Gig Economy

Definition

This entry presents the history, geography, business, regulations, and the roles of gig workers, platform/algorithms, and employers, focusing primarily on the USA and the EU. The gig economy is informally referred to also as the fourth industrial revolution or the 1099 economy, emphasising sharing, freelance, or platform work; it is a complex and changing business model and regulatory environment. In practice, the gig economy refers to a tripartite relation between workers, platforms/apps, and employers, leading to a two-sided market, where algorithms match supply and demand for paid labour and clients. It is only recently that the gig economy has started to be conceptualised, and its implications, challenges, and impacts are captured in economic law and society, including the power dynamics related to the interplay between economics, technology, regulation, and communities. Conceptually, the gig economy is important, as small paid work has always been present in society for all types of workers and beneficiaries. This new business model of on-demand work has some perceived advantages, such as freedom of work, under-regulation, efficient use of capital, driving down costs, and improving services. However, there is a dualisation of anti-power between workers and non-employers that may lead to precarious work, less free workers, and shadow corporations that distort the market using game changers like digital management algorithms. Currently, the size of the gig economy comprises 154–435 million gig workers out of the world’s 3.63 bn workers, with a market size of USD 557 bn, and is still expanding.

1. Introduction: Defining and Regulating Gig Economy

The gig economy, also referred to as the fourth industrial revolution, 1099 economy, on-demand economy, app economy, platform capitalism, or platform work, with built-in algorithmic management tools, is described by short-term tasks and the lack of a common workspace. It involves three types of market participants—workers, beneficiaries, and digital platforms—the latter of which facilitate communication via secure channels [1].

Accordingly, the gig economy consists of a tripartite relation between workers, platforms/apps, and employers, leading to a two-sided market where algorithms match supply and demand for paid labour and employers. Workers are colloquially known as freelancers who undertake work by choice, ranging from task-related jobs for decentralised beneficiaries, varying from food delivery and housework to online professional consulting or asset sharing, like renting an apartment. The platform/app intermediary matching algorithm performs its part to keep the market running. Beneficiaries are companies or persons who pay for the work received. Interestingly, some market participants in the gig economy can be registered as both freelancers and clients, oscillating between the two roles, leading, in a way, to prosumers [2].

There are four sectors in which the gig economy normally activates: asset sharing services, like home sharing and car sharing, with platforms like Airbnb; transport-based services, like ride sharing, Uber, and Blabla Car; professional services, such as business work, micro-tasking, writing services, and freelancing platforms like Upwork and Fiverr; and handmade goods and home services, such as babysitting, tutoring, Care.com, and Etsy [3].

This new business model of on-demand work has some perceived advantages, such as freedom of work, under-regulation, efficient use of capital, driving down costs, and improving services. However, there is a dualisation of anti-power between workers and employers, leading to a third business driver, namely, platforms. This situation may lead to precarious work and big non-employer entities that distort the market by challenging traditional market rules, introducing new types of market players, and altering the business landscape via digital management algorithms [4].

It is important to conceptualise the gig economy regardless of its form, as small paid work has always been present in society for all types of workers, including high-skilled or low-skilled individuals and all sorts of beneficiaries, natural persons, or companies. However, it is only recently that the gig economy has started to become a conceptualised phenomenon, considering its implications, challenges, and impact on the economy, law, and society.

Despite being a large umbrella concept, gig economy businesses are not a one-size-fits-all concept. It can be generally argued that platform work is a part of the gig economy, though the relationship between the two is more complex. The literature uses the terms interchangeably with certain differentiations in terms of work characteristics, work management, and motivations. The focal point can be the worker, the mediating platform, the employers, or the sharing part, prompting scholars to develop different terms to define the gig economy in a targeted way [5].

Furthermore, different countries highlight specific nuances of the gig economy according to the local culture, local understanding of the phenomenon, and specific challenges and needs. While there are various classifications, including misclassifications and non-classifications, the gig economy and its variations focus on the same theme, forming a classification of its own that does not fit neatly into traditional boxes [6].

For instance, the European Union (Directive 2024/2831) [7] put forward the following characterisation, addressing platform work and not gig economy: “work organised through a digital labour platform and performed in the Union by an individual on the basis of a contractual relationship between the digital labour platform or an intermediary, and the individual, irrespective of whether there is a contractual relationship between the individual or an intermediary and the recipient of the service”.

