View
0
Download
0
Category
Preview:
Citation preview
An Analysis of Citizens’ Trust in E-Government Services
and User Satisfaction and Their Impact on E-Services
Adoption in Pakistan Muhammad Shahid Tufail
*, Mohsin Bashir
†, Ayesha Sharif
‡ and
Riffat Noureen§
Abstract This study examines the impact of citizens‟ trust in e-government
services and user satisfaction associated with those services on
adoption level of e-government in Pakistan. Moreover, it reflects at the
mediating effects of citizens’ intentions to use e-services as well.
Population comprises of all citizens of Punjab Province using online
services, a total of 180 responses are collected through online survey
using adopted questionnaire. Findings reveal that „Trust‟ has
significantly positive impact on e-services adoption. Also, citizens‟
intentions to use fully mediate the relationship between citizens‟ trust
and e-services adoption. Furthermore, this research would benefit
policy makers in improving e-government services adoption.
Keywords: E-Government, Trust, E-Satisfaction, Intentions to Use, E-
Services Adoption, Pakistan.
Introduction
Pakistan is a country of 191 million people (Economic Survey of
Pakistan, 2015) and successive governments are striving to provide with
necessary services to the people of Pakistan at their doorsteps. Vision
2025 is also in line with this pursuit to establish Pakistan as a country of
e-governance. Conceptually, e-governance has drawn the attention of
researchers since long and many advanced economies have reaped the
benefits of such research. With the passage of time, they have been able
to implement true e-governance in their countries.
E-government has been turned in to an essential part of the
digital era since 1996 (Porter, 2003), so being an important topic
attracting more and more researchers (E. A. Abu-Shanab, 2017). The
concept of e-governance has no specific or concise definition but people
* Dr. Muhammad Shahid Tufail, Assistant Professor, Department of
Management, Lyallpur Business School, Government College University,
Faisalabad. Email: mshahidtufail@gcuf.edu.pk † Dr. Mohsin Bashir, Department of Management, Lyallpur Business School,
Government College University Faisalabad. ‡ Ayesha Sharif, Department of Marketing, Lyallpur Business School,
Government College University Faisalabad. § Riffat Noureen, Department of Public Administration, Government College
University, Faisalabad
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 492 Volume XI Number 03
tend to perceive it invariably in different ways. Halchin (2004)highlights
that there is no widely shared definition of e-Government yet and
Wimmer (2002)argues that “everybody talks about e-Government but all
have different interpretations”. Several definitions have been given by
several researchers time to time ranging from too narrow to extremely
general or broadly reflecting concept of e-government (Azab,
2009).Vassilakis, Lepouras, Fraser, Haston, and Georgiadis (2005)define
e-government assuccessively increasing use of Information Technology
in the society and in the government business. Both society and the
government become adaptive to new information and technology
advancement for the mutual benefits. Eventually the government
provision of information leads to the transactions of the business and
masses expect from the government to get every transaction to be carried
out electronically. Jaeger and Thompson (2003) explain government to
be a provision of government information through the internet to the
citizens and among government agencies. Rapid developmental changes
in the internet and its services have allowed the governments to provide
their services to citizens and others in new ways and how these
governments handle their operations inside. By its implementation, the e-
Government has transformed under revolutionary developments and seen
improvements in governments‟ functional abilities. The concept of
electronic-government may be examined in relation with citizens,
businesses, government employees and other sectors of
governments(Chadwick & May, 2003; Jaeger, 2003) and by aggravating
interactions between government and these parties, e-government makes
the interactions more effective, efficient, convenient, friendly and
transparent. Countries like Pakistan has a great influence on the business
of the people and involved in all types of the businesses including
communication, water supply, and electricity in addition to the usual
businesses of government. Past studies such as Jooho Lee, Kim, and Ahn
(2011); Carter and Bélanger (2005)identifiedvarious categories of the e-
government businesses such as G2C (Government to Citizens), G2B
(Government to Business), G2G (Government to Government). Each of
these categories has different conceptual understanding and defines the
business of government in a specific manner. Indeed, it is the
categorization of the government interaction with the stakeholders. This
can be simply categorized as the interactional and transactional functions
of e-governance. For example G2C category provides basic e-services to
the citizens such as license renewals and offers a single-point-of-access
anywhere and anytime to the citizens to see release of government
services, benefits and loans (McClure, 2001).McClure (2001)noted the
government‟s ability to expand electronic tax products as one example of
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 493 Volume XI Number 03
G2B initiatives. G2G category establishes common procedures for
governmental agencies for example collection, processing, analysing,
verifying and sharing of birth, marriage and death records and G2E is a
subset of G2C services in which specialized services for government
employees are provided exclusively. In the G2E initiative, government
employees are given a common platform for online training and
development of human capital (McClure, 2001). Although interactional
dimensions, as aforementioned, of e-Government have emerged, the
whole purpose has been ensuring transformation of governments (Sabraz
Nawaz & Thelijjagoda, 2015).Figure1portrays the e-Government
dimensions and its interaction with each sector.
Figure1 Dimensions of E-Government Interaction
Source: (Sabraz Nawaz & Thelijjagoda, 2015; Siau & Long, 2006)
According to Ornager and Verma (2005); Siau and Long (2006);
Yildiz (2007)four modes of e-government are G2C (to make the
government citizen friendly), G2B (to cut red tape, reduce operational
cost and increase transparency in dealing with government agencies),
G2G (Intra governmental interaction to enhance internal efficiency of
governmental agencies) and G2E (to strengthen the relationship between
government and employees).
According the United Nations e-government survey,
“Comprising 30 percent of the world‟s land area, with approximately 4.3
billion people, Asia is the largest continent and the most populous. With
such diversity, the countries in Asia also exhibit varying levels of online
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 494 Volume XI Number 03
presence and development; with the Republic of Korea leading the world
ranking at number one in the 2014 survey, and other countries like
Afghanistan, Myanmar, Timor-Leste and Pakistan trailing among the
bottom 30 countries globally” (United Nations e-government survey,
2014, p. 27). Therefore, it is crucial to pay attention to the adoption
factors of e-government in Pakistan.
FIGURE 2 Countries Leading in E-Government at Both World and Regional Levels
Source: (United Nations e-government survey, 2014, p.)
In addition to this, Pakistan is ranked 6th in the world‟s most populated
countries and ranked 33rd having graphically large area country of the
world. Administratively, Pakistan has one central government at the
federal level and there are four provincial governments, one government
for Gilgit- Baltistan areas and one for Azad Kashmir. The lowest level of
government structure exists at District level. Economically, people in
Pakistan represent a diversified classification starting from richest to
poorest. Similarly, the provision of education facilities are also restricted
to developed areas in particular as compared to under developed areas; as
private sector is dynamically involved in developed areas. Accordingly,
the services of telecommunication and information technology are
limited to developed areas due to non-availability of proper infrastructure
in underdeveloped areas. The role of education in advancement of
information and telecommunication technology is lucid. Pakistan
unfortunately has a vivid demarcation of highly educated class group that
belongs to economically and geographically developed areas whereas,
the menace of underdevelopment restricts to areas which have poor
education infrastructures. Remote areas of Sindh and Khyber Pakhtoon
Khawah (KPK) provinces and whole of Baluchistan province
unfortunately are scuffled with this situation. The government intentions
to provide e-commerce services to all the people at the same time require
extensive undertaking of various congruent projects so as the information
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 495 Volume XI Number 03
technology and ICT services reaching to the masses with universal
access and usage. The Ministry of Information Technology and
Telecommunication (MITT) at the federal level is responsible for
carrying on the e-government project of government of Pakistan. It is
also responsible to coordinate with the provincial ministries to
compliment the task effectively. In August 2014, MITT has merged two
of its former divisions; E-Government Directorate and Pakistan
Computer Bureau into a single organization which is named as National
Information Technology Board (NITB). NITB has undertaken various
projects so far which have been successfully implemented.
