Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-21T23:41:08.296Z Has data issue: false hasContentIssue false

Enablers of successful employment outcomes for people with disabilities

Published online by Cambridge University Press:  21 October 2024

Paul Ikutegbe
Affiliation:
Faculty of Business and Law, University of Wollongong, NSW, Australia
Melanie Randle*
Affiliation:
Faculty of Business and Law, University of Wollongong, NSW, Australia
Lynnaire Sheridan
Affiliation:
Department of Management, University of Otago, Dunedin, New Zealand
Robert Gordon
Affiliation:
Faculty of Business and Law, University of Wollongong, NSW, Australia
Samuel Allingham
Affiliation:
Faculty of Science, Medicine and Health, University of Wollongong, NSW, Australia
Alanna Connolly
Affiliation:
Faculty of Science, Medicine and Health, University of Wollongong, NSW, Australia
Sara Dolnicar
Affiliation:
UQ Business School, University of Queensland, St Lucia, QLD, Australia
*
Corresponding author: Melanie Randle; Email: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Successful employment outcomes are often beyond the reach of people with disabilities, but relatively little is known about the factors that best enable the achievement of this goal. Using survey data from 803 people with and without disabilities, we examine the association of eight factors with successful employment outcomes. Using regression tree analysis, five factors emerged as statistically significant predictors of successful employment outcomes for people with disabilities: corporate culture and climate, job characteristics, government support, employer attitudes, and societal attitudes. Key interrelationships between factors include: (1) government support linking with corporate culture and climate; and (2) job characteristics linking with corporate culture and climate. Findings are relevant to organisations and governments to inform policy and practice to improve employment outcomes for people with disabilities.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press in association with Australian and New Zealand Academy of Management.

Introduction

Improving employment outcomes for people with disabilities is a key focus of government reform globally. Article 27 of the United Nations Convention on the Rights of People with Disabilities recognises the social and economic imperative of ensuring better employment outcomes for people with disabilities (United Nations General Assembly, 2006). Goal 8 of the United Nations Sustainable Development Goals (decent work and economic growth) also emphasises the need for countries to promote policies that ensure full and productive employment for people with disabilities, as well as protection from discrimination and prejudice in mainstream workplaces (United Nations, 2018). The heightened urgency for, and international attention on, the participation of people with disabilities in the labour force has been further fuelled by the global decline in the working-age population (Vornholt et al., Reference Vornholt, Villotti, Muschalla, Bauer, Colella, Zijlstra and Corbiere2018). This has catalysed efforts to engage traditionally marginalised groups in employment in order to mitigate the economic effects of labour shortages and subsequent adverse impact on the world economy. Despite good strides by organisations towards embracing the talent advantages presented by diversity generally, efforts towards disability employment have lagged behind (Gould, Mullin, Parker Harris, & Jones, Reference Gould, Mullin, Parker Harris and Jones2022).

Achieving the employment of people living with disabilities involves employers, however the impetus for research into the employment of people with disabilities has predominantly come from the disability sector (the demand-side of the equation) and has had limited engagement with organisations, to enhance their practice, and with government, to inform policy. Employers require clear frameworks to help them create inclusive workplaces that effectively integrate people with disabilities into their organisation (Van Berkel, Reference Van Berkel2021). The purpose of the present study is to address this issue by identifying clear and pragmatic actions that employers can take to effectively, and sustainably, embed people with disabilities within their organisations in a mutually beneficial and rewarding way.

People with disabilities can perform most jobs well under the right work conditions (World Health Organisation, 2011), however they experience significantly lower employment rates than people without disabilities (Organisation for Economic Co-Operation and Development, 2022). It is estimated that people with disabilities account for 15.6% of the global workforce, which equates to around 785 million people (Cavanagh et al., Reference Cavanagh, Bartram, Meacham, Bigby, Oakman and Fossey2017). Yet, ‘the employment-to-population ratio of persons with disabilities aged 15 and older is almost half that of persons without disabilities’ (United Nations, 2018, p. 10). Poor work outcomes for people with disabilities are considered to result from widespread systemic employment discrimination stemming from prejudice within broader society (Australian Human Rights Commission, 2016; Royal Commission into Violence Abuse Neglect and Exploitation of People with Disability, 2021).

Improving work outcomes for people with disabilities requires greater understanding of the factors that enable and drive success in mainstream employment settings. Factors identified as being associated with employment success for people with disabilities include the individual being educated above high school level (Alverson & Yamamoto, Reference Alverson and Yamamoto2018; O’Neill et al., Reference O’Neill, Kang, Sánchez, Muller, Aldrich, Pfaller and Chan2015), organisational values and norms (Beatty, Baldridge, Boehm, Kulkarni, & Colella, Reference Beatty, Baldridge, Boehm, Kulkarni and Colella2019; Stone & Colella, Reference Stone and Colella1996), and workplace culture (McDonough et al., Reference McDonough, Ham, Brooke, Wehman, Wright, Godwin and Hurst2021; Schur, Kruse, Blasi, & Blanck, Reference Schur, Kruse, Blasi and Blanck2009). Matching people with jobs that are within their functional capacity is also linked with better employment outcomes for both the individual and their organisation because the individual is more likely to perform the job well (Choe & Baldwin, Reference Choe and Baldwin2017; Wen, Van Rensburg, O’Neill, & Attwood, Reference Wen, Van Rensburg, O’Neill and Attwood2023). At a broader level, people with disabilities are more likely to succeed at work when they are accepted as full members of society with protected rights (Bogenschutz, Im, & Liang, Reference Bogenschutz, Im and Liang2016; Lindsay, McDougall, Menna-Dack, Sanford, & Adams, Reference Lindsay, McDougall, Menna-Dack, Sanford and Adams2015) and have access to government-funded assistance that facilitates their sustained success, such as on-the-job support or assistive technology (Readhead & Owen, Reference Readhead and Owen2020).

The socio-economic rationale for hiring people with disabilities is clear and the factors enhancing employability for people with disabilities are becoming apparent. However, there is a gap between the aspirations of the human resource profession and organisational practice (Schloemer-Jarvis, Bader, & Bohm, Reference Schloemer-Jarvis, Bader and Bohm2022). Employing someone with a disability is espoused as generating competitive advantage in a tight labour market, or as a social good associated with sustainable human resource management (Richards, Reference Richards2022). Yet, employers still grapple with hiring people with disabilities, and managing existing employees who acquire an injury or illness (Andrew, Phillipson, & Sheridan, Reference Andrew, Phillipson and Sheridan2018; Bartram, Cavanagh, Meacham, & Pariona-Cabrera, Reference Bartram, Cavanagh, Meacham and Pariona-Cabrera2021). Disability raises human resource issues and, consequently, organisations require support to identify and resolve these challenges (Van Berkel, Reference Van Berkel2021).

