شناسایی پیامدهای اقتصاد گیگ در بستر پلتفرمها با رویکرد فراترکیب با تاکید بر چالش‌های منابع انسانی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه مدیریت، دانشکده مدیریت و علوم مالی، دانشگاه خاتم، تهران، ایران.

2 گروه مدیریت .دانشکده مدیریت و علوم مالی.دانشگاه خاتم.تهران.ایران

10.22080/shrm.2025.5652

چکیده

 
در چند سال اخیر رشد چشم‌گیر در عرصه فناوری و دیجیتال موجب پدید آمدن شکل تازه‌ای از مشاغل در جهان شده است که در حال حاضر به شکل یک اقتصاد تأثیرگذار درآمده و تحت عنوان " اقتصاد‌ گیگ " شناخته می‌شود. هدف اصلی پژوهش حاضر، شناسایی پیامدهای اقتصاد گیگ در بستر پلتفرم‌ها با رویکرد فراترکیب با تاکید بر چالش‌های منابع انسانی می‌باشد. این پژوهش از نظر هدف، توسعه‌ای؛ از لحاظ ماهیت و سبک تحلیل مؤلفه‌ها، جزء پژوهش‌های کیفی و براساس جمع‌آوری داده‌ها، اسنادی است. از منظر روش انجام پژوهش، تحلیلی- توصیفی است و مؤلفه‌های پژوهش با استفاده از روش کیفی فراترکیب هفت مرحله‌ای ساندلوسکی و باروسو جمع‌آوری و تحلیل شده‌اند. به‌منظور شناسایی پیامدهای اقتصاد گیگ پژوهشگران به جستجوی سیستماتیک پژوهش‌های انجام شده مربوط به این پیامدها در 4 پایگاه‌ علمی ساینس دایرکت، امرالد، وایلی، سیج و همچنین پایگاه استنادی اسکوپوس بین سال‌های 2010 تا 2024 پرداختند. در بررسی‌های اولیه، تعداد 117 منبع یافت شد که پس از طی مراحل غربال‌گری و اعتبارسنجی و بهره‌گیری از ابزار CASP در نهایت 21 مقاله مورد تجزیه ‌و ‌تحلیل قرار گرفت و با استفاده از روش کدگذاری، پیامدهای اقتصاد گیگ شناسایی و با استفاده از نرم‌افزار مکس کیودا ترسیم گردید. برای بررسی کیفیت یا پایایی شاخص‌ها از ضریب کاپا در نرم‌افزار SPSS استفاده شده است که در پژوهش حاضر برابر با 80/0 است که نشان‌دهنده پایایی مناسب شاخص‌های این پژوهش می‌باشد. در مجموع 2 پیامد اصلی شامل پیامدهای مثبت و منفی اقتصاد گیگ و 34 پیامد فرعی اقتصاد گیگ شناسایی شده‌ است.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying the Consequences of the Gig Economy in the Context of Platforms with the Meta-Synthesis Approach, Emphasizing the Challenges of Human Resources

نویسندگان [English]

  • Fatemeh Karimi Jafari 1
  • zahra Abbaszadeh Sourami 2
1 Assistant Professor, Department of Management, Faculty of Management and Finance, Khatam University, Tehran, Iran.
2 Department of Management, Faculty of Management and Financial Sciences, Khatam University, Tehran, Iran
چکیده [English]

The main purpose of the current research is to identify the consequences of the gig economy in the context of platforms with the Meta-Synthesis approach, emphasizing the challenges of human resources. This research is developmental in terms of purpose. In terms of the nature of the data and the style of data analysis, it is part of qualitative research. And based on data collection, it is documented. From the point of view of the research method, it is analytical-descriptive, and the data of the research were collected and analyzed using the seven-stage meta- Synthesis qualitative method of Sandelowski and Barroso. In order to identify the consequences of the gig economy, researchers systematically search for researches related to these consequences in 4 scientific databases: Science Direct, Emerald, Wiley, Sage, as well as the Scopus citation database between 2010 and 2024, In the initial investigations, 117 sources were found, and after screening and validation and using the CASP tool, finally 21 articles were analyzed and using the coding method, the consequences of gig economy were identified and using the MAXQDA software was drawn. To check the quality or reliability of the indicators, the Cohen's kappa coefficient in SPSS software was used, which in the current study is equal to 0.80, which indicates the appropriate reliability of the indicators of this research. In total, 2 main consequences including positive and negative consequences of the gig economy and 34 sub-consequences of the gig economy have been identified.

