On-demand Work Research Articles

Facing the Challenges of Platform-Mediated Labour: The Employment Relationship in Times of Non-Standard Work and Digital Transformation

This dissertation focuses on digital platforms and apps connecting pools of workers, employers and clients instantaneously. These working arrangements call into question the suitability and effectiveness of the current employment legislation. The emerging literature reveals pervasive commands, reinforced surveillance, constant monitoring, arbitrary disciplinary action and very little or no workers’ discretion in deciding how to complete a task. Standard methods of social science research and legal analysis are applied in the investigation, accompanied by a strong interdisciplinary approach. With a law-in-context methodology, this study revolves around four main sections, each of them looking at platform-mediated work from a particular angle. After describing the theoretical antecedents of hierarchical outsourcing and relational contracts, Section 1 contributes to the literature on the “nature” of the “non-standard firm” by applying the economic analysis of transaction costs. Building on models on the disarticulation of the employing entity and the pulverisation of work-related responsibilities, this chapter conceptualises the prototypical business model of these new economic and social actors. The expression “Cerberus firm” is used to define a network company built as an online middleman that reduces information asymmetries, minimises organisational costs and engages a pool of providers (virtually recruited, effectively directed and persistently disciplined) through rapid transactions on the market with an authoritative attitude. Section 2 carries out a critical scrutiny of two myths: technological displacement and the crisis of the standard employment relationship. This assessment also requires looking into the contractual arrangements. The typologies of employment generated by the on-demand economy are part of a broader class of non-standard forms of work emerging from digitalisation. These organisational patterns manifestly exclude workers from employment protections and social security benefits. Accordingly, a picture of the spread of precarious employment is drawn, by taking into account as many alternative working formats as possible including self-employment work, economically dependent self-employment and disguised employment relationship. This review concludes by representing the employment relationship as a resilient and flexible tool, capable of adapting to the incessantly changing nature of production systems. Section 3 maps a kaleidoscopic array of app-distributed arrangements, clustering the findings into three main subsets (passenger transport services, professional crowdsourcing, on-demand work at the client’s premises). In doing so, the relationship between a worker and the platform is assessed along five main critical stages of the process, starting with the registration and ending with the payment. Several initiatives aimed at promoting fair and decent work in the collaborative economy are scrutinised, namely (i) the European Commission’s Communication 356/2016, (ii) the principles enshrined in the European Pillar of Social Rights, and (iii) the ruling by the European Court of Justice on the nature of the service provided by Uber. Furthermore, existing regulatory schemes, ranging from the Directives on atypical employment to other casual work templates, are assessed to test their resilience against this background. Section 4 investigates the legal status of platform-coordinated workers by considering what is at stake in pending litigations. In the end, this dissertation intends to “normalise” the discourses surrounding the digital transformation of work, by also contrasting the sense that new realities of work have outgrown legal concepts. This thesis argues that, before exploring captivating hypotheses for reforms, lawyers and scholars must seek to square this fast-evolving phenomenon with the existing legal framework. There is indeed the need for a balance between safeguarding social rights and unleashing authentic societal improvements. Several available legal notions and tools, which can adequately address this challenge, are discussed with a view of advancing a tentative regulative framework of platform-mediated labour.

