Power relations are central to shaping collaborative governance of the urban sharing economy

The paper addresses how power relations between public authorities and private platforms shape the collaborative governance (CG) of the urban sharing economy. With ICT-enabled sharing services expanding and cities promoting “sharing city” agendas, governance challenges (e.g., disorderly parking in dockless bike-sharing schemes, DBSS) have prompted public–private CG arrangements. The authors argue that power relations are foundational to CG effectiveness because they influence convening, problem framing, negotiation, decision-making, trust, and resource mobilization. Existing literature identifies contextual determinants and two CG types—authoritarian (centralized power) and self-organised (decentralized power)—but has not sufficiently examined how these power configurations drive collaborative dynamics (actor engagement, motivations, and capacity for joint action). Focusing on DBSS as a salient shared mobility domain, the study explores this gap through illustrative cases in global cities to clarify how centralized versus decentralized power relations shape CG processes and outcomes.

The paper synthesizes scholarship on the sharing economy and CG, noting the role of socio-economic, cultural, political, institutional, policy, and legal contexts in shaping governance. Prior studies distinguish authoritarian CG (centralized, government-dominated) and self-organised CG (decentralized, more equal participation). However, power relations as determinants of collaborative dynamics remain underexplored. The authors reference work on CG regimes and power in collaboration, and empirical studies of DBSS across Chinese and Western cities, highlighting a gap: how specific power configurations condition engagement, motivation, trust, leadership, and decision processes in public–private governance of sharing initiatives.

The article is a commentary that develops a conceptual argument supported by illustrative case examples from dockless bike-sharing schemes (DBSS) in multiple cities. It draws on the authors’ fieldwork and prior empirical studies to compare authoritarian (e.g., Beijing, Shanghai, Nanjing, Shenzhen, Jinan, Chengdu in China) and self-organised settings (e.g., Boston Metropolitan Area, USA; Sydney and municipalities in NSW and Victoria, Australia). No new datasets were generated or analyzed; evidence consists of documented governance practices, policy documents (e.g., guidance, guidelines, MoUs, legislation), and prior peer-reviewed case studies. The approach is qualitative and comparative, aimed at theory-informed insight rather than hypothesis testing.

• Power relations fundamentally shape collaborative dynamics in CG of the sharing economy across three dimensions: actor engagement, motivations to collaborate, and capacity for joint action.
• Authoritarian CG (centralized power, government dominance): engagement is mandated; agendas, process design, and decisions are controlled by government; inclusivity is conditional; collaboration is driven by political authority and instrumental trade-offs; capacity for joint action is pre-determined and rapidly mobilized through top-down rules and resources. Risks include low trust, marginalization of enterprises, limited innovation, and enterprise free-riding on public investments. Examples: Beijing, Shanghai, Nanjing, Shenzhen, Jinan, Chengdu.
• Self-organised CG (decentralized power, shared leadership): engagement is voluntary and more equitable; negotiations emphasize inclusivity and reciprocity; motivation is underpinned by trust, mutual understanding, and shared identity; leadership and rules are co-developed (e.g., Inner Sydney Bike Share Guidelines). Downsides include slower consensus-building, decision-making delays, and initially limited resource mobilization. Examples: Boston Metropolitan Area; Sydney; Lime partnerships with local governments in NSW and Victoria.
• The capacity for joint action in authoritarian settings often precedes and shapes engagement and motivation (contrary to common CG sequence models), whereas in decentralized settings, trust-building and co-leadership evolve over time, gradually enabling greater resource commitment (e.g., NSW Share Bikes Impounding Amendment Act supporting local schemes).

The findings show that centralized versus decentralized power relations condition how public and private actors engage, what motivates them, and how effectively they can act jointly. This addresses the research gap by detailing mechanisms: in centralized regimes, government authority streamlines decision-making and resource deployment but can suppress trust and innovation; in decentralized regimes, shared power builds legitimacy and durable collaboration but may slow action. The work reframes CG theory in sharing economy contexts by suggesting that power configurations can invert the commonly posited sequence of engagement → shared motivation → joint capacity, particularly under authoritarian CG where capacity is imposed top-down. The relevance extends to urban policy design: choosing or adjusting power-sharing arrangements should be contingent on problem urgency, desired speed of implementation, and long-term sustainability of collaboration.

The paper contributes a power-centric perspective to the collaborative governance of the urban sharing economy, demonstrating that power configurations (centralized vs decentralized) are pivotal in shaping engagement, motivation, and joint action capacity. It offers practice-oriented guidance: authoritarian CG can efficiently mobilize resources and act quickly but should incorporate equitable negotiation and shared decision-making to foster trust and private investment; self-organised CG nurtures inclusion and trust but benefits from more proactive governmental support (policy, legislative, financial) and conflict-mediation mechanisms to avoid stagnation. Future research should broaden actor constellations beyond government–enterprise dyads and compare power dynamics across diverse sharing domains (e.g., housing, mobility, goods/services, food delivery, pets, knowledge sharing) to refine theory and inform context-sensitive governance design.

The analysis focuses on two actor groups (local governments and private enterprises) within a single domain (dockless bike-sharing schemes), limiting generalizability across other sharing economy sectors and multi-actor configurations. As a commentary using illustrative cases and prior studies, it does not provide new empirical datasets or quantify effects. Future work should examine cross-boundary collaborations involving volunteers, think-tanks, media, users, and industry associations, and conduct comparative studies across varied sharing practices to map diverse power arrangements and their effects on CG dynamics.