Local Talent vs. Expat Talent in UAE Private Sector Research Paper

Exclusively available on Available only on IvyPanda® Made by Human No AI

Correlation Analysis

Social Factors

The correlation table (Table 1) indicates that social factors have a strong positive correlation with the provision of job opportunities for Emiratis (r = 0.77) and very weak positive correlation with employment due to the quota requirement (r = 0.13). Moreover, the tables indicate that social factors have a very weak negative correlation with business sense to employ Emiratis (r = -0.03), and very strong negative correlations with Emiratisation as backdoor taxation (r = -0.82) and the experience of internal resistance towards Emiratisation (r = -0.96).

Table 1: Correlation between Social Factors and Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistanceSocial Factors
Business sense1.00
Job opportunities0.391.00
Backdoor taxation0.39-0.521.00
Quotas0.710.510.421.00
Internal resistance-0.23-0.890.68-0.361.00
Social Factors-0.030.77-0.820.13-0.961

Cultural Factors

Table 2 indicates that cultural factors have a moderate positive correlation with the business sense to employ Emiratis (r = 0.50), a very strong positive correlation with the provision of productive job opportunities (r = 0.97), and a strong positive correlation with the employment due to quota requirement (r = 0.70). Forstenlechner and Rutledge (2010) recommend the promotion of Emiratisation using policies that reflect social and cultural aspects of employers and employees. In contrast, cultural factors have a moderate negative correlation with Emiratisation as backdoor taxation and a very strong negative correlation with the experience of internal resistance towards Emiratisation.

Table 2: Correlation between Cultural Factors and Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistanceCultural Factors
Business sense1.00
Job opportunities0.391.00
Backdoor taxation0.39-0.521.00
Quotas0.710.510.421.00
Internal resistance-0.23-0.890.68-0.361.00
Cultural Factors0.500.97-0.310.70-0.831.00

Economic Factors

Correlation table (Table 3) reveals that economic factors have a moderate correlation with the business sense to employ Emiratis (r = 0.63) and strong positive correlations with the provision of productive job opportunities (r = 0.94) and the employment due to quota requirement (r = 0.76). Toledo (2013) asserts that the enactment of regulations that promote the quota system enhances Emiratisation. However, economic factors have a very weak negative correlation with Emiratisation as backdoor taxation (r = -0.22) and a very strong negative correlation with the internal resistance towards Emiratisation (r = -0.81).

Table 3: Correlation between Economic Factors and Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistanceEconomic Factors
Business sense1.00
Job opportunities0.391.00
Backdoor taxation0.39-0.521.00
Quotas0.710.510.421.00
Internal resistance-0.23-0.890.68-0.361.00
Economic Factors0.630.94-0.220.76-0.811.00

Regulatory Factors

From Table 4 below, it is apparent that regulatory factors have a strong positive correlation with the provision of job opportunities (r = 0.90) and moderate correlations with the employment due to quota requirement (0.56) and the business sense of employing Emiratis (r = 0.40). Motherly and Hodgson (2014) note that the quota system is integral in promoting Emiratisation and the creation of productive job opportunities. Moreover, regulatory factors have a moderate negative correlation with Emiratisation as backdoor taxation (r = -0.49) and a strong negative correlation with the internal resistance towards Emiratisation (r = -0.97).

Table 4: Correlation between Regulatory Factors and Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistanceRegulatory Factors
Business sense1.00
Job opportunities0.391.00
Backdoor taxation0.39-0.521.00
Quotas0.710.510.421.00
Internal resistance-0.23-0.890.68-0.361.00
Regulatory Factors0.400.90-0.490.56-0.971.00

Educational Factors

Correlation analysis shows that educational factors have a weak positive correlation with the employment of Emiratis as business sense (r = 0.29), a very strong positive correlation with the provision of productive job opportunities (r = 0.97), and a moderate positive correlation with employment due to quota requirement (r = 0.56). According to Muysken and Nour (2006), education level has a strong relationship with the employment of Emiratis. Additionally, educational factors have a moderate negative correlation with the Emiratisation as backdoor taxation (r = -0.45) and a very strong positive correlation with the internal resistance towards Emiratisation (r = -0.84).

