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Digital Work in Eastern Europe:

Overview of Trends, Outcomes, and Policy Responses

Mariya Aleksynska

# Abstract

This paper documents the emergence and growth of digital labour markets in Eastern Europe. It shows that the development of two types of digital work – online work through online labour platforms and offline work mediated by mobile apps – have a different history, root causes and dynamics. While both are enabled by digital technologies, each attracts a different worker profile and results in different outcomes for workers. The paper also reviews policy responses to digital work in three areas: bringing digital work under the scope of existing regulations; ensuring fair competition with workers in traditional forms of employment; and improving formalization and better tax compliance of digital workers. It concludes by discussing how low scope for organizing digital workers, poor law enforcement and proliferation of new modes of digital work remain key obstacles for effective regulation.

Key words: digital work, online labour markets, gig economy, labour platforms, work via apps.
Regional coverage: Eastern Europe, South-Eastern Europe, Central Asia.

# Introduction

The past two decades have been marked by the emergence of digital work. This includes online work through online labour platforms that allow remote delivery of electronically transmittable services, and also offline on-demand work that is mediated by online platforms and mobile apps (De Stefano, 2015; Codagnone et al. 2016; ILO, 2016). Both types of work have been spreading to numerous sectors and occupations and gaining prominence in all parts of the world. The use of online platform work alone is estimated to have grown by a quarter between 2016 and 2018 (Kassi and Lehdonvirta, 2018; OLI 2019).

Not all parts of the world have been marked by the phenomenon to the same extent, however. There are clear champions in digital work. In what concerns online work through online labour platforms, which connect workers with clients posting tasks from all over the world, clear leaders of work supply are the USA, India, and the Philippines. Those are closely followed by Eastern Europe and Russia. In 2013-2017, Ukraine and Russia occupied the fourth and the fifth place in the world, respectively, in terms of the amount of financial flows and the number of tasks executed on online platforms (Graham et al., 2017; Forbes Ukraine, 2015; OLI index, described in Kassi and Lehdonvirta, 2018). Two other Eastern European countries, Serbia and Macedonia, were ranked in 2018 among the leading countries, whether in Europe or in the world, by the percentage of digital workforce relative to the total country's population and the total workforce (AnalyticsHelp, 2018). Serbia and Romania were disputing this championship in 2013 (Kuek et al., 2015). In what concerns offline work that is mediated by online platforms and apps, several Eastern European countries feature greater than the European average share of such digital workers (EU, 2018).

This paper documents the emergence and the growth of the digital labour markets in Eastern Europe over the period of the past two decades. It draws the portraits of digital workers, overviews their working conditions, and discusses how they are shaped by business models of online platforms and apps. It also reviews regulatory response to regulate digital economy in the region.

The regional focus of the paper is not accidental. It allows placing the emerging digital work phenomenon into the context of broader labour market developments, in order to better understand why digital work was embraced so widely in the region, and also to better understand the challenges and particularities of its regulation. By doing so, the paper explains why the uptake of digital technologies for searching and accessing work was much more natural in some parts of Eastern Europe than in other countries, and especially than in the rest of Europe. At the same time, it also shows why collective and legal responses have been somewhat limited to date, especially in the area of labour market regulations.

Several main findings are reported. First, development of the two types of work – online work through online labour platforms and offline work mediated by online platforms and mobile apps – has been following different paths. Online work through online platforms has a longer history in the majority of countries, dating back to the early 2000-es in some. Initially, its development was mainly led by “freelancers” finding their ways into the international markets, and also creating local platforms that fit the local culture and the local needs. Macro-task online platforms, rather than micro-task online platforms, seem to be more popular among the Eastern European “freelancers”, possibly because the latter do not offer sufficiently attractive pay.1

In contrast, work through apps emerged at least a decade later. In many instances (though not always), it was driven by the entry into the local markets of international companies, such as Uber for transportation, and most recently Glovo for delivery, and by the transposition of their existing business model into the local markets. This also translated into differences across countries: while in some, online work predominates, in others, it is work through apps that is more important.

Second, the paper shows that the two types of digital work, while both enabled by digital technologies, attract different worker profiles and result in very different outcomes for workers. On the one hand, the emergence of work through online labour platforms corresponded to the emergence of a new generation of workers, often with a new set of skills (high and IT-backed), a new entrepreneurial mindset and aspirations of flexibility, independence, creativity, and self-reliance. These workers, who often call themselves “digital freelancers”, often see work through online labour platforms as a modern way of work, as a means of transcending the boundaries of the local labour market and better applying their skills, and as a means of liberating themselves from “old-fashioned” employment relationships and dysfunctional welfare states. As shown in the paper, they have a generally high level of satisfaction with this work, and their working conditions are either comparable or better than those in the local offline economy. At the same time, this mode of work is also promulgated by the flexibility and cost-saving needs of enterprises. As this type of work generalizes and spreads into different sectors of activity, it may be expected that working conditions of online workers may worsen.

On the other hand, and in contrast, the emergence of work through mobile apps, and to some extent of online labour platforms oriented to the work exclusively in the local labour market,2 can be seen as a continuation of the precarisation and informalization trend. In part, this situation is due to the occupational specifics of such platforms and apps, as they operationalize in sectors that are already largely informal and precarious, including delivery, transportation, home repair, or domestic care work. But also, workers usually take up jobs through mobile apps and through local platforms because they are constrained to do so. Hence, they find themselves much more often in a situation of disguised (bogus) self-employment; with poorer working conditions and lower satisfaction with this work. Thus, it may be argued that the two types of digital work, at least at this initial stage, reinforced labour market inequalities in the region.

Third, the paper reveals that there are very strong local, regional, and international dimensions of the digital labour markets within Eastern Europe. Work through mobile apps is primarily local, as it is only mediated by digital technology but is performed offline. Yet, its international dimension is related to the fact that the owners of the apps are often foreign. This allows them to more easily practice the discourse of bringing in “modern” and “innovative” practises, while at the same time escape compliance with local regulations, either because they insist on being held to different standards, or because they disregard existing regulation, or because, in some instances, the pace of innovation has outpaced that of regulation. Depending on the scenario, the paper shows that there have been different policy responses to the emergence of work through the apps.

Work through online labour platforms, in contrast, exists on all three levels, connecting workers with clients on the local (national), regional, and international online markets.

The national online market seems to be strongly affected by the population size of the local offline labour market. For example, Russia and Ukraine are the countries with the largest population size in the region, they are also the ones that have the highest number and diversity of local online platforms. Poland, while featuring a relatively low share of online workers in relative terms, also has a substantial number of platforms developed to serve its national market, partly owing this to its national population size. In contrast, other countries of the region, especially those with small absolute population size, rarely boast a presence of national online platforms, even if some have relatively high shares of online workers.

The regional dimension, in turn, is shaped in a very important way by cultural and linguistic aspects. The Russian language, which is spoken in several countries of the region, largely mediates this regional dimension. In fact, this regional dimension has been largely disregarded in previous papers that measure work of Eastern Europeans exclusively on English-speaking international platforms. The paper thus shows that the real size of the digital online labour market of Eastern Europe and Russia is considerably larger than reported earlier.

Lastly, the paper shows that, despite this multi-level geography of digital work, policy responses to digital work so far were made mainly at the national level. The vast majority of policy responses also concerned work through mobile apps and not online work. Responses through labour laws have been modest at best, in a large part because of poor culture of unionisation and difficulties of organizing digital workers. Most of the responses to work through apps in fact pertained to the domain of ministries other than labour. They concerned bringing digital work under the scope of existing regulations; ensuring fair competition with workers in traditional forms of employment; improving formalization and better tax compliance of digital workers. In some instances, those policies had an effect of improving working conditions of digital workers. Yet, poor law enforcement, and the swift proliferation of new inventive modes of digital work remain key obstacles for effective regulation.

# Regional specifics of online work

In order to understand the development of digital work in Eastern European countries, it is important to place it into the wider socio-economic developments of the region.

Indeed, labour market has been historically quite different in Eastern Europe from the rest of the world. National labour markets within the region share several common features, distinguishing them from other countries. Those common features are mainly related to the transition from planned to market economy. They include rapid economic restructuring, sizeable worker displacement (Lehman et al., 2012) and working poverty (Bruck et al., 2010) throughout the 1990-es - 2010-es. These problems still persist today for some worker categories, such as notably elder workers. They have also profoundly marked work aspirations of the new generations. General regional problems also include misalignment of the education systems with labor market needs, skill mismatches, including mainly overeducation (Kupets, 2016), high and persisting informal employment 3 (Akay and Khamis, 2012; Lehman, 2015; Lehman and Pignatti, 2018, ILO, 2018), deteriorated image of trade unions and collective bargaining which is seen as a legacy of the communist past (Crowley, 2004 ; Ost, 2009 ; Kallaste and Woolfson, 2009). It is also in this context that new forms of employment, including agency work and dependent employment through services contracts, have sparked in the post-global recession period, making some countries of the region world champions of non-standard work generally (ILO, 2016). In this light, the uptake of digital technologies for searching and accessing work was much more natural in this region than elsewhere, and especially than in the rest of Europe.

At the same time, Eastern European countries are also quite heterogeneous. This heterogeneity explains, at least in part, why the uptake of online platform work and work through mobile apps has been uneven.

First, countries differ substantially in their population size, and hence in the sheer number of workers and clients in their internal labour markets. As will be shown further, it is indeed the largest countries, such as Russia and Ukraine, and to a certain extent Poland, that have most aggressively seized digital labour opportunities. In part, this happened because digital platforms allowed serving the large local market, as manifested by the number of local digital labour platforms. They also alleviated some of the unemployment pressures on the national labour markets, as manifested by the amount of work done by workers of these countries with foreign clients on international labour platforms. In addition, many international platforms function in English. Some of them entered into the national markets by proposing their national-language versions. This, however, again happened primarily in countries with large populations, because such entry paid off quicker in larger markets.

Second, countries differ in the level of their economic development and political stability. Several Eastern Europe countries are now part of the European Union (Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia). Even if progress is still to be made in many areas, many of their labour laws and enforcement practices have been reformed over the past two decades, often in order to meet the EU legal requirements. Social security systems have also been reformed and rendered more sustainable and inclusive in several countries. One of such examples is Romania, in which social security system was reformed in 2018 with the main objective of fighting undeclared work by reducing incentives for employers to use civil contracts instead of labour contracts (Roşioru, 2019). Moreover, EU-level rulings and regulations of digital work became important sources of law for the Eastern European EU-member states. Examples of this include European Court of Justice 2017 ruling on the status of some applications, such as Uber (Judgment in Case C-434/15), which was used in the national court rulings in Slovakia. Lastly, Eastern European EU member states enjoy a relatively higher economic and political stability as compared to their neighbours. As a result, even if digital work developed there, it was not as over-board, and mainly concerned the already precarious sectors. Policy responses were in many instances also swifter.

In contrast, countries such as Ukraine or Moldova, continue operating with rather dysfunctional social security systems (ex.: ILO, 2019), general lack of trust in the state-provided social support, insufficient or inadequate labour regulation, and poor enforcement. There is also more of economic and political instability in some of these countries, pushing their workers to secure their employment and obtain savings through various means, including digital work. This has meant that digital work was more omnipresent, touching a broader range of skills and sectors, even those that traditionally are less precarious.

Eastern European countries also differ in their incomes per capita. Six countries (the Baltic states – Estonia, Latvia, Lithuania, Czech Republic, Slovakia and Slovenia) are in fact now considered as “advanced economies” (IMF, 2019). In poorer and more unequal countries, working for foreign clients is more attractive as it often offers higher earnings as compared to the local market. In richer and more equal countries, earnings in the local economy though traditional employment, coupled with more solid social security protections, remain sufficiently attractive to keep workers in these traditional modes of work.

Finally, countries differ in the rate of Internet penetration and Internet usage (ITU, 2019), and the general level of digital skills of their populations. For example, in Europe, the proportion of the population with digital skills is the lowest in Bosnia and Herzegovina; it is the highest in Slovakia, Hungary, and Estonia (ibid). The latter are also the countries in which digital work gained more prominence.

As a result, several Eastern European countries witnessed a real surge in digital work, while others have not. Digital work also took different proportions and different shape: in some countries, online work flourished at national, regional, and international dimensions; in others, only international dimension of online work was strongly present; yet in others, it is rather work through apps that gained popularity. If policy responses to digital work varied, many countries of the region faced similar challenges in their enforcement and often looked at the neighbouring examples of successful policy implementation.

# Work through online labour platforms

## 2.1 Extent of the phenomenon and general regional trends

There is no unified statistics measuring the extent of work through online labour platforms. In its absence, researchers rely on a range of survey data and various estimates of registered users of platforms, financial flows, and performed tasks, as reported by the platforms. Table 2.1 reviews existing estimates. It shows that Ukraine and the Russian Federation systematically ranked first in Eastern Europe in terms of the financial flows, number of executed tasks on online platforms, and number of “digital freelancers” over the 2013-2018 period. Serbia and Macedonia were ranked first in the world by the percentage of digital workforce relative to the total country's population and the total workforce.

Table 2.1 Ranking of countries in terms of employment in online labour markets

OLI, 2019

Kuek et al., 2015
(data as of 2013)

Graham, 2015
(data as of 2013)

AnalyticsHelp, 2018

Absolute number
of workers

Relative to
population size

Absolute number
of workers

Absolute number
of workers

Relative to
population size

7 Russian Federation

1 Serbia

4 Ukraine

7 Ukraine: 53529

1 Serbia

9 Ukraine

5 Russian Federation

8 Russian Federation: 44534

2 Macedonia

11 Serbia

9 Poland

11 Serbia: 24605

4 Armenia

11 Belarus

16 Romania: 16731

6 Montenegro

7 Bosnia and Herzegovina

Source: Own compilation based on the data reported in these sources. OLI, 2019: data from 5 leading English-Speaking platforms; Graham et al., 2015: data from 1 English-speaking platform; Kuek et al., 2015 and AnalyticsHelp, 2018: number of platforms not indicated; English-speaking platforms only.

Note: The information refers only to online work through online labour platforms.

One important feature of online labour markets is that they do not have geographical boundaries. Yet, cultural and linguistic boundaries seem to be very important. In fact, the existing analogue cultural differences translate into differences in the types and the functioning of digital labour markets. As a result, workers in the region access three types of platforms and markets: national (local), regional (strongly shaped by common language, such as Russian or Serbian), and international (mainly English-speaking).

These three geographical dimensions of online work are depicted in Figure 2.1, which takes the viewpoint of a country of origin of online workers, such as Ukraine or Belarus. It shows the complexity of online work in the sense that the geographical location of a platform, a client, and a worker, do not necessarily coincide. In this figure, the thickness of each arrow approximates the workflow (number of tasks or financial flow). However, to the best of our knowledge, no data exists to estimate precisely the amount of these flows. Figure 2.2 depicts also the three geographical dimensions of online work from a viewpoint of a platform.

