Conference Agenda

The emergence of technology-based platform economy in the Indian cities is seen as one of the potential sectors for generating employment for a large number of youths and is also a process of formalization of informal employment on a large scale; however, whether such a type of formalization is actually benefiting the workers or not requires a detailed empirical examination. This brings our aim for the study to examine the quality of employment generated in the Indian ridesharing platforms by comparing the quality of employment between traditional and digital cab services in two Indian megacities with different political and economic setups, Kolkata and Bengaluru. We have collected information from 650 cab drivers, out of which 400 samples are app-based cab drivers associated with the OLA/Uber platform and 250 in conventional taxi models. Out of 650 samples, 350 drivers are interviewed from Bengaluru and 300 from Kolkata.

We have adopted ILO measures of the quality of the employment index based on three dimensions: earnings, the nature of working conditions, and security and social dialogue. Subsequently, using regression analysis, we have identified the underlying factors influencing the overall quality of employment and also each dimension. The results show higher employment quality associated with OLA/Uber drivers in both cities compared to the drivers associated with conventional taxi models. Our model shows the quality of employment is higher for Kolkata than Bengaluru. This is possible due to the higher traffic density in Bengaluru, which makes drivers have fewer rides but end up spending more hours of work for an earning. Secondly, the Security and Social Dialogue index has a higher magnitude in Kolkata than in Bengaluru, indicating that Kolkata being a worker-supportive state with higher union representation helps drivers to have more access to negotiated benefits and legal representation. However, the magnitude of these dimensions is found to be less, and any provision of fair work and remuneration through benefit programs can enhance the quality of employment for drivers in the digital sphere. One major recommendation is the review of work conditions on the platform, where several schemes must be ensured for the social protection of workers. Workers are found to be deprived of social-security benefits, insurance, and other basic privileges in a standard work arrangement, where a policy response is to reform the existing legal framework that covers the term independent contractors inside the legal purview.

Over the past decade, gig platforms have evolved into a key constituting element of the gig economy, enabling clients to hire workers for one-time, occasional or recurring services (Koutsimpogiorgos et al., 2020). These platforms rely on algorithmic management (AM) systems to automate staffing, performance evaluation, and workflow coordination (Duggan et al., 2020; Meijerink & Bondarouk, 2023). While algorithmic-enabled Human Resource Management (HRM) features promise efficiency, they also introduce opaque ranking mechanisms, automated decision-making, and digital surveillance, intensifying control while limiting worker agency. This creates a fundamental “autonomy paradox”: gig work is marketed as flexible and independent, yet AM limits workers’ ability to make meaningful decisions (Möhlmann et al., 2021).

With an estimated 154–435 million workers worldwide engaged in online gig work (World Bank, 2023), online gig platforms have become de facto labour market institutions. Yet, the lack of transparency and worker participation in AM processes raises concerns about fairness, bias and the erosion of worker voice (Rahman, 2021). Unlike on-site gig platforms where worker interactions occur in physical spaces, online gig workers increasingly rely on third-party review platforms (e.g. Trustpilot) to navigate these algorithmic systems, share experiences and challenge unfair practices.

Despite growing academic interest in AM’s implications for worker autonomy, the literature remains fragmented with persistent challenges in measurement, generalisability beyond single-platform case studies within the onsite gig economy (Meins & Seiner, 2015) and its influence on platform outcomes (Kadolkar, 2024). Addressing this gap, we ask: How do algorithmic-enabled HRM features and their effects on worker autonomy explain platform satisfaction ratings on online gig platforms?

We analyse over 56,000 satisfaction ratings across 89 online gig platforms from Trustpilot, Glassdoor, Sitejabber, and G2 - providing a rare avenue for worker voice in a system lacking collective bargaining mechanisms. Building on AM literature and adopting netnographic approaches, we examine two key constructs influencing platform satisfaction: 1) algorithmic-enabled HRM platform features; and 2) platform-enabled worker autonomy measuring choice and control. Their interplay is assessed through regression analysis at the platform level, controlling for platform characteristics (revenue model, sectoral focus, and country of headquarters), while also investigating the moderating role of algorithmic transparency.

Theoretically, our findings evaluate the applicability of organisational behavioural theories in algorithmically-managed work. On a policy level, by identifying which AM features enhance or undermine worker agency across different platform interaction stages, we offer actionable recommendations for policymakers navigating to strengthen worker voice in the age of algorithmic control.

This study examines the growing disparity between customer expectations and the operational realities faced by gig workers in the Philippines, specifically within the ride-hailing and delivery sectors. As the gig economy has expanded rapidly, workers often find themselves struggling to meet customer demands that exceed the support or resources provided by the platforms they work for. This research investigates the key factors contributing to this expectation-reality gap, explores its effects on worker well-being and performance, and proposes strategies to better align customer expectations with the realities of gig work.

Innovatively, the study focuses on the emotional and operational challenges that gig workers face when dealing with unrealistic customer demands. It extends the existing body of literature by providing a comprehensive understanding of how this gap negatively impacts workers’ mental health, job satisfaction, retention, and overall platform performance. The research also introduces new perspectives on the role of customer expectations and platform accountability in maintaining a sustainable gig economy. This contribution is critical as it addresses a previously underexplored dimension of gig work—the interaction between customers, platforms, and workers in shaping the dynamics of the gig economy.

