“The effect of talent management practices on employee turnover intention in the Information and Communication Technologies (ICTs) sector: case of Jordan”

This research aims to examine the intention of talented employees to leave an organization and discover how talent management practices could affect employee intention to leave an organization. This paper`s framework intends to outline the relationship between variables to present the idea of talent management practices and employee retention. The hypothesis was tested using a survey data set of 210 questionnaires collected from employees working in 82 ICT companies in Jordan to attain the research objectives. The collected data were analyzed using the SPSS program, and EMOS program, and basic and initial statistical techniques were applied. The results show that talent management practices significantly affect employee intention to leave an organization. Accordingly, whenever firms applied talent management practices, employee intention to leave decreases. The results demonstrated that attracting talented employees has emerged to have the strongest effect on decreasing employee intention to leave; however, developing and rewarding talented employees was revealed to have the lowest effect. Thus, the ICT firms’ managers have to generate specific training programs to reward and develop talented employees.


INTRODUCTION
Human resources possessing adequate capabilities and skills are of critical importance in all organizations, regardless of the field of activity in which they work (Dajnoki et al., 2018;Wiwczaroski, 2016).Ever since the McKinsey group devised the phrase "the war for talent" in 1997 (Lewis & Heckman, 2006), the issue of Talent Management (TM) has gained interest from scholars and practitioners.Despite the increasing popularity of TM, the concept of TM is still not very obvious.Moreover, how TM and other managerial perceptions are related is not covered in the literature, either (Anlesinya et al., 2019).TM is becoming a priority for organizations worldwide since they have realized its importance and its effects on performance (Cascio & Boudreau, 2016).Theron (2010) suggested that employee satisfaction and effective commitment often tend to lower worker intention to leave an organization.Bhatnagar (2008) wrote that good Human Resource Management (HRM) practices would create a good level of engagement, which will lead to a high level of retention.Bhatti et al. (2011) developed a model to examine the effect of effective HRM practices on developing employees with the required capabilities and skills to achieve organizational goals, arguing that it is important to keep those employees in the organization who possess them and reduce their intention to leave the organization.
The researchers have been interested in exploring the effects of talent management employee turnover (ETO) intention.However, studies on this issue using the samples from the ICT sector are still few.Therefore, the present study is of interest and provides additional understanding by demonstrating the effect of talent management practices in the ICT sector on employees' intention to leave the organization and their significance in improving employee engagement and performance, which, in turn, affects the overall success of the organization.

Talent management concept
During the last decade, the importance of talent management has emerged in the business world as a strategic dimension in the organization (Stevens, 2008;Jafari & Khanmohamadi, 2016).TM has a great impact on an organization's performance by minimizing the costs of the hiring process; it also increases the productivity, profitability, and output of a firm (Colling & Mellahi, 2009).When an organization applies TM, it creates tremendous opportunities for competitive advantages (Schuler et al., 2011).Indeed, an organization's position in its industry is determined by its ability to retain, engage, and develop talent.Therefore, TM is a factor leading to the failure or success of an organization (Luna-Arocas & Morley, 2015).
In modern times, researchers have been struggling to associate HRM and TM, due largely to the general confusion between both concepts.Problematic is the reality that TM and HRM are seen as two sides of the same coin (Luna-Arocas & Morley, 2015).
HRM widely focuses on all employees as an intangible asset, with no differentiation in skills, competency, or experience.On the other hand, TM focuses on certain pools of employees according to their talents and productivity (Jenkins, 2009;Schiemann, 2014).HRM has a relatively limited vision and scope of productivity since it focuses on people, while TM has a larger vision since it focuses on organizational goals and expected outcomes (Sheehan & Anderson, 2015).
Another difference appears in terms of employee determination; TM focuses on key employees and top talented employees.According to Morgan and Jardin (2010), key employees are those individuals who usually astonish their managers with their level of performance, showing preferred behaviors, and following the organization's code of conduct.They also possess a great interest in self-development (Cheloha & Swain, 2005).These employees are the main reasons why more customers are attracted, and more employees are motivated to work (Collings & Mellahi, 2009).
TM first analyzes the skills crucial for an organization's success, then aims to develop these skills.TM is considered a method to improve employee performance on the job by offering employees salary increases, which assists in psychologically tying the company's employees (Sonnenberg et al., 2014).This research focuses on three main talent management practices, which are considered the core components in the talent management process.Workforce planning, talent attraction, and development are critical links in an organization's talent supply chain (Anlesinya et al., 2019).Successful workforce planning helps organizations focus on meeting specifically identified workforce needs; thus, talent management is all about selecting the right people for the right positions.Furthermore, developing specific policies for attracting and retaining talent and evaluating future needs controlled using talent audits is also an essential part of the talent management process (Hedayati et al., 2016).Developing talent needs effort and longterm plans; however, creating a development plan is not difficult, but sustaining and measuring its ef-ficiency is (Ananthan et al., 2019).Educating and training employees helps to improve performance and retention (Schiemann, 2014).A more thorough discussion is performed, and specific examples of employee training are presented in detail by Wiwczaroski andRichter (2017, 2018).

