The Adoption of Electric Vehicles in the Sultanate of Oman:

A Conceptual Study

HAMED ABDULLAH SAID ALSALMI1, SIVADASS THIRUCHELVAM2

1College of Management,

Universiti Tenaga Nasional (UNITEN),

Kajang, Selangor,

MALAYSIA

2College of Engineering,

Universiti Tenaga Nasional (UNITEN),

Kajang, Selangor,

MALAYSIA

Abstract: - This research aims to propose a conceptual framework that links Personal and Technological

Factors with Electric Vehicle (EV) adoption in Oman, and to test the validity and reliability of the research

model. Based on the Social Cognitive Theory, the framework contained Omani Social Norms, Perceived

Usefulness (as Personal Factors), the Government’s Personnel Information Technology IT Competencies,

Electric Vehicles System Quality, and the Lack of charging infrastructure (as Technological Factors) as

independent variables; with Electric Vehicles in Oman (as dependent variable). The researcher followed the

quantitative research methodology by testing the score of Cronbach Alpha as a measurement of the Reliability

of the scale, and Person correction as a measurement of the research model validity. The researcher used the

mean of the survey questionnaire as a research instrument, on which the researcher developed a 26 items

questionnaire and distributed 30 questionnaires. The findings of this study revealed that the scores of the

Cronbach Alpha for all of the constructs achieved a satisfactory level of scale reliability. In addition, the

Pearson Correlation between all Social Norms, Perceived Usefulness, Personnel IT Competencies, System

Quality, and the Lack of charging infrastructure with the EV have all been found to be statistically significant.

Key-Words: - Social Norms, Perceived Usefulness, Personnel IT Competencies, System Quality, the Lack of

charging, Electric Vehicles, Oman

Received: March 2, 2023. Revised: June 25, 2023. Accepted: July 1, 2023. Published: July 14, 2023.

1 Introduction

In today's world, when decreasing oil reliance and

minimizing carbon emissions are key goals, the

electric vehicle (EV) business is one of the fastest-

expanding industries. EVs are the most

environmentally friendly alternative to conventional

modes of transport. An electric vehicle is made up

of three parts: a battery, a power wire, and a socket.

Electric vehicles were first introduced in the

nineteenth and twentieth centuries, but their

popularity faded due to low oil costs, large driving

ranges, and inexpensive pricing of regular vehicles,

[1]. The goal these days is to have electric vehicles

with batteries that can be recharged by renewable

energy sources (RESs) like solar power, allowing

EVs to be integrated into smart grids. A smart grid

is an electric power grid that reacts intelligently to

all of its linked components, such as suppliers and

customers, to supply electric power services

effectively, cheaply, and sustainably. Furthermore,

when demand is low and output is high, EVs may be

utilized to store extra energy and supply power back

to the smart grid when supply exceeds need, [2].

However, a rapid rise in the number of electric

vehicles on the road might produce grid congestion

and voltage issues. Electric vehicle sales are

increasing over the world as a result of their

efficiency and ability to function as a distributed

energy source. In 2015, over 800,000 electric

vehicles (EVs) were sold in the United States alone,

with 600,000 EVs sold in Japan. Following suit,

Europe and China bought 200,000 electric vehicles

to keep up with the trend, [3].

Many challenges, problems, uncertainties, and

concerns have arisen as a consequence of the rapid

expansion of electric vehicles. These issues are

divided into three categories: (1) smart grid

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challenges, (2) electric vehicle adoption challenges,

and (3) challenges connected to a regular and

dependable supply of raw materials for the

manufacture of EV components like batteries. First,

from the standpoint of the smart grid, these issues

include system overload, power losses, line

reliability, renewable energy production, EV driver

behavior, and smart grid fluctuations induced by

uncontrolled EV battery recharging. Second, from

the standpoint of adoption, driving EVs at high

speeds while carrying an auxiliary load such as air

conditioning (AC) or heating is seen as a big risk.

The current adoption of electric vehicles as a

mainstream transport system is hampered by their

long recharging times and limited driving range.

Similarly, repeated G2V (Grid-to-Vehicle) and V2G

(Vehicle-to-Grid) charging and discharging cycles

may wear out batteries and reduce battery life.

Furthermore, the attitudes of EV drivers are a

significant component of the risk connected with

electric vehicles, [2]. Therefore, the main objective

of this study is to validate a conceptual framework,

the framework contained Omani Social Norms,

Perceived Usefulness (as Personal Factors), the

Government’s Personnel Information Technology

IT Competencies, Electric Vehicles System Quality,

and the Lack of charging infrastructure (as

Technological Factors) as independent variables;

with Electric Vehicles in Oman (as dependent

variable).

