Money matters,but what else? Mature worker motives and the importance of gender,age,socioeconomic status and age-inclusive HR practices

Abstract

Policies encouraging extended workforce participation mainly focus on financial motives, but socioemotional selectivity theory and research suggest that mature worker motives are multifaceted, with emotionally meaningful goals gaining importance with age. We adopt a person-centred approach using latent class analysis of survey data from 1501 Australian workers aged 45 years and over. Two motivational profiles based on patterns of motives were identified, which we term income-dominant (income is the main reason) and socioemotional-income (socioemotional reasons are dominant, but income is important too). Contrary to expectations, we found no evidence of a socioemotional-dominant profile. This provides new theoretical insights, as it suggests that even though socioemotional reasons may increase in importance with age, financial reasons remain important to most mature workers, especially those who may view work as being transactional. Being female, older, and having higher socioeconomic status and age-inclusive HR policies increase the odds of having a socioemotional-income rather than income-dominant profile. The socioemotional-income subgroup had lower turnover intentions and later desired retirement ages than the income-dominant subgroup, highlighting the potential for more socioemotionally focused policies and practices to encourage extended workforce participation.

JEL Classification:

J26, M12, M54

Keywords

Age-inclusive HR practices employee motivation older workers working longer

1. Introduction

Research suggests that longer working lives can benefit both individuals and organisations, resulting in better financial, health and well-being outcomes for employees, as well as better performance, reduced recruitment costs, and retention of corporate knowledge and skills for organisations (Aitken and Singh, 2023; Fisher et al., 2016a; Kachan et al., 2015; Wickrama et al., 2013). Global population ageing has resulted in a policy focus on extending working lives and delaying the age at which people retire from the paid labour market (Caines et al., 2020; Nagarajan and Sixsmith, 2023; Winefield, 2002) to generate productivity gains (Organisation for Economic Co-operation and Development (OECD), 2020). Consequently, better understanding mature workers’ motives for continuing work is important for individuals, employers and governments.

In Australia, labour market participation rates among mature workers, defined by the Australian Bureau of Statistics (ABS, 2005) as those aged 45 and above, have increased in recent decades, driven mainly by government policies designed to encourage mature workers to remain in or re-enter the labour market. Measures such as increasing pension eligibility ages, wage subsidies for employers hiring mature workers and support through the employment services system (Caines et al., 2020; Fideler, 2020; Henkens, 2022) have largely focused on extrinsic, financial motives for continuing work. However, the rate of increase in participation has begun to plateau (Chomik and Khan, 2021; Neumark and Yen, 2020), suggesting that it may be valuable to investigate other motives for continuing work.

Results from a survey of 1502 workers in the United States aged 45–74 found that the top two reasons for planning to work beyond retirement were enjoyment derived from working and the need for extra money (American Association of Retired Persons (AARP), 2014), highlighting the importance of both socioemotional (emotionally meaningful) and financial reasons. Although workers are often assumed to have either extrinsic (e.g. financial need) or intrinsic (e.g. enjoyment) reasons for continuing work, emerging evidence suggests that workers can have both extrinsic and intrinsic reasons (Smyer and Pitt-Catsouphes, 2007). Yet little is known about how different reasons might combine to motivate prolonged workforce participation. This study aims to address these gaps and contribute to the literature on extended working lives in several ways. First, we redirect research attention that has typically focused on reasons for retirement towards a better understanding of mature workers’ reasons for continuing work. Existing research on mature worker motives has focused on factors predicting retirement, at either the individual or organisational level (e.g. Fisher et al., 2016a; Scharn et al., 2018; Wetzel et al., 2022). However, as more workers expect to continue working for longer before and/or after retirement (American Advisors Group (AAG), 2021; Chomik and Khan, 2021), it is helpful to examine their motives for continuing work (more broadly than simply their motives for retirement) (Shacklock et al., 2009). Although there are overlaps between reasons for retirement and reasons for continuing work, specifically focussing on reasons for continuing work has the potential to better encompass groups of workers for whom the concept or experience of retirement may be markedly different. These include workers (often females) with interrupted or precarious patterns of work participation who may never have engaged in full-time career work or have done so at relatively older ages due to childrearing or other care responsibilities (Dendinger et al., 2005; Loretto and Vickerstaff, 2015). This also includes the growing group of workers experiencing diverse pathways into and out of retirement, including ‘working retirees’, who take up or continue paid employment after retiring from their career work (Dingemans et al., 2017; Loh, 2015).

Second, we employ a person-centred approach using latent class analysis (LCA) to identify distinct motivational profiles based on the idea that workers are likely to have multiple different reasons for continuing work simultaneously and that subgroups of workers may be identified based on meaningful patterns or combinations of reasons (Bouckenooghe et al., 2019; Knight et al., 2022; Nurmeksela et al., 2023). In doing so, we contribute to theory and practice by modelling more complex and holistic motivational profiles than could be afforded by previous studies that have tended to take a variable-centred approach, where different reasons are analysed as separate, independent variables, and the possibility of workers simultaneously having a combination of multiple different reasons is overlooked (Howard et al., 2016; Kuvaas et al., 2017). One exception is Hess et al. (2021) who adopted a person-centred approach to analyse data collected in 2013 from 744 German workers aged 54–65 who could imagine working after retirement. While about 41% of their sample had a financially driven motivational profile, the majority had a more socioemotional motivational profile, being either contact and fun-driven (32%), generativity-driven (15%) or recognition-driven (11%). As the authors note, their analysis was limited to workers who want to work after retirement, which may have underestimated the importance of financial motives and the proportion of workers who may have to work for financial reasons. Our study extends this research by analysing reasons for continuing work more broadly, rather than specifically in retirement, and among a more diverse group of workers aged 45 and up. By modelling motivational profiles that combine different reasons, person-centred approaches can also support the implementation of more effective employer and government policies and measures aimed at influencing whole motivational profiles, rather than specific types of motivation individually (Howard et al., 2016).

