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Determinants of Job Satisfaction: A Review of Empirical Literature

Prof. Thomas Katua Ngui
Mar 16, 2023
Human resource management

Prof. Thomas Katua Ngui United States International University – Africa, KENYA

The commonly held opinion is that “a satisfied worker is a productive worker”. There is a reciprocal relationship between satisfaction and performance; this means that satisfaction causes performance and performance causes satisfaction. When an employee is satisfied with their job they commit their energies and effort towards achievement of organizational goals sometimes at the expense of their personal goals. The purpose of this study is to find out the factors that influence the level of job satisfaction among the workforce. Increased job satisfaction will motivate employees to achieve the organizational goals. A satisfied work force will create a pleasant atmosphere within the organization to perform well (Pushpakumari, 2008). Low job satisfaction could cause employees to move away from their jobs, search for new jobs, or change their existing jobs and careers. The degree of organizational loyalty of employee is higher when employee job satisfaction increased (Javed, Balouch & Hassan, 2014). It is therefore, very critical for organizations to approach their performance improvement goal from the employee job satisfaction point. For this to happen effectively, it is necessary for the managers to understand the factors that determine job satisfaction among employees. Studies have shown that job satisfaction is influenced by a variety of factors- both internal and external to the organization. This study sought to review literature on the factors that determine or influence job satisfaction. From the study it was found that job satisfaction is an outcome of different factors like pay, the work itself, job security, supervision, leadership styles, relationships with co-workers and opportunities for promotions. The findings of this study will help managers at all levels to play a key role in improving the levels of job satisfaction among employees within their jurisdictions. This in turn will lead to higher performance both at the individual, team and organizational levels.

Key Words: Job security, Job satisfaction; Performance

INTRODUCTION

With increased technological growth and globalization of markets the business environment has become very competitive and complex. This requires organizations to up their game in order to remain competitive and survive in the changed business environment. To succeed in this very turbulent market, most organizations have invested in acquisition of high quality resources that are valuable, unique, non- imitable and rare in order to sustain their competitiveness. Such resources include human, physical, technological and financial resources. Among the identified resources, the human resources have been found to be the best source of sustainable competitive advantage. The success of any organization depends on the satisfaction of its workforce (Mekonin & Teklu, 2021).

Every organization’s success indeed depends on employee satisfaction on job as their effort has been paid off ( Khaira, Afifah, Shariff & Sima, 2021) . Leaders today believe that impressive human resource is the power factor of an organization. This is because human resources are unique and cannot be copied. Human resource is an active resource which has emotions and can react differently to different situations. Human resource is considered as the most important asset which serves as the engine for providing a sustainable source of energy and service delivery in the organization (Muhammad & Wajidi, 2013). The importance of intellectual capital has increased to the point of being one of the most valuable assets that must be better understood in order to be developed (Ouedraogo & ALeclerc, 2013). This is largely because the human resource is an active resource that has the capability to activate other resources in pursuit of organizational goals/ objectives. It is also very unique and cannot be copied.

The millennium generation employees (millennials) have different expectations from the job environment compared to the expectations of the previous generation of workers. For this new generation of employees to be productive and to unleash their full potential, they should be satisfied with their job. This requires managers to be very cautious while dealing with the millennials and also to understand their needs/ expectations in order to fully benefit from their skills and knowledge. Job satisfaction is a result of employees’ perception of how well their job provides those things which are viewed as important (Ndulue & Ekechukwu, 2016). If the human resource or employees are happy and contended with the moves and actions of the employer, they do their best for the best of the organization (Khan, Nawaz, Aleem & Hamed, 2012). A satisfied work force will create a pleasant atmosphere within the organization to perform well (Pushpakumari, 2008).

There is a reciprocal relationship between satisfaction and performance; this means that satisfaction and performance influence each other. Increased job satisfaction will motivate employees to achieve the organizational goals. When employees perform well and achieve the organizational goals they are also likely to be motivated by the improved performance which in turn leads to higher job satisfaction. The factors that contribute to the positive morale and attitude also result in a higher degree of job satisfaction (Saranya, 2014). A highly satisfied work force is absolutely necessary for achieving a high level of performance in an organization. Satisfied workers tend to extend more effort to job performance, then work harder and better (Pushpakumari, 2008). Job satisfaction is an important factor for improving effectiveness and also a person’s satisfaction in a company. Job satisfaction is achieved from situations a person experience in his job, so factors such as management method, organization policy and structure, job conditions and type of relation with coworkers are important (Weiss, 2002).

Many studies have been done on the relationship between job satisfaction and performance, for example, Khan, Nawaz, Aleem and Hamed, (2012); Revenio Jr. (2016); Ndulue and Ekechukwu (2016) and Bakotic, (2016) have all done studies on this topic. However, due to the changing nature of the work environment as a result of advancement in technology and the changed expectation of the current millennial employee, this topic remains a topic of interest and requires continuous research in order to meet the psychological needs of the new category of employees whose expectations are quite different from those of the previous generation of workers. The purpose of this paper is to review literature on the factors that influence level of job satisfaction among the workforce and its effects on performance.

Job satisfaction

Job satisfaction is an affective or emotional response towards various facets of one’s job (Ndulue & Ekechukwu, 2016). Cranny, Smith and Stone (2014) defined job satisfaction as employees’ emotional state regarding the job, considering what they expected and what they actually got out of it. According to Willem, (2007) job satisfaction shows the relation between human expectations and advantages taken from job. Vroom (1964) as cited in Revenio Jr. (2016) defines job satisfaction as an “effective orientations on the part of the individuals towards work roles which they are presently occupying”. Job satisfaction is a positive emotional state that arises from the employee’s work or practical experience, and results in job satisfaction from the realization of the extent to which the employees work provides the things that he or she considers important (Hareem, 2013). According to Spector (1997) job satisfaction shows peoples emotion about their job generally or about some parts of it (i.e. organization, job, supervisory, coworkers, salary and income and promotions). Job satisfaction describes the positive or negative attitude of a person regarding his employment and work environment (Weiss, 2002; Greenberg, 2008). This could be both psychological as well as physiological factors (Revenio Jr., 2016).

Satisfaction is a complex and multifaceted concept (Revenio Jr., 2016) that is influenced by both internal and external environmental factors. Work environment is an important determinant of job satisfaction of employees (Herzberg, 1968; Spector, 2008). Existing literature and research results show that job satisfaction is influenced by a variety of factors- both internal and external to the organization. The organizations have a level of control over the internal factors, however, they have very limited or no control of the external environmental factors that influence job satisfaction. Different factors within the working environment such as wages, working hours, autonomy given to employees, organizational structure and communication between employees and management may affect job satisfaction (Lane, Esser, Holte, & Anne, 2010). Therefore, the organization should strive to improve on the factors that they have control over in order to increase the level of job satisfaction. At the same time they should try as much as possible to support those responsible for the external environment to improve it. This may call for initiatives that are similar to the existing public-private partnerships.

The results of a study by Dawal and Taha, (2015) showed that job and environmental factors are significantly related to job satisfaction. Job satisfaction is an outcome of different factors like pay, promotion, the work itself, supervision, relationships with co-workers and opportunities for promotions (Opkara, 2002). Ndulue and Ekechukwu, (2016) have also identified pay, the work itself, promotions, supervision, workgroup, and working conditions as the factors that influence job satisfaction. The level of job satisfaction is affected by intrinsic and extrinsic motivating factors, the quality of supervision, social relationships with work group and the degree to which individuals succeed or fail in their work (Armstrong, 2006).

Pay, the work itself, promotions, supervision, workgroup and working conditions have a great influence on the level of an employee’s satisfaction with the job (Luthans, 1985). According to Saranya, (2014) the important factors that contribute to the higher level of job satisfaction are challenging and responsible job, numerous promotional opportunities, impartial treatment by the management, creativity and innovative ideas of job security, attractive salary and perks, freedom in work situation, participative management and welfare facilities like medical, uniform, canteen etc. Smith, Kendall and Hullin (1969) expressed the five aspects that can be used to determine job satisfaction as; being satisfied from job (i.e. interesting tasks and opportunities for learning and training), being satisfied from supervisor (i.e. technical and managing abilities and their considerations about employees), being satisfied from coworkers (technical qualification and support they show), being satisfied from promotion (achieving real opportunity to advance), being satisfied from income (amount of income, its equality and way of paying to staff).

Other researchers who have investigated the factors that affect job satisfaction include Tabassum, Khan, Sherani, and Khan, (2016) who say that the major determinants of job satisfaction are basically nine facets which are pay, promotion, supervision, fringe benefits, contingent rewards, operating procedures, co-workers, nature of works and communication. Purcell, Kinnie, Hutchinson, Rayton, and Swart, (2003) also did a research and found that the key factors affecting job satisfaction were career opportunities, job influence, team work and job challenge. According to Revenio Jr. (2016) leadership style also has a great role in the employee’s level of job satisfaction. Brudney and Coundry (1993) have also explained different variables that influence performance of the employees in the organization. They included factors such as pay, organization commitment, relationship between pay and performance, etc. Working conditions have positive impact on job satisfaction (Guest, 2004; Silla, Gracia & Peiro, 2005). Job satisfaction is adversely affected by factors such as lack of promotion, working conditions, low job security and low level of autonomy (Guest, 2004; Silla et al., 2005).

It is essential for an organization to motivate their employees to work hard for achieving the organizational goals and objectives. According to Jerrell, Coggburn, Battaglio Jr., and Bradbury, (2014) how an organization manages conflict also has a bearing on employee job satisfaction.

Empirical Review

Various studies have been done on the factors affecting job satisfaction. Some of the factors researched about include job security, leadership/ supervision styles, salaries, promotion opportunities among others. Javed, Balouch and Hassan, (2014) did a study on the determinants of job satisfaction and its impact on employee performance and turnover intentions. The results of the study showed a significant positive association of employee empowerment, workplace environment, job loyalty and job performance with job satisfaction. The results show that employee empowerment has a significant positive relationship and it contributes more than 37% to job satisfaction. Therefore, when an employee is given autonomy in business decisions then his satisfaction level will rise. Furthermore, there was a significant negative relationship between job satisfaction and turnover intention. According to the result of the study, job satisfaction has a significant negative relationship with turnover intentions contributing more than 32% to turnover intentions. Whenever there is low level of employee satisfaction in any organization, the employees of that organization will intentionally leave that organization.

Cheginy, Isfahani, Mohseni, Khakian and Khosravizadeh (2014) did a study to investigate the factors influencing job satisfaction among hospital personnel. The results of the study showed that there is a significant relationship between job satisfaction and personnel’s perceptions about their work conditions, satisfaction with supervision, satisfaction with coworkers, satisfaction with work nature and satisfaction with salary and advantage. Rukh, Choundhary and Abbasi (2015) did a study on the analysis of factors affecting employee satisfaction in Pakistan. Research findings indicated the significant factors that affect the satisfaction level of employees as pay, promotion, relation with employees, relation with supervisor, work stress and job security. The results further showed that the median group differences existed between responses based on age, work experience, salary and designation (i.e. job position/rank) of employees. Job satisfaction was also positively and significantly associated with job related factors such as pay, promotion, relation with employees, relation with supervisor, work stress and job security. From the study they concluded that job satisfaction of employees was significantly affected by demographic, financial and non-financial factors. Employees who are older than 50 years, with greater experience, and in higher management positions were more satisfied with pay, promotion, work stress, work condition and working environment. The employees’ departments did not play any significant role in affecting satisfaction levels.

