level of job satisfaction research paper

ORIGINAL RESEARCH article

Job satisfaction, organizational commitment and job involvement: the mediating role of job involvement.

• Department of Industrial Engineering and Management, Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia

We conducted an empirical study aimed at identifying and quantifying the relationship between work characteristics, organizational commitment, job satisfaction, job involvement and organizational policies and procedures in the transition economy of Serbia, South Eastern Europe. The study, which included 566 persons, employed by 8 companies, revealed that existing models of work motivation need to be adapted to fit the empirical data, resulting in a revised research model elaborated in the paper. In the proposed model, job involvement partially mediates the effect of job satisfaction on organizational commitment. Job satisfaction in Serbia is affected by work characteristics but, contrary to many studies conducted in developed economies, organizational policies and procedures do not seem significantly affect employee satisfaction.

1. Introduction

In the current climate of turbulent changes, companies have begun to realize that the employees represent their most valuable asset ( Glen, 2006 ; Govaerts et al., 2011 ; Fulmer and Ployhart, 2014 ; Vomberg et al., 2015 ; Millar et al., 2017 ). Satisfied and motivated employees are imperative for contemporary business and a key factor that separates successful companies from the alternative. When considering job satisfaction and work motivation in general, of particular interest are the distinctive traits of these concepts in transition economies.

Serbia is a country that finds itself at the center of the South East region of Europe (SEE), which is still in the state of transition. Here transition refers to the generally accepted concept, which implies economic and political changes introduced by former socialist countries in Europe and beyond (e.g., China) after the years of economic stagnation and recession in the 1980's, in the attempt to move their economy from centralized to market-oriented principles ( Ratkovic-Njegovan and Grubic-Nesic, 2015 ). Serbia exemplifies many of the problems faced by the SEE region as a whole, but also faces a number of problems uniquely related to the legacy of its past. Due to international economic sanctions, the country was isolated for most of the 1990s, and NATO air strikes, related to the Kosovo conflict and carried out in 1999, caused significant damage to the industry and economy. Transitioning to democracy in October 2000, Serbia embarked on a period of economic recovery, helped by the introduction of long overdue reforms, major inflows of foreign investment and substantial assistance from international funding institutions and others in the international community. However, the growth model on which Serbia and other SEE countries relied between 2001 and 2008, being based mainly on rapid capital inflows, a credit-fueled domestic demand boom and high current account deficit (above 20% of GDP in 2008), was not accompanied by the necessary progress in structural and institutional reforms to make this model sustainable ( Uvalic, 2013 ). The central issue of the transition process in Serbia and other such countries is privatization of public enterprises, which in Serbia ran slowly and with a number of interruptions, failures and restarts ( Radun et al., 2015 ). The process led the Serbian industry into a state of industrial collapse, i.e., deindustrialization. Today there are less than 400,000 employees working in the industry in Serbia and the overall unemployment rate exceeds 26% ( Milisavljevic et al., 2013 ). The average growth of Serbia's GDP in the last 5 years was very low, at 0.6% per year, but has reached 2.7% in 2016 ( GDP, 2017 ). The structure of the GDP by sector in 2015 was: services 60.5%, industry 31.4%, and agriculture 8.2% ( Statistical Office of the Republic of Serbia, 2017 ).

Taking into account the specific adversities faced by businesses in Serbia, we formulated two main research questions as a starting point for the analysis of the problem of work motivation in Serbia:

1. To what extent are the previously developed models of work motivation (such as the model of Locke and Latham, 2004 ) applicable to the transition economy and business practices in Serbia?

2. What is the nature of the relationships between different segments of work motivation (job satisfaction, organizational commitment, job involvement and work characteristics)?

The Hawthorn experiment, conducted in early 1930s ( Mayo, 1933 ), spurred the interest of organizational behavior researchers into the problem of work motivation. Although Hawthorn focused mainly on the problems of increasing the productivity and the effects of supervision, incentives and the changing work conditions, his study had significant repercussions on the research of work motivation. All modern theories of work motivation stem from his study.

Building on his work, Maslow (1943) published his Hierarchy of Needs theory, which remains to this day the most cited and well known of all work motivation theories according to Denhardt et al. (2012) . Maslow's theory is a content-based theory , belonging to a group of approaches which also includes the ERG Theory by Alderfer (1969) , the Achievement Motivation Theory, Motivation-Hygiene Theory and the Role Motivation Theory.

These theories focus on attempting to uncover what the needs and motives that cause people to act in a certain way, within the organization, are. They do not concern themselves with the process humans use to fulfill their needs, but attempt to identify variables which influence this fulfillment. Thus, these theories are often referred to as individual theories , as they ignore the organizational aspects of work motivation, such as job characteristics or working environment, but concentrate on the individual and the influence of an individual's needs on work motivation.

The approach is contrasted by the process theories of work motivation, which take the view that the concept of needs is not enough to explain the studied phenomenon and include expectations, values, perception, as important aspects needed to explain why people behave in certain ways and why they are willing to invest effort to achieve their goals. The process theories include: Theory of Work and Motivation ( Vroom, 1964 ), Goal Setting Theory ( Locke, 1968 ), Equity Theory ( Adams, 1963 ), as well as the The Porter-Lawler Model ( Porter and Lawler, 1968 ).

Each of these theories has its limitations and, while they do not contradict each other, they focus on different aspects of the motivation process. This is the reason why lately they have been several attempts to create an integrated theory of work motivation, which would encompass all the relevant elements of different basic theories and explain most processes taking place within the domain of work motivation, the process of motivation, as well as employee expectations ( Donovan, 2001 ; Mitchell and Daniels, 2002 ; Locke and Latham, 2004 ). One of the most influential integrated theories is the theory proposed by Locke and Latham (2004) , which represents the basis for the study presented in this paper.

The model of Locke and Latham is show in Figure 1 . As the figure shows, it includes individual needs, values and motive, as well as personality. Incorporating the theory of expectations, the goal-setting theory and the social-cognitive theory, it focuses on goal setting, goals themselves and self-efficiency. Performance, by way of achievements and rewards, affects job satisfaction. The model defines relations between different constructs and, in particular, that job satisfaction is affected by the job characteristics and organizational policy and procedures and that it, in turn, affects organizational commitment and job involvement. Locke and Latham suggested that the theory they proposed needs more stringent empirical validation. In the study presented here, we take a closer look at the part of their theory which addresses the relationship between job satisfaction, involvement and organizational commitment. The results of the empirical study conducted in industrial systems suggest that this part of the model needs to be improved to reflect the mediating role of job involvement in the process through which job satisfaction influences organizational commitment.

Figure 1 . Diagram of the Latham and Locke model. The frame on the right indicates the part of the model the current study focuses on.

Job satisfaction is one of the most researched phenomena in the domain of human resource management and organizational behavior. It is commonly defined as a “pleasurable or positive emotional state resulting from the appraisal of oneś job or job experiences” ( Schneider and Snyder, 1975 ; Locke, 1976 ). Job satisfaction is a key element of work motivation, which is a fundamental determinant of one's behavior in an organization.

Organizational commitment, on the other hand, represents the degree to which the employees identify with the organization in which they work, how engaged they are in the organization and whether they are ready leave it ( Greenberg and Baron, 2008 ). Several studies have demonstrated that there is a strong connection between organizational commitment, job satisfaction and fluctuation ( Porter et al., 1974 ), as well as that people who are more committed to an organization are less likely to leave their job. Organizational commitment can be thought of as an extension of job satisfaction, as it deals with the positive attitude that an employee has, not toward her own job, but toward the organization. The emotions, however, are much stronger in the case of organizational commitment and it is characterized by the attachment of the employee to the organization and readiness to make sacrifices for the organization.

The link between job satisfaction and organizational commitment has been researched relatively frequently ( Mathieu and Zajac, 1990 ; Martin and Bennett, 1996 ; Meyer et al., 2002 ; Falkenburg and Schyns, 2007 ; Moynihan and Pandey, 2007 ; Morrow, 2011 ). The research consensus is that the link exists, but there is controversy about the direction of the relationship. Some research supports the hypothesis that job satisfaction predicts organizational commitment ( Stevens et al., 1978 ; Angle and Perry, 1983 ; Williams and Hazer, 1986 ; Tsai and Huang, 2008 ; Yang and Chang, 2008 ; Yücel, 2012 ; Valaei et al., 2016 ), as is the case in the study presented in this paper. Other studies suggest that the organizational commitment is an antecedent to job satisfaction ( Price and Mueller, 1981 ; Bateman and Strasser, 1984 ; Curry et al., 1986 ; Vandenberg and Lance, 1992 ).

In our study, job involvement represents a type of attitude toward work and is usually defined as the degree to which one identifies psychologically with one's work, i.e., how much importance one places on their work. A distinction should be made between work involvement and job involvement. Work involvement is conditioned by the process of early socialization and relates to the values one has wrt. work and its benefits, while job involvement relates to the current job and is conditioned with the one's current employment situation and to what extent it meets one's needs ( Brown, 1996 ).

2.1. Research Method

Based on the relevant literature, the results of recent studies and the model proposed by Locke and Latham (2004) , we designed a conceptual model shown in Figure 2 . The model was then used to formulate the following hypotheses:

H0 - Work motivation factors, such as organizational commitment, job involvement, job satisfaction and work characteristics, represent interlinked significant indicators of work motivation in the organizations examined.

H1 - Work characteristics will have a positive relationship with job satisfaction.

H2 - Organizational policies and procedures will have a positive relationship with job satisfaction.

H3 - Job satisfaction will have a positive relationship with job involvement.

H4 - Job satisfaction will have a positive relationship with organizational commitment.

H5 - Job involvement will have a mediating role between job satisfaction and organizational commitment.

Figure 2 . The research model.

2.2. Participants

For the purpose of this study, 125 organizations from the Serbian Chamber of Commerce database ( www.stat.gov.rs ) were randomly selected to take part in this study. Each organization was contacted and an invitation letter was sent. Eight companies expressed a desire to take part and provided contact details for 700 of their employees. The questionnaire distribution process was conducted according to Dillman's approach ( Dillman, 2011 ). Thus, the initial questionnaire dissemination process was followed by a series of follow-up email reminders, if required. After a 2-month period, out of 625 received, 566 responses were valid. Therefore, the study included 566 persons, 235 males (42%) and 331 women (58%) employed by 8 companies located in Serbia, Eastern Europe.

The sample encompassed staff from both public (53%) and private (47%) companies in manufacturing (31%) and service (69%) industries. The companies were of varied size and had between 150 and 6,500 employees, 3 of them (37.5%) medium-sized (<250 employees) and 5 (62.5%) large enterprises.

For the sake of representativeness, the sample consisted of respondents across different categories of: age, years of work service and education. The age of the individuals was between 20 and 62 years of age and we divided them into 5 categories as shown in Table 1 . The table provides the number of persons per category and the relative size of the category wrt. to the whole sample. In the same table, a similar breakdown is shown in terms of years a person spent with the company, their education and the type of the position they occupy within the company (managerial or not).

Table 1 . Data sample characteristics.

2.3. Ethics Statement

The study was carried out in accordance with the Law on Personal Data Protection of the Republic of Serbia and the Codex of Professional Ethics of the University of Novi Sad. The relevant ethics committee is the Ethics Committee of the Faculty of Technical Sciences of the University of Novi Sad.

All participants took part voluntarily and were free to fill in the questionnaire or not.

The questionnaire included a cover sheet explaining the aim of the research, ways in which the data will be used and the anonymous nature of the survey.

2.4. Measures

This study is based on a self reported questionnaire as a research instrument.

The questionnaire was developed in line with previous empirical findings, theoretical foundations and relevant literature recommendations ( Brayfield and Rothe, 1951 ; Weiss et al., 1967 ; Mowday et al., 1979 ; Kanungo, 1982 ; Fields, 2002 ). We then conducted a face validity check. Based on the results, some minor corrections were made, in accordance with the recommendations provided by university professors. After that, the pilot test was conducted with 2 companies. Managers from each of these companies were asked to assess the questionnaire. Generally, there were not any major complaints. Most of the questions were meaningful, clearly written and understandable. The final research instrument contained 86 items. For acquiring respondents' subjective estimates, a five-point Likert scale was used.