Pakistan has low level of e-services adoption. Owing to the
lower internet usage, people has lower access to e-government services
(Rehman, Kamal, & Esichaikul, 2016). People still prefer traditional
communication to interact with government institutions to avail services.
Calling on a person in-person is still the first preference to be sure of
getting a service (Ahmad, Markkula, & Oivo, 2012; Malik, Shuqin,
Mastoi, Gul, & Gul, 2016). Literature shows Trust, Security, Privacy,
Lack of awareness and transparency are critical factors for e-government
services adoption in developing countries such as Pakistan(Ahmad et al.,
2012; Ahmed, Zin, & Majid, 2016; Malik, Shuqin, Mastoi, & Ghais,
2016; Malik, Shuqin, Mastoi, Gul, et al., 2016; Qureshi, Ilyas, Yasmin,
& Whitty, 2012; Rehman, Esichaikul, & Kamal, 2012; Rehman et al.,
2016). This study aims to delineate the factors affecting citizens‟ trust
and satisfaction level regarding use of government‟s e-services in
Pakistan. Moreover this study also explores the potential intervening
effects of citizens‟ intentions to use e-government services. In existing
literature, researchers have studied and applied the broader adoption
models such as UTAUT model and TAM etc. to analyze the influence of
trust &user satisfaction regarding government‟s e-services. But a few
studies have exclusively focused on the analysis of trust in e-government
and user satisfaction concerning its impact on e-services adoption.
Moreover it has been argued that previous researchers mainly focused on
e-government services from the supplier side; however the stakeholder‟s
or citizens‟ side has been overlooked and resulted in limited research
work in this perspective (Alzahrani, Al-Karaghouli, & Weerakkody,
2016; Jooho Lee et al., 2011; Thomas & Streib, 2003; Welch, Hinnant, &
Moon, 2005). This research has filled this gap by analyzing the impact of
trust and user satisfaction on e-services adoption from stakeholder‟s or
citizens‟ perspective.
Literature Review
“E-Government provides opportunities to move forward with
high quality, cost effective government services delivery and creation of
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 496 Volume XI Number 03
better relationship between the public and government”(Sharma, Bao, &
Peng, 2013). Invariably, various different names have been given to the
concept of e-government such as e-administration or e-democracy to
provide with the public services delivery (Baločkaitė, Morkevičius,
Vaidelytė, & Žvaliauskas, 2008).According tothe World Bank“E-
Government refers to the use of information technologies by government
agencies (such as wide area networks, the internet, and mobile
computing) that have the ability to transform relations with citizens,
businesses, and other arms of government. These technologies can serve
a variety of different ends: better delivery of government services to
citizens, improved interactions with business and industry, citizen
empowerment through access to information, or more efficient
government management. The resulting benefits can be less corruption,
increased transparency, greater convenience, revenue growth, and/or cost
reductions”(World Bank‟s e-Government website, 2015). In mid-1990s,
after the explosion of internet, e-government mechanism got impetus by
developed countries (Chadwick & May, 2003). Later on, with the
development of communication technologies, e-government turns the
attention of all the countries around the globe.
In Pakistan, internet trend was emerged in 1995 and since then
ICT has become one of the fastest growing industry in the country.
However, Pakistan has low level of e-services adoption. People still
prefer traditional communication to interact with government institutions
to avail services. Calling on a person in-person is still the first preference
to be sure of getting a service (Ahmad et al., 2012).
Trust in E-Government
Trust has direct linkage with the beliefs of the citizens. This belief has
duality in nature; firstly, the belief in government services and secondly;
believing in the internet technology (Bélanger & Carter, 2008; Carter &
Bélanger, 2005; Pavlou, Tan, & Gefen, 2003; Rehman et al., 2012). First
kind of trust establishes that the services being offered by the
government are exactly the same as desired by the citizens and second
type of trust is that the internet is not providing harm to the individual.
Trust in internet means “the trust levels that citizens have on internet and
its related applications” (Mofleh and Vanous, 2008, p. 4). Trust in
government means “the trust level that citizens have in the government”
(Mofleh and Vanous, 2008, p. 4). Gatautis (2015) highlights, that ICT
can be used proficiently, only if it is trusted. Baier (1986) states that trust
factor involves such a belief that nobody will take one‟s advantage or
produce any harm as well. Level of adoption is a predictable
phenomenon which is linked to the level of trust and confidence. On the
other hand, Citizens‟ belief posits the view that the government has
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 497 Volume XI Number 03
necessary administrative and technical skills to make sure that every
service being offered is safe and secured. The belief and trust in safety of
transaction lead to the higher level of adoption. Similarly the citizens
believe that the transaction being carried out electronically is exactly the
same as being carried out by visiting any office of the government will
lead to adoption of e-Government systems. Likewise, adopting e-
Government services must engage citizens to encompass the intentions to
receive and provide information through on-line channels (Warkentin,
Gefen, Pavlou, & Rose, 2002). The governments are expected to
implement necessary strategies to enhance the level of confidence and
trust of the citizens in adoption of e-services.
In most of the past studies, trust has been taken as an element to
facilitate the adoption of new technologies such as Technology
Acceptance Model and Diffusion of Innovation Theory (Bélanger &
Carter, 2008). The earlier researchers have identified that the trust was a
key element in adoption of internet, e-governance, perceived usefulness
of government services and quality of services (S. E. COLESCA,
2007)and the people who have higher degree of propensity to trust are
generally able to exhibit more trust in the e-government (Mayer, Davis,
& Schoorman, 1995).
Determinants of trust in e-government: In line with the
previous studies, a view can be established that IT literacy, perceived
organizational trustworthiness, trust in technology, privacy and security
concerns and risk perceptions may influence one‟s trust level in e-
government services (E. A. Abu-Shanab, 2017; S. Alateyah, Crowder, &
Wills, 2013; Alomari, Woods, & Sandhu, 2012; Carter & Bélanger,
2005; Cole & Kelsey, 2004; S. Colesca & Dobrica, 2008; S. E.
COLESCA, 2007, 2015; Cremonini & Valeri, 2003; Cronin, 1995;
Croxall & Cummings, 2000; Kamiński, 2010; JinKyu Lee & Rao, 2007;
Malik, Shuqin, Mastoi, Gul, et al., 2016; Picciano & Seaman, 2009;
Sabraz Nawaz & Thelijjagoda, 2015; Tassabehji, Elliman, & Mellor,
2007; Van de Walle & Bouckaert, 2003; Warkentin et al., 2002).
User Satisfaction
User satisfaction is known as one of the most momentous stimuli for
adoption of e-government (Weerakkody, Irani, Lee, Hindi, & Osman,
2016).Citizens‟ satisfaction in e-services provided through any form of e-
government is the key to success. The level of satisfaction may link to
the level of technological security and the efficacy of the governmental
plans. World leading organizations such as United Nations, World Bank
which operate at world level and the organization which operate at
country specific level also measures true level of citizens‟ satisfaction
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 498 Volume XI Number 03
associated with usage of e-services using different indices and methods
provided by the governments (Alawneh, Al-Refai, & Batiha, 2013).
A large number of influencing factors have been identified in
past researches which lead to satisfaction of the citizens in e-services.
