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Role of Gender Variances in Job Satisfaction of Employee Working in Public Sector Universities |
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INTRODUCTION

Participation in the work satisfaction of University staff members has always been the development of the organization's human resources. In fact, the employee satisfaction survey of staff members is a way of knowing the human status of an organization. The biographical (demographic) characteristics of staff, such as gender, age, education, marital status, etc. various studies have been conducted and their impact on employee satisfaction. These features, the nature of gender and its impact on the physical differences between men and women and their attitudes crucially affect people's job satisfaction. In order to develop human resources, it is necessary to participate in the work related needs of the members of the organization's staff. If this is ignored, other problems will affect you. Over the past few years, the importance and role of the gender gap have led to studies on various social, political and legal issues. There are currently many seminars and conferences on women's rights around the world. Examination of the relationship between satisfaction regarding job and gender, especially in developing countries is a critical issue for conducting the study. The sex has a quite worthy impact on job satisfaction of workers in particular organization. In Pakistan, the behavior of our civilization shows that men have the upper arm in their relations and that they have an overwhelming power in the organization. Female workers generally have many problems with organizations compared to male workers due to a number of challenges and obstacles, such barriers being abandoning marriage, maternity, and discrimination, preventing female employees from working in organizations. Extremely skilled women cannot attain managerial status in governments (Li and Leung, 2001). Female staffs cannot effort long times inside the group and cannot change from one apartment to another (Pinar et.al., 2011). In administrations, female workers get less chances for elevation that are significant to meet the prospects of female personnel (McCuddy et.al., 2010). Workers leave the association for an extended time employed hours and a deprived working situation (Kusluva and Kettublock, 2000).

Disgruntled workers permission their location in the body likened to the most satisfied workforces (G Liselli et.al., 2001). Female and male workers do not only work long hours, work pressure, low revenue, no period on their working life, lack of motivation for employees, and attitudes of employees and executives (Brymer and Pavesic, 1990). Additionally, Okumus et.al., (2010) also discovered that female workers do not have sufficient time for their groups and household, and they are facing problems, long employed hours and working conditions, and they do not have time for housework. Given the extensive correlations and penalties of employee gratification with the association, this study aims to analyze sex changes in worker satisfaction.

GENDER DIFFERENCES

Demographic factors also contribute in the different work of teachers (Niehoff, 1997; Bedeian, Ferris & Kacmar, 1992; Crossman & Harris, 2006; Bogler, 2002). Significant interaction with teachers' satisfaction. These clusters are gender (Clark and ​​Oswald, 1996; Clark, 1997), age (Clark, Oswald & Warr, 1995), training (Rumberger and Levin, 1991; Clark & ​​Oswald, 1996) Sousa-Poza, 2000). Sex was often studied as a factual factor in job gratification surveys (Crossman & Harris, 2006, Hagerdorn, 1996, Poole, 1992; MacMillan, 1999). The Paradox of Gender/Job Gratification (Kaiser, 2002) or the Satisfied Female Employee Paradox (Bender, Donohue & Heywood, 2005) suggests that women report job satisfaction better than men.

Marwan (2012) explored the association among demographic features such as work experience, oldness and neck and neck of schooling and job gratification. In his study of 858 people working in various private and public Jordanian organizations, he found that work experience and age positively emphasized job satisfaction, and he also argued that pay, gender, degree of education and age are very good predictors of job satisfaction.

JOB SATISFACTION

Evans (1997) defines work satisfaction as a mood by determining to what extent an individual finds that his / her job needs meet. Therefore, also explains job consummation as a pleasant emotional national due to the value of work in achieving values. Job satisfaction can affect the commitment that Nasurdin & Ramayah (2003) refers to a commitment from employee attitude towards their organization. Usually, employees commit themselves if they are really satisfied with their current job. Satisfaction usually depends on what employees can get or get work done.

