Editorial Board

A Refereed Monthly International Journal of Management

How Knowledge Management Mediates the Strategic Role of Talent Management in Enhancing Customers' Satisfaction

Author

Dr. Zeyad Faisal Al-Azzam Education Malaysia Jordan, Jordan E-mail:- zeyad77@gmail.com

Dr. Atif Badri Al-Qura'an Jordan Bank, Jordan E-mail:- quraanatif@yahoo.com

Abstract

This article aims to investigate the nature and effect of talent management strategies on customer satisfaction in Jordan’s banking sector, as well as the mediating effect of knowledge management in this relationship. Based on the extant literature, the author developed indicators and multi-item measures for the independent variable, dependent variable, and the mediator using a survey instrument (sample N=1189, with an 89% response rate). The results show those employees’ perceptions of Talent Attraction Strategy, Talent Development Strategy, Succession Planning Strategy, and especially Talent Retention Strategy are the most important contributors to Talent Management. They also suggest that Talent Management Strategies contribute to enhancing customer satisfaction through improvements in knowledge management. Overall, the Study Equation Model demonstrates that knowledge management mediates the relationship between talent management strategies and customer satisfaction. As a rule, Talent Management Strategies have a positive relationship with knowledge management, which in turn has a positive influence on customer satisfaction.

JEL: M10, M19, M51.

Keyword : Talent Management; Strategies; Knowledge Management; Customer Satisfaction; Jordan Banking Sector.

1. Introduction

Knowledge is a vital and strategic resource that guarantees organizational survival in today's hypercompetitive environment. Both explicit and tacit knowledge are important to generate a competitive advantage, but this knowledge maybe managed inappropriately (McDonnell, Lamare, Gunnigle, and Lavelle, 2010). To succeed in a hostile environment, organizations need distinguished talent to confront the trends and challenges facing them. Moreover, top management must understand the necessity to attract, recruit, develop, and retain such talent, a critical resource for achieving strategic goals (Nilson and Ellström, 2012).

In today’s knowledge-based economy, the concepts of knowledge management (KM) and talent management (TM) have been used to improve organizational competitiveness and thus ensure a greater market share. KM is considered an intangible asset: tacit knowledge resides in the minds of an organization's workers, so organizations must manage those workers to compete in the marketplace. This requires adopting new strategic approaches to manage high-potential and high-performing workers, by investing in tacit knowledge and retaining (talented) workers (Kiessling and Harvey, 2006; Lawler and Ulrich, 2008; Senthilkumar and Kumudha, 2011; Whelan and Carcary, 2011).

Overall, KM denotes set of activities designed to discover, acquire, share, and apply knowledge among the workers in an organization, while the term talent—as in “war of talent,” a phrase coined by Steven Hankin of McKinsey & Company in 1997—refers to finding the most skilful candidates for the vacant positions. Thus, TM is concerned with the implementation of certain strategies and systems to enhance work productivity by developing processes for attracting, nurturing, developing, retaining, and utilizing workers’ knowledge (Bahrami and Gholami, 2016; Muntean, 2014; Shaemi, Allemah, and Bajgerani, 2011; Waheed, Zaim, and Zaim, 2012).

Traditionally, the role of human resource management departments was focused on HRM processes, but today’s HR departments have taken on a more strategic role in retaining the most critical key talents in the organization. Meanwhile, organizations’ strategic orientations have moved dramatically toward an increasing demand for high-quality products that continues to outstrip available resources (Hor, Huang, Liang-Chih, Hsu-Shih, Yen-Hua, and Lee, 2012; Kehinde, 2012; Koketso and Rust, 2012). Notably, most scholars and practitioners have argued that KM has been widely adopted and rigorously implemented in diverse industries, and is linked with organizational performance (Gholami, Asli, Shirkouhi,and Noruzy, 2013; Suraj and Ajiferuke, 2013; Yang, Lee, and Cheng, 2016; Zwain, Teong, and Othman, 2012).

In particular, this study investigates the strategic role of talent management strategies (TMS) in enhancing customer satisfaction within the banking sector of Jordan, by evaluating the mediating role of knowledge management. A Shortfall of talented and high-performing workers could affect the whole banking sector and harm the quality services it provides to customers. However, few efforts have been made to examine the relationship between talent management, customer satisfaction, and knowledge management in Jordan, despite the many studies assessing t service quality in other sectors and countries (Irtaimeh, Al-Azzam, and Khaddam, 2016).

2. Theoretical Background

2.1. Knowledge Management

Knowledge management (KM) was initially emerged in 1990s when the Skandia hired Leif Edvinsson as the Chief-Knowledge- Officer (CKO). Then, the KM idea was gradually taken up by academicians and scholarly such as Ikujiro Nonaka, Hirotaka Takeuchi, Thomas H. Davenport and Baruch Lev. (Wikipedia, 2016). As a result of evolution of this term, Thomas A. Stewart had developed the term of intellectual capital (IC) in 2001 protested that KM leads to IC. Regardless the school of thoughts, the keystone component of KM includes people, culture, process, structure, and technology; therefore, the synergies between these interrelated components constitute an infrastructure of KM (Becerra-Fernandez and Sabherwal, 2010).

Scholars and practitioners have postulated many definitions of KM, but there is no consensus on its big-picture definition. Knowledge creation is the most unique strategic resource in value-added creation. It prevents competitors from imitating and transferring intellectual competencies, as a high potential for value creation can be found in individuals who possess the highest knowledge. However, the challenge behind knowledge management is how to disseminate that knowledge properly (Halawi, Aronson, and McCarthy, 2005; Wernerfelt, 1984). As noted above, knowledge management strategies are used to discover, acquire, share, and apply knowledge among workers in the organization, to gain a competitive advantage. Generally, tacit knowledge is the most valuable intellectual resource to an organization since it comes from the long experience and expertise of individuals.

