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Self determination theory and employed job search
Journal of Economic Psychology 44 (2014) 34–44
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Self determination theory and employed job search Riccardo Welters a,⇑, William Mitchell b,c,1, Joan Muysken d,2 a
James Cook University, School of Business, Townsville, 4811 QLD, Australia Centre of Full Employment and Equity, University of Newcastle, Callaghan, 2308 NSW, Australia Charles Darwin University, Brinkin, 0810, NT, Australia d Maastricht University, School of Business and Economics, 6200 MD Maastricht, The Netherlands b c
a r t i c l e
i n f o
Article history: Received 10 December 2013 Received in revised form 5 June 2014 Accepted 14 June 2014 Available online 20 June 2014 JEL classification: J08 J28 PsycINFO classification: 2228 3650
a b s t r a c t Self Determination Theory (SDT) predicts that employees who use controlled motivation to search for alternate (better) work are less successful than their counterparts who use autonomous motivation. Using Australian labour market data, we find strong support for SDT. We find that workers who face externally regulated pressures (pressure arising from involuntary part-time or casual labour contracts) to search for alternate employment are less likely to find better work, than workers who use autonomous motives to search for work. Our findings suggest that labour market policies trending towards ‘labour market flexibility/deregulation’ – which provide workers with controlled motives to search for work – will contribute to workers cycling through spells of insecure employment and possibly intermittent spells of unemployment with no realistic prospect of career development. Ó 2014 Elsevier B.V. All rights reserved.
Keywords: Personnel attitudes & Job satisfaction Self determination theory Motivation Empirical study
1. Introduction In 1994, the Organisation for Economic Co-ordination and Development (OECD) made various recommendations to ‘‘increase wage and labour cost flexibility’’ and ‘‘reform employment security provision’’ in an attempt to reduce unemployment. OECD (1994) claimed that a more flexible, deregulated labour market would entice employers to create more employment and hence lead to lower unemployment. This induced most OECD member countries to promote labour market policies which (among others) reduced job security of employees. However, when the OECD evaluated its reform agenda in 2006, it concluded: ‘... the reduction of unemployment does not correlate very strongly with reform intensity’ (OECD, 2006: 69) indicating its reform package had not been a success – see also Mitchell and Muysken (2008) for a comprehensive critique of the OECD Jobs Study reforms at the macroeconomic level.
⇑ Corresponding author. Tel.: +61 (0)7 4781 4325. E-mail addresses: [email protected] (R. Welters), [email protected] (W. Mitchell), [email protected] (J. Muysken). 1 Tel.: +61 (0)2 4921 7283. 2 Tel.: +31 (0)4 3388 3808. http://dx.doi.org/10.1016/j.joep.2014.06.002 0167-4870/Ó 2014 Elsevier B.V. All rights reserved.
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This paper will look at the consequences of the OECD reform agenda at the micro-level. We will use insights from Self Determination Theory (SDT) to test the consequences of this climate of reduced job security on job search behaviour and job satisfaction of workers (for an extensive overview of SDT see Deci & Ryan, 2000). When applied to the labour market, SDT claims that there are two broad motives why workers may search for alternative employment: (a) autonomous motivation which refers to activities that the individual engages in freely or for external reasons that have been internalised; and (b) controlled motivation which arises from externally regulated pressures. SDT argues that autonomous motivation is more likely to lead to a successful outcome (find alternative better employment) than controlled motivation and therefore more likely to promote job satisfaction following a job change. Clearly, reduced job security is an externally regulated pressure that may prompt controlled job search motivation, because the employee’s job security is at stake. The OECD (2001: 14) concluded that in terms of labour market policies, Australia ‘... has been among the OECD countries complying best with this Strategy.’. Therefore, we decide to test the micro-level consequences of the OECD’s reform agenda in the context of the Australian labour market. We will draw on data from the first eleven waves of the Household, Income and Labour Dynamics Australia (HILDA) data set. Though SDT has been applied to the labour market before (see Vansteenkiste, Lens, De Witte, De Witte, & Deci, 2004; Vansteenkiste, Lens, De Witte, & Feather, 2005 and 2007), that research focuses mainly on the unemployed. Instead, we focus on employees searching for work and their motivations. Since, the unemployed are at the bottom of the job ladder, they do not face substantial downside risks from not searching, as opposed to employees, who may lose their job. Consequently, we expect effects of externally regulated pressures to lead to stronger controlled behavioural effects for employees than for the unemployed. If SDT has explanatory power then we should see that reduced job security stimulates more externally regulated job search. We should also observe that such job search will be less successful and if successful associated with lower increments in job satisfaction following job change. The paper will first briefly describe SDT in the context of the labour market followed by a discussion of the increased precariousness of employment in Australia. Section 2 will describe our data sources and hypotheses, while Section 3 discusses the methods we use to test our hypotheses. Section 4 contains the results, while Section 5 presents a discussion of our results and concluding remarks. 1.1. Self Determination Theory Self Determination Theory posits that to achieve psychological well-being, people have to fulfil several needs (Deci & Ryan, 2000). Three broad categories of such needs are identified: the need for competence, relatedness and autonomy. Paid employment contributes to the satisfaction of all three needs simultaneously. That is, workers can show their competence in a job; develop relations and networks at work to address the relatedness need; and employment is a means to generate income which provides the worker a route towards autonomy. Once employed, climbing the job ladder addresses the needs for competence and autonomy. Consequently, SDT argues that people work towards goals that enable them to achieve needs satisfaction, which – if successful – leads to positive psychological outcomes. There is ample evidence that employment or career advancement indeed contributes to psychological wellbeing (see for example Warr, Jackson, & Banks, 1988; Winefield, Winefield, Tiggeman, & Goldney, 1991). However, SDT claims that the type of motivation used to work towards goal achievement crucially impacts on the likelihood that goal achievement is accomplished. Consequently, SDT may provide insights into why some job seekers are more successful than others, which – as we will see – may include the institutional setting in which job search takes place. SDT distinguishes autonomous and controlled motivation – see Deci and Ryan (2000). Autonomous motivation can be intrinsic, identified or integrated. Intrinsic motivation refers to activities people freely engage in; identified or integrated motivation refers to external reasons to engage in an activity that people have internalised, i.e. the motivation is considered autonomous. Consequently, the locus of control is internal for autonomous motivation, as opposed to controlled motivation, which has an external locus of control. That is, the reason for engagement in an activity is external and not integrated. Applied to the case of employed job search, the employed job seeker who searches for other jobs because she enjoys attempting to find out the value of her skills in an alternative work setting is intrinsically motivated. The employed job seeker who for example searches for alternate work to expand her career uses identified or integrated motivation. However, the employed job seeker who searches for alternate work, because her present job is at risk, does not search because she dislikes her present job, but because external forces (potential job loss) force her to search. The vast body of empirical literature in this area of psychology provides ample evidence that (a) both autonomous and controlled motivation drive people to set and strive for goals in order to satisfy needs, but (b) that people with autonomous motivation are more successful in achieving these goals than people led by controlled motives and hence more successful in satisfying needs with better psychological wellbeing as an outcome. Empirical studies have tested SDT in various settings, including education, sport and health care (see and Williams, Rodin, Ryan, Grolnick, & Deci, 1998; Sarrazin, Vallerand, Guillet, Pelletier, & Cury, 2002; Vallerand & Bissonnette, 1992 as representative examples). Though job search has been widely researched in both psychological and economic literature (see Kanfer, Wanberg, & Kantrowitz, 2001 for a meta-analysis), studies linking SDT to job search are surprisingly rare.
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Vansteenkiste, Lens, De Witte, De Witte, and Deci (2004) found that the long-term unemployed who were autonomously motivated were more likely to search for work than the unemployed utilising controlled motivation. In a later paper, Vansteenkiste, Lens, De Witte, and Feather (2005) also study job search behaviour of the unemployed and find similar results. However, they do not find a positive relationship between psychological well-being and type of motivation (either autonomous or controlled). The authors suggest this may be explained by the outcome of the job search process, which is beyond their analysis. That is, the autonomously motivated unemployed may derive more satisfaction from search for employment than the unemployed utilising controlled motivation. However, not succeeding in finding employment will lead to more dissatisfaction for the autonomously motivated unemployed (see Vansteenkiste et al., 2007), leaving the overall effect of type of motivation on well-being ambiguous. Our analysis can be related to the findings of Vansteenkiste et al. (2004), Vansteenkiste et al. (2005) in two ways. Vansteenkiste et al. (2004) explain their observation by assuming that the unemployed who use controlled motivation to search for jobs, may – after several fruitless efforts – develop an autonomous motivation to remain unemployed and stop searching, which enables them to better accept their situation. An alternative explanation of this observation might be that because the unemployed are at the bottom of the job ladder, they have little to lose by not searching for employment, especially in countries with relatively strong social security systems (like Belgium – the study area of Vansteenkiste et al., 2004). Controlled motivations may be too weak to prompt job search. Therefore we decide to move one step up the job ladder and focus on job seekers who do face significant potential losses from not searching: the employed job seekers who are at risk of losing their current job. Second, we can solve the ambiguity in Vansteenkiste et al. (2005), since we will not only relate the job search decision to type of motivation but also – once a positive decision has been detected – to the outcome of job search. SDT states that job seekers who are autonomously motivated to search for employment are more likely to be successful than those driven by controlled motivation. We will test that hypothesis. We are aware of one study that looked at employed job search. Halvari, Vansteenkiste, Brorby, and Karlsen (2013) apply SDT to the decision of part-time workers to search for fulltime work. However, their data on motivation are based on selfreport, which may artificially strengthen their results. Our proxies for autonomous and controlled motivation are based on more objective measures – as we outline in the next paragraphs. 1.2. Trends towards increased labour market precariousness The deregulation of the Australian labour market has manifested in increased precariousness in the labour market. Precarious work has two dimensions which are measured systematically: involuntary part-time employment and casual employment. We use these indicators to show the incidence of precariousness of the labour market and its development over time. In their analysis of the trends in precarious work Abhayaratna, Andrews, Nuch, and Podbury (2008) show that Australia ranks second across the OECD in terms of the proportion of part-time workers in total employment. Mitchell and Muysken (2008) find that the trend of the incidence of part-time employment has clearly been upwards, from 15% in 1978 to 30% of total employment in 2010. However, there is also a clear indication that the recessions pushed the trend growth upwards. An observation which is relevant to our analysis is that a substantial number of part-time workers prefer more hours of work per week as a percentage of total part-time workers. This is illustrated in Fig. 1, which shows that the share of involuntary part-time workers fluctuates around seven per cent of all employees since 1990. Consequently, about seven per cent of all employees would like to work more hours, but cannot fulfil that preference. We will argue that these workers face externally regulated pressures (presumably financial pressures) to search for additional work either in their current or a new job.
