefen,

Karahanna and Straub (2003) argued that when

consumers initially trust e-vendors and believe that

adopting an online service is beneficial to their job

performance and productivity, they will perceive the

online service as useful. Burda and Teuteberg (2014)

have recognized trust to be a major determinant of

cloud adoption decisions that significantly reduces

perceived risk on the one hand, and increases

usefulness perceptions of cloud services on the other

hand. Kim, Ferrin and Rao (2008) have shown that a

consumer’s trust has a strong negative influence on

perceived risk; that is as trust increases, consumers

are likely to perceive less risk than if trust were

absent. Drawing from these findings, this study has

hypothesized that:

H7: Trust in G-Cloud has a significant positive

effect on performance expectancy.

H8: Trust in G-Cloud has a significant negative

effect on perceived risk.

Extant research has suggested that perceived

ease of use (PEOU) has a positive effect on trust

since it helps promoting consumers’ favorable

impressions on the e-vendor in the initial adoption of

an online service (Wu and Chen, 2005). This

argument is supported by the cognition-based trust

which is built upon first feelings and impressions

toward a certain behavior rather than through

experiences, which is relevant to the initial stages of

adoption (Gefen, Karahanna and Straub, 2003). Wu

and Chen (2005) provided empirical evidence that

PEOU influences trust and explains 19% of the

variance in trust. Thus, it is hypothesized that:

H9: Effort expectancy has a significant positive

effect on trust in G-Cloud.

4 CONCLUSIONS

Today, governments, due to the complexity of their

processes and massive data records and the need for

a powerful infrastructure, are almost obligated to

turn to new technological innovations to provide

better public information and services with lower IT

costs. Therefore, many government organizations

tend to exploit advanced technology trends such as

government cloud. Despite the appealing benefits of

the cloud, the adoption of such technology raises

various challenges including trust that has been

reported as one of the major barriers to the

widespread growth and uptake of the cloud. This

paper, as an attempt to address the gap in the

literature, proposes an extended UTAUT model that

accounts for trust as a key construct to investigate

the acceptance of G-Cloud by government agencies

in Saudi Arabia. Approaching this issue would be an

added value to the literature of e-government

practices, as well the literature of cloud computing.

Furthermore, understanding the factors affecting G-

Cloud acceptance through validated theoretical

foundation, is critical for effective and successful

implementation of this technology. As a matter of

fact, the understanding of these factors is useful to

both cloud computing adopters and providers.

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