A contributing factor to this situation is the fact that disability management within organisations has remained the remit of the work health and safety (allied health) professionals responsible for reasonable adjustments in the workplace (Sheridan, Reference Sheridan2023), rather than being a primary concern of the human resource profession. Employer perspectives of disability are thus derived from a deficit mindset, where standard job roles require ‘accommodations’ to overcome the individual’s medical problem. This results in human resource professionals feeling ill-equipped to manage, or even understand, the nature of the injury or illness and how it can be ‘overcome’ in a workplace setting. Some may argue that it is stigma and negative employer attitudes that explain the deficit legacy of employer perspectives on disability (Khayatzadeh-Mahani, Wittevrongel, Nicholas, & Zwicker, Reference Khayatzadeh-Mahani, Wittevrongel, Nicholas and Zwicker2019). However, in some scenarios, there may be a willingness of employers to support people with disabilities into work, but the complexity stems from the deficit legacy which focuses human resource managers minds on sensitive health-based enquiries as being taboo and potentially a legal risk (Ikutegbe, Randle, Sheridan, Gordon, & Dolnicar, Reference Ikutegbe, Randle, Sheridan, Gordon and Dolnicar2023b). This study seeks to overcome this by informing human resources practice on disability and work by presenting a data-informed approach (as per Beatty et al., Reference Beatty, Baldridge, Boehm, Kulkarni and Colella2019).

First, this study is contextualised within its theoretical lens, the social model of disability. This model is useful to human resource scholars and practitioners as it is a relatively new perspective on disability and it is important to understand that many, less useful, alternate views continue to be pervasive in broader society and limit the employment of people with disabilities. Second, the survey method and data analysis via classification and regression tree analysis are introduced. This approach can lead to meaningful insights into inter-related factors that contribute to successful employment outcomes and the benefit of adopting a comparison of people with and without disability to identify factors that are specific to people with disabilities. The results are then presented before interpreting these for business and government stakeholders to identify specific actions they can take to enhance employment of people with disabilities.

Theoretical background

The present study is underpinned by the social model of disability (Oliver, Reference Oliver1996; UPIAS, 1976). The social model understands disability as a failure of society to recognise and accommodate the needs and rights of people with disabilities (Riddle, Reference Riddle2020). This understanding of disability is in contrast with other models of disabilities that have traditionally shaped public policy and how society interacts with people with disabilities, such as medical, functional, and environmental models. For example, the medical model of disability considers disability as a health condition that makes the individual different to ‘normal’ people and that needs to be fixed. Consequently, taking a medical view of disability can dehumanise people with disabilities and expose them to heightened levels of prejudice, discrimination, and exclusion from society, including in employment (Smart & Smart, Reference Smart and Smart2006).

Alternatively, the social model of disability distinguishes between the health condition of an individual and their experience of being ‘disabled’ within society (World Health Organization, 2022). It offers an understanding of disability that is more inclusive as it seeks to identify and remove all social structures that may hinder people with disabilities from fully participating in society (Jones, Mavromaras, Sloane, & Wei, Reference Jones, Mavromaras, Sloane and Wei2014; Scholz & Ingold, Reference Scholz and Ingold2020). The capacity of the social model of disability to promote inclusion exceeds that of other models because it consistently demands societal changes that reduce stigma and discrimination against people with disabilities (Levitt, Reference Levitt2017; Smart, Reference Smart2009).

Ikutegbe et al. (Reference Ikutegbe, Randle, Sheridan, Gordon and Dolnicar2023b) used the social model of disability to holistically consider the individual, structural, and societal factors associated with successful employment outcomes for people with disabilities. They identified factors on three levels: supply-side factors (those related to the person with a disability), demand-side factors (those related to the workplace), and environmental factors (those related to the external environment). Qualitative research has identified eight factors in particular that are most important for successful employment outcomes: nature of the disability, disability disclosure, personal motivation, employer attitudes, job characteristics, corporate culture and climate, government support, and societal attitudes (Ikutegbe, Randle, Sheridan, Gordon, & Dolnicar, Reference Ikutegbe, Randle, Sheridan, Gordon and Dolnicar2023a). The present study adds to the extant literature by further examining these eight factors to determine their statistical significance in predicting employment outcomes for people with disabilities.

Method

Research context

This research was conducted in Australia, where one in six people have a disability (Australian Bureau of Statistics, 2018). In recent decades, the workforce participation rate for people with disabilities has remained at just over 50%, compared to 84% for people without disabilities (Australian Bureau of Statistics, 2018). It is a priority of the Australian government to increase employment of people with disabilities in mainstream workplaces (Commonwealth of Australia, 2021). This approach is consistent with many countries which are shifting away from segregated or sheltered employment systems that do not support inclusive mainstream workplaces (Hemphill & Kulik, Reference Hemphill and Kulik2017). Increasing employment of people with disabilities is also a key aim of the National Disability Insurance Scheme (NDIS) which was introduced in Australia in 2017. The NDIS was intended to revolutionise the way Australian people with a disability are supported by government to live an ordinary life, which involves building ‘skills and capability so they can participate in the community and employment’ (National Disability Insurance Agency, 2017). Key to the economic success of the NDIS was the expectation that many people with a disability and their carers would be able to enter the workforce and contribute to the economy. However, this success is jeopardised by the persistently low workforce participation rates of people with disabilities.

Data collection

This study is part of a larger program of work being conducted on employment outcomes for people with disabilities. For the present study, we use data collected through an online survey of 803 people with and without disabilities who were employed in mainstream work settings in Australia. Data was collected in November–December 2021 using a national online panel. We used an online panel company because it they enable recruitment of large samples easily and quickly (Evans & Mathur, Reference Evans and Mathur2005) and greater access to marginalised populations in the workforce that can be difficult to reach, such as people with disabilities (Thompson, Bergman, Culbertson, & Huffman, Reference Thompson, Bergman, Culbertson and Huffman2013). Screening questions were used to exclude participants who were younger than 18 years old, unemployed, self-employed, employed for less than 90 days, or employed in sheltered or supported employment settings. The university’s Human Research Ethics Committee approved this research prior to data collection commencing (approval number 2018/332).

Measures

Survey measures were informed and developed using qualitative data collected through interviews with people with disabilities, employers, and disability employment service providers. Items were developed using the C-OAR-SE procedure for scale development (Rossiter, Reference Rossiter2011), which specifies that constructs are defined in terms of the object, attribute, and rater entity. Items were formulated according to whether each construct was defined as being singular or having multiple components. Unlike psychometric theory, C-OAR-SE theory emphasises content validity as the only essential requirement of a measure. Rossiter (Reference Rossiter2011) advises against the use of coefficient alpha because it assumes that the measure of a construct can be validated by examining the scores obtained from that measure. Instead, C-OAR-SE theory assesses the validity of a measure based on the relationship between the conceptual definition of the construct and the measure that is developed. For the measures in the present study, content validity was established by conducting open-ended, semi-structured interviews with people with disabilities as part of the questionnaire pre-testing phase, and before any data was collected.

