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1 – 10 of 132This paper aims to explore workplace learning practices within two types of crowdwork – microwork and online freelancing. Specifically, the paper scopes and compares the use of…
Abstract
Purpose
This paper aims to explore workplace learning practices within two types of crowdwork – microwork and online freelancing. Specifically, the paper scopes and compares the use of workplace learning activities (WLAs) and self-regulatory learning (SRL) strategies undertaken by microworkers (MWs) and online freelancers (OFs). We hypothesised that there may be quantitative differences in the use of WLAs and SRL strategies within these two types of crowdwork, because of the underpinning differences in the complexity of tasks and skill requirements.
Design/methodology/approach
To test this hypothesis, a questionnaire survey was carried out among crowdworkers from two crowdwork platforms – Figure Eight (microwork) and Upwork (online freelancing). Chi-square test was used to compare WLAs and SRL strategies among OFs and MWs.
Findings
Both groups use many WLAs and SRL strategies. Several significant differences were identified between the groups. In particular, moderate and moderately strong associations were uncovered, whereby OFs were more likely to report (i) undertaking free online courses/tutorials and (ii) learning by receiving feedback. In addition, significant but weak or very weak associations were identified, namely, OFs were more likely to learn by (i) collaborating with others, (ii) self-study of literature and (iii) making notes when learning. In contrast, MWs were more likely to write reflective notes on learning after the completion of work tasks, although this association was very weak.
Originality/value
The paper contributes empirical evidence in an under-researched area – workplace learning practices in crowdwork. Crowdwork is increasingly taken up across developed and developing countries. Therefore, it is important to understand the learning potential of this form of work and where the gaps and issues might be. Better understanding of crowdworkers’ learning practices could help platform providers and policymakers to shape the design of crowdwork in ways that could be beneficial to all stakeholders.
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Thomas Gegenhuber, Elke Schuessler, Georg Reischauer and Laura Thäter
Working conditions on many digital work platforms often contribute to the grand challenge of establishing decent work. While research has examined the public regulation of…
Abstract
Working conditions on many digital work platforms often contribute to the grand challenge of establishing decent work. While research has examined the public regulation of platform work and worker resistance, little is known about private regulatory models. In this paper, we document the development of the “Crowdwork Agreement” forged between platforms and a trade union in the relatively young German crowdworking field. We find that existing templates played an important role in the process of negotiating this new institutional infrastructure, despite the radically new work context. While the platforms drew on the corporate social responsibility template of voluntary self-regulation via a code of conduct focusing on procedural aspects of decent platform work (i.e., improving work conditions and processes), the union contributed a traditional social partnership template emphasizing accountability, parity and distributive matters. The trade union’s approach prevailed in terms of accountability and parity mechanisms, while the platforms were able to uphold the mostly procedural character of their template. This compromise is reflected in many formal and informal interactions, themselves characteristic of a social partnership approach. Our study contributes to research on institutional infrastructures in emerging fields and their role in addressing grand challenges.
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Jo Bates, Elli Gerakopoulou and Alessandro Checco
Underlying much recent development in data science and artificial intelligence (AI) is a dependence on the labour of precarious crowdworkers via platforms such as Amazon…
Abstract
Purpose
Underlying much recent development in data science and artificial intelligence (AI) is a dependence on the labour of precarious crowdworkers via platforms such as Amazon Mechanical Turk. These platforms have been widely critiqued for their exploitative labour relations, and over recent years, there have been various efforts by academic researchers to develop interventions aimed at improving labour conditions. The aim of this paper is to explore US-based crowdworkers’ views on two proposed interventions: a browser plugin that detects automated quality control “Gold Question” (GQ) checks and a proposal for a crowdworker co-operative.
Design/methodology/approach
The authors interviewed 20 US-based crowdworkers and undertook a thematic analysis of collected data.
Findings
The findings indicate that US-based crowdworkers tend to have negative and mixed feelings about the GQ detector, but were more enthusiastic about the crowdworker co-operative.
Originality/value
Drawing on theories of precarious labour, this study suggests an explanation for the findings based on US-based workers’ objective and subjective experiences of precarity. The authors argue that for US-based crowdworkers “constructive” interventions such as a crowdworker co-operative have more potential to improve labour conditions.
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Christine Gerber and Martin Krzywdzinski
The term “crowdwork” describes a new form of digital work that is organized and regulated by internet-based platforms. This chapter examines how crowdwork platforms ensure their…
Abstract
The term “crowdwork” describes a new form of digital work that is organized and regulated by internet-based platforms. This chapter examines how crowdwork platforms ensure their virtual workforce’s commitment and control its performance despite its high mobility, anonymity, and dispersion. The findings are based on a case study analysis of 15 microtask and macrotask platforms, encompassing 32 interviews with representatives of crowdwork platforms, and crowdworkers, as well as an analysis of the platforms’ homepages and community spaces. The chapter shows that performance control on crowd platforms relies on a combination of direct control, reputation systems, and community building, which have until now been studied in isolation or entirely ignored. Moreover, the findings suggest that while all three elements can be found on both microtask and macrotask platforms, their functionality and purpose differ. Overall, the findings highlight that platforms are no neutral intermediaries but organizations that adopt an active role in structuring the digital labor process and in shaping working conditions. Their managerial structures are coded and objectified into seemingly neutral technological infrastructures, whereby the underlying power relations between capital and labor become obscured.
