Introduction

Happiness is the degree to which you perceive and evaluate your life as beneficial (Naseem, 2018). In addition to an enduring, psychological feeling of contentment (Mohanty, 2014). In the hedonic view, happiness is pleasant feeling and favourable judgment, while the contrasting eudemonic view describes it as doing what is morally right, what is righteous, that will enhance growth and all that is meaningful to an individual (Ryff & Singer, 2008). Both these views contribute to the overall happiness of an individual.

The extent of employee happiness has been found to have a considerable positive influence on the employee motivation and overall job satisfaction at work (Al-Ali & Shibami, 2019). In particular, workers who display a general sense of happiness and emotional satisfaction with their overall well-being are likely to be inspired to perform extremely well in the workplace environment. Often-happy workers strive to synchronise and convert their emotional happiness by displaying habits that contribute to higher efficiency towards achieving organisational objectives (Jebb & Oishi, 2018). The national culture, which plays an important role in generating and maintaining employee morale in the company, is essential to employee satisfaction (Sony& Mekoth, 2016). People that are pleased with their lives usually experience greater satisfaction and happiness in their jobs

In addition, happiness is correlated with evidence of success in the workplace and can increase an employee’s effectiveness, performance and job satisfaction levels at work (Walsh & Lyubomirsky, 2018). It is therefore, important for organizations to identify the factors which influence employee happiness to enhance its cultural value-offering for employees and, in turn, increase their levels of job satisfaction.

However, addressing a seminar organized by the Emirates Government Services Excellence Programmer, Ms. Al Roumi said: “The UAE government, under the leadership of Sheikh Mohammed bin Rashid Al Maktoum, Vice President and Prime Minister of the UAE and Ruler of Dubai, is keen to transform all government ministries and institutions by creating a happy work environment with the aim of maintaining employee rather than turnover (Lee & Mitchell, 2017; Bakhtiari et al., 2019).

Furthermore, UAE public and private both organizations facing high employee turnover rates (Alhashmi & Papastathopoulos, 2017). In 2014 there are only 38% employee in UAE would like to change their employer Gulf News. There percentage is increased to 56% in 2017. In addition, it is reported that, most employee want the employers to provide a wider array of benefits that can purchase on their own. Although they received high salary, the employees are unsatisfied with the work-life balance support that given by employer. The work-life balance support includes preventive care and stress management. These results show that salary is not the only way to avoid employee retention and maintain happiness among employee.

Helmreich & Merritt (2019) noted that changes in the work style, work culture, family needs, and work demands in UAE public organizations are rapidly taking place, which eventually increased the population of dual earner couples, single parent families and eldercare responsibilities. These increased changes in UAE public organizations have adverse impact on employees’ as well as organizational performance, which is quite evident in the amount of backlog in the UAE public organizations (Al Suwaidi & Alshami, 2020), poor attitude towards work and poor interpersonal relationships, increased pressure at the workplace in UAE public organizations negatively affects the work-life balance (Parakandi & Behery, 2016).

Further, Employees in the public organizations in UAE are not well satisfied due to poor workplace conditions( Bhatnagar & George, 2016 ; Rouhani & Asadi, 2020 ), most of the staff in the government organizations are not happy with their work because of outdated working equipment, rigorous supervision and weak government services in their organizations. This forced many government staff moved to private sectors. These issues tremendously affect the employee happiness in the UAE government organization.

Research Methodology

Since the population of this study is 11787 therefore, the sample size will be determining sample size from a given (Krejcie & Morgan, 1970) which will be 370. AMOS-SEM software package for simulation and modelling procedure is used in locating the significant and dominant factors. Purposive sampling techniques was used while Structural Equation Modelling (SEM) was used to develop a new model of happiness at the workplace in promoting employee happiness in public organization.

The questionnaires were distributed to the staff of Dubai Electricity and Water Authority in UAE. Questions will be provided in both languages English and Arabic language as it is assuming that the citizen of UAE includes UAE national that prefer Arabic language and non-UAE national (expatriates) that use English for communication with local people. The questionnaire included the instruments related to transformational leadership, organizational culture, employee’s empowerment, employee satisfaction and happiness. Thus, an aggregate 370 completed questionnaire were distributed to targeted respondents. Of these, 260 questionnaires were received. The study was conducted from Month, January 2020 to May 2020.

The data were distributed through Posting, Email, and survey and in Person from the sample group. The reason behind this approach is that most of the employees have access to a Personal Computer and Internet. It is also a timely and effective way to receive responses. These prospective respondents will be requested to complete the questionnaire. Table 1 shows the questionnaire was divided into four sections.

