A Study of Working Conditions in Platform Work

Abstract

Despite growing academic interest in platform work and the gig economy, most existing research focuses on Western Europe, often neglecting the unique institutional and socioeconomic contexts of Central and Eastern Europe. This study addresses that gap by exploring the working conditions of platform workers in Poland, with particular emphasis on both material and psychosocial dimensions from the workers’ own perspectives. Data were collected from a nationally representative sample of 450 platform workers engaged in both online and location-based tasks, using the computer-assisted web interviewing (CAWI) method. The findings show a high level of perceived autonomy, with 74% of respondents feeling that they are independent in their work. However, autonomy is often limited by external factors, in particular, the availability of work. Workers who treat platform work as a side job are significantly more likely to report a sense of autonomy. In terms of health and safety, only 27% expressed concerns about negative health impacts, and 24% reported poor working conditions. Those who received health and safety information from the platform were more likely to acknowledge potential risks. Interestingly, workers relying on platform work as their primary source of income were more likely to perceive their work as safe, compared to those treating it as supplementary employment.

1. Introduction

Platform work refers to “work organized through a digital labor platform and performed by an individual on the basis of a contractual relationship between the digital labor platform or an intermediary and the individual, irrespective of whether there is a contractual relationship between the individual or an intermediary and the recipient of the service” [1]. The vast majority of platforms supervise, monitor, and control not only the execution of and payment for this work but also the relationships between clients and workers, primarily through the use of algorithms and artificial intelligence.

Platform work holds significant potential to contribute to sustainable development, particularly by promoting social equity and economic inclusion. It can generate decentralized employment opportunities, help reduce income inequality, and support the development of new skills—key factors in ensuring that economic growth benefits all segments of society. These outcomes align closely with the objectives of the United Nations’ Sustainable Development Goals (SDGs) [2].

However, despite its potential, many platform workers face precarious conditions, including low pay, limited social protection, job insecurity, and unsafe or unregulated working environments, which are widely documented across gig economy sectors [3,4]. Addressing these challenges is essential for achieving several SDGs, especially Goal 8: Decent Work and Economic Growth and Goal 10: Reduced Inequalities. Ensuring fairness, security, and equity in the gig economy is not only a matter of social justice but is also a strategic necessity for long-term sustainable development. To unlock the full potential of platform work, coordinated action is required from all stakeholders, including governments, platform companies, and labor organizations, to ensure decent working conditions for platform workers [3,5]. Studying the conditions of platform work plays a crucial role in this process. It offers insights into the impacts of digital platforms on worker well-being and social inclusion, while helping to ensure that policies are grounded in the realities of the evolving labor market.

This paper explores the results of research conducted to understand platform workers’ perceptions of their working conditions and to determine the key factors shaping those views.

2. Literature Review

Existing literature on the working conditions within platform work largely focuses on employment and economic aspects [6,7]. A desk analysis by Eurofound, reviewing 63 studies published between 2014 and 2019, revealed that most of these studies aimed to estimate the scale and economic characteristics of platform work. Only a few studies explored non-economic aspects such as the working environment [8]. Likewise, a review conducted under the INGRID (Integrating Research Infrastructure for European Expertise on Inclusive Growth) project found that out of 72 studies from 2014 to 2020, only 4 included extractable data on non-economic working conditions [9].

Among the few EU-based questionnaire surveys that examine both the prevalence of platform work and its non-economic conditions, two stand out. The COLLEEM survey, an online panel survey carried out by the European Commission’s Joint Research Centre (JRC) in cooperation with the Directorate-General for Employment, Social Affairs, and Inclusion (DG-EMPL), was conducted in 2017 (pilot) and again in 2018. It assessed the scope of platform work, along with profiles of workers, task types, income sources, remuneration, and working conditions [10,11]. The EIGE survey, which was conducted by the European Institute for Gender Equality in 2020, focused on gender-related differences in working conditions, patterns, and work–life balance among platform workers in 10 EU Member States [12]. These studies, which encompass various types of platform work, are widely regarded as reliable sources of information on the scale and conditions of platform work [3]. They confirm that a key factor motivating individuals to engage in platform work is its flexibility. This flexibility is reflected in the ability to choose tasks, determine one’s working hours, set one’s own schedule, select the place of work, control the workload, and self-organize. It is frequently also perceived as a feature that enhances work–life balance [13,14]. However, in practice, it is often the opposite; this flexibility is frequently constrained, and it can blur the boundaries between private and professional life, potentially leading to a deterioration in work–life balance [15].

