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This study aims to synthesize existing findings in the gig worker training literature and identify the training rationales adopted by these studies, using a synthesized framework of organizational training rationales. This study seeks to delineate the rationales behind gig worker training and highlight unaddressed training needs within digital platforms, ultimately proposing a research agenda for future studies in this area.

A systematic review methodology is adopted to synthesize and analyze empirical, peer-reviewed studies on gig worker training.

The systematic review reveals that competency and economic rationales are predominantly adopted in gig worker training studies, with the relationship rationale, common in traditional training, notably absent. This study also outlines seven future research directions to highlight identified challenges and unaddressed training needs.

To the best of the author’s knowledge, this study is the first work that systematically reviews existing findings on gig worker training.

This chapter will introduce the concept of the gig economy. It begins with a brief discussion of technological changes and their impact on the workforce and labour market, demonstrating how the trend shifts towards the gig economy. It then examines the trends that are influencing this transformation and discusses various perspectives and the attractiveness of the gig economy for workers and businesses. This chapter will also discuss the gig economy, platform economy, digital platform, and gig worker categories. It concludes with a brief discussion of some of the opportunities, issues, and challenges associated with the gig economy.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

In the previous chapters, we discussed the gig economy, knowledge economy, and its characteristics of each. The concept of knowledge workers is discussed in detail and their role in the knowledge economy and in creating knowledge. This chapter will explain how the knowledge economy and gig economy are connected and how the concept of knowledge workers and professional gig workers are connected. We will differentiate skilled gig workers from low-skilled workers and their role in economic development and productivity. Furthermore, we will explain their involvement in the organisation and how they can manage them and utilise their knowledge to increase productivity. The end of this chapter will discuss the platform economy concept and explain the platform economy's aspects in detail. This chapter emphasises how working globally is facilitated by digital transformation and IT infrastructure and how managing the professional workforce will create the opportunity to connect to a variety of job demands, particularly from developed countries.

The emerging nonstandard employment (i.e. gig work) makes gig workers face a series of forms of labor insecurity. Prior studies focus on the linkage between gig work insecurity and precariousness. However, how gig workers and platforms jointly handle gig work insecurity has been so far overlooked. To this end, this study aims to explore how gig platforms and workers jointly cope with the insecurity of the gig work model.

Building upon the JD-R model, this study used a double-level perspective to hypothesize how gig platforms and workers jointly cope with gig work insecurity. Second, 248 questionnaire data were collected from workers who worked for several gig platforms (e.g. Meituan, Eleme, DidiTax, Zhihu and Credamo) in China. Third, the analysis method based on the partial least squares structural equation model (PLS-SEM) was employed to test the study theoretical model.

Empirical findings show that gig workers can cope with gig work insecurity by crafting their work; gig platforms' formalization governance not only reduces gig work insecurity but also helps gig workers address it by more easily crafting their work.

Gig workers do always have not enough job resources and motivation to work hard. Gig workers merely rely on job crafting to cope with the insecurity of the gig work model, which is insufficient. Gig platforms should also formalize their current governance mechanisms, which can supplement gig workers' job resources and reduce their job demands so as to help them cope with such gig work insecurity.

These results advance the understanding of the joint roles of gig platforms and workers in addressing gig work insecurity and improve governance effectiveness and value of gig platforms.

The unique employment status of gig workers as independent contractors and their impact on consumers provide an important opportunity for the current research to understand gig workers' perceptions of their employment and how that affects job performance outcomes. These gig workers serve as the frontline service providers for platforms like Airbnb hosts, Lyft drivers and Wag walkers performing customer-facing services. However, their status as gig workers, not traditional employees, presents challenges to platforms. The purpose of this research is to gain insights into the profiles of gig workers, examine the challenges platforms have in retaining high-performing workers and provide a research agenda on this important group of frontline service providers.