This is the degree of benefit or other way in which an employee evaluates their work. In this case, the work environment, work planning, and workflow hardware affect the employee's satisfaction with the job. Employees are happy with jobs like those with a wealth of positive behaviors such as independence, job identity, mission mark, good feedback, recognition, and empowerment. Job satisfaction differs from the satisfaction of unemployment, as the former concerns the work done by the employer, while the latter concerns work as a whole. Cole and Cole (2014) note that with increasing research, the idea that job attitudes (e.g. Job Satisfaction) may be positively linked to performance outcomes have continued to train academic researchers and practitioners. Olatunji, Mokuolu and Dare (2014) define satisfaction in a satisfactory way because employees are happy with their work. Oswald, Proto and Sgroi (2014) note that happiness makes people more productive, an employee who is happy with his job is always happy and such a worker is very productive. Cordeiro's work (as mentioned in Bateh & Heyliger, 2014) concludes that the success of an organization depends on hiring and retaining satisfied employees.

CONCEPTUAL FRAMEWORK AND HYPOTHESIS DEVELOPMENT

External and internal factors are resolute by circumstances that remain not under the switch and influential on/of an operative (Atchison, 1999). These include management conditions, pay, promotion in errands, supervision, employment, working orientation etc.

Management Conditions: focused on the feeling of competence or insufficiency of organization management. This comprises decent / bad communication, policies, procedures and rules (Bennell & Akyeampong, 2007).

Exercises HRM on strategy and actions related to managing employees, including recruitment, selection, management, compensation, evaluating, training, developing and analyzing industrial relations work (Nieto, 2014). The rendering of Hofstede, Minkov and Hofstede (2010), HRMP is a major part of structural change in culture, in other words, measures to ensure corporate identity. So far, there is no single definition of HRMP approved although most similar proposals proposed by Schuler (1992:27) in the sense that they are “special actions that companies use to attract, motivate, maintain and develop workers”. Many experts (Andreassi, Lawter, Brockerhoff and Rutigliano, 2014, Becker, Brandt and Eggeling, 2015, Nieto, 2014), it should be emphasized that the benefits of approving HRMP companies help maximize the capabilities of their HR resources, but a combination that fits the strategic vision of the company, from this point of view the key issue of continuous human resource management would be to be a powerful HRMP (Becker et al. HRMP help create value and improve the mechanisms of organizations (Oliveira de Brito, 2016, El-Ghalayini, 2017, Sojka, 2017), the mechanisms that affect the organization the results will not entendie. They clearly all in all, recent theoretical models of human resource management (Verburg, den Hartog Koopman, 2007, Way & Johnson, 2005) support the hypothesis that HRMP does not directly affect the organization's performance. These are the theoretical assumptions since the 1990s have confirmed empirical evidence that the impacts of an organization's results on HRMP occur in other variables. This activity depends on these variables of the organization's perceptions of moderate behavior. Although Korff, Biemann and Voelpel (2017) reported that the next trend is growing in the explanatory link HRMP, job satisfaction and commitment to organization.

Supervision: Comprises the instructor's readiness to impart or empower the authorities, equality and work tasks. Education monitoring is a energetic procedure and it is a grouping of doings that involves teaching and improving the university. The superior's aptitude to deliver open, practical provision and leadership to job-related errands plays a key role in occupation satisfaction (Robbins et al., 2003). Administrators with a great affiliation to behavior have a strong influence on job satisfaction (Graham & Messner, 1998).

The study shows that there is a positive relationship between control and satisfaction (Koustelios, 2001). Supervision plays an important role in job satisfaction. This role is obvious in terms of the ability of the supervisor to provide emotional and technical support and guidance in job-related tasks (Robbins, 2003). The supervisor's attitude and behavior to employees can also affect job-related complaints (Sherman, 1992). Relatively behaviors have a great impact on job satisfaction (Graham, 1998). Wech, B. (2002) supports this view by adding that supervisory activities have a strong impact on the development of trust in employee relations. In making a study, Packard (1999) found that employee supervisors who demonstrated democratic leadership experienced higher job satisfaction compared to those who were supervisors who demonstrated styles of self-governing leadership or laissez-faire. Brewer and Hensher (1998) showed that supervisors whose management approaches emphasize and worried about workers' generally more satisfied employees and supervisors. Similarly Basset, G. (1994) said supervisors who provide a humanistic part of the job to be attentive to helping them raise staff job satisfaction with the employee.

