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Review

Technology, Behavior, and Governance: Far Away, Yet So Close! A Comprehensive Review of the Sustainable Mobility and Transportation Literature

by
Ioannis Kanakis
1,
Stathis Arapostathis
1,2 and
Stelios Rozakis
1,*
1
School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece
2
Department of History and Philosophy of Science, National and Kapodistrian University of Athens, University Campus, Illisia, 15771 Athens, Greece
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(9), 4228; https://doi.org/10.3390/su17094228
Submission received: 6 March 2025 / Revised: 25 April 2025 / Accepted: 29 April 2025 / Published: 7 May 2025
(This article belongs to the Section Sustainable Transportation)

Abstract

:
Within the multidisciplinary field of Sustainable Mobility and Transport(ation) (SMT), there are few review studies that analyze the vast and complex literature in a comprehensive manner, often paying limited attention to the key structural and interpretive elements and their interrelationships. Aiming to fill this research gap, the present study offers a thorough review of the literature from the past thirty years (1992–2020), analyzing and organizing it to ultimately provide a unified synthesis. Bibliometric network visualization of the SMT literature (2084 peer-reviewed journal articles) and content analysis of its most influential subset (220 articles) are combined using a mixed-methods approach. Based on this synthesis, three main bibliographic clusters are identified: “technology”, “behavior change”, and “policy–governance”, each addressing twenty-one bibliographic themes. These structural elements (clusters and themes) are then interpreted through three main narratives and twelve sub-narratives, revealing their dynamic interactions. The entire set of clusters, themes, narratives, and sub-narratives, along with their interconnections, constitutes a conceptual framework of the SMT literature. This study highlights the importance of fostering interdisciplinarity through deeper collaboration between researchers from applied sciences, social sciences, and the humanities, and identifies key thematic research areas and topics for future exploration.

1. Introduction

The exponential growth of passenger and freight motor transport, which began in the 20th century and continues to this day [1], has significantly contributed to the material prosperity of millions of people worldwide, particularly in the developed countries of the Global North. However, since the late 1980s, the severe environmental impacts of increasing (road) motor transport have become more apparent, revealing the unsustainable nature of the transport system [2,3] and prompting scholars to engage in research in this field. In the years that followed, additional concerns relevant to sustainability emerged in the literature, particularly those related to its social dimension. These include concepts such as transport equity [4], transport inequality [5], and mobility poverty [6].
While there is consensus that the current transport system is unsustainable, there is disagreement on what a sustainable transport system or sustainable mobility/transport(ation) (SMT) is (Although the concepts of “mobility” and “transport/transportation” are not identical, in this study we follow the usual practice in the literature and use them without discrimination. The term “transport” is mainly used in Britain while the term “transportation” is mainly used in the USA [7]). The meaning of sustainable mobility has undergone transformations in both public debate and the literature following the fluctuating concerns of researchers who hail mainly from the various social sciences and humanities (SSH) disciplines that have gradually entered the field of transport studies since the 1990s [7]. These disciplines (e.g., sociology, social psychology, anthropology, political science, history, public health, innovation studies, sustainability transitions, etc.) complemented, transformed, challenged, and even revised the perspectives of the hitherto dominant disciplines that had essentially shaped “traditional transport studies”, such as civil engineering, transport engineering, and urban design and planning (For the historical development of the scientific disciplines that entered the field of transport during the last 30 years, see [7] pg 7–8, while for the comparison between the “dominant” conception of traditional “transport studies” and a version of the emerging “New Perception” of the Late 20th Century, see OECD, 2002, pg 14–15 [8]).
While until the 1990s the dominant term in the transport studies literature was the term “sustainable transport(ation)”, from 1992 onwards (with the 1992 publication of the Green Paper on the Impact on Transport and Environment by the EU [9]), the term “sustainable mobility” began to be used.
Since then, numerus definitions of “sustainable mobility” or “sustainable transport” have appeared in the literature [9,10,11]. A common element among them is their reference to the Brundtland Report [12], as they attempt to adapt the notion of sustainability—and its three pillars: environmental, economic, and social—to the domain of transport [13]. Despite this shared foundation, different approaches result in varying methodological frameworks, as sustainable mobility accommodates a broad range of interpretive definitions. These definitions reflect even broader conceptual divisions, such as the distinction between strong and weak sustainability [14]. Similar to the broader concept of sustainability, sustainable mobility appears to be a “wicked” concept [15,16], or a type of boundary object [17]—a term that allows diverse scientific communities and stakeholders within the transport system to construct interpretations aligned with their respective interests and values. In this sense, sustainable mobility is a socially constructed concept [18]. The wide variety of definitions has raised concerns that the term may become so ambiguous as to offer limited practical guidance for policymakers and researchers [13].
A description of the evolution of sustainable mobility as a concept was presented by Holden et al. [7], who suggest that a qualitative analysis of the literature from 1992 to 2018 is needed. Their paper claims “that mainstream interpretations of the conceptssustainabilityandmobilityare different today from what they were almost three decades agoand concludes that… This [sustainable mobility as a concept] is a difficult space to navigate for most professionals in the field of sustainable mobility, let alone those outside the field”.
Moreover, international organizations such as the European Union and the United Nations note in official documents that transitions to sustainable transport systems are lagging behind the targets set at both global and European levels of governance [19]. This shortfall is primarily due to the nature of incumbent transport systems—which have dominated for over a century—as complex socio-technical systems composed of infrastructure, technologies, regulations, and human behaviors, practices, and habits. The complexity of real-world transport systems is reflected in the diverse research questions and methodologies that have emerged over the past 30 years within the multidisciplinary literature on Sustainable Mobility and Transportation (SMT) [7].
The multiplicity of approaches and issues represented in the SMT literature often causes difficulties in communicating and interacting between the various scientific disciplines that have been involved in the study of SMT. We therefore believe that to accelerate the transition to a more sustainable transport system, we need to search for and analyze the basic conceptual threads that assign meaning to the complex and multidisciplinary SMT literature of approximately the last 30 years (1992–2020) (We choose 1992 as the beginning of the time period as it was then that the term “sustainable mobility” appeared in an official text of the European Union and then began to be used in the relevant literature [7]).
Existing reviews of the SMT literature typically focus on specific aspects of the field [20,21,22]. While a few comprehensive reviews do exist [7,23,24,25], they often pay limited attention to the key structural and interpretive elements of the entire body of literature and the interrelationships between them. To address this gap, we propose a novel review that integrates all dimensions of the SMT literature and examines the interplay between societal and technological factors, adopting a sociotechnical approach [26,27,28]. By employing a mixed-methods strategy—combining quantitative and qualitative analysis—we aim to provide a comprehensive understanding and a unified synthesis of the SMT field as it has evolved over the past 30 years, through a sociotechnical lens.
Our study differs from the four aforementioned review studies [7,23,24,25] in several key respects. These differences pertain to the study’s purpose, the number of articles analyzed, the range of scientific disciplines considered, and the methodological approach employed. In comparison to the works of Zhao et al. [23] and Roman [24], our quantitative analysis is based on a significantly larger corpus of articles. We broadened the scope by including publications that explicitly reference either “sustainable mobility” or “sustainable transport(ation)”. Furthermore, our study places a strong emphasis on interpreting the structural elements of the literature—namely, clusters and themes—through the development of narratives and sub-narratives.
Inspired by the foundational work of Holden et al. (2019) [7] and Holden et al. (2020) [25], our qualitative analysis (in-depth content analysis) extends to a broader and more diverse corpus of articles. This includes not only the disciplinary domains traditionally explored by these authors, but also those within the natural and applied sciences. By employing a mixed-methods approach, we complement, extend, and enrich the qualitative insights of [7,25] with quantitative analysis, thereby offering a more nuanced and comprehensive understanding of the SMT field through a sociotechnical lens.
Given the context outlined above, the primary research question that directed our study was the following:
What are the main structural and interpretive elements composing the entire SMT literature of three decades and how are they related to each other?
We anticipate that our study will, for the first time, present an original “conceptual image” of the entire SMT literature—defined as an integrated synthesis of its main structural and interpretive elements, along with the relationships and interconnections among them—viewed through a sociotechnical perspective. This approach focuses on identifying and analyzing the interactions between society and technology as they are reflected in the SMT literature.
Our study aims to serve as a comprehensive conceptual navigation guide through the complex landscape of the Sustainable Mobility and Transportation (SMT) literature, offering researchers complementary analytical tools to explore its concepts and develop a deeper understanding. Furthermore, this study aspires to facilitate communication and foster interdisciplinary dialogue—an essential element for enhancing the transformative potential of future research. Such dialogue is crucial for improving engagement with economic actors and policymakers, enabling the development of strategies and the proposal of viable alternatives to accelerate the transition toward a more sustainable transport system.
In addition, given the literature’s emphasis on the need to foster interdisciplinarity within the SMT field, our study aims to identify potential thematic areas and core units that could serve as focal points for enhanced collaboration between researchers in science, technology, engineering, and mathematics (STEM) and the social sciences and humanities (SSH).
This study is organized as follows. Section 2 outlines the methodology and research design, while Section 3 presents the bibliometric network visualization of the literature. Section 4 provides the thematic content analysis of the most influential segments of the literature, along with the construction and elaboration of the narratives and sub-narratives. Section 5 discusses the findings, addresses the study’s limitations, and suggests directions for future research. Finally, Section 6 presents the conclusions.

2. Materials and Methods

In our effort to conduct a systematic analysis of the SMT literature covering the period 1992–2020, we adopted a mixed-methods approach by combining two complementary methodologies. The first is bibliometric network visualization [29], applied to the entire body of the SMT literature, and the second is content analysis [30,31], focusing on the most influential subset of the literature. This mixed-methods strategy enables us to gain a comprehensive understanding of a vast and diverse body of research without requiring a thorough reading of every individual source. Bibliometric network visualization reveals how different topics within the literature are interconnected, while content analysis provides a deeper, qualitative interpretation of the literature’s thematic content. Thus, we use bibliometric visualization to complement—not replace—the expert judgment embedded in content analysis [29]. The integration of these two methods aligns with the principle of triangulation (In social research the term ‘triangulation’ is used to refer to the observation of the research issue from at least two different points) [32], thereby enhancing the robustness and validity of our findings.
Bibliometric network visualization is a quantitative method derived from network analysis. Simultaneously, our application of the qualitative method of content analysis, used to construct narratives and sub-narratives [33,34], supports the classification of our approach as a mixed method [35,36,37]. This mixed-method approach combines the key characteristics of two established review types: the systematic review and the narrative review [34]. As a systematic review, our study conducts a structured search of the available literature and applies explicit criteria for the inclusion and exclusion of studies. As a narrative review, it enables the extraction of in-depth qualitative insights, allowing for a richer interpretation of the data and the construction of meaningful conceptual frameworks.

2.1. Description of Bibliometric Network Visualization

Our first methodological approach, bibliometric network visualization (often referred to as “science mapping”, involves the visual representation of a literature corpus based on selected parameters (e.g., journals, researchers, institutions, countries, or keywords) and their interrelationships (e.g., co-authorship, co-citation, or co-occurrence). These elements are depicted as nodes and edges within the bibliometric network, enabling the transformation of quantitative bibliometric data into qualitative insights [38]. In our study, we constructed a keyword co-occurrence network based on keywords extracted from publications within the SMT literature from the past thirty years (1992–2020). To determine the relationships between keywords, we counted the number of co-occurrences—that is, instances where two keywords appear together in the keyword list of a single article—and established links accordingly. In this bibliometric network, the nodes represent keywords, while the edges represent co-occurrence relationships between them.
In our study, the network was constructed using VOSviewer 1.6.15 (https://www.vosviewer.com/, accessed on 25 May 2020), an open-source software tool for bibliometric network creation and visualization. We utilized bibliographic data from the Web of Science to form a network of nodes representing keywords (using the keyword co-occurrence technique). The size (or weight) of each keyword’s circle in the network increases with its frequency of occurrence in publications. Likewise, the strength of the link between two keywords corresponds to the frequency with which they co-occur in the same publications.
By default, VOSviewer assigns keywords in the network to clusters based on the strength of their links. A cluster is defined as a set of closely related keywords, with areas of high link density denoted by the same color. This process allows for the identification of research topic clusters. Each keyword in the network is assigned to exactly one cluster, and the number of clusters is determined by a resolution parameter [29].
To create the bibliometric network, we began by identifying the SMT literature through the Web of Science (WoS) database. We selected publications that explicitly referenced any of the terms “sustainable mobility”, “sustainable transport”, or “sustainable transportation” in their title, abstract, or keywords (The following data provide the full picture of our initial search at WoS. Search in: Web of Science Core Collection, Field of research: all fields, Language: English, Search strings: “sustainable mobility” OR “sustainable transport” OR “sustainable transportation”, “Time period”: 1970–2020). This search, conducted on 30 April 2020, yielded 2230 records for the selected time period Only articles published in peer-reviewed journals (including articles, reviews, and early access publications) were considered, while all other publication types were excluded. Our final corpus included 2084 articles. This corpus, referred to as the “total population”, was analyzed using VOSviewer software. A map was created, and a mapping analysis was conducted.