To better illustrate the diversity and complexity of working conditions in platform work,

Table 1. Review of studies on working conditions in platform work.

Study Source	Country/Scope	Methodology	Surveyed Aspects of Working Conditions
CERIC, University of Leeds (2017) [16]	Global (AMT, Clickworker, etc.)	Online survey (1200 workers)	Motivation, working time, pay, job satisfaction, autonomy, stress, social protection
Ipsos-MORI, (2016–2017) [17]	6 EU countries and Switzerland	Online + offline surveys, interviews	Flexibility, platform communication, client ratings, stress, health and safety, work–life balance
COLLEEM (JRC + DG EMPL, 2017) [10]	14 EU countries	Online panel survey (32,409 respondents)	Income, motivation, autonomy, work environment, stress, deadlines, skill development
COLLEEM (JRC + DG EMPL, 2018) [11]	16 EU countries	Online panel survey (38,022 respondents)	Pay, flexibility, monitoring, impact of ratings, social interaction, health risks
EIGE (2020) [12,18]	10 EU countries	Online survey (4932 workers)	Work-life balance, low/unfair pay, discrimination, skill development, unpredictability
ILO (2015, 2017) [19]	75 countries	Surveys + Skype interviews + Fair Crowd Work data	Wages, work availability, intensity, communication, social protection
Civey GmbH (2018) [20]	Germany	Online panel	Demographics, motivation, pay, satisfaction
EU study (2021) [21]	9 EU countries	Mixed methods	Income unpredictability, autonomy, safety, isolation, job satisfaction
UK national survey (2016) [22]	United Kingdom	Survey (5019 respondents)	Working time, flexibility, control, job satisfaction, skill development, wellbeing
Multi-country study [15]	8 EU countries	Semi-structured interviews (41 people)	Employment status, work intensity, taxation, environment, relationships, training
Uber + BSG (2014–2015) [23]	United States	Surveys (601 & 833 people) + admin data	Driver demographics, income, motivations
Uber—London (2018) [24]	United Kingdom	Telephone interviews (1001 drivers)	Income, working hours, motivation, flexibility, control, wellbeing
Couriers’ & drivers’ survey [25]	urban areas	Face-to-face interviews + online questionnaires	Work–life balance, risk awareness, safety responsibility, support from peers/supervisors
CERIC + EU project (2016–2017) [16]	8 EU countries	interviews with experts (50) + survey (1200 workers)	Pay, flexibility, intensity, skill development, job insecurity
Forum-based analysis [26,27]	English-speaking	Post analysis (1350) + 7 interviews	Algorithmic management, driver evaluations, autonomy, and control
Creative crowdsourcing interviews (2015) [28]	Global	20 face-to-face interviews	Working time, work-life balance
Work pressure survey (2020) [5]	China	Questionnaire, food delivery riders (9576)	Working time, work pressure, platform HRM practices
Job quality in the gig economy [29]	China	Questionnaire (500 gig economy workers) + 24 in-depth interviews	Salary and welfare, work enjoyment, work environment, health and safety, career development, work stress,

provides a summary of the key aspects examined in recent studies, emphasizing factors such as flexibility, income stability, social protection, health and safety, and algorithmic management.

Studies examining platform working conditions suggest that the tasks performed by platform workers are often identical to those carried out by individuals in traditional employment forms [17,30,31]. Consequently, the physical work environments and associated hazards are similar. Depending on the nature of the job, on-location platform workers may be exposed to various occupational risks, such as harmful chemicals, noise, dust, and vibration. Those performing delivery and transport tasks are frequently exposed to high temperatures, physical exertion, and a higher risk of accidents related to handling vehicles [7,32].

Conversely, online platform work, which typically involves computer use, presents physical hazards akin to those encountered by office workers: prolonged sitting, poor ergonomic conditions, repetitive hand and wrist movements, and eye fatigue stemming from long hours of work at a computer screen, poor screen positioning, or inadequate lighting [7,32].

Research shows that many platform workers lack an awareness of occupational health and safety risks. Often, they are not adequately informed or trained in this area. Moreover, platform workers tend to be younger and may lack experience in certain job types, especially when they perform such work irregularly. This trend raises concerns that platform workers may face greater health and safety risks than employees in traditional jobs [33,34].