Both figures show that the national digital labour markets are specific to a country and are mainly oriented towards satisfying national work demands. The national (local) dimension is mediated mainly by locally-based platforms, operating in local languages, and matching locally-based clients and workers. In addition, it is mediated by platforms based outside the country, but which also match locally-based clients and worker.

Figure 2.1 Local, Regional, and International Dimensions of Online Work. Viewpoint of a Country of Origin of Freelancers

Figure 2.2 Local, Regional, and International Dimensions of Online Work. Viewpoint of a Regional Platform

The regional dimension of digital work and of digital labour markets is mediated primarily by a common language, spoken in several countries of the region. In the former Soviet Union countries, such language is Russian. It is still spoken by large shares of workers. This market is primarily driven by Russian-speaking platforms located in the region, mainly in Russia and in Ukraine. These platforms match workers and clients within the region, even though, technically, workers or clients may be located anywhere in the world. According to some estimates, about two-thirds of all Russian-language freelancers come from the Russian Federation, while others are mainly from Ukraine, Belarus, Kazakhstan, and Moldova (Strebkov, Shevchuk, Spirina, 2015). Workers from over 30 countries are systematically found on Russian-speaking online labour platforms (Shevchuk and Strebkov, 2015), and some of them may be from Russian-speaking diaspora. Similarly, Serbian language mediates the regional dimension of online work in the Balkans, though evidence on this is much scarcer than on the Russian language. The regional dimension of online work would only be available to workers from those countries, in which the regional language is widely present. For this reason, the regional dimension of online work is almost inexistent in countries such as Hungary, Poland, or the Czech Republic.

Finally, the international dimension of digital work is defined primarily by the English language. International platforms are hosted mainly outside the region, with American- British- and Australian-based platforms being the largest. Some international platforms now have interfaces in local languages; still, majority of tasks on them are posted in English and other non-local languages. Clients are located all over the world, and are matched with locally-based workers.

In addition to the geographical dimensions, platforms differ in their specialization. Some platforms, such as international www.Upwork.com, can be considered as a platform of a general profile, in the sense that tasks in any field of specialization can be posted there and workers with any technical profile can sign up. There are also platforms that are specialized in a specific field of activity. For example, international www.translatorscafe.com is specialized in translations. In order to work on this platform, workers have to prove their formal credentials, education and experience before being admitted to the platform. Both general-type and specialized platforms exist on the international and regional levels. They are somewhat scarcer on the national level (except in Russia). However, as online work spreads into various sectors, they start appearing at the national level, too.

There is no systematic statistical evidence on the difference in tasks, tasks complexity, and skill composition of workers across these different types of platforms. Workers’ sorting across platforms depends on many factors, including not only their level of technical skill, but also their language skills (primarily English for international platforms; primarily Russian for regional platforms). In addition, the degree of their technical skill transferability matters. Some of the technical skills will be more easily transferable than others. Hence, for example, workers with easily transferable IT skills will be more often found on international platforms, both general and specialized. In contrast, workers with less transferable skills, such as in national legal practice, will be more often found on national platforms. Moreover, workers may not necessarily want, or be able, to apply their existing technical skills online. Indeed, there is strong evidence from many surveys that both horizontal and vertical skill mismatches are important on online platforms, particularly for women (Berg et al., 2018; Shevchuk, Strebkov, Davis, 2015).

Some evidence from qualitative surveys (ex.: Aleksynska, Bastrakova, Kharchenko, 2018), and from reading various freelancers’ blogs, indicates aspirations of workers with specific technical skills regarding platforms on which they wish to work. These aspirations result in a certain sorting of workers across different platforms, depicted in Figure 2.3. For example, workers in an occupation with fully-transferable skills, having most proficient level, will target specialized international platforms, where they can be matched with international clients offering most challenging tasks and the best pay (best return to their skill). In contrast, workers with poorly transferable poorly-developed skills will self-select mainly into national platforms of generalized type. They may also access regional and international platforms of general type, for simple tasks that do not match their field of specialization; it is for them that the extent of skill mismatch will be the greatest. Anecdotal evidence suggests that international specialized platforms are indeed the ones that offer the best pay. Regional platforms typically offer better pay than national platforms, but lower pay than international platforms, for similar types of tasks. Some workers “build their career” by first “trying and testing” national general-type platforms before moving to “more serious” platforms. Systematic evidence, however, about these transitions, remains limited. Moreover, such career strategies are jeopardized by the fact that the reputation and experience built on one platform is not transferable to another.

Figure 2.3 Schematic representation of workers’ aspirations and sorting by tasks, skills, and platforms

transferability across national borders

Examples of
occupations /

Worker’s technical skill in this domain

Geography
of the platforms targeted by a worker with this skill

Content type
of the platform
targeted by a worker with this skill

Type of skill
requested by the
client on this type of platform

Fully transferable

IT, design, work with photo and video

Proficient

International

Specialized

proficient

Regional

Specialized

proficient

International

General

Any

Regional

General

Any

Specialized

proficient

National

General

Any

Specialized, if they exist

proficient

Beginner

Regional

General

Beginner to
intermediate

National

General

Somewhat transferable

Work with texts:
content writing,
rewriting, copywriting

Proficient

International

Specialized

proficient

Regional

Specialized

National

Specialized

Intermediate to

Regional

General

Specialized

National

General

Specialized, if they exist

Beginner

Regional

General

Beginner to
intermediate

National

General

Poorly transferable

Legal services,
marketing, accounting

Regional

Specialized

proficient

National

Specialized

Intermediate to

Regional

General

National

Specialized, if they exist

General

Beginner

Regional

General

Beginner to
intermediate

National

General

Source: Own compilation based on the reviewed literature and on the review of selected platforms.

Note: Examples of general-type platforms: on the international level: www.Upwork.com; on the regional level: www.fl.ru; on the national level: www.Freelanceria.pl. Examples of specialized-type platforms: on the international level: www.translatorscafe.com, www.proZ.com; on the regional level: www.tranzilla.ru; www.Etxt.ru; on the national level: https://seoware.ua/.

If there is one field of online work for which there is some statistical evidence about its extent on the international level, it is the field of IT. This field is characterized by nearly perfect skill transferability across borders, and also by high technical skill requirements. In this field, Ukraine and Russia again have been clear champions in Europe throughout the past decade. In addition, other countries, particularly Serbia, Romania, and Poland, witnessed significant presence of IT online workers.

Based on a review of over 1,5 million projects (tasks) and over 160.000 profiles of online workers specialized in performing IT tasks for foreign clients on the largest general-type platforms (oDesk andElance, which later merged to become Upwork, Freelancer, and others), it was estimated that about a third of all IT tasks outsourced through digital platforms to Eastern Europe was performed by Ukrainians in 2013 (Topsdev, 2015). The share of the Ukrainian freelancers in the Eastern European IT market declined in 2014-2015, only to grow again in 2016 and reach 34% (Topsdev, 2017). Ukrainian IT freelancers were closely followed by the Russian freelancers, whose share in the Eastern European IT market reached 28% in 2016 (ibid). Other notable market players are Romania and Serbia. They seem to have entered the digital labour market somewhat later as compared to Ukraine and Russia. This is manifested by the record growth of their market share in IT freelance of 32% and 79% respectively in 2013-2014, albeit from a very low initial level (Topsdev, 2015). Moreover, this growth has slowed down to 3% and 21% respectively by 2016 (Topsdev, 2017). Another country that has witnessed a sizeable increase in its IT freelance is Belarus: its share grew by 69% in 2015, though also from a very low level (Topsdev, 2017). In 2015, Belarus occupied the third place in Eastern Europe in terms of the financial amount of orders (ibid). Figure 2.4 shows top 10 countries in Eastern Europe in terms of market share of IT tasks performed by workers through online platforms in 216.

Figure 2.4 Market share of IT tasks performed through online platforms, in per cent. Top ten countries of Eastern Europe
in 2016

Source: Topsdev, 2017.

Note: 20 countries of Eastern Europe were considered for this study: Albania, Belarus, Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Macedonia, Moldova, Montenegro, Poland, Romania, Russian Federation, Serbia, Slovakia, Slovenia, Ukraine.

The largest share of all IT tasks comes from the USA (55% in 2016: Topsdev, 2017). This was followed by the United Kingdom (10%), Australia (7%), and Canada (5%). Countries such as Germany, Israel, Sweden, the Netherlands, France, and Denmark are also present, but their market shares are less than 5% in all tasks outsourced to Eastern Europe through online platforms (ibid). The most popular IT skill was html+css (possessed by 10% of freelancers). This was followed by php (6%) and javascript (4,5%).

### 2.1.1 Online work in Ukraine

The development of the Ukrainian online work started in the mid-2000-es. It immediately featured a regional and an international dimension, while the development of the local freelance market took off somewhat later. The very first digital labour platform of the Russian-speaking region was a Ukrainian-based Russian-language portal Weblancer.net, founded in 2003 (Strebkov, Shevchuk, Spirina, 2015). Initially oriented towards IT sector, it exists until now and is considered to be one of the most serious and influential platforms, counting over one million users in 2019.4 The foundation of this platform was followed by the foundation of Freelancehunt.com in 2005 - a Ukrainian-based platform which, by 2019, was considered as one of the most serious players on both the local and the regional market.

But the real take-off of the Ukrainian freelancing started with the global economic recession of 2008, and sky rocketed since 2013 (Aleksynska, Bastrakova, Kharchenko, 2018). This rise is primarily explained by the deepest political changes in the country since its independence: the Revolution of Maidan of the 2013-2014 that resulted in the ousting of the previous president, the outbreak of a military crisis in the Eastern part of the country in the early 2014, and the annexation of Crimea. These political events exacerbated an already difficult economic and labour market situation, marked by high informality and poor law enforcement, low confidence in the functioning of social security systems and other public services. As a result, workers started massively looking for new employment opportunities, including online. This process was accompanied by a surge in the development of various online platforms of general type and also of platforms specialized in specific sectors and activities. Some evidence also suggests that the conflict with Russia led to the outflow of Ukrainian freelancers from Russian-based platforms. Those either turned towards international online markets, or towards Ukrainian-based platforms that have been witnessing a significant expansion ever since.

According to a survey led by a large human resources company, by 2016, nearly every fifth Ukrainian white-collar office worker had tried digital work and would like to switch to it fully; 48% view it as additional source of income (HH.ua, 2016). IT sector alone, one of the largest sectors of digital freelance, grew at a rate of 27% in Ukraine in 2017 (DOU.ua, 2018).

As of 2018, Ukrainians were accessing digital labour market through over forty platforms (Aleksynska, Bastrakova, Kharchenko, 2018), including international, regional (mainly Russian-speaking), and local. Both the absolute and relative number of Ukrainians has been growing on all types of platforms. As of March 2018, there were at least half a million registered workers from Ukraine on 6 largest platforms through which Ukrainians access digital work. This represents roughly 3% of the employed population. For example, international Upwork.com counted nearly 180.000 Ukrainians by 2017 (AIN, 2017). Ukrainian-based Freelancehunt.com counted over 260.000 registered freelancers and over 100.000 clients in 2019 (information from the site), recording a growth of over 25% in 2016-2017 (ITC.ua, 2017).5 Not only this platform became the leader on the local market, but also created a Russian-language version oriented to the Russian regional market. New platforms, oriented almost exclusively to the local market, also emerged. A prominent example is Kabanchik.ua, launched in 2012, and featuring over 50.000 Ukrainian workers and 200.000 clients by 2018 (information from the site).

### 2.1.2 Online work in Russia

Work on online platforms in Russia has a very strong national and regional dimensions. Its development kicked off somewhat later as compared to the developed countries. Researchers explain this lag by several factors, which include a low entrepreneurial culture in the post-Soviet space, low use of technologies by the general labour force, and a low initial penetration rate of the Internet (Shevchuk and Strebkov, 2012a, Strebkov, Shevchuk, Spirina, 2015). In the early 2000-es, when global online marketplaces for digital freelancers already existed, only around 2% of the Russian population had access to the Internet. This gap, however, has been closing rapidly: by 2012, there were already over 60 million Internet users in Russia, making it one of the largest Internet markets in Europe (ibid). In addition, it was also estimated that over 87 million people from the former Soviet republics and other countries were actively using the Russian-speaking Internet (Runet). As such, Runet overtook German-speaking and French-speaking Internet in terms of the number of users (ibid; Shevchuk and Strebkov, 2015).

Some of the first Russian-based Russian-speaking digital platforms appeared towards the turn of the millennium. Those early platforms copied Western examples and did not account for the specifics of the local labour relations. As a result, the initial local interest in them was mild (Strebkov, Shevchuk, Spirina, 2015). It was not until 2005 that the first serious Russian-based Russian-language platform FL.ru (originally Free-lance.ru), oriented towards the specifics of the Russian culture was created (Shevchuk and Strebkov, 2012a). By 2015, it became the largest Russian-speaking general profile platform of the region and also of the world, with over 1,6 million registered users (ibid). The foundation of this platform is considered to be the birth date of the “online freelancing” in the region, not only because it provided new mode of work and work opportunities, but also because the platform owners actively participated in the creation of a freelance culture. The platform is known to organize all-Russia conferences of freelancers; it created a Freelancer's Day; and regularly conducts information campaigns about the freelancers lifestyle (Strebkov, Shevchuk, Spirina, 2015).

Since 2005, the number of both platforms and freelancers in Russia exploded. A veritable take-off of the platform work took place in the 2005-2009 period with the development of several general profile and specialized platforms (ibid). It was further exacerbated by the global economic recession of 2008–2009, and a new economic recession of 2014. Currency devaluation made the Russian freelancers labour also cheaper as compared to other countries, making Russian freelancers more attractive also to foreign clients (ibid). By 2014, around 70 digital labour platforms operated in the Russian-speaking Internet. Six of them counted over 100,000 registered users. At the same time, around half of them had fewer than 5000 users, either because of a very narrow specialization, or because of a less than perfect survival rate (ibid). By 2019, at least one of them counted over 3 million active users (www.advego.ru: 3.250k in September 2019), and at least two counted over 1 million users (www.etxt.ru: 1.000k, www.fl.ru: +1.600k in September 2019). Also by 2019, some of the platforms operating in 2014 stopped functioning, while some new platforms also emerged.

Over the past two decades, the Russian digital labour market underwent significant changes, as witnessed by platforms' diversification and sophistication. About a third of Russian-language platforms are of general type (any task can be posted on them). Two thirds are specialized in a specific professional field, such as only writing, only IT, only design. There are also platforms specializing in HR, marketing, finance, engineering and architecture (ibid; Shevchuk and Strebkov, 2015). Anecdotal evidence suggests that specialized platforms offer more sophisticated tasks and attract more advanced professionals as compared to general-type platforms.

