UTAUT2 Model to Investigate the Adoption of E-HRM in the

Telecommunication Sector

JIHAD FRAIJ

Doctoral School of Management and Business

University of Debrecen

H-4032 Debrecen, Böszörményi út 138

HUNGARY

Abstract: - Because of internal dynamics and external influences, employee adoption of e-HRM in

developing countries is minimal. To provide a good working experience for e-HRM users, it is necessary

to investigate what variables could be influencing adoption. Consequently, the present research is

focused on discovering the reasons why the telecommunications sector in Jordan may or may not use

e-HRM systems. The Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was used to

generate and define the factors that would be tested experimentally to attain this goal. In this study, we

looked at the factors of e-HRM adoption behavior, and we predicted that all of these characteristics had

a beneficial impact on the behavior of the telecommunications sector employees. Employees of

three private companies which represent the telecommunications sector in Jordan have been given a

self-reported questionnaire to complete. SPSS version 25 was used for data analysis. The findings show

that e-HRM adoption behavior is favorably influenced by performance expectancy,

facilitating conditions, and social influence. In this research, the adoption of e-HRM was not

significantly impacted by Effort Expectancy or Hedonic Motivation. Using e-HRM suggests that

workers aren't really worried about the degree of conformity and satisfaction it provides. Using the

conceptual model, companies may better understand the factors that influence the adoption of e-HRM

by their workers, as well as pinpoint areas in which further effort can be made to improve adoption

rates.

Key-Words: - E-HRM, E-HRM acceptance, E-HRM adoption, Unified Theory of Acceptance and Use of

Technology 2 (UTAUT2), Telecommunications Sector, Jordan.

Received: July 25, 2021. Revised: March 10, 2022. Accepted: April 14, 2022. Published: May 6, 2022.

1 Introduction

The use of Electronic Human Resource

Management (e-HRM) allows for the

management and devolution of a broad variety of

Human Resource (HR) activities and

information to line managers and workers (Parry,

2011). Information technology (IT) that is used

to network and support at least two individuals

or groups in carrying out collaborative HR duties

is often referred to as e-HRM (Galanaki et al.,

2019). E-HRM may also be defined as a term

that incorporates all conceivable procedures and

contents of HRM integration with IT, with the

purpose of producing value inside and via

institutions for focused management and

employees (Cheng & Zou, 2021). Effective e-

HRM may have an important impact on

corporate performance and long-term workplace

competitiveness, according to a growing body of

studies (Rahman et al., 2018).

Effective characteristics of contemporary e-

HRM systems may aid firms in cutting costs and

improving the efficiency of HR service delivery

while also supporting increased competitiveness

and providing strategic capacity and support

(Tanya Bondarouk, Parry, et al., 2017a).

Businesses may acquire a competitive advantage

via the use of e-HRM. Panayotopoulou et al.

(2007) suggest that e-HRM may facilitate the

transformation of HRM's position into a more

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strategic one. E-HRM allows human resource

professionals to make a more significant

contribution to the company's strategic direction.

(Tanya Bondarouk & Ruël, 2013). According to

the researchers, HRM is a developing field of

study that focuses on all types of HRM material

that is exchanged across IT in order to make

HRM procedures remarkable, coherent, and

effective in order to assist organizations in

developing long-term opportunities both within

and outside the organization. As a result of fast

technological improvement, the literature is

overwhelmingly hopeful. (Tanya Bondarouk &

Ruël, 2013).

Classical HRM, which occurs as a consequence

of the development of e-HRM technology,

covered difficulties such as recruiting, finding,

developing, paying, keeping, assessing, and

motivating personnel inside an organization, all

of which could be converted to the virtual world

(Ruël et al., 2004a). While there is agreement

within academic and practitioner groups on the

benefits of e-HRM for HR managers, there is no

consensus on how best to implement it (Tanya

Bondarouk, Harms, et al., 2017).

Additionally, there is a growing requirement for

the e-HRM market value role to be more

trustworthy, efficient, and capable of supporting

the strategic goals of any business function and

the e-HRM market value role (Iqbal et al., 2019).

Labrosse (2008) concluded that e-HRM has

continuously earned precisely the right amount

of satisfaction from HR executives and leaders

outside of HR from the point of view of the

employees. There is a lot of evidence that e-

HRM can improve the performance of HR jobs

both conceptually and practically (Talukdar &

Ganguly, 2021). More empirical research is

needed to better clarify the paradigm of e-HRM

adoption and its consequences for organizations.

Additionally, there is no precise information

accessible on the variables that should be

considered while implementing e-HRM.

Simultaneously, staffing firms struggle to adapt

to new technology, and the outcomes of e-HRM

programs are not always as beneficial as the

public assumes. Rather than expressing the

obvious, e-HRM applications continue to reveal

issues (Rahman et al., 2018), that have been

shown to accomplish less than planned

(Chapman & Webster, 2003). Human interaction

complications, such as managing staff

acceptance of new e-HRM programs while

introducing new e-HRM programs, further

hindered the ability to fully exploit e-HRM

capabilities (Wiblen et al., 2010). For example,

according to Marler & Parry (2016), the

implementation of e-HRM resulted in the

substitution of administrative activities with

technologically enabled obligations, rather than

the freedom of time for human resource

professionals. In short, it had little effect on

HRM facilities. Additionally, HR professionals

have been poor at using technology to initiate

and maintain business decisions, as well as at

aligning such decisions with strategic objectives.

(Luftman et al., 1993). The empirical data

presented above demonstrated that, as a result of

a lack of awareness of variables that impact e-

HRM adoption, the majority of companies are

faced with a variety of difficulties.

