Open Access Indonesia Journal of Social Sciences

Algorithmic Control, Financial Precarity, and Subjective Well-being Among Indonesian Gig Workers: Evidence from PLS-SEM Using the Job Demands-Resources Framework

2026-05-04T08:20:32+00:00

The rapid expansion of platform-mediated gig work in the Global South has intensified debate over whether digital labor constitutes economic liberation or structured precarity. This study examined the structural associations among algorithmic management, financial precarity, perceived autonomy, subjective well-being, and job satisfaction among Indonesian gig workers, anchored in the job demands-resources (JD-R) framework. This investigation represents the first large-scale PLS-SEM analysis to delineate the financial precarity pathway within Indonesia's on-demand economy, addressing a critical gap in the Global South platform labor literature. A cross-sectional quantitative design was employed, with data collected from 684 motorcycle taxi and courier drivers across Jakarta, Surabaya, and Medan between March and May 2024 using stratified random sampling. Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5,000-subsample bootstrapping was applied via SmartPLS 4.0. Common method bias was assessed using Harman's single factor test (variance explained = 28.4%, below the 50% threshold). Measurement model assessment confirmed strong reliability (rho_A range: 0.847–0.928; AVE range: 0.688–0.810). Structural analysis revealed that algorithmic management was significantly positively associated with financial precarity (β = 0.642, p < 0.001) and negatively associated with subjective well-being (β = −0.210, p < 0.001). Financial precarity mediated this relationship (indirect β = −0.328, 95% CI [−0.392, −0.265], p < 0.001), constituting partial mediation. Perceived autonomy was positively associated with job satisfaction (β = 0.315, p < 0.001). In conclusion, algorithmic management in Indonesia's on-demand economy operates primarily through financial fragility to suppress worker well-being. These findings support urgent regulatory reform mandating algorithmic transparency and minimum income protection floors for platform workers.

Resource Nationalism, Enclave Industrialization, and Regional Divergence: A Spatial Econometric Assessment of Indonesia's Hilirisasi Mandate

2026-05-06T04:01:05+00:00

Indonesia's hilirisasi (downstreaming) mandate, enforced through a definitive nickel mineral export ban from January 2020, represents one of the most consequential applications of resource nationalism in contemporary Southeast Asian political economy. While aggregate indicators documented substantial Foreign Direct Investment (FDI) inflows into metallurgical industrial parks, the sub-national distributional consequences remained critically underexplored prior to this study. Employing a Spatial Durbin Difference-in-Differences (SDM-DiD) framework applied to a balanced provincial panel of 34 Indonesian provinces across the period 2015 to 2024 (N = 340 observations), this study empirically decomposed the direct, indirect (spatial spillover), and total effects of the export ban on regional economic growth and income inequality. The treatment group comprised the three primary nickel-downstreaming hub provinces: Central Sulawesi, Southeast Sulawesi, and North Maluku. Moran's I statistics confirmed significant spatial autocorrelation across all study years (range: 0.245-0.312, p < 0.001), validating the spatial modeling approach. The SDM-DiD estimation revealed a significant positive direct effect on regional GDP per capita in treated provinces (beta = 0.084, SE = 0.019, p < 0.001), confirming localized growth. However, the spatial spillover effect was significantly negative (theta = -0.052, SE = 0.021, p = 0.013), documenting a pronounced backwash effect on adjacent provinces. Within treated regions, income inequality widened significantly (Gini direct effect: beta = 0.018, p < 0.001), driven by skill-biased structural transformation associated with capital-intensive smelting operations. These findings established that Indonesia's hilirisasi mandate functions structurally as an enclave industrialization model, generating spatial polarization rather than inclusive regional development. Inter-regional fiscal equalization, enforceable backward linkage obligations, and peripheral human capital investment are identified as critical complementary policy mechanisms.