Table 5: Correlation between Educational Factors and Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistanceEducational Factors
Business sense1.00
Job opportunities0.391.00
Backdoor taxation0.39-0.521.00
Quotas0.710.510.421.00
Internal resistance-0.23-0.890.68-0.361.00
Educational Factors0.290.97-0.450.56-0.841.00

Motivational Factors

Table 6 below indicates that motivational factors have a strong positive correlation with the employment of Emiratis as business sense (r = 0.70). Moreover, motivational factors have weak positive correlations with the provision of job opportunities (r = 0.23) and internal resistance towards Emiratisation (r = 0.18), and moderate correlations with Emiratisation as backdoor taxation (r = 0.42) and the employment due to quota requirement (r = 0.36).

Table 6: Correlation between Motivational Factors and Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistanceMotivational Factors
Business sense1.00
Job opportunities0.391.00
Backdoor taxation0.39-0.521.00
Quotas0.710.510.421.00
Internal resistance-0.23-0.890.68-0.361.00
Motivational Factors0.700.230.420.360.181.00

Linear Regression Analysis

The Influence of Social Factors

Employment as Business Sense

The regression analysis reveals that social factors have a very weak influence for they explain 0.1% of the variation in the employment of Emiratis as business sense (R = 0.034, R2 = 0.001).

Table 7: Regression Statistics.

Multiple R0.034
R-Square0.001
Adjusted R Square-0.332
Standard Error73.454
Observations5.000

Provision of Productive Job Opportunities

According to regression analysis, social factors have a strong influence because they explain 59.6% of the variation in the provision of productive job opportunities to Emiratis (R = 0.772, R2 = 0.596).

Table 8: Regression Statistics.

Multiple R0.772
R-Square0.596
Adjusted R Square0.461
Standard Error46.651
Observations5.000

Emiratisation as backdoor taxation

Regression statistics shows that social factors have a very strong influence since they explain 67.8% of the variation in the Emiratisation as backdoor taxation (R = 0.823, R2 = 0.678).

Table 9: Regression Statistics.

Multiple R0.823
R-Square0.678
Adjusted R Square0.570
Standard Error30.258
Observations5.000

Quota Requirement in Employment

The following regression analysis depicts that social factors have a very weak influence because they explain 1.7% of the variation in the employment of Emiratis as quota requirement (R = 0.823, R2 = 0.678).

Table 10: Regression Statistics.

Multiple R0.131
R-Square0.017
Adjusted R Square-0.310
Standard Error47.891
Observations5.000

Internal Resistance towards Emiratisation

Regression table shows that social factors have a very strong influence for they explain 92.3% of the variation in the internal resistance towards Emiratisation (R = 0.131, R2 = 0.017).

Table 11: Regression Statistics.

Multiple R0.961
R-Square0.923
Adjusted R Square0.898
Standard Error27.336
Observations5.000

The Influence of Cultural Factors

Employment as Business Sense

From the regression table, it is apparent that cultural factors have a moderate influence because they explain 24.6% of the variation in the employment as a business sense (R = 0.496, R2 = 0.246).

Table 12: Regression Statistics.

Multiple R0.496
R-Square0.246
Adjusted R Square-0.006
Standard Error63.835
Observations5.000

Provision of Productive Job Opportunities

The regression table indicates that cultural factors have a strong influence for they explain 93.6% of the variability in the provision of productive job opportunities for Emiratis (R = 0.968, R2 = 0.936).

Table 13: Regression Statistics.

Multiple R0.968
R-Square0.936
Adjusted R Square0.915
Standard Error18.536
Observations5.000

Emiratisation as Backdoor Taxation

The regression analysis shows that cultural factors have a moderate effect because they explain 9.6% of the variation in the Emiratisation as backdoor taxation (R = 0.309, R2 = 0.096).

Table 14: Regression Statistics.