Psychosocial risks in platform work stem not only from the nature of the tasks performed but also from the unique characteristics of this form of employment. For example, direct interaction with clients—whether online or on-site—can expose platform workers to physical or psychological violence, a hazard that also exists in traditional employment settings (e.g., [32]). However, platform work introduces additional, distinctive stressors, primarily through algorithmic management and digital surveillance. These technologies control how tasks are assigned, monitored, and evaluated, often diminishing workers’ autonomy and contributing to heightened anxiety and stress. Key factors that amplify these risks include constant behavioral monitoring and continuous performance evaluations [35,36]. Moreover, the perception of exploitation by digital platforms has a direct negative impact on the subjective well-being of platform workers. Feelings of unfair income distribution and a lack of distributive justice significantly reduce job satisfaction and overall well-being. Uncertainty about working conditions, income instability, and the absence of social protections—largely driven by algorithmic management—intensify such workers’ sense of job insecurity [5].

Platform workers’ psychological well-being is also affected by a range of other factors: the pressure to be available on short notice, a lack of control over their work, professional isolation, unpredictable income, and the absence of employee representation. Most platform workers operate independently, often without direct client interaction or peer support [27,34,37]. The platforms themselves rarely provide managerial or organizational support, as management functions are carried out by algorithms [30,38].

Additionally, the ratings and evaluation systems used by platforms may incentivize workers to accept tasks for which they are unqualified or to engage in risky behaviors. This occurs when workers believe that quicker performance or accepting work at any time may improve their ratings and lead to more opportunities or higher earnings. The nature of platform work also often results in both physical and social isolation, as has been widely documented.

Due to the diversity of the business models used by digital platforms, the variety of tasks offered, and significant differences in workers’ qualifications and working contexts, it is often difficult—or even impossible—to obtain a comprehensive picture of platform working conditions. Additionally, platforms frequently modify their operational models, and working conditions may vary significantly depending on the country in which the work is performed. These variations can include differences in remuneration, employment status, and representation rights.

As a result, it is challenging to provide an assessment of platform working conditions. Many of the negative evaluations found in the literature cannot be generalized to all forms of platform work. Moreover, workers’ perceptions of their working conditions may be shaped by both organizational factors, particularly algorithmic management, and their individual characteristics and preferences.

3. Materials and Methods

The survey questionnaire was developed based on well-established instruments from surveys on the subjective assessment of working conditions in platform work, such as the pan-European COLLEEM Survey, the European Institute for Gender Equality (EIGE) panel survey, and the European Working Conditions Survey (EWCS). It addressed the following key areas: autonomy, work–life balance, and material and psychosocial working conditions. The working conditions aspects included in the survey of each area are shown in

Table 2. Areas and aspects of working conditions in platform work, as included in the survey.

Area	Aspects Assessed
Motivations for working through digital platforms	Sense of independence Ability to choose start/end times, tasks, and the pace of work Influence over income
Autonomy in task and time management	Ability to reconcile personal and work life Long working hours (>10 h/day) Working evenings/nights/weekends
Workplace safety and health	Health risks Accident risk Task monotony Workload pressure; stress Contact with colleagues Work sustainability (until age 65) Information about risks

.

Outside the area of working conditions, respondents were also asked about their motivations for engaging in platform work. They could select multiple reasons, such as the inability to find another job, the flexibility to decide when to start and finish work, what tasks to perform, and how and at what pace to work, the ability to influence their earnings, the opportunity to combine work with other commitments (such as other paid work or family responsibilities), the need for extra income, the chance to gain more clients, and the possibility of working from any location.

To assess those factors affecting work scheduling, the respondents chose from options such as: personal preferences as to when to work via online platforms and when to engage in other activities, the availability of tasks/work assignments on platforms during specific times of the day, week, month or other period, other commitments outside the platforms (e.g., other jobs or studies), caring for and/or educating children, disabled, elderly, or infirm family members or friends, and the preferences of clients.

Demographic and socioeconomic data were also collected, including gender, age, education, household size, sources of income, and the proportion of income derived from platform work, as well as the type of work carried out (online or on-location).