2.2. Descriprion of Thematic Content Analysis

Thematic analysis is a qualitative analytic method that enables researchers to identify and analyze patterns or themes within qualitative data [39,40]. A key characteristic of thematic analysis is its lack of attachment to any particular epistemological or theoretical perspective (e.g., grounded theory), which makes it a highly flexible method.
Although thematic analysis is often categorized as a type of content analysis [41], it differs primarily in that the themes identified through thematic analysis are typically not quantified, as is occasionally the case in traditional content analysis. The common feature between thematic analysis and content analysis is that both involve the process of transforming raw data into a standardized form (i.e., codes), which are then used to generate themes or categories through the generalization and connection of the codes [30,42]. However, in some studies, the two methods are referred to collectively as “thematic content analysis” [43], a term that will be used in this study. It is important to note that thematic analysis has been applied (either explicitly or implicitly) in the literature of fields such as arts and humanities, life sciences and biomedicine, and social sciences. However, we did not identify any research that explicitly employs this type of analysis within the fields of technology, energy sciences, or transportation studies.
The thematic content analysis begins with the identification and coding of data, ultimately leading to the construction of themes. The codes represent the most basic segments, or elements, of the raw data, which are constructed at the discretion of the researcher as they analyze the text, focusing on either semantic or latent content [41]. Through the analysis and synthesis of these codes, the researcher aims to identify patterns or meanings that can connect and unify seemingly unrelated groups of words—such as the codes—in order to construct coherent themes.
In our research, the “unit of analysis” was each article included in the “most-cited group”. The codes extracted from each article were related to its content, including its central idea, research questions, conclusions, and methodology. The codes (and subsequently the themes) were primarily developed based on the analysis of the “semantic” content of each article. By “semantic”, “manifest”, or “explicit” content, we refer to the visible, surface-level content, in contrast to “latent” content, which pertains to the “underlying” or “interpretive” meaning of the content [30]. We did not use pre-set codes; instead, we developed and refined the codes throughout the coding process. Themes were then created through a form of inductive reasoning or inductive inference, specifically “inductive generalization”. “Inductive generalization is a defeasible type of inference which we use to reason from the particular to the universal” [44]. The development of codes and themes was initially carried out independently by all three researchers, followed by extensive and repeated reflective discussions to finalize the codes and themes presented below. The overall process incorporated certain minimum characteristics of an inter-rater reliability (IRR) procedure [45].
The thematic content analysis in our study followed the steps outlined in [40]. The specific steps were as follows: Phase 1: Familiarizing with the data. Phase 2: Generating initial codes. Phase 3: Searching for themes. Phase 4: Reviewing and refining themes. Phase 5: Defining and naming themes. Phase 6: Producing the report analysis.
The thematic content analysis was applied to a subset of the total population of the literature, specifically the “most-cited group”, using the procedure described below. From the “total population”, we explicitly and clearly selected a much smaller subset for thematic analysis, based on the human resources and time available. To this end, we ranked the articles in the “total population” according to the “citations number”, as indicated by the TC index: Web of Science Core Collection Times Cited Count (The Times Cited count displays the total number of times a published paper was cited by other papers within Web of Science Core Collection, https://images.webofknowledge.com/images/help/WOS/hp_times_cited_count.html, accessed on 3 March 2022). We selected the top 220 articles—corresponding to approximately the upper decile (the top 10%) of the “total population” based on the TC index. This group was considered to represent the “most influential” portion of the literature, which we named the “most-cited group” (see Supplementary Material).

2.3. Description of Bibliographic Narrative Construction

As a continuation and expansion of the thematic analysis of the “most-cited group”, we proceeded to construct narratives and sub-narratives by analyzing the articles on a latent level, rather than solely on the semantic level (as was primarily undertaken during the thematic analysis). In latent-level analysis, the aim is to interpret the content of the articles, identify underlying ideas, hypotheses, and theories, uncover broader and more complex patterns and implications, and assign meaning by synthesizing different elements from various articles [30].
The creation of narratives (and sub-narratives) was intended to contribute to our effort to assign meaning not only to the entire literature of the SMT field, but also to individual aspects of it, as expressed through the themes that emerged from the thematic content analysis. This is the primary reason that, from this point onward, when we refer to the “synthesis” of the thematic content analysis and the creation of narratives and sub-narratives, we will use the term “in-depth content analysis” [46,47,48] (The term “in-depth content analysis” does not have an established definition in the literature and is used in different contexts and in a different way which, however, definitely includes the technique/method of content analysis. In our study the term is used in the way we have described).
The concept of narrative in the literature has evolved over the years, starting from the original notion of “oral narrative” or “storytelling” [42], and has been applied in many fields of study. It has been used in the social sciences [49,50], in the field of “Communicating Science” (as a “science narrative”) [51,52,53], in discourse analysis studies concerning energy policy [54,55], and more recently in the broader field of transportation studies [25].
Typical definitions of narrative could include the following: “a distinct form of discourse” … “as a retrospective meaning making” … “a way of understanding one’s own and others’ actions, of organizing events and objects into a meaningful whole, of connecting and seeing the consequences of actions and events over time” [42] (p. 947). In this text, we use the concept of narrative as a form of “storytelling”, where the aim is to assign meaning to “something”. In our study, this “something” is the literature of the SMT field. In other words, we use the concept of narrative to assign meaning to the SMT field, and more specifically, we employ the terms bibliographic narrative and sub-narrative to assign meaning to the themes identified through the thematic analysis of the “most-cited group”.
The designation “bibliographic” is adopted because our narratives are used to make sense of the SMT literature. Essentially, each separate sub-narrative answers the question, “What is the semantic story that links the specific themes to the SMT field?” The different sub-narratives we developed tell distinct stories, with which researchers from various scientific fields and disciplines connect their areas of research to the SMT field. Through these sub-narratives, central ideas, methods, observations, reflections, and conclusions are identified. Therefore, the narratives and sub-narratives are primarily told by researchers in the SMT field, although they are occasionally “borrowed” by policymakers, entrepreneurs, or other social or political actors.
The usefulness of bibliographic narratives and sub-narratives in our study is multifaceted, as they are directly related to our research questions. Their key contribution lies in assigning meaning to the entire SMT literature by uniting its seemingly disparate parts into coherent storytelling. These narratives can help new researchers orient and navigate the vast and complex field of SMT. Additionally, they can facilitate communication and collaboration among researchers from various scientific disciplines who have engaged with the SMT field in recent years.
It is important to note that for both the thematic content analysis and the creation of narratives and sub-narratives, we focused on the “most-cited group”. However, during the reflection that accompanied our analysis, we also consulted the literature outside the “most-cited group”, which assisted us throughout the analysis, discussion, and conclusion phases of the study.
The methodological approach described above can be summarized as follows: Given the large volume of literature to analyze (“total population”), we determined that we could not rely exclusively on qualitative methods. We chose to begin with bibliographic network visualization, creating a network and clusters to obtain an initial “bird’s eye view” of the literature [56,57]. Next, we systematically selected a smaller subset of the literature (“most-cited group”) to perform a content analysis and highlight the main bibliographic themes. To further relate the results of the content analysis to our research questions, we proceeded to construct narratives and sub-narratives. Finally, we interpreted the findings from one method in relation to the other, thereby enhancing the credibility of our analysis according to the logic of “triangulation” [32].
Figure 1 visualizes the research design and execution process described above.

3. Bibliometric Network Visualization of the SMT Literature

3.1. Preliminary Data Description

The key findings from the statistical description of the “total population” are presented below. Figure 2 shows the number of articles published per year. The exponential growth of articles in the last decade, especially from 2017 onwards, is evident. The small number for the year 2020 is because it only covers the first four (4) months of 2020, as our statistical population was collected on 30 April 2020.
Figure 3 shows the first 20 WoS categories to which the articles belong. Every record (article) in the WoS core collection contains the subject category of its source publication in the WoS categories field. In Figure 3, it is clearly seen that “transportation” is the largest category in the “total population”. It should be noted that “transportation”, along with the categories “transportation science technology”, “engineering civil” and “regional urban planning” are related to the “traditional” scientific disciplines of transportation, i.e., transportation scientists and engineers, civil engineers, urban planners. Categories related to the environmental component of SMT, such as “environmental studies”, “environmental sciences”, and “environmental engineering”, also have a strong presence. Finally, evident is the presence of other categories related to the “technology” research area associated with engineers outside the “traditional” scientific disciplines, such as electrical/electronic engineers and chemical engineers.
Figure 4 shows the first 20 countries/regions from which the articles originate. Data are extracted automatically from the “Addresses” field within records (articles) on the WoS database and refer to the “Country/Region” tab. Figure 4 shows that the vast majority of academic and research groups researching the SMT field belong to countries/regions from the so-called Global North. Only five countries/regions belong to the so-called Global South (People’s Republic of China, Brazil, India, Turkey, Taiwan).

3.2. Bibliometric Network Visualization

As previously explained, the articles belonging to the “total population” of the SMT literature were entered in Vosviewer, and their keyword co-occurrence map was created. This map provides information on the structure of the literature through the keywords (illustrated as circles) in publications. In our case, 7551 keywords were initially detected, of which 257 passed the limit of having a minimum of 10 occurrences and entered the map. In order to make the map clearer, we followed a procedure common in the relevant literature [23], omitting from the visual mapping of the network seven keywords that had the highest frequency of occurrence (namely, transport, transportation, sustainable transport, sustainable mobility, mobility, sustainable transportation, and sustainability).
The network visualization appearing in Figure 5 indicates that the SMT literature is organized in three clusters. The significant keywords contained in each cluster have many occurrences that create powerful links. The combination of the significant keywords and the set of keywords belonging to each cluster enable us to characterize the cluster. The names of the clusters were awarded according to our interpretation of each cluster’s composition, as follows:
(a) The “Technological” cluster (red) includes keywords related to alternative and innovative technologies, their systems, design, performance, and optimization.
(b) The “Change behavior–change mode” cluster (green) comprises keywords related to behavior change, attitudes, habits, changing transport modes, physical activity, health, alternative modes, bicycle, walking, and public transport.
(c) The “Policy, planning, and governance” cluster (blue) includes keywords related to policy, planning, urban planning, governance, accessibility, mobility management, land use, participation, smart city, frameworks, and indicators.
An analytical depiction of the three clusters through their significant keywords is available in Appendix A (Table A1). As can be seen from Figure 5, the clusters are distinct but there are many links between keywords of different clusters. A further analysis and the semantic correlation of the clusters with the SMT literature will follow in the Section 5, after the results of the thematic content analysis have been presented.

4. In-Depth Content Analysis

4.1. Thematic Content Analysis

This section presents the findings of the thematic analysis of the “most-cited group”, which was carried out with the procedure described in Section 2.2.
In Table 1, we present 21 bibliographic “themes” created by the thematic content analysis, which we believe describe and organize the content of the SMT literature. To better understand the elaboration of these themes, we briefly present how the theme “alternative fuels/technologies/non-electric vehicles” was created. From the set of codes recorded by the process of phase 1, a subset of codes was identified, based on the semantic content of each article, including the following: “hydrogen supply for fuel cell vehicles”, “blends of natural gas and hydrogen as a suitable “bridge technology” in vehicles”, “ producing biodiesel from plantations on eroded soils”, “evaluation of life cycle assessment (LCA)”, “environmental benefits/impacts of using bioethanol “, “biofuel/biomass to liquid fuel conversion processes”, “ producing biomethane for use as a transport fuel from various bio resources”, “construction of a model that evaluates the design and planning of a bioethanol supply chain” “possibility of replacing diesel with synthetic fuels”, “comparison of environmental impacts of gasoline, diesel and biodiesel using a life cycle assessment (LCA) methodology”, etc. From the subset of codes like the ones we mentioned above and using our judgment with the help of “inductive generalization” (see Section 2.2), we constructed the bibliographic theme “alternative fuels/technologies/vehicles (except electric vehicles)”. With the same procedure, all the bibliographic themes presented in Table 1 were constructed.
These bibliographic themes reflect our interpretation of the data analyzed through the thematic analysis process described above. The analysis of these themes and the attribution of meaning to them are presented in Section 4.2 through the creation of narratives and sub-narratives.
The question now is as follows: Is there a correlation between the bibliographic themes that emerged from the thematic content analysis and the three clusters that emerged from the bibliometric network visualization? Table 2 shows this correlation. The bibliographic themes are depicted in the first column, while the second column correlates each theme with the most relevant cluster. The third column shows some of the cluster’s keywords that can be meaningfully associated with the specific bibliographic theme.
The procedure carried out aimed to establish whether there are valid indications of a correlation between themes and clusters. The finding of a correlation would mean that the description and organization of the SMT literature (“total population”) carried out by the first method (bibliometric network visualization) at a higher level is compatible with the description and organization of a subset of the literature (“most-cited group”) by the second method (thematic content analysis). This provides robustness to the analysis of the SMT literature presented in this study, as the results of the two methods are compatible with each other (logic of triangulation) [32].
The procedure by which this correlation was made is presented below. The VOSviewer software categorizes the keywords into three clusters. The association of the keywords with the bibliographic themes was carried out by the authors. For this association, we considered both the content of each bibliographic theme that emerged from the thematic content analysis and the correlation of this content with the keywords contained in each cluster. Specific keywords are associated with one particular theme. However, some keywords semantically belong to more than one theme and have been classified accordingly (such as the keywords “accessibility”, “technology”, “energy”, etc.).
Most bibliographic themes are associated with a specific cluster. Nevertheless, some bibliographic themes (i.e., “public transport/transit transport”, “car sharing, carpooling, ridesharing”, “evaluation—indicators of sustainable mobility/transport”, and “transitions/MLP”) are associated with two different clusters (see Table 2). This occurs when part of the keywords explicitly associated with them belong to one cluster, and another part belongs to another cluster. For example, the theme “evaluation—indicators of sustainable mobility/transport” can be associated both with the “policy, planning, and governance” cluster (through the following keywords included in this cluster: decision-making process, dynamics, guidelines, indicators, monitoring, ranking, sustainability assessment tool, validation, etc.) and with the “technological” cluster (through the following keywords: algorithm, energy efficiency, environmental impact, environmental performance, life cycle assessment, optimization, quantitative analysis, sensitivity analysis, sustainability indicator, etc.).
The fact that some themes are “split” across two different clusters indicates that the conceptual–descriptive organization of the SMT literature (the “total population”) derived from the bibliometric network visualization is not identical to that obtained from the thematic content analysis of the “most-cited group”. This finding aligns with observations in the literature, which note that while bibliometric network visualization provides valuable insights, it also has limitations and must be complemented by content analysis to enhance analytical validity [29].
In conclusion, Table 2 clearly demonstrates that there is a correlation between clusters and themes, i.e., the semantic–descriptive organization of the SMT literature produced by the first method (bibliometric network visualization) is compatible with that produced by the second method (thematic content analysis).