Multiple R0.309
R-Square0.096
Adjusted R Square-0.206
Standard Error50.669
Observations5.000

Quota Requirement in Employment

The regression analysis shows that cultural factors have a strong effect for they account for 49.6% of the variation in the employment as quota requirement (R = 0.704, R2 = 0.496).

Table 15: Regression Statistics.

Multiple R0.704
R-Square0.496
Adjusted R Square0.328
Standard Error34.295
Observations5.000

Internal Resistance towards Emiratisation

According to the regression table, cultural factors have a strong influence since they account for 69.5% of the variation in the internal resistance to Emiratisation (R = 0.834, R2 = 0.695).

Table 16: Regression Statistics.

Multiple R0.834
R-Square0.695
Adjusted R Square0.594
Standard Error54.433
Observations5.000

The Influence of Economic Factors

Employment as Business Sense

The regression table reveals that economic factors have a moderate effect because they account for 39.2% of the variability in the employment of Emiratis as a business sense (R = 0.626, R2 = 0.392).

Table 17: Regression Statistics.

Multiple R0.626
R-Square0.392
Adjusted R Square0.189
Standard Error57.329
Observations5.000

Provision of Productive Job Opportunities

According to the regression table, economic factors accounts for 87.8% of the variability in the provision of job opportunities, and thus, they have a strong influence labor market (R = 0.937, R2 = 0.695).

Table 18: Regression Statistics.

Multiple R0.937
R-Square0.878
Adjusted R Square0.837
Standard Error25.623
Observations5.000

Emiratisation as backdoor taxation

From the regression table, it is evident that economic factors have a weak influence on the dependent variable accounts for they explain 4.7% of the variation in the Emiratisation as backdoor taxation (R = 0.217, R2 = 0.047).

Table 19: Regression Statistics.

Multiple R0.217
R-Square0.047
Adjusted R Square-0.270
Standard Error52.007
Observations5.000

Quota Requirement in Employment

The regression analysis reveals that economic factors have a strong influence for they explain 58.5% of the variation in the employment of Emiratis due to quota requirement (R = 0.765, R2 = 0.585).

Table 20: Regression Statistics.

Multiple R0.765
R-Square0.585
Adjusted R Square0.447
Standard Error31.123
Observations5.000

Internal Resistance towards Emiratisation

Economic factors, according to the regression analysis, have a very strong effect since they explain 65.9% of the variation in the internal resistance towards Emiratisation (R = 0.812, R2 = 0.659).

Table 21: Regression Statistics.

Multiple R0.812
R-Square0.659
Adjusted R Square0.546
Standard Error57.551
Observations5.000

The Influence of Regulatory Factors

Employment as Business Sense

Regulatory factors, according to the regression analysis, have a moderate effect for they account for 16.2% of the variability in the employment as business sense (R = 0.402, R2 = 0.162).

Table 22: Regression Statistics.

Multiple R0.402
R-Square0.162
Adjusted R Square-0.118
Standard Error67.299
Observations5.000

Provision of Productive Job Opportunities

The regression analysis reveals that regulatory factors have a strong influence as they account for 80.3% of the variation in the provision of productive job opportunities (R = 0.896, R2 = 0.803).

Table 23: Regression Statistics.

Multiple R0.896
R-Square0.803
Adjusted R Square0.737
Standard Error32.564
Observations5.000

Emiratisation as backdoor taxation

The regression analysis indicates that regulatory factors have a moderate effect since they explain 24.2% of the variation in the Emiratisation as backdoor taxation (R = 0.492, R2 = 0.242).

Table 24: Regression Statistics.

Multiple R0.492
R-Square0.242
Adjusted R Square-0.011
Standard Error46.402
Observations5.000

Quota Requirement in Employment

According to regression analysis, regulatory factors have a moderate influence for they explain 31.6% of the variation in the employment as quota requirement (R = 0.562, R2 = 0.316).

Table 25: Regression Statistics.

