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The Trade-Offs between Job Satisfaction, Performance, and Locus of Control on Job Performance: Case of Sohana Outfitters Company

Shahab Nazariadli*

Department of Parks, Recreation and Tourism Management, North Carolina State University, NC, USA

*Corresponding Author:
Shahab Nazariadli
Department of Parks
Recreation and Tourism Management
North Carolina State University, NC, USA
Tel: 919-448-8826

Received Date: February 05, 2017; Accepted Date: February 22, 2017; Published Date: February 28, 2017

Citation: Nazariadli S (2017) The Trade-Offs between Job Satisfaction, Performance, and Locus of Control on Job Performance: Case of Sohana Outfitters Company. J Tourism Hospit 6: 272. doi: 10.4172/2167-0269.1000272

Copyright: © 2017 Nazariadli S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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The purpose of this study is to understand the reason Sohanna Outfitters Company’s employees are performing highly effectively. This purpose hasbeen sought through analysis of three constructs which literature has supported their impact: job satisfaction, job stress and locus of control. This paper analyzed the secondary data gathered by Case Western Reserve University. The results indicate that these employees have been highly influenced by gender and their levels of education. In addition, each of the behavioral constructs has been impacting employees’ level of productivity relatively substantially. This study’s results might help the managers and investors of the similar companies to understand better the factors which impact the productivity of their personnel. After that, enabling them to set out strategic planning/policies in order to control, sustain and increase the productivity of their staff.


Job satisfaction; Job performance; Job stress; Locus of control


The two critical problems facing the modern organizations are job satisfaction and stress [1]. It is argued that although the irinterrelation might not seem obvious, by looking deeper, their synergy with job performance will divulge. Theories of neo-classical periods between 1920 and 1950, in fact, support the proposition of employee satisfaction leading to job performance and productivity. They believed in the causal relationship between satisfaction and productivity, and so organizations capitalized on increasing job satisfaction in order to escalate the productivity of their businesses [1].

Job stress is defined by Montgomery, Bodget and Barnes as the employee’s consciousness or feeling of dysfunction as a result of workplace conditions, and also the employee’s psychological and physiological reactions to the undesirable and unsuited immediate workplace environment. One of the first theories of stress was developed by Freud [2] by considering it the result of the reduced discharge. In the 1960s, the cognitive approach was created postulating that when one is not capable or believes s/he is not adroit enough to meet certain conditions, s/he would feel stressed. Based on the stress theory [3] prolonged exposure to the stressors results in paralysis of abiological system. This exposure prohibits the anticipatory changes, which helps in coping abilities, hence, resulting in poor health condition such as headaches, insomnia, and depression.

Several drivers of occupational stress have been found in the literature such as career advancement, working relations, organizational support, rewards, job security, job autonomy, job ambiguity, role conflict, and the work itself [4]. For instance, when employees are affected by interpersonal work relations such as team pressure and their opinions are not embraced by co-workers [5]. In a similar vein, several researchers have disentangled the role of locus of control and autonomy at the workplaces in relation to job stress [6]. Karasek [7] outlines the main causes of stress in three sections:

1. The main project the employee is dealing with in everyday basis.

2. The independence, authority, and autonomy on performing their duties (locus of control).

3. Interpersonal relationships with organizational co-workers

Job satisfaction is described as the overall personal feelings of employees about the different aspects of their jobs [7] and the reward system within their organization [8]. Job satisfaction has been considered as the critical outcome variable in organizations, fueling many studies hovering around the antecedents of satisfaction in the workplace [9]. Job satisfaction may be defined as “the pleasurable emotional state resulting from the appraisal of one’s job as achieving or facilitating the achievement of one’s job values” [10]. It is a multidimensional construct [11] and has been linked to job-related and customer-related affairs.

Job satisfaction is perceived as one of the acutest components of work life, and one of the major predictors of the workplace performance. It helps to maintain a healthy body and mind, and if not attained, it will degrade the employee’s health status and therefore, his/her job productivity [12]. However, in contrast with the neoclassical notions, job productivity could also lead to the job satisfaction through the rewards system [13]. Sometimes performance leads to the remuneration of various kinds which in turn created satisfaction in employees. Indeed, many theories are supporting that a satisfied worker is not necessarily a productive one [1]: Indeed, the relationship between job satisfaction and job performance has been flaming and not decisively reached to a state of certainty. It is doubtful if it is the satisfaction that leads to job performance or the reverse [14]. Customer satisfaction’s influence on job performance has been a volatile issue. For instance, Gupta and Zeithaml [15] found a positive relationship between customer satisfaction and financial performance, while Bernhardt, Dunthu and Kennett [16] found just the opposite.

