Directionality of transitions in space: Diverging trajectories of electric mobility and autonomous driving in urban and rural settlement structures

Highlights

• We are interested in how far different spatial structures influence the shape and direction of technological development and of transition processes.

• We mobilize a framework, which differentiates the essentially “flat” interpretation of a socio-technical regime into two “layers”: service and sector regimes.

• We use the examples of electric mobility and automated driving in Germany to illustrate how the extended regimes concept helps for getting a spatially more fine-grained understanding of potential future regime dynamics.

• We show that urban and rural contexts may support different directionalities when electric mobility or automated driving is introduced. This may affect the overall sustainability record of the future mobility sector.

• Governance strategies have to acknowledge that the diffusion of electric propulsion and automation does not necessarily lead to similar patterns of change in different spatial settings.

Abstract

How does the spatial context shape early innovation trajectories and how will this influence the directionality of transitions? We elaborate these questions for the case of transitions in personal mobility, focusing on emerging trajectories of electric vehicles and autonomous driving. We analyze how the dynamics depend on whether innovation and transition strategies are primarily geared towards urban or rural contexts. In order to identify potentially diverging trajectories, we specify socio-technical regime structures at two levels: the level of service regimes (i.e. rules that relate to specific means of transport, like the car) and the level of the sectoral regime (i.e. rules that regulate the interplay between the different service regimes). We will show that depending on whether the early innovation strategies are oriented at rural or urban contexts, quite different directionalities can result both regarding the technological trajectory of the new service option, but also regarding the overall sector configuration.

Introduction

The mobility sector is key for solving the global sustainability problem (Holden et al., 2019; Sims et al., 2014). To accommodate for these grand challenges, far-reaching transformations are needed and they will most likely be influenced by the rapid progress in electrification and digitalisation of individual vehicles and overall traffic management. Many experts believe that after long years of rather incremental change, these new technologies boost fundamental transformations leading ultimately to more sustainable mobility sector (Canzler and Knie, 2016; Docherty et al., 2018; Schippl and Arnold, 2020; Transport & Environment, 2019). However, the mobility sector will not only be shaped by the more or less rapid diffusion of individual technological solutions. Rather, we have to analyse how societal and technical dynamics co-evolve in order to assess how new technologies and services will shape future mobility options and their performance in terms of sustainability (Noy and Givoni, 2018; Sheller, 2012; Truffer et al., 2017). In other words, we have to disentangle the different forces, which will ultimately shape the directionality of these emerging transformation processes. In view of these major expected transformations, it is increasingly important to anticipate the outcome of current sociotechnical dynamics. Policy makers seeking to support sustainable development as well as industrial strategists seeking positions in these emerging mobility sectors should base their decisions on a solid understanding of potential future directions of such developments.

Over the last decades, a rich body of literature emerged in fields such as technology assessment, foresight, and transitions research, which provides tools and concepts for tackling this task (Decker et al., 2004; Geels et al., 2012; Grunwald, 2018, 2009; Markard et al., 2012). In the transitions literature, the question of directionality has been treated rather implicitly by many authors assuming that through the scaling and maturing of “clean technologies” more sustainable socio-technical systems would almost automatically be realized (Weber and Rohracher, 2012). The question of how to anticipate the overall impact of new technologies on sustainability requires an explicit evaluation of alternatives, which is typically outside of the scope of most transition studies. The technology assessment literature, on the other hand, has built up a broad set of foresight and assessment approaches (Grunwald, 2018) but is less explicit about how alternative development trajectories may emerge in the first place (Truffer et al., 2017). In the present contribution, we therefore explore how a better understanding of directionality in socio-technical dynamics may provide a solid basis for technological assessment that aims at advising sustainability oriented policies.

Given that mobility sectors essentially provide means to overcome spatial distances, density and form of settlement structures may have a strong influence on which technologies and services are better or less well suited for this task. In other words, we will in the following analyse in how far spatial structures influence the shape and direction of technological development and of transition processes (Binz et al., 2020; Coenen et al., 2012; Hansen and Coenen, 2015). We know from the history of technology, that specific context conditions may shape path dependencies and create lock-in of technological trajectories, like in the classical example of diverging directionalities in typewriter keyboard layouts (David, 1985). In order to tackle these questions, we have to elaborate how selection environments differ between different contexts and how they support particular trajectories rather than other ones. Issues of directionality have only rather recently gained prominence in transitions studies (Weber and Rohracher, 2012). As a consequence, a variety of specific studies started to address mechanisms for shaping directionality. Yap and Truffer (2019), for instance, analysed how emerging economies can shape technological trajectories by “internalizing windows of opportunity”. Or, van Welie et al.(2019) enquired how a wide variety of transition trajectories have to be considered in a context of informal settlements of the global south. Yang et al. (n.d.) (submitted) analysed how strategies of niche and regime actors in different Chinese regions resulted in competing dominant designs in solar PV technology. All these studies focused on the role of geographical variation in transition processes at the level of different jurisdictions (i.e. cities, regions, or countries) (Coenen et al., 2012; Hansen and Coenen, 2015). But, to our knowledge, no studies have elaborated on the differences of physical settlement structures so far.