Accessibility of information, trust in technology and government plans,
perceived security and privacy, quality of public services, knowledge of
acquiring the public services and machine anxiety are the founding
factors which play a vital role in satisfaction (Malik, Shuqin, Mastoi,
Gul, et al., 2016). These factors were also the main focus of studies in
various past researches and substantiated by (Batini, Viscusi, &
Cherubini, 2009; Christian Schaupp & Carter, 2005; Eid, 2011; H. Lee,
Choi, & Kang, 2009; Tung & Rieck, 2005; Verdegem & Verleye, 2009;
Welch et al., 2005; Zavareh et al., 2012). In Pakistan, there are not many
studies available to strengthen the literature on the subject, especially the
studies and researches on e-Learning, e-Government or e-Health. The
research literature in most of the studies entirely depends on the studies
which were carried out in developed countries (Verdegem & Verleye,
2009)to be a base of work for the studies being carried out in Pakistan. In
a recent study (Malik, Shuqin, Mastoi, Gul, et al., 2016) which was
carried out in Pakistan to investigate the perception of e-Government
services provided by the Punjab Government (a larger province
government in Pakistan) defined e-satisfaction as the feeling and
perception of the users on the quality of information procured so securely
that force the users to use e-services portal continuously.
Determinants of e-satisfaction: Literature shows citizens‟
satisfaction towards e-government services is influenced by awareness,
service quality, accessibility and machine anxiety (AlNuaimi, Shaalan,
Alnuaimi, & Alnuaimi, 2011; Choudrie & Dwivedi, 2005; S. Colesca &
Dobrica, 2008; Delone & McLean, 2003; Dong, Xiong, & Wang, 2011;
Gummerus, Liljander, Pura, & Van Riel, 2004; Kang & Lee, 2010; H.
Lee et al., 2009; Lin, Luo, Cai, Ma, & Rong, 2016; Malik, Shuqin,
Mastoi, Gul, et al., 2016; McKnight, Choudhury, & Kacmar, 2002;
Meuter, Ostrom, Roundtree, & Bitner, 2000; Oliver, 1999; Park & Kim,
2003; Rust & Lemon, 2001; Wang & Liao, 2008)
Intentions to Use The intentions to use are the willingness or extent to which users want to
use that particular technology to acquire a service(Gupta, Dasgupta, &
Gupta, 2008; Warkentin et al., 2002). The positive intentions lead to
positive actions as well as supportive behaviors. Adoption model
emphasize on the positive intentions to be a key element in using any e-
service provided by a government. Key element which carry out
executable intentions are quality of product or service (Oliver, 1999)and
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 499 Volume XI Number 03
various other studies have also confirmed this phenomena of behaviors
(S. A. Alateyah, Crowder, & Wills, 2012). Trust in product or service
quality and security of privacy lead to positive intentions whereas e-
readiness requires quality of web designing, culture of accepting
technologies and lesser machine anxiety (Chen & Chang, 2012).
Citizens’ Adoption Adoption is an important facet for the success of e-government projects
(S. A. Alateyah et al., 2012). Adoption of e-service is the totality of a
behavior which is desired by the service provider. Success of a service
largely depends on the level of adoption and its acceptance as a useful
service (Carter & Bélanger, 2005). In most of the developing countries,
adoption of e-government services is still in its primary stage. The
rewarding benefits of its adoption depend on the efforts of both the
government‟s as well as citizens‟ end (Sabraz Nawaz & Thelijjagoda,
2015). Willingness of the intended users can be triggered by the
governments by applying various communication tools. Experiences of
the users for direct contact with a technology may lead to positive
intentions to adopt it (AlAwadhi & Morris, 2008). Technology adoption
rate is usually higher in developed countries as established in past studies
(Titah & Barki, 2006; Venkatesh, Morris, Davis, & Davis, 2003),
whereas the adoption rate has been assessed as relatively low and
delayed in developing countries (AlAwadhi & Morris, 2008; AlShihi,
2005). In developing countries, adoptability of any e-government
initiative largely depends upon the customization of communicable part
and friendly interface development of the service (Yonazi, Sol, &
Boonstra, 2010). Complex formulation of communicable part and
stringent interfaces may lead to avoidance or resistibility (Heeks &
Andrade, 2007). Additionally, non-customization in web designing may
pose a challenge to technology or service adoption for the government
initiatives (Yonazi et al., 2010). Adoption is an important aspect for the
success of e-government initiatives in developing countries (Yonazi et
al., 2010). Many researchers focused on user‟s adoption of e-services
(Carter & Bélanger, 2005; Gefen & Straub, 2000; Pavlou et al., 2003;
Warkentin et al., 2002)but few studies provided empirical evidence to
identify critical factors affecting adoption level of e-government
services(Al-Adawi, Yousafzai, & Pallister, 2005; Kumar, Mukerji, Butt,
& Persaud, 2007).
Theoretical Framework
This study develops a theoretical framework by incorporating
factors affecting citizens‟ trust and satisfaction with e-government
services that in turn impact their intentions to use and subsequent level of
e-services adoption in Pakistan.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 500 Volume XI Number 03
Trust in E-Government and Intentions to Use
According to Carter and Bélanger (2005), trustworthiness is a significant
predictor of citizens‟ intentions to use e-services. Moreover previous
researches showed that trust in e-government positively influences
citizens‟ intentions to use e-government services (E. Abu-Shanab, 2014;
Al-Shbiel & Ahmad, 2016; Alzahrani et al., 2016; Carter, Weerakkody,
Phillips, & Dwivedi, 2016; Jayashree, Salehi, Abdollahbeigi, &
Malarvizhi, 2016; Rehman et al., 2016; Venkatesh, Thong, Chan, & Hu,
2016). Researchers defined trust as one‟s willingness to be vulnerable to
others along with expecting positive intents toward one‟s interest (E.
Abu-Shanab, 2014). Furthermore, some researchers described the
influence of trust on e-government adoption as a process where trust
antecedents build a momentum to citizens‟ trust in e-government
services and itis expected that higher level of trust would result in higher
level of e-services usage and adoption (E. Abu-Shanab, 2014; Beldad,
van der Geest, de Jong, & Steehouder, 2012; Carter &Campbell, 2011;
Ranaweera, 2016; Rehman et al., 2012). Previous research also shows
that lack of trust is a noteworthy barrier in e-government adoption
(Carter & Weerakkody, 2008)
User Satisfaction and Intentions to Use
Updated D&M IS success model (2003) indicates that User satisfaction
impacts citizens‟ intentions to use e-government services, which in turn
have effects on e-services adoption(Zhou, 2013). de Oña, de Oña, Eboli,
Forciniti, and Mazzulla (2016) found that behavioral intentions are
affected by level of user satisfaction with the service. Moreover, it is also
one of the momentous factors that influence e-government adoption
(Weerakkody et al., 2016).
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 501 Volume XI Number 03
Figure3 Delone and Mclean’s updated model
Source: (Delone & McLean, 2003)
Intentions to Use and E-Government Services Adoption
Adoption comes with individual‟s direct experience to that particular
technology and when the individual has decided to accept it as well, as it
is evident by previous researchers that individual must have intentions to
engage in e-government services for its adoption (AlAwadhi & Morris,
2008; Venkatesh et al., 2003; Warkentin et al., 2002). Adoption of e-
government services is influenced by user satisfaction and their
intentions to use e-services (Alzahrani et al., 2016).Ahmed et al.
(2016)found positive relationship between intentions to use and
e-services usage/adoption.
Research Model and Hypotheses Development
In line with the previous studies and literature review, it is considered
that Trust in E-Government and User‟s E-Satisfaction are two main
influencing factors that affect the level of E-Services Adoption. Also, it
can be assumed that intentions to use mediate the relationship among
IV‟s (Trust in E-Government & User‟s E-Satisfaction) and DV‟s (E-
Services Adoption).
