HRM RESEARCH PROPOSAL

 What factors influence gig workers’ acceptance of algorithmic management in the British food delivery industry?

Background

           This research process examines the factors that determine how gig workers are accepted on the algorithmic management platforms in the food delivery industry (Geraci, 2020). Gig workers in the food industry refer to those working in temporary jobs such as independent contractors, contract firm workers, online platform workers, and on-call workers. In the British food delivery industry, gig workers refer to those who use the algorithmic management platform to deliver food to customers. These gig workers include Uber drivers, Glovo operators, and Just Eat Takeaway, among others. Therefore, gig workers in the U.K. are the food delivery people who do the job freelance to earn their money. Still, they are not permanently contracted to the food restaurants or the algorithmic management platform (Geraci, 2020).

Meanwhile, some factors influence their acceptance in the food delivery industry, and this paper will look into the mechanism of compliance. Algorithmic management has predominantly been examined in terms of excessive disciplinary power of the gig workers and ration labor controls. Hence, gig workers are always bound to have fear, frustration, and passivity when using the platform. On such an algorithmic management platform, the gig workers must be in their best character possible because rational control, although fallible, is supported by methods of subjectification (Geraci, 2020).

Research Aim and Questions

           This research aims to establish the factors that influence gig workers’ acceptance of algorithmic management in the British food delivery industry. Thus, 55 respondents of the gig workers in the food delivery industry will be interviewed and examined to understand the factors, how they influence their acceptance of the algorithm management, their opinions about the platform, and why specifically the food delivery industry. Therefore, this research will involve data collection, analysis of the collected data, and discussion of the findings to extract possible theories to explain the phenomenon under study. 

The Key Objectives are:

• To establish the factors that influence gig workers’ acceptance towards algorithmic management in the British food delivery industry
• To understand the gig workers’ views and perspectives about the algorithmic management platform. 
• To explore how algorithmic management has changed the landscape of food delivery in the United Kingdom.

Literature Review

In this age and era, there have been increases in technological innovations that have made life easier. Hence, there has been rapid development of machine learning algorithms that underpin the current artificial intelligence systems and have developed automation innovations (Wood et al., 2018). At the beginning of the 21st century, there were advancements in the industrial sector due to the scientific management implementations, which introduced a new managerial approach that seeks to increase the efficiency of service delivery. Due to this kind of managerial approach, there have been detrimental effects on the gig workers. 

First, their autonomy is a result of the strictness of the algorithmic management with detailed planning of activities and close monitoring of the workers. Therefore, as a result, these new technologies have increased companies’ productivity in planning, monitoring, and rigorously controlling the workers’ performances. Thus, the gig economy has explicitly been the one most affected due to this change in managerial approach, which has drastically shifted the relations between gig and employers in the gig economy and brought about adjustments like employment (Wiggins, 2018). Industrial relations and fundamental rights are now in balance when there is no more contact between workers and employers. Workers are currently being employed online and managed by apps. These apps are empowered in ways that control workers, but they can also dismiss them, leading to serious questions about the accountability of these decisions. 

Meanwhile, trade unions in the U.K. and public institutions are increasingly coming under pressure to protect these workers who these companies term as independent contractors or freelancers (ReutersCostas, 2021). It is especially notable for those gig workers working full-time like in the food delivery industry because food is supplied and delivered daily. Therefore, these workers are working full-time, but they do not have their fundamental rights protected or any recognized benefits because of the unregulated nature of their employment status and contracts. Hence, on the gig workers part in the British food delivery industry, acceptance of algorithmic management has been difficult because they feel not fully protected from unemployment uncertainties. It is why there have been efforts in the recent past to pass labor laws that will protect the gig economy so that they have the minimum wage bills, retirement benefits, and generally proper employment rights (ReutersCostas, 2021).

For instance, a trade union lost a case in a U.K. court that lobbied for Deliveroo over employment and payment conditions on behalf of the food delivery industry’s gig workers, which was a massive setback to the efforts of those workers in the gig economy. The Independent Workers Union of Great Britain failed in which they lobbied for Deliveroo to revise the pay, hours, and holidays terms and conditions. The British courts have always stood with the workers in the gig economy and their employment rights (Keane, 2021). For instance, in 2018 June, the court found in favor of a tradesman that Pimlico plumbers limited should have treated him as a worker providing him the right to sue the company and vacation pay. Meanwhile, in the Deliveroo case, the company argues that it willingly lets its riders pass jobs to other people who can do it on their behalf; hence they cannot be classified as workers. This argument convinced the court to rule that the riders are not recognized for collective bargaining for their employment rights because they were not classified as company workers (Keane, 2021).

