Scottish Journal of Political Economy, Vol. 58, No.

5, November 2011
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society. Published by Blackwell
Publishing Ltd, 9600 Garsington Road, Oxford, OX4 2DQ, UK and 350 Main St, Malden, MA, 02148, USA

JOB SATISFACTION AND QUIT

INTENTIONS OF OFFSHORE
WORKERS IN THE UK NORTH SEA
OIL AND GAS INDUSTRY

Heather Dickey*, Verity Watson** and Alexandros Zangelidis*

A BSTRACT
The North Sea oil and gas industry currently faces recruitment and retention dif-
ficulties because of a shortage of skilled workers. One means of retaining exist-
ing employees is to improve workers’ job satisfaction. In this paper, we
investigate the determinants of job satisfaction and intentions to quit within this
industry sector. We find that individuals in good financial situations, those whose
skills are closely related to their job and those who received training reported
higher levels of job satisfaction. Furthermore, we establish the importance of
job satisfaction, promotion prospects and training opportunities in determining
workers’ intentions to quit their job.

I I NTRODUCTION
The oil and gas industry makes a vital contribution to UK’s economy. In
2006, the industry provided 96% of UK’s oil needs and 92% of its gas needs.
The industry is United Kingdom’s largest industrial investor, and has spent
around £12.3 billion on exploration, development and production operations.
Furthermore, the oil and gas industry plays a considerable role in UK’s
labour market, employing around 450,000 individuals, of which 18,000 work
offshore on a regular basis. These labour market effects are particularly
important in one regional economy, the north-east of Scotland. Approxi-
mately 45% of all UK oil and gas sector jobs are based in Scotland, and 38%
of all offshore jobs are based in the Grampian area in the north-east of Scot-
land. Overall, the industry has a substantial regional economic impact upon
the Scottish economy.
One of the most pressing problems currently facing the UK North Sea
sector is the shortage of skilled personnel (Offshore Technology, 2007).
Companies involved in oil and gas production in United Kingdom continue

*Business School, University of Aberdeen

**Health Economics Research Unit, University of Aberdeen

607
608 H. DICKEY, V. WATSON AND A. ZANGELIDIS

to suffer from a significant skills shortage. This skills shortage has its origins
in the period of low oil prices during the 1980s and 1990s, which resulted in
a slump in North Sea exploration and less recruitment of new workers into
the offshore industry (Dow Jones Newswires, 2007). As a result, the industry
faces an ageing workforce and a lack of new recruits, which constrains the
industry’s ability to react to favourable economic conditions, such as
increased demand and rising oil and gas prices. The shortage of skilled
workers has had other consequences as well. First, labour demand exceeded
supply and average wages rose by 7.2% in 2007, contributing to cost infla-
tion, which, when combined with rapid inflation in the cost of raw materials
and equipment, has slowed new oil and gas exploration and production
activity in the North Sea (Dow Jones Newswires, 2007). Second, the lack of
new recruits into the industry has resulted in companies simultaneously
recruiting from the same (limited) pool of skilled workers (DTI Oil and Gas
Industry Development Directorate, 2001). As a result of the ageing work-
force and the lack of qualified new entrants into the labour market, the
shortage of skilled workers is likely to persist in future years (DTI Oil and
Gas Industry Development Directorate, 2003). This will constrain the indus-
try’s ability to grow, and how these issues are resolved in the short term will
impact substantially on how productive the offshore industry is in the future
(Offshore Technology, 2007).
The failure to attract sufficient numbers of skilled workers into the sector,
and the problems of retaining these new recruits, as well as existing offshore
workers, has implications for oil companies’ recruitment and retention poli-
cies. Competition from other industries for skilled workers and the less attrac-
tive aspects of offshore work (e.g. long working hours and time away from
home) contribute to the offshore industry no longer being attractive to youn-
ger individuals. The aim of this paper is to focus on the retention problem
faced by the offshore industry and to investigate the factors that determine
offshore workers’ intentions to quit. Job satisfaction is found to be a good
predictor of quit intentions and therefore a close examination of job satisfac-
tion may provide some useful instruments to human resource managers and
related policy makers.
To the authors’ knowledge, this is the first detailed analysis of quit inten-
tions and job satisfaction of offshore workers in the North Sea oil and gas
industry within the economic literature. This cross-sectional study uses a
unique dataset that was specifically designed to collect detailed information
on offshore workers’ personal and job characteristics that is not available
from existing published secondary data. Understanding what factors influence
workers’ intentions to quit their job will help companies to retain existing
employees by lowering the probability of workers leaving the company. While
this study focuses on employees within the North Sea oil and gas industry, its
findings add to the wider literature on quit intentions and job satisfaction,
and has policy implications that will help companies to retain high-quality
individuals within the UK North Sea offshore sector.

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 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 609

II L ITERATURE
While the primary focus of this paper is quit intentions and job satisfaction
within the North Sea oil and gas industry, the recruitment and retention diffi-
culties faced by companies within the sector will be affected by job opportuni-
ties onshore. Specifically, workers’ willingness to spend time offshore will
depend on the nature and quantity of jobs onshore, and workers may need to
be compensated for the non-pecuniary disadvantages of working offshore
compared with working onshore.
The idea that job characteristics influence the nature of labour market equilib-
rium originated with Adam Smith (1776), who proposed that compensating
wage differentials arise to compensate workers for non-wage characteristics of
jobs. Hence, firms that have unpleasant working conditions must offer some off-
setting advantage (e.g. higher wages) to attract workers. Much of the literature
has focused on the compensating wage differential that arises for risky jobs, as
workers seldom have perfect information about the health and safety implica-
tions of their jobs. For example, early empirical work found that workers will
demand wage premiums for jobs posing added risks (Oi, 1973; Thaler and
Rosen, 1976; Viscusi, 1978). More recent empirical studies have focused on
undesirable job characteristics other than risk, for example, French and Dunlap
(1998) investigated whether there is a compensating wage differential for job
stress, and concluded that there is a significant wage premium attributable to
work-related stress. Given the nature of offshore work (spending long periods of
time away from home and family, and working in a high-risk environment), it is
reasonable to assume that companies in the oil and gas industry may have to
offer a wage premium to attract and retain workers within the offshore sector.
Previous research shows that understanding how workers perceive their
work is important because job satisfaction affects economic outcomes. Free-
man (1978) concluded that subjective expressions of job satisfaction are signif-
icantly related to future objective economic behaviour and in particular the
probability of an individual quitting their job. The hypothesis that job satis-
faction affects economic outcomes and behaviour is further supported by stud-
ies in Europe and the United States of America, which suggest that individual
job satisfaction has a positive effect on job performance and productivity
(Freeman, 1978; Patterson et al., 2004), a negative effect on voluntary turn-
over or quit behaviour (Freeman, 1978; Akerlof et al., 1988; Gordon and
Denisi, 1995; Clark et al., 1998; Hamermesh, 2001; Scott et al., 2006), and is
quantitatively more important than wages in determining an individual’s deci-
sion to quit their job (Freeman, 1978). Akerlof et al. (1988) and Clark et al.
(1998) established that the causality runs from job satisfaction to quitting out-
comes. Job satisfaction is also negatively related to absenteeism (Drago and
Wooden, 1992). Furthermore, job satisfaction affects an individual’s invest-
ment in their human capital (i.e. their level of skills and knowledge acquired
through formal education and on-the-job training). Specifically, a more satis-
fied worker will be more likely to invest in firm-specific human capital that
will increase his/her investment to the employer (Hamermesh, 2001).
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610 H. DICKEY, V. WATSON AND A. ZANGELIDIS