Turnover intention
Employee turnover could be defined by the percentage or quantity of employees that leave an organization and get replaced with other new ones.Examining turnover is considered helpful for an organization to study cost-to-hire for the budget (Wei, 2015).According to Gupta (2019), the study of such turnover is essential because whenever a team member leaves an organization, the whole team will be affected, both in the team's quality and flow of performance.Other aspects that will be influenced are the flow of work flexibility, the relationships among the team members, and communication between themselves and the top management (Siddiqi, 2013).The researchers divided turnover into two categories: voluntary and involuntary.Voluntary turnover refers to cases when the employee resigns from the organization and quits based on his/her own decision.On the other hand, involuntary refers to cases when an employee is sacked from the organization, whether he/she wanted to stay or not (Wei, 2015).
Many researchers agreed that employee loyalty and employees trust influence turnover decisions in a major way and the kind of relationship between them is an inverse relationship (Lazányi & Bilan, 2017).When loyalty increases, the percentage of turnover decreases, and vice versa (Santhanam & Srinivas, 2019).Additionally, turnover is a consequential challenge to all organizations worldwide due to its critical consequences (Turkyilmaz et al., 2011).Hence, turnover can affect performance, efficiency, productivity, creativity, profits, and workplace environment (Rana & Abassi, 2013;Ahn & Chaoyu, 2019).Also, it will eventually have a significant impact on any organization over a longer period (Siddiqi, 2013).Turnover intention refers to the possibility of an employee imminently leaving an organization and is also believed to be the best indicator of turnover behavior (Ghadi, 2017).
Another study done by Demirtas (2015) stated that organizational ethics would affect the organization's employees' turnover intention.Job satisfaction and performance level are directly associated with turnover intention, which motivates organizations to decrease the percentage or number of turnover behavior due to the consequence of the cost (Ströbel et al., 2018).To conclude, ambiguity still surrounds the main reasons for turnover intention and behavior.Many researchers have proposed that the main reasons behind turnover, in general, are related to HRM practices (Wei, 2015).
The current business environment goes through different changes; it is also described by complexity, unpredictability, and uncertainty.Due to these changes, it is important to recognize how to retain and attract talented employees to invest in their knowledge and skills to enhance an organization's productivity and performance (Stevens, 2008).Talent management is becoming a key instrument in adapting to these changes, as organizations need to decrease turnover intention and thereby avoid the costs of hiring new employees and those related to decreased organizational efficiency (Jenkins, 2009).Employee intentions to leave an organization and employee commitment to an organization are considered important factors that directly affect organization strategy (Cichy et al., 2009;Herachwati et al., 2018).Bhatnagar (2007) studied the effect of talent identification on employee attitudes, such as employee engagement, and how it could reshape employee attitudes towards leaving the company for another.According to Busari et al. (2017), the reason behind employees' intention to leave their company might be the desire and ability of employees to improve their skills to be successful in their jobs.
Social Exchange Theory (SET) supports this study's assumptions, which supposes that if employees receive emotional and economic resources from their organization, they feel obliged to respond in kind and repay their organization.The result is that they will be more loyal, more committed, and more satisfied.On the contrary, should the said employees not receive enough resources, their intention to leave the organization will increase (Oehley & Theron, 2010).Many studies conducted in HRM (Egan et al., 2004;Luna-2011;Jenkins, 2009) have likewise supported the factors generally used in talent management.The authors would like to highlight Egan et al. (2004) who established and evaluated the turnover intentions model (TIM) to determine frontline employees' turnover intention based on examining their perceptions.The outcomes of studies carried out in this area signify that turnover intention and commitment in employees have been affected by perceived management concern for employees and customers, while this relationship was moderated by employment status (full-time or part-time).Jenkins (2009) created a new theoretical perspective to understand the nature of employee satisfaction change.Regardless of whether the level of satisfaction declined or improved over a specific period, the research, based on prospect theory and social exchange theory (Cook et al., 2013), helps one to understand how employee satisfaction can control employees' turnover intention.
Many studies have found a relationship between human resources practices and employee work attitudes, asserting that satisfied and committed employees are likely to make more efforts leading to high performance.Thus, in this study, the talented employee is expected to be more committed to their job, commit extra effort on the tasks, and have low intention to leave the organization.