Thus, as long as information technology is developing, the importance of KM will increase: organization employees are competent only if they have high applicable knowledge (Sharif, Yaqub, Khan, and Javed, 2014). Modern business organizations must have knowledge for developing and enhancing products and services that meet customers’ evolving needs and desires. In addition to that, a successful organization should build a culture that promotes KM processes and learning process. Davenport & Prusak (1998) defined KM as a fluid mix of experience, policies and processes, while King (2009) mentioned that KM is a justified personal belief. Other researchers and practitioners view KM as a competitive strategy aimed at building, developing, sharing, pooling, and implementing knowledge to enhance individual competency, effectiveness, and the efficiency of the organization (Bratianu, 2010; Dahiya, Gupta, and Jain, 2012). Also, (Becerra-Fernandez and Sabherwal, 2010, 40) define KM as:

"KM is a performing the activities involved in discovering, capturing, sharing, and applying knowledge so as to enhance, in a cost-effective fashion, the impact of knowledge on the unit’s goal achievement."

Hence Tofighi, Fallah, and Khajeh (2012) agreed with scholars that knowledge management could be divided into two categories; overt and covert management. They confirmed that overt knowledge related to the formal ad verbal knowledge in which it can be transferred easily among employees. This type is, of course, known as explicit knowledge. While covert knowledge is so difficult to express and it is embedded in individual minds. This type of knowledge is known as tacit knowledge.

KM literatures have identified several dimensions of KM, mostly focusing on identification, acquisition, storage, sharing, and application (Barkhuizen, Mogwere and Schutte, 2014; Daud and Abdul Hamid, 2006; Gholami et al, 2013; Gold, Segars, and Malhotra, 2001;Kiessling, Richey, Meng, and Dabic, 2009; Lee, Ching, and Yang, 2000;Lee, Lee, and Yoo, 2000; Liao and Wu, 2009; Nonaka, Byosiere, Borucki, and Konno, 1995; Zwain et al., 2012), while Nonaka and Takeuchi(1995) divided knowledge into implicit, tacit, explicit, and external knowledge. Additionally, Nonaka (1994) identified two dimensions of knowledge: the epistemological dimension, which converts tacit knowledge into explicit knowledge and vice versa, and the ontological dimension, which transfers knowledge (whether it is tacit or explicit) from individuals to groups and further to the organization. For the purposes of this study, we will consider the four dimensions of KM that Becerra-Fernandez and Sabherwal (2010) identified: Discovery, Acquisition, Sharing, and Application.

2.2. Talent Management Strategies

Talent management quickly emerged into business in the early 1990s as a significant and strategic resource that can enhance overall organizational performance, and it has been widely adopted in 21^st century business organizations. Many practitioners and scholars have defined talent from different angles, for instance, Goffee & Jones (2007) defined talent as skilful employees who make new value-added contributions to the organization through demonstrating the highest levels of potential. There is still no consensus definition for talent, but some scholars have defined talents as individual abilities and capabilities that lead to competencies needed by the organization for future strategic purposes. These could include employees’ skills, knowledge, experiences, attitudes, behaviours, and potentials (Grobler and Diedericks, 2009; Lewis and Heckman, 2006; Michaels, Handfield-Jones, and Axelrod, 2001; Tansley, Stewart, Turner, and Lynette, 2006).

Although the precise definition of talent management remains controversial, scholars and theoreticians agree on the major pillars that formulate it. TM involves the human resource procedures, practices, and techniques used to perform HR activities—not only staffing and recruiting, selection and training, development and compensation, and succession planning, but also the attraction, identification, engagement, retention, and deployment of skilful individuals. In other words, TM is about finding the right person at the right time in the right place (Ahmadi, Ahmadi, and Abbaspalangi, 2012; Dhanalakshmi and Gurunathan, 2014; Reilly, 2012; Wilcox, 2016). Moreover, it entails extracting the high potential of talented employees for future incumbent positions, to meet present and future HR needs and to achieve competitive advantage (Campbell & Hirsh, 2013; Câmpeanu-Sonea, Sonea, Gabor-Supuran, and Mureşan, 2011; Jain, Sharma, and Sharma, 2012; Kehinde, 2012).

Even though many studies have been conducted on how to benefit from talent management as a technique over time, work on how to strategize organizational talents for the future is still lacking. To fill this gap, we investigate the following four talent management strategies:

1- Talent Attraction Strategy: competitive organizations must rethink their human resources to face current and future challenges such as globalization, technological advancement, and free trade agreements. These trends require flourishing new capabilities and talented individuals who are equipped with high experience, skills, knowledge, abilities, and tacit knowledge. They are always in demand to meet strategic organizational objectives, so businesses must apply successful talent attraction strategies to attract key talented individuals (Miller, 2014). Before attracting talented workers, HR departments should revise organizational needs through job analysis, to find out not only the vacant positions but also which competencies and capabilities suits the position, and to determine how to fill them accordingly. Generally speaking, they must adopt the concept of a talent profile to gather all their skilled and competent workers for future needs. HR managers should be alert and aware of organizational needs, so they can react swiftly to attract and hire talented workers.

2- Talent Development Strategy: from time to time, top management should assess its employees’ performance and their contributions to the organization. Performance gaps should be immediately bridged through administrative tools such as orientation and training programs, career development, and so onto identify and promote high- potential talents (Chodorek, 2012; Poorhosseinzadeh and Subramaniam, 2012, 2013; Ready, Hill, and Thomas, 2014). Talents need to be up-to-date with knowledge and technological innovations to be invested in organizational products and services. Different types of development techniques can be used, such as online training, on-the-job training, seminars, courses, and conferences.