Russian-language platforms also witnessed a growing share of Russian-speaking workers from outside of Russia. For example, the share of Ukrainian freelancers on FL.ru platform went up from 15% in 2009 to 26% in 2014. There has also been a growth of freelancers from Belarus, Kazakhstan, Moldova, the Central Asian countries (Uzbekistan, Kyrgyzstan, Tajikistan, Turkmenistan), Caucasus countries (Armenia, Azerbaijan, Georgia: they represented 0.6% at the latest count), and the Baltic States (Latvia, Lithuania, Estonia: 0.5%). There is a small share of Russian-speaking freelancers residing in the USA, Canada, Germany, Italy, Israel, Thailand and India (ibids).

### 2.1.3 Online work in other former Soviet Union countries

Systematic analytical overview of the digital work in other post-Soviet countries is scarce. It seems that the digital markets there developed with a lag, as compared to Russia and Ukraine. This lag is partly due to the general lag in the use of technologies and Internet penetration rate. The size of the population of other post-Soviet countries, and the share of professionals with digital skills is also lower as compared to Russia and Ukraine. This has meant that there was less scope for the development of purely local digital labour markets.

Digital online workers from other post-Soviet countries are often found on regional platforms serving the Russian-speaking market. Table 2.2 shows that there is a non-negligible presence of Belarussian, Moldovan, Kazakh and Armenian freelancers on Russian-speaking platforms based in Russia or in Ukraine. Other countries of former Soviet Union have only a small number of digital freelancers, at least on the two largest platforms examined here. This can either signify that digital freelance is not well developed in these countries yet, or that it is oriented towards other types of platforms (and possibly markets). Some local platforms exist, such as Belarussian-based Byelorussian-language platform Фрилансер.бел. However, the local digital market also seems to develop in many ways thanks to the local-market versions of Ukrainian and Russian platforms (example, Kabanchik.ua created a Byelorussian version Kabanchik.by).

Table 2.2 Country of residence of online workers of two largest regional Russian-speaking platforms

One of the largest Ukrainian-based
platform Freelancehunt.com

One of the largest Russian-based
platform FL.ru

Number of
freelancers, 2019

Percent of total,
2019

Estimated number
of freelancers, 2014

Percent of total,
2014

Eastern Europe, Former Soviet Union

Ukraine

262.994

62,74

390.000

26,00

Russian Federation

127.810

30,49

990.000

62,00

Belarus

10.637

2,54

66.000

4,40

Moldova

2.432

0,58

22.500

1,7

Caucausus, Former Soviet Union

Armenia

2.078

0,50

7.500

0,50

Azerbajdzhan

754

0,18

Georgia

456

0,11

Central Asia, Former Soviet Union

Kazakhstan

6.962

1,66

31.500

2,10

Uzbekistan

1.934

0,46

18.000

1,20

Kyrgyzstan

1.198

0,29

Turkmenistan

Baltic States, Former Soviet Union

Latvia

504

0,12

22.500

1,50

Lithuania

Estonia

Source: For Freelancerhunt.com: https://freelancehunt.com/freelancers (Official web statistics accessed August 2019); for FL.ru: Strebkov, Shevchuk, Spirina, 2015.

### 2.1.4 Online work in other Eastern European countries

There are several studies that attempt to estimate the extent of platform work in other Eastern European countries. Because of the methodological differences, such estimates vary substantially across studies. However, they all somewhat agree that the extent of platform work is no longer negligible in this region.

For example, according to a cross-country survey documented by Pesole et al. (2018), in 2017, the share of the adult population who has ever gained income through online platforms (whether online or offline), ranged from 9% in Lithuania to 6,7% in Hungary (Table 2.3). However, the share of those workers for whom this work represents the main activity remains substantially lower, and was estimated to be below 2% of adult population in the majority of countries (ibid).

The share of workers performing online work is higher than the share of workers performing offline work mediated by the platforms in Lithuania, Romania, Croatia, and Hungary; it is the highest in Romania. At the same time, in all surveyed countries, there is a small share of workers who work through online platforms of both types (ibid).

The cross-country surveys documented in Piasna and Drahokoupil (2019), find that the share of adult population who ever tried platform work is less than 2% in Poland, around 4% in Bulgaria and Latvia, and is slightly over 7% in Slovakia and Hungary. The share of adults who do platform work at least once a week is below 2% in all surveyed countries. These authors also find that there is an important share of individuals who generate income through other online activities, such as selling own possessions online (17% have done this at least once in their lives) or re-selling products (9%).

Table 2.3 Percentage of platform workers in selected Eastern European EU-member states, who ever gained income from online platform work

Country

Pesole et al. (2018)

Piasna and Drahokoupil (2019)

As percent of active internet
users (estimates), 2017

As percent of adult population (estimates), 2017

As percent of adult population (estimates), 2019

Lithuania

13,5

9,1

-

Romania

14,2

8,1

-

Croatia

12,1

8,1

-

Hungary

8,9

6,7

7,8

Slovakia

8,5

6,9

7,1

Poland

-

-

1,9

Latvia

-

-

4,0

Bulgaria

-

-

4,4

Source: Pesole et al. (2018), Piasna and Drahokoupil (2019)

Note: COLLEEM survey question, reported in Pesole et al. (2018) asks whether the respondent has ever gained income from different online sources, among which there are two corresponding to labour service platforms: "providing services via online platforms, where you and the client are matched digitally, payment is conducted digitally via the platform and the work is location-independent, web-based" and "providing services via online platforms, where you and the client are matched digitally, and the payment is conducted digitally via the platform, but work is performed on-location". Piasna and Drahokoupil (2019) asks whether the respondent has ever used “online platforms, which are internet websites or apps through workers can find short jobs or tasks, such as IT work, data entry, delivery, driving, personal services etc.”

National studies provide more nuanced pictures. For example, in Romania, “IT freelance”, oriented towards international markets, has a relatively long history, dating back to the mid-2000-es. It was sparked by the development of the IT industry generally, as the country ranked first in Europe and sixth in the world in its number of certified IT specialists (Roşioru, 2019; Grigoraș, Tănase, and Leonte, 2017). With over 64,000 IT specialists, the share of IT specialists in the Romanian labour market is higher than in other IT-leading countries, such as Russia (ibid). Moreover, the IT sector is considered to be the most dynamic, and receives wide government support. If the vast majority of IT specialists are wage employees, work through online labour platforms in this sector is nevertheless also a known phenomenon in the country. The post-crisis decade was marked by the generalization of online work. This included a better awareness of Romanians of international platforms, and a more general spread of online work, including through platforms oriented towards the national market. By 2019, Romanians worked through over twenty platforms, with at least four Romanian ones (Roşioru, 2019). The latter included both general and specialized platforms, such as the ones specializing in transcription, editing, and marketing.

In Poland, various national estimates of platform work vary from 6% 6 (Gumtree and DeLab, 2017) to 11 % 7 (Owczarek, 2018). The development of online work manifests itself by the presence of online platforms in Polish language, as well as of Polish versions of international platforms (Sienkiewicz, 2018). Platforms in Polish include general-type Freelanceria.pl, crowdsourcing-type platforms MillionYou.com and TakeTask.com, and specialized platforms such as Wpzlecenia.pl (for WordPress), and Napiszeprace.pl (writing student papers). Polish versions of international platforms include Freelancer.pl and Unicloud.pl.

In the Czech Republic, there were at least thirty platforms present by 2017. Those included Czech versions of international platforms, and also several nationally founded platforms oriented towards the local market (Veber, Krajčík, Hruška, 2016; National Training Fund, 2017).

In Bulgaria, around 23,000 online freelancers were enumerated on the main platforms in June 2015 (Yordanova and Kirov, 2017). By January 2018, this number has almost doubled. The most popular platforms were international www.guru.com and www.upwork.com.

## 2.2 Profiles of Eastern European workers on online labour platforms

The emergence of online work sparked interest in studying the profiles of digital workers by specialists from a variety of disciplines. Existing studies, whether qualitative or quantitative, allow to draw a relatively uniform portrait of Eastern European digital online workers.

This section is based principally on five large scale surveys of platform workers, conducted at the national level in Ukraine (Aleksynska, Bastrakova, Kharchenko, 2018), Serbia (Andjelkovic, Sapic, Skocajic, 2019), selected Eastern European EU-member states (Pesole et al., 2018 and Piasna and Drahokoupil, 2019), and on the largest regional platform in Russia (FL.ru: Shevchuk and Strebkov, 2015, 2018; Strebkov, Shevchuk, Spirina, 2015, 2016). The Russian survey has been conducted in four waves, allowing not only to have a snapshot of the workers’ profile, but also trace its evolution. Surveys’ findings are also summarized in Table 2.4.

All five surveys show that digital workers are generally young. On average, online workers are in their thirties, and younger than the average offline workers. They are also over-represented in in the 25-29 group (Serbia) and 18-26 group (Russia). Some additional evidence from Poland (Owczarek 2018) shows that Polish online workers are over-represented in the 18-24 group.

There is a relative gender parity in online work in Ukraine, Serbia, and Slovakia. Initially male-dominated, Russian freelancers workforce now almost reaches a gender parity: the share of women rose from 33% in 2009 to 46% in 2019. In contrast, in Croatia, there is just one woman for every three men working online.

Online digital workers in most of the Eastern Europe are generally high-skilled. The overwhelming share of Russian freelancers has at least some university education (83% in contrast to 30% of all Russian workers). The share of Russian freelancers with completed education has been growing, indicating professionalization of freelancing activities. Ten percent of freelancers have two university degrees, an MBA or a doctoral degree. Most frequently found areas of specialization are STEM degrees. In Ukraine, 73% of online workers have basic undergraduate degree or completed higher education, and 2% have a doctoral degree. The situation is similar in Serbia, Croatia, Romania, and Lithuania. There is also a higher share of workers with ISCED 5 and above level of education in EU Eastern European countries, as compared to the general population.

Initially overrepresented by the IT professionals, the pool of online workers is now much more diversified, and includes a whole range of occupations. Still, three types of occupations dominate the online freelance market: IT (including software and technolo¬gy development), working with texts (content writing, rewriting, translating, editing), and creative and multimedia industry (including design, work with photos and videos: ibids). There is a strong gender segregation in online occupations: in all countries, IT sector is strongly dominated by men, while working with texts is strongly dominated by women. This occupational segregation goes hand in hand with the market orientation: if IT freelance from Eastern Europe is known internationally, on the local and regional markets, it is work with texts and graphical design that presents the dominant sphere of activity. As a result, more women are found in the local markets, and more men are found in the international online market.

Table 2.4 Summary of findings from surveys of online workers, selected studies and countries

Country

Ukraine

Russian Federation

Serbia

Croatia, Hungary, Lithuania, Romania, Slovakia, and 9 Western European

Bulgaria, Hungary, Latvia, Poland, Slovakia*

Surveyed Period

2017

2009-2019 (4 waves)

2018

2017 – 2018 (2 waves)

2018-2019

Reference

Aleksynska, Bastrakova, Kharchenko, 2018

Shevchuk and Strebkov, 2015, 2018; 2019

Andjelkovic, Sapic, Skocajic, 2019

Pesole et al., 2018

Piasna and Drahokoupil, 2019

Sampling

Representative national quantitative survey (administered online); Face-to-face focus-groups for qualitative survey

Online survey on the largest national platform

Collection of open data on 5 international platforms; a quantitative survey; qualitative interviews.

Large-scale online survey, representative of internet users between 16 and 74 years of age

Face-to-face interviews, stratified random sampling of the entire adult population

Findings

Age

Average: 33 y.o. 2/3 of workers are below the age of 36.

In 2019: average age: 33 y.o. About 1/3 is aged 18-26. Average age increased between 2009 and 2019.

Over-represented in 25-29 group

Average for all countries : 34 y.o., which is 10 years less than offline workers. Age distribution skewed towards the young.

Average : 37,5 y.o., which is 4,3 less than other workers

Gender

52% men, 48% women. Gender segregation by tasks, ex.: IT is 88% male, translation is 74% female

Gender parity increases over time: 2009: 67% men versus 33% women; 2019: 54% men versus 46% women. Gender segregation by tasks, ex: IT is 78% male, work with texts is 71% female

Women are dominant in traditionally “female” sectors with lower pay (e.g. writing and translation).

Gender segregation by tasks: software development' is most male dominated services, 'translation' is mostly female dominated. More men have platform work as main occupation

Men are somewhat more likely than women to do platform work (among those doing platform work at least once a year, men represent 57 %)

Education

73% of online workers have basic undergraduate degree or complete higher education, and 2% have a doctoral degree

2019: At least some university education: 83% (and 70% completed), in contrast to 30% of all Russian workers. Education level of freelancers increased between 2009 and 2019.

The majority is highly educated

High education: over 50% of platform workers; vs 36,2 % of offline workers

No differences with other workers

Occupation / sector (most popular)

Work with texts (23%), IT (12%), filling in opinion polls and questionnaires (8%); sales, photo and video (6% each); collecting and processing information (5% each); design, translation and consulting (4% each).

In 2019: IT and web design (26 %); graphic design (35 %); photo, audio, video (14 %); work with texts and translation (29 %); business services (25 %); engineering (8 %).

Software and technolo­gy development (30%), writing and translation (29%), creative and multimedia industry (22%).

Croatia: sales, Slovakia : creative and clerical work; Hungary: creative sector, translation; Romania: microtasking and clerical work

Gender segregation by tasks: short tasks and click work is 59% female, creative and IT work is 57% male

Earnings

Online work is the only source of income for 25% of freelancers.

Average gross earnings for all freelancers: 260 USD per month ; which is slightly above the national average gross monthly wage.

2013: average gross earnings of freelancers, including online and offline work: 38.000 RUB per month (approx. 1000 USD). Average gross wages of offline workers: 29.800 RUB. Highest earnings are observed among “pure” onliners; earnings rose over the 2009-2019 period.

Online work is the only source of income for 1/3 of freelancers registered as self-entrepreneurs.

The average gross income for all freelancers is about 1,200 USD per month compared to average gross salary of 680 USD

40% of platform workers get less than 25% of their income via platforms, and a further 30% between 25 and 50%.

Online work is the only source of income for 19% of platform workers in Hungary, 5% in Bulgaria, 12% in Latvia, 3% in Slovakia, virtually 0 in Poland

Hours of work on the platforms

Paid and unpaid activities : average of 30h per week.