Mainstream employment success (MES) was operationalised by considering two elements. First, all participants included in the analysis had already experienced some degree of employment success in the traditional sense because they had been employed in paid work for 90 days or more and had regular work hours. Second, we measured participants’ own subjective assessments of their present employment by asking them to indicate their level of agreement with three statements: ‘I like my job,’ ‘I am able to progress in my job,’ and ‘I am able to achieve my full potential in my job.’ Participants responded by sliding a marker on a 100-point answer scale labelled ‘Strongly agree’ on the far-right end (100), ‘Neither agree nor disagree’ in the middle (50), and ‘Strongly disagree’ on the far-left end (0). The three scores were averaged to produce an overall score.

Supply-side measures

Participants with disabilities were asked to indicate the nature of their disability and could select one or more of the following: autism, intellectual, neurological, acquired brain injury, sensory, psychosocial, physical, or other. They were also asked to indicate the severity of their disability and whether, in their experience, it is obvious to other people that they had a disability. The other supply-side factors hypothesised to predict successful employment outcomes – disability disclosure and personal motivation – were measured by asking participants to indicate their level of agreement with a number of statements. Again, participants responded by sliding a marker on a 100-point bipolar answer scale labelled ‘Strongly agree’ on the far-right end (100), ‘Neither agree nor disagree’ in the middle (50), and ‘Strongly disagree’ on the far-left end (0). Where multiple items were used to measure a construct scores were then averaged to produce an overall score.

Disability disclosure was measured by asking participants with disabilities to indicate their agreement with the statement: ‘I am comfortable with telling an employer about my disability.’ Personal motivation was measured for all participants using five statements for which participants indicated their level of agreement: ‘Having a job enables me to be financially independent’; ‘Having a job enables me to contribute to my community’; ‘Having a job gives me a purpose in life’; ‘Having a job enables me to socialise with people I work with’; and ‘Having a job enables me to always keep busy.’

Demand-side measures

The demand-side factors hypothesised to predict successful employment outcomes – job characteristics, corporate culture and climate, and employer attitudes – were measured by asking participants to indicate their level of agreement with a number of statements. Again, participants responded by sliding a marker on a 100-point bipolar answer scale labelled ‘Strongly agree’ on the far-right end (100), ‘Neither agree nor disagree’ in the middle (50), and ‘Strongly disagree’ on the far-left end (0). Where multiple items were used to measure a construct scores were then averaged to produce an overall score.

Job characteristics was measured using three items: ‘My knowledge, skills and abilities enable me to be good at my job’; ‘I am happy to stay in my job for the foreseeable future’; and ‘I am suited well for my job.’ Corporate culture and climate was measured using five items: ‘I am allowed to make decisions at work’; ‘Managers at my workplace support me when needed’; ‘My workplace recognises and values my contribution’; ‘I feel like my workplace is where I belong’; and ‘The staff at my workplace care for one another.’ Employer attitudes were measured using four items: ‘My employer employs me because I am productive at work’; ‘My employer employs me because I am a loyal employee’; ‘My employer employs me because I am reliable’; and ‘My employer employs me because they value having a diverse range of employees.’

Environmental measures

The environmental factors hypothesised to predict successful employment outcomes – societal attitudes and government support – were measured by asking participants to indicate their level of agreement with a number of statements and answering on the same 100-point bipolar answer scale as for the supply-side and demand-side factors. Societal attitudes were measured using four items: ‘Most people in society believe people with disabilities can live independently’; ‘Most people in society treat people with disabilities fairly’; ‘Most people in society believe people with disabilities are just as capable as anyone else’; and ‘Most people in society believe people with disabilities have a bright future.’ Government support was measured using three items: ‘If needed, I know where to find information about government support for people with disabilities’; ‘It is easy for people with disabilities to access disability support from the government’; and ‘The government support provided to people with disabilities is adequate.’

Finally, all participants provided information regarding their age, sex, area of residence, level of education, and work classification.

Analysis

Data was cleaned using the IBM SPSS Statistics 27.0 software. Postcodes were used to determine participants’ geographic remoteness according to the Modified Monash Model (Australian Government, 2021). Initially, descriptive statistics were used to examine the data. Spearman’s rank correlation coefficients indicated the direction and strength of associations between constructs, using guidelines proposed by Cohen (Reference Cohen1988).

Classification and regression tree analysis was used to analyse the data as it is statistically robust, non-parametric, and non-linear (Breiman, Friedman, Olshen, & Stone, Reference Breiman, Friedman, Olshen and Stone1984; Poulsen, Johnson, & Ziviani, Reference Poulsen, Johnson and Ziviani2011). It is a recursive partitioning method that uses a decision tree with binary splits to examine each predictor variable and to identify those that are strongly associated with the outcome variable (Breiman et al., Reference Breiman, Friedman, Olshen and Stone1984; Fonarow et al., Reference Fonarow, Adams, Abraham, Yancy, Boscardin and Investigators2005). Classification and regression tree analysis was particularly appropriate for the present study because it handles highly skewed numerical data, uncovers meaningful complex relationships, and is relatively easy to interpret (Greene et al., Reference Greene, Hughes, Hanlon, Huang, Sommers and Meghani2019; Lewis, Reference Lewis2000; Zhang & Singer, Reference Zhang and Singer1999). R statistical software was used for the regression tree analysis (R Core Team, 2022). MES was included in the model as the dependent variable. The supply-side, demand-side, and environmental factors were included in the model as independent variables.

Results

The sample of 803 people included 392 (48.82%) people with disabilities and 411 (51.18%) people without disabilities. Participant ages ranged from 18 to 83 years (average 46, standard deviation 13). In relation to gender, 55.04% of participants were female and 44.96% were male. In terms of age, 78.46% of participants were 35 or older. In relation to education level, 83.56% of participants had some form of post-secondary school education, while 28.39% held professional roles, and 23.04% held managerial roles. In terms of place of residence, 76.84% of participants lived in metropolitan areas while 96.50% of participants spoke English as their main language. A detailed breakdown of participant characteristics can be found in Tables 1 and 2.

Table 1. Sample characteristics

Table 2. Characteristics of participants with disabilities

* Participants could select more than one type of disability, so percentages do not add to 100.

In relation to disability type, 33.16% of participants had multiple disabilities. Most commonly, participants reported having a physical (37.50%) or psychosocial (36.99%) disability. Participants were most likely to describe their disability as either severe (43.88%) or moderate (33.67%), and 63.10% of participants reported their disability as not obvious to other people.

Predictors of employment success for people with disabilities

Five of the eight factors emerged as important predictors of successful employment outcomes for people with disabilities. Figure 1 shows the regression tree which indicates the factors in order of importance. Corporate culture and climate emerged as most important, followed by government support, job characteristics, employer attitudes, and societal attitudes. The absence of nature of the disability, disability disclosure, and personal motivation from the tree indicates that these factors were not important predictors of successful employment outcomes for people with disabilities.