30 25 20 15 10 5 0 1982
1985 1988
1991
1994
casual employment
1997
2000
2003 2006
2009
2012
involuntary parttime employment
Fig. 1. Percentage share of precarious employment in Australia, 1982–2012. Source: ABS (2013a, 2013b).
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The rising part-time to total employment ratio and the increased incidence of underemployment has also been accompanied by a rise in the importance of casual employment. This trend has been well documented in the Australian context (see for example, Campbell, 1996; Campbell, 2001; Junor & Wallace, 2001; Pocock, Buchanan, & Campbell, 2004). The Australian Bureau of Statistics (ABS) defines casual employment as all employees that do not enjoy access to paid holiday and sick leave. Casual workers tend to be part-time and dominated by female workers in retail trade and in accommodation, cafes and restaurants. The jobs tend to be low-skilled and low-paid. Campbell (2001: 68) found the proportion of workers who were considered to be casual in 1982 was 13.3%. In Fig. 1 one sees that the proportion increased to 23.7% thirty years later. Not only do casual workers miss access to paid leave and sick leave, they are also excluded from some of the other legislative protections (including unfair dismissal). Consequently, they can lose their job with very little advance notice. Additionally, Pocock et al., (2004) found that a large proportion of casual jobs were precarious with respect to the predictability of earnings, the hours offered, the opportunities for skill development, low union representation, and an increased vulnerability to occupational health and safety hazards. We will – similar to involuntary part-timers – argue that these workers utilise controlled motives to search for work. 2. Materials 2.1. Controlled motivation and labour market precariousness If SDT is correct, workers who face externally regulated pressure to search for employment and follow up on such pressures are less likely to be successful in gaining alternate (better) employment than workers who apply autonomous motivation to search for alternative employment. To identify externally regulated pressure at an individual level, we draw on data from the first eleven waves of the Household, Income and Labour Dynamics Australia (HILDA) data set. The HILDA survey is funded by the Australian government and followed up on an annual basis. The first survey was conducted in 2001. The survey consists of three parts: a household questionnaire, a personal questionnaire and a self-completion questionnaire. We use the personal questionnaire which details the labour market status of respondents – job satisfaction; expectations about future labour market status; job search behaviour, and – since we use several waves – transition rates to different labour market positions in subsequent years. To capture externally regulated pressure, we study hours worked and contract type of the job. We categorise hours worked in the job into three groups: (1) workers who have fulltime employment, (2) workers who have part-time employment and are satisfied with those conditions (voluntary part-time) and (3) workers who have part-time employment and would like to work more hours but have not been able to achieve their working hours ambition (involuntary part-time). Job search of workers in the latter category is likely to be driven by budgetary constraints (i.e. controlled motives), while if workers in the first two categories decide to search for work, it is – in absence of externally regulated pressures – more likely for autonomous reasons. Next, we distinguish workers on (1) casual, (2) fixed term and (3) permanent contracts. A casual worker may lose her current job at any time, while a worker on a fixed term contract knows that her contract will come up at a fixed date. Both workers therefore need to be wary of job loss and consequently need to search for employment to avert potential job loss, with subsequent financial repercussions. That pressure is an externally regulated control on the behaviour of the worker, which the worker on a permanent job contract does not face. If the latter decides to search, it is more likely to be for autonomous reasons. We use both variables to construct a new variable which captures the degree of externally regulated pressures resulting from work conditions at three levels, which may lead to three levels of controlled motivation: – no controlled motivation (both permanent contract and fulltime or voluntary part-time employment); – some controlled motivation (either fixed-term/casual employment or involuntary part-time employment); – strong controlled motivation (both casual employment and involuntary part-time employment). All three categories will contain workers who are amotivated and workers who are autonomously motivated to search for alternate employment. However, we expect that employees in the second and especially the third group are more likely to utilise controlled motivation to search for alternate employment than employees in the first category. Once concentrating on employees who indicate to search for alternate employment, we discard the amotivated workers from our analysis. The workers.3 Assuming that workers can only be motivated to search for two reasons (autonomous or controlled motivation), then employees who face no externally regulated pressures and search for alternate employment are more likely to do so for autonomous reasons. We verified the plausibility of assigning the degrees of motivation to these groups by looking at the average perceptions of the three groups on job security and some other job satisfaction scores, which are available in the HILDA data. From Table 1 one sees that the perceived probability to lose one’s job increases and both job security and employment opportunities
3
The workers who are amotivated to search constitute 86.2% of the first group, 79.0% of the second group and 51.7% of the third group.
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Table 1 Perceptions of groups with different degrees of motivation (pooled sample). Source: HILDA data. Job perception variables
Degree of controlled motivation None
Some
Strong
The per cent chance to lose your job during the next 12 months
8.2
14.3
18.4
How satisfied are you with (scale 1–10) Your job security Your employment opportunities Your total pay Your financial situation The hours you work The work itself (what you do) Your job overall Your life
8.3 7.6 7.0 6.6 7.3 7.6 7.6 7.9
7.5 7.3 7.0 6.2 7.2 7.4 7.6 7.9
6.5 5.7 6.2 5.0 5.5 7.0 6.8 7.6
decrease with the strength of controlled motivation. In particular, those with strong controlled motivation experience a relatively bad financial situation, low satisfaction with the number of hours worked and with their job. The relatively low impact of strong controlled motivation on satisfaction with life is consistent with the finding of Vansteenkiste et al. (2004). A full set of characteristics of the three groups is provided in Tables A1 and A2 in Appendix A. As expected, the likelihood to leave the job voluntarily increases with the intensity of controlled motivation, although workers utilising strong controlled motivation have less confidence to find a (better) job. Young persons, women and workers living outside metropolitan areas are overrepresented in the group using controlled motivation. Not surprisingly, the degree of controlled motivation is negatively related to educational attainment. Finally, tenure held in a previous job is lower, the stronger the controlled motivation to search for another job is. 2.2. Controlled motivation and job search To test the impact of type of motivation on job search behaviour, job search success (if searching) and job improvement (if search was successful), we apply a three stage model – see Fig. 2. Since we define autonomously motivated job search as job search that takes place in absence of externally regulated pressures (casual employment and or involuntary part-time work) we can only isolate autonomously motivated employees from amotivated employees in Stages 2 and 3; not in Stage 1. In Stage 1 all three groups will contain amotivated employees. However, the three groups differ in terms of the strength of controlled motivation, ranging from no controlled motivation (residual motivation for this group must be autonomous) to some and strong controlled motivation. From our general discussion and SDT, the following hypothesis should hold in a precarious labour market environment: Hypothesis 1. Workers with some controlled motivation are (a) more likely to search for alternate employment than workers without controlled motivation and (b) less likely to search for alternate employment than workers with strong controlled motivation.
Stage 3 better job Stage 2 success Stage 1 no better job
motivated employee
no success amotivated
Fig. 2. Schematic overview of three stage model.