Proposed research model and hypothesis development
Some researchers state that HRM and TM have the same functions, i.e., planning, recruitment, selection, retention, and development.However, differences appear in terms of emphasis (Schuler et al., 2011;Mucha, 2004).Figure 1 exhibits the conceptual model of this research.This model incorporates two main variables: talent management measured by using the three main practices (workforce planning, attracting talented employees, and developing and rewarding talented employees), which are considered to be the most effective practices, and the second variable, which is employee turnover intention.The model was structured according to the hypothesis that talent management practices were assumed to affect employee turnover intention.2010) also found that a reduction in employee turnover intention is, possibly, caused by effective talent management practices.In other words, when employees are highly qualified and have superb skills, they will have a higher level of turnover intention.However, when the organization that they work at applies effective talent management practices, that organization will increase their sense of commitment and lower their degree of turnover intention in a positive relationship (Barkhuizen, 2010).As a conclusion to the discussion thus far, the following hypothesis will be assumed: there is a statistically significant and negative effect of talent management practices on employee turnover intention (Barkhuizen, 2010; Cho & Lewis, 2012).

Sample and procedures
The Information Technology Association of Jordan (Intaj) was established in 2000 to support and serve the Jordanian ICT sector.Considering the qualified and skilled human resources as the most important asset in the firms, Intaj was established to provide the IT products and services from Jordan as a regional country leader.
The ICT sector was chosen as a population of study as it represents a high talent management-intensive industry that needs highly skilled, performed, and talented employees.All Intaj members are integrated within the Information and Communication Technology (ICT) sector in Jordan, and this will be the population of this study, which were (240) companies, which were surveyed until June 2019.
After analyzing the ICT firms to specify the last study population, the final number of ICT firms participating in filling in the questionnaire was 82, and the total number of valid questionnaires for data analysis was 210 questionnaires.The data were obtained from two sources: firstly, secondary data, which include a variety of articles, studies, and journals, which are employed to build the theoretical side of the research, and secondary primary data where the questionnaire instrument was used as a tool to collect this type of data for the first time to gather the required data for the study.
The collection of data procedures was done as follows; we started by preparing a list of contact information of ICT firms using the official website of the Intaj, and if the contact information was not available, it was obtained from the ICT firm's websites.Then, each ICT firm's HR department was contacted by telephone or email, and that helped the researcher to contact directly who is authorized to distribute the questionnaires in the firm and explain briefly about the study and its purpose.The authors then specified the number of questionnaires allowed to be distributed in each firm and how the firms preferred to receive the questionnaire.Most of the ICT firms preferred to receive it by hand, directly from us.Additionally, the contact information was given in case the firms have any inquires.Then, to ensure that the response rate will be high, the questionnaire items were translated into Arabic to ensure that the questionnaire items are fully understood and contacted the firms by telephone weekly after the questionnaires had been delivered.The authors started distributing the questionnaires in the middle of July 2019, and the data collection period continued until mid-August.Therefore, this process took approximately two months.To manage the data collection process, a spreadsheet was used for tracking the returned questionnaires.
The limitation was that most of the ICT firms were eliminated from the data collection phase since they did not accept to participate in this study due to their internal policy, which reduces the overall number of ICT companies who participated in the study and may cause a problem in generalizing the results for all ICT firms.Furthermore, the study's time did not allow us to examine additional dimensions of research widely and in-depth.

Research instruments
This research aimed to explore TM's effect on employee turnover intention; the primary data was collected by questionnaire.The questionnaire items measured the respondents' perceptions of talent management practices and employee turnover intentions.Also, the demographic data of the respondents in ICT firms were collected.The questionnaire was designed as follows: the beginning was an introduction to illuminate the study's main objective and ensure their answers would be treated as completely confidential.The introduction letter also asked them to be as honest and accurate as possible.Then, the following two sections constituted the actual questionnaire itself.The first section involved gathering the respondents' demographic data, with a total of 7 items needing to be answered.The second section shows the questions related to the study's independent variable and dependent variables, which consisted of 19 questions.The questionnaire applied a 5-point Likert scale.All the questionnaire items were adopted from pre-established items, which were used to measure the component of each variable in the study previously.