2 Research Problem

E-HRM is intended for use in a networked

environment for the purpose of fulfilling

responsibilities in collaboration with others (Lin,

2011). HR departments in enterprises must be

confronted with a challenging issue when it

comes to introducing these modern technologies

to their employees. When it comes to effectively

implementing e-HRM in enterprises, there is a

substantial amount of information that must be

taken into consideration (Zhou et al., 2021). The

results of E-HRM adoption in the majority of

businesses are not always positive, as they have

been in the past (Parry, 2011; Ruël et al., 2004b),

and they are less than predicted (Tanya

Bondarouk, Parry, et al., 2017a; Galanaki et al.,

2019). The great majority of studies indicate that

HR practitioners have failed to implement e-

HRM systems (Panayotopoulou et al., 2007),

achieve improved results (Maatman, 2006;

Parry, 2014; Parry & Tyson, 2011), and maintain

their positions within strategic decision-making,

more importantly, the capacity of e-HRM to be

fully used was limited by the complexity of

human dynamics, such as the need to manage

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users' acceptance while accepting digital e-HRM

techniques (Tanya Bondarouk & Ruël, 2010;

Njoku et al., 2019), which made it more difficult

to fully harness the potential of e-HRM. Amin et

al. (2008) illustrate how electronic e-

HRM interacts directly with enterprise

employees. The newly established system's

efficiency is then judged by the viewpoints of its

users (Strohmeier, 2007). According to

empirical studies, a well-adapted e-HRM system

for employees results in positive consequences

for the organization in terms of productivity

(Chandradasa & Priyashantha, 2021).

As a result, the adoption rate was a major

challenge that corporations in nations around the

world faced when aligning HR operations with

the strategic goals of their enterprises (Tanya

Bondarouk, Parry, et al., 2017b; Njoku et al.,

2019; SHILPA & Gopal, 2011). On the other

hand, the clear acceptance of an e-HRM system

followed by a sequence of successful

implementations resulted in improved

performance for the businesses (Panos & Bellou,

2016). The lack of knowledge about variables

that impact employee adoption of e-HRM by

businesses results in conceptually and

empirically problematic outcomes regarding the

characteristics that workers seek whenever

adopting new e-HRM technologies to execute

their jobs. As a result, businesses will be unable

to adequately implement e-HRM for their staff

unless they are aware of this. This investigation

was carried out in order to discover solutions to

the current difficult scenario.

According to the Jordanian telecommunications

Regulatory Commission (TRC) annual report

2020 (TRC, 2020a), the telecommunications

sector is one of the country's fastest-growing

industries, and it plays a crucial role in the

country's financial system. Based on the

information provided by TRC, the number of

internet users were 4.63 million in 2015, while in

2020 the users' number has a huge improvement

to be 11, 17 million users. The Jordanian

population according to Worldometer

elaboration of the latest United Nations data is

10,352,788, which means that almost every adult

or inhabitant has access and a subscription to the

internet using one of the services providers,

considering the firms, companies, and

organizations and their

employees. Furthermore, they stated in their

report that the sector is principally constituted of

6 licensed voice and IP service providers as they

name it, which operate in a variety of

geographical regions across Jordan. The

telecommunications sector, which is one of

the most important sectors in the Jordanian

economy, contributes significantly to the overall

economic growth of the nation in a good and

significant way. IT is most used by employees in

the telecommunications sector, and all

telecommunications operations. As a service

sector, the provision of services is unavoidable,

and it has a substantial influence on the

employment situation. Prospective workers have

always been intrigued by technical

improvements, and keeping up with technology

advancements is critical for survival and

progress in today's highly competitive

environment.. Everything about a firm, from A

to Z, is influenced by IT. IT-related activities

must be accepted and applied in order for a

company to stay competitive; however, this is

only achievable if the company's employees are

willing to do so. This research is significant

because HRM is critical in the

telecommunications sector, where employees

are in close contact with consumers. As a result,

HRM that is assisted by electronic means is

rising in significance (Akman & Mishra, 2010).

As a consequence of the above, this study will

concentrate on the adoption of e-HRM in the

telecommunications sector in a developing

country such as Jordan. The key objectives of

this study are to investigate the factors that

impact e-HRM adoption and to identify the most

critical factors that personnel in the

telecommunications sector consider when

selecting whether or not to use e-HRM in their

job and use. The insights gathered will be

utilized to more efficiently and effectively

deploy specialists, maximizing utilization in

order to meet HR department goals that align

with the business's strategic objectives and,

ultimately, contribute to the company's success.

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3 Review of the literature

3.1 E-HRM

E-HRM has been defined in a variety of ways in

research articles, and Strohmeier & Kabst (2014)

is described as the design, development, and

deployment of IT to network and aid at least two

individual and group actors in performing HR

functions collaboratively. E-HRM is a wide term

that incorporates all of the integration techniques

and their associated content that exist between

HRM and IT, all of which are designed to

provide value to businesses (T. V. Bondarouk &

Ruël, 2009). By using e-HRM to manage

HR functions, they will become more exact,

quicker, transparent, and capable of being

performed in a short period (Fındıklı &

Bayarçelik, 2015). The goal of implementing e-

HRM in many areas and businesses is to assist

human resource departments in providing better

service to their clients (both employees and

management). As a consequence, HR will be

capable of playing a much more strategic role in

assisting the company in achieving its goals. The

use of e-HRM has helped organizations to

reduce their human resource headcount by

lowering costs and increasing the overall speed

of different activities.

E-HRM is classified into three types: relational,

operational, and transformational. The

application of E-HRM in the administrative

sector is referred to as operational E-HRM. The

compensation management (payroll) and human

data management functions are included in this.

