## 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 a very weak positive correlation with employment due to quota requirements (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*

### 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 requirements (r = 0.70). Forstenlechner and Rutledge (2010) recommend the promotion of Emiratisation using policies that reflect the 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*

### Economic Factors

The 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 employment due to quota requirements (r = 0.76). Toledo (2013) asserts that enactment of regulations that promote a quota system enhance 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*

### 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 employment due to quota requirements (0.56) and the business sense of employing Emiratis (r = 0.40). Motherly and Hodgson (2014) perceive 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*

### 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 requirements (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 Emiratisation as backdoor taxation (r = -0.45) and a very strong positive correlation with internal resistance towards Emiratisation (r = -0.84).

*Table 5: Correlation between Educational Factors and Dependent Variables*

### 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 employment due to quota requirements (r = 0.36).

*Table 6: Correlation between Motivational Factors and Dependent Variables*

## Linear Regression Analysis

### The Influence of Social Factors

#### Employment as Business Sense

The regression analysis reveals that social factors have a very weak influence, as they explain 0.1% of the variation in the employment of Emiratis as business sense (R = 0.034, R^{2} = 0.001).

*Table 7: Regression Statistics*

#### Provision of Productive Job Opportunities

According to the regression analysis, social factors have a strong influence because they explain 59.6% of the variation in the provision of productive job opportunities for Emiratis (R = 0.772, R^{2} = 0.596).

*Table 8: Regression Statistics*

#### Emiratisation as Backdoor Taxation

The regression statistics show that social factors have a very strong influence, as they explain 67.8% of the variation in Emiratisation as backdoor taxation (R = 0.823, R^{2} = 0.678).

*Table 9: Regression Statistics*

#### Quota Requirements in Employment

The following regression analysis indicates that social factors have a very weak influence, as they explain only 1.7% of the variation in the employment of Emiratis as a quota requirement (R = 0.823, R^{2} = 0.678).

*Table 10: Regression Statistics*

#### Internal Resistance towards Emiratisation

The regression table shows that social factors have a very strong influence, as they explain 92.3% of the variation in internal resistance towards Emiratisation (R = 0.131, R^{2} = 0.017).

*Table 11: Regression Statistics*

### The Influence of Cultural Factors

#### Employment as Business Sense

From the regression table, it is apparent that cultural factors have a moderate influence, since they explain 24.6% of the variation in employment as business sense (R = 0.496, R^{2} = 0.246).

*Table 12: Regression Statistics*

#### Provision of Productive Job Opportunities

The regression table indicates that cultural factors have a strong influence, since they explain 93.6% of the variability in the provision of productive job opportunities for Emiratis (R = 0.968, R^{2} = 0.936).

*Table 13: Regression Statistics*

#### Emiratisation as Backdoor Taxation

The regression analysis shows that cultural factors have a moderate effect, since they explain 9.6% of the variation in Emiratisation as backdoor taxation (R = 0.309, R^{2} = 0.096).

*Table 14: Regression Statistics*

#### Quota Requirements in Employment

The regression analysis shows that cultural factors have a strong effect, as they account for 49.6% of the variation in the employment as a quota requirement (R = 0.704, R^{2} = 0.496).

*Table 15: Regression Statistics*

#### Internal Resistance towards Emiratisation

The regression table shows that cultural factors have a strong influence, as they account for 69.5% of the variation in internal resistance to Emiratisation (R = 0.834, R^{2} = 0.695).

*Table 16: Regression Statistics*

### The Influence of Economic Factors

#### Employment as Business Sens**e**

The regression table reveals that economic factors have a moderate effect, as they account for 39.2% of the variability in employment of Emiratis as a business sense (R = 0.626, R^{2} = 0.392).

*Table 17: Regression Statistics*

#### Provision of Productive Job Opportuniti**es**

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 on the labour market (R = 0.937, R^{2} = 0.695).

*Table 18: Regression Statistics*

#### Emiratisation as Backdoor Taxation

From the regression table, it is evident that economic factors have a weak influence on the dependent variable accounts, as they explain 4.7% of the variation in Emiratisation as backdoor taxation (R = 0.217, R^{2} = 0.047).

*Table 19: Regression Statistics*

#### Quota Requirements in Employment

The regression analysis reveals that economic factors have a strong influence, since they explain 58.5% of the variation in the employment of Emiratis due to quota requirements (R = 0.765, R^{2} = 0.585).

*Table 20: Regression Statistics*

#### Internal Resistance towards Emiratisation

Economic factors have a very strong effect, since they explain 65.9% of the variation in the internal resistance towards Emiratisation (R = 0.812, R^{2} = 0.659).

*Table 21: Regression Statistics*

### The Influence of Regulatory Factors

#### Employment as Business Sense

According to the regression analysis, regulatory factors have a moderate effect since they account for 16.2% of the variability in the employment as business sense (R = 0.402, R^{2} = 0.162).

