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Systematic Review

Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research

Chair of Management and Logistics, Technical University of Darmstadt, 64289 Darmstadt, Germany
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(20), 13269; https://doi.org/10.3390/su142013269
Submission received: 19 August 2022 / Revised: 1 October 2022 / Accepted: 12 October 2022 / Published: 15 October 2022

Abstract

:
Synchromodal transportation is a novel multimodal transportation concept. It builds on a collaboration of shippers and logistic service providers to enable real-time switching between transport modes and mode-free transport bookings, enabling more flexible and sustainable freight transportation. This paper summarizes the current state of research since 2010 by means of a systematic literature review. A comprehensive taxonomy consisting of five dimensions and 13 categories for both qualitative and quantitative papers is developed. The results reveal a mixed picture, with high consistency in geographical areas of synchromodal transportation implementation and suitable modeling of operational disruptions and uncertainties. However, compared to multimodal or road transportation, there is little alignment in the forms of collaboration, network organization, or the advantages of synchromodal transportation. Finally, the main fields for future research are identified, namely business, legal, technological, modeling, and awareness.

1. Introduction

The European Union (EU) freight transport industry is responsible for 25.8% of the total GHG emissions, a major factor driving climate change [1]. Existing multimodal freight transport concepts have not been able to counteract the radical ecological changes. The inland freight modal split within the EU, consisting of 77.4% road freight in 2020, shows that neither the goal of a substantial modal shift nor comprehensive decarbonization of the transport sector was advanced in recent years [2].
Promoted by the European Commission, Synchromodal Transportation (SMT) is a new promising freight transport concept. It originated in 2010 in the Netherlands [3]. The revolutionary concept changes the process and organizational forms of existing multimodal freight transport concepts. It can be defined as the “synchronization of physical resources, business processes, and the parallel use of transportation modes in a mode-free way to offer shippers a more flexible and sustainable means of freight transportation.” [4]. In this context, synchromodal transport can be seen as a further development of intermodal transport concepts, in which the actors in the transport chain actively work together in a cooperative network in order to plan transport processes flexibly and to be able to switch between transport modes in real-time according to the available resources [5,6].
SMT has the potential to increase the attractiveness of more sustainable transport modalities and thus significantly improve the modal shift. Cost and resource efficiency, as well as reliability and resilience of transports, are guaranteed by unprecedented transparency of freight transport, intensive connectivity of infrastructure, and an in-depth collaboration of all actors involved. However, there is no single universal understanding of SMT. Substantially contrasting emphases are detected in various definitions such as the one by [7]: ”Structured, efficient and synchronized combination of two or more transportation modes.” or [8]: “A multimodal transportation planning system, wherein the different agents involved in the supply chain work in an integrated and flexible way that enables them to dynamically adapt the transport mode they use based on real-time information from stakeholders, customers, and the logistic network”.
As SMT entails profound operational, technical, and business changes, this paper aims to bundle and align existing research approaches. Therefore, a systematic literature review (SLR) is conducted. A conceptual elaboration of SMT is developed, which distinguishes it from previous transportation concepts. Synergies within research on SMT are explored to establish a well-founded and exhaustive overview of the topic. Furthermore, this paper extends the current body of literature. While Acero et al. [8] elaborate on the innovative factors of SMT, they focus on integrating SMT into the supply chain. The SLR presented by Delbart et al. [9] examines intermodal and synchromodal transportation problems but lacks a paper categorization tailored to the innovative features of SMT and their mathematical representation. The SLR conducted by Pfoser et al. [10], which examines antecedents, mechanisms, and effects of SMT, is most similar to this paper. However, their paper focuses solely on the qualitative properties of SMT, disregarding quantitative research, without establishing an individualized taxonomy for qualitative and quantitative papers.
Therefore, there is still a significant research gap in terms of understanding synchromodality holistically, developing a taxonomy to bundle all relevant qualitative and quantitative literature on synchromodal freight transport, comparing the two types of analysis approaches, and identifying future trends. This gap is addressed by answering the research question (RQ):
  • What is the current state-of-the-art of synchromodal transportation?
    To answer this research question conclusively, three sub-questions arise:
    1.1
    What is the most relevant literature in the context of synchromodal transportation?
    1.2
    How can research on SMT be systematically classified, what trends can be observed, what primary research methods are used, and how do they relate and compare to each other?
    1.3
    Which fields for future research can be derived from?
After introducing the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and the methodology in Section 2, the literature is analyzed by a two-step process [11]. First, descriptive characteristics of the research corpus are summarized in Section 3.1. Thereafter, based on the division of the literature into qualitative, Section 3.2, and quantitative papers, Section 3.3, the development of a taxonomy follows, consisting of distinguishing features on novel SMT characteristics and assessment criteria, which are then clustered into dimensions and categories. The following discussion in Section 4 compares qualitative and quantitative research results, and fields for future research are derived. Finally, we conclude in Section 5.

