Good, bad, and not so sad part-time employment

Journal of Vocational Behavior 104 (2018) 128–140

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Journal of Vocational Behavior journal homepage: www.elsevier.com/locate/jvb

Good, bad, and not so sad part-time employment a,⁎

b

Victor Y. Haines III , Pascal Doray-Demers , Vivianne Martin a b

MARK a

School of Industrial Relations, University of Montreal, Canada Department of Political Science, University of British Columbia, Canada

AR TI CLE I NF O

AB S T R A CT

Keywords: Part-time employment Latent class analysis Work design Job satisfaction Health

With increases in part-time employment, the need to understand its diverse forms is growing. The aim of this study is to develop a typology of part-time employment on the basis of role occupancy and work characteristics. Latent class analysis was applied to data from a sample of 1826 parttime workers. The pattern of conditional probabilities suggests four types of part-time employment: Good, bad, student, and transition. Further analysis indicates that gender, age, education, seniority, and work experience are correlates of being in one or other types of part-time employment. Finally, good part-time employment is associated with higher job satisfaction and health although better health is reported in student part-time employment.

1. Introduction Over 26 million persons in the United States are employed part time (BLS, 2014), well over three million in Canada (Statistics Canada, 2017) and about 19% of the workforce in the European Union (Eurostat, 2017); with steady increases observed in several countries (ESDC, 2014; Pak, 2013). Considered nonstandard or nontraditional work (Broschak & Davis-Blake, 2006; Chadwick & Flinchbaugh, 2016; Feldman, 1990; Hoque & Kirkpatrick, 2003; Kalleberg, 2000; Snider, 1995), often contrasted with full-time employment (Beham, Präg, & Drobnič, 2012; Broschak, Davis-Blake, & Block, 2008; MacDonald, Bradley, & Brown, 2009; Sinclair, Martin, & Michel, 1999; Smith & McDonald, 2016; Steffy & Jones, 1990; Thorsteinson, 2003; Warren & Walters, 1998), part-time work situations are in reality quite diverse; possibly ranging from good to bad in terms of job quality. Drawing from role theory (Katz & Kahn, 1978), Martin and Sinclair (2007) identified groups of part-time employees that suggest differences in patterns of role occupancy. Though an important step toward a better understanding of modern employment relationships, the role occupancy perspective does not admit that work characteristics are widely regarded as meaningful criteria for defining types of part-time work. Rather than identify groups of part-time employees, the first aim of this study is therefore to develop a typology of part-time employment. Drawing from the attraction-selection-attrition (ASA) framework (Schneider, 1987), we argue that people and work characteristics together best define part-time employment and job quality. We therefore include in a latent class analysis (LCA) individual differences related to role occupancy and work characteristics. The simultaneous consideration of work characteristics and role occupancy variables is expected to provide a more complete and realistic picture of part-time employment; one that may better inform discussions about part-time work in light of societal concerns about job quality (Brookings Institute, 2007; Jackson, 2010; Lyonette, Baldauf, & Behle, 2010; OECD, 2010; Osterman, 2010). The second aim of this study is to examine the antecedents of being involved in one or another types of part-time employment. We thereby distinguish types of part-time employment from the exogenous individual demographic and human capital characteristics that may be associated with being in different part-time situations. In so doing, our study will address a gap in the literature by investigating the correlates of part-time

⁎

Corresponding author at: School of Industrial Relations, University of Montreal, P.O. Box 6128, Station Centre-ville, Montreal, Quebec H3C 3J7, Canada. E-mail address: [email protected] (V.Y. Haines).

http://dx.doi.org/10.1016/j.jvb.2017.10.007 Received 2 February 2017; Received in revised form 14 October 2017; Accepted 18 October 2017 Available online 22 October 2017 0001-8791/ © 2017 Elsevier Inc. All rights reserved.

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employment type and this is a necessary step toward a better understanding of inequalities in employment relationships and job quality. The third aim of this study is to relate different types of part-time employment to meaningful outcomes. Research that compares part- and full-time work on attitudes or behavior (e.g., Saba, Blouin, & Lemire, 2006; Thorsteinson, 2003; Wakefield, Curry, Mueller, & Price, 1987) does little to capture the seemingly important finer inter-group contrasts between part-time work situations. Moreover, research on underemployment considers the consequences of working fewer hours than desired (Allan, Duffy, & Blustein, 2016; Duffy, Blustein, Diemer, & Autin, 2016), but not those of being involved in different types of part-time employment. Drawing from research on job quality (Knox, Warhurst, & Pocock, 2011; Loughlin & Murray, 2013), we expect different types of part-time employment to range from good to bad and therefore result in dissimilar levels of job satisfaction and self-reported health. Because employment types are by nature configurational, LCA should provide a rich account of this complex phenomena following an underdeveloped approach in management research (Delbridge & Fiss, 2013). 1.1. Typology of part-time employment The ASA framework provides a theoretical basis for the simultaneous consideration of role occupancy and work characteristics. To operate this integration, we however need to first develop the role occupancy and work characteristics perspectives. 1.1.1. Role occupancy Drawing from role theory (Katz & Kahn, 1978), much research on part-time work has attempted to determine the degree to which part-time employees are included in their focal organization. From this standpoint, they are often assumed to be less included than their full-time counterparts (Miller & Terborg, 1979; Thorsteinson, 2003); but there may also be varying degrees of inclusion within the part-time workforce. Martin and Sinclair (2007), for instance, argued that being married, attending school, working in a full- or part-time position elsewhere as well as the number of children at home, age, and income contribution could influence involvement levels in the part-time work role relative to other life roles that form self-identity. If, for instance, the part-time job simply supplements income from another source, the employee should be less included in the focal organization's social system. In this way, role occupancy (i.e., degree of inclusion or involvement) in part-time employment varies according to the salience for self-conception of that role relative to other role identities that compose the self. A student pursuing a college degree and working weekends in the kitchen of a local restaurant may not attach a great deal of importance to this work role relative to attending school. It is possible then to develop a typology of the part-time workforce on the basis of role occupancy profiles (Martin & Sinclair, 2007). Although role occupancy offers a meaningful perspective for studying part-time work, this theoretical stance alone is limited in terms of its predictive power. Reining in studies largely based on partial inclusion theory, a meta-analysis found no significant differences in job satisfaction, organizational commitment, and intention to leave between part- and full-time workers (Thorsteinson, 2003). The reason for this is most likely that work characteristics are not given adequate consideration in this stream of research. Simply put, being more included in a part-time job with lesser work characteristics may result in similar outcomes as being less included in a part-time job with better work characteristics. Role occupancy is nonetheless an important consideration as role theory predicts that involvement in different life roles, including the part-time worker role, fluctuates in a system of competing attachments. We therefore included in our configurational analysis having a partner, parenting, being a student, contribution to household income, and being employed elsewhere. 1.1.2. Work characteristics Assuming variability in part-time work (Feldman, 1990), observers noted that good part-time jobs have high pay, promotion opportunities, require many skills (Tilly, 1991, 1996), and are career occupations (Higgins, Duxbury, & Johnson, 2000). Conversely, bad part-time jobs have low pay, few promotion opportunities, require few skills, involve routine or monotonous tasks (Tilly, 1992, 1996) and are not career occupations (Higgins et al., 2000). Part-time police work, for example, was qualified as good as it involves high wages, challenging work and career potential (Dick, 2010). More generally, part-time employment may be set in a Taylorist system of work organization with low interdependence or in the context of enriched work that requires teamwork and cooperation (Edwards & Robinson, 1999). Two conclusions are easily drawn from these observations. First, types of part-time work are often described in terms of their work characteristics. In addition to those just mentioned, Feldman (1990) contrasted permanent and temporary as well as year round and seasonal part-time work. Other work characteristics used to delineate types of part-time employment include the provision of benefits (Kalleberg, 2000), job security (OECD, 2010), level of responsibility (Charlesworth & Whittenbury, 2007), performance of core work (Chadwick & Flinchbaugh, 2016), hours worked (Beham et al., 2012; Robotham, 2012), wages (Bardasi & Gornick, 2008), and the amount of training(Arulampalam, Booth, & Bryan, 2004; Bidwell, Briscoe, Fernandez-Mateo, & Sterling, 2013).Second, other than anecdotal reports and keen observations, the only empirical attempt to delineate different types of part-time work was based solely on individual role occupancy variables (Martin & Sinclair, 2007). This, in itself, is quite restrictive because the approach does not account for the work characteristics that may activate intrinsic motivation and the proclivity to work in one or another types of parttime employment. We therefore include a set of work characteristics that includes educational and experience requirements, work hours, supervision, pay level, flexibility, and permanent status. 1.1.3. Attraction-selection-attrition The main thesis of the ASA framework is that the attributes of people in a workplace define the way that place looks, feels, and behaves (Schneider, 1987, p. 437). Applied to our research, we advance that individual role occupancy profiles in a workplace help 129