4.2. Constructing Narratives and Sub-Narratives of the SMT Literature

We regard our effort to construct narratives and sub-narratives that assign meaning to the SMT literature as a deepening of the thematic analysis conducted on the “most-cited group”. The themes identified through this analysis gain interpretive significance through the narratives and sub-narratives we developed.
The thematic content analysis revealed that the notion of sustainability is most frequently conceptualized as an environmental challenge in the SMT literature, rather than as an economic or social one. Most articles share a central interpretation of sustainability in the transport system that primarily frames it in terms of mitigating environmental impacts, particularly greenhouse gas emissions. This emphasis on the environmental dimension is understandable, given the historical context in which the concept of sustainable mobility or transport has evolved. The Brundtland Report provides a widely accepted foundation for the concept of sustainability, defining it through three pillars—environmental, economic, and social. However, the environmental dimension has clearly emerged as the dominant focus in subsequent international and national debates, policy frameworks, and scholarly discussions [12,13].
Thus, the fundamental conceptual elements of the SMT field emerging from the “most-cited group” can be framed within a primary Major narrative centered on the environmental dimension of sustainability. According to this narrative, sustainable mobility or transport could simplistically be equated with identifying strategies to reduce greenhouse gas emissions produced by the incumbent motorized transport system, and doing so in ways that also account for economic viability and social justice. This perspective forms the foundation of the vast majority of SMT literature. If we accept that the notion of SMT is directly linked to emission mitigation, the central question becomes: “How can emissions mitigation be achieved?” According to our interpretation, the literature offers three main strategies—or bibliographic narratives—in response to this question.
Firstly, the “technology” narrative supports the view that less polluting and more efficient motor vehicles must be developed. This includes the advancement of new technologies such as electric vehicles, alternative-fuel vehicles, and autonomous vehicles, as well as the implementation of advanced traffic planning and control systems leveraging information and communication technologies (ICT). These innovations aim to manage traffic—particularly in urban areas—more efficiently. Within this technology-oriented narrative, the environmental dimension of sustainability is predominant, though it is occasionally linked to the economic dimension. The social dimension, however, is largely absent. The “technology” narrative is semantically related to the technology fix (tech fix) approach [58] (Technology fix approach is associated with effort the transportation system being made more sustainable using predominantly technological advances that improve the environmental and economic efficiency of transport systems’ operation [58] p. 30) and is governed by the ideological “doctrine” of “technological optimism [59,60,61]”.
Secondly, the “behavior change” narrative argues that achieving a more sustainable transport system requires a shift in passenger and commuter travel behavior. This involves transitioning to less polluting, alternative, or so-called action/healthy/slow modes of transport (e.g., cycling, walking), as well as an increased use of public transport. This narrative has a distinctly social character, evident in the subject matter it addresses, the scientific disciplines predominantly involved (e.g., sociology, psychology, etc.), and the research methods most employed (see the seventh sub-narrative below).
Thirdly, the “policy and governance” narrative argues that appropriate policies and planning methods—both for land use and for the organization of the transport system—as well as effective governance mechanisms should be pursued to facilitate changes in user behavior and promote a shift toward more sustainable modes of transport. Moreover, the necessary reduction in the number of trips—particularly those related to unnecessary travel—must be supported through coherent policies, integrated urban planning, and effective transport management, alongside the use of information and communication technologies (ICT). The evaluation, assessment, and monitoring of sustainable transport measures, policies, and strategies are enabled by the development and application of appropriate indicators, metrics, and frameworks.
The rationale underlying both the “behavior change” and “policy and governance” narratives does not dispute the important role of technology; rather, it acknowledges that technology alone cannot serve as the dominant factor in the transition toward a more sustainable transport system. Accordingly, these narratives may be characterized as “non-exclusively technology-oriented”. Furthermore, the significant semantic connections identified between them through in-depth content analysis support their classification as “socio-policy-oriented” narratives. These three narratives can be regarded as constituent components of the overarching major narrative within the sustainable mobility transitions (SMT) literature, each contributing to the construction of meaning within this field.
The description provided above, based on the “Major” narrative within the sustainable mobility transitions (SMT) field, does not aim to offer an exhaustive or fully comprehensive account of the entire body of literature. The thematic content analysis conducted in this study revealed a range of relevant topics that have been associated with the main bibliographic themes. These topics encompass various aspects of the environmental, social, and economic dimensions of SMT, including social equity, health and safety, quality of life, environmental integrity, the sustainability of local communities, transport resilience, infrastructure robustness, public participation and citizen education, and the enhancement of tourism’s contribution to local economies, among others. As such, these topics—along with additional ones identified during the analysis—have been synthesized into the following twelve (12) sub-narratives. These sub-narratives provide us the opportunity to delve into the analysis of almost all the bibliographic themes that were constructed through the thematic content analysis (As shown in Table 3, no bibliographic sub-narratives have been constructed for themes # 6 and # 7. For theme # 6 the articles included in ““most cited group” were only one for each mode -one for Planes, one for Ships, one for Trains- and it was obviously impossible to build a credible sub-narrative from such a limited sample. The construction of a sub narrative based on theme # 7 was beyond the scope of this article because its’ focus is on personal/passenger mobility/transport -as opposed to freight transport-. Moreover, the theme “freight transport” has some special characteristics and should be the subject of a separate article).
The protocol followed for the development of the twelve (12) sub-narratives involved the following steps: 1. Latent-level analysis of the “most-cited group” consisting of 220 articles. 2. Thematic consolidation, during which some of the original 21 bibliographic themes were merged. 3. Formulation of fundamental questions (see Key Questions in Table 3) that link each of the twelve groups of bibliographic themes to the broader SMT literature and the three main narratives. 4. Synthesis of the twelve sub-narratives, based on the insights obtained from the previous steps and supplemented by expert knowledge of additional key articles in the SMT literature that were not part of the 220 most-cited articles (“most-cited group”), as presented in Table 3.
The sub-narratives are conceptually linked to the three main narratives of the “Major” narrative. Table 3 presents these sub-narratives, with a primary focus on passenger road transport. The association of the twelve sub-narratives with the three main narratives, as indicated in column 2, is suggestive rather than definitive. Accordingly, the term “principally associated” is used to denote a relative, rather than absolute, semantic connection. Furthermore, some sub-narratives are linked to more than one main narrative. This indicates that, while the initial construction of the major narrative and its three main narratives provides a useful descriptive framework for organizing and interpreting the literature, a more detailed analysis reveals sub-narratives that transcend these categorical boundaries due to the high degree of interconnection among them. Column 3 identifies the bibliographic themes corresponding to each sub-narrative, while column 4 presents key questions that encapsulate the main concerns and focus of each sub-narrative.
The description, key topics, and methods appearing in each sub-narrative are analyzed below.
1. Alternative fuels and electrified vehicles
According to this sub-narrative (associated with the themes «alternative fuels/technologies» and «electric vehicles»), sustainable mobility is possible not through conventional (fossil fuel) vehicles, but through alternative-fuel (e.g., biofuel, hydrogen) or electric vehicles (PHEVs, PEVs, BEVs). Because the environmental impacts of these alternative vehicles are lesser than that of conventional vehicles (For electric cars it is very important for judging how “green” are to indicate the energy mix of the electricity they use (i.e., whether electricity is produced from fossil fuels or low-carbon fuels or RES). Otherwise, the pollution will be transferred from the cities to the operating areas of the polluting power plants), their increased use would cause the transport system to become more sustainable. At the same time, efforts must be made to develop technical solutions that will improve the efficiency of current internal combustion engines and to produce more efficient and environmentally friendly mixtures of conventional and alternative fuels (e.g., biofuel with natural gas and other mixes usually called “transition fuels”). This sub-narrative follows the logic of the so-called tech fix, which argues that the transition to sustainable mobility is a matter of developing the appropriate technological solutions [62,63] (e.g., ”Fuel cell vehicles running on hydrogen are seen as the long term solution to enable sustainable mobility” [62], or “…the electrification of automotive powertrains is clearly the principal path towards sustainable transportation” [63]). The majority of the articles in this category are permeated by an “ideology” of “technological optimism” [60], and other dimensions of SMT are either absent or appear in the margins.
Regarding biofuels, the articles address the production of biofuels from various raw materials (e.g., sugars [64], microalgae [65], etc.), the environmental impacts of various biofuels (e.g., [66,67], biomethane [68]), and comparisons of conventional fuels and biofuels using life cycle assessment (LCA) and life cycle sustainability assessment (LCSA).
Concerning hydrogen as an alternative fuel, articles discuss technical–economic problems arising from efforts to optimally store hydrogen in vehicles (which is associated with safety issues as hydrogen is a highly reactive and flammable gas) [62,69]. The study of transition fuel technologies, i.e., “bridge technology” (e.g., mixing hydrogen and natural gas) [70], and the use of solar energy for hydrogen production [71] are also discussed.
Regarding the theme “electric vehicles”, the articles focus on technical aspects related to the operation and infrastructure of electric vehicles, like technology and infrastructure for charging batteries [72,73] (e.g., wireless power transfer) [74]), Vehicle-to-Grid (V2G) networks [75,76], and the assessment of conventional technology vehicles and alternative technologies (mainly electric), either through the LCA method [77] or through the LCSA method [78].
However, there are articles which, although they can be included in the specific sub-narrative (and more broadly in the “technology” narrative), at the same time express concerns related to the “behavior change” and “policy and governance” narratives. For example, in these articles, policies for the development of alternative transport fuels [79] are studied, the logic of expectations in the field of alternative fuels [80] are analyzed, policies implemented in California and France (in the 1990s and beyond) for the development of electric and hybrid vehicles are compared [81], and the commercialization of electric vehicles in Shenzhen (China) by focusing on business innovation and its regulatory context are studied [82].
The methods, frameworks, perspectives, and approaches that are associated with this sub-narrative are predominantly technical and laboratorial in nature. The most common method or approach is the primarily quantitative approach of life cycle assessment (LCA) and its variations. There are also numerous laboratory quantitative methods, especially chemical ones (laboratory chemical technology procedures, thermodynamic process analysis, solar thermochemical procedures, oil extraction techniques, etc.), and there are computational, mathematical methods and frameworks (mixed-integer linear programming modeling framework, integrated optimization framework, etc.), but also other mixed (qualitative and quantitative) approaches such as the multi-criteria optimization approach, scenario building approach, etc.
2. Energy and emissions
An alternative title for this sub-narrative (which corresponds to the theme of the same title) could be “The Problem of Gaseous Emissions from All Perspectives”. This sub-narrative follows the logic that, since the main issue of sustainable transport is the mitigation of gas emissions, it is essential to study emission reduction from all angles. Therefore, methodologies must be developed to accurately estimate the gas emissions and energy consumption of the transport sector at the city, regional, national, and even economic activity levels (e.g., tourism). Furthermore, methodologies, scenarios, and forecasting models for future energy consumption and gas emissions must be developed, along with policies and strategies aimed at achieving the desired outcomes.
The estimation of energy consumption and the gaseous emissions of the transport sector [83,84]; the study of technological ways to reduce emissions [85] (mainly related to increases in engine efficiency); the study of strategies and scenarios [86] for reducing emissions at different spatial levels, but also in a specific sector of economic activity (e.g., tourism [87]); and the creation of models for forecasting energy/fuel consumption [88], as well as the production of gaseous emissions (and/or other pollutants) in the transport sector (mainly road transport) are some of the topics covered in articles which are correlated with this sub-narrative.
An interesting finding of some articles is that measures, policies, and strategies of an exclusively technological nature are not enough to reduce emissions. More comprehensive and holistic strategies are needed in order for efficiency-increasing strategies to make sense [89], like the ASIF2 (Avoid–Shift–Improve–Finance) framework [90] or the tackling of the so-called rebound effect [83]. In articles like these, there seems to be a differentiation from the strict interpretation of the so-called tech fix that leaves room for the “entry” of a socio-policy approach in the SMT field. On a more abstract level, the above can be considered as interactions between the “technology” narrative and the other two narratives and will be discussed in more detail in a subsequent section of this study.
The methods/frameworks/perspectives/approaches that are correlated with this sub-narrative are almost exclusively of quantitative and mathematical types (e.g., prediction models, well-to-wheels analysis/life cycle inventory assessment, distance-based method, Genetic Algorithm Transport Energy Demand Estimation (GATEDE) model, etc.).
3. Decoupling
This sub-narrative (based principally on the theme “Decoupling—economic dimension of sustainable transport/mobility”) maintains that in order to make the transition to sustainable mobility, GDP growth must be disengaged both from transport volume (especially that of road transport) and increases in gaseous pollutants ((That is, to have “decoupling”. According to the OECD (Organisation for Economic Co-operation and Development) the term ‘‘decoupling’’ means breaking the connection between environmental pressure and economic performance [91]), as all indices show that in most countries there is a direct correlation between transport volume (and transport CO2 emission volume) and GDP growth (In other words, there exists a coupling between transport volume and GDP as well as a coupling between transport CO2 emissions and GDP). The causes of this phenomenon need to be studied in depth and effective strategies/policies proposed in order to tackle it radically [91,92]. The main question that arises from this sub-narrative is the following: can there be an increase in GDP and, at the same time, a reduction in transport pollutants to such levels that it would indicate a transition to a sustainable mobility system? In other words, could there be a decoupling of economic growth and environmental pressure? A part of the literature answers this question in the affirmative, but there are also opinions in the literature (which mainly come from the perspective of the degrowth approach [93,94]) that argue that it is not possible to decouple the economy from environmental loads to the necessary extent and also keep GDP growing, and criticize the approaches of so-called «decoupling» [95].