3- Talent Retention Strategy: once talented workers are attracted and developed, organizations must follow a strategy to retain them. Retention of those talents means a full package of compensation with a corporate culture that meets their needs and expectations. This may seem costly but is very reasonable given the return on talent. According to Whelan & Carcary (2011), a sound retention strategy depends on hygiene and intrinsic factors, while Irtaimeh et al. (2016) emphasized performance, communication, loyalty and competitive advantage.

4- Talent Succession Planning Strategy: this strategy focuses on how to prepare talented workers for future vacant positions, especially through mergers and acquisitions. At this point, most successful organizations tend to have a pool of talent for future needs.

2.3. Customer Satisfaction

Satisfaction is the state of a person’s feelings (whether pleasure or disappointment) when comparing a product’s perceived performance or outcomes with their expectations of those products, such that satisfaction is the difference between expectations and actual performance (Kotler and Armstrong, 2002; Kotler, Armstrong, Saunders, and Wong, 1999; Kotler and Keller, 2009). As a matter of fact, satisfaction can vary from one person to another because it is a utility. Customer satisfaction in banking means the attitudes and responses of customers toward the bank's financial and marketing services or some aspect of trading (Ahmad, Nawaz, Khan, Khan, Rashid, and Khan, 2011; Jenkinson, Coulter, Bruster, Richards, and Chandola, 2002). Moreover, the bank’s executives should focus their efforts on how to increase customer satisfaction, to enhance the quality of banking services provided (Al-Abri and Al-Balushi, 2014).

Due to technological development, globalization, and social media, customers are becoming more knowledgeable about and aware of service standards, so their perception and expectations are continually evolving. Therefore, psychological and physical factors are the drivers for generating satisfaction and satisfaction behaviours. Many scholars and theoreticians agree that service quality is a determinant of customer satisfaction because it comes from the service provider (organizations), since customers benefit from service quality and their satisfaction is mandatory for the organization’s continuity and growth. Satisfaction and service quality have certain things in common, but satisfaction is generally a broader concept whereas service quality focuses specifically on dimensions of service (Agbor, 2011; Hejase, Hejase, Mikdashi, and Bazeih, 2016; Nzewi, Chiekezie, and Ogbeta, 2015).

3. Previous Studies

Several studies have been conducted to investigate the role of talent management in service sector, but only a few explored the role of knowledge management as a mediator between talent management and customer satisfaction. In their study Areiqat, Abdelhadi, and Al-Tarawneh (2012) studied the impact of talent management practices on employees’ performance, to enhance their ability to deal with high-demand prospective customers. Moreover, Soltani and Ardeshiri (2014) investigated the influence of knowledge management and talent management on competitive advantage. They concluded that both concepts have a significantly positive effect on competitive advantage.

Oladapo (2014) conducted a study to evaluate the most successful talent management strategies and programs employed (they choose the predictive power of job security, compensation, and opportunity) on the retention of talented workers in American companies. His study revealed that most organizations in the United States agree on the importance of employing talent management programmes, and for organizations with such programs the most significant effect variable was opportunity for job advancement, compared to organizations which didn’t employ such programs. Job security, compensation, and opportunity did not predict talent retention at all due to a lack of executive support.

Rácz, Bencsik, Bognár, and Stifter (2014) presented a similar paper at conference on the reproduction of human capital, aimed at raising attention to the importance of knowledge and talent management and their impact on business success. Surprisingly, they found no significant relationship between talent, knowledge managed, and the types of organizations where either effect was observed.

In their study, Bayyurt and Rizvi (2015) investigated the effect of five talent management dimensions on perceived organizational effectiveness in the service industry of Pakistan. Their results show that all five dimensions were significant. Moreover, the dimensions of talent management; human resource policy, training and development, ability, and motivation, were found to have a strong impact on perceived organizational effectiveness.

However, opportunity had no impact on perceived organizational effectiveness. This was contradicted by Morsy’s (2013) study of how talent affects job and organizational engagement at Zagazyg University Hospitals. The effect was significant and positive when work-family balance mediated between employees’ engagement and service quality.

Iratimeh et al. (2016) explored the effect of implementing talent management strategies (TMS) and service quality (ServQual) on beneficiaries’ (customers’) satisfaction (BS) in the healthcare sector of Jordan from the providers’ point of view. Positive correlations were found to be statistically significant between talent management strategies, service quality, and beneficiaries’ satisfaction. Finally, Nafei (2015a) concluded that a statistically significant relationship between talent management and health service quality exists. Optimistically, Nafei (2015b) conducted another study that proved the effect of talent management in enhancing service quality in the commercial banks of Egypt.

4. Research Hypotheses and Model

This research aims to investigate the relationship between TMS and customer satisfaction in the Jordan banking sector, as well as the role of knowledge management as a mediator in that relationship. Therefore, we test the following hypotheses to test our research model, shown in Figure 1.

H1: Talent management strategies have a significant impact on customer satisfaction in the Jordan banking sector.

H2: Talent management strategies have a significant impact on knowledge management.

H3: Knowledge management has a significant impact on customer satisfaction.

H4: Knowledge management plays a mediating role in the relationship between talent management strategies and customer satisfaction.

Figure 1. Research Model .

Source: Developed by author.

