ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI MASYARAKAT MENJADI GIG WORKER
DOI:
https://doi.org/10.21776/jdess.2023.02.4.06Keywords:
Gig Worker, Gig Economy, GigAbstract
The development of the gig economy sector in recent years has opened up new possibilities for flexible types of jobs, both in terms of time and location. This potential is also present in Malang City, and there is a need for a better understanding of the factors that may influence people's decisions to become gig workers. The objective of this research is to examine the influence of several factors such as technological skills and internet access, job opportunities, time flexibility, income security, financial benefits, and lifestyle on people's decisions to become gig workers. This study found that the variables examined have a positive relationship with people's decisions to become gig workers in Malang City.
References
Abraham, K. G., Haltiwanger, J. C., Sandusky, K., & Spletzer, J. R. (2018). Nber Working Paper Series Measuring the Gig Economy: Current Knowledge and Open Issues. National Bureau of Economic Research.
Agarwal, R., & Karahanna, E. (2000). Time Flies When You’re Having Fun: Cognitive Absorption and Beliefs about Information. In Source: MIS Quarterly (Vol. 24, Issue 4).
Ai Group. (2016). The Emergence of the Gig Economy Education & Training Policy Team 2. https://cdn.aigroup.com.au/-Reports/2016/Gig_Economy_August_2016.pdf
Apouey, B., Roulet, A., Solal, I., & Stabile, M. (2020). Gig Workers during the COVID-19 Crisis in France: Financial Precarity and Mental Well-Being. Journal of Urban Health, 97(6), 776–795. https://¬doi.org/10.1007/s11524-020-00480-4
Aristi, N. M., & Pratama, A. R. (2021). Peran Freelance Marketplace dan Media Sosial dalam Online Gig Economy Jasa Profesional. Techno.Com, 20(1). https://-doi.org/10.33633/tc.v20i1.4261
Arne L. Kalleberg and Michael Dunn. (2016). Good Jobs, Bad Jobs in the Gig Economy. Job Quality.
Badan Pusat Statistik Kota Malang. (2023). Pengangguran di Kota Malang, Jawa Timur, dan Indonesia Menurut Pendidik¬an (Jiwa), 2020-2022.
Bargain, O. (2014). The Informal Sector Wage Gap: New Evidence Using Quantile Estimations on Panel Data. http://www.¬jour¬nals.uchicago.edu/t-and-c
Beverly Yuen Thompson. (2018). Digital No¬mads: Employment in the Online Gig Economy.
Blau, F. D., & Kahn, L. M. (2016). The Gender Wage Gap: Extent, Trends, and Explanations. http://www.nber.org/¬pa¬pers¬¬/¬w21913
Bunjak, A., Černe, M., & Popovič, A. (2021). Absorbed in technology but digitally overloaded: Interplay effects on gig workers’ burnout and creativity. Infor¬mation and Management, 58(8). https://-doi.org/10.1016/j.im.2021.103533
D. G. Garson. (2016). Partial Least Square: Regression & Structural Equation Models. Statistical Publishing Associat¬es.
Daniels, K., & Grinstein-Weiss, M. (2018). The Impact of the Gig-Economy on Financial Hardship Among Low-Income Families. SSRN Electronic Journal. https://-doi.org/10.2139/ssrn.3293988
De Almeida, M. A., Correia, A., Schneider, D., & De Souza, J. M. (2021). COVID-19 as Opportunity to Test Digital Nomad Lifestyle. Proceedings of the 2021 IEEE 24th International Conference on Com¬puter Supported Cooperative Work in Design, CSCWD 2021, 1209–1214. https://doi.org/10.1109/CSCWD49262.2021.9437685
Direktorat Infrastruktur Ekonomi Kreatif, Deputi Bidang Pengembangan Destinasi dan Infrastruktur, & Kementrian Pari¬wisata dan Ekonomi Kreatif. (2017). Peni¬laian Mandiri Kota/Kabupaten Krea¬tif Indonesia (PMK3I) Kota Malang. Penilaian Mandiri Kota/¬Kabu¬paten Kreatif Indonesia (PMK3I).
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Mea¬sure¬ment Error. In Source: Journal of Marketing Research (Vol. 18, Issue 1).