Figure 4 integrated research model to analyze trust in e-government and user
satisfaction and their impact on e-government services adoption
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 502 Volume XI Number 03
Positively Effecting
Negatively Effecting
Figure 5 Breakdown Analysis Of The Research Model
Keeping in view the above discussion and literature review, research
hypotheses have been developed as follows:
H1: Trust in E-Government has positively significant effect on E-
Services adoption
H2: E-Satisfaction has positively significant effect on E-Services
adoption
H3: Intentions to Use has positively significant effect on E-Services
adoption
H4: Intentions to Use mediates the relationship between Trust in E-
Government and E-Services Adoption
H5: Intentions to Use mediates the relationship between E-Satisfaction
and E-Services Adoption
Research Methodology
Sample and Data Collection Procedure
Researcher has applied stratified random sampling technique along with
quantitative approach for data analysis through adopting questionnaire. A
period of two months has been set for final data collection from sample
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 503 Volume XI Number 03
respondents and total 180 responses were collected from citizens of
Punjab (Faisalabad)via online survey using five point Likert scale
questionnaire.
According to Cochran (2007), stratified random sampling
technique is applied when the whole population could be divided into
subgroups called strata and then random sample can be taken from each
stratum or group. In this research, population has been divided into three
stratums; employees in government sector, employees in business sector
and general citizens/ self-employed. Based on Previous Research &
literature review (Bélanger & Carter, 2008), in order to increase
generalizability in this research, responses were collected from a diverse
group of citizens. Hence, sample unit was selected randomly from each
Stratum; employees in government sector; employees in business sector
and general citizens. Moreover stratified sample size was selected as
20% respondents of each stratum.
Questionnaire is compiled from the validated instruments in the
literature to represent each construct, and wording has been modified to
fit in the E-Government context. Each construct items were adapted from
previous studies. Each Item is rated on a Likert scale of 1-5 (Strongly
Disagree to Strongly Agree). Moreover, the online questionnaire was
consisted of total 55 different questions. Table 1 presents the summary of
the sample used in this study.
(INSERT TABLE 1 HERE)
Measures
Trust in e-government: This variable has been calculated as a
composite variable of six factors (IT Literacy, Propensity to Trust, Trust
in Technology, Perceived Organizational Trustworthiness, Privacy
Concerns and Risk Perceptions). Moreover, total 24 items were taken to
measure this variable.
IT literacy: 3 item scale Adapted from Qureshi et al. (2012). For
example “I have the necessary skills for using e-government
services.” is a sample item to measure this factor.
Propensity to trust:3 item scale developed by S. E. COLESCA
(2007). For example “It is easy for me to trust a person/thing” is a
sample item to measure it.
Trust in technology:3 items scale developed by S. E. COLESCA
(2007). For example “I believe the technologies supporting the
system are reliable all the time.” is a sample item to measure this
factor.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 504 Volume XI Number 03
Perceived organisational trustworthiness:4 item scale developed by
S. E. COLESCA (2007).For example “I think I can trust government
agencies” is a sample item to measure this factor.
Privacy concerns:5 items scale developed by S. E. COLESCA
(2007). For example “My personal information given to a
governmental website may be shared with other government agents
to whom I do not want to provide the information” is a sample item
to measure this factor.
Risk perceptions:6 item scale developed by S. E. COLESCA (2007).
For example “I feel vulnerable when I interact with an e-government
service” is a sample item to measure this factor.
E-satisfaction: This variable has been calculated as a composite variable
of four factors (Awareness, Service Quality, Accessibility and Machine
Anxiety). Total 23 items were taken to measure this variable.
Awareness: 5 item scale developed by Malik, Shuqin, Mastoi, Gul,
et al. (2016). For example “I receive enough information about the
Govt. of Pakistan (GOP) e-portal.” is a sample item to measure this
factor.
Service quality:10 item scale developed by Malik, Shuqin, Mastoi,
Gul, et al. (2016).For example “GOP portal enables me to
accomplish governmental transactions more quickly” is a sample
item to measure this factor.
Accessibility:5 item scale developed by Malik, Shuqin, Mastoi, Gul,
et al. (2016).For example “GOP portal design is very efficient.” is a
sample item to measure this factor.
Machine anxiety: 3 item scale developed by Malik, Shuqin, Mastoi,
Gul, et al. (2016).For example “When I use GOP portal I fear of
losing my personal data” is a sample item to measure this factor.
Intentions to use e-services: Four items scale developed by Bélanger
and Carter (2008)to measure this variable. “I would use the Web for
gathering government information” is a sample item incorporated in
the scale.
E-services adoption: Four items were adapted from the scale developed
by Devi Juwaheer, Pudaruth, and Ramdin (2012); (Zhou, 2013). “I save a
lot of time using GOP e-Portal because I don‟t have to visit the offices
personally” is a sample item incorporated in the scale.
Control variables: Earlier research identifies that demographic
characteristics (age, gender, education, income, IT experience) may
influence the level of trust in e-government(S. Colesca & Dobrica, 2008;
S. E. COLESCA, 2007; Malik, Shuqin, Mastoi, Gul, et al., 2016)and it
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 505 Volume XI Number 03
would have ultimate effect on E-Services Adoption. In order to avoid
potential impacts of these variables on our dependent variables, current
research has controlled all these confounding variables. In order to avoid
potential impacts of these variables on our dependent variables, current
research has controlled all these confounding variables.
Analytical Strategy
Correlation and regression analysis were performed to test the study
hypotheses. Effects of mediator (Intentions to use e-services) were tested
using a statistical procedure suggested by Baron and Kenny (1986).
Since, study hypotheses involve indirect effects such sorts of mediation
hypotheses are usually conducted using Baron and Kenny procedure
(Baron & Kenny, 1986).Researcher used exploratory factor analysis
(EFA) as Data exploration technique. Moreover, before applying
regression analysis, data was first checked for all the assumptions like
missing values, outliers and multicollinearity issues etc., to make it pure
and fit for further analysis.
Analyses and Results
Respondents’ Demographic Profile
Table 1 presents demographic profile of the respondents. Of the overall
respondents (n=180), there were 149(82.8%) men while the women were
31(17.2%). The woman were less in number than men. Ratio and
frequency distribution of participants by age indicate that the largest
number (93) of participants were relatively younger generations of less
than 30 years of age. As far as educational qualifications are concerned,
87% respondents obtained postgraduate to doctorate degrees whereas
only 17% of the respondents were at lesser level of education. The
frequency distribution and ratio by participant‟s Marital Status show that
highest number of respondents 93(51.7%) were married. Moreover, the
frequency distribution and ratio by participant‟s Economic Sector show
that highest numbers of respondents (63.3%) were Government sector
employees.
(INSERT TABLE 2 HERE)
Reliability Analysis
Table 3 shows overall consistency of the measurement instrument and
very high value of alpha coefficient α=0.9, indicate that questionnaire
was developed with good internal consistency, as alpha value exceeding
0.70 is considered as highly acceptable(Guilford, 1965).
(INSERT TABLE 3 HERE) Moreover, Table 4 shows reliability values for each of the study
construct individually (Trust in E-Government, E-Satisfaction, Intentions
to Use and E-Services Adoption).
(INSERT TABLE 4 HERE)
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 506 Volume XI Number 03
Correlation Analysis
Table 5 presents results of correlation analysis which indicate that Trust
in E-Government has a significantly positive correlation with E-
Satisfaction (r= .502, P< 0.01), Intentions to Use (r= .380, P<0.01) and
E-Services Adoption (r=.380, P< 0.01).E-Satisfaction has a strong
positive correlation with Intentions to Use (r= .650, P<0.01) and E-
Services Adoption (r=.652, P<0.01). Moreover, results also indicate
strong positive correlation between Intentions to Use and E-Services
Adoption (r=0.752, P<0.01). Thus, Trust in E-Government, E-
Satisfaction and Intentions to Use are playing a vital role in E-Services
Adoption.