21% work for over 50 hours per week, 7% work in excess of 85 hours

Platform and non-platform work combined: 52 hours per week on average. 30% report working over 60 hours per week, most of them are self-employed. Highly atypical hours:

1/3 work less than 35 hours per week, but ½ work over 45 hours. 1/3 work every Sunday and public days off.

83% of digital workers work 40 hours a week or less

42% of platform workers work less than 10 hours a week, and three quarters less than 30 hours a week on the platforms

-

Status in employment

67% are employed offline, of which 32% are self-employed

Around 40% of freelancers are also wage employees, around 10% of freelancers are also employers. . The share of wage employees declined between 2009 and 2019; giving way to “pure” online freelancers who do not combine freelancing with other activities

54% are employed offline, with over a half being self-employed

75.7% are employed offline, with the vast majority being employees

Over 70% in paid work offline ; of which 18% are self-employed and 61% with full-time open-ended contract.

Informality

Over 75% are informal (not registered as self-employed, not paying taxes on online incomes)

Only about 12% of freelancers in 2014 had a written contract with clients (sign of formality)

About 2/3 remain in the shadow economy (not registered, not paying taxes on online incomes)

-

-

Source: Own compilation based on the reviewed studies.

Note : * - the paper provides findings for « internet workers », which is a broad category, including selling goods and renting services through the internet, and “platform
workers”, which is a narrower term and excludes such activities. Results here are given only for “platforms workers” as the most relevant comparison group.

Over two thirds of online workers in Ukraine, Russia, and Eastern European EU-member States have jobs in the offline economy. In Poland, 70/% of platform workers have another, main, job (Owczarek, 2018). Thus, the majority of online workers actually do this work to complement their income from other jobs. Usually quite a high share of online freelancers are self-employed in the offline labour market. In Russia, there has also been a growing share of freelancers for whom work through digital labour platforms represent the main source of income: their share increased from 42 to 53% between 2009 and 2014.

Approximately one third of Russian digital freelancers work for foreign clients. These findings are also verified by a joint Paypal - Netfluential survey of Russian freelancers (reported by Kommersant.ru, 2018), who estimate that 14% work for foreign clients exclusively. In Ukraine, 34% of freelancers work for Ukrainian clients, 13,4 % of online workers work for Russian-based clients, and 5% work for other Post-Soviet Russian-speaking clients. Others work for foreign clients (either exclusively or partly). Conversely, up to 26% of freelancers of the largest Russian-based platform were Ukrainian in 2014. This illustrates the national, regional, and international dimensions of online work.

Finally, most of the digital online workers live in large urban areas, especially in capital cities. Most of the Russian freelancers are located in Moscow and Saint-Petersburg, though their share has been steadily declining to give place to freelancers from other regions. This dynamics can partially be explained by better Internet access and access to technologies in the regions, and skill composition of the urban workforce. In case of IT freelancers specifically, 60% of them reside in 20 large cities of the region, ten of which are capital cities (Figure 2.5).

Figure 2.5 Market share of IT tasks performed through online platforms in Eastern Europe, in per cent, by city, 2016

Source: Topsdev, 2017.

Note: 20 countries of Eastern Europe were considered for this study: Albania, Belarus, Bosnia-Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Macedonia, Moldova, Montenegro, Poland, Romania, Russian Federation, Serbia, Slovakia, Slovenia, Ukraine.

## 2.3 Working conditions of Eastern European workers of online labour platforms

Unless stated otherwise, this section draws again on the results of large scale surveys of platform workers (Serbia: Andjelkovic, Sapic, Skocajic, 2019; selected Eastern European EU-member states: Pesole et al., 2018 and Piasna and Drahokoupil, 2019; Russia: Shevchuk and Strebkov, 2015, 2018, 2019; Strebkov, Shevchuk, Spirina, 2015, 2016; Ukraine: Aleksynska, Bastrakova, Kharchenko, 2018). Some of the findings are summarized in the remainder of Table 2.4.

### 2.3.1 Working hours and work-life balance

The average hours devoted to the online work usually do not exceed standard work-week hours. In the majority of cases, they fluctuate around 30 hours a week, reflecting the fact that for the majoirity of workers online freelance is a complementary activity. However, all studies with available information note an important dispersion, and even a polarization of working hours. For a small fraction of those workers for whom online freelance is their main activity, working hours can easily span over 60 hours a week. Many freelancers systematically work on week-ends and holidays. In Russia, half of on liners work over 45 hours, with one third stating that they work every Sunday and on public holidays, and one third stating that they work 6 days a week including on Saturdays. In Ukraine, employment of 6 or 7 days a week characterizes 26% of the respondents, with one seventh of the respondents working on every day of the week. Evidence from other European countries (Croatia, Hungary, Lithuania, Slovakia, Romania), suggests that, if the average hours devoted to online work are rather short, 12% of onliners, for whom this work represents the main activity, work over 60 hours a week.

In addition, online workers often report working on atypical hours, such as early in the morning, late in the evening, or at night. This happens for several reasons. For many, this is because day hours are occupied by either a regular employment, or by studying, or by family responsibilities. For some, this is also because they engaged into too many projects, or because they have clients located in other parts of the world and that require communication in different time-zone hours. Two-thirds of Russian online workers regularly work between 6pm and 12pm, and 30% work between 12pm and 3am. Similarly in Ukraine, 62% of online workers usually work from 6pm to 10pm, and 30% work between 10pm and 5am.

The situation with atypical hours of online workers is so striking in some countries that researchers even coined a term of “autonomy paradox” (Strebkov and Shevchuk, 2019). It consists in a scenario, in which online workers who are able to schedule their time in a flexible manner actually work disproportionately during the night. This has an adverse impact on their satisfaction with work–life balance and with life, and leads to an emotional exhaustion (ibid).

### 2.3.2 Earnings

Earnings from online work are the main motivators for uptaking these activities. The reviewed studies uniformly show that, in Eastern Europe, earnings from online work have so far been quite attractive, whether as a complementary, or as a main source of income. For example, in Russia, earnings of online freelancers from all activities are higher than the average earnings of Russian salaried workers using Internet for work. In Serbia, the average gross income of onliners is almost twice as high as the average gross salary in the country. In Ukraine, average gross online earnings (for an average 30h work-week) are above the gross minimum monthly wage in the country. In all countries, workers for whom online work represents the main source of income have the highest online earnings. These results explain why the majority of workers in these three countries report being satisfied with the online work.

The highest earnings are enjoyed by digital workers performing IT tasks. This is due to the technical skill requirements, but also due to the fact that the clients for this work are more often located abroad. Additional evidence suggests that those working exclusively for foreign clients earn, on average, 20% more than those working with local clients only (Kommersant.ru, 2018, Russia: Paypal - Netfluential survey).

The requested hourly rates for IT work are also among some of the most transparent and easy to track. This is because workers usually display their hourly rate in their profiles on international platforms through which the majority of such work is performed. The requested rate is not always the one that the worker will systematically receive. Clients may negotiate it, or propose a project-based type of pay. Nevertheless, on some platforms, such as Upwork.com, the displayed rate in the worker profile is quite a good approximation of what is actually received, as the latter would fluctuate around that number. A review of IT worker profiles on the major platforms (Topsdev, 2015) allowed obtaining average requested hourly rates by the workers’ country of origin (Figure 2.6). It also allowed obtaining paid hourly rates by the clients’ country of origin (Figure 2.7). These figures show that the highest average hourly rates were requested by Estonians and Montenegrins.

Hourly rates requested by Belarusians, Romanians, and Macedonians have declined between 2014 and 2016. This possibly reflected a very rapid take off of these markets in the same period. In other words, the supply of workers increased, but the amount of available work did not increase at the same pace. At the same time, there was an inflow of IT workers with heterogeneous skills, including with less specialized skills as compared to the first entrants into the market. This further depressed the average requested rate, as the decrease was driven by these new workers ready to perform easier tasks.

Figure 2.6 Average hourly rates requested by IT digital workers in Eastern Europe, USD

Source: Own compilation based on Topsdev, 2015; 2017.

Rates in other countries of origin rose, as did the rates offered by the majority of IT clients. It is notable that the rates in countries with the largest market shares of performed IT tasks (Ukraine) and requested IT tasks (USA) are the same. At this stage, it seems that the market witnesses a search of its equilibrium, which is being incessantly modified by new entry of workers and clients from different countries, by penetration of the digital modes of work into new spheres, and by sophistication and diversification of tasks and worker profiles.

Despite these generally attractive earnings possibilities, actual online earnings also feature a significant gender pay gap. The analysis of the factors behind this gap shows that it reflects gender segregation into different occupations (Aleksynska, Shevchuk, Strebkov, forthcoming), unequal sharing of domestic responsibilities, especially childcare, and poorer skill match of women (Shevchuk, Strebkov, Davis, 2015), who tend to specialize in easier tasks.

Figure 2.7 Average hourly rates offered by clients of IT tasks, Top 10 countries of origin, USD

Source: Topsdev, 2017.

### 2.3.3 Work autonomy

In several Eastern European countries (Croatia, Hungary, Lithuania, Slovakia, Romania), as well as Russia and Ukraine, flexibility and autonomy offered by platform work are among the main motivations to do this type of work.

Despite this, some workers find that they do not have full autonomy in their work. The limits on their autonomy can come either from a platform or from clients. Platforms may deliberately or intentionally require regular presence (by featuring most frequently present workers in the search function). They may also require a certain way of communicating with a client, or installing special software to track hours of work and work progress.

Clients, in their turn, may also monitor how work is executed. For example, 45% of Ukrainian online workers report that clients give detailed instructions on how to complete the work, and 42% report that clients directly supervise work execution and control work processes. The forms of control vary, and include requests for being available during certain work hours either frequently or all the time (36% of online workers find themselves in this situation) or even outside of regular work hours (21%) ; providing screenshots of the executed work (27%), or having to install special software on their computers making such screenshots on request of their clients. Control is usually executed using standard Windows software (Excel, Microsoft Project), Google sheets, but also special platforms’ software (time tracker, team app), or other programs, tools, and websites, such as Viber, Skype, Time Doctor, Teamviewer, Harvest. Often work progress has to be reported through regular emails.

In addition to this, some workers find themselves somewhat dependent on a platform or on a client. Dependency on a platform stems from the fact that the ratings obtained on a platform are not portable from one platform to another, and that a worker needs to spend ample amount of time on one platform in order to build his or her reputation. Dependency on a client may arise if a worker does not have many clients, and most of the income is generated from the work with one client only. Also, some workers report that they receive fixed daily, weekly or monthly remuneration, rather than a project-based work. This situation is observed for almost 20% of Ukrainian online workers, and around half of workers in Croatia, Hungary, Lithuania, Slovakia, Romania. Coupled with limited autonomy, such situations may result in a disguised employment relationship,8 either with a platform, or with a client. In Ukraine, it is estimated that up to a half of online “freelancers” are in a grey zone of dependent self-employment or disguised employment. While no estimates are provided, concerns over this issue are also raised in other Eastern European countries (Pesole et al., 2018). Nevertheless, the vast majority of online workers considers themselves as genuine self-employed.

### 2.3.4 Informality and social protection

Work relations through online digital platforms remain largely informal. In Ukraine, three quarters of online workers report working informally. They are not registered with the authorities as self-employed, and are not paying social security contributions. 45% are convinced that no registration is necessary. The rate of informality is higher among online workers than in the rest of the Ukrainian economy. In Serbia, two thirds of online workers are informal. On the largest Russian-based platform, only 12% of freelancers regularly relied on written contracts with their clients. This is the only feature of the Russian-speaking digital labour market that remained unchanged over the past decade.

As a result, online workers may face a risk of absent or inadequate social protection. This situation is reported in surveys of Ukraine and Serbia, and is stated as a concern for other Eastern European countries. Many of these workers, in fact, remain in wage employment in addition to their online work in order to benefit from social protection provided by the wage employment. Such behavior, however, creates challenges to the sustainability of social security systems and to the adequacy of protection that they offer.

# Offline work mediated by online platforms and work through mobile apps

## 3.1 Extent of the phenomenon

In addition to performing work online, digital technologies also allow finding work online but performing it offline. This includes two main types of activities:

• Finding offline work through online platforms and mobile apps that serve as job advertising boards for either one-time or regular activities that may be diverse in nature. Examples include kabanchik.ua platform (similar to taskrabbit.com), where examples of tasks range from assembling a piece of furniture, providing plumber services, printing business cards to babysitting.

• Finding and performing offline work through local app-based platforms that serve as intermediaries connecting clients and workers, usually in one type of occupation, such as personal transportation or food delivery services. The difference with the online platforms mentioned above is that worker and client remain connected through the app while the work is executed offline. Among other features, the app has a monitoring role; for example, the time of the tasks’ execution is not only counted but may also result in various bonuses or penalties for the worker, awarded by the app.

In both types of activities, workers and clients have to be geographically close to each other. In other words, both types of work are defined mainly by their local dimension. However, the ownership and management of some of these platforms and apps may be foreign-based, adding the regional or international dimensionality to regulatory issues.

These two types of work are also to be distinguished from the concept of the collaborative economy. Unlike actual work, activities in the collaborative economy include unprofessional ad-hoc ways of complementing income, for example, though own car sharing, or own apartment rental, or selling own possessions online. Even if individuals proposing such activities gain some income from them, such income is not considered as income from work. In other words, such income is neither a salary of an employee nor a profit of a self-employed resulting from work. For this reason, collaborative economy is not systematically examined in this paper. It is to be noted, however, that some of the activities of the collaborative economy (ex.: AirBnB rental or reselling of items through Ebay and similar sites) became professionalized over time, blurring the boundary between collaborative economy and the world of work.

In 2018, a Eurobarometer survey addressed the question of services provision through local-based online platforms and apps, though without making a strong distinction about their economic nature (and hence covering both work and non-work activities in the collaborative economy). The results of the survey allow having a glimpse of the general developments of these activities in the EU Member States. Note that, because collaborative economy is included, these figures are greater than the actual work performed through platforms and apps. The survey shows that 23% of the EU residents have ever used services offered via platforms and apps, though only 4% use them on a regular basis (EU, 2018).9 In Eastern European countries, among those who have used online apps and platforms to access various services, the vast majority used services in the transport sector (over half of respondents) and accommodation. Food-related services, including food delivery, were experienced by about a third of Eastern European respondents (Figure 3.1).

Figure 3.1 Share of users of online apps and platforms, by type of service

Source: Own computation based on Flash Eurobarometer 467, 2018.

Note: Respondents: population aged 15+. Multiple answers were possible.

The survey also shows that about 6% of Europeans have offered services via online platforms, including both unpaid activities and work (ibid). In Eastern Europe, Latvia is a clear leader. Slovakia, Slovenia, Romania, Hungary, and Croatia exhibit levels of services provision in the collaborative economy that are higher than the European average (Figure 3.2). If in Latvia the outcome is largely driven by the transportation related activities, the outcome in Slovakia is mainly due to food-related services.