2. Methodology

Systematic literature reviews aim to better understand a real-life phenomenon and identify and critically evaluate an existing body of knowledge in a precise, rigorous, and replicable method [12]. According to Denyer and Tranfield [12], the four basic principles of an SLR consist of transparency, inclusivity, explanation, and heuristic. Transparency is enabled by three factors: 1. disclosing the processes and methodologies used, 2. presenting the conclusions that are derived, which have clear dependencies on the found evidence in the literature, and 3. by a reflection of the author’s values towards the scientific topic to further prevent bias. Furthermore, the articles included in the review play a central but complex role. The quality of the used information sources needs to be appraised to uphold a high standard. The third principle, explanation, covers synthesizing the information into one piece of work, which goes far beyond merely combining the individual articles. Lastly, SLRs present a heuristic consisting of “rules, suggestions, guides, or prototype protocols” [12] instead of fixed solutions to a specific problem. As a result of the four principles that were formerly introduced, five straightforward steps are derived by Denyer and Tranfield [12], guiding this SLR:
First, the research question(s) must be formulated to define the scope of the SLR.
Subsequently, the literature has to be identified in a transparent and documented manner. Based on the research questions, we aim for a holistic view of SMT and have chosen a search string that is as broad as possible. We searched the database Web of Science with the string synchromodal* OR synchro-modal* starting in 2010, the first time synchromodality was mentioned. The broad search led to 83 articles.
To assess the importance of each article, we set up distinct selection criteria:
  • The article is written in English;
  • Articles have to be peer-reviewed, and if published in a journal, the journal has to be ranked Q2 or higher by the Scimago Journal & Country Rank;
  • Non-related papers or papers that only scarcely deal with SMT are excluded. Those papers were identified after reading the title and abstract;
  • Conference papers were excluded if they were adopted into journal publications or had no documented methodological approach.
After applying the selection criteria, 56 papers remained. An upstream and downstream search of the citations yielded another six papers. The procedure is summarized in the PRISMA flowchart (Figure 1). Qualitative content analysis sets the framework for analyzing the corpus on synchromodal transportation [13]. Thereby two different techniques can be considered: the deductive and the inductive approach. A deductive approach determines the assessment categories before reviewing each paper. In contrast to the deductive approach, categories are flexibly added during the data evaluation procedure in an inductive approach [14]. Although this procedure yields the need for iterative readings, the inductive approach is chosen due to the novel concept of synchromodal transportation and the lack of knowledge of well-fitting dimensions and categories. Based on the ontological and epistemological idiosyncrasies of SCM and logistics management research and the six idiosyncrasies (theoretical boundaries, unit of analysis, sources of data, study context, definitions and the operationalization of constructs, research methods), as identified by Durach et al. [15], we code and synthesize the literature and develop a taxonomy.

3. Results

To evaluate the corpus of 62 papers, we cluster the content and conduct extensive analysis, resulting in a sequential process. At first, a distinction is drawn between descriptive and content-based analysis. Henceforth, the content-based analysis is performed by distinguishing between qualitative and quantitative papers.

3.1. Descriptive Results

Although already introduced in 2010, the first papers on SMT were published in 2014 (Figure 2). It becomes apparent that the research on SMT started with a qualitative approach, and in subsequent years, papers with a quantitative focus picked up. As synchromodality is a concept coming from the Netherlands, it is no surprise that most research, totaling 35 publications, is located there. The remaining publications are spread worldwide in 15 countries, focusing on Europe.
As displayed in Figure 3, 20% of the authors were involved in around 50% of the publications on synchromodality. Therefore, although a linear relationship between authors and published papers is not observed, there is no Pareto distribution between authors and published papers. This is a good condition to counter mind bias [16]. Nevertheless, two authors (R. Tadei and B. Atasoy) contributed to more than five papers, and R. R. Negenborn to 16 papers, all focusing on quantitative research. Hence, 28 authors (21%) are engaged in publishing more than one paper. This does not necessarily speak for inconsistency in research, as the research is mainly driven by three universities (Research Group Logistics at Hasselt University, Belgium; Department of Maritime and Transport Technology & Center for Systems and Control both Delft University of Technology, Netherlands; Politecnico di Turino, Italy). We suspect that many Ph.D. students are involved in the research, which increases the number of authors with only one publication on SMT.

3.2. Results of the Qualitative Papers

In the following, we analyze qualitative papers in a twofold way. Firstly, Six distinguishing features, based on the six idiosyncrasies as identified by Durach et al. [15], are introduced, comparing reoccurring topics within the qualitative literature corpus. After that, the qualitative literature is divided into two dimensions and four categories based on the distinguishing features (Table 1). Hence, a taxonomy of the synchromodal transportation literature is accomplished.

