on-demand economy in victoria: a survey report...on-demand economy in victoria: a survey report...

On-demand Economy in Victoria: A Survey Report

Tracey Shea David Nikolas Brodsky

Brian Cooper Cathy Sheehan Ross Donohue Helen De Cieri

26 March 2020

26 MARCH 2020 - ON-DEMAND ECONOMY REVIEW 2020 | 1

TO CITE THIS REPORT

Shea, T., Brodsky, D.N., Cooper, B., Sheehan, C., Donohue, R., & De Cieri, H. (2020). On-demand Economy in Victoria: A Survey Report. Monash Business School, Monash University: Caulfield East, VIC, Australia.

ACKNOWLEDGEMENTS We gratefully acknowledge the generous support provided by WorkSafe Victoria and the Institute for Safety, Compensation and Recovery Research (ISCRR) for the research. We also acknowledge research assistance provided by Trisha Pettit, Monash University.

DISCLAIMER The information provided in this document can only assist an individual or organisation in a general way. Monash University is not engaged in rendering specific professional advice and Monash University accepts no liability arising from the use of, or reliance on, the material contained in this document. Before relying on the material, users should carefully make their own assessment as to its accuracy, currency, completeness and relevance for their purposes, and should obtain any appropriate professional advice relevant to their particular circumstances. The material in this report is subject to copyright rights, if any person wishes to use, reproduce or adapt the material in this report, please contact the authors.


TABLE OF CONTENTS

1 EXECUTIVE SUMMARY ................................................................................................................... 9

1.1 Background and aims ................................................................................................................................ 9

1.2 Research method ........................................................................................................................................ 9

1.3 Major findings ............................................................................................................................................... 9

1.4 Limitations ................................................................................................................................................... 11

1.5 Conclusions ................................................................................................................................................ 11

2 BACKGROUND ............................................................................................................................... 12

2.1 Aim of this report ....................................................................................................................................... 12

3 RESEARCH METHOD .................................................................................................................... 13

3.1 Sample and procedure ............................................................................................................................ 13

3.2 Survey measures ...................................................................................................................................... 13

4 RESULTS ........................................................................................................................................ 15

4.1 Characteristics of gig workers and the gig working environment .............................................. 15

4.2 Motivations and perceptions of work in the gig economy ............................................................ 32

4.3 Safety in the gig economy ...................................................................................................................... 36

4.4 Health and wellbeing in the gig economy .......................................................................................... 54

5 SUMMARY AND CONCLUSIONS .................................................................................................. 62

5.1 Gig workers and their working environment ..................................................................................... 62

5.2 Safety and the gig economy .................................................................................................................. 64

5.3 Health and wellbeing in the gig economy .......................................................................................... 65

5.4 Limitations ................................................................................................................................................... 65

5.5 Conclusions ................................................................................................................................................ 66

6 REFERENCES ................................................................................................................................ 67


LIST OF FIGURES

Figure 1: Main source of income ............................................................................................................. 15

Figure 2: Distribution of gender ............................................................................................................... 15

Figure 3: Distribution of age .................................................................................................................... 16

Figure 4: Education ................................................................................................................................. 16

Figure 5: Country of birth ........................................................................................................................ 17

Figure 6: Region of birth for respondents born overseas ........................................................................ 17

Figure 7: Citizenship status ..................................................................................................................... 18

Figure 8: Language spoken at home ...................................................................................................... 18

Figure 9: Relationship status ................................................................................................................... 19

Figure 10: Number of dependent children ............................................................................................... 19

Figure 11: Other unpaid caring responsibilities ....................................................................................... 20

Figure 12: Level of remoteness for home address .................................................................................. 20

Figure 13: Number of platforms used by respondents ............................................................................ 21

Figure 14: Region of work ....................................................................................................................... 24

Figure 15: Location of work ..................................................................................................................... 24

Figure 16: Length of time doing gig work ................................................................................................ 25

Figure 17: Typical hours per week spent working ................................................................................... 25

Figure 18: Payment for gig work ............................................................................................................. 26

Figure 19: Hourly pay rate for gig work ................................................................................................... 26

Figure 20: Average number of times where pay was withheld ................................................................ 27

Figure 21: Total annual income ............................................................................................................... 27

Figure 22: Distribution of country of birth by gender ............................................................................... 28

Figure 23: Dependent children under 18 years by gender ...................................................................... 28

Figure 24: Unpaid caring responsibilities by gender ............................................................................... 29

Figure 25: Main source of income by gender .......................................................................................... 29

Figure 26: Type of work by gender ......................................................................................................... 30

Figure 27: Location of work by gender .................................................................................................... 31

Figure 28: Hourly rate by gender ............................................................................................................ 31

Figure 29: Annual income by gender ...................................................................................................... 32

Figure 30: Motivations for working in the gig economy ........................................................................... 33

Figure 31: Distributive justice .................................................................................................................. 34

Figure 32: Individual items of the distributive justice scale ..................................................................... 34

Figure 33: Challenging work ................................................................................................................... 35

Figure 34: Individual items of the challenging work scale ....................................................................... 35

Figure 35: Comparison of safety incidents for gig workers ..................................................................... 36

Figure 36: Average number of injury or illness ........................................................................................ 36

Figure 37: Average number of near misses ............................................................................................ 37

Figure 38: Preventative action following injury or illness ......................................................................... 37


Figure 39: Perceived risk in the gig economy ......................................................................................... 38

Figure 40: Safety compliance in the gig economy .................................................................................. 38

Figure 41: Individual items of the safety compliance scale ..................................................................... 39

Figure 42: Safety motivation in the gig economy .................................................................................... 40

Figure 43: Individual items of the safety motivation scale ....................................................................... 40

Figure 44: Experience of violence and aggression ................................................................................. 41

Figure 45: Perpetrators of violence and aggression ............................................................................... 41

Figure 46: Reporting of violence and aggression .................................................................................... 42

Figure 47: Reporting channel for violence and aggression ..................................................................... 42

Figure 48: Support received following the experience of violence and aggression ................................ 43

Figure 49: Sources of support following the experience of violence and aggression ............................. 43

Figure 50: Experience of sexual harassment .......................................................................................... 44

Figure 51: Perpetrators of sexual harassment ........................................................................................ 44

Figure 52: Reporting of sexual harassment ............................................................................................ 45

Figure 53: Reporting channel for sexual harassment ............................................................................. 45

Figure 54: Support received following the experience of sexual harassment ......................................... 46

Figure 55: Sources of support following the experience of sexual harassment ...................................... 46

Figure 56: Experience of racial vilification ............................................................................................... 47

Figure 57: Perpetrators of racial vilification ............................................................................................. 47

Figure 58: Reporting of racial vilification ................................................................................................. 48

Figure 59: Reporting channels for racial vilification ................................................................................. 48

Figure 60: Support received following the experience of racial vilification .............................................. 49

Figure 61: Sources of support following the experience of racial vilification ........................................... 49

Figure 62: Comparison of safety incidents by gender ............................................................................. 50

Figure 63: Comparison of safety incidents by age .................................................................................. 50

Figure 64: Comparison of safety incidents by country of birth ................................................................ 51

Figure 65: Comparison of safety incidents by citizenship ....................................................................... 51

Figure 66: Personal wellbeing ................................................................................................................. 54

Figure 67: Individual items of the personal wellbeing index .................................................................... 55

Figure 68: Average scores on the brief resilience scale ......................................................................... 56

Figure 69: Comparing gig workers to established norms on the brief resilience scale ........................... 56

Figure 70: Individual items FROM the brief resilience scale ................................................................... 57

Figure 71: Average scores on the self-esteem scale .............................................................................. 57

Figure 72: Self-esteem ............................................................................................................................ 58

Figure 73: Individual items of the self-esteem scale ............................................................................... 59

Figure 74: Learning ................................................................................................................................. 60

Figure 75: Individual items of the learning subscale ............................................................................... 60

Figure 76: Vitality .................................................................................................................................... 61

Figure 77: Individual items of the vitality subscale .................................................................................. 61


LIST OF TABLES

Table 1: Definitions of constructs used in this report ................................................................................ 6

Table 2: Brief description of digitial platforms used by survey respondents ............................................. 8

Table 3: Multi-item measures used in the survey .................................................................................... 13

Table 4: Distribution of respondents across type of work by main source of income ............................. 21

Table 5: Distribution of respondents across platforms by main source of income .................................. 23

Table 6: Distribution of respondents across platforms by gender ........................................................... 30

Table 7: Comparison of average number of safety incidents by type of work ......................................... 52

Table 8: Comparison of average number of safety incidents across platforms ...................................... 53


LIST OF DEFINITIONS

Several terms used in this report may be unfamiliar to some readers so we provide a list below.

TABLE 1: DEFINITIONS OF CONSTRUCTS USED IN THIS REPORT Term Definition

Aggression “Deviant behaviour with intent to harm.”1 (p.456). Digital platform Definitions of the digital platform vary across disciplines. However, for

the purposes of this report we define digital platform as a “type of digital portal [that] facilitate[s] online exchanges between users and those providing services in the gig economy. These platforms host the various business functions specifically related to gig economy activity.”2 (p. 21). More specifically, we focus on labour based digital platforms that mediate work (e.g., Uber) rather than the use of assets (e.g., AirBNB).3

Distributive justice “Distributive justice is defined as the fairness associated with the … distribution of resources within an organisation (Colquitt, 2001) ... [it] pertains to the allocation of financial or nonfinancial resources, such as giving a bonus to an employee who has achieved some assigned organizational or performance targets. The resources distributed may be tangible (financial) … or intangible (nonfinancial) such as praise. Distributive justice is perceived to be achieved when employees notice that their efforts and rewards are assessed equally.”4 (p.799-800).

Gig work Gig work, which is the basis of the digital platform, has evolved out of earlier industry practices which in the context of this report represents “short-term contracts mediated by digital platform businesses.”3 (p. 1).

Microwork Microwork consists of “specialist services where providers perform fragmented and standardised micro-tasks … often repetitive and unqualified, they consist for example in identifying or naming objects on images, transcribing invoices, translating snippets of text, moderating content (such as videos), sorting or classifying search results, responding to online surveys.”5 (p. 1).

Near misses “Any unplanned incidents that occurred at the workplace which, although not resulting in any injury or disease, had the potential to do so.”6 (p. 6).

On-demand economy The on-demand economy is also known as the gig economy and the collaborative economy. “The gig economy involves exchange of labour for money between individuals or companies via digital platforms that actively facilitate matching between providers and customers, on a short-term and payment by task basis.”2 (p. 12).

Remoteness classifications “The Remoteness Structure of the Australian Statistical Geography Standard (ASGS) … divides each state and territory into several regions on the basis of their relative access to services.” (p. 4).7 The remoteness scores range from 0 (high accessibility to services centres) to 15 (high remoteness from services centres). The remoteness index results in several remoteness categories: • major city (e.g., Melbourne, Geelong); • inner regional (e.g., Ballarat, Bendigo); • outer regional (e.g., Horsham, Bairnsdale); • remote (e.g., Cowangie, Bonang); and • very remote (none in Victoria).

Resilience “… resilience has been defined in a variety of ways, including the ability to bounce back or recover from stress, to adapt to stressful circumstances, to not become ill despite significant adversity, and to function above the norm in spite of stress or adversity.”8 (p. 194).

Safety compliance “Core safety activities that need to be carried out by individuals to maintain workplace safety.”9 (p. 947). Examples of safety compliance activities could include, but are not limited to, lockout procedures and wearing personal protective equipment.10


Term Definition Safety motivation “An individual’s willingness to exert effort to enact safety behaviours

and the valence associated with those behaviours. Individuals should be motivated to comply with safe working practices and to participate in safety activities if they perceive that there is a positive safety climate in the workplace.”9 (p. 947).

Self-esteem “Self-esteem is literally defined by how much value people place on themselves. It is the evaluative component of self-knowledge. High self-esteem refers to a highly favorable global evaluation of the self. Low self-esteem, by definition, refers to an unfavorable definition of the self.”11 (p. 2).

Thriving “Thriving is a psychological state composed of the joint experience of vitality and learning … people who are thriving experience growth and momentum marked by both a sense of feeling energized and alive (vitality) and a sense that they are continually improving and getting better at what they do (learning).”12 (p. 250)

Violence “High intensity, physically aggressive behavior.”1 (p. 456). Wellbeing “‘Wellbeing’ refers to a positive rather than neutral state, framing health

as a positive aspiration. This definition was adapted by the 1986 Ottawa charter, which describes health as ‘a resource for everyday life, not the object of living’. From this perspective health is a means to living well, which highlights the link between health and participation in society.”13


SUMMARY OF PLATFORMS

Table 2 below is a list of digital platforms used by survey respondents along with a brief description of the services offered by each platform.

