8-HooleVermeulen.qxd In aviation, safety is paramount. The human factor is widely recognised to be critical to aviation safety and effectiveness. Numerous studies have indicated that the human factor is absolutely vital in maintaining or improving safety. These realities suggest that there is a need for consistent, long-term support for research, development, analysis and application of information related to human performance throughout the aviation system (McDonald, Johnston & Fuller, 1995). Because this need was recognised, a United States National Plan for Aviation Human Factors was developed and published in 1990. The strategic portion of the plan calls for research which leads to enhancements in (a) human centred design of controls, displays and advanced systems; (b) selection and training; (c) information transfer; (d) personal safety, well-being and survival and; (e) the measurement of performance and an understanding of variables that affect performance (FA A, 1990; Dismukes, 1994). This article supports objective (e) of this scientific programme in aviation human factor research. Since job satisfaction can be regarded as an important contributor to various aspects of work performance, an investigation of the level of job satisfaction of South African aircraft pilots and the variables that affect it can make a valuable scientific contribution. The importance of job satisfaction to human beings is a phenomenon that has been widely studied. The popularity of this field of study can be attributed to the relevance of job satisfaction to the physical and mental well-being of employees. Most of these studies focus on the humanitarian value of job satisfaction. They are based on the implicit assumption that job satisfaction (or lack thereof) is a major contributor to productivity, absenteeism, turnover, in-role job performance and extra-role behaviour and role stress, as well as the belief that management is able to influence the primary antecedents of job attitudes. Job satisfaction can be described as a person’s affective attachment to his/her job, either in its entirety (global satisfaction) or with regard to particular aspects, seen as facet job satisfaction (Tett & Meyer, 1993). Several studies have explored the relationship between job satisfaction and variables such as age, gender, rank, length of service, job facets, job levels, intention to quit and commitment (Oshagbemi, 1999; Khaleque & Rahman, 1987; Robie, Ryan, Schmieder, Parra & Smith, 1998; Tett & Meyer, 1993). However, none of these studies has investigated the relationship between pilot-related factors and the job satisfaction levels of aviators. There are numerous publications (Wiener & Nagel, 1988; Besco, 1989; Hawkins, 1993; Johnston, Fuller & McDonald, 1995; Fuller, Johnston & McDonald, 1995; O’Hare & Roscoe, 1994; Hayward & Lowe, 1996, 2000; Orlady & Orlady, 1999; Lowe & Hayward, 2000) that refer to research on the influence of specific factors (for example, automation, work overload, jet lag, irregular working hours, cockpit design and layout) on job performance and pilot error in flight operations. Very few of these publications refer to working conditions or their specific contribution to the intrinsic job satisfaction of pilots. The broad aim of the sudy was to rectif y these omissions. Hence, the objectives of the study were: � to ascertain whether the Job Satisfaction Scale developed by Brayfield and Rothe can be used for pilots in the South African context; and � to determine whether pilots’ levels of job satisfaction differ as a function of their area(s) of operation, the nature of their flying duty, the type of licence they have and their level of command. The following hypotheses were developed with regard to the second objective of the study: H1: There is a statistically significant difference between the mean job satisfaction scores of groups of pilots operating in different areas. H2: There is a statistically significant difference between the mean job satisfaction scores of groups of pilots who perform different flying duties. H3: There is a statistically significant difference between the mean job satisfaction scores of pilots licenced in different categories. H4: There is a statistically significant difference between the mean job satisfaction scores of pilots in different levels of command. METHOD Measuring instrument The study can be seen as exploratory in nature, investigating pilot-related factors that may influence the levels of job satisfaction of South African aircraft pilots. C HOOLE L P VERMEULEN Department of Human Resources Management University of Pretoria ABSTRACT The importance of job satisfaction to human beings is a widely