2 Literature Review

2.1 HEV/EV

The deployment of electric vehicles on the road is

an excellent concept. Electric vehicles are divided

into four groups. Mild-hybrid electric vehicles

(MHEV), hybrid electric vehicles (HEV), plug-in

hybrid electric vehicles (PHEV), and battery electric

vehicles (BEV) are all available (BEV). The 48v

electric vehicle is the mild hybrid's name. The

ultimate electric vehicle delivers several functions

and features, including voltage stabilization,

recuperation, start-stop, fuel-saving, sailing electric

parking, and fully battery-charged electric driving

with an onboard charger, as the electric vehicle

develops its upgrading and performance. Despite

this, the MHEV satisfies the 95 g/km CO2

emissions per vehicle requirement. As charging

infrastructure improves, the market will gradually

accept electric vehicles. Plans for a dynamic

induction charging system may see charging

facilities set up at airports, parking lots, and taxi

stops, [4].

Several obstacles in the form of plug-in electric

vehicles (PEVs) lie in the way. PEVs have several

drawbacks that make them difficult to implement.

The cost of the battery system, its range limits,

charging, and battery density are the factors to

consider. Vehicle electrification solutions need

meticulous development of an effective energy

management system for the vehicle engine. High

power and high voltage energy needs for battery

energy storage in electric vehicles are met by power

emulation by solar grid systems, [5]. Solar inverters

with maximum power point tracking storage provide

the best efficiency. The self-discharging

mechanisms of lithium-ion batteries are being

studied to have a better understanding of electric

vehicle energy management. The key areas of

research in electric vehicle technology include

automotive energy, battery testing, power device

modeling, and cell self-discharging technologies.

One can increase the vehicle actuation throughput

by improving the understanding of DC-to-DC

converter design. The gasoline-electric hybrid

vehicle (HEV), the full-electric vehicle (EV), and

the light electric vehicle (LEV) are the three

categories of electric vehicles (LEV). Compared to

electric vehicles, LEVs use less power. According

to the input voltage requirement, it is further divided

into low and high-power varieties, [6]. Table 1

indicates the various types of light electric vehicles.

Table 1. Light electric vehicles

Light electric vehicles

High power

(10 kw >

30 kw)

High

voltage

(48–144 V)

Low power

(1–10 kw)

Low voltage

(24–72 V)

a. Low-speed electric

vehicles

b. E-golf carts

c. E-forklifts

d. Light utility vehicles

e. E-motorbikes

f. E-three wheelers

g. E-rickshaws

h. E-bikes

i. E-scooters

2.2 Electric Vehicle Studies in Oman

Shortly, Oman intends to use cleaner and renewable

energy. The Authority for Electricity Regulations is

working on a clear framework for electric vehicles;

without it, the government would be unable to

approve charging stations at gas stations. According

to some reports, the Sultanate presently has 12

charging stations, however, they were only placed in

two sites for a Global EVRT event. It's unclear how

many and what kind of electric vehicles have been

deployed in Oman thus far. There is no central

database, and the information is not accessible to the

general public. The Sultanate of Oman's Authority

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for Electricity Regulation is working on laws to

regulate electric vehicles. This government

regulatory body is working to provide a framework

for EV regulation and enforcement. So far, the sole

action performed to promote electric vehicles in

Oman has been a Global EVRT event conducted in

January 2018. It included ten electric vehicles

traveling from Abu Dhabi to Muscat. The promoters

displayed EV charging stations at the only two stops

on this road trip, one in Muscat and one in Sohar,

both at IHG group hotels, [7].

The main entities (e.g., developers, government,

System Operator) and their roles in the deployment

of EVs in the jurisdiction in Oman are as follows:

 Authority for Electricity Regulation: The

authority is currently working on the framework

for EVs regulation and the introduction,

management, and operation of charging stations.

This government entity is likely to be the main

regulator for the sector.

 Vehicle manufacturers: These companies can

help the regulators to determine what

operational and regulatory requirements need to

be put in place to manage their enforcement.

 Charging station developers: These entities can

be used by the regulator to know how the

charging stations will be installed and what will

be needed in terms of practical requirements for

ongoing operation and management, including

the different types of charges (i.e., fast chargers,

home chargers, etc.).

 Petrol station companies: These entities will

have input on how they want to provide

charging stations and ancillary services for EVs.