Multiple R0.562
R-Square0.316
Adjusted R Square0.088
Standard Error39.952
Observations5

Internal Resistance towards Emiratisation

From the regression table, it is apparent that regulatory factors have a strong influence because they explain 94.5% of the variation in the internal resistance towards Emiratisation (R = 0.972, R2 = 0.945).

Table 26: Regression Statistics.

Multiple R0.972
R-Square0.945
Adjusted R Square0.927
Standard Error23.100
Observations5.000

The Influence of Educational Factors

Employment as Business Sense

Regression statistics indicate that educational factors have weak influence for they explain 8.3% of the variation in the employment of Emiratis as business sense (R = 0.287, R2 = 0.083).

Table 27: Regression Statistics.

Multiple R0.287
R-Square0.083
Adjusted R Square-0.223
Standard Error70.399
Observations5.000

Provision of Productive Job Opportunities

According to regression analysis, educational factors have a very strong influence because they account for 94.6% of the variation in the provision of job opportunities to Emiratis (R = 0.973, R2 = 0.946). Pech (2009) recommends the use of education in influencing Emiratisation and transforming labor sector in the United Arab Emirates. ,

Table 28: Regression Statistics.

Multiple R0.973
R-Square0.946
Adjusted R Square0.928
Standard Error17.080
Observations5.000

Emiratisation as backdoor taxation

From the table, regression analysis shows that educational factors have a moderate influence for they explain 20.6% of the variation in the Emiratisation as backdoor taxation (R = 0.454, R2 = 0.206).

Table 29: Regression Statistics.

Multiple R0.454
R-Square0.206
Adjusted R Square-0.059
Standard Error47.488
Observations5.000

Quota Requirement in Employment

According to the regression table, educational factors have a moderate influence because they explain 31.5% of the variation in the quota requirement in employment (R = 0.561, R2 = 0.315).

Table 30: Regression Statistics.

Multiple R0.561
R-Square0.315
Adjusted R Square0.087
Standard Error39.986
Observations5.000

Internal Resistance towards Emiratisation

The regression analysis indicates that educational factors have a strong influence since they account for 70.3% of the variation in the internal resistance towards Emiratisation (R = 0.839, R2 = 0.703).

Table 31: Regression Statistics.

Multiple R0.839
R-Square0.703
Adjusted R Square0.604
Standard Error53.708
Observations5.000

The Influence of Motivational Factors

Employment as Business Sense

The regression analysis shows that motivational factors have strong influence since they explain 48.3% of the variation in employment as business sense (R = 0.695, R2 = 0.483).

Table 32: Regression Statistics.

Multiple R0.695
R-Square0.483
Adjusted R Square0.311
Standard Error52.831
Observations5.000

Provision of Productive Job Opportunities

According to the regression analysis, motivational factors have weak influence because it accounts for 5.1% of the variation in the provision of productive job opportunities (R = 0.227, R2 = 0.051).

Table 33: Regression Statistics.

Multiple R0.227
R-Square0.051
Adjusted R Square-0.265
Standard Error71.443
Observations5.000

Emiratisation as backdoor taxation

From the regression analysis, motivational factors explain 17.5% of the variability in Emiratisation as backdoor taxation, and hence, they have a moderate influence on Emiratisation (R = 0.418, R2 = 0.175).

Table 34: Regression Statistics.

Multiple R0.418
R-Square0.175
Adjusted R Square-0.100
Standard Error48.393
Observations5.000

Quota Requirement in Employment

The R and R-square coefficients indicate that motivational factors account for 12.9% of the variability in employment owing to the quota requirement (R = 0.359, R2 = 0.129).

Table 35: Regression Statistics.

Multiple R0.359
R-Square0.129
Adjusted R Square-0.161
Standard Error45.086
Observations5.000

Internal Resistance towards Emiratisation

The coefficients of regression reveal that motivational factors have very weak influence since they account for 3.4% of the variation in internal resistance towards Emiratisation (R = 0.184, R2 = 0.034).

Table 36: Regression Statistics.