کلیدواژه‌ها [English]

  • Gig Economy
  • Platform
  • work changes
  • consequences
  • Meta-Synthesis Approach
AC, K., & P, P. (2023). Changing Contours of the Employment Landscape: A Study on Gig Work Options for the Platform Workforce of Kerala. SEDME (Small Enterprises Development, Management & Extension Journal), 50(4), 384–398. DOI: 
10.1177/09708464231209452.
Ai, W., Chen, Y., Mei, Q., Ye, J., & Zhang, L. (2023). Putting teams into the gig economy: A field experiment at a ride-sharing platform. Management Science, 69(9), 5336–5353. DOI: 10.1287/mnsc.2022.4624.
Aloisi, A. (2015). Commoditized workers: Case study research on labor law issues aris-ing from a set of on-demand/gig econ-omy platforms. Comp. Lab. L. & Pol’y J., 37, 653. DOI: 10.2139/ssrn.2637485.
Angrave, D., Charlwood, A., Kirkpatrick, I., Lawrence, M., & Stuart, M. (2016). HR and analytics: why HR is set to fail the big data challenge. Human Resource Management Journal, 26(1), 1–11. DOI: 
10.1111/1748-8583.12090.
Cameron, L. D. (2024). The Making of the “Good Bad” Job: How Algorithmic Management Manufactures Consent Through Constant and Confined Choices. Administrative Science Quar-terly, 69(2), 458–514. DOI: 10.1177/00018392241236163.
Chen, J., Luo, J., Hu, W., & Ma, J. (2023). Fit into work! From formalizing govern-ance of gig platform ecosystems to helping gig workers craft their platform work. Decision Support Systems, 174, 114016. DOI: 
10.1016/j.dss.2023.114016.
Choudhary, V., & Shireshi, S. S. (2022). Ana-lysing the gig economy in India and exploring various effective regulatory methods to improve the plight of the workers. Journal of Asian and African Studies, 57(7), 1343–1356. DOI: 
10.1177/00219096221082581.
Collier, R. B., Dubal, V., & Carter, C. (2017). Labor platforms and gig work: the fail-ure to regulate. DOI: 
10.2139/ssrn.3039742.
Corten, R., Kas, J., Teubner, T., & Arets, M. (2023). The role of contextual and con-tentual signals for online trust: Evi-dence from a crowd work experiment. Electronic Markets, 33(1), 41. DOI: 
10.1007/s12525-023-00655-2.
Crawford, K. (2021). The atlas of AI: Power, politics, and the planetary costs of artifi-cial intelligence. Yale University Press. DOI: 
10.56315/pscf3-22crawford.
Davidson, A., Gleim, M. R., Johnson, C. M., & Stevens, J. L. (2023). Gig worker typol-ogy and research agenda: advancing re-search for frontline service providers. Journal of Service Theory and Practice, 33(5), 647–670. DOI: 10.1108/JSTP-08-2022-0188.
De Stefano, V. (2016). The rise of the" just-in time workforce": on demand work, crowdwork, and labor protection in the" gig economy". Comparative Labor Law and Policy Journal, 37(3), 461–471. 
http://dx.doi.org/10.2139/ssrn.2682602.
Dey, C., Ture, R. S., & Ravi, S. (2022). Emerg-ing world of gig economy: Promises and challenges in the Indian context. NHRD Network Journal, 15(1), 71–82. DOI: 10.1177/26314541211064717.
Doshi, B. M., & Tikyani, H. (2020). A theoreti-cal integration of gig economy: Ad-vancing opportunity, challenges and growth. International Journal of Man-agement (IJM), 11(12), 3013-19.
Duggan, J., Sherman, U., Carbery, R., & McDonnell, A. (2022). Boundaryless careers and algorithmic constraints in the gig economy. The International Journal of Human Resource Manage-ment, 33(22), 4468–4498. DOI: 
10.1080/09585192.2021.1953565.