Incorporating variables deemed important in examining self-determination theory, a large-scale data collection via an online survey was administered, yielding 447 completed surveys. A two-step cluster analysis procedure was conducted to categorize sample respondents into four distinct groups.

Four groups emerged from the cluster analysis, labeled “Ambivalent Outsider,” “Competent Cog,” “Independent Insider” and “Committed Comrade.” The results suggest that there are significant differences across all variables and groups based on gig worker responses and self-reported customer satisfaction scores. The gig worker profiles developed are then utilized to formulate research propositions that are the basis for the research agenda presented.

The goal of many collaborative consumption platforms may be to hire Independent Insiders or Committed Comrades; however, that is difficult to attain with every hire. Thus, the segmentation results provide insights for companies seeking to hire, retain, and successfully motivate their workforce.

Given the freedom and flexibility afforded to gig workers, and the importance they have on the service experience for customers, understanding their own perceptions of employment and performance is critical to ensuring a positive experience for all parties. Research on collaborative consumption has largely focused on consumers or the management of freelance workers with only tangential applicability to gig work. This paper offers a comprehensive research agenda for gig worker management based on the typology of gig workers created.

High-quality employee motivation can contribute to an organization’s long-term success by supporting employees’ well-being and performance. Nevertheless, there is a paucity of research concerning how organizations motivate workers in non-traditional work contexts. In the algocratic context of the gig-economy, the purpose of this paper is to understand the role that technology can play in motivating workers.

Drawing on the self-determination theory, job-characteristic theory and enterprise social media research, this conceptual paper explores how the architecture of the digital labor platforms underlying the gig-economy (and the characteristics of jobs mediated through these IT artifacts) can impact key antecedents of self-motivation.

Combining theory and empirical evidence, this paper develops a mid-range theory demonstrating how organizations can support the self-motivation of gig-workers through the thoughtful design of their digital labor platforms and the integration of two social media tools (namely, social networking and social badging).

This paper answers calls for psychologically-based research exploring the consequences of gig-work as well as research studying the impacts of advanced technologies in interaction with work contexts on motivation. In theorizing around a large set of social-contextual variables operating at different levels of analysis, this paper demonstrates that individual-level motivation can be influenced by both task-based and organizational-level factors, in addition to individual-level factors.

The proposed theory provides novel insight into how gig-organizations can leverage widely accessible social media technology to motivate platform workers in the absence of human supervision and support. Theoretical and practical implications are discussed.

Gig workers form the backbone of any crowdsourcing platform where they showcase their talent and choose a job of their choice and freedom. The study explores the role of information quality (IQ) and social-mediated dialogue (SMD) in evaluating gig worker engagement and productivity on crowdsourcing platforms. The authors also propose to understand how gig worker productivity could be improved under the moderating effect of game elements.

A conceptual model was developed and empirically tested by integrating media richness theory and dialogic public relation theory. Data were collected from gig workers that are involved in crowdsourcing activities for the past three years. An overall sample of 346 gig workers contributing to at least one of the crowdsourcing platforms was collected. The authors tested the hypotheses using Warp PLS 7.0. Warp PLS 7.0 uses partial least square (PLS) structured equation modeling (SEM) and has been used widely to test path analytical models.

Results reveal that the information quality plays an essential role in the SMD, thereby fostering gig workers' productivity and engagement, which could be improved in the presence of game elements due to their nature of supporting rewards. However, engagement in the platform leading to improved productivity was not supported.

The study lays practical foundations for crowdsourcing platforms as it sets the importance of both IQ and dialogic communication channels. The two-way communication between gig workers and the platforms via accurate, timely, valuable and reliable information forms the key to the task's success. The introduction of the right game element will help to achieve better engagement and productivity.

This study also offers a new dimension to media richness theory and dialogic public relation theory in crowdsourcing platforms. The results would help platform designers and gig employers understand gig workers' quality and performance in a platform economy. The study uniquely positions itself in the area of crowdsourcing platforms by using game elements.