3.2.1. Distinguishing Features

Six distinguishing features of synchromodality were identified. Each paper’s main topic and methodology are broken down into the feature topic and methodology, giving the reader a chance to gain an overview of the paper’s findings. As SMT causes disruptive changes in the overall transport organization and execution, the topics of the studied papers are equally broad. The main methodology used is a literature review [7,17], often conducted systematically [7,9]. The second most used methodology is case studies, applied to the analysis of existing SMT implementation projects [18,19], on potential fields of SMT implementation [4,20], or demonstrators and simulation games [21,22].
The second feature, Stakeholder focus, assesses which stakeholders are most emphasized. Although authors agree that SMT impacts all existing stakeholders along the transportation chain [23], some papers highlight certain operators more than others or dedicate their research to one specific stakeholder.
The feature Development of synchromodality analyses aspects in need of expansion, such as technical, operational, or business. Mostly, authors use conceptual approaches to distinguish synchromodality from previous transportation concepts [17,24] and extract their key elements [8,10]. One of the few papers focusing on the business perspective of synchromodality is Perboli et al. [25], which highlights the need for a commercially sustainable solution for all stakeholders involved.
The application of synchromodal theory to case studies, real-world implementations, and research projects is captured by SMT application fields. Due to the conceptual-descriptive or mathematical nature of many papers, and the small number of SMT projects in the real-world, more than 50% of the reviewed papers lack an application of their research to a practical study [10].
How the transport corridors can be organized so that the concept of synchromodality and its benefits are realized, and at the same time, the requirements of all involved stakeholders are taken care of, is considered by the feature Network organization. While analyzing SMT, Tavasszy et al. [17] suppose that SMT is not the sum of a single origin-to-destination transport but rather an integrated way of transportation and therefore needs to be organized from a network perspective. Furthermore, a prerequisite for a functioning SMT network is the intensive exchange and cross-company integration of sensitive data to create a seamless flow of information along the entire transport chain [8,10]. Therefore, collaboration and trust are crucial in vertical relationships and significantly more important in horizontal cooperation [4,18,22].
The last feature, Comparative benefits of synchromodality, summarizes the various envisioned advantages of SMT and clusters these into the four facets planning and execution flexibility, cost- and resource efficiency, sustainability, and transparency.

3.2.2. Taxonomy of Qualitative Papers

A taxonomy comprising two dimensions and five categories is developed to structure the qualitative papers. The first dimension of Explanatory research on synchromodality tends to be more conceptual and introductory and shows a higher illustrative character. This dimension is split into two categories: Synchromodality theory refinement and Literature reviews on synchromodal transportation problem modeling.
With a higher practical reference, the second dimension Contextualizing research on synchromodality, covers papers that frame SMT in a more implementation-oriented way. Three further categories that differ in their focus were disclosed. Case studies on synchromodal transportation implementation comprise companies involved in the logistics context and the resources and tools that are already in place or needed for SMT implementation. Synchromodal transportation linked to further research topics examines the interconnection of the development of synchromodality in literature. Experimental learning about SMT explores the opportunities of serious simulation gaming.
Dimension 1: Explanatory research on synchromodality
Dimension 1 encompasses ten papers, of which six belong to the first category (see Table 2). Both categories include papers that, on the one side, belong to the earliest research on synchromodality [17,24] and, on the other side, to the most recent [8,9]. In general, comparing the papers in dimension one over time, their character becomes increasingly summarizing and unifying as the literature research body they build upon extends as well.
The category Synchromodality theory refinement extracts the innovative features and their distinction from existing transportation concepts while also elaborating on characteristics, critical success factors (CSFs), or barriers [8,10].
Although literature reviews on mathematical SMT problems in the second category exhibit the analysis of quantitative papers, they are summarizing and qualitative in their nature. In addition to these methodologies, surveys and interviews can be conducted to collect data [28]. Each of the four examined reviews focuses on different areas of mathematical transportation planning problems and covers different periods in their analysis. Analyzing mathematical SMT problems, distinguishing them from existing multimodal transport problems, and striving to set up a framework for different group characteristics of SMT modeling problems are core topics of the latter category.
Dimension 2: Contextualizing research on SMT
Dimension 2 comprises 13 papers, of which Case studies on synchromodal transportation implementation represent the most prominent category with seven papers, followed by Synchromodal transportation linked to further research topics and Experimental learning about synchromodal transportation (see Table 3).
Moving from theory to practice, the papers in category 3 elaborate on the possibility of implementing synchromodality and assess its degree of implementation and the necessary prerequisites. Tsertou et al. [20] and Bol Raap et al. [29] are similar in that they present the development of a technological tool to introduce synchromodality. The second set of papers examines how a-modal booking of shippers can be realized [30] and how to establish synchromodality as a whole in a country [4]. The remaining papers cover case studies on how far SMT implementation has advanced.
The papers in category 4 connect synchromodality with two further research directions: slow steaming and physical internet (PI). Fostering sufficient technological and managerial conditions to establish the former and accounting for the success of the latter is assumed by the implementation of SMT. A different yet promising approach to transferring the theoretical concept of synchromodality to newcomers in a tangible way is serious simulation gaming. Used by Buiel et al. [21] and Kurapati et al. [22], they strive to reveal the benefits of comprehensive planning freedom to Dutch logistics and transport experts through simulation games.

