Financial Precarity in the Platform Economy: An Empirical Analysis of Algorithmic Strain, Earnings Volatility and Financial Well-Being among Gig Workers
Aug 2026· International Journal of Advanced Research in Commerce, Management & Social Science· Vol 09, pp. 78-84· 0 citations
TL;DR
These findings extend the algorithmic-management literature by empirically linking financial strain to labor-supply behavior and carry direct implications for platform governance, minimum-earnings policy, and portable social-security design.
Abstract
The rapid expansion of platform-mediated labor has reconfigured income generation for millions of workers, yet the structural determinants of their financial well-being remain insufficiently quantified, particularly in emerging-market contexts. This study empirically examines how algorithmic work strain and earnings volatility shape the financial well-being of platform gig workers engaged in ride-hailing and delivery services. Using a quantitative, cross-sectional survey design, primary data were collected from 100 active gig workers through a structured, digitally administered questionnaire. Data were analyzed in SPSS using descriptive statistics, Principal Component Analysis, linear regression, and Pearson correlation at α = 0.05. Five latent constructs, were extracted which were productivity and daily output, financial well-being and satisfaction, operational and workplace challenges, work-related financial attitudes, and platform support and engagement. Regression analysis was also conducted to confirm the work-related financial attitudes and predict their daily productivity, indicating that financial pressure drives compensatory labor supply. Operational and workplace challenges were studied on the basis of mean score among the five constructs, closely followed by financial well-being and satisfaction, while platform sector type (ride-hailing versus delivery) relationship with financial satisfaction suggested that precarity is systemic rather than sector-specific. These findings extend the algorithmic-management literature by empirically linking financial strain to labor-supply behavior and carry direct implications for platform governance, minimum-earnings policy, and portable social-security design.
Incorporating technology and stock-broking applications affects retail investors' participation in the stock market. This study is organized in four technology-related explanatory constructs; Platform Efficiency; Analytical Tools; Security & Risk Concerns; Educational Support; and one dependent construct, Investor Participation. Technology acceptance, digital finance adoption, perceived risk, and financial capability, as theoretical perspectives, lead to a better understanding of platform design and feature quality as primary determinants of real market participation. Primary data was obtained by utilizing a 5-point questionnaire format of Likert-type response scales, and 104 valid survey responses remained to be processed for the evaluation. The analytic tool encompassed respondent profile analysis, descriptive statistics, item-level analysis, Cronbach’s alpha, Pearson correlation, multiple regression, independent-samples t test, one-way ANOVA, and Tukey post-hoc comparison. The outcome showed that Investor Participation is relatively high overall (mean = 4.034), Analytical Tools (4.029), Educational Support (4.013) and Platform Efficiency (3.769). There is a moderate level of Security & Risk Concerns (3.315), which means that respondents have high awareness of digital risks, yet do not let these come to eclipse their own investing behaviour. Across all constructs, the reliability is good or moderate, with the Cronbach’s alpha for each variable in the range of 0.722 to 0.887. All the explanatory constructs relate positively to Investor Participation. The strongest bivariate correlation (r = 0.675) appears with Analytical Tools. Platform Efficiency (p = 0.0049), Analytical Tools (p = 0.0004), and Educational Support (p = 0.0394) are positive and significant predictors of Investor Participation, while Security & Risk Concerns (p = 0.8957) are statistically insignificant when combined. The model overall accounts for 52.3 percent of the variance in Investor Participation and is robust. Overall, there is no statistical significance observed across the group-wise tests with respect to differences in gender, age, educational level, monthly income, and time in investments. While statistically insignificant within one trade type, it is notable in that discount brokers engage more people than do bank-app participants. The study reveals that the participation of retail investors in today's markets does not depend as much on the accessibility of digital-based resources as on decision support, efficiency, and embedded learning support.
Lonare Alaknanda, Iyer Geetha, Prathamesh Kumar et al.· International journal of com...· 0 citations
The rapid growth of quick commerce (Q-commerce) in India is transforming retail businesses while posing critical challenges to labour rights and worker welfare. The study focuses on the working conditions, labour rights and welfare of gig workers in the Q-commerce sector in India. A survey of 1,247 Q-commerce delivery workers from major metros in India was conducted utilizing a regression modelling approach. The robustness of the employed model is thoroughly substantiated by both the substantial sample size and the highly significant
p
values achieved during empirical testing. The most significant findings of the study were severe systemic compensation disparities, with the vast majority of the workforce earning below the statutory minimum wage, exacerbated by a widespread lack of basic social security. Furthermore, the findings demonstrate a strong positive correlation between a worker’s reliance on digital labour platforms and their susceptibility to acute financial instability, highlighting how algorithmic performance metrics directly dictate workers’ economic security. The study also identifies critical gaps in labour protections, particularly concerning excessive and unregulated working hours.