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In Stage 2 we drop employees who are amotivated to search and hence we can isolate autonomously motivated employees and test for the effect of autonomous motivation on job search success. SDT then predicts that autonomously motivated job search is more successful (in terms of finding better employment) than job search prompted by controlled motivation. This implies that either (a) job seekers utilising controlled motivation are less likely to find a job; and/or (b) if they find a job, the increase in job satisfaction is less compared to the new job found by an autonomously motivated job seeker. This leads to the following two hypotheses. Hypothesis 2. Of the workers who search for alternate employment, those with some controlled motivation are (a) less likely to secure alternate employment than those with autonomous motivation and (b) more likely to secure alternate employment than those with strong controlled motivation. In Stage 3 we concentrate on employees who were motivated to search in Stage 1 and who were successful in terms of finding alternate employment in Stage 2. Hypothesis 3. Of the workers who successfully searched for alternate employment, those with some controlled motivation are (a) less likely to secure better (in terms of job satisfaction increase) alternate employment than those with autonomous motivation and (b) more likely to secure better alternate employment than those with strong controlled motivation. To test these hypotheses properly we include a broad range of control variables related to the respondent or her environment. That is, variables that may impact on the job search decision and its success, but have no link to our research question. We include personal characteristics (age, gender, ethnicity, location, and educational level), job characteristics (sector, occupation, tenure) and two variables indicating labour market attitudes. One variable measuring the confidence that respondents have to find a (better) job within 12 months if need be and one variable measuring the likelihood that the respondent will leave the current job voluntarily within the next 12 months. Finally, we include a time variable to control for business cycle effects. 3. Methods We estimate three separate regression models to examine each of the three stages as identified in Fig. 2. Model 1 focuses on the job search decision of respondents. The dependent variable is thus constructed as a binary variable (search or not) within a logistical regression specification:
prðY ¼ 1jxÞ ¼
expða þ xbÞ 1 þ expða þ xbÞ
where Y is the dependent binary variable (job search vs no job search) and vector x contains a set of independent variables as outlined in Section 2.2. Model 2 focuses on respondents that have indicated to search for employment and interrogates the outcome of that job search (successful or not). Successful job search is defined as having changed jobs between periods t and t 1 while indicating to search for alternative employment in period t 1. The dependent variable is binary; the regression subsequently a logistical specification, which is similar in nature to model 1’s specification, barring that Y now differentiates successful from non-successful job search (in terms of finding a job). Model 3 focuses on respondents who successfully completed job search and compares job satisfaction in period t (the new job) to job satisfaction in period t 1 (the previous job). Job satisfaction is measured on a 0–10 scale, where 10 is maximum satisfaction. Since we are interested in the difference between job satisfaction in periods t and t 1, we end up with a dependent variable ranging from 10 to 10. Since we cannot treat the dependent variable as an interval variable, for the magnitudes between two values are not necessarily meaningful,4 we must treat it as an ordinal variable. We have further narrowed Model 3’s dependent variable to a five category ordinal construct (<2; 2 to 1; 0; 1 2; >2)5; the regression should subsequently be an ordinal logistical specification. However, an ordinal logistical regression assumes proportional odds. To verify whether our data support the proportional odds assumption, we conduct the Brant test, which rejects the null hypothesis of proportional odds at the 1% significance level (v2 (df = 54) = 120.2; p-value = 0.00). To relax the proportional odds assumption, we specify a generalised ordinal logistical model:
prðY ¼ jjxÞ ¼
expðsj xbj Þ 1 þ expðsj xbj Þ
prðY ¼ jjxÞ ¼
expðsj xbj Þ expðsj1 xbj1 Þ 1 þ expðsj xbj Þ 1 þ ðsj1 xbj1 Þ
for j ¼ 1
for j ¼ 2; 3; 4
4 With an interval variable respondent A reporting for example a four point improvement in job satisfaction, must be four times happier about her job change than respondent B who reports a one point improvement. Whilst no doubt, respondent A is happier about her job move than respondent B, it is unclear in our opinion whether that gap is exactly four, i.e. whether the magnitudes between two values are meaningful. 5 We tried various cut-off values to categorise the dependent variable, which do not lead to significantly different results. Also if we treat the dependent variable as an interval variable similar results are obtained.
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prðY ¼ jjxÞ ¼
expðsj1 xbj1 Þ 1 þ ðsj1 xbj1 Þ
for j ¼ 5
where j represents the (five) ordinal categories of our dependent variable (change in job satisfaction) and s represents the (four) cut points that demarcate the (five) j categories. This generalised ordinal logistics model is different to an ordinal logistics model in one respect: the bs are j-specific, which means the proportional odds assumption has been relaxed. The generalised ordinal logistical model is equivalent to a set of four binary logistics regressions. The first regression contrasts category 1 (j = 1) of the dependent variable to categories 2, 3, 4 and 5; the second regression contrasts categories 1 and 2 to categories 3, 4 and 5; the third regression contrasts categories 1, 2 and 3 to categories 4 and 5; and the fourth regression contrasts categories 1, 2, 3 and 4 to category 5. In this paper we look at instantaneous success. That is, if a worker searches for a job in year t 1, we measure the outcome of that search process in year t and do not include possible outcomes in year t + 1. The same applies to job satisfaction, if a worker indicates that she (a) searches for employment in year t 1, (b) changes jobs in year t, we measure change in job satisfaction as job satisfaction in year t minus job satisfaction in year t 1. Consequently, we focus on annual transition rates and also treat the data as such. That is, we will use pooled regression analysis, clustering on the respondent identifier in the data to obtain robust standard errors. The regression coefficients will be reported as odds ratios. The odds ratio is defined as the ratio of the odds of an event occurring in one group to the odds of it occurring in the control group. The odds ratio can be computed taking the natural exponent of coefficients of a logistical regression. 4. Results We discuss the three hypotheses successively. 4.1. Job search decision The decision to search for alternate employment should have a positive relation to controlled motivation, according to SDT. The odds ratios in the second column of Table 2 are consistent with this conjecture. Employees with some controlled
Table 2 Determinants of employed job search and its success (odds ratios), 2001–2011. Independent variablesa
Job search motivation No controlled motivation Some controlled motivation Strong controlled motivation Labour market attitude Confidence to find a (better) job Likelihood lo leave job voluntarily Personal characteristics Age cohort: 16–30 years 31–40 years 41–50 years 51–65 years Female Male Non-indigenous Australian Indigenous Living outside major statistical region Living in major statistical region (Pre-)primary/secondary school Certificate Advanced diploma and diploma (Post) Graduate, bachelor degree (Previous) Job characteristics Tenure Pseudo R-squared N
Dependent variables Job search
Job found (once searching)
0.87*** (0.03) Reference 4.02*** (0.29)
0.98 (0.05) Reference 0.88 (0.08)
1.004*** (0.00) 1.03*** (0.00)
1.004*** (0.00) 1.01*** (0.00)
0.85*** (0.03) Reference 1.05 (0.04) 0.72*** (0.04) Reference 1.18*** (0.04) Reference 1.36*** (0.14) Reference 1.04 (0.04) Reference 1.27*** (0.05) 1.35*** (0.08) 1.61*** (0.07)
0.96 (0.05) Reference 0.99 (0.07) 0.93 (0.08) Reference 1.00 (0.05) Reference 0.80 (0.13) Reference 0.94 (0.04) Reference 1.03 (0.06) 1.06 (0.09) 1.06 (0.07)
0.96*** (0.00) 0.19 66,932
0.96*** (0.01) 0.04 9824
Robust standard errors in parentheses. a Occupation, sector and business cycle controls are included in the models; not shown. * 10% Significance. ** 5% Significance. *** 1% Significance.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44 Table 3 Change in job satisfaction (odds ratios), 2001–2011. Independent variablesa
Job search motivation No controlled motivation Some controlled motivation Strong controlled motivation Labour market attitude Confidence to find a (better) job Likelihood lo leave job voluntarily Personal characteristics Age cohort: 16–30 years 31–40 years 41–50 years 51–65 years Female Male Non-Indigenous Australian Indigenous Living outside major statistical region Living in major statistical region (Pre-)primary/secondary school Certificate Advanced diploma and diploma (Post) Graduate, Bachelor degree (Previous) Job characteristics Tenure Pseudo R-squared N
Dependent variables Change in job satisfaction following job change ‘‘<2’’ vs ‘‘P2’’
‘‘<0’’ vs ‘‘P0’’
‘‘60’’ vs ‘‘>0’’
‘‘62’’ vs ‘‘>2’’
1.37** (0.21) Reference 0.60** (0.15)
1.23** (0.11) Reference 0.77* (0.13)
1.23*** (0.09) Reference 0.80 (0.12)
1.37*** (0.12) Reference 0.93 (0.16)
1.01* (0.00) 1.01*** (0.00)
1.003** (0.00) 1.01*** (0.00)
1.001 (0.00) 1.01*** (0.00)
1.003 (0.00) 1.02*** (0.00)
1.01 (0.19) Reference 0.89 (0.18) 0.91 (0.28) Reference 0.90 (0.13) Reference 0.59 (0.20) Reference 0.77* (0.11) Reference 0.98 (0.18) 1.62 (0.51) 1.53* (0.35)
0.79** (0.08) Reference 0.95 (0.12) 1.11 (0.18) Reference 1.02 (0.09) Reference 0.56*** (0.12) Reference 0.86* (0.07) Reference 1.01 (0.11) 1.39 (0.22) 1.24* (0.14)
0.80*** (0.07) Reference 0.97 (0.10) 1.14 (0.16) Reference 1.04 (0.08) Reference 0.86 (0.19) Reference 0.92 (0.06) Reference 1.04 (0.09) 1.48*** (0.19) 1.21** (0.11)
0.69*** (0.07) Reference 1.22* (0.13) 1.21 (0.19) Reference 0.94 (0.08) Reference 1.41 (0.35) Reference 1.02 (0.08) Reference 0.96 (0.10) 0.89 (0.13) 0.93 (0.10)
1.03 (0.02)
1.01 (0.01)
1.003 (0.01)
0.99 (0.01)
0.04 3820
Robust standard errors in parentheses. a Occupation, sector and business cycle controls are included in the models; not shown. * 10% Significance. ** 5% Significance. *** 1% Significance.