As for the proposed policies for “decoupling”, they primarily focus on the more effective development and utilization of technology, which is dominant in this sub-narrative. In this sense, it can be considered that this sub-narrative is mainly related to the “technology” narrative. Nevertheless, some aspects of the literature (e.g., proposed decoupling policies that involve dimensions not part of the so-called “tech fix”, such as policies that enhance demand management [91]) indicate that this sub-narrative also has affiliations with the “behavior change” and “policy and governance” narratives. Therefore, it could be positioned at the interface between the “technology”, “behavior change”, and “policy and governance” narratives.
The methods/frameworks/perspectives/approaches that are associated with this sub-narrative are almost entirely of the quantitative type (framework of the different aspects of decoupling, statistical analysis, quantifiable scenarios, Divisia index approach, etc.).
4. Traffic regulation
The fourth sub-narrative refers to the “optimization” of traffic flows through algorithms and traffic light regulation models, which are developed with the aid of information and communication technologies (ICTs), thus surpassing the “traditional model” of (urban) traffic regulation. The effective regulation of road traffic, especially in urban environments, contributes to sustainable mobility by simultaneously fulfilling environmental goals (reduced pollution due to lower fuel consumption) and social goals (improved quality of life, particularly in urban environments, due to reduced traffic congestion and accidents).
Articles associated with this sub-narrative address several topics of technical nature, including the development of traffic control strategies that adapt traffic control measures and optimize the performance of the traffic network [96], and the utilization of “Connected Vehicle Technology” for the regulation of connected (autonomous) vehicles in a node, achieved with advanced algorithms and controlled with simulations [97].
Τhis particular sub-narrative has a strong technical/technological character (i.e., intelligent transport systems) and can be attributed to the logic of tech fix. The methods/frameworks/perspectives/approaches that are correlated with this sub-narrative are entirely of quantitative and mathematical types (e.g., model-based predictive control (MPC), traffic flow model, emission model, fuel consumption model, simulation-based safety assessment model, traffic simulation model, etc.).
5. Alternative modes
This particular sub-narrative (related to the themes “bicycle, walking”, “e-bikes”, and “public transport/transit transport”) is associated with an increase in the rate of cycling and walking, known as slow/active/healthy modes (SAHM), and the reinforcement of transport modes that are (relatively) less polluting per passenger, such as public transport (PT). The argument of this sub-narrative is that in order to make SAHM and PT more attractive mobility choices for citizens, policies must be adopted to enhance the appropriate infrastructure for these modes of transport and remove the barriers that currently prevent citizens from choosing them.
The “alternative modes” sub-narrative follows a top–down, supply-side approach. The main actors are governments (at the local or national level) and policymakers who design and implement policies to make alternative transport modes (SAHM and PT) more attractive to the public, as well as to optimize multimodal urban transport systems.
Concerning the “bicycle part” of this sub-narrative, a fundamental point acknowledged by the majority of articles is that policies aimed at substantial increases in bicycling require the integration of many complementary interventions, including infrastructure provision and pro-bicycle programs, as well as supportive land use planning and restrictions [98]. Important topics identified in this section of the literature are the need to combine bicycle use with public transport (bike and ride) [99], issues of cyclist safety (which present a significant barrier to the expanded use of bicycles) [100], different aspects of bike share initiatives, models, and schemes [101,102], as well as the relationship between bicycles and the built environment, considering the influence that the latter has on decisions concerning mode of transport, specifically the dilemma of whether to use a “car or bicycle” [103,104]. This relationship between built environment and cycling or walking (which can also be seen as the relationship between built environment and transportation choice) connects the themes “bicycle, walking” “changing transport mode”, and “attitude, behavior” with the theme “land use planning, urban forms”, and is an indication of the interrelation that exists between themes and sub-narratives that are correlated with the “social” and “policy, governance” narratives.
In the articles that are associated with theme “e-bike”, the special features of e-bikes correlated with advantages and disadvantages, opportunities, and threats are analyzed [105], as well as how these features are perceived and judged by users [106,107].
Concerning the “walking part” of the theme “bicycle, walking”, the main conceptual ideas appear relate to the idea of walkability [108], the relationship between the modal shift from car to public transport, the contribution of “walking” to increases in daily physical activity and improvements in public health [109], and the importance of walking for the purpose of specific short trips, namely the journey-to-school trip [110,111].
The correlation of SMT with public transport is displayed via the environmental interpretation of sustainable mobility policies, such as the reduction in gas emissions. Because the proportion of emissions per commuter is much lower for all modes of public transport (buses, trams, subways, trolleys, city rail, metro/U-Bahn) compared to the private car, a gradual shift in favor of public transport will curb emissions. This, combined with the introduction of “greening” technologies (mainly in buses, as other fixed-track public transport modes are powered by electricity), such as electric propulsion or alternative fuels, will further lessen pollution. Moreover, a shift of passengers to public transport would reduce traffic congestion, which is associated with quality of life and the social dimension of sustainability.
Finally, the development of public transport support policies has positive “side-effects” for other aspects of sustainable mobility. One of them is the combination of public transport with slow/active/healthy modes (walking, bicycle). In the literature, various combinations of sustainable transport modes appear, like “bike and ride” [99,112], or the combined operation of bus lanes and exclusive lanes for bicycles and pedestrians [113]. Other topics discussed in articles associated with the theme “public/transit transport” are bus rapid transit/BRT [114,115], the correlation between public transport and tourism [116], and the importance of public transport in the Global South [117].
Overall, we would say that the desired “mode shift” of users to public transport is often linked (explicitly or implicitly) with the improvement of quality of life in cities, a prominent social dimension of sustainability. This becomes especially clear in studies on urban development and land use, like those about transit-oriented development (TOD) [118,119,120]. The notion of TOD is one of the connecting links between the bibliographic themes “bicycle, walking”, “public transport/transit transport”, “changing transport mode”, and “attitude, behavior” and the themes “land use planning, urban forms” and “policies, planning, governance”.
The methods/frameworks/perspectives/approaches that are correlated with this sub-narrative are of both qualitative type (e.g., agency theory, exploratory analysis, practice-based framework, survey approach, focus groups, practice theory, activity-based approach, etc.) and quantitative type (e.g., prediction models, multi-level logistic regression, mixed-integer linear programming, multi-periodic optimization formulation, multivariable multinomial regression models, nested logit model, etc.) but also mixed type (e.g., multi-criteria evaluation analysis, etc.).
6. Motorized shared mobility
This sub-narrative is associated with “ridesharing” (as a general term for “motorized shared mobility”). The rationale that correlates ridesharing with sustainable mobility has two dimensions. The first is environmental and refers to reducing emissions per commuter in cases where there is more than one passenger in a car. This dimension is mainly associated with “carpooling” and its variants, such as “vanpooling” [121,122], “collective ridesharing”, and “intra-household ridesharing” [123,124]. The second dimension concerns the transition from the dominant “car ownership model” to a model of specific and limited access to the use of a car (associated with certain behaviors and attitudes, as well as a system of general or specific values of individuals) that is expressed in different car-sharing patterns (e.g., P2P ridesharing [125]), related to the more general concept of Mobility as a Service (MaaS) [126]. These two dimensions are associated with changes in the travel behavior of citizens.
In the literature, the terms “car sharing” and “carpooling” are used quite often as forms of ridesharing. The term “carpooling” relates to the formation of a stable arrangement for community trips [127,128]. The term “car sharing” refers to more occasional arrangements and rentals that individuals might need [122]. The different forms of ridesharing are promoted by sustainable mobility policies, usually called “mobility management” or travel demand management (TDM), to stress the importance of demand management. Managing the demand side is achieved by using the transport system in the optimal way to fulfil mobile people’s needs [121].
The methods, frameworks, perspectives, and approaches that are associated with this sub-narrative are of both qualitative type (e.g., agency theory, practice-based framework, survey approach, focus groups, practice theory) and quantitative type (e.g., simulation study, mathematical model, multi-level regression model), but also mixed type (e.g., multicriteria decision-making approach).
7. Change behavior
This bibliographic sub-narrative is associated with the attitudes and behaviors of travelers, passengers, and commuters, as well as efforts to influence and change these behaviors so that alternative modes of transportation are preferred. The connection between values, habits, attitudes, and behaviors could be established through various theories and models (e.g., the Theory of Reasoned Action, the Norm-Activation Model, the Theory of Interpersonal Behavior [129]). The rationale of this sub-narrative is that the transition to more sustainable mobility patterns will be facilitated if people change their travel behavior. According to this rationale, SMT research and policies need to focus on behavioral patterns to understand the ways in which choices about transportation, traveling, and mobility are made and to configure the parameters that define these choices [130]. Various theories, such as the Theory of Planned Behavior [131] or the Value–Belief–Norm (VBN) theory [132], help in understanding mode choice.
Particularly important for policy makers is the design of appropriate policies enhancing changes in users’ travel behavior by shifting their preference towards slow/active/healthy modes (walking, bicycle) and public transport [131]. In order to make the design of such policies more effective, it is necessary to understand the relationship between all the variables (psycho-sociological, socio-demographic, situational, and so on) that can affect the choice of transport mode [133]. The peculiarity that the study of social, cultural, and psychological factors can have in terms of behavior change in the field of tourist transport (especially the attitude–behavior gap, which for some researchers is considered the major contributor to “tourism CO2”) [134] is the crux of the bibliography associated with the theme “travel behavior and tourism”.
A series of policy measures, commonly known as “travel/transportation demand management” (TDM) measures, have been proposed and implemented over the years to influence people’s behavior. Various combinations of either “hard”/“coercive” (e.g., increased cost for car use through congestion charging or control of road space) or “soft” (e.g., social marketing techniques or travel feedback programs) transport policy measures have been proposed [135,136]. “Soft” measures especially are designed to motivate individuals to voluntarily change their travel behavior to embrace more sustainable modes of mobility. The importance they have for TDM policies, as well as the many social and affective motives for car use, are highlighted in [137]. Studies that corresponds to the themes “changing transport mode” and “attitude, behavior” stress the importance of car-use habits in holding back an embrace of more sustainable modes of transport, and the importance of studying of how transport habits can be altered [138]. It is important to point out the inability of traditional transport modeling to predict the adjustments in people’s mobility behavior that occurs as a consequence of changes in road conditions (i.e., reallocating road space for the benefit of pedestrians, cyclists, or public transport users) [139]. One prominent trend in this specific literature is known as the segmentation approach, which studies clusters of mobile citizens as a basis for understanding and promoting behavioral change. This is carried out in order to make both the “push”/hard measures and “pull”/soft measures of SMT policies more effective [133,140,141].
The theme “gender” could be correlated with this sub-narrative, as the contemplations in articles relating to this theme focus on implicit questions like “how does gender affect behavior in matters concerning (sustainable) mobility?” (e.g., “how does mobility shape gender?” and inversely “how does gender shape mobility?” [142,143]). Some articles related to theme “gender” are also related to other themes, such as the theme “bicycle, walking” (mainly the bicycle component) [144] and the theme “social dimension of sustainable mobility” (mainly associated with the subject of equity [143] and social exclusion or gender inequality) [145].
The literature corresponding to this sub-narrative includes methods, frameworks, perspectives, and approaches that have both a qualitative character (e.g., qualitative questionnaire survey, qualitative interviews, situated social practice approach, sociocultural-psychological model of transport behavior, practice-based framework, etc.), as well as a quantitative character (e.g., discrete choice model, nested logit model, statistical regression analysis, binomial logit model, etc.). Several articles in this literature field include methods of both types (qualitative and quantitative), but the context in which they are used is primarily related to the wider field of social sciences.
8. Reducing car trips
This sub-narrative is associated with the themes “land use planning, urban forms” and “policies, planning, governance”. Its rationale is based on the assumption that reducing both the number of daily trips and the distances traveled offers a potential transition path to SMT. This, in turn, is strongly influenced by the structure of the city and land use patterns (In the literature is pointed out that there are some scholars who disagree with this view and consider that the correlation between travel behavior and city structure is overestimated and that other factors -besides the structure of the urban environment- influence more travel behavior -e.g., socioeconomic and attitudinal characteristics of people, or the hard and soft measures of TDM-. Complementary argument of these scholars is the so-called ‘self-selection bias’ i.e., people live in city centers because they prefer to travel less, not that they travel less because they live in city centers [146] pp. 141–142). The sub-narrative proposes that if workplaces, housing, public services, and other essential services are located within a relatively small radius, it would be easier for people to travel by slow/active/healthy modes (walking, cycling) rather than by motorized modes such as cars. Furthermore, it would be more convenient for people to use public transport instead of their private cars. Urban planning and compact city models align with this approach. Given the close link between transportation development and spatial and land use planning, it is desirable for land use planning policies and SMT planning policies to be integrated. Additionally, there is an urgent need to explore appropriate forms of governance (especially at the local level) for the implementation of policies that focus on transitions to more sustainable transport systems [147].
