key: cord-0060348-ivltjmwq
authors: Hamann, Thomas K.; Güldenberg, Stefan
title: New Forms of Creating Value: Platform-Enabled Gig Economy Today and in 2030
date: 2020-12-06
journal: Managing Work in the Digital Economy
DOI: 10.1007/978-3-030-65173-2_6
sha: 6fbb91e2e411956f8bfe311b585173f6977d2a98
doc_id: 60348
cord_uid: ivltjmwq

This chapter explains the origins and development of the so-called gig economy and it provides a typology for the platform-enabled gig economy, including all types of gig work reaching from location-independent microtasking towards location-bound and interaction-intensive knowledge work. In addition, the importance of the platform-enabled gig economy for households as well as for the labor market and the various industrial sectors is examined. Both the positive aspects and opportunities associated with the platform-enabled gig economy and its disadvantages and risks are presented in the form of short propositions. Finally, an outlook is ventured on the probable further development of the platform-enabled gig economy up to the year 2030.

While the term 'gig economy' is fairly new, there has always been a market for freelance, pay-per-job work. In fact, prior to the industrial revolution and the rise of the employeeemployer contract, this type of work was the norm. Since then, the security of a steady job and salary has made full-time employment the preferred approach. (Edwards 2018) The term "gig economy" first came to global attention on the breakfast television newscast "American Morning" broadcasted by the television channel Cable News Network (CNN) on January 14, 2009. The journalist Tina Brown (2009) , who was interviewed in this TV broadcast, had written a blog titled "The Gig Economy" 2 days earlier. Moreover, Google Trends shows that in February 2009, the term "gig economy" was for the first time of interest in web searches worldwide. Also, starting in the summer of 2015, one can see a clear trend in an increasing number of search queries on the Internet search engine Google for this keyword. From 2007 onwards, the Great Recession caused by the global banking and economic crisis led to the dissemination of (platform-enabled) gig work (Cable News Network 2009). High rates of youth unemployment also pushed young people towards looking for jobs outside of the traditional labor market. On the employers' side, the economic crisis with the concurrent budget cuts led to an increase in demand for gig workers as a cheaper alternative to full-time employees (de Groen et al. 2018) . Furthermore, they come with variable rather than fixed personnel costs.

Defining the Gig Economy Unfortunately, a coherent and generally accepted definition of the term "gig economy" has not yet been established (e.g., Meijerink and Keegan 2019) . A gig commonly refers to a single (paid) engagement of a musician or a band for a live performance, especially when it comes to pop/rock or other modern music. Thus, a gig is a single assignment of a relatively short or limited period of time. By analogy, the term "gig economy" refers to a part of the economic system in which requesters (individuals or companies) place single well-defined assignments with providers (mostly individuals or sometimes micro-companies) for a relatively short or limited period of time outside of permanent employment relationships (see also Friedman 2014) . Some observers (e.g., Risak 2020) perceive the term "gig economy" as a fighting word used by critics to emphasize the shortterm nature of what they see as an "hire-and-fire" economy and thus spread cheap propaganda against the relevant platforms.

Defining Gig Workers There is no reliable data on the number of gig workers in the economy since the renaissance of freelance work in 2009. One reason for this is that the increasing importance of the gig economy is still a relatively new phenomenon and has only been reflected with some delay or even not at all in the regular statistical surveys on the labor market in the various countries. Another reason is that such a poll is very difficult to operationalize because the terms and distinctions used in this context between different forms of work are not (yet) clearly defined, or there is no common understanding of them. For instance, according to a survey conducted by the research and analytics consultancy Edelman Intelligence (2019), "[i] ndividuals who have engaged in supplemental, temporary, project-or contractbased work, within the past 12 months" (p. 4) describe themselves as independent workers, self-employed, freelancers, contractors, small-business owners, on-demand workers, gig workers, or moonlighters (see also Yildirmaz et al. 2020). Nonetheless, "[t] here is a general agreement in the literature that the use of online platforms for managing work has been growing exponentially in the decade following the 2007-2008 financial crisis" (Huws et al. 2017, p. 13) . A short-time series for the last 5 years from the study done by Edelman Intelligence (2019) should at least convey an idea of the numerical development of freelancers (which includes gig workers) (Fig. 1 ).