These estimates are relatively comparable to those found in other EU-wide surveys. For example, Huws et al. (2019) also indicate that, in Europe, the highest levels of income generation through local-based apps and platforms for offline work are in Central and Eastern Europe, notably in the Czech Republic, Slovenia and Estonia.10 The highest percentage of workers operating through local-based apps and platforms for offline work was found in the Czech Republic: in 2019, up to 28.5 per cent of respondents aged between 18 and 55 did such work at least once a week.

Pesole et al. (2018) report findings similar to the Eurobarometer estimates for Croatia, Hungary, and Romania. Figures for Lithuania, in contrast, differ: it is this country that comes as an Eastern European leader in offline work mediated by the platforms according to Pesole et al., 2018.

Taken together, the statistical picture on the state and the growth of collaborative work obtained at the European level goes hand in hand with a discernible increase of mentioning of these issues in public discourse at the national level.

Figure 3.2 Share of individuals who have offered services via online platforms and apps

Source: Own compilation based on Flash Eurobarometer 467, 2018.

Note: Respondents: population aged 15+.

Compared to the development of online work, the development of offline work mediated by platforms and apps started somewhat later. It is not before the 2010-es that the first mobile apps for work were popularized. In some countries, local mobile apps developed ahead of foreign ones. In some others, changes to the traditional ways of work were brought by foreign companies, such as notably Uber (for transportation), and most recently Glovo (for food delivery). These major platforms, however, appeared with time lags in different markets, and they are not evenly present across countries (Table 3.1). This in part explains country-level variations in the extent of the digital work mediated by the apps.

Table 3.1 Examples of international, locally-operating, apps-based platforms in Eastern Europe, as of 2019

Country

Transportation

Delivery

Uber American, founded in 2009

Bolt, Estonian, founded in 2013

Yandex.Taxi, Russian, Founded in 2011

Glovo, Spanish, founded in 2015

UberEats, American, founded in 2014

FoodPanda, German HQ,
founded in 2012

Albania

-

-

-

-

-

-

Bulgaria

-
(banned)

-

-

-

-

Belarus

-

-

-

-

Bosnia and Herzegovina

-

-

-

-

-

-

Croatia

-

-

-

Czech Republic

-

-

-

Estonia

-

-

-

Hungary

-
(suspended)

-

-

-

-

Latvia

-

-

-

Lithuania

-

-

-

Montenegro

-

-

-

-

-

-

North Macedonia

-

-

-

-

-

-

Moldova

-

-

-

-

-

Poland

-

-

-

Romania

Russian Federation

(merged with a local player)

-

(absorbed by a local player)

_

Serbia

-

-

-

Slovakia

-

-

-

-

Slovenia

-

-

-

-

-

-

Ukraine

-

Source: Own compilation based on the information provided on international and local websites of each respective company.

This table also shows that, judging by the foreign presence, the most dynamic markets for work via apps were Romania and Ukraine, closely followed by Croatia, Czech Republic, Baltic States, Poland, Russia, and Serbia.

Indeed, national commentators note that in Romania, there has been a real upsurge of novel practices led by international mobile apps and platforms. Ride-hailing is led by Uber and Bolt (former Taxify), as well as a Romanian app, Clevertaxi; bike delivery is pioneered by Foodpanda and more recently, Glovo. In addition, there is at least a dozen of local apps for work in various sectors (Roşioru, 2019).

In Ukraine, there are several apps in the transportation sector, with the local Uklon, international Uber, and regional Taxify and Yandex being the largest market players. International, regional, and local apps flourish in the delivery sector, accommodation and care. Popular are also online platforms for offline work, such as Kabanchik.ua. The latter is a local analogue of the American TaskRabbit: it is a marketplace for matching clients with workers eager to perform any small works and running errands offline. In the delivery sector, Glovo app is increasingly reinforcing its positions: between December 2018 and March 2019, the company’s turnover increased tenfold; half a million Ukrainians installed the app, and roughly 5000 workers were providing delivery services in 2019 (Movchan, 2019).

In the Czech Republic, the growth of work through digital apps is prominent, and is largely driven by the entry of Uber into the country (National Training Fund, 2017; Euro, 2017). Over twenty different apps and platforms operated in different sectors by 2017. In the accommodation sector alone, there were at least five players in addition to AirBnB, including Flipkey, HomeAway, House Trip, Vacation Rentals, and Vrbo.

Poland is estimated to be Uber’s third largest EU market (The Krakow Post, 2017). Here, several other transportation and small parcel delivery apps have also flourished. Examples include local JadeZabiore and BananaCar, as well as local versions of international MyTaxi and Bolt (Sienkiewicz, 2019). There are also several Polish-market oriented platforms that only match clients and workers, but work is performed offline. Those include Oferia.pl (with over 220.000 registered workers as of 2019) and Sir Local (Sienkiewicz, 2018).

In Serbia, Uber is not present, but there is a local prototype CarGo, operating in a similar spirit.

Remarkably, owners of foreign apps come both from the same region and from outside of the region. For example, among some most widely used apps, Bolt (Taxify) is an Estonian transportation app, which has first tried out its operations in the Eastern European market before moving to the rest of the world in an Uber-type expansion. In several Eastern European markets, Bolt is the main Uber’s competitor. Similarly, Yandex.Taxi is now an internationally company. It originated in 2011 in Russia, two years ahead of Uber. It is present in all fifteen former Soviet Union republics, as well as a number of Eastern European countries. Hopin is a Slovak transportation app, which started its services in 2012, ahead of Uber. It operates in Bratislava, Košice, Michalovce, Poprad, Humenné (Slovakia), Prague, Ostrava (Czech Republic), Ljubljana (Slovenia), and Kyiv (Ukraine). It is also the only app that complies with all the legal regulations in the transportation sector, at least in Slovakia. A Ukrainian platform for offline work Kabanchik.ua recently created a local-market version for Belarus and for Kazakhstan.

Importantly, countries have varied greatly in how governments and local markets reacted to the appearance of different apps and their proposed business models, which either restrained the spread of work through apps, or accelerated its expansion. In the case of Uber and other apps in the transportation sector, for example, there was a whole spectrum of responses (Table 3.2). Some countries, such as Bulgaria, adopted Uber ban very early on, sending a strong signal to the market players that digital apps not respecting existing laws should not be allowed to operate. Some others, such as Belarus and Hungary, amended existing laws to bring Uber and Uber-type companies under the scope of existing regulation and to be able to require compliance with it. Yet some others, such as Estonia, introduced major legal changes to liberalize the traditional market to fully embrace apps-mediated mode of work beyond professional services. In Russia, Uber lost the market war to the local player Yandex.Taxi; with Uber.Eats being completely driven out of the market (see Box 3.1). This defeat was partly a result of the government support to the local player in the form of a “Google tax law”, which required foreign companies selling e-content via the Internet, including Uber, to pay an 18% value added tax. But in all cases, digital technologies seem to have disrupted the existing modes of work. They allowed non-professionals to step into traditional sectors (sometimes increasing the extent of the informality of those sectors), augmented competition (sometimes unfairly), and changed the old rules of the game.

Table 3.2 Uber Transportation Application: Examples of Experiences from Selected Eastern European countries

Country

Year of entry

Situation as of September 2019

Belarus

Spring 2015

17/07/2017: A Law №50-З « On Changes and Amendments in the Law of Belarus "On passenger transport and transportation " « , in force since January 2018. The law provides a new definition of taxi service. According to it, Uber and Uber-type companies are considered as taxi. As such, they have to comply with the existing taxi regulation. At the same time, some previous regulation was relaxed, such as the necessity to have a taxomemeter for any taxi provider. The law is aimed at eliminating non-professional drivers from the market and prevent unfair competition.

Bulgaria

December 2014

30/06/2015 : Banned by the decision of the Supreme court on the grounds of unfair practices (drivers working without official driving licenses or professional licenses).

Croatia

2015 (Zagreb), mid-2016 (Split, Dubrovnki), 2017 (SIbenik)

February 2018: The High Misdemeanor Court of Croatia has ruled that Uber is operating illegally, by providing a taxi service without a necessary taxi license. The court rejected Uber's appeal against the first-instance, and charged a fine, but did not ban the company from operation. The government is considering a new regulation to liberalize the taxi market regulate the work of Uber-type apps.

Czech Republic

2014 (Prague)

April 2017: The Brno court ruled that Uber drivers could not provide services without a taxi permit. All cars must be marked as taxis and feature a taximeter. However, in June 2017, the Czech Court of appeal lifted a ban on Uber in Brno. In 2018, Uber announced that it reached the agreement with the Minister of transportation to continue operations provided that drivers are licenced.

Estonia

2015

2017: Bill on Amendments to the Public Transport Act outlines the conditions of providing transportation services mediated by digital electronic platforms and regulates their position to traditional taxi services. As per this law, neither traditional taxi drivers nor new digital providers have to comply with the previously required conditions of professional training. Rather, everyone has an obligation to ensure their own training provision to their drivers.

Hungary

November 2014

July 2015: A new national regulation was passed (Government decree 176/2015 (VII.7.), extending the scope of existing provisions to cover not just the traditional taxi services but also all ‘car passenger services’. Thus, Uber has become subject to the overall national regulation on taxi services. The new law also allowed the Hungarian authorities to block "a provider of taxi services operating without a proper dispatch center" for up to one year. As a result, the company suspended its operations.

Latvia

End of 2013

New amendments in the Road Transport Law, adopted by the parliament on September 28, 2017, came into force on March 1, 2018. According to those, Uber and any other similar app or company is obliged to obtain a license for operations. Additional common basic requirements for the drivers regardless of service provided (taxi or ridesharing) were introduced: 3-year driving experience and an obligation to register in the Enterprise Register as a legal entity. At the same time, the process of obtaining licenses was simplified.

Lithuania

End of 2015

27/09/2016: Amendment to the Road Transport Code, in force since 01/01/2017. New provisions allow passenger transport to be organized by both natural and legal persons in both taxi and ordinary passenger cars, in return of tax compliance. Service providers are also subject to other requirements by the Rules on the Transportation of Passengers by Cars in Exchange for a Payment and by Taxi Cars, adopted in December 2016.

Poland

2014 (5 cities)

April 2019: A law is being discussed that will require Uber and other ride-sharing companies to use only licensed taxi drivers from 2020 on. Meanwhile, Uber opened a regional office to manage its operations in Poland, Estonia, Lithuania, Croatia, Belarus, Azerbaijan, Kazakhstan, and Ukraine. February 2018: UberEats is launched.

Romania

February 2015

The Association for monitoring taxi operations in Transylvania (Asociatia de Monitorizare Taxi Transilvania), and the Confederation of authorized transportation operators in Romania (Confederatia Operatorilor de Transport Autorizati din Romania, an employer confederation) , filed a lawsuit against the Dutch company Rasier Operations BV and Uber (SC Uber Systems Romania SRL), which holds the license to use the application developed by Uber Technologies, Inc, San Francisco, California. With the decision 1192/2018, the court concluded that the Uber practices constituted unfair competition, on the grounds that the application was not owned by the defendants. There are ongoing discussions in the government about a new law to regulate Uber-type apps.

Russia

2013

Absorbed by the largest Russian player on the taxi market, Yandex.taxi. UberEats, in contrast, had to stop its operations and withdraw from the market.

Serbia

No presence

October 2018: the National Assembly adopted amendments to the Law on transportation of passengers in the road traffic, requiring workers of apps to have professional licenses. As a result, Uber has not adventured to enter the Serbian market.

Slovakia

August 2015

March 2018: district Bratislava Court I ruled that Uber is practicing unfair competition and forced Uber to suspend its services for one year. A year later, Uber restarted its services, claiming that it now operates only with licensed drivers.

Ukraine

Mid-2016

No public regulation to date. Law proposals to allow passenger transportation by private persons in exchange of simplified license and a flat-rate tax are being jointly developed by key market players.

Sources: own compilation based on national sources. Bulgaria: Duncan et al., 2016. Slovakia : Sedláková 2018; Reuters.com., 2018. Hungary: Budapest Business Journal, 2017. Croatia: Pavlic, 2017. Romania: Roşioru, 2019. Czech Republic: Reuters, 2019. Poland: Reuters, 2019. Russia: Vedomosti.ru, 2018; Vox.com, 2017. Belarus: Avtobiznes, 2017. Ukraine: Samojlenko, 2018, AIN, 2019. Estonia: National Training Fund, 2017. Lithuania: OECD, 2018b. Latvia: OECD, 2018a. Serbia: Bjelotomic, S., 2018; Stojković Attorneys, 2018.