Multiple R0.184
R Square0.034
Adjusted R Square-0.288
Standard Error96.918
Observations5.000

The Most Significant Factors Influencing the Companies’ Willingness to Recruit National

Cultural Factors

The correlation and regression analysis reveals that cultural factors are the most significant factors influencing the companies’ willingness to recruit nationals. The demystification of cultural stereotypes, promotion of local labor and empowerment of women has enhanced Emiratisation in the United Arab Emirates (Gallant & Pounder 2008). The analyses reveal that cultural factors are statistically significant positive predictors of the provision of job opportunities to Emiratis (r = 0.97, R = 0.968, R2 = 0.93.6, p = 0.007). The coefficients show that a unit increase in cultural factors causes 1.198 units to increase in the provision of job opportunities to Emiratis.

Table 39: ANOVA.

dfSSMSFSignificance F
Regression115110.41715110.41743.9770.007
Residual31030.783343.594
Total416141.200

Table 40: Regression Coefficients.

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept-19.30019.452-0.9920.394-81.20742.606-81.20742.606
Cultural Factors1.1980.1816.6320.0070.6231.7730.6231.773

Economic Factors

According to the correlation and regression analyses, economic factors the most significant factors influencing the companies’ willingness to recruit nationals. Emiratisation has become a human resource strategy of transforming the labor system and increasing the productivity of Emiratis (Harry 2007; Rees, Mamman, & Bin-Braik 2007). As the most significant factors, economic factors are statistically significant positive predictors of the provision of productive job opportunities to Emiratis (r = 0.94, R = 0.937, R2 = 0.878, p = 0.019). The regression equation predicts that a unit increase in social factors results in 1.229 units increase in the provision of productive job opportunities.

Table 41: ANOVA.

dfSSMSFSignificance F
Regression114171.53414171.53421.5850.019
Residual31969.666656.555
Total416141.200

Table 42: Regression Coefficients.

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept-22.29928.198-0.7910.487-112.03767.438-112.03767.438
Economic Factors1.2290.2654.6460.0190.3872.0710.3872.071

Regulatory Factors

Regulatory factors are the most significant factors influencing the companies’ willingness to recruit nationals. Forstenlechner (2008) states that the enactment of legislation that supports Emiratisation has increased the employment rate of Emiratis in the United Arab Emirates. Regulatory factors are statistically significant positive predictors of the provision of productive job opportunities to Emiratis (r = 0.90, R = 0.896, R2 = 0.803, p = 0.040). The regression coefficients show that a unit increase in regulatory factors causes an increase in the provision of productive jobs to Emiratis by 1.242.

Table 43: ANOVA.

dfSSMSFSignificance F
Regression112959.95412959.95412.2220.040
Residual33181.2461060.415
Total416141.200

Table 44: Regression Coefficients.

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept-23.53737.534-0.6270.575-142.98695.913-142.98695.913
Regulatory Factors1.2420.3553.4960.0400.1112.3720.1112.372

Educational Factors

The correlation and regression analyses show that educational factors are the most significant factors influencing the companies’ willingness to recruit nationals. Fundamentally, educational factors are statistically significant predictors of the provision of productive job opportunities to Emiratis (r = 0.97, R = 0.973, R2 = 0.946, p = 0.005). These findings are in line with the findings of some studies, which affirm that which show that educational factors have a marked influence on Emiratisation because they determine the level of skills among Emiratis (Al-Ali 2008; Forstenlechner et al. 2012; Muysken & Nour 2006). The regression coefficients predict that a unit increase in educational factors causes an increase in the provision of productive job opportunities to Emiratis by 1.199.

Table 47: ANOVA.

dfSSMSFSignificance F
Regression115266.05515266.05552.3320.005
Residual3875.145291.715
Total416141.200

Table 48: Regression Coefficients.