TABLE 2: BRIEF DESCRIPTION OF DIGITIAL PLATFORMS USED BY SURVEY RESPONDENTS Platform Description

99des igns Design (e.g., websites, logos, merchandise advertising, packaging) Ai r taske r Broad range of tasks (e.g., cleaning, removalists, odd jobs, marketing, gardening)

Amazon MTurk Microtasks (e.g., simple repetitive tasks, content moderation, data collection) Black lane Transport (i.e., chauffeur service)

Care Co l lec t i ve Broad range of disability support services (e.g., transport, therapists, support workers) Care Suppor t Ne twork Disability support services (e.g., assistance with NDIS funding)

Care .com Caring services (e.g., childcare, aged care, tutors, pet care, housekeepers) Care r So lu t i ons Aus t ra l i a Community support services (e.g., disability support)

Careseeke rs Aged care and disability support Cho iceOne Recruitment service

Cl i ckworke r Microtasks (e.g., surveys, categorisation and tagging, web research) Connec t ing Up IT support services (e.g., training, project management, technical support)

CoSea ts Transport (e.g., ridesharing) De l i ve roo Food delivery service

Des ignCrowd Design (e.g., logos, business card design, web design, t-shirt design) Did i Chux ing Transport (i.e., taxi service)

Dr ibbb le Design (e.g., graphic design, product design) EASI Food delivery service

F i rs t2Care Disability support services (e.g., assistance with NDIS funding) F ive r r Freelance services (e.g., professional services including design, marketing, writing)

Free lance r Broad range of freelance services (e.g., data processing, writing, design, web design) Glamazon Beauty services

GoCatch Transport (i.e., taxi service) Guru Freelance (e.g., programming, writing, design, administrative)

He lp l i ng Cleaning services Hipages Tradespeople (e.g., plumber, electrician, carpenter)

Hi reup Disability support services (e.g., assistance with NDIS funding) Home Care Heroes Home care support (e.g., companionship, nonmedical support)

JobBoy Microtasks (e.g., commenting on social media pages and forums, writing) LASHD Beauty and wellness services

L ionb r idge Smar t C rowd Freelance (e.g., evaluating web content, evaluating map quality) Ly f t Transport (e.g., taxi, food delivery service)

Mab le Aged care and disability support MadPaws Pet services (e.g., pet sitting, pet day care, dog walking, dog grooming)

Menu log Food delivery service Mic roWorke rs Microwork (e.g., image mining, transcribing, surveys, image transcription)

Newly Caring services (e.g., aged care, healthcare, disability support, personal care) ODesk Freelance (e.g., web development, design, writing, administrative, accounting)

Ola Transport (i.e., taxi service) Onef la re Broad range of tasks (e.g., cleaning, removalists, odd jobs, accounting, gardening)

Pawshake Pet services (e.g., pet sitters, boarding, dog walking) Peop lePerHour Freelance services (e.g., translation, design, wealth managers, composers, illustration)

Shebah Transport (i.e., taxi service for women and children) Sherpa Transport (i.e., courier service) Sho fe r Transport (i.e., taxi service)

Sidek icke r Recruitment service Ta l i xo Transport (i.e., taxi service)

TaskRabb i t Broad range of tasks (e.g., cleaning, removalists, odd jobs, accounting, gardening) Tax i f y Transport (i.e., taxi service)

Toodoo loo Transport (i.e., taxi service) Top ta l Freelance (e.g., software development, design, finance, project management)

Uber Transport (i.e., taxi service) UberEATS Food delivery service

Upwork Freelance (e.g., web development, design, writing, administrative, accounting) WeGoLook Information gathering, inspection services (e.g., vehicles, property, brand compliance)

Zoom2U Transport (i.e., courier service)


1 EXECUTIVE SUMMARY

1.1 Background and aims

This report presents results of a survey conducted with Victorian workers who have, in the past 12 months, found paid work through a labour-based digital platform or app, also known as ‘gig’ work. Examples of gig work include driving passengers, food delivery services, professional work (e.g., legal advice), creative work (e.g., writing), administrative work, skilled manual work (e.g., plumber) or other personal services (e.g., cleaning). The aim of the report is to present WorkSafe Victoria with an overview of the characteristics of gig workers and their working environment in the State of Victoria, as well as their motivations for working in the on-demand economy. We also report on respondent perceptions of their health, safety and wellbeing as well as self-reported safety incidents (i.e., injury or illness, near misses, violence and aggression, sexual harassment and racial vilification).

1.2 Research method

This report is based on data collected using a Qualtrics panel conducted between January and March 2020. Prospective respondents were invited to participate in an online survey about their health, safety and wellbeing. The survey targeted people who reported working as gig workers in the on-demand economy in the last 12 months and who were based in the State of Victoria. The survey included questions on:

• respondent demographics (e.g., gender, age, education); • characteristics of their gig work (e.g., platform, time working in gig economy, location of work); • experience of gig work (e.g., motivation to work in gig economy, level of challenge); • safety (e.g., safety compliance, safety motivation, injuries, violence and aggression, sexual

harassment and racial vilification); and • health and wellbeing (e.g., wellbeing, resilience, self-esteem, thriving). The analysis in this report is presented using three comparisons: 1) all gig workers who participated in the survey (n = 1,015), and then two subgroups from within the sample; 2) respondents who reported that their main income was from gig work (n = 353); and 3) respondents who reported that their main income was from non-gig work (n = 576). In addition to the two subsets, there were a small number of gig workers who indicated that their main source of income was a government allowance including Newstart, disability support, age pension, youth allowance, Austudy, ABSTUDY, carer and parenting payments or other income (n = 86).

1.3 Major findings

1. Characteristics of gig workers. Respondents tended to be female, 33 years of age on average, with an education level at Bachelors degree or above. Paradoxically, while respondents whose main income was gig work tended to have a lower level of education compared to those whose main income was non-gig work, a higher proportion of these workers were also more likely to have a Masters degree or a PhD compared to those whose main source of income was non-gig work. Nearly all of the gig workers in the sample lived in the Melbourne area with few living in regional or remote areas. The majority of respondents were born in Australia and of those who were born elsewhere, most reported being born in Asia or Europe The respondents reported working in a range of industries with skilled trades, caring services, transport and food delivery, commercial or industrial services, catering and hospitality as well as writing and translation being the most prominent. More than half of the respondents in the sample worked across multiple platforms, with the main platforms being Airtasker, UberEATS and Uber. Deliveroo, Fiverr, Freelancer and Menulog were also platforms used by a substantial number of respondents in the sample. The main working location for respondents was at home. Fewer respondents worked from their car or bike, or the home or business of a client. Generally, nearly half of the respondents in the sample reported earning between $15 and $30 per hour.

2. Gender differences. Examining the characteristics of gig workers and their working environment revealed few differences across gender. As noted, respondents who identified as female were more likely to report non-gig work as their main source of income, while respondents who


identified as male were more likely to report that gig work was their main source of income. Respondents who identified as female were more likely to report working in caring services, domestic services, writing and translation and clerical and data entry. Respondents who identified as male were more likely to report working in transport and food delivery, odd jobs and maintenance work and professional services. While most gig workers tended to work from home, the dominant location of work differed between genders, with those respondents who identified as female being more likely to work at the home of a client and respondents who identified as male being more likely to work from a form of transport (e.g., car or bike).

3. Motivations and experience of working in the gig economy. Overall, the more common reasons respondents gave for working in the gig economy were to choose their own hours, because they enjoy the work they do, can work at their own pace, can choose their own tasks or projects and are able to complement the pay from other work. Respondents whose main income was gig work were much more likely to report that they worked in the gig economy because they had to work from home due to a disability or could not find other employment. Interestingly, respondents generally reported that their gig income was justified relative to their performance and reflects the effort they put into their work. They also tended to see their work as challenging and enabling them to use their skills and abilities. However, respondents whose main income was non-gig work tended to rate these items lower than those whose main income was gig work.

4. Safety in the gig economy. Overall, 36.9% of respondents reported experiencing some kind of safety incident in the last 12 months. The more commonly experienced safety issues for respondents in the sample were violence and aggression, near misses and racial vilification. The more common safety incidents experienced by respondents whose main income was gig work were violence and aggression and injury or illness while. The more common safety incidents experienced by respondents whose main income was non-gig work violence and aggression, near misses and racial vilification. Generally, respondents did not perceive high levels of risk in their environment although this was more pronounced for respondents whose main income was non-gig work. They also tended to rate their safety compliance and safety motivation at relatively high levels, which is consistent with earlier studies.14 Comparing safety incidents (injury or illness, near misses, violence and aggression, sexual harassment and racial vilification) across subgroups in the sample showed that there were statistically significant differences for country of birth where those born in Australia experienced higher levels of injury and illness, near misses and violence and aggression compared to those born elsewhere. No statistically significant differences were observed for gender, age group or citizenship status. Injuries, illness and near misses. Overall, 14.8% of respondents reported experiencing an injury or illness and 19.7% reported experiencing a near miss in the course of their gig work in the past 12 months. Respondents did not usually take further preventative action following the experience of injury or illness. It is not clear whether this is because most respondents in the sample do not perceive their working environment as risky or because they do not have established channels of reporting or safety training. Violence and aggression. Overall, 18.7% of the respondents reported experiencing violence and aggression in the course of their gig work in the 12 months preceding the survey. Most perpetrators of violence and aggression were clients, customers or passengers. Although respondents whose main income was gig work reported that supervisors or managers were the most likely perpetrator, those whose main income was non-gig work reported that family and friends of clients were the most likely perpetrators. Generally, respondents did not report their experiences of violence and aggression but when they did it was largely to the digital platform or another supervisor or manager. Respondents, whose main source of income was from gig work, were more likely to report their experience via the digital platform or the police, compared to those whose main income was from non-gig work. Those whose main income was from non-gig work were most likely to report to the digital platform or to a supervisor or manager. Of those who reported their experiences, most did not receive any support following the experience of violence and aggression. However, where they did receive support it tended to be from a range of sources including a supervisor or manager, counsellor and family or friends. To a lesser extent they received support from their digital platform, the police or a co-worker.


Sexual harassment. 9.7% of the respondents reported experiencing sexual harassment in the course of their gig work in the 12 months preceding the survey. Most perpetrators of sexual harassment were clients, customers or passengers. However, respondents also reported that other people who they described non-specifically (e.g., drunks, older men) were perpetrators and it is not clear what relationship these perpetrators had to the respondent or their work. While respondents generally did not report their experiences of sexual harassment to anyone, when they did, they tended to report their experiences to the digital platform and a supervisor or manager. Only respondents whose main income was from gig work said they reported their experiences of sexual harassment to the police. Of those who reported their experiences, most respondents did not receive any support following the experience of sexual harassment but where they did receive support it tended to be from a co-worker and to a lesser extent a supervisor or manager and family or friends. Racial vilification. Overall, 15.2% of the respondents reported experiencing racial vilification in the course of their gig work in the 12 months preceding the survey. Most perpetrators of racial vilification were clients, customers or passengers. Respondents also reported that supervisors or managers and co-workers were perpetrators. However, respondents also reported that other people who they described non-specifically (e.g., drunks, outsiders, members of the public) were perpetrators and it is not clear what relationship these perpetrators had to the respondent or their work. While respondents generally did not report their experiences of racial vilification to anyone, when they did, they tended to report their experiences to a supervisor or manager and the digital platform. Only respondents whose main income was from gig work said they reported their experiences to the police or family or friends. Only respondents whose main income was from non-gig work said they reported their experiences of racial vilification to a co-worker.

5. Health and wellbeing. Respondents in this sample reported low levels of health and wellbeing as measured the Australian Unity Personal Wellbeing Index where the average score for this sample was lower than established Australian norms. While most respondents were within the normal range for resilience and self-esteem they generally scored at the lower end of the normal range on both measures.

1.4 Limitations

We have used a cross-sectional survey with data collected at one point in time and as such we are not able to track changes in respondent perceptions over time in their social and economic context. This is important presently because we have collected data on workers in the Victorian gig economy prior to the major social and economic upheavals associated with the COVID-19 virus. While COVID-19 arose before the launch of this survey, the impact of COVID-19 in the Australian context has increased more recently. For example, respondent perceptions of risk or the likelihood of becoming ill in the course of their gig work are likely to have changed with the increased spread of COVID-19. Further, it could be expected that workers who rely of gig work, like others in the conventional economy, will be impacted by job losses and face economic choices such as needing to work due to the absence of sick pay or other entitlements. The current situation could be expected to have a profound impact on gig workers perceptions of risk, health, safety and wellbeing along with their financial security.

1.5 Conclusions This report summarises the characteristics and experiences of gig workers and their working environment in the State of Victoria. While interest in the gig economy has grown substantially in recent years, there is still very little quantitative research on gig workers in Australia. To date, McDonald and colleagues15 have provided the most extensive analysis of workers in the Australian gig economy. While this report focuses only on gig workers in Victoria, it extends that earlier research by investigating the motivations of gig workers in greater detail and by examining gig worker perceptions of their working environment and gig worker health, safety and wellbeing. The results also indicate that working in the on-demand economy is not necessarily experienced as exploitative. The gig workers in this study derived satisfaction from work and experienced their work as challenging, but there are vulnerabilities in terms of health, safety and wellbeing. However, the narrative that there are some workers within the on-demand economy who are more vulnerable than others is borne out in this research. We have noted that those who main income is gig work are more vulnerable to injury and illness, near misses, violence and aggression, sexual harassment and racial vilification. Further research is required to understand what drives these vulnerabilities and how to raise awareness of health, safety and wellbeing issues for workers in the on-demand economy.


2 BACKGROUND The on-demand, or gig, economy is a collection of markets16 that covers a wide range of jobs across industries where workers are hired to perform specific jobs, rather than hold ongoing employment within a workplace.17 The gig economy has been defined as involving an “exchange of labour for money between individuals or companies via digital platforms that actively facilitate matching between providers and customers, on a short-term and payment by task basis.”2 (p. 12). Gig work, which is the basis of these digital platforms, has also evolved out of earlier industry practices and while this short-term work that is flexible for both worker and workplace is not new, the evolution of the digital platform that facilitates this work is a growing phenomenon2 where digital platforms can now act as an intermediary between the worker and consumer.18, 19

The rise of the on-demand economy has resulted in new ways of working that bring an uneven distribution of opportunities and challenges for workers, employers, unions and regulators. Proponents of the on-demand economy point to the opportunities for autonomy, flexibility and growth. While highly skilled, entrepreneurial individuals may find this mode of working to be financially and personally satisfying,20 for those working in an unskilled environment, the on-demand economy may be more exploitative than rewarding.17, 21 Low skilled workers are unlikely to have the opportunities to develop the networks and skills that will enable them to operate effectively and safely within the on-demand economy.20 This divide, whereby some workers are empowered while others are open to exploitation, has substantial implications for occupational health and safety (OHS). Work in the on-demand economy is precarious by nature and there is evidence that those employed in such work may not receive adequate training or the resources necessary for them to understand their safety rights and obligations within the workplace. Previous research has suggested that those in precarious work are also more likely to experience physical injuries and greater exposure to risk21. This in turn potentially leads to associated problems with mental health outcomes such as anxiety or stress.20 Due to the fragmented and time pressured nature of gig work, gig workers may not have the resources to properly manage their own health and safety. Hence it is important to investigate the attitudes of gig workers towards their health, safety and wellbeing, and their motivations behind their engagement in the on-demand economy. The characteristics of gig workers and their environment and their motivations to engage in this kind of work are not fully understood.16, 19 Furthermore, there has been little research to date that is focused on the health, safety and wellbeing of gig workers, particularly in the Australian context. To understand the benefits and risks, as well as contextualise the areas of liability and responsibility associated with gig work, it is necessary to examine these issues in greater detail.

2.1 Aim of this report

The aim of this report is to develop an understanding of gig workers and their experiences of working in the on-demand economy in Victoria. Specifically, we investigated the:

• characteristics of gig workers in Victoria; • characteristics of the Victorian gig economy working environment; • gender differences in the Victorian gig economy; and • motivations for working in the gig economy. We also sought to understand:

• perceptions of risk; and • health, safety and wellbeing of gig workers.


3 RESEARCH METHOD

3.1 Sample and procedure

This report is based on data collected using a Qualtrics panel conducted between January and March 2020. The Qualtrics panel provides access to a large sample of adults in Victoria who are recruited online from a wide range of platforms. Prospective respondents were invited to participate in an online survey about their health, safety and wellbeing. The survey targeted people who reported working as gig workers in the on-demand economy in the last 12 months and who were based in the State of Victoria. The survey included questions on:

Victorian gig workers were identified using two items: 1. Do you currently live in the State of Victoria? 2. This survey asks about “gig work” that you have done in the past 12 months. We consider “gig

work” to be work that you have found through a labour-based digital platform or app. This work might include driving passengers, food delivery services, professional work (e.g., legal advice), creative work (e.g., writing), administrative work, skilled manual work (e.g., plumber) or other personal services (e.g., cleaning). At any time in the last 12 months, have you earned an income working through a labour-based digital platform as defined above?