Table 1 Questionnaire Descriptions
Section	Questionnaire	Purpose
Section 1	Demographic information such as Gender, Age, Ethnic Group, Marital Status, Number of Children, Exercise Frequency, Education Level, Years of Service, Job Level and Department	To identify the dimension and dynamics of the population of the developed model.
		To outlines various indirect factors of the developed model.
Sections 2	Independent variables	To capture the respondent’s perception of influence the government entities in promoting a happier work environment
Sections 3	Dependent Variables	To investigate the relationship between happier working environment and employee performance
Sections 4	Mediating	Investigate the relationship between organizational culture, happier working environment and employee performance.

The responses from the Dubai Electricity and Water Authority in UAE Survey will be analysed using Statistical Package for Social Sciences (SPSS) and AMOS to achieve the research objectives. In order to remove any bias or incorrect records from the datasets, data were cleaned. The nature of the responses was established with the use of descriptive and inferential statistical indexes. The reliability of the instruments was then established by calculating Cronbach alphas.

Analysis and Result

Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis is a more dependable method of factor analysis which is engaged to examine whether the measures of a construct are in agreement with the researcher’s perspective of the nature of that construct (Awang, 2014). In fact, (Awang, 2015) stated that CFA procedure has relieved the older methods such as EFA to establish construct validity.

The proposed assessment happiness at the workplace in promoting employee happiness in public organization was based on the previous validated empirical studies with comprehensive theoretical literature. Confirmatory Factor Analysis (CFA) is to confirm happiness at the workplace in promoting employee in public organization with a view to happiness values within the Abu Dhabi in UAE. Inferably, CFA is to test association that may exist between the observed variables under each hypothesised construct in order to quantitatively assess the quality of the factor structure which would provide further evidence of the construct validity of the new measurement.

Basically, the application of SEM with the combination of CFA for this research is in consonance with the standard steps as recommended by prominent scholars (Awang, 2015; Hair et al., 2012) such as: (1) model specification; (2) model identification; (3) estimation of parameter; (4) measure of goodness-of-fit; and (5) model re-specification.

To be exact, in this research analysis process, the preliminary measure is to test the validity of the measurement model before considering the structural model. Hence, both measurement and structural models were evaluated by model fitting through Maximum Likelihood (ML) estimation. The goodness-of-fit indices and level of acceptance used as guide in the assessment of the construct measurement models and structural equation models’ fitness was presented in Table 2.

Table 2 Goodness-of-Fit Index and Level of Acceptance
Name of category	Goodness-of-fit indices	Acceptance level	Comments	Literature support
Absolute fit	Chisq	P > 0.05	Sensitive to sample size greater than 200	Wheaton et al., (1977)
Absolute fit	RMSEA	RMSEA < 0.08	Range 0.05 to 1.00 is acceptable	Brownne & Cudeck (1993)
Absolute fit	GFI	GFI > 0.90	GFI = 0.95	Jorekog & Sorbom (1984)
			Is a good fit
Incremental fit	AGFI	AGFI > 0.90	AGFI = 0.95	Tanaka & Huba (1985
			Is a good fit
Incremental fit	CFI	CFI > 0.90	CFI = 0.95	Bentler (1990)
			Is a good fit
Parsimonious fit	Chisq/df	Chisq/df < 5.0	The value should be less than 5.0	Marsh & Hocevar (1985)

Subsequently, re-specified models in this research were tested before using the models for further analysis and Modification Indices (MI) were used as a guide to detect specification error during the process of model re-specification.

Therefore, confirmatory factor analyses of the measurement model of the entire latent constructs in the research assessment framework evaluated and presented in the subsequent sections accordingly. In addition, initial measurement models; fitness indexes; modification indices and; final measurement models were presented sequentially for each latent construct. The purpose of this was for the readers to understand every step of evaluating each of the measurement model fitness in the research assessment model.

Measurement Model for Organizational Culture Construct

The measurement model for organizational culture is a graphical representation of the relationship between response items and their underlying organizational culture construct and then analysis is carried out using CFA. The construct organizational culture has ten (10) items of questions in the questionnaire. However, (Awang, 2015; Hair et al., 2012) cautioned that the minimum number of items needed to measure a latent construct should not be less than four (4) and this is to avoid the model identification problem during the analysis process.