The questionnaire took about 30 min to fill in. It consisted of: 10 general demographic questions, 20 questions from the Minnesota Satisfaction Questionnaire (MSQ), 15 questions from the Organizational Commitment Questionnaire (OCQ), 10 questions from the Job Involvement Questionnaire (JIQ), 18 questions of the Brayfield-Rothe Job Satisfaction Scale (JSS), 6 questions of the Job Diagnostic Survey (JDS) and 7 additional original questions related to the rules and procedures within the organization.

The Minnesota Satisfaction Questionnaire (MSQ), 20 items short form ( Weiss et al., 1967 ), was used to gather data about job satisfaction of participants. The MSQ – short version items, are rated on 5-points Likert scale (1 very dissatisfied with this aspect of my job, and 5 – very satisfied with this aspect of my job) with two subscales measuring intrinsic and extrinsic job satisfaction.

Organizational commitment was measured using The Organizational Commitment Questionnaire (OCQ). It is a 15-item scale developed by Mowday, Steers and Porter ( Mowday et al., 1979 ) and uses a 5-point Likert type response format, with 3 factors that can describe this commitment: willingness to exert effort, desire to maintain membership in the organization, and acceptance of organizational values.

The most commonly used measure of job involvement has been the Job Involvement Questionnaire (JIQ, Kanungo, 1982 ), 10-items scale designed to assess how participants feel toward their present job. The response scale on a 5-point scale varied between “strongly disagree/not applicable to me” to “strongly agree/fully applicable”.

The Brayfield and Rothe's 18-item Job Satisfaction Index (JSI, Brayfield and Rothe, 1951 ) was used to measure overall job satisfaction, operationalized on five-point Likert scale.

Psychometric analysis conducted showed that all the questionnaires were adequately reliable (Cronbach alpha > 0.7). The suitability of the data for factor analysis has been confirmed using the Kaiser-Meyer-Olkin (KMO) Test (see Table 2 ).

Table 2 . Basic psychometric characteristics of the instruments.

For further analysis we used summary scores for the different scales. Job satisfaction was represented with the overall score of MSQ, as the data analysis revealed a strong connection between the extrinsic and intrinsic motivators. The overall score on the OCQ was used as a measure of organizational commitment, while the score on JDS was used to reflect job characteristics. The JSS and JIQ scales have been modified, by eliminating a few questions, in order to improve reliability and suitability for factor analysis.

Statistical analysis was carried out using the SPSS software. The SPSS Amos structural equation modeling software was used to create the Structural Equation Models (SEMs).

The data was first checked for outliers using box-plot analysis. The only outliers identified were related to the years of employment, but these seem to be consistent to what is expected in practice in Serbia, so no observations needed to be removed from the dataset.

3.1. Exploratory Factor Analysis

Although research dimensions were empirically validated and confirmed in several prior studies, to the best of our knowledge, the empirical confirmation of the research instrument (i.e., questionnaire) and its constituents in the case of Serbia and South-Eastern Europe is quite scarce. Furthermore, the conditions in which previous studies were conducted could vary between research populations. Also, such differences could affect the structure of the research concepts. Thus, exploratory factor analysis (EFA) was conducted in order to empirically validate the structure of research dimensions and to test the research instrument, within the context of the research population of South-Eastern Europe and Serbia.

Using the maximum likelihood method we identified four factors, which account for 67% of the variance present in the data. The scree plot of the results of the analysis is shown in Figure 3 . As the figure shows, we retained the factors above the inflection point.

Figure 3 . Scree plot of the EFA results.

The communalities for the variables loading into the factors are shown in Table 3 and the questions corresponding to our variables are listed in Table 4 . Initial communalities are estimates of the proportion of variance in each variable accounted for by all components (factors) identified, while the extraction communalities refer to the part of the variance explained by the four factors extracted. The model explains more of the variance then the initial factors, for all but the last variable.

Table 3 . Communalities.

Table 4 . Questions that build our constructs.

More detailed results of the EFA for the four factors, are shown in Table 5 . The unique loadings of specific items measured with the different questions in the questionnaire on the factors identified are shown in the pattern matrix (Table 6 ). As the table shows, each factor is loaded into by items that were designed to measure a specific construct and there are no cross-loadings. The first factor corresponds to job characteristics, second to job satisfaction, third to job involvement and the final to organizational commitment. The correlation between the factors is relatively low and shown in Table 7 .

Table 5 . Total variance explained by the dominant factors.

Table 6 . Pattern matrix for the factors identified.

Table 7 . Factor correlation matrix.

3.2. Confirmatory Factor Analysis

In the next part of our analysis we used Structural Equation Modeling to validate and improve a part of the model proposed by Locke and Latham (2004) that focuses on work characteristics, job satisfaction, organizational commitment and job involvement.

Although the EFA suggest the existence of four, not five, dominant factors in the model, diverging from the model proposed by Locke and Latham (2004) , in our initial experiments we used their original model, shown in Figure 4A , taking into account also organizational policies and procedures.

Figure 4 . The evolution of our model (the path coefficients are standardized): (A) the initial model based on Locke and Latham (2004) , (B) no partial mediation, and (C) partial mediation introduced.

In this (default) model, the only independent variable are the job characteristics. The standardized regression coefficients shown in Figure 4A (we show standardized coefficients throughout Figure 4 ) indicate that the relationship between the satisfaction and organizational commitment seems to be stronger (standard coefficient value of 0.54) than the one between satisfaction and involvement (standard coefficient value of 0.37). The effect of job characteristics and policies and procedures on the employee satisfaction seems to be balanced (standard coefficient values of 0.31 and 0.30, respectively).

The default model does not fit our data well. The Comparative Fit Index (CFI) for this model is 0.759, the Tucker-Lewis Index (TLI) is 0.598, while the Root Mean Square Error of Approximation (RMSEA) is 0.192.

A more detailed analysis of the model revealed that it could indeed (as the EFA suggests) be improved by eliminating the organizational policies and procedures variable, as it has a high residual covariance with job involvement (−3.071) and organizational commitment (−4.934).

We therefore propose to eliminate the “Organizational policies and procedures” variable from the model. Dropping the variable resulted in an improved model shown in Figure 4B . The improved model fits the data better, but the fit is still not good ( RMSEA = 0.125, CFI = 0.915 and TLI = 0.830).

We then hypothesized that job involvement influences organizational commitment, yielding the final model tested in this study (Figure 4C ). This model turned out to be the one that fits our data very well ( RMSEA = 0.000, CFI = 1 and TLI = 1.015).

4. Mediation Analysis

In the final part of the study we conducted the mediation analysis, to understand the relationship between job satisfaction, job involvement and organizational commitment. We used bootstrapping, based on 5000 samples and the confidence interval of 95%.

We started with a model that contains just one relation between satisfaction and commitment (Figure 5A ), then tested for full mediation (Figure 5B ) and finally partial mediation as indicated in out proposed model (Figure 5C ). The unstandardized, direct effect regression weights and the p -values obtained in these experiments are shown in Table 8 . As the p -values show, all the connections in our three models are significant and that they remain so throughout the evolution of the model. Therefore, job involvement mediates the influence of satisfaction on organizational commitment, but this is a partial mediation and a major part of the effect of satisfaction on the organizational commitment is achieved directly.

Figure 5 . Mediation analysis models. (A) , Model 1; (B) , Model 2; (C) , Model 3.

Table 8 . Mediation analysis regression weights.

5. Discussion

We conducted an empirical study aimed at exploring the relationship between employee satisfaction, job involvement, organizational commitment, work characteristics and organizational policies and procedures.

Based on the relevant scientific literature, recent studies in the area and the integrative model of work motivation of Locke and Latham (2004) , we have formulated an initial conceptual model for our research and hypothesized the connections between the relevant variables. The initial model has been improved iteratively, with the goal of increasing its fit to the empirical data collected in the study.

Starting from the model proposed by Locke and Latham (2004) we determined that their model does not fit our experimental data well and that we observe a connection between job involvement that is not present in their model. In addition, our data does not support the hypothesis that organizational procedures and policies affect employee satisfaction in the organizations considered. As a result we propose a 4 factor model shown in Figure 4C for the relationship between the concepts of work characteristics, employee satisfaction, job involvement and organizational commitment.

We analyzed the results of the study based on 1 general and 5 specific hypotheses. The research confirms that there is a link between work characteristics and job satisfaction (H1), but that it is weak, suggesting that a dominant effect of the material factors of motivation exists.

We have also determined that there is a connection between the rules and procedures variable (H2) and the rest of the variables, indicating that it should be considered in future studies, but that the constructs need to be operationalized better.

The third specific hypothesis (H3) that job satisfaction has a positive relationship with job involvement has been confirmed and we have observed that extrinsic work motivation has a stronger effect than intrinsic, which can be explained by low wages and insufficient funds for everyday life. Other research has confirmed this link ( Govender and Parumasur, 2010 ) and showed that most of the employee motivation dimensions have significant links with the dimensions of job involvement (9 out of 10 pairs).

The fourth specific hypothesis (H4 - Job satisfaction will have a positive relationship with organizational commitment) has also been confirmed and we can conclude that a positive relationship exists, which is in line with recent research in this area. The subscale focused on identification with the organization is strongly connected with both intrinsic and extrinsic factors of job satisfaction, but this cannot be said for the subscale focused on organizational attachment. Our research supports the existence of a weak connection between job satisfaction and organizational attachment, both when intrinsic and extrinsic satisfaction is considered as a motivator. A study of work motivation and organizational commitment conducted in Bulgaria (Serbia's neighbor) showed that extrinsic factors are key sources of organizational commitment ( Roe et al., 2000 ), as well as that job involvement and the chances for the fulfillment o higher-order needs pay a very important part in the motivation of the employees.

One of the reasons for such a result can be the economic situation in Serbia, which has a severely detrimental effect on work motivation. The transition and economic crisis is accompanied by the shrinking purchasing power of the population, higher unemployment rates and a rising disparity in the salary levels, all of which causes the adjustment of the behavior of the employees to these conditions. Under the economic conditions that exist in Serbia it is to be expected that the individuals will put more value on the salary and advancement prospects than on the opportunities for growth and development, which do not present a direct financial benefit.

The research did not reveal any differences with respect to the sex of the participants, regardless of the variable considered. Other research has not reached a consensus on the matter, as a part of the studies suggests that there are differences in job involvement between men and women ( Lodahl and Kejnar, 1965 ; Hall and Mansfield, 1975 ; Rabinowitz and Hall, 1977 ; Saal, 1978 ).

Regarding the ownership of the organizations examined, the research revealed statistically significant differences between the employees working in public and private companies, i.e., that the participants working in the private sector scores significantly higher on every variable except work characteristics, meaning that they are more committed to work, more involved and more satisfied.

In addition, we have determined that there are statistically significant differences when it comes to the position of the employees in the organization's hierarchy, i.e., whether they occupy a managerial or a non-managerial position. The study shows that managers have higher scores for organizational attachment, organizational commitment, intrinsic motivators, extrinsic motivators, job satisfaction and job involvement. We can, therefore, conclude that the managers are more satisfied with their work in general and that they are more committed to the organization than other employees. This can be explained by the fact that, due to the nature of the work they do, they are able to make decisions, they have a more varied job and have better material and non-material rewards. A more detailed analysis of the commitment of the managers, focused on identifying if we are dealing with normative, continuous or affective commitment would provide more insight into the structure and nature of the relationship between the organization and the individual.

Considering the type of the company (manufacturing or service) our study showed that the participants working in manufacturing companies are the ones who identify more with the company, are more committed to the company, more satisfied with their work and more involved.

Our study also identified a significant difference with respect to the vocation of the participants, showing that those with training in humanistic sciences awarded most positive scores to the characteristics of their work, while the opposite was true for those of technical vocations.