4. Sample and Respondent Characteristics

Following the methodology of the 2019 COLLEEM study, the target population included individuals aged 15 and older who had engaged in platform work at least once per month over the past 12 months. Given the lack of precise data on the number and structure of platform workers in Poland, the sample was based on estimates, indicating that approximately 3 million individuals were involved in platform work in 2021 [21]. A minimum sample size of 450 respondents was set to ensure sufficient representation. The sample covered different types of platform work, including approximately 30% of respondents working in transport services, 30% in delivery services, 20% in in-home services such as cleaning and repairs, and 20% in online work.

Data collection was carried out by a specialized research agency in February and March 2024, using the computer-assisted web interviewing (CAWI) method. Participants were recruited through online panels, social media, and internet forums. The data collection process was closely monitored to ensure the appropriate size, structure, and quality of the sample. In the final sample, 343 respondents were engaged in on-location platform work (e.g., transport, delivery, and in-home services), and 107 performed online tasks. The average age of the respondents was slightly above 30, with the majority aged between 31 and 40 years. Only a small number of respondents were over 50 years old.

Regarding educational background, 41% of respondents had completed secondary education, 15% had completed post-secondary education, 7% had completed vocational education, and 36% held university degrees. For most participants, platform work was not their main source of income. Among online workers, 52% also held regular employment contracts, while 48% of on-location workers did so. Self-employment was reported by 9% of online and 13% of on-location workers. Additionally, 7% of online and 5% of on-location workers had retired or were receiving pre-retirement benefits. Roughly half of the online workers and 42% of on-location workers reported that their income from platform work accounted for less than 25% of their total income, while only 5% of online and 4% of on-location workers relied solely on platform work for their income.

5. Results

5.1. Motivations for Working Through Digital Platforms

The study showed that the motivations for taking up platform work are diverse. Moreover, these motivations differ slightly, depending on the type of work and whether it is online or on-location (although these differences were rarely statistically significant). However, three basic reasons for taking up this type of work can be distinguished. The most commonly mentioned motivation for working through a platform was the ability to choose one’s working hours, as indicated by nearly 49% of respondents (over 50% among on-location platform workers and 41% among online workers). Another frequent reason was the ability to control the method and pace of work, as selected by 37% overall (47% online and 34% on-location respondents). Nearly 35% cited the need for additional income as an important motivation (mentioned by over 47% online and 32% on-location respondents).

Although flexibility of work is often emphasized in other studies, it was not so highly valued by the respondents here. About 30% appreciated the possibility of combining platform work with other professional or personal commitments (slightly more often online (33%) than on-location (30%)). Even fewer valued the ability to choose tasks independently (27%), select their place of work (24%), or influence income levels (20%).

Only 13% overall (8% and 15% among online and on-location respondents, respectively) reported an inability to find other work as a reason, and the least-cited motivation was the potential to attract more clients (6%) (Figure 1).

5.2. Autonomy in Task and Time Management

Respondents’ assessments of their autonomy in organizing their work are particularly noteworthy, given how frequently this aspect is highlighted in other studies as a key reason for engaging in platform work. The results confirm a high level of perceived autonomy, as a vast majority (74%) feel independent in their platform work. In particular, they report being able to decide when to start and end work (76%), how and at what pace to complete their tasks (75%), and which tasks to choose (68%). Respondents were least likely to agree with the statement that they have an influence on the amount of income they earn from platform work, as notably fewer respondents (56%) agreed that they could influence their earnings, while 26% selected the neutral “Neither agree nor disagree” response here (Figure 2).

The assessment of factors influencing the timing and scheduling of respondents’ platform work can be divided into two categories: subjective (related to individual preferences) and external factors (independent of personal choice). The subjective factors were rated the highest, with nearly 89% indicating that their schedule mainly depended on their own preferences. However, external factors also played an important role, as 88% pointed out the availability of work as a key influence, followed by obligations from other jobs or studies (84%) and client preferences (70%). Family responsibilities had the least impact (64%) (Figure 3).

5.3. Workplace Safety and Health

Most respondents believe that platform work does not negatively affect their health and can be performed until retirement. Only 27% expressed concern regarding health deterioration due to work conditions, 24% reported poor health and safety conditions, and 22% felt that accidents were likely. Only 12% of the surveyed platform workers stated that the conditions of their work were so harmful or demanding that they could not see themselves continuing in such work until the age of 65.

