Abstract
Economic dependence is consistently identified as a key factor in understanding gig workers’ experiences (e.g., Kuhn & Maleki, 2017; Schor et al., 2020; Spreitzer et al., 2017), but empirical estimates of the rate of economically dependent gig workers vary considerably across sources (e.g., from 3% to 56%). To obtain a reliable estimate of this rate, this work used an inductive approach and an experimental survey design to investigate the significance and size of (1) methodological (i.e., survey item wording) effects and (2) demographic predictors of whether gig workers endorse economic dependence items. Results are also compared across nonrandom but representative samples from two common types of gig work – crowdwork (N = 447, Study 1) and rideshare driving (N = 919, Study 2). This study offers a conservative estimate that 45% of crowdworkers and 74% of rideshare drivers are economically dependent on their gig. Three predictors of economic dependence were significant across both groups – item wording, marital status, and hours worked on-platform. Four more predictors were significant for one group only – hours worked off-platform for crowdworkers only; and age, sex, and gig tenure for rideshare drivers only. Methodological effects were larger among crowdworkers, and sex and marital status showed opposite effects compared to previous research on financial stress. Theoretical and practical implications are discussed with a focus on better understanding economic dependence and improving gig workers’ experiences.
Similar content being viewed by others
Notes
Age showed a significant omnibus difference by condition, with F(4,914) = 2.72, p = .03, but none of the Bonferroni-adjusted post hoc tests were significant, with ps ≥ 0.24.
References
Adams, J. S. (1965). Inequity in social exchange. Advances in Experimental Social Psychology, 2, 267–299. https://doi.org/10.1016/S0065-2601(08)60108-2.
Arechar, A. A., Kraft-Todd, G. T., & Rand, D. G. (2017). Turking overtime: How participant characteristics and behavior vary over time and day on Amazon Mechanical Turk. Journal of the Economic Science Association, 3, 1–11. https://doi.org/10.1007/s40881-017-0035-0.
Ashford, S. J., Caza, B. B., & Reid, E. M. (2018). From surviving to thriving in the gig economy: A research agenda for individuals in the new world of work. Research in Organizational Behavior, 38, 23–41. https://doi.org/10.1016/j.riob.2018.11.001
Ashforth, B. E., & Kreiner, G. E. (1999). How can you do it? Dirty work and the challenge of constructing a positive identity. Academy of Management Review, 24, 413–434. https://doi.org/10.5465/AMR.1999.2202129.
Bajwa, U., Gastaldo, D., Di Ruggiero, E., & Knorr, L. (2018). The health of workers in the global gig economy. Globalization and Health, 14, 124–127. https://doi.org/10.1186/s12992-018-0444-8.
Bakker, A. B., & Demerouti, E. (2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22, 309–328. https://doi.org/10.1108/02683940710733115.
Berg, J. (2016). Income security in the on-demand economy: Findings and policy lessons from a survey of crowdworkers (74No. vol.). International Labour Office. http://www.ilo.int/wcmsp5/groups/public/---ed_protect/---protrav/---travail/documents/publication/wcms_479693.pdf.
Black, K. J., DePhillips, O., & Britt, T. W. (2019). November 6–9). I can’t afford to relax: Relating financial adequacy to recovery and health [Conference presentation]. 13th International Conference on Occupational Stress and Health: Work, Stress, and Health, Philadelphia, PA, United States.
Bleweis, R., Boesch, D., & Gaines, A. C. (2020, August 3). The basic facts about women in poverty. Center for American Progress. https://www.americanprogress.org/.
Bozzon, R., & Murgia, A. (2022). Independent or dependent? European labor statistics and their (in)ability to identify forms of dependency in self-employment. Social Indicators Research, 160, 199–226. https://doi.org/10.1007/s11205-021-02798-1.
Brawley, A. M. (2017). The big, gig picture: We can’t assume the same constructs matter. Industrial and Organizational Psychology: Perspectives on Science and Practice, 10, 687–696. https://doi.org/10.1017/iop.2017.77.
Brawley, A. M., & Pury, C. L. S. (2016). Work experiences on MTurk: Job satisfaction, turnover, and information sharing. Computers in Human Behavior, 54, 531–546. https://doi.org/10.1016/j.chb.2015.08.031.
Bricka, T. M., & Schroeder, A. N. (2019). What’s the gig deal? Examining contemporary work issues in the gig economy. Industrial and Organizational Psychology: Perspectives on Science and Practice, 12, 491–494. https://doi.org/10.1017/iop.2019.116.
