The effects of technological supervision on gig workers: organizational control and motivation of Uber, taxi, and limousine drivers

How Algorithmic Management Influences Gig Workers' Job Crafting

Algorithmic management, as a digital management tool in the gig economy, has become a hotspot of concern at the intersection of theory and practice. However, there is a lack of research on the mechanisms and boundary conditions through which algorithmic management affects gig workers' job crafting. Based on the social information processing theory, this study constructed a dual-mediation model of how algorithmic management influences gig workers' job crafting through gameful experience and perceived job autonomy. Data from 687 valid samples were collected through a two-stage survey and statistically analyzed using structural equation modeling (SEM). The results demonstrate that algorithmic management increases gig workers' promotion-focused job crafting behaviors (increasing job resources and challenging job demands) by stimulating their gameful experiences and increases gig workers' prevention-focused job crafting behaviors (decreasing hindering job demands) by inhibiting their perceived job autonomy. In addition, the higher-order personality trait core self-evaluation moderates the relationship between algorithmic management and gameful experience and perceived job autonomy, as well as the indirect effects of algorithmic management on job crafting through gameful experiences and perceived job autonomy. This study advances empirical research on algorithmic management in the field of the gig economy and human resource management practices. Crucially, it provides practical insights for optimizing algorithmic systems in platform companies, potentially enhancing their efficiency and economic benefits.

What Is on Your Gig Radar? Toward a Hierarchical Structure of Coping

Digitalized independent workers, known as gig workers, have been shown to work under high-pressure, with a lack of autonomy, a lack of feedback and perceived competence, and a high level of isolation. We conducted a literature review to investigate how gig workers cope with these sources of stress. We identified primary sources of psychological stress in gig work and the main strategies used by workers for coping with them. We show that focusing solely on identifying coping strategies depicts a fragmented literature, making it impossible to compare, link, or aggregate findings. We suggest a radar classification of coping based on the motivational action theory of coping and self-determination theory that defines coping as a process to adapt to the environment and maintain well-being. We argue that this framework is both relevant and necessary for developing research on gig-worker coping.

Exploring Uber Taxi Application Using the Technology Acceptance Model

The goal of this study was to investigate the accountability of the technology acceptance model (TAM) for Uber taxi applications. As antecedents of usefulness, this study selected three elements: time information, price information, and driver information. Data was collected using a survey on Amazon Mechanical Turk. The survey participants were users of the Uber taxi application. The number of valid observations for the data analysis was 412. For data analysis, frequency analysis, confirmatory factor analysis, correlation matrix, and structural equation modeling were utilized. The results show that the usefulness is significantly influenced by time and driver information. They further indicate that ease of use positively affects both usefulness and attitude. In addition, usefulness significantly determines attitude, and attitude toward the Uber taxi application exerts a substantial effect on intention to use. This study contributes to the literature by demonstrating the explanatory power of TAM using the Uber taxi application as a research subject.

Understanding and shaping the future of work with self-determination theory

Self-determination theory has shaped our understanding of what optimizes worker motivation by providing insights into how work context influences basic psychological needs for competence, autonomy and relatedness. As technological innovations change the nature of work, self-determination theory can provide insight into how the resulting uncertainty and interdependence might influence worker motivation, performance and well-being. In this Review, we summarize what self-determination theory has brought to the domain of work and how it is helping researchers and practitioners to shape the future of work. We consider how the experiences of job candidates are influenced by the new technologies used to assess and select them, and how self-determination theory can help to improve candidate attitudes and performance during selection assessments. We also discuss how technology transforms the design of work and its impact on worker motivation. We then describe three cases where technology is affecting work design and examine how this might influence needs satisfaction and motivation: remote work, virtual teamwork and algorithmic management. An understanding of how future work is likely to influence the satisfaction of the psychological needs of workers and how future work can be designed to satisfy such needs is of the utmost importance to worker performance and well-being.

Technology is changing the nature of work by enabling new forms of automation and communication. In this Review, Gagné et al. describe how self-determination theory can help researchers and practitioners to shape the future of work to ensure that it meets the psychological needs of workers.

Barriers to entry of gig workers in the gig platforms: exploring the dark side of the gig economy

Purpose

The alternative arrangements to traditional employment have become a promising area in the gig economy with the technological advancements dominating every work. The purpose of this paper is to explore the barriers to the entry of gig workers in gig platforms pertaining to the food delivery sector. It proposes a framework using interpretive structural modelling (ISM) for which systematic literature review is done to extract the variables. This analysis helps to examine the relationship between the entry barriers to gig platforms. The study further proposes strategies to reduce the entry barriers in gig sector which would help to enhance productivity and generate employment opportunities.

Design/methodology/approach

The study uses interpretive structural model (ISM) to ascertain the relationship between various entry barriers of the gig workers to the gig platforms. It also validates the relationship and understand the reasons of their association along with MICMAC analysis. The model was designed by consulting the gig workers and the experts allied to food delivery gig platforms namely Zomato and Swiggy.

Findings

It was observed that high competition, longer login hours and late-night deliveries are the significant barriers with high driving power and low dependence power. Poor payment structures and strict terms and conditions for receiving the incentives are interdependent on each other and have moderate driving and dependence power. The expenses borne by the gig workers, such as Internet, fuel and vehicle maintenance expenses have high dependence power and low driving power. Hence, they are relatively less significant than other barriers.

Research limitations/implications

The study is confined to food delivery sector of India, without considering other important sectors of gig economy for generalizing the framework. As the study is based on forming an ISM framework through literature review only, it does not consider other research methods for analysing the entry barriers to the gig platforms.

Practical implications

The study attempts to dig out the low entry barriers for gig workers in food delivery platforms as there is a dearth of analysis of these factors. This study would weave them using ISM framework to help the gig platforms overcome these barriers at various levels, thus adding to the body of literature.

Originality/value

The study discusses the need for understanding relationship between the entry barriers in the form of ISM model to identify the dependent and driving factors of the same.