Are platform workers willing to unionize? Exploring survey evidence from 14 European countries

Vandaele, Kurt; Piasna, Agnieszka; Zwysen, Wouter Working Paper Are platform workers willing to unionize? Exploring survey evidence from 14 European countries ILO Working Paper, No. 106 Provided in Cooperation with: International Labour Organization (ILO), Geneva Suggested Citation: Vandaele, Kurt; Piasna, Agnieszka; Zwysen, Wouter (2024) : Are platform workers willing to unionize? Exploring survey evidence from 14 European countries, ILO Working Paper, No. 106, ISBN 978-92-2-039152-5, International Labour Organization (ILO), Geneva, https://doi.org/10.54394/QWUL5553 This Version is available at: https://hdl.handle.net/10419/283545 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Exploring survey evidence from 14 European countries Authors / Kurt Vandaele, Agnieszka Piasna, Wouter Zwysen February / 2024 ILO Working Paper 106 Copyright © International Labour Organization 2024 This is an open access work distributed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). Users can reuse, share, adapt and build upon the original work, as detailed in the License. The ILO must be clearly credited as the owner of the original work. The use of the emblem of the ILO is not permitted in connection with users’ work. Attribution – The work must be cited as follows: Vandaele, K., Piasna, A., Zwysen, W. Are platform workers willing to unionize? Exploring survey evidence from 14 European countries. ILO Working Paper 106. Geneva: International Labour Office, 2024. 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Information on ILO publications and digital products can be found at: www.ilo.org/publns ILO Working Papers summarize the results of ILO research in progress, and seek to stimulate discussion of a range of issues related to the world of work. Comments on this ILO Working Paper are welcome and can be sent to actr[email protected]. Authorization for publication: Maria Helena André, ACTRAV Director ILO Working Papers can be found at: www.ilo.org/global/publications/working-papers Suggested citation: Vandaele, K., Piasna, A., Zwysen, W. 2024. Are platform workers willing to unionize? Exploring survey evidence from 14 European countries, ILO Working Paper 106 (Geneva, ILO). https://doi. org/10.54394/QWUL5553 01 ILO Working Paper 106 Abstract Embedded in the particular model of work organization of digital labour platforms, platform workers face several hurdles discouraging them from becoming trade union members. These relate to algorithmic management, regulatory arbitrage regarding the employment arrangements and the promotion of an entrepreneurial orientation among platform workers. Nevertheless, based on data from a representative survey in 14 European countries, union density in the platform economy stands at 13.4 per cent. This should be interpreted as a kind of “platform unionism” that exists by coincidence, however, as union membership is most likely rooted in the labour market status of platform workers in the conventional economy. Compared to the general population, platform workers have stronger pro-union attitudes and are more receptive to union membership. Probably partly reflecting difficulties in the ability to unionize, there is still a gap, though, between attitudes and willingness to unionize: whereas about two-thirds of platform workers hold positive attitudes towards unions, only over a quarter state that they would like to join a union. Apart from those positive pro-union attitudes, the propensity to unionize also seems to be determined by engagement in offline networks that promote a social norm of union membership and online participation in digital work-related communities. While these findings could inform union recruitment and organizing strategies, it is needless to say that the heterogeneity of the platform workforce, strongly influenced by the different ways in which workers participate in the platform economy, requires at the same time tailor-made strategies. About the authors Kurt Vandaele is Senior Researcher at the European Trade Union Institute (ETUI), Brussels. His research interests include trade union revitalization; the collective action repertoire of workers; and the platform economy and labour. Agnieszka Piasna is Senior Researcher at the European Trade Union Institute (ETUI), Brussels. Her research interests include job quality, labour market policies and regulation, digitalisation and gender equality. She coordinates research activities within the framework of the ETUI’s Internet and Platform Work Survey, develops the European Job Quality Index and carries out research on working time reduction. Wouter Zwysen is Senior researcher at the European Trade Union Institute (ETUI), Brussels. He is a quantitative researcher studying inequalities in the labour market. He specifically looks at the future of work, migrant and ethnic inequalities, and wage developments and gaps. 02 ILO Working Paper 106 Abstract 01 About the authors 01 Acronyms 05 XIntroduction 06 X1 Workers’ various patterns of participation in the platform economy and union strategies 09 X2 Data and methods 12 X3 Accounting for the heterogeneity of platform work 14 X4 Existing unionization levels in the platform economy 18 X5 Drivers for unionization among platform workers 22 X6 Willingness to become union members among platform workers 25 X7 The relationship between unionization drivers and willingness to unionize 29 X8 Discussion, limitations and future directions 31 XConclusion 33 References 36 Acknowledgements 41 Table of contents 03 ILO Working Paper 106 List of Figures Figure 1 – Studying unionization in the platform economy 10 Figure 2: Platform workers’ attachment to the platform economy by labour market status 15 Figure 3: Workers’ main labour market status by types of platform work 16 Figure 4 Degrees of attachment by types of platform work 17 Figure 5: Unionization rates among platform workers and the general population, by individual characteristics (%) 18 Figure 6: Unionization rates among platform workers and the general population, by labour market status, working time and sector (%) 20 Figure 7: Unionization rates among platform workers by heterogeneity of platform work (%) 21 Figure 8: Attitudes towards trade unions among non-union members, by heterogeneity of platform work (%) 23 Figure 9: Engagement in union-friendly offline social networks and participation in online work-related communities among non-union members, by heterogeneity of platform work (%) 24 Figure 10: Comparing willingness to unionize between platform workers and the general population, by individual characteristics (%) 25 Figure 11: Comparing willingness to unionize between platform workers and the general population, by labour market status, working time and sector (%) 26 Figure 12: Willingness to unionize among platform workers by heterogeneity of platform work (%) 27 Figure 13: Differences in willingness to unionize between platform workers and the general population, by heterogeneity of platform work 28 Figure 14: The effects of drivers for