Nonetheless, they have a breakthrough in the recent U.K.’s Uber driver benefits. The company lost a court case in March 2021, so it was forced to offer guaranteed entitlements to its U.K. drivers, including pension plan, vacation pay, and minimum wage. In a statement, Uber said that it seeks to expand the benefits to the whole of Europe and the USA. Meanwhile, the British gig economy activists argued that even if Uber has agreed to improve their drivers’ employment terms, they have not implemented and complied with their full proposal. They vowed to continue putting pressure until it is fully implemented. Labor activists, especially those from the gig economy, worker groups, and legislators in the U.K., have always pushed gig workers to be recognized as employees and sometimes win court cases. But still, the struggle continues, and not all the companies have complied. 

Some companies are preparing for change, whether due to pressure or just their due diligence, such as Just Eat Takeaway. The company is now providing its food delivery riders employment contracts. Their workers will be paid above minimum wage, paid an hourly salary, and guaranteed employment insurance and social security compliance with U.K. legislation (Jarrahi et al., 2021). Therefore, the above examples of efforts from the workers’ unions, resistance from the concerned companies, and pressure from legislation, the gig workers’ acceptance of the algorithmic management has been a rough journey. The factors that influence their acceptance of the platforms have been well documented in their civil cases against their companies. The arguments have been around employment rights, job security, and compliance with the minimum wage bill and job benefits. It is an issue in the contemporary digital world because the gig economy employs millions of British citizens. Still, it is unregulated, and workers are the ones on the receiving end (Jarrahi et al., 2021).

Research Design and Methodology

The type of research I intend to carry out is qualitative research. The nature of the research question requires study to establish answers to the whys and hows of the phenomenon under investigation. Therefore, this research is subjective and will include its findings in a written format instead of a numerical one. Meanwhile, this research will involve collecting information from the gig workers in various food delivery companies, intending to understand their working environment, grievances, and study topics. Thus, there will be a sampling of research participants and collecting data. 

Sampling 

The best-suited sampling method for this research will be purposive sampling. This qualitative nonprobability sampling method selects participants from their sampling frame because they have characteristics that the researcher desires (Emmel, 2013). In this case, the research will specifically target the gig workers in the food delivery companies such as Uber Eats, Just Eat Take Away, and Deliveroo to establish their working experience and environment. Hence, in this kind of purposive sampling, this research will start with setting what factors influence the gig workers in the food delivery industry to accept algorithmic management. Thus, selection will specifically look to bring these workers together because they have the same characteristics as drivers or riders. They experience the same working environment and understand the underlying issues when it comes to their employment rights. This way, the study will be able to extract the information necessary for this research. Lastly, purposive sampling will be essential in this research because it will target specific trade unions, workgroups, and legislators who work closely with gig workers to push for reforms. 

Data Collection

Data collection is the method this research will use to collect data analyzed to come up with findings. Thus, the most suited qualitative research data collection methods for this study are interviews and focus groups.

• Interviews

Interviews will involve setting up a discussion with the research participants to collect first-hand data. Interviews will be conducted in three ways which are structured, semi-structured, and unstructured. These types of interviews are essential for this study because they will allow the collection of different kinds of data based on how comfortable the research participant will be with a particular type of interview. Hence, structured interviews are those that are administered via questionnaires whereby listed closed-ended questions will be asked (Billups, 2020). In this interview, the research participants will not elaborate on their responses to make the process quick and easy.

Meanwhile, for further elaborations, another set of unstructured interviews will be administered to allow the participants to expound on their responses to get the depth of their experiences. Unstructured interviews will be vital to this research because the researcher can dig more information from the research participants through follow-up questions. The research participants feel more comfortable in unstructured interviews, making it easy to extract more information. 

Advantages of using interviews for data collection 

• Interviews provide accuracy in screening whereby face-to-face interviews allow the interviewer to read the other non-verbal communications such as body language. It is also crucial in screening accuracy because the research participant cannot lie about their gender identity or sexual orientation. After all, the researcher can see it. Therefore, in this research, interviews will help reduce the collection of misleading information.
• Keep focus. Interviews allow the interviewer to focus on the topic under research because they have control over the interview process. Face-to-face interviews are in the moment, and there are no distractions that can lead to research participants giving false or misleading information. 
• It is also easy to capture emotions, feelings, and attitudes in interviews, which are part of the collected information. 

