Digital technology and job quality: multidimensional insights from the labor market in East Java

Jatu Mawar Widhiarti Putri; Devanto Shasta Pratomo; Susilo Susilo

doi:10.22437/ppd.v14i1.45877

Authors

Jatu Mawar Widhiarti Putri Department of Economics, Faculty of Economics and Business, Universitas Brawijaya, Malang, Indonesia
Devanto Shasta Pratomo Department of Economics, Faculty of Economics and Business, Universitas Brawijaya, Malang, Indonesia
Susilo Susilo Department of Economics, Faculty of Economics and Business, Universitas Brawijaya, Malang, Indonesia

DOI:

https://doi.org/10.22437/ppd.v14i1.45877

Keywords:

Digital technology, Human capital, Job quality index, Labor market

Abstract

Digital technology transformation has a significant impact on labor market dynamics, both in terms of job quantity and quality. This study aims to analyze the extent to which digital technology influences workers’ job quality in East Java Province using a multidimensional approach. The measurement method used in this study is the Job Quality Index (JQI) developed by the World Bank, which assesses four dimensions of job quality: income, security, benefits, and job satisfaction. This study uses 2023 Sakernas data, comprising 39,425 observations. The analytical method employed is binary logistic regression. Robustness tests across various model specifications are conducted to ensure the stability of the results. The findings show that using digital technology increases the likelihood of achieving better job quality by up to 2.3 times compared to non-users. Other individual characteristics, such as education, training, gender, and age, also positively influence workers’ job quality. Conversely, participation in the Pre-Employment Card (Prakerja) Program and living in urban areas are found to have negative effects. This study highlights the importance of digital literacy and inclusion, as well as human capital investment through education and competency-based training aligned with labor market needs.

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References

Ahmed, N., & Nauriyal, D. (2024). Re-examining Wage Disparities Across Segments of the Indian Labor Market. Global Journal of Emerging Market Economies, 17, 244–264. https://doi.org/10.1177/09749101241300829

Andina, E. (2022). Peran Pemerintah Daerah dalam Implementasi Program Kartu Prakerja di Provinsi Jawa Barat. Aspirasi: Jurnal Masalah-Masalah Sosial. https://doi.org/10.46807/aspirasi.v13i1.2994

APJII. (2023). Survei Internet Indonesia 2023. Jakarta: Asosiasi Penyelenggara Jasa Internet Indonesia

Atasoy, H., & Pavlou, P. (2012). Firm-Level Evidence of the Effects of IT Use on Employment and Labor Wages. (NET Institute Working Paper No. 11-23). NET Institute. http://www.NETinst.org,

Bajwa, U., Gastaldo, D., Di Ruggiero, E., & Knorr, L. (2018). The health of workers in the global gig economy. Globalization and Health, 14, 124. https://doi.org/10.1186/s12992-018-0444-8

Becker, G. S. (1962). Investment in Human Capital: A Theoretical Analysis. Journal of Political Economy, 70(5), 9–49. http://www.jstor.org/stable/1829103

Berg, J., Green, F., Nurski, L., & Spencer, D. (2023). Risks to job quality from digital technologies: Are industrial relations in Europe ready for the challenge? European Journal of Industrial Relations, 29, 347–365. https://doi.org/10.1177/09596801231178904

BPS. (2023). Keadaan Angkatan Kerja di Indonesia 2023. Jakarta: BPS

BPS. (2024). Keadaan Ketenagakerjaan Indonesia Agustus 2024. Jakarta: BPS

Brummund, P., Mann, C., & Rodriguez-Castelan, C. (2018). Job-Quality-and-Poverty-in-Latin-America. Review of Development Economics, 22(4), 1682-1700. https://doi.org/10.1111/rode.12512

Cai, Y., Liu, S., & Zhang, X. (2024). The digital economy and job quality: Facilitator or inhibitor? Evidence from micro-individuals. Heliyon, 10(4), e26536. https://doi.org/10.1016/j.heliyon.2024.e26536

Christensen, L., D’Souza, R., Gatti, R., Valerio, A., Puerta, M., & Palacios, R. (2018). Framing the Future of Work. Jobs Notes; No. 6. World Bank. http://hdl.handle.net/10986/30589.