Brief, A. P., Brett, J. F., Raskas, D., & Stein, E. (1997). Feeling economically dependent on one’s job: Its origins and functions with regard to worker well-being. Journal of Applied Social Psychology, 27, 1303–1315. https://doi.org/10.1111/j.1559-1816.1997.tb01807.x.
Bucher, E., Fieseler, C., Lutz, C., & Newlands, G. (2020). Shaping emotional labor practices in the sharing economy. In I. Maurer, J. Mair, & A. Oberg (Eds.), Theorizing the sharing economy: Variety and trajectories of new forms of organizing (Research in the Sociology of Organizations, Vol. 66, pp. 55–82). Emerald Publishing Limited. https://doi.org/10.1108/S0733-558X20200000066004.
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s mechanical Turk: A new source of inexpensive, yet high-quality. data? Perspectives on Psychological Science, 6, 3–5. https://doi.org/10.1177/1745691610393980.
Bureau of Labor Statistics (2018, September 28). Electronically mediated employment (CPS). Bureau of Labor Statistics. https://www.bls.gov/.
Byron, K. (2005). A meta-analytic review of work–family conflict and its antecedents. Journal of Vocational Behavior, 67, 169–198. https://doi.org/10.1016/j.jvb.2004.08.009.
Casey, L. S., Chandler, J., Levine, A. S., Proctor, A., & Strolovitch, D. Z. (2017). Intertemporal differences among MTurk workers: Time-based sample variations and implications for online data collection. SAGE Open, 7, 1–15. https://doi.org/10.1177/2158244017712774.
Cheung, J. H., Burns, D. K., Sinclair, R. R., & Sliter, M. (2016). Amazon Mechanical Turk in organizational psychology: An evaluation and practical recommendations. Journal of Business and Psychology, 32, 1–15. https://doi.org/10.1007/s10869-016-9458-5.
Chmielewski, M., & Kucker, S. C. (2020). An MTurk crisis? Shifts in data quality and the impact on study results. Social Psychological and Personality Science, 11, 464–473. https://doi.org/10.1177/1948550619875149.
Clark, L. A., & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7, 309–319. https://doi.org/10.1037/1040-3590.7.3.309.
Cook, C., Diamond, R., Hall, J., List, J. A., & Oyer, P. (2018). The gender earnings gap in the gig economy: Evidence from over a million rideshare drivers (No. 24732). National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w24732/w24732.pdf.
Crayne, M. P., & Brawley Newlin, A. (2023). Driven to succeed, or to leave? The variable impact of self-leadership in rideshare gig work. International Journal of Human Resource Management. https://doi.org/10.1080/09585192.2023.2211712.
David, E. M., Johnson, L. U., & Perry, S. J. (2023). Lean on me: A daily-diary study of the effects of receiving help in coworking spaces. Journal of Vocational Behavior. https://doi.org/10.1016/j.jvb.2021.103841.
Debus, M. E., Greulich, B., König, C. J., & Kleinmann, M. (2019). Insecure about how to rate your job insecurity? A two-study investigation into time frames applied to job insecurity measures. Occupational Health Science, 3, 421–435. https://doi.org/10.1007/s41542-019-00049-x.
U. S. Department of Labor (2020, September 22). Proposed rule: Independent contractor status under the FLSA, 29 CFR Parts, 780, 788, and 795. U. S. Department of Labor. https://www.dol.gov/.
U. S. Department of Labor (2008). Fact Sheet 13: Employment relationship under the Fair Labor Standards Act (FLSA). U. S. Department of Labor. https://www.dol.gov/.
Duggan, J., Sherman, U., Carbery, R., & McDonnell, A. (2020). Algorithmic management and app-work in the gig economy: A research agenda for employment relations and HRM. Human Resource Management Journal, 30, 114–132. https://doi.org/10.1111/1748-8583.12258.
Eagly, A. H., & Wood, W. (1999). The origins of sex differences in human behavior: Evolved dispositions versus social roles. American Psychologist, 54, 408–423. https://doi.org/10.1037/0003-066X.54.6.408.
Eagly, A. H., & Wood, W. (2016). Social role theory of sex differences. In N. A. Naples (Ed.), The Wiley Blackwell encyclopedia of gender and sexuality studies. https://doi.org/10.1002/9781118663219.wbegss183.
Farrell, D., Greig, F., & Hamoudi, A. (2018). The online platform economy in 2018: Drivers, workers, sellers, and lessors. JPMorgan Chase Institute. https://www.jpmorganchase.com/content/dam/jpmc/jpmorgan-chase-and-co/institute/pdf/institute-ope-2018.pdf.
Garin, A., & Koustas, D. (2021). The distribution of independent contractor activity in the United States: Evidence from tax filings. Joint Statistical Research Program of the Statistics of Income Division of the IRS. https://www.irs.gov/pub/irs-soi/21-rp-independent-contractor-activity.pdf.