motivation are (a) statistically significantly more likely to search for alternate employment than those with no controlled motivation and (b) statistically significantly less likely to search for alternate employment than those with strong controlled motivation. An interesting observation is that overall search incidence increases with educational attainment and being female or Indigenous Australian. A further Chi-square correlation analysis for the impact of gender shows that although women are overrepresented in the groups with some and strong controlled motivation, men in these two groups are significantly more likely to search than women.6 4.2. Job search success Differences between autonomous and controlled motivation are predicted in Stage 2: job search success. Autonomous motivation is predicted to elevate the chance of job search success, whereas controlled motivation is not. The second column of odds ratios in Table 2 contains the results. We do not find any evidence to support this hypothesis. That is, of the employees who search for work, those with some controlled motivation are (a) not less likely to secure alternate employment than those with no controlled motivation and (b) not more likely to secure alternate employment than those with strong controlled motivation. As an interesting side note, we observe the absence of a significant impact of personal characteristics on job search success. A further Chi-square correlation analysis for the impact of gender shows that this holds for all three degrees of controlled motivation. 4.3. Job satisfaction improvement Finally, we test the third hypothesis: when does successful job search lead to increased job satisfaction? SDT predicts that autonomous motivation will lead to improvements in job satisfaction (following successful job search completion) as 6 We tested the following hypotheses H0: no correlation between gender and the three groups of controlled motivation: v2 (2) = 1100; p = 0.00; H0: no correlation between search activity and gender within group with some controlled motivation: v2 (1) = 10.22; p = 0.00 and H0: no correlation between search activity and gender within the group with strong controlled motivation: v2 (1) = 5.49; p = 0.02.
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opposed to controlled motivation. We specified the generalised ordinal logistical model, the results of which can be found in Table 3. First we note that the odds ratios across the four regressions are not constant, which indeed suggests that a simple ordinal logistic regression would have been a misspecification. We find strong support for the first part of the third hypothesis. Of the workers who successfully searched for alternate employment, those with some controlled motivation are statistically significantly less likely to secure better alternate employment than those with autonomous motivation. We find that result across all four transitions, including the third transition (which distinguishes between achieving job satisfaction progress as a result of job change or not). We find weak support for the second part of the third hypothesis. The coefficient of ‘strong controlled motivation’ is consistently below unity, indicating that of the workers who successfully searched for alternate employment, those with some controlled motivation are more likely to secure better alternate employment than those with strong controlled motivation. However, this coefficient is only significantly different from unity for the first two transitions. This finding indicates that workers with strong controlled motivation are statistically significantly more likely to accept alternate employment that makes them worse off than workers with some controlled motivation.
5. Discussion/conclusion We have applied SDT to the field of employed job search, which is a field with strong externally regulated pressures in place in industrialised countries like Australia. As predicted, workers who search for a job without externally regulated pressures are more likely to find alternative jobs with subsequent augmented job satisfaction. Employees facing externally regulated pressures are not per se less likely to find alternative employment, but the fact that they do not transit to better jobs is indicative of the failure of contemporary labour market policies applied in OECD countries like Australia. The findings also accord with predictions from dual labour market (DLM) theory – Doeringer and Piore (1971) and Piore (1975). DLM theory argues that the labour market is segmented into a Primary Labour Market (PLM) and a Secondary Labour Market (SLM). The PLM worker who is typically employed in a secure internal labour market structure which provides for career advancement will use search activity to enhance her career aspirations, i.e. autonomous motivation. Conversely, the SLM worker may search for different reasons especially given the precariousness of their employment. Search thus may not be motivated by potential employment improvement, but might, rather, be fuelled by fear of future job loss, i.e.: controlled motivation. The two markets are separated by rigidities which inhibit mobility across them. Accordingly, if a worker becomes ‘trapped’ into the SLM, access to the better outcomes in the PLM becomes severely limited if not intractable. SDT would argue that lack of upward mobility from the SLM is not necessarily a result of rigidities but of externally regulated search motivation. The applicability of SDT to labour market analysis provides important new ways of appraising the current policy framework which has emphasised activism and deregulation. The implementation of the OECD Job Study agenda has increased the degree of job insecurity in labour markets. There has been a marked increase in the degree of precariousness and job instability over the last two decades in most economies. The application of SDT to this phenomenon tells us that the supply-side labour market policy framework has contributed to workers cycling through spells of insecure employment and possibly intermittent spells of unemployment with no realistic prospect of career development. In other words, the stated goals of the OECD activist strategy have not been fulfilled in practice when we consider the fortunes of the vulnerable workers in the labour market. This cohort was thought to be beneficiaries of the new approach to training and job placement. Our study suggests that they have not gained better jobs through increased (forced) search activity.
Acknowledgements This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either FaHCSIA or the Melbourne Institute. We thank one anonymous referee for providing us with constructive suggestions and comments. Appendix A See Tables A1 and A2.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44 Table A1 Descriptive statistics (means) for the whole sample/job searchers, 2001–2011. Independent variables
Type of motivation All
Total
No controlled motivation
Some controlled motivation
Strong controlled motivation
0.67/0.55
0.31/0.39
0.02/0.06
Labour market attitude Confidence to find a (better) job Likelihood lo leave job voluntarily
0.65/0.75 0.24/0.55
0.64/0.75 0.19/0.53
0.67/0.76 0.32/0.57
0.61/0.68 0.40/0.55
Personal characteristics Age cohort: 16–30 years 31–40 years 41–50 years 51–65 years Female Non-Indigenous Australian Non-metropolitan areas
0.35/0.45 0.23/0.24 0.24/0.21 0.18/0.10 0.47/0.48 0.98/0.98 0.41/0.39
0.28/0.36 0.26/0.29 0.27/0.24 0.20/0.12 0.43/0.42 0.99/0.98 0.39/0.36
0.49/0.56 0.18/0.19 0.19/0.18 0.14/0.08 0.56/0.54 0.98/0.97 0.44/0.41
0.51/0.56 0.14/0.16 0.18/0.16 0.17/0.12 0.58/0.55 0.96/0.96 0.57/0.55
(Pre-)primary/secondary school Certificate Advanced diploma and diploma (Post) Graduate, bachelor degree
0.43/0.40 0.23/0.23 0.09/0.09 0.25/0.29
0.38/0.31 0.25/0.25 0.10/0.10 0.28/0.34
0.54/0.48 0.19/0.20 0.07/0.07 0.20/0.24
0.61/0.58 0.22/0.23 0.06/0.05 0.11/0.14
(Previous) Job characteristics Tenure (years) N
5.7/3.5 66,932
7.0/4.7 44,932
3.2/2.1 20,550
2.2/1.5 1450
Table A2 Descriptive statistics dependent variable to type search motivation, 2001–2011. Dependent variables
Looking for work Found a job when looking Found a better job while looking
Type of motivation All
No controlled motivation
Some controlled motivation
Strong controlled motivation
0.17 0.39 0.59
0.14 0.37 0.62
0.21 0.41 0.57
0.52 0.38 0.51
References Abhayaratna, J., Andrews, L., Nuch, H. & Podbury, T. (2008). Part time employment: The Australian experience. In Productivity commission.. Australian Bureau of Statistics (ABS) (2013a). Employee Earnings, Benefits and Trade Union Membership. No. 6310.0, Canberra. Australian Bureau of Statistics (ABS) (2013b). Labour Force, Australia. No. 6202.0, Canberra. Campbell, I. (1996). Casual employment, labour regulation and Australian trade unions. Journal of Industrial Relations, 38(4), 571–599. Campbell, I. (2001). The spreading net: Age and gender in the process of casualisation in Australia. Journal of Australian Political Economy, 45, 68–99. Deci, E., & Ryan, R. (2000). The ‘‘What’’ and ‘‘Why’’ of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 4, 227–268. Doeringer, P., & Piore, M. (1971). Internal labor markets and manpower analysis. Lexington, Mass: D.C. Heath. Halvari, H., Vansteenkiste, M., Brorby, S., & Karlsen, H. (2013). Examining antecedents and outcomes of part-time working nurses’ motives to search and not to search for a full-time position. Journal of Applied Social Psychology, 43, 1608–1623. Junor, A. & Wallace, M. (2001). Regulating casual education work in Australia: Markets, professionalism and industrial relations. In D. Kelly (Ed.), Crossing boundaries: Employment, work, markets and social justice across time, discipline and place (Vol. 1, pp. 161–169). Wollongong: AIRAANZ. The 15th AIRAANZ Conference, 31 January–3 February 2001. Kanfer, R., Wanberg, C., & Kantrowitz, T. (2001). Job search and employment: A personality-motivational analysis and meta-analytic review. Journal of Applied Psychology, 86, 837–855. Mitchell, W., & Muysken, J. (2008). Full employment abandoned: Shifting sands and policy failures. Aldershot: Edward Elgar. OECD (1994). OECD jobs study, evidence and explanations, organisation for economic co-operation and development, Paris. OECD (2001). Innovations in labour market policies, the Australian way, organisation for economic co-operation and development, Paris. OECD (2006). The (New) OECD jobs study: Introduction and assessment, organisation for economic co-operation and development, Paris. Piore, M. (1975). Notes for a Theory of labor market stratification. In R. Edwards, M. Reich, & D. Gordon (Eds.), Labor market segmentation (pp. 125–150). Lexington, Mass.: Heath. Pocock, B., Buchanan, J., & Campbell, I. (2004). Securing quality employment: Policy options for casual and part-time workers in Australia. Sydney: Chifley Research Foundation. Sarrazin, P., Vallerand, R., Guillet, E., Pelletier, L., & Cury, F. (2002). Motivation and dropout in female handballers: A 21-months prospective study. Journal of Personality and Social Psychology, 65, 586–596. Vallerand, R., & Bissonnette, R. (1992). Intrinsic, extrinsic, and amotivational styles as predictors of behaviour: A prospective study. Journal of Personality, 60, 599–620. Vansteenkiste, M., Lens, W., De Witte, S., De Witte, H., & Deci, E. (2004). The ‘why’ and ‘why not’ of job search behaviour: Their relation to searching, unemployment experience, and well-being. European Journal of Social Psychology, 34, 345–363. Vansteenkiste, M., Lens, W., De Witte, H., & Feather, N. (2005). Understanding unemployed people’s job search behaviour, unemployment experience and well-being: A comparison of expectancy-value theory and self-determination theory. British Journal of Social Psychology, 44, 269–287.
