Kukuh Arisetyawan
Universitas Negeri Surabaya, Indonesia

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Location is Destiny? Unravelling the Income Gap of Gig Workers in Indonesia with Blinder-Oaxaca Decomposition Hendry Cahyono; Kukuh Arisetyawan; Yusmiaty Sabang; Fariz Al Thoriq; Ardika Tristyanto; Zain Fuadi Muhammad RoziqiFath; Nur Azirah Zahida Mohamad Azhar
Journal of Economics, Entrepreneurship, Management Business and Accounting Vol 4 No 4 (2026): Volume 4, Issue 4, July 2026
Publisher : CV. Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/jeemba.v4i4.1111

Abstract

Purpose – The objective of this study is to analyze and identify key factors of the income gap between gig workers in urban and rural areas in Indonesia. Secondary data from the 2023 National Socioeconomic Survey (Susenas) was used in this study. Design/methodology/approach – Data analysis was conducted by applying the Blinder-Oaxaca decomposition method to separate the sources of income inequality into components explained by differences in characteristics (endowments) and unexplained components (discrimination or non-observable factors). A robust regression model was also used to ensure the accuracy of the estimates. Finding/Results – This study reveals that gig workers in urban areas have significantly higher incomes (around 12%) than their counterparts in rural areas. Most of this gap is due to differences in characteristics (explained component), particularly access to digital technology and education levels. However, the unexplained component is also significant, indicating differences in market value or discrimination against the same characteristics in both regions. Other factors such as full-time employment, white-collar jobs, male gender, and marital status also positively affect income levels. Originality/Value – The value of this research lies in its primary focus on the long-term impact of spatial inequality among gig workers, as well as its comprehensive use of the Blinder-Oaxaca method in the context of the Indonesian gig economy to describe the sources of this inequality in detail
Determinants of Workplace Internet Use among Indonesian Workers: Probit and Logit Analysis Using SAKERNAS 2023 Rendra Dwi Saputra; Kukuh Arisetyawan; Irien Kamaratih; Axellina Muara Setyanti; Muhammad Andika Zalfiandra; Muhammad Syahril Mustofa; Muhammad Rafi Putra Ibrahim; Aldan Ardana Ahmad
Journal of Economics, Entrepreneurship, Management Business and Accounting Vol 4 No 5 (2026): Volume 4, Issue 5, September 2026
Publisher : CV. Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/jeemba.v4i5.1298

Abstract

Purpose – This study analyzes the determinants of workplace internet use among Indonesian workers, treated here as one measurable dimension of digital technology adoption, using SAKERNAS August 2023 (N =465,204). Design/methodology/approach – Binary probit and logit models, weighted using BPS individual sampling weights with the full linearized variance estimator (strata and PSU), and Average Marginal Effects (AME) for twelve explanatory variables. Finding/Results – Education ≥ senior high school again has the largest effect once BPS sampling weights are applied (AME = 0.222; p < 0.01), followed by urban location (AME = 0.122), Kartu Prakerja awareness (AME = 0.137), and employee/wage-worker status (AME = 0.056). Disability reduces adoption probability (AME = -0.070; OR = 0.663). Internet use is associated with 53.6 percent higher earnings (exact semi-log transformation of β = 0.429), rising to 61.7 percent for internet users who have also attained senior high school education or above; both are conditional associations rather than a causal wage return. The weighted model achieves acceptable in-sample fit (AUC = 0.82; Pseudo-R2 = 0.24). Originality/Value – To our knowledge, one of the first nationally representative micro-econometric studies of workplace internet adoption in Indonesia; identifies disability as a new determinant with double-penalty implications for digital labor market inclusion.