The Career Development of Food Delivery Riders in China: A Qualitative Investigation

The Career Development of Food Delivery Riders in China: A Qualitative Investigation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Career Development of Food Delivery Riders in China: A Qualitative Investigation Wei Wan, Weihua Liu, Huiling Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4935308/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: With the rise of the gig economy, platform work has has grown significantly throughout the world. As one of the most dynamic platform workers in China, food delivery riders are an underrepresented group in terms of securing decent work. Building on the Psychology of Working Theory(PWT), the current study aimed to explore how contextual and individual factorsinfluenced the career development of food delivery riders in China. This study also examined their attitudes towards platform work and their career aspirations. Methods: We conducted semi-structured interviews with 12 participants aged 18-45 and utilized Consensual Qualitative Research (CQR) approach to conduct data analysis. Results: The results revealed that economic constraints, inadequate education, and limited social capital were the main vocational barriers for these riders. Their coping resources included social support, critical consciousness, proactive personality, and self-leadership. Although food delivery work allowed them to earn a living, it featured long working hours, poor working conditions, limited benefits, etc. As such, they experienced job dissatisfaction, occupational fatigue, and turnover intentions. Regarding future goals, our participants mentioned finding a more decent job, learning new skills, and starting a business. Conclusion: Overall, this study marks the first known application of PWT to understand how food delivery riders navigate the new world of work in China. Practical implications and directions for future studies are discussed. Biological sciences/Psychology Health sciences/Health occupations career development psychology of working food delivery riders qualitative research China Introduction With the rise of the gig economy, research on platform work has seen a significant increase in recent years (Duggan et al., 2022; Rai & Mukherjee, 2024). As part of the rapidly expanding ‘platform capitalism’, platforms act as online labour intermediaries, connecting consumer demand with a supply of temporary or short-term workers (Graham et al., 2017; Spreitzer et al., 2017). Platform work has reshaped the nature of employment relations by promoting flexible work arrangements and transferring the responsibility for job security and necessary benefits (e.g., healthcare) to gig workers themselves, thereby resulting in precarious labor conditions and a host of undesirable work outcomes (Galière, 2020; Kellogg et al., 2020; Spurk & Straub, 2020; Wood et al., 2019). From a career perspective, it is crucial to understand the impact of external barriers on gig workers’ career development and to identify the coping resources they use to overcome these constraints (Retkowsky et al., 2023). The Psychology of Working Theory (PWT; Duffy et al., 2016) was developed to capture the career development of all individuals, with a particular focus on those who face contextual constraints in their pursuit of decent work. The theory highlights that decent work comprising basic workplace components should be accessible to all employed adults, as it is closely connected to individuals’ work fulfillment and overall well-being. To date, numerous research has utilized PWT to explore the work experiences of marginalized employed adults in the Western context (e.g., Allan et al., 2019; Kim et al., 2018; Tokar & Kaut, 2018), and some studies have expanded this theory to assess the experience of working adults in China (Han et al., 2022; Wan & Duffy, 2023; Wang et al., 2019). However, these research has primarily focused on formal employment groups, with relatively little attention given to informal employment groups. In particular, there is a significant gap in the PWT literature regarding the career development of platform workers in the era of booming gig economy. Additionally, extant studies typically utilize quantitative methods to investigate associations between predetermined variables, which may not fully capture the complex career paths of working populations and the factors that shape them. Therefore, this study attempts to address the aforementioned gaps by employing qualitative methods to explore the vocational experiences of Chinese platform workers from a PWT perspective. Given that food delivery riders epitomize gig workers and are particularly vulnerable in terms of career development (Wu et al., 2022), our primary aim is to investigate the contextual and individual factors that may impact their perception of choice and access to decent work. We are also interested in their attitudes towards their food delivery roles and the prospects they envision for the future. This qualitative research marks the first known use of PWT to understand how food delivery riders navigate the evolving world of work in a non-Western, collectivist cultural context. Our findings are expected to provide implications for career counselors, platform leaders, and policymakers who seek to promote the career development of food delivery riders on digital labor platforms. Food delivery riders in China The digitally-driven gig economy has emerged as one of the fastest-growing sectors in China, offering flexible work arrangements and new opportunities for employment (Sun, 2019). By the end of 2021, China had approximately 200 million flexible workers, which accounted for about 26% of the total employment population. As one of the most dynamic groups within this workforce, food-delivery platform workers have attracted widespread attention from academia due to their precarious labor conditions (Huang et al., 2023). These workers rely heavily on electric motorbikes to complete their tasks and thus are referred to as “riders” in China (Qian et al., 2024). A notable demographic characteristic of Chinese food delivery riders is that most of them are rural-to-urban migrant workers (Wu et al., 2022). This implies that they are socially and economically disadvantaged groups residing in urban areas. Under China’s household registration (hukou) system, rural migrants are not entitled to enjoy the same level of social welfare as urban residents, such as healthcare and education benefits (Wong et al., 2007). Additionally, numerous migrant workers flock to food delivery platforms due to the prospect of earning a substantial income (Huang et al., 2023). Time and physical labor are these riders’ primary resources for production, so they generally work long hours and take as many orders as possible in order to maximize their earnings (Zheng & Wu, 2020). Food delivery platforms in China are primarily modeled after Uber and heavily depend on algorithms to manage their laborers (Sun, 2019). First, these platforms use algorithms to assign orders to the rider who is closest to a particular restaurant (Huang et al., 2023). Once a delivery order is accepted, algorithms plan the most efficient delivery route for riders and begin tracking their real-time movements (Wu et al., 2022). Additionally, riders’ performance is closely monitored by algorithms and evaluated by delivery speed, customer ratings, and order completion rates (Huang, 2022). It is no exaggeration to say that the entire work process of food delivery riders is strictly managed by algorithmic technologies. Given that food delivery riders are a particularly vulnerable group amid the development of China’s gig economy, the contextual constraints and coping strategies related to their career development warrant attention from scholars and those advocating for workplace equity and social justice. It is also crucial to understand their perspectives on platform work and career goals, which may provide implications for career counselors, platform managers and policymakers. Theoretical Framework The current study is grounded in the newly developed PWT, which intends to capture the vocational experiences of all individuals (Duffy et al., 2016). While traditional vocational theories largely favor those who have a degree of choice in their careers, PWT articulates the significant obstacles that persist in obtaining decent work for many underprivileged populations throughout the world. As the core construct of PWT, decent work is conceptualized to encompass (1) a safe work environment, (2) fair compensation, (3) access to healthcare, (4) adequate time off, and (5) organizational values that match family and social values (Duffy et al., 2016). PWT is a complex theory which outlines 32 propositions about the predictors and outcomes of decent work. The predictor section of the PWT model suggests that economic constraints and marginalization prevent individuals from securing decent work, with these effects mediated by two psychological resources (i.e. work volition and career adaptability). Additionally, PWT proposes that four moderators (i.e. proactive personality, critical consciousness, economic conditions, and social support) may mitigate the negative impact of contextual constraints on psychological variables and access to decent work. Regarding the outcome portion of the model, decent work attainment is directly related to the satisfaction of basic human needs, including survival, social contribution, and self-determination needs (autonomy, relatedness, and competence). PWT posits that decent work satisfies these needs over time, which in turn increases work-related and general mental and physical well-being. To date, a large body of research has supported the core assumptions of the model among diverse working populations across both individualistic and collectivist cultural contexts (see Duffy et al., 2023 for a summary of studies on PWT). PWT serves as an informative theoretical framework for the current study, which informed our research questions. We delve into the work-related obstacles faced by food delivery riders, stemming from their lower socioeconomic status and other systemic constraints, which, as PWT suggests, contribute to the ongoing lack of access to decent work (Duffy et al., 2016). This framework offers particular insight into how food delivery riders surmount workplace adversities and interpret their jobs. Additionally, this study examines the interactions of contextual and individual factors in relation to food delivery riders’ work aspirations, which is also a central tenet of PWT (Duffy et al., 2016). The Present Study Food delivery riders are not often asked about their work-related experiences, challenges, and possibilities from a PWT perspective, making this an understudied phenomenon that requires further investigation. In the current study, we aimed to investigate the contextual and individual factors in the career development of Chinese food delivery riders through a PWT lens, as well as how these factors impact their work volition and access to decent work. Additionally, we sought to explore their gig work experiences and career aspirations. To achieve these goals, we conducted a qualitative research to gain an in-depth understanding of participants’ nuanced vocational trajectories. In particular, we employed Hill et al.’s (2005) Consensual Qualitative Research (CQR) approach to analyze the semi-structured interview data. Hill and Knox (2021) argued that CQR is “particularly useful for investigations of inner events about which participants may have ambivalent or suppressed feelings that cannot be easily observed by outsiders” (p.7). As such, the qualitative nature of this study allowed us to capture rich account of how participants perceive the world of work based on their lived experiences by examining the following questions: (a) What contextual barriers do the participants encounter, and how do these barriers affect their work volition and access to decent work? (b) What external supports and individual adaptive strategies do they employ to mitigate the adverse effects of contextual constraints? (c) How do participants perceive their current work and future prospects? Method Participants This study involved participants who met the following criteria: (a) being at least 18 years old, (b) being currently employed by digital labor platforms, and (c) working as food delivery riders in China. We conducted semi-structured interviews with 12 participants (10 men and 2 women) to explore their vocational experiences. The participants’ ages ranged from 18 to 45 years old, with a mean age of 26. In terms of education, six participants reported graduating from junior high school, four from trade school, and two from primary school. Regarding marital status, eight participants reported being unmarried, while four reported being married. When asked about residence registration, nine participants reported coming from rural areas, and three from urban areas. On average, the participants had worked as food delivery riders for 13 months. See Table 1 for a detailed summary of participants’ demographic information. [Insert Table 1 here] Protocol Development Building on the tenets of PWT (Duffy et al., 2016), we developed an initial interview protocol for participants’ career development. Additionally, we sought feedback from an experienced scholar in vocational psychology on the protocol and made minor adjustments to the wording of several questions. The final protocol, consisting of eight open-ended questions, explored a wide range of topics related to participants’ work lives, including structural barriers, external supports, personal resources, work volition, perceptions of decent work, and career aspirations. Prior to the above questions, the participants were required to provide demographic information, such as gender, age, education, marital status, and household residence registration. The detailed interview questions can be seen in the Appendix. After creating the protocol, we conducted pilot interviews with two eligible participants who confirmed that the questions were relevant to their vocational experiences. Procedure After obtaining IRB approval from the first author’s university, we utilized a combination of convenience and snowball sampling to recruit participants. Specifically, we identified two local offline work sites of Meituan Takeaway, a leading online food-delivery platform in China, and explained the purpose of our research to their managers. After obtaining their permission, we advertised the current study in their online work groups, relying heavily on word-of-mouth to inform prospective participants about our research. Those who expressed interest were directed to contact the first author for more information and to schedule an appropriate time for an in-person interview. All interviews were conducted at the participants’ offline work site and lasted approximately 60 minutes. We ceased data collection upon reaching the point of saturation, where new interviews yielded no further information (Morrow, 2005). Before each interview, we explained the purpose of our research to the participants and reassured them that their information would be kept confidential. Informed consent was obtained from all participants for this study, and they had right to withdraw at any time if they felt uncomfortable during the interview. Participants were not offered any financial incentives for participating in this research. Throughout the interviews, we followed the protocol to ensure participants answered all the open-ended questions. To elicit more details, we used prompts like “Why is that?” or “Any examples?” After each interview, the first author organized recordings and field notes within 24 hours to create transcripts. Prior to data analysis, we shared preliminary transcripts with participants for review, and they were given the opportunity to delete any information they did not wish to disclose. Since all interviews were carried out in Chinese, the data analysis process was also conducted in Chinese in order to minimize the loss of meaning. The first author of this study, who holds a Bachelor's degree in English, translated the interview protocol as well as all the codes (including domains, categories, and quotes) into English during the writing process. A native English speaker who is proficient in Chinese was also invited to increase the accuracy of the translation and to minimize any potential bias. Research Team The research team included three coders and an auditor, representing diversity in terms of gender, age, social class, educational background, and knowledge of related theory and research. All members were passionate about improving the employment prospects of food delivery riders. The first coder has a Ph.D. in human resource management and extensive experience conducting qualitative research on the career development of disadvantaged populations. In the current study, she trained the other two student coders on conducting the data analysis. One is a graduate student whose father worked as a food delivery rider, and the other is an undergraduate student who has experience of working as a food delivery rider. An external auditor with a strong understanding of PWT and qualitative research methods was included