Developing a Typology of the Platform-Enabled Gig Economy

Regrettably, the common and useful criteria for distinguishing the different types of platform-based gig work are not free of overlaps. Hence, a differentiation into mutually exclusive categories is not feasible. Apart from that, many terms are used in connection with the gig economy, some with synonymous meaning, so that not all of them can be considered here.

For the purpose of temporary engagements, requesters and providers are often brought together by third parties. This bringing together can be done either by simply offering a (virtual) marketplace, allowing requesters to search for providers or vice versa, or by a curated so-called matchmaking process in which the third-party mediator checks the requirements for the tasks to be assigned against the respective qualifications of the providers and assesses their suitability. For both of these mediation variants, the requesters and especially the providers must register with the mediator, facilitating interactions or transactions between requesters and providers on this basis. Industrial economists such as Rochet and Tirole (2003) call a mediator of this type a (two-sided or-if more than two groups are brought together-multi-sided) platform (Baldwin and Woodard 2008; Boudreau and Hagiu 2009) . These platforms can be digital, that is, based on digital technology, or non-digital (de Reuver et al. 2018) . The part of the economic system where platforms enable interactions or transactions between two or more groups of market participants, in general, is called platform economy. And the part of the gig economy where platforms connect requesters and providers is the platform-enabled gig economy (Meijerink and Keegan 2019) , which is also referred to by some (e.g., Rinehart and Gitis 2015) as the online gig economy. Figure 2 provides an overview of the typology of the platform-enabled gig economy as outlined below. 

Labor market(s) comprising workers "hired under 'flexible' arrangements, as 'independent contractors' or 'consultants,' [sic!] working only to complete a particular task or for a defined time" (Friedman 2014, p. 171 )-mediated by platforms Microtasking/ "click work"

Online market(s) for contingent (task-or project-based) intangible paid work that is processed online and organized via digital platforms intermediating between clients and workers (Pongratz 2018 , Graham et al. 2017 , Heeks 2017 , Lehdonvirta et al. 2014 , Horton 2010 

Labor market(s) for work that is typically carried out locally and usually intermediated by a matchmaking platform 

A conceivable criterion for the further breakdown of the platform-enabled gig economy is where-after successful online mediation-the work is performed (Gandini 2019 ). On the one hand, services can be contracted and provided completely online and irrespective of the location, that is, "the outsourcing of digitally processible tasks as paid work to a global workforce via Internet platforms such as Amazon Mechanical Turk (AMT), Upwork or Freelancer" (Pongratz 2018, p. 58 ) and called "online labor" (e.g., by Horton 2010; Condagnone et al. 2016; Pongratz 2018 ). On the other hand, this is distinguished from "mobile labor", where the work is carried out physically or requires intense direct interaction between requesters and providers like transport (e.g., Uber) or delivery services (e.g., Deliveroo) (Condagnone et al. 2016; Pongratz 2018) . The terms "online labor" and "mobile labor" are not clear in this context and may be misleading. Eventually, some relevant work processes such as matchmaking, contracting, invoicing, evaluating, etc. can also be carried out online for location-bound activities. And vice versa, people who work completely independently of the location are particularly mobile with respect to the choice of their worksite. Thus, the terms (almost fully) digitized location-independent work versus (mostly) location-bound or interaction-intense work are preferable.

Microtasking and "Click Work" Microtasking is when a task is further broken down into tiny piecemeal subtasks, each of which is rewarded with an equally small amount of money (Schmidt 2017; Howcroft and Bergvall-Kåreborn 2019) . Microtasking, whether digitized location-independent or, as addressed below, local, the individual providers are typically not selected directly by the requesters (Melián-González 2019). Digitized location-independent microtasking includes simple tasks such as researching specific information, completing questionnaires (Gadiraju et al. 2015) , and entering data (Heeks 2017) . Well-known platforms for the mediation of such microtasks are Amazon Mechanical Turk (MTurk), the Appen company Figure Macrotasking This involves more substantial and complicated tasks, which typically depend on the specific capabilities of the providers (Walsh et al. 2014 ). Examples of macrotasks are software development and data analytics. Common macrotasking platforms are Fiverr, Freelancer, and Upwork. A special form of macrotasking is so-called contest-based work, in which a task that cannot be subdivided may be performed simultaneously by several providers. In the end, only one result is selected and paid by the respective requester (Horton 2010; Heeks 2017; Schmidt 2017 ). This variant is mainly used for graphic design, in particular, logo design; well-known, relevant platforms are 99designs (Schmidt 2017) and LogoTurnament.