Viñas-Bardolet, Velazco and Torrent-Sellens (2013) did a study on the determinants of Job Satisfaction, the Role of Knowledge-based work: An illustration from Spain and found that job satisfaction, depends on worker attributes, financial and non-financial job characteristics. The results also show that net monthly income is a positive and highly significant variable in explaining job satisfaction. Evidence suggests that financial and non-financial (work organisation and work intensity) job dimensions are the most important determinants of knowledge-based workers satisfaction in Spain. Mosadegh Rad and De Moraes (2009) did a study to investigate the specific factors associated with job satisfaction and dissatisfaction in employees at the Isfahan University Hospitals (lUHs) in Isfahan, Iran. The study also focused on revealing homogeneous demographic characteristics that these employees exhibited, and which affect their satisfaction level. It was found that overall employees were moderately satisfied with their jobs, and more satisfied with the following aspects of their current work situation: supervision, job identity and co-workers. The lowest satisfaction scores were found for benefits, contingent rewards, communication, salaries, work conditions and promotion. Motivating factors included loyalty to employees, job security, good pay, good working conditions, tactful discipline, involvement, recognition and promotion.

Job security is a significant determinant of job satisfaction. Job security provides workers with a much-needed sense of structure (Woods, 2018). The effect of job security on worker job satisfaction is different depending on whether perceived job loss occurs (or not), whether job openings are scarce or whether job openings are plentiful (Artz & Kaya, 2014). In the results of their study Artz & Kaya (2014) showed that three measures of job security increase private sector worker job satisfaction, and reduce worker incentives to quit. Few workers quit when job openings are relatively scarce (during contractions) than when job openings are relatively plentiful (during expansions). People want to know their job is available for as long as they wish to hold it. When job security decreases, satisfaction and performance levels also take a hit. Results of a study by Reisel, Probst, Chia, Maloles and König, (2010) on the effects of job insecurity on job satisfaction, organizational citizenship behavior, deviant behavior, and negative emotions of employees show that job insecurity is negatively related to satisfaction and that job insecurity has both direct and indirect effects on work behaviors and emotions.

The work environment has also been researched in relation to job satisfaction. Raziq and Maulabakhsh, (2015) did a study on the Impact of Working Environment on Job Satisfaction and found a positive relationship between working environment and employee job satisfaction. Their study concluded that the businesses need to realize the importance of good working environment for maximizing the level of job satisfaction. Other results have also shown that there is a positive link between work environment and intrinsic aspect of the job satisfaction. According to Javed, Balouch, and Hassan, (2014) work place environment has a positive relation with job satisfaction and it contributes 16% to job satisfaction. Since it has a positive impact on job satisfaction so it shows that when an employee is given favorable and clean environment then his/her satisfaction level rises. Bakotic and Babic (2013) found that the workers who work under difficult working conditions, are dissatisfied through this work environment.

Promotions are also an important aspect of a worker’s career and life, affecting other facets of the work experience. With regard to promotions some studies have also been done by various researchers. Malik, Danish and Munir, (2012) did a study to determine the impact of pay and promotion on job satisfaction in higher education institutes of Pakistan and found that pay has significant influence on job satisfaction but the promotion has less influence and partially significant to the job satisfaction. Kosteas (2007) did a study on job Satisfaction and Promotions and found that promotions have a lasting, but diminishing impact on job satisfaction. Kosteas (2007) also find a strong, negative correlation between quits and both job satisfaction and promotion expectations. Promotion has a positive impact on job satisfaction (Nguyen et al., 2003; Teseema & Soeters, 2006). Khan and Mishra, (2013) also did a research on promotion as job satisfaction, a study on Colleges of Muscat, Sultanate Of Oman and the research findings indicate that academic teaching employees where satisfied with the promotion. There was a significant difference in the level of satisfaction. Analysis showed that promotion has a modest and positive effect on job satisfaction.

Mabaso and Dlamini (2017) did a study on the impact of compensation and benefits on job satisfaction and found a positive and significant effect of compensation on job satisfaction (p = 0.263). Moreover, they found that there was no significant effect between benefits and job satisfaction. Therefore, only compensation significantly predicted job satisfaction among academic staff. A study by Usman, Akbar and Ramzan (2013) on the effect of salary and stress on job satisfaction of teachers in District Sialkot, Pakistan found that from the two independent variables (salary and stress) only salary of the teachers was significantly affecting the job satisfaction of teachers. Financial rewards (salary) were found to significantly affect job satisfaction of teachers. Based on the findings of the study by Usman, Akbar and Ramzan (2013) it means that if employees are not given proper salary in time, they would be highly dissatisfied with their jobs and may ultimately start thinking of leaving the profession. This is due to the fact that cost of living is highly increasing in Pakistan. Other results of a study by Muhammed zia Ur Rehman, (2010) found that job satisfaction was significantly related with extrinsic rewards (salary and other benefits). Arian, Soleimani and Oghazian (2018) did a study on job satisfaction and the factors affecting satisfaction in nurse educators and found that there is a positive correlation between job satisfaction and promotion opportunities and that those professors with a high level of job satisfaction had a higher pay and salary. Job satisfaction of bank officers is significantly dependent upon compensation, promotion opportunities, rewards, relation with boss and coworkers. The study found that compensation is the main factor affecting job satisfaction, and it also has significant relationships with job involvement and promotion. Some evidence that workers who are dissatisfied with their bosses are more sensitive to their compensation in deciding on whether they are satisfied with their job was also established from the study.

An affable relationship between supervisor and employee leads to job satisfaction. According to the Essays, UK (November 2013) an amiable supervisor-employee relationship builds the employee’s morale, which makes him to feel affective about his job, especially when his efforts are recognized and rewarded. This brings him satisfaction in his job. Thus, the employee strives to achieve both organizational and personal goals.

A study by Nidadhavolu, Akhila, (2018) on the impact of leadership styles on employee job satisfaction and organizational commitment in the construction sector in India proved that an organization’s leadership style strongly influences employee job satisfaction and organizational commitment. The application of transformational leadership style leads to stronger job satisfaction. This finding established that leadership has a major influence on work outcome and job satisfaction in the company. The employees are most satisfied when they see their leaders possess both relation-oriented and task-oriented behaviors. The study also highlighted a laissez-faire leadership style is a consequence of job satisfaction. The findings show that the laissez-faire leadership style could result in low interpersonal relationships, resulting in weak employee job satisfaction and productivity levels. The research findings found that out of the three construction companies chosen for the study, the laissez-faire leadership style had a negative influence on job satisfaction and organizational commitment on the employees of two companies. Whereas, the transformational leadership style had a positive impact on the employees of one company. The study also discovered the negative influence of upper-management leadership style on employees has a negative influence on organization performance.

Saleem, (2015) did a study on the impact of leadership styles on job satisfaction and mediating role of perceived organizational politics. Research findings revealed that transformational leadership has a positive impact on job satisfaction and transactional leadership has a negative impact on job satisfaction. The findings also suggest that, perceived organizational politics partially mediate the relationship between both leadership styles and job satisfaction.

Sarwar, Mumtaz, Batool and Ikram, (2015) also did a study on the impact of leadership styles on job satisfaction and organizational commitment. This study tested the effects of both transactional and transformational leadership styles of supervisors/ managers on job satisfaction and organizational commitment of employees. Data was collected from the managers and employees working in IT research and development department in Pakistan. The results of the study revealed a positive effect of both transformational and transactional leadership on job satisfaction and organizational commitment, but this effect is more in case of transactional leadership.

Chien- Wen Tsai (2008) did a study on leadership style and employee’s job satisfaction in international tourist hotels. Through correlation analysis, this research found that employees are more satisfied under consideration-style-leadership than construction-style-leadership. After controlling for differences in salary, employees appear to prefer consideration-style-leadership. No matter what the leadership style is, employees’ job satisfaction does not relate towards their coworkers. Besides, employees have different perceptions on work, salary, and overall satisfaction depending on their education level and seniority.

Bulitia, Godrick (2006) did a survey of supervision styles and employee job satisfaction in commercial banks in Kenya. The findings of this study showed a high correlation between supervision styles and job satisfaction. All the correlated statements between supervision styles and job satisfaction had +1 correlation coefficient. This gave a perfect positive correlation meaning the two variables supervision styles and job satisfaction move together in the completely linear manner. However, based on the study results by Bulitia, Godrick (2006) there is need for line managers to improve the use of supervision styles and relationship with employee job satisfaction in Commercial banks in Kenya. For them to improve and succeed in their supervision styles there should be changes at the individual and organizational levels. At individual level improving line managers’ supervision styles, would involve basic education and specific job related training. They should also be encouraged to enhance their skills through continuous self-learning. At organizational level top management should provide appropriate reinforcements for line managers in learning about and improving their supervision styles (Bulitia, Godrick, 2006).

Ayodele, Ekemode and Kajimo-Shakantu (2020) investigated the job satisfaction levels of real estate firms’ employees and the relationship between employees’ personal and demographic characteristics and their job satisfaction levels. Data were analyzed using both descriptive and inferential statistical techniques. The result showed that financial consideration/personal accomplishment was the most important factor influencing employees’ level of satisfaction, followed by work environment skill variety/organizational culture, feedback/fairness, work passion and supervision/workload/work-life balance. The results of the analysis also showed that demographic factors such as age, marital status, academic qualification, management level, years spent under the current line manager, remuneration and number of firm branches had a significant relationship with job satisfaction.

Park (2020) did a study to investigate the direct effects of supervisor satisfaction, public service motivation, and job characteristics on job satisfaction and the indirect effects mediated by organizational commitment. The survey data used for the empirical analysis was collected from central government agencies in the Republic of Korea. The study found that all three factors indirectly affect job satisfaction through organizational commitment. Only job characteristics were found to directly affect job satisfaction (Park, 2020).

Another study done by Abdelmoula and Boudabbous (2021) with the aim of identifying the factors that affect the job satisfaction of professional accountants. The study examined the relative effects of intrinsic and extrinsic factors on job satisfaction among accounting professionals using the principal component analysis (PCA) and multiple regression methods of data analysis. The results of the study showed that three intrinsic factors, namely achievement, the work itself, recognition, along with four extrinsic ones, i.e., salary, relationship with supervisor and co-workers, working conditions, and the company policy, significantly affect the job satisfaction. However, promotion, growth and recognition do not have a significant effect on job satisfaction.

The study by Hussain and Diaz, (2021) identified factors affecting employee job satisfaction in the University of Karachi using a survey questionnaire data. The study found that a generous rewards and compensation packages lead to job satisfaction and are affected by promotion and job security. Good working relationship with co-workers also contributes to employee job satisfaction. The study also found that good working environment also contributes to employee motivation, and is influenced by better facilities, and training and development. Finally, good supervision provides motivation that enhances the quality of output and employee performance.

Jędrzejczak-Gas and Wyrwa (2020) conducted a study to analyze and evaluate environmental factors shaping job satisfaction in a company from the TSL industry. For the study the correlation between general job satisfaction and particular factors of job satisfaction was examined. The values of Spearman’s rank correlation coefficients and Kendall’s tau coefficients were also calculated. The results of the study show that the two most important factors necessary to achieve job satisfaction are access to information necessary for proper performance of work and independence in performing the entrusted tasks.

Okuwa (2019) examined the determinants of job satisfaction and job turnover intention of the workers of selected banks in Ibadan. Multiple sampling methods were used to select the sample (purposive sampling method was employed to select 12 banks that have the highest number of branches in Ibadan, while random sampling technique was used to select 20 respondents from each of the bank). The results showed that adequacy of salary, safety in work place, possibility of promotion, and interpersonal relations among the staff were the factors that enhanced job satisfaction. However, long working hours, job insecurity and conflicts between office and family schedules reduced the job satisfaction of the bankers.