Figure 1. Regression tree for people with disabilities.

The root node of the regression tree shows that people with disabilities had a mean score of 71 out of 100 for MES. After the root node, the regression tree is interpreted from top to bottom, with the right-side nodes (after each binary split) depicting the highest mean score of MES at each level. The highest mean score of 91 out of 100 appears in Node 7. The left-side nodes (after each binary split) depict the lowest mean score of MES at each level, with the lowest overall score of 21 out of 100 appearing Node 4.

The terminal nodes are segments of people constructed to be maximally different in their employment success value. Three terminal nodes predict lower levels of success (mean score 21–66) and five terminal nodes predict higher levels of success (mean score 67–91). The individual terminal nodes enabled us to identify the specific subgroups of people with disabilities reporting higher or lower levels of employment success.

Nodes 2 and 3 included people with mean scores for corporate culture and climate of <67 and ≥67 respectively. Node 2 was then split by corporate culture and climate into Node 4 (mean score < 40) and Node 5 (≥40). Node 4 could not be split further into two significantly discrete groups for any variable, which made it a terminal node. Node 5 was split by job characteristics into Nodes 8 (<79) and 9 (≥79). Node 9 was a terminal node. Node 8 was split by societal attitudes into Nodes 12 (<70) and 13 (≥70). Nodes 12 and 13 could not be split further, which made both of them terminal nodes. Node 3 was split by corporate culture and climate into Nodes 6 (<88) and 7 (≥88). Node 7 could not be split further into two significantly discrete groups for any variable, making it a terminal node. Node 6 was split by government support into Nodes 10 (<79) and 11 (≥79). Node 11 could not be split further, but Node 10 was split by employer attitudes into Nodes 14 (<73) and 15 (≥73). Nodes 14 and 15 could not be split further.

Of the five factors that were statistically significant predictors of MES for people with disabilities, corporate culture and climate (Node 7) was the most important predictor of employment success for people with disabilities. Around 29% reported the highest level of MES when mean scores for corporate culture and climate was at its highest (≥88), regardless of other predictor variables. Table 3 summarises the results of the regression tree analysis for people with disabilities, including the characteristics of significantly discrete subgroups for any predictor variable associated with employment success. Nodes are in descending order according to success value.

Table 3. Regression tree results for people with disabilities

Predictors of employment success for people without disabilities

The regression tree analysis for people who do not have disabilities necessarily excluded some factors that are not direct relevant to their own employment experiences. These were the nature of a disability, disability disclosure, societal attitudes towards people with disabilities, and government support for people with disabilities. The other four factors – personal motivation, job characteristics, employer attitudes, and corporate culture and climate – were entered as independent variables in the regression tree. All four factors were significant predictors of employment success for people without disabilities (see Fig. 2). Corporate culture and climate was most important, followed by job characteristics, personal motivation, and employer attitudes.

Figure 2. Regression tree for people without disabilities.

The root node of the regression tree indicates that the overall employment success score for people without disabilities was 72 out of 100. The highest mean score for employment success can be seen in Node 13 and the lowest in Node 4. Five terminal nodes predict lower levels of success (25–70 mean score) and five terminal nodes predict higher levels of success (71–95 mean score). Nodes 2 and 3 include people with mean scores for corporate culture and climate of <66 and ≥66 respectively. Node 2 was split by corporate culture and climate into Nodes 4 (<36) and 5 (≥36). Node 4 could not be split further, but Node 5 was split by job characteristics into Nodes 8 (<87) and 9 (≥87). Node 8 was split by corporate culture and climate into Nodes 14 (<58 score) and 15 (≥58). Node 15 was split by employer attitudes into Nodes 18 (<75) and 19 (≥75). Nodes 18 and 19 could not be split further.

Node 3 was split by corporate culture and climate into Nodes 6 (<91) and7 (≥91). Node 6 was split by personal motivation into Nodes 10 (<76) and 11 (≥76). Node 10 and Node 11 could not be split further into two significantly discrete groups for any variable. Node 7 was split by employer attitudes into Nodes 12 (<97) and 13 (≥97). Node 13 could not be split further, but Node 12 could be split by corporate culture and climate into Nodes 16 (<99) and 17 (≥99). Nodes 16 and 17 could not be split further into two significantly discrete groups for any variable.

Similar to the regression tree for people with disabilities, the regression tree for people without disabilities identified corporate culture and climate as the most important factor associated with employment success. Twelve percent of people without disabilities reported the highest employment success (Node 13) when mean scores for both corporate culture and climate (≥91) and employer attitudes (≥97) were at their highest, regardless of other predictor variables. Table 4 summarises the results of the regression tree analysis for people without disabilities. Nodes are in descending order according to employment success value.

Table 4. Regression tree results for people without disabilities

Discussion

The primary aim of the present study was to identify factors that predict successful employment outcomes for people with disabilities. Overall, corporate culture and climate was the strongest predictor of employment success, both for people with and without disabilities. Job characteristics and employer attitudes were also predictors of employment success for participants in both cohorts. Government support and societal attitudes were predictors of employment success for people with disabilities, and personal motivation was a predictor only for people without disabilities. These findings raise three points for discussion.

First, corporate culture and climate is the single most significant predictor of successful employment outcomes, both for people with and without disabilities. Prior studies acknowledge corporate culture and climate as a key factor affecting the likelihood that people with disabilities will be successful in the workplace (Gilbride, Stensrud, Vandergoot, & Golden, Reference Gilbride, Stensrud, Vandergoot and Golden2003; McDonough et al., Reference McDonough, Ham, Brooke, Wehman, Wright, Godwin and Hurst2021). It is especially important for people with disabilities seeking new job opportunities, career advancement, or simply job retention (Schur et al., Reference Schur, Kruse, Blasi and Blanck2009). This is because people with disabilities generally thrive in organisations that have an inclusive and supportive corporate culture and climate (Baldridge & Swift, Reference Baldridge and Swift2016; Meacham, Cavanagh, Bartram, & Laing, Reference Meacham, Cavanagh, Bartram and Laing2019). Conversely, a poor corporate culture and climate ‘can create attitudinal, behavioural, and physical barriers for workers and job applicants with disabilities’ (Schur, Kruse, & Blanck, Reference Schur, Kruse and Blanck2005, p. 5).