In parallel, in the USA, legislation concentrated on gig economy terminology in a rather cross-sectional way, covering worker classification, benefits, and algorithmic transparency, with some states like California’s Assembly Bill 5 addressing it in a more specific way, generating certain resistance at the time it was proposed [8]. The Gig Economy Act of 2025 was created “to protect the gig economy and small businesses that operate in large part through contractor services from the threat of costly class action litigation, and for other purposes” [9], preserving the status quo in many ways.

A less legal, yet comprehensive, definition can be found in the Cambridge Dictionary (2020) [10] where the gig economy is “a way of working that is based on people having temporary jobs or doing separate pieces of work, each paid separately, rather than working for an employer”.

Academically, scholars like Laín [11] have highlighted the informative value of these multifaceted characterisations; however, despite their accuracy, the diversity of the economic phenomenon captured in different frameworks, like pragmatism or more analytical explanations, makes common usage of the gig economy colloquially understandable but conceptually weak, with different benchmarks and methodologies. The variance is so large that the gig economy can be considered either as more inclusive capitalism or part of a post-capitalist economy, according to the different weights assigned to nature, money, and labour power.

Currently, there are some risks associated with the future of the gig economy, such as a new type of materialism that is post-humanist and ethical concerns about worker protection, as autonomous human subjects may lose agency to technological factors, by choice, under governmental regulation [6]. The gig economy is considered by some scholars to be the next step in the capitalist process and a capitalist mode of production based on the financialisation of big data, with new technologies, business models, organisational forms, governance, jobs, skills, and modes of capital accumulation. Srnicek [1] argues that platform capitalism “will be forced either to develop novel means of extracting a surplus from the general economic pie or to fold their expansive cross-subsidising monopolies into much more traditional business forms”, meaning that, eventually, the gig economy will become business as usual, connecting also to new technologies, climate change, etc.

According to some views, the gig economy can be seen as an advancement in the neo-liberal capitalist agenda; however, considering leftist views, the gig economy is just another way of value extraction, regardless of whether it is supported by normative politics. Regardless, the gig economy should be analysed using an institutional approach due to its size, considering market efficiency (peer-to-peer efficiency).

2. Short History

The idea of temporary work originated in the UK in 1650, but it only gained recognition and success towards the end of the 19th century via temporary recruitment agencies [12]. For example, after the 1906 San Francisco earthquake, a temporary employment agency was founded to supply provisional labour for the city’s reconstruction and offset the loss of employment caused by the natural disaster. The term “gig” economy originates from the arts world, in the 1900s, when jazz musicians were paid for individual performances, known as “gigs” [13]. Later, the term gig economy became extended and applied to all types of short-term jobs and projects. However, the term persisted only linguistically, with work on a one-off basis being more of a reminiscence, and gig workers nowadays choosing this type of employment longer term, seeking continuity of work and stable income and trying to avoid precarity.

As a matter of intellectual history, tracing the concept backward from its current development rather than its original period shows that temporary work agencies emerged during the Great Depression to help address the situation, including short-term contracts with the governmental authorities. The post-war boom also played a part in the development of the gig economy, as the world saw, for the first time, more work than workers, and there was a necessity to fill in small yet increasing gaps in labour. It can be argued that booms and busts made the gig economy develop for opposing reasons in very different periods of time and contexts. The opposite of the post-war boom period happened (again) in the 1970s, when labour issues and work stoppages were experienced due to economic struggles and limitations in resource allocation of work. A term used back then, which has survived to some extent today, was contingent workers. Semi-permanent employees became common, filling gaps when needed, such as during holidays or maternity leave, while the business continued to run [14].

The 1990s and the spread of the Internet made both informal and formal temporary jobs more feasible. Craigslist united demand and supply for projects. Furthermore, Simos Solutions and other temporary work agencies played a role in assigning customer-focused and results-oriented employees [14]. It has to be noted that for a period of time, the gig economy and temporary work were conflated, with temporary work effectively serving as the gig economy of its time.

Ultimately, the late 2000s shaped the gig economy to what it came to be today, as platforms such as Airbnb, TaskRabbit, Upwork, Uber, and Lyft revolutionised business practices and aspects of everyday life, such as transportation, travelling, and access to easy opportunities, posing regulatory challenges and forming new types of competition and business models; these developments separated conceptually gig work from temporary work provided by placement agencies, with the main difference being looking for work (self-entrepreneurship) vs. asking for work (employee mentality).

In the 1990s, only 10% of the workforce was involved in the gig economy in various forms; nowadays, the number has increased to 12%, possibly as an effect of the 2008 crisis, leading back to the argument that booms and busts fuelled the gig economy, due to low entry barriers, more income wanted/needed, income potential/volatility, and desire for bridge employment [15].