The literature recognizes a strong correlation between urban form and travel behavior, but has not yet formed a consensus on the causal link(s) that underlies it [148,149,150,151]. This shows, again, the “organic” relationship between the themes “changing transport mode”, “attitude, behavior”, “land use planning, urban forms”, “public transport”, and “bicycle, walking”, as public transport and slow/active/healthy modes (walking, bicycle) are associated with travel behaviors that contribute to a more sustainable transport system.
Various aspects of this sub-narrative can be detected in the literature that corresponds to themes “land use planning, urban forms” and “policies, planning, governance”. Some of the aspects that correlate with theme “land use planning, urban forms” are the following: the connection of SMT with the structure of the city and its land uses [152], the role of urban planning in assisting the transition to SMT [153], the nexus between transport and urban form in order to develop an eco-city (i.e., existing cities or new urban developmental cities that are more ecologically based and livable) [151], and the strong correlation of a city’s population patterns with commuting travel savings [154]. In developing countries, the mobility challenges are considerably different than those in wealthier, advanced countries. A number of case studies explore mobility challenges in developing countries through an investigation of the link between their forms of urban transport and land use, which is reviewed in [117]. The concept of accessibility provides a useful conceptual framework for the integration of transport and land use planning and is widely recognized as essential to the achievement of sustainable development [155].
The correlation of the themes “changing transport mode”, “attitude, behavior”, “land use planning, urban forms”, “public transport”, and “bicycle, walking” can also be seen in a series of articles (e.g., [117,156]), where it is demonstrated that the relationship between form, use, and density in urban development and their influence on human behavior and travel are key elements of many land use and transport policies. Transit-oriented development (TOD) is a concept that similarly relates to the aforementioned themes. TOD strategies and policies integrate land use and transport functions aimed at preventing urban sprawl and reducing car-based travel by increasing public transport and slow/active/healthy modes (walking, bicycle)”.
Other features of the literature related to the theme “policies, planning, governance” include the following: the connection between the Singapore story of land transport policy development and the pathway towards Sustainable Transport Planning (STP) [157], the organizational and institutional issues of urban sustainable transport policy integration and implementation mechanisms [158], public acceptance of these kinds of policies [159], the contradictory effects of sustainable passenger transport policies on every day and leisure travel, respectively [146], and the importance of addressing various interlinked “transport taboos” in order to design and effectively implement environmental ST policies in the European Union [160]. Urban sustainable transportation planning is the focus of [161] (potential policy measures for sustainable transportation system in Tel-Aviv) and [162] (urban sustainable transportation planning in a dynamically developing country like India). Various facets of integrative urban sustainable transportation planning and land use policies are studied in [156] (application of a new accessibility planning tool) and [163] (changes in transport and land use policies in Germany over the last 40 years based on a case study in the city of Freiburg), whereas in [158,164], the relationship between policies and governance is examined.
The methods/frameworks/perspectives/approaches that are correlated with this sub-narrative are more of the qualitative type (e.g., Delphi method, sustainability indicators approach, Value–Belief–Norm theory, new rural governance framework, scenario analysis, mobility biographies approach, etc.) and less of the quantitative type (e.g., accessibility model, GIS-based simulation tool, etc.) and mixed type (e.g., multi-criteria assessment (MCA), multi-criteria analysis, etc.).
9. Evaluation—assessment and indicators
This sub-narrative predominantly relates to the theme “evaluation—indicators of sustainable mobility/transport” and suggests that, since there is no consensus in the literature or among local, regional, national, and international actors on what constitutes the sustainability of transportation systems, there is a need for (a) constructing and developing indicators and metrics to evaluate and monitor both the sustainability performance of current transport systems [114,165,166] and the effectiveness of sustainable transport measures, policies, and strategies [147,167]; (b) evaluating and assessing the definitions, indicators, and metrics used to address sustainability in transportation [168,169]; and (c) employing frameworks and methods to identify and select small subsets of sustainable transport indicators from the vast number available in the literature [170,171,172]. The literature indicates that much research is still needed in the broader field of sustainable transport/mobility indicators, especially in the area of social sustainability indicators [23], as well as in the development of frameworks (and “meta frameworks”) that enable the effective selection and integration of sustainability indicators and measures into strategies, policies, and practices [173,174].
The methods/frameworks/perspectives/approaches that are associated with this sub-narrative are mainly of the mixed type (e.g., Evaluative and Logical Approach to Sustainable Transport Indicator Compilation (ELASTIC), sustainability footprint framework and model, analytic hierarchy process (AHP), ELECTRE multi-criteria approach, Index of Sustainable Urban Mobility method, Multiple Criteria Decision-Making (MCDM) approach) and less of the qualitative type (e.g., sustainability indicator approach, performance indicator framework, etc.) and quantitative type (e.g., additive weighted method, sustainability footprint framework and model, system dynamics model, etc.)
10. Transitions theory/MLP
By transitions theory, we refer to a series of theoretical frameworks that have been developed to study the so-called sustainability transitions [175], i.e., (1) the innovation systems approach to transitions [176]; (2) the multi-level perspective (MLP) approach [177] and the closely linked approach of strategic niche management (SNM) [178]; (3) transition management (TM) based on complex systems analysis [179]; and (4) evolutionary–economic views and multi-agent modelling of transitions [180]. According to [175], the separation between these various approaches is not clear.
The sub-narrative associated with the theme “transitions” is based on the socio-technical system approach of MLP, which “conceptualizes transport systems as a configuration of elements that include technology, policy, markets, consumer practices, infrastructure, cultural meaning and scientific knowledge” [181,182]. According to the MLP, the transport system is a “socio-technical” system, and major shifts of these systems are called socio-technical transitions. Transitions are seen as co-evolutionary processes of a range of actors, social groups, and structures, such as firms, consumers, legislation, technologies, and infrastructure, which take decades to unfold. Transitions are complex and dynamic processes that are shaped through the interaction of three different levels: niches (technological and market innovations), socio-technical regimes (rules, regulations, consumption patterns, dominant technologies), and an exogenous socio-technical landscape (financial crisis, wars, environmental crises, global sociopolitical trends, demography, migration, ideologies, etc.) [181,183].
The notion of “socio-technical” system refers both to material and non-material elements such as artifacts, market shares, infrastructure, regulations, consumption patterns, and public opinions. “Socio-technical” systems are actively created, (re)produced, and refined by social entities/actors like firms, universities and knowledge institutes, public authorities, public interest groups, and users. While the notion of a “socio-technical” system refers to material and non-material elements, the “regime” notion/term (introduced by the MLP approach) refers to the deep structural rules that coordinate and guide actor’s perceptions and actions [184]. The MLP identifies a dominant regime (auto-mobility), yet it provides sub-regimes that are related to mobility patterns and relevant infrastructures of specific communities. Such sub-regimes (e.g., train, tram, bus, cycling) can be in competition with the dominant regime [185].
The transitions theory/MLP sub-narrative focuses on the transition from the currently unsustainable transportation system to a more sustainable one. It uses MLP as an analytical framework to study and understand sustainable mobility transitions or quasi-transitions. Nykvist and Whitmarsh [10] use MLP to conceptualize three paths (technological change, modal shift, and reduced travel demand) via which a “transition to a more sustainable mobility system may be achieved”. In [186], a productive dialogue between MLP and geographical insights is presented. According to its authors, urban sustainable transitions are related to sociotechnical processes and policies of the reconfiguration of urban spaces. A detailed description and classification of street experiments (as a version of transition experiments) and their potential to fuel changes in the direction of a transition towards sustainable urban mobility is presented in [187]. In [188], a reflection on the strengths and limitations of the MLP in the socio-technical transitions literature focuses on experiences applying MLP in the domain of sustainable transport research. The MLP has also been the analytical framework for simulation modelling approaches such as in [26] (assessing systemic innovations, or ‘transitions’, of societal systems towards more sustainable development) and [189] (novel simulation model for assessing transitions to SM).
The transitions theory/MLP sub-narrative can be considered the one that most comprehensively connects the “technology”, “behavior change”, and “policy and governance” narratives. This is because it is based on the multi-level perspective (MLP) theoretical framework, which conceptualizes transport systems as configurations of technical and social elements engaged in a process of continuous interaction [190]. In this sense, it can be classified as a socio-technological sub-narrative.
The methods, frameworks, perspectives, and approaches associated with this sub-narrative are primarily qualitative in nature (e.g., multi-level perspective, strategic niche management, socio-technical scenarios, transition management, backcasting approach, innovation systems framework, etc.). However, some quantitative or mathematical approaches are also employed in certain cases (e.g., simulation models, system dynamics, agent-based modeling techniques, etc.).
11. General and theoretical
This sub-narrative, correlated with the bibliographic theme “general–theoretical”, is focused on understanding what Sustainable Mobility and Transport (SMT) means in urban environments, as well as identifying the key policy elements necessary for transitioning to sustainable transportation systems.
The central idea of this sub-narrative is that the transportation system of the 20th century is unsustainable. There is an urgent need for a transition to a more sustainable transport system (a low- or no-carbon system), and this transition must be accelerated through an appropriate mix of policies that combine technological solutions with changes in the mobility behavior of citizens.
In articles associated with this sub-narrative, various perspectives and theoretical frameworks concerning SMT policies are presented. Despite the diversity and variety of topics, a common finding of the majority of articles is that technological innovation alone is not the sole answer to the problem of climate change [11,191,192], but behavioral change is also necessary if the benefits of new sustainable mobility technologies are to be fully realized. Policy leaders’ efforts to secure the future of the present transport system of high mobility (a less carbonated version of it) exclusively via technological solutions are criticized, and a vision towards a low-mobility future is proposed [193]. Since 2008, Banister [11] has presented and later further developed [192,194,195] the so-called sustainable mobility paradigm, which is a point of reference not only in his own articles, but also in many articles in the SMT field. In his own words “…The sustainable mobility approach requires actions to reduce the need to travel (less trips), to encourage modal shift, to reduce trip lengths and to encourage greater efficiency in the transport system”. The above can only be achieved through a combination of technological innovations and land use planning policies. With similar reasoning in [147], it is argued that achieving more sustainable transportation requires a suitable establishment of policies based on four pillars: (1) governance, (2) funding/financing, (3) infrastructure, and (4) neighborhoods. Some authors try to link general principles of sustainability with transport systems in order to trace policy directions towards sustainable mobility [196].
Very interesting is the criticism of the car-centric system of cities in [197], where it is analyzed how the “invasion” of the car into cities brought about “awesome consequences” for social life (through the reconfiguration of urban life, which involves “distinct ways of dwelling, traveling and socializing in, and through, an automobilized time-space”). The reaction to this “civil society of automobility” should be (according to the authors) the redesign of cities with a vision for the future accompanied by appropriate policies that could “save towns and cities from this awesome Frankenstein-created monster of ‘auto’ mobility”.
European Union policies on SM in the 1990s are the focus of [198], which answers the question “what kind of policies should be implemented at the EU level in order to lead to a more sustainable system?” via the presentation of four policy strategy directions. These include (1.) demand-oriented policies, (2.) supply-oriented policies, (3.) technology policies, and (4.) physical planning policies and land use regulation. In [160], the concept of “transport taboos” («i.e., issues that constitute cognitive and affective barriers to significant decarbonisation of transport systems, as they constitute a risk to decision makers, who would be viewed as violators of norms and values.») has been used as a partial explanation for the failure of EU policies to reduce greenhouse gas emissions from transport.
The methods/frameworks/perspectives/approaches that are correlated with this sub-narrative are exclusively of the qualitative type (e.g., sustainable mobility paradigm framework, ecological economics perspective, transition management perspective, niche development perspective, scenario-building approach, low-mobility approach, etc.). Among the above approaches, the “sustainable mobility paradigm framework” is the one that holds the most prominent position.
12. Social Sustainability
This sub-narrative, corresponding to the theme “social dimension of sustainable mobility”, relates to the social dimension of sustainability and its adaptation to the SMT field. Some researchers argue that only a small portion of the SMT literature explicitly addresses the social dimension, while more often it appears implicitly [199]. This sub-narrative connects the transition to sustainable mobility with the in-depth study of (a) the social aspects of the current, well-entrenched unsustainable transport system, (b) the social dimensions of sustainable mobility and their interconnections with environmental and economic factors, and (c) the social consequences of the policies proposed or implemented as part of the transition paths to sustainable mobility. The social dimension of sustainability includes issues such as social exclusion, social equity, and social justice [200] (in different contexts and environments, as well as in different regions of the Global South and North), and their reflection both in the transport system and in the notions of mobility and accessibility.
The concepts that prevail in articles associated with this sub-narrative are those of transport/mobility poverty [201], environmental equity in transport/mobility systems [202], transportation equity [203], and the Framework for Strategic Sustainable Development (FSSD) [204].
The methods/frameworks/perspectives/approaches that are correlated with this sub-narrative are almost exclusively of a qualitative nature (e.g., Political Ecology of Health theoretical framework, Framework for Strategic Sustainable Development, Focus Group Discussions Approach, etc.) with minor exceptions of quantitative approaches (e.g., dynamic models).