5. Research Methodology

5.1. Research Population and Sample

This study is empirical based descriptive survey was used to collect data from a population of workers in the banking sector of Jordan. Total of (22) banks operating in Jordan were included in the study. A random sampling was used to identify potential participants from three different zones, located in the north, middle, and south of Jordan.

5.2. Data analysis

The researcher was used statistical package SPSS software (version 22.0) for data analysis. Cronbach Alpha was used to test the instrument reliability, Pearson correlations matrix between study variables, and finally structural equation modeling was employed to investigate the effect of the mediator in the relationships between independent and dependent variables.

5.3. Measurement Scale

The current study has reviewed the past literatures in order to design and develop questionnaire with a multidimensional measurement scale for the study variables. The first measurement scale was talent management strategies that have been developed consist of four dimensions namely; talent acquisition, talent attraction, talent retention, and talent succession planning. The second measurement scale was knowledge management that was developed and adapted from Bourini, Khawaldeh, and Al-Qudah (2013). Finally, the customers' satisfaction measurement scale was developed and adapted from Walfried, Manolis, and Winsor (2000). The survey’s answer options employed a five-point Likert-scale, from (1) "strongly agree" to (5) " strongly disagree". Prior to distributing the survey on respondents, seven experts and scholars were asked to review the survey items to be consistent with Jordan environment and make sure the readability of questionnaire survey. Subsequently, the 50 questionnaire surveys were randomly distributed, as a pilot study, on employees as well as managers in different regions of operating banks in Jordan to identify ambiguities in terms, easiness of the wording, and relevance of items used in the survey. Therefore, the questionnaire had a high level of content validity. 5500 questionnaires were distributed on the employees and managers working at different locations in the operating banks in Jordan. Only 2984 questionnaires were returned which included 2881 valid questionnaires and 103 invalid ones. The effective response rate was 54.25%.

Internal reliability of the survey instrument adapted was used and results of testing scale reliability show a good internal consistency. As seen in table 1 Cronbach alpha reliability coefficients are at acceptable levels and fall between 0.72 for the customer commitment scale and 0.97 for succession planning strategy.

Table 1. Cronbach’s Alpha.

Variables	Cronbach’s Alpha
Talent Management Strategies	0.91
Talent Attraction Strategy	0.87
Talent Development Strategy	0.94
Talent Retention Strategy	0.89
Succession Planning Strategy	0.97
Knowledge Management	0.83
Knowledge Discovery	0.79
Knowledge Acquisition	0.87
Knowledge Sharing	0.75
Knowledge Application	0.88
Customers' Satisfaction	0.76
Customer Commitment	0.72
Customer Loyalty	0.78

Source: Developed by the author based on SPSS results.

6. Results

6.1. Correlations

In general, the correlations between all the variables, as shown in Table 2, obviously show a positive and significant relationships between TMS and KM (sig.=0.912) and customer satisfaction (sig.=0.961). Moreover, these results show that each talent management strategy has a positive and significant relationship with each KM dimensions. Also, each TM strategy has a positive and significant relationship with the customer satisfaction dimensions. As we noted that although talent management and knowledge management continued to evolve, still they consisted of different theoretical constructs that caught scholars and practitioners attention because of their interconnectedness (Wang-Cowham, Kamoche, Tansley, and Iles, 2012). Therefore, the role of individuals in knowledge management has widely investigated, in which the theoreticians and scholars preferred the term of talent management instead.

Table 2. Correlations Results.

** Correlation is significant at P ≤ 0.05.

Source: Developed by the author based on SPSS results.

The recent works have been exploring talent management in knowledge- intensive corporations by incorporating talent management principles and practices in knowledge management practices which they significantly confirmed its relationship (Rechberg & Syed, 2011; Bonache & Zarraga-Oberty, 2008; Matsuo & Easterby-Smith, 2008; Miao, Choe, & Song, 2011; Whelan, Collings, & Donnellan, 2010; Whelan & Carcary, 2011). Despite of these researches investigations, still the connection between talent management and knowledge management scarce. However, this study addressed positive and significant relationships between talent management and knowledge management with its all dimensions in which it is considered a competitive advantage to the current theoretical literatures.

6.2. Results of Structural Equation Modelling Analysis

First of all, to estimate the hypothesized relationships, we followed Anderson and Gerbing’s (1988) and Henseler, Ringle, and Sinkovics’ (2009) approach of two-stage modelling, evaluating a) the measurement model and b) the structural model. CFA was conducted to assess the validity of the scales used in the study. The measurement fit model results revealed that they all have a goodness of fit and robustness of the model. All have significant values for their standardized coefficients (P ≤ 0.05) being the model is suitable for measuring the specified constructs. Hence, the convergent validity for all scales was established and all scales have above the recommended limit 0.5.

In the second phase, structural modelling (AMOS 20), as recommended by Anderson and Gerbing (1988), was carried out. In the present study, the relationship among talent management strategies, knowledge management, and customer satisfaction was assessed. Testing the first three hypotheses was necessary to prove mediation: 1) the independent variable (TMS) should significantly predict the dependent variable (customer satisfaction), 2) the independent variable (TMS) should significantly affect the mediator (KM), and 3) the mediating variable (KM) should significantly affect the dependent variable (customer satisfaction).

Table 3. Overall Indices of Fit of the Measurement Models.

Note: RMR= root mean squared error; GFI= goodness of fit index; AGFI= adjusted goodness of fit index; CFI= comparative fit index; RMSEA= root mean square error of approximation.

***P<0.001.

Source: Developed by the author based on statistical results.