(INSERT TABLE 5 HERE)
Exploratory Factor Analysis
EFA helps the researcher in identifying standard loads for each item
which should be equal to or more than 0.5 (Hair et al., 2006). In order to
run the EFA, it is important to conduct the test for KMO value and
Bartlett‟s test of sphericity. The KMO value > 0.5 is considered
acceptable; whereas, Bartlett‟s test of sphericity must be significant with
value <0.05 to run EFA (J Pallant, 2011; Julie Pallant, 2013).
(INSERT TABLE 6 HERE) The SPSS results have shown KMO value as 0.665, which is considered
to be acceptable (>.5) and a significant Bartlett‟s test at P<0.000 as
shown in Table. According to these values data is statistically valid to
run EFA (J Pallant, 2011; Julie Pallant, 2013).Factor analysis has been
conducted on questionnaire items to check for internal validity. As
suggested in many academic journals, the items with loading <0.4 would
be deleted in the analysis and all the items with loadings ≥0.4 would be
retained for analysis (Floyd & Widaman, 1995; Tabachnick & Fidell,
2007). The EFA was conducted using principle component analysis
(PCA) and varimax rotation to extract factors and it is found that all the
retained factors were showing loadings as ≥0.5. Hence, all the items in
the questionnaire were proper measures of their respective constructs.
Regression Analysis
In order to evidence a mediating effect of Baron and Kenny
(1986)procedure, four conditions must be met, firstly; the impact of
independent variable on dependent variable must be significant,
secondly; the independent variable must impact the mediator, thirdly; the
mediating variable must have impact on the dependent variable, and
finally; effect of independent variable on dependent variable is checked
by controlling the effect of mediator and this change in effect is shown
by regression coefficient(∆𝑅2). In addition, by controlling mediator, if
impact of independent variable on dependent variable becomes zero it
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 507 Volume XI Number 03
means full mediation exists, if impact becomes less it shows partial
mediation and if no change in impact occurs, then mediation doesn‟t
exist at all.
(INSERT TABLE 7 HERE) The step 1 has been conducted to evaluate the impact of Trust in E-
Government & E-Satisfaction on E-Services Adoption. Coefficients table
shows UNIQUE effect size of each variable individually. Results showed
significant values of Trust in E-Government (p=.024) and E-Satisfaction
(p=.000) because it is greater than α (0.05). If p≤α, it means that null
hypothesis will be rejected and alternative hypothesis will be accepted.
The results show significant positive impact of User‟s E-Satisfaction and
Trust in E-Government on E-Services Adoption, hence first condition of
Baron and Kenny procedure is satisfied.
(INSERT TABLE 8 HERE) The Step 2 has been conducted to evaluate the impact of Trust in E-
Government and E-Satisfaction on Intentions to Use e-government
services. Coefficients table shows that p-value of Trust in E-Government
& E-Satisfaction are significant because these both values are less than α
(0.05). If p≤0.05, it means that null hypothesis will be rejected and
alternative hypothesis will be accepted. On the basis of above available
table, it can be concluded that Trust in E-Government and E-Satisfaction
has significant positive effect on Intentions to Use. Hence, second
condition of Baron and Kenny procedure is also satisfied.
(INSERT TABLE 9 HERE) The step 3 has been conducted to evaluate the impact of Intentions to
Use (IU) on E-Services Adoption. Coefficient table shows that p-value
(.000) of Intentions to Use is significant because it is less than α (0.05).
Thus, Intentions to Use has significant positive effect on E-Services
Adoption.
(INSERT TABLE 10 HERE) In summary table, model 1 results showed that independent variables
Trust in
E-Government & E-Satisfaction explained the variance of 44% on
dependent variable E-Services Adoption as shown by the value of
𝑅2(.441). Whereas, model 2 results showed that independent variables
Trust in E-Government, E-Satisfaction and Intentions to Use explained
the variance of 61% on dependent variable E-Services Adoption by
showing the value of 𝑅2(.612). Moreover, R square change showed 27%
change in variance by showing the value of ∆𝑅2(.171).
(INSERT TABLE 11 HERE) In model 1, Coefficients table showing that Trust in E-Government and
E-Satisfaction has significant p-values (less than α =.05). Whereas, in
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 508 Volume XI Number 03
model 2, by controlling the effect of mediator (Intentions to Use), p-
value of Trust in E-Government becomes insignificant (.591) while p-
value of E-Satisfaction remains unchanged (.000).
Results
Table 11 presents regression results of mediation hypotheses. In line with
the study hypothesis it was found that „trust in e-government‟ positively
impacts the level of e-services adoption in Pakistan as people are more
concerned about trusting factors such as privacy and risk perceptions
when using e-government services. Moreover citizens‟ intentions to use
e-services fully mediate the relationship between user‟s trust and e-
services adoption level.
(INSERT TABLE 12 HERE) Table 12 presents the summary of study hypothesis. In line with the
study hypotheses (H1, H2 & H3), correlation analysis results show that
„trust in e-government‟ and „e-satisfaction‟ are positively correlated with
„intentions to use‟ and „eservices adoption‟ (Table 5). Moreover,
regression analysis results confirmed the mediating role of „intentions to
use‟ in the relationship between „trust in e-government‟ and „e-services
adoption‟ which supports H4. Lastly, mediating effects of „intentions to
use‟ in the relationship between „e-satisfaction‟ and „e-services adoption‟
show that H5 is not supported (Table 11).
(INSERT TABLE 13 HERE)
Conclusion
Government of Punjab is taking various initiatives to deliver e-
government services to the citizens. However, huge investments are
allocated to the e-government projects but still these projects are not
functioning affluently. Current study reveals that trust and satisfaction
associated with e-government services are the major concerns of the
citizens that are affecting e-services adoption in Pakistan. Government
must take some initiatives to enhance citizens‟ trust and satisfaction
regarding usage and benefits of these services so that e-government
projects could be implemented successfully.
Discussion and Recommendations
This research has uncovered the underlying factors impeding e-
government services adoption, hence it would help e-governmental
policy-makers in decision making to ensure citizens „satisfaction and
raise e-services adoption level by taking appropriate actions. Also, this
study would attract researchers to carry out similar studies in other South
Asian developing countries so as to ensure availability of operational
data for better future decisions.
Like other technology adoption studies, this study is also
inherent with some limitations. The subject of the study was limited to
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 509 Volume XI Number 03
single city of Punjab (Faisalabad) having limited generalizability.
Although, many similar studies have been conducted in developed
countries as well as developing countries, the findings are still indecisive
and mixed, therefore further studies needed in this perspective. In this
research, two main predictors (trust in e-government and e-satisfaction)
were measured as a composite variable of various factors, so future
research may be conducted to find out the individual impacts of those
underlying factors of trust in e-government and e-satisfaction on E-
Services Adoption in Pakistan in developing countries.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 510 Volume XI Number 03
References
Abu-Shanab, E. A. (2017). E-government familiarity influence on
Jordanians‟ perceptions. Telematics and Informatics, 34(1), 103-
113.
Abu-Shanab, E. (2014). Antecedents of trust in e-government services:
an empirical test in Jordan. Transforming Government: People,
Process and Policy, 8(4), 480-499.
Ahmad, M. O., Markkula, J., & Oivo, M. (2012). Factors influencing the
adoption of e-government services in Pakistan. Paper presented
at the European, Mediterranean & Middle Eastern conference on
information systems.
Ahmed, U., Zin, M. L. M., & Majid, A. H. A. (2016). Impact of Intention
and Technology Awareness on Transport Industry‟s E-service:
Evidence from an Emerging Economy. The Journal of Industrial
Distribution & Business, 7(3), 13-18.
Al-Adawi, Z., Yousafzai, S., & Pallister, J. (2005). Conceptual model of
citizen adoption of e-government. Paper presented at the The
Second International Conference on Innovations in Information
Technology (IIT‟05).