Recognition is a valorization of the workers' efforts and the positive contribution. If the credit scheme can be strong and reasonable in the opinion of the workers, it can lead to satisfaction at work (Ahuja & Shukla, 2007) Challenging work: The best work plan is continuously one that encounters the high performance structural requirements, is perfect for separate skills and requirements and delivers valued job predictions (Schermerhorn et.al., 2011). Responsibility: mentions to worker switch of his / her own work or accountability for other exertion (Desta, 2014).

H1:Management conditions are positively and significantly related with job satisfaction

H2:Supervision is positively and significantly related with Job satisfaction

H3:Recognition is positively and significantly associated with job satisfaction

CONCEPTUAL FRAMEWORK

Measures: For this study, some research measurement items were adopted on different studies and changed to take account of regional and study objectives, as well as participants and research. The questionnaire used to deal with these elements is 7 points for the Likert scale, which varies strongly from a completely agreed viewpoint.

Job Satisfaction: Ten items were used to assess the perception of managers regarding Job satisfaction items were originally developed by Ryan. E. Smerek and Marvin Peterson (2007).

Management Condition: Four items were used to assess the perception of employee regarding job satisfaction’s construct as management conditions in particular selected universities of Jamshoro Sindh.

Recognition to address this element four items were adopted, items were altered regarding the needs of this study.

SAMPLE AND PROCEDURE* This research focuses on public-sector universities located in Jamshoro, Sindh, Pakistan and all three universities selected to represent Pakistani public sector universities. This study focuses on job satisfaction, its impact, and the combination of employees' promotion. For this purpose, senior, middle and first-line leaders, teachers and other workers are faced with a population of 300

  • Three of the Jamshoro universities were selected for this study which are as under:
  • University of Sindh, Jamshoro.
  • Mehran University of Engineering and Technology.
  • Liaqat University of Medical and Health Science

This sample group is based on the available substances - those that are close or easily available (Bruce L. Berg, 2001). Sampling for large populations is very useful because everyone who meets the criteria is invited to participate the random sampling method was used on the grounds that the study covers all staff including administrative and teaching staff.

For the collection of data from this study, closed questions were used. Closed questions are more easily investigated. each answer can be known with a number or rate so that a statistical understanding can be evaluated, to measure these foundations, the 7-piont likert scale that goes from totally disagree to totally agree was used because, on a Likert scale, the respondent is asked to respond to each of the statements in terms of various grades, usually five grades (but sometimes 3 or 7 can also be used) in agreement or disagreement. For example, when asked to express their opinion about whether they think their work is pleasant enough, the respondent can respond in any of the following ways: (i) strongly agree, (ii) agree, (iii) undecided, (iv) disagree, (v) totally disagree (CR Kothari, 2004). Total population of particular participants in selected universities is approximately 8000, questionnaires were administered in employee which were the 10% of the total population with the help of convenience sampling technique, to specify participants quota sampling utilized and close ended structured questionnaires were used.

All statistical analysis of this study was conducted through SPSS version 22.0 and latest version of Smart PLs SEM.

DESCRIPTIVE RESULTS

According to Prem, S. (1995) “descriptive statistics is the discipline of quantitatively explaining the main characteristics of gathering information or the quantitative description itself”. The majority of respondents in the study were men with a frequency of 228 with an age group of 31 to 40 years. About 72 percent of the respondents had a master's degree and belonged to 1 to 10 years of experience. Table 1 presents the basic score of the measures used in this study. Initially, the scale was tested and for all constructions, Cronbach's Alpha was well above 0.7, which indicated a stronger internal consistency. Therefore, a large-scale study was carried out and in the same table the Cronbach's alpha is shown, followed by the mean and the standard deviation, which is considered quite well and is taken for the subsequent PLS SEM analysis.

TABLE-1

CRONBACH’S ALPHA AND DESCRIPTIVE STATISTICS

Variable Alpha[1] Alpha [2] Mean Std Deviation
Job Satisfaction 0.759 0.842 6.15 .813
Management Condition 0.729 0.868 5.32 1.243
Supervision 0.760 0.800 5.53 1.176
Recognition 0.728 0.713 6.55 .723

PLS SEM RESULTS

This study was performed using SEM using Smart PLS. SEM permits the measurement model to be amplified using CFA and tests the relationship between structures via route analysis (Hair et.al., 2010, Bentler, 1995, Hoyle, 1995). Smart PLS was selected for two reasons: first, it does not require information on multi-variance normality (MVN) and second small sample size (Barclays et.al., 1995). The objective of Smart PLS is similar to multiple regressions i.e. maximizing the described variance and ensuring that all links are statistically significant (Chwelos et.al., 2001, Chin, 1998, Gefen, 2004).