Crespo, N., Simoes, N., & Pinto, J. C. (2017). Determinant factors of job quality in Europe. Argumenta Oeconomica, 38(1), 15–40. https://doi.org/10.15611/aoe.2017.1.01

Dhyanasaridewi, I. G. A. D. D. (2020). Analisis Digitalisasi Industri, Penciptaan Kesempatan Kerja Dan Tingkat Pengangguran Terbuka Di Indonesia. Kompleksitas: Jurnal Ilmiah Manajemen, Organisasi, dan Bisnis, 9(1), 21-29. https://ejurnal.swadharma.ac.id/index.php/kompleksitas/article/view/18/18

Erumban, A. A. (2024). Informality and aggregate labor productivity growth: Does ICT moderate the relationship? Telecommunications Policy, 48(1), 102681. https://doi.org/10.1016/j.telpol.2023.102681

Fleischhauer, K.-J. (2007). A review of human capital theory: Microeconomics (University of St. Gallen, Department of Economics Discussion Paper No. 2007-01). https://doi.org/10.2139/ssrn.957993

Fossen, F. M., & Sorgner, A. (2018). The effects of digitalization on employment and entrepreneurship. Paper presented at the IZA MacroEcon Conference 2018. https://conference.iza.org/conference_files/MacroEcon_2018/sorgner_a21493.pdf

Gerber, C. (2022). Gender and precarity in platform work: Old inequalities in the new world of work. New Technology, Work and Employment, 37, 206–230. https://doi.org/10.1111/ntwe.12233

Ghodsi, M., Stehrer, R., & Barišić, A. (2024). Assessing the Impact of New Technologies on Wages and Labour Income Shares.Technological Forecasting and Social Change, 209, 123782. https://doi.org/10.1016/j.techfore.2024.123782

Heeks, R. (2017). Decent work and the digital gig economy: A developing country perspective on employment impacts and standards in online outsourcing, crowdwork, etc. (Development Informatics Working Paper No. 71). https://doi.org/10.2139/ssrn.3431033

Hovhannisyan, S., Montalva, V., Stamm, K., & Rodríguez Castelán, C. (2024, December 11). New insights for assessing and improving job quality in developing countries. World Bank Blogs. https://blogs.worldbank.org/en/developmenttalk/new-insights-for-assessing-and-improving-job-quality-in-developi

Hu, B., Shao, J., & Palta, M. (2006). Pseudo-R 2 In Logistic Regression Model. Statistica Sinica, 16(3), 847-860. https://www3.stat.sinica.edu.tw/statistica/oldpdf/a16n39.pdf

ILO. (2013). Decent work indicators: Guidelines for producers and users of statistical and legal framework indicators (2nd ed.). Geneva: International Labour Organization. https://www.ilo.org/sites/default/files/wcmsp5/groups/public/@dgreports/@integration/documents/publication/wcms_229374.pdf

Luptáčik, M., & Nežinský, E. (2026). Digitalization and productivity: production frontier approach. Applied Economics, 1–17. https://doi.org/10.1080/00036846.2026.2646316

Maier, C., Thatcher, J., Grover, V., & Dwivedi, Y. (2023). Cross-sectional research: A critical perspective, use cases, and recommendations for IS research. Int. J. Inf. Manag., 70, 102625. https://doi.org/10.1016/j.ijinfomgt.2023.102625

Mehta, B., & Awasthi, I. (2022). Dynamics of Urban Labour Market and Informality. The Indian Journal of Labour Economics, 65, 19–37. https://doi.org/10.1007/s41027-022-00354-0

Miho, A., Borowiecki, M., & Høj, J. (2023). Digitalisation and the labour market: Worker-level evidence from Slovenia (OECD Economics Department Working Papers No. 1767). OECD Publishing. https://doi.org/10.1787/d2bb40db-en

Mittlböck, M., & Schemper, M. (1996). Explained variation for logistic regression. Statistics in Medicine, 15 19, 1987–1997. https://doi.org/10.1002/(sici)1097-0258(19961015)15:19<1987::aid-sim318>3.0.co;2-9