The part of our analysis focused on the age of the participants revealed that there is a statistically significant connection between the age and job satisfaction, where the older the employee, the less satisfied he/she is with their job and cares less about the characteristics of work. A reason for such a result could again be found in the economic situation of Serbia and the high unemployment rate (over 20%), causing the younger people to be satisfied with the simple fact that they managed to get a job, rather than being satisfied with the job itself. Another reason could be the difference in the perception of desires and possibilities that exists between the younger and older employees.

The years with the company are negatively linked with employee satisfaction, as well as job characteristics, which is in line with the effect discussed in the previous paragraph, as those with more time spent in the company are less satisfied with their job and care less about the characteristics of their work.

Considering the level of education of the participants, our study showed that the more educated the employees are, the less involved they are in their work and that they seem to care more about the characteristics of their work.

Our research showed that links exist between all the variables studied and that the weakest of these links is between work characteristics and other constructs. Of those, the weakest link in turn is the link between the work characteristics and the subscale of organizational commitment related to the identification with the organization. Thus, we can conclude that work characteristics do not exhibit a significant influence on whether and to what extent the employee will identify with the organization in which he/she works, i.e., whether he/she will be committed to the organization.

A moderate to strong connection exists between organizational commitment and job satisfaction, which is in line with the results of numerous previous studies ( Currivan, 1999 ; Meyer et al., 2002 ; Malhotra and Mukherjee, 2004 ; Saari and Judge, 2004 ; Chen, 2007 ; Falkenburg and Schyns, 2007 ; Moynihan and Pandey, 2007 ; Getahun et al., 2008 ; Colakoglu et al., 2010 ; Yücel, 2012 ; Fu and Deshpande, 2014 ).

Our study confirms the existence of a strong connection between job satisfaction and job involvement ( Moynihan and Pandey, 2007 ; Wegge et al., 2007 ; Griffin et al., 2010 ; Raymond and Mjoli, 2013 ; Zopiatis et al., 2014 ). Many studies have been carried out in an attempt to examine and define the relationship between job involvement and organizational commitment. Our results are in line with previous studies, which diverge only on the strength of the connection, ranging from moderate to strong ( Blau and Boal, 1989 ; Brewer and Lok, 1995 ; Sjöberg and Sverke, 2000 ; Brooks and Swailes, 2002 ; Toga, 2011 ). Our study provides more evidence for the existence of such a relationship, which is moderately strong. Such a relationship does not exist in the integrative model of Locke and Latham (2004) , which served as a starting point for this study.

In addition, we have determined that job involvement has a mediating role between job satisfaction and organizational commitment. Job involvement mediates the influence of satisfaction on organizational commitment, but this is a partial mediation and a major part of the effect of satisfaction on the organizational commitment is achieved directly.

The construct related to organizational policies and procedures seems not to have significant bearing on employee satisfaction, based on the data collected. Two plausible explanations exist for this. The first is the fact that this was the only construct in our study for which a suitable standard questionnaire could not be found, so one had to be constructed specifically, meaning that the construct should be operationalized better in future studies and that this represents the limitation of our study. The other is the fact that in Serbia, as in most transition economies, the lack of suitable institutional and legislative framework at the national level is often accompanied with lax, not clearly defined and even less adhered-to business policies and procedures. In such a state of affairs, the employees seldom have a relatively clear idea of what the policies and procedures of their organization are and are unable to evaluate them with respect to those of other organizations, making this construct very hard to measure. At the same time it can be argued that, in such a situation, the policies and procedures are not perceived by the employees as a significant factor of their organizational behavior and indeed do not affect their work motivation. Whatever the reason, the relationship of policies and procedures to the other variables of work motivation within the transition economies merits further investigation.

Author Contributions

JĆ and SM designed the study. JĆ collected the data and conducted the bulk of the research. MD and DĆ conducted the statistical analysis and modeling. All authors took part in the manuscript writing, led by JĆ and DĆ.

The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme FP7/2012-2016/ under REA grant agreement n° 295220.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: work, job, satisfaction, involvement, employee, commitment, organizational, behavior

Citation: Ćulibrk J, Delić M, Mitrović S and Ćulibrk D (2018) Job Satisfaction, Organizational Commitment and Job Involvement: The Mediating Role of Job Involvement. Front. Psychol . 9:132. doi: 10.3389/fpsyg.2018.00132

Received: 07 November 2017; Accepted: 29 January 2018; Published: 16 February 2018.

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Copyright © 2018 Ćulibrk, Delić, Mitrović and Ćulibrk. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Milan Delić, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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JOB SATISFACTION AND EMPLOYEE PERFORMANCE: A THEORETICAL REVIEW OF THE RELATIONSHIP BETWEEN THE TWO VARIABLES

In today's increasing competitive environment, organizations recognize the internal human element as a fundamental source of improvement. On one hand, managers are concentrating on employees' wellbeing, wants, needs, personal goals and desires, to understand the job satisfaction. And on the other hand, managers take organizational decisions based on the employees' performance. The purpose of this study is to identify the factors influencing job satisfaction and the determinants of employee performance, and accordingly reviewing the relationship between them. This study is an interpretivist research that focuses on exploring the influence of job satisfaction on employee performance and vice, the influence of employee performance on job satisfaction. The study also examines the nature of the relationship between these two variables. The study reveals the dual direction of the relationship that composes a cycle cause and effect relationship, so satisfaction leads to performance and performance leads to satisfaction through number of mediating factors. Successful organizations are those who apply periodic satisfaction and performance measurement tests to track the level of these important variables and set the corrective actions.

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Job satisfaction and its related factors: A questionnaire survey of hospital nurses in Mainland China

The widespread nursing shortage is of concern in Mainland China and globally. Factors underpinning the increased mobility of the nursing workforce and their contribution to nurses’ turnover thus merit attention. Understanding nurses’ job satisfaction is important, as this is a key factor in nurses’ turnover.

The study aimed to explore nurses’ views and experience regarding different components of their working lives in Mainland China.

A cross-sectional survey design was selected and 512 nurses working in the medical and surgical departments in two teaching hospitals in Beijing completed questionnaires yielding a response rate of 81%.

More than half of nurses (53.7%; n =275) were satisfied or very satisfied with their jobs and 15% ( n =77) felt moderate to extreme occupational stress. The majority of the sample reported a high level of organizational commitment (63.7%; n =326) and professional commitment (85.9%; n =440) and only 5.9% ( n =30) and 10.0% ( n =51), respectively reported role conflict and role ambiguity often or very often. Nurses with a diploma or associate degree reported greater professional commitment and a lower level of role conflict than those with a bachelor degree ( p <0.05), but there were no significant differences in job satisfaction, organizational commitment, occupational stress and role ambiguity by educational programme ( p >0.05).

Conclusions

Hospital nurses’ positive feelings regarding their working lives may be influenced by developments in the health care system and the nursing profession in Mainland China. Nurses’ educational level is an influencing factor on nurses’ views and experiences of their working lives with the findings suggesting the need to develop a clinical career ladder for nursing staff in Mainland China.

What is already known about the topic?

• • The current worldwide shortage of nurses is of great concern and job satisfaction among nurses has been identified as a key factor in nurses’ recruitment and retention.
• • Several major factors are associated with job satisfaction of nurses, such as organizational commitment, occupational stress, professional commitment, role conflict and role ambiguity.
• • Much research has been conducted on nurses’ job satisfaction and related factors in western countries and some Asian countries.

What this paper adds

• • The developments in the health care system and nursing profession could influence nurses’ feelings towards their working lives.
• • National culture should be considered in understanding nurses’ views and experiences regarding different components of their working lives.

1. Introduction

The widespread nursing shortage and nurses’ high turnover has become a global issue ( Kingma, 2001 ). The nursing workforce in Mainland China also faces similar challenges in recruitment and retention as a consequence of China entering the World Trade Organization, which has opened their labour market. Job mobility has also been fuelled by more relaxed immigration policies which has meant an increase in the number of Chinese nurses being recruited to western countries where salaries and opportunities are better ( Ho, 1995 ). Recruitment and retention of nurses are persistent problems associated with job satisfaction. There is an urgent need for rigorous research regarding job satisfaction and related factors to inform the development of good nurse employment strategies in Mainland China.

2. Background and literature review

2.1. job satisfaction and its relating factors.

Job satisfaction is defined as all the feelings that an individual has about his/her job ( Spector, 1997 ). Researchers have attempted to identify the various components of job satisfaction, measure the relative importance of each component of job satisfaction and examine what effects these components have on workers’ productivity ( Lu et al., 2005 ).

A range of findings derived from quantitative as well as qualitative studies has been reported in the literature regarding sources of job satisfaction among nurses. These sources include working conditions ( Adamson et al., 1995 ; Nolan et al., 1995 ), interactions with patients/co-workers/managers ( Lee, 1998 ; Aiken et al., 2001 ), work itself ( Lundh, 1999 ; Adams and Bond, 2000 ), remuneration ( Price, 2002 ; Wang, 2002 ), self-growth and promotion ( Tzeng, 2002a , Tzeng, 2002b ), praise and recognition ( Nolan et al., 1995 ; Lundh, 1999 ), control and responsibility (Lee, 1998; Price, 2002 ), job security ( Nolan et al., 1995 , Nolan et al., 1998 ) and leadership styles and organizational policies (Lee, 1998; Tzeng, 2002a , Tzeng, 2002b ).

Job satisfaction among nurses has been identified as a key factor in nurses’ turnover with the empirical literature suggesting that it is related to a number of organizational, professional and personal variables ( Lu et al., 2005 ). Organizational commitment refers to identification with and loyalty to the organization and its goals ( Blau and Boal, 1987 ). Organizational commitment has been found to be positively related to job satisfaction of hospital nurses ( Blegen, 1993 ; Al-Aameri, 2000 ) and could explain 41% of the variance in job satisfaction ( Knoop, 1995 ).

Professional commitment is a person's involvement, pledge, promise or resolution towards his/her profession ( Fang, 2001 ). It has an incremental effect on a person's intention to leave the organization ( Blau and Lunz, 1998 ) and is positively associated with the job satisfaction of nurses ( Lu et al., 2000 ; Jones, 2000 ).

Occupational stress has also been found to be a major factor related to the job satisfaction of nurses ( Blegen, 1993 ) as well as role conflict and role ambiguity ( Tovey and Adams, 1999 ). Role conflict occurs as the nurse attempts to satisfy a number of incompatible demands arising from other people's expectations of his/her role ( Rosse and Rosse, 1981 ). Inadequate or confused information about what work the nurse should cover, the limits of the role and other people's expectations of how the nurse's role fits in with their expectations produce role ambiguity ( Hingley and Cooper, 1986 ).

2.2. Nursing in Mainland China

2.2.1. changes in health care policies.

With ongoing economic reform, China has made some major policy changes in health care. The government has liberalized the private ownership of health facilities and private clinical practices and public hospitals have been partially freed from strict governmental labour market controls ( Ho, 1995 ; Hsiao, 1995 ). Job mobility has become a reality and pressures are building for higher rewards for the country's health care professional workforce ( Ho, 1995 ).

Additionally, nursing model reforms have impacted on the delivery of health care. The patient-centred holistic nursing care model has gradually replaced the traditional disease-centred nursing care model. However, primary nursing has only been introduced in leading hospitals because of the nurse shortage and a lack of appropriate knowledge and skills in the nursing workforce ( Ministry of Health, China, 2003 ).

These developments have coincided with a growing recognition of the professional status of nurses. In the 1980s, the Government reaffirmed that like medicine nursing was an independent profession that required well-qualified personnel with nurses being awarded a protected title by the National Ministry of Health ( Li, 2001 ). At present, there are three levels of basic nursing education in Mainland China: diploma programmes delivered by health schools, associate degree programmes mainly provided by colleges of nursing and bachelor degrees through university-based education.

2.2.2. Nursing shortage and turnover

A nursing shortage has been reported in Mainland China for many years, but in recent years it has become greater. According to the Ministry of Health, China (2003) , the number of registered nurses was 10:10,000 of the population 1997–2002. Further, the turnover of nurses with an associate degree or a bachelor degree is more serious than that of nurses with a diploma ( Wu, 1999 ). It suggests that Mainland China needs to increase the number of nurses, especially well-educated nurses, however, the increased mobility of the nursing workforce is exacerbating the situation and highlights the need to identify factors which contribute to nurses’ turnover ( Lu et al., 2005 ).