Second, relational E-HRM, which corresponds

to more sophisticated HRM operations, is being

developed. Here, the emphasis is not on

administration, but rather on human resource

tools that support essential business operations

such as recruiting and choosing new workers;

training; performance monitoring and

evaluation; and recognition and rewards. An

online application or a paper-based strategy

(adverts, paper-based application forms, and

letters, etc.) can be used to aid in recruitment and

selection in relational e-HRM. Finally, there is

the Transformational E-HRM, which focuses on

the strategic components of HRM. This debate

covers organizational transformation methods,

strategic reorientation, strategic competence

management, and strategic knowledge

management, among other topics. Through

transformational e-HRM, an integrated

collection of web-based tools may be utilized to

develop a workforce that is prepared to respond

to the changes in the company's strategic goals.

Descriptive research was performed to conduct

the investigation. The researchers employed a

qualitative technique that includes an open-

ended survey as well as semi-structured

interviews to gather information. No one other

than personnel in the human resources

department was engaged in the selection process;

nobody from higher management levels or other

divisions was polled. It was discovered that e-

HRM is popular because it allows users to save

time, have access to personal information, and

save money on administrative expenditures.

Nagendra & Deshpande (2014) concluded that

more intelligent e-HRM systems are necessary

to increase the efficiency of HR planning.

According to the authors, they aimed to

investigate the function of the e-HRM subsystem

in training and recruiting as well as workforce

planning and the expansion of an organization's

personnel. Primary data was gathered from a

different department and administrative levels to

try to make the sample representative to sample

of 50 experienced and new

HR managers/executives from three firms in

Pune, with the sample size being 50. There is no

question that senior HR executives are well

aware of the fact that e-HRM has the potential to

increase the quality of HRM.

3.2 Adoption of e-HRM

Many researchers describe the adoption of

technology in a variety of ways, but in general, it

may be characterized as the positive technology

acceptance for use in one's working practices by

a majority of researchers (Strohmeier, 2007).

The distinction between E-HRM and HRIS is

that workers do not have access to the HRIS and

thus need assistance from the HR Department to

do so (Tanya Bondarouk, Harms, et al., 2017;

Obeidat, 2012). Employees, on the other hand,

may log into their E-HRM systems and carry out

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their HR responsibilities on their own. found that

developing countries are far behind the times in

terms of technical progress and that

implementing an E-HRM system is a difficult

task. Employee views toward the notion of E-

HRM also are negative (Cascio & Boudreau,

2014). Making the switch from a traditional

HRIS to an e-HRM system is an expensive but

useful strategy that also helps to decrease

administrative strain (Tanya Bondarouk, Harms,

et al., 2017). Because of a lack of information

about the adoption of E-HRM systems, adopting

the outcomes of an E-HRM system leads to the

generation of negative repercussions. The choice

to implement e-HRM varies from one setting and

one industry sector to another, and it is

influenced by a variety of unknown variables.

3.3 Theories of research variables

(Venkatesh et al., 2012) developed an expanded

UTAUT model called as UTAUT2 model as a

methodical synthesizing of earlier technology

adoption studies, based on a review of the

existing literature. Technology adoption is

influenced by several important dimensions such

as performance expectation, effort expectancy,

facilitating conditions, social influence, and

hedonic motivation, all of which are included in

UTAUT2.

The impact of performance expectancy (Masum

et al., 2015; Venkatesh & Zhang, 2010; Yusoff

& Ramayah, 2021), effort expectancy (Tanya

Bondarouk, Harms, et al., 2017; Chao, 2019),

facilitating conditions (Venkatesh & Zhang,

2010), social influence (El-Masri & Tarhini,

2017), hedonic motivation (Moorthy et al., 2019;

Tak & Panwar, 2017). Figure 1 illustrates the

conceptual framework of the research that was

constructed in light of the theoretical

underpinning and empirical data.

Figure 1: Conceptual Framework

Source: Author

3.4 The formation of hypotheses

Performance expectation (PE) may be defined as

the degree to which the individual feels that

following a certain technique will assist him or

her in achieving improvements in work

performance (Venkatesh et al., 2003).

Performance expectancy is an indicator of an

organization's intention to employ a new

technology(Venkatesh & Zhang, 2016).

According to the results of the present study,

performance expectation has a statistically

significant positive link with e-HRM adoption,

and the following hypothesis is proposed were

proposed in light of these findings.

H1: Performance Expectancy has a

positive and significant influence on the

adoption of e-HRM in the Jordanian

telecommunications sector.

The effort expectancy (EE) of technology is the

degree of ease with which it allows consumers to

interact with it (Venkatesh & Zhang, 2016). This

is the degree of comfort associated with the use

of a software system. Additionally, the extent to

which an individual believes he or she can

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employ technology without exerting additional

effort (Venkatesh et al., 2003). According to

several previous research (Zuiderwijk et al.,

2019), the Expected effort has a beneficial effect

on system acceptance and is a strong predictor of

system adoption for e-HRM implementation

(Mtebe & Raisamo, 2014). This study makes the

premise that if an e-HRM system is simple to

use, users will be more likely to use it, and the

following assumptions are based on that

assumption.

H2: Effort expectancy has a positive and

significant influence on the adoption of E-HRM

practices in the Jordanian telecommunications

sector.

Using the term "social influence," usually means

the degree to which a person believes that others

must agree with him or her that the new system

is something they should utilize (Venkatesh et

al., 2003). New technology is more likely to be

adopted if it is highly recommended by

individuals who are important to the user (Lee,

2005). The acceptance of e-HRM systems, for

example, is heavily influenced by social norms,

according to many kinds of research (El-Masri &

Tarhini, 2017). As a consequence, the following

theory was proposed.