Nguyen, P., Putra, F., Considine, M., & Sanusi, A. (2023). Activation through welfare conditionality and marketisation in active labour market policies: Evidence from Indonesia. Australian Journal of Public Administration, 82, 488–506. https://doi.org/10.1111/1467-8500.12602

Ningsih, S. R. (2024). Pengaruh Teknologi Terhadap Produktivitas Tenaga Kerja di Indonesia. Benefit: Journal of Bussiness, Economics, and Finance, 2(1), 1–9. https://doi.org/10.37985/benefit.v2i1.341

Ozili, P. K. (2022). The acceptable R-square in empirical modelling for social science research (Working paper). https://doi.org/10.2139/ssrn.4128165

Pandey, D. (2024). Impact of Digitalization on Employment Pattern in India. International Journal For Multidisciplinary Research, 6(1), 1-12 https://doi.org/10.36948/ijfmr.2024.v06i01.14396

Patoppoi, B. (2022, May 12). Pekerja sektor informal Jatim baru 5,32 persen mendaftar BPJS Ketenagakerjaan. BPJS Ketenagakerjaan. https://www.bpjsketenagakerjaan.go.id/berita/28061/Pekerja-Sektor-Informal-Jatim-Baru-5,32-Persen-Mendaftar-BPJS-Ketenagakerjaaan

Permana, M. Y., Izzati, N. R., & Askar, M. W. (2023). Measuring the gig economy in Indonesia: Typology, characteristics, and distribution (Working paper). https://ssrn.com/abstract=4349942

Piasna, A. (2024). Job quality and digitalisation (Working Paper 2024.01). Brussels: European Trade Union Institute. https://www.etui.org/sites/default/files/2024-01/Job%20quality%20and%20digitalisation_2024.pdf

Putranto, F. G. F., Natalia, C., & Pitriyani, N. K. D. (2024). Closing the Gap Between Education and Labor Market Requirement: Do Vocational Education Matter? The Journal of Indonesia Sustainable Development Planning, 5(3), 181–191. https://doi.org/10.46456/jisdep.v5i3.614

Royuela, V., & Suriñach, J. (2013). Quality of Work and Aggregate Productivity. Social Indicators Research, 113(1), 37–66. https://doi.org/10.1007/s11205-012-0081-1

Shi, Z. (2023). The impact of regional ICT development on job quality of the employee in China. Telecommunications Policy, 47(6), 102567. https://doi.org/10.1016/j.telpol.2023.102567

Spector, P. (2019). Do Not Cross Me: Optimizing the Use of Cross-Sectional Designs. Journal of Business and Psychology, 34, 125–137. https://doi.org/10.1007/s10869-018-09613-8

Stier, H., & Yaish, M. (2014). Occupational segregation and gender inequality in job quality: a multi-level approach. Work, Employment and Society, 28(2), 225–246. https://doi.org/10.1177/0950017013510758

Van Doorn, N., & Vijay, D. (2021). Gig work as migrant work: The platformization of migration infrastructure. Environment and Planning A: Economy and Space, 56, 1129–1149. https://doi.org/10.1177/0308518x211065049

Veall, M., & Zimmermann, K. (1996). Pseudo‐R2 Measures For Some Common Limited Dependent Variable Models. Journal of Economic Surveys, 10, 241–259. https://doi.org/10.1111/j.1467-6419.1996.tb00013.x

Wasito, A. (2023). Exploring Amartya Sen’s Capability Approach. Peradaban Journal of Economic and Business, 2(2), 115–136. https://doi.org/10.59001/pjeb.v2i2.109

World Bank. (2019). World Development Report 2019: The changing nature of work. World Bank. https://doi.org/10.1596/978-1-4648-1328-3

Xiong, B., & Yu, B. (2024). The Impact of Internet Development on Youth’s Job Quality in the Digital Economy Era: Transmission Mechanism and Empirical Test. Social Indicators Research, 175, 269-294. https://doi.org/10.1007/s11205-024-03439-z

You, J., Xu, X., Liao, D., & Lin, C. (2024). International comparison of the impact of digital transformation on employment. Journal of Asian Economics, 95, 101820. https://doi.org/10.1016/j.asieco.2024.101820