Particularly worth noting is that those respondents who received information from their platform about health and safety hazards were more likely than others to believe that their work could lead to adverse health outcomes or accidents. Statistical analyses revealed significant associations between receiving information on work-related hazards and assessments of the work’s harmfulness to health (chi-square test: χ²(16, N = 450) = 200.4, p < 0.001), as well as subjective assessments of the likelihood of a work-related accident (χ²(16, N = 450) = 196.3, p < 0.001). Goodman and Kruskal’s gamma (γ) confirmed statistically significant associations between the receipt of information and assessments of both the harmfulness of work (γ = 0.3, p < 0.001) and the likelihood of a work-related accident (γ = 0.4, p < 0.001), although the strength of these associations was moderate.

Mental strain was mostly attributed to task monotony (45%), high intensity (38%), and a lack of support from the platform (35%). Stressful situations were less commonly reported (25%) (Figure 4).

This relatively positive assessment of working conditions may stem from favourable views regarding both the satisfaction derived from platform work and its cognitive and developmental aspects, all of which were rated positively by more than half of the respondents. Nearly 58% fully or somewhat agreed that their work brought them a high level of satisfaction, 67% agreed that they learned new things through platform work, and just over 50% stated that the platform provided the necessary training for their tasks.

5.4. Ratings of Selected Aspects of Working Conditions in Respondent Groups with Different Characteristics

To identify what respondent characteristics may influence variations in opinions about different aspects of their working conditions, a series of in-depth analyses were conducted, based on the survey data. These analyses revealed that the mode of platform work (online or on-location), the types of tasks performed, and the respondents’ age and gender did not significantly affect their assessments of their working conditions. However, the analyses did distinguish two distinct groups among digital platform workers based on their employment context: those for whom this work was a casual sideline and those who relied on it as their main source of income. These groups differ in how they assess their working conditions.

5.4.1. Assessment of Autonomy in Platform Work: Side vs. Primary Work

The perception of platform work as either a sideline or a primary source of income significantly influences how workers assess their autonomy in organizing their work, particularly regarding work hours, methods of execution, and income. This relationship is positive, indicating that those respondents who viewed platform work as only suitable as a sideline were significantly more likely to believe that platform work guaranteed them autonomy (

Table 3. Chi-square test results and the strength of association measures.

Such Work Can Only Be a Sideline → To What Extent Do You Agree with the Following Statements Regarding Your Work via the Platform:	Chi-Square Test (12, N = 450)	Goodman and Kruskal’s Measure of the Strength of the Relationship γ
I feel independent in this job.	91.8; p < 0.001 *	0.01; p = 0.9
I have control over when I start and finish work.	107.1; p < 0.001 *	0.24; p < 0.001 *
I have a say in what kind of work I do.	95.9; p < 0.001 *	0.21; p < 0.001 *
I have control over how and at what pace I work.	115.1; p < 0.001 *	0.16; p < 0.01 *
I have influence over how much I earn.	94.1; p < 0.001 *	0.2; p < 0.001 *
I find it easy to balance work and private life.	72.1; p < 0.001 *	0.15; p < 0.05 *

* statistically significant values.

).

The analysis revealed statistically significant differences between the variables, although the strength of these relationships was weak, as indicated by the low coefficient values (see Table 3). Nonetheless, the analysis of residuals and the positive values of the Goodman–Kruskal gamma coefficient (which is appropriate for ordinal data) confirmed a consistent, positive relationship across all analyzed questions. The homogeneity of these correlations indicates that the questions formed a reliable scale for measuring work autonomy. This conclusion is further supported by a high Cronbach’s alpha (0.84) and average factor loadings above 0.7, both exceeding the accepted thresholds for scale reliability.

As a result, a work autonomy index was constructed by summing up the responses to the six questions listed above.

5.4.2. Autonomy Index

The calculated autonomy index was positively oriented: higher values corresponded to greater perceived autonomy in work organization. The index showed a negative skewness and an average above-the-scale midpoint, indicating a tendency among respondents to report high autonomy.

To determine whether perceptions of work autonomy (as reflected by the index) vary according to preference for working hours, a one-way ANOVA was conducted. The analysis revealed a statistically significant relationship between the variables: F(4, 449) = 8.7, p < 0.001. This significance was confirmed by Welch’s and Brown–Forsythe’s tests, which were used due to variance inhomogeneity.