Al-Shbiel, S. O., & Ahmad, M. A. (2016). A Theoretical Discussion of
Electronic Banking in Jordan by Integrating Technology
Acceptance Model and Theory of Planned Behavior.
International Journal of Academic Research in Accounting,
Finance and Management Sciences, 6(3), 272-284.
Alateyah, S., Crowder, R. M., & Wills, G. B. (2013). Factors Affecting
the Citizen‟s Intention to Adopt E-government in Saudi Arabia.
International Journal of Social, Human Science and
Engineering, 7(9), 80-85.
Alateyah, S. A., Crowder, R. M., & Wills, G. B. (2012). Towards an
integrated model for citizen adoption of e-government services.
International Journal of Information Technology and Computer
Science, 6, 47-57.
AlAwadhi, S., & Morris, A. (2008). The Use of the UTAUT Model in the
Adoption of E-government Services in Kuwait. Paper presented
at the Hawaii International Conference on System Sciences,
Proceedings of the 41st Annual.
Alawneh, A., Al-Refai, H., & Batiha, K. (2013). Measuring user
satisfaction from e-Government services: Lessons from Jordan.
Government information quarterly, 30(3), 277-288.
AlNuaimi, M., Shaalan, K., Alnuaimi, M., & Alnuaimi, K. (2011).
Barriers to electronic government citizens' adoption: A case of
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 511 Volume XI Number 03
municipal sector in the emirate of abu dhabi. Paper presented at
the Developments in E-systems Engineering (DeSE), 2011.
Alomari, M., Woods, P., & Sandhu, K. (2012). Predictors for e-
government adoption in Jordan: Deployment of an empirical
evaluation based on a citizen-centric approach. Information
Technology & People, 25(2), 207-234.
AlShihi, H. (2005). E-government development and adoption dilemma:
Oman case study. Paper presented at the 6th International We-B
(Working for e-Business) Conference.
Alzahrani, L., Al-Karaghouli, W., & Weerakkody, V. (2016). Analysing
the critical factors influencing trust in e-government adoption
from citizens‟ perspective: A systematic review and a conceptual
framework. International Business Review.
Azab, N. A. (2009). Assessing electronic government readiness of public
organizations. Communications of the IBIMA, 8(13), 95-106.
Baier, A. C. (1986). Moral Prejudices: Essays on Ethics (Cambridge,
Mass., 1995); idem,“. Trust and antitrust, 96, 231-260.
Baločkaitė, R., Morkevičius, V., Vaidelytė, E., & Žvaliauskas, G. (2008).
The Impact of New ICTs on Democracy: Positive and Negative
Scenarios. Social Sciences (1392-0758), 59(1).
Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable
distinction in social psychological research: Conceptual,
strategic, and statistical considerations. Journal of personality
and social psychology, 51(6), 1173.
Batini, C., Viscusi, G., & Cherubini, D. (2009). GovQual: A quality
driven methodology for E-Government project planning.
Government information quarterly, 26(1), 106-117.
Bélanger, F., & Carter, L. (2008). Trust and risk in e-government
adoption. The Journal of Strategic Information Systems, 17(2),
165-176.
Beldad, A., van der Geest, T., de Jong, M., & Steehouder, M. (2012). A
cue or two and I'll trust you: Determinants of trust in government
organizations in terms of their processing and usage of citizens'
personal information disclosed online. Government information
quarterly, 29(1), 41-49.
Carter, L., & Bélanger, F. (2005). The utilization of e‐government
services: citizen trust, innovation and acceptance factors.
Information systems journal, 15(1), 5-25.
Carter, L., & Campbell, R. (2011). The impact of trust and relative
advantage on internet voting diffusion. Journal of theoretical
and applied electronic commerce research, 6(3), 28-42.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 512 Volume XI Number 03
Carter, L., Weerakkody, V., Phillips, B., & Dwivedi, Y. K. (2016).
Citizen Adoption of E-Government Services: Exploring Citizen
Perceptions of Online Services in the United States and United
Kingdom. Information Systems Management, 33(2), 124-140.
Chadwick, A., & May, C. (2003). Interaction between States and
Citizens in the Age of the Internet:“e‐Government” in the United
States, Britain, and the European Union. Governance, 16(2),
271-300.
Chen, Y.-S., & Chang, C.-H. (2012). Enhance green purchase intentions:
The roles of green perceived value, green perceived risk, and
green trust. Management Decision, 50(3), 502-520.
Choudrie, J., & Dwivedi, Y. K. (2005). Investigating the research
approaches for examining technology adoption issues. Journal of
Research Practice, 1(1), 1.
Christian Schaupp, L., & Carter, L. (2005). E-voting: from apathy to
adoption. Journal of Enterprise Information Management, 18(5),
586-601.
Cochran, W. G. (2007). Sampling techniques: John Wiley & Sons.
Cole, I. J., & Kelsey, A. (2004). Computer and information literacy in
post-qualifying education. Nurse Education in Practice, 4(3),
190-199.
Colesca, S., & Dobrica, L. (2008). Adoption and use of e-government
services: The case of Romania. Journal of Applied Research and
Technology, 6(3), 204-217.
COLESCA, S. E. (2007). The main factors of on-line trust. Economia.
Seria Management, 10(2), 27-37.
Colesca, S. E. (2015). Understanding trust in e-government. Engineering
Economics, 63(4).
Cremonini, L., & Valeri, L. (2003). Benchmarking security and trust in
Europe and the US: Rand Corporation.
Cronin, G. (1995). Marketability and social implications of interactive
TV and the information superhighway. IEEE transactions on
professional communication, 38(1), 24-32.
Croxall, K., & Cummings, M. N. (2000). Computer usage in family and
consumer sciences classrooms. Journal of Family and Consumer
Sciences Education, 18(1), 9-18.
de Oña, J., de Oña, R., Eboli, L., Forciniti, C., & Mazzulla, G. (2016).
Transit passengers‟ behavioural intentions: the influence of
service quality and customer satisfaction. Transportmetrica A:
Transport Science, 12(5), 385-412.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 513 Volume XI Number 03
Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean
model of information systems success: a ten-year update.
Journal of management information systems, 19(4), 9-30.
Devi Juwaheer, T., Pudaruth, S., & Ramdin, P. (2012). Factors
influencing the adoption of internet banking: a case study of
commercial banks in Mauritius. World Journal of Science,
Technology and Sustainable Development, 9(3), 204-234.
Dong, X., Xiong, L., & Wang, W. (2011). How adoption is G2C model
e-government?—Evidence from Xi'an and Nan Jing. Paper
presented at the E-Business and E-Government (ICEE), 2011
International Conference on.
Eid, M. I. (2011). Determinants of e-commerce customer satisfaction,
trust, and loyalty in Saudi Arabia. Journal of electronic
commerce research, 12(1), 78.
Floyd, F. J., & Widaman, K. F. (1995). Factor analysis in the
development and refinement of clinical assessment instruments.
Psychological assessment, 7(3), 286.
Gatautis, R. (2015). The impact of ICT on public and private sectors in
Lithuania. Engineering Economics, 59(4).
Gefen, D., & Straub, D. W. (2000). The relative importance of perceived
ease of use in IS adoption: A study of e-commerce adoption.
Journal of the association for Information Systems, 1(1), 8.
Guilford, J. (1965). Fundamental statistics in psychology and education
4th Ed.
Gummerus, J., Liljander, V., Pura, M., & Van Riel, A. (2004). Customer
loyalty to content-based web sites: the case of an online health-
care service. Journal of services Marketing, 18(3), 175-186.