While the literature indicates common issues across the world, it is possible that different issues have greater significance in different countries due to the social context of particular labour markets. The current shortage of nurses in Mainland China highlights the importance of understanding nurses’ job satisfaction and related factors so that health care organizations can implement effective interventions to improve the retention of their nursing workforce. The little available research has significant methodological limitations and no research which directly addresses the topic has been conducted in Mainland China ( Yang and Cheng, 2004 ). In consequence, this study addressed an important gap in the available literature.

3.1. Aim and objectives

The study aimed to explore nurses’ views and experiences regarding different components of their working lives in Mainland China. The following objectives were set:

• • To describe job satisfaction, organizational commitment, professional commitment, occupational stress, role conflict and role ambiguity of nurses;
• • To compare job satisfaction, organizational commitment, professional commitment, occupational stress, role conflict and role ambiguity of nurses across the three educational programmes (diploma, associate degree and bachelor degree programmes).

3.2. Research design and sample

A cross-sectional survey design utilizing questionnaires was selected to fulfil the research objectives. A total population of 632 nurses working in the medical and surgical departments in two teaching hospitals in Beijing were surveyed. Five hundred and twelve nurses completed and returned a self-completed questionnaire representing a response rate of 81% (diploma: n =230, a response rate of 77.4%; associate degree: n =232, a response rate of 82.6%; bachelor degree: n =50, a response rate of 92.6%).

3.3. Instruments

The following instruments were utilized:

• Job Satisfaction Scale ( Warr et al., 1979 ): a five-point Likert type scale (1=very dissatisfied, 5=very satisfied) with 15 items. The coefficient alpha was 0.85–0.88 and test–retest correlation coefficient was 0.63 for 6-month period ( Warr et al., 1979 ). The Cronbach's alpha was 0.89 in this study.
• Organisational Commitment Scale ( Mowday et al., 1979 ): a five-point Likert type scale (1=strongly disagree, 5=strongly agree) with 15 items. Coefficient alphas ranged from 0.82 to 0.93 with a median of 0.90 and test–retest reliability coefficients were 0.53, 0.63 and 0.75 for 2-, 3- and 4-month periods, respectively ( Mowday et al., 1979 ). The Cronbach's alpha was 0.85 in this study.
• Nurses’ Occupational Stress Scale ( Hingley & Cooper, 1986 ): a five-point Likert type scale (1=no pressure, 5=extreme pressure) with 24 items. The Cronbach's alpha was 0.92 in this study.
• Professional Identification Scale ( Brown et al., 1986 ): a five-point Likert type scale (1=never, 5=very often) with 10 items. Items analysis of the scale yielded a Cronbach's alpha of 0.71 and factor analysis yielded an oblique solution ( Brown et al., 1986 ). The Cronbach's alpha was 0.82 in this study.
• Role Conflict and Ambiguity Scale ( Rizzo et al., 1970 ): a five-point Likert type scale (1=never, 5=very often) with 14 items. Cronbach's alphas were reported 0.816–0.82 for role conflict and 0.78–0.808 for role ambiguity ( Rizzo et al., 1970 ). In this study the Cronbach's alphas were 0.81 and 0.85 for role conflict and ambiguity, respectively.
• Biographical details were collected regarding personal profile and included nursing qualifications, length of time working in current hospital and educational level.

3.3.1. Instrument translation

In order to avoid the problems inherent in translation, this study used a combination of Brislin (1970) model for translating and back-translating instruments and committee approach. One bilingual expert translated the instruments from English to Chinese and a second bilingual expert back-translated blindly. A panel of three experts in the area of health care workforce management measured the face validity of the translated questionnaire.

3.4. Ethical considerations and negotiation of access

Ethical approval was gained from the Peking University's Research Ethics Committee. The main ethical issues were respondents’ right to self-determination, anonymity and confidentiality. The questionnaires with a participant information sheet on the nature of the study and a separate envelope were distributed to staff nurses working in medical and surgical departments in two teaching hospitals of Peking University. Completed questionnaires were recruited in sealed envelopes via a collection box places in ward offices. The questionnaire data were kept confidential and respondents were assured of their right to withdraw at any time. The names of the respondents were not recorded on the questionnaire, thus rendering the data anonymous.

3.5. Analysis of data

Data were entered and processed using the Statistical Package for the Social Sciences (SPSS) software, the English version 11.5. This study used descriptive statistics, χ 2 -test and Kruskal–Wallis test to analyse the data.

4. Findings

4.1. characteristics of respondents.

All respondents were female and were predominately between 21 and 35 years old ( n =463, 90.4%), with half being married ( n =256, 50.0%). The majority of respondents had a diploma or associate degree ( n =230, 44.9%, n =232, 45.3%, respectively) while less than 10.0% held a bachelor degree ( n =50, 9.8%). Slightly more respondents worked in medical wards ( n =272, 53.1%) compared with surgical wards ( n =240, 46.9%). Half of respondents had worked in their current hospital for 5 years or more ( n =324, 63.3%). In addition, more than two-thirds of respondents expressed their intention to leave the current hospitals ( n =368, 71.9%), with half reporting that nursing was their first choice of career ( n =278, 54.3%).

More than half of respondents reported that a system of primary care delivery was conducted in their wards ( n =300, 58.6%) while about a quarter reported that team nursing was used ( n =127, 24.8%). The majority of respondents had individualized written nursing care plans for each patient ( n =471, 92.0%) and for common nursing care problems/nursing diagnoses ( n =438, 85.5%). Almost all respondents reported that their hospitals had clearly stated standards and policies for nursing practice ( n =506, 98.8%) while over three-quarters thought that the Ministry of Health also produced such standards and policies ( n =398, 77.7%) and had regulatory power over nurses ( n =389, 76.0%).

Regarding respondents’ characteristics across the three educational programmes, there was a significant difference in age ( p <0.001). Bachelor degree nurses were oldest (mean=32.2 years, SD=5.5), followed by associate degree nurses (mean=28.2 years, SD=5.1), with diploma nurses having the lowest mean age (mean=26.5 years, SD=5.6). Similarly, bachelor degree nurses (mean=11.2 years, SD=6.3) had worked longer in current hospitals ( p <0.001) than associate degree or diploma nurses (mean=8.0 years, SD=5.6; mean=7.0 years, SD=5.6, respectively). Furthermore, the proportion of married nurses in the bachelor degree group (72.0%) was significantly more than that in the associate degree or diploma groups ( p <0.001). More than half of diploma nurses (62.2%) considered nursing as their first career choice, which was significantly higher than that of associate degree (49.1%) or bachelor degree nurses (42.0%). There was no significant difference in nurses’ intention to leave across the three nursing educational programmes ( p >0.05) (see Table 1 ).

Comparisons of characteristics of respondents by educational programme

* p <0.01, ** p <0.001.

4.2. Respondents’ job satisfaction

Regarding overall job satisfaction, more than half of respondents were satisfied ( n =275, 53.7%). Most respondents were satisfied or very satisfied with their immediate manager ( n =416, 81.2%) and their fellow workers ( n =413, 80.7%). On the other hand, almost three quarters of the sample felt dissatisfied or very dissatisfied with the rate of pay for nurses ( n =373, 72.9%) (see Table 2 ).

Frequency and percentage of each item in the job satisfaction scale

Although nurses with a bachelor degree (mean rank=234.92) reported a lower level of job satisfaction compared to those with an associate degree (mean rank=259.98) or diploma (mean rank=257.68), there was no significant difference in total job satisfaction of respondents from the different educational programmes ( p >0.05). However, nurses with a diploma (mean rank=264.05) were more likely to be satisfied with their fellow workers ( χ 2 =10.005, p <0.01) than those with an associate degree (mean rank=259.73) or bachelor degree (mean rank=204.72). Regarding other items of job satisfaction, there were no significant differences across the three nursing programmes ( p >0.05).

4.3. Respondents’ organizational commitment

Almost two-thirds of respondents reported a high-level of organizational commitment ( n =326, 63.7%). More than two-thirds of the sample agreed or strongly agreed that they really cared about the fate of their current hospitals ( n =369, 72.1%) and reported that they were willing to put in a great deal of effort beyond that normally expected in order to help their hospitals be successful ( n =366, 71.5%). Although more than half of the respondents disagreed or strongly disagreed that it would take very little change in their present circumstances to cause them to leave their current hospitals ( n =301, 58.8%) or to decide that working for these hospitals was a definite mistake on their part ( n =297, 58.0%), more than half agreed or strongly agreed that they could just as well be working for a different hospital as long as the type of work was similar ( n =271, 52.9%) (see Table 3 ).

Frequency and percentage of each item in the organizational commitment scale

There were no significant differences in total organizational commitment ( p >0.05) although nurses with a bachelor degree reported a lower level (mean rank=242.46) compared to those with an associate degree (mean rank=260.51) or diploma (mean rank=255.51). However, diploma nurses (mean rank=272.87) were more likely to agree that they would accept almost any type of job assignment in order to keep working for their current hospitals ( χ 2 =6.378, p <0.05) than those with an associate degree (mean rank=246.13) or bachelor degree (mean rank=229.34). In addition, diploma nurses (mean rank=240.40) were more likely to report that it would take very little changes in their present circumstances to cause them to leave their current hospitals ( χ 2 =7.171, p <0.05) compared to associate degree (mean rank=273.23) or bachelor nurses (mean rank=252.91). There were no significant differences in other items of organizational commitment across the three educational programmes ( p >0.05).

4.4. Respondents’ occupational stress

Just under two-thirds of respondents reported experiencing light to moderate stress at work ( n =311, 60.8%) while one-quarter reported no to light stress ( n =124, 24.2%), followed by less than one-sixth reporting moderate to extreme stress ( n =77, 15.0%). Scores of moderate to extreme stress reported by respondents related to workload ( n =398, 77.8%), time pressures and deadlines ( n =335, 65.4%), difficult patients ( n =309, 60.4%), staff shortages ( n =308, 60.1%) and involvement with life and death situations ( n =276, 53.9%) (see Table 4 ).

Frequency and percentage of each item in the occupational stress scale

There were no significant differences in total occupational stress across the three educational programmes ( p >0.05), although nurses with an associate degree (mean rank=260.05) reported experiencing more stress than those with a bachelor degree (mean rank=253.52) or diploma (mean rank=253.57). However, bachelor degree nurses (mean rank=292.63) were more likely to report experiencing stress regarding time pressures and deadlines ( χ 2 =6.738, p <0.05) than diploma (mean rank=263.78) or associate degree nurses (mean rank=241.50). Similarly, bachelor degree nurses (mean rank=284.05) were more likely to report experiencing stress regarding uncertainty about the degree or area of their responsibilities ( χ 2 =10.259) than associate degree (mean rank=271.92) or diploma nurses (mean rank=234.95).

In addition, regarding poor quality of supporting staff bachelor degree nurses (mean rank=281.30) were also more likely to report experiencing stress ( χ 2 =6.522, p <0.05) than associate degree (mean rank=268.10) or diploma nurses (mean rank=239.41). However, bachelor degree nurses (mean rank=189.45) were less likely to report experiencing stress regarding security of employment ( χ 2 =17.889, p <0.001) than associate degree (mean rank=248.08) or diploma nurses (mean rank=279.57). Regarding other aspects of stress, there were no significant differences across the three programmes ( p >0.05).

4.5. Respondents’ professional commitment

Most respondents reported a high-level of professional commitment ( n =440, 85.9%). The majority of respondents reported that they never or seldom: tried to hide belonging to the nursing profession ( n =466, 91.0%), were annoyed to say that they were members of the nursing profession ( n =416, 81.3%) or criticized the nursing profession ( n =398, 77.8%). However, only one-third reported that they were glad to belong to the nursing profession often or very often ( n =167, 32.6%) (see Table 5 ).