Local Microtasking This term refers to a microtask that is location-bound but is not carried out at the place of the requester and or does not require a lot of interaction with the requester. A local microtask can be, for example, the taking of specific photos in shops for assortment analysis, control of secondary placements, price recording, etc. Typical platforms for local microtasking are appJobber, Streetspotr, and Field Agent.

Consumer-Led Services and Manual Work Microtasks that are location-bound, carried out at the place of the requester, require intense interaction with, or (active) involvement of the requester fall in this category. Typical examples of such work are delivery work, passenger transportation, housework like cleaning, and skilled crafts work like electrical installation or plumbing. Widely known platforms for the mediation of such tasks are Deliveroo, Uber, and TaskRabbit.

These are platform-mediated tasks which are comprehensive and typically require specific expertise (so-called knowledge work) and which can only be performed in close cooperation with the respective requester, usually on-site. The addition "independent" indicates that the services are not run by an established provider possessing a strong brand character but by individuals or micro-enterprises. They include, for instance, activities such as management consulting or legal counseling. Better-known platforms in this area are the Business Talent Group (BTG) and COMATCH.

3 Key Characteristics of the Platform-Enabled Gig Economy in 2020

3.1 Importance for Households

The importance of the income generated by gig-economy work for the individuals and their households varies; thus, for just over a quarter of the European gig workers, platform-enabled gig work accounts for 50% or more of their personal income, while for the rest of gig workers their involvement in the gig economy is more a sideline or source of extra income (Fig. 3) . Similar data is also reported for the United Kingdom by Lepanjuuri et al. (2018) . In the last 12 months, 9% of gig workers earned more than 90% of their total income from gig work, while 65% of gig workers earned less than 5% of their total income from gig work. Manyika et al. (2016) from the McKinsey Global Institute likewise distinguish between those who derive their primary income and those who receive a supplementary income from independent work; furthermore, they differentiate between independent workers, who have consciously chosen this working style, and those who have no other choice. This results in four different types of gig workers:

• People who receive their primary income from independent work and have actively chosen this working style • Individuals who derive their primary income from independent work but would prefer traditional employment • People who supplement their income by choice from independent work • Persons who supplement their income with independent work, but who would rather not be constrained to take up such additional work However, based on the data available to them, Manyika et al. (2016) assume that the clear majority of independent workers, 72% in the USA and 68% in the EU-15, 1 are engaged in this kind of work by choice rather than out of necessity. Nonetheless, this means that a substantial proportion of the gig workers are compelled to pursue independent work. For these groups, which accept gig work out of necessity, the possibility of platforms abusing their market power could be particularly problematic, as will be discussed later. 

According to five studies by MBO Partners, Burson-Marsteller, Kelly Services, Freelancers Union, and MGI Survey that draw on different definitions, the proportion of primary and supplemental independent workers of the working-age population in the USA was estimated between 16% and 27% in 2015/2016 (Manyika et al. 2016) . When it comes to the primary independent workers only, three studies by Katz & Krueger, BLS, and MGI Survey arrived at shares between 10% and 12%. For the independent platform workers, the estimates by Katz & Krueger, Intuit, JPMorgan Chase Institute, and MGI Survey were up to 4% (Manyika et al. 2016) .

A large proportion of gig workers are active in the following industry sectors: professional and business services, construction, and education and health services (Fig. 4) . Well-known gig activities are consumer-led services/manual work that have a medium frequency of 6%-7% each-such as leasing assets like apartments via platforms like Airbnb (leisure and hospitality), selling goods via platforms like eBay (retail trade), and providing passenger driving services (transportation and utilities).

In comparison to the US data mentioned in Fig. 4 , Broughton et al. (2018) came up with the following proportional distribution of gig workers in the United Kingdom: professional/creative/high-skilled work (36%), office/short online tasks/admin (25%), taxi/transport (24%), physical low-skilled work (12%), physical skilled work (3%). Appreciation and Criticism of the Platform-Enabled Gig Economy

The platform-enabled gig economy "has the capacity to change the nature of work organization and to provide strategic value to workers, job providers, and intermediary platform owners" (Gol et al. 2019 ).