The application of AMOS is then used for the construct of organizational culture measurement model. The factor loading for each item, squared multiple correlation (R²) and fitness indexes for the organizational culture construct was examined. Hence, AMOS calculated standardized estimate of factor loading and R² value score of the initial measurement model for the organizational culture construct were presented in Figure 1

The factor loading for items (Q1 and Q2) is below 0.6, and Chisq/df is higher than 3.0 as presented in Figure 4.5, hence, the need for modification. Therefore, item (Q1 and Q2) were deleted because requirement was not achieved and the new measurement model re-specified and final measurement model for organizational culture construct presented in Figure 2. Hence, the remaining eight (8) items were used in the analyses of structural equation modelling and to test and validate research hypotheses.(Table 3)

Table 3 Confirmatory Factor Analysis for Organizational Culture
Name of category	Goodness-of-fit indices	Acceptance level	Comments
Absolute fit	Chisq	P > 0.05	Sensitive to sample size greater than 200
Absolute fit	RMSEA	RMSEA < 0.08	Range 0.05 to 1.00 is acceptable
Absolute fit	GFI	GFI > 0.90	GFI = 0.95
			Is a good fit
Incremental fit	AGFI	AGFI > 0.90	AGFI = 0.95
			Is a good fit
Incremental fit	CFI	CFI > 0.90	CFI = 0.95
			Is a good fit
Parsimonious fit	Chisq/df	Chisq/df < 5.0	The value should be less than 5.0

Finally, the organizational culture construct’s final measurement model (2) had satisfied all the acceptable cut-off values as recommended in the goodness-of-fitness indexes (Awang, 2014).

Measurement Model for Employee Satisfaction

The measurement model for employee satisfaction is graphically presented in the relationship between response items and their underlying employee satisfaction construct. Confirmatory Factor Analysis (CFA) was carried out and the result of the analysis presented in Figure 3. In the construct of employee satisfaction measurement model, factor loading for each item, squared multiple correlation (R²) and fitness indexes for each of the items examined.

The factor loading for items (Q11 to Q17) is below 0.5, and Chisq/df is higher than 3.0 as presented in Figure 4, hence, the need for modification. Therefore, item (Q11 to Q17) were deleted because requirement was not achieved and the new measurement model re-specified and final measurement model for LT construct presented in Figure 3. Hence, the remaining five (5) items were used in the analyses of structural equation modelling and to test and validate research hypotheses.(Table 4)

Table 4 Confirmatory Factor Analysis for Employee Satisfaction
Name of category	Goodness-of-fit indices	Acceptance level	Comments
Absolute fit	Chisq	P > 0.05	Sensitive to sample size greater than 200
Absolute fit	RMSEA	RMSEA < 0.08	Range 0.05 to 1.00 is acceptable
Absolute fit	GFI	GFI > 0.90	GFI = 0.95
			Is a good fit
Incremental fit	AGFI	AGFI > 0.90	AGFI = 0.95 Is a good fit
Incremental fit	CFI	CFI > 0.90	CFI = 0.95 Is a good fit
Parsimonious fit	Chisq/df	Chisq/df < 5.0	The value should be less than 5.0

Finally, the employee satisfaction construct’s final measurement model (4) had satisfied all the acceptable cut-off values as recommended in the goodness-of-fitness indexes (Awang, 2014).

Measurement Model for Transformational Leadership

Figure 5, presented the result of Confirmatory Factor Analysis (CFA) for the transformational leadership measurement model. In the construct of transformational leadership measurement model, factor loading for each item, squared multiple correlation (R²) and fitness indexes for each of the item observed were presented. The essence was to identify whether level of acceptance for every index are achieved in the transformational
leadership construct.

From the measurement model transformational leadership, all the factors loadings appear good as none is below 0.5. However, the Chi/df appears to need modification as it was below the minimum acceptable value of 3. Finally, the transformational leadership construct’s final measurement model had satisfied all the acceptable cut-off values as recommended in the goodness-of-fitness indexes (Awang, 2014; 2015). The factor loading for items (Q23 to Q25 and Q32 -Q35) is below 0.5, and Chisq/df is higher than 3.0 as presented in Figure 6, hence, the need for modification. Therefore, item (Q23 to Q25 and Q32 -Q35) were deleted because requirement was not achieved and the new measurement model re-specified and final measurement model for transformational leadership construct presented in Figure 4.10. Hence, the remaining five (5) items were used in the analyses of structural equation modelling and to test and validate research hypotheses. (Table 5)

Table 5 Confirmatory Factor Analysis for Employee Satisfaction
Name of category	Goodness-of-fit indices	Acceptance level	Comments
Absolute fit	Chisq	P > 0.05	Sensitive to sample size greater than 200
Absolute fit	RMSEA	RMSEA < 0.08	Range 0.05 to 1.00 is acceptable
Absolute fit	GFI	GFI > 0.90	GFI = 0.95
			Is a good fit
Incremental fit	AGFI	AGFI > 0.90	AGFI = 0.95
			Is a good fit
Incremental fit	CFI	CFI > 0.90	CFI = 0.95
			Is a good fit
Parsimonious fit	Chisq/df	Chisq/df < 5.0	The value should be less than 5.0

Finally, the transformational leadership construct’s final measurement model (6) had satisfied all the acceptable cut-off values as recommended in the goodness-of-fitness indexes (Awang, 2014).