Frequency and percentage of each item in the professional commitment scale

Nurses with a bachelor degree (mean rank=204.30) reported a lower level of professional commitment ( χ 2 =8.323, p <0.05) compared to those with an associate degree (mean rank=254.03) or diploma (mean rank=270.33). Bachelor degree nurses (mean rank=190.11) were more likely to criticize the nursing profession ( χ 2 =12.788, p <0.01) than associate degree (mean rank=262.76) or diploma nurses (mean rank=264.62). In contrast, diploma nurses (mean rank=268.27) were more likely to be glad to belong to the profession ( χ 2 =7.765, p <0.05) than associate degree (mean rank=255.57) or bachelor degree nurses (mean rank=206.69). There were no other significant differences relating to other items of professional commitment across the three programmes ( p >0.05).

4.6. Respondents’ role conflict and role ambiguity

The majority of respondents reported a low-level of role conflict and role ambiguity ( n =482, 94.1%; n =461, 90.0%, respectively). More than three-quarters of respondents never or seldom had to ‘buck’ a rule or policy in order to carry out an assignment ( n =439, 85.7%), had worked with two or more groups who operated quite differently ( n =391, 76.4%) or received incompatible requests from two or more people ( n =380, 74.2%). Almost four-fifths of respondents reported that they knew often or very often what their responsibilities were ( n =447, 87.3%). Around three-quarters of respondents reported feeling certain about how much authority they had and felt that they had clear, planned goals and objectives for their jobs ( n =391, 76.4%; n =374, 73.1%, respectively) (see Table 6 ).

Frequency and percentage of each item in the role conflict and role ambiguity scale

Nurses with a bachelor degree (mean rank=298.81) reported greater role conflict ( χ 2 =6.174, p <0.05) compared to those with an associate degree (mean rank=260.63) or diploma (mean rank=243.13). There were no significant differences in role ambiguity across the three programmes ( p >0.05). Bachelor degree nurses (mean rank=286.26) were more like to report receiving incompatible requests from two or more people ( χ 2 =6.568, p <0.05) than associate degree (mean rank=266.22) or diploma nurses (mean rank=240.22). Bachelor degree nurses (mean rank=294.57) were also more likely to report doing things that were likely to be accepted by one person and not accepted by others ( χ 2 =7.591, p <0.05) than associate degree (mean rank=263.82) or diploma nurses (mean rank=240.84).

In addition, bachelor nurses (mean rank=307.08) were more likely to report receiving an assignment without adequate resources and materials to execute it ( χ 2 =10.810, i <0.01) than associate degree (mean rank=263.41) or diploma nurses (mean rank=238.54). Regarding other items of role conflict and role ambiguity, there were no differences across the three programmes ( p >0.05).

5. Discussion

The sample in this local questionnaire survey was limited to nurses working in teaching hospitals in Beijing. Thus, the generalization of the findings needs to be treated with caution.

5.1. Hospital nurses’ job satisfaction

In contrast to Wang's (2002) survey of nurses working in a hospital in Beijing where nurses reported more dissatisfaction than satisfaction, the study found that more than half of respondents were satisfied with their jobs ( n =275, 53.7%). Interestingly, this study's findings are similar to those of other studies of the job satisfaction of nurses in the USA ( Blau and Lunz, 1998 ; Aiken et al., 2001 ), the UK ( Price, 2002 ), Singapore ( Fang, 2001 ), Hong Kong ( Siu, 2002 ) and Taiwan ( Lu et al., 2002 ; Tzeng, 2002a ) despite the health care systems being very different from that of Mainland China.

A possible explanation for such similarity may lie with changes in the labour market in Mainland China, which has become more open during the last 5 years and increasingly similar to that in western countries. An open labour market has brought new pressures and challenges for hospital managers. Nurses’ job satisfaction has received increasing attention and enhancing nurse job satisfaction has been emphasized as a major strategy to recruit and retain qualified nurses ( Sun et al., 2001 ; Bao et al., 2004 ).

It is also possible that the development of nursing, particularly the adoption of the patient-centred primary nursing care model has had an effect on nurses’ job satisfaction ( Bond et al., 1990 ; Thomas and Bond, 1991 ). In Mainland China primary nursing has experienced more than 10-years of development mainly in leading hospitals ( Ye et al., 1999 ), which include the data collection sites in the study.

5.2. Hospital nurses’ organizational commitment

The findings of nurses’ strong organizational commitment in the study is inconsistent with Knoop's (1995) survey in Canada, which found that nurses had a low level of organizational commitment. However, most of the study's respondents expressed their intention to leave their current hospitals. Such ambivalent findings might be explained by the influence of culture. Glazer et al. (2004) have suggested that people's understanding of organizational commitment could be affected by their national culture. Chang (1999) further pointed out that employees in Asian countries are more likely than employees in Western countries to expect job security from their employers as part of their psychological contract of employment. These employees, in turn, are more committed when they feel that their employers have fulfilled this commitment.

Therefore, nurses’ high level of commitment to their hospitals does not remove the potential of turnover. Indeed, organizational commitment due to the communal nature of a culture may not contribute to nurses’ retention, as nurses are encouraged to build up an equally strong commitment to their new organization following a job change.

5.3. Hospital nurses’ occupational stress

Two-thirds of respondents reported slight to moderate pressure relating to occupational stress ( n =311, 60.8%), which is similar to the findings in Dailey's (1990) study in the USA and Fang's (2001) study in Singapore. Cox (1987) suggested that stress resides in the person's perception of the balance or transaction between the demands on him/her and his/her ability to cope with these. Thus occupational stress exists in people's recognition of their inability to cope with demands relating to work ( Cox, 1985 ) and the findings suggest that the majority of the sample had the abilities to cope with the work demands placed upon them.

Hingley and Cooper (1986) pointed out that for all individuals competence is a primary need at work, with incompetence being a major source of job stress due to its thwarting the individual to perform effectively or to feel effective. Nurses’ improved professional competence might therefore be associated with their lower occupational stress. In this study, some characteristics of the respondents including age, length of working time and educational level may be a proxy of their higher professional competence. For example, half of respondents had worked in their current hospital for 5 years or more ( n =324, 63.3%). In general, they were proficient in nursing techniques and skills and were able to resolve problems independently at work. Further, most respondents were 35 years old or younger ( n =473, 92.4%) and half had an associate degree or bachelor degree ( n =282, 55.1%). Therefore, it is possible that they had abilities to cope with new situations and technology.

Another possible explanation lies with respondents’ good interpersonal relationships at work. For example, most respondents reported that they were satisfied or very satisfied with their fellow workers ( n =413, 80.7%) and immediate manager ( n =416, 81.2%). The nature and quality of relationships at work has been identified as a major source of occupational stress ( Greenburg, 1980 ). Hingley and Cooper (1986) also suggested that poor relationships with colleagues and superiors are an important source of stress for nurses. This was highlighted in Bradley and Cartwright (2002) study which found that nurses who perceived more support from managers were less likely to experience job stress ( r =−0.12, p <0.05) although the extent to which this applies to Mainland China is uncertain as no equivalent research has been published regarding Chinese nurses.

Regarding the main stressors, such as workload, time pressures and deadlines and staff shortages, the findings are consistent with previous studies in China ( He et al., 2001 ; Dai and Wang, 2002 ; Zhao et al., 2002 ). Furthermore, nurses’ workload has also been emphasized as a major work-related stressor in similar studies conducted in other countries ( Aiken et al., 2001 ; Lambert et al., 2004 ; Khowaja et al., 2005 ). It is possible that the current global nursing shortage might increase nurses’ workload and China is not an exemption from this challenge ( Gong, 1996 ).

5.4. Hospital nurses’ professional commitment

The finding of the respondents’ strong commitment to the nursing profession is consistent with that in Taiwan ( Lu et al., 2002 ). This is possibly associated with a number of factors, including: recognition of the value of the nursing profession, increasing professional status and increasing academic professional activities.

People can develop devotion to their profession if they think that the profession is valuable ( Altschul, 1979 ). Nurses, in some respects, embody the absolute moral worth of the person who gives unselfish and devoted care and in return receives a high regard in society. In Mainland China nurses are often referred to as ‘White Angels’ for their contributions to human health with nurses’ work during the period of the outbreak of Severe Acute Respiratory Syndrome (SARS) in 2003 reaffirming the value and importance of the nursing profession ( Liu et al., 2004 ).

Additionally, the Chinese government's recognition of nursing as an independent profession and the development of university degree nursing programmes have undoubtedly facilitated an increasing professional status ( Li, 2001 ). Increased academic activities such as seminars or workshops also enhance nurses’ engagement in their professional roles and influence their attitude towards the nursing profession, which in turn can promote a stronger professional commitment ( Lu and Chiou, 1998 ).

5.5. Hospital nurses’ role conflict and role ambiguity

The majority of the respondents reported a low level of role conflict and role ambiguity, which is similar to Seo et al.'s (2004) findings in South Korea, but contrasts with Dailey's (1990) study in the USA. Such findings in the study may reflect compatible demands from nurse educators, colleagues and nursing managers resulting in clear and sufficient information about working responsibilities. It is possible that the majority of respondents graduated from the same educational institution to which their hospitals were affiliated so that the nurse educators, colleagues and hospital managers of the respondents held similar values and principles regarding nurses’ roles, thus reducing the potential for role conflict ( Hingley and Cooper, 1986 ). In addition, in 1982, the Ministry of Health, China published ‘Working Responsibilities of Health Care Personnel in Hospitals’ which set out the working roles of staff nurses, health care assistants, doctors and other health care personnel. Although some reforms in nursing have occurred, this guide has not been modified and has been widely implemented in hospitals across Mainland China so that the opportunities for role overlap and conflict may been minimized in consequence.

5.6. The impact of nurses’ educational level upon their working lives

The findings of significant differences in nurses’ role conflict and professional commitment across the three educational programmes (diploma, associate degree and bachelor degree) suggest primary differences arising from the impact of education ( p <0.05). Such findings may be explained by the bachelor degree nurses’ higher role expectations. The knowledge enrichment of the university-educated nurses may yield a broader perspective and a higher expectation of their working roles compared to that of diploma and associate degree nurses ( Wetzel et al., 1989 ). However, the bachelor degree nurses’ role perception is not dominant in a nursing workforce as they only represent a minority with about 5% of registered nurses in 2002 having a bachelor degree in China ( Jiang et al., 2004 ). This study found even in the teaching hospitals in Beijing, as the highest health care institutes, less than 10% of nurses had a bachelor degree. Additionally, in hospitals, the bachelor degree staff nurses assume the same roles and tasks as those with a diploma or associate degree ( Yang and Cheng, 2004 ), which may increase the bachelor degree nurses’ role conflict arising from the different role expectations and task requirements from universities, hospitals, peers and themselves.

The bachelor degree nurses’ weaker professional commitment is similar to Lu and Chen's (1999) local survey. One possible explanation is that well-educated nurses are more likely to experience the conflict between their role expectations and actual working roles. Indeed, Jing (2000) has suggested that such a conflict could result in bachelor degree nurses not feeling that they belong to the nursing profession.

Another possible explanation is that the bachelor degree nurses may have a stronger intention to leave the nursing profession. Bartlett et al. (1999) found that graduates were less confident in their initial decision to enter the nursing profession compared with diplomats. Similarly, Lu and Chen (1999) found that half of nursing undergraduates disliked or strongly disliked the nursing profession with most of them reporting that they intended to change to another career.

The findings indicate that there were no significant differences in total job satisfaction of nurses across the three educational programmes ( p >0.05). This finding is inconsistent with previous studies, which found that nurses with a higher educational level were less likely to be satisfied with their job ( Lu et al., 2002 ; Chu et al., 2003 ).

Part of the explanation for this finding may rest with the interrelationships between age, working years, marital status and job satisfaction. For example, Blegen's (1993) meta-analysis found that nurses who were older and had longer working experiences were more likely to be satisfied with their job. Yin and Yang (2002) also found that married nurses were more satisfied with their job than those who were unmarried. In this study, nurses with a bachelor degree were significantly older and had more working experience than nurses with a diploma or associate degree ( p <0.001). Additionally, most of the nurses with a bachelor degree were married ( p <0.001). It is possible that these respondent characteristics had an impact on the relationship between job satisfaction and educational level.