Erwin, E. J., Brotherson, M. J., & Summers, J. A. (2011). Understanding qualitative metasynthesis: Issues and opportunities in early childhood intervention re-search. Journal of Early Intervention, 33(3), 186–200. DOI: 10.1177/1053815111425493.
Findlay, P., Kalleberg, A. L., & Warhurst, C. (2013). The challenge of job quality. Human Relations, 66(4), 441–451. DOI: 10.1177/0018726713481070.
Friedman, G. (2014). Workers without employ-ers: shadow corporations and the rise of the gig economy. Review of Keynesian Economics, 2(2), 171–188. DOI: 10.4337/roke.2014.02.03.
Ganraj, M., & SAWANT, S. (2022). PER-SPECTIVE OF GIG OUTLOOK: PROBLEMS AND PROSPECTS. 
ISSN: 2395-0072.
Giousmpasoglou, C., Ladkin, A., & Marinakou, E. (2024). Worker exploitation in the gig economy: the case of dark kitchens. Journal of Hospitality and Tourism In-sights, 7(1), 414–435. DOI: 10.1108/JHTI-10-2022-0477.
Gleim, M. R., Johnson, C. M., & Lawson, S. J. (2019). Sharers and sellers: A multi-group examination of gig economy workers’ perceptions. Journal of Busi-ness Research, 98, 142–152. DOI: 
10.1016/j.jbusres.2019.01.041.
Gussek, L., Grabbe, A., & Wiesche, M. (2023). Challenges of IT freelancers on digital labor platforms: A topic model ap-proach. Electronic Markets, 33(1), 55. DOI: 10.1007/s12525-023-00675-y.
Halliday, D. (2021). On the (mis) classification of paid labor: When should gig workers have employee status? Politics, Philos-ophy & Economics, 20(3), 229–250. OI: 
10.1177/1470594X211015467.
Harms, P. D., White, J. V, & Fezzey, T. N. A. (2024). Dark clouds on the horizon: Dark personality traits and the frontiers of the entrepreneurial economy. Jour-nal of Business Research, 171, 114364. DOI: 
10.1016/j.jbusres.2023.114364.
Hassani, H. (2021). Online Platforms and Shar-ing Economy: Promises and Challenges for Gig Workers. Global Media Journal-Persian Edition, 16(1), 53–76. (in per-sian). 
10.22059/gmj.2022.335644.1241.
Hornuf, L., & Vrankar, D. (2022). Hourly wag-es in crowdworking: A meta-analysis. Business & Information Systems Engi-neering, 64(5), 553–573. DOI: 
10.1007/s12599-022-00769-5.
Huang, N., Burtch, G., Hong, Y., & Pavlou, P. A. (2020). Unemployment and worker participation in the gig economy: Evi-dence from an online labor market. In-formation Systems Research, 31(2), 431–448. DOI: 
10.1287/ISRE.2019.0896.
James, A. (2024). Platform work‐lives in the gig economy: Recentering work–family re-search. Gender, Work & Organization, 31(2), 513–534. https://doi.org/10.1111/gwao.13087.
Jarrahi, M. H., & Sutherland, W. (2019). Algo-rithmic management and algorithmic competencies: Understanding and ap-propriating algorithms in gig work. In-formation in Contemporary Society: 14th International Conference, IConference 2019, Washington, DC, USA, March 31–April 3, 2019, Proceedings 14, 578–589. DOI: 10.1007/978-3-030-15742-5_55.
Kaine, S., & Josserand, E. (2019). The organisa-tion and experience of work in the gig economy. Journal of Industrial Rela-tions, 61(4), 479–501. DOI: 10.1177/0022185619865480.
Kässi, O., & Lehdonvirta, V. (2018). Online labour index: Measuring the online gig economy for policy and research. Tech-nological Forecasting and Social Change, 137, 241–248. DOI: 
10.1016/j.techfore.2018.07.056.
Kässi, O., Lehdonvirta, V., & Stephany, F. (2021). How many online workers are there in the world? A data-driven as-sessment. Open Research Europe, 1. DOI: 
10.12688/openreseurope.13639.4.