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Vansteenkiste, M., Neyrinck, B., Niemiec, C., Soenens, B., De Witte, H., & Van Den Broeck, A. (2007). On the relations among work value orientations, psychological need satisfaction and job outcomes: A self-determination theory approach. Journal of Occupational and Organizational Psychology, 80, 251–277. Warr, P., Jackson, P., & Banks, M. (1988). Unemployment and mental health: Some British studies. Journal of Social Issues, 44, 47–68. Williams, G., Rodin, G., Ryan, R., Grolnick, W., & Deci, E. (1998). Autonomous regulation and long-term medication adherence in adult outpatients. Health Psychology, 17, 269–276. Winefield, A., Winefield, H., Tiggeman, M., & Goldney, R. (1991). A longitudinal study of the psychological effects of unemployment and unsatisfactory employment on young adults. Journal of Applied Psychology, 76, 424–431.
Contents lists available at ScienceDirect
Journal of Economic Psychology journal homepage: www.elsevier.com/locate/joep
Self determination theory and employed job search Riccardo Welters a,⇑, William Mitchell b,c,1, Joan Muysken d,2 a
James Cook University, School of Business, Townsville, 4811 QLD, Australia Centre of Full Employment and Equity, University of Newcastle, Callaghan, 2308 NSW, Australia Charles Darwin University, Brinkin, 0810, NT, Australia d Maastricht University, School of Business and Economics, 6200 MD Maastricht, The Netherlands b c
a r t i c l e
i n f o
Article history: Received 10 December 2013 Received in revised form 5 June 2014 Accepted 14 June 2014 Available online 20 June 2014 JEL classification: J08 J28 PsycINFO classification: 2228 3650
a b s t r a c t Self Determination Theory (SDT) predicts that employees who use controlled motivation to search for alternate (better) work are less successful than their counterparts who use autonomous motivation. Using Australian labour market data, we find strong support for SDT. We find that workers who face externally regulated pressures (pressure arising from involuntary part-time or casual labour contracts) to search for alternate employment are less likely to find better work, than workers who use autonomous motives to search for work. Our findings suggest that labour market policies trending towards ‘labour market flexibility/deregulation’ – which provide workers with controlled motives to search for work – will contribute to workers cycling through spells of insecure employment and possibly intermittent spells of unemployment with no realistic prospect of career development. Ó 2014 Elsevier B.V. All rights reserved.
Keywords: Personnel attitudes & Job satisfaction Self determination theory Motivation Empirical study
1. Introduction In 1994, the Organisation for Economic Co-ordination and Development (OECD) made various recommendations to ‘‘increase wage and labour cost flexibility’’ and ‘‘reform employment security provision’’ in an attempt to reduce unemployment. OECD (1994) claimed that a more flexible, deregulated labour market would entice employers to create more employment and hence lead to lower unemployment. This induced most OECD member countries to promote labour market policies which (among others) reduced job security of employees. However, when the OECD evaluated its reform agenda in 2006, it concluded: ‘... the reduction of unemployment does not correlate very strongly with reform intensity’ (OECD, 2006: 69) indicating its reform package had not been a success – see also Mitchell and Muysken (2008) for a comprehensive critique of the OECD Jobs Study reforms at the macroeconomic level.
⇑ Corresponding author. Tel.: +61 (0)7 4781 4325. E-mail addresses: [email protected] (R. Welters), [email protected] (W. Mitchell), [email protected] (J. Muysken). 1 Tel.: +61 (0)2 4921 7283. 2 Tel.: +31 (0)4 3388 3808. http://dx.doi.org/10.1016/j.joep.2014.06.002 0167-4870/Ó 2014 Elsevier B.V. All rights reserved.
R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44
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This paper will look at the consequences of the OECD reform agenda at the micro-level. We will use insights from Self Determination Theory (SDT) to test the consequences of this climate of reduced job security on job search behaviour and job satisfaction of workers (for an extensive overview of SDT see Deci & Ryan, 2000). When applied to the labour market, SDT claims that there are two broad motives why workers may search for alternative employment: (a) autonomous motivation which refers to activities that the individual engages in freely or for external reasons that have been internalised; and (b) controlled motivation which arises from externally regulated pressures. SDT argues that autonomous motivation is more likely to lead to a successful outcome (find alternative better employment) than controlled motivation and therefore more likely to promote job satisfaction following a job change. Clearly, reduced job security is an externally regulated pressure that may prompt controlled job search motivation, because the employee’s job security is at stake. The OECD (2001: 14) concluded that in terms of labour market policies, Australia ‘... has been among the OECD countries complying best with this Strategy.’. Therefore, we decide to test the micro-level consequences of the OECD’s reform agenda in the context of the Australian labour market. We will draw on data from the first eleven waves of the Household, Income and Labour Dynamics Australia (HILDA) data set. Though SDT has been applied to the labour market before (see Vansteenkiste, Lens, De Witte, De Witte, & Deci, 2004; Vansteenkiste, Lens, De Witte, & Feather, 2005 and 2007), that research focuses mainly on the unemployed. Instead, we focus on employees searching for work and their motivations. Since, the unemployed are at the bottom of the job ladder, they do not face substantial downside risks from not searching, as opposed to employees, who may lose their job. Consequently, we expect effects of externally regulated pressures to lead to stronger controlled behavioural effects for employees than for the unemployed. If SDT has explanatory power then we should see that reduced job security stimulates more externally regulated job search. We should also observe that such job search will be less successful and if successful associated with lower increments in job satisfaction following job change. The paper will first briefly describe SDT in the context of the labour market followed by a discussion of the increased precariousness of employment in Australia. Section 2 will describe our data sources and hypotheses, while Section 3 discusses the methods we use to test our hypotheses. Section 4 contains the results, while Section 5 presents a discussion of our results and concluding remarks. 1.1. Self Determination Theory Self Determination Theory posits that to achieve psychological well-being, people have to fulfil several needs (Deci & Ryan, 2000). Three broad categories of such needs are identified: the need for competence, relatedness and autonomy. Paid employment contributes to the satisfaction of all three needs simultaneously. That is, workers can show their competence in a job; develop relations and networks at work to address the relatedness need; and employment is a means to generate income which provides the worker a route towards autonomy. Once employed, climbing the job ladder addresses the needs for competence and autonomy. Consequently, SDT argues that people work towards goals that enable them to achieve needs satisfaction, which – if successful – leads to positive psychological outcomes. There is ample evidence that employment or career advancement indeed contributes to psychological wellbeing (see for example Warr, Jackson, & Banks, 1988; Winefield, Winefield, Tiggeman, & Goldney, 1991). However, SDT claims that the type of motivation used to work towards goal achievement crucially impacts on the likelihood that goal achievement is accomplished. Consequently, SDT may provide insights into why some job seekers are more successful than others, which – as we will see – may include the institutional setting in which job search takes place. SDT distinguishes autonomous and controlled motivation – see Deci and Ryan (2000). Autonomous motivation can be intrinsic, identified or integrated. Intrinsic motivation refers to activities people freely engage in; identified or integrated motivation refers to external reasons to engage in an activity that people have internalised, i.e. the motivation is considered autonomous. Consequently, the locus of control is internal for autonomous motivation, as opposed to controlled motivation, which has an external locus of control. That is, the reason for engagement in an activity is external and not integrated. Applied to the case of employed job search, the employed job seeker who searches for other jobs because she enjoys attempting to find out the value of her skills in an alternative work setting is intrinsically motivated. The employed job seeker who for example searches for alternate work to expand her career uses identified or integrated motivation. However, the employed job seeker who searches for alternate work, because her present job is at risk, does not search because she dislikes her present job, but because external forces (potential job loss) force her to search. The vast body of empirical literature in this area of psychology provides ample evidence that (a) both autonomous and controlled motivation drive people to set and strive for goals in order to satisfy needs, but (b) that people with autonomous motivation are more successful in achieving these goals than people led by controlled motives and hence more successful in satisfying needs with better psychological wellbeing as an outcome. Empirical studies have tested SDT in various settings, including education, sport and health care (see and Williams, Rodin, Ryan, Grolnick, & Deci, 1998; Sarrazin, Vallerand, Guillet, Pelletier, & Cury, 2002; Vallerand & Bissonnette, 1992 as representative examples). Though job search has been widely researched in both psychological and economic literature (see Kanfer, Wanberg, & Kantrowitz, 2001 for a meta-analysis), studies linking SDT to job search are surprisingly rare.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44