According to C.R.Kothari (2004) "Factor loads are based on those values ​​that explain how close the variables are related to each of the exposed factors, also known as factor-variable correlations. The loadings and cross loadings for each indicator are presented in the Table 0.2 at this juncture, JS1, JS3 and JS5 having very much strong and valid value of 0.7 and they loaded quite strong into their own construct of JS, they are poorly loaded in other constructs alike in MC 0.422, 0.415 and 0.382. Findings are identical of JS variable items in other than JS variable, thus these poor values validate the findings and strong cross loading of JS items. Additionally, items of MC (MC2, MC3 and MC4) are also strong in their own family ass compare to other constructs. Consequently, all variables and their items are very much strong and valid in their own latent variables, detailed information and statistics regarding cross loading of all items and variables is given bellow in table 0.2

TABLE-2

CROSS LOADING

         
  JS MC REC SUP
JS1 0.727 0.422 0.684 0.393
JS3 0.704 0.415 0.451 0.376
JS5 0.798 0.382 0.301 0.509
MC2 0.648 0.910 0.367 0.393
MC3 0.761 0.935 0.382 0.359
MC4 0.761 0.935 0.382 0.359
REC2 0.505 0.311 0.835 0.173
REC4 0.534 0.373 0.854 0.347
SUP1 0.696 0.381 0.300 0.907
SUP2 0.422 0.271 0.193 0.728
SUP3 0.696 0.386 0.304 0.910
SUP4 0.422 0.269 0.193 0.726
TABLE-3

DISCRIMINANT VALIDITY

  JS MC REC SUP      
JS 0.723            
MC 0.708 0.923          
REC 0.616 0.406 0.844        
SUP 0.705 0.405 0.311 0.823      

Table 3 shows the discriminant validity refers to the degree to which two measures of the similar constructs are in fact not related. It is established by the unidimensionality via average variance removed and Discriminant validity”, Hair et.al., (2010) described that “it is the degree to which two theoretically similar concepts are different. It further guarantee that every latent variable contribute more variance with its own block of indicators as compared to another latent variable”. Correlation by diameter (Table-3) is greater than the correlation of other structures. In this case, the latent variable JS AVE is 0.523 (Tab -4) with a square root 0.723, this represents the larger number than the correlation values in the column JS (0.708, 0.521) and as well as larger than the row of JS, similarly AVE of MC is 0.851 having a square root 0.923 which is larger in column and also in string of MC, this exhibit that the constructs were comparatively separate and well operationalized. REC and SUP having AVE value of 0.713 and 0.677 with DV values of 0.844 and 0.823 respectively.

TABLE-4

CONSTRUCT RELIABILITY AND VALIDITY AND R SQUARE

  R Square rho_A Composite

Reliability

Average Variance Extracted (AVE)
JS 0.880 0.800 0.814 0.523
MC 0.00 0.841 0.920 0.851
REC 0.00 0.799 0.833 0.713
SUP 0.00 0.896 0.892 0.677

The confidence of the composite reliability should be 0.7 or greater. In the case of the exploratory study to be examined, 0.6 or more can be accepted. Reliability of internal consistency is very satisfactory here ", all of these variables such as MC, JS and REC are strong composite reliability values ​​of 0.920, 0.814 and 0.833, (Table 0.4) shows that all variables have good Rho-A correlation coefficient values ​​and all are greater than 0, and that all variables have good Rho-A correlation coefficient values ​​and all are greater than 0, 7, indicating strong combinations among LV. "In this study, the Cronbach alpha coefficients were close to 0.8 and higher. According to the findings of Table-4 which is all about R Square, entire independent variables having 0 R square value which is quite significant as independent or influential variables, however, dependent variable which is dependent on influential variables is adopting influence with value of 0.880, thus R square is totally strong in both independent and depend variable context.