Kirven, A. (2018). Whose gig is it anyway: technological change, workplace con-trol and supervision, and workers’ rights in the gig economy. U. Colo. L. Rev., 89, 249. 
https://scholar.law.colorado.edu/lawreview/vol89/iss1/6.
Koutsimpogiorgos, N., Van Slageren, J., Herrmann, A. M., & Frenken, K. (2020). Conceptualizing the gig econ-omy and its regulatory problems. Policy & Internet, 12(4), 525–545. DOI: 10.1002/poi3.237.
Kuhn, K. M., Meijerink, J., & Keegan, A. (2021). Human resource management and the gig economy: Challenges and opportunities at the intersection be-tween organizational HR decision-makers and digital labor platforms. Re-search in Personnel and Human Re-sources Management, 39, 1–46. DOI: 10.1108/S0742-730120210000039001.
Manian, A., & ronaghi,  mohammad hossein. (2015). A Comprehensive Framework for E-marketing Implementation by Meta-Synthesis Method. Journal of Business Management, 7(4), 901–920. 
https://doi.org/10.22059/jibm.2015.57097. (in persian). 
https://doi.org/10.22059/jibm.2015.57097.
Manyika, J., Lund, S., Robinson, K., Valentino, J., & Dobbs, R. (2015). A labor market that works: Connecting talent with op-portunity in the digital age. 
http://www.mckinsey.com/global-themes/employment-and-growth/connecting-talent-with-opportunity-in-the-digital-age.
McDonnell, A., Carbery, R., Burgess, J., & Sherman, U. (2021). Technologically mediated human resource management in the gig economy. The InTernaTIonal Journal of Human Resource Manage-menT, 32(19), 3995–4015. DOI: 
10.1080/09585192.2021.1986109.
Mehta, B. S. (2023). Changing nature of work and the gig economy: Theory and de-bate. FIIB Business Review, 12(3), 227–237. DOI: 
10.1177/2319714520968294.
Meijerink, J., Boons, M., Keegan, A., & Marler, J. (2021). Algorithmic human resource management: Synthesizing develop-ments and cross-disciplinary insights on digital HRM. In The International Jour-nal of Human Resource Management (Vol. 32, Issue 12, pp. 2545–2562). Taylor & Francis. DOI: 
10.1080/09585192.2021.1925326.
Minbaeva, D. (2021). Disrupted HR? Human Resource Management Review, 31(4), 100820. 
https://doi.org/10.1016/j.hrmr.2020.100820
Moore, M. T. (2019). The gig economy: a hypo-thetical contract analysis. Legal Studies, 39(4), 579–597. DOI: 10.1017/lst.2019.4.
Moradi, M., & Miralmasi, A. (2016). Types of coding in qualitative research. (in per-sian). 
Mousa, M., & Chaouali, W. (2023). Job craft-ing, meaningfulness and affective commitment by gig workers towards crowdsourcing platforms. Personnel Re-view, 52(8), 2070–2084. DOI: 10.1108/PR-07-2021-0495.
Newlands, G. (2021). Algorithmic surveillance in the gig economy: The organization of work through Lefebvrian conceived space. Organization Studies, 42(5), 719–737. OI: 10.1177/0170840620937900.
Newlands, G., & Lutz, C. (2024). Mapping the prestige and social value of occupations in the digital economy. Journal of Busi-ness Research, 180, 114716. DOI: 
10.1016/j.jbusres.2024.114716.
Perrig, L. (2023). Confronting algorithmic management using subject access re-quests: Insights using the case of food deliveries. The Economic and Labour Relations Review, 34(4), 720–732. DOI: 10.1017/elr.2023.55.
Petriglieri, G., Ashford, S. J., & Wrzesniewski, A. (2019). Agony and ecstasy in the gig economy: Cultivating holding envi-ronments for precarious and personal-ized work identities. Administrative Sci-ence Quarterly, 64(1), 124–170. DOI: 