Overall, 1,015 workers working across a broad range of digital platforms were recruited into the survey.

3.2 Survey measures

The survey included questions on:

• respondent demographics (e.g., gender, age, education); • characteristics of their gig work (e.g., platform, time working in gig economy, location of work); • experience of gig work (e.g., motivation to work in gig economy, level of challenge); • safety (e.g., safety compliance, safety motivation, injuries, violence and aggression,); and • health and wellbeing (e.g., personal wellbeing index, resilience, self-esteem, thriving). Table 3 below summarises the multi-item measures used in the survey. These measures are designed to elicit respondent attitudes, beliefs and feelings through a series of statements (items) that represent each construct included in the survey, and these measures are well validated in the academic literature.

TABLE 3: MULTI-ITEM MEASURES USED IN THE SURVEY

Measure Items Example item Motivations15, 22 12 “To be my own boss” Distributive justice23 4 “Does your gig work income reflect the effort you have put into your work?” Challenging work24 5 “My work lets me use my skills and abilities” Safety motivation25 3 “I feel that it is important to maintain safety at all times” Safety compliance25 3 “I ensure the highest levels of safety when I carry out my job” Personal wellbeing index26, 27 8 “How satisfied are you with your standard of living?” Resilience8 6 “I tend to bounce back quickly after hard times” Self-esteem28 10 “I feel that I have a number of good qualities” Thriving12 10 “I see myself continually improving”


Demographics

The survey recorded respondent demographics such as age, gender and education. We also collected details of respondent marital status and details of their caring responsibilities (e.g., dependent children or adults) and ethnicity (e.g., country of birth, language spoken at home, visa status). Finally, respondents were asked for the postcode of the area in which they lived and for their annual income.

Experience of working in the gig economy

Respondents were asked about their work role and experiences in the gig economy. These questions included the length of time they have been working in the gig economy, which platforms they used, the type of work they did, the typical number of hours they worked, the location from which they worked (e.g., at home, their car) and the region they worked in most of the time (e.g., Melbourne, Ballarat). They were also asked a series of questions regarding their income including how they were paid, their hourly rate, incidents where they were not paid and their main source of income (e.g., gig work, non-gig work). Finally respondents were asked to complete a series of multi-item measures about their motivation to work in the gig economy, how they were treated within the gig economy (i.e., distributive justice scale) and how they perceived their work (i.e., challenging work scale).

Safety

Respondents were asked about their safety while working in the gig economy. They were asked a series of single-item questions about injuries and illness and near misses experienced as a result of their work in the gig economy and the likelihood of becoming injured or ill as a result of their gig work. We also examined their experience of violence and aggression, sexual harassment and racism, abuse or mistreatment. These questions were either single item questions (i.e., frequency, reporting, and support) or open-ended questions (i.e., perpetrators, provision of support).They were also asked a series of questions about their safety motivation and safety compliance.

Health and wellbeing

Respondents were also asked about several aspects of their health and wellbeing. Health was measured via a single item in the personal wellbeing index (How satisfied are you with your health?). Wellbeing was measured from several multi-measures including the: personal wellbeing index, brief resilience scale, self-esteem scale and thriving at work scale.


4 RESULTS The analysis in this report is presented using three comparisons: 1) all gig workers who participated in the survey (n = 1,015), and then two subgroups from within the sample; 2) respondents who reported that their main income was from gig work (n = 353); and 3) respondents who reported that their main income was not from gig work (n = 576). These two subsets from the sample do not include a small number of gig workers who indicated that their main source of income was a government allowance including Newstart, disability support, age pension, youth allowance, Austudy, ABSTUDY, carer and parenting payments or other income (n = 86). Figure 1 below displays the distribution for the main source of income within the sample. This figure shows that less than half of the sample reported that gig work was their main source of income.

FIGURE 1: MAIN SOURCE OF INCOME

4.1 Characteristics of gig workers and the gig working environment

Characteristics of gig workers

As shown in Figure 2 below, just over half of the respondents identified as female. Less than one percent of the sample identified as non-binary or gender diverse. Compared to those who identified as male, respondents who identified as female were significantly more likely to report that their main income was from non-gig work rather than gig work (p < .05).

FIGURE 2: DISTRIBUTION OF GENDER

0%

20%

40%

60%

Main income is non-gig work Main income is gig work Main income is other

56.7%

34.8%

8.5%

0%

10%

20%

30%

40%

50%

60%

70%

All gig workers Main income is gig work Main income is non-gig work

39.1%44.5%

37.0%

59.9%54.6%

62.0%

1.0% 0.9% 1.0%

Male Female Non-binary / gender diverse


The average age of the gig workers in the sample was 33 years (SD = 11.5) which is consistent with earlier research in Australia15 and the United Kingdom.2 Figure 3 below displays the distribution of age for the sample, and shows that more than half of the respondents were aged 35 years or less and nearly all were aged 45 years or less with very few respondents being over 65 years of age. Respondents whose main income was from gig work were more likely to be younger (M = 30.8, SD = 10.1) than those whose main income was from non-gig work (M = 33.2, SD = 10.9), and this difference between the two groups was statistically significant (p = .001).

FIGURE 3: DISTRIBUTION OF AGE

Figure 4 below shows the distribution of education for the sample. Most of the sample reported having some level of post-secondary education, with half reporting that they had completed a bachelor’s degree or higher which is a slightly higher level of education than reported in earlier studies of gig workers.2 Respondents whose main income was from gig work were more likely to have a lower level of education (certificate level and below) compared to those whose main income was from non-gig work. However, there was a greater representation of respondents whose main income was gig work with a level of education beyond the bachelor’s degree (i.e., graduate diploma, master’s, PhD). The differences in level of education between the two groups was statistically significant (p = .048). However, the figure below shows a roughly consistent pattern for the level of education between the groups. Therefore, it should be noted that the chi-square test used to determine group differences is sensitive to sample size with small differences becoming significant in larger samples.

FIGURE 4: EDUCATION

0%

10%

20%

30%

40%


30.1%

36.8%

26.9%

35.2%37.1% 36.1%

20.8%16.4%

23.4%

8.6%6.5%

9.2%5.3%

3.1% 4.3%

18-25 years 26-25 years 36-45 years 46-55 years 55 years or more

0% 20% 40% 60% 80% 100%

All gig workers

Main income is gig work

Main income is non-gig work

5.6%

4.3%

5.7%

18.3%

20.2%

17.4%

15.8%

16.5%

12.8%

12.8%

11.7%

12.7%

30.8%

27.1%

35.9%

5.5%

7.1%

4.7%

10.9%

13.1%

10.8%

Less than Year 12 secondary school Year 12 secondary school or equivalent CertificateDiploma or Advanced Diploma Bachelor Degree Graduate Certificate or Graduate DiplomaMasters/PhD


Figure 5 below compares the percentage of the sample born in Australia and overseas. Overall, most respondents were born in Australia and this distribution within the sample was roughly consistent with the general population in Australia.29 The pattern between respondents roughly the same and there was no statistically significant difference between groups (p = .994).

FIGURE 5: COUNTRY OF BIRTH

Figure 6 below displays the distribution of respondents who were born overseas by geographical region. Most overseas born respondents reported being born in Asia or Europe. Fewer respondents reported being born in other regions including parts of Oceania that exclude Australia (e.g., New Zealand, Melanesia, Micronesia and Polynesia) and Africa or the Americas. This distribution was generally consistent across all gig workers but those respondents whose main income was from gig work were more likely to have been born in south-east Asia compared to those whose main income was non-gig work and this difference was significant (p = .001).

FIGURE 6: REGION OF BIRTH FOR RESPONDENTS BORN OVERSEAS

0%

20%

40%

60%

80%

100%


26% 26.1% 26.0%

74% 73.9% 74.0%

Born elsewhere Born in Australia

0% 20% 40% 60% 80% 100%

All gig workers

Main income is gig work

Main income is non-gig work

10.1%

13.3%

7.6%

13.0%

9.6%

13.8%

10.1%

6.0%

11.7%

3.2%

3.6%

2.8%

25.1%

14.5%

31.7%

7.3%

4.8%

9.7%

24.7%

38.6%

18.6%

4.5%

8.4%

2.1%

2.0%

1.2%

2.1%

Oceania North-west Europe Southern & Eastern Europe

North Africa & Middle East South-East Asia North-East Asia

Southern & Central Asia The Americas Sub-Saharan Africa


Figure 7 below shows the distribution of citizenship status for respondents not born in Australia. Nearly half of the respondents not born in Australia reported being Australian citizens with fewer respondents reporting that they were permanent residents or on temporary visas. Less than one percent reported their citizenship status as not determined. There was a roughly equivalent distribution of respondents whose main form of income was gig work across the categories of Australian citizen, permanent residents and temporary visa with none reporting their visa status as not determined. For those whose main income was non-gig work, most were either Australian citizens or permanent residents with few reporting visa status as not determined. However, these differences were not significant (p = .066).

FIGURE 7: CITIZENSHIP STATUS

Figure 8 below shows the main language spoken at home in the sample. Nearly all of the respondents in the sample reported speaking English at home and no statistically significant differences were observed between respondents whose main form of income was gig work compared to those whose main form of income was non-gig work (p > .05).

FIGURE 8: LANGUAGE SPOKEN AT HOME

The dominant languages, other than English, that were spoken at home were Indian languages (e.g., Punjabi, Urdu, Bengali, Gujurati, Hindu, Marathi), Chinese languages (e.g., Cantonese, Mandarin), Vietnamese, Korean, Sri Lankan (Singhalese, Tamil, Kannada), Arabic, Spanish, Greek, Russian and Macedonian. Other languages spoken at home by a small subset of the sample included Burmese, Croatian, Filipino, French, Hungarian, Indonesian, Italian, Japanese, Khmer, Malay, Persian, Polish and Ukrainian.

0%

10%

20%

30%

40%

50%


43.8%

35.2%

48.3%

31.2% 30.8% 30.9%

24.6%

34.1%

20.1%

0.4% 0.0% 0.7%

Australian citizen Permanent resident Temporary visa Status not determined

0%

20%

40%

60%

80%

100%


9.2% 8.2% 10.2%

90.8% 91.8% 89.8%

Language other than English English


Figure 9 below shows the relationship status of respondents in the sample. Overall, half of the respondents reported being partnered or married and just over a third reported that they had never been married, while few respondents reported being separated, divorced or widowed. Respondents whose main income was gig work tended to report that they had never married or were married at roughly equivalent levels while those whose main income was from non-gig work were more likely to report being partnered or married, although these differences were not statistically significant (p = .131).

FIGURE 9: RELATIONSHIP STATUS

Overall, just over a third of the respondents reported having dependent children (36.1%) with respondents whose main income was gig work reporting that they care for dependent children (36.8%) at roughly the same rate as those whose main income was non-gig work (35.6%).

Figure 10 below shows the distribution of the number of dependent children for those who reported caring for dependent children under the age of 18. Most of the respondents reported caring for one or two children under the age of 18 and few respondents reported caring for three or more children. Those whose main income was from gig work were more likely to report caring for one dependent child, and those whose main income was from non-gig work were equally likely to report caring for one or two dependent children, and this difference between groups was statistically significant (p = .010).

FIGURE 10: NUMBER OF DEPENDENT CHILDREN

0%

10%

20%

30%

40%

50%

60%


42.2%46.0%

39.0%

50.5% 49.1%53.4%

6.4% 4.3% 6.8%0.9% 0.6% 0.7%

Never married Partnered or married Separated or divorced Widowed

0% 10% 20% 30% 40% 50% 60%

One child

Two children

Three children or more

47.3%

39.4%

13.3%

58.9%

31.2%

9.9%

42.5%

43.8%

13.7%

Num

ber

of d

epen

dent

chi

ldre

n

Main income is non-gig work Main income is gig work All gig workers


Figure 11 below shows that most of the respondents in the sample do not have additional unpaid caring responsibilities. Overall, few respondents in the sample reported having additional unpaid caring responsibilities (e.g., an adult family member or friend who is not a dependent child) with respondents whose main income was gig work were more likely to report having additional unpaid caring responsibilities compared to those whose main income was non-gig work (20.5%) and this difference was statistically significant (p < .001).

FIGURE 11: OTHER UNPAID CARING RESPONSIBILITIES

Figure 12 below shows the level of remoteness for the sample which was ascertained from the respondents’ home postcodes. Statistically significant differences were observed with respondents whose main form of income was non-gig work being more likely to work in regional areas compared to those whose main income was gig work (p = .026).

FIGURE 12: LEVEL OF REMOTENESS FOR HOME ADDRESS

0%

20%

40%

60%

80%

100%


74.1% 66.0%79.2%

25.9% 34.0%20.8%

No unpaid caring responsibilities Unpaid caring responsibilities

0%

20%

40%

60%

80%

100%


82.1%88.5%

81.4%

15.3%10.3%

15.5%

2.5% 1.1% 3.0%0.1% 0.0% 0.2%

Major city Inner regional Outer regional Remote


Gig working environment

Table 4 below shows the type of work respondents have engaged in across the gig economy platforms. In general, transport and food delivery, caring services, creative and multimedia and clerical and data entry were the main types of work conducted by respondents in the sample. The distribution of respondents by group was roughly similar withe few differences in the type of work undertaken between groups. Respondents whose main source of income was gig work were more likely to work in caring services, domestic services and education compared to those whose main source of income was non-gig work. Respondents whose main source of income was from non-gig work were more likely to work in transport and food delivery and professional services compared to those whose main source of income was gig work. However, these differences were not statistically significant (p = .059).

TABLE 4: DISTRIBUTION OF RESPONDENTS ACROSS TYPE OF WORK BY MAIN SOURCE OF INCOME Type of work N (%) Main income gig Main income non-gig

Caring services 131 (12.9%) 15.0% 11.3% Clerical and data entry 112 (11.0%) 9.6% 11.6%

Commercial/Industrial services 33 (3.3%) 4.8% 2.6% Creative and multimedia 119 (11.7%) 11.3% 12.0%

Domestic services 74 (7.3%) 9.1% 6.1% Education 73 (7.2%) 9.1% 6.8%

Odd jobs and maintenance work 63 (6.2%) 6.5% 6.4% Personal services 20 (2.0%) 2.5% 1.6%

Professional services 46 (4.5%) 2.3% 6.3% Sales and marketing support 38 (3.7%) 3.7% 4.0%

Skilled trades work 25 (2.5%) 2.5% 2.4% Software development and technology 30 (3.0%) 3.4% 2.8%

Transport and food delivery 164 (16.2%) 14.4% 18.2% Writing and translation 44 (4.3%) 3.4% 4.3%

Other 43 (4.2%) 2.3% 3.6% Fewer than half of the respondents in the sample were registered with just one platform (45.8%) as respondents tended to work across multiple platforms over the past 12 months. On average, respondents whose main income was gig work tended to work across more platforms (M = 4.1, SD = 4.1) than those respondents whose main income was non-gig work (M = 2.4, SD = 3.0). This difference was statistically significant (p < .001).