Finally, we also investigate whether individual and organisational factors that have previously been linked to reasons for continuing working in later life, such as age, gender, socioeconomic status (measured in terms of income and education level) and age-inclusive HR practices, can be used to distinguish which mature workers belong to each motivational profile, and whether motivational profiles relate to important work outcomes such as desired retirement age and turnover intentions. Thus, our person-centred approach has the potential to guide interventions tailored not only to motivational profiles that may include a combination of reasons rather than singular reasons (Howard et al., 2016) but also to specific subgroups of mature workers who are more likely to belong to one motivational profile over another.

2. Exploring motivational profiles, individual and organisational antecedents, and potential interactions

2.1. Exploring motivational profiles of mature workers

Socioemotional selectivity theory (SST; Carstensen, 1995, 2021), a lifespan theory of motivation, states that whenever time is perceived as being limited or constrained rather than limitless or expansive, goal priorities tend to shift from future-focused, instrumental exploration or knowledge acquisition goals towards more proximal, emotionally meaningful (or socioemotional) goals. A core tenet of SST is that humans are inherently social beings, and our choice of social interactions and activities is often a function of our future time perspective. Changes in the perception of time from being expansive to limited can be elicited by natural developmental processes related to ageing, as well as by events that signal time limitations, such as the death of a loved one, having a serious or terminal illness, or even planning to move to a different location. Carstensen (1995) proposed that the three primary social motives of emotion regulation, development and maintenance of self-concept, and information seeking tend to vary in their primacy throughout the lifespan. From around middle age onwards, emotion regulation becomes increasingly salient while information seeking becomes less salient, and maintaining rather than developing self-concept becomes more important. According to SST, as individuals age and their time horizons become more limited, they become more selective with their goals and motivations such that positive, emotionally meaningful goals and experiences are increasingly prioritised over exploration goals (Carstensen, 1995, 2021).

SST was originally developed to explain the seemingly paradoxical observation that older adults report relatively high levels of social and emotional well-being despite facing significant age-related changes in health and shrinking social networks (Carstensen, 2021). However, a growing body of research has also begun examining mature workers from an SST perspective (e.g. Burmeister et al., 2020; Kim and Kang, 2017; Kooij and Zacher, 2016; Piszczek and Pimputkar, 2021). The focus in SST on the importance of emotionally meaningful goals in later life is well supported in the literature on mature worker motives. For example, Mor-Barak’s (1995) theory-based research on the meaning of work specifically for mature workers identified four main reasons for continuing work, three of which could be classed as emotionally meaningful: social reasons (e.g. social contact or interaction), personal reasons (e.g. personal satisfaction or a sense of pride) and generative reasons (e.g. sharing knowledge with others), which tend not to emerge until midlife (Dendinger et al., 2005; Kanfer et al., 2013; Mor-Barak, 1995). The other main reason for continuing work was financial reasons.

Different reasons for continuing work can be broadly classified as either extrinsic or intrinsic in nature (Kuvaas et al., 2017; Van den Berg, 2011). Extrinsic reasons include tangible incentives like income and other financial rewards that have instrumental value, while intrinsic reasons include intangible, emotionally meaningful incentives that have social, personal or psychological value like being socially connected, enjoying the work, wanting to stay productive and transferring knowledge to future generations (Kuvaas et al., 2017; Van den Berg, 2011). Research suggests that compared to extrinsic reasons, intrinsic reasons tend to yield more positive work outcomes such as improved work performance, reduced turnover, greater willingness to continue working and later retirement ages among mature workers (Brougham and Walsh, 2009; Kuvaas et al., 2017; Van Dam et al., 2009).

Consistent with SST, Kooij et al.’s (2011) meta-analysis of 86 studies relating age to work-related motives found that compared to younger workers, older workers reported stronger intrinsic motives related to accomplishment or achievement, skill utilisation and work enjoyment, but lower extrinsic motives related to financial compensation, recognition, advancement or promotion. Also supporting the SST claim that exploration and knowledge acquisition goals decrease in importance with age, they found that compared to younger workers, older workers reported lower growth motives related to new learning or development, advancement or promotion (Kooij et al., 2011). Thus, SST provides a useful framework for predicting general age-related changes in work motives among mature workers as a homogeneous cohort, but it does not help explain within-cohort differences that have been observed between workers in the same age cohort or life stage.

In their review of the literature, Smyer and Pitt-Catsouphes (2007) identified three distinct groups of mature workers: those who must work (e.g. for income or financial benefits), those who want to work (e.g. for social connection or enjoyment of work) and those who are working for both reasons. Those who wanted to work were more likely to have returned to work after retiring. In their survey of over 700 Canadian workers aged 50–70 years, Templer et al. (2010) found that while people in ‘career-jobs’ rated financial reasons as most important in their choices about continuing work, those in ‘bridge-jobs’ and self-employed respondents rated work fulfilment reasons as most important. Interestingly, generativity reasons were the least important in all three respondent groups.

As this research was variable-centred, it is not clear how these different reasons may combine to form different motivational profiles. Hess et al.’s (2021) person-centred research suggests that there may be up to four profiles, which they termed financially driven (41%), contact and fun-driven (32%), generativity-driven (15%) and recognition-driven (11%). However, the probabilities associated with selecting different reasons in each profile suggest that even in the financially driven profile, working for fun was as likely to be selected as a reason for wanting to continue work as working to earn money, supporting Smyer and Pitt-Catsouphes’ (2007) suggestion of a third motivational profile in which both financial and socioemotional reasons are important.