We will build on this earlier research and elaborate how spatially variegated settlement structures influence the specific shape of the mobility regimes and through this influence the directionality of specific technological trajectories and thus ultimately lead to diverging (in the sense of more or less sustainable) transition pathways. More specifically, we ask which kinds of innovation and transition dynamics may be expected depending on whether policy and industry strategies had primarily addressed urban or rural context conditions. Empirically, we will elaborate on these questions for the case of mobility transitions as currently discussed in Germany and how they relate to alternative development trajectories of battery electric vehicles (BEV) and automated vehicles (AV) when embedded in rural or urban contexts. Both technologies are considered to contribute to a fundamental restructuring of the automotive sector with potentially beneficial impacts on the sustainability of the mobility sector. Electric vehicles are already commercialised – however future directions of development have not fully panned out, yet. Autonomous vehicles, which enable the driver to pass partial or full control to the vehicle, are not commercialised yet. However, in many countries, pilot projects are running and there is widespread agreement that these vehicles will substantially impact the way we organize mobility services in the future (Fraedrich et al., 2017; May et al., 2020). Robo-taxis and similar forms of collective mobility, for instance, are expected to replace conventional private cars, or at least to push it into a subordinate niche (May et al., 2020; UITP, 2017). BEVs are often presented as a clean element of future ‘smart cities’ dominated by collective mobility offerings (Finger and Audouin, 2019; Vienna City Administration, 2014). Other authors highlight that BEVs are also well suited for rural areas (Plötz et al. 2013; Kester et al. 2020). Whether and to what extent the different technological trajectories will emerge and stabilize in these different settlement contexts is however rarely elaborated. Strategies to achieve sustainable mobility cannot only focus on urban areas. In Germany, for example, only about one-third of the population lives in cities with more than 100’000 inhabitants (Nobis and Kuhnimhof, 2018). We will show that, in contrast to the mostly urban inspired visions of collective mobility, rural settlements may be pushed onto less sustainable trajectories by these urban inspired visions. AVs, for instance, may lead to increased car-dependency and further weaken of public transport services. Once such self-reinforcing processes gain momentum, it might be difficult to reverse them. It is therefore essential to consider the context-specific dynamics of early innovations, in order to avoid non-desirable path-dependencies to emerge.

In order to analyse the role of spatial contexts on the directionality of innovation trajectories and transitions, we need to elaborate how different places provide distinct selection environments to support or hinder alternative directionalities (Yap and Truffer, 2019). In transition studies, the selection environment is strongly conditioned by the prevailing rules and norms that apply to specific services in a sector, i.e. the prevailing socio-technical regime. The regime concept has been widely applied for analysing mobility transitions (Geels et al., 2012; Whitmarsh, 2012). In particular, in the fields of electric mobility and automated driving, studies have provided valuable insights on sociotechnical dynamics and potential development pathways (Augenstein, 2015; Dijk et al., 2013; Skjølsvold and Ryghaug, 2020; Truffer et al., 2017). However, these applications of the regime concept usually treat space as a rather homogenous dimension and are therefore not well equipped to address spatially divergent development trajectories. Spatial divergence represents, however, a rather mundane reality in the mobility sector. Typically, design, organization and performance of different transport modes vary considerably between urban and rural areas. For instance, public transport is usually much more widely available in large cities than in small villages. In many OECD countries, in the last years, these differences even grew stronger with the introduction of a broad range of new mobility options, primarily in urban contexts. Striking examples are sharing and renting schemes for cars, bikes and scooters (Shaheen and Cohen, 2018). Moreover, the integration between modes substantially improved in particular in larger cities through online mobility platforms, integrating ticketing concepts and the like (Hirschhorn et al., 2019). Rural areas have experienced far less changes and in most cases, the private car remained by far the dominant form of transport.

We take from these empirical observations that we have to conceptualize the spatial variation of mobility regimes as operating at two levels: the level of the single modes or services, and the sectoral regime level that regulates the interrelations between the different modes. This is in line with a recent proposal by van Welie et al. (2018), who defined service regimes as “specific institutionalized combination of technologies, user routines and organizational forms for providing the service” (van Welie et al., 2018, p. 260). “Sectoral regimes refer to broader economic and societal realms (or organizational fields) that cover a societal function like transport, food, safe urban water, electricity, and so forth” (van Welie et al., 2018, p. 261). We draw on this understanding and add that different constellations in urban and rural sector regimes may give rise to different technological development trajectories.

The paper proceeds as follows: In section 2, we elaborate on the directionality of sociotechnical regimes before we introduce the concepts of service and sector regimes, in general. In section 3, we elaborate the service and sector regime structures in urban and rural mobility sectors in Germany. In section 4, we then show how these different selection environments may give rise to divergent directionalities for the development of electric vehicles and self-driving cars, and how this would impact the sustainability of future urban and rural mobility sectors. The concluding section 5 will elaborate on the wider implications of our findings both for the governance of mobility transitions in Germany and in other countries and for the role of space in shaping directionalities.