First, we tested the direct structural effect from talent management strategies to customer satisfaction (SRW=0.87, p ≤0.001). Secondly, we tested the direct structural effect from talent management strategies to knowledge management (SRW=0.95, p ≤0.001). Lastly, we tested the direct structural effect from knowledge management to customer satisfaction (SRW=0.93, p ≤0.001). Based on the data shown in Table 4, all three relations and their goodness of fit were appropriate, which leads us to accept our first three hypotheses, H1, H2 and H3, as well as to satisfy the three conditions of mediation.

Table 4. Result of Model Comparison.

Note. df= degree of freedom; RMSEA= root mean square error of approximation; NFI= normal fit index; CFI= comparative fit index.

***P<0.001.

Source: Developed by the author based on statistical results.

To assess the mediating role of knowledge management in the relationship between talent management strategies and customer satisfaction, a sequence of mediation tests given by Kelloway (1998) was employed by comparing three models (no mediation, partial mediation, and full mediation) and testing the significance of ∆χ². Differences between the models were assessed through both the chi-square difference test and the change in the CFI values (Arnold, McKee, Kelloway, Barling, and Turner, 2007). The first model (no mediation) traced the impact of the independent variable (TMS) and the mediating variable (KM) on the dependent variable (CS), with no path from (TMS) to (KM). The second model traced partial mediation by knowledge management. This model adds three paths that link TMS to CS to estimate the proportion of the direct effect of TM both directly and indirectly through KM. Introduction of the third model made the direct relationship between TMS and CS insignificant, hinting at full mediation . So, the third model (full mediation) traced the indirect impact of TMS on CS through KM as the mediator (Sobal test=2.596, p≤0.001).

Table 4 shows that the fully mediated model provided a better fit to the data than the partially mediated model (∆χ² = 7.345, p ≤0.1; ∆CFI= 0.2) or the non-mediated model (∆χ²= 213, p ≤0.1; ∆CFI= 0.5). In other words, the findings revealed strong support for the mediating role of knowledge management between talent management strategies and customer satisfaction. Therefore, Hypothesis 4 is accepted and the final model appears in Figure 2.

Figure 2. Final Model with significant pathways of focal variables.

7. Discussion and Conclusion

The major results of the present study revealed significant and positive effect of talent management strategies on both knowledge management (the mediator variable) and customer satisfaction (the dependent variable). Also, they revealed that knowledge management has a direct and positive effect on customer satisfaction as well as playing a mediating role in the relationship between talent management strategies and customer satisfaction. This finding can be explained by the strongest workers’ perceptions about the implementation of talent management strategies, knowledge management practices, and awareness of the importance of satisfying customers in a sensitive and supported banking sector of Jordan. This implies that the strategic role of aligning business strategies with the strategic human resource pool that emerged in detecting the talented workers have been clearly understood by strategic leaders, who are equipping their organizations with strategic vigilance and agility (Irtaimeh, 2017). We believe that implementing knowledge management processes (discovery, acquisition, sharing, and application) will certainly help organizations as a whole to diagnose their requirements and the talent shortfalls relevant to meeting their objectives.

Further, it can be inferred from the results that acquiring knowledge increases employees’ capabilities to discover and identify significant resources and opportunities, for the purpose of growth and diversification of the organization’s services as well as to remain competitive (Nguyen and Neck, 2009). Of course, the talent attraction process has always been used in organizations to promote effective and efficient organizational performance and to enhance their competitive position. Knowledge integration, utilization, and application have likewise been used effectively to increase talented workers’ knowledge, solve problems, and maintain competitive advantage. Additionally, organizations create and discover ways to enhance their talents and capabilities; besides this, most organizations take precautions to protect their tacit knowledge that resides in the minds of talented employees.

According to scholars and practitioners, organizations invest in their knowledge management because they can generate innovative ideas and thoughts from both internal and external knowledge, which makes them more innovative and creates a solid foundation of talented workers. Consequently, it is important to understand that while knowledge management is a part of any individual (knowledge, skills, and experience), its execution depends on the knowledge culture of the organization (Molina-Morales et al., 2011). This culture would ideally help individuals become more innovative by developing ideas, products, and processes and by creating new market opportunities. Moreover, through knowledge management processes and capability enhancement organizations develop skills by acquiring, moving, distributing, and implementing accumulated knowledge, thus increasing the variety of the organization’s memory (Akram, Siddiqui, Nawaz, Ghauri, and Cheema, 2011). In this sense, knowledge management functions as a coordinator for the explicit and tacit knowledge distributed in the organization. The strategic importance of talent management helps organizations identify abilities it can improve to gain sustainable competitive advantage as well as customer satisfaction.

Ultimately, implementing talent management strategies depends mainly on knowledge management processes that combine to create a sustainable competitive advantage, which in turn increases customer satisfaction by demonstrating their commitment to the organization and their loyalty to its services. Above all, talented workers need to be trained and developed, thus improving their capabilities, knowledge, and attitudes and creating a triangle of talent: skills, knowledge and attitudes (Al-Azzam, Irtaimeh, and Khaddam, 2017).Therefore, the authors recommend future in-depth research on the effect of talent management on organization performance, by considering certain indicators of growth and development such as growth strategies.

8. References

1. Agbor, Jenet Manyi. (2011) The Relationship between Customer Satisfaction and Service Quality: a study of three Service sectors in Umeå . Master Thesis (unpublished): Umea University.

2. Ahmad Iftikhar, Nawaz Allah, Khan Shadiullah, Khan Habibullah, Rashid Muhammad A.,& Khan Muhammad H. (2011) Predictors of Patient Satisfaction. Gomal Journal of Medical Sciences , V. 9, No. 2, p 183-188.