Consistent with prior research, we expect to find evidence of three motivational profiles in older workers. Rather than identifying profiles that are either extrinsic or intrinsic or combined, we seek to use a person-centred approach to identify how different motivations come together in different configurations. We expect all profiles to be combinations of motivations, and, consistent with SST, we expect socioemotional motivations to be present to some extent in all three profiles of mature workers. We expect one profile to reflect more extrinsic financial reasons, another to reflect more intrinsic socioemotional reasons, and one in which both financial and socioemotional reasons are of similar importance.

Hypothesis 1a: There is an income-dominant motivational profile where the main reasons for continuing work are financial.

Hypothesis 1b: There is a socioemotional-dominant motivational profile where the main reasons for continuing work are socioemotional.

Hypothesis 1c: There is a mixed motivational profile where the main reasons for continuing work are both financial and socioemotional.

The dearth of person-centred research examining the coexistence of extrinsic and intrinsic reasons for continuing work not only makes it difficult to predict the exact number of motivational profiles but it is also unclear how they may be shaped by individual and organisational factors, or how they might relate to important outcomes such as turnover intentions and intended retirement age. Hence, in addition to exploring how reasons for work combine into different motivational profiles, this article also explores how motivational profiles relate to individual-level (gender, age, socioeconomic status) and organisation-level (age-inclusive HR practices) factors and employee outcomes (turnover intentions, retirement age).

In the following sections, we discuss the proposed individual and organisational antecedents and outcomes of our proposed motivational profiles, extrapolating from the findings of existing variable-centred research.

2.2. Individual antecedents of motivational profiles

Individuals develop and change throughout the life course, and their reasons for working are likely to change accordingly (Baltes et al., 2019; Thrasher et al., 2016). For example, SST suggests that as individuals age, they will increasingly have more intrinsic, socioemotional reasons for continuing work. In addition, because they have had more time to accrue material wealth (Asher et al., 2017), mature workers may be less likely to be driven by financial reasons than younger workers. Considerable research and meta-analytic evidence suggests that intrinsic, socioemotional motives tend to become increasingly important with age, while extrinsic motives related to pay and promotion tend to become less important (Barnes-Farrell et al., 2019; Kooij et al., 2011; Kooij and Kanfer, 2019; Van den Berg, 2011). However, as previous research has tended to focus on narrow, later stage or single cohorts of mature workers (e.g. baby boomers; Hamilton and Hamilton, 2006), less is known about whether significant differences exist between different age subgroups among mature-age workers. The relatively broad age range of the mature workers in this study (aged 45 and above) enables us to examine if the relationship between age and motives commonly reported in the literature also applies to different age subgroups of mature workers. Consistent with both SST and prior research, older subgroups of mature workers are expected to indicate more socioemotional (intrinsic) reasons for continuing work than younger subgroups, while younger subgroups are expected to indicate more financial (extrinsic) reasons for continuing work than older subgroups.

Existing research shows that gender is also significantly related to different aspects of continuing to work (Fisher et al., 2016a; Tunney and Mulders, 2022). Compared to men, women are more likely to enter and exit the workforce multiple times throughout their working lives, driven by life events such as changes in marital status and childrearing (Andrea et al., 2022; Fujimoto et al., 2012). Moreover, their motives for returning or continuing to work may be more likely to change based on their life stage (Majeed et al., 2015). Consequently, women are more likely to experience career interruptions across the life course, engage in part-time or more precarious work (Majeed et al., 2015), and have lower pensions or retirement savings than men (Hamilton and Thomson, 2017), suggesting that mature women, more than men, may have financial reasons for continuing to work longer (Shacklock et al., 2009).

Even if women may be more financially motivated to continue working, less is known about whether intrinsic motives differ by gender, especially among mature workers. In a rare study examining how intentions to continue working vary by gender, Shacklock et al. (2009) found that women’s intentions to continue working were significantly related to personal relationships, work autonomy and flexibility, whereas men’s intentions were significantly related to the importance or significance of working. This research suggests that women and men may identify with motivational profiles differently, although more research is required to better understand how reasons for continuing work might vary between women and men.

Previous research suggests that socioeconomic factors such as education and income may also play a role in mature workers’ reasons for continuing work (Fisher et al., 2016a; Hess et al., 2021; Virtanen et al., 2022). For example, Fisher et al. (2016a) noted that education is consistently related to later retirement ages, as well as higher income occupations, which may mean that more highly educated workers are less likely to have extrinsic reasons such as financial need and more likely to have intrinsic reasons such as deriving satisfaction from the use of existing skills (Lord, 2004). In terms of income, the literature on retirement provides strong evidence that workers with lower income levels will be more motivated to continue working for financial (extrinsic) reasons, while having sufficient income tends to be associated with intrinsic work motivations (Fisher et al., 2016b; Hamilton and Hamilton, 2006). Individuals with higher education or income levels are also more likely to work in occupations or organisations that have more supportive working environments (Potočnik et al., 2009), which may not only explain the tendency towards working longer (Fisher et al., 2016a) but may also support more intrinsic reasons for continuing work.

Based on the variable-centred research findings discussed above, we expect that age, gender, education and income will each relate significantly to mature workers’ membership of different motivational profiles or configurations of reasons for continuing work. Specifically, we expect that being older, male, having a higher education or higher income will increase the likelihood of having a motivational profile that includes more intrinsic, non-financial, socioemotional reasons than extrinsic, financial reasons for continuing work.

Hypothesis 2: Compared to younger mature workers, older mature workers are less likely to have an income-dominant motivational profile and more likely to have a socioemotional-dominant or mixed motivational profile.

Hypothesis 3: Compared to women, men are less likely to have an income-dominant motivational profile and more likely to have a socioemotional-dominant or mixed motivational profile.