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define part-time employment in that workplace. Individuals select themselves into and out of part-time employment and the human environment within this work situation is determined by this process. As such, from the standpoint of interactional psychology, environments and people are not separable. Different kinds of work environments attract, select, and retain different kinds of people. From this standpoint, we expect different work characteristics within part-time employment to attract, select, and retain different types of people in terms of role occupancy profiles. Conversely, work conditions are often developed with particular employee attributes in mind. This interplay of individual and work characteristics again calls for a configurational approach. Part-time work situations would therefore look and feel different from each other because they combine different work characteristics and kinds of people. We therefore propose that varying role occupancy profiles are differentially attracted to different parttime work characteristics. Similarly, individual role occupancy profiles would be associated with the likelihood of being selected into or staying in one type or another of part-time work. The end result is a part-time work situation in which individual role occupancy profiles are similar to each other as they were attracted to, selected into, and remained in a particular setting involving work characteristics ranging from better to lesser. In terms of the associations related to the primary aim of this study, we expect a typology of part-time employment that associates more included individuals in part-time work with better work characteristics and less included individuals in part-time employment with lesser work characteristics. Drawing from work on flexible and inflexible attachments (Senter & Martin, 2007; Wittmer & Martin, 2011), we further expect that individuals with flexible attachments (i.e., presence of a partner or children) to be in part-time work with better work characteristics and those with inflexible attachments (i.e., students or employed elsewhere) to be in part-time work with lesser work characteristics. Another consideration for those with flexible attachments relates to the resources available to alleviate the pressures related to family care giving (Senter & Martin, 2007). Having a partner (spouse), though seen as an outside attachment associated with lower role occupancy in part-time work, is actually a flexible attachment associated with higher role occupancy to the extent that resources are available. The presence of children is also viewed as a flexible attachment and, to the extent that resources are available to parents, they are expected to be in part-time work with better work characteristics. When resources are not available, individuals with parenting responsibilities are expected to be in part-time work with lesser work characteristics. Finally, the inflexible outside attachments associated with being a student or with being employed elsewhere are expected to be associated with lesser part-time work characteristics, irrespective of the amount of resources. Though these associations between role occupancy profiles and work characteristics result from the ASA cycle, the net effect is likely be some consistency between how peripheral the employment is to both the individual and to the organization. In a system of dual labor markets (Doeringer & Piore, 1975), part-time employment of lesser quality is considered peripheral. The role occupancy profiles of individuals in such employment would then also be peripheral or rather their employment would not be central to their social identity. Work on psychological contracts (Rousseau, 1989, 1995) also sheds some light on these associations as more peripheral part-time employment fits within a transactional type of relationship characterized by limited employee involvement in the organization. These additional perspectives further support the prediction of interpretable patterns of role occupancy profiles and work characteristics. Fig. 1 highlights the contrasts between some parameters that inform our configurational analysis of part-time work employment types. 1.2. Antecedents of part-time employment type Five exogenous variables are examined in relation to the likelihood of being involved in one or another of part-time employment types. The perspective for each is that individuals more or less voluntarily gravitate toward one or another types of part-time employment; that there is agency and free choice (Hakim, 1991), but that it is socially constrained (Dick & Hyde, 2006), that numerous barriers constrain access to decent work (Duffy et al., 2016), and that there are differences in opportunities with regards to part-time work (Fagan, 2001); that constraints are exerted on both the formation and enactment of individual preferences. Gender is a status characteristic that acts as an organizing principle of social relationships (Thoits, 1986, 1992). From the perspective of gender inequality, the high participation of women in part-time employment is a function of their subordinate position in the labor market (MacDonald et al., 2009) and constrained choice under structural forces perpetuating gendered strategies (Moen & Yu, 2000). The expectation that women would be more involved than men in bad part-time work is an extension of this outlook. Preferences and constraints may also vary as a function of age. Older workers may prefer part-time work because it allows them

Fig. 1. Template for the analysis of part-time employment type.

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more free time as they transition from full-time employment to full retirement. In terms of constraints, an abundant literature points to negative attitudes toward older workers producing employment disadvantage (e.g., Duncan & Loretto, 2004; Finkelstein, Burke, & Raju, 1995; Gringart, Helmes, & Speelman, 2005). Younger adults may prefer to further their education to improve their career prospects. Part-time employment would allow them the time to pursue this goal and engage in independent exploration of possible life directions. Young adults, however, most often lack educational qualifications and the credentials to access better employment options. As such, preferences and constraints vary in nature at different stages of human development (Erikson, 1968; Levinson, 1986). Younger and older adults, however, appear to experience more constraints that would tend to place them in bad part-time employment. The three other antecedents of part-time employment type relate to human capital (Becker, 1994). More human capital in the form of educational qualifications, seniority, and work experience are associated with more positive career outcomes (Ng, Eby, Sorensen, & Feldman, 2005) and are expected to be associated with good part-time employment. The above variables are modelled as antecedents of part-time employment type rather than as clustering variables to be included in the LCA. The most basic assumption of this analytical approach is that observed indicators are caused by an unobserved latent categorical variable. Pay level, for instance, would be caused by the type of part-time employment the person is involved in. For variables such as gender and age, the causation obviously goes the other way. Similarly, life decisions regarding human capital development are made before entering part-time employment. Although seniority might be a function of the type of part-time employment, with high seniority associated with employment types characterized by low turnover, it is more directly addressed as relating to human capital. Moreover, these are neither role occupancy variables nor work characteristics.