The financial crisis of 2008 may also explain why many companies within the gig economy created in the 2000s only started to rise almost a decade later, with 1 million workers in 2015 in the USA alone [16].

The World Bank and ILO estimate that, in 2023, there were about 154–435 million gig workers out of the 3.63 bn workers in the world. For clarification, not all of these gig workers are active at the same time. While the number of workers, as well as the definition of gig workers, varies across countries for reasons presented in the next sub-chapter, the market is estimated to reach 4–5 trillion dollars by 2040, with places like India and SE Asia being increasingly important [17,18].

3. Geography of Gig Economy

For a clearer understanding, it is worth separating workers, platforms/apps, and employers. However, it is important to consider the annihilation of space in the digital economy with global marketing and the “flat world” or large global margins [19]. North America and Europe together represent the vast majority of the gig economy, with India and Australia coming up strong from behind.

In terms of platforms, official data from the EU show that there are about 500 main ones worldwide, with the European Union hosting 77%, with an extra 8% coming from the rest of Europe, while the US accounts for only 12% and the rest of the world accounting for only 3% only, mainly from Asia and Oceania [20]. Research by scholars like Parker [21] considers the opposite: that North America is the main home of platform work due to Google, Apple, Netflix, Facebook, and so on measuring more than 1 billion dollars in market capitalisation; Europe ranks third, with SAP and Spotify as major platforms, but they only have a quarter of the USA’s value. Hence, the gig economy or platform work does not necessarily have a common definition or methodology to collect and analyse data, especially as it is decentralised, with each continent presenting its own advantages and challenges. This should not be confused with biased research, as it reflects data availability and different methodologies, such as dividing freelancers, crowd workers, and home deliveries, or their combinations, and whether self-employment is counted, according to different legislations. In this respect, Srnicek [1] identified five types of platforms, which will be presented in the Platforms and Digital Management Algorithms Section of this entry.

In terms of the revenue of the gig economy, North America and Europe account for about USD 400 bn, while the revenue from India is only 1.54 bn, according to a 2025 report cited by Kandhari [17]. In terms of people’s earnings, German workers collected the most, 1 billion euros, followed by France (EUR 0.7 bn) and the Netherlands (EUR 0.4 bn) [20]. Other research, like that of Graham, Hjorth, and Lehdonvirta [19], revealed different results, as low-income countries comprise the vast majority of workers on the platforms.

India’s labour market faces a double-bind situation. With 660 million workers (and possibly more, as some rural workers are outside any formal regulatory oversight), the gig economy comprises a vast pool of both low- and high-skilled workers. The gig market in India is currently valued at half a billion USD and has about 8 million gig workers, with less than 1% being women. The market is expected to be around 2 bn USD by 2032, and it is predicted that, by 2047, there will be 62 million gig workers in India. Currently, the majority of workers are in sales, transport, IT programming, and manufacturing services, working for companies like Dunzo, Uber, and Swiggy, with some of them being international, while others are local [22].

While remote work solves some employment and payment issues for workers with offshore clients, the legacy of economic inequality persists, with large digital and global margins that do not necessarily influence the economic margins. Channels and connectivity engage people and companies in affordable contracts and digital production or even physical work, like in the case of food carriers or drivers; however, local rates remain important, along with perceived professionalism for outcomes from a certain geographical area [19].

Geographical considerations do not provide enough clarity about the gig economy, as it is cross-sectional, is digital, and has a rapid dynamism. India is growing fast, and it is followed by developed countries like China, South Korea, Japan, Argentina, Brazil, and some African countries. Rapid urbanisation, population density, access to the Internet, and, to some extent, innovation help to explain the gig economy, contrasting with Graham [19] and other common (mis)perceptions.

4. Workers

4.1. Types of Workers in Gig Economy

The World Bank and ILO estimate that, out of the total global workforce of 3.63 bn employees, between 154 and 435 million are gig workers, and up to 1.74 billion are self-employed [23]. What differentiates gig workers from non-gig workers is whether they employ others [24]. The differences arise from varying methodologies, legal distinctions among countries, the internal categorisation of gig workers, and how they are counted. In terms of gender, gig workers are 54% male and 46% female; they are also divided by generations: millennials (27–42) comprise almost one-half, Generation Z (18–26) one-third, and baby boomers (51–79) 15%. For instance, in the USA, there are between 57.3 million and 76.4 million freelancers. Gallup considers that they represent 36% of the US workforce working a primary or secondary job [18,25].