FIGURE 13: NUMBER OF PLATFORMS USED BY RESPONDENTS

0%

10%

20%

30%

40%

50%

60%

1 platform 2 platforms 3 platforms 4 or more platforms

45.8%

18.5%

11.0%

24.6%

32.3%

15.9%11.0%

40.8%

51.4%

20.1%

11.8%16.7%



Table 5 below shows the distribution for gig economy platforms used by respondents in the sample in the past 12 months. Airtasker, an Australian company that provides a marketplace for people wishing to outsource tasks (e.g., cleaning, gardening, odd jobs), was the most used platform with more than a third of all respondents in the sample working through this platform. Approximately one quarter of the respondents in the sample worked with UberEATS or Uber to earn an income in the past year. These three platforms were the main platforms that respondents worked through irrespective of whether their main source of income was gig work or other non-gig work.


TABLE 5: DISTRIBUTION OF RESPONDENTS ACROSS PLATFORMS BY MAIN SOURCE OF INCOME Platform N (%) Main income gig Main income non-gig

99des igns 31 (5.1%) 8.2% 2.8% Ai r taske r 214 (35.4%) 28.3% 36.8%

Amazon MTurk 49 (8.1%) 12.5% 4.7% Black lane 22 (3.6%) 7.1% 0.7%

Care Co l lec t i ve 24 (4.0%) 11.0% 3.8% Care Suppor t Ne twork 26 (4.3%) 6.8% 1.2%

Care .com 42 (6.9%) 8.2% 3.5% Care r So lu t i ons Aus t ra l i a 33 (5.5%) 8.8% 3.6%

Careseeke rs 48 (7.9%) 12.7% 5.2% Cho iceOne 46 (7.6%) 11.0% 5.0%

Cl i ckworke r 45 (7.4%) 11.3% 4.9% Connec t ing Up 13 (2.1%) 4.2% 1.0%

CoSea ts 16 (2.6%) 5.1% 0.7% De l i ve roo 79 (13.1%) 18.4% 9.9%

Des ignCrowd 26 (4.3%) 5.4% 1.9% Did i Chux ing 15 (2.5%) 6.8% 1.4%

Dr ibb le 11 (1.8%) 3.1% 1.2% EASI 13 (2.1%) 2.8% 1.2%

F i rs t2Care 12 (2.0%) 3.7% 1.0% F ive r r 77 (12.7%) 13.3% 11.6%

Free lance r 66 (10.9%) 12.5% 10.4% Glamazon 18 (3.0%) 5.4% 1.2%

GoCatch 30 (5.0%) 7.1% 3.6% Guru 20 (3.3%) 6.5% 1.9%

He lp l i ng 9 (1.5%) 2.8% 1.2% Hipages 23 (3.8%) 4.0% 3.0%

Hi reup 17 (2.8%) 2.8% 2.1% Home Care Heroes 12 (2.0%) 3.1% 0.9%

JobBoy 10 (1.7%) 2.5% 1.6% LASHD 8 (1.3%) 2.3% 0.7%

L ionb r idge Smar t C rowd 9 (1.5%) 1.7% 0.7% Ly f t 17 (2.8%) 5.1% 1.7%

Mab le 11 (1.8%) 2.5% 1.0% MadPaws 28 (4.6%) 5.1% 4.9%

Menu log 62 (10.2%) 13.6% 9.4% Mic roWorke rs 24 (4.0%) 2.8% 3.0%

Newly 8 (1.3%) 1.7% 0.7% ODesk 10 (1.7%) 2.0% 1.6%

Ola 35 (5.8%) 9.3% 3.3% Onef la re 10 (1.7%) 2.5% 1.0%

Pawshake 14 (2.3%) 1.7% 2.8% Peop lePerHour 14 (2.3%) 2.3% 2.1%

Shebah 7 (1.2%) 2.5% 0.7% Sherpa 6 (1.0%) 1.4% 0.3% Sho fe r 5 (0.8%) 1.1% 0.3%

Sidek icke r 16 (2.6%) 3.1% 2.3% Ta l i xo 11 (1.8%) 2.5% 0.5%

TaskRabb i t 25 (4.1%) 4.2% 3.8% Tax i f y 34 (5.6%) 7.4% 3.0%

Toodoo loo 8 (1.3%) 2.0% 0.5% Top ta l 7 (1.2%) 2.3% 0.3%

Uber 151 (25.0%) 33.1% 19.8% UberEATS 161 (26.6%) 34.8% 21.0%

Upwork 41 (6.8%) 6.5% 5.9% WeGoLook 13 (2.1%) 2.3% 1.7%

Zoom2U 22 (3.6%) 4.8% 1.0% Other 92 (15.2%) 10.2% 17.4%


Figure 14 below shows the geographical region where the respondents in the sample work. Nearly all of the respondents worked in the Melbourne area. Less than 20 percent of respondents reported working in regional areas.

FIGURE 14: REGION OF WORK

Figure 15 below shows where the respondents perform their work. Nearly half of the respondents reported working from home. Other dominant areas of work included driving their car (scooter, motorbike, or bicycle) and at the home or business of their employer. Few respondents reported working in other locations such as co-working spaces or public spaces such as libraries or cafes.

Respondents whose main income was gig work were less likely to report working at the business of a client compared to those whose main income was non-gig work. Those whose main income was non-gig work were more likely to report working from a mode of transport (e.g., car, bike) compared to those whose main income was gig work. These differences were statistically significant (p = .015).

FIGURE 15: LOCATION OF WORK

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Warrnambool & South West

Shepparton

North West

Latrobe – Gippsland

Hume

Geelong

Bendigo

Ballarat

Melbourne

0.9%

1.4%

1.2%

2.8%

1.7%

3.5%

4.6%

2.9%

80.9%

0%

10%

20%

30%

40%

50%


46.1% 46.0% 45.5%

16.7%18.6%

15.2%13.6%17.1%

11.8%

18.5%14.9%

21.7%

2.5% 1.7% 2.9%2.5% 1.7% 3.0%

At my home Home of the client Business of clientCar, motorbike, scooter, bicycle Coworking space Library, café, other public space


Figure 16 below shows the distribution of work tenure in the on-demand economy by group. On average, respondents in the sample reported working in the on-demand economy for approximately two years. Those respondents who reported that the on-demand economy was their main source of income reported having worked in the on-demand economy for an average of 2.7 years (SD = 2.7) while those whose main source of income was outside the on-demand economy reported having worked within the on-demand economy for an average of 2 years (SD = 2.6). This difference was statistically significant (p < .001).

FIGURE 16: LENGTH OF TIME DOING GIG WORK

Figure 17 below compares the average number of hours spent working in gig and non-gig work by group where respondents in the sample reported working, on average, 33.1 (SD = 19.4) hours per week. Overall, those respondents whose main income was from non-gig work spent, on average, a greater number of hours working per week (M = 34.1, SD = 17.9) compared to those whose main income was gig work (M = 30.3, SD = 20.7). This difference in total hours worked was statistically significant (p = .004).

Respondents who reported that their main source of income was from gig work reported working an average 17.2 (SD = 13.0) hours in the gig economy and an average 13.1 (SD = 13.4) hours in non-gig work. Respondents who reported that their main source of income was from non-gig work reported working an average 9.7 (SD = 9.3) hours in the gig economy and an average 24.4 (SD = 14.4) hours in non-gig work. These differences in hours spent in gig and non-gig work were statistically significant (p < .001).

FIGURE 17: TYPICAL HOURS PER WEEK SPENT WORKING

0.0

1.0

2.0

3.0


2.2

2.7

2.0

Year

s

0

10

20

30

40


12.2

17.2

9.7

18.9

13.1

24.4

31.1 30.3

34.1

Hou

rs p

er w

eek

Hours per week in gig work Hours per week in non-gig work Hours per week in all work


Figure 18 below shows the distribution of how respondents are paid for their gig work by group. In general, irrespective of their main source of income, more than half of gig workers reported being paid by completed job or task and approximately one third of respondents reported being paid for the hours they work. Few gig workers reported receiving a fixed income. No statistically significant differences were observed between the groups (p = .692).

FIGURE 18: PAYMENT FOR GIG WORK

Figure 19 below shows the distribution of respondents’ hourly pay rate for their gig work by group. Generally, nearly half of the respondents in the sample reported earning between $15 and $30 per hour. Few gig workers reported earning more than $50 per hour. Respondents whose main income was from gig work were more likely to report earning an hourly rate above $30. Respondents whose main income was from non-gig work were more likely to report an hourly rate below $30. These differences were statistically significant (p < .001).

FIGURE 19: HOURLY PAY RATE FOR GIG WORK

0%

10%

20%

30%

40%

50%

60%

70%


64.1% 62.8% 65.0%

30.3% 31.8% 29.2%

5.6% 5.4% 5.8%

Per completed task or job Paid by time or hours worked Fixed income

0%

10%

20%

30%

40%

50%

$0.01 - $14.99 $15.00 - $29.99 $30.00 - $49.99 $50.00 - $99.99 $100 or more

26.0%

47.0%

17.0%

7.2%

2.8%

20.7%

43.9%

20.4%

12.2%

2.7%

27.7%

49.4%

15.0%

4.8%3.1%



Figure 20 below shows the average number of times workers were not paid for their gig work over the past 12 months by group, with respondents whose main source of income was gig work being more likely to report not being paid for their work. Respondents who reported that their sole income was from the gig economy reported having not been paid approximately 4.1 (SD = 11.9) times over the past 12 months, while those who whose main source of income was outside the gig economy reported having not been paid approximately 2.4 (SD = 8.1) times over the past 12 months. The difference between groups was statistically significant (p = .020).

FIGURE 20: AVERAGE NUMBER OF TIMES WHERE PAY WAS WITHHELD

Figure 21 below shows the total annual income for respondents in the sample. Generally, more than half of the respondents earned less than $65,000 annually. Respondents whose main source of income was from gig work were more likely to earn lower levels of income (in the range of $1 to less than $41,600) than gig workers whose main income was non-gig work. Those whose main source of income was non-gig work were more likely to earn higher levels of income of $41,600 or more. This difference was statistically significant (p = .023).

FIGURE 21: TOTAL ANNUAL INCOME

0.0

1.0

2.0

3.0

4.0

5.0


3.1

4.1

2.4

0%

5%

10%

15%

20%

25%

30%

$1 - $15,599 $15,600 -$25,999

$26,000 -$41,599

$41,600 -$64,999

$65,000 -$90,999

$91,000 -$155,999

$156,000 ormore

12.7

%

12.5

%

14.3

%

22.1

%

19.1

%

15.1

%

4.3%

14.9

%

14.3

%

14.3

%

20.4

%

17.9

%

14.0

%

4.3%

9.4%

9.4%

12.9

%

24.6

%

21.7

%

17.3

%

4.8%



Selected comparisons across gender

Figure 22 below shows that respondents who identified as female were more likely to report being born in Australia compared to those who identified as male. However, this difference was not significant (p = .210).

FIGURE 22: DISTRIBUTION OF COUNTRY OF BIRTH BY GENDER

Overall, respondents who identified as female were more likely to report caring for dependent children under the age of 18 (39.2%) compared to those who identified as male (31.0%), and this difference was statistically significant (p = .005). Figure 23 below shows that respondents who identified as female were slightly more likely to care for multiple dependent children under the age of 18 years, but this pattern was not statistically significant (p = .147).

FIGURE 23: DEPENDENT CHILDREN UNDER 18 YEARS BY GENDER

0%

20%

40%

60%

80%

Male Female

28.5% 24.9%

71.5% 75.1%

Elsewhere Born in Australia

0%

20%

40%

60%

One child Two children Three children or more

54.1%

35.3%

10.5%

44.0% 41.2%

14.8%

Male Female


Figure 24 below shows that respondents who identified as female were slightly more likely to report having unpaid caring responsibilities for an adult family member or friend compared to those who identified as male. However, this difference was not significant (p = .195).

FIGURE 24: UNPAID CARING RESPONSIBILITIES BY GENDER

Figure 25 displays the distribution of income type by gender. While most respondents reported that non-gig work was their main source of income, respondents who identified as female were less likely than males to report that gig work was their main source of income. Respondents who identified as female were also more likely to report earning income from other sources (e.g., Newstart). This difference was statistically significant (p = .025).

FIGURE 25: MAIN SOURCE OF INCOME BY GENDER

0%

20%

40%

60%

80%

No unpaid caring responsibilities Unpaid caring responsibilities

76.6%

23.4%

72.9%

27.1%

Male Female

0%

10%

20%

30%

40%

50%

60%

70%

Gig work Non-gig work Other income

39.2%

53.9%

6.9%

31.4%

59.0%

9.6%

Male Female


Figure 26 displays the distribution across the types of work by gender. Respondents who identified as male were much more likely to work in transport and food delivery, skilled trades and odd jobs and maintenance work compared to participants who identified as female. Whereas, respondents who identified as female were more likely to report working in caring services, clerical and data entry, education and domestic work. These differences between genders for category of work were statistically significant (p < .001).

FIGURE 26: TYPE OF WORK BY GENDER

Table 6 below displays the gender distribution of respondents in the sample within platforms where differences by gender were statistically significant. Those respondents who identified as male were more likely to report being listed with the platforms: 99designs (p = .002), Amazon MTurk (p < .001), Blacklane (p = .033), Fiverr (p < .001), GoCatch (p = .023), JobBoy (p = .009), Lyft (p = 033), Uber (p = .001) and UberEATS (p = .001) compared to those who identified as female. Respondents who identified as female were more likely to report being listed with MadPaws (p < 001) compared to those who identified as male. No other gender differences were observed within platforms.

TABLE 6: DISTRIBUTION OF RESPONDENTS ACROSS PLATFORMS BY GENDER Platform N Male Female

99des igns 31 61.4% 38.6% Amazon MTurk 49 59.5% 40.5%

Black lane 22 59.3% 40.7% F ive r r 77 57.0% 43.0%

GoCatch 30 55.3% 44.7% Guru 20 38.2% 61.8%

JobBoy 10 68.4% 31.6% Ly f t 17 58.6% 41.4%

MadPaws 28 14.6% 85.4% Uber 151 48.3% 51.7%

UberEATS 161 47.6% 52.4%

0% 5% 10% 15% 20% 25%

Other

Writing and translation

Transport and food delivery

Software development and technology

Skilled trades work

Sales and marketing support

Professional services

Personal services

Odd jobs and maintenance work

Education

Domestic services

Creative and multimedia

Commercial/Industrial services

Clerical and data entry

Caring services

4.3%

2.5%

20.9%

4.8%

4.8%

3.8%

6.6%

2.8%

9.7%

6.1%

3.8%

10.9%

3.3%

9.4%

6.1%

4.3%

5.6%

13.5%

1.7%

0.8%

3.8%

3.3%

1.5%

4.0%

7.5%

9.5%

12.5%

3.0%

12.0%

17.1%

Type

of w

ork

Female Male


Figure 27 below displays the location of work by gender. Respondents generally reported working from home at roughly similar levels. Respondents who identified as male were more likely to report that they worked from a form of transport (e.g., car, bike), while respondents who identified as female were more likely to report working in the home of a client. These differences were statistically significant (p < .001).