1.3. Outcomes of part-time employment type There are long traditions of research associating job quality or well-designed work to job satisfaction and health (Humphrey, Nahrgang, & Morgeson, 2007; Parker, Van Den Broeck, & Holman, 2017). With part-time employment ranging from good to bad, different job satisfaction and health outcomes should be observed along this continuum. Meta-analytic findings suggest a strong association between job satisfaction and health (Faragher, Cass, & Cooper, 2005). Both of these outcomes are therefore considered in this study as corresponding dimensions of individual well-being. Moreover, though job satisfaction and health are qualitatively different in nature, examining them together should provide richer interpretations of the outcomes of different part-time employment types and possibly point to some dimensions of context in need of additional scrutiny (Johns, 2006). Having found very few pre-entry differences by full- and part-time status, Shockey and Mueller (1994) concluded that the structural conditions of work produce differences in attitudes. We recognize the primacy of work characteristics and extend this outlook to the study of different types of part-time employment. We extend it in another way by admitting that “people make the place” and thereby define part-time employment types as unique combinations of work characteristics and role occupancy profiles associated with job satisfaction and health.

2. Methods 2.1. Data The data for this study is from the Longitudinal and International Study of Adults (LISA); a survey that collects information from people across Canada about their jobs, education, health and family. LISA is sponsored by Employment and Social Development Canada and is administered by Statistics Canada. The survey itself is conducted by an interviewer via a computer assisted personal interview and data quality. The same individuals are surveyed every two years with multiple instruments combining questionnaire and administrative data. Not all participants were required to answer all the sections of the questionnaires and some are wave specific. At the time of this study, two waves of data were available, but only the first wave had all the variables relevant to our analysis. This wave was conducted from November 1st 2011 to June 27th 2012. Two conditions had to be met to qualify as a part-time worker. First, when asked to choose the statement that best describes their current situation, respondents had to select “part-time employed.” Second, they also had to report that they usually work 30 h or less per week in their main job. The cut-off between part- and full-time work varies significantly from one study to another, ranging from < 15 h (Arulampalam et al., 2004) to < 40 h per week (Shockey & Mueller, 1994). In this study, we applied the OECD cut-off taken in several studies (e.g., Bardasi & Gornick, 2008; Warren & Walters, 1998). This objective measure combined with respondents' subjective assessments of their own situation significantly increases the likelihood that final sample is in fact composed of a part-time workforce. Not included in this sample business owners, people with major health-related limitations or those involved in an apprenticeship. Individuals in the final sample were all involved in paid employment. Following the selection of cases on the basis of these criteria and the removal of 58 cases with missing values, the sample included 1826 part-time workers from the 32,311 respondents in this wave of data collection. The average age within the selected sample was 38.1 years and about three quarters of respondents were women (74.7%). More than half of respondents reported having a partner (55.9%) and about a quarter being currently enrolled in a program of study (25.4%).

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2.2. Measures 2.2.1. Role occupancy Five role occupancy variables were included in the LCA. Having a partner was coded as either not having (0) or having (1) a partner. Parental status was coded as not having (0) or having (1) children. Being a student was coded as not currently enrolled in a program of study (0) or being so enrolled (1). Household income contribution was coded in four categories ranging from 1 (10% and less) to 4 (> 40%). Having a job elsewhere in addition to the part-time job was coded as having just that one job (0) or more than one job (1).

2.2.2. Work characteristics Seven work characteristics were included in the LCA. The educational requirements of the part-time position was recoded at four levels ranging from 1 (high school diploma or less) to 4 (university diploma or more). The experience requirements relate to how much related work experience someone would need to qualify for the part-time position. This variable was recoded with responses ranging from 1 (none) to 4 (three years or more). Work hours were assessed as the number of hours usually worked per week in the part-time position, including overtime and excluding any breaks. We coded the work hours measure in three categories; the lowest involves working “ < 9 h” (1) and the highest involves working “ > 18 h” (3). Supervision as defined in the survey involves supervising or managing other employees and was coded “no” (0) or “yes” (1). Income data obtained by fiscal authorities from income tax statements was included in the dataset. To measure the pay level associated with part-time employment, we chose gross pay per week because it had the fewest missing values. The recoded measure of pay level ranged from 1 (140$ or less) to 5 (> 480$). Three items measured the amount of flexibility involved in the part-time position. They addressed the ability to choose or change (a) the sequence of tasks, (b) how the work is done, and (c) the speed or rate of work. The response scale ranged from 1 (not at all) to 5 (a very high extent). We computed the total score from these three items and recoded as a quintile. A fourth item about the extent to which the participant could choose or change working hours was omitted from the flexibility scale because the three-item scale proved more robust. Testing both the three and four items scale using PCA we found that three-item flexibility scale had higher reliability (α = 0.78) than the four-item scale (α = 0.74). Moreover, factor analysis with the three-item scale produced a clear single factor with comparable loading coefficients on the three items, justifying a simple additive index. We might point out as well that the threeitem scale used in our study is very similar to the three-item scale used by the European Foundation for the Improvement of Living and Working Conditions (2007). Having a permanent status was coded “no” (0) for seasonal, term or contract, casual, temporary, apprenticeship or other training scheme, no contract or other types of jobs and “yes” (1) when a permanent contract was reported.

2.2.3. Outcomes Job satisfaction and health were included as outcomes of part-time employment type. Job satisfaction was assessed using a singleitem measure (All things considered, how satisfied are you with your current job?) and responses were reported on a five-point scale ranging from 1 (extremely unsatisfied) to 5 (extremely satisfied). An initial ordered probit analysis indicated that some response category cut points were overlapping; making it difficult to differentiate those categories. The variable was therefore recoded on a three-point scale ranging from 1 (extremely unsatisfied) (anchors 1 and 2) to 2 (satisfied) (anchors 3 and 4) to 3 (extremely satisfied) (anchor 5) to solve this problem. The job satisfaction question, however, was only asked to a subsample of the survey panel, reducing sample size to 650 individuals for analysis involving this variable. Health (In general, would you say your health is…) was coded on a five-point scale ranging from 1 (poor) to 5 (excellent). These five levels were meaningful and no further recoding was therefore required.

2.2.4. Antecedents of part-time employment type Gender, age, education, seniority, work experience were modelled as exogenous variables associated with the likelihood of being involved in one or another of part-time employment types. Gender was coded female (0) or male (1). Age was recoded as a quintile, the lowest comprising individuals “under 20 years old” (1) and the highest, individuals “over 55 years old” (5). Participants were asked to report their highest education level obtained and their responses were recoded into a five-level scale ranging from “less than a high school diploma” (1) to “university certificates above bachelor degree” (5). Seniority was assessed using the year the participant started working for the current employer. We calculated seniority in number of years and recoded the responses as a quintile ranging from 1 (less than a year) to 5 (> 10 years). To assess work experience, we recoded the reported total number of years of full-time work considering all jobs and recoded as a quintile ranging from 1 (less than a year) to 5 (> 20 years).

2.3. Analysis Latent class analysis (LCA) was applied to identify unobservable groups of part-time employment. In this case, Mplus 7 computed the estimates using multiple categorical indicators. Once the classes were identified, we estimated with multinomial logit regression the associations between gender, age, education, seniority, work experience and the probabilities of being in one group or another of part-time employment. Finally, we analyzed the associations between the groups of part-time employment and job satisfaction and health using ordered probit regression with gender, age, education, seniority, and work experience modelled as covariates. 132

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3. Results 3.1. Latent class analysis In a first step, we ran LCA for male and female respondents separately. There was not a significant difference between these subgroups. To determine the number of classes we then ran models having from one to eight classes. The four class solution was favoured in the end and this choice was motivated by both empirical and theoretical considerations. First, the marginal decrease in information criteria scores starts to level off when more than four classes are formed. Three information criteria were considered: Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and Sample-Size Adjusted Bayesian Information Criterion (SSA-BIC). The slopes shown by the BIC and the SSA-BIC are telling as they suggest that adding a fifth group adds little in terms of improving the model. The Likelihood Ratio Test (LRT) compares a model with another that has one less class. A statistically significant LRT indicates that the added class improves model fit. The results of this analysis indicate that the LRT coefficient ceases to be significant when the five-class model is reached; meaning that the fifth class does not offer a significant improvement over the four-class model. From a theoretical standpoint, the fifth class was simply a subdivision of a class identified by the four-class model and this was not of any particular theoretical interest. The four-class model was therefore favoured on the basis of both statistical and theoretical considerations. Moreover, the entropy coefficient of the four-class model was 0.873; suggesting a clear distinction between the classes. Entropy values range from 0 to 1 and a score over 0.800 is generally considered good (Clark & Muthén, 2009). Therefore, in this case, with a four-class model selected on the basis of information criteria and LRT coefficients, the entropy coefficient simply confirms that this is a good solution.