Using an explanatory research design with a quantitative research approach Mekonin and Teklu (2021) did a study to investigate the determinants of employee job satisfaction in the case of kirkos sub-city of Addis Ababa city administration. The data for the study was collected using a structured close-ended questions from a sample of 310 randomly selected employees and was analyzed using inferential statistics with the aid of Statistical Packages for Social Scientists (SPSS) version 23.0. Multiple regression and ANOVA analysis techniques were also used to explain the nature and effects between employees’ job satisfaction and (Gender, Age, Academic level, Work experience, Work position, pay and benefit, working environment, promotion opportunity, relation with supervisors, trust in leadership). The study found that there is a significant effect with pay and benefit, working environment, Promotion opportunities, relation with supervisors, work experience, and trust in leadership to employees’ job satisfaction and regression analysis result indicated that 81.6% of the variation on the employees’ job satisfaction can be explained by the composite measure the independent variables.

Senek. et al. (2020) analyzed data from a cross-sectional mixed-methods survey to investigate the Determinants of nurse job dissatisfaction – findings from a cross-sectional survey analysis in the UK . Logistic regression analysis of the data was done in order to determine what impacts job dissatisfaction. The study found that nearly two-thirds of nurses were dissatisfied and demoralized.

Monica, Devi and Mohapatra (2020) did a study on Determinants of Job Satisfaction. Using a sample of 150 respondents and data collected using questionnaire method the study examined whether job characteristics (JC) and individual characteristics (IC) have an effect on worker’s job satisfaction (JS). The result suggest that job characteristics and self-efficacy are significant predictors of job satisfaction (JS).

Khaira, Afifah; Shariff, and Sima, (2021) did a study on the determinants of employee job satisfaction in Malaysia . This study aimed to determine demographic factors (gender and living areas), education and skills, work environment and compensation as the determinants of employee job satisfaction. Data collected from 132 employees from various sectors in Malaysia was analyzed using Pearson’s correlation and the Ordinal Logistic Regression. From the study it was concluded that living area, education qualification and skills and compensation are significant and considered important factors to meet their job satisfaction compared to gender and work environment.

Ranatunga, (2020) did a study to identify the relationship between pay, promotion, supervision, co-workers and work itself of job satisfaction and job performance among employees in classified hotels. A structured questionnaire was used to collect data from 150 non–executive employees selected using the convenience sampling method. Frequencies, univariate analysis, Pearson’s correlation, T-test and multiple regression analysis as well as multivariate analysis were used in the study. The study concluded that there is a significant positive relationship between selected factors of job satisfaction and job performance. The results of the correlation coefficient showed that pay, promotion, co-workers, supervision, work itself has a significant positive relationship with job performance and it emphasized that pay and co-workers have a strong relationship with job performance. According to the multiple regression analysis, the model was strongly fitted to the data and 40.6% variance of job performance was explained by pay, promotion, co-workers, supervision and work itself of job satisfaction.

Parveen, Maimani, and Kassim (2016) did a study to examine the effects of demographic characteristics on the QWL dimensions and satisfaction, and the relationships between the QWL dimensions and satisfaction, and between satisfaction and retention among nurses and other health care professionals Saudi Arabia. A sample of 360 nurses and other health care professionals was collected in Jeddah, in Saudi Arabia and the data collected was analysed using multivariate analysis of variance and structural equation modeling were used to test the hypotheses. The results of the study show that there is a significant difference between demographic and QWL dimensions and satisfaction. Satisfaction with personal growth and salary package were found to have significant positive impacts on overall retention.

Jigme, and Namgyal, (2021) did a study to determine the relationship between the determinants of job satisfaction such as work environment, pay and allowances, promotion, training and development, and job satisfaction in the Bhutanese context. Data from a sample of 76 civil servants were collected through a questionnaire survey and Google form and analyzed using SPSS 23. The Pearson correlation analysis was performed to find out the relationship between the independent variables (determinants of job satisfaction) and a dependent variable (job satisfaction). Linear regression and multiple regression analysis were also performed to understand the strength and types of relationship. The results of Pearson correlation and regression analysis indicate that the work environment (rp = 0.603, p < 0.01, R 2 = 0.364, B = 0.460), and training and development (rp = 0.583, p < 0.01, R 2 = 0.340, B = 0.383) have strong significant positive relationships with job satisfaction. However, other determinants such as pay and allowances (rp = 0.436, p < 0.01, R 2 = 0.190, B = 0.283) and promotion (rp = 0.395, p < 0.01, R 2 = 0.156, B = 0.288) have moderate relationships with job satisfaction. The result for multiple regression analysis shows that all the determinants have a strong correlation (R = 0.624, R 2 = 0.481, p < 0.01) with job satisfaction and these determinants determine 48.1 percent of the total satisfaction level perceived by the employee. The findings indicate that the work environment is the strongest predictor of job satisfaction as compared to other determinants.

Mensah, Amrago, Asare, Yeboah and Donkor (2020) did a study to investigate the factors affecting job satisfaction amongst workers of the poultry sub-sector: a test of equity theory in the Dormaa Municipality in the Bono Region of Ghana. The multistage sampling technique was employed in collecting data from 100 poultry workers with the aid of a structured questionnaire. The logit model was employed in modeling the factors affecting job satisfaction. The empirical findings reveal that occupational level, pay, and relationships with co-workers were the statistically significant determinants of job satisfaction.

Subarto, Solihin, and Qurbani, (2021) did a study on the determinants of job satisfaction and its implications for the lecturers performance. The purpose of the study was to examine the positive effects of leadership style, work environment, and organizational climate on lecturer performance through Pamulang University’s job satisfaction. The quantitative research method was used and data was collected using survey questionnaires distributed to a sample of 135 respondents selected using a proportional random sampling. Statistical analysis was done using the partial least squares (PLS). From the results of the analysis it was found that leadership style, work environment, and organizational climate have an impact on job satisfaction. Leadership style, work environment, and organizational atmosphere also affect the performance of lecturers. Job satisfaction affects the performance of lecturers and can mediate the influence of leadership style, work environment, and organizational climate on lecturer performance.

From this study it is concluded that the factors that contribute to the positive morale and attitude also result in a higher degree of job satisfaction (Saranya, 2014). The review has shown that the major determinants of job satisfaction are basically nine facets which are pay, promotion, supervision, fringe benefits, contingent rewards, operating procedures, co-workers, nature of works and communication. Job Satisfaction is thus derived from and is the result of many interrelated factors which cannot be completely isolated from one another for analytical purposes. Job Satisfaction is the essential component for employee motivation and encouragement towards better performance (Vroom, 1964). A highly satisfied work force is absolutely necessary for achieving a high level of performance in an organization. Satisfied employees are more likely to be friendly and responsive which attracts customers while dissatisfied employees can lead to customer dissatisfaction (Mahmud, Hasan, and Asif, 2014). It is therefore necessary for organizations to ensure that the above determinants are provided at the required levels to ensure optimum satisfaction of employees. Of all the major job satisfaction areas, satisfaction with the nature of the work itself—which includes job challenge, autonomy, variety, and scope—best predicts overall job satisfaction, as well as other important outcomes like employee retention (Fried & Ferris, 1987; Parisi & Weiner, 1999 as quoted in Ram, (2013).

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Job Satisfaction: A Literature Review

2011, Management Research and Practice

Job satisfaction represents one of the most complex areas facing today's managers when it comes to managing their employees. Many studies have demonstrated an unusually large impact on the job satisfaction on the motivation of workers, while the level of ...

Revisiting the Link between Job Satisfaction and Life Satisfaction: The Role of Basic Psychological Needs

Wenceslao unanue.

1 Business School, Universidad Adolfo Ibáñez, Santiago, Chile

Marcos E. Gómez

Diego cortez.

2 School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile

Juan C. Oyanedel

3 Facultad de Educación, Universidad Andres Bello, Santiago, Chile

Andrés Mendiburo-Seguel

Associated data.

The link between job satisfaction and life satisfaction has been extensively explored in the relevant literature. However, the great majority of past research has been carried out using cross-sectional analyses, and almost exclusively in the Western world. Moreover, the underlying psychological mechanisms explaining the link are not yet completely understood. Thus, we report the first research to date which uses both cross-sectional and longitudinal data among workers in Chile—a fast-developing Latin American economy—and which aims to tackle previous limitations. Three studies consistently support a positive link between the constructs. Study 1 ( N = 636) found that higher job satisfaction predicted higher life satisfaction both contemporaneously and longitudinally, and vice versa, above and beyond several key control variables. Study 2 ( N = 725) and Study 3 ( N = 703) replicated Study 1 results, but tested for the first time the role of satisfaction of basic psychological needs (as stated by self-determination theory) in the job–life satisfaction link. This is the most novel contribution of our paper. Key implications not only for individual quality of life, but also for companies' human resource practices emerge from our findings.

Introduction

How related are job satisfaction and life satisfaction? This question has been extensively explored in the literature (Heller et al., 2002 ). The spillover hypothesis (Bowling et al., 2010 ) is the most supported hypothesis to date. It argues that “job experiences spill over onto other spheres of life, and vice versa, suggesting that a positive relationship exists between the two variables” (Heller et al., 2002 , p. 816). However, there are still three important research gaps in this area. First, previous research has reported results mainly from the Western world (Rain et al., 1991 ; Heller et al., 2002 ; Diener and Tay, 2012 ). Second, most research in the subject is correlational, which does not allow for the inferring of causality (Bowling et al., 2010 ). Third, and finally, the lack of research aiming to give a solid theoretical explanation for the results is surprising (Rain et al., 1991 ; Judge and Watanabe, 1993 ; Rode, 2004 ). In fact, the underlying psychological mechanisms explaining the hypothesis are still not completely understood.

Further, aiming to tackle previous limitations, we explored three large samples of workers in Chile (a fast-developing Latin American economy) using both cross-sectional and longitudinal data, which is very rarely done in this field (Rode, 2004 ). In addition, because recent research has argued that the link between job satisfaction and life satisfaction might be spurious, and that a third variable could be involved (Judge and Watanabe, 1993 ; Rode, 2004 ), we tested for the first time the mediational role of basic need satisfaction (Deci and Ryan, 2000 ) in the job-life satisfaction link.

Job satisfaction and life satisfaction

Happiness has been conceptualized from the hedonic and eudaimonic approaches (Delle Fave et al., 2011 ). The hedonic approach defines happiness in relation to the attainment of pleasure and the avoidance of pain (Ryan and Deci, 2001 ). From this point of view, happiness is often called subjective well-being (Diener, 1984 ), which consists of cognitive (life satisfaction) and emotional (positive and negative emotions) experiences. Life satisfaction represents the judgment that a person makes about his/her life in several domains (Diener, 1984 ; Diener and Tay, 2012 ), and it is the most extended construct for assessing subjective well-being (Helliwell et al., 2013 ). A growing body of research has shown that higher life satisfaction is associated with several desirable companies' results, such as higher career satisfaction, organizational commitment, and especially, job satisfaction (Diener and Tay, 2012 ).

Job satisfaction is a key construct in industrial and organizational psychology, and has been associated with multiple desirable outcomes such as job performance, organizational citizenship behavior, absenteeism, and life satisfaction (Heller et al., 2002 ; Erdogan et al., 2012 ). Most definitions of job satisfaction tend to focus on how employees feel and think about their work (Locke, 1969 ; Smith et al., 1969 ; Weiss, 2002 ; Drafke, 2009 ). These definitions, in a very similar way to those of life satisfaction, involve emotional states, feelings, affective responses, and cognitive evaluations of work (Alonso, 2006 ).