Previous research, across all sectors in the economy, has found that individ-
uals’ job satisfaction is determined by their personal and job characteristics1
(Hamermesh, 1977; Freeman, 1978). Job satisfaction is positively related to
pay and the relationships between job satisfaction and both age and job ten-
ure are U-shaped (Clark et al., 1996; Gardner and Oswald, 2001; Theodossiou
and Zangelidis, 2009). Job security influences job satisfaction: job insecurity
leads to a deterioration of the employer–employee relationship and the expec-
tation of job losses has a negative effect on individuals’ job satisfaction
(Brockner et al., 1988; Blanchflower and Oswald, 1999).
Higher levels of education are associated with less satisfied workers (Clark,
1997). While it is widely accepted that more highly educated workers have
better jobs, education also raises expectations, which may lead to dissatisfac-
tion and disappointment (Hagenaars, 1986; Ross and Reskin, 1992). Further-
more, highly educated workers are more likely to suffer from educational
mismatch (Sloane et al., 1995). Allen and van der Velden (2001) focus on the
distinction between overeducation and overskilling and investigate whether it
is educational mismatch or skill mismatch that has the stronger effect on
labour market outcomes such as wages, job satisfaction and job mobility.
They find that neither overeducation nor undereducation have a significant
effect on job satisfaction, whereas skill mismatches exert a strong influence on
job satisfaction; in particular, a poor match between available and required
skills has a strong negative effect on individuals’ job satisfaction. Skill mis-
matches, therefore, provide an incentive for workers to engage in job search
to find a job that is better suited to their own abilities. Green and Zhu (2010)
also examine the consequences of overeducation and overskilling on job satis-
faction. They find that overeducation, where not accompanied by underutilisa-
tion of skills, is only a minor problem for job satisfaction, but where it is
accompanied by underutilisation of skills overeducation is a substantial source
of job dissatisfaction.
There is a well-documented gender differential in job satisfaction (Clark,
1997). Despite extensive evidence that women’s jobs are worse than men’s jobs
with respect to pay, hiring and firing, job content and promotion opportuni-
ties, women consistently report higher job satisfaction scores than men do
(Blanchflower and Oswald, 1992). There are various explanations for this
gender differential in job satisfaction presented in the literature. First, many
individual- and job-related characteristics differ considerably by gender (e.g.
age, education, hours of work, firm size and union membership), and many of
these individual and job characteristics have been found to be correlated with
job satisfaction. Second, sample selection occurs because of differing participa-
tion rates of men and women. As only employees are observed, the ‘true’ dis-
tribution of job satisfaction may be identical for men and women; however,
as fewer women work, dissatisfied women may be less likely to be in employ-

1
A vast part of the job satisfaction literature focuses on psychological determinants of job
satisfaction. For extensive reviews, see Locke (1976), Steel and Ovale (1984) and Warr
(1999).
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 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 611

ment compared with dissatisfied men. Third, men and women value aspects of
the job differently; for example, Clark (1997) found that men are more con-
cerned with the extrinsic aspects of work such as pay and promotion, whereas
women are more likely to value the intrinsic returns to work, and hence are
more likely to highlight good relations with managers, the actual work itself
and the hours of work. Fourth, if job outcomes are evaluated relative to
expectations, then women’s higher satisfaction with worse jobs can be
explained by women’s lower expectations regarding job aspects such as
income, hours of work, autonomy and authority. Investigating these possible
explanations, Clark proposed that the higher levels of job satisfaction for
women may be because of the role of expectations, that is, that women will
be more satisfied than men with the same objective characteristics and work
values if women expect less than men from their job. Other studies find no
significant differences between men and women; for example, Ward and Slo-
ane (2000) find no evidence of a gender differential in overall levels of job sat-
isfaction among male and female academics employed in Scottish universities.
However, their dataset is limited to a relatively homogeneous and highly edu-
cated workforce, in which female workers are likely to have job expectations
comparable with their male counterparts. Women academics, however, did
report lower levels of satisfaction with promotion prospects and job security,
and higher satisfaction with salary.
The significant determinants of job satisfaction within the oil and gas indus-
try found by previous studies include the worker’s age, with the usual
U-shaped relationship and promotion or a move to a new employer, which
increases job satisfaction (Parkes, 2002). Ulleberg and Rundmo (1997) identi-
fied three underlying factors contributing to overall job satisfaction: satisfac-
tion with employee relations (including workload, safety measures,
participation and communication); intrinsic job satisfaction (satisfaction with
personal achievement in one’s job); and extrinsic satisfaction with the working
conditions. Extrinsic satisfaction is affected by the perceived risk of disasters
and major accidents but not by perceived risk of ordinary occupational inju-
ries. In addition, studies have found that psychosocial factors such as the life-
style of the offshore environment and the combination of physical and
psychosocial stressors that this environment imposes upon offshore workers
also affect job satisfaction. Ulleberg and Rundmo (1997) found that job dis-
satisfaction is related to strain, and is caused by job stress. Parkes (2002)
found that unfavourable workloads, job insecurity and perceived high risks
were associated with lower levels of job satisfaction. Furthermore, French
et al. (1982) found that job satisfaction was a predictor of offshore oil work-
ers’ mental and physical health.

III Q UESTIONNAIRE
To investigate the determinants of intentions to quit and job satisfaction
within the North Sea oil and gas industry, we used a purposefully designed
questionnaire to collect information on offshore workers’ demographic and
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612 H. DICKEY, V. WATSON AND A. ZANGELIDIS

job/workplace characteristics, including their satisfaction with eight facets of

the job (work environment, workload, job stress, working hours, physical risk,
wages, job security and career prospects) and their overall job satisfaction.
The facets of the job were determined by the general job satisfaction literature
and previous psychology and occupational health research on job satisfaction
in the offshore oil and gas industry. The collection of primary data and the
careful design of the questions, allows us to control for many more factors in
the quit intentions and job satisfaction models than would be possible using
data from secondary published sources, because detailed individual-level data
on personal and work characteristics are not available for this industry.
Participants in the study were employed in offshore oil and gas installations
in the UK North Sea sector. The questionnaires were distributed to a random
sample of 760 offshore workers in January 2007 by offshore installation man-
agers (OIMs) in UK North Sea. Specifically, five questionnaires were sent to
152 OIMs, this represents almost all UK North Sea offshore installations. The
OIMs were asked to distribute these questionnaires to five employees on their
installation.2 The questionnaires were completed anonymously, and were then
returned to the researchers by post. Accompanying the questionnaires was a
letter to the OIM, which detailed who the researchers were, and the primary
aims of the research project (to increase our knowledge of the working prac-
tices in the North Sea oil and gas sector, and to gather information on demo-
graphic and workplace characteristics of employees within the industry). The
OIMs were also informed that this was an independent study, not commis-
sioned by any company or government body.
The questionnaires contained questions about the offshore workers’ individ-
ual and household characteristics, their job characteristics and working
arrangements, their level of job satisfaction and their future expectations
(including their intention to quit). Respondents’ subjective job satisfaction
was measured on a 6-point scale where a value of 1 corresponded to ‘very dis-
satisfied’ and a value of 6 corresponded to ‘very satisfied’. First, respondents
were asked about their job satisfaction for eight facets of their job: work envi-
ronment, workload, job stress, working hours, physical risk, wages, job secu-
rity and career prospects. Second, respondents were asked about their overall
job satisfaction. The exact question in the survey read as follows: ‘All things
considered how satisfied or dissatisfied are you with your present job, using
the 1–6 scale (1 is very dissatisfied and 6 is very satisfied)?’
This approach is similar to other measures of job satisfaction reported in
the literature and included in major surveys. The 6-point response scale used
in this study is the same as that used in the European Household Panel
Survey (ECHP). While job satisfaction is measured in similar ways in most