Work Will Not Disappear. So We Should Make It Better

Workers everywhere worry about the future of their jobs. After all, for the vast majority, income from paid employment (in one form or another) is the dominant means to provide for the necessities of life. The availability, stability, and earning potential of paid work are essential to our well-being. The world of work is being transformed by technology: machines and computers can perform ever-more complex tasks (including those involving judgment and learning), reigniting age-old fears that workers will be replaced by machines. Of course, workers have worried about machines taking their jobs since the dawn of capitalism. In historical experience, technological change by itself does not produce long-lasting unemployment: unemployment certainly does exist, but usually for other reasons (like failed macroeconomic policies). But technological change certainly causes dislocation and hardship for certain groups of workers – and the resulting costs are much worse if affected workers don’t get alternative job opportunities, mobility assistance, and retraining. There is nothing inevitable about how technology is developed, applied, and managed; the impacts of technology depend entirely on choices made regarding its design, implementation, and management. At present, most of those decisions are made unilaterally by the owners and top managers of private businesses, who have free rein (in most countries) to choose what technologies are implemented, to what ends, and who bears the resulting costs and benefits. Perhaps we should be less concerned with technology, and more with the unbalanced decision-making structure within which technology is presently governed. Moreover, technology is not the only force transforming the world of work. The organisational and social context of work is also in major flux. Indeed, changes in work organisation and employment relations are having a more immediate impact on workers than the much-hyped advent of robots and artificial intelligence. A permanent, fulltime , paid job with accompanying benefits (like job security, paid time off, and pension and health programs) is no longer normal practice in most labour markets – and is a utopian dream for most young workers. In its place, precarious work in many forms (including temporary, part-time, casual, irregular, and nominally independent or selfemployed positions) is the new normal. In the extreme, precarious work is now organised through ‘gigs’: on-demand, piece-work tasks allocated and compensated through faceless digital platforms. These twin disruptions – changing technology and changing working relationships – have led some observers to conclude that work, broadly defined, can no longer be the financial and social foundation of households and society. People will need to find other ways to support themselves, and/or fall back on income supports delivered by the state (perhaps through a guaranteed annual income). This vision of a workless future can be described positively (as a world in which humans have ample leisure time to pursue a range of interests) or negatively (as a dystopia in which wealth becomes concentrated amongst a narrow property-owning elite, while most people huddle at the margins seeking a way to survive). Both scenarios assume that paid work is diminishing in importance. This assumption is misplaced. Robots or no robots, work is here to stay There are enduring features of paid work that ensure it will remain the cornerstone of the economy, and the major pillar of financial well-being for most households. The question is not whether or not work will somehow ‘disappear’: it can’t. The question is how society will choose to treat, protect, and compensate the work that will remain essential to its economic and social progress. In the realm of digital platforms and ‘gigs’, for example, paid work is still very clearly the driving force of production and growth. Modern digital businesses rely on paid workers to produce their ultimate output. But those firms have developed clever systems to minimise or evade the risks, costs and obligations traditionally faced by employers (minimum wages, notice of dismissal, pension and health benefits, etc.). Contrary to the popular assumption that digital platforms are the ‘cutting edge’ of business innovation, their work practices are centuries old: including piece-work compensation, on-demand work scheduling, and labour hire systems that have been around as long as capitalism. In previous decades, limits were imposed on some of...

Intrinsic motivation and organizational identification among on-demand workers.

On-demand firms provide services for clients through a network of on-demand workers ready to complete specific tasks for a set contractual price. Given such on-demand work is defined by payment on short-term contracts with no obligation for continued employment, there is little reason to believe on-demand workers experience more than extrinsic motivation and a transactional relationship with the on-demand firm. However, using self-determination theory, we argue that to the degree that on-demand work fulfills innate psychological needs individual on-demand workers will develop intrinsic motivation, which further leads to organizational identification with the on-demand firm. Across 2 survey-based studies we find support for this path to organizational identification. This adds to the literature on motivation and identification by strengthening the link between individual needs and the individual-organizational relationship. Implications for theory and for the management of on-demand workers are discussed. (PsycINFO Database Record

The context of on-demand work

Two years of ethnographic fieldwork, in the U.S. and India, together with rich quantitative data, shine light on the world of on-demand work invisible to many of us, yet core to the functioning of the Internet and the future of automation.