unionization on willingness to join a union 29 Figure 15: The effects of drivers for unionization on willingness to unionize, by heterogeneity of platform work 30 04 ILO Working Paper 106 List of Tables Table 1: Comparison between the general population and platform workforce 14 Table 2: Drivers for unionization among non-platform and platform workers 22 05 ILO Working Paper 106 Acronyms ETUI European Trade Union Institute EU European Union IPWS Internet and Platform Work Survey 12 ILO Working Paper 106 X2 Data and methods To analyse the attitudes of platform workers towards trade unions and their willingness to unionize, this paper makes use of large-N individual-level data from the Internet and Platform Work Survey (IPWS) carried out by the European Trade Union Institute (ETUI).50 This is a representative cross-national, multi-lingual survey among a simple random sample of the working age population between 18-65 years old, with the fieldwork harmonized and coordinated by Ipsos. Interviews are conducted via computer-assisted telephone interviewing implying answer options being kept simple and the questionnaire reasonably compact. The analysis uses data pooled from two survey waves, carried out in Spring and Autumn 2021, and including in total 36,124 respondents from fourteen European countries of which seven are in central and eastern Europe: Austria, Bulgaria, Czechia, Estonia, France, Germany, Greece, Hungary, Italy, Ireland, Poland, Romania, Slovakia and Spain. The country selection offers a good geographical representation of Member States of the European Union (EU), spanning all regions apart from the Nordic countries – the latter being marked by high union density. Moreover, the 14 countries included in the survey in fact cover 84 per cent of the working age population in the 27 EU Member States. This, together with the large representative random sample of respondents, allows the generalizing of conclusions to the workforce at EU level with a reasonable degree of confidence. This working paper adopts a more holistic approach, however, instead of highlighting country differences or similarities. Post-stratification weights have been applied in both the descriptive analyses and regression models. The survey contains a battery of questions on the prevalence and intensity of different types of digitally-mediated work.51 Platform workers are those respondents who self-report having performed any of the following digitally-mediated services in the past 12 months, with overall six types of platform work discerned on this basis: (1) remote platform workers performing relatively simple micro-tasks; (2) remote professional freelancers performing more complex tasks such as graphic design and multimedia, sales and marketing support, software and web development, writing and translation, although differentiating between requesteror worker-initiated transactions is not possible; (3) location-based private ride-hailing; (4) location-based app-oriented food delivery; (5) other types of location-based services carried out in the private sphere, usually in clients’ households, such as care, tutoring or handyperson work; and (6) workers who are combining more than one of the above activity types, the latter being labelled as “multiple platform work”.52 To validate these self-reports of digitally-mediated work, respondents are also asked to provide the name of the website or app they use. Only when this name matches an actual online labour platform, algorithmically matching workers with clients, collecting client ratings and handling payments, are respondents classified as platform workers. The main focus of the analysis in this working paper is on non-unionized platform workers,53 defined as respondents who have performed work through a digital labour platform in the last twelve months and who are not a member of a trade union. Willingness to unionize is measured by the question “Would you be willing to become a trade union member in the near future?”, with 50 For further details, see Piasna et al. (2022). 51 See Piasna et al. (2022). 52 “Multiple platform work” is distinguished here from the practice of “multi-apping” or “multi-homing”, which is defined as working for two or more different competing labour platforms but within the same type of platform work. “Multi-apping” or “multi-homing” is here not considered a separate type of platform work. In other words, platform workers who are engaged with various digital labour platforms and performing the same kind of tasks such as, for instance, food delivery, are attributed to a single type of platform work. 53 Platform workers who are employers with employees are a priori excluded from the analysis; they simply cannot be considered a target for recruitment drives by trade unions and it is also very doubtful if such platform workers would show any interest in becoming a union member. 13 ILO Working Paper 106 “yes” and “no” as possible responses.54 The final sample for the analysis includes 1,961 platform workers of whom 1,698 are non-unionized; 28.3 per cent of the latter declared that they would like to join a union in the near future. To contextualize the findings about platform workers and to reveal to what extent they might be distinct from other workers, throughout this working paper they are compared to the general population; thus, working age adults who have not worked on digital labour platforms in the past 12 months. The individual-level data from the IPWS provide rich information on the respondents, allowing for comparisons between similar workers in the online, platform economy and the offline, traditional economy. Apart from several sociodemographic characteristics of the respondents, their attachment to and tenure in the platform economy and their labour market status are considered. Regarding the latter, it is assumed that self-reported status mostly refers to status in the conventional economy, although this might be different for platform workers with a strong attachment to the platform economy. Overall, five possible combinations of platform work with “offline” labour market statuses are distinguished: the active, either (1) employees (i.e. wageand salary-earners either on temporary or open-ended contracts), (2) own-account workers or the solo self-employed and (3) the unemployed; and the inactive, either (4) students or (5) persons economically inactive because of care responsibilities or other reasons like pension. The formal contractual status of platform workers vis-à-vis the digital labour platform is not known, however. This implies that country differences in the regulatory or legal framework on the employment status of platform workers cannot be analysed. Put differently, only the probability of platform workers becoming unionized is researched; their formal ability to become a union member is thus not part of the analysis due to a lack of relevant data. 54 Those respondents (n=2,860) who answered “I don’t know” to this question are attributed to the “no” category, while those respondents (n=231) who preferred not to answer are excluded from the analysis. 