3.3. Results of the Quantitative Papers

Similar to the qualitative analysis, an initial explanation and overview of the applied evaluation criteria are provided. Instead of distinguishing factors that examined whether and how certain areas of synchromodality are covered in the qualitative papers, 13 assessment criteria are applied to the quantitative papers. The reason for this slightly different approach is that the analyzed quantitative papers are mostly very distinct about certain factors and thus can be clearly assessed. Based on the detailed assessment criteria, a taxonomy comprising three dimensions and nine categories is accomplished (Table 4).

3.3.1. Assessment Criteria

Although the SMT problems are based on classic transportation problems [34], their complexity far exceeds the usual problem. This is primarily due to the a-modal booking of shippers and real-time switching until shortly before, but also during, transport execution. In two-thirds of cases, the underlying mathematical formulations are recognized as mixed integer (MIP) or integer problems (IP). Furthermore, simulation and Markov Chains are applied. Most papers deal with operational issues, thereby integrating real-time information evolution and stochastic information.
Nearly 80% of the papers apply their models to intra-continental transportation. Moreover, 29 papers refer to port hinterland transportation in their studies. The Port of Rotterdam as the source or sink for an SMT network appears especially suitable, as it opens the door for the tri-modal Rhine corridor. Besides, also the hinterland corridors from the Greece port in Piraeus to Prague [35], the Shanghai container hinterland [36], and the Klaipeda seaport hinterland in Lithuania [37] are subject of SMT network analysis.
The majority of 25 papers test their proposed model in a case study. However, the case studies differ significantly in size. As presented by [34] or [35], smaller networks more often relate to synthetic data and comprise less than ten terminals. In general, case studies on SMT with small scope must be viewed with caution since important features such as en-route real-time switching, integrated network planning, and infrastructure interconnection only develop their potential with increasing network size. On the contrary, more extensive networks cover hundreds of shipment requests, links and nodes, hundreds of services, and several dozen terminals [38,39].
Adapted from Juncker et al. [26], the System characteristics distinguish between four model cases that differ in the SMT actors’ knowledge level and the optimization perspective. In limited models, information availability and optimization are local, unlike cooperative models, where information is still only available locally, but optimization is global. A model is called selfish if, on the one hand, global information is available for each stakeholder, but on the other hand, optimization is still local. Lastly, social models assume global information and optimization. In addition, an extension of the classification is provided by further separating social models by their organizing scope.
Although global optimization requires the highest level of mutual trust among transport operators, it was chosen by more than 69% of all papers (see Figure 4). Nineteen papers based their assumptions on a social orchestrator that, when equipped with global information, optimally organize an entire synchromodal network, testifying to the authors’ great interest in optimization approaches for entire transportation networks. Nonetheless, representing the second largest identified group, papers identified with selfish system characteristics reveal a wide range of coordination forms within synchromodal networks.
The evaluation of the Cooperation mechanisms shows that, with almost 70% of all papers, a full horizontal collaboration between the transport actors is modeled most frequently.
The Transport service characteristics differ substantially from those of previous multimodal transport concepts. Four underlying criteria were determined to assess how the authors understand real-time switching and integrated network planning as a crucial part of synchromodality and to what extent these are integrated into the model formulations. As a prerequisite to other service criteria, the models were reviewed for a-modal booking of the shippers. Whereas this is a prerequisite for real-time switching before transport execution, it was also examined if the model promoted en-route mode or tour re-scheduling for the shipped cargo in case of unforeseen disturbances or new transport orders. Closely related, truck tours were analyzed concerning whether or not they are predefined or flexible.

