Burning gig, rewarding risk: Effects of dual exposure to incentive structure and heat condition on risky driving among on-demand food-delivery motorcyclists in Kaohsiung, Taiwan
{"title":"Burning gig, rewarding risk: Effects of dual exposure to incentive structure and heat condition on risky driving among on-demand food-delivery motorcyclists in Kaohsiung, Taiwan","authors":"Cheng-Kai Hsu","doi":"10.1016/j.aap.2024.107841","DOIUrl":null,"url":null,"abstract":"<div><div>The gig economy, characterized by short-term, task-based work facilitated via digital platforms, has raised various occupational safety concerns, including road safety risks and heat exposure faced by on-demand food delivery (ODFD) workers. Often using open modes of transportation, such as motorcycles and bicycles, these workers have minimal physical protection and direct environmental exposure while working long hours on the road, interacting with larger vehicles. Prior research has suggested that their road risks result from prevalent risky driving incentivized by platform-established business models, but quantitative evidence is lacking. Furthermore, while prolonged heat exposure may contribute to increased risky driving, our understanding of this relationship remains limited. This study investigates the impact of dual exposures to incentive structure and heat condition on risky driving among ODFD motorcyclists in Kaohsiung, Taiwan. A wearable sensing scheme was implemented, tracking a cohort of 40 ODFD workers during their work shifts in real time, collecting data on their speed, acceleration/deceleration patterns, incentive issuances, and heat exposure. Through a case-crossover approach, generalized linear cross-level mixed-effects models were employed to demonstrate the impact of incentive issuance on increasing risky driving among ODFD workers, including faster driving speeds, higher risks of speeding, harsher acceleration and braking, and more erratic acceleration patterns. Additionally, this study reveals that heat exposure, characterized by higher temperatures and humidity levels, exacerbates speed-related risky driving. These findings advance our understanding of causal mechanisms in two key areas of literature: firstly, the road safety risks faced by ODFD gig workers, and secondly, the broader relationship between heat exposure and risky driving. This research offers insights for policymakers to mitigate risky driving among ODFD workers, which is crucial in the context of climate change, where such urban economic dynamics may amplify climate-related inequities and place disproportionate safety burdens on vulnerable workers within the rapidly evolving gig economy.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"210 ","pages":"Article 107841"},"PeriodicalIF":5.7000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accident; analysis and prevention","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0001457524003865","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ERGONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The gig economy, characterized by short-term, task-based work facilitated via digital platforms, has raised various occupational safety concerns, including road safety risks and heat exposure faced by on-demand food delivery (ODFD) workers. Often using open modes of transportation, such as motorcycles and bicycles, these workers have minimal physical protection and direct environmental exposure while working long hours on the road, interacting with larger vehicles. Prior research has suggested that their road risks result from prevalent risky driving incentivized by platform-established business models, but quantitative evidence is lacking. Furthermore, while prolonged heat exposure may contribute to increased risky driving, our understanding of this relationship remains limited. This study investigates the impact of dual exposures to incentive structure and heat condition on risky driving among ODFD motorcyclists in Kaohsiung, Taiwan. A wearable sensing scheme was implemented, tracking a cohort of 40 ODFD workers during their work shifts in real time, collecting data on their speed, acceleration/deceleration patterns, incentive issuances, and heat exposure. Through a case-crossover approach, generalized linear cross-level mixed-effects models were employed to demonstrate the impact of incentive issuance on increasing risky driving among ODFD workers, including faster driving speeds, higher risks of speeding, harsher acceleration and braking, and more erratic acceleration patterns. Additionally, this study reveals that heat exposure, characterized by higher temperatures and humidity levels, exacerbates speed-related risky driving. These findings advance our understanding of causal mechanisms in two key areas of literature: firstly, the road safety risks faced by ODFD gig workers, and secondly, the broader relationship between heat exposure and risky driving. This research offers insights for policymakers to mitigate risky driving among ODFD workers, which is crucial in the context of climate change, where such urban economic dynamics may amplify climate-related inequities and place disproportionate safety burdens on vulnerable workers within the rapidly evolving gig economy.
期刊介绍:
Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.