14 ILO Working Paper 106 X3 Accounting for the heterogeneity of platform work The workforce in the conventional economy is not uniform in its interests and needs. The workforce in the platform economy has equally been found to be diverse and non-homogenous.55 Accounting for the heterogeneity of platform work is therefore crucial for trade unions. Heterogeneity might refer, for instance, to the economic risks of the work or the effective job autonomy over which tasks are undertaken and how they are performed. All of this is likely to influence union strategies and tactics for extending their offer to platform workers as well as informing their priorities in selecting target groups and understanding their (diverse) interests and needs. Two major distinctions for considering the heterogeneity of platform work are made in the empirical analysis below: the first is based on the degree of economic dependency or attachment to platform work;56 and the second is connected to the type of tasks performed in platform work. In addition, differences between workers with various lengths of tenure in platform work are considered. The overview below provides an overall picture of the heterogeneity and segmentation of the workforce in the platform economy, with a focus on the links and commonalities with the conventional, offline economy. XTable 1: Comparison between the general population and platform workforce57 General population (n=31,953) Platform workforce (n=1,961) Employees 61.6% 56.0% Solo self-employed 7.8% 15.4% Unemployed 10.0% 11.2% Students 5.6% 10.8% Inactive 14.8% 6.6% Table 1 provides an overview of the specific insertion of workers in the platform economy based on their labour market status in the conventional economy. A comparison of the labour market status of platform workers with that of the general population – that is, those who have not worked on a platform in the last twelve months – reveals that the two groups are statistically significantly different. The overall share of the economically active (i.e. employees, solo self-employed and the unemployed) does not differ too much between the two groups and is around 80 per cent. However, a much higher proportion of platform workers are solo self-employed, with over fifteen per cent defining themselves as such, although the contractual status – genuine or bogus self-employed, “independent contractor” or otherwise – in the platform economy is unknown. In addition, more than half of the respondents engaged in the platform economy are employees – a difference of five percentage points from the general population. Just over ten per cent of platform workers are either unemployed or students, while almost seven per cent are economically inactive in the traditional labour market. The platform workforce thus also differs from the non-platform workforce in terms of the higher proportion of students and 55 Drahokoupil and Vandaele (2021); Piasna and Drahokoupil (2021); Wilkinson et al. (2022). 56 See also Piasna and Drahokoupil (2021); Schor et al. (2020). 57 Source: ETUI IPWS Spring and Autumn 2021. 15 ILO Working Paper 106 the lower share of the economically inactive.58 These two groups traditionally do not belong to the workforce in the conventional economy, whereas students and the inactive can be part of the platform workforce. Following previous studies,59 a distinction is made between two degrees of economic attachment to platform work, based on the number of working hours and the share of personal income derived from platform work. A higher level of attachment is defined as spending 20 hours or more per week on platform work or earning more than 50 per cent of personal income through platforms.60 This group is called “main platform workers”, and a little over one in four (27.2%) platform workers fall into this category. Put differently, main platform workers account for 1.6 per cent of the general working age population, the latter including both the workforce (employees, the solo self-employed and unemployed) as well as the non-workforce (students and the economically inactive). The remaining platform workers are considered to be weakly attached to platform work as they work fewer than 20 hours per week or earn less than half their income from platform work. XFigure 2: Platform workers’ attachment to the platform economy by labour market status61 Note: Attachment is statistically significantly different across the labour market status (p<0.01). Figure 2 shows differences in the degree of economic attachment to the platform economy depending on labour market status in the conventional economy – a variation that is statistically significant. The solo self-employed, followed by the unemployed, are most likely to be highly attached to platform work, with 42.5 per cent and 31.6 per cent respectively being main platform workers. It can only be speculated why this is the case. One possible reason might be that some solo self-employed consider working via digital labour platforms as an expansion of their client base. Alternatively, they presumably engage in platform work more intensely to compensate for their relatively more precarious position and insufficient incomes, or indeed to fill in income gaps during periods of job search and drops in demand in the traditional labour market. Conversely, the shares of main platform workers are the lowest among those economically inactive in the conventional economy (21.7%), those in dependent employment (23.4%) and students (24.9%). 58 The labour market status of platform workers with a migrant background is statistically significantly different (F=3.85, p<0.01): they are more often unemployed and less often employees. The percentage of employees is below fifty per cent. 59 For example Pesole et al. (2018); Piasna et al. (2022). 60 The same thresholds are applied to all types of platform work. 61 Source: ETUI IPWS, Spring and Autumn 2021. 16 ILO Working Paper 106 Apart from degree of attachment to the platform economy, a second feature that differentiates platform workers is the type of platform work they do, defined by type of tasks and format of task delivery, with a major distinction being made between “geographically tethered” location-based platform workers and online, remote platform workers performing “cloud work”.62 Perhaps contrary to conventional wisdom, shaped by first-hand observation and public debate, most of the platform work in Europe actually does not take place in public settings, with food delivery and ride-hailing being the main examples.63 Conversely, the largest group of platform workers in the survey sample are micro-taskers (38.4%), followed by remote professional platform workers (15.0%) and those performing on-location platform work in private settings (14.8%). Delivery work (11.7%) and ride-hailing (7.3%) are relatively less common. Some 12.7% of platform workers perform more than one type of platform work. In terms of the split between location-based and remote platform work, more workers perform remote work (59.4%) than any type of location-based platform work (40.6%). XFigure 3: Workers’ main labour