3.3.2. Taxonomy of Quantitative Papers

Based on three dimensions and ten subcategories, papers with similar content are compared and clustered. Dimension 1, Shipment matching problems in SMT, covers operational decision processes under varying scenario conditions. Dimension 2 addresses the Transport network mapping under the influence of synchromodality features. This comprises strategic terminal planning, transport service pricing, transport mode schedule planning, and decentralized cooperation mechanisms. Lastly, dimension 3 focuses on Adapting synchromodality in a supply chain context and developing digital tools for SMT applications.
Dimension 1: Shipment matching problems in SMT
The first and largest dimension comprises 16 papers concentrated on synchromodal shipment matching. These are clustered according to their information quality, and their results are compared to intermodal solutions in category 3 (Table 5).
Deterministic shipment matching problems focus mainly on transport mode and route real-time switching, implying integrated network planning and a centralized network organization. Whereas [40] highlights a-modal booking, Nabais et al. [41] and Guo et al. [42] concentrate on real-time switching as the central aspect of synchromodality.
The second category consists of Online and stochastic problems. Like Guo et al. [36], all three papers by Guo et al. [34,40,42] consider a digital matching platform, yet with different dynamic and stochastic variables. In contrast, the models presented by Rivera and Mes [43,44,45] are not placed in an application-based context but rather stand for themselves. While [43] and [44] seek overall transportation cost minimization, profit maximization is the objective of [45].
The third category includes three papers that specialize in Comparing synchromodal and intermodal transportation, i.e., in the Rotterdam transport hinterland. Whereas in SMT, a-modal booking allows for flexible re-scheduling in case of delays, shipments in intermodal transportation remain with their initial transport plan. This fact is considered a distinct advantage in the current literature on SMT, but the findings of [39,46,47] do not provide unconditional evidence for this.
Dimension 2: Synchromodal network mapping
Fifteen papers in four categories deal with the framework of a synchromodal network, differentiating between strategic, tactic, and operational levels as well as decentralized cooperation mechanisms (Table 6). On a strategic level, this includes the consideration of SMT characteristics in the positioning of transshipment terminals. At the tactical level, the papers in category 5 describe how transportation pricing policies need to be adjusted to support SMT. Category 6 is characterized by the effort to determine the schedules and route and tour planning of the vehicles within a synchromodal network. In contrast to an often-assumed centralized network organization, several decentralized cooperation mechanisms are introduced by the papers in category 7.
Category 4 includes two papers addressing the strategic issue of how transhipment locations can be optimally placed in an SMT network. Next to the already immensely complex challenge of ideally locating facilities within a transport network, Crainic et al. [52] also consider the operational processes of a multi-period Synchronized Location-Transshipment Problem already at the strategic planning horizon.
Two papers cover the Tactical planning problem of defining the transportation product conditions. In general, products in the transportation context are defined by their price, lead time, and resulting service level. In contrast to traditional pricing mechanisms, van Riessen et al. [53] and van Riessen et al. [54] designed new pricing strategies that consider the synchromodal characteristics of a-modal booking and real-time switching.
Truck or barge routing, as well as schedule determination, is the focus of category 6. Operational transport means and container movements are represented by various cargo allocations and VRPs [55,56,57]. Moving from tour optimization to transport network resource scheduling, Behdani et al. [58] focus on rail and barge schedules.
Cooperation mechanisms that are significantly different from previously mentioned cooperation mechanisms are considered in the category of Decentralized decision-making. Instead of a central unit controlling the entire network, the coordination of routes and schedules is based on a decentrally organized process. Instead of assuming complete horizontal cooperation among actors within a synchromodal network, Larsen et al. [59] and Li et al. [60] present various coordination strategies to achieve intensified cooperation among transport operators, and Juncker et al. [61] model an agent-centric synchromodal network.
Dimension 3: SMT application
Papers in the third dimension are characterized by their high application relevance (Table 7). Category 8 represents digital planning tools. Category 9 broadens the focus beyond a purely transportation-based synchromodality view to a synchromodal supply chain.
Del Vecchyo et al. [67] and Dobrkovic et al. [68] research prerequisites to enable digital tools for SMT. The former observes that in operational SMT planning, costs and transport times are the most important KPIs. Dobrkovic et al. [68] focus on IT platforms in the context of SMT that require reliable ship arrival and delay data. This information is a prerequisite for barge planning of LSPs, which are given the freedom by synchromodality to replan hinterland transports flexibly. The overall goal of papers concerning digital planning tools for synchromodal transportation is to provide a planner of SMT with a support tool. Focusing on the transport route from Piraeus to Prague, Kapetanis et al. [35] introduces a support tool for LSPs, which enables transparent tour planning. Offering various multimodal alternatives, the tool entirely relies on a-modal booking, the horizontal collaboration of transport operators, and integrated network planning.
The last category is characterized by the combination of SMT and supply chain optimization. Economic, environmental, and performance-oriented synchromodal decisions are considered part of a corporate supply chain. Hence, material and information synchronization is not limited to SMT processes but applies to the entire supply chain. Synchromodality no longer only represents a transportation concept but rather a supply chain principle. [69] shape the term Synchromodality from a Supply Chain Perspective (SSCP) and model the optimal freight allocation within an SMT network while simultaneously considering inventory costs. The authors argue that although synchromodal rail-road transportation causes higher travel times than road-only transportation, SSCP reduces the total logistics costs by 6% through the cost advantage of SMT. However, the limited transport corridor of the presented case study neglects flexible replanning during the transport execution. On the contrary, [70] includes real-time switching of transport modes into their synchromodality decision rule.