studied phenomenon, due to the assumption that job satisfaction is a major contributor to the well-being of employees and to several organisational outcomes. Most of these studies have focused on the influence of organisational variables on job satisfaction. Few studies have investigated the relationship between pilot-related factors and the job satisfaction levels of aviators. In a study of 704 South African pilots, significant differences were found in job satisfaction levels with regard to the nature of a pilot’s flying duty, area(s) of operation, type(s) of licence and level of command. OPSOMMING Werkstevredenheid en die belangrikheid daarvan vir die mens is ‘n onderwerp waaroor navorsing dikwels gedoen word. Die rede hiervoor is die aanname dat werkstevredenheid ‘n belangrike bydraende faktor is tot werknemerswelsyn en verskeie organisatoriese uitkomste. Die meeste van hierdie studies het gekonsentreer op die invloed van organisatoriese veranderlikes op werkstevredenheid. Min navorsing is egter gedoen oor die verband tussen vliegverwante veranderlikes en die vlakke van werkstevredenheid van vlieëniers. In ‘n studie van 704 Suid-Afrikaanse vlieëniers is beduidende verskille gevind tussen die werkstevredenheidsvlakke van vlieëniers met betrekking tot die aard van vlieëniers se vliegtaak, area(s) van werksaamheid, soort(e) lisensie(s) en vlak van bevelvoering. JOB SATISFACTION AMONG SOUTH AFRICAN AIRCRAFT PILOTS Requests for copies should be addressed to: C Hoole, Department of Human Resource Management, University of Pretoria, Pretoria, 0002 52 SA Journal of Industrial Psychology, 2003, 29 (1), 52-57 SA Tydskrif vir Bedryfsielkunde, 2003, 29 (1), 52-57 JOB SATISFACTION OF AIRCRAFT PILOTS 53 The first part of the survey focused on the evaluation of items measuring job satisfaction. The instrument used in the survey was the Job Satisfaction Scale (JSS) developed by Brayfield and Rothe (1951). The scale consists of 18 items with five-point agree-disagree responses. Other items also included in the survey consisted of biographical questions and some crew resource management questions. The instrument was developed to measure job satisfaction in a wide variety of jobs. A mean score of 63,8 (SD 9,4) and an internal consistency of 0,87 were reported. Studies using the Brayfield-Rothe scale reported reliability scores of 0,87 (Brayfield & Rothe, 1951), 0,90 and 0,78 (Brayfield, Wells & Strate, 1957), 0,99 (Stinson & Johnson, 1977), 0,9 (Carson, Carson, Roe, Birkenmeyer & Phillips, 1999). At least one study also used the Brayfield-Rothe scale to focus on a narrower aspect of job satisfaction, namely satisfaction with the work itself (Stone, Mowday & Porter, 1977). They found that this type of satisfaction correlated 0,43 with job scope (perceived variety, autonomy, task identity and feedback). The Brayfield-Rothe instrument was also used in several other studies (Martin, 1979; Orpen, 1978; O’Reilly & Caldwell, 1979; Khaleque & Rahman, 1987; Iverson, 1999; Carson et al., 1999). Procedure Questionnaires were distributed in two phases. The Air Force Headquarters distributed 250 questionnaires to the various pilot divisions. In the second phase, the South African Civil Aviation Authority distributed 7929 questionnaires via the Aeronautical Information circular (NOTAM) to all licenced pilots in the following categories: 4625 private pilots, 1512 airline transport pilots, 1468 commercial pilots, 218 helicopter commercial pilots and 106 helicopter airline transport pilots. Altogether, a total of 8179 questionnaires were distributed. A total of 704 questionnaires were returned, a return rate of 8,60%. The descriptions of the respondents in terms of biographic characteristics, areas of flight operation and the nature of these pilots’ aviation duty are presented in Tables 1 and 2. TABLE 1 BIOGRAPHIC CHARACTERISTICS OF RESPONDENTS Biographic Variables Gender Male n=672 Female n= 32 704 Educational qualifications Degree n=152 Diploma n=133 Other n=419 704 Age Mean 35,6 SD 10,68 Total flying hours Mean 3877,48 SD 4274,04 Statistical analysis Parametric statistics were used to determine associative and comparative trends in the data. An interval scale was used as the level of measurement for the dependent variable (job satisfaction). To examine the internal structure and factor validity of the Job Satisfaction Scale, a principal factor analysis and confirmatory factor analysis were used. Principal factor analysis was used because this is the procedure recommended when an attempt is made to determine the number and content of factors measured by an instrument (Hatcher, 1994). The internal reliability of the Job Satisfaction Scale was assessed by