FIGURE 27: LOCATION OF WORK BY GENDER Figure 28 below shows the hourly rate by gender. While respondents who identify as female tend to report earning an hourly rate in the lower income categories compared to those who identify as male, the distribution across categories for hourly rate is similar across gender and no statistically significant differences were observed (p = .085).

FIGURE 28: HOURLY RATE BY GENDER

0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%

Library, café, other public space

Coworking space

Car, motorbike, scooter, bicycle

Business of client

Home of the client

At my home

1.0%

2.9%

24.8%

13.6%

11.0%

46.7%

3.6%

2.4%

14.7%

13.4%

20.5%

45.5%

Loca

tion

of w

ork

Female Male

0%

10%

20%

30%

40%

50%

Male Female

22.8%28.5%

48.6%46.0%

18.1% 16.5%

8.6%5.5%

1.9% 3.5%

$0.01 - $14.99 $15.00 - $29.99 $30.00 - $49.99 $50.00 - $99.99 $100 or more


Figure 29 below shows the annual income by gender. Although respondents who identify as female tended to report earning an hourly rate in the lower income categories below $41,599, while those who identify as male were more likely to be represented in the categories above $41,600, the distribution across categories for hourly rate is similar across gender and no statistically significant differences were observed (p = .062).

FIGURE 29: ANNUAL INCOME BY GENDER

4.2 Motivations and perceptions of work in the gig economy

Motivations for working in the gig economy

Figure 30 below displays the average scores on motivations for working in the gig economy. Overall, the most common reasons respondents gave for working in the gig economy were to choose their own hours, because they enjoy the work they do, can work at their own pace and can choose their own tasks or projects. The reasons least likely to be endorsed by respondents overall were because they could not find other employment, have caring responsibilities or because they have a disability.

While this pattern was consistent across the two groups, some statistically significant differences were observed. Respondents whose main income is gig work were much more likely to report that they worked in the gig economy because they had to work from home due to a disability (p < .001), could not find other employment (p < .001), had caring responsibilities (p < .001), to earn money while studying (p < .001) or to build a business (p = .014). Respondents whose main income was non-gig work were much more likely to say they worked in the gig economy because they were complementing pay from other work, and this difference was statistically significant (p < .001).

0%

10%

20%

30%

Male Female

10.9%

14.1%11.4%

12.9%11.4%

16.1%

22.1% 22.3%20.7%

18.2%18.1%

12.7%

5.3%3.8%

$1 - $15,599 $15,600 - $25,999 $26,000 - $41,599 $41,600 - $64,999$65,000 - $90,999 $91,000 - $155,999 $156,000 or more


FIGURE 30: MOTIVATIONS FOR WORKING IN THE GIG ECONOMY

2.2

2.4

2.6

3.1

3.3

3.7

3.8

3.8

3.9

3.9

3.9

4.0

2.5

2.8

3.0

3.3

3.6

3.8

3.7

3.6

3.8

3.9

3.9

3.9

1.9

2.2

2.4

3.1

3.2

3.7

3.8

4.0

3.9

3.9

3.9

4.0

1.5 2.0 2.5 3.0 3.5 4.0 4.5

I can only work from home because I have a disability

I can only work from home because I am a carer

I could not find other employment

To build a new business in addition to regular work

To earn money while I am studying

I prefer to be my own boss

I prefer to work from home

To complement pay from other work

I get to choose my own tasks/projects

I get to work at my own pace

I enjoy the work I do

I can choose my own hours



Experience of working in the gig working environment

Figure 31 below shows that respondents who reported that their main source of income was from gig work reported slightly higher levels of perceived distributive justice (M = 3.6, SD = 0.9) compared to those respondents who reported that their main source of income was from non-gig work (M = 3.3, SD = 0.8), and this difference was significant (p < .001).

FIGURE 31: DISTRIBUTIVE JUSTICE

Figure 32 below displays the average scores for each of the items in the distributive justice scale for respondents in the sample. The pattern of responses across the items is roughly consistent across groups with both groups generally agreeing that their gig income is justified relative to their performance and reflects the effort they put into their work. Those respondents who reported that their main income was from gig work were more likely to endorse all items of the distributive justice scale, compared to those whose main income was from non-gig work. The differences between the two groups in how they rated the individual items were statistically significant (p < .001).

FIGURE 32: INDIVIDUAL ITEMS OF THE DISTRIBUTIVE JUSTICE SCALE

0.0

1.0

2.0

3.0

4.0

5.0


3.4 3.63.3

3.3

3.4

3.4

3.5

3.5

3.6

3.6

3.6

3.1

3.3

3.3

3.4

1.5 2.0 2.5 3.0 3.5 4.0

Gig work income reflects efforts put into work

Gig income appropriate for the work completed

Gig work income reflects contribution to work

Gig work income justified given performance



Figure 33 below displays the average scores for the challenging work scale for respondents in the sample with both groups generally agreeing that their gig work allows them to use their skills and abilities and to do work that is meaningful to them. Respondents who reported that their main source of income was from gig work report slightly higher levels of challenging work (M = 3.8, SD = 0.8) compared to those respondents who reported that their main source of income was from non-gig work (M = 3.6, SD = 0.8), and this difference was significant (p = .008).

FIGURE 33: CHALLENGING WORK

Figure 34 below displays the average scores for each of the items on the challenging work scale for respondents in the sample. The pattern of responses across the items is roughly consistent across groups with both groups generally agreeing that their gig work allows them to use their skills and abilities. Respondents whose main income was from gig work rated some items at higher levels: my work requires me to keep learning new things (p = .001), my work requires that I be creative (p = .002), the work I do is meaningful to me (p = .029) and I get to do a lot of different things (p = .012).

FIGURE 34: INDIVIDUAL ITEMS OF THE CHALLENGING WORK SCALE

0.0

1.0

2.0

3.0

4.0

5.0


3.7 3.8 3.6

3.6

3.6

3.9

3.7

3.7

3.7

3.7

3.9

3.8

3.8

3.5

3.6

3.8

3.7

3.6

1.5 2.0 2.5 3.0 3.5 4.0

My work requires that I keep learning new things

My work requires that I be creative

My work lets me use my skills and abilities

The work I do is meaningful to me

I get to do a lot of different things through my work



4.3 Safety in the gig economy

Overall, 36.9% of respondents reported experiencing some kind of safety incident at work in the last 12 months. The most commonly experienced safety issues for respondents in the sample were violence and aggression, near misses and racial vilification. Figure 35 below shows the average number of incidents experienced by respondents in the sample.

FIGURE 35: COMPARISON OF SAFETY INCIDENTS FOR GIG WORKERS

Experience of illness and injury

Figure 36 below shows the average number of incidents of injury or illness by group. Overall, 14.8% of respondents in the sample reported experiencing an injury or illness as a result of their gig work (n = 149) in the past 12 months. Respondents whose main source of income was gig work were more likely to report having experienced an injury or illness (23.6%) compared to those whose main source of income was non-gig work (9.5%). This difference was statistically significant (p < .001).

FIGURE 36: AVERAGE NUMBER OF INJURY OR ILLNESS Figure 37 below shows the average number of near misses by group. Overall, 19.7% of respondents in the sample reported experiencing a near miss as a result of their gig work (n = 196) in the past 12 months. Respondents whose main source of income was gig work were more likely to report having experienced a near miss (26.2%) compared to those whose main source of income was non-gig work (15.0%). This difference was statistically significant (p = .014).

0.0

0.5

1.0

1.5

Injury & illness Near misses Violence & aggression Sexual harassment Racial vilification

0.50.7

1.1

0.40.6

0.0

0.5

1.0

1.5


0.5

0.9

0.2


FIGURE 37: AVERAGE NUMBER OF NEAR MISSES Figure 38 below shows whether or not respondents (n = 149) took any action to prevent experiencing further injury or illness. While more than half of the respondents who had experienced an injury or illness did not take action to prevent further injury or illness, respondents whose main income was gig work were much more likely to take further action to prevent the recurrence of injury or illness compared to gig workers whose main income was non-gig work. However, these differences were not significant (p = .114).

FIGURE 38: PREVENTATIVE ACTION FOLLOWING INJURY OR ILLNESS

0.0

0.5

1.0

1.5


0.7

0.9

0.5

0%

10%

20%

30%

40%

50%

60%

70%


34.0%25.9%

38.6%

66.0%74.1%

61.4%

Preventative action taken No preventative action taken


Figure 39 below shows respondent perceptions of risk in the gig economy. More than half of the respondents reported that it was very unlikely or extremely unlikely to be injured or become ill as a result of their gig work. This was more pronounced for those whose main source of income was gig work. These workers reported feeling less safe and were more likely to report that they were very likely or extremely likely to become injured in the course of their gig work compared to those workers whose main income was from non-gig work. These differences were statistically significant (p < .001).

FIGURE 39: PERCEIVED RISK IN THE GIG ECONOMY

Figure 40 below shows the average scores on a measure of safety compliance. The respondents in the sample reported higher levels of safety compliance, indicating that they used the correct safety procedures and equipment and ensured the highest level of safety when carrying out their jobs. This result was consistent between groups irrespective of their main source of income and there was no statistically significant difference between groups (p = .082).

FIGURE 40: SAFETY COMPLIANCE IN THE GIG ECONOMY

0%

10%

20%

30%

40%


28.9%

23.0%

31.9%33.6%29.4%

36.9%

27.4%31.5%

24.7%

7.1%10.2%

5.3%3.1%

5.8%1.2%

Extremely unkely Very unlikely Somewhat likely Very likely Extremely likely

0.0

1.0

2.0

3.0

4.0

5.0


4.1 4.1 4.1


Figure 41 below displays the average scores for each of the items on the safety compliance scale for respondents in the sample. The pattern of responses across the items is roughly consistent across groups with both groups generally agreeing that they are compliant on all aspects of safety in their gig work. However, respondents whose main source of income was from non-gig work rated their compliance higher on the item I ensure the highest level of safety when carrying out my job, and for this item there was a statistically significant difference between groups (p = .012).

FIGURE 41: INDIVIDUAL ITEMS OF THE SAFETY COMPLIANCE SCALE

4.1

4.1

4.1

4.1

4.1

4.0

4.1

4.2

4.2

1.5 2.0 2.5 3.0 3.5 4.0 4.5

I use all the necessary safety equipment to do my job

I use the correct safety procedures for carrying out my job

I ensure the highest levels of safety when I carry out my job



Figure 42 below shows the average scores on a measure of safety motivation. The respondents reported high levels of safety motivation indicating that they thought it was both important and worthwhile to maintain and improve their health and safety and reduce the risk of accidents in their work. Respondents whose main source of income was non-gig work reported slightly higher levels of safety motivation and this difference was statistically significant (p = .006).

FIGURE 42: SAFETY MOTIVATION IN THE GIG ECONOMY

Figure 43 below displays the average scores for each of the items on the safety motivation scale for respondents in the sample. The pattern of responses across the items shows that respondents whose main income is non-gig work are more likely to endorse the safety motivation items compared to those respondents whose main income was gig work. There were statistically significant differences between groups on the items: I feel that it is important to maintain safety at all times (p = .002) and I believe that it is important to reduce the risk of safety incidents where I work (p = .007), but not I feel that it is worthwhile to put in effort to maintain or improve my personal health and safety (p = .149).

FIGURE 43: INDIVIDUAL ITEMS OF THE SAFETY MOTIVATION SCALE

0.0

1.0

2.0

3.0

4.0

5.0


4.1 4.0 4.2

4.0

4.2

4.1

3.9

4.1

4.0

4.0

4.3

4.2

1.5 2.0 2.5 3.0 3.5 4.0 4.5

I feel that it is worthwhile to put in effort to maintain orimprove my personal health and safety

I feel that it is important to maintain safety at all times

I believe that it is important to reduce the risk of safetyincidents where I work



Experience of violence and aggression

Overall, 18.7% of respondents in the sample reported experiencing violence or aggression in the course of their gig work (n = 176) in the past 12 months. Respondents whose main source of income was gig work were more likely to report having experienced violence or aggression (25.5%) compared to those whose main source of income was non-gig work (17.2%) and this difference was significant (p = .002).

Figure 44 below shows the average number of incidents of violence and aggression experienced by each group. On average, respondents who reported the experience of violence or aggression reported at least one incident of violence and aggression in the past twelve months while they were working in their gig work.

FIGURE 44: EXPERIENCE OF VIOLENCE AND AGGRESSION

Figure 45 below shows the perpetrators of violence and aggression for those respondents who had experienced violence and aggression in the past 12 months. Customers, clients or passengers were the main perpetrators of violence or aggression. Respondents whose main source of income was from non-gig work reported that customers, clients or passengers were the most common perpetrators of aggression. However, they were also more likely to report that supervisors or managers were a substantial source of violence and aggression compared to those whose main income was from non-gig work. This difference in attributions for perpetrators of violence and aggression was not statistically significant (p = .090).

FIGURE 45: PERPETRATORS OF VIOLENCE AND AGGRESSION

0.0

0.5

1.0

1.5


1.11.3

1.1

0%

20%

40%

60%

80%


76.0%69.2%

78.9%

3.2% 0.0%5.3%3.2% 2.6% 3.9%

17.6%

28.2%

11.8%

Customer, client, passenger Family or friend of customer Coworker Supervisor or manager


Figure 46 below shows that respondents tended to not formally report their experience of violence and aggression with less than one third of respondents (29.5%), who had experienced violence and aggression in the past 12 months, formally reporting their experiences.

FIGURE 46: REPORTING OF VIOLENCE AND AGGRESSION

Figure 47 below shows that, when respondents formally reported the violence or aggression, those whose main source of income was gig work tended to report their experience to the police, while those whose main source of income was non-gig work tended to report their experience to the platform operator or supervisor or manager and very rarely the police.