Gray, M. L., & Suri, S. (2019). Ghost work: How to stop Silicon Valley from building a new global underclass. Houghton Mifflin Harcourt.
Herrmann, A. M., Zaal, P. M., Chappin, M. M., Schemmann, B., & Lühmann, A. (2023). We don’t need no (higher) education: How the gig economy challenges the education-income paradigm. Technological Forecasting and Social Change, 186, 122136. https://doi.org/10.1016/j.techfore.2022.122136.
Hilton, J. M., & Desrochers, S. (2008). The influence of economic strain, coping with roles, and parental control on the parenting of custodial single mothers and custodial single fathers. Journal of Divorce & Remarriage, 33, 55–76. https://doi.org/10.1300/J087v33n03_04.
Hoang, L., Blank, G., & Quan-Haase, A. (2020). The winners and the losers of the platform economy. Who Participates? Information Communication and Society, 23, 681–700. https://doi.org/10.1080/1369118X.2020.1720771.
Ilsøe, A., Larsen, T. P., & Bach, E. S. (2021). Multiple jobholding in the digital platform economy: Signs of segmentation. Transfer: European Review of Labour and Research, 27, 201–218. https://doi.org/10.1177/1024258921992629.
Ipeirotis, P. G. (2010). Demographics of Mechanical Turk (No. CeDER-10-01). New York University Center for Digital Economy Research. https://archive.nyu.edu/bitstream/2451/29585/2/CeDER-10-01.pdf.
Keith, M. G., Harms, P., & Tay, L. (2019). Mechanical Turk and the gig economy: Exploring differences between gig workers. Journal of Managerial Psychology, 34, 286–306. https://doi.org/10.1108/JMP-06-2018-0228.
Keith, M. G., Harms, P. D., & Long, A. C. (2020). Worker health and well-being in the gig economy: A proposed framework and research agenda. In P. L. Perrewé, P. D. Harms, & C.-H. Chang (Eds.), Entrepreneurial and small business stressors, experienced stress, and well-being (Research in occupational stress and well-being, Vol. 18) (pp. 1–33). Emerald Publishing Limited. https://doi.org/10.1108/S1479-355520200000018002.
Kuhn, K. M., & Maleki, A. (2017). Micro-entrepreneurs, dependent contractors, and instaserfs: Understanding online labor platform workforces. Academy of Management Perspectives, 31, 183–200. https://doi.org/10.5465/amp.2015.0111.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer.
Litman, L., Robinson, J., & Rosenzweig, C. (2015). The relationship between motivation, monetary compensation, and data quality among US- and India-based workers on mechanical Turk. Behavior Research Methods, 47, 519–528. https://doi.org/10.3758/s13428-014-0483-x.
Litman, L., Robinson, J., & Abberbock, T. (2017). TurkPrime.com: A versatile crowdsourcing data acquisition platform for the behavioral sciences. Behavior Research Methods, 49, 433–442. https://doi.org/10.3758/s13428-016-0727-z.
Maffie, M. D. (2020). The role of digital communities in organizing gig workers. Industrial Relations: A Journal of Economy and Society, 59, 123–149. https://doi.org/10.1111/irel.12251.
Marquez, S., Alanis, J., & Brawley Newlin, A. (2021). Making it happen: Keeping precarious workers’ experiences central during COVID-19. Industrial and Organizational Psychology: Perspectives on Science and Practice, 14, 189–193. https://doi.org/10.1017/iop.2021.36.
Martin, J. E., & Sinclair, R. R. (2007). A typology of the part-time workforce: Differences on job attitudes and turnover. Journal of Occupational and Organizational Psychology, 80, 301–319. https://doi.org/10.1348/096317906X113833.
Matthews, R. A., Pineault, L., & Hong, Y. H. (2022). Normalizing the use of single-item measures: Validation of the single-item compendium for organizational psychology. Journal of Business and Psychology, 37, 639–673. https://doi.org/10.1007/s10869-022-09816-0.
Menard, S. (2001). Applied logistic regression analysis (2nd ed.). Sage.
Michel, J. S., O’Neill, S. K., Hartman, P., & Lorys, A. (2018). Amazon’s mechanical Turk as a viable source for organizational and occupational health research. Occupational Health Science, 2, 83–98. https://doi.org/10.1007/s41542-017-0009-x.
Munyon, T. P., Carnes, A. M., Lyons, L. M., & Zettler, I. (2020). All about the money? Exploring antecedents and consequences for a brief measure of perceived financial security. Journal of Occupational Health Psychology, 25, 159–175. https://doi.org/10.1037/ocp0000162.
