Alternative work arrangements continue to increase in number and variety. We review the literature on alternative work arrangements published since the most recent major review of nonstandard work by Ashford et al. (2007). We look across the research findings to identify three dimensions of flexibility that undergird alternative work arrangements: (a) flexibility in the employment relationship, (b) flexibility in the scheduling of work, and (c) flexibility in where work is accomplished. We identify two images of the new world of work-one for high-skill workers who choose alternative work arrangements and the other for low-skill workers who struggle to make a living and are beholden to the needs of the organization. We close with future directions for research and practice for tending to the first image and moving away from the second image of the new world of work.

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Existing literature examines control and resistance in the context of service organizations that rely on both managers and customers to control workers during the execution of work. Digital platform companies, however, eschew managers in favor of algorithmically mediated customer control—that is, customers rate workers, and algorithms tally and track these ratings to control workers’ future platform-based opportunities. How has this shift in the distribution of control among platforms, customers, and workers affected the relationship between control and resistance? Drawing on workers’ experiences from a comparative ethnography of two of the largest platform companies, we find that platform use of algorithmically mediated customer control has expanded the service encounter such that organizational control and workers’ resistance extend well beyond the execution of work. We find that workers have the most latitude to deploy resistance early in the labor process but must adjust their resistance tactics because their ability to resist decreases in each subsequent stage of the labor process. Our paper, thus, develops understanding of resistance by examining the relationship between control and resistance before, during, and after a task, providing insight into how control and resistance function in the gig economy. We also demonstrate the limitations of platforms’ reliance on algorithmically mediated customer control by illuminating how workers’ everyday interactions with customers can influence and manipulate algorithms in ways that platforms cannot always observe.

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On-demand or “gig” workers show up to a workplace without walls, organizational routines, managers, or even coworkers. Without traditional organizational scaffolds, how do individuals make meaning of their work in a way that fosters engagement? Prior literature suggests that organizational practices, such as recruitment and socialization, foster group belonging and meaningfulness, which subsequently leads to engagement, and that without these practices alienation and attrition ensue. My four-year qualitative study of workers in the largest sector in the on-demand economy (ridehailing) suggests an alternative and more readily available mechanism of engagement—workplace games. Through interactions with touchpoints—in this context, the customer and the app—individuals turn their work into games they find meaningful, can control, and “win.” In the relational game, workers craft positive customer service encounters, offering gifts and extra services, in the pursuit of high customer ratings, which they track through the app’s rating system. In the efficiency game, workers set boundaries with customers, minimizing any “extra” behavior, in the pursuit of maximizing money per time spent driving and they create their own tracking tools outside the app. Whereas each game resulted in engagement—as workers were trying to “win”—games were associated with two divergent stances or relationships toward the work, with contrasting implications for retention. My findings embed meaning-making in what is fast-becoming the normal workplace, largely solitary and structured by emerging technologies, and holds insights for explaining why people remain engaged in a line of work typically deemed exploitative.

Managers and customers often expect individuals to be "ideal workers" devoted entirely to work, and this devotion is typically displayed through being available to work at any time, on any day (Reid, 2015). During the COVID-19 pandemic, many individuals in lower-paid, customer-facing jobs were expected to not only be available but also to take on physical risk. However, the ideal worker literature has paid relatively little attention to how risk relates to ideal worker expectations, reflecting in part the extant literature's focus on professionals who face relatively little physical and financial uncertainty. In this article, we draw upon the experiences of nonprofessional "gig" workers (TaskRabbit workers) to examine how they manage customers' ideal worker expectations-including risk-using data from interviews (n = 49), postings from online worker forums social media, and offical company communications. We show how these workers engage in different tactics to manage risk in response to customers' expectations, including two tactics-covering and withdrawing-that have not been discussed in prior ideal worker literature. In doing so, we expand scholarly understanding by showing how concerns about risk shape workers' responses to ideal worker expectations, particularly in customer-facing service work outside of traditional organizations.

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