The methodology is both rigorous and comprehensive, utilizing a mixed-methods approach to gain insights into the worker experience and the operational realities of the gig economy. Surveys were administered to gig workers to gather quantitative data on their experiences with customer expectations, mental health, and job satisfaction. In-depth interviews with platform representatives and industry experts provided qualitative insights into the operational challenges and customer management strategies. This methodological combination strengthens the study’s analytical rigor, ensuring a holistic understanding of the issue.

Findings from the research reveal that the expectation-reality gap is primarily driven by factors such as unrealistic customer demands, inadequate support from platforms, and a lack of alignment between platform promises and actual working conditions. The study highlights the mental and emotional strain placed on gig workers due to the pressure of meeting customer expectations without adequate compensation or resources. It calls for policy and platform reforms, including better support systems for workers, clearer communication regarding customer demands, and fairer compensation structures. The research emphasizes the importance of educating customers about the realities of gig work and recommends strategies for creating a more balanced and sustainable gig economy.

The research provides actionable insights for policymakers, platform developers, and industry stakeholders to improve worker conditions, promote sustainability, and foster better customer-worker relationships in the Philippine gig economy.

As digitalisation accelerates globally, the gig economy has emerged as both a key driver of flexible employment and a complex challenge for decarbonisation and environmental sustainability. In India, this dynamic is evident in the rapid growth of e-cab and food delivery services, which has provided essential jobs, especially for young and semi-skilled individuals, but also intensified urban congestion, air pollution, and emissions. As the world confronts urgent environmental challenges, there is a growing recognition of the need to align economic activities with sustainable practices to reduce carbon emissions. The green transition represents a comprehensive shift toward sustainable economic models, aimed at minimising environmental impact by reducing carbon emissions, promoting renewable energy, and fostering sustainable development.

This research examines the environmental and occupational impacts of India’s gig economy expansion, particularly regarding the trade-offs between job creation, digitalisation, and the need for decarbonisation. Thus, the aim is to explore the extent to which gig workers—especially those engaged in e-cab services and online food delivery—are impacted by these environmental factors, and to assess the adequacy of government policy in addressing the dual objectives of employment generation and environmental stewardship. The study utilises a qualitative research design, with primary data collected through semi-structured interviews with 60 e-cab drivers and 60 food delivery workers across Guwahati and Mumbai in India. Additional insights were gathered from key informants, including state and non-state actors, to provide a comprehensive understanding of the policy landscape and its impact on gig workers.

The findings reveal that while gig work provides economic flexibility, it also exposes workers to considerable environmental health risks, including respiratory issues, traffic-induced stress, and prolonged exposure to air pollution. Interviews with state, especially officials from the labour commission and environment ministry, and non-state actors further underscore the limited regulatory focus on the environmental dimensions of gig work and the marginal attention to worker well-being within the policy discourse. Certain recommendations include incentives for electric vehicle adoption in gig services, improved urban traffic management, and measures to reduce workers’ environmental exposure, particularly as India faces rising temperatures above 40°C in summer. This research, situated at the intersection of Sustainable Development Goals (SDGs) 8 and 13, aims to contribute to the discourse on sustainable employment by highlighting the environment-jobs paradox within India’s gig economy. Ultimately, it questions whether digitalisation supports decarbonisation or exacerbates environmental and occupational vulnerabilities, challenging the assumption that digitalisation and sustainability can progress together.

The platform economy has emerged as a transformative mode of work globally, revolutionizing services from transportation, food delivery and accommodation. While extensive research has documented how this new mode of working creates worker precarity through algorithmic exploitation and limited social security, a critical gap exists in understanding how climate change compounds these challenges, particularly in climate-vulnerable regions like Southeast Asia.

This study examines how platform workers in Vietnam's urban areas, specifically those in ride-hailing and food delivery services, navigate the dual challenges of technological precarity and climate change impacts. Specifically, the research addresses the following questions: (i) how have workers perceive climate impacts in urban areas? and (ii) how have they exercised their agency in the face of climate and technology challenges? Methodologically, the paper uses qualitative design and grounds the analysis on Katz's (2004) theoretical framework of everyday strategies including resilience, reworking and resistance to examine workers’ responses to these challenges. Through semi-structured interviews, responses of 50 workers were collected. The analysis was then triangulated with document analysis of existing studies about platform workers in Vietnam. Firstly, workers identify heat-related health hazards and associated financial risks as their primary concerns. Secondly, despite operating within a regulatory void and lacking formal organising mechanisms such as grievance channels and collective bargaining workers demonstrate both individual and collective agency in responding to these challenges. At the individual level, workers actively prepare for and adapt to both climatic and technological challenges rather than remaining passive recipients of platform policies. Collectively, they establish self-help online and face-to-face networks for information sharing and mutual support. These strategies allow workers to reconfigure platform constraints to their advantage while avoiding direct confrontation with platform management, illustrating how they employ resilience and reworking within the platform economy. Despite such efforts, it should be noted that competitive dynamics and moral distance among workers continue to impede stronger collective action.

This research makes two significant contributions. First, it addresses the intersection of climate change impacts and platform work, particularly in a climate-vulnerable area. Second, it reveals how workers leverage digital technologies to build resilience and resistance strategies, despite structural constraints. These findings have important implications for understanding worker agency in the platform economy and for developing climate-responsive labour policies.