3.2. Four-group model of part-time employment Conditional probabilities are reported in Table 1 and they should be interpreted as the probability of being in the response category for individuals assigned to that group. For example, 255 individuals from the sample were assigned to Class 3 (Student) and the probability for them of having a partner is 1.2%. As such, a very low percentage of individuals in the “Student” group have a partner. A very high percentage of individuals in what we labelled as “Good” part-time employment have a partner and parenting responsibilities. They are also more likely than other part-time employment groups to have a higher household income contribution. Individuals in good part-time employment are also more likely than those in other groups to report higher educational and experience requirements associated with their job. Other work characteristics that justify qualifying this class as good part-time employment are more work hours, supervisory responsibilities, a permanent status and somewhat more flexibility than in other groups. Finally, a clear distinction between good part-time employment and the other types is higher pay. Interestingly, high percentages of those in “Bad” part-time employment also have a partner as well as parenting responsibilities. Their income contribution is also relatively high. Although these variables that represent flexible attachments outside of the part-time job are at levels comparable to those found in good part-time employment, what sets them apart is the amount of resources available within those outside roles. In a separate test, we found household income to be significantly higher among those in good (M = 124,815, SD = 3444) relative to bad (M = 87,716, SD = 2535) part-time employment [t(1.132) = 8.878, p = 0.00]. Relative to good part-time employment, higher percentages of those in bad part-time employment reported lower educational and experience requirements as well as fewer work hours and supervisory responsibilities, lower pay levels, and somewhat less flexibility. Moreover, a lower percentage within the bad part-time work group reported a permanent status. The “Student” group had much lower percentages respondents with a partner or children. A very high percentage of individuals in this group reported being currently enrolled in a program of study. As might be expected, their contribution to household income was mostly in the lowest category and a very low percentage reported having a job elsewhere. Very high percentages in student part-time employment reported low educational and experience requirements and few work hours. They were the least likely to report supervisory responsibilities or higher pay levels. Lower percentages of individuals in this group reported higher levels of flexibility or a permanent status. “Transition” part-time employment shares some of the features of student part-time employment, but with somewhat better work characteristics. Individuals in the transition group were not likely to have a partner or children. Over 40% of those in this group reported being currently enrolled in a program of study; a percentage that is high relative to good and bad part-time employment, but about half the percentage found in the student group. Contribution to household income is low relative to good and bad part-time employment, but more than in the student group. Educational and experience requirements are low relative to good part-time employment, but higher than in the student group. The percentage of individuals in this group reporting more work hours is much higher than in the student group and higher than in bad part-time employment. Also, those in the transition group were about twice as likely to report supervising or managing other employees than are individuals in bad or student groups. The pattern of results also suggests higher pay levels in the transition group than in the student group. There is less flexibility in the transition group than in the good part-time employment group, but more than in the student group. A higher percentage reported a permanent status in the transition group than in the student group. As such, transition part-time employment seems to reflect a type of employment encountered at an early career stage (Rabinowitz & Hall, 1986).

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Table 1 Conditional probabilities of the four-class model. Latent Class

Class 1

Class 2

Class 3

Class 4

Good

Bad

Student

Transition

N

539

595

255

437

Sample %

30%

32%

14%

24%

1 2

0.094 0.906

0.165 0.835

0.988 0.012

0.928 0.072

1 2

0.104 0.896

0.111 0.889

0.996 0.004

0.994 0.006

1 2

0.938 0.062

0.956 0.044

0.142 0.858

0.579 0.421

1 2 3 4

0.045 0.155 0.371 0.429

0.122 0.209 0.313 0.356

0.858 0.072 0.052 0.018

0.346 0.351 0.193 0.110

1 2

0.839 0.161

0.859 0.141

0.944 0.056

0.851 0.149

1 2 3 4

0.003 0.170 0.407 0.420

0.390 0.426 0.173 0.011

0.775 0.186 0.039 0.000

0.399 0.400 0.116 0.085

1 2 3 4

0.240 0.188 0.322 0.249

0.474 0.300 0.189 0.037

0.650 0.283 0.052 0.014

0.424 0.372 0.174 0.030

1 2 3

0.029 0.142 0.830

0.129 0.292 0.579

0.264 0.627 0.109

0.054 0.180 0.766

1 2

0.776 0.224

0.915 0.085

0.924 0.076

0.848 0.152

1 2 3 4 5

0.017 0.017 0.057 0.254 0.655

0.188 0.228 0.296 0.234 0.053

0.605 0.352 0.033 0.010 0.000

0.105 0.193 0.363 0.252 0.087

1 2 3 4 5

0.131 0.195 0.198 0.243 0.233

0.295 0.177 0.157 0.177 0.194

0.275 0.244 0.159 0.181 0.141

0.231 0.213 0.164 0.214 0.178

1 2

0.350 0.650

0.532 0.468

0.652 0.348

0.542 0.458

Variables Partner No Yes Parent No Yes Student No Yes Income contribution Category Category Category Category Job elsewhere No Yes Education required Less than high school High school Some university University diploma Experience required Category Category Category Category Work hours Category Category Category Supervision No Yes Pay level Category Category Category Category Category Flexibility Category Category Category Category Category Permanent No Yes

3.2.1. Antecedents of part-time employment type Two demographic and three human capital variables were introduced in a multinomial logit regression with good part-time employment as a reference category. The results that appear in Table 2 indicate a gender distribution that suggests more men than women in student and transition than in good part-time employment. Gender does not appear to be associated with being in good relative to bad part-time employment. Age presents a very clear pattern. Relative to the good part-time group, older individuals tend to be in bad part-time and younger individuals appear to gravitate toward student and transition part-time employment. The three human capital variables show a similar pattern of findings with higher educational attainment and more seniority and work experience in good part-time employment relative to the other types.

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Table 2 Multinomial logit analyses of part-time employment type on demographic and human capital variables.

Gender (male) Age Education Seniority Work Experience Intercept N

Class 2 (Bad)

Class 3 (Student)

Class 4 (Transition)

0.246 (0.316) 0.559⁎⁎⁎ (0.139) − 1.297⁎⁎⁎ (0.272) − 0.749⁎⁎⁎ (0.125) − 0.311⁎⁎⁎ (0.095) 3.241⁎⁎⁎ (0.824) 1826

2.749⁎⁎⁎ (0.626) −4.909⁎⁎⁎ (0.710) −2.590⁎⁎⁎ (0.470) −0.921⁎⁎⁎ (0.290) −1.553⁎⁎⁎ (0.278) 10.345⁎⁎⁎ (1.073) 1826

3.222⁎⁎⁎ (0.564) −3.108⁎⁎⁎ (0.371) −0.659⁎⁎⁎ (0.237) −0.735⁎⁎⁎ (0.208) −0.912⁎⁎⁎ (0.165) 8.016⁎⁎⁎ (0.979) 1826

Note. SE in parentheses. ⁎⁎⁎ p < 0.05.