10.1177/0001839218759646.
Rosenblat, A., & Stark, L. (2016). Algorithmic labor and information asymmetries: A case study of Uber’s drivers. Interna-tional Journal of Communication, 10, 27. DOI: 
10.2139/ssrn.2686227.
Schou, P. K., & Bucher, E. (2023). Divided we fall: The breakdown of gig worker soli-darity in online communities. New Technology, Work and Employment, 38(3), 472–492. DOI: 10.1111/ntwe.12260.
Scully-Russ, E., & Torraco, R. (2020). The changing nature and organization of work: An integrative review of the lit-erature. Human Resource Development Review, 19(1), 66–93. DOI: 10.1177/1534484319886394.
Shanahan, G., & Smith, M. (2023). Fair’s fair: Psychological contracts and power in platform work. In Technologically Me-diated Human Resource Management (pp. 84–115). Routledge. DOI: 10.1080/09585192.2020.1867615.
Snyder, B. H. (2016). The disrupted workplace: Time and the moral order of flexible capitalism. Oxford University Press. 
https://doi.org/10.1093/acprof:oso/9780190203498.001.0001.
Stewart, A., & Stanford, J. (2017). Regulating work in the gig economy: What are the options? The Economic and Labour Re-lations Review, 28(3), 420–437. DOI: 
10.1177/1035304617722461.
Torpey, E., & Hogan, A. (2016). Working in a gig economy. Career Outlook.
Uchiyama, Y., Furuoka, F., Akhir, M. N. M., & MN, M. (2022). Gig Workers, Social Protection and Labour Market Inequali-ty: Lessons from Malaysia. Jurnal Ekonomi Malaysia, 56(3), 165–184. DOI: 10.17576/JEM-2022-5603-09.
Vyas, N. (2021). Gender inequality-now availa-ble on digital platform’: an interplay be-tween gender equality and the gig econ-omy in the European Union. European Labour Law Journal, 12 (1), 37-51. DOI: 
10.1177/2031952520953856.
Wood, A. J., Graham, M., Lehdonvirta, V., & Hjorth, I. (2019). Good gig, bad gig: au-tonomy and algorithmic control in the global gig economy. Work, Employment and Society, 33(1), 56–75. DOI: 10.1177/0950017018785616.
Wood, A. J., Lehdonvirta, V., & Graham, M. (2018). Workers of the Internet unite? Online freelancer organisation among remote gig economy workers in six Asian and African countries. New Technology, Work and Employment, 33(2), 95–112. DOI: 10.1111/ntwe.12112.
Woodcock, J. gig economy, & Graham, M. (2019). The Gig Economy. A Critical Introduction. Cambridge: Polity. ISBN-13: 978-1-5095-3637-5.
Xu, G., Lin, H., Yang, S., & Du, Y. (2018). The challenge of gig economy to enter-prise human resource management. 2018 2nd International Conference on Education Innovation and Social Science (ICEISS 2018), 404–407. DOI: 
10.2991/iceiss-18.2018.98.
Yaraghi, N., & Ravi, S. (2017). The current and future state of the sharing economy. Available at SSRN 3041207. DOI: 
10.2139/ssrn.3041207.
Zhou, Y. (2022). Trapped in the platform: Mi-gration and precarity in China’s plat-form-based gig economy. Environment and Planning A: Economy and Space, 0308518X221119196. DOI: 10.1177/0308518X221119196.
Zhu, G., Huang, J., Lu, J., Luo, Y., & Zhu, T. (2024). Gig to the left, algorithms to the right: A case study of the dark sides in the gig economy. Technological Forecasting and Social Change, 199, 123018. DOI: 
10.1016/j.techfore.2023.123018.
Zysman, J., & Kenney, M. (2015). Where will work come from in the era of the cloud and big data. Berkeley Roundtable on the International Economy Working Pa-per.