RESULTS
After data collection, the collected data were classified, sorted, and edited to be coded and analyzed using the SPSS program and the AMOS program.
Eighty-two firms operating in the ICT sector in Jordan accepted the request to participate in this study.250 questionnaires were distributed to the targeted sample, consisting of all the employees at different levels.240 questionnaires were returned.Because of their inadequacy for statistical analysis, 30 of these questionnaires were eliminated from the beginning due to missing data.Thus, the total number of analyzable questionnaires was 210 out of 250, with a response rate of 84%.Basic, initial statistical techniques were applied as follows.

Descriptive analysis for respondents
The respondents' demographic characteristics in the research consist of respondents' age, gender, educational level, job position, experience tenure, and monthly income.

Descriptive statistics for variables
The researchers conducted a descriptive analysis for the study variables, as shown in the following tables, to describe the respondents' answers and opinions towards the questionnaire items.The mean and the standard deviation were calculated for each study dimension.Table 2 shows the overall attitude of the respondents towards the first variable's dimensions.The results showed that the highest arithmetic mean is 4.95 for attracting talented employees and developing talented employees, with a standard deviation of 0.22, while the lowest arithmetic mean is 4.90, with a standard deviation of 0.29.This indicates that the Jordanian ICT sector's firms often implement policies that develop and reward talented employee practices.They encourage employees to develop their capabilities and aim to attract talented employees.

Normality test
The normality distribution test will be used to determine if data is distributed normally or not.In other words, this test aims to know if the sample of the study is representative of the population or not.The skewness test and the Kurtosis test will be used; thus, if the result of the skewness test ranges from 2 to -2, then that will be evidence that the data is normally distributed (West et al., 1995).It is clear from the results of Table 3 that all skewness values were between 2 and -2.This indicates that the data are distributed normally; the results of the sample can be generalized to the population.

Reliability and validity
Construct validity is not assessed in this study because the scales have already been developed and validated.Reliability is mostly related to how stable and consistent the measure is by using the same measurement tool over time in getting the same outcomes and results under similar conditions, so it is a sign of a biased (error-free) measurement.Reliability consists of internal repeatability consistency.Internal consistency is the "homogeneity of the items in the measure that tap the construct" (Sekaran & Bougie, 2009).Internal consistency is usually measured by Cronbach's coefficient alpha (Cronbach, 1946), which indicates if the items that are supposed to measure the same thing are positively associated with each other as a set.Cronbach's alpha reliability, in general, ranges between 0.0 and 1.0.The reliability of the constructs was tested using Cronbach's alpha coefficient.The alpha values were 0.833 for Workforce Planning, 0.865 for Tracking Talented Employees, 0.917 for Developing and Rewarding Talented Employees, and 0.941 for employee turnover the intention.These values indicated acceptable internal consistency with α > 0.70 for the constructs (Hair et al., 2010).Table 4 represents Cronbach's alpha coefficients for the study independent and dependent variables, which all show high reliability.

Correlation matrix and hypothesis test
Before testing the study hypothesis, the researchers must emphasize the relationship between the study variables using a correlation test.Table 5 shows the correlation between the research variables.Note: F1 -Talent Management Practices, F4 -Employee Turnover Intention.
Table 6 shows that the value of R 2 for the dependent variable (employee turnover intention) is 0.052, which means that TM practices can account for 5.7% for the variation of employee turnover intention.The above results show that TM has a negative statistical effect on employee turnover intention at the level of significance (0.05), where the statistical significance value (0.000) is less than 0.05, and the value of this effect is negative (-0.221).The increase in one unit in TM is expected to decrease employee turnover intention by (-0.221); therefore, according to the previous test, the hypothesis H1, which assumed that there is a statistically significant and negative effect of talent management practices on employee turnover intention, is accepted.
The overall mean for Developing and Rewarding Talented Employees is 4.03, with high relative importance for all of the items; the highest mean value is for item number one, saying top performers are challenged to improve their skills and take the next steps in their careers.
In an era where human resources management related resources are considered the backbone to achieve a sustainable competitive advantage, organizations need to know how to develop and maintain such resources.Talent management can be considered an effective tool in different organizations to achieve a competitive advantage by attracting and developing talented employees and maintaining them.One of the main purposes of this study is to investigate the effect of talent management practices on maintaining employees and how it could affect their intention to leave the ICT firms operating in Jordan.The findings emerging from hypotheses testing proved a statistically significant and negative effect of talent management practices on turnover intention.Talent management practices can reduce employee turnover intention.The findings of data analysis have con-firmed the effect of talent management practices on employee turnover intention.This result is consistent with previous literature that analyzed this relationship (Jenkins, 2009;Barkhuizen, 2010;Du Plessis et al., 2010).The talent management practices that had decreased employee turnover intention (β = -0.221,sig = .000).