3.3. Outcomes of part-time employment type We again used the good part-time group as a reference category to analyze the associations between part-time employment type and job satisfaction and health. The standard ordered probit analysis included five control variables that are typically investigated in studies of job satisfaction and health. As expected and shown in Table 3, higher levels of job satisfaction and health were found in good relative to bad part-time employment. Also, higher job satisfaction was found in good part-time relative to student and transition part-time employment. Interestingly, although we controlled for age, individuals in student part-time reported higher levels of health than those in good part-time employment. Beyond coefficient significance, we determined whether the size of the effects are substantially meaningful by running simulations to observe how group membership affects job satisfaction and health. Ordered probits model the probability for each individual to be in a given category of the dependent variable. The simulation strategy required that we set the value of age, education, seniority, and work experience to their median value. The simulations were run assuming that gender was male, with no loss of ability to generalize since we tested and did not detect any gender effect at any stage of the process. We then predicted the probability

Table 3 Ordered probit regression of job satisfaction and health on part-time employment type. Job satisfaction Class 2 bad Class 3 Student Class 4 transition Gender (male) Age Education Seniority Work experience N Cuts Cuts Cuts Cuts Cuts

confidence intervals 1 2 3 3

⁎⁎⁎

Health

− 0.265 (0.133) − 0.517⁎⁎ (0.275) − 0.429⁎⁎⁎ (0.194) − 0.150 (0.122) 0.160⁎⁎⁎ (0.063) − 0.097⁎⁎ (0.052) − 0.026 (0.051) − 0.079 (0.048) 650

− 0.194⁎⁎⁎ (0.075) 0.253⁎⁎ (0.144) − 0.070 (0.109) − 0.013 (0.063) − 0.071⁎⁎ (0.037) 0.177⁎⁎⁎ (0.029) − 0.009 (0.027) − 0.026 (0.026) 1826

− 2.309 to − 1.322 − 0.123 to 0.827

− 2.910 to −2.240 − 1.786 to −1.240 − 0.778 to −0.249 0.314 to 0.843

Note. SE in parentheses. ⁎⁎ p < 0.10. ⁎⁎⁎ p < 0.05.

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Table 4 Predicted probability of job satisfaction per types of part-time employment (N = 650). Job satisfaction

Dissatisfied (1)

Neutral (2)

Satisfied (3)

Good Bad Student Transition

6.2% 10.1% 15.3% 13.3%

67.3% 71.3% 72.1% 72.1%

26.5% 18.6% 12.6% 14.5%

of being sorted into each of the three categories of job satisfaction and each of the five categories of self-reported health while varying the type of part-time employment. As reported in Table 4, the highest probability of being in the “satisfied” response category is found in the good part-time group. Overall, in terms of the predicted probability of being in the “satisfied” response category, this analysis shows a progression from the lowest to the highest probabilities; from student, to transition, to bad, to good part-time employment. As shown, the probability of being in the highest category of job satisfaction is more than double in good relative to student part-time employment. A similar analysis was conducted with the five categories of self-reported health ranging from “not healthy” (1) to “healthy” (5). As can be viewed in the probabilities reported in Table 5, the effect of being in good relative to bad part-time employment is about a seven percentage-point difference in the probability of being in the highest level of self-reported health. We can also see a youth effect for student part-time employment with the probability of being in the healthiest level being higher than in any other group. (See Table 6.) 4. Discussion Qualifying full-time employment as good and part-time employment as bad is a simplification that is clearly challenged by the findings of this study. The dualism previously reported in part-time work (Tilly, 1992) is again a simplification in need of further scrutiny. What appears to be a better reflection of modern employment relations is a wider-range of part-time situations; some with more desirable features than others. In support of this outlook, with increasing professional and managerial part-time work, some protagonists have noted an expansion of part-time employment into the primary labor market (Campbell, Charlesworth, & Malone, 2011; Edwards & Robinson, 1999; Lawrence & Corwin, 2003; Lee, MacDermid, & Buck, 2000; Millward, Bryson, & Forth, 2000) and Martin and Sinclair (2007) aptly identified eight groups of part-time employees. This nuanced view of contemporary part-time work is reflected in our study that identified four types of part-time employment that are identifiable by their distinct sets of work characteristics and role occupancy profiles. The clearest distinction stemming from our work is the contrast between good and bad part-time employment. Student part-time is another distinct type with its own features whereas transition part-time reflects an early career stage with some potential for growth. As such, both student and transition part-time employment might be qualified as “not so sad” as they suggest a rather difficult situation, but one with some potential for a better future. These interpretations are further supported by our examination of their antecedents and outcomes. 4.1. Research implications Ashford, George, and Blatt (2007) called for more research on job quality within nonstandard employment. The identification in this study of four types of part-time employment with contrasting work characteristics and patterns of involvement in school, family, and work roles is responsive to this call. Our findings suggest that organizational research that implicates a substantial representation of part-time employment would gain from careful consideration of which types of part-time employment are included in the sampling frame. This is important because different types of part-time employment involve different configurations of individual role-occupancy profiles and work characteristics. As such, part-time work is likely to be a quite different experience and yield quite different research outcomes depending on whether it is good, bad, student or transition part-time work. Our study further underscores the need to consider a configuration of characteristics in making the determination of what type of part-time employment is involved in one organizational context or another. It would not be sufficient to rely solely on wage level or the amount of flexibility involved in a part-time work situation to make that determination. To better grasp what is going on, it would Table 5 Predicted probability for health per types of part-time employment (N = 1826). Health

Not Healthy (1)

(2)

(3)

(4)

Healthy (5)

Good Bad Student Transition

0.2% 0.4% 0.1% 0.3%

4.1% 5.9% 2.3% 4.7%

19.4% 23.7% 14.2% 21.0%

41.0% 41.5% 38.3% 41.3%

35.3% 28.4% 45.0% 32.7%

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Table 6 Partial descriptive statistics. Dichotomous variables

Category coded 1

Percentage of cases coded 1

Gender (male) Partner Parent Student Job elsewhere Permanent Supervision

Male Couples Yes Yes Yes Yes Yes

25% 56% 56% 25% 14% 50% 14%

Categorical variable

Number of categories

Approximate percentage per categories

Age Seniority Work experience Income contribution Work hours Pay level Flexibility

5 5 5 4 3 5 5

20% 20% 20% 25% 33% 20% 20%

Categorical variable

Number of categories

Percentage per categories (low to high)