in the research to provide critique on the coding results. To ensure that all team members were well-versed in the CQR procedure, they were required to read Hill et al.’s (2005) article and attend several meetings to study recent examples of CQR analyses (e.g., Gilson et al., 2022; Kenny et al., 2023). Prior to the beginning of the coding process, coding members engaged in discussions regarding their biases concerning the current research. Based on our personal experiences and familiarity with PWT research, we believed that economic constraints and marginalization would negatively affect food delivery riders’ vocational experiences. All coders not only endorsed expectations that participants would report barriers related to access to decent work but also acknowledged potential biases related to social security issues faced by food delivery riders. For instance, the first author, who lives in a bustling commercial district, is exposed to numerous food delivery riders every day. This situation has led to reflection on the challenges these riders encounter, such as the dangers posed by severe weather and the inherent risks of riding motorcycles. Given these biases, the coding team agreed on the importance of strictly adhering to the CQR guidelines and avoiding premature interpretation. Throughout the coding process, the coding members should return to the data repeatedly to check the accuracy of the codes and engage in group discussion to resolve areas of discrepancies. Additionally, the research team sought to create an equal setting where the student coders were encouraged to express their opinions freely in the consensus-building process. They were also given opportunities to speak first in meetings in order to mitigate the potential effect of the “dominant” faculty coder. Data Analysis The interview data were analyzed using the CQR approach, which involves three key steps: coding of domains, creating core ideas, and conducting a cross-analysis (Hill et al., 2005). At each stage of the data analysis, coding was independently completed by the three coders. The coding team then met to review their respective lists of codes and discussed points of disagreement before reaching a consensus on the codes. Finally, the auditor checked the codes to reduce the effects of group thinking. Coding of domains . Based on existing literature and interview questions, we first established a list of domains which allowed us to categorize large amounts of data into manageable sections (Hill et al., 2005). Throughout the coding process, domains can be merged, separated, or added if necessary. For instance, a domain called “Work-related Outcomes” emerged after creating our initial list because we did not ask any direct questions about it, but this domain arose in the data regardless. After creating an initial list of domains, each coding member independently analyzed transcripts by assigning similar data to the appropriate domain. Finally, the coding team met to discuss the coded transcripts until reaching a consensus on the domains of each interview. Core ideas . To create core ideas, the coding team aimed to extract the most important information from the participants’ responses. For example, if a transcript within the domain of “Structural Barriers” discussed the lack of social capital that comes with migrating to urban areas, a core idea for that domain might be “Participants reported having limited social connections due to rural-to-urban migration.” Following Hill et al.'s (2005) guidelines, we made sure that all core ideas were closely related to the data and did not include any personal interpretations. Each coder independently developed core ideas before meeting with other team members to address any discrepancies and reach a consensus. Cross-analysis . The coding team conducted a cross-analysis to generate a list of categories for each domain by examining recurring themes across interviews. This stage required more interpretation from researchers than previous ones. For example, when observing core ideas about limited social capital appearing in multiple interviews, we developed a category named “limited social capital”. Each coder independently performed the cross-analysis and then presented their generated categories to the group for discussion. We collaborated to reach a consensus on the wording of the categories and how to arrange the core ideas into them. Auditing . After each round of the above analysis, the auditor was asked to provide feedback on the results for the coding team. Specifically, the auditor's role was to verify that the raw data fell within appropriate domains, that the core ideas succinctly captured the essence of all relevant information, and that the categories generated by the cross-analysis were appropriately named. The auditor provided written feedback that largely validated the work of the coding team, but suggested that some categories be renamed for clarity and conciseness. After determining that the transcripts contained sufficient evidence to support the auditor's suggested changes, the coding team incorporated his feedback into the findings. Results The data analysis revealed five domains: (a) structural barriers, (b) coping resources, (c) view of current work, (d) work-related outcomes, and (e) view of future. Categories that emerged from each of these domains were labeled according to the CQR method. General categories were those discussed by all or almost all participants, while typical and variant categories were those mentioned by more than half or less than half of the sample, respectively. Categories that appeared in only one or two cases were dropped. In the sections below, we provide a detailed description of the general and typical categories, supported by participant quotes. A list of domains, categories, and frequencies is provided in Table 2. [Insert Table 2 here] Structural barriers The domain labeled as “Structural Barriers” captured factors that participants reported as either directly or indirectly hindering their capacity to obtain decent work. The general and typical categories within this domain consisted of economic constraints, a lack of education, and limited social capital. Economic constraints. All participants identified limited economic resources as a major obstacle to their career development. They discussed various aspects of financial struggles, with the most frequently mentioned difficulty being the need to pay for basic survival needs. In order to reduce the financial burden on their families, most of our participants chose to work after completing junior high school. Bob shared his early experience of working in a restaurant due to limited family income: When I turned 15, my parents asked me to stop schooling. They thought sending me to school was a waste of money as I was not good at it. Many factories didn’t hire minors, so I ended up working as a dishwasher in a relative’s restaurant, earning about 1,500 RMB (approximately $210) per month. The salary was far from enough to lift my family out of poverty, but it allowed me to meet my basic needs, like buying food and clothes. Additionally, participants frequently discussed how economic constraints had driven them to join food delivery platforms. Peter described his experience as follows: I worked as an excavator operator for two years at a construction site. It was physically demanding, but I only earned 2,000 RMB ($280) per month. It made me feel my efforts weren’t worth it. Later, a friend suggested me to deliver takeout. He told me this job is remunerated on a piece rate basis, which means my earnings depend on the number of orders I fulfill each month. Inadequate education. Ten participants reported that limited education was an overarching obstacle to pursing their career goals. They specifically emphasized the adverse impact of inadequate education on their work volition and eventual access to decent work. When asked about barriers to securing decent work, Molly said that not having much education limited her options: Although I admire white-collar workers, I know my own limitations. Nowadays, perhaps the only industry that does not require a degree is food-delivery. I have no education or skills. In order to earn a living, I had no choice but to become a food delivery riders as I am not qualified for any other work. Limited social capital. Eight participants mentioned significant challenges in securing decent employment opportunities due to a lack of social capital. They shared the view that Guanxi, or connections to influential individuals, is essential for career advancement. However, as most of our participants come from rural areas, they reported being socially disadvantaged in urban settings. Mario, for example, articulated how insufficient social capital impeded his capability to land a decent job: I come from a small village. I don’t know anyone in the city. I have no one to rely on but myself. I find it so hard to find a job without connections because most employers require a reference. This makes me feel very frustrated. The only jobs available are temporary and low-paid service jobs. They don’t care about your background; all they need is your manual labor. Coping Resources The domain labeled as “Coping Resources” represented factors that participants identified as contributing to their vocational pathways. General and typical categories within this domain were social support, proactive personality, critical consciousness, and self-leadership. Social support . All but one of our participants reported that social support was a crucial resource in their career development. Specifically, they mentioned receiving assistance from their families, establishing connections with fellow villagers, and networking with other food delivery riders. Regarding family support, most participants reported receiving emotional support and guidance on navigating the workforce. Jason, who recently started working as a food delivery rider, put it this way: My parents don’t interfere with what I do as long as it’s not illegal. However, my older brother often reminds me to be polite to people, especially customers. He asked me to be patient and not rush into things, otherwise it’s easy to get into conflicts with others. Additionally, the majority of participants stated that their connections to people from their hometown were a valuable source of information regarding employment opportunities. Alex shared an example of how a conversation with a fellow villager influenced his decision to become a food delivery rider: I used to work as an assembly line worker in the factory. One day after work, I chatted with him [fellow villager] and complained about the hard work and low salary. He told me he was delivering takeout and it was more flexible than other physically demanding jobs. He said he could earn 6,000 RMB (around $840) a month, and sometimes even more than 10,000 RMB (about $1,400). After this, I became very interested and decided to quit my job. Finally, most participants stated that interacting with other delivery riders was a valuable source of support for them. They described this as advantageous because it reduced feelings of loneliness and motivated them to persist in achieving their goals. Mario, a newcomer to the food delivery platform, elucidated how socializing with other riders helped him enhance his work efficiency: I’m not familiar with many of the local roads. In the beginning, I relied heavily on navigation, but after working for a while, I found it’s sometimes unreliable and often leads me to a small alley where there is no signal. By chatting with other food delivery riders, I’ve learned how they strategically plan their routes before delivering food. This has helped me improve delivery speed. Proactive personality. Eight participants reported that they adopted positive coping strategies to overcome various difficulties they encountered in their work. One such strategy was providing additional services to customers beyond just delivering food. Lucy shared how offering extra services helped her achieve desirable outcomes, “Every time I’m on my way to deliver food, I will call the customer in advance to see if they need me to bring anything else, like cigarettes or drinks. After the delivery, I also offer to help them take out the trash. In return for my help, most customers agree to give me positive reviews on my service on the platform.” Additionally, most participants emphasized the importance of proactively communicating with platform staff. For instance, Arron stated: During peak hours for food-delivery, such as from 12 pm to 2 pm, the platform assigns multiple orders at once with significant distances between destinations. If I anticipate difficulty completing all the tasks, I will call the back-end personnel and inform them that I am currently on a delivery and suggest assigning the other orders to other riders. Critical consciousness. More than half of the participants ( n = 7) described that their social disadvantages had actually heightened their critical consciousness. In particular, they were aware that platforms were exploiting their labor via algorithms. John exemplified this by stating, “Our entire working process is exposed to algorithmic monitoring, and the platform uses algorithms to push us to continuously improve delivery speed. Under the hegemony of algorithms, we are forced to self-exploit and rely on increasing the number of orders to generate more income.” In addition to critically reflecting on algorithmic control, several participants also engaged in advocacy to protect their rights when confronted with unreasonable treatment. Bob shared his experience as follows: If I receive a long-distance order and the system keeps assigning other long-distance orders, it’s very likely that the previous order was given negative feedback or complained about by the customer. Maybe the platform wants to punish you. When this happens, you need to figure out the reason in time, and appeal to the platform or report to your station. Self-leadership. Seven participants reported that self-leadership, including goal setting, self-motivation, and emotional regulation, was a vital psychological resource for managing work-related stress. First, some participants discussed that they would adjust their work goals in a timely manner based on the surrounding environment. Molly shared, “When picking up orders, I keep an eye out for popular restaurants or those with promotions or special events. These types of restaurants usually have more orders and faster service. During non-peak hours, I prefer to wait for orders near such restaurants.” Likewise, Lucy described how she plans her daily work, “Before starting my work every day, I set a target for the number of orders I want to delivery and roughly plan my delivery routes. This helps me establish a more regular routine for my working hours and increase my work efficiency.” In addition, some participants mentioned that if they completed their tasks for the day ahead of schedule, they would reward themselves with a half day off the next day. In terms of emotional regulation, several participants reported actively regulating their emotions and internalizing external expectations as their own. Jason described how emotional management helped him get through difficult times: During a particularly difficult period, I frequently encountered customers who gave bad reviews without any justification. Even though I felt really depressed and unfairly treated, I had no choice but to tolerate it. But whenever I remind myself that my job is to serve others, I would feel much better. View of Current Work The “View of Current Work” domain revealed the participants’ perspectives on their work for food delivery platforms. General and typical categories in this domain included means of livelihood, lack of essential benefits, long working hours, indecent work conditions, and low skill requirements. Means of livelihood. All participants linked their current work to independence and the financial support of their daily lives. They described that being financially independent allowed them to fulfill their basic needs, such as paying for rent, food and clothing. Tim stated, “With the money I earn, I’m able to rent a small apartment in the city and live on my own.” In addition to meeting their own needs, some participants also reported that the income derived from food delivery work allowed them to support their families. Arron emphasized that the meaning of work was to alleviate the financial burden on his parents: Both my parents work in agriculture, growing vegetables and raising chickens. I also have a younger sister who has a talent for studies. I spend long hours delivering takeout every day because I hope to support her to attend college in the future. Lack of essential benefits. All participants reported receiving limited benefits from their work. They explained that online labor platforms only provided them with accident insurance due to the high risk of occupational injuries. However, they did not have access to insurance related to healthcare, pension, unemployment, and maternity, which are available to traditional employees. Bob explained this in details, “The platform takes 3 RMB (around $0.4) from the earnings of our first delivery order each day as daily accident insurance, but the coverage provided