5. Discussion

The aim of this study was to identify and analyze the main structural elements (i.e., clusters and themes) and interpretive elements (i.e., narratives and sub-narratives) that constitute the Sustainable Mobility and Transport (SMT) literature of the past three decades, as well as the interrelationships among them. This analysis provides a comprehensive configuration viewed from a sociotechnical perspective—that is, with a focus on the interactions between society and technology as manifested in the SMT literature.
We define this integrated synthesis—encompassing clusters, bibliographic themes, narratives, sub-narratives, and their interconnections—as the “conceptual image” of the SMT literature of the last 30 years.
In the following subsections, we discuss some critical issues of our analysis.

5.1. Correlation Between Results of Bibliometric Network Visualization and In-Depth Content Analysis

The bibliometric network visualization of the total population revealed that the entire body of SMT literature is divided into three major clusters: (a) the technological cluster, (b) the change behavior–change mode cluster, and (c) the policy, planning, and governance cluster. From the thematic content analysis of the most influential subset of the total population (i.e., the most-cited group), we identified 21 main bibliographic themes (see Table 1).
As a natural extension and deepening of the thematic analysis, we developed a Major narrative, from which three main narratives emerged: technology, behavior change, and policy and governance. We then formulated 12 sub-narratives that provide a more detailed analysis and interpretation of nearly all the bibliographic themes (see Table 2).
Each of the three main narratives—technology, behavior change, and policy and governance—is directly associated with one of the three clusters and serves to assign interpretive meaning to them (see Figure 1). Similarly, the 12 sub-narratives are linked to the corresponding bibliographic themes (see Figure 1 and Table 3).
The connection between the narratives and the clusters was established by combining the results of the bibliometric network visualization with those of the thematic content analysis. The main and associated keywords of each cluster, derived from the first method, were semantically linked to the codes, topics, methods, research questions, and concepts that emerged from the second method.
For example, to link the technology cluster to its corresponding main narrative, we utilized a range of relevant keywords (e.g., air pollutant, algorithm, alternative fuel, biodiesel, biofuel, biomass, carbon dioxide emission calculation, electric vehicle, emission, emissions reduction, energy efficiency, energy consumption, environmental impact, external cost, fuel cell vehicle, fuel consumption, hybrid vehicle, hydrogen, life cycle, life cycle assessment, natural gas, optimization, performance, plug-in hybrid, road traffic, vehicle emission, etc.) that were meaningfully linked with codes (e.g., “biofuel/biomass-to-liquid fuel conversion processes”, “evaluation of life cycle assessment (LCA)”, “comparison of environmental impacts”, “hydrogen supply for fuel cell vehicles”, etc.) and with methods or techniques (e.g., life cycle assessment, well-to-wheels analysis, simulation-based safety assessment model, Genetic Algorithm Transport Energy Demand Estimation, etc.).
The same procedure was applied to establish the connection between the other two clusters and their corresponding narratives. Furthermore, all bibliographic themes were associated with the three clusters, as described in Section 4.1 (see Table 2).
The conclusion drawn from the above-described correlations is that the “conceptual map” of the SMT literature derived from bibliometric network visualization—represented through the network of keywords and the formation of clusters—is compatible with the “conceptual map” resulting from the in-depth content analysis, represented through the development of bibliographic themes, narratives, and sub-narratives. These two analytical approaches complement and reinforce one another, contributing to a comprehensive and robust description, organization, and interpretation of the SMT literature.
We argue that the integrated synthesis of clusters, bibliographic themes, narratives, sub-narratives, and the relationships among them constitutes a coherent “conceptual image” of the SMT literature and assigns interpretive meaning to its structure and evolution.

5.2. The Relationship Between Clusters, Narratives, and Remarkable Approaches in the SMT Literature

The three bibliographic clusters that structure the SMT literature exhibit strong semantic similarities with prominent approaches identified in the SMT literature concerning policies and strategies aimed at reducing air emissions—one of the primary environmental goals in the transition toward a more sustainable transport system. The three main policy approaches for reducing transport-related emissions—(1) improving technology, (2) changing travel patterns, and (3) reducing travel volume [8,124]—as well as the sustainable mobility paradigm—(1) enhancing efficiency in the transport system, (2) encouraging modal shifts, and (3) reducing the need to travel and shortening trip lengths [171]—broadly correspond to our three bibliographic clusters.
Specifically, the first two approaches align with the “technology” and “change behavior” clusters, respectively, while the third is a core component of the “policy/governance” cluster. A key contribution of our study is the establishment of this connection between the conceptual structure of the SMT literature and these influential strategic frameworks.
Furthermore, the three bibliographic clusters identified in our study correspond to the three vertices of the Social Change and Sustainable Transport (SCAST) triangle [205] (Figure 6), and can be interpreted as follows: achieving sustainable mobility requires changes in technology (red cluster) and individual behavior (green cluster), both of which must be supported by an appropriate mix of policies and governance (blue cluster).
In terms of the correlation between our bibliographic narratives and sub-narratives and the grand narratives and sustainable mobility narratives proposed by Holden et al. (2020) [25], we observe minor similarities in content, alongside important differences in their nature, scope, and purpose. Table A2 in Appendix B provides a detailed comparison between the narratives identified in this study and those of Holden et al. (2020) [25].

5.3. Segmentation and Interaction, or “Far Away, Yet So Close!”

Despite the diversity and complexity of the SMT field, it is clear that the SMT literature is divided into three distinct clusters: “technological” (red), “behavior change–change mode” (green), and “policy, planning, and governance” (blue) (see Figure 5). These clusters correspond to the three main narratives: “technology”, “behavior change”, and “policy, governance”. However, this classification does not imply that the three clusters and their associated narratives are isolated from one another. Both the bibliometric network visualization (which addresses clusters) and the in-depth content analysis (which addresses themes, narratives, and sub-narratives) suggest a network of interactions between the three clusters (and their corresponding narratives), creating “boundary” interfaces between them [206].
The interactions and connections are strongest between the green and blue clusters. In the bibliometric keyword network, many links connect keywords from these two clusters. This finding is further supported by the in-depth content analysis, which identified strong semantic correlations between themes and sub-narratives associated with the “behavior change” and “policy, governance” narratives. The most frequent connections involve the themes of public transport, transportation mode change, attitudes/behavior, land use planning/urban forms, and policies/governance.
We identified much weaker interactions and connections between the “technological” (red) cluster and the other two clusters—namely, the “behavior change–change mode” (green) and “policy, planning, and governance” (blue) clusters—compared to those between the green and blue clusters.
The above observations potentially indicate a relative isolation of “tech fix” approaches, which are directly related to the “technological” (red) cluster. The underlying causes of this isolation and their implications for future research are discussed below. The following remarks are based on two assumptions: first, that the “technological” (red) cluster is primarily associated with STEM (science, technology, engineering, mathematics) disciplines, while the other two clusters (“change behavior–change mode” (green) and “policy, planning, and governance” (blue) are principally associated with SSH (social sciences and humanities) disciplines; and second, that the interactions between clusters correlate with the cooperation between the disciplines and researchers associated with them.
The first underlying cause of the “technological” cluster’s relative isolation is related to the extensive differences between engineers and natural scientists (or STEM disciplines) on one side, and social and political scientists (or SSH disciplines) on the other, which hinder communication and interaction between them. These differences are rooted in the distinct scientific “cultures” and research paradigms that have evolved over time within the STEM and SSH disciplines. The differing “cultures” [207] are associated with contrasting methodological approaches (quantitative vs. qualitative; reductionism vs. holism), epistemological differences (objective vs. subjective knowledge; certainty vs. ambiguity), varying standards of evidence (experimental evidence vs. case studies), divergent collaboration norms (more hierarchical vs. more decentralized), differences in timeframes and scales (short-term projects vs. long-term trends), and distinct research goals (practical solutions to problems vs. understanding and explaining human behavior and social phenomena), among others.
The second underlying cause is related to the privileged position held by STEM disciplines in terms of research funding (compared to SSH disciplines) from both private companies and governments or supranational organizations (e.g., the European Union) [208,209]. Since funding is relatively sufficient for purely technological research projects, there is little economic or scientific incentive for STEM researchers to seek collaborations with researchers from the SSH field. In contrast, the majority of SSH researchers seek interdisciplinary collaboration not only for economic reasons, but also for epistemological ones [210,211].
The third underlying cause is related to the perceived superiority of STEM disciplines (particularly in society and decision-making centers), which seemed to prevail especially in the post-World War II period when “scientific triumphalism and technological optimism” dominated for several decades [210]. The prevailing belief among engineers and natural scientists was that science and technology alone could solve all global problems, leading to a “solitary summit” for STEM disciplines while simultaneously marginalizing the SSH to an “end-of-pipe” role in technical research and development [210].
The final cause directly reflects the preceding one within the SMT domain and is linked to the “ideology” of the tech(nology) fix [58,212,213] that permeates most of the literature in the “technological”/red cluster. Furthermore, this “ideology” resonates with a segment of policymakers and leaders, as well as with entrenched incumbent actors of the private car-centered transport system who can fund research and influence public opinion. The notion that the transportation system can become more sustainable using predominantly or exclusively technological advances significantly contributes to the “isolation” of STEM researchers within their own disciplinary silos. In contrast, a large portion of SSH researchers consider sustainable mobility/transport to be a “sociotechnical phenomenon” and seek cooperation with STEM researchers [214,215].
Given the aforementioned, we argue, in agreement with other researchers [215,216], that future research in the SMT field should become more robustly and deeply interdisciplinary (although in the last approximately ten years, there has been a strengthening of SMT interdisciplinarity [7,215]). In our study’s “language”, interactions between the three clusters should be more frequent, intensive, and profound. This can primarily be interpreted as a call for more extensive and deeper collaboration between STEM and SSH researchers. The following remarks contribute to this direction.
The significance of SSH in the development of technology itself and its integration into society has been extensively studied in the literature [217,218]. Furthermore, the increasing complexity of SMT issues has highlighted the shortcomings of narrow disciplinary approaches, leading to a demand for greater interdisciplinary and transdisciplinary research in this field [215]. This, in turn, translates into the “language” of our own study, supporting the need for both the quantitative and qualitative upgrading of cooperation between STEM researchers (related to the red cluster) and SSH researchers (related to the green and blue clusters). In practice, this demand can be supported by insights regarding the problems, obstacles, and prospects of STEM and SSH collaboration experiences through the implementation of national or European research programs [210,219,220]. The enhanced role that the European Union appears to be giving to SSH disciplines through the renewed Research and Innovation funding program Horizon Europe (2021–2027) [214], and their co-existence with STEM disciplines, can be leveraged, as “…targeted funding opportunities are an essential ingredient of successful interdisciplinary collaboration in research” [215]. Furthermore, for the first time, it is stated explicitly and categorically that SSH need to be effectively integrated across all clusters, missions, and partnerships of the Horizon Europe strategic plan [221].
To this end, our mixed-methods review allowed us to identify certain privileged areas in the SMT field where cooperation between STEM and SSH researchers could be strengthened and deepened. Some of these thematic areas initially emerged from the bibliometric network visualization and were confirmed by the in-depth content analysis, while others emerged directly from the in-depth content analysis.
A promising initial area is the identification and in-depth study of “unsustainabilities” (a new term for technologies, institutions, and practices that make or keep societies less sustainable [222]) in the SMT field. Potentially “unsustainable” technical innovations could include, for example, (electric) Sports Utility Vehicles (SUVs) [222], autonomous vehicles (AVs), etc. Especially for AVs [223,224,225], which are currently mainly studied from the perspective of a tech fix [226], a fundamental research question could be as follows: “Autonomous vehicles (AVs): opportunity or threat to sustainable mobility and transport?”
A broader and more diverse area for collaboration between STEM and SSH researchers is represented by ten core thematic units, related primarily (but not exclusively) to the development and implementation of SUMPs at a European level [227], or similar holistic sustainable urban transport planning schemes in non-European countries. These ten thematic units are as follows: 1. Stakeholders and Public Participation; 2. Transformative Power of ICT; 3. Mobility as a Service (MaaS); 4. SUMP and Sociotechnical Transitions; 5. Behavior Change and Mobility Patterns; 6. SUMP and Challenges of Governance; 7. Sustainable Urban Mobility Indicators (SUMIs); 8. Mobility, Justice, and Social Equity; 9. Sustainable Air Mobility; and 10. Sustainable Freight Transport.
A detailed description and analysis of the content of collaborations within the above thematic units falls outside the scope of this study. However, it could be the subject of further research, also utilizing the experience that exists in the literature from similar collaborations [208,210,219].
Cutting-edge technologies and innovations, such as autonomous and connected vehicles, Mobility as a Service (MaaS), and big data, are crucial for sustainable transportation by enhancing efficiency, reducing emissions, and optimizing resource use. Autonomous vehicles improve fuel efficiency and reduce congestion, while connected vehicles enable real-time traffic management, reducing idle times and emissions [228]. MaaS promotes shared mobility, reducing the need for private car ownership and optimizing transportation choices [229]. Big data enables better traffic management, predictive maintenance, and personalized mobility, leading to reduced energy consumption and more sustainable transportation systems [230,231]. Together, these technologies contribute to cleaner, more efficient, and environmentally friendly mobility solutions. These positive characteristics, along with the challenges they present [225,232], require broader and deeper research, particularly through collaboration between STEM and SSH researchers.