Commoditized Workers The Rising of On-Demand Work, A Case Study Research on a Set of Online Platforms and Apps

In the framework of the so-called “sharing economy”, the number of on-demand companies matching labour supply and demand is on the rise. These schemes may enlarge opportunities for people willing to find a job or to top up their salaries. Despite the upsides of creating new peer marketplaces, these platforms may also be used to circumvent employment regulation, by operating informally in traditionally regulated markets.Literature showed how, by 2009, over 2 million worker accounts had been generated within these frameworks. Productivity may be fostered but, at the same time, a new version of Taylorism is disseminated (i.e. the fragmentation of labour into hyper-temporary jobs – they call them microtasks – on a virtual assembly line), strengthened by globalisation and computerisation. All these intermediaries recruit freelance or casual workers (these continue to be independent contractors even though many indicators seem to reveal a disguised employment relationship).Uncertainty and insecurity are the price for extreme flexibility. A noteworthy volume of business risk is shifted to workers, and potential costs as benefits or unemployment insurance are avoided. Minimum wages are often far from being reached.This paper will present a case study analysis of several “on-demand work” platforms, starting from the Amazon Mechanical Turk, one of the first schemes founded in 2005, which is arguably “employing humans-as-a-service”. It splits a single service in several micro “Human Intelligence Tasks” (such as tagging photographs, writing short descriptions, transcribing podcasts, processing raw data); “Turkers/Providers” (workers) are selected by “Requesters” to rapidly accomplish assignments online, are then rated according to an internal system and are finally paid (also in gaming credits) only if delivery is accepted. After having signed up and worked within some platforms, I comment upon TaskRabbit (thousands people on the service who bid to do simple manual tasks), Handy and Wonolo (personal assistance at a local level), oDesk and Freelancer (online staffing), Uber and Lyft (peer-to-peer ridesharing), Airbnb (hosting service), InnoCentive (engineering solutions), Axiom (legal research or service), BitWine (consultancy).Finally I highlight downsides and upsides of work in these platforms by studying terms of service or participation agreements to which both parties have to agree. I look into several key features such as (i) means of exchange/commodities, (ii) systems of payment, (iii) demographics, (iv) legal issues concerning status and statutory protection of workers, indicators of subordination, treatment of sickness, benefits and overtime, potential dispute resolution, and deprived “moral valence of work” and I discuss potential strategies to address these issues.

A scalable, parallel algorithm for maximal clique enumeration

The problem of maximal clique enumeration (MCE) is to enumerate all of the maximal cliques in a graph. Once enumerated, maximal cliques are widely used to solve problems in areas such as 3-D protein structure alignment, genome mapping, gene expression analysis, and detection of social hierarchies. Even the most efficient serial MCE algorithms require large amounts of time to enumerate the maximal cliques in networks arising from these problems that contain hundreds, thousands, or larger numbers of vertices. The previous attempts to provide practical solutions to the MCE problem through parallel implementation have had limited success, largely due to a number of challenges inherent to the nature of the MCE combinatorial search space. On the one hand, MCE algorithms often create a backtracking search tree that has a highly irregular and hard-or-impossible to predict structure; therefore, almost any static decomposition of the search tree by parallel processors results in highly unbalanced processor execution times. On the other hand, the data-intensive nature of the MCE problem often makes naive dynamic load distribution strategies that require extensive data movement prohibitively expensive. As a result, good scaling of the overall execution time of parallel MCE algorithms has been reported for only up to a couple hundred processors. In this paper, we propose a parallel, scalable, and memory-efficient MCE algorithm for distributed and/or shared memory high performance computing architectures, whose runtime scales linearly for thousands of processors on real-world application graphs with hundreds and thousands of nodes. Its scalability and efficiency are attributed to the proposed: (a) representation of the search tree decomposition to enable parallelization; (b) parallel depth-first backtracking search to both constrain the search space and minimize memory requirement; (c) least stringent synchronization to minimize data movement; and (d) on-demand work stealing intelligently coupled with work stack splitting to minimize computing elements’ idle time. To the best of our knowledge, the proposed parallel MCE algorithm is the first to achieve a linear scaling runtime using up to 2048 processors on Cray XT machines for a number of real-world biological networks.