New York City Department of Consumer and Worker Protection (2022). A minimum pay rate for app-based restaurant delivery workers in NYC. https://www.nyc.gov/assets/dca/downloads/pdf/workers/Delivery-Worker-Study-November-2022.pdf.
Newman, D. A. (2003). Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques. Organizational Research Methods, 6, 328–362. https://doi.org/10.1177/1094428103254673.
Ollier-Malaterre, A., Jacobs, J. A., & Rothbard, N. P. (2019). Technology, work, and family: Digital cultural capital and boundary management. Annual Review of Sociology, 45, 425–447. https://doi.org/10.1146/annurev-soc-073018-022433.
Phetmisy, C. N., Bardwell, T., Davenport, M. K., & King, D. D. (2023). April 19–22). A meta-analytic investigation of financial stress and employee job experiences [Conference presentation]. 38th Annual Conference of the Society of Industrial-Organizational Psychology, Boston, MA, United States.
Ravenelle, A. J. (2019a). Hustle and gig: Struggling and surviving in the sharing economy. University of California Press.
Ravenelle, A. J. (2019b). We’re not Uber: Control, autonomy, and entrepreneurship in the gig economy. Journal of Managerial Psychology, 34, 269–285. https://doi.org/10.1108/JMP-06-2018-0256.
Richter, A., Näswall, K., Bernhard-Oettel, C., & Sverke, M. (2014). Job insecurity and well-being: The moderating role of job dependence. European Journal of Work and Organizational Psychology, 23, 816–829. https://doi.org/10.1080/1359432X.2013.805881.
Rosenblat, A. (2018). Uberland. University of California Press.
Ross, J., Irani, L. C., Silberman, M. S., Zaldivar, A., & Tomlinson, B. (2010). Who are the crowdworkers? Shifting demographics in Mechanical Turk. In CHI ‘10 Extended Abstracts on Human Factors in Computing Systems (pp. 2863–2872). Association for Computing Machinery (ACM). https://doi.org/10.1145/1753846.1753873.
Said, C. (2021, January 12). Lawsuit seeks to overturn Prop. 22, measure that keeps gig workers from becoming employees. San Francisco Chronicle. https://www.sfchronicle.com/business/article/Lawsuit-seeks-to-overturn-Prop-22-measure-that-15864699.php.
Scheiber, N. (2020, Jul 20). When scholars collaborate with tech companies, how reliable are the findings? The New York Times. https://www.nytimes.com/2020/07/12/business/economy/uber-lyft-drivers-wages.html.
Schor, J. B. (2020). After the gig: How the sharing economy got hijacked and how to win it back. University of California Press.
Schor, J. B., Attwood-Charles, W., Cansoy, M., Ladegaard, I., & Wengronowitz, R. (2020). Dependence and precarity in the platform economy. Theory and Society, 49, 833–861. https://doi.org/10.1007/s11186-020-09408-y.
Schwarz, N. (1999). Self-reports: How the questions shape the answers. American Psychologist, 54, 93–105. https://doi.org/10.1037/0003-066X.54.2.93.
Sinclair, R. R., & Cheung, J. H. (2016). Money matters: Recommendations for financial stress research in occupational health psychology. Stress and Health, 32, 181–193. https://doi.org/10.1002/smi.2688.
Sinclair, R. R., Martin, J. E., & Michel, R. P. (1999). Full-time and part-time subgroup differences in job attitudes and demographic characteristics. Journal of Vocational Behavior, 55, 337–357. https://doi.org/10.1006/jvbe.1999.1686.
Sinclair, R. R., Sears, L. E., Probst, T., & Zajack, M. (2010). A multilevel model of economic stress and employee well-being. Contemporary Occupational Health Psychology: Global Perspectives on Research and Practice, 1, 1–20. https://doi.org/10.1002/9780470661550.
Sinclair, R. R., Probst, T., Hammer, L. B., & Schaffer, M. M. (2013). Low income families and occupational health: Implications of economic stress for work-family conflict research and practice. In A. G. Antoniou, & C. L. Cooper (Eds.), The psychology of the recession on the workplace (pp. 308–323). Edward Elgar Publishing. https://doi.org/10.4337/9780857933843.00030.
Smith, A. (2016). Gig work, online selling and home sharing. Pew Research Center. https://www.pewresearch.org/internet/2016/11/17/gig-work-online-selling-and-home-sharing/.
Soper, S. (2020, Sept 1). Amazon drivers are hanging smartphones in trees to get more work. Bloomberg. https://www.bloomberg.com/news/articles/2020-09-01/amazon-drivers-are-hanging-smartphones-in-trees-to-get-more-work.