Box 3.1 Uber in Russia

Uber entered the Russian market in 2013. By that time, the market was already dominated by other players of digital taxi haling, and in particular by the local app Yandex.taxi, which detained 20% of the market share. Initially, Uber undertook a usual strategy of subsidizing the rides, in order to obtain a larger market share. Even if it managed to get up to 23% of the market share by 2017, and become the second largest player, Yandex.taxi reached 50% market share by that time. Uber, which spent over $170 mln in subsidized rides over three years to catch up with the local market leader, had simply entered the Russian market too late. Nevertheless, it managed to somewhat disrupt the market, by driving other players out of the market. While the “market war” with Yandex.taxi could have continued, in 2017, the Russian government announced changes to the tax legislation (a ‘Google Tax Law’), requiring foreign companies selling e-content via the Internet to submit information on their sales in the country, and pay an 18% value added tax. This “push” from the government intended to support local players in face of the often unlawful competition from the foreign-based locally-operating apps, such as Uber. As a result, an already unprofitable activity of Uber lost any of its sense. Uber lost the “market war” and accepted the merge with (ceded its control to) Yandex.Taxi. Yandex is controlling 56 % stake in the company, and Uber 35% per cent. A new application, UberRussia, was launched, covering Russia, Belarus, Azerbaijan, Armenia, Georgia and Kazakhstan. By 2019, the merged company operated in 250 cities. UberEats, in contrast, was fully absorbed by Yandex.Food and had to stop its operations and withdraw from the market. Sources: Vedomosti.ru, 2018; Forbes, 2017. ## 3.2 Profiles of Eastern European workers operating through mobile apps and online platforms for offline work The profile of workers operating through mobile apps differs substantially from the worker profile of digital freelancers operating online. Four key factors contribute to this difference. First, most popular digital platforms for offline work, as well as mobile apps, emerged in the traditional sectors of activity, such as transportation or care. The pool of individuals working through apps thus included first and foremost those workers who were already present in these sectors, whether formally or informally. Most of them had a relatively low level of skills. At the same time, given that workers switching to apps were somewhat more technologically savvy than others and open to trying new technologies, they came rather from a mid-range of the skill distribution. The apps did not change the nature of the work per se (i.e., drivers still had to drive), but only helped matching the existing demand from clients to the existing supply of work. This meant that principally new skills acquisition was neither possible nor required. This was also different from online work on the online platforms, which, in addition to being concentrated in intellectually- and creativity- demanding sectors, in many instances came hand in hand with principally new types of tasks (ex: demand for IT development) or new modes of work (ex: competitive programming). Second, some apps allowed non-professionals to step into the existing market. For many of them, work via apps represented secondary work and an additional source of income. This had an effect of flattening the skill distribution of workers operating through the apps. Third, because apps had very low requirements on who can do the work (at least initially, virtually anyone could sign up with very little formal checks), there was also a self-selection into these kinds of jobs of those individuals who otherwise had limited employment prospects. This included not only workers outside of the legally defined scope of the profession (such as licensed drivers in case of transportation apps), but also for example migrant workers, including without proper visas or work authorization. For instance, anecdotal evidence from Poland shows that there is a high share of Indian and Ukrainian workers working for UberEats. Some of them entered the country on student or tourist visas, and Uber does not check whether they have work authorization (Szostak, 2019). In the Russian capital, anecdotal evidence suggests that the majority of drivers working through apps come from Central Asia (Radio Freedom, 2018). Finally, work through mobile apps and local platforms for offline work is performed locally, and does not give access to better-paying clients located abroad. As such, it is not attractive to workers speaking foreign languages and having high level of technical skills, who prefer to utilize them on international online labour platforms. Given these factors, unlike online workers, workers of the mobile apps in Eastern Europe have education levels similar to those in the general offline labour market, and sometimes below it (Pesole et al., 2018). They are also on average 10 years older than platform workers, and resemble much more a general workforce profile (ibid; Huws et al., 2019). Some particularities, though, reflect also the particularities of each sector. For example, the transportation sector is dominated by males, while the accommodation and cleaning sector has rather a female face. In food delivery, anecdotal evidence shows a higher presence of young “strong and sporty” men. This worker profile is not static, however, with several factors contributing to its constant evolution. First, as more apps enter into each sector, and work through apps generalizes further, technologies simply become a mediator of professional activities rather than a generator of new work opportunities. Evidence from the Czech Republic and from Slovenia, for example, shows that the original apps of private properties’ clean-sharing gradually become classical business subjects, such as traditional professional cleaning agencies (National Training Fund, 2017). Second, regulations play an important role in shaping the worker profile. Interestingly, this is less influenced by general labour laws, and more often by competition laws, tax laws, and the laws regulating activities in each specific sector. For example, Uber and Uber-type applications initially allowed non-professionals to perform tasks similar to the professionalized transportation sector. Regulatory responses throughout the region widely recognized these apps as performing passenger transportation services rather than purely “client matching” services. This created new obligations for the workers using these apps to comply with the regulations on professional licensing, insurance, social security contributions, and taxation. Thus, following the adoption of these regulations, the pool of workers shrank back to include mainly the sector’s professionals and a few former non-professionals who, after experiencing this work thanks to the app, self-selected to join the profession. For example, evidence from Belarus and Hungary confirms that, as a result of legal changes that brought Uber under the scope of existing regulations in the transport sector, non-professional drivers massively left the application (Avtobiznes, 2017; Duncan et al., 2016). As a result, the portrait of a worker operating via an app started to reflect again the worker profile of the transportation sector. Similar changes can be expected in other sectors if the activity of local apps-based platforms if these sectors starts being regulated. ## 3.3 Working conditions: linkages with institutional factors and business models If there is one common feature across apps in Eastern Europe, it is that, as in the rest of the world, workers are not considered as employees but as self-employed. As a result, workers face a particularly high risk of informality. This is especially true of those apps and platforms that have been operating in the grey zone, outside of the scope of existing regulations and positioning themselves as “intermediaries” of the “sharing economy” and allowing non-professionals to exercise economic activity through them. In the absence of formal research, it is hard to conclude whether the emergence of work through apps raised informality levels. Some commentators suggest that it only revealed an already high level of informality, by making invisible economic activity visible. For example, city hitchhiking was not unusual and not formally prohibited in several Eastern European countries; but its extent was revealed by the arrival of the apps in the transportation sector. Others reckon that the digital economy did amplify an already ongoing informalization trend, with the “new business models” promoting the idea that informal may be “normal”. They also amplified the trend towards precarity: after all, apps do not have any promise that there will be work when a worker is making herself available for work, and can unilaterally shut down an account at any time. A “portrait”-type survey of Slovak and Hungarian apps workers shows that, currently, while their earnings may be comparable to an average worker in the rest of the economy, they still face precariousness on other dimensions of working conditions (Kahancová, Meszmann, Sedláková, 2019). The majority of workers do not pay social security contributions and are not covered by social security or private insurance against professional and health risks. However, the vast majority of these workers use work through apps to complement pay from their main job (a universal finding of all studies). As such, they rely on social security protection through their main job (ibid; Pesole et al., 2018). The situation with informality, however, is also quite dynamic. It is possible that the increased informality is only transitory, as technologies carry a chance for formalization: if they allow for cashless transactions, they can also potentially be used to monitor economic activity by public agents, prevent evasion of taxes and social security payments, prevent fraudulent payment and cybersecurity risks. Here, policy responses may be helpful to indeed ensure that the formalization of the previously informal activities is actually happening. In addition to informality, employment status determines to a large extent other working conditions. But because work through mobile apps is so sector-specific, working conditions also reflect the working conditions in each respective sector. Moreover, they are strongly shaped by two other, related, factors. One important factor is the legal environment of each country. Countries differ in whether they have a legal framework and a sufficiently developed judiciary practice in place to determine the existence of an employment relationship. They also differ in the degree of compliance with these laws and the strength of the enforcement bodies (labour inspectorates) overlooking their implementation. This has important implications for workers operating via local-based platforms and apps. The concern is that the way some apps operate creates a situation of a disguised employment relationship, with apps serving a de facto, but not a de jure, role of an employer. Interestingly, the risk that a worker would find herself in a disguised employment relationship seems to be more severe in countries with poorest legislation in the matter of employment relationship, and poorest enforcement. Also, apps that are present in several countries (ex.: Glovo), seem to adapt their business models to have more abusive practices in the weakest legal environments. Slow public reaction to redress the situation, coupled with the demand for cheapest services, augments the longevity of their businesses and hence the duration of the impact on workers. Thus, a related – and perhaps by far the most important factor shaping working conditions – is the business model adopted by each particular app. The elements of such business models include price-setting and remuneration-setting mechanisms, commissions, direct work or work via intermediaries, monitoring of hours, various incentives to continue working, and rating systems. Unlike online work, it is rare that work via an app can be performed several times, or on a prolonged basis, for the same client. Moreover, clients have little say over remuneration. Thus, in a much more systemized manner, it is an app that exercises control over remuneration, while workers are price-takes in this relationship. The differences in the business models translate into the differences of working conditions across the apps users. In fact, it is because they varied so greatly from one app to another, and from one country to another, that policy responses were quite specific to those apps, to their sectors of activity, and to countries. Turning to specific examples, Uber systematically practiced the same market-entry behavior in each new market: in order to attract new drivers, it initially set ride rates below the market rates, but subsidized its drivers. Little by little, as the pool of drivers increased, subsidization also went down. The commissions that Uber charges to its drivers, however, did not diminish, and often increased. On average, over 2014-2019, workers of Uber were charged 25% on each performed task. Moreover, in Eastern Europe, workers often do not work directly through Uber apps, but through intermediaries, which also charge commissions. As a result, total commissions may represent up to 40% of earnings. Uber also practices “dynamic price list”: it offers higher rates when there is a particularly high demand for drivers, such as on Friday and Saturday nights. There are several immediate consequences of this business model. First, over time, earnings of Uber drivers diminished. To earn a decent living, workers have to put increasingly greater hours into this work – to the detriment of their own health and the safety of passengers. Second, because of the dynamic pricing, workers are selecting to work during atypical hours, including at night. The presence of intermediaries can also lead to various types of abuses, including arbitrary additional charges, withholding of payment, and general pressure on any voicing of workers’ concerns. Evidence from Poland shows that Uber drivers work on all week days, and especially on week-ends, for 12 hours a day. They regularly drive to the center city from neighboring towns, and sleep in their cars before driving again (Szuba, 2018). In Russia, where Uber was merged with the local Yandex.Taxi, according to the Head of the association Forum Taxi, “if drivers were to follow the labour legislation, they would not earn anything” (Radio Freedom, 2018). Workers of this joint app had to work up to 70 hours per week in 2017 – 2018 in order to be profitable. Some migrant workers practice “shift methods”: they share a car in 12-hour shifts for two to three months, before returning to rest in their home countries, and being replaced by other compatriots. This model, however, is not sustainable for local drivers wishing to work on a permanent basis (ibid). Moreover, it comes with a high toll on health and safety. According to the official statistics, between 2015 and 2017 the car accidents involving taxi drivers rose by 35% (Analytic Center of the Government of the Russian Federation, 2018). But it seems that it is the business models of apps in the delivery sector that result in particularly drastic working conditions of their workers. For example, UberEats, in addition to practicing similar strategies as Uber for transportation, also often requires that workers perform a certain number of orders per week in order to be paid at all (situation varies across countries). Moreover, UberEats intermediaries may decide whether or not to give a contract to the worker, and when and how to make payments to the worker – sometimes delaying payments or giving payments that are below the incurred expenses (Szostak, 2019). Workers are also required to use their own equipment (cars, bikes, bags), which is not reimbursed by the app (Uber Drivers Facebook Group, 2019; Alekseeva, 2019). Usually they are paid for the delivery, but not for the time they need to return, even if the delivery is outside the city. As a result, not only pay for work is meager, but workers may also find themselves in debt towards intermediaries (ex: Poland: Szostak, 2019). Yandex.Food, which purchased Uber.Eats in Russia, as well as its main competitor in Russia, Delivery Club, have similar practices. In addition, workers of these apps do not have the right not to work because they are sick or want to go on holidays: they may be disconnected, have their rating diminished because of interrupted availability, or even receive a fine because of “absence” or “being late at work” (Petljanova, 2019). Delivery which takes longer time than that calculated by the app results in financial penalties. Anecdotal evidence shows that workers of these apps may be working up to 12-14 hours a day, covering 40 to 60 kilometers per day by bike or on foot. In 2019, there was a case of a death from a heart attack of a 20-year old worker in Saint-Petersbourg during the delivery of Yandex.Food, and another death of a delivery worker of Delivery Club (Petljanova, 2019). Another example is Glovo, a Spanish courier app that operates in Croatia, Romania, Serbia, and Ukraine. It specializes in food delivery (restaurant pickup), supermarket purchases, and small parcels delivery. Workers can work either with their own transportation, or lease the transportation from the company. They also have to purchase the equipment (delivery bag). In Ukraine, when the company stepped into the market, it offered hourly pay and a system of bonuses for more than 10 deliveries per week. But once it attracted a sizeable number of workers, it switched to payments per order and per kilometer, with payments disbursed once a week. Moreover, a new system of bonuses was applied, with bonuses available starting from 20 deliveries per week (Glovo website; Dudin, 2019, Movchan, 2019). The app is changing both the rates, and the rules on bonuses, unilaterally, while workers unhappy with such changes are asked to leave the app. Their working hours are regulated by an app: it switches off a user for “one hour lunch break” if work is performed for over 8 hours per day. However, it also decreases ratings of those who take breaks more often. Workers are also given specific instructions about transporting food, and about their clothing (ibids). There is also evidence that the app has access to other apps installed on a worker’s phone. It can thus monitor comments about Glovo made on social media. Upon those, it can unilaterally close a worker’s account, for example, in case of “negative’’ comments on Facebook, as stated in its Terms and Conditions (ibids). But despite all attributes of the employer, the app does not recognize that it enters into an employment relationship with its workers. Thus, workers are responsible for their own insurance, social security contributions, and paying taxes. The company is not checking compliance with these obligations. In some countries, like Ukraine, the app operates in a particularly abusive way, setting hourly rates and bonuses below the minimum wage rate (ibids). As a result, in order to gain meaningful living, workers have to work very hard and put substantial hours into this work simply to break even. This comes with a very high toll on health and safety. For example, in Ukraine, it is estimated that the average time to make a delivery with Glovo is 45 minutes. To complete 100 deliveries, for which one can get the greatest bonus, a courier must work 75 hours a week - 11-hour shifts everyday without a day off. This is under the conditions that orders come smoothly, which almost never happens. In reality, workers need to spend 14 hours a day, seven days a week to get the maximum bonus. The fact that no bonuses are paid for less than 20 rides per week also mean that it is not profitable to work for the app as a part-time activity (Movchan, 2019). Workers are complaining about being mistreated by the company. They also report extreme tiredness from this work, despite the fact that most of them are 20-30 year-old men. There is also a reported case of a Glovo courier death in a road accident, possibly because of the pressure to deliver fast and not being attentive. The courier’s family did not receive any compensation (ibid). Given this, it is clear that policy responses need to address the issues of working conditions simultaneously on several levels: clarifying workers’ status in employment vis-à-vis the apps, regulating working conditions regardless of the status in employment, and addressing the informality and professionalization issues through tax, social security, and competition laws. The next section examines country-specific examples of such responses. # Regulating digital work The developments of digital work outlined exhibit several layers of complexity. They include a panoply of markets (national, regional, and international), differences in business models of platforms for online work and platforms for offline work, sectoral peculiarities, and the existing legal frameworks in each country. As a result, there is no unique response to regulating digital work. The review of existing national attempts to regulate digital work shows that policy responses included changes in labour laws, changes in laws regulating specific sectors of activity, but also elaborating measures of better enforcement of existing regulations, formalization, and tax compliance. The response to digital apps was swifter than the response to the online work. This is because digital apps carried more risks of disrupting existing modes of work, more systematically created unfair competition within the local markets, and more often resulted in poor working conditions. Despite an important regional and international dimensions of digital work, existing policy responses took place mainly at the national level. ## 4.1 Collective responses: challenges of representing and organizing digital workers Traditionally, one of the first steps towards creating regulatory responses for any new type of work has been worker organization, representation in new or existing trade unions, and collective bargaining. However, the development of digital markets has so far faced challenges of both organization and representation worldwide (Johnston and Land-Kazlauskas, 2018). The key challenge, first and foremost, includes the fact that most of the digital workers, whether those working online or offline, are classified as self-employed. As such, they fall outside of the scope of existing labour laws regulating employment relationship. Usually, they legally cannot be part of a trade union. Collective bargaining agreements often cannot apply to them, and they do not have a clearly attributable employer who would serve as a collective bargaining counterpart. Another key challenge is practical. It is related to platform fragmentation and dispersion of workers across different platforms, sectors of activity, and types of performed work. Most of the digital workers do not know each other, and their interaction is virtual at best. Furthermore, as many digital workers perform a variety of activities, sometimes in different sectors, it is not always clear which trade union could best represent their interest. These challenges are common to all countries worldwide, including Eastern Europe (Akgüç et al., 2018; ESDE, 2018). For example, in Poland, until very recently, self-employed or those working under civil contracts officially could not be a member of a trade union (Sienkiewicz, L., 2019). The situation may be changing following up the Constitutional Tribunal’s judgment of 2015, which ruled that the limitation of trade union membership to employees is unconstitutional, and that any worker who is not an employer, can be a trade union member. The ruling is yet to find its way into the legislation regulating trade unions’ activities (ibid). In Slovakia, trade unionists argue that the “structural obstacles” within their traditional organizations prevent digitals workers to join the unions (Sedláková 2018). Throughout the world, three main response strategies have been played out. They included addressing worker misclassification actions; where possible, extending collective agreements to all workers in the sector regardless of their employment status; creating new alternative organizations of digital workers (Johnston and Land-Kazlauskas, 2019). The role of existing traditional trade unions has been paramount in this regard. However, recalling the regional context can help nuancing why these strategies have been very modest in Eastern Europe so far and why, unlike Western Europe, trade unions have not been very active yet with respect to digital workers. The first reason is the general weakness of trade unions. Since the collapse of the communist regimes, trade unions have been largely seen as a legacy of the past. Trade union membership has been continuously declining (Figure 4.1). Looking at most recent available data, the regional trade union density rate is just below 20%; it is below 10% in Hungary, Lithuania, and Estonia. In some countries, it is also particularly weak or inexistent in traditional sectors of accommodation service or transport – precisely where the digital work is spreading (Hungary, Slovakia: Kahancová, Meszmann, Sedláková, 2019). In some countries, such as Romania, trade unions were further weakened through legislative changes adopted during the crisis (ETUI, 2019). Limited number of trade union members, limited capacities and funds, contrasted with the high investment necessary for organizing a dispersed and fluid pool of digital workers, mean that collective responses to digital work remain limited or inexistent. Figure 4.1 Evolution of Trade Union Density Rate (in per cent), Selected Eastern European Countries Source: ILO STAT. Another reason is that, with the persistence of informal employment and the rise of various forms of non-standard employment in the post-crisis decade in some countries (Kahancová, 2016, Meszmann 2016), work though apps is largely seen as a general continuation of the informalization and precarization trend. This is partly due to the fact that this work enters mostly into labour market segments that are already flexible. As such, it is not necessarily seen as something novel in the society, but rather as a simple mediation by technologies of an already existing situation (Kahancová, Meszmann, Sedláková, 2019 witness this in Slovakia and Hungary; Owczarek, 2018 observe the same phenomenon in Poland). Hence, it does not necessarily provoke an out-cry neither in the society, nor among tripartite partners. In addition to this, and as shown throughout the paper, there is a great disparity between workers working through digital platforms online and offline. Those working online are rarely interested in being organized (at least in the currently existing structures). This especially concerns online workers who position themselves as genuine freelancers, who truly benefit from the advantages that the platform work offers to them. Those for whom this work represents the main activity often chose it in order to escape abusive employment relationships in local labour markets (Aleksynska, Bastrakova, Kharchenko, 2018). They are also the ones who usually enjoy higher earnings and overall better working conditions as compared to what is offered in the local labour markets. As such, they are not unhappy with the development of digital work and do not seek its regulation. At the same time, for the vast majority of workers, digital work represents only a secondary activity in all reviewed countries (ibid; Pesole et al., 2018; Akgüç, et al., 2018; Kahancová, Meszmann, Sedláková, 2019; Owczarek, 2018). Thus, digital workers often rely on income security, social security provisions and other protections offered to them though their main job in the traditional sector. They do not seek labour protections in the digital labour market other than protections against non-pay, which are often remedied without involving trade unions, with the help of the platforms. For workers operating offline through mobile apps, there is generally also a low awareness of trade union activities, and of the fact that worker interests can be represented by anyone. This is particularly true of young workers who are over-represented in some apps, but also of migrant workers, who either do not know about their rights, or do not speak the language, or are only interested in working temporarily (ibids; ESDE, 2018; Dudin, 2018). Trade union activities are also time-consuming. Some apps workers mention in interviews that they cannot afford spending time on such activities even if there were opportunities to do so (Akgüç, et al., 2018). The void of trade unions’ response is somewhat filled, in some countries, by guilds-type and association-type actors. For example, in Hungary, there is an association of individual accommodation providers (MAKE- “Magyar ApartmanKiadók Egyesület” (Association of apartment rentiers). It serves mainly as a collective voice in face of the local government. Some of its actions concern providing information, training, and awareness-raising for accommodation providers operating through online platforms (Kahancová, Meszmann, Sedláková, 2019). In Slovakia, civic association “Vitaj Doma” (Welcome Home) was founded by AirBnB services providers. Its main functions so far consisted of providing a forum for exchanging information, including about regulatory changes and tax requirements (ibid). Online forums and social media groups have also flourished to exchange information