Value Creation for Providers For the providers, the intermediary platforms offer a much broader access to potential clients than would be possible exclusively through the respective personal network and thus increase the chances of being awarded a contract. In the case of digitized location-independent work, the geographical scope is also expanded because it avoids barriers such as any necessary work permits and travel costs. Obviously, the gig economy offers more flexibility than a traditional employment relationship, even for those who, as self-employed people, do not want to take care of their own business development or have difficulties with it for whatever reason.

Value Creation for Requesters The mediation platforms offer requesters access to a larger number of suitable potential contractors and thus reduce their search costs. Additionally, they are offered, depending on the platform and their curative activities, a pre-qualification of relevant providers to a certain degree. This can be realized by conducting interviews as part of the registration process, by additional clarification of suitability for currently requested tasks, and by evaluations of the providers by other requesters for jobs completed earlier. Moreover, according to Gol et al. (2019) , the gig economy enables a reduction in labor costs by providing organizations with flexible access to a large pool of resources and usually cheap temporary workers. Even if the gig workers are not cheaper than permanent employees, the share of fixed or at least remnant personnel costs can be reduced by making them flexible and terminable on short notice.

Value Creation for Intermediary Platforms Basically, a distinction can be made between peer-to-peer and commercially oriented platforms. In contrast, the former, so-called commons platforms, mediate between requesters and providers free of charge and also allow external parties to benefit from their network, for example, by making the provider profiles publicly available, the latter is clearly aiming at economic benefits. An example of a commons platform is Umbrex, with its derivative Veritux. There, members and externals can contact the registered providers directly and also award contracts without involving the platform. The commercial platforms, on the other hand, claim a share of the value they generate as remuneration. Depending on the billing model, the willingness of requesters and providers to pay means that the value created by the platforms for these players can also be quantified. Platforms have been found to be more efficient than their non-platform competitors, like traditional consulting companies or recruitment agencies; they generate roughly the same revenue with significantly fewer employees because they access resources outside the company and build a business without actually owning nearly as many assets as comparable non-platform companies (Cusumano et al. 2019 ).

Basically, (profit-oriented) platforms tend to shift most of the costs, risks, and responsibilities to the other parties. They usually offer only a virtual service such as an app or a website. They hence can grow exponentially without having to bear proportionally increasing labor costs or production resources (Schmidt 2017 (2018, pp. 9, 32-33) , which pursues the goal of "a fair, trusting and innovationdriven ecosystem around online platforms [. . .] , in which business traders have the necessary safeguards to prevent harm from unfair trading practices, general lack of redress, and regulatory fragmentation [. . .]" to fully exploit the potential of the online platform economy, has adopted findings of de Bas et al. (2017) and developed them further, by addressing the key problems driven by "imbalanced bargaining power" and the "dependency of businesses on online platforms". These research results were reflected with own ethnographic experiences, and, on that basis, critical propositions on digital gig economy platforms were developed.

Lack of Transparency Only a minority of digital matchmaking platforms follow a fully open and transparent approach about their terms and conditions; the platforms tend to fog up the asymmetric terms and conditions.

Delisting and Suspension of Accounts There is a clear imbalance of (market) power between digital matchmaking platforms and platform workers. In case of conflict, the platforms tend to fully exploit their power over platform workers.

The quality of matching, which should be the core competency, varies significantly between digital matchmaking platforms. Search costs are partially externalized to the crowd of platform workers. Digital matchmaking platforms tend to use rankings and feedback not as objective information towards the client but as a means of pressure on platform workers.

Discrimination and Favoring of Own Services Digital matchmaking platforms tend to follow aggressively a "grow-fast imperative" to get on the safe side of a probable future market consolidation (so-called winner takes it all phenomenon) at the cost of the individual platform worker. In order to maintain or expand their market position accordingly, platforms typically offer contracts with strict anti-circumvention clauses that do not allow the platform worker to work for a (potential) client organization or company group to that the platform worker was introduced by the platform without involving the platform, usually for a period of 18-36 months. Platform workers are usually subject to such a ban on circumvention even in cases when they-for various possible reasons-forward their own project requests to platforms. Furthermore, digital matchmaking platforms tend to make use of their workers' expertise and working power free of charge, for example, for the preparation of pitch presentations in situations where the platforms compete against traditional consultancies and need more substantial content rather than candidate profiles or when it comes to press inquiries to the platform, in order to impose opportunity and transaction costs towards the platform workers but do not allow them to mention the names or brands of their own legal entities.