Hypothesis 4: Compared to mature workers with lower education and income levels, mature workers with higher education and income levels are less likely to have an income-dominant motivational profile and more likely to have a socioemotional-dominant or mixed motivational profile.

2.3. Organisational antecedents of motivational profiles

From an SST perspective, which states that socioemotional goals become increasingly important as individuals age, organisations that provide more opportunities for emotionally meaningful work and social interactions may be more likely to retain and perhaps even attract more intrinsically motivated mature workers who are willing to continue working for longer (Sacco et al., 2022). There is an emerging body of literature describing how employer attitudes and practices towards mature workers influence their experiences and satisfaction with their work and workplaces (Andrei and Parker, 2022; Farr-Wharton et al., 2023; Kunze et al., 2011; Teo et al., 2022). Organisational practices influence the work climate and set expectations for employee behaviours and attitudes (Bowen and Ostroff, 2004), and may, in turn, influence motivation to continue working (Pak et al., 2019). For example, Polat et al. (2017) found that human resource (HR) practices involving employee development were positively related to perceived development climate and psychological contract fulfilment. This, in turn, was associated with organisational commitment and work engagement, and subsequently to motivation to continue working beyond the standard retirement age among those aged between 40 and 63 years.

Despite some research on HR practices in relation to retirement timing, the focus has mostly been on flexible work arrangements and developmental workplace practices (Fisher et al., 2016a; Pak et al., 2019; Wilckens et al., 2022), with very few examining how age-related HR practices might relate to reasons for continuing work across different subgroups of mature workers. Recent research by Teo et al. (2022) has found that the use of age-related HR practices, in particular mature-age HR practices, positively relates to employee psychological well-being. Furthermore, it has also been suggested that age-inclusive HR practices could also be beneficial for mature workers and organisations (Andrei and Parker, 2022; Kilroy et al., 2022). Some research has begun examining these practices, which are aimed at reducing age differentiation and fostering employee development and opportunities to contribute, regardless of age (Berg and Piszczek, 2022; Boehm et al., 2014). This research shows that more age-inclusive HR practices can provide positive outcomes for organisations, including better performance and lower turnover intentions (Boehm et al., 2014). However, it is unknown how these practices might relate to the membership of different motivational profiles for continuing work.

Previous research suggests that age-inclusive HR practices signal information to employees about the employer’s intentions towards its workforce, which may in turn stimulate a reciprocal response from employees (Blau, 1964; Connelly et al., 2011). That is, as organisations adopt more age-inclusive HR practices, they signal to employees of all ages that they are valued, which can in turn encourage mature workers to adopt more intrinsic reasons for continuing work. We therefore expect that employees in organisations with more age-inclusive HR practices will be more likely to have a motivation profile that includes more intrinsic reasons than those in organisations with fewer age-inclusive HR practices.

Hypothesis 5: Compared to mature workers reporting fewer age-inclusive HR practices in their organisation, mature workers reporting more age-inclusive HR practices are less likely to have an income-dominant motivational profile and more likely to have a socioemotional-dominant or mixed motivational profile.

2.4. Exploring potential interactions

Most studies examining factors related to the decision to continue working analyse these factors individually and do not account for the potential interactions between them and how this might relate to different reasons for continuing work. Hence, in extending the current knowledge of mature worker motives for continuing work, we also examine the joint effects of the above individual and organisational antecedents. In particular, we focus on exploring the potential interactions involving gender given its centrality to work–life histories, experiences of work and retirement incomes (Baird and Williams, 2022; Blackburn et al., 2016; Fujimoto et al., 2012; Taylor et al., 2021).

Although women are more likely than men to cite financial reasons for continuing work (Templer et al., 2010), these gender differences may vary for different age subgroups of mature workers. Given that SST predicts that socioemotional reasons will be more prevalent among older than younger adults (Carstensen, 2021), gender differences in motivational profiles may therefore reduce with increasing age.

Gender may also interact with socioeconomic variables such as income and education. For example, a German study involving 1500 workers aged 55–65 found that while higher professional status women reported greater willingness to continue working in retirement than lower professional status women, there was no difference in willingness to continue working among men based on professional status (Micheel et al., 2010). As income was one of their key indicators of professional status (the other being position in the company hierarchy) and education is often highly correlated with professional status (Micheel et al., 2010), the effect of income on work motives may also be expected to be stronger for women than for men.

Thus, given both the centrality of gender to work–life trajectories and decisions to continue working in later life, gender is expected to interact with the other antecedent variables in how they relate to reasons for continuing work, though the expected direction of these interactions remains unclear. This study takes an important first step in exploring these potential interactions, proposing that the effects of age, education and income on socioemotional motives are likely to be stronger for women than for men.

Hypothesis 6: The effect of age, education, income and age-inclusive HR practices on motivational profile is likely to be stronger for women than for men.

3. Method

3.1. Design and participants

This study uses a cross-sectional research design and data from the 2019 Mature Workers in Organisations Survey (MWOS), a large-scale, national survey assessing mature workers’ perceptions of support in the workplace (Andrei et al., 2019). A private research company specialising in online recruitment of participants was used to recruit Australian residents who were actively employed and working for a minimum of 15 hours per week. As the focus of this survey was on organisational support, people working in organisations of all sizes were included but those who were self-employed were not included in the sample.

Participants were offered a financial incentive at the provider’s standard rates for filling in the survey. Several screening measures were embedded within the online survey to ensure the quality of the data collected (Ward et al., 2017; Ward and Meade, 2018). First, two items were included to filter out participants who did not pay attention to the specific content of the item (Ward and Meade, 2018). These items were placed between other items in the surveys and each of them required participants to respond in a pre-determined manner (e.g. ‘Please select strongly disagree for this item’). Second, a question at the end of the survey was used to explain the importance of only including data from participants who carefully filled in the survey. Participants who indicated that their data should not be used were excluded from further analysis. Third, we implemented a check for response time with a minimum cut-off of 2 seconds per item (Ward and Meade, 2018). Participants who were rushing were automatically screened out and data provided by them are not included in the final dataset.