Gupta, B., Dasgupta, S., & Gupta, A. (2008). Adoption of ICT in a
government organization in a developing country: An empirical
study. The Journal of Strategic Information Systems, 17(2), 140-
154.
Halchin, L. E. (2004). Electronic government: Government capability
and terrorist resource. Government information quarterly, 21(4),
406-419.
Heeks, R., & Andrade, J. A. (2007). Implementing and Managing
eGovernment: An International Text. Enl@ ce, 4(2).
Jaeger, P. T. (2003). The endless wire: E-government as global
phenomenon. Government information quarterly, 20(4), 323-
331.
Jaeger, P. T., & Thompson, K. M. (2003). E-government around the
world: Lessons, challenges, and future directions. Government
information quarterly, 20(4), 389-394.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 514 Volume XI Number 03
Jayashree, S., Salehi, F., Abdollahbeigi, B., & Malarvizhi, C. A. (2016).
Factors Influencing Intention to use E-Government Services
among Iran Citizens. Indian Journal of Science and Technology,
9(34).
Kamiński, A. (2010). Computer Integrated Enterprise in the MRP/ERP
Software Implementation. foundations of management, 2(2), 25-
36.
Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in
online service continuance: An extended perspective of user
satisfaction. Computers in Human Behavior, 26(3), 353-364.
Kumar, V., Mukerji, B., Butt, I., & Persaud, A. (2007). Factors for
successful e-government adoption: a conceptual framework. The
electronic journal of e-Government, 5(1), 63-76.
Lee, H., Choi, S. Y., & Kang, Y. S. (2009). Formation of e-satisfaction
and repurchase intention: Moderating roles of computer self-
efficacy and computer anxiety. Expert Systems with
Applications, 36(4), 7848-7859.
Lee, J., Kim, H. J., & Ahn, M. J. (2011). The willingness of e-
Government service adoption by business users: The role of
offline service quality and trust in technology. Government
information quarterly, 28(2), 222-230.
Lee, J., & Rao, H. R. (2007). Perceived risks, counter-beliefs, and
intentions to use anti-/counter-terrorism websites: an exploratory
study of government–citizens online interactions in a turbulent
environment. Decision Support Systems, 43(4), 1431-1449.
Lin, Y., Luo, J., Cai, S., Ma, S., & Rong, K. (2016). Exploring the
service quality in the e-commerce context: a triadic view.
Industrial Management & Data Systems, 116(3), 388-415.
Malik, B. H., Shuqin, C., Mastoi, A. G., Gul, N., & Gul, H. (2016).
Evaluating Citizen e-Satisfaction from e-Government Services:
A Case of Pakistan. European Scientific Journal, 12(5).
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative
model of organizational trust. Academy of management review,
20(3), 709-734.
McClure, D. L. (2001). Electronic government: challenges must be
addressed with effective leadership and management: General
Accounting Office.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and
validating trust measures for e-commerce: An integrative
typology. Information systems research, 13(3), 334-359.
Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000).
Self-service technologies: understanding customer satisfaction
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 515 Volume XI Number 03
with technology-based service encounters. Journal of marketing,
64(3), 50-64.
Mofleh, S. I., & Wanous, M. (2008). Understanding factors influencing
citizens adoption of e-government services in the developing
world: Jordan as a case study. Journal of Computer Science,
7(2), 1–11.
Oliver, R. L. (1999). Whence consumer loyalty? the Journal of
Marketing, 33-44.
Ornager, S., & Verma, N. (2005). E-Government Tool-Kit for
Developing Countries: UNESCO New Delhi.
Pallant, J. (2011). SPSS Survival Manual 4th edition: A step by step
guide to data analysis using SPSS version 18. Maidenhead,
Berkshire: Open University Press. Retrieved on from
http://www. allenandunwin. com/spss.
Pallant, J. (2013). SPSS survival manual: McGraw-Hill Education (UK).
Park, C.-H., & Kim, Y.-G. (2003). Identifying key factors affecting
consumer purchase behavior in an online shopping context.
International Journal of Retail & Distribution Management,
31(1), 16-29.
Pavlou, P. A., Tan, Y.-H., & Gefen, D. (2003). Institutional trust and
familiarity in online interorganizational relationships. Paper
presented at the Proceedings of the European Conference on
Information Systems (ICIS) Naples, Italy.
Picciano, A. G., & Seaman, J. (2009). K-12 Online Learning: A 2008
Follow-Up of the Survey of US School District Administrators:
ERIC.
Porter, C. (2003). A new way of governing in the digital age. The
Evolving Internet. An Electronic Journal of the US Department
of State, 8(3), 19-23.
Qureshi, I. A., Ilyas, K., Yasmin, R., & Whitty, M. (2012). Challenges of
implementing e-learning in a Pakistani university. Knowledge
Management & E-Learning: An International Journal
(KM&EL), 4(3), 310-324.
Ranaweera, H. (2016). Perspective of trust towards e-government
initiatives in Sri Lanka. SpringerPlus, 5(1), 1-11.
Rehman, M., Esichaikul, V., & Kamal, M. (2012). Factors influencing e-
government adoption in Pakistan. Transforming Government:
People, Process and Policy, 6(3), 258-282.
Rehman, M., Kamal, M. M., & Esichaikul, V. (2016). Adoption of e-
Government Services in Pakistan: A Comparative Study between
Online and Offline Users. Information Systems
Management(just-accepted).
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 516 Volume XI Number 03
Rust, R. T., & Lemon, K. N. (2001). E-service and the consumer.
International Journal of Electronic Commerce, 5(3), 85-101.
Sabraz Nawaz, S., & Thelijjagoda, S. (2015). University academics‟
behavioural intention to use E-Government services in Sri
Lanka.
Sharma, G., Bao, X., & Peng, L. (2013). Public Participation and Ethical
Issues on E-governance: A Study Perspective in Nepal.
Siau, K., & Long, Y. (2006). Using social development lenses to
understand e-government development. Journal of Global
Information Management, 14(1), 47.
Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics,
5th. Needham Height, MA: Allyn & Bacon.
Tassabehji, R., Elliman, T., & Mellor, J. (2007). Generating citizen trust
in e-government security: Challenging perceptions. International
Journal of Cases on Electronic Commerce (IJCEC), 3(3), 1-17.
Thomas, J. C., & Streib, G. (2003). The new face of government:
citizen‐initiated contacts in the era of E‐Government. Journal of
public administration research and theory, 13(1), 83-102.
Titah, R., & Barki, H. (2006). E-government adoption and acceptance: A
literature review. International Journal of Electronic
Government Research (IJEGR), 2(3), 23-57.
Tung, L. L., & Rieck, O. (2005). Adoption of electronic government
services among business organizations in Singapore. The Journal
of Strategic Information Systems, 14(4), 417-440.
United Nations. (2014). United Nations e-government survey. Retrieved
from
http://unpan3.un.org/egovkb/Portals/egovkb/Documents/un/2014
-Survey/E-Gov_Complete_Survey-2014.pdf
Van de Walle, S., & Bouckaert, G. (2003). Public Service Performance
and Trust in Government: The Problem of Causality.
International Journal of Public Administration, 26(8-9), 891-
913. doi:10.1081/PAD-120019352
Vassilakis, C., Lepouras, G., Fraser, J., Haston, S., & Georgiadis, P.
(2005). Barriers to electronic service development. E-service
Journal, 4(1), 41-63.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User
acceptance of information technology: Toward a unified view.
MIS quarterly, 425-478.
Venkatesh, V., Thong, J. Y., Chan, F. K., & Hu, P. J. (2016). Managing
Citizens‟ Uncertainty in E-Government Services: The Mediating
and Moderating Roles of Transparency and Trust. Information
systems research, 27(1), 87-111.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 517 Volume XI Number 03
Verdegem, P., & Verleye, G. (2009). User-centered E-Government in
practice: A comprehensive model for measuring user
satisfaction. Government information quarterly, 26(3), 487-497.