HYPOTHESES TESTING

The Path coefficient effect, Total effects, Beta and T-statistic for the entire items in the dimension model with high loadings for nearly all measures are shown in the Table-5. Hair et.al., (2010) described that “if T- Statistics is larger than 1.96 in marketing and 1.65 for exploratory research then path co-efficient will be considered significant”. With the consideration of this study, table 0.5 is disclosing that the entire variables have considerable relationship with each other. By considering T statistics value at significance level of T = 1.96 MC and JS having quite strong relationship among each other with the value of 15.236, similarly REC linkage with JS is also stronger with the value of 6.780. Additionally, remaining variable SUP association with Job satisfaction JS is also significant with the values of 11.182 respectively.

TABLE NO. 4.10

MEAN, STDEV, T-VALUES, P-VALUES

  Original

Sample (β)

Standard Deviation T Statistics (|O/STDEV|)
MC -> JS 0.412 0.027 15.236
REC -> JS 0.214 0.032 6.780
SUP -> JS 0.333 0.030 11.182

By considering the statitics of table 0.5 regarding path coefficent analysis of hypotheses on orignal sample size of 410, the beta value of entire latent varible’s relationships are pretty significant. The relationship of MC, REC with JS is very much significant with the values of 0.412 and 0.214 at significant value of β = 0.05. Similarly SUP is also significantly hypothesized with JS with worthy values of 0.333 at significance level of β = 0.05 respectively, thus all hypotheses are significant and supported.

DISCUSSION

According to the results and findings of hypotheses testing, it has been founded that there are certain JS factors which are getting influenced by gender differences and leaving impact on job satisfaction of workers which are employed at Jamshoro based universities.

The findings of this research revealed that management condition MC is a factor of job satisfaction which is usually getting influenced in distinguished genders and impacts on job satisfaction of employee of that particular organization as presented above in table 4.10 similar findings were also found in different studies conducted by various authors alike (Witte and Buitendach, 2005; Atchison, 1999 and Bennell & Akyeampong, 2007) and their findings validated findings of this research.

According to the studies of Ahuja & Shukla, (2007) and Schermerhorn et.al., (2011) recognition is positively associated with employee job satisfaction and having worthy impact on it, as this research is also explicated linkages of REC and JS with association of gender differences, research validated findings of above mentioned researchers and further implicated theoretically and managerially by providing detailed findings regarding impact of GD on employee recognition and their association with employee job satisfaction as presented in table 4.10 by T and Beta statistics in path-coefficients analysis.

Similarly, Supervision is influential factor of job satisfaction in perspective of gender differences the entire findings regarding this factor is presented in tab 4.10 as beta and T statistics analyses, these findings are confirmed by the researcher likewise, (Robbins et.al., 2003; Graham & Messner, 1998; Leithwood, 2006 and Robbins, 2005) respectively.

IMPLICATIONS

This research implicated in two perspectives, theoretically and practically, theoretical implication is that, this research enhanced existing literature. Secondly, this research implicated in practical point of view, research provided model along with validation from literature and primary data evidence by testing collectively the opinions of respondents and highlighted extensive need of diversity management in public sector universities to manage their demographic profiles dissimilarities.

CONCLUSION

The Gender differences at workplace could impact on other important factors just like, employee motivation, organizational justice, organizational citizenship of performance, learning, job security, employee turnover and human aptitude development.

Additionally research should investigate relationship among Gender difference, job satisfaction and factors of job satisfaction in other areas or cities in both public and private sectors institutions.

Future researches should also identify impact of the GD on innovation potential, outcome and motivation. research should be pay attention on redefining and examination of measurement scales mainly considered for measurement of GD and employee job satisfaction activities in context of Pakistan’s private organizations, nearby should be more concentration about private and government sector organizations with more huge model size and population in circumstance of both executive and non-management population of both government and private sector. The main motive about future research should be the expansion of measurement model in perspective of structural model demonstration the total impact of Gender variance on job satisfaction of employee and other basic elements of study in context of Pakistan.

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  1. Cronbach’s Alpha of Pilot Study
  2. Cronbach’s Alpha of final Study
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