 Governmental entities:

i. The Ministry of Environment and Climate

Affairs – This government ministry is

likely to be key in forming the regulatory

landscape and promoting the use of EVs

within the jurisdiction. In addition to EVs,

they will have input into the regulation of

hybrids, petrol, and diesel cars.

ii. Public Authority for Water and Electricity

and NAMA Group SAOC – These two

government bodies are often heavily

involved with the policy drivers for

energy and energy-related projects in the

Sultanate. Even at a cursory level, each

entity is likely to be consulted on the

introduction of a framework for EVs.

The major challenges currently are finishing the

framework for electric vehicles in the Sultanate of

Oman - what it should contain, how it will look,

who will be in charge of enforcement and legislative

reform, and how the sector will create and function

in the interim. One of the most important factors to

examine is how the regulator will handle charging

stations, including tariffs, distinct sites from gas

stations/conjoined locations, yearly requirements,

and government registrations (e.g., Mulkiya

registration and renewal). Detailed information on

whether to price the tariffs higher, cheaper, or equal

to traditional gasoline or fuel automobiles will be

required as part of this analysis. Refocusing

emphasis on "greener" and more ecologically

friendly vehicles would mark an utter sea-change at

many levels, both in the public and commercial

sectors, for a nation that is so highly reliant on its

petroleum economy, [7], [8].

Due to various economic and environmental

concerns, interest in electric and hybrid electric

vehicles (EVs & HEVs) has risen quickly in recent

years. Increasing fuel costs, climate change

concerns, and environmental protection have opened

the way for EVs and HEVs to gain significant

market share, particularly in Europe, the United

States, and East Asia, [9]. In these areas, EV sharing

is also becoming increasingly prevalent and

accepted. Although performance and comfort EVs

from well-known manufacturers such as Tesla,

Smart, BMW, and Mitsubishi are gaining more

public attention and acceptance, the Gulf Arab

states, which are considered one of the largest

automotive markets for German vehicles with

around €3.7 billion in turnover in 2012 have no real

EV market, [10]. EV producers will need more

precise and scientific information regarding the

performance, potential, and acceptability of such

technology in the Gulf Arab states to break into this

vital market. Most oil-rich Gulf Arab governments

are now becoming more interested in alternative

vehicle technology and renewable energy in a bold

endeavor. They want to diversify their energy

resources in this move and maybe profit in the

process. The number of Gulf Arab governments

betting on green technology and renewable energy

as essential components in the global economy and

the environment have increased dramatically in

recent years. For example, the United Arab

Emirates' efforts to host the headquarters of the

International Renewable Energy Agency (IRENA)

in Abu Dhabi have resulted in the success of their

efforts in the renewable energy industry and climate

change challenges, [11]. Despite these efforts, the

use of electric vehicles as green technology and the

relationship between EVs and environmental

consequences are not fully understood. This

research project was established by the Research

Institute of Automotive Engineering and Vehicle

Engines Stuttgart (FKFS) in collaboration with

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Dhofar University (DU) in Salalah, where several

tests were conducted to study the performance of

EVs in the Gulf Arab states in general and in Oman

in particular. This will provide a thorough

understanding of the many EV applications, as well

as the fuel savings and environmental implications

of utilizing both EVs and renewable energy

charging stations, [10].

2.2.1 Salalah Driving Cycle (2015)

The objective test methodology used by Mohareb et

al. (2015) is meant to define a driving cycle in

Salalah, Oman, as depicted in Fig. 1. It is built up

from three interdependent steps. In phase I, a 30-

question questionnaire is produced and delivered to

320 applicants who reflect the population

distribution of Salalah. The questionnaire translates

the study objectives into precise questions to

ascertain two key parameters: the driven route types

and driving cycle, as well as information on people's

attitudes and knowledge about EVs and climate

change. Based on the survey results, a sample

driving cycle for Salalah is created, as illustrated in

Fig. 2. In phase II, utilizing a specially-designed

measuring box, the essential data for the Salalah

Driving Cycle (SaDC) driver profile is acquired

(MessBox). In phase III, the gathered data,

including temperatures, vehicle velocity, and solar

irradiation, are utilized in a simulation model to

analyze the performance and potential of electric

vehicles in Gulf Arab nations, [10].

Fig. 1: Test methodology structure

In addition, Mohareb et al. (2015) used a

scientific approach to analyze the quantitative data

from the 320 questionnaires to determine the total

daily average distance, the road type distribution in

terms of Major Highway, Primary Street, and City

Street, a representative driving cycle for Salalah,

and the required numbers of test drivers. The

Salalah Driving Cycle is about 36 kilometers long

and consists of three kinds of roads: 41% Major

Highway, 29% Primary Street, and 30% City Street.