4. Discussion and Fields of Future Research

This paper compared qualitative and quantitative papers, providing insights into commonalities and differences in SMT characteristics. While the assumptions and results of the papers have been analyzed and compared in detail so far, this discussion offers a comparison on a meta-level and identifies open research fields in the context of SMT. As identified in the descriptive analysis, research on SMT started with qualitative approaches, and it was only afterward that quantitative papers were published. Therefore, the extent to which the quantitative papers’ models reflect the theoretical findings of the qualitative papers on SMT is examined, and, further, it is analyzed to what degree the quantitative papers’ modeling results support the qualitative papers’ conclusions regarding the positive effects of SMT.
An analysis of the planning horizons of the quantitative models has shown that SMT problems can indeed be divided into the conventional categories of operational, tactical, and strategic, as assumed by Delbart et al. [9]. However, planning horizons increasingly merge in SMT. Due to the real-time synchronization and a global network orchestrator, the analysis of the quantitative papers dealing with strategic hub-location problems revealed that the operational level needs to be taken into account even more than in previous multimodal transportation problems. An operational-tactical hybrid of planning problems in SMT arises. Contrary to fixed transport resources with fixed schedules, the short-term operational demand determines which means of transport are used and when [65].
The quantitative papers provide a realistic representation of operational uncertainties in SMT, as identified by qualitative papers. More than 50% of the papers model the SMT problems using stochastic and dynamic parameters. In addition, the geographical references of the case studies in the quantitative papers are well aligned with actual SMT application areas. Nearly 75% of the models refer to port hinterland transportation. Moreover, the claim of [27] that existing models describing multimodal transportation problems are unsuitable for representing SMT, is confirmed. Due to real-time switching and horizontal collaboration within SMT, quantitative papers are developing new models precisely tailored to these characteristics [72].
At the same time, many inconsistencies exist between the results of the qualitative papers and the representation of SMT in the quantitative models. For example, the form of cooperation between the actors and the acceptance of a central network organizer. Several qualitative papers conclude that horizontal cooperation, a-modal booking, real-time switching, and the preceding mind-shift to transfer competencies and responsibilities represent the greatest challenges for the introduction of SMT [17]. Since today’s market positions are based on a business model of data evaluation, logistics companies tend to avoid these characteristics of SMT [18]. Furthermore, qualitative papers emphasize that legal barriers must first be overcome before such sensitive data can be exchanged. On the other hand, more than 70% of the quantitative papers build their models on full horizontal cooperation. Another issue concerns the optimization objectives of the quantitative papers. While SMT is to be introduced especially because of its environmental friendliness and promised outstanding potential for sustainable cargo transportation, 70% of all quantitative papers optimize economic objectives exclusively.
While qualitative conceptual-oriented papers exclusively expect cost benefits from the application of SMT [4,8], it turns out that handling costs and pro-active route and mode switching lead to higher costs compared to static intermodal transport [7]. Furthermore, the conclusion of the qualitative papers that SMT leads to a reduction in road freight transport has to be considered in a differentiated way. However, the quantitative papers agree that SMT increases the share of rail transportation, [39] documenting a drastic increase in road transport in the vicinity of transshipment terminals.
Synchronizing the papers’ results and comparison to current drivers impacting the European transport sector opens the door for future research fields on SMT. Five distinct research areas are disclosed and summarized in Table 8.
Considering future research on business aspects of synchromodality, business models, a two-sided platform, and trust are the key subjects. While various quantitative papers represent an orchestrator and its tasks, necessary business models, including profit and loss sharing mechanisms for all engaged actors within a centralized network organization, are entirely missing. The necessity to establish profit and loss compensation mechanisms that treat all involved parties fairly and are accepted by all involved stakeholders becomes even more critical when realizing that SMT causes very different cost changes.
Several papers [4,33] highlight legal barriers, liability, and insurance issues to the proposed horizontal collaboration. However, no paper deals with the legal controversy of what laws at national and European levels are involved and which specific changes are required to allow for intensive data sharing, real-time switching, and horizontal collaboration in SMT.
Although identified as one of the requirements for SMT by qualitative research and presumed in quantitative papers, loading units and interconnections of infrastructure remain an uncovered prerequisite of SMT in scientific literature. No paper deals with physical interoperability problems of SMT that exist between neighboring countries and impede real-time switching. Furthermore, the characteristics of loading units are not mentioned, or containers are assumed to be most suitable for real-time switching. While the technologies of Blockchain and IoT are emerging, their application to data security in horizontal collaboration and connectivity of loading units, respectively, have yet to be explored.
The remarkable share of quantitative papers in the overall literature corpus could not lead to the clarification of all modeling issues concerning SMT but rather represents the beginning of the transport problems to be investigated. In general, all mathematical models should include data from real-life SMT projects. To better reflect ongoing trends affecting the European transportation industry, truck driver shortages, alternative fuels and engines (e.g., electric trucks, Methanol powered barges), as well as short-duration disruptions, need to be considered in modeling SMT problems.
As the concept of synchromodality still occupies a niche position in the discussion on sustainable transport logistics, awareness needs to be strengthened. Studies on increasing shippers’ willingness regarding a-modal booking [30] and the methods of serious gaming [18,19] can help foster this development. The combination of qualitative, which form the basis for modeling assumptions, and quantitative literature is an essential approach to cover the presented areas of future scientific research on synchromodality.