calculating the Cronbach alpha coefficient. One-way analysis of variance (ANOVA) was used to compare the job satisfaction levels of three or more independent groups. To indicate which group or groups differ significantly, the post hoc test of Scheffé was applied. The BMDP4M and SAS-Proc Calis computer programmes were used to perform a factor analysis of the items. The rest of the statistical analyses were done by means of the Statistical Programme for Social Sciences (SPSS for Windows 9.0). TABLE 2 MAIN AREAS OF OPERATION AND NATURE OF FLYING DUTY Areas of Operation N % National airline 188 26,2 Charter 88 12,5 Corporate 39 5,5 Freight 8 1,2 Military 219 31,2 Other 162 23,4 Total 704 100 Nature of Flying Duty Passenger transportation 377 53,5 Freight 14 2,0 Agricultural (crop dusting, etc.) 10 1,4 Industrial/construction 10 1,4 Aerial surveying (photography, mapping, etc.) 11 1,6 Aerial patrol 31 4,4 Pilot training/Flight instruction 80 11,3 Sales and demonstration 2 0,3 Personal flying (sport, recreation) 61 8,8 Student pilots 50 7,1 Other 58 8,2 Total 704 100 RESULTS Factor analyses The responses of 704 pilots on the Job Satisfaction Scale were subjected to the Principal Factors Analysis using the BMDP4M programme. The first round of the analyses indicated a three- factor solution, where three roots had eigenvalues greater than one. The eigenvalues of the inter-correlation matrix are set out in Table 3. TABLE 3 EIGENVALUES OF THE INTER-CORRELATION MATRIX Root Eigenvalue 1 6,7589 2 1,2305 3 1,0441 4 0,9546 5 0,8942 6 0,8297 7 0,7797 8 0,7127 9 0,6895 10 0,6675 11 0,5553 12 0,5256 13 0,4949 14 0,4390 15 0,4301 16 0,3716 17 0,3422 18 0,3068 The difference between the three eigenvalues already suggested that there was actually only one significant factor. A two-factor solution was requested and the items were subjected to further exploratory factor analysis. After three rounds of exploratory factor analysis, only two items remained in the second scale, which did not represent a suitable solution. In the next round of the analysis, the one-factor solution was subjected to exploratory factor analysis. Only one item (number 18) did not meet with the requirement of a loading above 0,3. The results are set out in Table 4. TABLE 4 EXPLORATORY FACTOR ANALYSIS – ONE-FACTOR SOLUTION Item Description Factor loading Q08 Most of the time I have to force myself to go to work (R) 0,811 Q10 I feel that my job is no more interesting than others I 0,749 could get (R) Q06 I am often bored with my job (R) 0,740 Q14 Each day of work seems like it will never end (R) 0,681 Q12 I feel that I am happier in my work than most 0,677 other people Q05 I enjoy my work more than my leisure time 0,658 Q07 I feel fairly well satisfied with my present job 0,657 Q16 My job is pretty uninteresting (R) 0,653 Q11 I definitely dislike my work (R) 0,641 Q15 I like my job better than the average worker does 0,563 Q17 I find real enjoyment in my work 0,553 Q04 I consider my job rather unpleasant (R) 0,548 Q02 My job is usually interesting enough to keep me 0,489 from getting bored Q03 It seems that my friends are more interested in 0,419 their jobs (R) Q09 I am satisfied with my job for the time being 0,394 Q01 My job is like a hobby to me 0,374 Q13 Most days I am enthusiastic about my work 0,328 The one-factor solution explained 61,3 % of the total variance. An interactive item analysis of the 17 items yielded an internal consistency of 0,919 (Cronbach alpha). In order to see whether there was a good fit between the data and the model, the one factor solution was subjected to a Confirmatory Factor Analysis (CFA) using the SAS–Proc Calis programme. The indices of the CFA indicated a good fit between the model and the data. The results are set out in Table 5. TABLE 5 INDICES OF THE CONFIRMATORY FACTOR ANALYSIS – ONE-FACTOR SOLUTION Fit indices Goodness of fit Index (GFI) 0,9227 GFI Adjusted for degrees of Freedom (AGFI) 0,9006 Root Mean Square Residual (RMR) 0,0420 Parsimonious GFI (Mulaik, 1989) 0,8073 Chi-Square 466,6293 Chi-Square DF 119,0000 Independence model Chi-Square 4293,1000 Independence model Chi-Square DF 136,0000 RMSEA Estimate 0,0647 Bentler’s Comparative Fit Index 0,9164 Akaike’s Information criterion 228,6293 Bentler and Bonnet’s (1980) Non-normed index 0,9044 Bollen (1986) Normed Index Rh01 0,8758 Bollen (1988) Non-normed Index Delta2 0,9167 Next, the one factor solution of the Job Satisfaction Scale was investigated further. A procedure advocated by Bagozzi and Heatherton (1994) was used. It is based on the principle that the fit indicated by the indices yielded by the CFA can be an underestimation of the quality of the fit when the scales included in