2
As with all survey research, the data may have a sample selection problem: where respon-
dents differ from non-respondents in either their observable or unobservable characteristics.
Unfortunately, we were unable to investigate this as no official data are available that
describe the characteristics of offshore workers in the oil and gas industry. However, from
the perspective of the type of occupations and companies the data appear to cover the full
range of offshore jobs.
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 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 613

studies, there are many different scales used to measure job satisfaction.3
Many job satisfaction scales measure satisfaction with facets of the job. In this
study, we do not use the generic facets of job satisfaction in existing scales
because we wish to capture satisfaction with the particular working practices
and the potentially serious health and safety concerns in UK’s offshore oil
and gas industry.
With respect to respondents’ individual and household characteristics,
respondents were asked about their gender, age, marital status, financial status
and their health.4 Household income may not take into account the different
financial responsibilities that individuals and their household have. To assess
respondents’ financial status, we asked respondents how they felt they were man-
aging financially: responses were gathered on a 5-point scale (living comfortably,
doing alright, just about getting by, finding it difficult and finding it very diffi-
cult). Respondents’ health was measured using the following self-assessed health
(SAH) question ‘Please think back over the last 12 months about how your
health has been. Compared to people of your own age, would you say that your
health has on the whole been excellent/good/fair/poor/very poor?’
Regarding respondents’ job characteristics and working arrangements,
respondents were asked about their occupation, the type of company they
worked for within the sector, their job security, job match, training experi-
ences and expectations. Close-ended questions were used to collect the respon-
dents’ occupation and type of company they worked for. The categories
presented to respondents are shown in Table 1. These lists were comprehen-
sive and complied with advice from experts within the industry. This informa-
tion allows us to assess whether, given our sampling strategy we have a fair
coverage of all types of offshore workers.
Furthermore, to assess respondents’ job security we asked respondents
about their employment status using three categorisations of contract (perma-
nent, fixed term or temporary5). We also explore respondents’ expectations on
their career prospects by asking if they expect to ‘get a better job with their
current employer/promotion’ in the following 12 months. To examine how
well respondents’ skills match their job we asked respondents if their current
job was ‘closely related’, ‘somewhat related’ or ‘not related’ to their qualifica-
tions/skills. Finally, to assess respondents’ past and future training opportuni-
ties we asked individuals if they had received training in the past 12 months
and also if they expect to receive work-related training in the following
12 months.

3
For example, the BHPS asks respondents their level of job satisfaction with eight facets
of their job, and measures job satisfaction on a scale of 1–7, with 1 representing ‘not satisfied
at all’ and 7 representing ‘completely satisfied’. The Workplace Employee Relations Survey
(WERS) specifies its job satisfaction variable on a scale of 1–5, with 1 representing ‘very dis-
satisfied’ and 5 representing ‘very satisfied’.
4
In general, the questions on individual, household and job characteristics followed the
question and answering formats of numerous large, national household surveys such as the
BHPS in the United Kingdom.
5
A permanent contract has no fixed period of time for ending; a fixed term contract lasts
between 1 and 3 years; and a temporary contract lasts less than 12 months.
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614 H. DICKEY, V. WATSON AND A. ZANGELIDIS

Table 1
Descriptive statistics

Variable Mean SD

Personal and household characteristics

Male (1: male; 0: otherwise) 0.960
Age (age of individual) 43.913 9.129
Married (1: married/cohabitating; 0: otherwise) 0.819
Good health (1: has good health; 0: otherwise) 0.782
Manage well (1: household manages well financially; 0: otherwise) 0.860
Job characteristics
Permanent contract (1: permanent contract; 0: otherwise) 0.882
Fewer hours (1: prefers to work fewer hours; 0: otherwise) 0.695
Had training (1: had training in the past 12 months; 0: otherwise) 0.907
Good job match (1: good skill match; 0: otherwise) 0.551
Union member 0.308
Promotion in next 12 months (1: expects promotion in next 12 months; 0: 0.296
otherwise)
Training in next 12 months (1: expects training in next 12 months; 0: 0.477
otherwise)
Quit (1: expects to quit job in next 12 months; 0: otherwise) 0.153
Occupations
Drilling (1: drilling occupation; 0: otherwise) 0.125
Drilling service support (1: drilling service support occupation; 0: otherwise) 0.028
Production/process operator (1: production/process operator; 0: otherwise) 0.137
Maintenance personnel and technicians (1: maintenance personnel and 0.212
technicians; 0: otherwise)
Geologist/geophysicist (1: geologist/geophysicist; 0: otherwise) 0.003
Engineer (1: engineer; 0: otherwise) 0.059
Engineering support (1: engineering support occupation; 0: otherwise) 0.028
Administrative (1: administrative occupation; 0: otherwise) 0.109
Catering staff (1: catering staff; 0: otherwise) 0.040
Other (1: other occupation; 0: otherwise) 0.252
Type of company
Operating company (1: operating company; 0: otherwise) 0.402
Drilling company (1: drilling company; 0: otherwise) 0.287
Engineering contractor (1: engineering company; 0: otherwise) 0.109
Catering company (1: catering company; 0: otherwise) 0.056
Service company (1: service company; 0: otherwise) 0.121
Other company (1: other company; 0: otherwise) 0.025
Number of observations 321

IV M ETHODOLOGY
A utility maximisation model of separation can provide the theoretical frame-
work for developing a simple expression for the propensity to quit. Individu-
als, while employed, may explore the labour market to find more attractive
employment opportunities. In this framework, people compare the utility they
receive from their current employment with that they expect to experience in
another job. Quit, as an outcome of this search activity, occurs when the pres-
ent value of the expected utility stream from an alternative job is higher than
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 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 615

that in the current employment, after allowing for any mobility costs. Consid-
ering V as a value function representing the utility stream from the current
job i, an individual will quit job j if Vi < Vj
C, where C is any mobility cost
incurred. The value of the utility stream can be defined as: V = V(z, h, y, j, w,
s), a function of respondents’ personal characteristics z, household characteris-
tics h, income y, job characteristics j, working conditions w, and job satisfac-
tion, s.
We investigate the relationship between job satisfaction and quitting behav-
iour by asking respondents about their future employment expectations or
intentions, that is, latent turnover (Shields and Ward, 2001; Scott et al.,
2006). Specifically, we asked respondents whether they expect to start a new
job with a new employer in the following 12 months or if they expected to
start up their own business in the following 12 months (possible responses to
each question were ‘yes’ or ‘no’). If respondents answered ‘yes’ to either start-
ing a new job with a new employer or starting up their own business, they are
considered to be a ‘quitter’; otherwise, they are a ‘stayer’.
The impact of job satisfaction and other determinants on quit intentions is
studied using a probit model, linking the probability of an individual quitting
his/her job to the characteristics of the individual and his/her job, including
job satisfaction. Considering the dichotomous nature of our quitting variable
(i.e. stayer = 0 and quitter = 1), we estimated a binary probit model to calcu-
late the probability of offshore workers intending to quit their jobs in the next
12 months. We assume that intentions to quit are a function of current job
satisfaction, along with personal and job characteristics.
Early theoretical models defined job satisfaction as a function of the money
wage and the monetary equivalent of non-pecuniary aspects of a job (Hamer-
mesh, 1977; Borjas, 1979). As the latter are generally difficult to observe and
measure, they are commonly proxied by a vector of job attributes. Therefore,
taking into account a vector of personal and household characteristics, we
model job satisfaction s as a function of respondents’ personal characteristics
z, household characteristics h, income y, job characteristics j and working
conditions w:
s ¼ fðz; h; y; j; wÞ: ð1Þ
When the dependent variable in a regression equation is the overall job sat-
isfaction or its different facets, the multinomial probability model can be used
to predict the influence of various factors on the probability of giving a cer-
tain response. Given that s is measured as an ordinal variable, an ordered
probit model is estimated. The regressions control for a number of personal,
household and job characteristics that have been identified by previous litera-
ture as important predictors of job satisfaction. The explanatory variables
specified in the job satisfaction model included standard measures of the
objective position of the offshore worker, including age, gender, marital sta-
tus, health, household financial situation, type of contract, as well as variables
relating to the individual’s expectations of the future with respect to training
and promotion.
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616 H. DICKEY, V. WATSON AND A. ZANGELIDIS