DISCUSSION
There takes place the statistically significant effect of the talent management practices on the employees' turnover intention.This study's results are consistent with the results of the previous studies, which have discussed the same topic.Ironically, developing and rewarding talented employees were the least applied practices of talent management practices in the surveyed ICT firms.Additionally, tracking talented employees practically is the most practiced process in surveyed ICT firms.
Furthermore, to explain talent management practices and the ability to maintain employee relations better, TM is crucial for building employee satisfaction.Employee satisfaction, in turn, was found to be significant in employee retention.
The results of this study generated three important implications for managers and organizations in implementing talent management practices.First, organizations and managers can apply TM practices to enhance positive employee behaviors and reduce undesirable behaviors.Second, managers and organizations must note that employee satisfaction mediates the relationship between TM practices and maintaining employees.Consequently, they have to invest in and carry out TM practices that will increase employee satisfaction and enhance their affective commitment to obtain maximum employee effectiveness and success on the job.Finally, managers and organizations should note that employee satisfaction directly affects work attitudes, such as employee loyalty and commitment.Thus, organizations should introduce practices and ensure existing practices are followed to maintain these attitudes and reduce employee turnover intention.The previous findings of this study lead us to the following recommendations.This study's empirical evidence supports the general suggestion of using talent management practices and maintaining good employee relations.Managers and top management in the ICT sector are required to be "talent leaders" who must be aware of the relationship between talent and those who possess it to effectively develop their firm's human capital.ICT managers are open to examining how to include talent management practices in their firm's business strategy.They want to put systems into place to effectively integrate HRM activities and employee behaviors and with management to improve the firm's overall business position.
As has been confirmed before, attracting talented employees has emerged to have the strongest effect on maintaining employees, and developing and rewarding talented employees emerged to have the lowest effect.Thus, the managers of ICT firms are encouraged to have systematic programs to develop and train talented employees to convert implicit knowledge and skills into explicit knowledge, shared with all staff.
The results showed that ICT firms operating in Jordan have a high level of talented employees, indicating that ICT firms pay great attention to talented employees and make them satisfied and loyal.However, ICT firms with a low level of applying talent management practices will struggle to retain talented employees.These firms should pay more attention to their talent management practices to retain talented employees.
Employee satisfaction has emerged as an important catalyst for effectively keeping employees, and talent management practices need to reflect this.ICT firms also must stimulate talent management culture to encourage talented employees to make the most of the organization's opportunities and find the right role for themselves in the company.

CONCLUSION
By examining the literature findings on talent management relationship with turnover intention, there is quite a limited number of published research studies related to this paper's subject and especially related to the Jordanian ICT sector.Therefore, this study aims to reduce the gap in such a sector by examining the effect of talent management on Jordan's employee turnover intention.
A key contribution emerging from this study is that it has followed a comprehensive approach to examining the relationships between TM practices and employee turnover intention by developing a model comprising three key talent management practices: workforce planning, attracting talented employees, and developing and rewarding them.
Nevertheless, this study's findings agreed with those of prior studies, which emphasized the necessity for managers to pay more attention to and become more committed to stratifying talent management.
With a view of future research, one would suggest implementing such a study in Jordan's insurance sector since no literature was found in this field.The results would provide an opportunity to compare the implications and results from more than one sector by doing such a study.The authors would also propose developing this study by investigating other talent management practices not considered in this study.

A
model is created using the current empirical research in the area of TM and the latest research in human resources management area monitoring by reviewing the ideal research studies.The proposed model supports the existing understanding of TM by collecting and sorting various research study models, including SET, TM, and the reviewed model of turnover intention.A fair variety of TM research (Egan et al., 2004; Luna-Arocas & Camps, 2007; Hart & Thompson, 2007; Jenkins, 2009) has actually helped understand the turnover intent of employees from different companies.Besides, TM perspective and organizational perspective are closely related to each other.Therefore, organizational performance has important implications in the area of this study.The authors choose specific practices from TM, adjusted from Bagozzi's (1992) framework, such as employee commitment and employee satisfaction (Jenkins, 2009), and other practices of TM and HRM, as used in other studies (Mucha, 2004; Cheloha & Swain, 2005).The relationship between TM and turnover intention has actually been covered by numerous researchers, including (Barkhuizen, 2010; Cho & Lewis, 2012).Cho and Lewis (2008) test a model about employees' turnover intention and the best HR practic-Source: Own editing (2019).

Table 1 .
Table 1 presents the respondents' characteristics and the frequency and percentage of each variable.Research respondents' characteristics