Three Essays on Strategic Operations with Government Intervention

Abstract

This dissertation investigates the strategic interplay between government interventions and operational decision-making in complex service and industrial systems.

The first chapter of the dissertation focuses on service operations management in socially beneficial sectors. Addressing the dual challenges of affordability and accessibility of the service, we model the dynamic interaction among a government and a service provider as well as citizens using a continuous-time Markov chain (CTMC). We evaluate two different supply-side capacity-expansion incentives and demonstrate an operational insight: subsidizing idle capacity (risk mitigation) is consistently more cost-effective than fee-for-service rewards (reward enhancement). By identifying whether the system bottleneck lies on the demand side (affordability) or the supply side (accessibility), we propose a near-optimal mixed-subsidy mechanism that maximizes the expected service level under a fixed government budget.

The second chapter investigates the impact of government interventions on the firm's resource allocation problem regarding innovation. In a setting where firms face finite resources, e.g., managerial capacity or high-skilled personnel, we analyze the trade-off between R\&D effort and production exploitation. We identify scenarios where demand-side subsidies, while expanding market size, may inadvertently crowd out long-term innovation in favor of short-term profitability. In such cases, the effectiveness of supply-side subsidies that are aimed at stimulating innovation, can be harmed alongside demand-side subsidies. However, we show that technological maturity serves as a prudent buffer mitigating this crowding-out effect. This underscores the need for policymakers to calibrate incentives based on the firm's characteristics and operational constraints.

The third part explores strategic technology management in the platform economy, specifically the adoption of autonomous vehicles (AVs) in competing ride-hailing markets. Using a game-theoretic framework, we analyze how platforms balance the cost benefits of automation against the competitive dynamics of pricing and labor-supply management. Our analysis reveals that technological advancement does not always translate into improved consumer surplus or social welfare. Instead, it can lead to suboptimal market configurations and wage suppression. We find a U-shaped relationship between technology costs and social welfare, which reveals that radically promoting new technologies without considering costs can actually have negative effects.

Date of Award	26 Jun 2026
Original language	English
Awarding Institution	City University of Hong Kong
Supervisor	Stephen Wan Hang SHUM (Supervisor)