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept-19.43017.865-1.0880.356-76.28437.425-76.28437.425
Educational Factors1.1990.1667.2340.0050.6721.7270.6721.727

Motivational Factors

The correlation and regression analysis indicate that motivational factors are neither statistically significant positive or negative predictors of the dependent variables (p > 0.05). From the correlation and regression analysis, motivational factors have a strong relationship with the employment of Emiratis as business sense and explain 48.3% of its variation, but they are not statistically significant predictors (r = 70, R = 0.695, R2 = 0.483, p = 0.193). Studies show that extrinsic factors such as high remuneration, promotion, and rewards motivate Emiratis and thus promote Emiratisation (Abdulla, Djebarni, & Mellahi 2011; Lim, 2014; Lim 2013).

The Most Significant Factors Influencing the Companies’ Regret to Recruit Nationals.

Social Factors

From the correlation and regression analyses, social factors are the most significant factors influencing the companies’ regret to recruit nationals because they are statistically significant negative predictors of Emiratisation (p < 0.05). According to Sadi and Henderson (2010), social factors such as negative attitudes, high expectations, and low-level job opportunities have a negative effect on Emiratisation. Specifically, correlation and regression analyses indicate that social factors are statistically significant negative predictors of the challenge of the internal resistance towards Emiratisation (r = -0.96, R = 0.961, R2 = 0.923, p = 0.009). The regression equation shows that a unit increase in social factors results in a decline in the internal resistance towards Emiratisation by 1.255.

Table 37: AVONA.

dfSSMSFSignificance F
Regression126927.39726927.3970336.0340.009
Residual32241.802747.268
Total429169.2

Table 38: Coefficients of Internal Resistance.

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept219.61923.7489.2470.003144.041295.197144.041295.197
Social Factors-1.2550.209-6.0030.009-1.920-0.589-1.920-0.589

Regulatory Factors

Regulatory factors are the most significant factors influencing the companies’ regret to recruit nationals. Regulations and policies compel companies to employ Emiratis, which is against their willingness to recruit them (Mellahi 2007; Noland & Pack 2008; Randeree, 2009). Essentially, economic factors also are statistically significant negative predictors of the internal resistance towards Emiratisation (r = 0.97, R = 0.972, R2 = 945 p = 0.006). The regression coefficients show that a unit increase in regulatory factors causes a decline in the internal resistance towards Emiratisation by 1.811.

Table 45: ANOVA.

dfSSMSFSignificance F
Regression127568.39227568.39251.6650.006
Residual31600.808533.603
Total429169.200

Table 46: Regression Coefficients.

CoefficientsStandard Errort StatP-valueLower 95%Upper 95%Lower 95.0%Upper 95.0%
Intercept273.78526.62510.2830.002189.051358.518189.051358.518
Regulatory Factors-1.8110.252-7.1880.006-2.613-1.009-2.613-1.009

Mean, Median, Standard Deviation for the ‘Dependant Variables’.

According to the descriptive statistics, the dependent variables of the employment of Emiratis as business sense having a median of 91 (M = 97.74, SD = 63) and provision of job opportunities having a median of 102 (M = 97.4, SD = 63.52) have a moderate variability. Comparatively, the dependent variable of Emiratisation as a backdoor taxation having a median of 109 (M = 97.4, SD = 46.14) and the employment to meet quota requirement having a median of 81 (M = 97.4, SD = 41.84) have lower variability. The dependent variables of Emiratisation facing internal resistance have a median of 101 (M = 97.4, SD = 85.39), which means that it has the highest variability.

Table 49: Descriptive Statistics of Dependent Variables.

Business senseJob opportunitiesBackdoor taxationQuotasInternal resistance
Mean97.497.497.497.497.4
Median9110210981101
Standard Deviation63.6563.5246.1441.8485.39
Sum487487487487487
Count55555

Mean, Median, Standard Deviation for the ‘Explanatory Variables’.

As per the descriptive statistics of explanatory variables, social factors have the highest variability (M = 97.4, SD = 65.39, Median = 71.8) while motivational factors have the lowest variability (M = 97.4, SD = 21.72, Median = 106.4). Cultural factors (M = 97.4, SD = 51.29, Median 104.20), economic factors (M = 97.4, SD = 45.54, Median = 114.25), and educational factors (M = 97.4, SD = 51.51, Mode = 105.25) have approximately the same variability in distribution.