by this policy is significantly less than that offered by employee work-related injury insurance.” For those participants who were more aware of social security, they would purchase medical insurance on their own or pay for relevant insurance through their friends or relatives’ companies. Long working hours. Ten participants reported working more than ten hours every day, with only three or four days off every month. They also mentioned that online labor platforms tend to increase the number of tasks during holidays or harsh weather, thereby leading to extended working hours and no days off. Peter shared his experience of coping with excessive workload on rainy days: On normal days, there are only around ten orders during peak hours, but when it rains heavily, the number of orders is beyond count. Despite this, I still have to deliver them because if I don’t, the platform may punish me by not assigning me any orders in the future. And in order to complete these tasks on rainy days, I don’t even have time to eat. Indecent work conditions. Nine participants shared their experiences of working in poor environments, where they were often exposed to harsh weather conditions. For instance, Robin described the negative impact of the heat on his work, “The summer here is notoriously hot, with temperatures often exceeding 40 degrees Celsius. Prolonged exposure to the sun can easily lead to heatstroke. For someone like me who is overweight and sensitive to heat, it can be a real challenge to complete tasks in such work conditions.” Additionally, most participants mentioned a host of safety issues while riding motorcycles on the road. Alex shared his experience of almost having a car accident: As I was waiting at the intersection, there were no cars in sight. I decided to ride through it quickly. Suddenly, a car sped past me and I was completely taken aback. All I could think of was making sure I didn’t hit it, or else I would be late. Luckily, I wasn’t hurt, but the soup inside my bag spilled out. Low skill requirements. Over half of the participants ( n = 8) reported that their job requirements were minimal and involved a low level of technical expertise. Molly elaborated on the process of becoming a food delivery rider: The first step is to register online and provide your ID card to the platform. They will verify if you have a criminal record, and if you do, you will not be eligible for the job. After that, you need to show your ability to use a smartphone and ride a motorcycle. Finally, you are required to pay a deposit to the platform in exchange for essential items, such as a thermal box, uniforms, a helmet, gloves, etc. Additionally, as food delivery work does not have specific skill requirements, most participants expressed a low sense of career identity and felt worried about their career prospects. For example, Eric stated, “I’ve been working as a food delivery rider for two years, but I’m not better than those new riders. I don’t have any specialized skills or training. I don’t see much room for growth working in this field.” Work-related Outcomes The domain labeled as “Work-related Outcomes” captured the impact of the participants’ current work on other work-related variables. Typical categories within this domain included lower job satisfaction, occupational fatigue, and turnover intentions. Lower job satisfaction. Most of our participants ( n = 10) reported that they were not very satisfied with their current work. Specifically, they complained a lot about the increasingly strict algorithmic management, which has led to extended working hours and reduced income. Eric expressed his dissatisfaction with the following statements: Last year, I only had to work 10 hours a day and my monthly income was over 10,000 RMB (around $1,400). But now I have to work 13 hours a day and my monthly income is less than 8,000 RMB (approximately $1,118). The platform not only keeps reducing our delivery time but also lowers the pay for each order. It’s really frustrating. I feel like I’m working harder but not getting paid enough. Occupational fatigue. Nine participants reported that they experienced physical and mental exhaustion in their work. They specifically mentioned feeling nervous and anxious due to the omnipresent algorithmic control imposed by platforms. Peter put it this way, “In front of the algorithm, I feel like a transparent person. No matter where I go, I’m constantly monitored by the system.” In addition to this prison-style monitoring, most participants reported feeling stressful due to the real-time normative guidance and tracking evaluation provided by the platform. John, for example, described the time pressure that most food delivery riders face. He said, “When we receive an order, algorithms will automatically calculate the delivery time, and we need to deliver it within that time. If we are one second late, we may face fines from the platform or negative reviews from customers.” Meanwhile, most of our participants expressed concerns about their physical health due to long working hours. For instance, Tim stated: I work more than 14 hours every day to earn more money. In just one month of non-stop work, I lost 10 pounds or so. When I get home, I often feel so exhausted that I fall asleep as soon as my head hits the pillow. This job is pushing me to my limits. I can no longer afford to overdraw my health like this. Turnover intentions. Over half of the participants ( n = 9) discussed their intention to seek out a different job that would provide greater safety and dignity. Alex reported, “I work outdoors in all weather conditions, no matter it’s scorching in summer or chilly in winter. It’s especially easy to slip and fall on rainy days. My families have great concerns about my safety. If there are better options, I will quit this job immediately.” Robin mentioned a similar intent to find alternative employment opportunities: I understand that some people view our work as inferior, and the media often portrays us negatively. They claim that we lack quality and don’t follow traffic rules or something like that. This kind of stigmatization makes me depressed. Although I don’t have much education, I still hope to have a job that is respected by others. View of Future The “View of Future” domain reflected the participants’ plans for their future. Typical categories in this domain included the desire to find a more decent job, learn new skills, and start a business. Find a more decent job. Eight participants regarded their current work as a stepping stone to a more decent and stable job in the future. They shared the belief that gig work was not their ideal career. Eric described his plan as follows: I think this job has no future. Except earning a living, there is no social security, no social status, and no promotion opportunities. I plan to quit next month. I have a friend who is engaged in live-streaming e-commerce. He is in need of staff. I know the job will be challenging, but he promised to offer me healthcare and other benefits. Learn new skills. Instead of explicitly describing their career goals, eight participants reported their plans to develop more survival skills. Tim, who just turned 18 last year, is preparing to obtain his driver’s license. He said, “Driving is a necessary skill. If one day I don’t want to deliver takeout anymore, at least I can be a ride-hailing driver.” Several participants also highlighted the importance of acquiring new skills in order to adapt to the ever-changing world of work. For example, Robin stated: I used to fix computers in the factory, and saw many jobs on the assembly line being replaced by robots. This made me realize that we should pick up new skills to avoid being replaced by AI. I plan to enroll in a data analysis training course because many companies need talents in this field. Start a business. When asked about their long-term career goals, half of the participants expressed a desire to start their own business. They explored various possibilities, such as opening a small restaurant, a fruit store, or a pet store. They emphasized that they disliked being managed by others and that their ultimate goal was to become the CEO of their own lives. John described his career goal as follows: I like to play pool and I'm quite good at it. The best job in the world would be one that allows me to use my strengths and interests. If one day I don't want to work for someone else, I’d like to open my own pool hall. But first I have to save enough money and make as many connections as possible. Discussion The aim of this research was to investigate how the contextual and personal factors affect food delivery riders’ perceptions of choice and access to decent work from a PWT perspective. Additionally, we also explored their attitudes towards food-delivery platform work and their aspirations. An analysis of 12 semi-structured interviews with food delivery riders in China echoed several main tenets of the PWT model. Our findings contribute to the PWT literature by providing initial evidence for understanding the vocational experiences of platform workers. In the following sections, we discuss the theoretical and practical implications of our findings, as well as potential avenues for future studies. Career Challenges One of the valuable aspects of this study is its contribution to understanding Chinese gig workers’ vocational experiences at contextual and individual levels. A central finding reflects the role of structural barriers in shaping food delivery riders’ work lives. Consistent with Duffy et al.’s (2016) premises in PWT, all participants reported that financial hardship resulted in a decreased sense of career choices and less access to decent work. Specifically, they were forced to enter the workforce at an early age due to financial difficulties in their families. Although food delivery work was not their preferred type of employment, they were driven to join this industry because it offered better remuneration than factory jobs. The literature has also documented that rural-to-urban migrant workers have increasingly turned to digital platform work in recent years due to relatively high earnings and the immediacy of wage payment (Chen & Sun, 2020). Our participants also reported inadequate education as a major barrier to achieving their vocational goals. Indeed, previous studies have affirmed the importance of high-quality education to individuals’ success in the labor market (Hooley, 2021; Sultana, 2021). Since our participants reported having relatively low levels of education, they had no other choice but to join the gig economy and become food delivery riders. In addition to a lack of human capital, most participants viewed limited social capital as a primary obstacle to their upward employment mobility in urban areas. They reported that they faced significant challenges in finding decent jobs due to a lack of social networks. This finding aligns with the research by Han and colleagues (2023), who suggested that a dearth of Guanxi could impede the ability of migrant workers from China to secure decent employment opportunities. Copying Resources The role of inner and relational resources, including the three moderators of PWT - social support, proactive personality, and critical consciousness (Duffy et al., 2016) - as well as self-leadership, was also salient in the descriptions of food delivery riders in this study. Most participants viewed social support as essential to their work-based experiences. First, consistent with Wu et al.’s (2022) finding, our participants reported that family support - a major source of social support - provided them with the necessary guidance and encouragement to pursue their career aspirations. Additionally, interacting with fellow villagers helped participants find better-paying jobs, which aligns with Keung et al.’s (2007) claim that developing networks with townsmen facilitates the exchange of information regarding employment opportunities. Finally, mirroring previous studies (Kost, 2020), communicating with other food deliver riders not only fulfilled our participants’ relational needs but also offered them opportunities to acquire skills and knowledge that could enhance work efficiency. Taken together, our study offers new insights into how different types of social support impact the career experiences of platform-based workers. Consistent with the findings of Autin et al. (2018), most participants in our study reported proactive personality and critical consciousness as facilitators of their career pursuits. Regarding proactive personality, participants displayed active coping strategies such as providing extra service for customers in order to receive their positive feedback. Additionally, our participants reported that they critically evaluated algorithmic management and took actions to protect their rights. Although critical consciousness did not facilitate the career trajectories of emerging adults in the US (San Antonio & Kaplan-Bucciarelli, 2022), our study found that it positively impacted the vocational experiences of food delivery workers. Although self-leadership was not proposed as the PWT moderators, we found that it played a positive role in our participants’ work-related experiences. As reported by most participants, the nature of their work is independent and flexible, requiring them to set goals, create routines, and implement self-rewards to promote their work progress. Additionally, participants reported that they may encounter malicious negative reviews or misunderstandings from customers during their work, so they had to regulate their emotions in a positive manner. This aligns with Ashford et al.’s (2018) view that emotional regulation is crucial for gig workers to navigate the new world of work. In response to Duffy et al.’s (2023) call for further studies to explore different moderators, quantitative studies may be needed to examine the role of self-leadership in the relationship between contextual factors and work outcomes within PWT. Work Characteristics and Outcomes Another goal of this study was to explore food delivery riders’ perspectives on their current work and career aspirations. When asked about their attitudes towards food delivery work, all participants in the present study regarded it as a means of earning money, which echoes the survival needs in the PWT. Furthermore, when the survival aspects of working emerged in the interviews, participants’ narratives extended beyond individual survival and encompassed the provision for their families. As suggested by Zheng and Wu (2022), food delivery riders tend to cite their responsibility as breadwinners as a fundamental motivation for choosing food delivery work. However, most participants expressed a sense of job dissatisfaction, stating that the amount of money they received did not reflect the effort they put in. Corroborating PWT-informed research (Duffy et al., 2016; Wan & Duffy, 2022), a lack of decent work (e.g., inadequate pay) was associated with lower job satisfaction. Another notable characteristic of food delivery work is long working hours. In stark contrast to Duffy et al.’s (2016) conceptualization of decent work, most participants in our study worked overtime and did not have adequate time for rest and leisure activities. Irregular working hours were more prevalent on holidays and rainy days, as online labor platforms tend to increase the number of tasks assigned to food delivery riders on these days. As a result, more than half of the participants in this study reported feeling physically and mentally exhausted due to working overtime. This finding echoes prior PWT research (Duffy et al., 2019, 2021), where a lack of decent work (e.g., insufficient rest) was associated with numerous physical and mental health problems. However, our findings go beyond existing literature and theory, as work fatigue was exacerbated by the fact that many participants had to endure the intense algorithmic scrutiny imposed by digital platforms while performing delivery tasks. Regarding work conditions, many participants reported that they had to work in precarious environments, which often included heavy traffic congestion and harsh weather conditions. This not only made their work more challenging but also posed a significant threat to their safety and overall well-being (Gregory, 2021). Hence, many participants in this study expressed an intention to quit their jobs. This is not surprising given the evidence in the PWT literature that indecent and precarious work conditions are positively associated with employees’ withdrawal intentions (Wan & Duffy, 2022, 2023). When it comes to social benefits, all participants in this study reported that they were unable to access basic benefits such as healthcare through their work. A common explanation is that gig workers are often classified as self-employed service providers rather than formal employees, which gives platform companies an excuse to avoid government regulations on employee rights and benefits (Allon et al., 2023; Wu et al., 2022). As a result, participants who recognized the importance of job security chose to pay for their own health care and retirement plans. The final characteristic of food delivery work highlighted by our participants was its low barriers to entry. Prior research has indicated that food-delivery platform