Three hypotheses have been argued to explain the link between job satisfaction and life satisfaction: the segmentation, compensation, and spillover hypotheses (Rain et al., 1991 ; Heller et al., 2002 ; Bowling et al., 2010 ).

The segmentation hypothesis

The segmentation hypothesis suggests that there is no relationship between job satisfaction and life satisfaction. Theoretical positions such as partial inclusion have been proposed to explain the link between both concepts from this perspective (for a review see Rain et al., 1991 ). However, only one study supported this hypothesis in the meta-analysis by Rain et al. ( 1991 ). Indeed, Gupta and Beehr ( 1981 ) found more support for the segmentation hypothesis than for the compensation and spillover ones, among 651 employees of five Midwestern organizations. According to the authors, these findings show that work (e.g., job satisfaction) and non-work aspects (e.g., life satisfaction) load on separate factors.

The compensation hypothesis

The compensation hypothesis states that people compensate for their job dissatisfaction by finding more satisfaction in other areas of their life, and vice versa (Iris and Barrett, 1972 ). Thus, a negative relationship is postulated. Theoretical positions such as the principle of substitution and catharsis theory have been proposed to explain this hypothesis (Rain et al., 1991 ). Very few studies, however, have supported it (e.g., Champoux, 1980 ; Chacko, 1983 ; Schlenker and Gutek, 1987 ; for a review see Rain et al., 1991 ). For example, Schlenker and Gutek ( 1987 ) studied 132 government-employed social workers. Half of them were reassigned to non-professional jobs, and this allowed understanding the impact of their dissatisfaction with the new job on their life satisfaction. The authors found that their discontent because of their work role-loss focused on their new jobs instead of on their satisfaction with life, thus supporting the compensation hypothesis. Chacko ( 1983 ) studied a US national probability sample, which was representative of the American labor force. The authors found that satisfaction with working conditions was a negative source of life satisfaction, thus also supporting the compensation hypothesis.

The spillover hypothesis

The spillover hypothesis argues that there is a positive relationship between job satisfaction and life satisfaction. Theoretical explanations such as generalization of belief and attitudes, conditioning , and cognitive dissonance have been given to explain it (Tait et al., 1989 ; Rain et al., 1991 ). To date, the spillover hypothesis is by far the most supported one in the literature. Meta-analytic techniques and literature reviews confirm these findings (Rice et al., 1980 ; Tait et al., 1989 ; Rain et al., 1991 ; Bowling et al., 2010 ). For example, a meta-analysis by Rice et al. ( 1980 ) explored 350 associations between job satisfaction and overall life satisfaction reported in 23 studies. More than 90% of the 350 statistical relationships supported a positive correlation. However, the reported zero-order correlations were mostly small (mid −0.30 for males and mid –0.20 for females), and none of the negative correlations they found was statistically significant.

The Tait et al. ( 1989 ) meta-analysis also confirmed that the spillover hypothesis is the most evidence-backed one. They explored 34 studies assessing the link between job and life satisfaction, but the authors found larger correlations than Rice et al. ( 1980 ). The corrected correlation (for both sampling error and measurement error) was 0.44. Importantly, whereas the corrected correlation was greater for men ( r = 0.40) than for women ( r = 0.20) in studies prior to 1974, the difference between men ( r = 0.37) and women ( r = 0.39) disappeared in studies after that year. Demographic changes among women, and the role of work in their lives, may explain these findings.

The causal direction of the link between job satisfaction and life satisfaction

Despite the strong empirical support for the spillover hypothesis, most research to date is correlational in nature, which does not allow for the inferring of causality. Does life satisfaction predict job satisfaction or vice-versa? Would a bi-directional link be possible? Unfortunately, only a few studies to date have explored cause–effect patterns, and even these have mostly done so under the assumption that either job satisfaction or life satisfaction are dependent variables. For example, whereas Schmitt and Mellon ( 1980 ) showed that only life satisfaction predicts job satisfaction, Orpen ( 1978 ) and Chacko ( 1983 ) showed that only job satisfaction causes life satisfaction (Judge and Watanabe, 1993 ). Thus, there are hardly any studies that explore and show a reciprocal link (Rain et al., 1991 ; Judge and Watanabe, 1993 ). Nonetheless, a bi-directional link may be expected, thus making previous results inconsistent with the theory.

The causal influence of life satisfaction in job satisfaction: the top-down model

The link between job satisfaction and life satisfaction can be interpreted in two ways: top-down vs. bottom-up models. The top-down model offers a dispositional explanation, claiming that “basic differences in personality and affectivity predispose people to be differentially satisfied with various aspects of their lives, including their jobs” (Heller et al., 2002 , p. 816). Thus, affective states spillover into people's evaluations of their jobs (Judge and Watanabe, 1993 , p. 939). In fact, a substantial body of research has shown that higher life satisfaction is associated with several desirable results for companies, such as higher career satisfaction, organizational commitment, and—of interest here—job satisfaction (Diener and Tay, 2012 ).

The causal influence of job satisfaction on life satisfaction: the bottom-up model

Job satisfaction is a key indicator of workers' well-being (Diener and Tay, 2012 ), and therefore can also influence life satisfaction (Judge et al., 2001 ). Thus, the bottom-up model suggests a situational explanation. That is, “because the job is an important part of adult daily life, people who enjoy their jobs will report greater overall satisfaction with their lives” (Heller et al., 2002 , p. 816). Indeed, research has consistently found that higher job satisfaction is associated with higher life satisfaction (Rice et al., 1980 ; Rain et al., 1991 ). This causal influence of job satisfaction on life satisfaction reflects the importance of work in people's lives, and is the most hypothesized direction of the link (Judge and Watanabe, 1993 ).

The bi-directional link between job satisfaction and life satisfaction

The relationship between job and life satisfaction is likely not only to be a one-way direction, but also reciprocal. Thus, a bi-directional link may be expected (Heller et al., 2002 ). However, only a few exceptions have explored and found reverse causality (Keon and McDonald, 1982 ; Judge and Watanabe, 1993 ). For example, Keon and McDonald ( 1982 ) found that job satisfaction and life satisfaction were jointly determined among employees of an auto parts manufacturer in the US. Judge and Watanabe ( 1993 ) tested a causal model exploring bi-directional associations between job and life satisfaction, over a 5-year period, and controlling for several exogenous influences on life satisfaction (such as age, gender, education, wage rate, and marital status). Based on a national probability sample of US workers, they found that job and life satisfaction were significantly and reciprocally related both cross-sectionally and longitudinally. However, due to the small amount of research on this, and various limitations in the previous studies, scholars have advocated for more longitudinal research in the field exploring causality and the bi-directional link (Judge and Watanabe, 1993 ; Rode, 2004 ). Finally, the meta-analysis by Bowling et al. ( 2010 ) explored longitudinally the association between job satisfaction and subjective well-being. Despite the authors having found a reciprocal causal link between the constructs, the subjective well-being measure did not assess life satisfaction independently. The composite subjective well-being measure included not only life satisfaction, but also positive affect, happiness, and negative affect.

Individual differences in the link between job satisfaction and life satisfaction: moderators and mediators

To date, the great majority of previous research has supported the spillover hypothesis. However, what are the underlying psychological processes behind the link between job satisfaction and life satisfaction? Unfortunately, most studies have not advocated a theoretical proposition (Kabanoff, 1980 ; Rain et al., 1991 ), and the three hypotheses approach seems too simplistic (Rain et al., 1991 ). Indeed, researchers have suggested that more than one relationship between job satisfaction and life satisfaction may operate at any given time point, and that the three hypotheses “may exist for different individuals” (Heller et al., 2002 , p. 816). Thus, more studies exploring different mediators and moderators are needed (Rice et al., 1980 ; Tait et al., 1989 ; Rain et al., 1991 ). Initially, the focus was on the moderator role of gender (Tait et al., 1989 ; Rain et al., 1991 ). However, other potential moderators (such as age, self-employment, locus of control, importance of work, need for achievement) have been suggested later on, but either they are not all consistent or they have not been tested yet (for a review see Rain et al., 1991 ).

Nobel research has proposed another look at the job–life satisfaction link. For example, it has been suggested that “much of the relationship between job satisfaction and life satisfaction is spurious, resulting from common influences” (Rode, 2004 , p. 1206). Therefore, a third or confounding or mediator variable could be involved (Heller et al., 2002 ). Following this theorization, Heller et al. ( 2002 ) explored the role of personality (Big Five, positive/negative affectivity, and core self-evaluations) in the link between job satisfaction and life satisfaction. Using a longitudinal design among US employees, and multisource data, the authors found support for the confounding role of personality, especially core self-evaluations (neuroticism, locus of control, self-esteem, and generalized self-efficacy). After controlling for personality, the magnitude of the association between job and life satisfaction decreased significantly, suggesting the presence of a third variable involved.

However, despite the importance and novelty of these results, they need to be treated with caution, due to some limitations. First, despite the fact that Heller et al. ( 2002 ) argued that their design was longitudinal, it is correlational in nature. A suitable longitudinal model needs to include all relevant T1 and T2 variables in the same model and modeling the stability paths, which in their study was not the case. Second, the authors did not test reciprocal causality: in their first two models, they assumed that job satisfaction precedes life satisfaction, while in the latter two models they took the opposite approach, meaning that life satisfaction precedes job satisfaction.

In another study, Rode ( 2004 ) replicated the findings of Heller et al. ( 2002 ). Using a nationally representative US sample, the author tested a comprehensive model examining the relationship between job satisfaction, life satisfaction and core self-evaluations and found a positive relationship between job satisfaction and life satisfaction over time. Interestingly, the link became non-significant after controlling for the effects of core self-evaluations. Similarly to Heller et al. ( 2002 ), Rode's ( 2004 ) findings present some limitations. First, the author only measured life satisfaction at time 1 (T1) and core self-evaluations at time 2 (T2). Therefore, although he argued the model is a longitudinal cross-lagged one, it is only cross-sectional in nature. A suitable cross-lagged model needs to include lagged paths from each relevant measure (e.g., life satisfaction, job satisfaction) at T1 to all relevant measures at T2, controlling for stability effects (i.e., all constructs need to be represented as potential antecedents and as potential consequences of all other constructs).

Previous results have given initial empirical support to the idea that the link between job satisfaction and life satisfaction may be spurious, and that a third variable could be involved. However, those studies only focused on personality and affectivity variables, without exploring other constructs. We hypothesize that the satisfaction of basic psychological needs as proposed by self-determination theory (Deci and Ryan, 2000 ) may also play a key role in the job–life satisfaction link. Initial evidence may be found in Hombrados-Mendieta and Cosano-Rivas ( 2013 ) and Di Fabio and Kenny ( 2016a ). Hombrados-Mendieta and Cosano-Rivas ( 2013 ) found that workplace support (a proxy of the need for relatedness) protects job satisfaction and life satisfaction against the negative effects of burnout. Di Fabio and Kenny ( 2016a ) stated that the need for relationship and the need for self-determination (a proxy of the need for autonomy) are crucial for workers' well-being. These preliminary results allow us to hypothesize that need satisfaction may mediate the relationship between job satisfaction and life satisfaction.

The role of basic psychological needs in the job–life satisfaction link

Self-determination theory (Deci and Ryan, 2000 ) is a “macro theory of human motivation, emotion and personality” (Vansteenkiste et al., 2010 , p. 105). It states that human beings have three psychological needs—autonomy, competence, and relatedness—which are essential for psychological well-being and integration. Just as plants need essential nutrients, such as water and minerals, so people have essential needs too (Reis et al., 2000 ).