Table 50: Descriptive Statistics for Explanatory Variables.

Social FactorsCultural FactorsEconomic FactorsRegulatory FactorsEducational FactorsMotivational Factors
Mean97.497.497.497.497.497.4
Median71.8104.2104.25114.25105.25106.4
Standard Deviation65.3951.2948.4345.8451.5121.72
Sum487487487487487487
Count555555

References

Abdulla, J, Djebarni, R, & Mellahi, K 2011, ‘Determinants of job satisfaction in the UAE: A case study of the Dubai police’, Personnel Review, vol. 40, no. 1, pp. 126-146.

Al-Ali, J 2008, ‘Emiratisation: drawing UAE nationals into their surging economy’, International Journal of Sociology and Social Policy, vol. 28, no. 9/10, pp. 365-379.

Al-Waqfi, M & Forstenlechner, I 2010, ‘Stereotyping of Citizens in an Expatriate Dominated Labor Market: Implications for Workforce Localization Policy,’ Employee Relations, vol. 32, no. 4, pp. 364-381.

Forstenlechner, I & Rutledge, E 2010, ‘Unemployment in the Gulf: Time to update the “Social Contract’, Middle East Policy Council, vol. 17, no. 2, pp. 38-51.

Forstenlechner, I 2008, ‘Workforce nationalization in the UAE: Image versus integration’, Education, Business and Society: Contemporary Middle East Issues, vol. 1, no. 2, pp. 82-91.

Forstenlechner, I, Madi, M, Selim, H, & Rutledge, E 2012, ‘Emiratisation: determining the factors that influence the recruitment decisions of employers in the UAE’, The International Journal of Human Resource Management, vol. 23, no. 2, pp. 406-421.

Gallant, M & Pounder, J 2008, ‘The employment of female nationals in the United Arab Emirates (UAE): An analysis of opportunities and barriers’, Education, Business and Society: Contemporary Middle East Issues, vol. 1, no. 1, pp. 26-33.

Harry, W 2007, ‘Employment creation and localization: the crucial human resource issue for the GCC’, International Journal of Human Resource Management, vol.18, no.1, pp. 132-146

Lim, H 2014, ‘The Emergent Gen Y Workforce: Implications for Labor Nationalization Policies in the UAE and Saudi Arabia’, Journal of Business Theory and Practice, vol. 2, no. 2, pp. 267-285.

Lim, L 2013, ‘Work Motivators of Saudi and Emirati Generation Y: A Pilot Study’, International Journal of Economy, Management and Social Sciences, vol. 2, no. 5, pp. 185-194.

Lindsay, C 2005, ‘McJobs, Good jobs and Skills: Job-seekers’ Attitudes to Low-Skilled Service Work,’ Human Resource Management, vol. 15, no. 2, pp. 50-65.

Mellahi, K 2007, ‘The Effect of Regulations on HRM: Private Sector Firms in Saudi Arabia,’ International Journal of Human Resource Management, vol. 18, no. 1, pp. 85-99.

Motherly, L & Hodgson, S. 2014, ‘Implementing Employment Quotas to Develop Human Resource Capital: A Comparison of Oman and the UAE’, International Journal of Liberal Arts and Social Science, vol. 2, no. 7, 75-90.

Muysken, J & Nour, S 2006, ‘Deficiencies in Education and Poor Prospects for Economic Growth in the Gulf Countries: The Case of the UAE,’ The Journal of Development Studies, vol. 42, no. 6, pp. 957-960.

Noland, M & Pack, H 2008, ‘Arab Economies at Tipping Point,’ Middle East Policy, vol. 15, no. 1, pp. 60-69.

Pech, R 2009, ‘Emiratisation: Aligning Education with Future Needs in the United Arab Emirates,’ Education, Business, and Society: Contemporary Middle Eastern Issues, vol. 2, no. 1, pp. 57-65.