To investigate the profile of the prescribed driving

cycle, a minimum of 42 distinct drivers are

recruited. To gather valid data from the SaDC, a

particular number of drivers is necessary. Table 2

shows the gender and age distribution of the test

drivers based on the available volunteer drivers. The

MessBox, which is explained in the following part,

is used to capture data throughout each driving cycle

for each test drive, [10].

Fig. 2: Salalah Driving Cycle (SaDC) with road

distribution

Table 2. Categorization of test drivers

Total test drivers

Total per gender

Age groups (Year)

Male

Female

21 - 30

31 - 40

41 - 50

51 - 60

61 - 70

Mohareb et al. (2015)'s study delve into the

possibilities for employing electric vehicles, the fuel

savings potentials, and the environmental

implications of using both electric vehicles and

renewable energy charging stations. Despite the

abundance of oil in the Gulf Arab nations, the

measurements and simulation findings stimulate

further research into using solar energy to power

electric vehicles in the region. As a result, the

irradiance of the sun is measured during the test

drives. This information is fed into a computer

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model of a solar charging station, which is used to

assess the viability of employing them. As a result,

hazardous pollutants and operating expenses may be

lowered even more. Many viable business cases for

employing electric vehicles and solar charging

stations for this region, which is regarded as one of

the largest automobile markets, may be analyzed

using the data gathered during the test drives and by

using these trustworthy simulation models, [10].

2.2.2 Electrification of Transport in Oman

(2020)

The electrification of vehicles is a promising

pathway to decarbonize road transportation and

combat climate change. A comprehensive public

policy is required to ensure a successful smooth

transition to clean and energy-efficient road

transport vehicles. Based on the circumstances of

Oman, the electric vehicles policy can be founded

on four pillars, [12].

Fig. 3: The trend of transportation emissions per

source categories in Oman, 2000–2015.

Fig. 4: The trend of shares contribution per emission

categories of transportation in Oman, 2000–2015.

Integration of electric vehicles with renewable

energy: The emission advantage of electric vehicles

is highly dependent on charging power generation.

Electric vehicles produce more GHG than gasoline-

electric hybrid or internal combustion engine

vehicles if they are not powered by renewable

supply. Currently, Oman's entire electric sector runs

on fossil fuels (97 percent natural gas and 3%

diesel), and the country's electrical power

consumption is growing at a rate of 5% per year,

reaching 6170 MW in 2018. The electrification of

road transportation will raise electrical power

consumption by at least a factor of two, resulting in

an increase in CO2 emissions owing to a shortage of

clean energy in the national energy mix. The nation

will see a tremendous surge in electric vehicles in

the next years, but renewable energy deployment

will remain poor. This impasse will inevitably raise

future total GHG emissions, preventing the

government from meeting its committed objective

of reducing 2% of absolute GHG emissions by 2030

as part of the Paris Agreement's nationally defined

contributions. The electrification of vehicles is

required to significantly increase the contribution of

renewable energies in the present energy mix to

decarbonize road transport. With over 365 days of

clear sky in all sections of the nation, Oman is listed

among the best countries in the world in terms of

solar density potential, which may reach 6.1

KWh/m2 per day during the summer season. The

governorate of Dhofar, in the southern portion of

Oman, is the lone exception, where the solar density

drops somewhat due to the southeast summer

monsoon. Despite the tremendous potential of solar

radiation, which may easily be utilized to supply

power demand, solar energy is currently confined to

a few off-grid uses in Oman's isolated locations. In

this setting, the top objective is to eliminate

technological, financial, and regulatory barriers to

on-grid solar energy deployment. The next stage is

to delve more into how to scale up solar energy for

road transport electrification in terms of power plant

location, grid preparedness, transportation network,

and charging stations. All of these concerns should

be included in future strategic planning for

supplying clean energy to electric vehicles, [13].

Fig. 5: Trends of road transportation emissions per

source categories in Oman, 2000–2015.

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Fig. 6: The trend of shares contribution per emission

categories of road transportation in Oman, 2000–

2015.

Planning for charging stations: The adoption of

electric vehicles in Oman necessitates a deeper dive

into the best policies for future charging station

distribution and the best approaches to integrate

them with present urban patterns and power grid

restrictions. Furthermore, an ideal approach for

reducing the investment cost of charging stations as

well as the renovation and extension of the power

infrastructure must be developed. The rate of

urbanization in Oman is fast, with many plans to

grow and new cities forming, such as Duqum on the

country's central-east coast, however, electric

vehicle infrastructure is still not included in present

or future urban plans. This will make determining

the best locations for electric vehicle infrastructure a

difficult and expensive task for city planners.