the analysis consist of several items or when large samples are used. Bagozzi and Heatherton (1994) suggest that an aggregation of the factor scores can be used to reduce this problem. The items on the Job Satisfaction Scale were then aggregated and again subjected to a CFA. The indices obtained indicated a much better fit between the model and the data. The results are set out in Table 6. TABLE 6 INDICES OF THE CONFIRMATORY FACTOR ANALYSIS – ONE-FACTOR SOLUTION Fit indices Goodness of fit Index (GFI) 0,9836 GFI Adjusted for degrees of Freedom (AGFI) 0,9509 Root Mean Square Residual (RMR) 0,0199 Parsimonious GFI (Mulaik, 1989) 0,4918 Chi-Square 28,2088 Chi-Square DF 5,0000 Independence model Chi-Square 1811,2000 Independence model Chi-Square DF 10,0000 RMSEA Estimate 0,0813 Bentler’s Comparative Fit Index 0,9871 Akaike’s Information criterion 18,2088 Bentler and Bonnet’s (1980) Non-normed index 0,9742 Bollen (1986) Normed Index Rh01 0,9689 Bollen (1988) Non-normed Index Delta2 0,9872 Based on the results of the Principal Factor Analysis, the CFA and the satisfactory reliability coefficient (Cronbach alpha), it can be stated with confidence that the Job Satisfaction Scale of Brayfied and Rothe (1951) can be used for aircraft pilots in the South African context. Multiple comparisons A series of one-way analyses of variance (ANOVA’s) was carried out to determine whether the pilots’ job satisfaction levels (dependent variable) differed in terms of the main areas of operation, the nature of the pilots’ tasks, the type of licence held and the pilots’ levels of command (independent variables). For this purpose, the pilots were divided into different groups, as indicated in Table 7. Main areas of operation The results of the one-way analysis of variance (ANOVA) regarding areas of operation are set out in Table 8, which illustrates that there is a statistically significant difference, F(2,529)=20,103; p<0,001, between the mean job satisfaction scores of pilots operating in different areas. This supports Hypothesis H1. HOOLE, VERMEULEN54 TABLE 7 CLASSIFICATION OF PILOTS FOR ANALYSIS OF VARIANCE (ANOVA) Group of pilots N Main areas of operation National airline pilots 188 General aviation pilots 135 Military 219 Nature of flying duty Passenger transport 367 Commercial aviation* 74 Training and instruction 80 Private pilots and student pilots 168 Licence Airline transport pilot licence (ATP) 242 Commercial pilot licence (CPL) 198 Private pilot licence (PPL) 218 Level of command Captain multi-crew 204 First officer multi-crew 130 Single pilot in command 235 *The commercial aviation category refers to freight, agriculture, aerial survey and patrol, construction and flying for industrial purposes. TABLE 8 ANOVA: JOB SATISFACTION BY MAIN AREAS OF OPERATION Areas of operation Sum of df Mean F p(F) squares square Between groups 2040,059 2 1020,029 20,103 <0,001* Within groups 26842,174 529 50,741 Total 28882,233 531 *p<0,001 TABLE 9 SCHEFFÉ’S POST HOC MULTIPLE COMPARISONS OF THE AREAS OF OPERATION IN RELATION TO JOB SATISFACTION (I)Areas of (J)Areas of Mean Std error p operation operation difference(I-J) Airline pilots General aviation 3,4069 0,8116 0,000* Military 4,3965 0,7131 0,000* General aviation Airline pilots -3,4069 0,8116 0,000* Military 0,9897 0,7092 0,457 Military Airline pilots -4,3965 0,7131 0,000* General aviation -0,9897 0,7902 0,457 *p<0,001 Scheffé’s post hoc multiple comparison technique was used to determine the statistical difference between the groups. The results (reported in Table 9) indicate that pilots who fly for major airlines are clearly more satisfied (p<0,001) than any of the other groups of pilots. The mean job satisfaction scores of pilots who fly for major airlines (73,9947) are higher than those of pilots operating in general aviation (70,5878) or in the military arena (69,5981). Nature of flying duty The results for the one-way analysis of variance (ANOVA) and the post hoc Scheffé test for the nature of flying duty are set out in Tables 10 and 11 respectively. TABLE 10 ANOVA: JOB SATISFACTION BY NATURE OF FLYING DUTY Job satisfaction Sum of df Mean F p(F) Squares Square Between groups 1635,879 3 545,293 8,925 <0,001* Within groups 41914,598 686 61,100 Total 43550,477 689 *p<0,001 TABLE 11 SCHEFFÉ’S POST HOC MULTIPLE COMPARISONS OF FLYING DUTY IN RELATION TO JOB SATISFACTION (I)Nature of (J) Nature of Mean Std p flying duty flying duty difference error (I-J) Passenger transport Commercial aviation 3,3536 0,9958 0,010* work Training and 3,5912 0,9693 0,004* instruction Private and student 2,6236 0,7263 0,005* pilots Commercial aviation Passenger transport -3,3536 0,9958 0,010* Training and 0,2376 1,2646 0,998 