Education Education required Experience required N

5 4 4 1826

17%/32%/29%/17%/6% 33%/31%/21%/15% 42%/28%/21%/10%

be advisable to also consider role occupancy profiles and a host of other work characteristics. As such, a configurational perspective appears better suited for a task such as this one that involves addressing some of the inherent complexities of modern employment relationships. This brings us back to the question of why it is important for research in various areas to distinguish types of part-time employment. For research on gender and occupations, beyond the known fact that a greater percentage of women are in part-time relative to full-time employment (OECD, 2017), our findings indicate that higher percentages of men are in student and transition relative to good part-time employment. The perspective of gender inequality might therefore be more meaningful for distinguishing full-time and part-time employment (MacDonald et al., 2009) than it is for distinguishing good from bad part-time employment. Significant differences between good, student, and transition part-time employment, however, point to new research directions as they suggest that men more than women are gaining some early work experience that may subsequently be leveraged for career progression. For research relating age or life stages to career stages or career success, it now seems important to consider that older workers tend to be more involved in bad relative to good part-time employment and that younger workers tend to be more involved in student and transition relative to good part-time employment. Although meta-analytic findings indicate a positive association between age and objective career success (Ng et al., 2005), our findings point to different outcomes in the realm of part-time employment. The pattern is quite clear, younger adults tend to be in “not so sad” student and transition part-time whereas older adults tend to be in bad part-time employment. Human capital variables that were previously shown to be consistently associated with objective and subjective career success (Ng et al., 2005), were significantly associated in this study with the probability of being in good relative to bad, student or transition part-time employment. This parallels research that more broadly associates human capital accumulation to better labor market outcomes (Becker, 1994) and better models good part-time employment as requiring more education, experience, and seniority. It underscores the value of human capital development for positive career outcomes also within the realm of part-time employment; even if this means suffering through student part-time employment. The research implications of this study relative to the outcomes of part-time employment not only support the four-class typology in terms of nomological validity, but also research in general associating job quality to job satisfaction and health (Humphrey et al., 2007; Parker et al., 2017). One clear implication of these findings is that future comparisons of full- and part-time employment might also consider the diversity of part-time employment situations and possibly undertake to compare good full-time to good part-time employment and bad full-time to bad part-time employment to better capture true differences in employment status rather than differences in job quality. A finer analysis might also be gained in this stream of research by considering the full spectrum of 137

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parameters that formed the template for the analysis of part-time employment configurations (Fig. 1) as they were found to be useful in this study and may provide a basis for future research.

4.2. Practical implications For individuals considering part-time employment as an occupational choice, our typology may provide a basis for evaluating the options that are out there. First, just knowing that there is such a thing as good part-time work is important for those who cannot or do not wish to be in full-time employment. Second, understanding that the accumulation of human capital generally leads to good part-time employment may be a source of motivation for pursuing educational credentials. A third implication for individuals is that part-time employment situations are not only what they are because of work characteristics, but that they are also formed by people and their role occupancy profiles. It may also be relevant for individuals to reflect upon their role occupancy in terms of more or less flexible attachments and the resources they have access to. These considerations are especially important in light of the finding that different part-time employment types are associated with job satisfaction and health. For managers in organizations that employ part-time workers, this study provides a template for a more complete analysis of different part-time employment situations; one that integrates role occupancy profiles and work characteristics. Although work design decisions result from numerous factors at multiple levels of analysis (Parker et al., 2017), managers may benefit from having a wider range of options when considering the design of part-time work. For instance, with an aging workforce, some managers may see the need to recruit more experienced workers and thereby initiate a transition from student to another form of part-time employment with work characteristics that are better aligned with the role occupancy profiles of this segment of the population. This would require serious consideration of how to adjust work characteristics to evolving role occupancy profiles as well as the preferences and constraints that might be involved when hiring older male and female employees into part-time positions. Finally, for managers dealing with increasing rates of health-related absenteeism, our findings suggest that the quality of part-time work might be looked into given that bad relative to good part-time work was clearly associated with lower self-reported overall health. This study also touches upon some societal concerns about quality of employment. Media reports generally applaud job creation, especially the creation of full-time jobs that are viewed as good jobs. Moreover, women are considered discriminated against because of their stronger representation in part-time employment. Although we would not challenge the value of good full-time employment nor would we argue the absence of discrimination, our findings do favour a more mitigated view as it would seem that some part-time employment qualifies as good. If media reports and policy decisions were to better address the diversity of part-time employment types, nations might better address job creation to foster quality within part-time employment.

4.3. Limitations and future research An important consideration in part-time employment research is whether or not it is voluntary and working fewer hours than desired would qualify part-time work as a form of underemployment (Allan et al., 2016; Duffy et al., 2016; Feldman, 1996). Although our study is grounded in research on job quality more than in research addressing employment discrepancies, there does seem to be an opportunity for a better integration of these streams of research. Job satisfaction and health were assessed in this study with single-item measures that are presumed to have low reliability. This limitation should however be considered in light of findings showing that single-item measures of job satisfaction have adequate validity (Wanous, Reichers, & Hudy, 1997) and are most appropriate for comparisons of the job satisfaction of workers in different occupations (Oshagbemi, 1999) or when the sampled population is diverse (Fuchs & Diamantopoulos, 2009). Given the sample of this study included workers from a diversity of occupations, the use of a single-item measure of job satisfaction may indeed have been the best approach. Health research has also supported the use of single-item measures of overall health (see Bowling, 2005, for a brief review). Moreover, having two outcomes with interpretable associations to types of part-time employment further supports the use of single-item measures.

5. Conclusion This study advanced a typology of part-time employment based on data from a population survey. The model that includes good, bad, student, and transition part-time employment had interpretable patterns of work characteristics and role occupancy profiles. As such, the attraction-selection-retention theoretical perspective was helpful as it turned out that both individual and organizational factors together provided a more complete picture of part-time employment than what had previously been achieved. We found it useful as well to consider the flexibility and the resources available to individuals involved in part-time employment. Demographic and human capital variables were significantly associated with the probability of being in one or another part-time employment type. Finally, both job satisfaction and health were associated in meaningful way to part-time employment types.

Acknowledgement The authors would like to thank Statistics Canada for the data and assistance that made this study possible. 138