For comparative purposes, adults of all ages were included in the initial sample, but mature workers aged 45 and over were deliberately oversampled. This resulted in 2009 (49% females, 51% males) Australian employees aged 18–81 (M = 49.38, SD = 12.83) who completed the MWOS Survey. Following the ABS’s (2005) definition of mature-age workers, this analysis focused on the sub-sample of 1501 (41% females, 59% males) participants aged 45 years and over (M = 55.39, SD = 7.84). Most participants fell into the 45–54 (44%) or 55–64 (44%) age group, with the remaining 12% falling into the 65 and over age group. Ten-year age groups were used to examine whether motivational profiles differ between different age subgroups of mature workers, while ensuring that each age group was sufficiently sampled.

3.2. Measures

The key demographic variables of interest in this analysis were gender (0 = male, 1 = female), age (in years), education (from 1 = some high school to 7 = postgraduate degree) and total weekly income (1 = low/less than AUD 1000, 2 = mid/AUD 1000 to 1999, 3 = high/AUD 2000 or more). Marital status (0 = single, 1 = married/living with partner), unpaid care responsibilities (0 = no, 1 = yes) and self-rated health (from 1 = poor to 5 = excellent) were also included in the model as background control variables that may relate to reasons for continuing work (Fisher et al., 2016a; Noone et al., 2018; O’Loughlin et al., 2017; Polat et al., 2017; Templer et al., 2010).

3.2.1. Reasons for continuing work

Participants were asked

Which of the following represent the main reasons for you to continue working? Please indicate all that apply: (1) I need the income; (2) I want to stay active and productive; (3) I enjoy it; (4) I want to stay involved with people; (5) It gives me a sense of purpose; and (6) I need the benefits.

Each reason scored 1 if selected, and 0 if not. This measure was adapted from the United States of Aging Survey (AARP, 2012), and the items included in this measure were the top six most frequent reasons selected by workers aged 60–64 years as reasons for why they were still working.

3.2.2. Age-inclusive HR practices

This eight-item scale¹ measured which age-inclusive management practices and programmes are available within the participant’s organisation (1 = not at all; 5 = a very large extent). Sample items included training (e.g. ‘Monitoring the skills of workers irrespective of their age and providing training to upgrade and maintain skills’), career development (e.g. ‘Opportunities for employees of all ages to take on challenging and meaningful new roles or work assignments’) and planning practices (e.g. ‘Phased retirement programmes that allow employees to ease into retirement’); Cronbach’s α = 0.95.

3.2.3. Outcome variables

Our analyses focused on two key outcomes: desired retirement age and turnover intention. Desired retirement age was assessed with the question ‘What is your desired retirement age in years?’ Turnover intention was assessed with a single-item measure by Spector et al. (1988) indicating agreement with the statement ‘I have seriously considered quitting my job in the last 6 months’ using a 5-point Likert-type scale (from 1 = strongly disagree to 5 = strongly agree). This one-item measure of turnover intentions has been previously used and found to be valid (Côté and Morgan, 2002).

3.3. Statistical analyses

Given our aim was to provide a more holistic and exploratory approach, we utilised an LCA using Mplus version 8.7 (Muthén and Muthén, 2017) to identify the number of distinct subgroups or profiles of responding to the six main reasons for continuing work. LCA involves running a series of models testing first one class, then two classes, then three classes, and so on until the optimal number of classes is identified. Following common practice, the optimal number of classes was guided by both statistical criteria and theory (Ram and Grimm, 2009). Statistical criteria included indices of model fit such as Akaike’s information criteria (AIC), Bayesian information criteria (BIC), and sample size–adjusted BIC (aBIC), where lower values indicate a better model fit (Knight et al., 2022; Nylund et al., 2007). The classification accuracy (entropy) of models was also examined with values greater than 0.80 and closer to 1.0 indicating better classification accuracy. Consistent with recommendations emphasising the importance of theoretical considerations in determining the number of classes, the distinctiveness and interpretability of identified classes were also considered to ensure a parsimonious and meaningful solution (Jung and Wickrama, 2008; Ram and Grimm, 2009).

After determining the number of distinct subgroups or profiles based on responses to the six main reasons for continuing work, the associations between subgroup membership and key demographic and organisational variables were then examined in IBM SPSS Statistics Version 28 using separate chi-square tests, correlation analyses and logistic regression.

4. Results

4.1. Number of latent class subgroups of reasons for continuing work

The model fit indices (AIC, BIC and aBIC) from the LCA are plotted in Figure 1. Following existing recommendations (Ram and Grimm, 2009), the two-class model was selected as the most parsimonious and best fitting model for classifying reasons for continuing work. Although the two-class model did not have the absolute lowest model fit indices, there is an inflection point after which additional latent classes yielded relatively smaller reductions in these criteria. In addition, only the two-class model had sufficiently high entropy (>.80), indicating that individuals can be most accurately classified into two classes or subgroups of respondents.

4.2. Main reasons for continuing work

Supporting Hypotheses 1a and 1c, which proposed an income-dominant and mixed motivational profile, respectively, there were two main patterns of responding suggested by the two-class model. These are depicted in Figure 2 as the ‘income-dominant’ subgroup for whom the need for income is the dominant reason, and the ‘socioemotional-income’ subgroup, for whom socioemotional reasons are more important than income but where income remains important.