FIGURE 47: REPORTING CHANNEL FOR VIOLENCE AND AGGRESSION

0%

20%

40%

60%

80%


70.5% 71.3% 69.1%

29.5% 28.7% 30.9%

Did not report OVA Reported OVA

0%

10%

20%

30%

40%

50%


40.4%36.8%

46.2%

38.3%

26.3%

42.3%

19.1%

36.8%

7.7%2.1% 0.0%

3.8%

Platform Supervisor or manager Police Regulator


Figure 48 below shows the follow-up support received following the experience of violence and aggression by group. Approximately one quarter of respondents received support to manage their experience of violence and aggression and respondents whose main form of income was non-gig work reported slightly greater levels of follow-up support. This difference was not statistically significant (p = .443).

FIGURE 48: SUPPORT RECEIVED FOLLOWING THE EXPERIENCE OF VIOLENCE AND AGGRESSION

Figure 49 below shows the sources of support for respondents in the sample following the experience of violence and aggression. Overall, respondents were more likely to get support from a supervisor or manager, counsellor or family and friends.

FIGURE 49: SOURCES OF SUPPORT FOLLOWING THE EXPERIENCE OF VIOLENCE AND AGGRESSION

0%

20%

40%

60%

80%


73.7% 76.3%71.1%

26.3% 23.8%28.9%

Not supported Supported

0%

10%

20%

30%

40%


14.3%18.2%

13.0%

28.6%

18.2%

34.8%

2.9%

9.1%

0.0%

5.7%9.1%

4.3%

25.7% 27.3%

21.7%22.9%18.2%

26.1%

Platform Supervisor or manager Coworker Police Counsellor Family or friends


Experience of sexual harassment

Overall, 9.7% of respondents in the sample reported experiencing sexual harassment in the course of their gig work (n = 98) in the past year. Respondents whose main source of income was gig work were more likely to report having experienced sexual harassment (14.2%), compared to those whose main source of income was non-gig work (8.7%). This difference was statistically significant (p = .009). Figure 50 below shows the average number of incidents of sexual harassment experienced by respondents in the sample. On average, respondents who reported having experienced sexual harassment, reported less than one incident of sexual harassment in the past twelve months while they were working in their gig work.

FIGURE 50: EXPERIENCE OF SEXUAL HARASSMENT

Figure 51 below shows the perpetrators of sexual harassment. Customers and clients were the main perpetrators of sexual harassment for both groups, respondents also reported that other people whom they described non-specifically (e.g., drunks, older men) as perpetrators and it is not clear what relationship these perpetrators had to the respondent or their work.

FIGURE 51: PERPETRATORS OF SEXUAL HARASSMENT

0.0

0.5

1.0


0.4 0.5 0.4

0%

10%

20%

30%

40%

50%

60%

70%


56.3%50.0%

56.8%

11.3% 10.0% 11.4%9.9% 10.0% 9.1%

22.5%30.0%

22.7%

Customer, client, passenger Coworker Supervisor or manager Other


Figure 52 shows that overall, respondents tended not to formally report their experience of sexual harassment. Respondents whose main form of income was gig work were more likely to formally report their experience of sexual harassment, compared to those whose main form of income was non-gig work.

FIGURE 52: REPORTING OF SEXUAL HARASSMENT

Figure 53 below shows that when respondents formally reported the sexual harassment, those whose main source of income was gig work tended to report their experience to the police or a supervisor or manager, while those whose main source of income was non-gig work tended to report their experience to the platform operator or a supervisor or manager, rather than to police.

FIGURE 53: REPORTING CHANNEL FOR SEXUAL HARASSMENT

0%

20%

40%

60%

80%


83.7% 74.4% 91.7%

16.3%

25.6%

8.3%

Did not report sexual harassment Reported sexual harassment

0%

20%

40%

60%


36.4%

28.6%

50.0%45.5% 42.9%

50.0%

18.2%

28.6%

0.0%

Platform Supervisor or manager Police


Figure 54 below shows the support received following the experience of sexual harassment. Most respondents did not receive support to manage their experience of sexual harassment and this pattern was roughly equivalent across groups (p = .808).

FIGURE 54: SUPPORT RECEIVED FOLLOWING THE EXPERIENCE OF SEXUAL HARASSMENT

Figure 55 below shows the sources of support for respondents in the sample for those who did receive support. Overall, respondents were more likely to get support from a co-worker.

FIGURE 55: SOURCES OF SUPPORT FOLLOWING THE EXPERIENCE OF SEXUAL HARASSMENT

0%

20%

40%

60%

80%

100%


82.7% 81.4% 83.3%

17.3% 18.6% 16.7%


0%

10%

20%

30%

40%

50%

60%


30%25.0%

33.3%40%

50.0%

33.3%30%

25.0%

33.3%

Supervisor or manager Coworker Family or friends


Experience of racial vilification

Overall, 15.2% of respondents in the sample reported experiencing racial vilification in the course of their gig work in the past year. Respondents whose main source of income was gig work were more likely to report having experienced racial vilification (19.5%) compared to those whose main source of income was non-gig work (10.9%). This difference was statistically significant (p < .001). Figure 56 below shows the average number of incidents of racial vilification experienced by each group. On average, respondents who reported experiencing racial vilification reported less than one incident of racial vilification in the past twelve months while they were engaged in their gig work. Those who reported that gig work was their main source of income experienced more incidents of racial vilification, on average, compared to those whose main income was from non-gig work.

FIGURE 56: EXPERIENCE OF RACIAL VILIFICATION

Figure 57 below shows the source of racial vilification by group. Overall, the main source of racial vilification was customers and clients. However, supervisors or managers and co-workers were also reported to be perpetrators. Further, respondents also reported that other people who they described non-specifically (e.g., drunks, outsiders, members of the public) were also perpetrators of racial vilification but it is not clear what relationship these perpetrators had to the respondent or their work.

FIGURE 57: PERPETRATORS OF RACIAL VILIFICATION

0.0

0.5

1.0


0.6

0.7

0.5

0%

10%

20%

30%

40%

50%


42%

36.1%

46.4%

1% 0.0% 1.8%

16%11.1%

16.1%20% 19.4% 19.6%

1% 2.8%0.0%

21%

30.6%

16.1%

Customer, client, passenger Family or friend of client customer CoworkerSupervisor or manager Platform operator Unconnected person


Figure 58 below shows that, overall, few respondents formally reported their experience of racial vilification. Respondents whose main form of income was gig work were slightly less likely to formally report their experience of racial vilification, compared to those whose main form of income was non-gig work. This difference was not statistically significant (p = .257).

FIGURE 58: REPORTING OF RACIAL VILIFICATION

Figure 59 shows that, while respondents were more likely to report racial vilification to a supervisor or manager, reporting practices varied by group.

FIGURE 59: REPORTING CHANNELS FOR RACIAL VILIFICATION

0%

20%

40%

60%

80%

100%


85.2% 81.8%88.9%

14.8% 18.2%11.1%

Did not report racial vilification Reported racial vilification

0%

20%

40%

60%

80%


17%25.0%

0.0%

58%50.0%

75.0%

8%0.0%

25.0%

8%12.5%

0.0%8%

12.5%

0.0%

Platform Supervisor or manager Coworker Police Family or friends


Figure 60 below shows support received following the experience of racial vilification. Most respondents did not receive support to manage their experience of racial vilification and this pattern was similar across groups.

FIGURE 60: SUPPORT RECEIVED FOLLOWING THE EXPERIENCE OF RACIAL VILIFICATION

Figure 61 below shows the sources of support for respondents in the sample for those who did receive support. Overall, respondents were most likely to get support from family or friends and supervisors or managers.

FIGURE 61: SOURCES OF SUPPORT FOLLOWING THE EXPERIENCE OF RACIAL VILIFICATION

0%

20%

40%

60%

80%

100%


80.0% 75.8%84.1%

20.0%24.2%

15.9%


0%

20%

40%

60%

80%

100%


9%16.7%

0.0%

27%33.3%

20.0%9%

16.7%

0.0%

55%

33.3%

80.0%

Platform Supervisor or manager Coworker Family or friends


Comparing all safety incidents across subsets of gig workers

Overall, 32.6% of respondents in the sample reported experiencing some type of safety incident (i.e., illness or injury, near miss, violence and aggression, sexual harassment or racial vilification) in the course of their gig work in the past 12 months. Respondents who identified as female were slightly more likely to report experiencing a safety incident (32.6%) compared to those who identified as male (31.6%). Figure 62 below shows the average number of safety incidents and near misses by gender. No statistically significant differences were observed for injury or illness (p = .476), near misses (p = .402), violence and aggression (p = .288), sexual harassment (p = .174) or racism (p = .439).

FIGURE 62: COMPARISON OF SAFETY INCIDENTS BY GENDER

Figure 63 below shows the average number of safety incidents across each age group. Violence and aggression was generally the most commonly reported safety incident across all age groups, racial vilification was reported at higher levels in the 55 years and older age group. Statistically significant differences were observed between age groups for sexual harassment (p = .017) and racism (p = .012). Post hoc tests showed that respondents in the 55 years and older age group reported experience more incidents of sexual harassment (p < .05) and racism (p < .05) compared to the other age groups. No statistically significant differences were observed for injury or illness (p = .070), near misses (p = .680), violence and aggression (p = .818).

FIGURE 63: COMPARISON OF SAFETY INCIDENTS BY AGE

0.0

0.5

1.0

1.5

Male Female

0.60.5

0.70.6

0.8

1.3

0.3

0.50.5

0.6

Injury or illness Near misses Violence and aggression Sexual harassment Racial vilification

0.0

0.5

1.0

1.5

2.0

2.5

18-25 26-25 36-45 46-55 55+

0.4

0.8

0.5

0.1 0.2

0.60.7 0.7

0.50.3

1.0 1.1

1.6

0.9

0.30.2

0.6

0.20.4

2.0

0.50.7

0.20.4

2.3



Overall, respondents who were born in Australia were more likely to say they had experienced a safety incident (33.9%) compared to those who were born elsewhere (28.9%). Figure 64 below shows the average number of safety incidents by country of birth. Respondents who were born in Australia reported experiencing higher frequencies of all safety incidents, particularly violence and aggression, compared to those not born in Australia. The group differences for injury or illness (p = .002), near misses (p = .004) and violence and aggression (p = .003) were statistically significant.

FIGURE 64: COMPARISON OF SAFETY INCIDENTS BY COUNTRY OF BIRTH

Figure 65 below displays the average number of safety incidents by citizenship status. In general, those who reported that they were Australian citizens experienced a greater number of safety incidents on average compared to those who were permanent or temporary residents, although these differences were not significant (p > .05). The dominant safety incident reported by Australian citizens was violence and aggression, while those on a temporary visa reported near misses as well as racial vilification as the dominant safety incidents experienced by this group.

FIGURE 65: COMPARISON OF SAFETY INCIDENTS BY CITIZENSHIP

0.0

0.5

1.0

1.5

2.0

2.5

Born elsewhere Born in Australia

0.3

0.60.4

0.7

0.4

1.4

0.30.50.4

0.6


0.0

0.5

1.0

Australian citizen Permanent resident Temporary visa

0.4

0.20.1

0.40.3

0.50.6

0.2 0.30.4

0.20.1

0.50.3

0.5



Table 7 below compare the average number of safety incidents experienced by respondents in the past 12 months across the type of work they were predominantly engaged in. Overall, approximately half of the respondents who said that their main type of work was in the caring services or commercial and industrial services reported experiencing some kind of safety incident. Respondents who work in the caring services reported nearly twice as many incidents, on average, compared to respondents in other types of work. Respondents whose main type work was clerical and data entry, professional services and software development and technology were less likely to report experiencing a safety incident compared to respondents in other types of work.

The respondents who work in the caring services reported the highest number of safety incidents associated with violence and aggression, sexual harassment and racism, on average, compared to other groups. Respondents who work in skilled trades reported the highest number of injuries and illness, on average, compared to other groups. Respondents who work in commercial and industrial services reported the highest number of near misses, on average, compared to other groups.

TABLE 7: COMPARISON OF AVERAGE NUMBER OF SAFETY INCIDENTS BY TYPE OF WORK Platform Experienced

incident Injury or illness

Near misses

Violence & aggression

Sexual harassment

Racial vilification

Total incidents

Caring services 65 (49.6%) 0.8 1.2 3.3 1.5 2.0 8.8 Clerical and data entry 23 (20.5%) 0.2 0.5 0.4 0.2 0.3 1.5

Commercial/Industrial services 17 (51.5%) 1.8 1.2 0.8 0.5 0.7 5.0 Creative and multimedia 49 (41.2%) 0.7 0.7 1.0 0.3 0.5 3.2

Domestic services 26 (35.1%) 0.5 0.6 0.5 0.5 0.5 2.6 Education 25 (34.2%) 0.3 0.3 0.3 0.2 0.3 1.3

Odd jobs and maintenance work 26 (41.3%) 0.3 0.7 1.3 0.7 0.7 3.7 Personal services 9 (45.0%) 0.7 1.2 2.0 0.3 0.4 4.6

Professional services 10 (21.7%) 0.7 0.5 0.5 0.1 0.4 2.1 Sales and marketing support 14 (36.8%) 0.4 0.2 0.4 0.1 0.7 1.8

Skilled trades work 8 (32.0%) 2.1 0.6 1.4 0.2 0.2 4.6 Software development & technology 7 (23.3%) 0.2 0.4 0.1 0.1 0.1 0.7

Transport and food delivery 68 (41.5%) 0.1 0.8 1.2 0.3 0.1 2.6 Writing and translation 12 (27.3%) 0.2 0.0 0.1 0.2 0.4 1.0

Table 8 below compares the average number of safety incidents experienced by all gig workers across platforms. Overall, the average number of total safety incidents (i.e., injury or illness, near misses, violence and aggression, sexual harassment, racial vilification) in the past 12 months reported for the sample was 3.3 (SD = 12.4), but workers on some platforms reported a substantially higher number of safety incidents than the average for the sample. However, caution should be used when interpreting these data because the sample sizes for some platforms (e.g., Mable) were very small in comparison to other platforms where workers reported fewer safety incidents (e.g., Airtasker, Uber or UberEATS). Furthermore, respondents reported being listed across multiple platforms and it is beyond the scope of this study to examine the number of incidents by platform or provide sufficient data for each platform based on respondents who are listed with one platform only. Consequently, these data may be specific to the respondent and not necessarily representative of safety on these platforms.