Moreover, a stressed staff makes incorrect decisions and creates undesirable relationships with colleagues. Both these elements can bear a negative outcome in the productivity of a group thus generating an added cost to a company. However, sometimes stress acts as a motivator which results in creativity and satisfaction and resolves the boredom and mundaneness but normally yields to aggression and low job satisfaction. For instance, Jamal [17] found the negative relationship between job stress and performance meaning people with high job stress also tended to perform poorly. He also found the similar association of job stress with job satisfaction [17]. However, in different contexts, the different dimensions of stress might be more influential in affecting the level of satisfaction from hospitals to department stores and universities.

Locus of Control the second stress-creator element postulated by Karasek [18] assesses individual’s expectations for either the need of internal or external control of power [19]. For example, the assessment of the external factors such as powerful others and chances are in control of their lives [20]. Individuals with low LOC scores (internals) believe that their own capabilities, behaviors, and attributes determine the rewards they obtain while those with higher LOC scores (externals) believe that the rewards received in their lives are outside their control [21].

There have been several studies analyzing trade-offs between the LOC and job stress, satisfaction and performance [9] on different settings, whereas hardly providing generalizable data. This study aims to unfold which demographic is more related to job performance at Sohana Outfitters Company, sparked from a needed attention for sustaining its progress, amazing profitability and prosperity. Also, this study wants to uncover the interrelationship of Locus of Control (LOC) and work-related measures of stress, satisfaction, and performance. Altogether, this study based on the prior findings has formulated and tested these hypothesis and research questions:

H1. Two groups of low LOC and high LOC show significantly different levels of job satisfaction, job performance and job stress.

H2. High-performance employees report more external control on their job-related activities.

H3. The main effect of job satisfaction and LOC on job performance are significant.

Q1. Have education level, gender and job category influenced the job performance and job stress?

Q2. Does relations with customers or work per se will positively implicate the job performance?


Study site and sample

The present study has found the Sohana Outfitters, a national retailer of specialty clothing and sporting goods is a nice example to be researched. Sohana Outfitters started as a small surf shop during the 1950s catering to the needs of local surfers in the San Diego coastal area. Sohana prided itself on its ability to keep up with the equipment and clothing needs of its fast paced clientele. During its first 20 years of existence, Sohana Outfitters went from a single store doing less than $100,000 in business to a network of stores in Southern California with retail sales of over $10,000,000. The data used in this study were the secondary data previously gathered by the researchers of Case Western Reserve University examining the success of Sohana Outfitters Company.

In order toinvestigate the relationship between job satisfaction, LOC, job stress and job performance, a study on a random sample of 305 employees was performed. The population of study comprising of Sohana Outfitters employees received structured questionnaires from their office mailboxes, and 221 valid questionnaires were returned, indicating are sponserate of about 72%. Most employees - female (74%), the age of respondents ranged between 18 and 73, the mean age of 30.91 and a standard deviation of 10.01. Most customers (55.3%) have income ranging from $30,000 to $30,999. Additionally, 52% of the respondents had obtained at least 1-3 years at college.

Measurement scales

A nine-item, five-point Likert-type scale ranging from “strongly disagree” to “strongly agree” assessed respondent’s satisfaction with various aspects of their jobs (i.e., work and customer dimensions). It included asking their level of agreement with statements such as “My job performance improves from year to year” and “I am satisfied with my working conditions.” A Cronbach’salpha of 0.79 was obtained for this measure by Johnson [22]. Alpha for present study’s job satisfaction scale discovered to be 0.65.

A 13-item, seven-point summated rating scale ranging from poor to excellent was used to assess the employees’ job performance (high, medium and low). It included self-rate of quality service they deliver to the customer through statements such as “consistently resolving customer concerns the first time” and “Following-up after the phone call.” The Cronbach’s alpha for the performance measure was 0.92. Alpha for present study’s job performance scale discovered to be 0.73. A factor analysis of these items produced a single meaningful factor, accounting for 38% of the variation [23].

Locus of Control scale developed by Rotter [19] consists ofa 29-item fixed choice questionnaire where respondents were asked to select the one best of two options for each item. Six of the items are filler items, so the maximum possible score is 23. It included asking questions of “Do you think that people can get their own way if they just keep trying?” and “Are some people just born lucky?” Reliability estimates for Rotter’s Locus of Control Scale ranged between 0.49 and 0.8 [24]. Alpha for present study’s locus of control scale discovered to be 0.85.