The need for autonomy (DeCharms, 1968 ) refers to the perception that our behavior is volitional and meaningful; the need for competence (White, 1959 ) refers to feeling effective and efficient in our behavior, as well as being able to successfully manage difficult challenges and meet performance standards; the need for relatedness (Baumeister and Leary, 1995 ) refers to feeling connected, appreciated and understood by others who are important (Vansteenkiste et al., 2010 ; Unanue et al., 2014 ). Therefore, feeling able to decide what to do and that these actions are valuable and enjoyable ( autonomy ); feeling good at daily activities ( competence ); and having meaningful and deep relationships with people who is important to us ( relatedness ) are the key nutrients for people flourishing (Deci and Ryan, 2000 ).

A substantial amount of research has supported the self-determination theory claims, showing that satisfaction of psychological needs is significantly associated with higher well-being both in general life and at work. For example, in everyday life settings, Unanue et al. ( 2014 ) showed that higher need satisfaction in life settings is associated with higher well-being (e.g., life satisfaction, vitality and positive affect) and lower ill-being (physical symptoms, negative affect and depressive symptoms). These findings have been replicated across the lifespan, as well as cross-culturally (Chen et al., 2014 ). In job settings, a recent meta-analysis (Van den Broeck et al., 2016 ), reviewing 99 studies with 119 distinct samples, found that the satisfaction of basic psychological needs at work is significantly associated not only with higher well-being (e.g., life satisfaction) but also with several desirable organizational outcomes (e.g., job satisfaction).

Previous findings allow us to hypothesize that the link between job satisfaction and life satisfaction may be spurious, and instead is rooted in basic needs satisfaction. This is because both job satisfaction and life satisfaction seem to be dispositionally based, and the same characteristics that predict one construct (job satisfaction) also predict the other (life satisfaction) (Heller et al., 2002 ). The role of psychological needs was suggested more than 30 years ago (Champoux, 1981 ; Rain et al., 1991 ). However, it has not been tested until now.

Therefore, in our research, we explore the confounding influence of basic need satisfaction (Deci and Ryan, 2000 ) on the link between job and life satisfaction. Because need satisfaction in life settings as well as at work predict well-being, our research will test both kinds of need satisfaction in the mentioned link.

Research gaps: justification for the present research

As mentioned before, meta-analytic techniques and literature reviews confirm that the spillover hypothesis is the most supported explanation for the link between job and life satisfaction. However, several methodological and theoretical research gaps have emerged in the field (Tait et al., 1989 ; Rain et al., 1991 ; Heller et al., 2002 ).

In methodological terms, there are two aspects that need to be improved: samples and design (Rain et al., 1991 ). First, most research so far has focused on samples from the Western world 1 . Therefore, culture has not been taken into account. Nonetheless, cross-cultural research has shown that cultural aspects might influence several links (Thomas and Au, 2002 ; Thomas and Pekerti, 2003 ). Moreover, recent research has shown that the effects of happiness (such as life satisfaction) may be specific to some individualistic cultures (Ford et al., 2015 ). Such findings raise the question of whether the associations between job and life satisfaction found in the Western world are also held in different populations with different demographic characteristics, like Chile (Heller et al., 2002 ).

Second, most designs are still correlational in nature, and reciprocal causality has not been extensively explored using suitable cross-lagged models (Rain et al., 1991 ; Judge and Watanabe, 1993 ; Rode, 2004 ). In theoretical terms, and in spite of the spillover hypothesis receiving most of the empirical support, no satisfactory theoretical explanation has been offered (Rain et al., 1991 ). Indeed, research so far has done little to test the underlying psychological process behind the link (Rain et al., 1991 ; Judge and Watanabe, 1993 ).

Job satisfaction research in Chile

Data on well-being has only appeared recently in Latin America (Montero and Vásquez, 2015 ), and there is only one paper in which the job-life satisfaction link in Chile is studied: Loewe et al. ( 2014 ). Loewe et al. ( 2014 ) found support for the spillover hypothesis, showing that Chilean workers attribute most importance to their financial “situation, followed by family, work, and health” (p. 80). However, several limitations emerge from the paper. For example, it is correlational in nature and neither alternative models nor causality was tested. In addition, no underlying mechanisms for explaining the job-life satisfaction link were tested.

A few additional researchers have explored job satisfaction in Chile. For example, Cassar ( 2010 ) studied a representative sample of the Oxford Poverty and Human Development Initiative (OPHI) database, and found that the degree of employment protection, workplace facilities and level of independence were positively associated with job satisfaction. Using the same data set, Montero and Rau ( 2014 ) found a positive relationship between salaries and job satisfaction, while Montero and Vásquez ( 2015 ) showed the impact of reference wages on job satisfaction. Finally, using the CASEN survey (National Socio-Economic Characterization Survey) and OPHI, Montero and Rau ( 2015 ) found that part-time work has a negative effect on job and life satisfaction for men, but a positive effect for women. The above-mentioned represent a notable contribution to the job satisfaction literature in Chile. Nonetheless, these studies suffer from certain limitations. They are cross-sectional in nature, they did not explore the underlying psychological process, and more importantly, they did not test the link between job satisfaction and life satisfaction.

Summary of aims and predictions

With the aim of tackling previous research gaps, we conducted three different studies among Chilean workers. We had three objectives in mind. First, to test whether the cross-sectional positive link (spillover hypothesis) between job and life satisfaction found in the Western world is held among workers from Chile, controlling for several key confounding variables not assessed to date. Second, because the great majority of past research has been carried out using cross-sectional analyses, we used longitudinal designs to test a possible bi-directional causal link between the core variables. Third, and finally, for the first time a comprehensive model was tested. It allowed us to examine the relationship between job and life satisfaction over time while taking into account the possible confounding role of a third variable: basic psychological needs.

Chile is a country with increasing mental health problems at work (MINSAL, 2017 ). Indeed, the Ministry of Labour in Chile warns that Chilean employees are in danger of serious psychological problems at work (Mutual de Seguridad, 2015 ). By understanding the job-life satisfaction dynamic we aim to help companies to develop strategies not only for protecting their employees' mental health, but also for improving employees' quality of life and happiness. In addition, because of the close link between life/job satisfaction and productivity, our findings may help to improve companies' profitability and sustainability (Diener and Tay, 2012 ; Montero and Vásquez, 2015 ).

Further, based on the previous evidence, we tested the following hypotheses:

(H1) Job satisfaction is positively associated with life satisfaction correlationally (Study 1; Study 2; Study 3).
(H2) Higher job satisfaction predicts higher life satisfaction prospectively and vice versa (longitudinally) (Study 1; Study 2; Study 3).
(H3) Need satisfaction at work explains the positive link between job satisfaction and life satisfaction both contemporaneously (correlationally) and prospectively (longitudinally). (Study 2).
(H4) Need satisfaction in life explains the positive link between job satisfaction and life satisfaction both contemporaneously (correlationally) and prospectively (longitudinally). (Study 3).

Study 1 was carried out in accordance with the guideline recommendations of the American Psychological Association, British Psychological Society and World Medical Association Declaration of Helsinki. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ethics Committee of the Adolfo Ibáñez University.

At baseline (June 2016; T1), participants were invited online to take part in a research project where the core measures for the present paper were collected (job satisfaction and life satisfaction) 2 . Two months later (August 2016; T2), the same participants were asked to complete another online survey with identical measures. Initially, respondents were sent an introductory email containing a brief description of the study, along with a web link to the survey created using Qualtrics software.

Following Simmons et al.'s ( 2011 ) guidelines, all target sample sizes were determined in advance in Study 1, and in all further studies. Using a power analysis with G * Power 3.1 (Faul et al., 2009 ), considering a hypothesized small effect size (0.18; Bosco et al., 2015 ), power of 0.80, and p -value = 0.05, the desired sample was estimated as a minimum of N = 187. Both our cross-sectional data at T1 ( N = 636) and T2 ( N = 268), and our longitudinal data ( N = 210), fulfill the required sample size. This minimum sample size ( N = 187) also applies to Study 2 and Study 3.

We followed a key rule for collecting T1 data. We informed participants that the online system would be open for only 3 days (due to the original design of Unanue et al., 2017 ). Participants were informed that the project was part of a longitudinal study and were asked for their consent in participating in future waves. All T1 participants were sent a further email in August 2016 (T2). The rule for collecting T2 data was only slightly different. To be able to find reasonable effect sizes, we considered that it would be important to recruit a large sample aiming to reach a power of 0.80 both cross-sectionally and longitudinally.

Almost all constructs used in Study 1 showed acceptable distributions (George and Mallery, 2010 ). Skew values were acceptable for life satisfaction (T1: −1.45; T2: −0.05) and job satisfaction (T1: −1.2; T2: −1.03). Kurtosis values were acceptable for job satisfaction (T1: 1.75; T2: 1.34). In the case of life satisfaction, Kurtosis values were acceptable at T2 (0.58), but not at T1 (4.41).

In total, 636 Chilean working adults (52.8% female) aged from 22 to 71 years (Mean age = 39.76; SD = 8.61) finished the whole survey and completed our T1 measures. Of them, 475 (74.69%) provided their e-mail address for future waves. At T2, 268 participants (55.6% female) aged from 20 to 80 years (Mean age = 40.47; SD = 10.73) answered our core measures (56.42% response rate). Finally, 210 workers (56.2% female) aged from 23 to 71 years (Mean age = 40.16; SD = 9.17) answered both waves. 3

We used the following measures for Study 1.

Job satisfaction

We used a single question: “All in all, how satisfied are you with your job?” Participants answered on an 11-point scale, ranging from “extremely unsatisfied” (0) to “extremely satisfied” (10). Meta-analytic analysis demonstrated that this single question is highly valid for measuring job satisfaction (Dolbier et al., 2005 ).

Life satisfaction

We used a single question: “All in all, how satisfied are you with your life?” Participants answered on an 11-point scale, ranging from “extremely unsatisfied” (0) to “extremely satisfied” (10). This question is the most extensive single item question designed to measure life satisfaction, and it has shown good psychometric properties (Helliwell et al., 2013 ).

Demographic variables

At T1, we asked participants to report their age and gender status. However, at T2, we asked participants also to report additional demographic variables such as education, economic sector (mining, transport, etc.), working area (marketing, finance, etc.), managerial functions (whether or not they lead people), monthly personal income, and monthly family income. Our results showed that participants who answered both waves differed in several demographic characteristics such as education (high school education 5.71%, Bachelors degree 31.90%, post-graduate degree 61.43%, other 0.95%); economic sector (health and social services 18.10%, education 14.76%, commerce 7.62%, community services 5.71%, public sector 4.76%, mining 4.29%, financial services 3.81%, manufacturing 3.81%, transport 3.81%, others 33.33%); working area (accounting 0.95%, technology 1.90%, administration 4.29%, finance 5.71%, operations 7.14%, marketing 6.19%, human resources 36.20%, others 37.62%); managerial positions (58%); net personal monthly average income (mean = US$ 5,789.30; SD = 3,664.30); and net family monthly average income (US$1,853.10; SD = 1,396.30). As stated by Judge and Watanabe ( 1993 ), what is crucial when studying the link between job and life satisfaction is “the use of extensive controls derived from past theory and research”, the lack of which was a limitation in previous studies (p. 940). Thus, we aimed to tackle this limitation by using our extensive number of control variables.