There are different labels for gig economy workers—independent worker, freelancer, crowd worker, or self-employed—with some typologies specific to the gig economy: home delivery, rideshare, consultants, etc., with different statuses according to different legislation over the Atlantic and Pacific oceans. Status is important due to individual rights, taxes, and one’s identity. At times, work on platforms can be misleading in terms of rights and obligations, even misclassifying workers.

From the perspective of the gig economy, one easy aspect to classify is part-time and full-time workers; Kurian and Madhavi [26] identified two types of gig workers, according to the type of income they aim for:

• Primary income;
• Supplementary income.

These two categories have different motivations and characteristics, though the categories are not homogeneous themselves. Furthermore, not all gig workers are remote workers, despite the original contracting being carried out via a digital framework. Working gigs as a primary job is a matter of choice for personal and professional reasons, like taking control of one’s time and chosen projects. Within this category, some might do it out of necessity, like immigrants with an unclear work status. In the case of supplementary earners, some are casual earners who want to boost their earnings, while others do it because there are financial constraints that prompt them to obtain another source of income [27,28].

While this separation is useful, there are more differentiations among gig economy workers, and additional challenges remain. Vallas and Schor [29] identified five types of workers:

• Highly skilled employees performing specific jobs for substantial pay.
• Freelancers who offer professional services with high technical skills, securing a stable income as firms outsource services.
• Freelancers who engage via platforms, like food delivery, home repair, and temporary on-demand jobs.
• Freelancers who undertake jobs AI cannot do yet, like micro-tasking, editing, and validating.
• Aspirational workers or freelancers who hope to gain attention and earn income.

One important characteristic of gig workers is the revival of Taylorism, mainly due to micro-tasking and algorithm supervision [30,31]. The next level of scientific management is expected to develop due to algorithms, optimisation, performance criteria, and standardisation of micro-tasking. Frederick Taylor’s characterisation of Taylorism was the establishment of a multitude of specific rules for workers and managers with stopwatches to record work and performance, which is especially important for short-term projects [19,32]. Yet, research shows that it is difficult to calculate related KPIs like employment productivity and whether the gig economy has a higher return on investment compared to traditional work, although it generally looks more affordable [33]. According to another scholar, Roedl [34], the gig economy is an example of post-Fordism, mainly due to its solution-oriented approach and decentralised structure.

4.2. Legal Classification for Workers

For these reasons, among others, outside of the EU directive on platform workers, individual European member states have their own internal legislation regulating gig workers up to the point they are no longer considered gig workers. For example, France regulated the gig economy in 2017, 2018, and 2019, making gig work synonymous with being self-employed. This comes with a whole set of rights and obligations at both ends: companies have to handle work accidents, provide professional training, and give the right to strike. Gig workers became actual workers [8,35]. Other countries, like Australia, despite classifying gig workers as independent workers, acknowledge some ambiguities [23].

In the USA, it is generally not allowable to classify workers as independent workers, thus maintaining a distinction, though labour policies specific to certain categories of gig workers exist, especially for drivers, who temporarily became employees [36].

The USA’s Gig Economy Act of 2025 was created “to protect the gig economy and small businesses that operate in large part through contractor services from the threat of costly class action litigation, and for other purposes” [9]. Some tests to determine status exist, like the ABC test and economic reality tests, taking into consideration full control of work, hours worked inside or outside the working programme, and tax returns [37]. Additionally, gig economy workers are associated with specific North American Industry Classification System (NAICS) codes, such as like ride shares 485310, food delivery services 492210, dog walking 812910, and photography 541920; have to use IRS forms like 1099-MISC, 1099-NEC, 1099-K, and 1040 forms; and report as independent contractors [38].

Uber’s CEO declared that “our current employment system is outdated and unfair. It forces every worker to choose between being an employee with more benefits but less flexibility, or an independent contractor with more flexibility but almost no safety net” [39]. The perspective from the other side, identified by one researcher, is that drivers choose this way of work, one declaration being: “I would quit if they tried to make me an employee, because I value my freedom as an independent contractor too much”, providing an example of pro-gig work discourse [4].

In California, Assembly Bill 5, which addresses gig workers, has created a slightly different situation compared to the rest of the USA, as companies that employ independent contractors are required to grant employee status, with some exceptions [40].