about various aspects of online work (ex.: BeFree Facebook group for Ukrainian freelancer, counting over 40.000 active users). This situation may be changing, however, as platform work generalizes. Indeed, there is evidence that the maturity of digital markets is what makes the difference for the trade union response. For example, in Poland, the phenomenon of digital work simply has not gained momentum yet, while other issues tend to dominate public debate and tripartite dialogue. Those include harnessing general over-flexibility of the labour market, general regulation of the excessive use of civil contracts, and improving working conditions for all workers, such as appropriate setting of the minimum wage (Sienkiewicz, L., 2019). Importantly, it is also the business strategies and actions of some specific platforms that can provoke specific reactions on behalf of digital workers and of the existing trade unions. Some platforms are more aggressive and value-extracting than others. Their unilateral actions that substantially worsen working conditions can provoke collective response. For example, after Uber and Yandex.Taxi in Moscow raised commissions, drivers organized a 3-day strike in 2015, and another strike in 2017. However, the protesters were not numerous, and their concerns were not heard (Radio Freedom, 2018). Since July 2018, Glovo couriers organized three protests in Kyiv (Movchan, 2019). They protested against a particularly aggressive business model with the clear signs of violating the existing laws and engaging workers in a disguised employment relationship. Yet, the only reaction that they obtained from the app owners was their bans from the Glovo app. In response, couriers set up a trade union of delivery services workers, supported by the Ukrainian Social Movement NGO. While this trade union has no specific rights in Ukrainian law so far, it is also one of the very few examples of workers organization in the digital economy. Their main task as of now is to prove that their relationship with Glovo should be considered officially as employment (ibid). Where unions have been unanimous throughout the region is in the personal transportation sector. Entry of Uber and Uber-type applications (such as Car.Go in Serbia) into the local markets provoked a general outcry of traditional players in this market. However, most of the demands did not concern working conditions of drivers. Rather, they focused on protesting against unfair competition practices of those applications that allowed drivers to work without proper professional licenses, insurances, and other obligations that the professional actors in the sector have to comply with. Also, they were aimed at fighting against unfair price setting that some companies practiced, such as dumping of transportation services in exchange of subsidizing drivers in order to break into the market. ## 4.2 Regulation through labour law: determination of the existence of an employment relationship The question of worker classification is at the heart of the digital workers protection in all countries of the world (ILO, 2016). It also concerns workers in Eastern Europe, and especially those who find themselves in various forms of dependency from a platform or an app. Appropriate classification of workers as employees rather than self-employed can help granting workers the rights that they are due under the existing labour laws. In their turn, clear laws on the determination of the existence of an employment relationship, and their proper enforcement, can reduce incentives for companies to have an abusive recourse to self-employment. They can also reduce incentives for the apps developers and owners to build their business models around the possibility of relying on disguised employment relationships. Some countries of the region do not have specific legal provisions on the determination of the existence of an employment relationship. Moreover, the topic seems to be quite sensitive. For example, when in 2018, the Ministry of Social Policy of Ukraine put forward a law proposal on the determination the existence of an employment relationship – a law proposal that was closely based on the ILO Employment Relationship Recommendation No 198 – it created a large wave of protests on behalf of the workers that it intended to protect. Many online workers saw this as an attempt of the government to “cut” platform work, and a threat to the flourishing IT sector where self-employment is omnipresent. But for other workers, such as those working through apps and more often being in the grey zone of disguised employment, this meant that it is not easy to bring claims to court (Dudin, 2018). The problem of worker reclassification in Ukraine is also exacerbated by the absence of specialized labour courts, and hence of experienced labour law practitioners and judges who would be able to mainstream the reclassification cases. Other countries, such as Romania, were more successful in this regard. When the share of self-employed hit over 40% in the country in the mid 2010-es, the country managed to adopt legal instruments establishing a series of criteria to determine the legal nature of a work relationship. Interestingly, the legal change was integrated into the Tax Code rather than the Labour code. Also, instead of listing the criteria for an employment relationship, the new provisions rather list the criteria of qualifying as a true freelancer (at least four out of seven conditions have to be met: Roşioru, 2019). In addition, in 2018, a law on teleworking was adopted, setting up very clear definitions and conditions of this activity. Importantly, this law, coupled with the reformed social security provisions, according to which social security contributions are paid only be employees, sets substantial incentives for certain platforms and clients to award their workers the legal status of an employee (ibid). ## 4.3 Regulation through labour law: New provisions specifically addressing digital work Local app-based platforms mediating offline work and online platforms often require different types of regulatory responses. Work performed through the local app-based platforms is mostly local in nature. As such, it can be rather successfully regulated at the national level. The caveat, however, is in the enforcement of such regulation: it may be jeopardized by the foreign ownership and non-national location of the apps’ managers. In its turn, online work performed through online platforms exists at national, regional, and international levels. As such, it would benefit the most from the regulation on these three levels. Yet, regional and international cooperation in the area of labour law regulation of online work so far lagged behind the development of online work. More generally, as the phenomenon of digital work is still quite new, regulations of working conditions by means of labour laws have so far been rather disparate. Of all reviewed countries, any specific attempts to regulate work though local app-based platforms, by means of labour law, were found only at the national level, and only in the Russian Federation. Here, a law is currently being discussed in the parliament (second reading: end of 2019) about working conditions in the transportation sector. Among other issues, the law proposes to limit the working hours of taxi drivers (both traditional and those working through apps), including tracking whether they switch between different apps; monitoring their tiredness with special cameras installed in the vehicles; prohibiting employment of foreigners; and prohibiting driving without licenses by imposing fines on the apps rather than on drivers. Regarding online platform work, similarly, as of 2019, only national attempts to regulate such work were found. Most of them are still at the negotiation and proposal stages. For example, in Poland, an attempt to address the issue of platform work under the Commission for the Codification of Labour Law has ended without any conclusions (Owczarek, 2018). Perhaps the most (if not the only) advanced efforts to regulate online platform work by labour law is found in the Russian Federation. In 2013, its Labour Code was amended by the Federal Law N.60-F31 to include Chapter 49.1 “On distinctive features of remote work of employees” (Filatkina, 2015; Lioutov and Tsypkina, 2018). The new chapter aimed specifically at legalizing and regulating “on-distance”, “remote” labour relationship that are mediated by digital technologies, and Internet in particular. Article 312.1 of the Labour Code defines its scope of application as pertaining uniquely to work performed outside of employers premises and outside a standard workplace controllable by an employer, and for which ICT networks are used for communication between the employer and the employee on execution of a job. Remote employees are considered to be those who concluded a work contract about remote work, and should be normally covered by labour law, taking into account the particularities of this work. They should receive a salary, rather than civil-contract-type compensations, have a right to paid leave, and be considered as staff. The control over employee is performed remotely, with electronically set milestones and deadlines and sent work by those dates considered as proofs of work being done (ibids). The remote employees thus defined are different from home workers, which are also regulated by the Labour Code. Differences, among others, include the workplace: for a home worker, the workplace is the employer’s organization, while for a remote worker, the workplace is his or her own home, without territorial limits (ibids). The list of works to be performed remotely, however, is not fixed by the legislator. These new provisions also grant remote workers a number of exemptions from the general rules applicable to hiring and execution of employment contracts. For example, the parties are allowed to exchange documents in an electronic form (“electronic documents”) as long as they are authenticated with a so called “reinforced qualified electronic digital signature”, which in Russia are formal legal terms also defined by legislation. They are also allowed to abstain from maintaining “work books” - the official track record of a worker’s life-long experiences, which all employers and employees are obliged to keep. Finally, the law allows a remotely working employee to set his or her own work and rest regimes in a unilateral manner (Gerasimova, Korshunova, Chernyaeva, 2017). Other particularities include provisions on confidentiality and information protection clauses that should be part of the employment contracts of remote employees. They should concern the company information accessed by the remote worker, but also that is produced by the remote worker for the company. Thus, the law forsees that both remote worker and employer should follow the rules of information safety. Personal computers of remote employees can be equipped with crypto-protection systems, preventing information sharing with third parties. In return, a remote worker can ask for a purchase or amortization of computer equipment necessary to execute work (Lioutov and Tsypkina, 2018). Yet, the new regulation is seen only as a first step towards creating a real regulatory field of online work. Some Russian lawyers consider that the concept of remote work was defined too narrowly, as it does not cover remote work performed for an employer located outside of the Russian Federation. As a result, there are currently no provisions on the rights and obligations of workers operating remotely across borders, and neither there are provisions to guarantee equal treatment or safety (Gerasimova, Korshunova, Chernyaeva, 2017). Moreover, for the new provisions to be effective and complete they have to be supplemented by a series of amendments, including a possibility to execute remote (telework) arrangement only on a part-time or temporary basis, otherwise combining it with regular work with the same employer; the “right to disconnect” (Lioutov, 2018); more clear regulation of working time of remote workers ; and a more clear set of criteria of proving the existence of an employment relationship (Lioutov, 2019). The subordination criteria, necessary for establishing an employment relationship, should also be complemented by the economic dependency criteria, as well as by acknowledging the asymmetry in economic powers of both parties of the agreement (ibid). Some scholars also regret the abolishing of “work books”, suggesting that technologies allow to have “electronic work books” (Kurennoy, Kostyan, Khnykin, 2017), which may be a useful tool for proving online work experience and for claiming social security (particularly pension) rights. ## 4.4 Fair competition, tax compliance, and other regulatory responses In addition to the issue of status in employment and working conditions, the emergence of digital work was accompanied by the concern regarding the legal status of workers and of the platforms through which they operate. The concern is that, under the pretext of being a “new” mode of work, these platforms and workers actually get a competitive advantage by avoiding various local regulations required to enter the market in a given segment. In addition, tax avoidance and under-reporting of income by workers operating via online platforms of any sort are often an issue. ### 4.4.1 Regulatory responses to local app-based platforms The main issue with the local app-based platforms is that they often claim to be only a technology service. For example, this was the case of Uber and Uber-type applications, who refused to acknowledge that they are a transportation company. As such, they claimed to fall out of the scope of current national legislations regarding the licensing and insuring of drivers and of their vehicles. Thus, they refused to be bound by the same legal obligations as other traditional market players in the sector, despite de facto providing the same personal transportation service (Duncan et al., 2016). The concern, however, is that by doing so, they practice unfair competition with respect to the licensed services. Similar concerns are voiced with respect to platforms for short-term property renting. They allowed some private individuals to compete with the professionals in the hotel industry, but without having to comply with all the safety and hygiene regulations of the sector, and hence undermining the business of the latter. A related issue is fiscal obligations and taxation: platforms are open to participation of non-professionals and are not checking whether those non-professionals are paying taxes. This adds to the unfair competition concern, but also results in omnipresent tax evasion and income underreporting. For example, in Hungary, official complaints were brought to court claiming that Uber Hungary Kft. as the subsidiary of Uber International Holding B. V. (registered in the Netherlands) carried out their activities without meaningful tax payments (Duncan et al., 2016). Thus, several countries reacted to the development of the digital work first and foremost by reconsidering what legal status such applications and platforms should have. Regarding the local app-based platforms, regulatory responses were undertaken on both national and regional level. A key example of the regional regulation is the EU-level European Court of Justice 2017 ruling (Judgment in Case C-434/15), on the status of applications that provide intermediation service in the field of passengers’ transportation, such as Uber. According to the Judgement, services provided by such applications must be regarded not as ‘an information society service’ but as ‘a service in the field of transport’. This ruling became important source of law for the EU-member states, including Eastern European. It allowed them to extend the scope of the existing sectoral (transportation) laws to Uber-type applications. For example, Slovakia’s court referred in its decision to this European Court of Justice 2017 Judgement, ruling that Uber should be viewed as a transportation company and hence comply with the existing laws on professional licensing of drivers and safety requirements for the cars. (Reuters, 2018). Hungary amended the existing law on transportation to bring Uber-type companies under the scope of the existing regulations. Such legal changes meant that all drivers had to comply with professional licensing and insurance obligations. Some other non-EU countries of the region, such as Belarus and Serbia, adopted similar modifications. However, some other countries adopted different national responses to the unfair competition claims against local app-based platforms (Table 3.2). The Baltic States responded to unfair competition complaints by putting everyone on an equal – liberalized – ground, but in exchange for tightened obligations to declare activities and pay taxes. For example, in 2017, the Estonian parliament passed a law that outlines the conditions of providing transportation services mediated by digital electronic platforms and regulates their position to traditional taxi service (National Training Fund, 2017). As per this law, neither traditional taxi drivers nor new digital providers have to comply with the previously required conditions of professional training. Rather, they have now an obligation to ensure their own training provision to their drivers. In addition, the Estonian tax and customs committee (EDCR) initiated a pilot project for the transportation sector, in cooperation with Uber, to connect the digital payment system of the digital transportation provider directly to the EDCR digital tax system. This has a double effect of reducing undeclared payments and substantially decreasing the administrative burden for service providers (ibid). In a similar spirit, Lithuania amended its Road Transport Code in 2016. New provisions allow passenger transport to be organized by both natural and legal persons in both taxi and ordinary passenger cars. In return, the passenger transporter must provide the passenger data to the road transport control authorities, declare the service to the municipal authority, and declare the income received from these activities to the State Tax Inspectorate. The requirement for passenger transport operators to obtain a permit to carry passengers has disappeared from the Code (Verslo Zinios, 2017; OECD, 2018b). Latvia amended its Road Transport Law in 2017 (with effect on March 2018). On the one hand, the Act establishes equal licensing requirements for any personal transport-operating entity. The Act and its accompanying secondary legislation provisions also oblige “ridesharing” apps to accept only electronic payments, and to register in the Enterprises Register as legal entities providing full accounting of business activity. On the other hand, the Act liberalized and simplified the process of obtaining licenses (OECD, 2018a). In case of property-rental apps, there was also a range of national responses, similarly framed around the issue of fair competition, taxation, and bringing workers under the scope of existing regulations in the tourism and accommodation sector. Differently from Uber, however, some of the regulations may be implemented at the city and district levels. Some additional regulations also come in response to the price escalation of rented properties and a resulting depopulation, disturbing neighbors and pollution. For example, in Prague (Czech Republic), municipal authorities can charge private hosts a fine for failing to register with their local tax office. Despite this tax regulation, municipal counselors are also calling for a more global and comprehensive approach to regulating the work of mobile apps. In 2018, they launched a petition urging authorities to address the unfair competition in the hospitality sector (Kafkadesk, 2018). If, in response to this, legal changes will be implemented to classify hosts of Airbnb and other similar platforms as accommodation services, the hosts will have to comply with the Trade Licensing Act. They will be under obligation to declare performance of a trade to the Trade License Office and paying an administrative fee. Failure to do so would constitute an infraction and the offender would faces a fine. Providers would also have to levy radio and television broadcasting fees. In addition, hosts would need to report to the foreign police department that a non-EU national has been provided with accommodation, within three working days after the provision of accommodation, and to maintain a guest register. Failure to do so would constitute an administrative offence subject to a fine (Ecovis, 2019). In Hungary, some municipalities of the central districts of Budapest amended their local townscape regulation. Pursuant to the amendment, unless a local condominium's bylaws explicitly allow the registered use of a given unit to be changed from "residential" to "temporary accommodation", such a change is not permitted. This is seen as an obstacle for private hosts, as in the absence of explicit permission in the bylaws, they may not be able to start their Airbnb business. The Supreme Court of Hungary ruled that a condominium is indeed free to prohibit or restrict other uses of units to ensure uninterrupted residential use. To enforce compliance with the prohibition or restriction, the condominium may sue a private non-complying host (Schoenherr.eu, 2018). ### 4.4.2 Regulatory responses to online work through online platforms Online work through online platforms faced a somewhat different set of issues. If income under-reporting and tax non-compliance are important, related concerns are also raised with respect to the possibility of transferring money from abroad altogether, and administrative registration of “online freelancers”. As of 2019, no regional or international regulation seemed to address these issues. On a national level, attempts to formalize online “freelancers” by improving their tax compliance are found in Ukraine. Here, the 2016 law (No 4496) marked the first step towards decreasing administrative barriers for the “export of services” and somewhat simplified the legal procedures for doing business of online entrepreneurs. As such, this law was a move towards legalizing online freelance activity for foreign clients, which previously completely fell outside the scope of legal regulation (Ain.ua, 2017). Still, many freelancers struggle to understand cumbersome administrative rules and monetary regulations for cashing money for their work from abroad. More regulatory progress is expected in the nearest time in the area of foreign currency regulation, to allow for money transfer through intermediaries (and online platforms are often seen as such), and to abolish the obligation to immediately convert foreign currency into the local currency in case of direct transfers from clients. Those regulations are expected to reduce the practice of transferring online earnings to foreign, rather than Ukrainian, banks, with their subsequent cashing abroad. # Instead of a conclusion: the future of digital work and the challenges of its regulation The literature reviewed in this paper suggests that we are still only at the beginning of the digital transformation of the world of work. New online platforms and apps mushroom in new sectors and occupations. Many of them have novel business models, which sometimes take advantage of the existing legal loopholes and which often require regulatory responses. If regulatory responses varied across Eastern Europe, most of them were made mainly at the national level so far, and concerned mainly work through local apps-based platforms. Digital work through new technologies requires a lot of ingenuity from the regulator. The ingenuity starts with understanding the differences between the digital work and the traditional work. What types of problems are new, and what problems are actually the rebranded old problems? Can existing regulation be applied to the rebranded old problems? What new regulation is most appropriate to new problems? But even when these questions are answered, the main difficulty is on the enforcement side. Labour inspectorates and tax authorities may not necessarily have the legal mandate, or the means, to effectuate the necessary and timely control. In case of detected problems, the legal responsibility of proof is often with the worker, rather than with the app or the platform. These general problems are complemented by several specificities of regulating digital work. First, owners of the apps usually have a strong lobby and are exercising pressure on the governments and the media to adapt the existing laws to their own business models on the grounds of “modernity” and “progress”, and employment creation. For example, in Slovakia, even before the court ruling on Uber practicing unfair competition, Uber drivers technically fell under the scope of personal transport regulation. However, they did not comply with the requirements to visibly mark “Taxi” on their vehicles, while the police had the mandate to only control cars with such marks (Sedláková 2018, Meszmann 2018a). When the Slovak Trade Inspection stepped in to control Uber vehicles in 2016, Uber simply blocked their access to the system after several controls. It is in response to these actions that traditional taxi drivers filed a lawsuit claiming unfair competition by Uber. In March 2018, district Bratislava Court I ruled in favor of the claimants. Uber was forced to suspend its services (ibid). But Uber remained in the local market and joined the National Union of Employers, thus technically now being one of the players in the national social dialogue (ibid). Second, in case of enforcing tax compliance regulation, private privacy laws and the fact that some apps’ headquarters are located abroad, may be an obstacle. In fact, platforms rarely publically reveal the detailed information about their users, such as their exact number, their exact earnings, and the nature of activity (whether it is systematic or ad-hoc). Countries needing this information to enforce tax compliance have to request this information from the platforms on a case-by-case basis. For example, in Slovenia, by 2017, it was recognized that Airbnb networked business had all characteristics of hospitality business which has been already regulated by a dozen of legal acts in the country (Zupan Korze, 2018). It was thus decided that “the problem is not in regulation, but in strict implementation of the regulation” (ibid). Hence, it was up to tax authority and inspectors to better supervise AirBnB short-term home-rentals in Slovenia and individuals operating through AirBnB to respect relevant regulation and pay taxes on their activity in the tourism and hospitality sector. This position was officialized by the Ministry for tourism in 2017. Moreover, the Ministry of finance requested and received the data from Airbnb headquarters about Airbnb hosts in Slovenia and their earnings. It called the hosts on the Airbnb and other accommodation platforms to self-declare their tax obligation and to follow other rules regarding short-term rental activity, under a threat of being charged a fine (ibid). But such cooperation between platforms and government authorities is not systematic. For example, Uber and Yandex.Taxi rather refuse such collaboration, claiming that the revelation of individual data may contradict individual data-protection regulations. For online platforms, either workers or clients may hide behind a virtual name, or a digital personality. The nickname may mask the real person (even though an IP address may be identified, and even if a real name may be requested in order to cash earnings); an algorithm may be used to assign a nickname to a user. This means that a proper identification of a non-complying individual may involve different types of law, coordination of different agencies, and possibly violation of privacy data of the individual in question and of other individuals (Talapina, 2018). There is also a mushrooming of different modes of digital work. One example includes work through “closed” online platforms, in which online work is dispatched to a restricted circle of users who joined the platform by invitation of the platforms’ owners (Aleksynska, Bastrakova, Kharchenko, 2018). Another example is online intermediation chains. They emerge when a worker accepts a task only to outsource it (repost) further. Work may be dispatched either to a team of worker(s) located in the same country and managed by the first worker, or it may be simply reposted on another platform and picked by worker(s) located in yet another country. This complicates regulation, as it is no longer clear what roles each individual has in the process. In countries adopt regulations that lack compliance incentives, the risk is that platforms, clients, and workers will find creative ways of avoiding them. Workers and clients may switch to direct contacts, exchange work tasks by email or through social networks rather than through platforms, or switch to using encrypted platforms, making law enforcement impossible altogether. These challenges mean that national regulators have to be increasingly vigilant, inventive, and reactive in their policy responses. The designed policy tools need to have a strong self-enforcing component. Increasingly, there is also a need for coordinated policy responses across different ministries and agencies. Lastly, the paper has shown that there is an increasing need for policy dialogue and concrete policy measures at the regional and international levels. # References AIN.UA, 2017. 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# Acknowledgements