market status by types of platform work64 Note: Ordered by share of employees. Labour market status is statistically significantly different across platform type (p<0.01). Figure 3 illustrates the differences between platform workers doing different types of platform work in terms of their main labour market status in the conventional economy. Overall, there are statistically significant differences in status between the types, although there is no clear division between on-location and remote forms of task delivery. While most platform workers are dependent employees in the conventional economy, their share is the highest among those doing more than one type of platform work and among food delivery couriers, while it is by far the lowest among ride-hailing drivers. There is also considerable variation in the prevalence of the solo self-employed, with the highest share in private ride-hailing followed by multi-platform work and remote professional platform work. Students are especially common in micro-task remote platform work, among on-location platform workers in the private sphere and remote professional work, while they are relatively less active in ride-hailing and multi-platform work. The unemployed are similarly likely to engage in each of these types of platform work, with on-location platform work in the private sphere being the most attractive for them. Finally, those economically 62 Drahokoupil and Vandaele (2021); Graham and Woodcock (2020); Howcroft and Bergvall-Kåreborn (2019); ILO (2021); Johnson (2020); Vallas and Schor (2020); Vandaele (2021). 63 See also Piasna et al. (2022). 64 Source: ETUI IPWS, Spring and Autumn 2021. 17 ILO Working Paper 106 inactive in the conventional economy are somewhat more likely to engage in ride-hailing, remote micro-tasking and other types of on-location platform work. XFigure 4 Degrees of attachment by types of platform work65 Note: Platform attachment is statistically significantly different across platform type (p<0.01). Previous studies have pointed out that platform work is usually only supplementary income, yet at the same time that the algorithms allocating work tend to favour workers with a higher degree of attachment to platform work, thus those who declare greater availability and have a greater number of tasks completed.66 Figure 4 shows that attachment to platform work varies considerably depending on the type of tasks performed. Unsurprisingly, those who work on multiple platforms and perform several types of tasks have the highest economic attachment to platform work, with nearly half of them (45.8%) classified as main platform workers. Conversely, the attachment of micro-taskers is by far the weakest, with 85.3% of workers considering it a marginal commitment which should come as no surprise given the extremely low rates of pay in this type of work. For all other types of platform work, the level of attachment is fairly similar, with around one-third of respondents being main platform workers. 65 Source: ETUI IPWS, Spring and Autumn 2021. 66 Piasna and Drahokoupil (2021); Schor et al. (2020); Shanahan and Smith (2021). 18 ILO Working Paper 106 X4 Existing unionization levels in the platform economy Depending on status in the traditional labour market, workers are likely to bring a certain degree of unionization with them into the platform economy. Levels will be relatively higher for employees, albeit with considerable variation across occupations and economic sectors, than for groups who are temporarily or completely outside the labour market.67 This section therefore maps and describes existing levels of unionization among platform workers and compares these levels with similar groups in the conventional economy. Two caveats are warranted here. First, it should be remembered that platform workers are defined here as those who have done tasks through a digital labour platform at least once in the past twelve months, thus also including occasional platform workers. Second, to avoid comparing apples with oranges, the calculation of union density includes non-workers in the conventional economy. This means that density in the conventional economy is underestimated, as the non-working population (students and the economically inactive) is usually not included in such calculations. In other words, union density rates in the conventional economy are actually higher than what is presented here. As many platform workers are not part of the workforce in the traditional labour market, union density is thus captured as the share of union members in the total working age population. This allows a more meaningful comparison of the density rates of platform workers and those who do not engage in platform work. XFigure 5: Unionization rates among platform workers and the general population, by individual characteristics (%)68 Note: Differences in unionization between platform and non-platform workers are statistically significant (p<0.05) for migrants and those with low and high educational attainment. 67 Where internal rules or regulations allow, special horizontal structures within trade unions are sometimes set up for students, the unemployed or pensioners, often with reduced membership rates. 68 Source: ETUI IPWS, Spring and Autumn 2021. 19 ILO Working Paper 106 In general, the proportion of platform workers who are union members is remarkably similar to the general population in the sample and amounts to 13.4 per cent.69 However, a comparison of groups with similar sociodemographic characteristics reveals some noticeable differences – see Figure 5. While women are slightly more likely to be union members among platform workers than men (14.2% and 12.6%, respectively), the reverse is observed in the general population (12.9% and 13.9%). There is little difference among younger workers but, among those older than 54, unionization is visibly higher among platform workers (20.2%) than in the rest of the population (16.0%). Union membership among people with a migrant background is much more common for those who work on digital labour platforms (16.2%) compared to those who do not (10.7%). Platform workers with a higher level of education are less likely to be union members (13.1%) than those with a similar level of education who do not work on digital labour platforms (16.6%); while the opposite is found for those with lower educational levels, with 16.9 per cent of platform workers and only 9.4 per cent of others being union members. 69 Trade union density in the conventional economy in the survey sample is 17.7 per cent if only employees are taken into account. 