The job stress scale [25] was unidimensional. There are 11 items each scored on a five-point Likert-like scale. A higher score represents higher the amount of job stress as perceived by the respondent. It included asking the frequency of happening such as “dealing with policies which change from one day to the next” and “trying to meet the conflicting demands of my family and my job.” Reliability estimates for Price’s job stress scale varied between 0.77 and 0.83 [26]. Alpha for this study’s job stress scale discovered to be 0.76 (Table 1). Demographics were collected from age, income years in current job, marital status, gender, education level and job category, but the later three were analyzed. For content validity, the measurement instrument before distributed was thoroughly evaluated by six PhD students studying the consumer behavior at Michigan State University (Table 1).

Scale/Item Mean Standard Deviation Skewness Kurtosis Alpha if item deleted
Job stress (α=0.76) 4.15 0.96 1.23 -0.23  
Job satisfaction (α=0.65) 3.20 0.78 -1.43 0.56  
Customer-related 3.13 0.93 -0.76 -0.34 0.56
Work -related 3.28 0.88 0.73 -0.67 0.78
Locus of control (α=0.85) 10.06 2.84 0.89 0.76  
Internals (low) 12.16 3.11 0.45 0.23 0.56
Externals (high) 8.00 3.92 1.12 0.65 0.67
Job performance (α=0.73) 4.82 1.02 0.56 0.76  
Low 4.56 1.12 -0.87 -0.23 0.69
Medium 5.67 1.23 -0.65 0.28 0.72
High 4.23 1.63 1.56 0.79 0.77
Test alpha based on standardized items         0.79

Table 1: Descriptive statistics and internal consistency of items and subscales of job stress, job satisfaction and job performance used in this study (N=305).


The demographic variables are considered first while the main variables of interest are job satisfaction, job stress, job performance and LOC (Table 1). The data were analyzed using a 2 × 2 (Gender × Job Category) Factorial ANOVA, and the results indicated that the main effect of gender in job performance was significant yielding anF ratio of F(1,303)=2.13, p=0.001, η2=0.058. Gender differences account for 5.8% of the variability in job performance. Further, female’s (M=3.10, SD=0.97) job performance was significantly higher (p=0.01) than the male’s (M=2.90, SD=0.85). Job category results also show that human resources staff (M=2.96, SD=0.89) than the business analysts (M=3.15, SD=0.98) expressed significantly higher job performance attributes (F(1, 303)=3.87, p=0.02, η2=0.23) being responsible for 23% of the variability in job performance. What is more, the significant interaction of gender and job category indicated that males in human resource positions (M=3.35, SD=0.84) expressed higher job performance than male business analysts (M=3.05, SD=0.67), females in human resource positions (M=3.02, SD=0.78) and female business analyst (M=3.13, SD=1.03) indicating a F ratio of (F(1,303)=3.12, p=0.03, η2=0.112) in interaction effect. This interaction explained 11.2% of variation on job performance (Figure 1).


Figure 1: Significant interaction effect of job category and gender on job performance.

Further, the results from a one-way ANOVA disclosed a significant difference in perceived job performance within different education groups (F(2,302)=12.23, p=0.001, η2=0.049). Fisher’s LSD posthoc test showed that those employees with Master’s degree (M=5.45, SD=1.01) revealed a higher degree of job performance than those with high school (M=4.12, SD=0.80) and college degree (M=3.88, SD=0.45). However, the difference between high school and college degree employees were not significant at 0.05 significance level (Table 2).

Source     Df F η2 p Mean SD N
Gender Male   1 2.13 .058 0.001** 2.90 0.85 80
Female           3.10 0.97 225
Job category Business analyst   1 3.87 0.23 0.02*      
Human resource managers           3.15 0.98 159
          2.96 0.89 146
Education Master’sCollegeHigh school   2 12.33 0.049 0.001***      
          5.45 1.01 118
          3.88 0.45 76
          4.12 0.80 111
Job category*Gender Male   1 3.12 0.112 0.03*      
Business analyst       0.15 3.05 0.67 38
Human resource managers       0.02* 3.35 0.84 41
  Female Business analyst       0.06 3.13 1.03 121
    Human resource managers       0.09 3.02 0.78 105

Table 2: Fisher LSD posthoc analysis for effect of gender, job category and education on job performance.

