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This paper examines governance responses to Mobility as a Service (MaaS). The analysis focuses on the interactions between public transport systems and MaaS developments in Amsterdam, Birmingham, and Helsinki. Case comparison is informed by the multilevel perspective on sociotechnical transitions and literature on meta-governance of networks. Drawing on these frameworks and empirical findings, the paper identifies six governance approaches to MaaS across cases: analyser, architect, convener, experimenter, lawmaker, and provider. These basic models encompass strategies ranging from hands-on strong intervention to information collection efforts. Consistent with the transitions literature, these six approaches indicate that public transport regimes seek to control the apparent disruptive potential of MaaS by incrementally absorbing innovations; to this end, regime actors adopt governance responses that tend to reproduce existing institutionalised ways of doing and prevailing logics. Furthermore, the six approaches reveal intense interaction between regime and niche, suggesting that a niche-regime space might have emerged in the cases; actors travel and operate across niche, regime, and niche-regimes, mainly driven by concerns with market share and revenue streams in the mobility system.

Driven by the technological capabilities that ICTs offer, data enable new ways to generate value for both society and the parties that own or offer the data. This article looks at the idea of data collaboratives as a form of cross-sector partnership to exchange and integrate data and data use to generate public value. The concept thereby bridges data-driven value creation and collaboration, both current themes in the field. To understand how data collaboratives can add value in a public governance context, we exploratively studied the qualitative longitudinal case of an infomobility platform. We investigated the ability of a data collaborative to produce results while facing significant challenges and tensions between the goals of parties, each having the conflicting objectives of simultaneously retaining control whilst allowing for generativity. Taken together, the literature and case study findings help us to understand the emergence and viability of data collaboratives. Although limited by this study's explorative nature, we find that conditions such as prior history of collaboration and supportive rules of the game are key to the emergence of collaboration. Positive feedback between trust and the collaboration process can institutionalise the collaborative, which helps it survive if conditions change for the worse.

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