Spector, P. E. (2017). The lost art of discovery: The case for inductive methods in occupational health science and the broader organizational sciences. Occupational Health Science, 1, 11–27. https://doi.org/10.1007/s41542-017-0001-5.
Spector, P. E., Dwyer, D. J., & Jex, S. M. (1988). Relation of job stressors to affective, health, and performance outcomes: A comparison of multiple data sources. Journal of Applied Psychology, 73, 11–19. https://doi.org/10.1037/0021-9010.73.1.11.
Spector, P. E., Van Katwyk, P. T., Brannick, M. T., & Chen, P. Y. (1997). When two factors don’t reflect two constructs: How item characteristics can produce artifactual factors. Journal of Management, 23, 659–677. https://doi.org/10.1016/S0149-2063(97)90020-9.
Sprague, R. (2015). Worker (mis)classification in the sharing economy: Trying to fit square pegs into round holes. ABA Journal of Labor and Employment Law, 31, 53–76. https://www.jstor.org/stable/26410781.
Spreitzer, G. M., Cameron, L., & Garrett, L. (2017). Alternative work arrangements: Two images of the new world of work. Annual Review of Organizational Psychology and Organizational Behavior, 4, 473–499. https://doi.org/10.1146/annurev-orgpsych-032516-113332.
Sundararajan, A. (2016). The sharing economy: The end of employment and the rise of crowd-based Capitalism. The MIT Press.
Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Allyn and Bacon.
Thebault-Spieker, J., Kluver, D., Klein, M., Halfaker, A., Research, W., Hecht, B., Terveen, L., & Konstan, J. (2017). Simulation experiments on (the absence of) ratings bias in reputation systems. Proceedings of the ACM on Human-Computer Interaction, 1, 101. https://doi.org/10.1145/3134736.
Tonidandel, S., & LeBreton, J. M. (2011). Relative importance analysis: A useful supplement to regression analysis. Journal of Business and Psychology, 26, 1–9. https://doi.org/10.1007/s10869-010-9204-3.
Tran, M., & Sokas, R. K. (2017). The gig economy and contingent work: An occupational health assessment. Journal of Occupational and Environmental Medicine, 59, e63–e66. https://doi.org/10.1097/JOM.0000000000000977.
Vallas, S., & Schor, J. B. (2020). What do platforms do? Understanding the gig economy. Annual Review of Sociology, 46, 273–294. https://doi.org/10.1146/annurev-soc-121919-054857.
Vanhove, A. J., Miller, A. D., & Harms, P. D. (2021). Understanding subpopulations on mechanical Turk: A comparison of three employment status subgroups. Journal of Personnel Psychology, 20, 176–186. https://doi.org/10.1027/1866-5888/a000281.
Voydanoff, P. (1990). Economic distress and family relations: A review of the eighties. Journal of Marriage and the Family, 52, 1099–1115. https://doi.org/10.2307/353321.
Watson, G. P., Kistler, L. D., Graham, B. A., & Sinclair, R. R. (2021). Looking at the gig picture: Defining gig work and explaining profile differences in gig workers’ job demands and resources. Group & Organization Management, 46, 237–361. https://doi.org/10.1177/1059601121996548.
Wong, S. I., Kost, D., & Fieseler, C. (2018). Meaningful work and subjective well-being: The role of job-career (in)congruence in the gig economy. Academy of Management Proceedings, 2018, 10572. https://doi.org/10.5465/AMBPP.2018.10572abstract.
Woo, S. E., O’Boyle, E. H., & Spector, P. E. (2017). Best practices in developing, conducting, and evaluating inductive research. Human Resource Management Review, 27, 255–264. https://doi.org/10.1016/j.hrmr.2016.08.004.
Wood, A. J., Graham, M., Lehdonvirta, V., & Hjorth, I. (2019). Good gig, bad gig: Autonomy and algorithmic control in the global gig economy. Work Employment and Society, 33, 56–75. https://doi.org/10.1177/0950017018785616.
Funding
This work was generously funded by Gettysburg College. The author has no relevant financial or non-financial interests to disclose.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethics Approval and Consent to Participate
Both Study 1 and Study 2 received ethical approval by the Institutional Review Board of Gettysburg College. Informed consent was obtained from all participants in both studies. The author completed all research and manuscript preparation solo.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Brawley Newlin, A. Methodological and Demographic Variation in Estimates of Economic Dependence Across Two Types of Gig Work. Occup Health Sci 8, 161–190 (2024). https://doi.org/10.1007/s41542-023-00168-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41542-023-00168-6