Corporate climate and culture emerging as so critical to the successful employment of people with disabilities means that if we want people with disabilities to enter mainstream employment, we must generate environments that enhance their positive self-image while at work. Otherwise they will find self-employment to be the only potentially positive option (Martin & Honig, Reference Martin and Honig2020). Situating disability within the broader diversity portfolio is an important first step to be followed up by a disability inclusion strategy. This strategy should be sustained using key performance indicators that link with the business’s fundamental goals and maintained through engagement with key organisational stakeholders (Gould et al., Reference Gould, Mullin, Parker Harris and Jones2022). Particularly useful is Kwan’s corporate culture mezzo-level intervention study which informs organisations on how to improve their corporate culture to ensure it is ‘disability-friendly’ (Kwan, Reference Kwan2021). In addition, the International Labor Organization’s Businesses leading the way on disability inclusion is a useful guide on existing good practice within organisations (International Labour Organization, 2023). When people with disabilities find themselves only ‘partially included’ at work, human resources practitioners and researchers need to collaborate to strive to understand the precursors and causes through research into the nuanced aspects of organisational culture (Beatty et al., Reference Beatty, Baldridge, Boehm, Kulkarni and Colella2019). Disability can no longer lag behind other diversity initiatives (Gould et al., Reference Gould, Mullin, Parker Harris and Jones2022) because of stigma (Khayatzadeh-Mahani et al., Reference Khayatzadeh-Mahani, Wittevrongel, Nicholas and Zwicker2019) and the impact it has on corporate climate and culture.

Second, the provision of government support to people with disabilities in workplaces with a suboptimal corporate culture and climate can mitigate potential barriers to successful employment outcomes. Prior studies have shown that government funded financial support is effective in incentivising employers to ensure positive employment outcomes for people with disabilities (Greenan, Wu, & Black, Reference Greenan, Wu and Black2002; Waghorn, Parletta, & Dias, Reference Waghorn, Parletta and Dias2019). This can facilitate initiatives such as on-the-job training, rehabilitation technology services, and vocational rehabilitation counselling services, which are all associated with favourable employment outcomes (Pack & Szirony, Reference Pack and Szirony2009). In particular, small and medium-sized organisations, which typically have limited resources, often respond positively to financial incentives such as tax credits and wage subsidies (Fraser, Ajzen, Johnson, Hebert, & Chan, Reference Fraser, Ajzen, Johnson, Hebert and Chan2011). To shift perceptions of the capability of people with disabilities in our workplaces, organisations must experience their presence and the full – including financial – benefits they bring. When governments do not support efforts to overcome any financial barriers to employment of people with disabilities, they enable the ‘productivist ideology’, the idea that people with disabilities are not as productive as other workers, to dominate (Ge, Chen, Tang, & Cong, Reference Ge, Chen, Tang and Cong2021).

Third, effective job-matching does not necessarily ensure employment success for people with disabilities if corporate culture and climate is suboptimal. The effect of this interrelationship was particularly prominent in the regression tree for people with disabilities. This supports prior studies which find that effective job-matching enhances employment outcomes for people with disabilities, including higher earnings and increased work hours (Choe & Baldwin, Reference Choe and Baldwin2017; Dreaver et al., Reference Dreaver, Thompson, Girdler, Adolfsson, Black and Falkmer2020). Findings from this research build on this to emphasise that in addition to effective job matching, a good corporate culture and climate is, however, necessary for this to occur.

Notably, none of the supply-side factors considered in the present study (nature of the disability, disability disclosure, and personal motivation) were statistically significant predictors of successful employment outcomes for people with disabilities. Prior studies have suggested that supply-side factors are typically more important during the pre-employment period, where people with disabilities receive necessary skills training and support to enter the workforce successfully (Chan et al., Reference Chan, Strauser, Maher, Lee, Jones and Johnson2010). It is possible that the lack of supply-side factors in the regression tree for people with disabilities is a result of all participants having already obtained mainstream employment.

This study builds on existing models of successful employment outcomes for people with disabilities (Ikutegbe et al., Reference Ikutegbe, Randle, Sheridan, Gordon and Dolnicar2023b) by statistically testing the relative predictive strength of individual, organisational, and social factors on employment outcomes. Prior studies typically consider a limited range of factors, such as individual or organisational, and do not provide statistical evidence of their relative weight, thereby responding to Beatty et al.’s (Reference Beatty, Baldridge, Boehm, Kulkarni and Colella2019) call for a holistic, data-informed, approach.

The present study shows that organisational factors, such as corporate culture and climate, employer attitudes and job characteristics are important predictors of success, regardless of disability. But it also highlights differences between people with and without disabilities. The provision of government support and societal attitudes are significant predictors when employees have disabilities, and personal motivation is a significant predictor for people without disabilities.

This study offers several practical implications to employers seeking to improve mainstream employment outcomes for people with disabilities. First, findings highlight several organisational factors which predict employment outcomes and can be influenced by managers and human resources professionals. This includes building an inclusive and equitable corporate culture and climate by promoting fair policies and practices at work, which ensures that everyone feels psychologically safe to voice their opinions and request job accommodations when required. Job characteristics is also a significant predictor and illustrates the importance of effective job matching for all employees. Organisations which do not have formal job-matching programs could formalise these to ensure managers consider this when appointing employees, and employees know they can raise this issue with their manager without fear of negative consequences. Employer attitudes are also important predictors and highlight the importance of educating managers on disability, the benefits of including people with disabilities in the workplace, and the types of supports people with disabilities may require.

We propose that the field of human resources shift the domain of disability from a workplace health and safety perspective towards a talent management perspective. In so doing, human resources practitioners could focus on the skill set of the individual rather than the modification of an existing job role that has been planned according to organisational needs, and that needs to be ‘modified’ or ‘adjusted’ in accordance with workplace health and safety legislation. The job crafting emerging from the field of talent management could then inform job crafting for people with disability, because human resources would be focused on the talents of all staff rather than the medical challenges of some.

Talent management lends itself to this perspective, as talent is ‘a socially constructed phenomenon that takes on different meanings in different contexts’ (Downs & Swailes, Reference Downs and Swailes2013, 268). Downs & Swailes argue that the focus in the field of human resources on talent management being restricted to a small, elite, percentage of the workforce is erroneous and under values the potential contribution of all employees. Their views align with Iles, Peerce, and Chauai who endorse talent management as process that facilitates the ‘strategic management of the flow of talent through an organisation’ (Iles, Preece, & Chuai, Reference Iles, Preece and Chuai2011, p. 127).

The focus on capability presented by Downs and Swailes (Reference Downs and Swailes2013), easily aligns with focusing on ‘ability’ rather than ‘disability’ and helps to overcome the deficit mindset currently holding back the human resources practices behind employment of people with disabilities. This is endorsed by Sheehan and Anderson who advocate for ‘a belief that all employees are talented and whose talent can be developed further to enhance value to the organisation’ (Reference Sheehan and Anderson2015, p. 351). Aside from enabling organisations to acquire talent, an inclusive approach to talent management may avoid the job stagnation and lack of career progression facing anyone in the organisation currently labelled as a ‘non-high-potential employee’ (Kwon & Jang, Reference Kwon and Jang2021, p. 95). A shift towards talent management for all employees including people with disabilities may also overcome the current phenomenon raised by Park and Park (Reference Park and Park2019)whereby people with disabilities struggle to get recruited but, even once successfully recruited, quit soon after due to a lack of potential for career progression.

