Differences That Make a Difference: The Impact of Platform Worker Type on Drivers of Job Satisfaction in the Gig Economy

Differences That Make a Difference: The Impact of Platform Worker Type on Drivers of Job Satisfaction in the Gig Economy

  Nikki Sonneveld – Research Intern TNO Sarike Verbiest – Researcher TNO Dr. Mark Boons – Vrije Universiteit Amsterdam Dr. Jeroen Meijerink – University of Twente Division: Business & Economics  

EXTENDED ABSTRACT

Platform workers are the lifeblood of the gig economy. With more and more organizations moving towards the use of digital platforms to organize tasks performed by individuals who are not employed by the organization, it has become ever important to understand their drivers and motivations to perform tasks on behalf of digital platform organizations. A key determinant of employees’ willingness to work in traditional organizations is their job satisfaction (e.g. Locke, 1969). However, the concept of a ‘job’ in the gig economy is likely to be perceived differently than in traditional work contexts. For example, flexibility to work when and where one would like is likely to be much more important for gig workers than it is for employees of traditional organizations (e.g. Brawley & Pury, 2016). We would therefore expect different characteristics of the job to determine one’s degree of job satisfaction in the context of the gig economy. Moreover, anecdotal evidence suggests that platform workers come in different forms; a student who considers gig work as a side job to earn some extra cash will value different job characteristics than someone who works full time for a digital platform and is trying to support a family. This research aims to shed light on how these different platform worker types affect the importance of different job characteristics on job satisfaction. This research thus offers an interesting venue for further developing our understanding of the gig economy and its potential impact on the future of work. Based on a literature study of job satisfaction in traditional work contexts and exploratory research consisting of expert interviews in the context of the gig economy, we developed a model of job satisfaction in the gig economy. Combining potential drivers of job satisfaction from the literature with different personas of workers identified during the expert interviews led us to a research model in which we hypothesize that different types of workers emphasize different job characteristics as drivers of their job satisfaction. This research model is currently being tested by means of a survey that was sent out to platform workers through various Dutch gig work platforms. While the survey data collection has not been completed at the moment of submission of this abstract, we believe that the results of the survey will shed more light on several important aspects of gig economy platforms. Most importantly, we expect to be able to identify the most relevant drivers of platform workers’ job satisfaction as well as provide more insights into how these drivers might differ depending on the type of platform worker one is. The results of this research will thus have potentially interesting implications for both academia and practitioners. Ever since the concept of gig work has emerged, academics have been debating whether certain job characteristics of job work are good for workers or bad. We hope to contribute to this discussion by showing how this outcome depends on the type of platform worker one is; The aspects of gig work that some types of platform workers might value, other types of platform workers might actually dislike, and vice versa. Identifying the key types of platform workers will thus help researchers in better understanding how job characteristics drive platform workers’ degrees of job satisfaction. While practitioners are aware of the fact that there are different worker types active on their platform, they often do not know how these different types of platform workers are affected differently by the characteristics of jobs performed through the platform. Gaining a better understanding of the different platform worker types and how job characteristics impact their job satisfaction, helps platform organizers improve their decision making with regard to how they organize work through their platforms.