As the importance of controlling stress is substantiated through the literature and to answer the related research questions, a 3 × 2 × 2 Factorial ANOVA was conducted to compare the effect of education levels, job category and gender of the respondents on reporting job stress levels. The significant results (F(2, 302)=2.11, p=0.02, η2=0.077) indicate that the significant difference could be between any or all of the education levels. To clarify, Fisher’s LSD posthoc test revealed that the respondents with a college degree (M=3.23, SD=0.93) reported significantly lesser (p=0.01) job stress level scores than respondents with Master’s (M=5.64, SD=1.12) and high school (M=6.54, SD=0.45) diplomas. However, the difference between those with high school and Master’s degrees were not significant (p>05). The main effect of job category on job stress was non-significant (F(1,303)=1.18, p=0.34, η2=0.002) and similarly, gender did not affect perceived job stress (F(1,303)=2.12, p=0.008). However, the interaction effect between education level and gender was significant (F(1, 287)=11.13, p=0.04, η2=0.13) explaining 13% of the variance in stress level. A followup test carried out to further discover the mere effect of each level/ subcategory. Therefore, posthoc comparisons using the Tukey HSD test indicated that the mean score for female workers with college degree (M=5.94, SD=1.07) was significantly higher than (p=0.01) males with college (M=4.08, SD=0.78), Master’s (M=3.66, SD=0.98) or high school degrees (M=3.44, SD=0.54) by showing greater levels of stress. What is more, there was also a significant interaction effect between job category, education level and gender (F(2, 287)=22.49, p=0.01, η2=0.034) affecting job stress (Figure 2). This interaction explains 3.4% of the variability in job stress. All other main effects and interactions were irrelevant to our hypotheses/research questions (Table 3).


Figure 2: Significant interaction effect of job category, gender for college degree employees.

Source     Df F η2 p Mean SD N
Gender Male   1 2.12 0.008 0.63 3.76 0.98 80
Female   1 1.18 0.002 0.34 3.54 1.23 225
Job category Business analyst           2.98 0.56 159
Human resource managers           3.13 0.87 146
Education Master’s
  2 2.11 0.077 0.02*      
        0.9 5.64 1.12 118
        0.01** 3.23 0.93 76
High school         0.23 6.54 0.45 111
Education*Gender Male Master’s
1 11.13 0.13 0.04*      
      0.09 3.66 0.98 6
      0.45 4.08 0.78 53
High school       0.31 3.44 0.54 18
Female Master’s
      0.06 5.33 0.87 92
      0.02* 5.94 1.07 105
High school       0.22 4.10 0.55 22
Education*Gender*Job category     2 22.49 0.034 0.01**      

Table 3: Tukey HSD results for the differences in job stress scores among different educational backgrounds, genders and job categories.

According to the scale developed by Rotter [19], LOC scores range from 0 to 23, and the scores sitting higher than 13 are considered as high (externals) LOC and lower than 12 are considered as low (internals) LOC. This study’s results ranging from 1 to 19 did rely on more sophisticated and accurate way to split high from low LOC. In this regard, they were separated into three groups so that the upper and lower groups were associated with nearly 32 percent of the total sample. Therefore, those with scores between 14and 19 (31.6) were assigned to the external LOC group, and those with scores between 1 and 6 (31.6 percent) were assigned to the low LOC group.

In order to test Hypothesis 1 regarding the different behavioral characteristics of low and high LOC groups, an independent t-test was conducted. The results show the significant difference between the high (M=12.16, SD=3.11) and low LOC (M=8.00, SD=3.92) groups in their rating of job satisfaction (t (178)=2.80, p=0.005, η2=0.032) and job performance (t (178)=4.12, p=0.02, η2=0.051), indicating small magnitude of the difference in the means for both, 3.2% and 5.1% respectively. However, this difference was nonsignificant between these two groups regarding job stress (t (178)=0.051, p=0.002, η2=0.002). Therefore the requirements for supporting the H1 is partially accomplished (Table 4). Looking deeper into the data, and towards the Hypothesis 2, the job performance data was divided into three groups of high, medium and low performance. The results of chi square test indicate that those high-performance employees reported more external LOC than the internal LOC (χ2(2)=15.67, p=0.04), hence, accepting H2.

Variables Internal (n=92) External (n=143) t-test
  Mean SD Mean SD t p value
Job satisfaction 3.08 0.95 3.78 0.54 4.18 0.005**
Job stress 3.89 0.84 3.22 0.53 -3.56 0.002**
Job performance 5.43 0.74 4.98 0.89 4.11 0.02*

Table 4: Independent t-test between internal and external control in LOC.