In the total sample, the most selected reason for continuing work among all workers was ‘I need the income’ (72.5%), while a substantial number of mature workers also indicated wanting ‘to stay active and productive’ (66.8%), highlighting the importance of more intrinsic, socioemotional reasons for continuing work. The pattern of responses for the income-dominant subgroup (n = 707, 47.1%) showed that they predominantly selected income only as their main reason for continuing work. In contrast, the pattern of responses for the socioemotional-income subgroup (n = 794, 52.9%), which comprised more than half of all mature workers in our sample, indicated that while income was a reason for most people in this subgroup (69.3%), socioemotional reasons were even more prominent, with an overwhelming majority selecting ‘I want to stay active and productive’ (97.9%), ‘It gives me a sense of purpose’ (95.0%), ‘I want to stay involved with people’ (89.2%) and ‘I enjoy it’ (87.4%), as their top four reasons for continuing work. Although socioemotional reasons were slightly more dominant than financial reasons in this second subgroup, Hypothesis 1b, which proposed a profile in which the main reasons for continuing work are socioemotional, was not supported, as financial reasons were also chosen as main reasons for the most workers in this subgroup.

4.3. Subgroup characteristics and outcomes

Descriptive statistics for the total sample and each subgroup are presented in Table 1. Chi-square tests indicated that mature workers in the socioemotional-income subgroup had significantly higher levels of education, income and good health, and were also more likely to have care responsibilities than those in the income-dominant subgroup. Independent-sample t-tests indicated that the socioemotional-income subgroup was also more likely to report working in an organisation with a higher degree of age-inclusive HR practices than those in the income-dominant subgroup. In terms of indicators of work continuance, as expected, the socioemotional-income subgroup reported an older mean desired retirement age (66.5 vs 64.5 years of age) and was around half as likely to have considered quitting in the last 6 months than the income-dominant subgroup (17.9% vs 35.4%). There were no significant subgroup differences in gender, age or marital status.

Table 1.

Antecedents and outcome variables for each subgroup and for all workers.

Variable	All workers	Income-dominant subgroup	Socioemotional-income subgroup	p
n	1501	707	794
Gender (% female)	41.3	39.9	42.5	0.305
Mean age in years (SD)	55.4 (7.8)	55.0 (7.0)	55.7 (8.5)	0.060
Education (%)				0.000*
High school	21.7	25.2	18.5
Certificate or diploma	32.4	35.8	29.4
Degree	45.9	39.0	52.1
Income (%)				0.016*
Low	33.2	32.5	33.8
Mid	37.6	41.1	34.4
High	29.2	26.4	31.8
Married/living with partner (%)	71.7	71.6	71.8	0.937
Care responsibility (%)	34.0	31.1	36.6	0.024*
Self-rated health (%)				0.000*
Poor/fair	16.1	22.6	10.2
Good/very good/excellent	83.9	77.4	89.8
Age-inclusive HR practices (SD)	2.8 (1.1)	2.5 (1.0)	3.0 (1.1)	0.000*
Desired retirement age (SD)	65.6 (6.1)	64.5 (5.9)	66.5 (6.1)	0.000*
Turnover intention (%)	26.1	35.4	17.9	0.000*

SD: standard deviation; HR: human resource.

p-values from chi-square or independent-samples t-test.

p < 0.05.

4.4. Effects of gender, age, socioeconomic status and age-inclusive HR practices on motivational profile

The results of the logistic regression examining the main and interaction effects of antecedent demographic and organisational variables on subgroup membership are presented in Table 2. The first model, which included main effects only, suggested that being female, being older, having higher education and income levels, having better health and working in an organisation with age-inclusive HR policies increased the odds of being in the socioemotional-income subgroup. This is consistent with Hypotheses 2, 4 and 5, which stated that older mature workers, those with higher education and income levels, and those in organisations with more age-inclusive HR practices would be more likely to have a mixed rather than an income-dominant motivational profile. Hypothesis 3, which proposed that men would be more likely to have a socioemotional-dominant or mixed profile than women, was not supported, with the opposite relationship found.

Table 2.

Binomial logistic regression of the income-dominant (0) versus socioemotional-income subgroup (1).

	Main effects		With interaction effects
	Exp(B)	95% CI	Exp(B)	95% CI
Gender (1 = female)	1.41*	[1.10, 1.81]	2.28	[0.87, 5.96]
Age (45–54 vs 55–64)	1.53*	[1.18, 1.98]	1.91*	[1.30, 2.81]
Age (45–54 vs 65+)	3.26*	[2.19, 4.83]	6.32*	[3.74, 10.69]
Education	1.11*	[1.03, 1.19]	1.09	[1.00, 1.19]
Income (low vs mid)	0.75*	[0.57, 0.98]	0.73	[0.49, 1.09]
Income (low vs high)	0.76	[0.54, 1.07]	1.02	[0.66, 1.59]
Married/living with partner	0.81	[0.62, 1.04]	0.80	[0.61, 1.03]
Care responsibility	0.98	[0.76, 1.26]	0.96	[0.74, 1.24]
Self-rated health	1.50*	[1.32, 1.70]	1.54*	[1.35, 1.75]
Age-inclusive HR practices	1.47*	[1.30, 1.65]	1.54*	[1.30, 1.83]
Gender × age (45–54 vs 55–64)			0.68	[0.40, 1.14]
Gender × age (45–54 vs 65+)			0.16*	[0.07, 0.36]
Gender × education			1.03	[0.90, 1.19]
Gender × income (low vs mid)			1.06	[0.61, 1.83]
Gender × income (low vs high)			0.36*	[0.17, 0.74]
Gender × HR practices			0.98	[0.77, 1.26]

CI: confidence interval; HR: human resource.

Exp(B) refers to change in odds ratio with one unit change in the predictor. CI = confidence interval. Nagelkerke R² = 0.150 for the main effects model and 0.172 for the model with interaction effects.

p < 0.05.