5. Conclusions

The purpose of this paper is to provide a systematic review of the scientific literature that addresses SMT from a logistics and management perspective. A comprehensive summary was achieved by employing broad search terms, and an in-depth analysis was performed to provide an overview of the current state-of-the-art SMT research. Concerning the limitations of the work, two points should be mentioned: The database search was conducted exclusively in the Web of Science. The papers identified in this way were subjected to a forward and backward search, through which six further papers were identified. However, the possibility that further literature on SMT exists cannot be excluded entirely. Furthermore, we limited the review’s scope to references that explicitly focus on synchromodal transportation. Therefore, the possibilities of transforming approaches from other related research fields, such as the physical internet or digitalization of the transport sector, are not investigated.
The review’s main findings can be concluded according to the research questions (RQ).
Regarding RQ 1.1, SMT can be seen as an active topic that has attracted the interest of researchers worldwide, but especially in Europe, in the past years. Starting with mainly qualitative research, the focus shifted to mathematical planning problems over the years. To organize the literature and answer RQ 1.2, a comprehensive taxonomy of five dimensions and 13 categories for qualitative and quantitative papers is developed. Consequently, an extensive evaluation of the papers’ content is achieved, connections between the papers are established, and research results are consolidated. Furthermore, the two research approaches are compared, and commonalities and differences are identified. The results reveal a mixed picture, with high consistency in geographical areas of SMT implementation and suitable modeling of operational disruptions and uncertainties but little alignment in the forms of collaboration and synchromodal transportation network organization. Finally, future research fields, namely business, legal, technological, modeling, and awareness of synchromodal transportation (RQ 1.3), are disclosed to foster the successful long-term implementation of synchromodal transportation.

Author Contributions

The authors confirm contribution to the paper as follows: study conception and design: J.R., R.E. and F.W.; data collection: F.W.; analysis and interpretation of results: J.R. and F.W.; draft manuscript preparation: J.R. and F.W. All authors reviewed the results and approved the final version of the manuscript.

Funding

We acknowledge support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) and the Open Access Publishing Fund of Technical University of Darmstadt.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The procedure of SLR jrfm-1905447-tracked to the PRISMA flowchart.
Figure 1. The procedure of SLR jrfm-1905447-tracked to the PRISMA flowchart.
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Figure 2. Publications on synchromodality per year.
Figure 2. Publications on synchromodality per year.
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Figure 3. Paper to author and author to paper ratio.
Figure 3. Paper to author and author to paper ratio.
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Figure 4. System characteristics analysis results.
Figure 4. System characteristics analysis results.
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Table 1. Distinguishing features and taxonomy of qualitative papers.
Table 1. Distinguishing features and taxonomy of qualitative papers.
Distinguishing FeaturesDimensionCategory
  • Topic and methodology
  • Stakeholder focus
  • Development of synchromodality
  • SMT application fields
  • Network organization
  • Comparative benefits of synchromodality
1. Explanatory
research on
synchromodality
  • Synchromodality theory refinement
  • Literature reviews on SMT problem modeling
2. Contextualizing research on synchromodality
3.
Case study on SMT implementation
4.
SMT implementation linked to further research topics
Table 2. Taxonomy of 1. qualitative dimension: Explanatory research on synchromodality.
Table 2. Taxonomy of 1. qualitative dimension: Explanatory research on synchromodality.
1. Dimension: Explanatory research on synchromodalityAuthorTopic FocusMethod-ology *Stakeholder Focus *Development of SMTApplicationNetwork
Organization
Comparative Benefits of SMT
Category 1: Synchromodality theory refinement
[8]Conceptual SMT
definition and
empirical validation
SLR, I, FG, SD2DConceptual,