TABLE 8: COMPARISON OF AVERAGE NUMBER OF SAFETY INCIDENTS ACROSS PLATFORMS Platform Experienced

incident Injury or illness

Near misses

Violence & aggression

Sexual harassment

Racial vilification

Total incidents

99des igns 28 (59.6%) 1.8 2.2 2.0 2.3 1.6 8.3 Ai r taske r 125 (36.8%) 0.6 0.7 0.8 0.4 0.5 2.4

Amazon MTurk 40 (54.1%) 1.8 2.0 1.5 1.3 1.9 6.9 Black lane 20 (69.0%) 3.6 3.4 2.7 2.6 2.5 11.8

Care Co l lec t i ve 37 (59.7%) 1.9 2.2 1.7 1.2 1.9 7.6 Care Suppor t Ne twork 24 (77.4%) 2.5 3.1 2.6 2.5 2.5 10.1

Care .com 35 (68.6%) 1.8 2.1 2.2 3.3 3.8 11.4 Care r So lu t i ons Aus t ra l i a 36 (66.7%) 2.8 2.0 2.5 2.9 3.5 12.3

Careseeke rs 43 (57.3%) 1.5 0.9 1.6 0.5 0.8 4.5 Cho iceOne 34 (47.2%) 0.8 0.9 2.2 2.1 1.9 7.3

Cl i ckworke r 31 (43.7%) 0.9 0.7 0.6 0.4 1.4 3.2 Connec t ing Up 14 (66.7%) 2.2 2.0 1.7 1.5 1.4 6.9

CoSea ts 16 (72.7%) 3.7 2.1 2.5 1.2 1.2 9.0 De l i ve roo 68 (54.8%) 0.9 1.2 2.2 0.9 0.7 4.9

Des ignCrowd 21 (65.6%) 3.2 2.0 2.2 1.4 2.5 9.5 Did i Chux ing 20 (62.5%) 2.1 1.6 1.6 1.2 1.2 6.0

Dr ibb le 11 (61.1%) 1.9 1.7 1.1 1.2 0.9 5.9 EASI 8 (47.1%) 0.5 1.3 0.7 0.3 1.2 2.8

F i rs t2Care 12 (63.2%) 1.3 1.8 0.7 1.0 1.2 4.6 F ive r r 51 (41.5%) 0.3 0.7 0.6 0.4 0.6 2.0

Free lance r 37 (33.6%) 0.2 0.5 0.7 0.3 0.6 1.8 Glamazon 18 (69.2%) 1.2 1.3 1.4 0.7 1.0 4.4

GoCatch 25 (53.2%) 1.2 1.7 5.5 0.6 1.8 9.5 Guru 21 (61.8%) 1.1 1.0 1.1 0.4 0.9 3.8

He lp l i ng 9 (50.0%) 0.6 0.7 0.2 0.2 2.4 3.4 Hipages 16 (51.6%) 0.7 1.6 2.5 1.7 1.6 6.5

Hi reup 14 (60.9%) 1.1 1.8 2.3 1.0 1.3 5.7 Home Care Heroes 8 (50.0%) 1.2 1.8 1.8 1.0 1.1 5.3

JobBoy 13 (68.4%) 1.3 2.3 1.5 1.1 1.5 5.4 LASHD 9 (75.0%) 0.9 1.1 0.5 0.3 3.2 4.9

L ionb r idge Smar t C rowd 5 (50.0%) 3.4 1.6 0.6 0.7 0.7 5.5 Ly f t 19 (65.5%) 1.5 0.9 3.1 0.9 0.6 6.0

Mab le 10 (66.7%) 2.1 2.8 15.4 1.1 3.8 23.0 MadPaws 25 (49.0%) 0.6 0.5 0.9 0.7 1.0 3.2

Menu log 54 (50.0%) 0.5 0.7 2.5 0.6 0.7 4.4 Mic roWorke rs 18 (60.0%) 0.5 0.6 7.2 0.4 1.0 9.1

Newly 9 (81.8%) 1.5 1.5 1.1 0.7 0.7 4.5 ODesk 4 (25.0%) 0.1 0.6 0.3 0.0 0.3 0.6

Ola 28 (51.9%) 0.6 1.0 0.9 0.5 0.6 2.8 Onef la re 10 (62.5%) 1.8 1.3 2.7 0.9 1.8 7.9

Pawshake 13 (52.0%) 0.5 1.0 0.8 0.3 0.4 2.1 Peop lePerHour 9 (45.0%) 0.4 0.3 0.7 0.1 0.2 1.5

Shebah 9 (69.2%) 0.6 1.4 1.0 0.4 3.4 5.5 Sherpa 5 (71.4%) 1.1 1.6 3.9 0.9 0.4 6.3 Sho fe r 5 (83.3%) 1.0 1.2 1.2 0.8 8.0 11.2

Sidek icke r 15 (62.5%) 0.8 1.0 0.8 0.6 0.7 2.9 Ta l i xo 9 (75.0%) 2.8 2.2 3.0 0.9 1.0 8.8

TaskRabb i t 23 (59.0%) 1.2 1.1 1.3 0.7 2.1 5.2 Tax i f y 22 (51.2%) 1.1 1.3 1.4 0.9 0.8 4.4

Toodoo loo 5 (50.0%) 3.4 3.1 2.9 1.3 2.0 10.7 Top ta l 5 (45.5%) 0.7 0.7 0.4 0.2 0.4 1.7

Uber 111 (45.5%) 0.5 0.8 1.9 0.4 0.5 3.3 UberEATS 121 (48.0%) 0.5 0.8 2.2 0.3 0.5 3.5

Upwork 20 (32.3%) 0.3 0.5 0.4 0.2 0.8 1.7 WeGoLook 7 (38.9%) 0.6 0.2 0.5 0.2 0.1 1.5

Zoom2U 10 (40.0%) 3.2 0.3 1.4 0.3 0.3 5.2 Other 41 (24.8%) 0.2 0.2 0.9 0.1 0.4 1.6


4.4 Health and wellbeing in the gig economy

Health and wellbeing

Figure 66 below shows respondent scores on the personal wellbeing index by group. These scores represent respondent satisfaction with several aspects of their health and wellbeing. The average score (scored 0 to 100 with higher scores indicating greater well-being) for respondents whose main income was from gig work indicated higher levels of wellbeing compared to those whose main income was from non-gig work and this difference between groups was statistically significant (p < .001).

Australian norms for the personal wellbeing index range from approximately 73.4 to 76.4.27 Comparing the wellbeing score of respondents in the sample to population norms, revealed that the personal wellbeing scores of both the main income is gig work (p = .001) and the main income is non-gig work (p < .001) respondent groups were significantly lower than the lowest reported threshold for Australian norms.

FIGURE 66: PERSONAL WELLBEING

0.0

20.0

40.0

60.0

80.0

100.0


66.5 70.265.9


Figure 67 below shows average scores on each item of the personal wellbeing index by group. Overall, the areas where respondents were generally more satisfied in their lives were feeling safe, personal relationships, health and standard of living. Future security and life achievement were the areas they were least satisfied with, and this was consistent for both groups, irrespective of their main source of income.

Respondents whose main income was from gig work attained higher scores on all items in the personal wellbeing index. The differences in ratings for items your life as a whole (p = .002), your standard of living (p = .002), your health (p = .003), what you are currently achieving in life (p = .001), feeling part of a community (p < .001) and your future security (p = .004) were statistically significant.

FIGURE 67: INDIVIDUAL ITEMS OF THE PERSONAL WELLBEING INDEX

6.3

6.4

6.6

6.6

6.7

6.8

7.0

7.2

6.7

6.7

7.0

7.0

7.1

7.0

7.1

7.5

6.2

6.3

6.4

6.5

6.7

6.6

6.8

7.2

0 1 2 3 4 5 6 7 8 9 10

Life achievement

Future security

Feeling part of a community

Life as a whole

Standard of living

Health

Personal relationships

Feeling safe



Figure 68 below shows respondent scores on the brief resilience scale. Generally, scores for the respondents in the sample were at the lower end of the normal range for resilience.30 Respondents whose main source of income was from gig work (M = 3.1, SD = 0.6) had roughly equivalent scores on the brief resilience scale to those whose main source of income was from non-gig work (M = 3.2, SD = 0.7, p = .861).

FIGURE 68: AVERAGE SCORES ON THE BRIEF RESILIENCE SCALE

Figure 69 shows the distribution of gig workers across resilience categories calculated on the basis of their scores on the brief resilience scale. These categories are based on scale norms developed by Smith and colleagues.30 Overall, scores for gig workers, irrespective of source of income, generally fell into the normal resilience range. However, scores for approximately a third of the sample fell into the low resilience range.

FIGURE 69: COMPARING GIG WORKERS TO ESTABLISHED NORMS ON THE BRIEF RESILIENCE SCALE

1.0

2.0

3.0

4.0

5.0


3.1 3.1 3.2

0%

10%

20%

30%

40%

50%

60%

70%


32.7%29.2% 32.3%

62.4% 64.6% 63.7%

4.9% 6.2% 4.0%

Low resilience Normal resilience High resilience


Figure 70 below shows average scores on each item of the brief resilience scale by group. Note that items two, four and six were recoded so that higher scores indicated a higher level of resilience. Overall, the area of resilience most likely to be endorsed by respondents was bouncing back after hard times while the area of resilience least likely to be endorsed by respondents was having a hard time making it through stressful events.

Despite similarity on the overall scores, there were statistically significant differences in scores between groups on some l items. Respondents whose main income was from gig work scored lower on items: taking a long time to get over life’s setbacks (p = .001), difficulty in snapping back when something bad happens (p = .010) and having a hard time making it through stressful events (p = .045). Respondents whose main income was from non-gig work scored lower on the items: coming through difficult times with little trouble (p = .006), taking a long time to recover from a stressful event (p = .003) and bouncing back after hard times (p = .033).

FIGURE 70: INDIVIDUAL ITEMS FROM THE BRIEF RESILIENCE SCALE

Figure 71 below shows respondent scores on the self-esteem scale. Generally, scores for the respondents in the sample were at the lower end of the normal range for self-esteem. Respondents whose main source of income was from gig work (M = 17.1, SD = 4.8) had roughly equivalent scores on the brief resilience scale to those whose main source of income was from non-gig work (M = 17.5, SD = 5.4, p = .332).

FIGURE 71: AVERAGE SCORES ON THE SELF-ESTEEM SCALE

3.6

2.8

3.3

2.9

3.3

2.9

3.7

2.7

3.5

2.8

3.5

2.8

3.6

2.8

3.3

3.0

3.3

3.0

1.5 2.0 2.5 3.0 3.5 4.0

Tend to bounce back after hard times

Have a hard time making it through stressful events

Does not take long to recover from a stressful event

Difficult to snap back when something bad happens

Usually come through difficult times with little trouble

Tend to take a long time to get over life's set-backs


0.0

5.0

10.0

15.0

20.0


17.2 17.1 17.5


Figure 72 below shows respondent scores on the self-esteem scale by group. Overall, the average score on the self-esteem scale was 17.2 (SD = 5.3) which is at the lower range of normal self-esteem.31 Respondents whose main income was gig work (M = 17.1, SD = 4.8) had roughly equivalent scores on the self-esteem scale to those whose main source of income was non-gig work (M = 17.5, SD = 5.4). The difference was not statistically significant (p = .332).

FIGURE 72: SELF-ESTEEM

0%

20%

40%

60%

80%


26.5% 24.6% 25.7%

65.9% 68.0% 66.8%

7.6% 7.4% 7.5%

Poor self-esteem Normal self-esteem High self-esteem


Figure 73 below shows average scores for each item of the self-esteem scale by group. Note that some items were reverse coded so that higher scores indicate a higher level of self-esteem. These items include: at times I think I am no good at all, I feel I do not have much to be proud of, I certainly feel useless at times, I wish I could have more respect for myself and all in all, I am inclined to feel that I am a failure.

The items of the self-esteem scale most likely to be endorsed by respondents were: at times I think I am no good at all and I feel I do not have much to be proud of. Overall, the items that were most difficult for respondents in the sample to endorse were: I feel useless at times, I am satisfied with myself and I take a positive attitude to myself. While some item scores for the respondent groups were roughly equivalent, some significant differences were observed. Respondents whose main income was gig work had lower scores on at times I feel useless at times (p = .024), I feel I am a failure (p = .001) and I take a positive attitude to myself (p = .029). Respondents whose main income was non-gig work had lower scores on at times I feel I am no good at all (p = .008) and I feel I do not have much to be proud of (p = .001).

FIGURE 73: INDIVIDUAL ITEMS OF THE SELF-ESTEEM SCALE

1.3

1.4

1.4

1.6

1.7

1.8

1.9

1.9

2.1

2.1

1.3

1.3

1.4

1.5

1.5

2.0

1.9

2.0

2.1

2.1

1.4

1.4

1.4

1.7

1.8

1.8

1.9

1.9

2.1

2.1

0.0 1.0 2.0 3.0

I take a positive attitude toward myself

I am satisfied with myself

I feel useless at times

I feel that I am a failure

I am able to do things as well as most other people

I wish I could have more respect for myself

I feel that I'm a person of worth

I have a number of good qualities

I feel I do not have much to be proud of

At times I think I am no good at all



Thriving at work

Figure 74 below shows respondent scores on the learning subscale by group. The respondents in the sample reported moderate levels of thriving at work as measured by the learning subscale, indicating that they see themselves as learning and improving. Respondents whose main income was gig work (M = 5.1, SD = 1.1) had roughly equivalent scores on the learning subscale scale compared to those whose main source of income was non-gig work (M = 5.1, SD = 1.1, p = .998).

FIGURE 74: LEARNING

Figure 75 below shows average scores on each item of the learning subscale by group. Note that the item I am not learning was recoded so that a higher score indicated a higher level of learning at work.

Item scores were consistent across groups with the exception of the item I am not learning. The only statistically significant difference found was that respondents whose main source of income was non-gig work were more likely to report that they were not learning compared to those whose main source of income was gig work (p < .001).

FIGURE 75: INDIVIDUAL ITEMS OF THE LEARNING SUBSCALE

1.0

2.0

3.0

4.0

5.0

6.0

7.0


5.1 5.1 5.1

5.0

5.3

5.3

3.3

5.0

5.1

5.3

5.4

3.6

5.2

5.0

5.3

5.3

3.1

5.0

1 2 3 4 5 6 7

I find myself learning often

I continue to learn more as time goes by

I see myself continually improving

I am not learning

I am developing a lot as a person



Figure 76 below shows respondent scores on the vitality subscale by group. The respondents in the sample reported moderate levels of thriving at work as measured by the vitality subscale indicating that they see themselves as energetic and enthusiastic. Respondents whose main income was gig work (M = 4.8, SD = 1.2) had roughly equivalent scores on the vitality scale to those whose main source of income was non-gig work (M = 4.7, SD = 1.1, p = .104).

FIGURE 76: VITALITY

Figure 77 below shows average scores on each item of the vitality subscale by group. Note that the item I do not feel very energetic was recoded so that a higher score indicated a higher level of vitality at work. Respondents whose main source of income was gig work were more likely to report that they had higher levels of vitality as measured by the items I feel alive and vital (p = .004), I have energy and spirit (p = .010), I feel alert and awake (p = .004) and I am looking forward to each new day (p = .031). Respondents whose main source of income was non-gig work were more likely to report that they had higher levels of vitality as measured by the item I do not feel very energetic (p = .001).