Measurement Model for Employee Empowerment Construct

In the same order of presentation, Figure 7 presented the result of the CFA for the ER measurement model. The factor loading for each item, squared multiple correlation (R2) and fitness indexes were observed.

The factor loading for items (Q36 to Q40) is below 0.5, and Chisq/df is higher than 3.0 as presented in Figure 7, hence, the need for modification. Therefore, item (Q36 to Q40) were deleted because requirement was not achieved and the new measurement model re-specified and final measurement model for employee empowerment construct presented in Figure 8. Hence, the remaining four (4) items were used in the analyses of structural equation modelling and to test and validate research hypotheses. (Table 6)

Table 6 Confirmatory Factor Analysis for Employee Empowerment
Name of category	Goodness-of-fit indices	Acceptance level	Comments
Absolute fit	Chisq	P > 0.05	Sensitive to sample size greater than 200
Absolute fit	RMSEA	RMSEA < 0.08	Range 0.05 to 1.00 is acceptable
Absolute fit	GFI	GFI > 0.90	GFI = 0.95
			Is a good fit
Incremental fit	AGFI	AGFI > 0.90	AGFI = 0.95
			Is a good fit
Incremental fit	CFI	CFI > 0.90	CFI = 0.95
			Is a good fit
Parsimonious fit	Chisq/df	Chisq/df < 5.0	The value should be less than 5.0

Finally, the employee empowerment construct’s final measurement model (see Figure 8) had satisfied all the acceptable cut-off values as recommended in the goodness-of-fitness indexes (Awang, 2014). The result showed that all items had suitable factor loading, in summary, all employee empowerment items construct that satisfied the level of acceptance were used for the structural equation modelling in this research.

Measurement Model for Happiness Construct

In the same order of presentation, Figure 9 presented the result of the CFA for the happiness measurement model. The factor loading for each item, squared multiple correlation (R²) and fitness indexes were observed.

The result showed that the items from Q45 to Q49 and Q55 to Q58 had low factor loading, so, they candidates to be deleted. Therefore, items were deleted because requirement was not achieved and the new measurement model re-specified and final measurement model for happiness construct presented in Figure 9. Hence, the remaining five items (5) items were used in the analyses of structural equation modelling and to test and validate research hypotheses. The final measurement model is as Figure 10 shown below. (Table 7)

Table 7 Confirmatory Factor Analysis for Happiness
Name of category	Goodness-of-fit indices	Acceptance level	Comments
Absolute fit	Chisq	P > 0.05	Sensitive to sample size greater than 200
Absolute fit	RMSEA	RMSEA < 0.08	Range 0.05 to 1.00 is acceptable
Absolute fit	GFI	GFI > 0.90	GFI = 0.95
			Is a good fit
Incremental fit	AGFI	AGFI > 0.90	AGFI = 0.95
			Is a good fit
Incremental fit	CFI	CFI > 0.90	CFI = 0.95
			Is a good fit
Parsimonious fit	Chisq/df	Chisq/df < 5.0	The value should be less than 5.0

In summary, all happiness items construct that satisfied the level of acceptance were used for the structural equation modelling in this research.

Conclusion

The findings will also be useful to other organizations services, not only in the country, but also across the region. Specifically, determination of whether the implementation of happiness strategy among their employee has positively contributed towards its performance is expected to provide a benchmark for other agencies in the region in order to foster their performance as well. As such, the findings in this study are expected to not only be useful to the AD organizations, but also to the entire Gulf region as well.

To the best knowledge of the researcher, this is the first study of this kind in the Arab World, and hence the findings are expected to be quite impactful in establishing the specific management issues that face the region. More so, since UAE is a developing country, the findings obtained are expected to create a springboard for other researches in the region with regard to strategic management practices in the happiness systems in the countries within the region. With the adoption of quantitative research methods in this study, new findings on the specific strategic management practices in the UAE’s employee force were expected, and hence this study contributed largely towards enrichment of management research and theories in the Arab world. Validation results proved the factors and measurement models developed and indicated their applicability in happiness evaluations. SEM models were proposed in building satisfaction and performance evaluations using dependent and independent factors. The models provide a guide for better understanding of these facilities and their interactive behaviour. Methodologically, findings of this study add to existing knowledge of relation of happiness.

Acknowledgement

We would like to thank Universiti Teknikal Malaysia Melaka for supporting us in publishing this paper.

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