Exploring motivational mechanisms behind the intention to adopt mobility as a service (MaaS): Insights from Germany

Schikofsky, Jan; Dannewald, Till; Kowald, Matthias

doi:10.1016/j.tra.2019.09.022

Cited by 81 publications

(66 citation statements)

References 58 publications

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“…• Expected strong complementary relationship in an autonomous vehicle (AV) future Given that the relationship is shifting to complementarity, we can expect that tendency will be accelerated in the next generation of ICT and transportation where those two elements are combined into a new type of transportation service. Autonomous vehicles (AVs) or mobility as a service (MaaS) meaning "the accessibility and usage of individual intermodal and multimodal solutions" [28] such as Uber and Lyft could be a case. As those markets are explosively emerging, two main industries which are directly connected with AV technology, i.e., vehicle manufacturing and communications, will be likely to be growing simultaneously.…”

Section: Discussionmentioning

confidence: 99%

Is the Relationship between Transportation and Communications Industries Complementary or Substitutional? An Asian Countries-Based Empirical Analysis Using Input-Output Accounts

2020

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The relationship between transportation and communications has been discussed throughout the past decades. This study also investigates that relationship to determine whether they are complementary or substitutive in terms of the industrial perspective, focusing mainly on six Asian countries (China, Japan, India, Korea, Indonesia, and Taiwan). National input-output (I-O) tables from the World Input-Output Database (WIOD) were used to construct research dataset. Each activity in the table was examined and fell into either transportation or communications category when they are related to those categories, thereby establishing six categories: Transportation manufacturing (TM), transportation utilities (TU), communications manufacturing (CM), communications utilities (CU), all transportation (AT), and all communications (AC). To examine the interrelationship between two sectors, direct and total coefficients were calculated for four benchmark years (2000, 2005, 2010, and 2014), then Spearman correlation analysis was conducted using those two coefficient matrices after weighting each coefficient using the economic contribution-based weight (ECBW). As a result, we confirm the predominant complementary relationship between two industries. Most Asian countries present consistent, dominant complementarity in both direct and total analysis. Although there are mixed total effects in Japan and Taiwan, the overall pattern demonstrates remarkable positive relationships. In analyzing the same effects in western countries, we also find the same straightforward positive association between two sectors, mostly in France, the US, and the UK. We believe that our findings can contribute to the literature by providing compelling evidence of the overall trend of a complementary relationship between two industries.

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Section: Discussionmentioning

confidence: 99%

Is the Relationship between Transportation and Communications Industries Complementary or Substitutional? An Asian Countries-Based Empirical Analysis Using Input-Output Accounts

2020

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“…Furthermore, the focus of CBC analysis is on the attributes and attribute levels of the smart mobility apps, in other words, on how techno-economic characteristics affect choice decision (Naous and Legner 2017). The results of Schikofsky et al (2020) show, however, that in the present context the intention to adopt a smart mobility app might also depend on further motivational factors, such as hedonic motives (e.g., fun, pleasure), perceived usefulness (e.g., perceived efficiency and performance) and perceived ease of use. Hence, in order to understand the acceptance of smart mobility apps in it's entirely, the results of the present study should be used to inform further research that adopts the Technology Acceptance Model (TAM).…”

Section: Limitations and Further Researchmentioning

confidence: 61%

Smart mobility – an analysis of potential customers’ preference structures

et al. 2020

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Cities around the world face major challenges caused by the extensive use of private cars. To counteract these problems, a new paradigm is necessary which promotes alternative mobility services. ‘Smart mobility’ refers to a new mobility behaviour that makes use of innovative technical solutions, such as the IT-supported combination of different alternative mobility services during a trip from an origin to a destination. Unfortunately, relatively few customers use apps that provide recommendations for smart mobility and there is limited knowledge about the desires, priorities and needs of potential customers. To fill this gap, we use conjoint analysis to explore differences in smart mobility app preferences across groups of people with varying mobility behaviour. Our study also considers the effect of age and place of residence on preference structures. Our results show, for example, that only car drivers do not consider the price of the smart mobility app to be particularly important for their selection decision.

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“…The total body of this literature has been exclusively published from 2011 onwards, with more papers being issued every year. These studies cover many MaaS angles, including user experience [52][53][54], attitudes [55,56], integration with public transport [57][58][59], business models [60,61], travel behaviour [62,63], governance and policy [64,65], urban futures [66,67] and even Blockchain adaption [68].…”

Section: Mobility-as-a-servicementioning

confidence: 99%

Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era

et al. 2020

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Artificial intelligence (AI) is a powerful concept still in its infancy that has the potential, if utilised responsibly, to provide a vehicle for positive change that could promote sustainable transitions to a more resource-efficient livability paradigm. AI with its deep learning functions and capabilities can be employed as a tool which empowers machines to solve problems that could reform urban landscapes as we have known them for decades now and help with establishing a new era; the era of the “smart city”. One of the key areas that AI can redefine is transport. Mobility provision and its impact on urban development can be significantly improved by the employment of intelligent transport systems in general and automated transport in particular. This new breed of AI-based mobility, despite its machine-orientation, has to be a user-centred technology that “understands” and “satisfies” the human user, the markets and the society as a whole. Trust should be built, and risks should be eliminated, for this transition to take off. This paper provides a novel conceptual contribution that thoroughly discusses the scarcely studied nexus of AI, transportation and the smart city and how this will affect urban futures. It specifically covers key smart mobility initiatives referring to Connected and Autonomous Vehicles (CAVs), autonomous Personal and Unmanned Aerial Vehicles (PAVs and UAVs) and Mobility-as-a-Service (MaaS), but also interventions that may work as enabling technologies for transport, such as the Internet of Things (IoT) and Physical Internet (PI) or reflect broader transformations like Industry 4.0. This work is ultimately a reference tool for researchers and city planners that provides clear and systematic definitions of the ambiguous smart mobility terms of tomorrow and describes their individual and collective roles underpinning the nexus in scope.

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Exploring motivational mechanisms behind the intention to adopt mobility as a service (MaaS): Insights from Germany

Cited by 81 publications

References 58 publications

Is the Relationship between Transportation and Communications Industries Complementary or Substitutional? An Asian Countries-Based Empirical Analysis Using Input-Output Accounts

Is the Relationship between Transportation and Communications Industries Complementary or Substitutional? An Asian Countries-Based Empirical Analysis Using Input-Output Accounts

Smart mobility – an analysis of potential customers’ preference structures

Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era

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