20 ILO Working Paper 106 XFigure 6: Unionization rates among platform workers and the general population, by labour market status, working time and sector (%)70 Note: Differences in unionization between platform and non-platform workers are statistically significant (p<0.05) for the solo self-employed; the inactive; full-time workers; and in the construction sector. In terms of labour market status, trade union membership is relatively high among platform workers who are not employees in their main paid job – see Figure 6. Thus, among those who earn from platform work but occupy “marginal” or “outsider” positions in the traditional labour market, such as the solo self-employed, the unemployed, students or the economically inactive, unionization rates surpass by a considerable margin – between 1.3 and 6.6 percentage points – those of the rest of the population. The reverse is observed among employees, with membership rates of 16.0 per cent among platform workers and 17.7 per cent among the rest. A parallel pattern is found among those with full-time jobs in the conventional economy, with platform workers having lower unionization rates (13.6%) than offline workers (16.8%). As could be expected, the sectors with the highest shares of unionized workers in the sample are manufacturing and public services (i.e. education, healthcare and public administration); platform workers with jobs in these sectors are more likely to be unionized than non-platform workers. In other industries, apart from the residual category of “other services”, platform workers are less likely to be unionized than offline workers. 70 Source: ETUI IPWS, Spring and Autumn 2021. 21 ILO Working Paper 106 XFigure 7: Unionization rates among platform workers by heterogeneity of platform work (%)71 Note: Ordered within types of heterogeneity. Differences by platform type are statistically significantly different (p<0.05); other differences are not. In devising trade union strategies for the platform economy, it is key to recognize and understand not only the differences between platform workers and those working in the conventional economy, although there is a large overlap between the two, but also the heterogeneity among platform workers in their views on and experiences with trade unions. Figure 7 reveals this heterogeneity in terms of union membership. There is virtually no variation in membership by level of platform economic attachment, with main platform workers and those with weak attachment to platform work standing at the same unionisation level. Unionization rates are lower among platform workers with the shortest tenure, of less than one year, however. Furthermore, while the overall unionization rate among platform workers stands at 13.4 per cent, as shown earlier, it is by far the lowest in food delivery, with 7.5 per cent of couriers being union members, followed by remote professional work and ride-hailing, where union density hovers around 10 per cent. Low unionization rates among food delivery couriers might be surprising in view of the high visibility of bottom-up organizing and collective initiatives,72 but this is at least partly due to union membership being confounded in the conventional and platform economies. Furthermore, micro-taskers and workers in on-location private work show middle-range unionization rates, while those engaging in multiple types of platform work report by far the highest rate of just over 20 per cent. As in the conventional economy, all of this suggests that there is still considerable scope for unions to set up initiatives to organize the platform workforce, given that 86.6% overall are not unionized in the 14 European countries considered. The remainder of the analysis will therefore focus on this group, with the aim of improving understanding of their openness to becoming union members in the future and the possible drivers for such a decision. 71 Source: ETUI IPWS, Spring and Autumn 2021. 72 Tassinari and Maccarrone (2020); Vandaele (2023). 28 ILO Working Paper 106 XFigure 13: Differences in willingness to unionize between platform workers and the general population, by heterogeneity of platform work81 Note: Positive values show higher willingness among platform workers compared to non-platform workers. Effects are estimated from logistic regression controlling for gender, age, migrant background, education, place of residence, trade union membership in the past and labour market status, including union presence in the workplace for those employed, and including fixed effects. Four separate models are estimated, divided by horizontal lines in the figure. Finally, Figure 13 maps the willingness to join a trade union among workers in the platform economy compared to the general population, accounting for differences that may be linked to sociodemographic profile. The latter includes individual characteristics such as gender, age, educational attainment, type of place of residence and migrant background, as well as labour market status, and information on past union membership and the presence of a union in the workplace. In general, the results confirm that platform workers are more willing to unionize than the rest of the population – a statistically significant difference of nearly three percentage points – once other differences between these groups are accounted for. Main platform workers do not differ from non-platform workers in their declared willingness to unionize, while those weakly attached to platform work are significantly more likely to join a union although the differences in tenure in platform work turn out not to be statistically significant. When considering different types of platform work, professional remote workers stand out as the only category that is significantly less inclined to unionize, with nearly six percentage points fewer than the general population expressing an intention to join a union in the near future. Those engaged in several different types of platform work are much more likely to unionize than non-platform workers (by over 11 percentage points), with other categories of platform workers not significantly different from the rest of the population. 81 Source: ETUI IPWS, Spring and Autumn 2021. 29 ILO Working Paper 106 X7 The relationship between unionization drivers and willingness to unionize This section ties together the issues discussed in the previous two and examines the impact of three drivers for unionization on willingness to join a union in the future. As a reminder, the drivers include: (1) pro-union attitudes; (2) union exposure in terms of being embedded in union-friendly social networks; and (3) engagement in digital, online communities. Figure 14 shows the overall relationship between each of these three drivers and the share of respondents likely to unionize in the near future, accounting for individual differences between workers in terms of their sociodemographic profile and labour market status. In the general working age population, the overall effect of each of these three drivers on willingness to unionize is positive and statistically significant. For instance, people who express pro-union attitudes are nearly 12 percentage points more likely to unionize. Those embedded in a union-friendly social network are nearly 10 percentage points more likely, while those engaged in online communities are nearly eight percentage points more likely to become a union member. XFigure 14: The effects of drivers for unionization on willingness to join a union82 Note: Effects are estimated from logistic regressions controlling for gender, age, migrant background, education, place of residence, trade union membership in the past and labour market status, including union presence in the workplace for those employed, and country fixed effects. Each block separated by horizontal lines indicates a separate model. 