Because today's urban plans will be the cities of the

future, charging station planning should be included

as an extra constraint in urban planners' techniques,

[4], [14].

Fig. 7: Comparison of share contribution per source

categories to the total GHG emission in Oman, a-

2000, and b-2015.

Evaluating grid distribution with transportation

network constraint: The predicted growth in electric

vehicle charging stations will bring the power grid

and transportation networks closer together. Both

systems will regulate and have an inverse effect on

the distribution of traffic flows of electric vehicles.

To maintain the effectiveness of the linked

transportation and power systems in Oman, an

integrated, educated science policy concerning the

management of future large-scale electrical vehicles

is greatly necessary, [12].

Adopting Norway's Model to Speed Up Electric

Vehicle Transition: Several developed nations have

adopted directly funded purchase incentives to

encourage the fast adoption of electric vehicles,

including direct cash payments, tax deductions, and

tax exemptions for each electric vehicle purchaser.

Many analysts believe that Norway is the most

advanced nation in terms of individual household

adoption of electric vehicles. Norway has a

population of 5368 people in 2018, and there were

around 296,000 electric vehicles registered. Norway

stands out as a suitable example to emulate because

of its population-to-registered electric vehicle ratio.

The Norway approach is founded on the

complementarity of direct and indirect incentives to

make electric car ownership particularly appealing

to individual users. There is no sales tax on electric

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vehicles as a direct incentive (very high for

conventional cars). Furthermore, electric

automobiles now get a 25% VAT exemption on

purchase. Electric vehicle parks also benefit from

free municipal parking and toll road fee exemptions.

Electricity is quite cheap ($0.11) in Norway, and

gasoline is highly expensive ($ 2.05/Liter), hence

the operating costs of electric vehicles are very low

compared to traditional automobiles. State budget

subsidies for petroleum products mostly used in

transportation were $4.37 billion in 2015. The

appropriate solution to decarbonize road

transportation and establish sustainable

transportation networks is to phase out this subsidy

arrangement in favor of the automobile zero-

emission program on Omani roads, [12].

2.2.3 Carbon Footprint and Environmental

Impact in Oman

When buying a new car, Omanis car buyers have

two main concerns: fuel efficiency and

environmental friendliness. Only HEVs have the

best chance of achieving the two conditions outlined

above. However, while comparing conventional and

HEV vehicles, it's necessary to consider the

advantages and disadvantages of each. Greater

mileage, increased resale value, and cleaner energy

are all advantages of HEVs, but they come at a

price, with higher maintenance costs and no sport-

tuned suspensions. Conventional fuel automobiles,

on the other hand, have a cheaper price tag, superior

engine power, and minimal maintenance costs, but

they have dangerous emissions and poor mileage.

According to a paper issued by Argonne in 2009,

HEVs can save 90 percent on petroleum energy and

40-80 percent on greenhouse gas emissions, [15].

In the case of Oman, current environmental data

indicates that carbon statistics have been steadily

increasing since the country's early oil and gas

discoveries and production. Oman's total CO2

emissions increased dramatically from 2,000 Gg to

40,000 Gg between 1972 and 2011, [16]. Similarly,

Yousif et al. (2017) found that CO2 and greenhouse

gas emissions in the nation are expected to rise by

about 60 million tonnes over the next decade.

Continuous fuel burning (57.9%), manufacturing

(24.2%), and transportation (12.3%) are the

principal sources of these emissions, [17]. When the

CO2 released by conventional automobiles in the

nation is coupled with the transportation and fuel

combustion components, the result is a substantially

greater statistic. In this sense, the Sultanate of Oman

sees HEVs as having the ability to reduce the

country's steadily rising CO2 and GHG emissions,

[15].

In 2015, several car brands released HEVs in

Oman, including the Toyota Prius, which is leading

the Middle East's transition to HEVs (Times of

Oman, 2016). According to the car model's

expectations, it will likely cut CO2 emissions by 67

million tonnes over the next 20 years, [15]. Because

it is unknown how many HEVs were deployed in

Oman, the precise assessment of their influence on

the country's CO2 emissions decrease remains

unknown, [7]. In terms of future HEV deployment

in Oman, various problems have been identified,

one of which is the formation of regulators to

monitor the activities entailed by the introduction of

HEVs in the nation. One of the most important

questions is who will be in charge of implementing

and regulating regulations like charging stations,

tariff setting, and government registration and

requirements, [7].