Other important predictors for successful employment outcome for people with disabilities are the environmental factors of government support and societal attitudes. These factors are largely outside the control of individuals or organisations but are factors that can be influenced by governments. Khayatzadeh-Mahani et al. (Reference Khayatzadeh-Mahani, Wittevrongel, Nicholas and Zwicker2019) found that, in fact, a whole of government and society approach was fundamental if redressing the lowest labour participation, that of people with intellectual disabilities. Moreover, our findings highlight the importance of governments investing in financial supports to help employers cover any costs associated with hiring people with disabilities, and also providing employment services which specifically focus on matching people with disabilities with suitable employers and roles. Publicly funded social marketing campaigns have proven successful in improving societal attitudes towards people with disabilities (Randle & Reis, Reference Randle and Reis2016). Findings from this study demonstrate that improved attitudes among the general population increase inclusion for people with disabilities across society as a whole, they also have positive implications specifically in employment. Governments should prioritise investing in social marketing campaigns as a way of indirectly improving employment outcomes for people with disabilities.

This study was conducted in Australia; therefore, findings may not be generalizable to other countries with different employment conditions and policies to support people with disabilities. Future research should investigate how the factors identified in the present study are associated with successful employment outcomes for people with disabilities in other countries. This would advance global understanding of disability in mainstream employment settings and identify similarities and differences in different cultural settings. It should be noted that the present study excluded people who were unemployed, self-employed, or had mainstream employment for less than 90 days. Studies which include people with disabilities who are not employed would provide useful insights into the barriers to gaining employment and inform organisational or government policies to overcome these barriers. In addition, this study did not include employers in the sample. Future studies which report the perspective of employers would generate further insights into successful employment outcomes for people with disabilities.

Conclusion

Adopting the social model of disability, this study identified five factors that predict successful employment outcomes for people with disabilities: corporate culture and climate, job characteristics, government support, employer attitudes, and societal attitudes. It also identified key interrelationships between government support and corporate culture and climate, and job characteristics and corporate culture and climate. This study recognises the potential for drawing on existing, more advanced, equity, diversity, and inclusion initiatives to stop disability employment from lagging behind. A talent management approach is encouraged to overcome perspectives derived from the medical model of disability, that may encourage ‘productivist ideologies’ to linger. Most interaction between human resources and disability has been mediated through a workplace health and safety lens and ‘reasonable adjustments’ which can infer, to some, deficiencies rather than strengths. Employers can use our findings to focus on the aspects of their organisation that are likely to improve employment outcomes for people with disabilities, such as building an inclusive corporate culture and formalising job matching practices. The present study is limited to the Australian context and did not include unemployed people or employers. Future studies which broaden the scope of this work to other countries and stakeholder groups would add further insights into successful employment outcomes for people with disabilities.

Financial support

This work was supported by the Australian Research Council Linkage Projects Scheme (LP170100690).

Conflict of interest

The authors declare none.