Vansteenkiste, Lens, De Witte, De Witte, and Deci (2004) found that the long-term unemployed who were autonomously motivated were more likely to search for work than the unemployed utilising controlled motivation. In a later paper, Vansteenkiste, Lens, De Witte, and Feather (2005) also study job search behaviour of the unemployed and find similar results. However, they do not find a positive relationship between psychological well-being and type of motivation (either autonomous or controlled). The authors suggest this may be explained by the outcome of the job search process, which is beyond their analysis. That is, the autonomously motivated unemployed may derive more satisfaction from search for employment than the unemployed utilising controlled motivation. However, not succeeding in finding employment will lead to more dissatisfaction for the autonomously motivated unemployed (see Vansteenkiste et al., 2007), leaving the overall effect of type of motivation on well-being ambiguous. Our analysis can be related to the findings of Vansteenkiste et al. (2004), Vansteenkiste et al. (2005) in two ways. Vansteenkiste et al. (2004) explain their observation by assuming that the unemployed who use controlled motivation to search for jobs, may – after several fruitless efforts – develop an autonomous motivation to remain unemployed and stop searching, which enables them to better accept their situation. An alternative explanation of this observation might be that because the unemployed are at the bottom of the job ladder, they have little to lose by not searching for employment, especially in countries with relatively strong social security systems (like Belgium – the study area of Vansteenkiste et al., 2004). Controlled motivations may be too weak to prompt job search. Therefore we decide to move one step up the job ladder and focus on job seekers who do face significant potential losses from not searching: the employed job seekers who are at risk of losing their current job. Second, we can solve the ambiguity in Vansteenkiste et al. (2005), since we will not only relate the job search decision to type of motivation but also – once a positive decision has been detected – to the outcome of job search. SDT states that job seekers who are autonomously motivated to search for employment are more likely to be successful than those driven by controlled motivation. We will test that hypothesis. We are aware of one study that looked at employed job search. Halvari, Vansteenkiste, Brorby, and Karlsen (2013) apply SDT to the decision of part-time workers to search for fulltime work. However, their data on motivation are based on selfreport, which may artificially strengthen their results. Our proxies for autonomous and controlled motivation are based on more objective measures – as we outline in the next paragraphs. 1.2. Trends towards increased labour market precariousness The deregulation of the Australian labour market has manifested in increased precariousness in the labour market. Precarious work has two dimensions which are measured systematically: involuntary part-time employment and casual employment. We use these indicators to show the incidence of precariousness of the labour market and its development over time. In their analysis of the trends in precarious work Abhayaratna, Andrews, Nuch, and Podbury (2008) show that Australia ranks second across the OECD in terms of the proportion of part-time workers in total employment. Mitchell and Muysken (2008) find that the trend of the incidence of part-time employment has clearly been upwards, from 15% in 1978 to 30% of total employment in 2010. However, there is also a clear indication that the recessions pushed the trend growth upwards. An observation which is relevant to our analysis is that a substantial number of part-time workers prefer more hours of work per week as a percentage of total part-time workers. This is illustrated in Fig. 1, which shows that the share of involuntary part-time workers fluctuates around seven per cent of all employees since 1990. Consequently, about seven per cent of all employees would like to work more hours, but cannot fulfil that preference. We will argue that these workers face externally regulated pressures (presumably financial pressures) to search for additional work either in their current or a new job.
30 25 20 15 10 5 0 1982
1985 1988
1991
1994
casual employment
1997
2000
2003 2006
2009
2012
involuntary parttime employment
Fig. 1. Percentage share of precarious employment in Australia, 1982–2012. Source: ABS (2013a, 2013b).
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The rising part-time to total employment ratio and the increased incidence of underemployment has also been accompanied by a rise in the importance of casual employment. This trend has been well documented in the Australian context (see for example, Campbell, 1996; Campbell, 2001; Junor & Wallace, 2001; Pocock, Buchanan, & Campbell, 2004). The Australian Bureau of Statistics (ABS) defines casual employment as all employees that do not enjoy access to paid holiday and sick leave. Casual workers tend to be part-time and dominated by female workers in retail trade and in accommodation, cafes and restaurants. The jobs tend to be low-skilled and low-paid. Campbell (2001: 68) found the proportion of workers who were considered to be casual in 1982 was 13.3%. In Fig. 1 one sees that the proportion increased to 23.7% thirty years later. Not only do casual workers miss access to paid leave and sick leave, they are also excluded from some of the other legislative protections (including unfair dismissal). Consequently, they can lose their job with very little advance notice. Additionally, Pocock et al., (2004) found that a large proportion of casual jobs were precarious with respect to the predictability of earnings, the hours offered, the opportunities for skill development, low union representation, and an increased vulnerability to occupational health and safety hazards. We will – similar to involuntary part-timers – argue that these workers utilise controlled motives to search for work. 2. Materials 2.1. Controlled motivation and labour market precariousness If SDT is correct, workers who face externally regulated pressure to search for employment and follow up on such pressures are less likely to be successful in gaining alternate (better) employment than workers who apply autonomous motivation to search for alternative employment. To identify externally regulated pressure at an individual level, we draw on data from the first eleven waves of the Household, Income and Labour Dynamics Australia (HILDA) data set. The HILDA survey is funded by the Australian government and followed up on an annual basis. The first survey was conducted in 2001. The survey consists of three parts: a household questionnaire, a personal questionnaire and a self-completion questionnaire. We use the personal questionnaire which details the labour market status of respondents – job satisfaction; expectations about future labour market status; job search behaviour, and – since we use several waves – transition rates to different labour market positions in subsequent years. To capture externally regulated pressure, we study hours worked and contract type of the job. We categorise hours worked in the job into three groups: (1) workers who have fulltime employment, (2) workers who have part-time employment and are satisfied with those conditions (voluntary part-time) and (3) workers who have part-time employment and would like to work more hours but have not been able to achieve their working hours ambition (involuntary part-time). Job search of workers in the latter category is likely to be driven by budgetary constraints (i.e. controlled motives), while if workers in the first two categories decide to search for work, it is – in absence of externally regulated pressures – more likely for autonomous reasons. Next, we distinguish workers on (1) casual, (2) fixed term and (3) permanent contracts. A casual worker may lose her current job at any time, while a worker on a fixed term contract knows that her contract will come up at a fixed date. Both workers therefore need to be wary of job loss and consequently need to search for employment to avert potential job loss, with subsequent financial repercussions. That pressure is an externally regulated control on the behaviour of the worker, which the worker on a permanent job contract does not face. If the latter decides to search, it is more likely to be for autonomous reasons. We use both variables to construct a new variable which captures the degree of externally regulated pressures resulting from work conditions at three levels, which may lead to three levels of controlled motivation: – no controlled motivation (both permanent contract and fulltime or voluntary part-time employment); – some controlled motivation (either fixed-term/casual employment or involuntary part-time employment); – strong controlled motivation (both casual employment and involuntary part-time employment). All three categories will contain workers who are amotivated and workers who are autonomously motivated to search for alternate employment. However, we expect that employees in the second and especially the third group are more likely to utilise controlled motivation to search for alternate employment than employees in the first category. Once concentrating on employees who indicate to search for alternate employment, we discard the amotivated workers from our analysis. The workers.3 Assuming that workers can only be motivated to search for two reasons (autonomous or controlled motivation), then employees who face no externally regulated pressures and search for alternate employment are more likely to do so for autonomous reasons. We verified the plausibility of assigning the degrees of motivation to these groups by looking at the average perceptions of the three groups on job security and some other job satisfaction scores, which are available in the HILDA data. From Table 1 one sees that the perceived probability to lose one’s job increases and both job security and employment opportunities
3
The workers who are amotivated to search constitute 86.2% of the first group, 79.0% of the second group and 51.7% of the third group.
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Table 1 Perceptions of groups with different degrees of motivation (pooled sample). Source: HILDA data. Job perception variables
Degree of controlled motivation None
Some
Strong
The per cent chance to lose your job during the next 12 months
8.2
14.3
18.4
How satisfied are you with (scale 1–10) Your job security Your employment opportunities Your total pay Your financial situation The hours you work The work itself (what you do) Your job overall Your life
8.3 7.6 7.0 6.6 7.3 7.6 7.6 7.9
7.5 7.3 7.0 6.2 7.2 7.4 7.6 7.9
6.5 5.7 6.2 5.0 5.5 7.0 6.8 7.6
decrease with the strength of controlled motivation. In particular, those with strong controlled motivation experience a relatively bad financial situation, low satisfaction with the number of hours worked and with their job. The relatively low impact of strong controlled motivation on satisfaction with life is consistent with the finding of Vansteenkiste et al. (2004). A full set of characteristics of the three groups is provided in Tables A1 and A2 in Appendix A. As expected, the likelihood to leave the job voluntarily increases with the intensity of controlled motivation, although workers utilising strong controlled motivation have less confidence to find a (better) job. Young persons, women and workers living outside metropolitan areas are overrepresented in the group using controlled motivation. Not surprisingly, the degree of controlled motivation is negatively related to educational attainment. Finally, tenure held in a previous job is lower, the stronger the controlled motivation to search for another job is. 2.2. Controlled motivation and job search To test the impact of type of motivation on job search behaviour, job search success (if searching) and job improvement (if search was successful), we apply a three stage model – see Fig. 2. Since we define autonomously motivated job search as job search that takes place in absence of externally regulated pressures (casual employment and or involuntary part-time work) we can only isolate autonomously motivated employees from amotivated employees in Stages 2 and 3; not in Stage 1. In Stage 1 all three groups will contain amotivated employees. However, the three groups differ in terms of the strength of controlled motivation, ranging from no controlled motivation (residual motivation for this group must be autonomous) to some and strong controlled motivation. From our general discussion and SDT, the following hypothesis should hold in a precarious labour market environment: Hypothesis 1. Workers with some controlled motivation are (a) more likely to search for alternate employment than workers without controlled motivation and (b) less likely to search for alternate employment than workers with strong controlled motivation.