4.3. Precarious Work

There are pros and cons related to the above-mentioned categories, including the type of income, type of workers, and legal classification. In terms of advantages, the gig economy means more flexibility, income, time, and even specialisation. In terms of disadvantages, there is job insecurity, stigma in certain traditional cultures, and possible exploitation [3]. Thus, a paradox is observed, as there are advantages to gig work; however, gig work comes with job insecurity. Furthermore, a global oversupply of workers compared to demand can be seen, leading to another challenge: gig workers’ lack of bargaining power compared to employers. Laín, framing these arguments in Karl Polonyi’s substantivism, argues that “the fact that an economic system is more collaborative and provides more scope for communities does not necessarily entail a fairer economy. Rather, its fairness is subject to the degree of commodification to which the natural resources, medium of exchange and employed labour force are subjected” [11].

Due to remote geography, workers from countries with high salaries compete with workers from poorer countries, who are willing to accept even USD 1 for certain tasks [41]. At times, because workers have to work for clients in different time zones, their social life may be affected due to different sleeping schedules.

This leads to the point of fair work, conditions, management, and obviously pay, as there is a difference in bargaining power among workers, platforms, and employers. The dynamics and structure of power may lead to precarious work, a concept coined by Pierre Bourdieu in 1963 to describe casual work in Algeria, implying vulnerability, insecurity, and instability. At present, a structural vulnerability may exist due to an arbitrary trap that captures workers in a relationship of domination by both algorithms and employers.

Kalleberg [42] characterises this and defines it as “employment that is uncertain, unpredictable, and risky from the point of view of the worker”, narrowing down precarity to a certain class related to modern capitalism. Therefore, precarious work can be an effect but also a context, not necessarily a job or a task performed. Precarious work is an organising tool governing and limiting labour options associated with the uncertainty of task allocation and unstable and fluctuant income, leading to emotional and psychological effects [4,43].

One possible explanation may be the zero-hour contracts related to on-demand work, which are unpaid until work is required. Small, discrete jobs may have some predictability and relate to the willingness and effort of the worker to perform tasks that are not nearby, such as in the case of food deliveries, which add extra costs to drivers. For some gig workers, the gig economy might not be a choice but a necessity [27]. They would prefer another type of employment that is unavailable at the time, with a career development plan, increasing skills, knowledge, and enjoyment. From this perspective, the gig economy for workers may look like forced entrepreneurialism, associated with risks and a search for money-making opportunities.

In Africa, the situation of gig workers is different compared to that in developed countries. Yet, they still receive social recognition, though not necessarily a positive view. For instance, in more traditional cultures like Nigeria, freelancers might be mistaken for scammers [31]. It is estimated that 58% of the workforce is employed in low-skilled jobs, and there is even a mismatch of skills. This autonomy of work is not as straightforward as imagined. Workers have to maintain high reputation scores, and freedom is actually dictated by the hours you need to work—sometimes not in your own time zone—along with platforms’ strict rules [41].

In the UK, gig economy workers are united in trade unions, like the App Drivers and Couriers Union; similarly, in Australia, New South Wales and AirTasker signed an agreement for better integration of workers [31,44].

Accordingly, gig workers should not be considered passive players or just “mechanical” problem solvers; they use the algorithm for their own advantage and to optimise time and earnings [34]. They have space for choice, from deciding whether to accept a task to engaging in collective agency through forums and social media groups. Newlands [45] observed how workers coordinate and react to platforms and employers, trying to manipulate algorithms, identify better opportunities, and create networks for their own advantage. Pilatti et al. [46] mention that regulations are also an important aspect protecting workers from precarity, as there is a stark balance of power between workers and platforms; collective agency may not be strong enough.

4.4. Gig Workers and (Self-)Entrepreneurship

Outside precarious work, the gig economy can also be an advantage for workers. Flexibility and the possibility to choose projects may be the most common aspects. In the USA, the income of gig workers varied from a mean gig income of USD 10,000 in 2012 (when only about 37,572 workers existed, and about 12% of them were earning a gig income more than USD 20,000) to USD 14,000 in 2021 (when almost 5 million workers were active, the mean income increased to 14,000, and about 18% earned more than 20,000, which still is under the national average per capita) [16]. Despite this financial aspect, the number of gig workers in the USA has gradually increased, making money just one of the many variables to consider when choosing gig work.

While moving beyond gig work but not the gig context, some former gig workers create firms, operating both inside and outside of the gig economy. Compared to non-gig workers, former gig workers are more likely to start companies in personal services, trade, arts, and media [16].

Entrepreneurship derived from the gig economy is based on the classical values of traditional entrepreneurship, mainly risk and uncertainty. Keeping customers happy and satisfied is one way to keep up with algorithms and keep the business running [34]. Despite this link between gig work and entrepreneurship, these two should not be confused, as precarious work and working out of necessity may situate gig workers and entrepreneurs at very different ends of the financial spectrum.