Moreover, a 2 × 2 Factorial ANOVA design was employed to compare the main effects of job satisfaction and LOC and the interaction between job satisfaction and LOC on job performance. Job satisfaction had two levels (work and customer dimensions), and LOC included two levels (high and low) (Table 4).

All main effects were significant at the 0.05 significance level, allowing us to find support for H3. The main effect for job satisfaction yielded a F ratio of F(37,267)=1.12, p=0.01, η2=0.092. Job satisfaction differences account for 9.2% of the variability in job productivity. It indicates that those employees satisfied through customers relations (M=3.13, SD=0.93), performed better at the workplace than those satisfied with job-related practices (M=3.28, SD=0.88). Moreover, the main effect of LOC yielded a F ratio of F(12,292)=14.42, p<.001, η2=0.067. Different levels of LOC (low and high) account for 6.7% of the variability in job performance. It indicates that the low LOC (internals) group (M=12.16, SD=3.11) showed more productivity in the workplace than high LOC (externals) group (M=8.00, SD=3.92). Interestingly while the effect of each independent variable was significant, in interaction it turned to be non-significant (F(36, 269)=0.76, p=0.08, η2=0.004) (Table 5).

Source   Df F η2 p Mean SD N
Job satisfaction Customer-related 37 1.12 0.092 0.01** 3.13 0.93 198
Work-related         3.28 0.88 207
LOC Low 12 14.42 0.067 0.001*** 12.16 3.11 112
High         8.00 3.92 143
Job stress   43 12.56 0.16 0.001***      
Job stress* Job satisfaction* LOC   36 0.76 0.004 0.08      

Table 5: Results for the differences in job performance scores among different levels of job stress, job satisfaction, and LOC.


This study investigates the interplay between job satisfaction, job stress and locus of control and their influence on job performance in Sohana Outfitters Company. The results indicate that education level, gender and job category had a significant effect on job performance, and the interaction between gender and job category was also significant. Female workers showed higher performance when their job category was not considered, as males in human resource positions, showed higher productivity rates than females in both human resources and business analyst positions. Although each of these variables was implicating job performance, only the effect of education level on job stress was reliable indicating more stressed college degree workers than those with Master’s and high school diplomas. However, the deeper probe into the data revealed female workers are more stressed than their male counterparts given their education level. This finding is consistent with previous research highlighting the gender-basedpower workspaces influencing perceived stress and productivity (Gardiner and Tiggemann, 1999).

In addition, the work-related stress perception of internal and external LOC groups unfolded a non-significant difference, while this difference was significantly higher for external LOC groups than the internal LOC groups in terms of both job satisfaction and performance. This non-significance shows mostly inconsistency with some findings such as with Kalbers and Fogarty, Rahim [27] and Blau [28], but, the significance difference adheres to the findings of Judge, Erez, Bono and Thoreson, [29-35]. Moreover, the results have confirmed the substantial effect of job satisfaction on job performance, in a way that those workers with highly desirable customer relations perform more efficiently in the workplace than those satisfied with the work per se.

The potential implications of this study are plenty in particular for the Sohana Outfitters Company managers and policy makers. Considering that job satisfaction, job stress and work-related LOC are nice predictors of job performance, supported by literature through empirical evidence and also through findings of the presentstudy; customized recruitment policies could be adopted. The decision makers could devise policies to target specific sexes with different education levels and recruit them for particular job positions. This will enable them to predict the job performance of the employees at least to the extent influenced by the variables examined in this study [36-39].

This study has not been flawless and has several limitations. First, the sample is consisted of those employees working in business analysis and human resource positions, and leaving us uncertain about other positions within the Company. Moreover, the results would be barely generalizable to other settings as the literature has supported the relatively different results in different contexts. In addition, while the survey has been anonymously gathered, there is a sensible risk of bias, since the employees might have been apprehensive of the illusion/fact that their response would risk the current recruitment policies and the like. For future, researchers could replicate this study on different settings and also include more variables such as the physical environment, natural environment, and family cycle into the interaction with other variables to reach more conclusive goal oriented results. Also, the replication of this study in different countries might be helpful in understanding the traditional/cultural constraints impacting the job performance.

In the end, this research has not checked the results with the Sohana Outfitters Company and might not be validated. Therefore, the interested researchers are instead encouraged to look at the process of research and try to get insights for replicating research in other applicable settings to better enhance/evaluate productivity of other companies’ businesses.


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