The findings indicate that there were no significant differences in organizational commitment, occupational stress and role ambiguity across the three educational programmes ( p >0.05). This may be the result of the limited sample size of bachelor degree nurses ( n =50) so that further research with a larger sample with different educational background is needed to explore these issues. Another possibility is that regardless educational level, the staff nurses in the study assumed similar roles and responsibilities, which were clearly described in hospital guideline. In these circumstances a significant difference in nurses’ role ambiguity across the three educational programmes would not be expected.

6. Conclusion

The findings in the study indicate that the hospital nurses in this study had a positive feeling towards their working lives in Mainland China. This may be a reflection of the developments in the health care system and nursing profession. But it is worthwhile to note that nurses’ intention to leave is still a serious problem and warrants more attention. International migration of nurses has increased as nurses pursue opportunities for improved pay and opportunities in the wake of global liberalization of trade spurred on by developed countries increasing their international recruitment to meet their health care workforce needs and in doing so creating a ‘skills drain’ in many developing countries ( Kingma, 2001 ). One might expect to observe dissatisfaction with changes in education with the influence of American curricula and higher education and limited changes to the nurse's role in the guideline established by the Ministry of Health, China, but it is likely that those experiencing greatest dissonance between the expectations and reality of their role will have entered the global labour market and such individuals would not have been recruited to this study. Further research is needed to test the impact of educational level upon job satisfaction, occupational commitment, occupational stress and role ambiguity using other samples.

The study also indicates that the bachelor degree nurses had weaker professional commitment and a higher level of role conflict. It is suggested that nurses’ educational background should be considered an important factor in understanding nurses’ working lives and may indicate the need for a clinical career ladder for nursing staff in Mainland China. Such a ladder, which uses a grading structure to facilitate career progression by defining different levels of clinical and professional practice in nursing, has been successfully introduced in other countries such as the UK ( Buchan, 1999 ). Further, Krugman et al.'s (2000) work in the USA found that the use of a clinical ladder facilitated nurses’ professional development, strengthened their organizational commitment and increased their job satisfaction in a study evaluating 10 years of progressive change.

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Fuzzy Logic-Based Quantitative Development Model for Job Satisfaction in College Graduates

• Research Article
• Open access
• Published: 02 September 2024
• Volume 17 , article number  226 , ( 2024 )

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• Yuqi Cheng 1  

College graduates’ job satisfaction is validated via their feedback, experiences and personal developments during their career progression. Validation is accomplished to ensure the students’ job satisfaction and retain them for a prolonged time. The traditional validation models have difficulties in analyzing the individual satisfaction level. The research issue is addressed by introducing the Quantitative Assessment Method (QAM) using Fuzzy Logic to validate the job satisfaction level of different newly placed students. The QAM approach assesses the student experience and personal development across various quarters. The fuzzy optimization uses two factors differentially using partial derivatives. The partial derivatives are extracted using the min–max functions of the fuzzification process such that the derivatives are halted after the maximum factors. The proposed method optimizes the validation using individual satisfaction levels and cumulative experience shared by the students. The available derivatives identify the best-afford job satisfaction level for different progression levels. This best-fit feature is handled using multiple min and max derivatives to extract optimal outputs. This proposed method is valid for improving satisfaction levels and experience analysis.

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1 Introduction

Job satisfaction is defined as the range of contentment that employees feel about their jobs. Job satisfaction also provides happiness and positive energy, motivating them to improve their performance [ 1 ]. Job search methods and satisfaction practices are provided to college students during the learning period. The employee’s job satisfaction is examined based on job offers, satisfaction, positivity, performance, and salary rate [ 2 ]. The exact satisfaction level is evaluated based on the factors that improve job significance. Many techniques are provided to students during college [ 3 ]. Learning disabilities and functionalities are identified using job offers and performance. Various job fair methods are provided to college graduates [ 4 ]. Professional educational courses, practices, and vocational courses are available in college. The vocational courses provide feasible education and training sessions to the students, which improves the employee’s overall satisfaction range [ 5 , 6 ]. Profit and non-profit-based training sessions are also provided to college graduates. The profitable benefits are calculated based on functionalities that minimize the complexity of the job search process [ 7 ].

Quantitative development is a process that develops a particular area or field. Quantitative development is used for job satisfaction. The main goal of the quantitative approach is to analyze the exact relationship between employees and jobs in an organization [ 8 ]. The quantitative approach predicts the actual satisfaction level based on the performance range of the employee. An integrated model is used for job satisfaction improvement [ 9 ]. The integrated model uses a meta-analysis technique to evaluate the workers’ satisfaction range. The meta-analysis minimizes the computation process’s time and energy consumption ratios [ 10 ]. The integrated model provides optimal information for the quantitative development process, which enhances the systems’ overall performance range. A quantitative approach is also used for job satisfaction [ 11 ]. The quantitative approach predicts the relationship between performance and work. The expected information produces the relevant data for development and improvement processes. The quantitative approach increases the efficiency and feasibility range of the job satisfaction process [ 12 , 13 ].

The fuzzy logic approach is used for the job satisfaction evaluation process. The fuzzy logic approach uses fuzzy sets, which contain appropriate information for the evaluation process [ 14 ]. The fuzzy logic approach uses a set theory that measures the exact job satisfaction range of the workers. The performance range of employees, active ratio, and preference level are evaluated using set theory [ 15 ]. The attributes contain optimal key values for the job satisfaction measurement process. The set theory-based fuzzy logic approach increases the accuracy of the satisfaction detection process [ 16 ]. A fuzzy logic-based satisfaction detection method is also used in organizations. The exact satisfactory range of workers is identified from the database, reducing further processes’ latency [ 17 ]. The workers’ satisfaction range is calculated, providing optimal information for improvement and development. The fuzzy logic-based method increases employees’ overall performance range, enhancing the organization’s feasibility ratio [ 11 , 18 ]. A fuzzy logic-based quantitative approach is also used to improve job satisfaction. The quantitative approach analyzes the exact quality of jobs that are performed by the workers [ 19 ]. The traditional analysis has difficulties exploring the individual satisfaction level at different quarters. The problems are overcome by applying the Quantitative Assessment Method (QAM) with Fuzzy logic. The approach uses the fuzzy derivatives to identify the experiences and best affords definitive outputs. According to the discussions, the study’s contribution is listed as follows:

1.1 Contributions

Propose and discuss the process of developing a quantitative assessment model for evaluating the job satisfaction of college students using multi-variate data.

Analyzing the variations based on independent data attributes using fuzzy derivatives for experience extractions and best-afford definitive outputs.

Incorporating an ideal data source for analyzing the fuzzy impact on satisfaction and personal development at various professional levels.

Performing a self-analysis for different metrics by varying a certain factor to identify its impact on the assessment.

2 Related Works

Jiang et al. [ 20 ] developed a career-oriented satisfaction architecture for information technology (IT) professionals. The main aim of the architecture is to identify the exact career satisfaction range of IT professionals. The developed architecture tests the model based on job demands, managerial demands, and the satisfaction ratio of employees. The developed model provides IT professionals with proper career paths and career demands to, minimizing the complexity of the field.

Storey et al. [ 21 ] presented a job satisfaction theory for software developers. The proposed theory detects the impact of software developers’ productivity and career satisfaction levels. The proposed theory identifies both social and technical factors and features of developers. The identified features produce optimal information for the satisfaction detection process. The proposed theory increases the career growth range of software developers.

Hayat and Afshari [ 22 ] proposed a mediation model for job satisfaction detection. The proposed model is mainly used to detect the impacts of corporate social responsibility (CSR) among employees. CSR contains exact employee details, producing feasible data for the job satisfaction process. Structural equation modelling (SEM) is used here to analyze the data presented in CSR. The proposed model improves the overall feasibility and efficiency of employees.

Haerens et al. [ 23 ] introduced a job satisfaction method for school teachers. The main goal of the technique is to predict teachers’ chaotic leadership styles. The chaotic leadership style contains both positive and negative emotions among the teachers. The educational style and presentation are also detected based on teachers’ performances. The introduced method identifies the exact job satisfaction range of teachers.

Cheung et al. [ 24 ] designed a new job satisfaction prediction strategy for the indoor environment. The workers’ indoor environment quality (IEQ) ratio is predicted using analysis tools. IEQ parameters provide necessary information that minimizes the complexity of the job satisfaction detection process. The IEQ parameters also contain the workers’ workspace environment. The designed method improves the overall job satisfaction level of workers.

Samerei et al. [ 25 ] developed a classification and regression tree (CART) algorithm-based job satisfaction assessment process. The CART algorithm mainly extracts features presented by bus rapid transit (BRT) drivers. BRT is used here as input to produce relevant data for the assessment process. BRT drivers provide details such as their mental health state, stress ratio, behaviours, and body condition among drivers. The developed assessment method maximizes the efficiency and performance range of organization workers.

Karaferis et al. [ 26 ] proposed a job satisfaction method using factor analysis for healthcare systems. The factor analysis technique is used here to analyze the important factors necessary for detection. The main aim of the technique is to improve the quality of service (QoS) of employees. Experimental results show that the proposed method enhances healthcare systems’ significance and feasibility.

Seok et al. [ 27 ] developed an artificial neural network (ANN) based job satisfaction method for educational institutions. Multiple regression analysis is used to analyze the actual relationship between teachers and students. The regression analysis approach decreases the computation process’s time and energy consumption. The developed ANN method accurately predicts the technical factors that the teachers use.

Moslehpour et al. [ 28 ] introduced a configurational approach to job satisfaction (JS). The actual aim of the approach is to analyze the job satisfaction range of the workers. The emotional competence (EC) and positivity ratios of workers are identified. EC produces optimal data that minimizes the latency in the JS detection process. Compared with other approaches, the introduced approach increases the workers’ tendency and ethical ambiguity level.

Grolleau et al. [ 29 ] developed an empirical analysis method for job satisfaction in French firms. A lagged predictor is used in the method to predict the necessary variables for the detection process. The developed method also produces innovative ideas and techniques to improve the overall job satisfaction range of the employees. The developed analysis method improves the performance and efficiency range of employees.

Sung and Hu [ 30 ] proposed a new detection method using job satisfaction. The technique aims to identify the exact impact of airline internal branding based on work outcomes. The identical idea, working ability, communities, productivity, and leadership ratio of workers are detected in the database. The detected data provide optimal data for the job satisfaction detection process. The proposed method increases the feasibility and effectiveness organizations.

Chang et al. [ 31 ] designed a regression analysis-based job satisfaction detection method for healthcare centres. The developed method is mostly used in rural areas to identify the impacts of electricity and lights in healthcare. The designed method also predicts the issues that occur while providing emergency services to users. The developed method minimizes the complexity level of providing services to users in healthcare centres.

Quantitative assessments are fond of various impacting features/ attributes subject to fluctuations. Based on the various impacting features, a professional’s job satisfaction level and personal development are tedious to analyze. The study is due to internal and external demands and data circulation. By augmenting productivity-dependent data, the variations are less identified, regardless of the optimization function defined. This article introduces a fuzzy derivative-based assessment method to mitigate such issues in data handling.

Compared to traditional methods of measuring satisfaction on the job, the proposed method has far more beneficial aspects. For instance, compared with existing qualitative methods, the proposed model’s quantitative precision provides a more exact measurement, allowing for unambiguous and tangible findings about satisfaction levels. Then, the process guarantees that characteristics particular to each employee are considered by adapting assessments to their experiences and personal development. By incorporating fuzzy logic, the evaluation process can be more efficient and effective in optimizing work satisfaction levels while decreasing analytical overhead. The proposed technique facilitates continuous improvement by enabling continual adjustments in response to feedback and evolving conditions.

3 Data Representation

The “employee satisfaction index dataset” from [ 32 ] is used throughout the article to validate the best-affordable solution. Figure  1 presents the data representation with impact from the considered dataset.

Data representation

The attributes from the given dataset are split into personal, designation, and assessment metrics. From this data, the certifications, awards, and level attributes are the impacting features for the satisfaction determination as either yes or no (refer to Fig.  1 ).