H3: Social influence has a positive and

significant effect on the adoption of e-HRM in

the Jordanian telecommunications sector.

Facilitating conditions (FC) may be defined as

the physical surroundings or the environmental

elements that influence an individual's decision

to engage in a certain activity (Venkatesh et al.,

2003). It is a feature of the environment that

influences people's perceptions of how difficult

or easy it is to complete a job. When the

technology and organizational infrastructure

necessary to build FCs are accessible, people are

motivated to use e-HRM programs to improve

their views. FC is often regarded as a critical

quality in identifying an individual's technology

usage in the realm of information technology.

Venkatesh & Zhang (2016), and the majority of

research presumes that FC has an impact on the

user behaviour of e-HRM. As a result of this

debate, the following idea has been proposed:

H4: Facilitating conditions have a

positive and significant influence on the

adoption of E-HRM by organizations in the

Jordanian telecommunications sector.

Hedonic motivation (HM) is defined as the

pleasure or satisfaction derived from the

application of technological innovation

(Venkatesh & Zhang, 2016). It assesses the

participants' subjective happiness and

enjoyment. Venkatesh found extremely

favourable findings when he used this vector in

the UTAUT2 model to investigate the function

of intrinsic utilities. The findings of the Anouze

& Alamro (2020) study demonstrate that HM is

critical in influencing customers' adoption

behaviour when it comes to technology (Panos &

Bellou, 2016). Since utilizing an e-HRM boosts

people's happiness, they are more receptive to

using it again. Therefore, the following theory is

put forth.

H5: Hedonic motivation has a positive

and significant influence on the adoption of E-

HRM practices in the Jordanian

telecommunications sector.

4 Methods

A deductive approach has been adopted to

investigate the factors that affect the adoption of

e-HRM in the Jordanian telecommunication

sector. Jordan has three big telecom companies

with a total of 4224 employees (TRC, 2020b).

An online questionnaire survey was used to

conduct this quantitative investigation, which

allowed researchers to examine correlations

between variables indicated in the model and

provide evidence to support or reject the

hypotheses. From the current literature, five

independent factors were selected and tested.

After reviewing the literature and developing the

five hypotheses for testing, the conceptual model

shown in figure 1 has been produced, and it now

serves as an explanatory model.

A simple random sample was adopted to make

sure that the sample is representative of the

population. Random sampling guarantees that

the findings acquired from your sample are

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representative of those obtained by measuring

the full population (Shadish, 2002). This inquiry

was designed for anyone working in the

telecommunications sector at all administrative

levels, as all employees are forced to use

electronic means. As a result, persons were used

as the unit of analysis. The personnel in Jordan's

telecommunications sector make up the target

population for this research. A questionnaire was

created with Google Forms because it is the only

possible way to collect data in the covid_19 time.

There were 4,5,5,5, and 4 questions used to

assess each of the variables (Venkatesh et al.,

2003). Questionnaires were disseminated to

employees who work in 3 main

telecommunications Companies located in

Amman province, and 358 replies were

obtained. The components PE, EE, FC, SI, HM,

and e-HRM adoption were evaluated using a

five-point Likert scale, with respondents rating

their agreement on a scale ranging from strongly

disagree (1) to strongly agree (5). This study

used SPSS to analyze the data, and multiple

regression was used to assess the hypotheses that

were generated.

4.1 Sample size:

The survey has targeted three Jordanian

telecommunications sectors that use an E-HRM

system. A simple random sampling technique

was adopted to spread the online questionnaire.

With a confidence interval of 5% (margin of

error) and a confidence level of 95%, and a total

population of 4224 (tentative total of all

employees of the selected companies), the

sample size required is 353. A sample of such

population was used, which was based on the

Yamane, (1967) equation which reveals that:

𝑛 = 𝑁

1 + 𝑁(𝑒)2

where n = sample of study, N = population of

study, and e (precision) = 0.05. The sample size

of this research population, where N is 4224

employees are therefore determined to be 353 as

the previous equation applied. A total of 368

questionnaires were returned, with 358 being

completed and 10 were incomplete. Finally, the

completed questionnaires were, in numbers,

sufficient for this study and more than enough to

represent the population.

4.2 Data Analysis:

Sample composition is shown in Table 1 of the

research.

Table 1: Sample Characteristics

Category

Sub. Category

Freq.

Gender

Male

239

Female

119

Age

18-25 years

26-33 years

118

34-40 years

41-50 years

50-60 years

Education

Diploma

Undergraduate

287

Postgraduate

Source: Author collected data

It was determined that no missing values were

present in the data set once the data cleaning

screening process had been completed.

Cronbach's alpha is a common estimate for

determining internal consistency in a statistical

sample. An acceptable reliability score is 0.6 or

above on the dependability scale (Bagozzi &

Youjae Yi, 1988). As seen in Table 2, all of the

variables in the research had Cronbach's alpha

values more than 06, as shown by the numbers in

the table.

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Table 2: Test for Reliability

Variable

Cronbach’s Alpha

No of Items

Performance Expectancy

0.639

Effort Expectancy

0.750

Social Influence

0.676

Facilitating Conditions

0.699

Hedonic Motivation

0.634

E-HRM adoption behaviour

0.778

Source: Author collected data

Table 3: Descriptive Statistics

Variable

Mean

Std. Deviation

Performance Expectancy

3.5855

0.67084

Effort Expectancy

3.4786

0.58996

Social Influence

3.6964

0.59188

Facilitating Conditions

3.7334

0.58511

Hedonic Motivation

3.6854

0.76474

E-HRM adoption behaviour

3.9235

0.45957

Source: Author collected data

Following the descriptive analysis reported in

Table 3, the most significant mean value was

obtained from e-HRM adoption behaviour, while

the least significant mean value was obtained

from effort expectation. Hedonic motivation

produced the biggest standard deviation, while e-

HRM adoption behaviour produced the lowest

standard variance.