Stage 3 better job Stage 2 success Stage 1 no better job
motivated employee
no success amotivated
Fig. 2. Schematic overview of three stage model.
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In Stage 2 we drop employees who are amotivated to search and hence we can isolate autonomously motivated employees and test for the effect of autonomous motivation on job search success. SDT then predicts that autonomously motivated job search is more successful (in terms of finding better employment) than job search prompted by controlled motivation. This implies that either (a) job seekers utilising controlled motivation are less likely to find a job; and/or (b) if they find a job, the increase in job satisfaction is less compared to the new job found by an autonomously motivated job seeker. This leads to the following two hypotheses. Hypothesis 2. Of the workers who search for alternate employment, those with some controlled motivation are (a) less likely to secure alternate employment than those with autonomous motivation and (b) more likely to secure alternate employment than those with strong controlled motivation. In Stage 3 we concentrate on employees who were motivated to search in Stage 1 and who were successful in terms of finding alternate employment in Stage 2. Hypothesis 3. Of the workers who successfully searched for alternate employment, those with some controlled motivation are (a) less likely to secure better (in terms of job satisfaction increase) alternate employment than those with autonomous motivation and (b) more likely to secure better alternate employment than those with strong controlled motivation. To test these hypotheses properly we include a broad range of control variables related to the respondent or her environment. That is, variables that may impact on the job search decision and its success, but have no link to our research question. We include personal characteristics (age, gender, ethnicity, location, and educational level), job characteristics (sector, occupation, tenure) and two variables indicating labour market attitudes. One variable measuring the confidence that respondents have to find a (better) job within 12 months if need be and one variable measuring the likelihood that the respondent will leave the current job voluntarily within the next 12 months. Finally, we include a time variable to control for business cycle effects. 3. Methods We estimate three separate regression models to examine each of the three stages as identified in Fig. 2. Model 1 focuses on the job search decision of respondents. The dependent variable is thus constructed as a binary variable (search or not) within a logistical regression specification:
prðY ¼ 1jxÞ ¼
expða þ xbÞ 1 þ expða þ xbÞ
where Y is the dependent binary variable (job search vs no job search) and vector x contains a set of independent variables as outlined in Section 2.2. Model 2 focuses on respondents that have indicated to search for employment and interrogates the outcome of that job search (successful or not). Successful job search is defined as having changed jobs between periods t and t 1 while indicating to search for alternative employment in period t 1. The dependent variable is binary; the regression subsequently a logistical specification, which is similar in nature to model 1’s specification, barring that Y now differentiates successful from non-successful job search (in terms of finding a job). Model 3 focuses on respondents who successfully completed job search and compares job satisfaction in period t (the new job) to job satisfaction in period t 1 (the previous job). Job satisfaction is measured on a 0–10 scale, where 10 is maximum satisfaction. Since we are interested in the difference between job satisfaction in periods t and t 1, we end up with a dependent variable ranging from 10 to 10. Since we cannot treat the dependent variable as an interval variable, for the magnitudes between two values are not necessarily meaningful,4 we must treat it as an ordinal variable. We have further narrowed Model 3’s dependent variable to a five category ordinal construct (<2; 2 to 1; 0; 1 2; >2)5; the regression should subsequently be an ordinal logistical specification. However, an ordinal logistical regression assumes proportional odds. To verify whether our data support the proportional odds assumption, we conduct the Brant test, which rejects the null hypothesis of proportional odds at the 1% significance level (v2 (df = 54) = 120.2; p-value = 0.00). To relax the proportional odds assumption, we specify a generalised ordinal logistical model:
prðY ¼ jjxÞ ¼
expðsj xbj Þ 1 þ expðsj xbj Þ
prðY ¼ jjxÞ ¼
expðsj xbj Þ expðsj1 xbj1 Þ 1 þ expðsj xbj Þ 1 þ ðsj1 xbj1 Þ
for j ¼ 1
for j ¼ 2; 3; 4
4 With an interval variable respondent A reporting for example a four point improvement in job satisfaction, must be four times happier about her job change than respondent B who reports a one point improvement. Whilst no doubt, respondent A is happier about her job move than respondent B, it is unclear in our opinion whether that gap is exactly four, i.e. whether the magnitudes between two values are meaningful. 5 We tried various cut-off values to categorise the dependent variable, which do not lead to significantly different results. Also if we treat the dependent variable as an interval variable similar results are obtained.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44
prðY ¼ jjxÞ ¼
expðsj1 xbj1 Þ 1 þ ðsj1 xbj1 Þ
for j ¼ 5
where j represents the (five) ordinal categories of our dependent variable (change in job satisfaction) and s represents the (four) cut points that demarcate the (five) j categories. This generalised ordinal logistics model is different to an ordinal logistics model in one respect: the bs are j-specific, which means the proportional odds assumption has been relaxed. The generalised ordinal logistical model is equivalent to a set of four binary logistics regressions. The first regression contrasts category 1 (j = 1) of the dependent variable to categories 2, 3, 4 and 5; the second regression contrasts categories 1 and 2 to categories 3, 4 and 5; the third regression contrasts categories 1, 2 and 3 to categories 4 and 5; and the fourth regression contrasts categories 1, 2, 3 and 4 to category 5. In this paper we look at instantaneous success. That is, if a worker searches for a job in year t 1, we measure the outcome of that search process in year t and do not include possible outcomes in year t + 1. The same applies to job satisfaction, if a worker indicates that she (a) searches for employment in year t 1, (b) changes jobs in year t, we measure change in job satisfaction as job satisfaction in year t minus job satisfaction in year t 1. Consequently, we focus on annual transition rates and also treat the data as such. That is, we will use pooled regression analysis, clustering on the respondent identifier in the data to obtain robust standard errors. The regression coefficients will be reported as odds ratios. The odds ratio is defined as the ratio of the odds of an event occurring in one group to the odds of it occurring in the control group. The odds ratio can be computed taking the natural exponent of coefficients of a logistical regression. 4. Results We discuss the three hypotheses successively. 4.1. Job search decision The decision to search for alternate employment should have a positive relation to controlled motivation, according to SDT. The odds ratios in the second column of Table 2 are consistent with this conjecture. Employees with some controlled
Table 2 Determinants of employed job search and its success (odds ratios), 2001–2011. Independent variablesa
Job search motivation No controlled motivation Some controlled motivation Strong controlled motivation Labour market attitude Confidence to find a (better) job Likelihood lo leave job voluntarily Personal characteristics Age cohort: 16–30 years 31–40 years 41–50 years 51–65 years Female Male Non-indigenous Australian Indigenous Living outside major statistical region Living in major statistical region (Pre-)primary/secondary school Certificate Advanced diploma and diploma (Post) Graduate, bachelor degree (Previous) Job characteristics Tenure Pseudo R-squared N
Dependent variables Job search
Job found (once searching)
0.87*** (0.03) Reference 4.02*** (0.29)
0.98 (0.05) Reference 0.88 (0.08)
1.004*** (0.00) 1.03*** (0.00)
1.004*** (0.00) 1.01*** (0.00)
0.85*** (0.03) Reference 1.05 (0.04) 0.72*** (0.04) Reference 1.18*** (0.04) Reference 1.36*** (0.14) Reference 1.04 (0.04) Reference 1.27*** (0.05) 1.35*** (0.08) 1.61*** (0.07)
0.96 (0.05) Reference 0.99 (0.07) 0.93 (0.08) Reference 1.00 (0.05) Reference 0.80 (0.13) Reference 0.94 (0.04) Reference 1.03 (0.06) 1.06 (0.09) 1.06 (0.07)
0.96*** (0.00) 0.19 66,932
0.96*** (0.01) 0.04 9824
Robust standard errors in parentheses. a Occupation, sector and business cycle controls are included in the models; not shown. * 10% Significance. ** 5% Significance. *** 1% Significance.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44 Table 3 Change in job satisfaction (odds ratios), 2001–2011. Independent variablesa
Job search motivation No controlled motivation Some controlled motivation Strong controlled motivation Labour market attitude Confidence to find a (better) job Likelihood lo leave job voluntarily Personal characteristics Age cohort: 16–30 years 31–40 years 41–50 years 51–65 years Female Male Non-Indigenous Australian Indigenous Living outside major statistical region Living in major statistical region (Pre-)primary/secondary school Certificate Advanced diploma and diploma (Post) Graduate, Bachelor degree (Previous) Job characteristics Tenure Pseudo R-squared N
Dependent variables Change in job satisfaction following job change ‘‘<2’’ vs ‘‘P2’’
‘‘<0’’ vs ‘‘P0’’
‘‘60’’ vs ‘‘>0’’
‘‘62’’ vs ‘‘>2’’
1.37** (0.21) Reference 0.60** (0.15)
1.23** (0.11) Reference 0.77* (0.13)
1.23*** (0.09) Reference 0.80 (0.12)
1.37*** (0.12) Reference 0.93 (0.16)
1.01* (0.00) 1.01*** (0.00)
1.003** (0.00) 1.01*** (0.00)
1.001 (0.00) 1.01*** (0.00)
1.003 (0.00) 1.02*** (0.00)
1.01 (0.19) Reference 0.89 (0.18) 0.91 (0.28) Reference 0.90 (0.13) Reference 0.59 (0.20) Reference 0.77* (0.11) Reference 0.98 (0.18) 1.62 (0.51) 1.53* (0.35)
0.79** (0.08) Reference 0.95 (0.12) 1.11 (0.18) Reference 1.02 (0.09) Reference 0.56*** (0.12) Reference 0.86* (0.07) Reference 1.01 (0.11) 1.39 (0.22) 1.24* (0.14)
0.80*** (0.07) Reference 0.97 (0.10) 1.14 (0.16) Reference 1.04 (0.08) Reference 0.86 (0.19) Reference 0.92 (0.06) Reference 1.04 (0.09) 1.48*** (0.19) 1.21** (0.11)
0.69*** (0.07) Reference 1.22* (0.13) 1.21 (0.19) Reference 0.94 (0.08) Reference 1.41 (0.35) Reference 1.02 (0.08) Reference 0.96 (0.10) 0.89 (0.13) 0.93 (0.10)
1.03 (0.02)
1.01 (0.01)
1.003 (0.01)
0.99 (0.01)
0.04 3820
Robust standard errors in parentheses. a Occupation, sector and business cycle controls are included in the models; not shown. * 10% Significance. ** 5% Significance. *** 1% Significance.