3. Ahmadi, Ali Akbar, Ahmadi, Freydon, and Abbaspalangi, Javad. (2012) Talent Management and Succession Planning. Interdisciplinary Journal of Contemporary Research in Business , V. 4, No. 1, p 213 – 224.

4. Al-Abri Rashid, & Al-Balushi Amina. (2014) Patient Satisfaction Survey as a Tool Towards Quality Improvement. Oman Medical Journal , V. 26, No. 1, p 3-7. doi: https://dx.doi.org/10.5001%2Fomj.2014.02 .

5. Al-Azzam, Zeyad Faisal, Irtaimeh, Hani Jazza’a, & Khaddam, Aminah Abdul Halim. (2017) Examining the Mediating Effect of Strategic Agility in the Relationship between Intellectual Capital and Organizational Excellence in Jordan Service Sector. Journal of Business , V. 6, No. 1, p 7-15.

6. Akram, Kashif, Siddiqui, Suleman H., Nawaz, Muhammad A., Ghauri, Tauqir A.,& Cheema, AmjadK H. (2011) Role of Knowledge Management to Bring Innovation: An Integrated Approach, International Bulletin of Business Administration, V. 11, p 121-134.

7. Anderson, J.C., & Gerbing, D.W. (1988) Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin , V. 103, No. 3, p 411–423.

8. Areiqat A. Y., Abdelhadi T., & Al-Tarawneh H. A. (2010) Talent Management as a Strategic Practice of Human Resource Management to Improve Human Performance. Journal of Contemporary Research in Business , V. 2, No. 2.

9. Arnold, K.A., Turner, N., Barling, J., Kelloway, E.K., & McKee, M.C. (2007) Transformational Leadership and Psychological Well-being: The Mediating Role of Meaningful Work. Journal of Occupational Health Psychology , V. 12, No. 3, p 193–203.

10. Bahrami, Mohammad Amin & Gholami, Abdolkhalegh (2016) The Relationship between Knowledge Management and Talent Management and Employee Engagement Export Development Bank of Iran. International Academic Journal of Accounting and Financial Management , V. 3, No. 10, p 32-41.

11. Barkhuizen N., Mogwere P., & Schutte N. (2014). Talent Management, Work Engagement and Service Quality Orientation of Support Staff in a Higher Education Institution. Mediterranean Journal of Social Sciences , V. 5, No. 4, p 69-77.

12. Bayyurt, Nizamettin, & Rizvi (2015). Impact of Talent Management on Perceived organizational Effectiveness: Service Industry in Lahore, Pakistan. Research Journal of Business and Management , V. 2, No. 4, p 468-487.

13. Becerra-Fernandez, Irma & Sabherwal, Rajiv Sabherwal (2010) Knowledge Management: Systems and Processes. M. E Sharpe Inc. New York: USA.

14. Bratianu, Constantin (2010) A Critical Analysis of Nonaka’s Model of Knowledge Dynamics. Electronic Journal of Knowledge Management , V. 8, No. 2, p 193 –200.

15. Campbell V., & Hirsh W. (2013) Talent Management: A Four-Step Approach. Institute for Employment Studies: UK.

16. Câmpeanu-Sonea, E., Sonea A., Gabor-Supuran, R., Mureşan, A. (2011) “Organizational Competence – A Development Framework”. Management & Marketing , V. 6, No. 2, p 301–318.

17. Chodorek Monika. (2012) The Place and Role of Talent Management in the Positive Organizational Potential: An Empirical Study of Companies Operating in Poland. Competition Forum , V. 10, No. 2.

18. Dahiya, D., Gupta, M., & Jain, P. (2012) Enterprise Knowledge Management System: A Multi Agent Perspective. Information Systems, Technology and Management , V. 285, p 271-281

19. Daud, S., & Abdul Hamid, H. (2006) Successful Knowledge Sharing in Private Higher Institutions Education: Factors and Barriers . Paper presented at the Knowledge Management International Conference and Exhibition, Kuala Lumpur, Malaysia.

20. Davenport, T.H., & Prusak, L. (1998) Working Knowledge: How Organizations Manage What They Know . Massachusetts, Harvard Business School Press, Boston

21. Dhanalakshmi, R. V., & Gurunathan, K. Balanaga (2014) A Study on “Talent Management as a Strategy to Influence Employee Engagement and Its Affect on The Organizational Outcome”. International Journal of Business and Administration Research Review , V. 2, No. 4, p 183-186.

22. Gholami, Mohamad H., Asli, Mehrdad Nazari, Shirkouhi, Salman Nazari, & Noruzy, Ali (2013) Investigating the Influence of Knowledge Management Practices on Organizational Performance: An Empirical Study. Acta Polytechnica Hungarica , V. 10, No. 2, p 205-216. DOI: http://10.12700/APH.10.02.2013.2.14 .

23. Goffee R., & Jones G. (2007) Leading Clever People. Harvard Business Review, p 72-79.

24. Gold, Andrew H., Malhotra, Arvind, & Segars, Albert H. (2001) Knowledge Management: An Organizational Capabilities Perspective. Journal of Management Information Systems, V. 18, No. 1, p 185-214.

25. Grobler P. A., & Diedericks H. (2009) Talent management: An empirical study of selected South African hotel groups. Southern African Business Review , V. 13, No. 3, p 1–27.

26. Halawi, Leila A., Aronson, Jay E., & McCarthy, Richard V. (2005) Resource-Based View of Knowledge Management for Competitive Advantage. The Electronic Journal of Knowledge Management , V. 3, No. 2, p 75-86.

27. Hejase, Hussin Jose, Hejase, Ale J., Mikdash, Ghinwa, & Bazeih, Zakaa Farhat (2016) Talent Management Challenges: An Exploratory Assessment from Lebanon. International Journal of Business Management and Economic Research , V. 7, No. 1, p 504-520.

28. Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009) The Use of Partial Least Squares Path Modeling in International Marketing. Advances in International Marketing , V. 20, p 277–320.

29. Hor, F.C., Huang, Liang-Chih, Shih, Hsu-Shih, Lee, Yen-Hua, & Lee, Stanley. (2012) Establishing Talent Management for Company’s Succession Planning through Analytic Network Process: Application to an MNC Semiconductor Company in Taiwan. Computers and Mathematics Applications , V. 60, p 528–540.

30. Horváthová Petra. (2011) The Application of Talent Management at Human Resource Management in Organization . 3^rd International Conference on Information and Financial Engineering IPEDR vol.12, IACSIT Press, Singapore.

31. Irtaimeh HJ., Al-Azzam ZF, & Khaddam AA. (2016) Exploring The Impact of Talent Management Strategies and Service Quality on Patients’ Satisfaction. International Journal of Management (IJM) , V. 7, No. 7, p 23-38..

32. Irtaimeh Hani J. (2017) Impact of Strategic Leadership Competencies on Enhancing Core Competencies in organizations: An Applied Study on AlManaseer Group. International Journal of Advanced Research (IJAR) , V. 5. No. 2, p 2528-2538. Doi: http://dx.doi.org/10.21474/IJAR01/3436 .

33. Jain Divya, Sharma Abhineet, & Sharma Vishakha. (2012) Talent Management Strategies in Current Scenario. VSRD International Journal of Business & Management Research , V. 2, No. 9, p 496-501.

34. Jacobucci D., Ostrom A., & Grayson K. (1995) Distinguishing Service Quality and Customer Satisfaction: The Voice of the Customer. Journal of Consumer Psychology , V. 4, No. 3, p 277-303.

35. Jenkinson C., Coulter A., Bruster S., Richards N., & Chandola T. (2002) Patients' Experiences and Satisfaction with Health Care: Results of a Questionnaire Study of Specific Aspects of Care. Quality and Safety in Health Care , V. 11, No. 4, p 335-339.

36. Kehinde James Sunday. (2012) Talent Management: Effect on Organizational Performance. Journal of Management Research , V. 4, No. 2, p 178-186.

37. Kelloway, E. K. (1998) Using LISREL for Structural Equation Modelling. Thousand Oaks, CA: Sage.

38. Kiessling, T. & Harvey, M. (2006) The Human Resource Management Issues During an Acquisition: The Target Firms Top Management Team and Key Managers. International Journal of Human Resource Management . V. 17, No. 7, p 1307-1320.

39. Kiessling, T. S., Richey, R. Glenn, Meng, Juan, & Dabic, Marina (2009) Exploring Knowledge Management to Organizational Performance Outcomes in a Transitional Economy. Journal of World Business , V. 44, p 421- 433.

40. King, Wiliam R. (2009) Knowledge Management and Organizational Learning. Annals of Information Systems , V. 4, p 3-13.

41. Koketso L. P. & Rust, A. A. Braam. (2012) Perceived Challenges to Talent Management in the South African Public Service: An Exploratory Study of the City of Cape Town Municipality”. African Journal of Business Management , V. 6, No. 6, p 2221-2233.

42. Kotler P. & Armstrong, G. (1999) Principles of Marketing. 8th Ed. Prentice-Hall. Englewood Cliffs: New Jersey.

43. Kotler P., Armstrong G., Saunders J., & Wong V. (2002) Principle of Marketing. 3^rd Edition. Pretence Hall: Europe.

44. Kotler, P., & Keller, K. L. (2009) Marketing Management. 13^th Ed. Pearson Education Inc, Upper Saddle.

45. Lawler III, Edward E., & Ulrich Dave. (2008) Talent: Making People Your Competitive Advantage. Johan Wiley and Sons Inc., San Francisco.

46. Lee Haksik, Lee Yongki, & Yoo Dongkeun. (2000) The Determinants of Perceived Service Quality and its Relationship with Satisfaction. Journal of Services Marketing , V. 14, No. 3, p217-231.

47. Lee, Ching Chyi, & Yang, Jie (2000) Knowledge Value Chain. The Journal of Management Development , V. 19, No. 9, p 783-794.

48. Lewis Robert E. & Heckman Robert J. (2006) Talent Management: A Critical Review. Human Resources Management Review , V. 16, p 139 – 154.

49. Liao, Shu-hsien, & Wu, Chi-chuan (2009) The Relationship Among Knowledge Management, Organizational Learning, and Organizational Performance. International Journal of Business and Management , V. 4, No. 4, p 64-76.

50. McDonnell, A., Lamare, R., Gunnigle, P., & Lavelle, J. (2010) Developing Tomorrow's Leaders—Evidence of Global Talent Management in Multinational Enterprises. Journal of world business , V. 45, No. 2, p 150- 160.

51. Miller Crystal. (2014) Ready for My Close-Up: The New Rules of Talent Attraction. Retrieved on 18/10/2016. http://recruitingdaily.com/ready-close-new-rules-talent-attraction/ .

52. Michaels E., Handfield-Jones H. & Axelrod B. (2001) The War for Talent. Boston, MA: Harvard Business School Press.

53. Morsy Mervat Mohammed Elsaied. (2013) The Impact of Talent Management on Employee’s Engagement through Work – Family Balance As a Mediator: A field Study on Zagazyg University Hospitals. Jordan Journal of Business Administration , V. 9, No. 1, p 22-40.

54. Muntean S. N. (2014) Talent Management and its Contributions to the Performance of the Multinational Organizations. Management and Economic , V. 3, No. 75, p 300-306.