Table 4: Regression model summary and ANOVA (a)

Source: Author collected data

According to the results of Table 4, The multiple

regression coefficients (R) for the variables

components and e-HRM adoption behaviour were

0.514. The R-Square was 0.254 (25.4 percent) and

the adjusted R-Square was 0.246, according to

research data (24.6 percent ). The collection of

variables has a significant level of 0.000.

Table 5: Coefficient

Unstandardized

Coefficients

Standardized

Coefficients

Sig.

Results

Std. An

error of

the

Estimate

Change Statistics

Square

Adjusted R

Square

Change

Sig. F

Change

.514a

0.254

0.246

0.3994

0.264

13.637

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Std.

Error

Beta

Performance Expectancy

0.056

0.038

0.087

1.897

0.007

Supported

Effort Expectancy

0.089

0.054

0.105

1.788

0.388

Not supported

Social Influence

0.142

0.052

0.187

2.899

0.002

Supported

Facilitating Conditions

0.323

0.051

0.435

5.591

0.001

Supported

Hedonic Motivation

0.048

0.03

0.078

1.009

0.341

Not supported

Source: Author collected data

Beta values of all chosen independent factors are

positive in Table 5, and it has been shown that

these variables have a positive influence on the

adoption of e-HRM practices. Particularly

significant were the statistical significance

values of 0.007, 0.002, and 0.001 for PE, SI, and

FC.

5 Results and discussion

After the study was completed, the beta

coefficient for PE was found to be 0.087, with a

positive significant and sign indicating that it

supported the hypothesis's direction. The

significant level was found to be 0.007.

According to the obtained results, H1 was

accepted and adopted. In this study, the beta

coefficient for EE was 0.105, and the

significance value was 0.388. Therefore, it does

not meet the required significance threshold and

H2 couldn’t be supported. According to the

results, the SI beta value was 0.187, with 0.002

being the significance level. H3 is accepted as a

conclusion due to the positive direction and

significance value. The facilitating conditions

produced a beta coefficient value and

significance of 0.435 with a 0.001 acceptable

level of significance. H4 was accepted as a result

of this. The hedonic motivation was associated

with beta coefficient values of 0.78 and a level

of significance of 0.341. It reveals that the

hedonic motivation orientation toward adoption

is encouraging, but that it does not have a

significant impact on the adoption of e-HRM

among employees working in the

Jordanian telecommunications sector. Then, in

this study, H5 was not accepted as a hypothesis.

Employees in the telecommunications sector in

Jordan have a positive significant impact on the

adaptation of e-HRM, according to the findings

of the research. According to the results, the

most significant factors of e-HRM adoption are

facilitating conditions, social influence, and

performance expectation. Individuals are

persuaded to engage in certain activities when

they are presented with favourable physical and

environmental circumstances. The findings of

this study confirmed that the environment has an

impact on telecommunications

sector employees' perceptions of how easy or

difficult it is to complete a task.

As a result, they feel that if they have favourable

conditions, such as technology and

organizational infrastructure, they will be more

likely to embrace and use e-HRM software.

Social influence has a significant effect on the

adoption of e-HRM by Jordanian

telecommunications sector staff. Employees in

Jordan's telecommunications sector will evaluate

the other ideas and suggestions when

determining whether or not to use e-

HRM solutions. Employees in the

telecommunications sector are anticipated to

make extensive use of e-HRM. It demonstrates

that telecommunications Staff feel that e-HRM

may assist or even enhance job results, and as a

result, they prefer to accept and use e-HRM

systems in their work. The effect of hedonic

motivation and effort expectancy on the adoption

of an e-HRM system by Jordanian

telecommunications employees is also

confirmed in this study, although the effect of

hedonic motivation and effort expectancy on the

adoption of an e-HRM system by Jordanian

telecommunications employees is not

considered.

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Jihad Fraij

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Volume 21, 2022

This study contributes both practical and

theoretical. According to theory, the conceptual

model established in building the context may

provide a more complete explanation of the

variables that influence workers' e-HRM

adoption behaviour at work. The

telecommunications sector in Jordan was tackled

in this research as recommended by (Venkatesh

& Zhang, 2016), as it is one of the fastest-

growing sectors with a high percentage of staff

retention, and it was done so by choosing a

domain that could be verified in a varied setting.

This study made use of an expanded UTAUT2 to

include more perspectives on

telecommunications sector workers' e-HRM

adoption behaviour. The goal of this research

was to offer patients a clear route forward. The

findings will reveal where additional resources

should be directed to guarantee the efficacy of

the e-HRM implementation process. It also gives

the telecommunications sector officials in

Jordan an accurate image of their personnel'

characteristics in the occasion of implementing

an e-HRM device, as well as what employees

want to see included in their technological

working process, enabling prospective

deployments and existing installations to meet

the demands and wishes of employees. The

outcomes of this study will undoubtedly

help and advise on the critical aspects that

influence the adoption of e-HRM in the

telecommunications sector in developing

countries.