Post hoc comparisons using the Games–Howell test showed that not all group differences were significant (see Figure 5). Statistically significant differences were observed only between the two strongest agreement categories (p < 0.01) and between the most affirmative and neutral responses (p < 0.001). This may be attributed to the small number of negative responses and the non-linear pattern, as the “rather disagree” group still had a relatively high index score (Figure 5).

Despite this finding, contrast analysis confirmed the overall linearity of the relationship (p < 0.001).

These findings suggest that viewing platform work as strictly a sideline was associated with a higher perceived level of autonomy in organizing one’s work. The relationship was rather positive and linear, with a medium effect size (eta-squared = 0.073), placing it within the zone of desirable effects.

5.4.3. Health and Safety Ratings of Platform Work According to Preferences for Casual or Permanent Employment

The analysis revealed that attitudes toward the preferred nature of platform work (specifically, whether it was viewed as suitable only for side employment) significantly influence subjective safety ratings. To explore this relationship, a job safety rating index was calculated, based on their responses to the following three statements:

-

My health may deteriorate if I continue this job for a longer period.

-

I can easily have an accident in this job.

-

I will be able to perform this job until I am 65 years old.

The index was positively oriented, meaning that higher values indicated a higher perceived level of job safety. A comparison of index scores across responses to the question about whether platform work should be only a sideline showed that individuals who supported this view rated job safety significantly lower. Conversely, those who disagreed reported higher safety ratings.

A one-way analysis of variance (ANOVA) confirmed a statistically significant relationship between the respondents’ views on the nature of platform work and the safety index: F(4, 449) = 5.9; p < 0.001. This result was also confirmed by Welch’s and Brown–Forsythe’s robustness tests (p < 0.001), which were used due to the violation of the homogeneity of variance assumption. The effect size, measured by eta-squared, was 0.05, indicating a moderate association. Contrast analysis also revealed a significant linear trend (p < 0.005).

These findings provide strong evidence that workers who consider platform work their primary source of income and full-time occupation perceive significantly higher levels of job safety than those who regard it as merely a side activity (see Figure 6).

An in-depth analysis using post hoc comparisons with the Games–Howell test showed that not all group differences reached statistical significance. Significant differences were observed between the most negative response and both the neutral and positive responses, as well as between the neutral and most positive responses (p < 0.005). Specifically, index values for the positive responses were slightly higher than for the neutral ones (see Figure 6), suggesting that the relationship may not be strictly linear, despite the linear trend confirmed through contrast analysis.

These results point to the potential presence of a curvilinear relationship and raise the possibility of an unmeasured moderating variable, such as the type of platform work. This may be especially relevant among respondents who believe that platform work should be limited to side activities. To explore this further, a subgroup interaction analysis was conducted to examine the differences in response patterns by type of platform work.

Further analysis incorporating the type of platform work provided only partial support for the hypothesis of a curvilinear relationship. The findings revealed that online platform workers who strongly agreed that platform work should be performed solely as a side activity rated their job safety higher than on-site platform workers who held the same view. This subgroup exhibited the largest difference in the job safety index (see Figure 7). Conversely, online platform workers who strongly disagreed with the statement rated their job safety lower than their on-site counterparts with similar views.

However, a multivariate analysis of variance (UNIANOVA) did not find a statistically significant interaction between job type and a preference for side work: F(4, 449) = 0.7; p = 0.6. This outcome may be due to the sample composition and the relatively small number of online-only workers.

6. Discussion

The results of this study provide a comprehensive overview of the experiences, motivations, and perceptions of individuals engaged in platform-based work, particularly in relation to their working conditions. The findings reveal a complex landscape in which flexibility and autonomy coexist with precarity and limited worker protection.

A key insight is the strong emphasis that respondents place on autonomy, especially the ability to control their working hours and the manner in which tasks are performed. This aligns with broader research on the gig economy, which consistently identifies flexibility as a primary motivation for engaging in platform work [19]. The COLLEEM survey conducted by the European Commission [11] supports this view, highlighting flexibility and autonomy as among the most frequently cited reasons for participating in platform work. Similarly, the EIGE panel study on platform work and gender equality found that time flexibility is a key driver of participation, particularly among women who are balancing paid work with caregiving responsibilities [12,18].

However, while many respondents report a sense of independence, both the current findings and previous studies [11,12,18,39] suggest that this autonomy is often conditional. It may be constrained by factors such as the availability of tasks, algorithmic management, and client expectations. This reflects the paradox of “controlled autonomy,” in which workers appear to have freedom but operate within set parameters defined by platforms or market forces. According to EIGE, this apparent flexibility often comes at the cost of intensified working, irregular hours, and a lack of access to social protection, particularly for those who depend on platform work as their main source of income.