Data analysis

All constructs of interest were measured at T1 and T2. Descriptive statistics and intercorrelations for all the study variables are shown in Table Table1 1 (cross-sectional analyses) and Table Table2 2 (longitudinal analysis). We used AMOS 22 software (Amos Development Corporation, Florida, USA) to estimate an autoregressive cross-lagged model (Finkel, 1995 ) through path analysis. We used full maximum likelihood estimation in all our analyses. All the paths in Study 1 and all further studies were standardized. Because this was a saturated model, the fit indices were perfect.

Descriptives and inter-correlations between all study 1 variables .

Descriptives and inter-correlations between all study 1 variables, at Time 1 (T1) and Time 2 (T2) (longitudinal data) .

Cross-sectional analyses

First, we set up a cross-sectional model to test H1, and to determine the size of the association between job satisfaction and life satisfaction at T1 and T2. We controlled for age and gender. At T1 (Figure (Figure1), 1 ), we found that job satisfaction was significantly and positively related to life satisfaction, β = 0.43, p < 0.001. At T2 (Figure (Figure1), 1 ), job satisfaction was also significantly and positively related to life satisfaction, β = 0.49, p < 0.001. These results show a medium effect size (Cohen, 1992 ) for the association between job and life satisfaction, supporting H1 at both T1 and T2.

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Study 1 . Structural correlational model for the association between job satisfaction and life satisfaction at Tl and T2. T2 data are in brackets. Coefficients shown are standardized paths.T1, Time 1; T2, Time 2. *** p < 0.001.

Longitudinal analysis

We used a cross-lagged longitudinal design to disentangle the causal direction between job satisfaction and life satisfaction, aiming to test H2 and H3. Here, we controlled for age and gender, but also for education, economic sector, working area, managerial functions, net monthly personal income, and net monthly family income. A two-factor model where each T2 measure was regressed on both its own lagged measure as well as the other lagged measures was defined. We allowed the observed measures to covary within each time point. Thus, all constructs were represented as potential antecedents and as potential consequences of all other constructs, while controlling for stability effects. Values of R 2 were also acceptable ( p < 0.001) ranging from 0.49 (life satisfaction) to 0.43 (job satisfaction) ( p < 0.001). We found that job satisfaction was a significant and positive prospective predictor of life satisfaction, β = 0.21, p < 0.01. In addition, we found that life satisfaction was a significant and positive prospective predictor of job satisfaction, β = 0.23, p < 0.001. These results show that longitudinally, job satisfaction predicts life satisfaction and vice versa, supporting H2. Importantly, the prospective bi-directional link remained above and beyond all our control variables. Paths are reported in Figure Figure2 2 .

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Study 1 . Structural longitudinal model for the association between job satisfaction and life satisfaction. Coefficients shown are standardized paths. Error terms and covariances are not shown to enhance visual clarity. Tl, Time 1; T2, Time 2. *** p < 0.001.

Study 1 brief discussion

Study 1 supported H1 and H2, but also allowed us to tackle several limitations found in the previous literature. Supporting the spillover hypothesis (Tait et al., 1989 ; Rain et al., 1991 ; Bowling et al., 2010 ), we found a cross-sectional and causal positive bi-directional link between job satisfaction and life satisfaction among workers from Chile. Importantly, the correlational and longitudinal links were found while controlling for several demographic and confounding variables not assessed in previous research (age, gender, education, marital status, salary, etc.). Indeed, Judge and Watanabe ( 1993 ) argued that when studying the link between job and life satisfaction, the use of extensive controls is crucial. Indeed, our results suggest taking into account the demographic variables as control variables when studying the job-life satisfaction link. Finally, it is worth mentioning that a limitation of Study 1 design is that it did not allow testing a third variable that may be driving the mentioned link. Thus, in Study 2 we tested the confounding influence of need satisfaction at work, whereas in Study 3 we tested the confounding influence of need satisfaction in general life setting.

Study 2 followed the same ethical rules as Study 1. We utilized a cross-lagged longitudinal design with 4 weeks between the two observations and a wide sample of Chilean worker adults. At the baseline (September 2016; T1), participants were invited online to take part in a research project where the core measures for the present paper were collected (job satisfaction, life satisfaction and need satisfaction at work 4 ). A university in Santiago provided a mailing list for both Study 2 and Study 3. Participants were informed that the project was part of a longitudinal study and were asked for their consent to participate in future waves. Four weeks later (October 2016; T2), the same participants were asked to complete another online survey with identical measures. Respondents received an introductory email containing a brief description of the study, along with a web link to the survey created using Qualtrics software.

We followed a key rule for collecting T1 and T2 data. The survey was kept open for only 1 week, and every working day a polite reminder was sent to those respondents who had not answered. Both our cross-sectional data at T1 ( N = 725) and T2 ( N = 275), and our longitudinal data ( N = 274) fulfilled the required minimum sample size according to our power analysis mentioned previously.

In total, 725 Chilean worker adults (47.9% female) aged from 21 to 72 years (Mean age = 38.03; SD = 10.01) finished the whole survey and completed our T1 measures. At T2, 275 participants (47.3% female) aged from 21 to 72 years (Mean age = 39.69; SD = 10.24) answered our core measures (37.93% response rate). Finally, 274 workers (47.1% female) aged from 21 to 72 years (Mean age = 39.75; SD = 10.20) answered both waves.

All constructs used in Study 2 showed acceptable distributions (George and Mallery, 2010 ). Skew values were acceptable for life satisfaction (T1: −1.14; T2: −0.98), job satisfaction (T1: −0.69; T2: −0.91) and need satisfaction at work (T1: −0.53; T2: 0.62). Kurtosis values were acceptable for life satisfaction (T1: 1.53; T2: 0.91), job satisfaction (T1: −0.13; T2: 0.62) and need satisfaction at work (T1: 0.09; T2: −0.04).

Job satisfaction and life satisfaction were measured using the same single items used in Study 1. However, in this study, the job satisfaction question was answered on a scale from 1 to 7. Need satisfaction was measured using the Satisfaction items of the Need Satisfaction and Frustration scales adapted to the work context (Chen et al., 2014 ). The satisfaction subscale included 12 items: four for autonomy (“I feel my choices on my job express who I really am”), four for competence (“At work, I feel capable at what I do”), and four for relatedness (“At work, I feel connected with people who care for me, and for whom I care”). Participants rated these statements on a 7-point Likert-type scale ranging from 1 (not at all true) to 7 (very true) . The internal reliability of the need satisfaction scale was good, both at T1 (α = 0.90) and T2 (α = 0.90). Chen et al.'s ( 2014 ) scale has shown good psychometric properties and demonstrated that the items load in a single factor. Thus, we calculated a need satisfaction mean score by averaging its 12 indicators.

All constructs were measured at T1 and T2. Descriptive statistics and intercorrelations for all the study variables are shown in Table Table3 3 (cross-sectional analyses) and Table Table4 4 (longitudinal analysis). We used AMOS 22 software (Amos Development Corporation, Florida, USA) to estimate an autoregressive cross-lagged model through path analysis (Finkel, 1995 ). We used full maximum likelihood estimation in all our analyses. Because this was a saturated model, the fit indices were perfect.

Descriptives and inter-correlations between all study 2 variables .

Descriptives and inter-correlations between all study 2 variables, at Time 1 (T1) and Time 2 (T2) (longitudinal data) .

First, we set up a cross-sectional model. At T1 (Supplementary Figure 1 ), we found that job satisfaction was significantly and positively related to life satisfaction, β = 0.30, p < 0.001. Thus, H1 was supported at T1. Then, to test H3, we included need satisfaction in the model. We allowed need satisfaction to predict both job and life satisfaction. We found that need satisfaction was positively associated with both life satisfaction, β = 0.40, p < 0.001, and job satisfaction, β = 0.64, p < 0.001. In support of H3, when need satisfaction was included in the model, the path between life and job satisfaction becomes non-significant, β = 0.06, p = 0.09 (Supplementary Figure 2 ). At T2 (Supplementary Figure 1 ), we found that job satisfaction was significantly and positively associated with life satisfaction, β = 0.40, p < 0.001. Thus, H1 was also supported at T2. Then, to test H3, we included need satisfaction in the model. We found that need satisfaction was positively associated with both life satisfaction, β = 0.42, p < 0.001, and job satisfaction, β = 0.74, p < 0.001 (Supplementary Figure 2 ). In support of H3, when need satisfaction was included in the model, the path between life satisfaction and job satisfaction, although still significant, decreased by almost half of its original value, β = 0.16, p < 0.10.

First, we started with a structural cross-lagged reciprocal model for our core variables (job and life satisfaction), following the same strategy as for Study 1. Second, we allowed the three measures to covary within each time point, and we modeled lagged paths from each of the three measures to all three measures at each successive time point. Therefore, all constructs were represented both as potential antecedents and potential consequences of all other constructs, while controlling for stability effects. Supporting H2, we found that job satisfaction was a positive prospective predictor of life satisfaction, β = 0.09, p < 0.05, and that life satisfaction was a significant and positive prospective predictor of job satisfaction, β = 0.14, p < 0.001 (Figure (Figure3). 3 ). R 2 was good for job satisfaction (0.43) and life satisfaction (0.53). Given the important role hypothesized by need satisfaction at work in the job-life satisfaction relationship, we tested a structural model to establish whether need satisfaction influenced both variables (Figure (Figure4). 4 ). In this new model, R 2 was good for job satisfaction (0.50), life satisfaction (0.53), and need satisfaction at work (0.62). We found that need satisfaction at work was a significant and positive prospective predictor of job satisfaction, β = 0.35, p < 0.001 and that life satisfaction was a significant and positive prospective predictor of need satisfaction at work, β = 0.08, p < 0.05. They were the only significant paths. Importantly, after controlling for need satisfaction at work, the reciprocal link between job satisfaction and life satisfaction becomes non-significant, supporting H3. Indeed, job satisfaction did not predict life satisfaction longitudinally, β = 0.07, p = 0.17 and similarly, life satisfaction did not predict job satisfaction longitudinally, β = 0.06, p = 0.13 when controlling for need satisfaction at work.

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Study 2 . Structural longitudinal model for the association between job satisfaction and life satisfaction. Coefficients shown are standardized paths. Error terms are not shown to enhance visual clarity. T1, Time 1, T2, Time 2. *** p < 0.001.

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Study 2 . Structural longitudinal model for the association between job satisfaction and life satisfaction, and need satisfaction at work. Coefficients shown are standardized paths. Error terms are not shown to enhance visual clarity. T1, Ti me 1; T2, Time 2. *** p < 0.001.

Study 2 brief discussion

The results of Study 2 replicated the findings of Study 1, thus supporting H1 and H2, and, in turn, the spillover hypothesis (Tait et al., 1989 ; Rain et al., 1991 ). More importantly, taking a bottom-up approach (Diener and Tay, 2012 ), we found that the cross-sectional and longitudinal links between job satisfaction and life satisfaction was mediated by need satisfaction at work (Deci and Ryan, 2000 ). This key finding supports H3. However, despite the important results of Study 2, it only tested the confounding role of need satisfaction in job settings. Thus, Study 3 is aimed to test the role of need satisfaction in general life settings.

Study 3 followed the same ethical rules as Study 1 and Study 2. We used a cross-lagged longitudinal design with 4 weeks between the two observations and a sample of Chilean working adults. At the baseline (September 2016; T1), participants were invited online to take part in a research project including the core measures for the present paper (job satisfaction, life satisfaction and need satisfaction in life 5 ). Participants were informed that the project was part of a longitudinal study and were asked for their consent to participate in future waves. All T1 participants were sent a further email in October 2016 (T2). Thus, 4 weeks later (October 2016; T2), the same participants were asked to complete another online survey with identical measures. Respondents were sent an introductory email containing a brief description of the study, along with a web link to the survey created using Qualtrics software.