Sample Interview Questions

• What kind of a gig worker are you in the food delivery industry?
• What is your opinion about algorithmic management?
• What grievances do you have concerning your employment rights in your work environment?
• What factors do you think affects the acceptability of algorithmic management in your line of work?
• What changes would you want to see in the legislation or employment terms to feel fully protected in your line of work?

1. Focus Groups

Focus groups are more like unstructured interviews, but they have unique characteristics and are suitable for this research. Thus, a focus group is a group discussion organized around a particular topic under study. The forum is guided, controlled, monitored, and recorded by the researcher to collect information. Hence, in this case and context, the focus group will comprise the members of the gig economy and specifically those gig workers in the food delivery industry, the different workgroups, legislators of the labor laws, labor unions, and the researcher will be the group’s moderator. The focus group aims to get the opinion of different parties involved in the gig economy or concerned about it and discuss their thoughts, views, perspectives, experiences, beliefs, behaviors, and attitudes towards the topic under research. 

Analysis and Discussion

When data collection is complete, it needs to be analyzed to make sense. Hence, because this is a qualitative type of research, the grounded theory is the most suitable method to analyze the data. In grounded theory, set inductive techniques are used to conduct a study to develop an idea (Bazeley, 2020). It is the best-suited data analysis method because the type of data collected in this research will be written; hence, this kind of data requires an approach that aims to construct mid-level theories directly from the collected data. 

Advantages of using grounded theory for data analysis 

• It provides explicit, sequential guidelines for conducting qualitative research. 
• Advancement of qualitative data conceptual analysis. 
• Integrates and streamlines the collection of data and analysis. 
• It Provides legitimacy to the qualitative study as scientific research.

 

How grounded theory works 

Grounded theory is iterative and recursive, which involves the meticulous application of particular processes and methods (Bryant & Charmaz, 2019). In this sense, methods are the systematic tools or procedures used in data collection and analysis. In this research, the grounded theory will start with purposive sampling, then data collection and analysis characterized by various coding stages that will be undertaken in conjunction with theoretical sampling, comparative analysis, and memoing (Tie et al., 2019). Theoretical sampling will be conducted on the collected data until reaching theoretical saturation. Thus, these processes and methods develop an unfolding and iterative system of interactions and actions inherent in the grounded theory. The methods interconnect and inform the recurrent elements in the study process, which are dynamic and iterative hence multidirectional. Therefore, the grounded theory involves purposive sampling, constant comparative analysis, memoing, generating data, and finally coding (Tie et al., 2019). After all these methods and processes, patterns and themes start appearing in the analyzed data, which forms the findings of the topic under research. 

Ethical Considerations

Every research has its ethical considerations that must be considered because of the legal and moral obligations involved and required. Thus, the ethical considerations foreseeable in this research are;

• Respect for confidentiality and anonymity

Research requires data collection from research participants to make meaningful findings from the data (Miller et al., 2012). While engaging the research participants for data gathering, the researcher must consider the confidentiality and anonymity of their research participants. Therefore, this implies that personal information about the research participants, such as names and contacts, should never be shared with third parties. In this case and context, the gig economy and its politics make it a sensitive and controversial topic in the U.K. today because so much is at stake, such as involved company share prices getting affected by certain individual opinions. Hence collecting data from participants should be an activity that is carried out with utmost professionalism. It means that the research participants should be guaranteed that their identity will remain anonymous and personal data will not be shared with third parties. Thus, this research will have a confidentiality agreement that the researcher and participant will sign to ascertain commitment to confidentiality and anonymity. 

• Informed Consent 

Informed consent as an ethical issue in research means the participant should consent to the information shared in the study before it is used. Based on Armiger’s definition, informed consent means a person should share information voluntarily, knowingly, and with a clear mind (Miller et al., 2012). Thus, informed consent seeks to prevent assault in the integrity of the research participants, protecting them from researchers using their information without their knowledge hence tainting their public image. In this research, informed consent will be enforced by signing a consent form, an agreement between the researcher and participants that the information collected from the research participant was shared voluntarily, knowingly, and with a clear mind. Hence, this consent form will provide a clear outline of how the information shared by the research participants is intended to be used by the researcher. 

• Vulnerable groups of people

In the current world of research, there is an increase in the ethical concerns of using vulnerable groups of people as subjects in the study. According to Fisher, vulnerable groups of people are unable to protect their rights and welfare; hence the gig workers fall under this group because they do not have employment rights, and for the longest time, they have been fighting for these rights in courts (Miller et al., 2012). Ethical concerns arise based on the arguments and opinions that vulnerable groups of people cannot give informed consent and their inability to protect themselves against the topic’s sensitivity under study. They may be forced or threatened to participate. Therefore, vulnerability increases the need for justification of the research for the involvement of such research subjects.