5.4. Policy Implications and Recommendations for Action

From the analysis of both themes and narratives, we can identify the following fundamental policy implications and recommendations for action in the direction of the sustainable development of transportation in the future. As far as the “technology” narrative is concerned, it is evident that while innovation in electric vehicles (EVs), smart infrastructure, and data-driven mobility solutions is accelerating, policy and governance often lag behind. Possible recommendations for action include (a) heavy investment in EV infrastructure (e.g., widespread charging stations), (b) supporting R&D and public–private partnerships producing low-emission transport technologies, and (c) the implementation of open data standards to enable integration across mobility platforms.
Regarding the “behavior change” narrative, it can be concluded that shifting individual and collective travel behaviors is critical and requires long-term engagement and incentives. Therefore, it is necessary to (a) launch systematic campaigns to raise awareness and promote public transit, walking, and cycling; (b) provide financial incentives or subsidies for sustainable travel choices; and (c) implement congestion pricing, low-emission zones, or other similar “light” measures.
Finally, with respect to the “policy, governance” narrative, we point out that fragmented governance structures often hinder coherent and integrated transport strategies. Thus, it is essential to (a) establish cross-sectoral governance bodies that align transport, environment, and urban planning policies; (b) set clear, measurable sustainability targets and monitoring frameworks; and (c) encourage participatory planning that includes decision-making communities (e.g., as attempted in the development of Sustainable Urban Mobility Plans [SUMPs]).

5.5. Limitations of Our Study and Future Research

The procedure used to select the initial set of 2230 articles inevitably excluded a portion of the literature that may address topics related to SMT without explicitly using the terms “sustainable mobility” or “sustainable transport/transportation” in their titles or abstracts. Furthermore, our “total population” consists exclusively of articles written in English.
Although the process we followed to create the “most-cited group” using the Total Citations (TC) index was straightforward, transparent, and well defined, variations in the TC index over time inevitably result in the formation of different groups at different points. Consequently, the “most-cited group” is not fully reproducible. Furthermore, using the TC index as a criterion for identifying the “most influential” segment of the literature may introduce a bias against more recently published papers.
It should also be noted that we did not utilize all the tools available within the bibliometric network visualization methodology (e.g., co-citation analysis, citation bursts, etc.). A more comprehensive analysis of the entire SMT literature employing advanced scientometric techniques could be a valuable subject for future research. Additionally, a more detailed investigation into the differences between natural or engineering science approaches and social science approaches in the SMT literature—through a comparative analysis of two distinct bibliometric network maps based on data from journals representative of each domain—would offer significant scientific insight.
With respect to the analysis of the literature through the 12 sub-narratives, we acknowledge that our study may not have captured all aspects of each theme. Additionally, as previously explained, we did not construct a sub-narrative for the bibliographic theme of freight transport—a gap that should be addressed in future research.
The notable absence of articles in the “most-cited group” explicitly addressing air mobility, and more broadly long-distance travel, warrants further investigation. The creation of a related sub-narrative should also be explored in future research. It is important to determine whether this absence is due to potential bias in the method used to select the “most-cited group”, or whether it reflects the literature’s tendency to treat this critical aspect of sustainable transport as a marginal issue. Regarding air mobility—an admittedly significant source of environmental pollution—this absence may signal a reflection in the literature of policymakers’ relative “reluctance” to adopt global policies that could limit air travel and encourage the use of more sustainable transport modes, such as trains [160].
Cutting-edge technologies and innovations, such as autonomous and connected vehicles [228], Mobility as a Service (MaaS) [229], and big data applications [233,234], have gained increasing prominence in recent years within the SMT literature. However, the scope and depth of coverage of these themes in this article—due to the broad time frame of this review—do not adequately reflect their importance for the present and future transition to sustainable mobility. This gap underscores the need for future, more systematic research on these topics.

6. Conclusions

Despite the vast and growing body of literature on Sustainable Mobility and Transportation (SMT) over the past three decades, few studies have provided comprehensive reviews of the entire field. Our research builds on existing reviews by employing a mixed-methods approach and an expanded bibliographic corpus to analyze the full scope of the SMT literature. This approach allows us to identify key structural and interpretive elements within the SMT literature, including clusters, themes, narratives, and sub-narratives, as well as their interrelationships, thereby enhancing the conceptual understanding of the field. While our mixed-methods approach has limitations, it offers valuable insights for analyzing large, multidisciplinary bodies of literature like SMT, both longitudinally and cross-sectionally.
Our research reveals that the SMT field draws upon expertise from a diverse array of disciplines. In addition to the well-established domains of transportation, environmental science, and engineering, it integrates insights from the social and political sciences, as well as interdisciplinary fields such as innovation studies and sustainability transitions. Furthermore, we identified substantial contributions from engineers and scientists in disciplines including electrical engineering, chemical engineering, chemistry, and physics—areas that have been underrepresented in previous literature reviews.
The bibliometric network visualization of the total population of the literature provided a bird’s-eye view of the existing body of work. This analysis revealed three distinct clusters, each representing a major thematic area. By examining both the keywords associated with these clusters and their positions within the network, we were able to discern their conceptual orientation and assign the following labels: (a) technological, (b) change behavior–change mode, and (c) policy, planning, and governance. Subsequently, a thematic content analysis of the most influential articles enabled us to identify core bibliographic themes that further structure the SMT literature.
The aforementioned structural elements (clusters and themes) were subsequently interpreted through a process of narrative construction, which revealed the dynamic interactions among them. On this basis, the literature can be described as organized around a major narrative that primarily seeks to answer the following question: How can emissions mitigation be achieved? This overarching narrative is supported by three main sub-narratives: through technology, through behavioral change approaches, and through policy and governance intervention strategies. We broadly validate Holden’s (2020) [25] conclusion that each of these narratives can generate strategies that contribute to sustainable mobility; however, their synergy is essential to move beyond emissions mitigation and achieve a sustainable transformation of the transport system.
The 12 sub-narratives further unravel the conceptual threads of SMT, revealing the diverse stories constructed by researchers in the field. They also suggest that the segmentation of the SMT literature into three clusters is not impermeable, as interactions occur between clusters—particularly through specific themes or topics. This was demonstrated through both the bibliometric network visualization and the in-depth content analysis. These dynamic interactions appeared stronger between the “change behavior–change mode” and “policy and governance” clusters, and weaker between the “technological” cluster and the other two, potentially indicating a relative isolation of “tech fix” approaches.
By analyzing the underlying causes of the relative isolation of “tech fix” approaches and their implications for future research, we highlight the need to foster interdisciplinarity within the SMT field. In particular, a more extensive and deeper collaboration between researchers in STEM (science, technology, engineering, and mathematics) and SSH (social sciences and humanities) is essential to accelerate the transition toward a more sustainable transport system. Furthermore, we identified specific thematic areas and topics within the SMT field where such collaboration is both necessary and potentially fruitful. This process also led to the identification and in-depth examination of key “unsustainabilities” in SMT, as well as ten core research thematic units, which are detailed in Section 5.3.
In conclusion, our study contributes to the advancement of knowledge by offering a unified synthesis of the structural and interpretive elements of the Sustainable Mobility and Transportation (SMT) literature, integrating both technological and social dimensions, as well as their interactions. Moreover, it serves as a reliable research navigation tool within this vast and complex field, supporting the development of interdisciplinary research and fostering collaboration among policymakers, scientists, and civil society to accelerate the transition toward a more sustainable transport system.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su17094228/s1, Table S1: The 220 “Most-Cited Group” articles.

Author Contributions

Conceptualization, I.K., S.A. and S.R.; methodology, I.K., S.A. and S.R.; software, I.K., S.R.; validation, I.K., S.A. and S.R.; formal analysis, I.K.; investigation, I.K.; resources, I.K., S.A. and S.R; data curation, I.K.; writing—original draft preparation, I.K.; writing—review and editing, I.K., S.A. and S.R.; visualization, I.K.; supervision, S.A. and S.R.; project administration, S.R; funding acquisition, S.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partly funded by Horizon Europe’s Maria Skłodowska-Curie Staff Exchange program as BioTrainValue (BIOmass Valorization via Superheated Steam Torrefaction, Pyrolysis, Gasification Amplified by Multidisciplinary Researchers TRAINing for Multiple Energy and Products’ Added VALUEs), with grant number: 101086411. The APC was funded by the same project.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GDPGross domestic product
LCALife cycle assessment
MLPMultiple-level perspective
STEMScience, technology, engineering, mathematics
SSHSocial sciences and humanities
SMTSustainable mobility/transport(ation)
WoSWeb of Science

Appendix A. Clusters of Bibliometric Network Visualization

Table A1. Clusters (co-occurrence of keywords). Source: Authors.
Table A1. Clusters (co-occurrence of keywords). Source: Authors.
Cluster (Co-Occurrence of Keywords Technique)Number of Total KeywordsSignificant Keywords (According Their Total Link Strength and Number of Occurrences)
Red cluster (technological)104Emissions, energy, life cycle assessment, alternative fuels, electric vehicles, hydrogen, biofuels, performance, efficiency, environmental impacts, system, consumption
Green cluster (change behavior)65Behavior, planned behavior, travel behavior, attitude, habit, travel mode choice, health, bicycle, walking, physical activity, public transport,
Blue cluster (policy, planning, governance)81Policy, planning, governance, accessibility, management, land use, participation, smart city, transit-oriented development, urban planning cities, transport planning