References

Alverson, C. Y., & Yamamoto, S. H. (2018). VR employment outcomes of individuals with autism spectrum disorders: A decade in the making. Journal of Autism and Developmental Disorders, 48(1), 151162.CrossRefGoogle Scholar
Andrew, C., Phillipson, L., & Sheridan, L. (2018). What is the impact of dementia on occupational competence, occupational participation and occupational identify for people who experience onset of symptoms while in paid employment? A scoping review. Australian Occupational Therapy Journal, 66(2), 130144.CrossRefGoogle ScholarPubMed
Australian Bureau of Statistics. (2018). Disability, ageing and carers. Australia: Summary of Findings. Retrieved June 20 , 2024, from https://www.abs.gov.au/statistics/health/disability/disability-ageing-and-carers-australia-summary-findings/latest-release.Google Scholar
Australian Government. (2021). Modified Monash Model. Department of Health. Retrieved May 05 , 2022 from https://www.health.gov.au/health-topics/rural-health-workforce/classifications/mmm.Google Scholar
Australian Human Rights Commission. (2016). Willing to work: National inquiry into employment discrimination against older Australians and Australians with disability. Author. Retrieved May 8, from https://www.humanrights.gov.au/sites/default/files/document/publication/WTW_2016_Full_Report_AHRC_ac.pdf.Google Scholar
Baldridge, D. C., & Swift, M. L. (2016). Age and assessments of disability accommodation request normative appropriateness. Human Resource Management, 55(3), 385400.CrossRefGoogle Scholar
Bartram, T., Cavanagh, J., Meacham, H., & Pariona-Cabrera, P. (2021). Re-calibrating HRM to improve the work experiences of workers with intellectual disability. Asia Pacific Journal of Human Resources, 59(1), 6383.CrossRefGoogle Scholar
Beatty, J. E., Baldridge, D. C., Boehm, S. A., Kulkarni, M., & Colella, A. J. (2019). On the treatment of persons with disabilities in organizations: A review and research agenda. Human Resource Management, 58(2), 119137.CrossRefGoogle Scholar
Bogenschutz, M., Im, H., & Liang, A. (2016). Ecological model of a good life for people with disabilities in Vietnam. Global Social Welfare, 3(4), 243254.CrossRefGoogle Scholar
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984). Classification and regression trees. Monterey: Brooks/Cole Publishing.Google Scholar
Cavanagh, J., Bartram, T., Meacham, H., Bigby, C., Oakman, J., & Fossey, E. (2017). Supporting workers with disabilities: A scoping review of the role of human resource management in contemporary organisations. Asia Pacific Journal of Human Resources, 55(1), 643.CrossRefGoogle Scholar
Chan, F., Strauser, D., Maher, P., Lee, E.-J., Jones, R., & Johnson, E. T. (2010). Demand-side factors related to employment of people with disabilities: A survey of employers in the Midwest region of the United States. Journal of Occupational Rehabilitation, 20(4), 412419.CrossRefGoogle ScholarPubMed
Choe, C., & Baldwin, M. L. (2017). Duration of disability, job mismatch and employment outcomes. Applied Economics, 49(10), 10011015.CrossRefGoogle Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: L. Erlbaum Associates.Google Scholar
Commonwealth of Australia. (2021). Australia’s Disability Strategy 2021-2031. Retrieved March 9, from https://www.disabilitygateway.gov.au/sites/default/files/documents/2021-11/1786-australias-disability.pdf.Google Scholar
Downs, Y., & Swailes, S. (2013). A capability approach to organizational talent management. Human Resource Development International, 16(3), 267281.CrossRefGoogle Scholar
Dreaver, J., Thompson, C., Girdler, S., Adolfsson, M., Black, M. H., & Falkmer, M. (2020). Success factors enabling employment for adults on the autism spectrum from employers’ perspective. Journal of Autism and Developmental Disorders, 50(5), 16571667.CrossRefGoogle ScholarPubMed
Evans, J. R., & Mathur, A. (2005). The value of online surveys. Internet Research, 15(2), 195219.CrossRefGoogle Scholar
Fonarow, G. C., Adams, K. F., Abraham, W. T., Yancy, C. W., Boscardin, W. J., Adhere Scientific Advisory Committee, S. G., & Investigators, F. T. (2005). Risk stratification for in-hospital mortality in acutely decompensated heart failure: Classification and regression tree analysis. JAMA: The Journal of the American Medical Association, 293(5), 572580.CrossRefGoogle ScholarPubMed
Fraser, R., Ajzen, I., Johnson, K., Hebert, J., & Chan, F. (2011). Understanding employers’ hiring intention in relation to qualified workers with disabilities [Research paper]. Journal of Vocational Rehabilitation, 35(1), 111.CrossRefGoogle Scholar
Ge, Z. M., Chen, R. X., Tang, W. Z., & Cong, Y. (2021). Why strong employment support for persons with disabilities has not brought about positive outcomes? A qualitative study in mainland China. Children and Youth Services Review, 121, .CrossRefGoogle Scholar
Gilbride, D., Stensrud, R., Vandergoot, D., & Golden, K. (2003). Identification of the characteristics of work environments and employers open to hiring and accommodating people with disabilities. Rehabilitation Counseling Bulletin, 46(3), 130137.CrossRefGoogle Scholar
Gould, R., Mullin, C., Parker Harris, S., & Jones, R. (2022). Building, sustaining and growing: Disability inclusion in business. Equality, Diversity and Inclusion, 41(3), 418434.CrossRefGoogle Scholar
Greenan, J. P., Wu, M., & Black, E. L. (2002). Perspectives on employing individuals with special needs. The Journal of Technology Studies, 28(1/2), .CrossRefGoogle Scholar
Greene, M. Z., Hughes, T. L., Hanlon, A., Huang, L., Sommers, M. S., & Meghani, S. H. (2019). Predicting cervical cancer screening among sexual minority women using Classification and Regression Tree analysis. Preventive Medicine Reports, 13, 153159.CrossRefGoogle ScholarPubMed
Hemphill, E., & Kulik, C. T. (2017). The tyranny of fit: Yet another barrier to mainstream employment for disabled people in sheltered employment. Social Policy & Administration, 51(7), 11191134.CrossRefGoogle Scholar
Ikutegbe, P., Randle, M., Sheridan, L., Gordon, R., & Dolnicar, S. (2023a). Factors and key interactions influencing successful employment outcomes for people with disabilities. Asia Pacific Journal of Human Resources, 125.Google Scholar
Ikutegbe, P., Randle, M., Sheridan, L., Gordon, R., & Dolnicar, S. (2023b). Successful employment outcomes for people with disabilities: A proposed conceptual model. Consulting Psychology Journal, 75(3), .CrossRefGoogle Scholar
Iles, P., Preece, D., & Chuai, X. (2011). Talent management as a management fashion in HRD: Towards a research agenda. Human Resource Development International, 13(2), 125145.CrossRefGoogle Scholar
International Labour Organization. (2023). Businesses leading the way on disability inclusion: A compilation of good corporate practices. Retrieved June 21 , 2024, from https://www.ilo.org/publications/businesses-leading-way-disability-inclusion.Google Scholar
Jones, M., Mavromaras, K., Sloane, P., & Wei, Z. (2014). Disability, job mismatch, earnings and job satisfaction in Australia. Cambridge Journal of Economics, 38(5), 12211246.CrossRefGoogle Scholar
Khayatzadeh-Mahani, A., Wittevrongel, K., Nicholas, D. B., & Zwicker, J. D. (2019). Prioritizing barriers and solutions to improve employment for persons with developmental disabilities. Disability & Rehabilitation, 42(19), 26962706.CrossRefGoogle ScholarPubMed
Kwan, C. K. (2021). Helping people with disabilities in the workplace: Mezzo-level interventions targeting corporate culture. Social Work, 66(4), 339347.CrossRefGoogle ScholarPubMed
Kwon, K., & Jang, S. (2021). There is no good war for talent: A critical review of the literature on talent management. Employee Relations: The International Journal, 44(1), 94120.CrossRefGoogle Scholar
Levitt, J. M. (2017). Developing a model of disability that focuses on the actions of disabled people. Disability & Society, 32(5), 735747.CrossRefGoogle Scholar
Lewis, R. J. (2000). An introduction to classification and regression tree (CART) analysis. Annual meeting of the Society for Academic Emergency Medicine, San Francisco, CA. Retrieved March 15, 2020, from https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.95.4103&rep=rep1&type=pdf.Google Scholar
Lindsay, S., McDougall, C., Menna-Dack, D., Sanford, R., & Adams, T. (2015). An ecological approach to understanding barriers to employment for youth with disabilities compared to their typically developing peers: Views of youth, employers, and job counselors. Disability & Rehabilitation, 37(8), 701711.CrossRefGoogle ScholarPubMed
