an analysis of citizens’ trust in e-government services

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: [email protected] † 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

mailto:[email protected]

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



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



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



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



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



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



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



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.



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).



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



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



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.



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



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.


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).




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.


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



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



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).


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



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.



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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



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



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)


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)


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)


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



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