motivation are (a) statistically significantly more likely to search for alternate employment than those with no controlled motivation and (b) statistically significantly less likely to search for alternate employment than those with strong controlled motivation. An interesting observation is that overall search incidence increases with educational attainment and being female or Indigenous Australian. A further Chi-square correlation analysis for the impact of gender shows that although women are overrepresented in the groups with some and strong controlled motivation, men in these two groups are significantly more likely to search than women.6 4.2. Job search success Differences between autonomous and controlled motivation are predicted in Stage 2: job search success. Autonomous motivation is predicted to elevate the chance of job search success, whereas controlled motivation is not. The second column of odds ratios in Table 2 contains the results. We do not find any evidence to support this hypothesis. That is, of the employees who search for work, those with some controlled motivation are (a) not less likely to secure alternate employment than those with no controlled motivation and (b) not more likely to secure alternate employment than those with strong controlled motivation. As an interesting side note, we observe the absence of a significant impact of personal characteristics on job search success. A further Chi-square correlation analysis for the impact of gender shows that this holds for all three degrees of controlled motivation. 4.3. Job satisfaction improvement Finally, we test the third hypothesis: when does successful job search lead to increased job satisfaction? SDT predicts that autonomous motivation will lead to improvements in job satisfaction (following successful job search completion) as 6 We tested the following hypotheses H0: no correlation between gender and the three groups of controlled motivation: v2 (2) = 1100; p = 0.00; H0: no correlation between search activity and gender within group with some controlled motivation: v2 (1) = 10.22; p = 0.00 and H0: no correlation between search activity and gender within the group with strong controlled motivation: v2 (1) = 5.49; p = 0.02.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44
opposed to controlled motivation. We specified the generalised ordinal logistical model, the results of which can be found in Table 3. First we note that the odds ratios across the four regressions are not constant, which indeed suggests that a simple ordinal logistic regression would have been a misspecification. We find strong support for the first part of the third hypothesis. Of the workers who successfully searched for alternate employment, those with some controlled motivation are statistically significantly less likely to secure better alternate employment than those with autonomous motivation. We find that result across all four transitions, including the third transition (which distinguishes between achieving job satisfaction progress as a result of job change or not). We find weak support for the second part of the third hypothesis. The coefficient of ‘strong controlled motivation’ is consistently below unity, indicating that of the workers who successfully searched for alternate employment, those with some controlled motivation are more likely to secure better alternate employment than those with strong controlled motivation. However, this coefficient is only significantly different from unity for the first two transitions. This finding indicates that workers with strong controlled motivation are statistically significantly more likely to accept alternate employment that makes them worse off than workers with some controlled motivation.
5. Discussion/conclusion We have applied SDT to the field of employed job search, which is a field with strong externally regulated pressures in place in industrialised countries like Australia. As predicted, workers who search for a job without externally regulated pressures are more likely to find alternative jobs with subsequent augmented job satisfaction. Employees facing externally regulated pressures are not per se less likely to find alternative employment, but the fact that they do not transit to better jobs is indicative of the failure of contemporary labour market policies applied in OECD countries like Australia. The findings also accord with predictions from dual labour market (DLM) theory – Doeringer and Piore (1971) and Piore (1975). DLM theory argues that the labour market is segmented into a Primary Labour Market (PLM) and a Secondary Labour Market (SLM). The PLM worker who is typically employed in a secure internal labour market structure which provides for career advancement will use search activity to enhance her career aspirations, i.e. autonomous motivation. Conversely, the SLM worker may search for different reasons especially given the precariousness of their employment. Search thus may not be motivated by potential employment improvement, but might, rather, be fuelled by fear of future job loss, i.e.: controlled motivation. The two markets are separated by rigidities which inhibit mobility across them. Accordingly, if a worker becomes ‘trapped’ into the SLM, access to the better outcomes in the PLM becomes severely limited if not intractable. SDT would argue that lack of upward mobility from the SLM is not necessarily a result of rigidities but of externally regulated search motivation. The applicability of SDT to labour market analysis provides important new ways of appraising the current policy framework which has emphasised activism and deregulation. The implementation of the OECD Job Study agenda has increased the degree of job insecurity in labour markets. There has been a marked increase in the degree of precariousness and job instability over the last two decades in most economies. The application of SDT to this phenomenon tells us that the supply-side labour market policy framework has contributed to workers cycling through spells of insecure employment and possibly intermittent spells of unemployment with no realistic prospect of career development. In other words, the stated goals of the OECD activist strategy have not been fulfilled in practice when we consider the fortunes of the vulnerable workers in the labour market. This cohort was thought to be beneficiaries of the new approach to training and job placement. Our study suggests that they have not gained better jobs through increased (forced) search activity.
Acknowledgements This paper uses unit record data from the Household, Income and Labour Dynamics in Australia (HILDA) survey. The HILDA project was initiated and is funded by the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) and is managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors and should not be attributed to either FaHCSIA or the Melbourne Institute. We thank one anonymous referee for providing us with constructive suggestions and comments. Appendix A See Tables A1 and A2.
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R. Welters et al. / Journal of Economic Psychology 44 (2014) 34–44 Table A1 Descriptive statistics (means) for the whole sample/job searchers, 2001–2011. Independent variables
Type of motivation All
Total
No controlled motivation
Some controlled motivation
Strong controlled motivation
0.67/0.55
0.31/0.39
0.02/0.06
Labour market attitude Confidence to find a (better) job Likelihood lo leave job voluntarily
0.65/0.75 0.24/0.55
0.64/0.75 0.19/0.53
0.67/0.76 0.32/0.57
0.61/0.68 0.40/0.55
Personal characteristics Age cohort: 16–30 years 31–40 years 41–50 years 51–65 years Female Non-Indigenous Australian Non-metropolitan areas
0.35/0.45 0.23/0.24 0.24/0.21 0.18/0.10 0.47/0.48 0.98/0.98 0.41/0.39
0.28/0.36 0.26/0.29 0.27/0.24 0.20/0.12 0.43/0.42 0.99/0.98 0.39/0.36
0.49/0.56 0.18/0.19 0.19/0.18 0.14/0.08 0.56/0.54 0.98/0.97 0.44/0.41
0.51/0.56 0.14/0.16 0.18/0.16 0.17/0.12 0.58/0.55 0.96/0.96 0.57/0.55
(Pre-)primary/secondary school Certificate Advanced diploma and diploma (Post) Graduate, bachelor degree
0.43/0.40 0.23/0.23 0.09/0.09 0.25/0.29
0.38/0.31 0.25/0.25 0.10/0.10 0.28/0.34
0.54/0.48 0.19/0.20 0.07/0.07 0.20/0.24
0.61/0.58 0.22/0.23 0.06/0.05 0.11/0.14
(Previous) Job characteristics Tenure (years) N
5.7/3.5 66,932
7.0/4.7 44,932
3.2/2.1 20,550
2.2/1.5 1450
Table A2 Descriptive statistics dependent variable to type search motivation, 2001–2011. Dependent variables
Looking for work Found a job when looking Found a better job while looking
Type of motivation All
No controlled motivation
Some controlled motivation
Strong controlled motivation
0.17 0.39 0.59
0.14 0.37 0.62
0.21 0.41 0.57
0.52 0.38 0.51
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