V R ESULTS
A total of 330 complete questionnaires were returned, giving a response rate
of 43%. As a result of missing values in some of the questions,6 the empirical
analysis was carried out on a sample of 321 individuals. Table 1 presents the
descriptive statistics of the individual and household characteristics and work-
place features used in this study. The average respondent is a married man,
aged 44 years, in good health, whose household manages well financially. Of
the total sample, 96% were men, 82% were married or co-habitating, 78%
reported they have good health and 86% reported that their household man-
ages well financially.
All the main offshore jobs/occupations were adequately represented in the
sample: 21% of respondents were maintenance personnel and technicians,
14% were production/process operators, 15% were either drillers or support
staff and 11% were administrators. Respondents were primarily employed by
operating (40%) and drilling companies (29%), followed by service companies
(12%) and engineering contractors (11%). The majority of the respondents
have permanent contracts (88%). Just under half of respondents (48%) expect
to receive some kind of training in the following 12 months. Approximately
30% of the respondents expect to get a better job/promoted with their current
employer in the next 12 months; this suggests that career development oppor-
tunities exist in the oil and gas industry.
More than half (55%) of the respondents stated that their job was ‘closely
related’ to their skills/qualifications. Ninety-one per cent of respondents had
received training in the past 12 months and 48% of respondents expected to
receive some kind of training in the following 12 months. Respondents were
asked about their preferences over the days spent offshore and the majority
(70%) stated that they would prefer shorter offshore periods.
Four different specifications of a quit intentions model are estimated using
a probit regression and the derived marginal effects are presented in Table 2.
Overall, quit intentions are primarily affected by workplace attributes, and
not personal or household characteristics. In Model 1, respondents’ demo-
graphic characteristics do not have a significant effect on their intention to
quit. Only respondents’ expectations of future promotion or training expecta-
tions are significant. Specifically, the expectation of receiving training and pro-
motion in the next 12 months reduces offshore workers’ intentions to quit
their jobs. If respondents are in a work environment where they expect to
receive training or promotion, these may indicate that employers have sig-
nalled to the respondents their commitment in developing their skills and
career.
In Table 2, Model 2, we consider the effect of workers’ reported level of
overall satisfaction on quit intentions. The inclusion of job satisfaction as an
explanatory variable in the quit intentions model implicitly assumes that the
6
There is one missing observation in each of the following variables: overall job satisfac-
tion; satisfaction with work environment, job stress, working hours, physical risk, wages and
job security; and type of company. Moreover, there are two additional missing observations
in the variable satisfaction with job security.
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 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 617

error terms in the job satisfaction and quit intentions models are not corre-
lated (i.e. there is no unobservable individual heterogeneity that simulta-
neously determines job satisfaction and quit intentions). This issue is
addressed in a number of studies (Clark et al., 1998; Shields and Ward, 2001).
Shields and Ward (2001) conclude that ‘the relationship between job satisfac-
tion and quitting, identified in cross-sectional studies, is robust to concerns
about unobserved individual heterogeneity’ (p. 693).
We find that job satisfaction is a significant determinant of quit intentions
in the next 12 months, and respondents who report higher levels of job satis-
faction are less likely to state an intention to quit their job. This is consistent
with both the theoretical literature and previous empirical studies; Freeman
(1978) and Shields and Ward (2001) reported that job satisfaction is a signifi-
cant determinant of the probability of quitting. Freeman (1978) concluded
that satisfaction is a major determinant of labour mobility, and that this sta-
tistical link between job satisfaction and quit intentions suggests that non-
pecuniary factors are important in workers’ mobility between jobs. As pointed
out by Shields and Ward (2001), our results represent a lower bound estimate
of the impact of job satisfaction on quitting because the most dissatisfied
workers are likely to have already left their job, resulting in downward-biased
estimated job satisfaction effects.
Furthermore, in this specification (Table 2, Model 2), having undertaken
training increases respondents’ intentions of quitting their job in the next
12 months; this can be explained when training increases workers’ human cap-
ital and employability. Receiving training acts as a signal of the individual’s
ability and skills to outsiders. Consequently, individuals who received training
may attract more outside offers, or alternatively, start their own business
using the skills and experience they have acquired.
Although Model 2 reveals the importance of individuals’ overall job satis-
faction on their quit intentions, it is not clear whether satisfaction with spe-
cific facets of the job drives this effect. To further explore this issue, the quit
equation is re-estimated with the inclusion of satisfaction with the eight facets
of the job (Model 3). The estimates suggest that satisfaction with the work
environment, wages and job security reduce the probability of quitting.7 This
identifies the specific aspects of the job that are important to workers’ job
mobility decisions. Employers and human resource managers can design more
successful retention policies by focusing more on these job facets.
Given that the constructs underlying the eight facets may overlap, one
might expect respondents’ satisfaction with these eight job facets to be corre-
lated; in this case, we should not include all facets in our model of quit inten-
tion. Hence, in addition to considering all eight facets of job satisfaction in a
quit intention equation, we use principal component analysis to summarise
satisfaction with the eight facets into composite factors, which are included as
7
One puzzling finding is the positive relationship between satisfaction with the level of
physical risk in the offshore job and the probability of intending to quit that job. This may
be driven by the high correlation between this and the rest of the facets of job satisfaction
(Table 4).
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
 Table 2
618

Determinants of quit intentions in current job

(1) (2) (3) (4)

Job satisfaction
Overall
0.082*** (
4.07)
Working environment
0.069*** (
3.21)
Workload
0.022 (
1.13)
Job stress 0.022 (1.2)
Working hours 0.012 (0.63)