82 Source: ETUI IPWS, Spring and Autumn 2021. 30 ILO Working Paper 106 The next step is to test whether these three drivers for unionization are indeed different for platform workers. The results are shown below the dotted lines in Figure 14. They reveal that the effect of pro-union attitudes is much stronger among platform workers and is statistically significantly different from the effect among the rest of the population. Thus, platform workers who express pro-union attitudes are also nearly 18 percentage points more likely to want to join a union, compared to just over 11 percentage points among the rest. The other two drivers for unionization – union-friendly network and online communities – have the same effects among platform workers as among the general population. XFigure 15: The effects of drivers for unionization on willingness to unionize, by heterogeneity of platform work83 Note: Effects are estimated from logistic regressions for platform workers controlling for gender, age, migrant background, education, place of residence, trade union membership in the past and labour market status, including union presence at the workplace for those employed, and country fixed effects. Each block separated by horizontal lines indicates a separate model. The driver of unionization is interacted with platform heterogeneity variables. Finally, whether or not the drivers of unionization affect all platform workers in a similar way is examined, with the results shown in Figure 15. Overall, pro-union attitudes are positively associated with willingness to unionize for all types of platform workers. Having union-friendly social networks is also positively associated with the likelihood of unionizing for platform workers overall. While the differences are not statistically significant, the effect seems weaker for platform workers engaged in ride-hailing or food delivery work and stronger for micro-taskers, on-location private work and multiple types of platform work. Engagement in online communities for discussing work-related issues is positively associated with a willingness to unionize but seems to affect some groups more positively than others. It is particularly important for platform workers in ride-hailing, those carrying out remote professional work and those engaged in multiple types of platform work. It does not seem to be important for on-location workers in the private sphere or food delivery couriers. Online communities also appear to be important only for platform workers who have been engaged in platform work for at least one year, possibly due to their longer exposure to platform organizational practices.84 83 Source: ETUI IPWS, Spring and Autumn 2021. 31 ILO Working Paper 106 X8 Discussion, limitations and future directions To the best of our knowledge, this working paper is the first to examine both existing levels of unionization among platform workers and their propensity to unionize in the future from a comprehensive cross-national, quantitative perspective. The analysis covers six types of platform work in 14 European countries. In contrast to previous studies,84 attitudes towards collective organization via trade union membership in the platform economy are explicitly compared with the conventional economy. The individual-level data allow accounting for the range of individual and sociodemographic characteristics of platform workers, as well as the heterogeneity of platform work. Where feasible and relevant, workplace and industrial characteristics are also considered. Despite these strengths offered by a unique, representative individual-level dataset, the analysis carried out also has a number of limitations due to which it can therefore only be considered exploratory. To begin with, many of the measures used are based on dichotomous variables and single items in the survey. For instance, only the embeddedness in and engagement with onand offline networks per se are measured, not their frequency and the dynamics of those contacts. Follow-up research could include measures with more complex response options and derived from multiple items to allow testing of the reliability and validity of the findings. The measurement context may also have had an impact on the results as the survey was conducted during the Covid-19 pandemic; it is well known, for instance, that food delivery couriers suffered from poor working conditions in this context. Obviously, only attitudes and intentions to join a trade union were surveyed; no claims could be made about actual behaviour. Furthermore, with the data at hand, it is not possible to determine to what extent willingness to unionize is actually rooted in work experiences in the platform economy as opposed to the conventional economy or other types of life experience. This issue has been addressed, at least in part, by comparing platform workers with similar groups in the conventional economy which revealed, among other things, that platform workers hold stronger pro-union attitudes and have a relatively higher propensity to unionize. Moreover, assuming that trade unions are active in the platform economy, and that platform workers are aware of their right to unionize, it is not known which union they would like to join. The survey did not differentiate between grassroots unions and mainstream unions, although their conceptions of membership are likely to differ, with grassroots union members tending to be more active than in mainstream unions.85 Generalization of the findings should also be undertaken with caution as they apply predominantly to formal unionism in the European context whereas informal types of worker representation are more prevalent in the Global South.86 Possible differences in union activity in the platform economy between countries has not been considered here, such as outreach to platform workers, union efforts to mobilize and recruit platform workers or legal action to reclassify their employment status. In this sense, it might be useful for future analysis to include information on the number and type of trade unions active in the platform economy and their activities to date. At individual level, the survey did not ask about instrumental reasons for unionization, such as perceptions of income from platform work and working conditions, even though dissatisfaction with these seems to drive support for collective organization in the platform economy.87 Similarly, although offline embeddedness in 84 Geyer et al. (2023); Newland et al. (2018); Wood et al. (2022). 85 See Joyce and Stuart (2021); Vandaele et al. (2019). 86 Atzeni (2020). 87 Geyer et al. (in press); Wood et al. (2022). 