Martin, B. C., & Honig, B. (2020). Inclusive management research: Persons with disabilities and self-employment activity as an exemplar. Journal of Business Ethics, 166(3), 553575.CrossRefGoogle Scholar
McDonough, J., Ham, W., Brooke, A., Wehman, P., Wright, T. S., Godwin, J. C., … Hurst, R. (2021). Health care executive perceptions of hiring and retention practices of people with disabilities: Results from executive focus groups. Rehabilitation Counseling Bulletin, 64(2), 7585.CrossRefGoogle Scholar
Meacham, H., Cavanagh, J., Bartram, T., & Laing, J. (2019). Ethical management in the hotel sector: Creating an authentic work experience for workers with intellectual disabilities. Journal of Business Ethics, 155(3), 823835.CrossRefGoogle Scholar
National Disability Insurance Agency. (2017). What is the NDIS? Retrieved April 24, from https://www.ndis.gov.au/about-us/what-ndis.Google Scholar
Oliver, M. (1996). Fundamental principles of disability. In Understanding disability (pp. 1929). London: Palgrave.CrossRefGoogle Scholar
O’Neill, J., Kang, H.-J., Sánchez, J., Muller, V., Aldrich, H., Pfaller, J., & Chan, F. (2015). Effect of college or university training on earnings of people with disabilities: A case control study. Journal of Vocational Rehabilitation, 43(2), 93102.CrossRefGoogle Scholar
Organisation for Economic Co-Operation and Development. (2022). Disability, work and inclusion. Retrieved July 21 , 2023, from https://doi.org/doi:https://doi.org/10.1787/1eaa5e9c-en.CrossRefGoogle Scholar
Pack, T. G., & Szirony, G. M. (2009). Predictors of competitive employment among persons with physical and sensory disabilities: An evidence-based model. Work, 33(1), 6779.CrossRefGoogle ScholarPubMed
Park, J. Y., & Park, E. Y. (2019) Factors affecting the acquisition and retention of employment among individuals with intellectual disabilities International Journal of Developmental Disabilities, 67(3), 188201.CrossRefGoogle ScholarPubMed
Poulsen, A. A., Johnson, H., & Ziviani, J. M. (2011). Participation, self-concept and motor performance of boys with developmental coordination disorder: A classification and regression tree analysis approach. Australian Occupational Therapy Journal, 58(2), 95102.CrossRefGoogle ScholarPubMed
Randle, M., & Reis, S. (2016). Changing community attitudes toward greater inclusion of people with disabilities: A rapid literature review. Retrieved November 29, from https://www.facs.nsw.gov.au/__data/assets/file/0008/372608/Rapid-Review-V3-interactive.pdf.Google Scholar
R Core Team. (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. Retrieved March 21, 2021, from https://www.R-project.org/.Google Scholar
Readhead, A., & Owen, F. (2020). Employment supports and outcomes for persons with intellectual and/or developmental disabilities: A review of recent findings. Current Developmental Disorder Reports, 7(3), 155162.CrossRefGoogle Scholar
Richards, J. (2022). Putting employees at the centre of sustainable HRM: A review, map and research agenda. Employee Relations: The International Journal, 44(3), 533554.CrossRefGoogle Scholar
Riddle, C. A. (2020). Why we do not need a ‘stronger’ social model of disability. Disability & Society, 35(9), 15091513.CrossRefGoogle Scholar
Rossiter, J. R. (2011). Measurement for the social sciences: The C-OAR-SE method and why it must replace psychometrics. New York: Springer.CrossRefGoogle Scholar
Royal Commission into Violence Abuse Neglect and Exploitation of People with Disability. (2021). Overview of responses to the employment issues paper. Royal commission into violence abuse neglect and exploitation of people with disability. Retrieved April 8, from https://disability.royalcommission.gov.au/system/files/2021-03/Overview%20of%20responses%20to%20the%20Employment%20Issues%20paper.pdf.Google Scholar
Schloemer-Jarvis, A., Bader, B., & Bohm, S. (2022). The role of human resource practices for including persons with disabilities in the workforce: A systematic literature review. The International Journal of Human Resource Management, 33(1), 4598.CrossRefGoogle Scholar
Scholz, F., & Ingold, J. (2020). Activating the ‘ideal jobseeker’: Experiences of individuals with mental health conditions on the UK Work Programme [Article]. Human Relations, 74(10), 16041627.CrossRefGoogle Scholar
Schur, L., Kruse, D., & Blanck, P. (2005). Corporate culture and the employment of persons with disabilities. Behavioral Sciences & the Law, 23(1), 320.CrossRefGoogle ScholarPubMed
Schur, L., Kruse, D., Blasi, J., & Blanck, P. (2009). Is disability disabling in all workplaces? Workplace disparities and corporate culture. Industrial Relations: A Journal of Economy and Society, 48(3), 381410.CrossRefGoogle Scholar
Sheehan, M., & Anderson, V. (2015). Talent management and organizational diversity: A call for research. Human Resource Development Quarterly, 26(4), .CrossRefGoogle Scholar
Sheridan, L. (2023). An Australian and New Zealand human resource management guide to work health and safety. Dunedin: University of Otago. Retrieved March 25 , 2023, from https://oercollective.caul.edu.au/conceptual-guide-whs-hr-managers-nz-au/chapter/compliance/.Google Scholar
Smart, J. F. (2009). The power of models of disability. The Journal of Rehabilitation, 75(2), 311.Google Scholar
Smart, J. F., & Smart, D. W. (2006). Models of disability: Implications for the counseling profession. Journal of Counseling and Development, 84(1), 2940.CrossRefGoogle Scholar
Stone, D. L., & Colella, A. (1996). A model of factors affecting the treatment of disabled individuals in organizations. Academy of Management Review, 21(2), 352401.CrossRefGoogle Scholar
Thompson, R., Bergman, M., Culbertson, S. S., & Huffman, A. H. (2013). Yes, we’re fishing—In rough waters for hard-to-find fish. Industrial and Organizational Psychology, 6(1), 6165.CrossRefGoogle Scholar
United Nations. (2018). Disability and development report: Realizing the Sustainable Development Goals by, for and with persons with disabilities. Author. Retrieved July 22 , 2022, from https://social.un.org/publications/UN-Flagship-Report-Disability-Final.pdf.Google Scholar
United Nations General Assembly. (2006). Convention on the Rights of Persons with Disabilities. Author. Retrieved May 7 , 2019, from https://www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_RES_61_106.pdf.Google Scholar
UPIAS. (1976). The Union of the Physically Impaired Against Segregation and the Disability Alliance discuss fundamental principles of disability. Union of the Physically Impaired Against Segregation. https://disabledpeoplesarchive.com/wp-content/uploads/sites/39/2021/01/001-FundamentalPrinciplesOfDisability-UPIAS-DA-22Nov1975.pdf.Google Scholar
Van Berkel, R. (2021). Employer engagement in promoting the labour-market participation of jobseekers with disabilities: An employer perspective. Social Policy and Society, 20(4), 533547.CrossRefGoogle Scholar
Vornholt, K., Villotti, P., Muschalla, B., Bauer, J., Colella, A., Zijlstra, F., … Corbiere, M. (2018). Disability and employment – Overview and highlights. European Journal of Work Organizational Psychology, 27(1), 4055.CrossRefGoogle Scholar
Waghorn, G., Parletta, V., & Dias, S. (2019). The influence of wage subsidies on the open employment of people with disabilities. The Journal of Rehabilitation, 85(4), 2432.Google Scholar
Wen, B., Van Rensburg, H., O’Neill, S., & Attwood, T. (2023). Autism in the Australian workplace: The employer perspective. Asia Pacific Journal of Human Resources, 61(1), 146167.CrossRefGoogle Scholar
World Health Organisation. (2011). World Report on Disability. Author. Retrieved March 5, from https://www.who.int/publications/i/item/9789241564182.Google Scholar
World Health Organization. (2022). Global report on health equity for persons with disabilities. Retrieved June 21 , 2024, from https://www.who.int/publications/i/item/9789240063624.Google Scholar
Zhang, H., & Singer, B. (1999). Recursive partitioning in the health sciences. New York: Springer.CrossRefGoogle Scholar
Figure 0

Table 1. Sample characteristics

Figure 1

Table 2. Characteristics of participants with disabilities

Figure 2

Figure 1. Regression tree for people with disabilities.

Figure 3

Table 3. Regression tree results for people with disabilities

Figure 4

Figure 2. Regression tree for people without disabilities.

Figure 5

Table 4. Regression tree results for people without disabilities