*Table 22: Regression Statistics*

#### 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, R^{2} = 0.803).

*Table 23: Regression Statistics*

#### Emiratisation as Backdoor Taxation

The regression analysis indicates that regulatory factors have a moderate effect, since they explain 24.2% of the variation in Emiratisation as backdoor taxation (R = 0.492, R^{2} = 0.242).

*Table 24: Regression Statistics*

#### Quota Requirements in Employment

According to the regression analysis, regulatory factors have a moderate influence, since they explain 31.6% of the variation in the employment as a quota requirement (R = 0.562, R^{2} = 0.316).

*Table 25: Regression Statistics*

#### Internal Resistance towards Emiratisation

From the regression table, it is apparent that regulatory factors have a strong influence, since they explain 94.5% of the variation in the internal resistance towards Emiratisation (R = 0.972, R^{2} = 0.945).

*Table 26: Regression Statistics*

### The Influence of Educational Factors

#### Employment as Business Sense

The regression statistics indicate that educational factors have a weak influence, since they explain 8.3% of the variation in the employment of Emiratis as business sense (R = 0.287, R^{2} = 0.083).

*Table 27: Regression Statistics*

#### Provision of Productive Job Opportunities

According to the regression analysis, educational factors have a very strong influence, as they account for 94.6% of the variation in the provision of job opportunities to Emiratis (R = 0.973, R^{2} = 0.946). Pech (2009) recommends the use of education in influencing Emiratisation and transforming the labour sector in the United Arab Emirates.

*Table 28: Regression Statistics*

#### Emiratisation as Backdoor Taxation

The regression analysis presented in Table 29 shows that educational factors have a moderate influence, as they explain 20.6% of the variation in Emiratisation as backdoor taxation (R = 0.454, R^{2} = 0.206).

*Table 29: Regression Statistics*

#### Quota Requirements in Employment

According to the regression analysis in Table 30, educational factors have a moderate influence, as they explain 31.5% of the variation in the quota requirement in employment (R = 0.561, R^{2} = 0.315).

*Table 30: Regression Statistics*

#### 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, R^{2} = 0.703).

*Table 31: Regression Statistics*

### The Influence of Motivational Factors

#### Employment as Business Sense

The regression analysis shows that motivational factors have a strong influence, since they explain 48.3% of the variation in employment as business sense (R = 0.695, R^{2} = 0.483).

*Table 32: Regression Statistics*

#### Provision of Productive Job Opportunities

According to the regression analysis, motivational factors have a weak influence because they account for 5.1% of the variation in the provision of productive job opportunities (R = 0.227, R^{2} = 0.051).

*Table 33: Regression Statistics*

#### 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, R^{2} = 0.175).

*Table 34: Regression Statistics*

#### Quota Requirements 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, R^{2} = 0.129).

*Table 35: Regression Statistics*

#### Internal Resistance towards Emiratisation

The coefficients of regression reveal that motivational factors have a weak influence, since they account for 3.4% of the variation in internal resistance towards Emiratisation (R = 0.184, R^{2} = 0.034).

*Table 36: Regression Statistics*

## The Most Significant Factors Influencing Companies’ Willingness to Recruit Nationals

### Motivational Factors

The correlation and regression analyses indicate that motivational factors are the most influential and statistically significant positive predictors of the willingness of companies to recruit Emirati nationals (p = 0.023). Moreover, motivational factors have a very strong relationship with the willingness to recruit Emiratis (R = 0.927) and explain 86% of its variation (R^{2} = 0.860). 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). An increase in the motivational factors by a unit causes the willingness to increase by 0.685.

*Table 37: The Influence of Motivational Factors*

### Social Factors

Social factors comprise the second leading factors that influence the willingness of companies to recruit Emiratis. Regression analysis demonstrates that social factors have a moderate relationship with the willingness of companies to recruit nationals (R = 0.439). Prediction shows that the social factors accounts for 19.2% of the variation in the willingness to recruit Emiratis. Regression coefficient (β = -0.108) shows that when social factors increase by a unit, the willingness to recruit Emiratis declines by 0.108 units.

*Table 38: The Influence of Social Factors*

### Economic Factors

According to the correlation and regression analyses, economic factors are the third most significant factors that influent the willingness of companies to recruit nationals. Emiratisation has become a human resource strategy for transforming the labour system and increasing the productivity of Emiratis (Harry 2007; Rees, Mamman, & Bin-Braik 2007). Economic factors are statistically insignificant positive predictors because they explain 14% of the willingness to recruit Emiratis (R = 0.374, R^{2} = 0.140, p = 0.019). The regression coefficient (β = 0.155) predicts that a unit increase in social factors results in a 0.155 unit increase in the willingness to recruit Emiratis.