Appendix B. Grand Narratives, Narratives, and Sub-Narratives

Table A2. Comparison between our view and Holden et al., 2020 [25]. Source: Authors.
Table A2. Comparison between our view and Holden et al., 2020 [25]. Source: Authors.
Our ViewHolden et al., 2020 [25]
NarrativesSub-NarrativesTo Whom (Mainly) Are They Addressed?CharacterGrand NarrativesNarrativesTo Whom (Mainly) Are They Addressed?Character
One “major” narrative that consists of three bibliographic narratives:
“technology” narrative, “change behavior” narrative, and “policy, governance” narrative
1. Alternative fuels and electrified carsResearchersBibliographicThree (3) grand narratives (electro mobility, collective transport 2.0, low-mobility societies)1. The green governmentPolicy makersStrategic
2. Energy and emissions
3. Decoupling2. The green purchaser
4. Traffic regulation3. The clean vehicle
5. Alternative modes4. The public transport provider
6. Motorized shared mobility
7. Change behavior5. The responsible traveler
8. Reducing car trips6. Shared mobility schemes
9. Evaluation—assessment and indicators7. The compact city
10. Socio-technical transitions theory
11. General and theoretical8. Essential life
12. Social sustainability9. Traveling electrons

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Figure 1. Overview of the research design used in this study. Source: Authors.
Figure 1. Overview of the research design used in this study. Source: Authors.
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Figure 2. The number of journal articles (total population) published from 1993 to 2020. Source: Authors.
Figure 2. The number of journal articles (total population) published from 1993 to 2020. Source: Authors.
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Figure 3. Number of articles per WoS subject category. Source: Authors.
Figure 3. Number of articles per WoS subject category. Source: Authors.
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Figure 4. Number of journal articles per country/region. Source: Authors
Figure 4. Number of journal articles per country/region. Source: Authors
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Figure 5. Network visualization of the sustainable mobility/transport literature (co-occurrence of keywords). Source: Authors.
Figure 5. Network visualization of the sustainable mobility/transport literature (co-occurrence of keywords). Source: Authors.
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Figure 6. SCAST triangle. Source: Authors, reconstructed from [205].
Figure 6. SCAST triangle. Source: Authors, reconstructed from [205].
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Table 1. Main themes identified in the most influential part of the SMT literature. Source: Authors.
Table 1. Main themes identified in the most influential part of the SMT literature. Source: Authors.
1. Alternative fuels/technologies/vehicles (except electric vehicles)8. Bicycle, walking15. Gender
2. Electric vehicles 9. e-bikes16. Land use planning, urban forms
3. Emissions and energy 10. Public transport/transit 17. Policies, planning, governance
4. Decoupling—economic dimension of sustainable transport/mobility transport11. Car sharing, carpooling, ridesharing18. Evaluation—indicators of sustainable mobility/transport
5. Traffic regulation (pollutant reduction)12. Travel behavior and tourism19. Social dimension/component of sustainable mobility
6. Planes, ships, trains13. Changing transport mode20. Transitions
7. Freight transport 14. Attitude, behavior 21. General–theoretical
Table 2. Association of themes with the three clusters through keywords and network visualization. The red, green and blue colors have been added as they correspond to the colors of the clusters depicted in Figure 5 of the network visualization.
Table 2. Association of themes with the three clusters through keywords and network visualization. The red, green and blue colors have been added as they correspond to the colors of the clusters depicted in Figure 5 of the network visualization.
Cluster
(Bibliometric Network Visualization)
Keywords
(Bibliometric Network Visualization)
Theme
(Thematic Content Analysis)
Technological cluster (red cluster)Alternative fuel, alternative-fuel vehicle, biodiesel, bioenergy, biofuel, biomass, conventional vehicle, energy efficiency, environmental impact, ethanol, fuel cell, fuel cell vehicle, fuel consumption, hydrogen, life cycle assessment, natural gas, optimization, performance system dynamics, technology#1 Alternative fuels, technologies (except electric vehicles)
Battery, electric mobility, electric vehicle, energy efficiency, environmental impact, hybrid vehicle, life cycle assessment, optimization, performance, plug-in hybrid, system dynamics, technology#2 Electric vehicles, batteries, infrastructure
Air pollutant, carbon dioxide emission, carbon footprint, CO2 emissions, climate change mitigation, efficiency, emission, emissions reduction, energy, energy consumption, energy efficiency, energy use, environmental benefit, environmental impact, fuel consumption, industry, greenhouse gas emission, performance, petroleum, pollutant emission, renewable energy, scenario analysis, sensitivity analysis, simulation, technology, vehicle emission#3 Emissions and energy
Cost, consumption, customer economic, economic impact, economy, GDP, gross domestic product, external cost, industry, market, market share, network, scenario analysis, supply chain, system dynamic#4 Decoupling—economic dimension of sustainable transport/mobility
Algorithm, calculation, design, new technology, operations, optimization, performance, road traffic, simulation, simulation result, sensitivity analysis, speed, system, system dynamics, vehicle emission#5 Traffic regulation (pollutant reduction)
Aviation, climate change mitigation, CO2 emission, emission reduction, port, railway#6 Planes, ships, trains
Consumer cost, economic impact, economy, freight, freight transport, gross domestic product, low cost, market share, profit, subsidy, supply chain, ton, total cost, truck#7 Freight transport
Algorithm, barriers, calculation, carbon footprint, carbon dioxide emission, climate change mitigation, economic, economic impact, energy consumption, energy efficiency, environmental benefit, environmental impact, environmental performance, external cost, life cycle assessment, network, operation, optimization, performance, quantitative analysis, scenarios, scenario analysis, sensitivity analysis, simulation result, strategies, sustainability indicator, uncertainty, vehicle emission#18 Evaluation—indicators of sustainable mobility/transport (part of)
Autonomous vehicles, barriers, innovation, system, transitions#20 Transitions
(part of)
Change behavior cluster (green cluster)Active transport, active transportation, bike sharing, active travel, bicycle, built environment, children, cyclist, fatalities, habit, health, mode choice, neighborhood, obesity, pedestrians, physical activity, risk, safety, satisfaction, school, time, travel time, walking, walkability, weather condition#8 Bicycle, walking
Bike sharing, e-bike, electric bike, commute, risk, urban form#9 e-bikes
Commute, commuting, distance, metro, mode choice, public transport, quality, travel mode choice, travel behavior, urban form, work#10 Public transport/transit transport (part of)
Car use, car ownership, choice, commute, drivers, habit, intention, quality, mobility management, satisfaction, travel behavior#11 Car sharing, carpooling, ridesharing (part of)
Attitude, behavior, choice, determinants, environmental concern, travel mode, travel mode choice, travel behavior, willingness#12 Travel behavior and tourism
Attitude, behavior, quality, questionnaire, satisfaction, modal choice, mode choice, multimodality, preference#13 Changing transport mode
Attitude, behavior, choice, determinants, environmental concern, experiences, mobility management, mobility behavior, modal choice, mode choice, multimodality, preference#14 Attitude, behavior
Policy, planning, and governance (blue cluster)Bus, public transit, public transportation, transit, transit-oriented development, transport management, transportation time, travel time, urban transport, urban transportation#10 Public transport/transit transport (part of)
Car sharing, cities, connectivity, impacts, mode, patterns, service, sharing economy, smart city, stations, transport management#11 Car sharing, carpooling, ridesharing (part of)
Family, gender, habit, household, intention, school, survey, woman# 15 Gender
Access, accessibility, area, density, GIS, knowledge, land use lesson, location, management, methodology, network design, perception, planning support, transport planning, travel time, urban planning, urban transport, urban transportation#16 Land use planning, urban forms
Citizen, coordination, decision, decision making, dynamics, framework, governance, implementation, participation, patterns, people, policy, policy development, policy making, selection, stakeholder, strategy# 17 Policies, planning, governance
Appraisal, accessibility, analytic hierarchy process, best practice, connectivity, decision making process, dynamics, guideline, framework, governance, impact, implementation, indicators, infrastructure, knowledge, management, methodology, models, monitoring, ranking, patterns, planning, selection, smart city, strategy, sustainability assessment, tool, validation#18 Evaluation—indicators of sustainable mobility/transport (part of)
Accessibility, equity, framework, justice, participation, people, perception, policies, selection services, pillar, social exclusion, social sustainability, sustainable development, sustainable urban mobility, transport policy# 19 Social dimension/component of sustainable mobility
Accessibility, actor, city, dynamics, governance, multi-level perspective, transport policy, urban transport#20 Transitions
(part of)
Accessibility, cities, connectivity, discourse, European union, framework, integration, impacts, knowledge, lessons, management, mobilities, model, modal share, participation, patterns, planning, policies, politics, pillar, strategy, policy making, sustainable development, sustainable future, sustainable mobility system, sustainable practice, sustainable urban mobility, stakeholder, urban planning, urban transport, urban transportation#21 General–theoretical
Table 3. Bibliographic sub-narratives. Source: Authors.
Table 3. Bibliographic sub-narratives. Source: Authors.
Sub-Narrative“Principally Associated” NarrativeAssociated ThemesKey Questions
1. Alternative fuels and electrified vehicles“technology”#1. “Alternative fuels/technologies/vehicles (except electric vehicles)”
#2. “Electric vehicles”
How can alternative fuels for efficient motor vehicles (e.g., biofuels) or alternative energy sources (e.g., electrification) that reduce environmental impacts be produced or developed, and how can the associated (primarily technical) challenges be addressed?
2. Energy and emissions“technology”#3 “Emissions and energy”How can the efficiency of conventional fuel-powered vehicles be maximized? How can energy consumption and greenhouse gas emissions in transport systems be estimated—using models, quantitative methods, and other tools—at the city, regional, or national scale, and how can future trends be forecast?
3. Decoupling“technology”#4“Decoupling—economic dimension of sustainable transport/mobility”How do the economic and environmental dimensions of sustainability interact with each other (economic–environmental entanglement) in transport systems? How could a ‘‘decoupling’’ effect be achieved?
4. Traffic regulation“technology”#5“Traffic regulation (pollutant reduction)”Through which technical means can vehicle traffic be efficiently regulated—particularly in urban areas—to reduce congestion and emissions?
5. Alternative modes“behavior change” and “policy, governance”#8 “Bicycle, walking”
#9. “e-bikes”
#10 “Public transport/transit transport”
How can the development of soft/active transport modes (including hybrid active modes such as e-bikes) and public transport be promoted to support and encourage shifts in individual behavior and preferences toward more sustainable mobility options?
6. Motorized shared mobility“policy, governance” and “behavior change”#11 “Car sharing, carpooling, ridesharing”What role do motorized shared mobility modes play in advancing sustainable transportation systems, and how can they be more effectively organized and utilized?
7. Change behavior“behavior change”#12 “Travel behavior and tourism”
#13 “Changing transport mode”
#14 “Attitude, behavior”
#15 “Gender
What insights can the social sciences (e.g., psychology, sociology) offer into understanding people’s travel behaviors and attitudes, and how can the findings from such research be integrated into Sustainable Mobility and Transport (SMT) policies at local and national levels?
8. Reducing car trips“policy, governance”#16 “Land use planning, urban forms”
#17 “Policies, planning, governance”
In what ways is the concept of SMT related to the structure of cities, land-use patterns, and the design of integrated urban and spatial planning policies?
9. Evaluation—assessment and indicators“policy, governance”#18 “Evaluation—indicators of sustainable mobility/transport”How can indicators (or systems of indicators) and integrated frameworks be used to assess the viability of transport systems at the city, regional, or national scale, as well as the effectiveness of policies intended to accelerate the transition to sustainability?
10. Transitions theory“policy, governance”#20 TransitionsHow can transition theories—particularly the multi-level perspective approach—be applied to study, interpret, and transform transport systems and policies (in whole or in part) to support the shift toward a more sustainable transport paradigm?
11. General and theoretical“policy, governance”#21 General–theoreticalHow is the concept of Sustainable Mobility and Transport (SMT) understood in the literature, and what are (from a descriptive perspective) or should be (from a normative perspective) the general characteristics of policies and approaches aimed at achieving a more sustainable transport system?
12. Social Sustainability“policy, governance”#19 Social dimension/component of sustainable mobilityWhat elements constitute the social dimension of sustainable mobility, and how can they be integrated into transition policies aimed at developing a more sustainable transport system?
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MDPI and ACS Style

Kanakis, I.; Arapostathis, S.; Rozakis, S. Technology, Behavior, and Governance: Far Away, Yet So Close! A Comprehensive Review of the Sustainable Mobility and Transportation Literature. Sustainability 2025, 17, 4228. https://doi.org/10.3390/su17094228

AMA Style

Kanakis I, Arapostathis S, Rozakis S. Technology, Behavior, and Governance: Far Away, Yet So Close! A Comprehensive Review of the Sustainable Mobility and Transportation Literature. Sustainability. 2025; 17(9):4228. https://doi.org/10.3390/su17094228

Chicago/Turabian Style

Kanakis, Ioannis, Stathis Arapostathis, and Stelios Rozakis. 2025. "Technology, Behavior, and Governance: Far Away, Yet So Close! A Comprehensive Review of the Sustainable Mobility and Transportation Literature" Sustainability 17, no. 9: 4228. https://doi.org/10.3390/su17094228

APA Style

Kanakis, I., Arapostathis, S., & Rozakis, S. (2025). Technology, Behavior, and Governance: Far Away, Yet So Close! A Comprehensive Review of the Sustainable Mobility and Transportation Literature. Sustainability, 17(9), 4228. https://doi.org/10.3390/su17094228

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