work is a low-status job with low skill requirements (Le Breton & Galière, 2023). Consistent with Goods et al.’s (2019) findings, some of our participants struggled to establish a sense of meaning and well-being at work. This was due to their perception that their jobs were easily replaceable and lacked opportunities for growth. Supporting PWT-informed research, the absence of decent work is associated with a diminished sense of work fulfillment due to the failure to satisfy basic needs for self-determination (Blustein et al., 2019; Duffy et al., 2016). When asked about their future goals, most participants in the present study expressed a desire to obtain more decent and stable positions which provide basic benefits such as health insurance. Some participants aimed to acquire specialized skills to prepare themselves for the ever-changing world of work. Meanwhile, several participants expressed an interest in starting their own business at the opportune moment. These findings are consistent with Zwettler et al.’s (2023) observation that gig workers tend to leverage online work platforms as a stepping stone to advance their careers. Practical Implications First, this study found that inner and relational resources, including proactive personality, social support, critical consciousness, and self-leadership, could effectively help participants cope with challenges at work. These findings have significant implications for career counselors and organizational leaders. To enhance critical consciousness, counselors may find it useful to help clients critically assess their circumstances and take actions to advocate for their rights when confronted with unjust treatment. It is also important for counselors to assist clients in developing active coping strategies and establishing a personal social support system as they navigate their careers. For instance, counselors may use interventions to inspire clients to initiate positive changes in their work lives and make the most of relational resources in the work and non-work domains. Additionally, to foster self-leadership, online labor platforms should encourage food delivery riders to take ownership of their work. Recognizing the positive impact of individual agency on one’ work, platform leaders can incorporate setting clear goals, implementing self-reward, and regulating emotions into on boarding training for food delivery riders. Second, most participants reported experiencing immense pressure from algorithmic management, which resulted in physical and mental exhaustion. As such, online labor platforms should adopt a moderately efficiency-oriented approach when designing and implementing algorithms. For example, takeout delivery platforms can use algorithmically neutral methods to reduce the burden on food delivery riders during peak hours, thereby demonstrating the organization’s commitment to their well-being. In addition, platforms can offer gig workers appropriate support by establishing effective channels for feedback and complaints, addressing algorithm evaluation errors in a fair and transparent manner, and taking appropriate action against customers who make malicious or false comments. Finally, the results showed that most participants were dissatisfied with their work and had intentions to withdraw from the platform. To address these issues, we recommend that platform organizations provide gig workers with fair compensation, opportunities for skill development and career advancement, and adequate time for rest and leisure activities. Platform managers should also take effective measures to ensure their safety at work. At the systemic level, policymakers should enact laws to protect the rights of gig workers and require platform enterprises to provide them with benefits such as healthcare and work-related injury insurance. Meanwhile, policymakers should leverage media channels to promote a positive portrayal of gig workers and cultivate an egalitarian work ethic across society. Such actions will enhance the work fulfillment and overall well-being of food delivery riders, and ultimately promote the healthy development of the gig economy. Limitations and Future Directions This study has several limitations that invite opportunities for future research. First, sampling bias may have affected our study as most of our participants were recruited from southern China, limiting the transferability of the findings to other contexts. Moreover, our participants were all full-time food delivery riders with relatively low levels of education, so our findings may not apply to part-time riders or those with higher levels of education. Hence, future research should examine the career trajectories of food delivery riders across a broader range of geographic regions, employment statuses, and educational levels. Second, this study only focused on food delivery riders who primarily engage in physically demanding work in China, which may restrict the transferability of our findings to other types of gig workers. For instance, online car-hailing drivers may not be as economically constrained as food delivery riders due to entry requirements such as owning a vehicle and having a local hukou in some large cities. Therefore, future research could consider collecting data from a variety of gig workers to compare their work experiences within the PWT model. Third, the present study only recruited participants from China, which may limit the generalizability of the findings. Given the significant differences in government policies and regulations in shaping the gig economy across countries, the career challenges faced by gig workers in China may not be applicable to those in the West. To the best of our knowledge, delivery workers in the United States mainly use cars rather than motorcycles to deliver food, which prevents them from experiencing adverse working conditions outdoors. Therefore, it would be worthwhile to conduct a cross-cultural comparative study with samples from both Western and Eastern cultures in future research. Finally, this study used a qualitative approach to explore the work experiences of gig workers, which inevitably involves a degree of subjectivity. While the findings provided insight into the core constructs of PWT, they were unable to establish causality between these variables. Therefore, future research could consider using a quantitative paradigm to gain a better understanding of the career development of food delivery riders. A longitudinal design would be particularly beneficial to illustrate how gig workers' careers evolve over time and how their experiences within the PWT model shape their future career trajectories. Conclusion This study aimed to explore the career development of gig workers from a PWT perspective. We conducted semi-structured interviews with 12 food delivery riders in China and employed the CQR approach to analyze the data. We found that vocational barriers included economic constraints, inadequate education, and limited social capital, while resources promoting their work experiences encompassed social support, critical consciousness, proactive personality, and self-leadership. Additionally, although participants reported that their work enabled them to earn a living, but their work was characterized by a lack of essential benefits, long hours, precarious working conditions, and low skill requirements. As a result, they experienced decreased work satisfaction, occupational fatigue and withdrawal intentions. These findings provided initial support for the applicability of the PWT in understanding the career trajectories of gig workers in a non-Western, collectivist cultural context. Implications for future research rooted in the psychology of work and vocational interventions aimed at promoting social justice are presented. Declarations Author Contribution Conceptualization: W.W.; Data curation: W.W.; Formal analysis: W.W., W. L.; Methodology: W.W. ; Data collection: W.W.; Supervision: H. H.; Writing original draft: W.W.; Reviewing and editing :W.W., W. L.,H.H. Acknowledgment The authors would like to thank all participants for their voluntary participation in this study. Human Ethics and Consent to Participate declarations This article received ethical approval from East China Jiao Tong University, and was conducted according to the guidelines of the Declaration of Helsinki. All subjects were informed about the study and participation was fully on a voluntary basis. Participants were ensured of confidentiality and anonymity of the information associated with the surveys. Data availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article. References Allan, B. A., Tebbe, E. 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Journal of Career Assessment , 10690727231212188. https://doi.org/10.1177/10690727231212188 Tables Table 1 Participant Self-reported Demographics Pseudonym Age Gender Education Marital status Residence registration Work months Alex 20 Male Junior high school Unmarried Rural 12 Eric 27 Male Trade school Unmarried Urban 24 Bob 19 Male Junior high school Unmarried Rural 8 Arron 25 Male Junior high school Unmarried Rural 15 Lucy 38 Female Primary school Married Rural 16 Peter 21 Male Junior high school Unmarried Rural 6 Molly 45 Female Primary school Married Rural 18 John 28 Male Trade school Married Rural 30 Robin 30 Male Trade school Married Urban 10 Jason 22 Male Trade school Unmarried Urban 4 Mario 18 Male Junior high school Unmarried Rural 3 Tim 19 Male Junior high school Unmarried Rural 10 Note . Pseudonyms were selected by participants or, at their request, by the first author. Table 2 List of Domains, Categories, and Frequencies Domain Category Frequency Cases Structural barriers Economic constraints General 12 Inadequate education Typical 10 Limited social capital Typical 8 No driver’s license Variant 4 Marginalization due to rural hukou Variant 3 Coping resources Social support General 11 Proactive personality Typical 8 Critical consciousness Typical 7 Self-leadership Typical 7 Resilience Variant 4 View of current work Means of livelihood General 12 Lack of essential benefits General 12 Long working hours Typical 10 Indecent work conditions Typical 9 Low skill requirements Typical 8 Autonomy Variant 5 Work-related outcomes Lower job satisfaction Typical 10 Occupational fatigue Typical 9 Turnover intentions Typical 9 Limited sense of work meaning Variant 5 View of future Find a more decent job Typical 8 Learn new skills Typical 7 Start a business Typical 6 Uncertainty about future Variant 4 Note . For our participants, general applies to 11-12 cases; typical applies to 6-10 cases; and variant applies to 3-5 cases. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4935308","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":358617884,"identity":"cbe34b92-ee11-49bb-8ae4-09606f704baa","order_by":0,"name":"Wei Wan","email":"","orcid":"","institution":"East China Jiaotong University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wan","suffix":""},{"id":358617885,"identity":"05a75133-5a36-475b-b24f-9df919d4299a","order_by":1,"name":"Weihua Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACNmb+hw8/VNjI8bM3HyBOCx87D7OxxJk0Y8meYwnEaZHj52ET4G07nLhhRo4BsQ7jPcYgceYw4waJnI833jDYyek2ENTCl/agoCKd2Zzn7WbLOQzJxmYHCGphMDeQOGPNZtmeu02ah+FA4jYitJhJ8LYx8xgcyHlGrBYekBZnCYMTOWzEamFLBgWyATCQjS3nGBDhF/n+wwdBUVnfz9788MabCjs5glpQgAQPkVGDrIVUHaNgFIyCUTAiAAAwHD4UjLe/HAAAAABJRU5ErkJggg==","orcid":"","institution":"Hainan College of Economics and Business","correspondingAuthor":true,"prefix":"","firstName":"Weihua","middleName":"","lastName":"Liu","suffix":""},{"id":358617888,"identity":"c333139c-6302-4154-b9b9-0b81ce71d91b","order_by":2,"name":"Huiling Hu","email":"","orcid":"","institution":"National Taipei University of Business","correspondingAuthor":false,"prefix":"","firstName":"Huiling","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2024-08-19 02:21:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4935308/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4935308/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70324070,"identity":"b8afbba7-fda8-40cd-a2b5-1a535d05048d","added_by":"auto","created_at":"2024-12-02 07:17:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":680837,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4935308/v1/b312f751-4318-4fb5-aad7-794fb37db09a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Career Development of Food Delivery Riders in China: A Qualitative Investigation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith the rise of the gig economy, research on platform work has seen a significant increase in recent years (Duggan et al., 2022; Rai \u0026amp; Mukherjee, 2024). As part of the rapidly expanding \u0026lsquo;platform capitalism\u0026rsquo;, platforms act as online labour intermediaries, connecting consumer demand with a supply of temporary or short-term workers (Graham et al., 2017; Spreitzer et al., 2017). Platform work has reshaped the nature of employment relations by promoting flexible work arrangements and transferring the responsibility for job security and necessary benefits (e.g., healthcare) to gig workers themselves, thereby resulting in precarious labor conditions and a host of undesirable work outcomes (Gali\u0026egrave;re, 2020; Kellogg et al., 2020; Spurk \u0026amp; Straub, 2020; Wood et al., 2019). From a career perspective, it is crucial to understand the impact of external barriers on gig workers\u0026rsquo; career development and to identify the coping resources they use to overcome these constraints (Retkowsky et al., 2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Psychology of Working Theory (PWT; Duffy et al., 2016) was developed to capture the career development of all individuals, with a particular focus on those who face contextual constraints in their pursuit of decent work. The theory highlights that decent work comprising basic workplace components should be accessible to all employed adults, as it is closely connected to individuals\u0026rsquo; work fulfillment and overall well-being. To date, numerous research has utilized PWT to explore the work experiences of marginalized employed adults in the Western context (e.g., Allan et al., 2019; Kim et al., 2018; Tokar \u0026amp; Kaut, 2018), and some studies have expanded this theory to assess the experience of working adults in China (Han et al., 2022; Wan \u0026amp; Duffy, 2023; Wang et al., 2019). However, these research has primarily focused on formal employment groups, with relatively little attention given to informal employment groups. In particular, there is a significant gap in the PWT literature regarding the career development of platform workers in the era of booming gig economy.\u0026nbsp;Additionally,\u0026nbsp;extant studies typically utilize quantitative methods to investigate associations between predetermined variables, which may not fully capture the complex career paths of working populations and the factors that shape them.\u003c/p\u003e\n\u003cp\u003eTherefore, this study attempts to address the aforementioned gaps by employing qualitative methods to explore the vocational experiences of Chinese platform workers from a PWT perspective. Given that food delivery riders epitomize gig workers and are particularly vulnerable in terms of career development (Wu et al., 2022), our primary aim is to investigate the contextual and individual factors that may impact their perception of choice and access to decent work. We are also interested in their attitudes towards their food delivery roles and the prospects they envision for the future. This qualitative research marks the first known use of PWT to understand how food delivery riders navigate the evolving world of work in a non-Western, collectivist cultural context.\u0026nbsp;Our findings are expected to\u0026nbsp;provide implications for career counselors, platform leaders, and policymakers who seek to promote the career development of food delivery riders on digital labor platforms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFood delivery riders in China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe digitally-driven gig economy has emerged as one of the fastest-growing sectors in China, offering flexible work arrangements and new opportunities for employment (Sun, 2019). By the end of 2021, China had approximately 200 million flexible workers, which accounted for about 26% of the total employment population. As one of the most dynamic groups within this workforce, food-delivery platform workers have attracted widespread attention from academia due to their precarious labor conditions (Huang et al., 2023). These workers rely heavily on electric motorbikes to complete their tasks and thus are referred to as \u0026ldquo;riders\u0026rdquo; in China (Qian et al., 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA notable demographic characteristic of Chinese food delivery riders is that most of them are rural-to-urban migrant workers (Wu et al., 2022). This implies that they are socially and economically disadvantaged groups residing in urban areas. Under China\u0026rsquo;s household registration (hukou) system, rural migrants are not entitled to enjoy the same level of social welfare as urban residents, such as healthcare and education benefits (Wong et al., 2007). Additionally, numerous migrant workers flock to food delivery platforms due to the prospect of earning a substantial income (Huang et al., 2023). Time and physical labor are these riders\u0026rsquo; primary resources for production, so they generally work long hours and take as many orders as possible in order to maximize their earnings (Zheng \u0026amp; Wu, 2020).