The similarities between gig work and entrepreneurship are not accidental; they are cross-sectional and indirect, related to the nature of the job performed and the structure of the labour market. Denes et al. [16], researching US tax returns, showed that the gig economy fosters a mindset conducive to entrepreneurship, providing skills and experiences that facilitate the management and running of a business.

5. Platforms and Digital Management Algorithms

Platforms are a form of economic value creation and value consumption, democratising consumption and leading to a different type of interaction compared to traditional pipeline models [21]. A keyword for platforms in the gig economy would be third-party intermediaries, as platforms are considered the very heart of the gig economy and the dominant—but not principal—market player. Platforms match workers with employers, holding the upper hand in their relationship via the market conditions they created, as well as via algorithms, data analysis, and artificial intelligence usage, creating a mix between value creation and value extraction.

In his book Platform Capitalism, Srnicek [1] identified five types of gig economy platforms:

• Advertising platforms like Facebook and Google, which also make use of user data;
• Cloud platforms like Salesforce, which combine hardware and software usage;
• Industrial platforms (e.g., GE and Siemens), changing infrastructures to more Internet-friendly processes;
• Product platforms (e.g., Spotify) that transform traditional goods into a service;
• Lean platforms (e.g., Uber and Airbnb), which change business models and operate on asset-light ownership.

While some platforms address more B2B aspects, other platforms concentrate on B2C, covering asset sharing to digital services, both tangible and intangible economy, with amateurs, peers, semi-professionals, and professionals working and competing, leading to unclear models and overlap [47].

Platforms are not always successful in sharing the economic pie of the gig economy. There were cases of closed businesses or mergers for competitive advantage. A Fairwork report in 2025 [48] disclosed that 4/16 gig platforms do not provide constant work due to differences in supply and demand, circling back to the precarity argument surrounding gig workers.

Green and other scholars [49] argue that there are different types of risks using the PESTLE framework: Political, Economical, Social, Technological, and Legal. There is not much regulation to address platforms and intermediaries, except taxation and the work aspect in platform work (see EU Directive 2024/2831) [7]. Labour laws also cannot necessarily keep up with technological development and associated business models. Practical problems can exist on both sides, like when employers choose subpar contractors not by choice to reduce costs but by coincidental selection. The other side of the coin is that freelancers can encounter risks when choosing a job that was misadvertised, or they were just too bold and self-confident.

Challenges exist, for example, when calculating delivery time correctly or “recruiting” the right person to carry out the job. This is important, as gig workers face sanctions if the task is not completed on time or refuse orders if their life–work balance is destabilised. They adjust schedules, improve performance, modify prices accordingly to the market conditions, and strategically respond to high/low demand and supply with dynamic pricing. Even so, Alauddin and other scholars [50] argue that “digital platforms do not provide adequate ‘reward versus effort’ or ‘fair compensation’ for investments in time, costs, and creative skills, forcing gig workers to make their investments”. This leads to a take-it-or-leave-it scenario, which is effectively a zero-sum game, especially for gig workers.

Upwork is an example of a successful platform with over 18 million gig workers registered, earning an average of USD 39 per hour (only 1/800 workers make more than 1000 a month) and generating USD 689 million for Upwork itself in 2023 [51]. Upwork addresses an issue in the market, as professionals were hard to find, while professionals could not find jobs at times due to various reasons like overqualification, human character, and work permits. Online outsourcing made human resources more reachable; however, it is also a different type of competition between people who do not even know each other, situated in different countries, age groups, etc. As platforms and intermediaries, Upwork, Fiverr, and others assume little to no liability for the parties contracting with each other, focusing on ensuring that payment is made because they take a share of the transaction. In this sense, there are warnings against parties contacting one another outside the platform’s communication framework [49].

Fiverr.com is a platform that started with tasks for USD 5—hence its name—and still operates on a low-cost strategy. Therefore, Fiverr was not designed for high-cost work. Compared to other platforms, Fiverr differentiates itself by being characterised as a platform where workers express their skills and knowledge, not employers placing requests, making a clear statement of who they represent [49].

Airbnb serves as a case study, as rental prices increased in Hong Kong simply due to the company’s operations. Liang and others [52] computed that the cost of renting a house increased by about 4%, with a similar rent-to-income ratio. The authors argue that in the current circumstances, the unaffordability of housing is becoming a theme of concern and home-sharing businesses should be regulated—for example, with a quota—to protect the local market.

Other digital platforms that have a clear physical impact on business, like Uber, make use of data, artificial intelligence, and analytics to influence prices based on supply and demand [53]. Uber also lobbied the EU Platform Work Directive to serve its own interests [54].