I am particularly grateful to Uma Rani, Hannah Johnston, Valerio De Stefano, Andrey Shevchuk, and two anonymous referees for their very helpful comments and suggestions. All remaining errors are mine.

1

“Micro-tasks” platforms are those that mainly specialize in tasks of very short duration, which generally also require a low level of skilll (ex.: product categorization, “liking” a page) . Some platforms, such as AMT, are famous for offering mainly micro-task work (see Berg et al., 2018 for more examples). « Macro-tasks », in contrast, require considerable time and skill for their execution (ex.: website development). Some authors also speak about complex tasks, which are similar to continuous relatively high-skill work performed by firm employees or by a specialized contractor (Felstiner 2011).

2

Some of the online platform work serving international markets, especially related to microtasks, can also be precarious. Here, however, we speak of general trends observed in the region.

3

The degree of informality varies, however, within the region. For example, according to the estimates of Schneider et al. (2010), the size of the informal economy increases as we move further east: throughout the 2000-es it was the lowest in Central and Eastern Europe and the Baltic States, and the highest in the European CIS and the Caucasus.

4

This includes freelancers from all former Soviet Union countries.

5

Some observers worry that there is a double-counting of freelancers on the platforms. While this concern is legitimate, research shows that, in Ukraine, workers operate through over 40 platforms, but on average, each worker is registered on two platforms only (Aleksynska, Bastrakova, Kharchenko, 2018). This is because maintaining an active account can be costly for a worker: it requires inputs into creating an attractive account, performing work and gaining reputation. In contrast, the true concern is that many of those who register on a platform remain, in fact, inactive. Nevertheless, these numbers show the interest in this type of work.

6

Representative sample of adult Poles who would consider engaging in such activities.

7

Sample of survey respondents who declared they had conducted work using an on-line platform in Poland in the past. In addition, in the same survey, 15% intended to continue to undertake such work in the future (ibid).

8

It is a situation, in which there are various indications of an existence of an employment relationship between a worker and a client, even if (one of) the parties claim that such relationship is absent.

9

There is also the 2016 Eurobarometer survey dedicated to this question. However, a comparison of results suggests that there could have been a change in the methodology and / or of sample between the two waves. For this reason, only the latest results are reported here.

10

Including taxi and delivery services, as well as ‘household services’, which cover ‘occasional, unscheduled work in other people’s homes (e.g. plumbing, repair of appliances, electrical work, carpentry)’; ‘regular, scheduled, work in somebody else’s home (e.g. daily or weekly cleaning, babysitting, gardening)’; and ‘personal service work (e.g. hairdressing, massage, manicure)’ (Huws et al., 2019).