Regarding occupational health and safety, most respondents do not report serious concerns. However, a significant minority (around one-quarter) perceive their work environment as potentially harmful to their health or report difficult working conditions. This finding resonates with previous research showing that occupational safety in platform work is frequently overlooked, due to the informal and decentralized nature of their employment [17]. Notably, those who receive information about potential hazards are more likely to recognize risks, suggesting that awareness may heighten risk perception. Similar results were observed in the COLLEEM survey, in which participants generally rated the health risks of their work as low. Interestingly, those performing professional online services were more likely to identify their work as harmful, whereas those engaged in transport, delivery, or field-based services, despite often working in more hazardous environments, were less likely to do so. This may be linked to a lack of information or awareness about occupational risks in these sectors.

It is also worth noting that platform workers tend to express less concern about health risks than workers in other sectors. Only 27% of platform workers in the current study believed that their work could negatively impact their health, compared to 38% of respondents in the European Working Conditions Telephone Survey (EWCTS) 2021 [40]. However, this average likely conceals significant variation. COLLEEM found that workers who rely heavily on platform income report greater job insecurity, higher levels of stress, and more frequent mental health challenges.

The analysis also underscores the finding that the perception of platform work as supplementary rather than primary employment significantly shapes how workers assess their experiences. Respondents who treat platform work as a side activity report higher levels of autonomy and satisfaction—likely because they are less financially dependent and have greater flexibility in choosing tasks. In contrast, those who rely on platform work as their main source of income tend to be more critical, especially regarding working conditions, safety, and income predictability. These patterns are echoed in EIGE’s findings, which emphasize the importance of socio-economic status, caregiving responsibilities, and the degree of employment dependency in shaping workers’ experiences.

7. Summary

This study explores the motivations, autonomy, and health-related experiences of platform workers in Poland, based on a survey of 450 individuals engaged in both online and on-location platform work. The findings reveal that autonomy, particularly in managing time and tasks, is a key motivation, with 74% of respondents reporting a sense of independence. Workers cite the ability to choose their working hours (49%) and control their work pace (37%) as primary incentives. However, the autonomy of platform work is often conditional, shaped by external constraints such as work availability and client preferences. The study shows that workers relying on platform work as their primary income source assess their autonomy as lower than those who treat it as supplementary. These results underscore the diversity of platform work experiences and the need for differentiated policy responses.

Perceptions of health and safety risks were mixed. Most respondents did not view their work as harmful, but around one-quarter reported poor conditions or health concerns. Notably, workers who had been informed about safety risks by the platform were more likely to acknowledge potential health hazards, highlighting the role of awareness. Interestingly, workers who considered platform work as their primary source of income and full-time occupation rated job safety significantly higher than those who viewed it merely as a sideline.

The presented study highlights the importance of understanding platform work not as a uniform phenomenon but as a spectrum of experiences that is influenced by worker motivations and socio-demographic factors.

While this study provides valuable insights into the working conditions of platform workers in Poland, several limitations must be acknowledged. Although the sample was designed to be representative of the broader population of platform workers in Poland, it relied on self-reported data and voluntary participation, which introduced the risk of self-selection bias. Workers with particularly positive or negative experiences may have been more likely to respond, potentially skewing the results. The next limitation is that while the survey included a broad set of indicators on material and psychosocial working conditions, it did not capture the specific algorithms, digital tools, or platform management practices that shape workers’ autonomy and labor dynamics. Further qualitative research, including interviews or ethnographic studies, could help uncover these mechanisms more precisely. Additionally, although some socioeconomic factors were analyzed, the study did not explore intersectional dimensions, such as migration status, which may significantly influence workers’ experiences. These aspects warrant deeper investigation to better understand the inequalities within platform work.

Future research should prioritize longitudinal and comparative studies across countries and regions to assess both the temporal trends and contextual differences in platform work. Moreover, a mixed-methods approach, combining survey data with in-depth interviews or platform data analysis, would provide a richer and more nuanced picture of how algorithmic management, client behavior, and policy environments influence working conditions. Future research should also aim to evaluate the effectiveness of the emerging legal frameworks and social protections tailored to platform workers.