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References Allan, B. A., Duffy, R. D., & Blustein, D. L. (2016). Under (and over) employment: Measurement and correlates of employment discrepancy. The Counseling Psychologist, 44, 815–840. http://dx.doi.org/10.1177/0011000016654766. Arulampalam, W., Booth, A. L., & Bryan, M. L. (2004). Training in Europe. Journal of the European Economic Association, 2, 346–360. http://dx.doi.org/10.1162/ 154247604323068041. Ashford, S. J., George, E., & Blatt, R. (2007). Old assumptions, new work: The opportunities and challenges of research on nonstandard employment. Academy of Management Annals, 1, 65–117. http://dx.doi.org/10.1080/078559807. Bardasi, E., & Gornick, J. C. (2008). Working for less? Women's part-time wage penalties across countries. Feminist Economics, 14, 37–72. https://doi.org/10.1080/ 13545700701716649. Becker, G. (1994). Human capital: A theoretical and empirical analysis with special reference to education (3rd ed.). Chicago: University of Chicago Press. Beham, B., Präg, P., & Drobnič, S. (2012). Who's got the balance? A study of satisfaction with the work-family balance among part-time service sector employees in five western European countries. International Journal of Human Resource Management, 23, 3725–3741. http://dx.doi.org/10.1080/09585192.2012.654808. Bidwell, M., Briscoe, F., Fernandez-Mateo, I., & Sterling, A. (2013). The employment relationship and inequality: How and why changes in employment practices are reshaping rewards in organizations. Academy of Management Annals, 7, 61–121. http://dx.doi.org/10.1080/19416520.2013.761403. BLS (2014, November). The employment situation – October 2014 [Online statistical report by the Bureau of Labor Statistics]. . Retrieved from http://www.bls.gov/ news.release/pdf/empsit.pdf. Bowling, A. (2005). Just one question: If one question works, why ask several? Journal of Epidemiology & Community Health, 59, 342–345. http://dx.doi.org/10.1136/ jech.2004.021204. Brookings Institute (2007). Better workers for better jobs: Improving worker advancement in the low-wage labor market – The Hamilton project. Washington, DC: Brookings Institute Press. Broschak, J. P., & Davis-Blake, A. (2006). Mixing standard work and nonstandard deals: The consequences of heterogeneity in employment arrangements. Academy of Management Journal, 49, 371–393. http://dx.doi.org/10.5465/AMJ.2006.20786085. Broschak, J. P., Davis-Blake, A., & Block, E. S. (2008). Nonstandard, not substandard: The relationship among work arrangements, work attitudes, and job performance. Work and Occupations, 35, 3–43. http://dx.doi.org/10.1177/0730888407309604. Campbell, I., Charlesworth, S., & Malone, J. (2011). Part-time of what? Job quality and part-time employment in the legal profession in Australia. Journal of Sociology, 48, 149–166. http://dx.doi.org/10.1177/1440783311408970. Canada, S. (2017). Government of Canada, Statistics Canada, CANSIM, table 282-0002. Retrieved from http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/ cst01/labor12-eng.htm. Chadwick, C., & Flinchbaugh, C. (2016). The effects of part-time workers on establishment financial performance. Journal of Management, 42, 1635–1662. http://dx. doi.org/10.1177/0149206313511116. Charlesworth, S., & Whittenbury, K. (2007). ‘Part-time and part-committed’?: The challenges of part-time work in policing. Journal of Industrial Relations, 49, 31–47. http://dx.doi.org/10.1177/0022185607072237. Clark, S. L., & Muthén, B. (2009). Relating latent class analysis results to variables not included in the analysis. Retrieved from http://www.statmodel.com/download/ relatinglca.pdf. Delbridge, R., & Fiss, P. C. (2013). Styles of theorizing and the social organization of knowledge. Academy of Management Review, 38, 325–331. http://dx.doi.org/10. 5465/amr.2013.0085. Dick, P. (2010). The transition to motherhood and part-time working: Mutuality and incongruence in the psychological contracts existing between managers and employees. Work, Employment and Society, 24, 508–525. http://dx.doi.org/10.1177/0950017010371648. Dick, P., & Hyde, R. (2006). Consent as resistance, resistance as consent: Re-reading part-time professionals' acceptance of their marginal position. Gender, Work and Organization, 13, 543–564. http://dx.doi.org/10.1111/j.1468-0432.2006.00322.x. Doeringer, P. B., & Piore, M. J. (1975). Unemployment and the “dual labor market”. The Public Interest, 38(Winter), 67–79. Duffy, R. D., Blustein, D. L., Diemer, M. A., & Autin, K. L. (2016). The psychology of working theory. Journal of Counseling Psychology, 63, 127–148. http://dx.doi.org/ 10.1037/cou0000140. Duncan, C., & Loretto, W. (2004). Never the right age? Gender and age-based discrimination in employment. Gender, Work and Organization, 11, 95–115. http://dx.doi. org/10.1111/j.1468-0432.2004.00222.x. Edwards, C., & Robinson, O. (1999). Managing part-timers in the police service: A study of inflexibility. Human Resource Management Journal, 9, 5–18. http://dx.doi. org/10.1111/j.1748-8583.1999.tb00207.x. Erikson, E. H. (1968). Identity: Youth and crisis (no. 7). New York: WW Norton & Company. ESDC (2014, November). Indicators of well-being in Canada. Employment and social development Canada. [online statistical report]. Retrieved from http://www4. hrsdc.gc.ca/[email protected]?iid=13#M_6. European Foundation for the Improvement of Living and Working Conditions (2007). Teamwork and high performance work organization. Retrieved from https:// www.eurofound.europa.eu/observatories/eurwork/articles/working-conditions/teamwork-and-high-performance-work-organisation. Eurostat (2017). Statistics explained: Employment statistics. Retrieved from http://ec.europa.eu/eurostat/statistics-explained/index.php/Employment_statistics#Parttime_work. Fagan, C. (2001). Time, money and the gender order: Work orientations and working-time preferences in Britain. Gender, Work and Organization, 8, 239–266. http:// dx.doi.org/10.1111/1468-0432.00131. Faragher, E. B., Cass, M., & Cooper, C. L. (2005). The relationship between job satisfaction and health: A meta-analysis. Occupational and Environmental Medicine, 62, 105–112. http://dx.doi.org/10.1136/oem.2002.006734. Feldman, D. C. (1990). Reconceptualizing the nature and consequences of part-time work. Academy of Management Review, 15, 103–112. http://dx.doi.org/10.5465/ AMR.1990.4308279. Feldman, D. C. (1996). The nature, antecedents and consequences of underemployment. Journal of Management, 22, 385–407. http://dx.doi.org/10.1016/S01492063(96)90030-6. Finkelstein, L. M., Burke, M. J., & Raju, N. S. (1995). Age discrimination in simulated employment contexts: An integrative analysis. Journal of Applied Psychology, 80, 652–663. https://doi.org/10.1037/0021-9010.80.6.652. Fuchs, C., & Diamantopoulos, A. (2009). Using single-item measures for construct measurement in management research. Die Betriebswirtschaft, 62, 195–210. Gringart, E., Helmes, E., & Speelman, C. P. (2005). Exploring attitudes toward older workers among Australian employers: An empirical study. Journal of Aging & Social Policy, 17, 85–103. http://dx.doi.org/10.1300/J031v17n03_05. Hakim, C. (1991). Grateful slaves and self-made women: Fact and fantasy in women's work orientations. European Sociological Review, 7, 101–121. http://dx.doi.org/ 10.1093/oxfordjournals.esr.a036590. Higgins, C., Duxbury, L., & Johnson, K. L. (2000). Part-time work for women: Does it really help balance work and family? Human Resource Management, 39, 17–32. http://dx.doi.org/10.1002/(SICI)1099-050X(200021). Hoque, K., & Kirkpatrick, I. (2003). Non-standard employment in the management and professional workforce: Training, consultation and gender implications. Work, Employment and Society, 17, 667–689. http://dx.doi.org/10.1177/0950017003174004. Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Journal of Applied Psychology, 92, 1332–1356. http://dx.doi.org/10.1037/0021-9010.92.5.1332. Johns, G. (2006). The essential impact of context on organizational behavior. Academy of Management Review, 31, 386–408. http://dx.doi.org/10.5465/AMR.2006. 20208687. Kalleberg, A. L. (2000). Nonstandard employment relations: Part-time, temporary, and contract work. In K. S. Cook, & J. Hagen (Vol. Eds.), Annual Review of Sociology.

139

Journal of Vocational Behavior 104 (2018) 128–140

V.Y. Haines et al.