4 Quantitative Assessment Method (QAM) for Improving Satisfaction Levels

The QAM- is designed to improve the job satisfaction of college students based on their experience and personal development inputs. The inputs from the college students are obtained, (i.e.) the partial derivative is observed each quarter. The main objective of this quantitative assessment method is to reduce errors in analyzing experience levels and personal development. The challenging task in this proposed method is the differential augmentation and correlation of two factors using fuzzy assessment for extracting the partial derivatives with the previous successive quarter validation. The partial derivatives are stored as records for the previously validated instances. The processes involved in the QAM-FL are represented in Fig.  2 .

Processes in QAM-FL

The experience and personal development of the college students are observed through their performance analysis for step-in to career progression. The observed inputs are classified as experience levels and personal growth. In experience analysis, the activity of college students in each quarter is said to be continuous and similar based on time and day. In contrast, this data is not observed on consecutive days in a personal development analysis, such as skill assessment/career awareness for the time/day. The partial derivatives are extracted using the min–max functions of the fuzzification process. After achieving the maximum factors, the remaining derivatives are halted by fuzzy logic. In this process, the proposed method optimized the validation based on cumulative experience and individual satisfaction levels shared by the students in different quarters. The best-afforded job satisfaction level is detected using this minimum and maximum derivative for various progression levels. The validation and identification process reduces the chance of analysis overhead and time spent utilizing the fuzzification process. The analysis overhead is detected using the available derivatives for different progression levels. The proposed QAM focuses on such analysis overhead through extracted partial derivatives using fuzzy logic. The Initial quantitative assessment of college students’ job satisfaction is validated using the sequence of experience and personal development \(\text{Exp}\left(Q\right)\) and \(\text{Pdv}\left(Q\right)\) identified/observed in different quarters, such that the job satisfaction \({\text{Job}}^{\text{Satif}}\left(Q\right)\) is expressed as

In Eq. ( 1 ), the variable \({C}^{\text{e}}\) represents the causing error at each quarter analysis, and the objective of reducing the causing error is for all \(Q\left(\text{Exp}*\text{Pdv}\right)\in {\text{Job}}^{\text{Satif}}\left(Q\right)\) is defined as validating successive quarters for job satisfaction. The quarter is divided into two factors (i.e.) experience \(({Q}_{\text{Exp}})\) and personal development \(({Q}_{\text{Pdv}})\) . This proposed method implies that in the job satisfaction analysis based on experience and personal development, the QA-based method will validate the best-afford job satisfaction level based on partial derivatives conditions, and the aid of fuzzy optimization is to identify all possible job satisfaction of the placed students \(\left(\Delta \right)\) is expressed as in Eq. ( 2 )

According to the above conditions, the partial derivatives of all students can be continuously validated.

Equation ( 3 ) computes the maximum possible job satisfaction of all the placed students for a prolonged time \(T\) . The above validation is pursued, augmenting job satisfaction and retaining students at \(T\) . If \(V\) means the optimal job satisfaction validation of different newly placed students. Table 1 presents the derivatives and \({C}^{\text{e}}\) they were observed during two-quarters of the four levels of the job presented in the data source.

Table 1 presents the \({C}^{\text{e}}\) and the derivatives used to validate the performance of the employees in 2 different quarters. This quarter varies for the various levels (job designation) for \(\text{pdv} (Q)\) and its corresponding \({C}^{\text{e}}\) . The appraisal and performance estimations are considered satisfied as the derivatives are fewer. Therefore the \({C}^{\text{e}}\) is less based on different dataset attributes and quarters. Hence, the successive quarter is identified with the condition \(Q={Q}_{\text{Exp}}+{Q}_{\text{Pdv}}\) such that the proposed assessment improves college students’ experience and personal development across different quarters. If \({\exists }^{d}\) means the partial derivative is validated from the model mock interviews, then \({\exists }^{d}=\left({\text{Std}}^{n}\times Q\right)-{C}^{e}\) the partial derivative observed instance will be classified using the min–max functions. The variable \(Fzy({\text{Q}}_{\text{Exp}})\) and \(Fzy({Q}_{\text{Pdv}})\) represent the fuzzy optimization of \({\text{Job}}^{\text{Satif}}\left(Q\right)\) is observed from all the students \({Std}^{n}\) in \(i\) quarters is observed such that

As per Eqs. ( 4 ) and ( 5 ), the partial derivatives are extracted using the maximum and minimum functions of the fuzzification process observed from the instances are mapped with \(\text{Exp}\left(Q\right)\) and \(\text{Pdv}\left(Q\right)\) . Based on the extracted partial derivatives, Eq. ( 1 ) is re-written as

For the expanded job satisfaction assessment, the sequence of \(\left({\text{Std}}^{n}\left(Q\right)\in T\right)\) is to validate job satisfaction for all placed students and retain them for a prolonged time. In this assessment, the first-year student experience and personal development analysis are shown in Eq. ( 6 ). The job satisfaction measure \({\text{JS}}^{m}\) is validated to identify analysis overhead based on partial derivatives using min–max functions. In this analysis, the above derivatives for the factors considered in Table  1 are used for computing \({J}^{\text{sat}}(Q)\) for different levels. This is presented in Table  2 .

In Table  2 , the \({J}^{\text{sat}}(Q)\) is validated based on the experience and fuzzy \(\left({Q}_{\text{Adv}}\right)\) from which min–max variations are identified. This computation is optimal for \({\exists }^{\text{d}}\) such that the conditions in Eq. ( 3 ) are validated. Therefore, the optimal fuzzification is performed using \({J}_{S}^{m}\) such that the Fuzzy \(\left({Q}_{\text{Pdv}}\right)\) is relied upon \(\Delta\) . From the \(\Delta\) the \({\exists }^{d}\) are extracted using \(\text{Exp}(Q)\) and \({C}^{\text{e}}\) from the previous inputs. In this case, the validations are performed using \(\text{min}\left|\sum \text{Exp} \left(Q\right)+\text{Pdv}\left(Q\right)\right|\) where \({C}^{\text{e}}\) stands for experience, which is never less than a lagging factor. Thus the \({\exists }^{\text{Sat}}(Q)\) is handled using different \({J}_{S}^{m}\) such that \(\sum_{\text{Std}=1}^{T}.\) satisfies \(\sum_{r=1}{V}_{\Delta }\) represents for fuzzy assessment. The correlating of experience and personal development of the placed students across different quarters is validated using the available data through consecutive processes. For this validation, the sequence of \({\text{Std}}^{n}\left(Q\right)\in T\) is expressed as

The above Eq. ( 7 ) follows the partial derivatives of all students, which can be continuously validated using the sequence of the previously stored data for achieving successive quarters. It is analyzed based on two factors that validate differentially. Therefore, based on the proposed method assessment, \({\text{Job}}^{\text{Satif}}\left(Q\right)=Fzy\left({Q}_{\text{Exp}}\right)+Fzy\left({Q}_{\text{Pdv}}\right)\left[1-T\left({\text{Std}}^{n}\left(Q\right)\right)\right]\) is the final output without causing errors and analysis overhead. The final job satisfaction measure based on minimum and maximum derivatives \(({\mu }_{\left({Q}_{\text{Exp}}\right)})\) and \(({\mu }_{\left({Q}_{\text{Pdv}}\right)})\) for experience and personal development validation at the first level is expressed as

Equations ( 8 ) and ( 9 ) validate that the job satisfaction of the placed students is observed using the experience and personal development for the sequence across different quarters through partial derivatives. In this initial assessment method, the validation of \({\mu }_{\left({Q}_{\text{Exp}}\right)}\) , \({\mu }_{\left({Q}_{\text{Pdv}}\right)}\) , \(Fzy\left({Q}_{\text{Exp}}\right)\) and \(Fzy\left({Q}_{\text{Pdv}}\right)\) represents the serving inputs for the successive quarter identification. The consecutive processing of fuzzy optimization helps to identify the analysis overhead in this proposed method. This fuzzification process is discussed in the following section. Where, \(\left(\frac{\text{Exp}\left(Q\right)+\text{Pdv}\left(Q\right)}{{C}^{\text{e}}}\right)\) is the job satisfaction level observed from the individual student based on partial derivatives extracted for different progression levels. Based on Eqs. ( 8 ) and ( 9 ), the variations across \({J}_{S}^{m}\) is validated in Fig.  3 .

Min–max variation for \({J}_{S}^{m}\) analysis

The satisfaction measure is computed using \(\text{Exp} (Q)\) and \(\text{Pdv}(Q)\) from the post. Based on the fuzzy optimization across various fuzzy \(\left({Q}_{\text{Pdv}}\right)\) and Fuzzy \(({Q}_{\text{Exp}})\) the variations are computed. Therefore, successive quarters are required to suppress the variations across multiple \({Q}_{\text{ex}}\) or \({Q}_{\text{Pdv}}\) such that \({J}_{S}^{m}\) based sequenced are optimized. This validation is normalized for \(\mu \forall {Q}_{m}\) . The optimality is retained using variation suppression. This variation is suppressed using different entries of \({\text{Job}}^{\text{sat}}(Q)\) provided \(T ({\text{std}}^{n}(Q)\) retains maximum \({J}_{S}^{m}\) (Refer to Fig.  3 ). At a prolonged time, QAM identifies the best-afford satisfaction level when validating the students’ appropriate experience and personal development for the next validation. This validation improves job satisfaction levels and retains students for different progression levels. According to the above condition, the two factors are differentially validated using fuzzy optimization between students’ jobs and satisfaction level, and min–max derivatives can be obtained, which is the final quantitative output of the placed student.

In Eq. ( 10 ), the college students’ experience and personal development must achieve the best-afford job satisfaction level and validate the partial derivatives using min–max functions. The quantitative assessment measure \({\text{QA}}_{m}\) represents the expected job satisfaction level to be met when extracting partial derivatives. After the maximum factors are satisfied using partial derivatives by fuzzy optimization, the job satisfaction level of the individual student will be validated, and analysis overhead will be identified in advance with progression levels. In this process, when the student’s job satisfaction level exceeds the threshold, the fuzzy process stops the derivatives. Otherwise, it will continue to identify best-fit features using min–max derivatives for extracting optimal output, and this process will continue for a prolonged time. In the fuzzification process of \({\text{QA}}_{m}\) and min–max derivatives, the proposed method is to reduce the analysis overhead and time as much as possible across different quarters. Therefore, the objective function \(F\) is computed as in Eq. ( 11 )

5 Fuzzy Optimization Based on Min–Max Derivatives

This article maximizes college students’ best-afforded job satisfaction and improves their experience and personal development to achieve optimal output using the available derivatives. The proposed method will optimize the extraction of partial derivatives defined in the previous section. This section introduces the implementation process of fuzzification to validate the students’ job satisfaction level. The goal is to identify the best-fit feature based on fuzzy optimization. In this sequential process, the QAM validates the individual student job satisfaction level, the output result differs for each student, and the analysis overhead is reduced. The output of the input student’s job satisfaction with min and max derivatives can be expressed as in Eq. ( 12 )

The proposed method extracted optimal output using individual satisfaction levels and cumulative experience shared by the students. In addition to the job satisfaction level and optimization output, a hidden layer handles multiple min and max derivatives for extracting optimal output across different quarters. The derivatives based on min–max variations and their applicability are verified using the factors mentioned in Table  3 .