Scottish Journal of Political Economy

Physical risk 0.041** (2.57)
Wages
0.035** (
2.27)
Job security
0.032* (
1.75)
Career prospects 0.004 (0.23)
Comp1
0.044*** (
3.19)
Comp2
0.007 (
0.46)
Male
0.029 (
0.32)
0.076 (
0.79)
0.075 (
0.76)
0.067 (
0.67)
Age
0.002 (
0.91)
0.001 (
0.73)
0.001 (
0.88)
0.002 (
0.83)
Married
0.009 (
0.17)
0.024 (
0.46)
0.046 (
0.97)
0.026 (
0.49)
Good health
0.072 (
1.37)
0.016 (
0.37)
0.047 (
0.99)
0.041 (
0.84)
Manage well
0.049 (
0.80)
0.023 (
0.42) 0.011 (0.26)
0.019 (
0.36)
Permanent contract 0.011 (0.21) 0.023 (0.52) 0.035 (1.07) 0.046 (1.15)
Fewer hours 0.004 (0.09)
0.024 (
0.54) 0.003 (0.08)
0.014 (
0.30)
Had training 0.063 (1.3) 0.076** (2.24) 0.064** (2.19) 0.073** (2.03)
Good job match 0.017 (0.43) 0.025 (0.71)
0.001 (
0.03) 0.02 (0.54)
Promotion in next 12 months
0.124*** (
3.41)
0.128*** (
4.09)
0.110*** (
4.26)
0.116*** (
3.48)
H. DICKEY, V. WATSON AND A. ZANGELIDIS

Training in next 12 months
0.126*** (
3.21)
0.120*** (
3.30)
0.096*** (
2.95)
0.117*** (
3.19)

© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
Type of company Yes Yes Yes Yes
Pseudo-R2 0.130 0.204 0.274 0.186
log pseudo-likelihood
119.27
109.15
99.58
111.6

Notes: Marginal effects with z-statistics in parentheses, based on probit estimates.

*p < 0.1; **p < 0.05; ***p < 0.01.
Comp1 and Comp2, components 1 and 2.
 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 619

explanatory variables in the quit intentions model (Model 4). The objective of
principal component analysis is to create a small number of new component
variables, which summarise the information contained in the larger set of vari-
ables.
The results from the principal component analysis are presented in the
Appendix. Component 1 is mainly constructed based on the individuals’ per-
ceived level of satisfaction from the work environment, physical risk, wages,
job security and career prospects. The three remaining domains of job satis-
faction, satisfaction with the workload, job stress and working hours are the
primary factors of the second component. These two components are then
included in the quit intention equation along with the other demographic and
workplace characteristics (Model 4).
One of the advantages of using the principal component analysis is that it
allows us to identify those particular aspects of the job that are more impor-
tant in influencing offshore workers’ intentions to quit their jobs. Higher levels
of satisfaction associated with facets of the job in the first component are sta-
tistically significant and reduce the probability of quitting, whereas the coeffi-
cient for the second component is statistically insignificant. Therefore, lower
intentions to quit are associated with higher satisfaction with job security,
career prospects, wages and the work environment. This finding confirms the
results obtained in the previous model specification, and has implications for
companies’ retention policies. Policy design should concentrate on those
aspects of the job that reduce the probability of quitting; specifically, career
development policies that provide job security, future opportunities for pro-
motion and training, as well as policies aimed at improving both pay and the
offshore work environment.
The findings from the quit intention models highlights the importance of
job satisfaction as a significant determinant of offshore workers’ intentions to
quit their jobs. This consequently raises the important question of what deter-
mines offshore workers’ job satisfaction. Specifically, if higher levels of satis-
faction with particular aspects of the job (e.g. the work environment, wage,
job security and career prospects) reduce the probability of offshore workers
intending to quit, then it will be important for companies when forming their
retention policies to know what influences offshore workers’ satisfaction with
these particular aspects of their job.
A summary of respondents’ job satisfaction with the eight facets of their
job and their overall job satisfaction is presented in Table 3. While responses
varied over respondents, on average, respondents appear to be fairly satisfied
with their employment. The correlations between reported satisfaction for the
eight facets are presented in Table 4. While there is some correlation between
each of the facets, this is low in most cases, which indicates that these facets
are capturing different aspects of the job and respondents are distinguishing
between the facets. For three facets, work environment, workload and job
stress, the correlations are higher between 0.6 and 0.7. This may indicate that
these facets are measuring the same underlying construct. The ranking of
respondents’ job satisfaction with the eight facets of their job, from most
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
620 H. DICKEY, V. WATSON AND A. ZANGELIDIS

Table 3
Distribution of job satisfaction

Frequency of scores (%)

Job satisfaction
Score: 1 2 3 4 5 6 Mean SD

Overall 1.56 5.3 13.08 38.94 33.96 7.17 4.20 1.04

Work environment 1.87 5.61 13.4 36.76 35.2 7.17 4.19 1.06
Workload 2.18 14.33 16.51 31.15 29.91 5.92 3.90 1.21
Job stress 3.74 10.9 21.18 35.2 23.68 5.3 3.80 1.18
Working hours 3.43 12.77 20.56 32.09 25.86 5.3 3.80 1.21
Physical risk 2.8 4.36 12.77 30.22 36.45 13.4 4.33 1.16
Wages 4.98 10.59 21.81 26.48 28.97 7.17 3.85 1.28
Job security 3.43 7.17 17.76 28.04 38.63 4.98 4.06 1.17
Career prospects 6.23 9.97 18.38 26.48 33.02 5.92 3.88 1.30

Notes: This table shows that respondents reported satisfaction with their overall job, and eight aspects of
their job. The columns correspond to the scale used to rank job satisfaction, with one representing ‘very
dissatisfied’ and six representing ‘very satisfied’. The numbers in the table report the percentage of respon-
dents who reported that level of satisfaction, for example, 7.17% of respondents reported that they were
very satisfied with their present job.

satisfaction to least satisfaction, is: physical risk, work environment, job secu-
rity, workload, career prospects, wages, working hours and job stress. The sta-
tistical significance of the observed differences in the reported mean job
satisfaction is also presented in Table 4. Overall, there appears to be signifi-
cant variation on the job satisfaction scores across the eight different job
domains and the overall perceived level of satisfaction.
We found that respondents were most satisfied with the physical risk of off-
shore jobs. This is contrary to the concerns raised by the Health and Safety
Executive (HSE, 2007; Key Programme 3: Asset Integrity Programme) about
safety in UK’s oil and gas industry.8 However, respondents’ reported satisfac-
tion with their job’s physical risk is based on their perceptions of risk and the
incidences or accidents they have experienced. These perceptions and experi-
ences may be quite different from the actual safety conditions present in their
offshore installation.9 Respondents were least satisfied with their job stress
and their working hours. This may be driven by the offshore work environ-
ment. The working time arrangements for the majority of offshore workers
consist of working 12-hour shifts for 15 consecutive days: 69.5% of respon-
dents stated that they would prefer to work fewer days offshore.
The overall job satisfaction equation is estimated and presented in
Table 5.10 When considering the impact of personal and household character-
istics on individual’s overall job satisfaction, we found that several of the

8
This investigation involved inspections of nearly 100 offshore installations concerning
their safety and integrity and the equipment on installations.
9
Studies have found that individuals are often too optimistic about their risk of injury or
illness compared with their assessment of the risks that others face (Weinstein, 1984).
10
The calculated marginal effects for the six different response outcomes are provided in
Table A3.
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
 Table 4
Correlation matrix of job satisfaction domains

Work Job Working Physical Job Career

Scottish Journal of Political Economy

Overall environment Workload stress hours risk Wages security prospects

Overall 0.615 0.477*** 0.495*** 0.529*** 0.420** 0.525*** 0.567** 0.615***

Work 0.537*** 0.421*** 0.495*** 0.464** 0.403*** 0.540** 0.416***
environment
Workload 0.648* 0.666* 0.273*** 0.312 0.310** 0.283
Job stress 0.602 0.329*** 0.275 0.320*** 0.329
Working hours 0.357*** 0.412 0.391*** 0.379
Physical risk 0.341*** 0.435*** 0.394***
Wages 0.474*** 0.493
Job security 0.537***
Career prospects

Notes: Pair-wise correlation coefficients presented. All correlation coefficients are significant at p < 0.01. Pair-wise comparisons of mean score of job satisfaction in different job fac-
ets were also performed. Asterisks indicate statistically significant differences.
*p < 0.1; **p < 0.05; ***p < 0.01.

© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS
621
622 H. DICKEY, V. WATSON AND A. ZANGELIDIS

characteristics commonly found to be important in the job satisfaction litera-

ture had a significant effect for offshore workers, while others did not. Gender
and age are not important determinants of job satisfaction for offshore work-
ers, whereas health and marital status do influence their levels of job satisfac-
tion. Respondents who are married or living with a partner are less satisfied
with their jobs, perhaps reflecting the nature of offshore work, where workers
are offshore for 15 days consecutively and are away from their families for
this time.
The significant positive effect of health on job satisfaction supports previous
empirical studies such as those by Clark (1997), who found that good health
has a consistent, large and well-defined positive effect on job satisfaction.
However, the causality of the relationship between poor health and low job
satisfaction is not clear. Are respondents dissatisfied because they are in poor
health or they are in poor health because they are dissatisfied? In general,
studies have suggested that job satisfaction affects individuals’ health, through
stress, anxiety and depression (see Faragher et al., 2005, for a literature review
on the issue). This relationship between health and job satisfaction also con-
curs with the findings of French et al. (1982) for offshore workers.
With respect to job characteristics, the strongest influence on reported job
satisfaction is the effect of working hours, where longer working hours are
associated with lower overall job satisfaction. This result is in line with previ-
ous studies such as those by Clark (1997). This finding may have important
implications for the recruitment and retention of skilled workers within the
offshore industry. If long working hours are the main determinant of job dis-
satisfaction amongst offshore workers, then companies should consider the
current working time arrangements and the role they play in hindering recruit-
ment into the industry.
With respect to income, individuals who reported that their household man-
ages well financially exhibit higher levels of job satisfaction. If we use this
household income variable as a proxy of pay, this finding supports the
hypothesis that job satisfaction is positively correlated with pay. In line with
the literature (Allen and van der Velden, 2001; Vieira, 2005), skill mismatches
are a good predictor of job satisfaction, with individuals in jobs with good
skill matches experiencing higher levels of job satisfaction. At the time of
recruitment, giving consideration to an individual’s skills level and their job
match may promote higher levels of job satisfaction. In addition, providing
ongoing training and human capital investment after hiring will reduce the
probability of workers leaving their employers.
Interestingly, we find that individuals respond more to their past experi-
ences than to anticipated future prospects. Specifically, people who received
training in the previous 12 months have higher job satisfaction than those
who did not receive training. However, expectations of receiving training, or
getting promoted in the next 12 months do not appear to affect current levels
of job satisfaction. Shields and Ward (2001) found that the largest effect on
the job satisfaction, of nurses working in the National Health Service in
England, was being in a workplace where training and other forms of human
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
 Table 5
The determinants of job satisfaction

Work Working Physical Job Career

Overall environment Workload Job stress hours risk Wages security prospects

Male
0.217
0.155
0.006
0.425
0.238
0.018 0.021
0.504* 0.18
(
0.59) (
0.37) (
0.01) (
1.18) (
0.62) (
0.06) (0.08) (
1.83) (0.8)
Age 0.007 0.141**
0.027
0.045
0.03 0.113**
0.023 0.067 0.091
(0.11) (2.41) (
0.46) (
0.79) (
0.55) (1.99) (
0.42) (1.2) (1.58)

Scottish Journal of Political Economy

Age2 8.33e
5
0.002** 3.95e
4 4.94e
4 4.38e
4
0.001** 2.64e
4
0.001
0.001*
(
0.12) (
2.31) (0.58) (0.75) (0.68) (
2.01) (0.40) (
1.28) (
1.82)
Married
0.339*
0.589***
0.248
0.109
0.2
0.18
0.440*** 0.02
0.299**
(
1.90) (
3.63) (
1.53) (
0.69) (
1.26) (
1.12) (
2.86) (0.11) (
1.98)
Good health 0.491*** 0.292* 0.158 0.185 0.145 0.198
0.016 0.464*** 0.338**
(3.26) (1.96) (1.11) (1.22) (1.09) (1.21) (
0.11) (3.07) (2.20)
Manage well 0.493*** 0.341** 0.595*** 0.360** 0.218
0.053 0.883***
0.008 0.328*
(3.04) (2.01) (3.39) (2.05) (1.22) (
0.30) (4.94) (
0.05) (1.91)
Permanent contr. 0.041 0.147
0.05 0.225 0.281 0.464** 0.576*** 0.604***
0.001
(0.20) (0.64) (
0.24) (1.05) (1.23) (2.28) (2.76) (2.85) (
0.00)
Fewer hours
0.659***
0.380***
0.229*
0.271**
0.721***
0.251*
0.295**
0.167
0.417***
(
4.43) (
2.60) (
1.69) (
2.11) (
5.44) (
1.93) (
2.17) (
1.18) (
3.20)
Had training 0.480** 0.348* 0.231 0.104 0.499** 0.14 0.333 0.156 0.632**
(2.08) (1.69) (1.24) (0.59) (2.17) (0.63) (1.33) (0.58) (2.51)
Good job match 0.252* 0.182 0.061 0.267** 0.043 0.208 0.066
0.007 0.169
(1.93) (1.45) (0.47) (2.13) (0.32) (1.58) (0.54) (
0.05) (1.3)

© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
Union member
0.082
0.146
0.068
0.274**
0.215*
0.021
0.025
0.085
0.045
(
0.61) (
1.14) (
0.55) (
2.22) (
1.68) (
0.17) (
0.20) (
0.69) (
0.35)
Promotion in next
0.150
0.060 0.017 1.00e
4 0.092
0.003 0.155
0.100 0.073
JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS

12 months (
1.02) (
0.39) (0.12) (0.00) (0.68) (
0.02) (1.06) (
0.69) (0.51)
623
 624

Table 5 (Continued)

Work Working Physical Job Career

Scottish Journal of Political Economy

Overall environment Workload Job stress hours risk Wages security prospects

Training in next
0.059
0.054 0.002
0.206
0.117
0.083 0.054 0.005 0.058
12 months (
0.47) (
0.42) (0.02) (
1.55) (
0.89) (
0.63) (0.42) (0.04) (0.46)
Occupation Yes Yes Yes Yes Yes Yes Yes Yes Yes
Type of company Yes Yes Yes Yes Yes Yes Yes Yes Yes
Constant 2.033 4.572*** 1.377 0.539 1.257 3.994*** 1.813 3.172** 4.047***
(
1.44) (
3.4) (
1.04) (
0.4) (
0.96) (
2.92) (
1.42) (
2.42) (
3.03)
Pseudo-R2 0.103 0.068 0.043 0.044 0.065 0.052 0.08 0.061 0.073
log pseudo-
405.88
427.5
476.61
478.04
472.17
456.15
478.04
447.35
476.11
likelihood

Notes: Coefficients with z-statistics in parentheses, based on ordered probit estimates.