The main objective of this research was to

identify the important characteristics that affect

the adoption of e-HRM management in the

Jordanian telecommunications sector using the

results of the expanded UTAUT2 study as well

as empirical data from the field of technology

adoption. The UTASUT2 model was used to

determine average expected performance,

average expected effort, and facilitation

conditions, as well as social influence and

delicious stimuli, among others. This research

identifies the most important areas for the

adoption of e-HRM in the Jordanian

telecommunications sector. Three hypotheses

were accepted with statistically significant

values based on the theories and empirical

evidence, while two hypotheses were not

acceptable according to the analysis and

statistical significance. According to the findings

of this study, the most important positive and

influential factors in Jordan's

telecommunications industry are performance

expectancy, social influence, and facilitating

conditions. The most significant factors

influencing employees in the Jordanian

telecommunications sector's adoption of e-HRM

are, in particular, the facilitating conditions

available.

6 Future research

A list of the study's limitations was recognized,

and new research suggestions were given in light

of these findings. 358 people responded to the

survey using simple random sampling, although

different kinds of sampling might be performed

to give deeper statistical power and strengthen

the study's findings. For example, using a cluster

type of sampling. Adoption and use are

considered psychological processes, and

research utilizing longitudinal empirical

investigations would assist to acquire a good

grip. Future studies using a longitudinal study

design would greatly add to the literature. A

restricted number of instruments were utilized to

measure variables because of the unique

properties of the obtained context data. It is

recommended to incorporate additional

instruments in the questionnaire in future

research to provide more reliable results.

According to UTAUT2 theory and empirical

data, only five parameters were considered in

this investigation which contains aspects that

could affect the uptake of E-HRM. Many

mediators and moderators could help the

findings to be more understandable like

experience, knowledge transfer, and system

agility. Using some other variables would also

help the researchers to go more deeply into some

creative support for businesses and knowledge.

In the future, researchers will be able to

overcome these constraints in their studies.

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References:

[1]. Akman, I., & Mishra, A. (2010). Gender, age

and income differences in internet usage

among employees in organizations.

Computers in Human Behavior, 26(3), 482–

490.

https://doi.org/10.1016/j.chb.2009.12.007

[2]. Amin, H., Hamid, M. R. A., Lada, S., &

Anis, Z. (2008). The Adoption of Mobile

Banking in Malaysia: The Case of Bank

Islam Malaysia Berhad (Bimb).

International Journal of Business and

Society, 9(2), 43.

http://search.proquest.com/openview/bf0d0

d4d36c2861e284344f0ecb888c8/1?pq-

origsite=gscholar&cbl=28871

[3]. Anouze, A. L. M., & Alamro, A. S. (2020).

Factors affecting intention to use e-banking

in Jordan. International Journal of Bank

Marketing, 38(1), 86–112.

https://doi.org/10.1108/IJBM-10-2018-0271

[4]. Bagozzi, R. P., & Youjae Yi. (1988). On the

Evaluation of Structural Equation Models.

Journal of the Academy of Marketing

Science, 16(1), 74–94.

https://doi.org/10.1177/0092070388016001

[5]. Bondarouk, Tanya, Harms, R., & Lepak, D.

(2017). Does e-HRM lead to better HRM

service? International Journal of Human

Resource Management, 28(9), 1332–1362.

https://doi.org/10.1080/09585192.2015.111

8139

[6]. Bondarouk, Tanya, Parry, E., & Furtmueller,

E. (2017a). Electronic HRM: four decades of

research on adoption and consequences.

International Journal of Human Resource

Management, 28(1), 98–131.

https://doi.org/10.1080/09585192.2016.124

5672

[7]. Bondarouk, Tanya, Parry, E., & Furtmueller,

E. (2017b). Electronic HRM: four decades of

research on adoption and consequences.

International Journal of Human Resource

Management, 28(1), 98–131.

https://doi.org/10.1080/09585192.2016.124

5672

[8]. Bondarouk, Tanya, & Ruël, H. (2013). The

strategic value of e-HRM: Results from an

exploratory study in a governmental

organization. International Journal of

Human Resource Management, 24(2), 391–

414.

https://doi.org/10.1080/09585192.2012.675

142

[9]. Bondarouk, Tanya, & Ruël, H. (2010). The

strategic value of e-HRM: Results from an

exploratory study in a governmental

organization. CEUR Workshop Proceedings,

570, 15–32.

https://www.tandfonline.com/doi/abs/10.10

80/09585192.2012.675142

[10]. Bondarouk, T. V., & Ruël, H. J. M.

(2009). Electronic human resource

management: Challenges in the digital era. In

International Journal of Human Resource

Management (Vol. 20, Issue 3, pp. 505–514).

https://doi.org/10.1080/0958519080270723

[11]. Cascio, W., & Boudreau, J. (2014).

HR strategy: optimizing risks, optimizing

rewards. Journal of Organizational

Effectiveness, 1(1), 77–97.

https://doi.org/10.1108/JOEPP-01-2014-

0005

[12]. Chandradasa, A. H., & Priyashantha,

K. G. (2021). Key Determinants of E-HRM

Adoption Behavior.

http://192.248.48.160/handle/iruor/3704

[13]. Chao, C. M. (2019). Factors

determining the behavioral intention to use

mobile learning: An application and

extension of the UTAUT model. Frontiers in

Psychology, 10(JULY).

https://doi.org/10.3389/fpsyg.2019.01652

[14]. Chapman, D. S., & Webster, J.

(2003). The use of technologies in the

recruiting, screening, and selection processes

for job candidates. In International Journal

of Selection and Assessment (Vol. 11, Issues

2–3, pp. 113–120). Blackwell Publishing

Ltd. https://doi.org/10.1111/1468-

2389.00234

[15]. Cheng, Y., & Zou, Y. (2021).

Whether and when e-HRM improves

organizational performance: A meta-

analysis. Academy of Management

Proceedings, 2021(1), 13990.

https://doi.org/10.5465/ambpp.2021.133

WSEAS TRANSACTIONS on COMMUNICATIONS

DOI: 10.37394/23204.2022.21.12

Jihad Fraij

E-ISSN: 2224-2864

Volume 21, 2022

[16]. El-Masri, M., & Tarhini, A. (2017).