Freelancers Union. (2018). Freelancing¬ina-mericareport-2018. https://www.free-lan¬cer¬sunion.org/about/freelancing-in-ame¬rica/
GoTo Gojek Tokopedia. (2023). GOTO Annual Report 2022.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.¬org/¬10.2753/MTP1069-6679190202
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. In European Business Review (Vol. 26, Issue 2, pp. 106–121). Emerald Group Publishing Ltd. https://-doi.org/10.1108/EBR-10-2013-0128
Heale, R., & Twycross, A. (2015). Validity and reliability in quantitative studies. In Evidence-Based Nursing (Vol. 18, Issue 3, pp. 66–67). BMJ Publishing Group. https://doi.org/10.1136/eb-2015-102129
Herrmann, A. M., Zaal, P. M., Chappin, M. M. H., Schemmann, B., & Lühmann, A. (2023). “We don’t need no (higher) education” - How the gig economy challenges the education-income para¬digm. Technological Forecasting and Social Change, 186. https://doi.org/-10.1016/j.techfore.2022.122136
Huang, N., Burtch, G., Hong, Y., & Pavlou, P. A. (2020). Unemployment and worker participation in the gig economy: Evidence from an online labor market. Information Systems Research, 31(2), 431–448. https://doi.org/10.1287/¬ISRE.-2019.0896
Kässi, O., & Lehdonvirta, V. (2018). Online labour index: Measuring the online gig economy for policy and research. Technological Forecasting and Social Change, 137. https://doi.org/10.¬1016/-j.techfore.2018.07.056
Koustas, D. K. (2019). What Do Big Data Tell Us about Why People Take Gig Economy Jobs? AEA Papers and Proceedings, 109, 367–371. https://doi.¬org¬/¬-10.1257/pandp.20191041
Koutsimpogiorgos, N., van Slageren, J., Herrmann, A. M., & Frenken, K. (2020). Conceptualizing the Gig Economy and Its Regulatory Problems. Policy and Internet, 12(4). https://doi.org/¬10.1002/¬poi3.237
Labib Fardany Faisal, A., Sucahyo, Y. G., Ruldeviyani, Y., & Gandhi, A. (2019). Discovering Indonesian digital workers in online gig economy platforms. 2019 International Conference on Information and Communications Technology, ICOIACT 2019. https://doi.org/¬10.11-09/¬ICOIACT46704.2019.8938543
Lehdonvirta, V. (2018). Flexibility in the gig economy: managing time on three online piecework platforms. New Technology, Work and Employment, 33(1), 13–29. https://doi.org/10.1111/ntwe.12102
Milkman, R., Elliott-Negri, L., Griesbach, K., & Reich, A. (2021). Gender, Class, and the Gig Economy: The Case of Platform-Based Food Delivery. Critical Sociology, 47(3), 357–372. https://¬doi.¬org/-10.1177/0896920520949631
Myhill, K., Richards, J., & Sang, K. (2021). Job quality, fair work and gig work: the lived experience of gig workers. International Journal of Human Resour¬ce Management, 32(19), 4110–4135. https://doi.org/10.1080/09585192.2020.1867612
Norlander, P., Jukic, N., Varma, A., & Nestorov, S. (2021). The effects of technological supervision on gig workers: organizational control and motivation of Uber, taxi, and limousine drivers. International Journal of Human Resource Management, 32(19), 4053–4077. https://doi.org/10.1080/¬095851¬92.¬-2020.1867614
Nurhayati-Wolff, H. (2021). Number of internet users in Indonesia 2017-2026. Statista. https://www.statista.com/¬statis¬tics/-254456/number-of-internet-users-in--indonesia/
Ozili, P. K. (2023). The acceptable R-square in empirical modelling for social science research.
Rigdon, E. E. (2014). Rethinking Partial Least Squares Path Modeling: Breaking Chains and Forging Ahead. Long Range Planning, 47(3), 161–167. https://doi.¬org¬/10.-1016/j.lrp.2014.02.003
Sanders, M., Zeng, J., Hellicar, M., & Fagg, K. (2015). The Power of Flexibility: A Key Enabler to Boost Gender Parity and Enga¬gement.
Sarstedt, M., Ringle, C. M., Henseler, J., & Hair, J. F. (2014). On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012). Long Range Planning, 47(3), 154–160. https://doi.org/¬10.1016/j.lrp.-2014.02.007
Sinchaisri, P., Allon, G., & Cohen, M. (2019). The Impact of Behavioral and Economic Drivers on Gig Economy Workers. Academy of Management Proceedings, 2019(1). https://doi.org/10.5465/¬am¬bp¬p¬.¬¬-2019.287
Streukens, S., & Leroi-Werelds, S. (2016). Bootstrapping and PLS-SEM: A step-by-step guide to get more out of your bootstrap results. European Manage-ment Journal, 34(6), 618–632. https://¬doi.-org/10.1016/j.emj.2016.06.003
Taniguchi, K., & Tuwo, A. (2014). New Evidence on the Gender Wage Gap in Indonesia. https://ssrn.¬com/abstract-=25¬1¬2¬096
Umar, M., Xu, Y., & Mirza, S. S. (2021). The impact of Covid-19 on Gig economy. Economic Research-Ekonomska Istrazi¬vanja , 34(1), 2284–2296. https://doi.¬org¬/10.-1080/1331677X.2020.1862688
Wheelahan, L., & Moodie, G. (2022). Gig qualifications for the gig economy: micro-credentials and the ‘hungry mile.’ Higher Education, 83(6), 1279–1295. https://doi.org/10.1007/s10734-021-00742-3
Wolcott, E. L. (2021). Employment inequality: Why do the low-skilled work less now? Journal of Monetary Economics, 118, 161–177. https://doi.org/10.1016/¬j.jmo¬n-eco.2020.09.004
Yang, G., Yao, S., & Dong, X. (2023). Digital economy and wage gap between high- and low-skilled workers. Digital Eco¬nomy and Sustainable Development, 1(1). https://doi.org/10.1007/s44265-02¬3¬-00009-y
Yorga Permana, M., Risfa Izzati, N., & Wahyudi Askar, M. (2023). Measuring the Gig Economy in Indonesia: Typology, characteristics, and distri¬bution. https://ssrn.com/abstract¬=4349¬9¬42
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