Algorithms are monitored and used for the platform’s advantage, as the platform is a business in itself. Hao and other scholars [55] argue that close to 1000 unicorn companies are active in the digital economy, having some involvement in the gig economy. Furthermore, the platform economy promotes and creates additional enterprise value and new markets, improving labour and knowledge gaps and prompting technological innovation [56].

Furthermore, algorithmic control over the information channels between freelancers seeking work and the demand side gives the gig economy a complex dynamism, creating a two-sided market [15,21,57]. Algorithms play a dual role, providing both control and flexibility—that is, supporting both promotion- and prevention-focused job crafting—while also acting as cost drivers and influencing predictive behaviour. This is carried out via gamification; that is, by winning points, rewards, incentives, and rankings for stimulation, motivation, and satisfaction. Workers are willing to “play” the algorithm to become more proactive, but negative reviews or poorly performed tasks hinder their ability to secure future work in accordance with their own desires. The difference from a traditional job is that algorithmic management offers options based on big data, predicts incentives, and encourages gig work, fostering perceived independence and self-rule, all as part of the gamification process [11,58].

Understanding this digital coordination leads to a reconfiguration of the nature of work, an aspect that circulates back to the connections between Taylorism and the gig economy. Some research considers that workers are more dependent on platforms and algorithms compared to employers, as data drivers react in opaque ways [31,59]. The same algorithm that provides dynamic pricing also offers flexible work and dead time, inspiring FT’s headline “When your boss is an algorithm” [60].

Platform work in the gig economy comes with challenges; for instance, in the EU, there is specific legislation on personal and non-personal data and its potential use by data intermediaries and data altruism organisations, along with debates on how profit is calculated vs. non-profit, the fees involved, and who can be the beneficiaries [61].

Platforms have also advanced automated payment methods, improving speed and increasing the options available. Full online payment reduces the risk of fraud and theft. For these reasons and more, platforms in the gig economy are not simply third parties or intermediaries; they control the market.

6. (Non-)Employers

The literature on employers in the gig economy is limited and mainly concentrates on employment relationships, labour laws, the shift in focus to cost-efficiency, and challenges to the traditional employment [62]. In this sense, more research is needed to address this literature gap.

Friedman [63] and Ljungholm [64] comment on the situation and argue that gig workers are employees without employers, leading to shadow corporations or non-employers. This may seem unprecedented: employers without employees, “taxi” companies without taxis, or a “hotel” without owning a building, even distorting competition in its traditional sense; however, it can be seen as an advancement in business models.

Employers or clients in the gig economy are not necessarily companies but natural persons who need services. Hence, the terminology used is very unspecific and confusing, as anybody who calls an Uber technically hires a driver for a few minutes as an asset-sharing service. Furthermore, due to certain legal obligations in some countries, platforms like Uber and others behave like employers, giving them a dual role of platform and a sort of employer (see legal changes in the USA, France, and the Netherlands). For instance, a Dutch transportation platform with gig workers in Switzerland was recently ordered by a court to retroactively pay social security contributions to its workers. This is the very responsibility of the employer, making the gig economy relationship between employer and employee very complex [65].

There are cases where companies that hire gig workers for a task drop the term gig workers and shift to more traditional language, such as contractors or consultants. In this sense, Jaishree [66] argues that “there is absence of employee-employer relationships in the gig economy”, with workers remaining self-employed, engaging in contracting and sub-contracting, and involving third parties that constantly change, thus leading to non-traditional standardised ways of work.

Companies may prefer gig workers due to cost-effectiveness, saving money on pension plans, all sorts of insurances, paid leave, and even offices. Another advantage is represented by better access to talent, hiring for specific jobs without a long-term obligation that would impose costs. Covering short-term skills gaps is also another main reason for hiring gig workers. Productivity is an additional driver in selecting gig workers, offering a higher return on investment for a very specific amount of time and helping rationalise the cost of operations [15].

Challenges faced by employers are related, first of all, to HR (Human Resources) shifting from internal communication and employers to external communication, addressing the different needs of contractors. This requires a new approach to workforce management, increased quality assurance checks, and improved customer relationship management (CRM), shifting work from the front office to the back office. Managing gig workers can be hard for a firm, as they are independent and may work for competition, and confidentiality clauses can be difficult to enforce [63,64].

Employers’ obligations in the gig economy vary from country to country due to differences in legal systems [67], mainly on whether an employee is considered to be employed or an independent worker, like in France and the USA, respectively. Additionally, gig economy workers generally see themselves as their own “small bosses” and employers as their clients, which is a shift in perspective.