Vol. 26. Annual Review of Sociology (pp. 341–365). Palo Alto, CA: Annual Reviews. http://dx.doi.org/10.1146/annurev.soc.26.1.341. Katz, D., & Kahn, R. L. (1978). The social psychology of organizations (2nd ed.). New York: Wiley. Knox, A., Warhurst, C., & Pocock, B. (2011). Job quality matters. Journal of Industrial Relations, 53, 5–11. http://dx.doi.org/10.1177/0022185610390293. Lawrence, T. B., & Corwin, V. (2003). Being there: The acceptance and marginalization of part-time professional employees. Journal of Organizational Behavior, 24, 923–943. http://dx.doi.org/10.1002/job.229. Lee, M. D., MacDermid, S. H., & Buck, M. L. (2000). Organizational paradigms of reduced-load work: Accommodation, elaboration, and transformation. Academy of Management Journal, 43, 1211–1226. http://dx.doi.org/10.2307/1556346. Levinson, D. J. (1986). A conception of adult development. American Psychologist, 41, 3–13. http://dx.doi.org/10.1037/0003-066X.41.1.3. Loughlin, C., & Murray, R. (2013). Employment status congruence and job quality. Human Relations; Studies Towards the Integration of the Social Sciences, 66, 529–553. http://dx.doi.org/10.1177/0018726712460705. Lyonette, C., Baldauf, B., & Behle, H. (2010). Quality part-time work: A review of the evidence. London: Government Equality Office. MacDonald, P., Bradley, L., & Brown, K. (2009). ‘Full-time is a given here’: Part-time versus full-time job quality. British Journal of Management, 20, 143–157. http://dx. doi.org/10.1111/j.1467-8551.2008.00560.x. Martin, J. E., & Sinclair, R. R. (2007). A typology of the part-time workforce: Differences on job attitudes and turnover. Journal of Occupational and Organizational Psychology, 80, 301–319. http://dx.doi.org/10.1348/096317906X113833. Miller, H. E., & Terborg, J. R. (1979). Job attitudes of part-time and full-time employees. Journal of Applied Psychology, 64, 380–386. https://doi.org/10.1037/00219010.64.4.380. Millward, N., Bryson, A., & Forth, J. (2000). All change at work: British employment relations 1980–98. London: Routledge. Moen, P., & Yu, Y. (2000). Effective work/life strategies: Working couples, work conditions, gender, and life quality. Social Problems, 47, 291–326. http://dx.doi.org/ 10.2307/3097233. Ng, T. W. H., Eby, L. T., Sorensen, K. L., & Feldman, D. C. (2005). Predictors of objective and subjective career success: A meta-analysis. Personnel Psychology, 58, 367–408. http://dx.doi.org/10.1111/j.1744-6570.2005.00515.x. OECD (2010). OECD employment outlook 2010: Moving beyond the job crisis. Organization for economic co-operation and development. OECD (2017, January). Labour force statistics. Organization for economic co-operation and development. Retrieved from http://stats.oecd.org/Index.aspx? DatasetCode=INVPT_I. Oshagbemi, T. (1999). Overall job satisfaction: How good are single versus multiple-item measures? Journal of Managerial Psychology, 14, 388–403. http://dx.doi.org/ 10.1108/02683949910277148. Osterman, P. (2010). Job design in the context of the job market. Journal of Organizational Behavior, 31, 401–411. http://dx.doi.org/10.1002/job.639. Pak, M. (2013). Le travail à temps partiel. Synthèse Stat, 4, 1–41. Parker, S. K., Van Den Broeck, A., & Holman, D. (2017). Work design influences: A synthesis of multilevel factors that affect the design of jobs. Academy of Management Annals, 11, 267–308. http://dx.doi.org/10.5465/annals.2014.0054. Rabinowitz, S., & Hall, D. T. (1986). Changing correlates of job involvement in three career stages. Journal of Vocational Behavior, 18, 138–144. http://dx.doi.org/10. 1016/0001-8791(81)90002-6. Robotham, D. (2012). Student part-time employment: Characteristics and consequences. Education and Training, 54, 65–75. http://dx.doi.org/10.1108/ 00400911211198904. Rousseau, D. M. (1989). Psychological and implied contracts in organizations. Employee Rights and Responsibilities Journal, 2, 121–139. Rousseau, D. M. (1995). Psychological contracts in organizations: Understanding written and unwritten agreements. Thousand Oaks, CA: Sage. Saba, T., Blouin, M., & Lemire, L. (2006). Modalités de travail à temps plein ou partiel et son influence sur les attitudes et comportements au travail: L'effet médiateur de la violation du contrat psychologique. Canadian Journal of Administrative Sciences, 23, 318–333. http://dx.doi.org/10.1111/j.1936-4490.2006.tb00610.x. Schneider, B. (1987). The people make the place. Personnel Psychology, 40, 437–453. http://dx.doi.org/10.1111/j.1744-6570.1987.tb00609.x. Senter, J. L., & Martin, J. E. (2007). Factors affecting turnover in different groups of part-time workers. Journal of Vocational Behavior, 71, 45–68. http://dx.doi.org/10. 1016/j.jvb.2007.03.004. Shockey, M. L., & Mueller, C. W. (1994). At-entry differences in part-time and full-time employees. Journal of Business and Psychology, 8, 355–364. Sinclair, R. R., Martin, J. E., & Michel, R. P. (1999). Full-time and part-time subgroup differences in job attitudes and demographic characteristics. Journal of Vocational Behavior, 55, 337–357. http://dx.doi.org/10.1006/jvbe.1999.1686. Smith, N., & McDonald, P. (2016). Facilitating sustainable professional part-time work: A question of design? Journal of Management & Organization, 22, 205–223. http://dx.doi.org/10.1017/jmo.2015.27. Snider, S. (1995). Characteristics of the part-time workforce and part-time employee participation in health and pension benefits. Journal of Labor Research, 16, 239–248. http://dx.doi.org/10.1007/BF02685753. Steffy, B. D., & Jones, J. W. (1990). Differences between full-time and part-time employees in perceived role strain and work satisfaction. Journal of Organizational Behavior, 11, 321–329. http://dx.doi.org/10.1002/job.4030110407. Thoits, P. A. (1986). Multiple identities: Examining gender and marital status differences in distress. American Sociological Review, 51, 259–272. http://www.jstor.org/ stable/2095520. Thoits, P. A. (1992). Identity structures and psychological well-being: Gender and marital status comparisons. Social Psychology Quarterly, 55, 236–256. http://www. jstor.org/stable/2786794. Thorsteinson, T. J. (2003). Job attitudes of part-time vs. full-time workers: A meta-analytic review. Journal of Occupational and Organizational Psychology, 76, 151–177. http://dx.doi.org/10.1348/096317903765913687. Tilly, C. (1992). Dualism in part-time employment. Industrial Relations, 31, 330–347. http://dx.doi.org/10.1111/j.1468-232X.1992.tb00312.x. Tilly, C. (1996). Half a job: Bad and good part-time jobs in a changing labor market. Philadelphia: Temple University Press. Wakefield, D. S., Curry, J. P., Mueller, C. W., & Price, J. L. (1987). Differences in the importance of work outcomes between full-time and part-time hospital employees. Journal of Occupational Behavior, 8, 25–35. http://dx.doi.org/10.1002/job.4030080104. Wanous, J. P., Reichers, A. E., & Hudy, M. J. (1997). Overall job satisfaction: How good are single-item measures? Journal of Applied Psychology, 82, 247–252. http:// dx.doi.org/10.1037/0021-9010.82.2.247. Warren, T., & Walters, P. (1998). Appraising a dichotomy: A review of ‘part-time/full-time’ in the study of women's employment in Britain. Gender, Work and Organization, 5, 102–118. http://dx.doi.org/10.1111/1468-0432.00049. Wittmer, J. L. S., & Martin, J. E. (2011). Effects of scheduling perceptions on attitudes and mobility in different part-time employee types. Journal of Vocational Behavior, 78, 149–158. http://dx.doi.org/10.1016/j.jvb.2010.07.004.

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