*p < 0.1; **p < 0.05; ***p < 0.01.
H. DICKEY, V. WATSON AND A. ZANGELIDIS

© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 625

capital development were encouraged. One explanation for the positive rela-
tionship between training and job satisfaction is that training signals the
employer’s commitment to its employees’ skills development, and within the oil
and gas industry, improving health and safety standards. Alternatively, workers
who have received training in the previous 12 months may link this investment
by their employer to their job security: Blanchflower and Oswald (1999) found
job security to be the most important determinant of job satisfaction.
The quit intention results reported in Table 2, Models 3 and 4, motivate a
further examination of the job satisfaction facets and their impact upon quit-
ting behaviour. Specifically, if higher levels of satisfaction with the working
environment, wages, job security and career prospects reduce the probability
of offshore workers intending to quit their jobs, then it is of interest to investi-
gate what affects satisfaction with these particular aspects of offshore jobs.
Hence, separate job satisfaction equations are estimated for each of the eight
facets, respectively, and presented in columns (2)–(9) of Table 5. Overall,
respondents’ demographic characteristics are not significant explanatory vari-
ables for their satisfaction with the eight job facets, except for individuals’
marital status. The estimates reveal that married people report lower levels of
job satisfaction regarding the work environment, wages and career prospects.
Individuals who are doing well financially are found to be more satisfied not
only with their wages but also with their workload and job stress. Having a
permanent work contract increases the reported satisfaction with physical risk,
wages and job security. Individuals with a preference for fewer working hours
are less satisfied with various job facets. Individuals who received training are
more satisfied with their career prospects in the current job, while those in a
good job match are more satisfied with their job stress. Finally, union mem-
bers are less satisfied with the level of job stress, a finding that may be
explained by a self-selection process whereby individuals dissatisfied with the
level of job stress join a trade union to voice their discontent.
With respect to the job facets that significantly impact upon offshore work-
ers’ intentions to quit: having a permanent contract increases satisfaction with
pay and job security; being in good health positively affects individuals’ satis-
faction with the work environment, job security and future job prospects; and
having received training in the past increases satisfaction with both the work-
ing environment and future job prospects. In contrast, being married and pre-
ferring to work fewer hours has a negative impact on satisfaction with the
working environment, pay and future prospects.
The estimates in Table 5 allow us to design a working environment that
would reduce quit intentions by increasing individuals’ overall job satisfaction
and satisfaction with specific facets of the job. Such a workplace would (a)
offer pecuniary rewards that would enable individuals’ household to manage
well financially; (b) provide training; (c) offer a permanent job contract; (d)
allocate individuals to jobs that are a good match with their qualifications
and skills; and (e) allow people to work their desired number of hours. To
estimate the magnitude of the effect that such workplace characteristics may
have on job satisfaction, we examined what would happen when an individual
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
626 H. DICKEY, V. WATSON AND A. ZANGELIDIS

Table 6
The effect of moving from a ‘bad’ to a ‘good’ workplace on job satisfaction scores

Score: 1 2 3 4 5 6

Overall
0.104
0.200
0.244
0.053 0.458 0.144

Work environment
0.082
0.158
0.193
0.038 0.360 0.111
Workload
0.076
0.227
0.093 0.059 0.263 0.075
Job stress
0.133
0.184
0.137 0.110 0.261 0.082
Working hours
0.183
0.284
0.150 0.132 0.369 0.116
Physical risk
0.074
0.079
0.146
0.082 0.220 0.160
Wages
0.402
0.243
0.058 0.209 0.380 0.114
Job security
0.080
0.115
0.136 0.010 0.272 0.049
Career prospects
0.237
0.188
0.131 0.079 0.381 0.096

Note: This table provides the estimated change in the probability of individuals reporting a specific job
satisfaction score when moving from a ‘bad’ job to a ‘good’ job.

moves from a ‘bad’ workplace, one that does not offer the aforesaid features,
to a ‘good’ workplace. Table 6 provides the change in the probability of indi-
viduals reporting a specific job satisfaction score when such a workplace
change occurs. According to the estimates, the probability of reporting a level
of overall job satisfaction equal to 5 increases by 45.8%.11 This example sug-
gests aspects in the workplace that managers could focus on to increase
employees’ job satisfaction and improve retention rates. It is estimated that an
increase in the reported overall job satisfaction from 4 to 5 decreases the
probability of intending to quit by around 7%.
Nevertheless, there are also other work-related characteristics that may have
a more direct and significant effect on quit intentions. One example is promo-
tion or training opportunities. It is found that individuals who expect to get
promoted or receive training in the coming 12 months are around 12% less
likely to want to quit their job.12 In addition, some aspects of the job have a
direct and indirect effect on quit intentions that may work in opposite direc-
tions. For example, individuals who had training in the past 12 months are
6.8% more likely to intend to quit their current job. However, having received
training also increases overall job satisfaction, which reduces the propensity of
quit intentions.
There are three main limitations in this study. First, the paper focuses on
employees within a very particular industry sector, the UK sector of the
North Sea oil and gas industry. Therefore, one may question how the findings
add to the wider literature on job satisfaction and quit intentions. While the
results found in the study may not be useful for understanding worker behav-
iour in all sectors, they may reflect job satisfaction and job mobility patterns
observed in other industry sectors that have similar characteristics in terms of

11
Similarly, the effect on the different facets of job satisfaction ranges from 22% to 38%.
12
Almost double the effect an increase in the overall job satisfaction score from 4 to 5 can
achieve.
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 627

their working time arrangements, workforce composition and market features.

However, this does not limit the importance of the results for managers in the
oil and gas sector, and suggests that similar studies could be carried out in
other industries to better inform retention policies within these sectors. Sec-
ond, as with all survey research, the respondents may have a different profile
of observable and unobservable characteristics from the non-respondents.
Unfortunately, because of the lack of official data on the overall characteris-
tics of the offshore workforce we were unable to investigate the representative-
ness of our survey sample. Nevertheless, from the perspective of the type of
occupations and companies the data appear to have adequate representation
of the full range of offshore jobs. Third, this study focuses on individuals’
intentions to quit in the following 12 months. Given that there is no follow-
up in our questionnaire, we do not know how many of those who intended to
quit, actually did. There are two possible reasons why an individual who
intended to quit in the coming 12 months would not do this. First, those who
intend to quit may be more informed or more engaged in the job market,
which allows them to identify job opportunities, or they could be more
aggressive in their job search. Second, moving to a new job is the outcome of
a two-step process: an individual queues for a job, and the employer hires the
individual from a pool of applicants. This implies that those who intend to
quit and those who intend to stay may also differ in their attractiveness to
employers. By focusing on individuals’ intentions to quit, we avoid these
caveats, and we are able to examine what makes individuals want to quit their
job.