2.3 Overview of the Conceptual Framework

Social Cognitive Theory emphasizes that

relationships between personal behavior,

environmental factors, and human behavior may

result in a human behavior outcome, [18]. People

can learn in a variety of forms, according to

Bandura (1986), namely not just through direct

experience, but also through interactions and

observations. People's behavior is determined by a

combination of environmental and personal

influences, such as their thought patterns, emotional

reactions, and beliefs. As a consequence of these

actions, the person's future convictions are likely to

be formed, [19]. Overall, this study applies the

Social Cognitive Theory, this research examines

Omani Social Norms, Perceived Usefulness (as

Personal Factors), the Government’s Personnel

Information Technology IT Competencies, Electric

Vehicles System Quality, and the Lack of charging

infrastructure (as Technological Factors) as

independent variables; with Electric Vehicles in

Oman (as dependent variable). Fig. 8 displays the

proposed framework.

Fig. 8: Proposed Conceptual Framework

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Perceived usefulness refers to the degree to

which a person believes that using a particular

system would enhance his or her job performance,

[20].

Social Norms refer to established rules -mostly

unspoken- of conduct in a society that the individual

members are expected to abide by. Individuals learn

them by observing fellow members and following

them to obtain the approval of the larger society,

[21].

Information Technology Competency: it is the

ability to utilize information technology tools to

find, use and evaluate the information for a specific

purpose, [22].

System Quality is a desirable characteristic of an

information system that focuses on the usability and

performance of a particular system, [23].

The charging station is an important component

for the healthy growth of the electric vehicle

industry. A charging station refers to an

infrastructure similar to a petrol station (for

conventional vehicles) that provides electric energy

for the charging of plug-in hybrid electric vehicles

(PHEVs). Many charging stations are on-street

facilities provided by electric utility companies;

mobile charging stations have been recently

introduced. From the grid standpoint, a charging

station is one way that the operator of an electrical

power grid can adapt energy production to energy

consumption, both of which can vary randomly over

time. EVs in a charging station are charged during

times when production exceeds consumption and

are discharged at times when consumption exceeds

production. In this way, electricity production need

is not drastically scaled up and down to meet

momentary consumption, which would increase

efficiency and lower the cost of energy production

and facilitate the use of intermittent energy sources,

such as photovoltaic and wind, [24].

Adoption intention: it is the individual’s

readiness to perform a given behavior. Here

readiness to buy mobile services, [25].

3 Research Methods

In this research, the researcher will utilize

quantitative research methods. Primary data was

collected from employees working for the Oman

Royal Police, which is the official body in Oman

that is in charge of imposing and facilitating the

necessary systems for Electric Vehicles. Therefore,

the researcher distributed a total of 30

questionnaires.

4 Instrument Development

The development of instruments was carefully

executed to reflect the nature of this research. As

such, the questionnaire was designed to include 26

items, and the variables were measured using the

five-point Likert scale, with five standing for

‘Strongly Agree’ and one standing for ‘Strongly

Disagree’. Since the participants spoke Arabic, the

survey needed to be accurately translated from

English to Arabic. As a result, a reverse translation

was conducted, which is a common method for

determining the accuracy of a translation in a cross-

cultural survey, [26]. Furthermore, the validated

instruments listed in Table 3 were adopted from

relevant prior research to measure the variables in

this research.

Table 3. Research Instrument

Construct

No of

Items

Adapted

Citation

Social Norms

SN1: My relatives

believe that they should

use electric vehicles.

SN2: The people who are

important to me hotly

wish to drive electric

vehicles in Oman.

SN3: Often my relatives

recommend electric

vehicles because they

respect the environment

in Oman.

SN4: I have learned from

the society in Oman

about environmental

foreseeable problems

which makes electric

vehicles the best option

to avoid them.

[27],

[28]

Perceived

Usefulness

PU1: I think the smart

system of Electric

vehicles can improve the

traffic services in Oman.

PU2: I believe that

electric vehicle systems

will enrich the research

on traffic data in Oman.

PU3: I think electric

vehicles can the

environment in Oman.

PU4: I think adopting an

electric vehicle system

can improve my work

efficiency.

[29]

Personnel IT

competencies

PC1: I know how to use

basic digital equipment.

PC2: I collaborate in

schemes of work or

planning, using the use of

a technical tool.

PC3: I think I am willing

to handle different

programs to do specific

tasks.

PC4: I have knowledge

of legal and ethical issues

regarding systems used in

Electric Vehicles.

[28]

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System quality

SQ1: I believe the

Electric Vehicles system

will be easy to use in case

if adopted in Oman.

SQ2: Electric Vehicles’

system should be easy to

comprehend by all users.

SQ3: Electric Vehicles’

system should contain

necessary features and

functions that help us

while monitoring.

SQ4: The data of the

Electric Vehicles’ system

should be fully integrated

and consistent with the

traffic system in Oman.