Factors affecting the adoption of e-learning

systems in Qatar and USA: Extending the

Unified Theory of Acceptance and Use of

Technology 2 (UTAUT2). Educational

Technology Research and Development, 1–

21. https://doi.org/10.1007/s11423-016-

9508-8

[17]. Fındıklı, M. A., & Bayarçelik, E.

beyza. (2015). Exploring the Outcomes of

Electronic Human Resource Management

(E-HRM)? Procedia - Social and Behavioral

Sciences, 207, 424–431.

https://doi.org/10.1016/j.sbspro.2015.10.112

[18]. Galanaki, E., Lazazzara, A., &

Parry, E. (2019). A Cross-National Analysis

of E-HRM Configurations: Integrating the

Information Technology and HRM

Perspectives. In Lecture Notes in

Information Systems and Organisation (Vol.

27, pp. 261–276). Springer Heidelberg.

https://doi.org/10.1007/978-3-319-90500-

6_20

[19]. Iqbal, N., Ahmad, M., Raziq, M. M.,

& Borini, F. M. (2019). Linking e-hrm

practices and organizational outcomes:

Empirical analysis of line manager’s

perception. Revista Brasileira de Gestao de

Negocios, 21(1), 48–69.

https://doi.org/10.7819/rbgn.v21i1.3964

[20]. Labrosse, M. (2008). Project

Management The Traction of Success. Wiley

Online Library, 83–88.

https://doi.org/10.1002/ert

[21]. Lee, L. B. (2005). Factors

influencing email usage: applying the

UTAUT model. Eprints.Usm.My, May, 1–

89.

http://eprints.usm.my/25624/1/FACTORS_I

NFLUENCING_EMAIL_USAGE_APPLY

ING_THE_UTAUT_MODEL.pdf

[22]. Lin, L. H. (2011). Electronic human

resource management and organizational

innovation: The roles of information

technology and virtual organizational

structure. International Journal of Human

Resource Management, 22(2), 235–257.

https://doi.org/10.1080/09585192.2011.540

149

[23]. Luftman, J. N., Lewis, P. R., &

Oldach, S. H. (1993). Transforming the

enterprise: the alignment of business and

information technology strategies. IBM

Systems Journal, 32(1), 198–221.

https://doi.org/10.1147/sj.321.0198

[24]. Maatman, M. (2006). Measuring the

effectiveness of e-HRM : the development of

an analytical framework for the

measurement of e-HRM and its application

within a Dutch Ministry. December.

http://essay.utwente.nl/583

[25]. Marler, J. H., & Parry, E. (2016).

Human resource management, strategic

involvement and e-HRM technology.

International Journal of Human Resource

Management, 27(19), 2233–2253.

https://doi.org/10.1080/09585192.2015.109

1980

[26]. Masum, A. K. M., Kabir, M. J., &

Chowdhury, M. M. (2015). Determinants

that influencing the adoption of E-HRM: An

empirical study on Bangladesh. Asian Social

Science, 11(21), 117–124.

https://doi.org/10.5539/ass.v11n21p117

[27]. Moorthy, K., Yee, T. T., T’ing, L.

C., & Kumaran, V. V. (2019). Habit and

hedonic motivation are the strongest

influences in mobile learning behaviours

among higher education students in

Malaysia. Australasian Journal of

Educational Technology, 35(4), 174–191.

https://doi.org/10.14742/ajet.4432

[28]. Mtebe, J. S., & Raisamo, R. (2014).

Investigating students’ behavioural intention

to adopt and use mobile learning in higher

education in East Africa. International

Journal of Education and Development

Using Information and Communication

Technology (IJEDICT), 10(3), 4–20.

https://www.learntechlib.org/p/148476/

[29]. Nagendra, A., & Deshpande, M.

(2014). Human Resource Information

Systems (HRIS) in HR Planning and

Development in Mid to Large Sized

Organizations. Procedia - Social and

Behavioral Sciences, 133, 61–67.

https://doi.org/10.1016/j.sbspro.2014.04.169

[30]. Njoku, E., Ruël, H., Rowlands, H.,

Evans, L., & Murdoch, M. (2019). An

Analysis of the Contribution of e-HRM to

Sustaining Business Performance (pp. 21–

39). https://doi.org/10.1108/s1877-

636120190000023003

[31]. Obeidat, B. Y. (2012). The

Relationship between Human Resource

Information System (HRIS) Functions and

Human Resource Management (HRM)

Functionalities. Journal of Management

Research, 4(4).

https://doi.org/10.5296/jmr.v4i4.2262

WSEAS TRANSACTIONS on COMMUNICATIONS

DOI: 10.37394/23204.2022.21.12

Jihad Fraij

E-ISSN: 2224-2864

Volume 21, 2022

[32]. Panayotopoulou, L., Vakola, M., &

Galanaki, E. (2007). E-HR adoption and the

role of HRM: Evidence from Greece.

Personnel Review, 36(2), 277–294.

https://doi.org/10.1108/0048348071072614

[33]. Panos, S., & Bellou, V. (2016).

Maximizing e-HRM outcomes: a moderated

mediation path. Management Decision,

54(5), 1088–1109.

https://doi.org/10.1108/MD-07-2015-0269

[34]. Parry, E. (2011). An examination of

e-HRM as a means to increase the value of

the HR function. International Journal of

Human Resource Management, 22(5), 1146–

1162.

https://doi.org/10.1080/09585192.2011.556

791

[35]. Parry, E. (2014). e-HRM: A Catalyst

for Changing the HR Function? (pp. 589–

604). https://doi.org/10.1007/978-3-642-

39747-9_24

[36]. Parry, E., & Tyson, S. (2011).