55. Nafei Wageeh A. (2015a) Talent Management and Health Service Quality from the Employee Perspective: A Study on Teaching Hospitals in Egypt. American International Journal of Social Science , V. 4, No. 1, p 91-110.

56. Nafei Wageeh A. (2015b) The Effects of Talent Management on Service Quality: A Study on Commercial Banks in Egypt. International Business Research , V. 8, No. 4, p 41-58.

57. Nzewi, Hope Ngozi, Chiekezie, Obianuju Mary, & Ogbeta, Mercy E. (2015) Talent Management and Employee Performance in Selected Commercial Banks in Asaba, Delta State, Nigeria. European Journal of Business and Social Sciences , V. 4, No. 9, p 56-71.

58. Nilsson, Staffan, & Ellström, Per-Erik (2012) Employability and Talent Management: Challenges for HRD Practices. European Journal of Training and Development , V. 36, No. 1, p 26 – 45. Doi: http://dx.doi.org/10.1108/03090591211192610 .

59. Nonaka, I. (1994) A Dynamic Theory of Organizational Knowledge Creation. Organization Science , V. 5, No. 1, p 14.

60. Nonaka, I., Byosiere, P., Borucki, P.C., & Konno, N. (1995) Organizational Knowledge Creation Theory: A First Comprehensive Test. International Business Review , V. 3, No. 4, p 337-351.

61. Nonaka, I., &Takeuchi, H. (1995) The Knowledge-Creating Company. How Japanese Companies Create the Dynamics of Innovation. Oxford University Press, Oxford.

62. Oladapo, Victor (2014) The Impact of Talent Management on Retention. Journal of Business Studies Quarterly , V. 5, No. 3, p 19-36.

63. Ready, Douglas A., Hill, Linda A., & Thomas, Robert J. (2014) Building A Game-Changing Talent Strategy. Harvard Business Review , January-February.

64. Poorhosseinzadeh Mahan & Subramaniam Indra Devi. (2012) Determinants of Successful Talent Management in MNCs in Malaysia. Journal of Basic and Applied Scientific Research , V. 2, No. 12, p 12524–12533.

65. Poorhosseinzadeh Mahan & Subramaniam Indra Devi. (2013) Talent Management Literature Review. Australian Journal of Basic and Applied Sciences , V. 7, No. 6, p 330–338.

66. Rácz, Irma, Bencsik, Andrea, Bognár, Tamás, & Stifter, Viktória (2014) Management of Knowledge by Talented Intellectual Workers. Reproduction of Human Capital - Mutual Linkages and Connections. 24-25 November, 2014. Czech Republic.

67. Robertson A. & Abbey G. (2003) Managing Talented People. Edinburgh, Pearson Education Limited.

68. Reilly P. (2012) International Talent Management. In Reilly P., & William T. Global HR: Challenges Facing the Functions. Gower.

69. Senthilkumar & Kumudha. (2011) Talent Management: The key to Organization Success. Industrial Engineering Letters , V. 1, No. 2, p 26-40.

70. Shaemi A., Allemah S. M., & Bajgerani M. A. (2011) Impact of Talent Management Strategies on Employees’ Emotional Intelligence in Isfahan Municipality. Interdisciplinary Journal of Contemporary Research in Business , V. 3, No. 6, p 229-241.

71. Sharif, Muhammad Tariq, Yaqub,Rana Muhammad Shahid, Khan, Muhammad Asif, & Javed, Fahad (2014) Knowledge Management Maturity and Growth: A Strategic Perspective of Pakistani Universities. Industrial Engineering Letters , V. 4, No. 2, p 55-71.

72. Soltani, Iraj, & Ezat allah (2014) Impact of Knowledge Management and Talent Management on Competitive Advantage (Technical and Professional Organization of Hormozgan Province). International Journal of Basic Sciences & Applied Research , V. 3, No. SP, p 147-152.

73. Suraj, Olunifesi Adekunle & Ajiferuke, Isola (2013) Knowledge Management Practices in the Nigerian Telecommunications Industry. Knowledge and Process Management , V. 20, No. 1, p 30-39.

74. Tansley C., Stewart J., Turner P., & Lynette H. (2006) Change Agenda: Talent Management Understanding the Dimensions . UK: CIPD.

75. Waheed Sajjad, Zaim Abdülhalim, & Zaim Halil. (2012) Talent Management in Four Stages. The USV Annals of Economics and Public Administration , V. 121, No. 15, p 130-137.

76. Wernerfelt, Birger (1984) A Resource-Based View of the Firm. Strategic Management Journal , V. 5, No. 2, p 171- 180

77. Whelan E. & Carcary M. (2011) Integrating Talent and Knowledge Management: Where are the Benefits?. Journal of Knowledge Management , V. 15, No. 4, p 675-687.

78. Wilcox Marc. (2016) Effective Talent Management. Routledge: New York, USA.

79. Vladescu Angela. (2012) The Possibility of Implementing Talent Management in The Public Sector. Management & Marketing , V. 7, No. 2, p 351-362.

80. Zwain, Ammar A. Ali, Teong, Lim Kong, &Othman, Siti Norezam (2012) Knowledge Management Processes and Academic Performance in Iraqi HEIs: An Empirical Investigation. International Journal of Academic Research in Business and Social Sciences , V. 2, No. 6, p 273-293.

81. Yang Y, Lee PKC,& Cheng TCE (2016) Continuous Improvement Competence, Employee Creativity, and New Service Development Performance: A Frontline Employee Perspective. International Journal of Production Economics , V. 171, No. 2, p 275-288.