I. Goswami, Nigel Raylyn Dsilva, R. Choudhury· Global Business Review· 0 citations
This research investigates how capital structure (measured by DER), asset efficiency (measured by TATO), and liquidity (measured by CR) impact the corporate value of infrastructure firms listed on the Indonesia Stock Exchange (IDX) from 2020 to 2024. Adopting a quantitative methodology, secondary data were gathered from audited corporate annual reports. A purposive sampling technique selected 45 eligible companies out of 70, establishing 225 initial data points. Following the removal of extreme outliers using boxplot analysis, a final set of 156 observations was evaluated via multiple linear regression using SPSS 26. The simultaneous F-test reveals that all independent variables concurrently exert a significant effect on corporate value. Individually (t-test), both capital structure and liquidity show a significant negative relationship with firm value, whereas asset efficiency does not demonstrate any meaningful impact. These findings indicate that maintaining prudent financing strategies and optimizing working capital without over-leveraging are vital components for enhancing market valuation among investors in the infrastructure sector.
In emerging markets, where businesses frequently have low financial resources and relatively weak institutional supervision, aggressive accounting techniques continue to undermine the credibility of financial reporting. This study examined firm-specific determinants of income smoothing practices among firms listed at NSE, Kenya. The study looked specifically at the effect that it had on profitability, financial leverage, liquidity and operational efficiency on earning management behavior. The research was reliant on the Positive Accounting Theory, Trade-off Theory, Credit Risk Theory, Pecking Order Theory and Risk and Return Theory. The study employed a mixed-source quantitative design. 279 finance professionals from 55 listed companies provided primary data, and audited financial statements from 2019 to 2023 provided secondary data. Descriptive statistical techniques were employed to analyze the data as well as Pearson correlation, multiple regression, fixed effects panel regression and diagnostic tests. The findings indicated that financial leverage (β = 0.270, p < .001) and profitability (β = 0.472, p < .001) were the most significant determinants of income smoothing practices, and liquidity had a positive but less significant effect (β = 0.173, p < .001). Operational efficiency did not significantly affect earning management (β = 0.014, p =.670). The regression model explained 64.1% of the variation in aggressive accounting practices (R² = 0.641), which is a substantial explanatory power. The results imply that financing pressures and falling profitability are the main incentives for managers to use aggressive accounting in emerging capital markets. In addition to adding to the existing body of knowledge, regarding the quality of financial reporting by offering empirical data from a developing African economy. The results indicate that in order to enhance the early detection of earning management practices, authorities should include financial distress indicators into risk-based surveillance systems.
Timothy Kalume Kahindi, Dr. Isaac Otiende Ojung’a, Prof. Wahida Mahmud Bana et al.· International Journal of Res...· 0 citations
This research examines the effect of liquidity, leverage, activity, and profitability on financial distress among manufacturing companies included in the LQ45 Index in Indonesia during 2020–2024. This research used a quantitative explanatory approach to investigate the relationship between the variables. The analysis relied on secondary data obtained from the audited annual reports of 7 manufacturing companies selected by purposive sampling method, resulting in a balanced panel dataset consisting of 35 observations. Financial distress was measured using the Altman Z-Score, while TATO, ROA, DER, and CR were employed as the independent variables. To evaluate both the individual and combined effects of these variables on financial distress, panel data regression analysis was conducted using the CEM, supported by t-test and F-test analysis. The results reveal that liquidity (t = 2.426; p = 0.022) and profitability (p = 0.070) have positive and statistically significant correlations with the Altman Z-Score, indicating that stronger liquidity and higher profitability mitigate financial distress risk, with profitability emerging as the dominant predictor. Conversely, leverage and asset efficiency show no significant individual effects, suggesting that manufacturing firms can adjust their capital structure and asset utilization without necessarily increasing financial distress risk. However, when all four ratios are considered simultaneously, they collectively explain a substantial portion of the variation in financial distress (F = 3.797; p = 0.013; R² = 33.61%). These findings highlight that financial ratio indicators, particularly those related to liquidity and profitability, are useful for evaluating the financial health of established manufacturing firms in Indonesia's LQ45 Index.
Farhan Dzulfiqri, Y. Sudaryo, Nunung Ayu Sofiati et al.· Eduvest - Journal Of Univers...· 0 citations
Background: Financial performance in the food and beverage sector remained uneven through the pandemic and recovery, creating potential incentives to stabilize reported earnings.
Objective: This study tests profitability, leverage, and firm size as determinants of income smoothing in Indonesian food and beverage firms during 2020–2024.
Methods: Using a causal-comparative quantitative design, secondary financial data from 23 purposively selected firms produced 112 observations. ROA, DAR, log total assets, and the Eckel Index represented the study variables. Logistic regression was used to test the hypotheses.
Results: The three predictors were jointly significant (Nagelkerke R² = 0.122). Profitability and leverage were positively significant, while firm size was negatively significant.
Conclusion: The findings indicate that earnings-smoothing behavior varies with profitability, debt exposure, and company scale and provide evidence relevant to assessing financial-reporting quality.
Muhammad Zharfan Marsyafadhlan, Wiwin Aminah, Brady Rikumahu· Journal of Business, Social...· 0 citations