\u003c/p\u003e\n\u003cp\u003eFood delivery platforms in China are primarily modeled after Uber and heavily depend on algorithms to manage their laborers (Sun, 2019). First, these platforms use algorithms to assign orders to the rider who is closest to a particular restaurant (Huang et al., 2023). Once a delivery order is accepted, algorithms plan the most efficient delivery route for riders and begin tracking their real-time movements (Wu et al., 2022). Additionally, riders\u0026rsquo; performance is closely monitored by algorithms and evaluated by delivery speed, customer ratings, and order completion rates (Huang, 2022). It is no exaggeration to say that the entire work process of food delivery riders is strictly managed by algorithmic technologies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven that food delivery riders are a particularly vulnerable group amid the development of China\u0026rsquo;s gig economy, the contextual constraints and coping strategies related to their career development warrant attention from scholars and those advocating for workplace equity and social justice. It is also crucial to understand their perspectives on platform work and career goals, which may provide implications for career counselors, platform managers and policymakers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTheoretical Framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study is grounded in the newly developed PWT, which intends to capture the vocational experiences of all individuals (Duffy et al., 2016). While traditional vocational theories largely favor those who have a degree of choice in their careers, PWT articulates the significant obstacles that persist in obtaining decent work for many underprivileged populations throughout the world. As the core construct of PWT, decent work is conceptualized to encompass (1) a safe work environment, (2) fair compensation, (3) access to healthcare, (4) adequate time off, and (5) organizational values that match family and social values (Duffy et al., 2016).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePWT is a complex theory which outlines 32 propositions about the predictors and outcomes of decent work. The predictor section of the PWT model suggests that economic constraints and marginalization prevent individuals from securing decent work, with these effects mediated by two psychological resources (i.e. work volition and career adaptability). Additionally, PWT proposes that four moderators (i.e. proactive personality, critical consciousness, economic conditions, and social support) may mitigate the negative impact of contextual constraints on psychological variables and access to decent work. Regarding the outcome portion of the model, decent work attainment is directly related to the satisfaction of basic human needs, including survival, social contribution, and self-determination needs (autonomy, relatedness, and competence). PWT posits that decent work satisfies these needs over time, which in turn increases work-related and general mental and physical well-being. To date, a large body of research has supported the core assumptions of the model among diverse working populations across both individualistic and collectivist cultural contexts (see Duffy et al., 2023 for a summary of studies on PWT).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePWT serves as an informative theoretical framework for the current study, which informed our research questions. We delve into the work-related obstacles faced by food delivery riders, stemming from their lower socioeconomic status and other systemic constraints, which, as PWT suggests, contribute to the ongoing lack of access to decent work (Duffy et al., 2016). This framework offers particular insight into how food delivery riders surmount workplace adversities and interpret their jobs. Additionally, this study examines the interactions of contextual and individual factors in relation to food delivery riders\u0026rsquo; work aspirations, which is also a central tenet of PWT (Duffy et al., 2016).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Present Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFood delivery riders are not often asked about their work-related experiences, challenges, and possibilities from a PWT perspective, making this an understudied phenomenon that requires further investigation. In the current study, we aimed to investigate the contextual and individual factors in the career development of Chinese food delivery riders through a PWT lens, as well as how these factors impact their work volition and access to decent work. Additionally, we sought to explore their gig work experiences and career aspirations. To achieve these goals, we conducted a qualitative research to gain an in-depth understanding of participants\u0026rsquo; nuanced vocational trajectories. In particular, we employed Hill et al.\u0026rsquo;s (2005) Consensual Qualitative Research (CQR) approach to analyze the semi-structured interview data. Hill and Knox (2021) argued that CQR is \u0026ldquo;particularly useful for investigations of inner events about which participants may have ambivalent or suppressed feelings that cannot be easily observed by outsiders\u0026rdquo; (p.7). As such, the qualitative nature of this study allowed us to capture rich account of how participants perceive the world of work based on their lived experiences by examining the following questions: (a) What contextual barriers do the participants encounter, and how do these barriers affect their work volition and access to decent work? (b) What external supports and individual adaptive strategies do they employ to mitigate the adverse effects of contextual constraints? (c) How do participants perceive their current work and future prospects? \u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involved participants who met the following criteria: (a) being at least 18 years old, (b) being currently employed by digital labor platforms, and (c) working as food delivery riders in China. We conducted semi-structured interviews with 12 participants (10 men and 2 women) to explore their vocational experiences. The participants\u0026rsquo; ages ranged from 18 to 45 years old, with a mean age of 26. In terms of education, six participants reported graduating from junior high school, four from trade school, and two from primary school. Regarding marital status, eight participants reported being unmarried, while four reported being married. When asked about residence registration, nine participants reported coming from rural areas, and three from urban areas. On average, the participants had worked as food delivery riders for 13 months. See Table 1 for a detailed summary of participants\u0026rsquo; demographic information.\u003c/p\u003e\n\u003cp\u003e[Insert Table 1 here]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtocol\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDevelopment\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBuilding on the tenets of PWT (Duffy et al., 2016), we developed\u0026nbsp;an initial\u0026nbsp;interview protocol\u0026nbsp;for\u0026nbsp;participants\u0026rsquo;\u0026nbsp;career development.\u0026nbsp;Additionally, we\u0026nbsp;sought feedback from\u0026nbsp;an experienced scholar in vocational psychology\u0026nbsp;on\u0026nbsp;the protocol and made minor adjustments to\u0026nbsp;the wording of several\u0026nbsp;questions. The\u0026nbsp;final\u0026nbsp;protocol,\u0026nbsp;consisting of eight\u0026nbsp;open-ended questions, explored a wide range of topics related to participants\u0026rsquo; work lives, including structural barriers, external supports, personal resources, work volition, perceptions of decent work, and career aspirations. Prior to the above questions, the participants were required to provide demographic information, such as gender, age, education, marital status, and household residence registration. The detailed interview questions can be seen in the Appendix. After creating the protocol, we conducted pilot interviews with two eligible participants who confirmed that the questions were relevant to their vocational experiences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter obtaining IRB approval from the first author\u0026rsquo;s university, we utilized a combination of convenience and snowball sampling to recruit participants. Specifically, we identified two local offline work sites of Meituan Takeaway, a leading online food-delivery platform in China, and explained the purpose of our research to their managers. After obtaining their permission, we advertised the current study in their online work groups, relying heavily on word-of-mouth to inform prospective participants about our research. Those who expressed interest were directed to contact the first author for more information and to schedule an appropriate time for an in-person interview. All interviews were conducted at the participants\u0026rsquo; offline work site and lasted approximately 60 minutes. We ceased data collection upon reaching the point of saturation, where new interviews yielded no further information (Morrow, 2005).\u003c/p\u003e\n\u003cp\u003eBefore each interview, we explained the purpose of our research to the participants and reassured them that their information would be kept confidential. Informed consent was obtained from all participants for this study, and they had right to withdraw at any time if they felt uncomfortable during the interview. Participants were not offered any financial incentives for participating in this research. Throughout the interviews, we followed the protocol to ensure participants answered all the open-ended questions. To elicit more details, we used prompts like \u0026ldquo;Why is that?\u0026rdquo; or \u0026ldquo;Any examples?\u0026rdquo; After each interview, the first author organized recordings and field notes within 24 hours to create transcripts. Prior to data analysis, we shared preliminary transcripts with participants for review, and they were given the opportunity to delete any information they did not wish to disclose.\u003c/p\u003e\n\u003cp\u003eSince all interviews were carried out in Chinese, the data analysis process was also conducted in Chinese in order to minimize the loss of meaning. The first author of this study, who holds a Bachelor\u0026apos;s degree in English, translated the interview protocol as well as all the codes (including domains, categories, and quotes) into English during the writing process. A native English speaker who is proficient in Chinese was also invited to increase the accuracy of the translation and to minimize any potential bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Team\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research team included three coders and an auditor, representing diversity in terms of gender, age, social class, educational background, and knowledge of related theory and research. All members were passionate about improving the employment prospects of food delivery riders. The first coder has a\u0026nbsp;Ph.D.\u0026nbsp;in human resource management and extensive experience conducting qualitative research on the career development of disadvantaged populations. In the current study, she trained the other two student coders on conducting the data analysis. One is a graduate student whose father worked as a food delivery rider, and the other is an undergraduate student who has experience of working as a food delivery rider.\u0026nbsp;An external\u0026nbsp;auditor\u0026nbsp;with a strong understanding of PWT and qualitative research methods was included in the research to provide\u0026nbsp;critique\u0026nbsp;on the coding results.\u003c/p\u003e\n\u003cp\u003eTo ensure that all team members were well-versed in\u0026nbsp;the\u0026nbsp;CQR procedure, they\u0026nbsp;were required to read\u0026nbsp;Hill et al.\u0026rsquo;s (2005) article and attend several meetings to\u0026nbsp;study recent\u0026nbsp;examples of CQR analyses\u0026nbsp;(e.g., Gilson et al., 2022; Kenny et al., 2023).\u0026nbsp;Prior to the beginning of the coding process, coding members engaged in discussions regarding their biases concerning the current research. Based on our personal experiences and familiarity with PWT research, we believed that economic constraints and marginalization would negatively affect food delivery riders\u0026rsquo; vocational experiences. All coders not only endorsed expectations that participants would report barriers related to access to decent work but also acknowledged potential biases related to social security issues faced by food delivery riders. For instance, the first author, who lives in a bustling commercial district, is exposed to numerous food delivery riders every day. This situation has led to reflection on the challenges these riders encounter, such as the dangers posed by severe weather and the inherent risks of riding motorcycles. Given these biases, the coding team agreed on the importance of strictly adhering to the CQR guidelines and avoiding premature interpretation. Throughout the coding process, the coding members should return to the data repeatedly to check the accuracy of the codes and engage in group discussion to resolve areas of discrepancies. Additionally, the research team sought to create an equal setting where the student coders were encouraged to express their opinions freely in the consensus-building process. They were also given opportunities to speak first in meetings in order to mitigate the potential effect of the \u0026ldquo;dominant\u0026rdquo; faculty coder.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe interview data were analyzed using the CQR approach, which involves three key steps: coding of domains, creating core ideas, and conducting a cross-analysis (Hill et al., 2005). At each stage of the data analysis, coding was independently completed by the three coders. The coding team then met to review their respective lists of codes and discussed points of disagreement before reaching a consensus on the codes. Finally, the auditor checked the codes to reduce the effects of group thinking.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCoding of domains\u003c/em\u003e\u003c/strong\u003e. Based on existing literature and interview questions, we first established a list of domains which allowed us to categorize large amounts of data into manageable sections (Hill et al., 2005). Throughout the coding process, domains can be merged, separated, or added if necessary. For instance, a domain called \u0026ldquo;Work-related Outcomes\u0026rdquo; emerged after creating our initial list because we did not ask any direct questions about it, but this domain arose in the data regardless. After creating an initial list of domains, each coding member independently analyzed transcripts by assigning similar data to the appropriate domain. Finally, the coding team met to discuss the coded transcripts until reaching a consensus on the domains of each interview.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCore ideas\u003c/em\u003e\u003c/strong\u003e. To create core ideas, the coding team aimed to extract the most important information from the participants\u0026rsquo; responses. For example, if a transcript within the domain of \u0026ldquo;Structural Barriers\u0026rdquo; discussed the lack of social capital that comes with migrating to urban areas, a core idea for that domain might be \u0026ldquo;Participants reported having limited social connections due to rural-to-urban migration.\u0026rdquo; Following Hill et al.\u0026apos;s (2005) guidelines, we made sure that all core ideas were closely related to the data and did not include any personal interpretations. Each coder independently developed core ideas before meeting with other team members to address any discrepancies and reach a consensus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCross-analysis\u003c/em\u003e\u003c/strong\u003e. The coding team conducted a cross-analysis to generate a list of categories for each domain by examining recurring themes across interviews. This stage required more interpretation from researchers than previous ones. For example, when observing core ideas about limited social capital appearing in multiple interviews, we developed a category named \u0026ldquo;limited social capital\u0026rdquo;. Each coder independently performed the cross-analysis and then presented their generated categories to the group for discussion. We collaborated to reach a consensus on the wording of the categories and how to arrange the core ideas into them.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuditing\u003c/em\u003e\u003c/strong\u003e. After each round of the above analysis, the auditor was asked to provide feedback on the results for the coding team. Specifically, the auditor\u0026apos;s role was to verify that the raw data fell within appropriate domains, that the core ideas succinctly captured the essence of all relevant information, and that the categories generated by the cross-analysis were appropriately named. The auditor provided written feedback that largely validated the work of the coding team, but suggested that some categories be renamed for clarity and conciseness. After determining that the transcripts contained sufficient evidence to support the auditor\u0026apos;s suggested changes, the coding team incorporated his feedback into the findings.