[30]

Lack of charging

infrastructure

LCI1: When the drivers

of Electric Vehicles have

access to the charging

facilities either at home

or university, it would

make it easier for Electric

Vehicles to be widely

adopted by the Omanis.

LCI2: The availability of

charging units for

Electric Vehicles makes

it easier for drivers to be

satisfied with their

decision of driving these

vehicles.

LCI3: When the drivers

have sufficient

knowledge about the

availability of charging

units for Electric

Vehicles, it will make the

Police’s work much

easier.

LCI4: When drivers

experience any

difficulties in accessing

the charging units, they

may refrain from using

Electric Vehicles.

[31],

[32]

EVs Adoption

EVA1: I think the Omani

people would consider

vehicle emissions when

they plan to purchase a

car.

EVA2: It can be

anticipated that the staff

of Oman Royal Police

have a positive attitude

towards electric vehicle

adoption in their

guidelines and policies.

EVA3: Compared to

traditional cars, an

electric vehicle is similar

in performance.

EVA4: Compared to

traditional cars, an

electric vehicle is cheaper

over the long term.

EVA5: I (might) have

more mechanical

problems with an electric

vehicle than with

traditional cars.

EVA6: I would prefer to

drive a traditional car to

an electric vehicle.

[33]

5 Results and Analysis

The pilot study is always conducted before the data

collection. Saunders, Lewis, and Thornhill (2016)

assure the usefulness of carrying out a pilot study

before collecting the data. It will provide great help

by giving the researcher an index to correct any

inadequacies in the research instrument before the

data collection, [34], [35]. In this study, first, the

researcher will demonstrate the descriptive statistics

of the respondents (respondent profile), followed by

the reliability and validity tests for the pilot study.

5.1 Respondent Profile

The first segment of the instrument compiled

information on the background profile of the

respondents which comprises their Gender, Age,

Level of employment, and Level of Education. The

characteristics of each demographic profile are

described below in Table 4.

Table 4. Respondent Profile (Frequencies)

Item

Choice

Frequencies

(Percentage)

Gender

Male

17 (56.6)

Female

13 (43.3)

Age (in

years)

20-25 years

11 (36.6)

26-35 years

8 (26.6

36-45 years

5 (16.6)

46-55 years

4 (13.3)

56 years and above

2 (6.6)

Level of

employment

Executive

Employee

14 (46.6)

Head of the

department

9 (30.0)

Middle

management

4 (13.3)

Head of division

2 (6.6)

Top management

1 (3.3)

Level of

education

University degree

21 (70)

Master

7 (23.3)

PhD

2 (6.6)

5.2 Reliability of the Scale

The reliability of the instrument will be tested in this

study; as a prior literature review was the source of

the questions. At the same time, Cronbach alpha

will be conducted on a sample of 30 participants to

make sure that the instrument is valid and reliable.

Hair et al. (2019) highlighted that a cut-off point of

0.6 is required during the pilot test level to consider

the research instrument is reliable with a valid

internal consistency, on which any value below 0.7

is considered poor and unacceptable, while the value

of Cronbach Alpha above 0.7 is considered as good

and acceptable, above 0.8 is excellent, and above

0.9 will be considered perfect, [36].

In this study, all of the constructs achieved a

satisfactory level of reliability. Table 5 is illustrating

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Hamed Abdullah Said Alsalmi,

Sivadass Thiruchelvam

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Volume 20, 2023

the results of the reliability of the scale of the

current study. The scores of the Cronbach Alpha

were acceptable and above 0.7 for the constructs of

Social Norms and Lack of charging infrastructure

(0.705 and 0.779 respectively) and excellent for the

constructs of Perceived Usefulness, Personnel IT

Competencies, System Quality, and Electric Vehicle

Adoption (0.898, 0.800, 0.876, and 0.885

respectively).

Table 5. Results of Scale Reliability

Reliability Statistics

Constructs

Cronbach's Alpha

N of Items

0.705

0.898

0.800

0.876

LCI

0.779

EVA

0.885

5.3 Validity of the Research Model

Criterion-related validity reflects the success of

measures used for prediction or estimation. To

achieve the validity of the research model, the

researcher will utilize Pearson Bivariate Correlation

using SPSS 28.0, [37]. The Pearson correlation

coefficient is a standardized measure of covariance.