Lack of Access to Data and Breaches of Data Security When it comes to feedback, the digital matchmaking platforms are hardly concerned about personal and professional development. Consequently, the data behind worker ratings are frequently not made transparent to the platform worker (Rahman 2020) , which was pointed out in the fictitious release for ECareer and EHire in the introduction to this chapter. Some platforms do not push the clients for (qualitative) feedback or discuss that with the platform worker for purposes of professional development. Digital matchmaking platforms have less interest in securing important organizational data for the platform worker and take personal data protection rights less seriously than demanded from their platform workers. For instance, the data stored in the log in area of platforms that display historical data like applications to the user are not always complete. In addition, they let platform workers access to the personal profiles or résumés of other platform workers, for example, when forwarding proposal documents.

Pricing Digital matchmaking platforms prefer to refrain from business opportunities to enforce asymmetric commissions with platform workers. Moreover, they intentionally intensify price competition as part of their business model. This means lowering earning possibilities for highly qualified platform workers and increasing the price pressure for the traditional consulting industry.

Termination Risk, Especially on Short Notice and Occurring Opportunity Cost Platforms strive for the entrepreneurial risks to be borne as far as possible by the platform workers. At the same time, the opposing opportunities are claimed for the platform. The platforms insist on the adherence to given promises of availability. On the other hand, a project or a task can usually be withdrawn without compensation from the platform worker by the platform or client at short notice. Platform workers have to bear the opportunity costs for any other, not accepted projects themselves.

Lack of Effective Redress Digital matchmaking platforms deliberately prohibit effective internal redress mechanisms to protect their own interest and shift the business risks towards platform workers. Reasonable out-of-court external redress mechanisms hardly exist. Digital matchmaking platforms intentionally take advantage of the limited use of judicial remedies on the side of the platform worker.

Possible scenarios for the future development of the platform-enabled gig economy up to 2030 are challenging to make. This is partly due to the still fuzzy database on its current state and the very open question of future state regulation of the sector. Therefore, in the following part, we only describe trends that are already visible or are, in our opinion, very likely to occur in the future.

Likely Consolidation of the Platform Landscape Even though the term "gig economy" appeared for the first time in 2009, the concept of labor-intermediating Internet platforms is actually older. Its emergence reaches back to the so-called dot-com boom at the end of the 1990s. As evidence one only has to look at Guru, the first platform for the intermediation of management consulting services (independent knowledge work) launched in the USA in 1998. As Fig. 5 shows, the absolute increase in such platforms was strongest from 2014 to 2016, from 21 to 37 platforms. According to Haslam et al. (2018) as well as Mazareanu (2020), it is not surprising , 1998-2020 (own research) that these platforms were established in the largest markets for consulting services in terms of total revenue, that is, the USA, the United Kingdom, Australia, and the German-speaking countries Germany, Austria, and Switzerland. Platforms typically scale up their business by expanding rapidly into other countries. This growth is largely due to the fact that there are hardly any marketentry barriers for such platforms and that they can be brought to market quickly and easily as me-too solutions. It is very questionable whether all these platforms will be successful in the long run. The first consolidations of the platform landscape have already taken place. The platforms Elance and oDesk, founded in 1999 and 2003, respectively, merged in 2013 to form Upwork. In 2017, only 2 years after its foundation, the platform projectchamps was integrated into the more recently established platform consultingheads (founded in 2016). Furthermore, the platform KLAITON, founded in 2015, was acquired by the Haufe Group and renamed Haufe Advisory in 2018. In 2019, the Hillgate platform, established in 2014, joined the Business Talent Group and became its European branch. The platform Zentaur, founded in 2015, was put up for sale in 2019 and finally shut down in the spring of 2020. Significant consolidation of the platform landscape can be expected in the long term.