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe data analysis revealed five domains: (a) structural barriers, (b) coping resources, (c) view of current work, (d) work-related outcomes, and (e) view of future. Categories that emerged from each of these domains were labeled according to the CQR method. General categories were those discussed by all or almost all participants, while typical and variant categories were those mentioned by more than half or less than half of the sample, respectively. Categories that appeared in only one or two cases were dropped. In the sections below, we provide a detailed description of the general and typical categories, supported by participant quotes. A list of domains, categories, and frequencies is provided in Table 2.\u003c/p\u003e\n\u003cp\u003e[Insert Table 2 here]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructural barriers\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe domain labeled as \u0026ldquo;Structural Barriers\u0026rdquo; captured factors that participants reported as either directly or indirectly hindering their capacity to obtain decent work. The general and typical categories within this domain consisted of economic constraints, a lack of education, and limited social capital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEconomic constraints.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAll participants identified limited economic resources as a major obstacle to their career development. They discussed various aspects of financial struggles, with the most frequently mentioned difficulty being the need to pay for basic survival needs. In order to reduce the financial burden on their families, most of our participants chose to work after completing junior high school. Bob shared his early experience of working in a restaurant due to limited family income:\u003c/p\u003e\n\u003cp\u003eWhen I turned 15, my parents asked me to stop schooling. They thought sending me to school was a waste of money as I was not good at it. Many factories didn\u0026rsquo;t hire minors, so I ended up working as a dishwasher in a relative\u0026rsquo;s restaurant, earning about 1,500 RMB (approximately $210) per month. The salary was far from enough to lift my family out of poverty, but it allowed me to meet my basic needs, like buying food and clothes.\u003c/p\u003e\n\u003cp\u003eAdditionally, participants frequently discussed how economic constraints had driven them to join food delivery platforms. Peter described his experience as follows:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eI worked as an excavator operator for two years at a construction site. It was physically demanding, but I only earned 2,000 RMB ($280) per month. It made me feel my efforts weren\u0026rsquo;t worth it. Later, a friend suggested me to deliver takeout. He told me this job\u0026nbsp;is remunerated on a piece rate basis, which\u0026nbsp;means my earnings depend on the number of orders I fulfill each month.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInadequate education.\u003c/em\u003e Ten participants reported that limited education was an overarching obstacle to pursing their career goals. They specifically emphasized the adverse impact of inadequate education on their work volition and eventual access to decent work. When asked about barriers to securing decent work, Molly said that not having much education limited her options:\u003c/p\u003e\n\u003cp\u003eAlthough I admire white-collar workers, I know my own limitations. Nowadays, perhaps the only industry that does not require a degree is food-delivery. I have no education or skills. In order to earn a living, I had no choice but to become a food delivery riders as I am not qualified for any other work.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimited social capital.\u003c/em\u003e Eight participants mentioned significant challenges in securing decent employment opportunities due to a lack of social capital. They shared the view that Guanxi, or connections to influential individuals, is essential for career advancement. However, as most of our participants come from rural areas, they reported being socially disadvantaged in urban settings.\u0026nbsp;Mario, for example, articulated how insufficient social capital impeded his capability to land a decent job:\u003c/p\u003e\n\u003cp\u003eI come from a small village. I don\u0026rsquo;t know anyone in the city. I have no one to rely on but myself. I find it so hard to find a job without connections because most employers require a reference. This makes me feel very frustrated. The only jobs available are temporary and low-paid service jobs. They don\u0026rsquo;t care about your background; all they need is your manual labor.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCoping Resources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe domain labeled as \u0026ldquo;Coping Resources\u0026rdquo; represented factors that participants identified as contributing to their vocational pathways. General and typical categories within this domain were social support, proactive personality, critical consciousness, and self-leadership.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSocial support\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eAll but one of our participants reported that social support was a crucial resource in their career development. Specifically, they mentioned receiving assistance from their families, establishing connections with fellow villagers, and networking with other food delivery riders. Regarding family support, most participants reported receiving emotional support and guidance on navigating the workforce. Jason, who recently started working as a food delivery rider, put it this way:\u003c/p\u003e\n\u003cp\u003eMy parents don\u0026rsquo;t interfere with what I do as long as it\u0026rsquo;s not illegal. However, my older brother often reminds me to be polite to people, especially customers. He asked me to be patient and not rush into things, otherwise it\u0026rsquo;s easy to get into conflicts with others.\u003c/p\u003e\n\u003cp\u003eAdditionally, the majority of participants stated that their connections to people from their hometown were a valuable source of information regarding employment opportunities. Alex shared an example of how a conversation with a fellow villager influenced his decision to become a food delivery rider:\u003c/p\u003e\n\u003cp\u003eI used to work as an assembly line worker in the factory. One day after work, I chatted with him [fellow villager] and complained about the hard work and low salary. He told me he was delivering takeout and it was more flexible than other physically demanding jobs. He said he could earn 6,000 RMB (around $840) a month, and sometimes even more than 10,000 RMB (about $1,400). After this, I became very interested and decided to quit my job.\u003c/p\u003e\n\u003cp\u003eFinally, most participants stated that interacting with other delivery riders was a valuable source of support for them. They described this as advantageous because it reduced feelings of loneliness and motivated them to persist in achieving their goals. Mario, a newcomer to the food delivery platform, elucidated how socializing with other riders helped him enhance his work efficiency:\u003c/p\u003e\n\u003cp\u003eI\u0026rsquo;m not familiar with many of the local roads. In the beginning, I relied heavily on navigation, but after working for a while, I found it\u0026rsquo;s sometimes unreliable and often leads me to a small alley where there is no signal. By chatting with other food delivery riders, I\u0026rsquo;ve learned how they strategically plan their routes before delivering food. This has helped me improve delivery speed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eProactive personality.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eEight participants reported that they adopted positive coping strategies to overcome various difficulties they encountered in their work. One such strategy was providing additional services to customers beyond just delivering food. Lucy shared how offering extra services helped her achieve desirable outcomes, \u0026ldquo;Every time I\u0026rsquo;m on my way to deliver food, I will call the customer in advance to see if they need me to bring anything else, like cigarettes or drinks. After the delivery, I also offer to help them take out the trash. In return for my help, most customers agree to give me positive reviews on my service on the platform.\u0026rdquo; Additionally, most participants emphasized the importance of proactively communicating with platform staff. For instance, Arron stated:\u003c/p\u003e\n\u003cp\u003eDuring peak hours for food-delivery, such as from 12 pm to 2 pm, the platform assigns multiple orders at once with significant distances between destinations. If I anticipate difficulty completing all the tasks, I will call the back-end personnel and inform them that I am currently on a delivery and suggest assigning the other orders to other riders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCritical consciousness.\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eMore than half of the participants (\u003cem\u003en\u003c/em\u003e = 7) described that their social disadvantages had actually heightened their critical consciousness. In particular, they were aware that platforms were exploiting their labor via algorithms. John exemplified this by stating, \u0026ldquo;Our entire working process is exposed to algorithmic monitoring, and the platform uses algorithms to push us to continuously improve delivery speed. Under the hegemony of algorithms, we are forced to self-exploit and rely on increasing the number of orders to generate more income.\u0026rdquo; In addition to critically reflecting on algorithmic control, several participants also engaged in advocacy to protect their rights when confronted with unreasonable treatment. Bob shared his experience as follows:\u003c/p\u003e\n\u003cp\u003eIf I receive a long-distance order and the system keeps assigning other long-distance orders, it\u0026rsquo;s very likely that the previous order was given negative feedback or complained about by the customer. Maybe the platform wants to punish you. When this happens, you need to figure out the reason in time, and appeal to the platform or report to your station.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSelf-leadership.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eSeven participants reported that self-leadership, including goal setting, self-motivation, and emotional regulation, was a vital psychological resource for managing work-related stress. First, some participants discussed that they would adjust their work goals in a timely manner based on the surrounding environment. Molly shared, \u0026ldquo;When picking up orders, I keep an eye out for popular restaurants or those with promotions or special events. These types of restaurants usually have more orders and faster service. During non-peak hours, I prefer to wait for orders near such restaurants.\u0026rdquo; Likewise, Lucy described how she plans her daily work, \u0026ldquo;Before starting my work every day, I set a target for the number of orders I want to delivery and roughly plan my delivery routes. This helps me establish a more regular routine for my working hours and increase my work efficiency.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, some participants mentioned that if they completed their tasks for the day ahead of schedule, they would reward themselves with a half day off the next day. In terms of emotional regulation, several participants reported actively regulating their emotions and internalizing external expectations as their own. Jason described how emotional management helped him get through difficult times:\u003c/p\u003e\n\u003cp\u003eDuring a particularly difficult period, I frequently encountered customers who gave bad reviews without any justification. Even though I felt really depressed and unfairly treated, I had no choice but to tolerate it. But whenever I remind myself that my job is to serve others, I would feel much better.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eView of Current Work\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u0026ldquo;View of Current Work\u0026rdquo; domain revealed the participants\u0026rsquo; perspectives on their work for food delivery platforms. General and typical categories in this domain included means of livelihood, lack of essential benefits, long working hours, indecent work conditions, and low skill requirements.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMeans of livelihood.\u0026nbsp;\u003c/em\u003eAll\u0026nbsp;participants linked their current work to independence and the financial support of their daily lives. They described that being financially independent allowed them to fulfill their basic needs, such as paying for rent, food and clothing. Tim stated, \u0026ldquo;With the money I earn, I\u0026rsquo;m able to rent a small apartment in the city and live on my own.\u0026rdquo; In addition to meeting their own needs, some participants also reported that the income derived from food delivery work allowed them to support their families. Arron emphasized that the meaning of work was to alleviate the financial burden on his parents:\u003c/p\u003e\n\u003cp\u003eBoth my parents work in agriculture, growing vegetables and raising chickens. I also have a younger sister who has a talent for studies. I spend long hours delivering takeout every day because I hope to support her to attend college in the future.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLack of essential benefits.\u0026nbsp;\u003c/em\u003eAll participants reported receiving limited benefits from their work. They explained that online labor platforms only provided them with accident insurance due to the high risk of occupational injuries. However, they did not have access to insurance related to healthcare, pension, unemployment, and maternity, which are available to traditional employees. Bob explained this in details, \u0026ldquo;The platform takes 3 RMB (around $0.4) from the earnings of our first delivery order each day as daily accident insurance, but the coverage provided by this policy is significantly less than that offered by employee work-related injury insurance.\u0026rdquo; For those participants who were more aware of social security, they would purchase medical insurance on their own or pay for relevant insurance through their friends or relatives\u0026rsquo; companies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLong working hours.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eTen participants reported working more than ten hours every day, with only three or four days off every month. They also mentioned that online labor platforms tend to increase the number of tasks during holidays or harsh weather, thereby leading to extended working hours and no days off. Peter shared his experience of coping with excessive workload on rainy days:\u003c/p\u003e\n\u003cp\u003eOn normal days, there are only around ten orders during peak hours, but when it rains heavily, the number of orders is beyond count. Despite this, I still have to deliver them because if I don\u0026rsquo;t, the platform may punish me by not assigning me any orders in the future. And in order to complete these tasks on rainy days, I don\u0026rsquo;t even have time to eat.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIndecent work conditions.\u003c/em\u003e\u003c/strong\u003e Nine participants shared their experiences of working in poor environments, where they were often exposed to harsh weather conditions. For instance, Robin described the negative impact of the heat on his work, \u0026ldquo;The summer here is notoriously hot, with temperatures often exceeding 40 degrees Celsius. Prolonged exposure to the sun can easily lead to heatstroke. For someone like me who is overweight and sensitive to heat, it can be a real challenge to complete tasks in such work conditions.\u0026rdquo; Additionally, most participants mentioned a host of safety issues while riding motorcycles on the road. Alex shared his experience of almost having a car accident:\u003c/p\u003e\n\u003cp\u003eAs I was waiting at the intersection, there were no cars in sight. I decided to ride through it quickly. Suddenly, a car sped past me and I was completely taken aback. All I could think of was making sure I didn\u0026rsquo;t hit it, or else I would be late. Luckily, I wasn\u0026rsquo;t hurt, but the soup inside my bag spilled out.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLow skill requirements.