Randeree, K 2009, ‘Strategy, Policy, and Practice in the Nationalization of Human Capital: Project Emiratisation’, Research and Practice in Human Resource Management, vol. 17, no. 1, pp. 71-91.

Rees, C, Mamman, A, & Bin-Braik, A 2007, ‘Emiratization as a strategic HRM change initiative: Case study evidence from a UAE petroleum company’, International Journal of Human Resource Management, vol. 18, no.1, 33-53.

Sadi, M & Henderson, J 2010, ‘Towards job localization in Saudi Arabia: Drivers and barriers within the services industry’, Journal of Immigrant & Refugee Studies, vol. 8, no.1, pp. 121-134.

Toledo, H 2013, ‘The political economy of Emiratisation in the UAE’, Journal of Economic Studies, vol. 40, no.1, pp. 39-53.

More related papers Related Essay Examples
Cite This paper
You're welcome to use this sample in your assignment. Be sure to cite it correctly

Reference

IvyPanda. (2022, May 27). Local Talent vs. Expat Talent in UAE Private Sector. https://ivypanda.com/essays/local-talent-vs-expat-talent-in-uae-private-sector/

Work Cited

"Local Talent vs. Expat Talent in UAE Private Sector." IvyPanda, 27 May 2022, ivypanda.com/essays/local-talent-vs-expat-talent-in-uae-private-sector/.

References

IvyPanda. (2022) 'Local Talent vs. Expat Talent in UAE Private Sector'. 27 May.

References

IvyPanda. 2022. "Local Talent vs. Expat Talent in UAE Private Sector." May 27, 2022. https://ivypanda.com/essays/local-talent-vs-expat-talent-in-uae-private-sector/.

1. IvyPanda. "Local Talent vs. Expat Talent in UAE Private Sector." May 27, 2022. https://ivypanda.com/essays/local-talent-vs-expat-talent-in-uae-private-sector/.


Bibliography


IvyPanda. "Local Talent vs. Expat Talent in UAE Private Sector." May 27, 2022. https://ivypanda.com/essays/local-talent-vs-expat-talent-in-uae-private-sector/.

If, for any reason, you believe that this content should not be published on our website, please request its removal.
Updated:
This academic paper example has been carefully picked, checked and refined by our editorial team.
No AI was involved: only quilified experts contributed.
You are free to use it for the following purposes:
  • To find inspiration for your paper and overcome writer’s block
  • As a source of information (ensure proper referencing)
  • As a template for you assignment
Privacy Settings

IvyPanda uses cookies and similar technologies to enhance your experience, enabling functionalities such as:

  • Basic site functions
  • Ensuring secure, safe transactions
  • Secure account login
  • Remembering account, browser, and regional preferences
  • Remembering privacy and security settings
  • Analyzing site traffic and usage
  • Personalized search, content, and recommendations
  • Displaying relevant, targeted ads on and off IvyPanda

Please refer to IvyPanda's Cookies Policy and Privacy Policy for detailed information.

Required Cookies & Technologies
Always active

Certain technologies we use are essential for critical functions such as security and site integrity, account authentication, security and privacy preferences, internal site usage and maintenance data, and ensuring the site operates correctly for browsing and transactions.

Site Customization

Cookies and similar technologies are used to enhance your experience by:

  • Remembering general and regional preferences
  • Personalizing content, search, recommendations, and offers

Some functions, such as personalized recommendations, account preferences, or localization, may not work correctly without these technologies. For more details, please refer to IvyPanda's Cookies Policy.

Personalized Advertising

To enable personalized advertising (such as interest-based ads), we may share your data with our marketing and advertising partners using cookies and other technologies. These partners may have their own information collected about you. Turning off the personalized advertising setting won't stop you from seeing IvyPanda ads, but it may make the ads you see less relevant or more repetitive.

Personalized advertising may be considered a "sale" or "sharing" of the information under California and other state privacy laws, and you may have the right to opt out. Turning off personalized advertising allows you to exercise your right to opt out. Learn more in IvyPanda's Cookies Policy and Privacy Policy.

1 / 1