instruction Private and student -0,7300 1,0896 0,930 pilots Training and instruction Passenger transport -3,5912 0,9693 0,004* Commercial aviation -0,2376 1,2646 0,998 work Private and student -0,9676 1,0658 0,843 pilots Private and student pilots Passenger transport -2,6236 0,7263 0,005* Commercial aviation 0,7300 1,0896 0,930 work Training and 0,9676 1,0653 0,843 instruction *p< 0,01 The information in Table 10 supports Hypothesis H2, namely that there is a significant difference between the mean job satisfaction scores of pilot groups performing different flying duties. The overall F-value is significant, F (3,686)=8,925; p<0,001. The results of Scheffé’s post hoc multiple comparisons (Table 11) indicated that pilots involved in transporting passengers reported significantly (p<0,01) higher levels of job satisfaction than the other groups of aviators. However, the levels of job satisfaction of commercial aviators, instructors and private and student pilots did not differ significantly from each other. The mean job satisfaction scores of the pilots performing different flying duties are the following: passenger transport = 71,9076; commercial aviation = 68,5541; training and instruction = 68,3165 and private and student pilots = 69,2840. Type of licence The results of the one-way analysis of variance (ANOVA) and Scheffé’s post hoc multiple comparisons with regard to type of licence are set out in Tables 12 and 13 respectively. JOB SATISFACTION OF AIRCRAFT PILOTS 55 TABLE 12 ANOVA: JOB SATISFACTION BY TYPE OF LICENCE Sum of df Mean F p(F) squares square Between groups 1920,865 2 960,433 17,158 <0,001* Within groups 36663,767 655 55,975 Total 38584,632 657 *p < 0,001 TABLE 13 SCHEFFÉ’S POST HOC MULTIPLE COMPARISONS OF TYPE OF LICENCE IN RELATION TO JOB SATISFACTION (l) Licence (J) Licence Mean Std p difference error (l-J) Airline transport (ATP) Commercial (CPL) 2,3577 0,7169 0,005* Private (PPL) 4,0650 0,6986 0,000* Commercial (CPL) Airline transport (ATP) -2,3577 0,7169 0,005* Private (PPL) 1,7073 0,7345 0,068 Private (PPL) Commercial (CPL) -1,7073 0,7345 0,068 Airline transport (ATP) -4,0650 0,6986 0,000* *p<0,01 The results of the ANOVA in respect of job satisfaction according to the type of licence held are shown in Table 12. The table clearly indicates that there is a statistically significant difference F(2,655)=17,158; p<0,001 between the three licence categories. The significant F-value supports Hypothesis H3. Scheffé’s post hoc multiple comparisons indicated that there is a difference between pilots with each of the three types of licences (p<0,001). Pilots with an airline transport pilot licence (ATP) are the most satisfied group (72,8678), followed by pilots with a commercial licence (70,5101). The group with a private pilots’ licence have the lowest mean score (68,8028). Level of command The results of the one-way analysis of variance (ANOVA) and the post hoc multiple comparisons with regard to the level of command held by a pilot are set out in Tables 14 and 15. TABLE 14 ANOVA: JOB SATISFACTION BY LEVEL OF COMMAND Sum of df Mean F p(F) Squares square Between groups 1077,924 2 538,962 8,901 <0,001* Within groups 34271,344 566 60,550 Total 35349,269 568 *p<0,001 The ANOVA of Table 14 clearly indicates that the levels of command held by pilots affect the job satisfaction of pilots. This result supports Hypothesis H4. The overall F-value is significant F (2,566) = 8,901; p<0,001. The post hoc multiple comparisons (Table 15) indicate that first officers and captains operating in a multi-crew environment are more satisfied (p<0,01) with their work than single pilots in command of smaller aircraft. The mean job satisfaction scores for the three positions were 72,6462 for First Officer, 71,3775 for Captains and 69,2468 for single pilots. TABLE 15 SCHEFFÉ’S POST HOC MULTIPLE COMPARISONS OF LEVEL OF COMMAND IN RELATION TO JOB SATISFACTION (I) Position (J) Position Mean Std p difference error (I-J) Captain multi-crew First officer -1,2687 0,8733 0,349 multi-crew Pilot in command 2,1306 0,7446 0,017* First officer Captain multi-crew 1,2687 0,8733 0,349 multi-crew Pilot in command 3,3993 0,8505 0,000* Pilot in command Captain multi-crew -2,1306 0,7446 0,017* First officer multi-crew -3,3993 0,8505 0,000* *p<0,05 DISCUSSION Pilots have to face the challenges of continuous development of improved and more complicated technology and aircraft, large amounts of information and a steady growth in the amount of daily flying activities. It can safely be assumed that the job satisfaction levels of pilots are influenced by their trying to cope with these demands on a daily basis. A review of aviation publications since 1990 indicated