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eOver half of the participants (\u003cem\u003en\u003c/em\u003e = 8) reported that their job requirements were minimal and involved a low level of technical expertise. Molly elaborated on the process of becoming a food delivery rider:\u003c/p\u003e\n\u003cp\u003eThe first step is to register online and provide your ID card to the platform. They will verify if you have a criminal record, and if you do, you will not be eligible for the job. After that, you need to show your ability to use a smartphone and ride a motorcycle. Finally, you are required to pay a deposit to the platform in exchange for essential items, such as a thermal box, uniforms, a helmet, gloves, etc.\u003c/p\u003e\n\u003cp\u003eAdditionally, as food delivery work does not have specific skill requirements, most participants expressed a low sense of career identity and felt worried about their career prospects. For example, Eric stated, \u0026ldquo;I\u0026rsquo;ve been working as a food delivery rider for two years, but I\u0026rsquo;m not better than those new riders. I don\u0026rsquo;t have any specialized skills or training. I don\u0026rsquo;t see much room for growth working in this field.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eWork-related Outcomes\u003c/p\u003e\n\u003cp\u003eThe domain labeled as \u0026ldquo;Work-related Outcomes\u0026rdquo; captured the impact of the participants\u0026rsquo; current work on other work-related variables. Typical categories within this domain included lower job satisfaction, occupational fatigue, and turnover intentions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLower job satisfaction.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eMost of our participants (\u003cem\u003en\u003c/em\u003e = 10) reported that they were not very satisfied with their current work. Specifically, they complained a lot about the increasingly strict algorithmic management, which has led to extended working hours and reduced income. Eric expressed his dissatisfaction with the following statements:\u003c/p\u003e\n\u003cp\u003eLast year, I only had to work 10 hours a day and my monthly income was over 10,000 RMB (around $1,400). But now I have to work 13 hours a day and my monthly income is less than 8,000 RMB (approximately $1,118). The platform not only keeps reducing our delivery time but also lowers the pay for each order. It\u0026rsquo;s really frustrating. I feel like I\u0026rsquo;m working harder but not getting paid enough.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOccupational fatigue.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNine participants reported that they experienced physical and mental exhaustion in their work. They specifically mentioned feeling nervous and anxious due to the omnipresent algorithmic control imposed by platforms. Peter put it this way, \u0026ldquo;In front of the algorithm, I feel like a transparent person. No matter where I go, I\u0026rsquo;m constantly monitored by the system.\u0026rdquo; In addition to this prison-style monitoring, most participants reported feeling stressful due to the real-time normative guidance and tracking evaluation provided by the platform. John, for example, described the time pressure that most food delivery riders face. He said, \u0026ldquo;When we receive an order, algorithms will automatically calculate the delivery time, and we need to deliver it within that time. If we are one second late, we may face fines from the platform or negative reviews from customers.\u0026rdquo; Meanwhile, most of our participants expressed concerns about their physical health due to long working hours. For instance, Tim stated:\u003c/p\u003e\n\u003cp\u003eI work more than 14 hours every day to earn more money. In just one month of non-stop work, I lost 10 pounds or so. When I get home, I often feel so exhausted that I fall asleep as soon as my head hits the pillow. This job is pushing me to my limits. I can no longer afford to overdraw my health like this.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTurnover intentions.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eOver half of the participants (\u003cem\u003en\u003c/em\u003e = 9) discussed their intention to seek out a different job that would provide greater safety and dignity. Alex reported, \u0026ldquo;I work outdoors in all weather conditions, no matter it\u0026rsquo;s scorching in summer or chilly in winter. It\u0026rsquo;s especially easy to slip and fall on rainy days. My families have great concerns about my safety. If there are better options, I will quit this job immediately.\u0026rdquo; Robin mentioned a similar intent to find alternative employment opportunities:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eI understand that some people view our work as inferior, and the media often portrays us negatively. They claim that we lack quality and don\u0026rsquo;t follow traffic rules or something like that. This kind of stigmatization makes me depressed. Although I don\u0026rsquo;t have much education, I still hope to have a job that is respected by others.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eView of Future\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u0026ldquo;View of Future\u0026rdquo; domain reflected the participants\u0026rsquo; plans for their future. Typical categories in this domain included the desire to find a more decent job, learn new skills, and start a business.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFind a more decent job.\u003c/em\u003e\u003c/strong\u003e Eight participants regarded their current work as a stepping stone to a more decent and stable job in the future. They shared the belief that gig work was not their ideal career. Eric described his plan as follows:\u003c/p\u003e\n\u003cp\u003eI think this job has no future. Except earning a living, there is no social security, no social status, and no promotion opportunities. I plan to quit next month. I have a friend who is engaged in live-streaming e-commerce. He is in need of staff. I know the job will be challenging, but he promised to offer me healthcare and other benefits.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLearn new skills.\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eInstead of explicitly describing their career goals, eight participants reported their plans to develop more survival skills. Tim, who just turned 18 last year, is preparing to obtain his driver\u0026rsquo;s license. He said, \u0026ldquo;Driving is a necessary skill. If one day I don\u0026rsquo;t want to deliver takeout anymore, at least I can be a ride-hailing driver.\u0026rdquo; Several participants also highlighted the importance of acquiring new skills in order to adapt to the ever-changing world of work. For example, Robin stated:\u003c/p\u003e\n\u003cp\u003eI used to fix computers in the factory, and saw many jobs on the assembly line being replaced by robots. This made me realize that we should pick up new skills to avoid being replaced by AI. I plan to enroll in a data analysis training course because many companies need talents in this field.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStart a business.\u0026nbsp;\u003c/em\u003eWhen asked about their long-term career goals, half of the participants expressed a desire to start their own business. They explored various possibilities, such as opening a small restaurant, a fruit store, or a pet store. They emphasized that they disliked being managed by others and that their ultimate goal was to become the CEO of their own lives. John described his career goal as follows:\u003c/p\u003e\n\u003cp\u003eI like to play pool and I\u0026apos;m quite good at it. The best job in the world would be one that allows me to use my strengths and interests. If one day I don\u0026apos;t want to work for someone else, I\u0026rsquo;d like to open my own pool hall. But first I have to save enough money and make as many connections as possible.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of this research was to investigate how the contextual and personal factors affect food delivery riders\u0026rsquo; perceptions of choice and access to decent work from a PWT perspective. Additionally, we also explored their attitudes towards food-delivery platform work and their aspirations. An analysis of 12 semi-structured interviews with food delivery riders in China echoed several main tenets of the PWT model. Our findings contribute to the PWT literature by providing initial evidence for understanding the vocational experiences of platform workers. In the following sections, we discuss the theoretical and practical implications of our findings, as well as potential avenues for future studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCareer Challenges\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne of the valuable aspects of this study is its contribution to understanding Chinese gig workers\u0026rsquo; vocational experiences at contextual and individual levels. A central finding reflects the role of structural barriers in shaping food delivery riders\u0026rsquo; work lives. Consistent with Duffy et al.\u0026rsquo;s (2016) premises in PWT, all participants reported that financial hardship resulted in a decreased sense of career choices and less access to decent work. Specifically, they were forced to enter the workforce at an early age due to financial difficulties in their families. Although food delivery work was not their preferred type of employment, they were driven to join this industry because it offered better remuneration than factory jobs. The literature has also documented that rural-to-urban migrant workers have increasingly turned to digital platform work in recent years due to relatively high earnings and the immediacy of wage payment (Chen \u0026amp; Sun, 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur participants also reported inadequate education as a major barrier to achieving their vocational goals. Indeed, previous studies have affirmed the importance of high-quality education to individuals\u0026rsquo; success in the labor market (Hooley, 2021; Sultana, 2021). Since our participants reported having relatively low levels of education, they had no other choice but to join the gig economy and become food delivery riders. In addition to a lack of human capital, most participants viewed limited social capital as a primary obstacle to their upward employment mobility in urban areas.\u0026nbsp;They reported that they faced significant challenges in finding decent jobs due to a lack of social networks.\u0026nbsp;This finding aligns with the research by Han and colleagues (2023), who suggested that a dearth of Guanxi could impede the ability of migrant workers from China to secure decent employment opportunities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCopying Resources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe role of inner and relational resources, including the three moderators of PWT - social support, proactive personality, and critical consciousness (Duffy et al., 2016) - as well as self-leadership, was also salient in the descriptions of food delivery riders in this study.\u003c/p\u003e\n\u003cp\u003eMost participants viewed social support as essential to their work-based experiences. First, consistent with Wu et al.\u0026rsquo;s (2022) finding, our participants reported that family support - a major source of social support - provided them with the necessary guidance and encouragement to pursue their career aspirations. Additionally, interacting with fellow villagers helped participants find better-paying jobs, which aligns with Keung et al.\u0026rsquo;s (2007) claim that developing networks with townsmen facilitates the exchange of information regarding employment opportunities. Finally, mirroring previous studies (Kost, 2020), communicating with other food deliver riders not only fulfilled our participants\u0026rsquo; relational needs but also offered them opportunities to acquire skills and knowledge that could enhance work efficiency. Taken together, our study offers new insights into how different types of social support impact the career experiences of platform-based workers.\u003c/p\u003e\n\u003cp\u003eConsistent with the findings of Autin et al. (2018), most participants in our study reported proactive personality and critical consciousness as facilitators of their career pursuits. Regarding proactive personality, participants displayed active coping strategies such as providing extra service for customers in order to receive their positive feedback. Additionally, our participants reported that they critically evaluated algorithmic management and took actions to protect their rights. Although critical consciousness did not facilitate the career trajectories of emerging adults in the US (San Antonio \u0026amp; Kaplan-Bucciarelli, 2022), our study found that it positively impacted the vocational experiences of food delivery workers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough self-leadership was not proposed as the PWT moderators, we found that it played a positive role in our participants\u0026rsquo; work-related experiences. As reported by most participants, the nature of their work is independent and flexible, requiring them to set goals, create routines, and implement self-rewards to promote their work progress. Additionally, participants reported that they may encounter malicious negative reviews or misunderstandings from customers during their work, so they had to regulate their emotions in a positive manner. This aligns with Ashford et al.\u0026rsquo;s (2018) view that emotional regulation is crucial for gig workers to navigate the new world of work. In response to Duffy et al.\u0026rsquo;s (2023) call for further studies to explore different moderators, quantitative studies may be needed to examine the role of self-leadership in the relationship between contextual factors and work outcomes within PWT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWork Characteristics and Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnother goal of this study was to explore food delivery riders\u0026rsquo; perspectives on their current work and career aspirations. When asked about their attitudes towards food delivery work, all participants in the present study regarded it as a means of earning money, which echoes the survival needs in the PWT. Furthermore, when the survival aspects of working emerged in the interviews, participants\u0026rsquo; narratives extended beyond individual survival and encompassed the provision for their families. As suggested by Zheng and Wu (2022), food delivery riders tend to cite their responsibility as breadwinners as a fundamental motivation for choosing food delivery work. However, most participants expressed a sense of job dissatisfaction, stating that the amount of money they received did not reflect the effort they put in. Corroborating PWT-informed research (Duffy et al., 2016; Wan \u0026amp; Duffy, 2022), a lack of decent work (e.g., inadequate pay) was associated with lower job satisfaction.\u003c/p\u003e\n\u003cp\u003eAnother notable characteristic of food delivery work is long working hours. In stark contrast to Duffy et al.\u0026rsquo;s (2016) conceptualization of decent work, most participants in our study worked overtime and did not have adequate time for rest and leisure activities. Irregular working hours were more prevalent on holidays and rainy days, as online labor platforms tend to increase the number of tasks assigned to food delivery riders on these days. As a result, more than half of the participants in this study reported feeling physically and mentally exhausted due to working overtime. This finding echoes prior PWT research (Duffy et al., 2019, 2021), where a lack of decent work (e.g., insufficient rest) was associated with numerous physical and mental health problems. However, our findings go beyond existing literature and theory, as work fatigue was exacerbated by the fact that many participants had to endure the intense algorithmic scrutiny imposed by digital platforms while performing delivery tasks.\u003c/p\u003e\n\u003cp\u003eRegarding work conditions, many participants reported that they had to work in precarious environments, which often included heavy traffic congestion and harsh weather conditions. This not only made their work more challenging but also posed a significant threat to their safety and overall well-being (Gregory, 2021). Hence, many participants in this study expressed an intention to quit their jobs. This is not surprising given the evidence in the PWT literature that indecent and precarious work conditions are positively associated with employees\u0026rsquo; withdrawal intentions (Wan \u0026amp; Duffy, 2022, 2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen it comes to social benefits, all participants in this study reported that they were unable to access basic benefits such as healthcare through their work. A common explanation is that gig workers are often classified as self-employed service providers rather than formal employees, which gives platform companies an excuse to avoid government regulations on employee rights and benefits (Allon et al., 2023; Wu et al., 2022). As a result, participants who recognized the importance of job security chose to pay for their own health care and retirement plans.\u003c/p\u003e\n\u003cp\u003eThe final characteristic of food delivery work highlighted by our participants was its low barriers to entry. Prior research has indicated that food-delivery platform work is a low-status job with low skill requirements (Le Breton \u0026amp; Gali\u0026egrave;re, 2023). Consistent with Goods et al.