Desired goals and actual outcomes of e-

HRM. Human Resource Management

Journal, 21(3), 335–354.

https://doi.org/10.1111/j.1748-

8583.2010.00149.x

[37]. Rahman, M., Mordi, C., &

Nwagbara, U. (2018). Factors influencing E-

HRM implementation in government

organisations: Case studies from

Bangladesh. Journal of Enterprise

Information Management, 31(2), 247–275.

https://doi.org/10.1108/JEIM-05-2017-0066

[38]. Ruël, H., Bondarouk, T., & Looise,

J. K. (2004a). E-HRM: Innovation or

Irritation. An Explorative Empirical Study in

Five Large Companies on Web-based HRM.

Management Revu, 15(3), 364–380.

https://doi.org/10.5771/0935-9915-2004-3-

364

[39]. Ruël, H., Bondarouk, T., & Looise,

J. K. (2004b). E-HRM: Innovation or

Irritation. An Explorative Empirical Study in

Five Large Companies on Web-based HRM.

Management Revu, 15(3), 364–380.

https://doi.org/10.5771/0935-9915-2004-3-

364

[40]. Shadish, W. R. (2002). Revisiting

field experimentation: Field notes for the

future. In Psychological Methods (Vol. 7,

Issue 1, pp. 3–18).

https://doi.org/10.1037/1082-989X.7.1.3

[41]. SHILPA, V., & Gopal, R. (2011).

The Implications of Implementing

Electronic-Human Resource Management

(E-HRM) Systems in Companies. Journal of

Information Systems and …, 2(1), 10–29.

https://search.proquest.com/openview/c25ba

470cbaf3bb10e4b06452a0e8b41/1.pdf?pq-

origsite=gscholar&cbl=616602

[42]. Strohmeier, S. (2007). Research in e-

HRM: Review and implications. Human

Resource Management Review, 17(1), 19–

37.

https://doi.org/10.1016/j.hrmr.2006.11.002

[43]. Strohmeier, S., & Kabst, R. (2014).

Configurations of e-HRM - an empirical

exploration. Employee Relations, 36(4),

333–353. https://doi.org/10.1108/ER-07-

2013-0082

[44]. Tak, P., & Panwar, S. (2017). Using

UTAUT 2 model to predict mobile app based

shopping: evidences from India. Journal of

Indian Business Research, 9(3), 248–264.

https://doi.org/10.1108/JIBR-11-2016-0132

[45]. Talukdar, A., & Ganguly, A. (2021).

A dark side of e-HRM: mediating role of HR

service delivery and HR socialization on HR

effectiveness. International Journal of

Manpower. https://doi.org/10.1108/IJM-01-

2021-0038

[46]. TRC. (2020a). Annual report TRC.

https://trc.gov.jo/Pages/viewpage?pageID=2

[47]. TRC. (2020b).

TELECOMMUNICATIONS REGULATORY

AUTHORITY ANNUAL REPORT 2020.

https://trc.gov.jo/Pages/viewpage?pageID=2

[48]. Venkatesh, V., Morris, M. G., Davis,

G. B., & Davis, F. D. (2003). User

acceptance of information technology:

Toward a unified view. MIS Quarterly:

Management Information Systems, 27(3),

425–478. https://doi.org/10.2307/30036540

[49]. Venkatesh, V., Thong, J., & Xu, X.

(2012). Consumer acceptance and user of

information technology: Extending the

unified theory of acceptance and use of

technology. MIS Quarterly, 36(1), 157–178.

https://doi.org/10.1111/j.1365-

2729.2006.00163.x

[50]. Venkatesh, V., & Zhang, X. (2010).

Unified theory of acceptance and use of

technology: U.S. vs. China. Journal of

Global Information Technology

Management, 13(1), 5–27.

https://doi.org/10.1080/1097198X.2010.108

WSEAS TRANSACTIONS on COMMUNICATIONS

DOI: 10.37394/23204.2022.21.12

Jihad Fraij

E-ISSN: 2224-2864

Volume 21, 2022

56507

[51]. Venkatesh, V., & Zhang, X. (2016).

Unified theory of acceptance and use of

technology: U.S. vs. China. Journal of

Global Information Technology

Management, 13(1), 5–27.

https://doi.org/10.1080/1097198X.2010.108

56507

[52]. Wiblen, S., Grant, D., & Dery, K.

(2010). Transitioning to a new HRIS: The

reshaping of human resources and

information technology talent. Journal of

Electronic Commerce Research, 11, 251–

267.

http://ro.uow.edu.au/cgi/viewcontent.cgi?art

icle=1960&context=buspapers

[53]. Yamane, T. (1967). Elementary

sampling theory. Taro Yamane.

[54]. Yusoff, Y. M., & Ramayah, T.

(2021). The Adoption of e-HRM: A View of a

Telecommunications Company in

Zimbabwe.

http://libraryaplos.com/handle/123456789/7

950

[55]. Zhou, L., Chen, Z., Li, J., Zhang, X.,

& Tian, F. (2021). The influence of

electronic human resource management on

employees proactive behavior: based on the

job crafting perspective. In Journal of

Management and Organization.

https://doi.org/10.1017/jmo.2021.33

[56]. Zuiderwijk, A., Shinde, R., &

Janssen, M. (2019). Investigating the

attainment of open government data

objectives: is there a mismatch between

objectives and results? International Review

of Administrative Sciences, 85(4), 645–672.

https://doi.org/10.1177/0020852317739115

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