32 ILO Working Paper 106 union-friendly social networks and online participation in work-related communities may indicate platform workers’ own potential involvement in social protest, this has not been measured directly. The organizational status of these work-related communities is also unknown: they could simply refer to online participation or to self-organized online collectives. Neither have other determinants of unionization, such as the political attitudes of platform workers, been included in the analysis although such a link seems of less importance in the platform economy.88 Other contextual (macro) variables have also not been accounted for, such as the changing regulatory environment in which digital labour platforms operate, as the costs and benefits of unionization may vary between different jurisdictions.89 Equally, dispute resolution mechanisms within platform companies may influence the decision to unionize. Finally, one dimension of the heterogeneity of platform work that has received much less attention in this study are workers with a migrant background, including circular or undocumented migrants, who are particularly active in the platform economy because of the low entry barriers with minimal formal requirements and limited alternative labour market opportunities in the conventional economy.90 Some of them may have been less familiar with trade unions in their home country, which may translate into a lesser willingness to unionize in their current country of residence, although union experience is also a function of individual biographies. Even if they are positive towards collectivism, they have been found to be simply “too pressed for time and caught up in their daily hustle to free up space in their heads and agendas for collective organisation”.91 This may be a general observation: while the overall majority of platform workers are generally positive about unions, far fewer of them express a willingness to unionize in the future. Thus, similar to findings in the conventional economy,92 there is a considerable gap between pro-union attitudes, unionization levels and actual willingness to unionize which might be a further research avenue to be explored. 88 Newland et al. (2018). 89 This reasoning may apply as well to particular platforms within the same type of platform work. 90 Altenried (2023); ILO (2021); van Doorn et al. (2022). 91 Van Doorn (2023: 173). 92 Piasna et al. (2022). 33 ILO Working Paper 106 XConclusion Although (still) limited in relative terms, with 5.6 per cent of the working age population engaged in platform work in Europe,93 the platform workforce is quite substantial in absolute terms and is growing rapidly. This study contributes to the understanding of unionization in the platform economy, both in terms of membership rates among different groups of platform workers and the potential for unionization among those who are not yet members. The findings are based on a unique cross-national and comparative survey, dedicated to the analysis of various forms of digitally-mediated work and trade union-related behaviour, which allows for an explicit link between the platform economy and the conventional economy. Four main conclusions can be drawn from the analysis about the possibilities to foster associational power via trade unions in the platform economy. These conclusions relate to trade union membership per se; the attitudes of platform workers towards unions; network-like drivers for unionization; and the heterogeneity of the platform economy – all of which have implications for possible union recruitment and organizing strategies in the platform economy. First, the platform economy is not, by default, completely free of trade union membership. A small share of platform workers are already unionized: the survey results indicate that union density in the platform economy in Europe stands at a (low) level of around 13.4 per cent. This percentage should not be all that surprising. In all likelihood, it is less the result of any dedicated or specific union activity in the platform economy: it is simply related to the labour market status of platform workers rooted in the conventional economy. Already unionized platform workers largely follow unionization patterns in the traditional labour market that are specific to their personal sociodemographic characteristics. Exceptions are workers aged over 54, those with lower educational attainment and migrants, all of whom report relatively higher unionization rates in the platform economy. Workers who carry out platform work are particularly active in relatively well-unionized sectors of the traditional economy, such as manufacturing and public services. In terms of labour market status, union density is relatively higher among platform workers who are unemployed, the solo self-employed and the economically inactive in the conventional economy. All in all, however, “platform unionism” merely exists by coincidence; that is, through the specific inclusion of platform workers in relation to their labour market status in the conventional economy. This small share of platform workers who are already unionized could nevertheless be an entry point for union organizing strategies. Second, the generally pro-union attitudes of platform workers and their intentions to unionize stand at odds with conventional wisdom about the platform economy. Induced by Californian ideology,94 this wisdom is often based on the newspeak of the digital labour platforms themselves. It tends to portray this economy as a union-free zone with highly independent, flexible and autonomous platform workers showing little interest in unionization or even being hostile towards trade unions. Yet, in fact, over two-thirds – 69.2 per cent – of platform workers express a positive attitude towards unions, a percentage that is even higher than in the general population. Equally, more than one in four platform workers say they would be willing to join a union – again a slightly higher proportion than in the general population. Openness to future union membership is particularly high among younger platform workers, those with a migrant background and those with lower levels of education. Third, the drivers for unionization are quite similar in the conventional and platform economies, with pro-union attitudes alone being a relatively more important driver for platform workers than for the general population, but it is unknown to what extent those drivers are rooted in the conventional economy or the platform economy. Nevertheless, trade unions tapping into offline 93 Piasna et al. (2022). 94 Srnicek (2017). 