In the second model which included interaction effects, there were no longer significant main effects of gender, education and income, but two significant interaction effects involving gender and age (45–54 vs 65+), and gender and income (low vs high) were significant. As seen in Figure 3, more men and women in the oldest age group (65+) than in the youngest age group (45–54) belonged to the socioemotional-income subgroup, but the difference between the oldest and youngest groups was greater for men (71% vs 53%) than for women (60% vs 52%). Similarly, the difference in socioemotional-income subgroup membership between the highest and lowest income groups was greater for men (60% vs 50%) than for women (52% vs 44%). In other words, age and income played a larger role in influencing the likelihood of whether men would be in the socioemotional-income subgroup, whereas for women, age and income were less important. Unexpectedly, these results are the opposite of Hypothesis 6, which suggested that the effect of age, education, income and HR practices would be stronger for women than for men.

5. Discussion

Workers are often assumed to have either extrinsic or intrinsic reasons for continuing work, and SST suggests that reasons become more intrinsic, or socioemotionally focused, as people age. This article set out to explore how different reasons might combine to motivate prolonged workforce participation. Using a person-centred approach, this study aimed to identify distinct motivational profiles among mature workers, to examine the extent to which those profiles align with key sociodemographic and organisational factors, and to interrogate the value of SST in understanding mature worker decision-making.

The present study contributes to research on mature workers in several ways. First, we extend previous research by shifting the focus from reasons for retirement towards reasons for continuing work to better understand the main motives for continuing work among a relatively broad mature-age cohort. Second, in extending previous, predominantly variable-centred research, we adopted a person-centred approach using LCA to identify two distinct motivational profiles of mature workers’ main reasons for continuing work, which we termed ‘income-dominant’ and ‘socioemotional-income’. Our person-centred approach allows us to move beyond preferences for single motive types to examine how mature workers may be driven by a combination of different types of motives at the same time, providing a more nuanced and holistic picture of mature worker motives for continuing work. Finally, we also found evidence that several individual and organisational antecedent factors, including gender, age and age-inclusive HR policies, could be associated with membership in these two profiles and that socioemotional-income profiles were associated with later intended retirement ages and lower turnover intentions than income-dominant profiles.

Existing qualitative and variable-centred research (e.g. Smyer and Pitt-Catsouphes, 2007) posited at least three possible motivational profiles of reasons for continuing work: an extrinsically motivated profile or ‘need to work’, an intrinsically motivated profile or ‘want to work’ and a mixed profile in which both income and socioemotional reasons are strong. However, our person-centred, quantitative analyses revealed only two distinct motivational profiles: an extrinsically motivated profile (income-dominant) in which income is the main reason and a mixed profile (socioemotional-income) in which income still featured as a main reason, but more intrinsic reasons such as ‘wanting to stay active and productive’ and having ‘a sense of purpose’ were more consistently indicated in this subgroup. The distribution of mature workers in each profile was roughly equivalent. Critically, a solely intrinsically motivated profile, or even a mostly intrinsically motivated profile, was not evidenced in our data. The results of our person-centred analyses may help in explaining variable-centred research that has yielded conflicting results when comparing or contrasting the relative importance of extrinsic versus intrinsic reasons for continuing work.

Our descriptive analysis of potential antecedent factors associated with each motivational profile suggests that mature workers in the socioemotional-income subgroup are likely to report having more personal (e.g. higher education, income and better health) and organisational resources (age-inclusive HR practices). This is consistent with past variable-centred research (e.g. Fisher et al., 2016b; Hamilton and Hamilton, 2006), which has suggested that workers with higher education and income are more likely to have intrinsic rather than extrinsic reasons for continuing work. Our regression results partly support this view, with higher levels of education, income, self-rated health and age-inclusive HR practices increasing the likelihood of being in the socioemotional-income rather than income-dominant subgroup in the main effects model, although education was no longer significant in the interaction effects model.

Our analysis also suggests that it is important to consider the interactive effects of gender and age to better understand mature worker motives for continuing work. While existing research suggests that women are more likely than men to have financial reasons for continuing work, the main effects in our regression analyses suggest that controlling for all the other individual and organisational antecedents in the analysis, women are more likely than men to be in the socioemotional-income than the income-dominant subgroup. Although the main effect of gender was not significant in the interaction effects model, two of the four interactions involving gender were significant. Specifically, our findings suggest that women are more likely to have mixed (socioemotional-income) reasons for continuing work regardless of age and income, whereas men’s motivational profiles are more variable based on age and income. This may be partially driven by the higher percentage of older and high-income men in the socioemotional-income subgroup (see Figure 3). These findings challenge the conception that women, who tend to have lower retirement savings than men, are more likely than men to continue working for financial reasons. Instead, we found that while financial reasons remained important, women were more likely to have socioemotional reasons than men, controlling for other antecedent factors.

As predicted by SST, our regression results also indicated that compared to the youngest age group (aged 45–54), older age groups (i.e. workers aged 55–64 and workers aged 65 and over) are more likely to be in the socioemotional-income than income-dominant subgroup. The finding that significant age group differences exist in relation to motivational profile membership highlights the value of focusing on narrower age groups of mature workers rather than treating the group as homogeneous.

In comparing our two employee outcomes of desired retirement age and turnover intention, we found significant motivational subgroup differences. Specifically, mature workers in the income-dominant subgroup were twice as likely to have seriously considered quitting their job in the last 6 months than those in the socioemotional-income subgroup and had a planned retirement age of 2 years younger on average than the socioemotional-income subgroup. Although the socioemotional-income subgroup was on average 0.7 years older than the income-dominant subgroup, this age difference was not statistically significant and does not completely explain the difference in employee outcomes. These findings further highlight the value of employing a person-centred approach to identify distinct configurations of reasons that tend to be endorsed simultaneously by mature workers and examining how these different configurations might affect other important work and employee outcomes such as job satisfaction, work engagement and job performance.