Wang, Y.-S., & Liao, Y.-W. (2008). Assessing eGovernment systems
success: A validation of the DeLone and McLean model of
information systems success. Government information quarterly,
25(4), 717-733.
Warkentin, M., Gefen, D., Pavlou, P. A., & Rose, G. M. (2002).
Encouraging citizen adoption of e-government by building trust.
Electronic markets, 12(3), 157-162.
Weerakkody, V., Irani, Z., Lee, H., Hindi, N., & Osman, I. (2016). Are
UK Citizens Satisfied With E-Government Services? Identifying
and Testing Antecedents of Satisfaction. Information Systems
Management, 33(4), 331-343.
Welch, E. W., Hinnant, C. C., & Moon, M. J. (2005). Linking citizen
satisfaction with e-government and trust in government. Journal
of public administration research and theory, 15(3), 371-391.
Wimmer, M. A. (2002). A European perspective towards online one-stop
government: the eGOV project. Electronic commerce research
and applications, 1(1), 92-103.
Yildiz, M. (2007). E-government research: Reviewing the literature,
limitations, and ways forward. Government information
quarterly, 24(3), 646-665.
Yonazi, J., Sol, H., & Boonstra, A. (2010). Exploring issues underlying
citizen adoption of e-government initiatives in developing
countries: The case of Tanzania. Paper presented at the
Proceedings of the 10th European Conference on E-Government:
National Center for Taxation Studies University of Limerick,
Ireland.
Zavareh, F. B., Ariff, M. S. M., Jusoh, A., Zakuan, N., Bahari, A. Z., &
Ashourian, M. (2012). E-service quality dimensions and their
effects on e-customer satisfaction in internet banking services.
Procedia-social and behavioral sciences, 40, 441-445.
Zhou, T. (2013). Understanding continuance usage of mobile sites.
Industrial Management & Data Systems, 113(9), 1286-1299.
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 518 Volume XI Number 03
APPENDIX-A
TABLE 1
Summary of Sample Used in the Study (N=180)
Sr. Stratum
(Economic Sector)
Population Stratified
Sample
(20 %)
Category
(Level of
Education)
1 Employees from
Government Sector
1140 114 Doctoral 59
Masters/M.Phil 46
Inter/Bachelors 09
2 Employees from
Business Sector
320 32 Doctoral 00
Masters/M.Phil 28
Inter/Bachelors 04
3 General Citizens/ Self
Employed
340 34 Doctoral 04
Masters/M.Phil 11
Inter/Bachelors 19
TABLE 2
Demographic Characteristics of Respondents (N=180)
Characteristics Frequency %
Participants
Male 149 82.8
Female 31 17.2
Marital Status
Married 93 51.7
Single 87 48.3
Age
Less than 30 Years 93 51.7
31 to 40 Years 77 42.8
41 to 50 Years 5 2.8
51 to 60 Years 5 2.8
Education
Doctoral 63 35.0
Masters/M.Phil 85 47.2
Inter/Graduation 32 17.8
Economic Sector
Government Sector 114 63.3
Business Sector 32 17.8
General Citizens/Self
Employed
34 18.8
Total (For each characteristic) 180 100
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 519 Volume XI Number 03
TABLE 3
Showing Overall Reliability of the Measurement Instrument
Cronbach's Alpha N of Items
.949 55
TABLE 4
Reliability Values for Each Study Construct (N=180)
Construct/Variable Number of Items Cronbach‟s α
Trust in E-Government 24 .824
E-Satisfaction 23 .953
Intentions to Use 4 .878
E-Services Adoption 4 .910
TABLE 5
Correlation Values for Trust in E-Government, E-Satisfaction, Intentions
to Use and E-Services Adoption
Variable Trust in E-
Government
E-
Satisfaction
Intentions
to Use
E-Services
Adoption
Trust in E-
Government
1
E-
Satisfaction
.502**
1
Intentions
to Use
.453**
.650**
1
E-Services
Adoption
.380**
.652**
.752**
1
Correlation is significant at the 0.01 level (2-tailed).
TABLE 6
KMO Values and Bartlett’s Test
Kaiser-Meyer-OlkinMeasure of Sample Adequacy .665
Bartlett’s Test of Sphericity Chi. Square value 11863.371
Df 1485
Significance .000
TABLE 7
Coefficients, when Trust in E-Government and E-Satisfaction independent
variables and E-Services Adoption is a dependent variable.
(Regression Analysis: Step-I)
Model Unstandardized
Coefficients
Standardized
Coefficients
T Sig.
B Std.
Error
Beta
(Constant) .146 .391 .372 .710
Trust in E-
Government
.304 .133 .151 2.284 .024
E-Satisfaction .727 .084 .573 8.674 .000
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 520 Volume XI Number 03
TABLE 8
Coefficients, when Trust in E-Government and E-Satisfaction are
independent variables and Intentions to Use is a dependent variable
(Regression Analysis: Step-II)
Model Unstandardized
Coefficients
Standardized
Coefficients
T Sig.
B Std. Error Beta
(Constant) .204 .358 .570 .570
Trust in E-Government .402 .122 .215 3.294 .001
E-Satisfaction .634 .077 .537 8.247 .000
TABLE 9
Coefficients, when Intentions to Use is independent variable and E-Services
Adoption is a dependent variable
(Regression Analysis: Step-III)
Model Unstandardized
Coefficients
Standardized
Coefficients
T Sig.
B Std. Error Beta
(Constant) .598 .199 3.009 .003
Intentions to
Use
.810 .053 .752 15.213 .000
TABLE 10
Summary Table, when Trust in E-Government, E-Satisfaction and
Intentions to Use are independent variables and E-Services Adoption is a
dependent variable
Model R R
Square
Adjusted R
Square
Change Statistics
R Square
Change
Sig. F
Change
1 .664a .441 .435 .441
.171
.000
2 .782b .612 .605 .000
TABLE 11
Coefficients, when Trust in E-Government, E-Satisfaction and Intentions to
Use are independent variables and E-Services Adoption is a dependent
variable (Regression Analysis: Step-IV)
Model Unstandardized
Coefficients
Standardized
Coefficients
T Sig.
B Std. Error Beta
1 (Constant) .146 .391 .372 .710
Trust in E-
Government
.304 .133 .151 2.284 .024
E-Satisfaction .727 .084 .573 8.674 .000
2 (Constant) .022 .327 .069 .945
Trust in E-
Government
.062 .115 .031 .538 .591
E-Satisfaction .345 .082 .272 4.185 .000
Intentions to Use .603 .069 .560 8.801 .000
Future of Marketing and Management (FMM 2017)
Journal of Managerial Sciences 521 Volume XI Number 03
TABLE 12
Results of Direct as well as Mediation Effects of Intentions to Use E-
Services
Sr. Relationship Path Direct
Effects
β (p)
Mediating
Effects
β (p)
Results
1 Relationship of
IV(Trust in E-
Government) with
DV(E-Services
Adoption)
.304(.024) 062(.591) Full
Mediation
2 Relationship of
IV(E-Satisfaction) with
DV(E-Services
Adoption)
.727(.000) .345(.000) No
Mediation
TABLE 13
Summary of Study Hypotheses
Sr. Hypotheses Results
H1 Trust in e-government has positively significant effect on
e-services adoption
Supported
H2 E-satisfaction has positively significant effect on e-services
adoption
Supported
H3 Intentions to use has positively significant effect on
e-services adoption
Supported
H4 Intentions to use mediates the relationship between trust in
e-government and e-services adoption
Supported
H5 Intentions to use mediates the relationship between
e-satisfaction and e-services adoption
Not
Supported
Recommended