Covariance coefficients retain information about the

absolute scale ranges so that the strength of

association for scales of different possible values

cannot be compared directly. Researchers find the

correlation coefficient useful because they can

compare two correlations without regard for the

amount of variance exhibited by each variable

separately, [38]. According to Pallant (2016), the

Sig. value, which is less than 0.05 in the correlation

test means there is a relationship between the two

variables, and statistically shows a significant

unique contribution to the equation, [39]. Table 6

shows the value of Pearson Bivariate Correlation

alongside the significance of the association

between the variables, which highlights the validity

of the research model of the current study.

Table 6. Pearson Bivariate Correlation Results

Correlations

Constructs

Pearson Correlation

P-value

.552

0.000

.626

0.000

.680

0.000

.700

0.000

LCI

.508

0.000

Dependent Variable: EVA

6 Discussions

This study aims to propose a conceptual framework

that links the Personal and Technological Factors

with Electric Vehicle (EV) adoption in Oman and to

test the validity and reliability of the research

model. Based on the Social Cognitive Theory, the

framework contained Omani Social Norms,

Perceived Usefulness (as Personal Factors), the

Government’s Personnel Information Technology

IT Competencies, Electric Vehicles System Quality,

and the Lack of charging infrastructure (as

Technological Factors) as independent variables;

with Electric Vehicles in Oman (as dependent

variable). The statistical data analysis was carried

out using SPSS and revealed that all of the

constructs in this research have achieved a

satisfactory level of scale reliability using the

Cronbach Alpha scores. In addition, the results of

the Pearson Correlation showed a significant level

of validity.

The findings of this study were inconsistent

with the published literature. Charters and

Heffernan (2021) proposed a conceptual model that

identifies and incorporates the factors affecting

owners' attitudes toward PV adoption to solve the

existing paucity of solar photovoltaic (PV) adoption

by Australian apartment residents. The model

depicts the steps that an apartment owner may take

to get from investigating solar PV adoption to

advocating it to their strata property's Owners'

Committee. In decision-making and social

connections and status, it contains three motivating

drivers (pragmatic concerns, perceived values, and

perceived social norms), [40]. In addition, Jaiswal et

al. (2022) published research that looked at the

importance of electric vehicle knowledge in

predicting customer adoption intentions both

directly and indirectly in the context of a developing

market. The findings support the current study

model, which reveals that electric vehicle

knowledge, perceived utility, perceived ease of use,

and perceived risk all play a role in customer

adoption, [41]. Furthermore, Ngo et al. (2014)

published research that looked at the relationship

between HRM competencies and the adoption of

high-performance work systems (HPWS). HRM

competency has a significant and positive impact on

business success, according to the findings. The

accomplishment of external fit, but not the adoption

of HPWS, is shown to mediate this impact, [42]. the

goal of this research is to propose interaction quality

as an extra, but a more relevant quality metric that

leads to trust in and adoption of an AI-based VAS.

The findings imply that the quality of interactions

and trust are important factors in the adoption of AI-

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based VASs. In the context of AI-based VASs, the

results also show that traditional quality factors (i.e.

system quality) influence interaction quality, [43].

Kumar et al. (2021) also investigated a vehicle

supply chain and proposed several charging

infrastructure development modes that impact EV

adoption. The data revealed that investing in

charging infrastructure as well as providing a

subsidy for EV purchases are both successful in

increasing EV demand, market share, and adoption,

[44].

7 Limitations and Future

Recommendations

This research was surrounded by many limitations.

The current study collected data from only 30

respondents, which is enough for the pilot study.

However, this sample size can be increased in future

research to achieve empirical results. In addition,

the sample of the current study was limited only to

the personnel working for the Oman Royal Police,

which is the official body in Oman that is in charge

of imposing and facilitating the necessary systems

for Electric Vehicles. Therefore, surveying other

affiliated institutions in Oman like the Ministry of

Economy and Ministry of interior affairs. This study

was conducted only to show the reliability and

validity of the conceptual framework using

Cronbach Alpha scores and Pearson Correlation.

This study has a lot of potentials, and many of them

could be addressed here to make sure that future

researchers are aware of them. For instance;

focusing on models of other Social Cognitive

Theories, like technology adoption or Diffusion of

innovation among the personnel working for the

Oman Royal Police with systematic selection would

generate different types of results on the factors that

affect EV adoption. Moreover, an empirical study

that considers both the measurement and structural

model may be the perfect completion of the current

study results. In this study, System Quality was

considered as the independent variable while a good

sum of studies focused on the dimensions of system

quality as independent variables, it is recommended

that future studies may consider Service or System

Quality and associate them with EV adoption in a

holistic study.

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Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

The authors equally contributed in the present

research, at all stages from the formulation of the

problem to the final findings and solution.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

No funding was received for conducting this study.

Conflict of Interest

The authors have no conflict of interest to declare

that is relevant to the content of this article.

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