that there was very little information on the relationship between pilot-related factors and job satisfaction. The results of the first part of the analyses performed indicate that South African pilots experience a relatively high level of job satisfaction. Pilots love flying. The study also attempted to determine whether there are significant differences between various pilot groups in terms of their job satisfaction levels. The results of the ANOVAs indicated significant differences between job satisfaction levels of some of the groups studied. In terms of areas of flight operation, there was a significant difference between pilots flying for national airlines and other areas such as general aviation and military pilots. Scheffé’s post hoc multiple comparisons indicated that there are differences between the airline pilots on the one hand and general aviation and military pilots on the other. In terms of flying duties, there was a significant difference between pilots involved in passenger transportation and pilots involved in commercial flying, training and flying for recreation. Further results obtained from the ANOVAs indicated a significant difference between pilots with ATP, CPL and PPL licences. Significant differences were found with regard to the mean job satisfaction scores of pilots operating in a multi- crew environment versus pilots operating in a single command position. From the above results it is clear that pilots involved in the area of passenger transportation and working for national airlines experience a higher level of job satisfaction. This is an important finding, seeing that these pilots have a greater responsibility with regard to human life. More structure and set rules and standard operating procedures (SOPs) apply in national airlines than for other commercial operators. One can also argue that the larger carriers offer a more “protected” environment for pilots, resulting in higher job satisfaction, although they work long and irregular shifts. Other reasons for the higher job satisfaction may be the possibility of interaction during flight, sharing responsibilities, more prestige and more promotion opportunities and better remuneration. Stone and Babcock (1988) have an interesting view on promotion and remuneration. According to them, many of the larger airlines pay higher salaries, but their pilots progress more slowly from HOOLE, VERMEULEN56 first officer to captain. Although smaller airlines pay less, they are sometimes more attractive to pilots because faster promotion is possible. In the end, both types of airlines yield similar career earnings, but a pilot who is promoted faster would experience more career satisfaction. Pilots who make a living out of commercial flying (freight transport, crop dusting, aerial survey, construction and so forth), experience less job satisfaction. This may be due to the nature of their work environment. They earn less, have less job security, work mainly on their own and operate in a less structured environment. Smaller companies often expect their pilots to exceed safety margins in order to meet budget deadlines. This practice is referred to as “pilot pushing”, a situation where small operators force a pilot, by direct or indirect means, to compromise safe practices in order to complete flights (Stone & Babcock, 1988) . This may cause conflict and uncertainty, which can result in lower job satisfaction. Military pilots score lower on job satisfaction levels than both airline or commercial pilots. This finding can possibly be explained by a lack of job security in the South African Air Force, budget constraints, and very little flying time. However, much more research in this regard is necessary. The study has a number of limitations. Although steps were taken to ensure that the sample was representative of all licenced pilots, the sample was dominated by white male pilots, which reflects the current status of the industry. It should be noted that the results must be interpreted with care. Differences were found between the various groups of pilots but these differences were relatively small. Although the results indicate that South African pilots are satisfied with their jobs and this implies that job satisfaction must have a positive influence on their job performance, no real measures of performance are included in this study. Although the current study sheds some light on the job satisfaction levels of South African pilots, much more research is required. Further studies should investigate other factors that may influence pilots’ job performance to determine what pilot behaviour may lead to human error. 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