We followed the same rules as in Study 1 for collecting T1 and T2 data. Both our cross-sectional data at T1 ( N = 703) and T2 ( N = 263), and our longitudinal data ( N = 258) fulfilled the required minimum sample size according to the power analysis.

Almost all constructs used in Study 3 showed acceptable distributions (George and Mallery, 2010 ). Skew values were acceptable for life satisfaction (T1: −1.30; T2: −1.60), job satisfaction (T1: −0.83; T2: −0.87), and need satisfaction in life (T1: −1.14; T2: −1.61). Kurtosis values were acceptable for life satisfaction (T1: 2.06; T2: 2.68), job satisfaction (T1: 0.24; T2: −0.01). However, Kurtosis values for need satisfaction in life were acceptable at T1 (1.86), but not at T2 (4.37).

In total, 703 Chilean working adults (43.2% female) aged from 21 to 69 years (Mean age = 38.45; SD = 9.59) finished the whole survey and completed our T1 measures. At T2, 263 participants (44.5% female) aged from 23 to 68 years (Mean age = 39.32; SD = 9.72) answered our core measures (37.41% response rate). Finally, 258 workers (44.6% female) aged from 23 to 68 years (Mean age = 39.10; SD = 9.63), answered both waves.

Job satisfaction was measured using the same single items used in Study 2. Life satisfaction was measured using the same single items used in Study 1. Need Satisfaction in life was measured using the items of the Need Satisfaction and Frustration scales, but in its original version, which aimed to explore life settings (Chen et al., 2014 ). The internal reliability of the need satisfaction scale was good, both at T1 (α = 0.90) and T2 (α = 0.93). We calculated a need satisfaction mean score by averaging its 12 life indicators.

All constructs were measured at T1 and T2. Descriptive statistics and intercorrelations for all the study variables are shown in Table Table5 5 (cross-sectional analyses) and Table Table6 6 (longitudinal analysis). We used AMOS 22 software (Amos Development Corporation, Florida, USA) to estimate an autoregressive cross-lagged model through path analysis (Finkel, 1995 ). We used full maximum likelihood estimation in all our analyses. Because this was a saturated model, the fit indices were perfect.

Descriptives and inter-correlations between all study 3 variables .

Descriptives and inter-correlations between all study 3 variables, at Time 1 (T1) and Time 2 (T2) (longitudinal data) .

First, we set up a cross-sectional model. At T1 (Supplementary Figure 3 ), we found that job satisfaction was significantly and positively related to life satisfaction, β = 0.52, p < 0.001. Therefore, H1 was supported at T1. To test H4, we included need satisfaction in the model. We allowed need satisfaction to predict both job satisfaction and life satisfaction (Supplementary Figure 4 ). Need satisfaction was positively associated with both life satisfaction, β = 0.47, p < 0.001, and job satisfaction, β = 0.72, p < 0.001. However, in support of H4, when need satisfaction was included in the model, the path between job satisfaction and life satisfaction decreased by almost half of its original value, β = 0.30, p < 0.001. At T2 (Supplementary Figure 3 ), we found that job satisfaction was significantly and positively related to life satisfaction, β = 0.66, p < 0.001. Thus, H1 was supported at T2. To test H4, we included need satisfaction in the model (Supplementary Figure 4 ). We found that need satisfaction was positively associated with both life satisfaction, β = 0.77, p < 0.001, and job satisfaction, β = 0.66, p < 0.001. In support of H4 at T2, when need satisfaction was included in the model, the path between life and job satisfaction decreased to almost half of its original value, β = 0.32, p < 0.001.

First, we started with a structural cross-lagged reciprocal model for our core variables (job and life satisfaction), following the same strategy as for Study 2. Second, we allowed the three measures to covary within each time point, and we modeled lagged paths from each of the three measures to all three measures at each successive time point. Thus, all constructs were represented as potential antecedents and consequences of all other constructs, while controlling for stability effects. Supporting H2, we found that job satisfaction was a positive prospective predictor of life satisfaction, β = 0.08, p < 0.05, and that life satisfaction was a significant and positive prospective predictor of job satisfaction, β = 0.18, p < 0.001 (Figure (Figure5). 5 ). R 2 was good for job satisfaction (0.56) and life satisfaction (0.70). Then, given the role hypothesized by need satisfaction in the job-life satisfaction relationship, we ran a structural equation model to assess whether need satisfaction influenced both variables aiming to test H4 (Figure (Figure6). 6 ). In this model, R 2 was good for job satisfaction (0.60), life satisfaction (0.72), and need satisfaction (0.71). We found that need satisfaction in life was a significant and positive prospective predictor of both job satisfaction, β = 0.29, p < 0.001 and life satisfaction, β = 0.22, p < 0.001. Moreover, we found that job satisfaction was a significant and positive prospective predictor of need satisfaction in life, β = 0.09, p < 0.05. No other significant prospective paths were found. After controlling for need satisfaction, the reciprocal link between job satisfaction and life satisfaction became non-significant, supporting H4. We found that job satisfaction does not predict life satisfaction longitudinally, β = 0.05, p = 0.21 and life satisfaction does not predict job satisfaction longitudinally, β = 0.08, p = 0.99, when controlling for need satisfaction.

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Study 3 . Structural longitudinal model for the association between job satisfaction and life satisfaction. Coefficients shown are standardized paths. Error terms are not shown to enhance visual clarity. T1, Time 1; T2, Time 2. *** p < 0.001.

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Study 3 . Structural longitudinal model for the association between job satisfaction and life satisfaction, and need satisfaction at life. Coefficients shown are standardized paths. Error terms are not shown to enhance visual clarity. Tl, Time 1; T2, Time 2. *** p < 0.001.

Study 3 brief discussion

Study 3 results also replicated Study 1 findings, thus supporting H1 and H2. In addition, taking a top-down approach (Heller et al., 2002 ), it was found that the cross-sectional and causal bi-directional positive link between job satisfaction and life satisfaction is rooted in need satisfaction in life (Deci and Ryan, 2000 ). This key finding supports H4.

General discussion

So, returning to our initial question—Are job satisfaction and life satisfaction related?—we can say that despite the limitations of previous research, three hypotheses have emerged to explain their possible association (Rain et al., 1991 ; Heller et al., 2002 , p. 288): the segmentation, compensation, and spillover hypotheses. The segmentation hypothesis suggests that there is no association between both variables. The compensation hypothesis states that either high job satisfaction or high life satisfaction compensates for the dissatisfaction in the other area (i.e., there is a negative association). Finally, the spillover hypothesis claims that both variables are positively associated. We have tested these hypotheses through three studies involving both cross-sectional and longitudinal analysis among workers in Chile.

Consistently, Study 1, Study 2, and Study 3 showed that job satisfaction and life satisfaction are positively related both cross-sectionally and longitudinally bi-directionally, thus supporting the spillover hypothesis. Study 1 found that job satisfaction predicts increases in life satisfaction, which in turn predict increases in job satisfaction, and vice versa, thereby creating a virtuous circle in both individual and organizational well-being. Importantly, the link holds when controlling for age, gender, education, economic sector, working area, managerial functions, net monthly personal income, and net monthly family income. Thus, Study 1 aimed to approach Judge and Watanabe ( 1993 ) suggestion. He stated that when studying the link between job and life satisfaction, the use of extensive controls is crucial. Studies 2 and 3 replicated the findings of Study 1 in independent samples. Therefore, our results support the spillover hypothesis in the case of Chile and also show that this relationship is bi-directional.

However, a novel contribution of our research is the fact that the association between job satisfaction and life satisfaction may be spurious, and that a third variable could have an effect: basic need satisfaction (Deci and Ryan, 2000 ). Across two longitudinal studies (Studies 2 and 3), we can see that when need satisfaction is included at the same time as job satisfaction and life satisfaction, the job-life satisfaction bi-directional link becomes non-significant over time. These results were found using both a bottom-up approach (Study 2: need satisfaction at work ) and a top-down approach (Study 3: need satisfaction in general life settings ). This “spurious association” hypothesis has been proposed before (Heller et al., 2002 ; Rode, 2004 ), but only with regard to personality variables as mediators (e.g., Big Five, core self-evaluations). However, our research is the first attempt to test the role of the psychological needs for autonomy, competence and relatedness as stated by self-determination theory (Deci and Ryan, 2000 ). The results show that need satisfaction plays a key role in the process. Thus, our results support previous theorizations and findings in that a third variable may be driving the job-life satisfaction link.

Studying Chile allows us to extend previous research mostly done in the Western world. Our aim is for our results to be able to help companies to develop strategies not only for protecting their employees' mental health, but also for improving the employees' quality of life and happiness. Indeed, this issue is especially important in Chile, a country where the Ministry of Labor has recently warned that employees are in danger of serious mental health problems (Mutual de Seguridad, 2015 ). In addition, as mentioned previously, due the strong link between life/job satisfaction and productivity, we hope our findings may also help companies to increase their profitability and sustainability (Diener and Tay, 2012 ; Montero and Vásquez, 2015 ).

Practical implications for people and organizations

What can be drawn from our research? Job satisfaction and life satisfaction are strongly related to several desirable outcomes both in life and at work (Diener and Tay, 2012 ). For example, whereas job satisfaction has been associated with higher job performance, organizational citizenship behavior and life satisfaction and lower absenteeism and turnover intentions (Heller et al., 2002 ; Erdogan et al., 2012 ), life satisfaction has been associated with higher career satisfaction, organizational commitment and job satisfaction (Diener and Tay, 2012 ). Our results show a key mechanism which companies may use if they wish to have happier and more engaged and productive workers: organizations should help employees to satisfy their psychological needs for autonomy, competence, and relatedness. Further, companies should help workers to feel that their behavior is volitional and meaningful (autonomy satisfaction); that they are effective and efficient in their behavior (competence satisfaction) and feel connected, appreciated and understood by important others (relatedness satisfaction) as stated by self-determination theory (Deci and Ryan, 2000 ; Van den Broeck et al., 2016 ).

Therefore, helping workers to feel that they are able to decide what to do, as well as feeling good at daily activities, and having meaningful and deep relationships with people who is important for them, are key nutrients for satisfying their psychological needs, making them more satisfied not only with their lives, but also with their jobs (Deci and Ryan, 2000 ; Van den Broeck et al., 2016 ). Thus, when companies help employees to satisfy their needs for autonomy, competence and relatedness, organizations might start a virtuous circle of flourishing both in employees' lives and at work. However, a vicious circle is also possible. If employees feel low need satisfaction, or even worse, feel that their psychological needs are frustrated (Unanue et al., 2014 ; Van den Broeck et al., 2016 ), companies may start a dangerous circle of employees' unhappiness.