34 ILO Working Paper 106 pro-union social networks and online work-related communities seems to be a fruitful strategy for unions in the platform economy as well. Online communities might thus be a breeding ground for future unionization, acting as a stepping stone to union membership95, and such online communities are thus likely to pose less of a risk of simply replacing unions.96 The importance of pre-existing offand online networks calls respectively for networked organizing tactics and strategies, and digital unionism. Tapping into pre-existing networks is of course more feasible in the on-location platform economy due to the spatial proximity of workers, engaged in physical, timeand place-dependent platform jobs that depend on local customers. It remains an empirical question, however, to what extent such onand offline networks are marked by stability in terms of their organizers, given the generally high turnover in the platform economy. There is nevertheless a gap between the level of pro-union attitudes and willingness to unionize. A much higher proportion of platform workers hold positive attitudes towards unions than are willing to become members. Possible explanations for this gap could be related to the different insertion of workers into the platform economy and the degree of openness of trade unions to groups beyond their traditional core members, like those on workfare and the solo self-employed. Union membership may also be less open to the unemployed, especially as countries in the survey sample do not have unemployment systems in which unions are involved in their administration. The unemployed who also work on platforms are nevertheless more likely to unionize compared to those who do not work online. Furthermore, while students and the economically inactive are likely to be sympathetic to unions, they may have far fewer reasons actually to join them as they are outside the traditional workforce. Also, while some unions in certain occupations have a tradition of organizing the solo self-employed, and others have been catching up by opening up union membership and introducing dedicated structures for them, there is still work to be done.97 Fourth, looking more closely at the platform economy and the heterogeneity of its workforce, differences in existing union density are small when it comes to the degree of attachment to platform work. In general, those who are more economically attached to platform work are less inclined to join a union, but they represent a minority of all platform workers. The majority are only weakly economically attached to their platform job, primarily relying on other sources of income, especially those engaged in micro-tasking, and they are relativity more likely to be pro-union. Moreover, students engaging in platform work are demonstrating a greater willingness to unionize compared to students outside the platform workforce. As this is a young population that is relatively unfamiliar with trade unions, this is thus an interesting target group for outreach activities in the platform economy, especially as a first personal impression of unions seems to be important for future union membership.98 There are some differences in unionization rates depending on type of platform work, ranging from 7.5 per cent in food delivery to the one in five platform workers engaged in multi-type platform work. The latter thus seems an attractive group for brownfield organizing strategies, and they account for about 13 per cent of the platform workforce. Moreover, not only are multiple platform workers the most unionized of all platform workers, but they are also highly dependent on their platform jobs and they are more receptive to union membership than workers in other types of platform work. Together with food delivery couriers, who are the most strongly embedded in union-friendly social networks, and ride-hailing drivers, multiple platform workers are also comparatively more inclined to unionize in the future. Yet, perhaps even more than other types, multiple platform workers may be difficult to integrate into existing union structures of representation; of all platform workers, they may be the most in need of a dedicated union representation structure as their work spans multiple sectors. Needless to say, some, but 95 See also Vandaele and Piasna (2023). 96 Visser (2019). 97 Vandaele (2021). 98 Vandaele (2018b). 35 ILO Working Paper 106 not all, grievances and issues of platform workers are likely to vary between different types of platform work. Trade unions appear to be mainly active in the delivery and private ride-hailing sectors. Unions with a tradition of organizing a similarly precarious, transient or dispersed workforce, such as in cleaning or transport, are seen as more successful in connecting with platform workers and mobilizing them.99 Reflecting again the interconnection between the conventional and platform economies, it is in particular unions with previous experience in network-driven organizing that are engaging with those platform workers. Although delivery work and private ride-hailing are the most visible types of platform work, and therefore emblematic of the platform economy, most platform work – about 80 per cent – does not take place in public settings, however. Platform workers in the private sphere are relatively strongly embedded and engaged in union-friendly offline social networks and online digital communities. While micro-taskers are the largest group, on-location platform work in private settings and professional remote workers are almost of equal size. Performing the most complex and highly skilled tasks in the platform economy, more than half of professional remote workers has employee status, but a large share is made up of the solo self-employed. Remote professional workers differ from other types of platform work in that they hold relatively less pro-union attitudes and are less likely to unionize compared to the general population – those results might also reflect the inability of those workers to unionize related to their labour market status. Nevertheless, trade unions are not without inspiration, strategies and tactics for recruiting and organizing them. Tapping into online, digital communities of remote professional workers seems most feasible here, especially as they are among the most active compared to other types of platform work. Yet, attention to offline social networks should not be dismissed. Remote platform work is not only still place-bound and likely city-based100 but possibly also marked by regional specialization,101 all of which might open opportunities for offline (transnational) union organizing tactics and strategies. While some mainstream trade unions have opened up membership to the solo self-employed, 102 their membership base is unlikely to be solid among remote professional workers. This is probably also true of grassroots unions. Yet the latter’s engagement with workers in location-based platform work and bottom-up activism add to their legitimacy to speak on behalf of and in solidarity with these workers.103 In contrast, the claim of mainstream unions to represent workers in the platform economy are largely based on their expert role and embeddedness in social dialogue institutions.104 These claims might not always reflect the interests and needs of platform workers, however, which might strengthen their perceptions of being less represented by mainstream unions.105 The legitimacy of their representative claims in the platform economy could therefore be brittle if the membership of platform workers does not grow sufficiently. 99 Cini et al. (2022). 100 Herr et al. (2021). 101 Aleksynska et al. (2021). 102 Vandaele (2021). 103 Cini et al. (2022); Joyce et al. 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