The gig economy comes with challenges for companies in terms of business models, as the traditional linear pipe model had to be replaced with a triangular platform model, where production and demand meet in the middle on a platform. This comes with other changes, such as a transition from products to services; the emergence of new value ecosystems, ways of attracting finance, and operating models; and a shift in value creation from shareholders to stakeholders [21]. New aspects and comments exist on the rather modern situation where the algorithm is also the boss [60].

7. Conclusions: Regulations, Economics, Workers, Platforms, Employers, and Future of Gig Economy

The gig economy is not a straightforward phenomenon, and even numbers and statistics vary due to different methodologies, legal frameworks, and academic perspectives. The gig ecosystem today is vastly different from the early gigs of the 1900s and the temporary work conditions under the Great Depression, post-war boom, and other periods of booms and busts. It is interesting that both of these two opposing phenomena—booms and busts—generate a need for gig workers, either to cover for shortages or handle generally unwanted work, providing people with work in times of crisis [14]. While temporary work and posted workers were originally similar to the gig economy, they are now two separate concepts: one involves an employee mentality, while the second involves self-entrepreneurship. Furthermore, the original gig was not a continuous activity, unlike in the modern gig economy, where it may also lead to precarious work.

Ultimately, digitalisation and platforms like Uber, Airbnb, TaskRabbit, and Upwork shaped the concept of the gig economy as we know it today, enabling asset sharing in accommodation and transport, digital professional services, home services, and a wide range of micro-tasks. Nowadays, the gig economy is considered by Horowitz [68] to be “the Industrial Revolution of Our Time”, comparing its importance to the shift from an agricultural to an industrial economy.

The gig economy is a model of business with three types of participants—workers, platforms/apps, and clients/employers—with a cross-geographical distribution and various combinations among all market participants.

While platforms are the less obvious players in the gig economy, their algorithms generate reactions from workers and employers in a dynamic regulatory and business environment [69,70]. Algorithms are used for the platform’s advantage, as the platform is a business in itself. Algorithmic management controls the information channels between freelancers seeking work and the demand side, giving the gig economy a complex dynamism and creating a two-sided market, where algorithms play a dual role, both controlling and enabling flexibility for both workers and (non-)employers [15,21,57].

Hao and other scholars [55] argue that close to 1000 unicorn companies are active in the digital economy, having some involvement in the gig economy. The USA and European Union lead the gig economy in terms of platform work, both in market capitalisation and major brands, with India and Australia rapidly catching up. The global gig market is estimated to reach USD 4–5 trillion by 2040 [17].

In terms of workers, in 2023, about 12% of the global workforce, comprising 154–435 million workers, were involved in the gig economy, including both high- and low-skilled workers, those seeking a primary or secondary income, and those performing online or physical work. The term gig economy is an umbrella term encompassing a wide range of tasks and employment statutes, from more structured employment, like in France and the Netherlands, to a more independent type of work, like in the USA, originally only intended for certain professions. What appears to differentiate between gig workers and non-gig workers is whether they employ others [24].

Regardless of their legal status, for workers, gig work is a zero-sum game in which a paradox can be observed: gig work offers various opportunities, but it comes with the risk of job insecurity. Recent research has revealed that gig workers have created trade unions [31,32]. However, gig work can be associated with (self-)entrepreneurship and hence associated with risk and uncertainty. Despite this link between gig work and entrepreneurship, these two should not be confused, as precarious work and working out of necessity may situate gig workers and entrepreneurs at very different ends of the financial spectrum, though they may both involve a similar mindset for opportunity-grabbing [16].

Employers or clients in the gig economy are not necessarily companies and may be natural persons who need services; however, more research is needed in this respect. Some studies claim the existence of shadow corporations resulting from the gig economy [63], as “there is absence of employee-employer relationships in the gig economy” [66], leading to the presence of shadow corporations or huge companies with light assets that dominate the gig economy.

The future of the gig economy is an issue that requires further research on how markets function efficiently and how professional success is defined. The future of the gig economy lies not in gig work itself—which is currently a trend—but in the regulatory frameworks and social constructions surrounding it. The domains of the gig economy may diversify beyond traditional food delivery, transportation, and (semi-)professional services. Artificial intelligence (AI) is also a challenge, as some repetitive tasks currently performed by gig workers may soon be replaced by AI; it may also improve algorithms for more personalised services. Moreover, the gig economy has a role in addressing climate change and environmental challenges, contributing to a circular economy and a resource-efficient global society [49,71].