FIGURE 77: INDIVIDUAL ITEMS OF THE VITALITY SUBSCALE

1.0

2.0

3.0

4.0

5.0

6.0

7.0


4.7 4.8 4.7

4.9

4.9

4.1

4.8

4.9

5.1

5.2

3.9

5.0

5.1

4.9

4.9

4.2

4.7

4.9

1 2 3 4 5 6 7

I feel alive and vital

I have energy and spirit

I do not feel very energetic

I feel alert and awake

I am looking forward to each new day



5 SUMMARY AND CONCLUSIONS This report has presented the key findings from a survey of Victorian gig workers conducted between January and March 2020. The aim of this report was to provide a summary of: 1) the demographic characteristics of gig workers in Victoria; 2) the characteristics of the on-demand economy working environment; 3) gig worker motivations for working in the on-demand economy; and 4) gig worker perceptions of their health, safety and wellbeing.

5.1 Gig workers and their working environment

Results were received from 1,015 respondents who reported working in the on-demand economy in Victoria in the past 12 months in some capacity. More than half of the respondents in the sample reported that non-gig work was their main source of income, while a small subset of the sample reported that other income such as a government allowance (including Newstart, disability support, age pension, youth allowance, Austudy, ABSTUDY, carer and parenting payments) were their main source of income.

Demographic characteristics of gig workers in Victoria

Overall, the respondents tended to be female, average age of 33 years, with an education level at Bachelors degree or above. Nearly all of the respondents in the sample lived in the Melbourne area with few living in regional areas or remote areas. This is broadly consistent with earlier research conducted by McDonald and colleagues15 in an Australian population, except that respondents in that study were predominantly male. This pattern was generally observed for all respondents irrespective of their main source of income, but there was a greater representation of males among respondents whose main income was from gig work and those respondents also tended to be younger. While respondents whose main income was gig work tended to have a higher representation at lower levels of education (i.e., certificate and below), these workers were also more likely to have a Masters degree or a PhD compared to those whose main source of income was non-gig work. The majority of respondents in the sample were born in Australia and among those who were born elsewhere, most reported being born in Asia or Europe. Fewer than half of the respondents in the sample were Australian citizens with more than half reporting that they were either a permanent resident or working on a temporary visa. This pattern was partly observed in both subgroups of gig workers. Respondents whose main income was from gig work were more likely to have been born in Asia than Europe, and there was a greater representation of workers in this group from southern and central Asia and fewer from south-east Asia compared to those whose main income was from non-gig work. Differences were also observed for citizenship status where respondents whose main income was from gig work were relatively evenly distributed across the categories of Australian citizen, permanent resident and temporary visa status. Respondents whose main income was from non-gig work were more likely to be Australian citizens and permanent residents rather than temporary visa holders. Finally, most respondents reported that they spoke English at home. Other than English, there was no one dominant language spoken at home, but of those who did speak another language at home, the main languages were Indian or Chinese languages.

Overall, about half of the respondents in the sample reported that they were partnered or married, and most were caring for one or two dependent children, with one quarter of respondents reporting additional unpaid caring responsibilities for an adult family member or friend. Respondents whose main income was gig work were more likely to have dependent children at home and have additional unpaid caring responsibilities for an adult family member or friend.

Gig working environment

The respondents reported working in a range of industries with skilled trades, caring services, transport and food delivery, commercial or industrial services, catering and hospitality as well as writing and translation being the most likely industries in which they worked. This is partially consistent with the earlier study by McDonald and colleagues15 who reported a similar distribution of platforms, but whose sample contained a greater percentage of professional services workers and odd jobs and maintenance workers. More than half of the respondents in the sample worked across multiple platforms, with the main platforms that respondents reported working through being Airtasker, UberEATS and Uber. Deliveroo, Fiverr, Freelancer and Menulog were also popular platforms.


Most respondents in the sample worked in the Melbourne area, with few working in regional areas, which is consistent with the locations for their home address. The main working location for respondents was at home. Fewer respondents worked from their car or bike, or the home or business of a client. Respondents rarely reported working from co-working or public spaces such as a library or coffee shop.

Respondents reported working in the on-demand economy for an average of two years, although those whose main income was from gig work reported having worked in the on-demand economy over a longer period of time compared to those whose main income was non-gig work. Further, respondents whose main income was gig work reported working slightly fewer hours per week overall than those whose main income was from non-gig work. Overall, respondents, irrespective of their main source of income, were generally paid by the task or job. However, about one third of the sample were paid by the hour rather than being paid by gig job or task. The hourly pay for the sample was generally less than $30 per hour. However, there was a greater representation of workers whose main source of income was from non-gig work earning less than $30 per hour, while those whose main source of income was from gig work were comparatively more likely to earn $30 or more per hour. Respondents whose main income was from the gig economy were more likely to report instances of not being paid for the work they did compared to those whose main income is from the non-gig economy. Whether this is the product of being more exposed to gig work and therefore more likely to experience not being paid, or another issue, is not clear. Finally, respondents reported an annual income across the entire range of income brackets. Respondents whose main income was from gig work were more likely to report an annual income below $41,600 and respondents whose main income was from non-gig work were more likely to report an annual income above $41,600. Examining the characteristics of gig workers and their working environment revealed few substantial differences across gender. Main source of income, type of work and location varied across gender, with respondents who identified as male being more likely to earn their main income from gig work, work in transport and food delivery and work mainly from their car or other form of transport. Respondents who identified as female were more likely than those who identified as male to report non-gig work as their main source of income, work in caring services, clerical and data entry and domestic services and report that their main location of work was someone else’s home.

Motivations and experience for working in the gig economy

Overall, the most common reasons respondents gave for working in the gig economy was to choose their own hours, because they enjoy the work they do, can work at their own pace, can choose their own tasks or projects and are able to complement the pay from other work. The reasons least likely to be endorsed by respondents in the sample overall were because they could not find other employment, have caring responsibilities or because they have a disability. While this pattern was consistent across the two groups, some differences were observed. Respondents whose main income was gig work were much more likely to report that they worked in the on-demand economy because they had to work from home due to a disability, could not find other employment, had caring responsibilities, to earn money while studying or to build a business. Respondents whose main income was non-gig work were much more likely to say they worked in the on-demand economy because they were complementing pay from other work.

The experience of working in the on-demand economy was generally consistent across groups but was slightly more positive for those whose main income was gig work. Surprisingly, these workers reported that the income they received was appropriate for the work they completed and was reflective of the effort they put in, and reported a greater sense of challenge in their work compared to those whose main income was non-gig work.


5.2 Safety and the gig economy

Experience of injury and illness

Overall, respondents in the sample tended to report that they were unlikely to become injured or ill as a result of their gig work and this was more pronounced for those whose main work was non-gig work. In general, all gig workers, irrespective of main source of income, rated their safety compliance and safety motivation at high levels, which is consistent with earlier research.14 The experience of injury and illness associated with gig work was lower than incident rates reported in earlier Australian research.14 Respondents whose main income was from gig work experienced a much higher rate of injury or illness and near misses compared to those whose main income was from non-gig work. Further, those whose main income was from gig work were more likely to take action following an incident to prevent further injury or illness than those whose main income was from non-gig work.

Experience of violence and aggression

Most respondents in the sample reported that they had not experienced violence and aggression while doing gig work, and their exposure was substantially lower than other populations such as nurses32 or teachers.33 Respondents whose main income was from gig work were slightly more likely to report experiencing violence and aggression in the course of their gig work, than those whose main income was not from gig work. Perpetrators of violence and aggression were from a wide range of groups, but the most common perpetrators of violence and aggression were clients or customers, particularly for those whose main income was not from gig work.

Respondents tended not to report their experiences of violence or aggression to anyone. However, for those that did report, there were differences in who they chose to report to. Specifically, those whose main income was from gig work were more likely to report violence and aggression to the police and less likely to report to the digital platform or a supervisor or manager compared to those were whose main income was from non-gig work. Conversely, those whose main income was from non-gig work tended to report their experiences of violence or aggression to the platform or supervisor or manager rather than the police. Most respondents did not receive follow-up support for their experiences of violence or aggression, and this is consistent with their lack of reporting of such incidents.

Experience of sexual harassment

Most respondents in the sample reported that they had not experienced sexual harassment while doing gig work. Respondents whose main income was from gig work were more likely to report experiencing sexual harassment in the course of their gig work than those whose main income as not gig work. Perpetrators of sexual harassment were from a wide range of groups, but the most common perpetrators were either clients or customers or people unconnected to the gig work respondents were conducting. Respondents tended not to report their experiences of sexual harassment to anyone, but those respondents whose main income was from gig work were less likely to report. In general, respondents were more likely to report these incidents to a supervisor or manager. Respondents whose main income was gig work tended to report to the platform or a supervisor or manager. Most respondents did not receive follow-up support for their experiences of sexual harassment.

Experience of racial vilification

Most respondents in the sample reported that they had not experienced racial vilification while doing gig work. Respondents whose main income was from gig work were more likely to report experiencing racial vilification in the course of their gig work than those whose main income was not gig work. Perpetrators of racial vilification were from a wide range of groups, but the most common perpetrators were customers or clients, irrespective of the main source of income.

Respondents tended not to report their experiences of racial vilification to others (e.g., the digital platform), but those respondents whose main income was from gig work were more likely to report. Overall, respondents were more likely to report these incidents to a supervisor or manager. However, respondents whose main income was from gig work tended to report to the platform operator or supervisor or manager. Respondents whose main income was non-gig work tended to report their experiences to a supervisor or manager or police. Most respondents, particularly those whose main income was from non-gig work, did not receive follow-up support for their experiences of racial vilification.


Comparing safety incidents across subset of gig workers

A comparison of all safety incidents across selected subsets of the sample shows that violence and aggression was the most commonly experienced safety incident. There are few significant differences between these subsets with respect to safety. The difference that was observed was that those born in Australia were more likely to report experiencing violence and aggression compared to those born elsewhere. No significant differences across safety incidents were observed on the basis of gender, age or citizenship status. Finally, differences were observed for type of work. Those in the caring services or commercial and industrial services were more likely than respondents in other types of work to report experiencing some kind of safety incident while respondents who reported that their main work was clerical and data entry, professional services and software development and technology were less likely to report experiencing a safety incident compared to respondents in other types of work. Respondents who reported working in the caring services reported the highest number of safety incidents associated with violence and aggression, sexual harassment and racism, on average, compared to other groups. While the largest number of injuries and illnesses, on average, were reported by those working in skilled and the largest number of near misses, on average, were reported by those working in commercial and industrial services.

5.3 Health and wellbeing in the gig economy

Wellbeing for respondents in the sample was lower than Australian norms, particularly for those who reported that their main source of income was non-gig work. While the average scores across the items of the personal wellbeing index were generally consistent, the areas where respondents were generally more satisfied in their lives were feeling safe, personal relationships, health and standard of living, whereas future security and life achievement were the areas they were least satisfied with, and this was consistent for both groups irrespective of their main source of income. Overall, respondents in the sample reported normal levels of resilience but compared to earlier studies, this was at the lower end of the resilience scale. There was little difference between groups for respondents’ self-reported resilience. Similarly, respondent self-esteem was at the lower end of the normal range and there were no differences between groups on the basis of main source of income.

Interestingly, despite the range of work related activities that respondents in this sample undertook, their scores on the thriving at work scale were moderately high and there were no substantive differences between respondents whose main income was gig work or non-gig work. It could have been expected, given the fragmentation of work in the on-demand economy that thriving, particularly with its focus on learning and vitality, would be lower, but in the present study this was not the case.

5.4 Limitations

We have used a cross-sectional survey with data collected at one point in time and as such we are not able to track changes in respondent perceptions over time in their social and economic context. This is important presently because we have collected data on workers in the Victorian gig economy prior to the major social and economic upheavals associated with the COVID-19 virus. While COVID-19 arose before the launch of this survey, the impact of COVID-19 in the Australian context has increased more recently. For example, respondent perceptions of risk or the likelihood of becoming ill in the course of their gig work are likely to have changed with the increased spread of COVID-19. Further, it could be expected that workers who rely of gig work, like others in the conventional economy, will be impacted by job losses and face economic choices such as needing to work due to the absence of sick pay or other entitlements. The current situation could be expected to have a profound impact on gig workers perceptions of risk, health, safety and wellbeing along with their financial security.


5.5 Conclusions

This report summarises the characteristics and experiences of gig workers and their working environment in the State of Victoria. While interest in the on-demand economy has grown substantially in recent years, there is still very little quantitative research on gig workers in the Australian on-demand economy. Presently, McDonald and colleagues15 have provided the most extensive analysis of workers the Australian on-demand economy. While this report focuses only on gig workers in Victoria, it extends that earlier research by investigating the motivations of gig workers in greater detail and by examining gig worker perceptions of their working environment and gig worker health, safety and wellbeing. Workers in the on-demand economy work through a wide range of platforms across many industries, so the services that they offer vary considerably. This also means that strengths and vulnerabilities vary across workers within the on-demand economy. In particular, we have observed that differences exist between workers whose main income is derived from gig work and those whose main income is from non-gig work, particularly with respect to motivations to work in the on-demand economy and safety issues. Presently, the drivers of these differences are unclear, and it would be valuable for future research to take this into account. It may also be an issue that regulators and policy makers need to consider in their decision making around gig workers.

This narrative that there are some workers within the on-demand economy who are more vulnerable than others is borne out in this research. We have noted that those who main income is gig work are more vulnerable to injury and illness, near misses, violence and aggression, sexual harassment and racial vilification. However, the extent of gig worker vulnerability is not clear cut. In the context of the safety research conducted by the Work Health and Safety team, the workers in this sample have lower rates of work-related injury and illness14 as well as fewer experiences of violence and aggression33, 34 than observed with non-gig economy workers in our earlier research. However, the low levels of reporting violence and aggression by gig workers is consistent with earlier research.32, 35, 36 This is an area that needs further investigation in order to understand not only what avenues are available to gig workers for reporting incidents such as violence and aggression, but also what kinds of education and post-incident support could be provided to them. Our results also show that the level of wellbeing for respondents in this sample is lower than the Australian average and that, while respondents generally demonstrated normal levels of resilience and self-esteem, their scores were at the lower end of normal, which may suggest that the pressures for gig workers vary from that of other workers. Overall, this research has extended our understanding of work in the on-demand economy in the Australian context. The results also indicate that working in the on-demand economy is not necessarily experienced as exploitative. Respondents in this study derived satisfaction from work and experienced their work as challenging, but there were vulnerabilities in terms of safety and wellbeing. Further research is required to understand what drives these vulnerabilities and how to raise awareness of health, safety and wellbeing issues for workers in the on-demand economy.


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Further information

Professor Helen De Cieri Monash Business School Monash University 900 Dandenong Road Caulfield East, Victoria 3145 Australia E: [email protected] W: workhealthsafetyresearch.org W: monash.edu.au

CRICOS provider: Monash University 00008C

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