VI C ONCLUSION
Oil and gas companies operating in the UK North Sea sector report that
there is a substantial shortage of skilled workers within the industry, which is
a result of both a failure to attract sufficient new entrants into offshore occu-
pations and the poor retention of existing qualified offshore workers. This
skills shortage within the industry is predicted to continue, and will therefore
have serious implications for the industry’s ability to sustain long-term
growth. This paper addresses the retention difficulties faced by oil and gas
companies by analysing quit intentions and job satisfaction of offshore
employees in the UK North Sea oil and gas industry. The data were collected
through the purpose-designed questionnaire that provides valuable and
unique information on the demographic and socioeconomic characteristics of
the respondents and their households, and the respondents’ views about their
current employment.
We find that, on the whole, workers are satisfied with their offshore job
and with specific aspects of their employment. Respondents report that they
are most satisfied with the level of physical risk they face in their offshore
jobs, followed by their work environment and job security. In line with other
studies of job satisfaction, we find a positive relationship between respon-
dents’ health and job satisfaction. We find that individuals in good financial
Scottish Journal of Political Economy
© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
628 H. DICKEY, V. WATSON AND A. ZANGELIDIS

condition, those whose skills are closely related to their offshore job, and those
who received training in the previous 12 months are estimated to report higher
levels of perceived job satisfaction. With respect to financial condition (which
is a proxy for income), our results are consistent with the findings of Clark
et al. (1996) and Gardner and Oswald (2001). However, in contrast to these
studies we do not find a significant relationship between age and job satisfac-
tion. Our results further provide evidence that a preference to work fewer
hours offshore is a very important determinant of job satisfaction among
offshore workers, suggesting that recruitment and retention policy design
should place more importance upon the working time arrangements within the
industry.
We also find strong evidence that job satisfaction, promotion prospects and
training opportunities are the most important determinants of intentions to
quit among offshore workers. Interestingly, providing training could be
regarded as a double-edged sword for employers, as the workers who had
training in the previous 12 months report higher levels of job satisfaction, but
are also more likely to intend to quit. Nevertheless, this finding is consistent
with the relatively recent training literature based on the assumption of imper-
fectly competitive labour markets that identifies the conditions under which
firms may finance general training (Katz and Ziderman, 1990; Stevens, 1994;
Stevens, 1996; Loewenstein and Spletzer, 1998; Acemoglu and Pischke, 1999;
Booth and Zoega, 1999; Booth and Bryan, 2002).
Overall, these findings establish the importance of job satisfaction, and pro-
motion and training opportunities in determining workers’ intentions to quit
within UK’s North Sea oil and gas industry, and suggest policies that focus
only on improving pay will have limited success unless they are accompanied
by promotion and training opportunities aimed at investing in worker’s skills
and career development. Giving consideration to the match between an indi-
vidual’s skills/qualifications and the job at the time of recruitment may help
to promote higher levels of job satisfaction once employees have been hired,
and providing ongoing investment in employees’ skills, along with opportuni-
ties to gain promotion, will reduce the probability of workers leaving their
employers.

A CKNOWLEDGEMENTS
The authors gratefully acknowledge grants from the Carnegie Trust for the
Universities of Scotland, and the College of Arts & Social Sciences at the Uni-
versity of Aberdeen. They would also like to thank the two anonymous
reviewers for their valuable comments. The views expressed in this article are
of the authors and any remaining errors remain their responsibility.

APPENDIX
The objective of principal component analysis is to create a small number of
new component variables, which summarise the information contained in the

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 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 629

Table A1
Principal components/correlation

Component Eigenvalue Difference Proportion Cumulative

Comp1 3.97499 2.79415 0.4969 0.4969

Comp2 1.18084 0.478683 0.1476 0.6445
Comp3 0.702159 0.14413 0.0878 0.7322
Comp4 0.558029 0.0298881 0.0698 0.802
Comp5 0.528141 0.118315 0.066 0.868
Comp6 0.409826 0.0420777 0.0512 0.9192
Comp7 0.367748 0.0894858 0.046 0.9652
Comp8 0.278262 . 0.0348 1

Table A2
Scoring coefficients

Variable Comp1 Comp2

Work environment 0.3031 0.2386

Workload
0.0596 0.6075
Job stress
0.0359 0.5629
Working hours 0.0696 0.5013
Physical risk 0.4028 0.0225
Wages 0.4601
0.0224
Job security 0.5165
0.0395
Career prospects 0.5077
0.0574

Note: Rotated factor matrix calculated from a two-component solution.

larger set of variables. This is done by identifying the linear combinations of

the original variables with the greatest variance (i.e. that contains most of the
information in those variables).
The eight components along with the corresponding scoring coefficients are
presented in Tables A1 and A2. As a rule of thumb, only the components
with eigenvalues above unity are kept. In this case, two components are
formed, which together capture 64% of the variance in the responses to the
eight job satisfaction variables. The rotated matrix of the scoring coefficients,
obtained from a two-component solution, is provided in Table A2. The
scoring coefficients take values between
1 and 1, and the significant factors
in each component are highlighted in the table. Component 1 is mainly
constructed based on individuals’ perceived level of satisfaction from the
work environment, physical risk, wages, job security and career prospects.
The three remaining domains of job satisfaction, satisfaction with the work-
load, job stress and working hours are the primary factors of the second
component.

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© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
 630

Table A3
Marginal effects from overall job satisfaction equation

Overall job satisfaction outcome

1 2 3 4 5 6

Scottish Journal of Political Economy

Male 0.003 (0.72) 0.013 (0.68) 0.031 (0.63) 0.038 (0.50)
0.063 (
0.61)
0.022 (
0.50)
Age
1.18e
4 (
0.11)
4.69e
4 (
0.11)
0.001 (
0.11)
0.001 (
0.11) 0.002 (0.11) 0.001 (0.11)
Age2 1.51e
6 (0.12) 6.00e
6 (0.12) 1.27e
5 (0.12) 1.20e
5 (0.12)
2.50e
5 (
0.12)
7.22e
6 (
0.12)
Married 0.005 (1.60) 0.021** (1.97) 0.048** (2.07) 0.060 (1.57)
0.098** (
1.99)
0.036 (
1.57)
Good health
0.013* (
1.88)
0.044** (
2.33)
0.079*** (
2.93)
0.045*** (
3.04) 0.146*** (3.31) 0.034*** (3.29)
Manage well
0.014 (
1.50)
0.046** (
2.18)
0.080*** (
2.84)
0.038*** (
2.77) 0.146*** (3.14) 0.032*** (3.11)
Permanent contract
0.001 (
0.19)
0.003 (
0.19)
0.006 (
0.19)
0.006 (
0.20) 0.012 (0.20) 0.003 (0.20)
Fewer hours 0.010* (1.87) 0.040*** (3.72) 0.091*** (4.18) 0.116*** (3.31)
0.183*** (
4.73)
0.073*** (
3.09)
Had training
0.014 (
1.29)
0.046 (
1.49)
0.078** (
2.00)
0.034** (
2.51) 0.142** (2.19) 0.030** (2.57)
Good job match
0.005 (
1.47)
0.019* (
1.80)
0.039* (
1.85)
0.035* (
1.84) 0.075* (1.91) 0.021* (1.91)
Union member 0.002 (0.57) 0.006 (0.60) 0.013 (0.60) 0.011 (0.63)
0.025 (
0.61)
0.007 (
0.62)
Promotion in next 12 months 0.003 (0.89) 0.011 (0.95) 0.023 (1.00) 0.020 (1.09)
0.045 (
1.02)
0.012 (
1.08)
Training in next 12 months 0.001 (0.48) 0.004 (0.46) 0.009 (0.46) 0.009 (0.47)
0.018 (
0.47)
0.005 (
0.47)
Occupation Yes Yes Yes Yes Yes Yes
Type of company Yes Yes Yes Yes Yes Yes
H. DICKEY, V. WATSON AND A. ZANGELIDIS

© 2011 The Authors. Scottish Journal of Political Economy © 2011 Scottish Economic Society
Notes: Marginal effects with z-statistics in parentheses, based on ordered probit estimates.
*p < 0.1; **p < 0.05; ***p < 0.01.
 JOB SATISFACTION AND QUIT INTENTIONS OF OFFSHORE WORKERS 631

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Date of receipt of final manuscript: 17 February 2011

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