Convergence of the Operations of the Digital Labor Platforms and Those of Traditional Recruitment Agencies This convergence could be one of the steps towards the consolidation mentioned above. It involves both sides, that is, on the one hand traditional recruitment agencies are expanding their business to include digital mediation platforms, and on the other hand, the digital platforms of the gig economy are entering the field of classic HR consulting. For example, The Barton Partnership, founded in 2007 as a niche executive recruitment firm, has even set up two recruitment platforms: Independent Consulting (2014) and HourlyConsulting. com (2018). Conversely, gig economy platforms such as consultingheads, Movemeon, and TalMix also show job advertisements for permanent positions, which can also be systematically filtered. Moreover, the digital platform COMATCH even offers a correspondingly dedicated service called COMATCHperm.

Increasing Importance of the Gig Economy According to Smart Business Labs and Gallup, about 36% of the US workers currently participate in the gig economy and according to MBO Partners, the number of US workers who participate or at least did participate at some point in their career in the gig economy, even if only occasionally, should be up to 52% by 2023 (Mitic 2019) . Due to the currently emerging economic crisis caused by the Sars-CoV-2 virus, it can be assumed that-analogous to the economic crisis of 2008/2009-companies will want to reduce their personnel costs or at least make these variable and release people who will then try their luck as gig workers. It can also be anticipated that the proportion of gig workers who make their living entirely from this form of work will increase.

Increasing Control and Regulation of the Gig Economy for the Benefit of Gig Workers Analogous to the Protection of Permanent Employees in Labor Law As already described, gig work is associated with disadvantages and risks, especially for the providers. In order to reduce these, it is very likely that more appropriate measures will be taken in the future. These could be regulatory interventions on the part of the state responsible. For example, "California's new measure requiring the state's gig workforce to be treated as conventional employees is only the latest sign of the limits of this approach" (Irwin 2019). Another possible development towards avoiding the negative aspects of the gig economy could be the promotion of more peer-to-peer oriented platforms with elements of decentralized platform governance. This is because such platforms are less prone to the concentration of power, which can then be misused (Gol et al. 2019) .

• The Great Recession, which followed the global banking and economic crisis from 2007 onwards has led to a strong dissemination of the platformenabled gig economy. High youth unemployment has forced young people to look for jobs outside of the traditional labor market. Also, on the client side, the economic crisis with the concurrent budget cuts led to an increase in demand for gig work as a cheaper alternative, which comes with variable rather than fixed personnel costs. • This chapter develops a typology for the platform-enabled gig economy, including all types of gig work reaching from location-independent microtasking towards location-bound and interaction-intensive knowledge work. Leaders should be very aware of these different types of gig works as they include different tasks to accomplish, different kinds of workers, and therefore have to be managed with a situational leadership approach to achieve sustainable results. • Besides the advantages of the gig economy by creating strategic value to workers, job providers, and intermediary platform owners, there are also some already visible disadvantages with which we have to deal in a growing gig economy. The most important among them is that profitoriented platforms tend to shift most of the costs, risks, and responsibilities to the other parties. They very often have a lack of transparency in their terms and conditions, and there is a clear imbalance of (market) power between digital matchmaking platforms and platform workers. This may lead to platforms tending to exploit their power over platform workers in case of conflict, and they can intentionally take advantage of the limited use of judicial remedies on the side of the platform workers. • In order to reduce the disadvantages of the gig economy, more appropriate measures will likely be taken by 2030. These could be, for instance, regulatory interventions on the part of the responsible governing bodies.

Another possible development towards avoiding the negative aspects of the gig economy could be promoting more peer-to-peer-oriented platforms with elements of decentralized platform governance. Such platforms are less prone to the concentration of power, which can then be misused.

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Thomas is a licentiatus oeconomiae (lic. oec. HSG) and holds a doctoral degree from the University of St. Gallen, Switzerland. In addition to his advisory services for various companies, Thomas conducts scientific research and lectures at various business schools. He focuses on strategic management, including business war-gaming, sales and marketing, leadership and organization, and operational issues. Before founding his own consulting firm

He studied Business Mathematics, Philosophy, and English at the University of Ulm, then received his doctorate and habilitation at the Vienna University of Economics and Business. Stefan has 25 years of experience in research, knowledge transfer, and practice. He conducts research on and supports the development of strategy and transformation processes. Stays abroad led him, among others, to Harvard University, the Massachusetts Institute of Technology (MIT), and the National University of Singapore