The different levels of jobs are correlated with quarters based on their attributes such that \(\mu\) are balanced between the min and max values. The fuzzification is balanced for \(\mu \left({Q}_{\text{Pdv}}\right)\) and \(\mu \left({Q}_{\text{Exp}}\right)\) such that \({J}_{S}^{m}\) is observed for successive quarters. In this process, the \({Z}_{i}\) is optimized using \(F\) provided \({\text{QA}}_{m}\) is high, and therefore, the consecutive measure is validated as \(\left[\text{Exp}{\left(\text{Q}\right)}_{\text{T}}+\text{Pdv}{\left(Q\right)}_{T}\right]\) . These features are verified using Eq. ( 3 ) for the conditional fuzzy assessment. In this conditional assessment, the derivatives are summoned to detect the best-afford solution. Therefore \({\exists }^{d}\) is used for balancing \(F\) for \(f(Q)\) and \({A}_{\text{o}}\left(Q\right)\) . The partial derivatives are extracted using min–max functions of the fuzzy process. The student job satisfaction level and output of the hidden layer are expressed in Eqs. ( 13 ) and ( 14 )

where, \(f\left(.\right)\) represents the minimum and maximum functions of the fuzzification process. This corrects the extraction of optimal output and enhances satisfaction levels. Therefore, the experience analysis of the student can be expressed as in Eq. ( 15 )

The fuzzy optimization uses the extracted partial derivatives to continuously satisfy the satisfaction levels and identify the analysis overhead toward the minimum. The analysis overhead function is expressed as in Eq. ( 16 )

The conditions for achieving the best-afford job satisfaction level are expressed in Eq. ( 17 )

In this process, the output of the proposed method is compared with other existing methods to identify the best-afforded job satisfaction level for each student. The above condition determines the occurrence of analysis overhead in different quarters and the occurrence of min–max function observation. In this, extracting optimal output achieves \({H}_{1}=0\) as the previous output based on experience and personal development analysis such that \(\in\) maximum factor, where the improvement is needed. Therefore, this is not considered in the fuzzy process. This best-afford solution extraction based on variation optimization is analyzed in Fig.  4 . This analysis confirms the fuzzy assessment output considering \(F\) .

Best-afford solution based on variation analysis

The best-afford solutions using \(f\left(Q\right)\) for \(\mu\) and \({\text{QA}}_{m}\) are validated in Fig.  4 . Considering the derivatives \(\forall {Q}_{\text{Exp}}\) and \({Q}_{\text{Pdv}}\) , the \(F\) is satisfied by variation suppression. This process optimizes the flow of \({A}_{\text{o}}(Q)\) for multiple derivatives providing new suggestions on best-afford satisfaction outputs. In the \({J}_{S}^{m}\) Validate that the outputs vary across the min–max (variation) suppression. If this case is satisfied, then the maximum best-affordable solutions are achieved (refer to Fig.  4 ). The best-fit feature is observed at the end of all the fuzzy assessments or before the start of the next evaluation. Identification for different progression levels and minimum and maximum derivatives are observed at the best-afford job satisfaction level. Therefore, the best-fit feature holds the minimum and maximum derivatives where the first job satisfaction level is validated and later causing errors are minimized. It is to be analyzed that student experience and personal development are based on job satisfaction level validation for extracting optimal output. This observation of partial derivatives is valid from the min–max derivatives until maximum factors are achieved. Instead, the occurrence of \({A}_{\text{O}}\) continuously changes both minimum and maximum functions until the fuzzification process halts it. The identification of causing error due to less experience and less personal development observed from the students using conventional methods. Now, the job satisfaction validation (i.e.) \({\text{ Job}}^{\text{Satif}}{\left(Q\right)}_{T}\) with analysis overhead and time in experience and satisfaction level, analysis is the final observed sequence of \({\text{QA}}_{m}\) . If \(\text{Exp}\) and \(\text{Pdv}\) are not analyzed, then the whole class of \({\text{Job}}^{\text{Satif}}{\left(Q\right)}_{T}\) will be processed under min–max derivatives, resulting in high satisfaction analysis and experience extraction.

6 Discussion

This section presents a briefing on the impact of assessment on experience extraction, satisfaction analysis, quantitative output, analysis time, and overhead. Regardless of the method-based comparisons, the job satisfaction measure varies by 0.4, 0.6, 0.8, and 1 for analyzing the impact of the metrics. In this analysis, the number of students considered is 120 (the maximum), and the experience for a maximum of 48 months is accounted for.

Figure  5 represents the partial derivative extraction for student job satisfaction levels based on experience and personal development analysis. In the proposed method, the validation of the two factors is maximized by identifying accurate satisfaction levels using the fuzzification process. The initial quantitative assessment of validating the job satisfaction level of different newly placed students in college was based on experience analysis in various quarters to identify the best-afford satisfaction level. For this process, the two factors are differentially validated through available derivatives, whereas experience extraction identifies some errors due to min–max derivatives at previous levels. Therefore, the QAM is modelled to determine the best-afford job satisfaction levels in any quarter; the experience and personal development are better findings. Based on the occurrence of min–max functions of the fuzzification process for the instances, \({\text{Exp}}_{T}\) and \({\text{Pdv}}_{T}\) belongs to \(\text{arg}\underset{Q}{\text{min}}\sum {C}^{\text{e}}\left(Q\right)\forall Q\left(\text{Exp}*\text{Pdv}\right)\) it identifies the causing errors and analysis overhead. Therefore, the number of experience extraction leveraging the job satisfaction validation is high in the proposed method in a continuous manner. Detecting such derivatives improves job satisfaction such that \(Q\left(\text{Exp}*\text{Pdv}\right)\in {\text{Job}}^{\text{Satif}}\left(Q\right)\) represents the highest experience extraction in this article.

Discussion on experience extraction

In Fig.  6 , the experience and personal development of the students across different quarters are analyzed to improve job satisfaction and retain students for a prolonged time based on validation and partial derivatives for extracting optimal output. The best-fit features are extracted from the different quarters mapping in time intervals. The job satisfaction level is validated for other students based on their experience analysis to identify the best-afford job satisfaction level. The fuzzy assessment gives outputs in continuous satisfaction level identification with partial derivatives and min–max functions for time. The partial derivatives are extracted based on the available derivatives and the experience associated with job satisfaction. This is performed using the min–max functions to satisfy both the condition \(Fzy({Q}_{\text{Exp}})\) and \(Fzy({Q}_{\text{Pdv}})\) to identify the optimal output and error occurrence. The analysis overhead and time are determined using fuzzy assessment and achieved in successive quarters, preventing overhead. The error occurrence is minimized for achieving high satisfaction analysis using the proposed method for both conditions satisfying high quantitative output using min–max derivatives.

Discussion on satisfaction analysis

The optimal job satisfaction validation of different newly placed students based on partial derivative extraction is observed for identifying the best-afford job satisfaction level is depicted in Fig.  7 . In this proposed method satisfies less analysis overhead and error occurrence by mapping the condition \(\text{Exp}\left(Q\right)\) and \(\text{Pdv}\left(Q\right)\) using fuzzy logic. In this, the partial derivatives of all students can be continuously validated by analyzing individual students’ experience and personal development in different quarters. The \(\text{Exp}\left(Q\right)\) and \(\text{Pdv}\left(Q\right)\) is validated until the maximum factor is identified from the available derivatives. The fuzzification process requires minimum and maximum functions based on the extracted partial derivative, reducing analysis overhead at the time of job satisfaction level identification for the students. The error is identified using the min–max derivatives to compute the job satisfaction measure based on the available correlation between the experience and personal development of the placed students across different quarters. It is validated using the available data through consecutive processes. Therefore, the optimal derivatives are extracted for experience and personal development analysis. Hence, this proposed method identifies the satisfaction level using min–max functions computed across multiple derivatives, and the quantitative output is high.

Discussion on quantitative output

The analysis overhead and time are identified at the fuzzy assessment across different quarters for students’ job satisfaction level detection through partial feature extraction, which is illustrated in Fig.  8 . This proposed method satisfies the minimum analysis time by computing the satisfaction level and cumulative experience of the individual student based on the improvement in personal development, and its post-maximum factor is accurately identified for retaining students for a prolonged period of time. In this manuscript, the condition \({\text{Job}}^{\text{Satif}}\left(Q\right)=Fzy\left({\text{Q}}_{\text{Exp}}\right)+Fzy\left({Q}_{\text{Pdv}}\right)\left[1-T\left({\text{Std}}^{n}\left(Q\right)\right)\right]\) is validated for achieving optimal output. The causing errors and analysis overhead is mitigated due to min–max functions until best-fit feature identification wherein the different progression levels are preceded using Eqs. ( 4 ), (5), (6), (7), (8), and (9) computations. In this proposed method, experience and personal development are analyzed to identify the satisfaction level. Based on this validation, the analysis time is less than the other factors in this article.

Discussion on analysis time

In Fig.  9 , the analysis overhead identified in the proposed method is considerably less due to different satisfaction levels, and min–max derivatives can be obtained for individual students observed from various quarters. Based on the consecutive validation of fuzzy assessment, it helps to improve job satisfaction levels and identify the analysis overhead using partial derivatives. The condition \(\left(\frac{\text{Exp}\left(Q\right)+\text{Pdv}\left(Q\right)}{{C}^{\text{e}}}\right)\) is used to achieve optimal job satisfaction level observation for the individual student depending on extracted partial derivatives for different progression levels. This validation uses the fuzzy assessment and min–max functions for best-afford job satisfaction level detection, which helps map the two factors across different quarters. After this fuzzification process, the experience and personal development analysis based on job satisfaction level is identified for the individual student to reduce analysis time and overhead. This fuzzy assessment and quantitative output help to reduce the maximum factor with the validation, improve job satisfaction levels, and retain students for different progression levels in other quarters, reducing analysis overhead in this proposed method.

Discussion on analysis overhead

7 Conclusion

The student’s job satisfaction level is assessed with the help of a quantitative assessment method with fuzzy logic. The assessment is performed according to workplace attributes and personal development. A professional’s experience is initially computed to identify their personal growth and willingness. The fuzzy optimization is applied to derive the partial derivatives for every attribute and identify the maximum best-afford solution. The minimum and maximum values for cumulative experience and variations are computed considering individual satisfaction levels. The computations are validated using different fuzzy derivatives and their impact on the partial derivatives across multiple considerations. The best-afford solution condition is validated using min–max progression and its optimal output. Therefore, this proposed method handles less complex quantitative outputs for different experienced persons over differential satisfaction levels. The proposed quantitative assessment method with fuzzy logic shows promise for evaluating job satisfaction among student professionals. However, its reliance on subjective inputs and its effectiveness across diverse considerations are still limitations. Thus, future work will focus on resolving these constraints on the proposed model by developing a more objective fuzzy model that can handle multi-attribute experience and personal data development. With this improvement, the future scope aims to improve the precision and reliability of quantitative measures.

Availability of Data and Material

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Cheng, Y. Fuzzy Logic-Based Quantitative Development Model for Job Satisfaction in College Graduates. Int J Comput Intell Syst 17 , 226 (2024). https://doi.org/10.1007/s44196-024-00637-y

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An examination of employee's perceived level of their leader's religiosity as a moderator of the relationship between an employee's religiosity and job satisfaction.

Brad Carney , Liberty University Follow

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Benjamin Wood

religiosity, moderation, employee religiosity, job satisfaction, leader’s perceived level of religiosity

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Carney, Brad, "An Examination of Employee's Perceived Level of Their Leader's Religiosity as a Moderator of the Relationship Between an Employee's Religiosity and Job Satisfaction" (2024). Doctoral Dissertations and Projects . 5927. https://digitalcommons.liberty.edu/doctoral/5927

The purpose of this study was to investigate whether an employee’s perceived level of their leader’s religiosity moderates the relationship between an employee’s level of religiosity and job satisfaction. The participants in this research study were recruited through the utilization of a snowball sampling method, primarily leveraging Liberty University’s doctoral student email list and social media platforms such as Facebook and LinkedIn. Participants in the study were required to be 18 and older and had been employed under their current leader for a minimum of one year. The total sample size was N=65. The researcher used a quantitative self-reporting survey approach to data collection using the Huber and Huber (2012) Centrality of Religiosity Scale (CRS-15) survey to measure a leader's level of religiosity as perceived by the employee and an employee's level of religiosity. The Spector (1985) Job Satisfaction Survey (JSS) was used to measure an employee's level of job satisfaction. The data collected from the online CRS-15 and JSS surveys was analyzed employing a correlation research design using linear regression with moderation analysis. The results did not show a significant moderating effect on an employee’s perceived level of their leader’s religiosity. Still, they did find that employees who perceived their leader to have a high level of religiosity reported higher levels of job satisfaction. Furthermore, this study is the first to investigate an employee’s perceived level of their leader’s religiosity and the effect it has on employee job satisfaction.

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