Despite previous arguments supporting the importance of need satisfaction, recent research by Di Fabio and colleagues (Di Fabio and Palazzeschi, 2015 ; Di Fabio and Kenny, 2016a , b ) has highlighted the importance of other employees' psychological resources (life resources and job resources) for promoting both job satisfaction and life satisfaction. Di Fabio and Kenny ( 2016a ) recognize that decent work and well-being require the needs for “power, relationship, and self-determination” to be satisfied (similarly to self-determination theory postulates). However, there are a set of additional flexible life and work skills that also need to be developed. In work settings, for example, career management and self-management skills are crucial (e.g., maintaining their employability, intentionality, life-long learning, autobiographical reasoning, meaning-making, and building resilience). In life settings, for example, the development of self and reflexivity are additional key elements in this process. Further, the authors developed the Positive Self and Relational Management (PS&RM) model and found that Positive Lifelong Life Management (e.g., hedonic and eudaimonic well-being), Positive Lifelong Self-Management (e.g., individual level resources and self-insight in the work context), and Positive Lifelong Relational Management (e.g., relational adaptation in work and life) are the key resources that people should develop for happier lives and jobs. Other psychological resources for protecting and promoting well-being have been explored recently. For example, Di Fabio and Kenny ( 2016b ) has shown that trait of emotional intelligence is associated with higher life satisfaction, above and beyond fluid intelligence and personality traits. In addition, Di Fabio and Palazzeschi ( 2015 ) have explored the role of resilience (among other variables): they show that resilience is associated with higher life satisfaction above and beyond fluid intelligence and personality trait.

All the skills mentioned previously draw upon psychological resources, and when developed, could help employees to foster their well-being both in life and at work. This process would complement the powerful role of need satisfaction. Thus, based on previous findings, future perspectives for intervention could focus not only on the satisfaction of the needs for autonomy, competence and relatedness, but also on developing career management and self-management skills, as well as emotional intelligence and resilience. A few programs have emerged recently in Chile for dealing with the promotion of well-being in the workplace. For instance, the Universidad Adolfo Ibáñez has launched a Graduate Program in Organizational Happiness, the Diploma en Felicidad Organizacional (DFO; UAI, 2016 ). The DFO has become a successful program aimed at training managers and consultants in the business skills and psychological resources needed for promoting well-being both in their lives and in their companies. In addition, the Chilean Ministry of Labor has developed an instrument for measuring mental health risks in the work place, called Protocolo de Vigilancia de Riesgos Psico-sociales (MINSAL, 2017 ). Depending on the companies' results with regard to employees' mental health, companies could be forced by law to implement programs to protect their employees' happiness.

Limitations and future research

We should acknowledge some limitations in our research.

First, all our measures are self-reported, which increases the risk of common-method bias. However, self-report measures are justifiable when studying constructs that are self-referential, such as job satisfaction, life satisfaction and need satisfaction (Van den Broeck et al., 2016 ). In addition, we put in place several a priori controls (Podsakoff et al., 2003 ; Conway and Lance, 2010 ) in order to mitigate common-method bias: protecting respondent anonymity, explaining that there would be no right or wrong answers, and allowing participation at the location of the respondents' choice (home, office, etc.). Nonetheless, future research could consider using an additional source of data, such as asking “significant others” to triangulate information, although previous research (Heller et al., 2002 ) has shown that self-report measures of job satisfaction and life satisfaction do not differ significantly from measures collected from “significant others,” which gives support to the use of self-reported information in our three studies.

Second, following our first concern, the use of self-reported data may be problematic due to shared method variance. However, in our longitudinal analyses, we modeled stability paths from all T1 to all T2 measures. This procedure helps to avoid the possibility that shared method variance might inflate the cross-lagged paths across time. Third, given that the great majority of our participants were all university graduates, we should be cautious about generalizing these findings to poorer and less educated groups. Fourth, and finally, despite the strong evidence showing that job satisfaction is a temporal antecedent of life satisfaction and vice versa—and that need satisfaction explains this link, our longitudinal design still does not rule out the possibility of a third, different, unmeasured variable that influences both constructs.

Importantly, despite the previous limitations, our results considerably strengthen the case not only for a causal path from job satisfaction to life satisfaction, but also for the confounding role of basic need satisfaction in the link mentioned. We presented the first research to date in a Latin American context, showing that job satisfaction and life satisfaction are reciprocally, positively and prospectively linked to each other, but that the link may be spurious due to the important role played by need satisfaction.

Author contributions

All authors listed have made substantial, direct and intellectual contribution to the work. WU, MG, DC, JO and AM conceptualized the study, chose the theoretical framework and measures. WU, MG and DC designed overall study. All authors wrote several sections of the initial draft, carried out analysis and interpreted results. All authors wrote, read and revised the final paper and approved it for publication.

WU thanks the Chilean Comisión Nacional de Investigación Científica y Tecnológica. Studies 1, 2, and 3 are part of a series of papers funded by the Chilean Fondo Nacional de Desarrollo Científico y Tecnológico (Fondecyt Iniciacion) Project N o 11160389.

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.

Acknowledgments

The authors thank UAI Open, which provided us with all the relevant mailing lists required in order to collect the data sets used in this research.

1 It is important to mention that Haar et al. ( 2014 ) explored work-life balance and several well-being outcomes across seven cultures (Malaysian, Chinese, New Zealand Maori, New European, Spanish, French, and Italian). However, despite measures of job satisfaction and life satisfaction being included, the authors did not test the associations between both constructs. In addition, Morrison et al. ( 2011 ) explored the relationship between national satisfaction and several specific well-being indicators (e.g., job satisfaction and life satisfaction) among a sample representing 95% of the world's adult population, yet although the authors reported the correlation between job satisfaction and life satisfaction (0.26), they did this to the aggregate level. Thus, they did not show the results for every single country. In addition, only the correlation between the constructs was shown, and no suitable statistical model was tested. Therefore, causality may not also be implied.

2 Other measures (e.g., positive/negative emotions, happiness, trust, materialism, etc.) were collected as part of a broader survey on soccer and happiness (Unanue et al., 2017 ), but they are not relevant to the present research. For that study we collected data from working and non-working adults. However, for the present one, we only used data from employees in Chile. The same applies to Study 2 and Study 3.

3 Some demographic data for participants who stayed in T1 and T2 may differ between T1 and T2 due to changes in working status between the two waves. The same applies to Study 2 and to Study 3.

4 We also collected measures of need frustration, materialism, work outcomes (engagement, burnout, etc.), gratitude and beneficence, but they are not relevant to the present research.

5 We also collected measures of flourishing, pro-social behavior, beneficence, work outcomes (engagement, burnout, etc.), and gratitude, but they are not relevant to the present research.

Supplementary material

The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00680/full#supplementary-material

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Measuring community nurses' job satisfaction: literature review

Affiliation.

1 Centre for Corporate Sustainability, Hogeschool-Universiteit Brussel, Belgium. [email protected]
PMID: 18355229
DOI: 10.1111/j.1365-2648.2008.04620.x

Aim: This paper is a report of a review of the literature on community nurses' job satisfaction, including research using different scales and settings, what is known to date and directions for future research.

Background: Job satisfaction is one of the strongest predictors of intent to stay and retention of nurses. An adequate understanding of the sources of job satisfaction and their importance can aid policymakers in the community nursing setting to cope with the growing demand for its services.

Data sources: A database of papers was established using ISI Web of Knowledge. Cited references were used to expand the database. Journals adding to the database were scanned for related research. This technique was repeated until no additional papers could be found.

Findings: Twelve job satisfaction scales were found, with striking differences in methodology, settings and sample characteristics of the studies concerned. A wide variety of job satisfaction and dissatisfaction sources is identified, but little is known on their relative importance. The Measure of Job Satisfaction and the Home Healthcare Nurses' Job Satisfaction Scale prove highly reliable and applicable.

Conclusion: Findings on the level and sources of community nurses' job satisfaction are ambiguous. Of all the scales reviewed, the Home Healthcare Nurses' Job Satisfaction Scale seems most promising for use in future research, based on its strong psychometric properties and its specificity for the community nursing setting.

Publication types

Community Health Nursing*
Home Care Services
Job Satisfaction*
Nursing Research / methods*
Nursing Staff / psychology*
Personnel Turnover*
Psychometrics

Optimal Leadership Styles for Teacher Satisfaction: a Meta-analysis of the Correlation Between Leadership Styles and Teacher Job Satisfaction

Published: 15 April 2024

Cite this article

Xiao Shi 1 ,
Qing-ze Fan 1 ,
Xin Zheng 2 ,
De-feng Qiu 3 ,
Stavros Sindakis ORCID: orcid.org/0000-0002-3542-364X 4 &
Saloome Showkat 5

Principal leadership significantly influences teacher job satisfaction, yet a conclusive consensus remains elusive. A meta-analysis was undertaken to investigate diverse leadership styles’ impact on teacher satisfaction, guided by the Two-factor Theory. Examining 98 papers with 148 effect sizes and 740,477 participants, the results unveiled positive correlations (1) between leadership styles like transactional, instructional, authentic, transformational, distributed, paternalistic, servant, ethical, and teacher job satisfaction. Ethical leadership yielded the highest influence, followed by servant leadership. (2) Cultural context, leadership measurement, job satisfaction assessment, and publication language partially moderated the relationship. (3) These findings substantiate theoretical assumptions, resolve research debates, and offer a foundation for principals to enhance teacher job satisfaction.

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This article was funded by the Chongqing Education Science “14th Five-Year Plan” 2023 Annual Project (Project No.: K23YG2060239).

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Shi, X., Fan, Qz., Zheng, X. et al. Optimal Leadership Styles for Teacher Satisfaction: a Meta-analysis of the Correlation Between Leadership Styles and Teacher Job Satisfaction. J Knowl Econ (2024). https://doi.org/10.1007/s13132-023-01697-9

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Introduction. How related are job satisfaction and life satisfaction? This question has been extensively explored in the literature (Heller et al., 2002).The spillover hypothesis (Bowling et al., 2010) is the most supported hypothesis to date.It argues that "job experiences spill over onto other spheres of life, and vice versa, suggesting that a positive relationship exists between the two ...
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Aim: This paper is a report of a review of the literature on community nurses' job satisfaction, including research using different scales and settings, what is known to date and directions for future research. Background: Job satisfaction is one of the strongest predictors of intent to stay and retention of nurses. An adequate understanding of the sources of job satisfaction and their ...
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Principal leadership significantly influences teacher job satisfaction, yet a conclusive consensus remains elusive. A meta-analysis was undertaken to investigate diverse leadership styles' impact on teacher satisfaction, guided by the Two-factor Theory. Examining 98 papers with 148 effect sizes and 740,477 participants, the results unveiled positive correlations (1) between leadership styles ...

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Job Satisfaction: A Literature Review

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Revisiting the Link between Job Satisfaction and Life Satisfaction: The Role of Basic Psychological Needs

Marcos E. Gómez

Juan C. Oyanedel

Andrés Mendiburo-Seguel

Introduction

Job satisfaction and life satisfaction

The segmentation hypothesis

The compensation hypothesis

The spillover hypothesis

The causal direction of the link between job satisfaction and life satisfaction

The causal influence of life satisfaction in job satisfaction: the top-down model

The causal influence of job satisfaction on life satisfaction: the bottom-up model

The bi-directional link between job satisfaction and life satisfaction

Individual differences in the link between job satisfaction and life satisfaction: moderators and mediators

The role of basic psychological needs in the job–life satisfaction link

Research gaps: justification for the present research

Job satisfaction research in Chile

Summary of aims and predictions

Job satisfaction

Life satisfaction

Demographic variables

Data analysis

Cross-sectional analyses

Longitudinal analysis

Study 1 brief discussion

Study 2 brief discussion

Study 3 brief discussion

General discussion

Practical implications for people and organizations

Limitations and future research

Author contributions

Conflict of interest statement

Acknowledgments

Supplementary material

Measuring community nurses' job satisfaction: literature review

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Optimal Leadership Styles for Teacher Satisfaction: a Meta-analysis of the Correlation Between Leadership Styles and Teacher Job Satisfaction

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