Community Dynamics and Policy Resistance as Determinants of Green Transition Adoption: A Cross-Sectional Study in Indonesian Cities

2026-05-12T08:22:16+00:00

Rapid urbanization in Southeast Asian cities has intensified environmental pressures, yet the adoption of green transition practices remains uneven across communities. While individual-level determinants have been extensively studied, the contributions of community-level social factors remain poorly understood in developing urban contexts. This cross-sectional study examined determinants of green transition adoption (GTA) among 398 residents of four Indonesian cities—Surabaya, Semarang, Bandung, and Yogyakarta—between March and August 2024. Binary logistic regression with nine predictors revealed that Community Dynamics was the strongest predictor (AOR=2.87, 95% CI: 1.79–4.60, p<0.001), followed by Policy Resistance (AOR=2.18, 95% CI: 1.39–3.42, p<0.001) and Social Equity Perception (AOR=1.92, 95% CI: 1.23–3.00, p=0.004). Environmental Knowledge Score and Health Risk Perception were not significant in the multivariate model. The model demonstrated adequate discrimination (AUC=0.79) and calibration (Hosmer-Lemeshow p=0.548), explaining 32.6% of outcome variance. Mediation analysis revealed that 35% of the CD–GTA relationship operated through social equity perception (Sobel z=3.21, p=0.001). Community-level social cohesion and institutional legitimacy are more powerful drivers of green transition adoption than individual knowledge or risk perception.

Citizen Trust, Perceived Surveillance, and Polycentric Governance Participation in Indonesian Smart City Programs

2026-05-12T07:13:30+00:00

Smart city programs in Indonesia expand digital governance infrastructure while raising concerns about citizen surveillance and data privacy. Understanding how perceived surveillance affects citizen trust and participation in polycentric governance structures is critical for sustainable smart city development. This study examined 352 citizens across nine Indonesian cities representing three administrative tiers (Tier-1: Jakarta, Bandung, Surabaya; Tier-2: Semarang, Makassar, Medan; Tier-3: Palembang, Balikpapan, Manado) to investigate the relationships among perceived surveillance intensity, citizen trust in governance institutions, and participation in polycentric governance mechanisms. Hierarchical multiple regression analysis revealed a statistically significant model explaining 42.1% of variance in citizen trust (R² = 0.421, adjusted R² = 0.399, f² = 0.727). Facial recognition perceived intensity demonstrated the strongest negative predictor (β = -0.378, 95% CI [-0.498, -0.258]), while multi-stakeholder governance participation showed the strongest positive predictor (β = 0.334, 95% CI [0.218, 0.450]). Additional significant predictors included closed-circuit television surveillance intensity (β = -0.312), citizen feedback mechanisms (β = 0.298), data transparency (β = 0.287), decentralized decision-making participation (β = 0.256), governance literacy (β = 0.213), e-government service use (β = 0.189), and educational attainment (β = 0.145). These findings indicate that while surveillance technologies undermine institutional trust, inclusive governance processes and transparency mechanisms strengthen citizen confidence. Indonesian smart city programs should prioritize polycentric governance structures, data transparency, and digital literacy initiatives to mitigate surveillance-related trust erosion. Results support policy recommendations emphasizing stakeholder participation, technological accountability, and institutional transparency as essential components of citizen-centric smart city governance.

Transnational Networks and Social Cohesion Among Climate-Displaced Populations: A Cross-Sectional Study in Coastal Indonesia

2026-05-20T01:39:38+00:00

Climate-induced displacement in coastal Indonesia creates unprecedented challenges for affected populations seeking economic stability and psychological resilience. This cross-sectional analytical study examined the role of transnational networks, social cohesion, government support, and digital connectivity in climate adaptation success among 373 internally displaced persons (IDPs) across three coastal districts (Demak, Pekalongan, and Indramayu) in Central Java from January to June 2024. Using binary logistic regression, we assessed nine predictors of successful climate adaptation, defined as sustainable livelihood restoration and psychological well-being. Transnational Network Strength (TNS) emerged as the strongest predictor (adjusted odds ratio [AOR] = 2.58, 95% CI 1.59–4.18, p < 0.001), followed by Social Cohesion (AOR = 2.14, 95% CI 1.33–3.44, p = 0.002) and Government Support (AOR = 1.62, 95% CI 1.03–2.56, p = 0.038). Digital Connectivity Index and low psychological distress were also significant protective factors (AOR = 1.68, p = 0.034 and AOR = 1.82, p = 0.014, respectively). The multivariate model demonstrated good discrimination (area under the curve = 0.81) and acceptable calibration (Hosmer-Lemeshow p = 0.592), with 75.3% overall accuracy. Partial correlation analysis revealed a moderate positive association between TNS and social cohesion (r = 0.47, controlling for confounders). These findings underscore the critical importance of fostering transnational connections, strengthening community bonds, and expanding digital access to enhance adaptation outcomes among climate-displaced populations in vulnerable coastal regions.