Meanwhile, in this case, this research is purely for educational purposes and hopefully helps solve the stand-off between the gig workers and the company they work for. The topic under study is meant to understand the factors that affect the acceptance of algorithmic management in the gig economy and, specifically, the gig workers in the food delivery industry. Hence, even if the gig workers are subjects in this study and are considered a vulnerable group, this study is meant to help them by establishing findings that can help tackle the problem at hand.

• Maintenance of the highest level of objectivity 

Objectivity means sticking to the topic under study and not going out of the case where research subjects may get offended (Miller et al., 2012). It is an ethical issue because the sensitivity of the matter under study and the vulnerable group of the gig workers’ employment rights result from algorithmic management require utmost professionalism and objectivity. Hence, this research intends to carry out the data collection process with an objective and open mind, respecting the beliefs and opinions of these research subjects and sticking to the topic under study.  

Project Time Table

 

Project Stage	Date
Submit Research Proposal
Arrange Access of research participants
Interviews with data analysis
Draft submission
Revise and finalize
Revise and finalize
Submit Dissertation

 

Conclusion

The gig economy and worker’s grievances are a 21st-century problem and require proper research to find a solution on the factors that affect the acceptance of algorithmic management in the gig economy and, specifically, the food delivery industry. That is the reason why this research is necessary because it seeks to collect data from the affected people in the food delivery industry, workgroups, and labor unions to understand the whole problem and establish potential findings and solutions. Meanwhile, this research will seek to consider all the ethical issues that may arise during the research process to remain objective to its cause.

References

Bazeley, P. (2020). Qualitative data analysis: Practical strategies. SAGE.

Billups, F. D. (2020). Qualitative data collection tools: Design, development, and applications. SAGE Publications.

Bryant, A., & Charmaz, K. (2019). The SAGE handbook of current developments in grounded theory. SAGE.

Cram, W. W., Wiener, M., Tarafdar, M., & Benlian, A. (2020, December 1). Algorithmic controls and their implications for gig worker well-being and behavior completed research paper. ResearchGate. Retrieved August 30, 2021, from https://www.researchgate.net/publication/348372950_Algorithmic_Controls_and_their_Implications_for_Gig_Worker_Well-being_and_Behavior_Completed_Research_Paper

Emmel, N. (2013). Sampling and choosing cases in qualitative research: A realist approach. SAGE.

Geraci, M. (2020, April 10). Algorithmic management: A liability-free method to manage workers’ performance? Sistema de Información Científica Redalyc, Red de Revistas Científicas. Retrieved August 30, 2021, from https://www.redalyc.org/journal/6002/600263428002/html/

Jarrahi, M. H., Newlands, G., Lee, M. K., & Kinder, E. (2021, May). (PDF) Algorithmic management in a work context. ResearchGate. Retrieved August 30, 2021, from https://www.researchgate.net/publication/351462257_Algorithmic_Management_in_a_Work_Context

Keane, J. (2021, April 12). Europe could be seeing the decline of its gig economy. And new rules could mean higher prices. CNBC. Retrieved August 30, 2021, from https://www.cnbc.com/2021/04/12/europe-could-be-seeing-the-end-of-its-gig-economy-deliveroo-uber.html

Miller, T., Birch, M., Mauthner, M., & Jessop, J. (2012). Ethics in qualitative research. SAGE.

ReutersCostas, P. (2021, March 17). Uber’s U.K. driver benefits highlight broader gig-worker challenges. Reuters. Retrieved August 30, 2021, from https://www.reuters.com/world/europe/ubers-uk-driver-benefits-highlight-broader-gig-worker-challenges-2021-03-17/

Tie, Y. C., Birks, M., & Francis, K. (2019, January 2). Grounded theory research: A design framework for novice researchers. PubMed Central (PMC). Retrieved August 28, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6318722/

Wiggins, K. (2018). U.K. Food Delivery Service Riders Lose Employment Rights Bid. Insurance Journal. https://www.insurancejournal.com/news/international/2018/12/05/511099.htm

Wood, A. J., Graham, M., & Lehdonvirta, V. (2018, August 8). Good gig, bad gig: Autonomy and algorithmic control in the global gig economy – Alex J wood, Mark Graham, Vili Lehdonvirta, ISIS Hjorth, 2019. SAGE Journals. Retrieved August 30, 2021, from https://journals.sagepub.com/doi/full/10.1177/0950017018785616