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This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.
Abstract
Purpose
This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.
Design/methodology/approach
This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.
Findings
The two core types of work in crowdworking differ in certain respects. However, similar learning activities and strategies are key to success in both cases making it imperative to gain greater knowledge of the practices. Gaining such insight will aid future development of crowdworking and subsequently help increase its impact to the advantage of different stakeholders involved.
Originality/value
The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.
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Gordon B. Schmidt, Jestine Philip, Stephanie A. Van Dellen and Sayeedul Islam
As conventional practices of working continue to be modified in the gig economy, more theoretical work examining the experiences of gig workers is needed. Relying on person-based…
Abstract
Purpose
As conventional practices of working continue to be modified in the gig economy, more theoretical work examining the experiences of gig workers is needed. Relying on person-based fit and levels of analysis literature, this paper proposes an adaptation to the traditional Attraction-Selection-Attrition (ASA) framework to the gig economy.
Design/methodology/approach
Drawing on the ASA framework, this conceptual paper explores how gig workers join, leave and could be retained by gig employers.
Findings
The authors recognize an intermediary “organizing” phase within the ASA framework for gig workers. Using examples of appwork and crowdwork, the authors show that workers tend to self-organize through third-party websites to help gig work become economically sustainable, avoid being exploited and enhance gig workers' sense of community and identity.
Practical implications
The practical implications of this research lie in gig employers understanding how workers experience gig employment and in helping employers be successful in attracting, selecting and retaining quality workers and thereby lowering permanent attrition.
Originality/value
The authors propose a novel adaptation to the conventional ASA framework to include organizing as a phase in gig worker employment. This research defines gig attraction and attrition at the individual-level, selection at the individual- and task-levels based in person-job (PJ)-fit and the various aspects of gig organizing as encompassing fit with one's job, organization, and environmental (i.e., PJ-, PO-, PE-fit) at the individual-, task-, and network-levels.
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Eliane Bucher, Christian Fieseler and Christoph Lutz
Online gig labor platforms bring together a global and fast-growing workforce to complete highly granular, remote and decontextualized tasks. While these environments might be…
Abstract
Purpose
Online gig labor platforms bring together a global and fast-growing workforce to complete highly granular, remote and decontextualized tasks. While these environments might be empowering to some workers, many others feel disenfranchised and removed from the final product of their labor. To better understand the antecedents of continued participation in forms of crowdsourced digital labor, the purpose of this paper is to explore the relationship between worker’s ability to create a narrative of their work mattering regardless, and their continued work engagement (WE) in these work setups.
Design/methodology/approach
The authors approach the relationship between individual mattering and digital WE through a longitudinal study among workers on the crowdworking platform Amazon Mechanical Turk. The authors further provide qualitative insight into individual perceptions of mattering based on essay data.
Findings
The authors develop a measure of mattering in crowdworking with four dimensions: reliance, social recognition, importance and interaction. Reliance is the most pronounced dimension, followed by interaction, importance and social recognition. In the final longitudinal model, only importance affects WE positively, while the other three mattering dimensions do not have a significant effect.
Originality/value
The findings indicate that individuals who feel that they themselves and their work “count” and “make a difference” will be more engaged in their digital labor. By clarifying the dimensionality of mattering in crowdwork and studying its differentiated effect on WE, the paper makes a contribution to research on crowdwork and the future of work. Beyond the theoretical contributions, the finding that perceived importance fosters WE has important implications for task and platform design.
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Yuhki Shiraishi, Jianwei Zhang, Daisuke Wakatsuki, Katsumi Kumai and Atsuyuki Morishima
The purpose of this paper is to explore the issues on how to achieve crowdsourced real-time captioning of sign language by deaf and hard-of-hearing (DHH) people, such that how a…
Abstract
Purpose
The purpose of this paper is to explore the issues on how to achieve crowdsourced real-time captioning of sign language by deaf and hard-of-hearing (DHH) people, such that how a system structure should be designed, how a continuous task of sign language captioning should be divided into microtasks and how many DHH people are required to maintain a high-quality real-time captioning.
Design/methodology/approach
The authors first propose a system structure, including the new design of worker roles, task division and task assignment. Then, based on an implemented prototype, the authors analyze the necessary setting for achieving a crowdsourced real-time captioning of sign language, test the feasibility of the proposed system and explore its robustness and improvability through four experiments.
Findings
The results of Experiment 1 have revealed the optimal method for task division, the necessary minimum number of groups and the necessary minimum number of workers in a group. The results of Experiment 2 have verified the feasibility of the crowdsourced real-time captioning of sign language by DHH people. The results of Experiment 3 and Experiment 4 have shown the robustness and improvability of the captioning system.
Originality/value
Although some crowdsourcing-based systems have been developed for the captioning of voice to text, the authors intend to resolve the issues on the captioning of sign language to text, for which the existing approaches do not work well due to the unique properties of sign language. Moreover, DHH people are generally considered as the ones who receive support from others, but our proposal helps them become the ones who offer support to others.
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