\u0026rsquo;s (2019) findings, some of our participants struggled to establish a sense of meaning and well-being at work. This was due to their perception that their jobs were easily replaceable and lacked opportunities for growth. Supporting PWT-informed research, the absence of decent work is associated with a diminished sense of work fulfillment due to the failure to satisfy basic needs for self-determination (Blustein et al., 2019; Duffy et al., 2016).\u003c/p\u003e\n\u003cp\u003eWhen asked about their future goals, most participants in the present study expressed a desire to obtain more decent and stable positions which provide basic benefits such as health insurance. Some participants aimed to acquire specialized skills to prepare themselves for the ever-changing world of work. Meanwhile, several participants expressed an interest in starting their own business at the opportune moment. These findings are consistent with Zwettler et al.\u0026rsquo;s (2023) observation that gig workers tend to leverage online work platforms as a stepping stone to advance their careers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePractical Implications\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, this study found that\u0026nbsp;inner and relational resources, including proactive personality, social support, critical consciousness, and self-leadership,\u0026nbsp;could effectively help participants cope with challenges at work. These findings have significant implications for career counselors and organizational leaders. To enhance critical consciousness, counselors may find it useful to help clients critically assess their circumstances and take actions to advocate for their rights when confronted with unjust treatment. It is also important for counselors to assist clients in developing active coping strategies and establishing a personal social support system as they navigate their careers. For instance, counselors may use interventions to inspire clients to initiate positive changes in their work lives and make the most of relational resources in the work and non-work domains. Additionally, to foster self-leadership, online labor platforms should encourage food delivery riders to take ownership of their work. Recognizing the positive impact of individual agency on one\u0026rsquo; work, platform leaders can incorporate setting clear goals, implementing self-reward, and regulating emotions into on boarding training for food delivery riders.\u003c/p\u003e\n\u003cp\u003eSecond, most participants reported experiencing immense pressure from algorithmic management, which resulted in physical and mental exhaustion. As such, online labor platforms should adopt a moderately efficiency-oriented approach when designing and implementing algorithms. For example, takeout delivery platforms can use algorithmically neutral methods to reduce the burden on food delivery riders during peak hours, thereby demonstrating the organization\u0026rsquo;s commitment to their well-being. In addition, platforms can offer gig workers appropriate support by establishing effective channels for feedback and complaints, addressing algorithm evaluation errors in a fair and transparent manner, and taking appropriate action against customers who make malicious or false comments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, the results showed that most participants were dissatisfied with their work and had intentions to withdraw from the platform. To address these issues, we recommend that platform organizations provide gig workers with fair compensation, opportunities for skill development and career advancement, and adequate time for rest and leisure activities. Platform managers should also take effective measures to ensure their safety at work. At the systemic level, policymakers should enact laws to protect the rights of gig workers and require platform enterprises to provide them with benefits such as healthcare and work-related injury insurance. Meanwhile, policymakers should leverage media channels to promote a positive portrayal of gig workers and cultivate an egalitarian work ethic across society. Such actions will enhance the work fulfillment and overall well-being of food delivery riders, and ultimately promote the healthy development of the gig economy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations and Future Directions \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations that invite opportunities for future research. First, sampling bias may have affected our study as most of our participants were recruited from southern China, limiting the transferability of the findings to other contexts. Moreover, our participants were all full-time food delivery riders with relatively low levels of education, so our findings may not apply to part-time riders or those with higher levels of education. Hence, future research should examine the career trajectories of food delivery riders across a broader range of geographic regions, employment statuses, and educational levels.\u003c/p\u003e\n\u003cp\u003eSecond,\u0026nbsp;this study only focused on food delivery riders who primarily engage in physically demanding work in China, which may restrict the transferability of our findings to other types of gig workers. For instance, online car-hailing drivers may not be as economically constrained as food delivery riders due to entry requirements such as owning a vehicle and having a local hukou in some large cities. Therefore, future research could consider collecting data from a variety of gig workers to compare their work experiences within the PWT model.\u003c/p\u003e\n\u003cp\u003eThird, the present study only recruited participants from China, which may limit the generalizability of the findings. Given the significant differences in government policies and regulations in shaping the gig economy across countries, the career challenges faced by gig workers in China may not be applicable to those in the West. To the best of our knowledge, delivery workers in the United States mainly use cars rather than motorcycles to deliver food, which prevents them from experiencing adverse working conditions outdoors. Therefore, it would be worthwhile to conduct a cross-cultural comparative study with samples from both Western and Eastern cultures in future research.\u003c/p\u003e\n\u003cp\u003eFinally, this study used a qualitative approach to explore the work experiences of gig workers, which inevitably involves a degree of subjectivity. While the findings provided insight into the core constructs of PWT, they were unable to establish causality between these variables. Therefore, future research could consider using a quantitative paradigm to gain a better understanding of the career development of food delivery riders. A longitudinal design would be particularly beneficial to illustrate how gig workers\u0026apos; careers evolve over time and how their experiences within the PWT model shape their future career trajectories.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study aimed to explore the career development of gig workers from a PWT perspective. We conducted semi-structured interviews with 12 food delivery riders in China and employed the CQR approach to analyze the data. We found that vocational barriers included economic constraints, inadequate education, and limited social capital, while resources promoting their work experiences encompassed social support, critical consciousness, proactive personality, and self-leadership. Additionally, although participants reported that their work enabled them to earn a living, but their work was characterized by a lack of essential benefits, long hours, precarious working conditions, and low skill requirements. As a result, they experienced decreased work satisfaction, occupational fatigue and withdrawal intentions. These findings provided initial support for the applicability of the PWT in understanding the career trajectories of gig workers in a non-Western, collectivist cultural context. Implications for future research rooted in the psychology of work and vocational interventions aimed at promoting social justice are presented.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: W.W.; Data curation: W.W.; Formal analysis: W.W., W. L.; Methodology: W.W. ; Data collection: W.W.; Supervision: H. H.; Writing original draft: W.W.; Reviewing and editing :W.W., W. L.,H.H.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all participants for their voluntary participation in this study. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article received ethical approval from East China Jiao Tong University, and was conducted according to the guidelines of the Declaration of Helsinki. All subjects were informed about the study and participation was fully on a voluntary basis. Participants were ensured of confidentiality and anonymity of the information associated with the surveys. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Conflicting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors\u0026nbsp;declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAllan, B. 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Kicking off a Gig Work Career: Unfolding a Career Learning Cycle of Gig Workers. \u003cem\u003eJournal of Career Assessment\u003c/em\u003e, 10690727231212188. https://doi.org/10.1177/10690727231212188\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e \u003cem\u003eParticipant Self-reported Demographics\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"599\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003ePseudonym\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eResidence registration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003eWork months\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eAlex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eEric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eTrade school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eBob\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eArron\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eLucy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003ePeter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eMolly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003ePrimary school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eJohn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eTrade school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eTrade school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eJason\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eTrade school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eMario\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eTim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7.33333%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.3333%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003eJunior high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.6667%;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.8333%;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.6667%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Pseudonyms were selected by participants or, at their request, by the first author.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eList of Domains, Categories, and Frequencies \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eDomain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eFrequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eCases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eStructural barriers\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eEconomic constraints \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eGeneral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eInadequate education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLimited social capital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eNo driver\u0026rsquo;s license\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVariant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eMarginalization due to rural hukou\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVariant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eCoping resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eGeneral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eProactive personality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eCritical consciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eSelf-leadership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eResilience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVariant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eView of current work\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eMeans of livelihood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eGeneral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLack of essential benefits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eGeneral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLong working hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eIndecent work conditions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLow skill requirements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eAutonomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVariant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eWork-related outcomes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLower job satisfaction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eOccupational fatigue\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eTurnover intentions\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLimited sense of work meaning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVariant\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eView of future\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eFind a more decent job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eLearn new skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eStart a business\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eTypical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 238px;\"\u003e\n \u003cp\u003eUncertainty about future\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eVariant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. For our participants, \u003cem\u003egeneral\u003c/em\u003e applies to 11-12 cases;\u003cem\u003e\u0026nbsp;typical\u003c/em\u003e applies to 6-10 cases; and \u003cem\u003evariant\u0026nbsp;\u003c/em\u003eapplies to 3-5 cases.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"career development, psychology of working, food delivery riders, qualitative research, China","lastPublishedDoi":"10.21203/rs.3.rs-4935308/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4935308/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eWith the rise of the gig economy, platform work has has grown significantly throughout the world. As one of the most dynamic platform workers in China, food delivery riders are an underrepresented group in terms of securing decent work. Building on the Psychology of Working Theory(PWT), the current study aimed to explore how contextual and individual factorsinfluenced the career development of food delivery riders in China. This study also examined their attitudes towards platform work and their career aspirations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe conducted semi-structured interviews with 12 participants aged 18-45 and utilized Consensual Qualitative Research (CQR) approach to conduct data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe results revealed that economic constraints, inadequate education, and limited social capital were the main vocational barriers for these riders. Their coping resources included social support, critical consciousness, proactive personality, and self-leadership. Although food delivery work allowed them to earn a living, it featured long working hours, poor working conditions, limited benefits, etc. As such, they experienced job dissatisfaction, occupational fatigue, and turnover intentions. Regarding future goals, our participants mentioned finding a more decent job, learning new skills, and starting a business.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Overall, this study marks the first known application of PWT to understand how food delivery riders navigate the new world of work in China. Practical implications and directions for future studies are discussed.\u003c/p\u003e","manuscriptTitle":"The Career Development of Food Delivery Riders in China: A Qualitative Investigation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-08 04:19:21","doi":"10.21203/rs.3.rs-4935308/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8815171d-a06e-4c48-9d0c-2f1c9a5f5fef","owner":[],"postedDate":"October 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":38156288,"name":"Biological sciences/Psychology"},{"id":38156289,"name":"Health sciences/Health occupations"}],"tags":[],"updatedAt":"2024-12-02T07:09:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-08 04:19:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4935308","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4935308","identity":"rs-4935308","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}