Applying the sociotechnical systems theory to crowdsourcing food delivery platforms: the perspective of crowdsourced workers. Issue 7 (11th April 2022) - Lee, Somi; Chang, Howook (Sean); Cho, Meehee
Abstract : Purpose: Crowdsourcing food delivery represents great potential for future development and expansion of the restaurant business. Accordingly, job performance and retention of delivery workers are critical for success. Therefore, this paper aims to investigate how to enhance crowdsourced delivery workers' job performance and intent to continue working by applying the sociotechnical systems theory. Design/methodology/approach: The data analysis was conducted using responses obtained from crowdsourced food delivery workers. A structural equation model was developed to verify the hypothesized relationships. To test the proposed moderating roles of a three-dimensional concept of social capital within the research model, multi-group analyses were implemented. Findings: This study confirmed the significant relationships between crowdsourcing risks related to workers' low job commitment and technical systems, attributing to reduced job performance and intent to continue working. Results documented that social systems including networks, trust and shared vision mitigated the negative impact of the perceived difficulty and complexity of technical systems and job performance. Originality/value: Although technology has contributed significantly to the effectiveness of online food delivery, the literature has mainly focused on its benefits and has ignored the critical aspects derived from a virtual and technology-based workplace. This gap was addressed by verifying the important roles of social factors (networks, trust and shared visions) in reducing the negative impacts of technology-driven risks (perceived difficulty of task requirements and technology complexity) within the crowdsourcing food delivery context.