*Table 39: The Influence of Economic Factors*

### Cultural Factors

The fourth most significant factors influencing companies’ willingness to recruit nationals are cultural factors. The demystification of cultural stereotypes, promotion of local labour and empowerment of women has enhanced Emiratisation in the United Arab Emirates (Al-Waqfi & Forstenlechner 2010; Gallant & Pounder 2008). The analyses reveal that cultural factors are statistically insignificant positive predictors of the recruitment of Emiratis (R = 0.272, p = 0.658). These factors account for 7.4% of the variation in the willingness to recruit Emiratis (R^{2} = 0.074). Additionally, the coefficient (β = 0.085) show that a unit increase in cultural factors produces a 0.085 unit increase in the willingness to recruit Emiratis.

*Table 40: The Influence of Cultural Factors*

### Educational Factors

Educational factors comprise the fifth most significant factors that influence the willingness of Emirati companies to recruit nationals. Educational factors have a very weak positive relationship with the willingness to employ Emiratis (r = 0.105). Moreover, these factors explain 1.1% of the variation in the employment of Emiratis (R^{2} = 0.011, p = 0.866). These findings are consistent with the findings of studies that 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 coefficient (β = 0.041) predicts that a unit increase in educational factors causes an increase in the provision of productive job opportunities to Emiratis by 0.041 units.

*Table 41: The Influence of Educational Factors*

### Regulatory Factors

Regulatory factors are the least significant factors that influence the willingness of companies to recruit nationals. These factors are the most influential because they account for 0.00% of the variation in the recruitment of Emiratis (R = 0.006, R^{2} = 0.000, p = 0.992). The regression coefficient (β = -0.003) illustrates that a unit increase in regulatory factors causes a decrease in the employment of Emiratis 0.003 units. This finding is not consistent with the report of Forstenlechner (2008) that the enactment of legislation that supports Emiratisation has increased the employment rate of Emiratis in the United Arab Emirates.

*Table 42: The Influence of Regulatory Factors*

## The Most Significant Factors Influencing Companies’ Regret after Recruiting Nationals

### Motivational Factors

Motivational factors are the most influential factors that make companies regret employing Emiratis. These factors have a moderate relationship with the regret to recruit Emiratis (R = 0.463). Motivational factors explain 21.5% of the variation in the regret to employing Emiratis (R = 0.215). Normally, a unit increase in the motivational issues makes regret to employing Emiratis to increase by 0.316 units.

*Table 43: The Influence of Motivational Factors*

### Economic Factors

The analysis of economic factors illustrates that they are the second most factors that influence companies to regret employing nationals. Economic factors have a weak relationship with the regret to recruit Emiratis because they account 8.8% of the variation (R^{2 }= 0.088). Although the regression model is not significant, the coefficient shows that when economic factors increase by a unit, the regret to recruit increases by 0.113 units.

*Table 44: The Influence of Economic Factors*

### Social Factors

From the correlation and regression analyses, social factors are the third most significant factors influencing companies’ regret after recruiting nationals (r = -0.255, 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, the regression analysis indicate that social factors explain 6.5% of the variation in the regret to recruitment of Emiratis (R^{2} = 0.065, p = 0.460). The slope of the regression equation (β = -0.099) shows that a unit increase in social factors results in a decline in the internal resistance towards Emiratisation by 0.1 units.

*Table 45: The Influence of Social Factors*

### Cultural Factors

The fourth leading factors that influence the regret to the recruitment of Emirati employees are cultural factors. Regression analysis demonstrates that cultural factors have a weak positive relationship with the regret of recruiting Emiratis and explains 4.2% of the variation in the regret to recruitment. A unit increase in cultural factors causes the regret of employing Emiratis increase by 0.059 units.

*Table 46: The Influence of Cultural Factors*

### Educational Factors

Educational factors forms the fifth factors that make companies regret after recruiting Emiratis. Regression analysis shows that educational factors have a very weak relationship with the regret to employing Emiratis, which is not statistically significant and unhelpful in prediction.

*Table 47: The Influence of Educational Factors*

### Regulatory Factors

Regulatory factors are the least significant factors influencing companies’ regret after recruiting nationals. Regulations and policies compel companies to employ Emiratis, which acts against their willingness to recruit them (Mellahi 2007; Noland & Pack 2008; Randeree, 2009). Regulatory factors are statistically insignificant negative predictors (r = 0.011) because they account for 0.0% of the variation in the regret to employing Emiratis (R^{2} = 0.000, p = 0.986). The regression coefficient (β = 0.005)is negligible in regression model and predicting the influence of regulatory factors.

*Table 48: The Influence of Regulatory Factors*

## Mean, Median and Standard Deviation for the Dependent Variables

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

*Table 49: Descriptive Statistics for the Dependent Variables*

## Mean, Median and Standard Deviation for the Explanatory Variables

As per the descriptive statistics for the 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*

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