5.1. Theoretical contributions

Our research extends prior variable-centred SST research, which has typically examined older adult preferences for socioemotional versus other types of motives in different non-work scenarios. Our findings were generally consistent with the predictions of SST, suggesting that SST may provide a useful theoretical framework for examining general age-related differences at work, including mature worker motives for continuing work. However, it is important to note that specific within-cohort differences are likely to exist between workers in the same age cohort or life stage, and organisations need to take a more individualised approach to retain and motivate mature workers (Bal et al., 2022). For example, some mature workers in the income-dominant group (20% of the total sample) did not select any socioemotional motives as their main reasons for continuing work. This is contrary to what might be expected according to SST, which suggests that socioemotional motives become increasingly important as individuals age. One possible explanation for this could be that some individuals view work as being transactional and are not interested in the socioemotional benefits of work regardless of their age, preferring instead to pursue such goals in other, non-work settings. An emerging literature on the role of psychological contract type in predicting mature workers’ post-retirement bridge employment intentions provides support for this view. According to Garcia et al. (2021), transactionally oriented workers tend to prefer work that is bounded and short-term, and provides an economic exchange of monetary rewards for work, whereas relationally oriented workers tend to view work as being more long-term and open-ended, seeking both monetary and socioemotional rewards in exchange for work. Future research would benefit from investigating the role of psychological contract in determining mature worker motives for continuing work in later life, and also whether transactionally oriented workers prefer to pursue socioemotional goals in other, non-work settings.

The person-centred analysis in this article challenges orthodoxies about mature workers’ motives for continuing work extending both theory and practice. Although past research and theory have often juxtaposed extrinsic with intrinsic motives, suggesting that workers are either extrinsically or intrinsically motivated to work, our analysis suggests that many mature workers are likely to have both extrinsic (or financial) and intrinsic (or socioemotional) reasons for continuing work. The lack of a solely intrinsically motivated profile, or even a mostly intrinsically motivated profile, in our data suggests that even though socioemotional reasons may be increasingly prioritised over financial reasons with increasing age, as predicted by SST, financial reasons still play a central role in both profiles, either acting as the main driving force for continuing work or operating alongside intrinsic reasons for continuing work.

The finding that motivational profiles differ according to age also draws attention to the necessity of looking closely at different subgroups within the mature worker cohort. In particular, our research suggests that the predictive potential of SST may be moderated by the personal and organisational resources available to mature workers, with those with fewer resources being less driven by socioemotional motives. More research is required to examine this potential moderating effect statistically.

5.2. Practical implications

This research has important implications for policymakers and employers. Our results suggest that policymakers need to take a more nuanced approach that moves beyond the treatment of mature workers as a homogeneous group and the strong focus on financial reasons and incentives for extending working lives. The increasing primacy of socioemotional goals with age suggests that acknowledging and supporting more socioemotional motives at work may be an effective way to encourage mature workers to continue working longer. The finding that significant age group differences exist within the broader mature worker cohort points to the potential value of designing policies aimed at specific subgroups of mature workers based on age, gender or other personal factors (e.g. Ali, 2016) and assessing how these targeted (e.g. mature-age, gender-focused) policies compare to more generalised (e.g. age-inclusive) policy measures across important work and employee outcomes.

This study also suggests that having work that is enjoyable and provides opportunities to remain active, productive and socially connected is likely to have a stronger impact on prolonging working lives than financial reasons, suggesting non-financial policy approaches – those that focus on the nature of work – are decidedly important. Furthermore, our findings suggest that age-inclusive workplaces are associated with increased socioemotional reasons for continuing work and, in turn, with later retirement ages and lower turnover intentions. This highlights the value to employers of designing organisational practices that better address the needs of mature-age workers, including different and specific subgroups of mature workers (Bal et al., 2022; Mok et al., 2023; Sykes-Bridge et al., 2023).

5.3. Limitations and future research directions

This study had several limitations. First, our analysis was based on cross-sectional data, thereby limiting our ability to draw conclusions about direct causal pathways between possible antecedent factors, motivational profiles and outcomes. Future research should aim to collect longitudinal data, including repeated measurements to enable more complex mediation models to be tested and examined. Another limitation was the lack of clarity about one of the reasons for continuing work concerning benefits. ‘Needing the benefits’ was a main reason for continuing work among 41% of mature workers in the socioemotional-income subgroup, compared to 26% of workers in the income-dominant subgroup (see Figure 2). However, the term ‘benefits’ is not clearly defined in the Australian context. In the American context, where the item was created, benefits tend to refer to other employer-provided benefits such as health insurance. In Australia, however, this is not a commonly used term and could have been interpreted by participants as referring to either financial or non-financial benefits. Therefore, we recommend future research explore this reason further and adapt the item specifically based on the study context. A related limitation is that the list of reasons examined in this study is relatively short, being based solely on the results of the United States of Aging Survey (AARP, 2012), and could be expanded specifically to study how generative reasons might change or fit into these motivational profiles (Kanfer et al., 2013).

Finally, as noted by Bouckenooghe et al. (2019), although person-centred approaches such as LCA can effectively identify subgroups of profiles within a particular sample, further research with different samples is required to establish consistent profiles that generalise across different studies.

Footnotes

Acknowledgements

We are grateful to all the staff and participants involved in the Mature Workers in Organisations Survey (MWOS) for their contribution. The team would like to thank Associate Professor Helena Nguyen for her excellent feedback on a draft of this paper.

Final transcript accepted 28 April 2023 by Muhammad Ali (AE Human Resource Management).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This research was supported by the Australian Research Council Centre of Excellence in Population Ageing Research (project number CE170100005).

ORCID iD

Vanessa Loh

Notes

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