Verification & Validation
N/AUsing tools from SYNCHRO-NET or IDS companyFlexibility, Efficiency, Sustainability,
Transparency
[10]Prerequisites and distinguishing
factors of SMT
SLRShipper, D2D, legal entityConceptualN/ANeutral network orchestratorFlexibility, Efficiency, Sustainability,
Transparency
[23]SMT network organizer and technology to enable SMTLRShipper, TSP, D2D, IMConceptualRotterdam, CS:SYNCHRONET5 party logistics providerFlexibility, Efficiency, Sustainability,
Transparency
[6]Critical success
factors of SMT
LR, CSF, IShipper, TSP, D2D, IM, legal entityConceptual,
Verification & Validation
N/ANot explicitly mentionedFlexibility, Efficiency, Sustainability,
Transparency
[17]Enablers/barriers of SMTLRShipper, TSP, D2D, IM, legal entityConceptualN/AExisting actors along the transportation chain or ICT platformFlexibility, Efficiency
[24]Ontology to create definitions of transportation conceptsLRN/AConceptualN/AN/AFlexibility, Efficiency
Category 2: Literature reviews on synchromodal transportation problem modeling
[9]SMT problems dealing with uncertaintySLRTSP, D2D, IMMathematicalN/AN/AN/A
[26]SMT problem classificationLRN/AMathematicalN/AGlobal controllerFlexibility, Efficiency, Sustainability
[27]Methods for SMT planning in inland container networksLR, CSShipper, TSP, D2D, IMMathematical, ConceptualEuropean Gateway Services, RotterdamNetwork
operator
Flexibility, Efficiency, Sustainability
[5]Problem modeling and solution techniquesLRShipper, TSP, D2D, IMMathematicalN/AN/AFlexibility, Efficiency
* Methodology: LR = Literature review|I = Interview with experts|FG = Focus groups with transport logistics experts|S = Survey amongst transport logistics experts|CS = Case study|* Stakeholder focus: D2D = Door-to-door service provider|TSP = Transportation service provider|IM = Inframanager.
Table 3. Taxonomy of 2. qualitative dimension: Contextualizing research on synchromodality.
Table 3. Taxonomy of 2. qualitative dimension: Contextualizing research on synchromodality.
2. Dimension: Contextualizing research on synchromodalityAuthorTopic FocusMethod-ology *Stakeholder FocusDevelopment of SMTApplicationNetwork OrganizationComparative Benefits of SMT
Category 3: A case study on synchromodal transportation implementation
[30]Control over transport modeSShipper, TSP, D2DOperational, BusinessN/ALSP as orchestratorEfficiency, Flexibility
[18]Degree of SMT within companiesQ, I, CSShipper, TSP, D2D, IMOperational, Verification & ValidationContinental & intercontinental companiesLogistics orchestrator via control towerFlexibility, Efficiency
[19]Degree of SMT at European portsLR, FG, CSTSP, D2D,
IM
Conceptual, Operational, TechnicalRotterdam, Antwerp, HamburgCentral institution including a central platformFlexibility, Efficiency, Sustainability
[4]SMT implementation in GhanaLR, CSF, RA, Q SWOTShipper, TSP, D2D, legal entity, IMConceptual, OperationalCS: GhanaLSP as orchestrator + common platform as a control towerFlexibility, Efficiency, Sustainability, Transparency
[29]Automated retrieval of real-time dataI, FGShipper, TSP, D2DOperational, TechnicalCS: 4PL at the Schiphol Airport4PL using a common data platformFlexibility, Efficiency, Transparency
[20]Container consolidationLR, CSShipper, TSP, D2DTechnicalCS: Piraeus, GreeceCloud-based cooperation portalFlexibility, Efficiency, Transparency
[31]Architecture for real time dataCSShipper, TSPOperational, TechnicalN/AControl towerN/A
Category 4: Synchromodal transportation linked to further research topics
[32]Introduction of smart steamingLR, SWOTTSP, D2D,
IM, legal entity
Operational, TechnicalN/ALSP as orchestrator + common information platformFlexibility, Efficiency, Sustainability
[7]Correlation of SMT and PISLRTSP, D2DOperational, TechnicalN/AMulti-stakeholder platformFlexibility, Efficiency, Sustainability
[33]SYNCHRO-NET projectLR, CS: gamingShipper, TSP, D2D, IMOperational, Technical, BusinessSYNCHRO-NETSYNCHRO-modal supply chain eco-NETFlexibility. Efficiency, Sustainability, Transparency
[25]Business models in the field of slow steamingLR, S, BMC, VPCShipper, TSP, D2D, IMOperational, Technical BusinessSYNCHRO-NETOne single platformFlexibility, Efficiency, Sustainability, Transparency
[22]Test information strategiesS, FG,
CS: gaming
IM, legal entityOperationalGaming CS: Modal managerIM as SMT network orchestratorFlexibility, Efficiency, Sustainability, Transparency
[21]Teach SMT conceptQ, CS: gamingShipper, TSP, D2DOperationalGaming CS: Synchro-maniaForwarder as a network orchestratorFlexibility, Efficiency, Sustainability
* Methodology: Q = Structured questionnaire|SWOT = Strengths, weaknesses, opportunities, threats analysis|RA = Regression analysis|BMV = Business Model Canvas|VPC = Value Proposition Canvas.
Table 4. Assessment criteria and taxonomy of quantitative papers.
Table 4. Assessment criteria and taxonomy of quantitative papers.
Assessment CriteriaDimensionCategory
General criteria
  • Overarching problem
  • Mathematical model
  • Solution method
  • Planning horizon
  • Optimization objective
  • Information evolution and quality
Synchromodal transportation-specific criteria
  • System characteristics
  • Scope of horizontal collaboration
  • Transport service characteristics
A-modal booking of shippers
En-route mode and tour recalculation
Predefined truck routes
Predefined departure/arrival schedule
1. Shipment matching problems in synchromodal transportation
  • Deterministic problems
  • Online and stochastic problems
  • Synchromodality and intermodality comparison
2. Synchromodal network mapping
4.
Synchromodal transshipment location planning
5.
Synchromodal transportation revenue management
6.
Transport mode schedule and tour determination
7.
Decentralized decision-making
3. Synchromodal transportation application
8.
Digital planning tools for synchromodal transportation
9.
Synchromodal transportation in the supply chain context
Table 5. Taxonomy of 1. quantitative dimension: Shipment matching problems in synchromodal transportation.
Table 5. Taxonomy of 1. quantitative dimension: Shipment matching problems in synchromodal transportation.
1. Dimension: Shipment matching problems in synchromodal transportationAuthorOverarching Problem*Mathematical Model *Solution Method *Planning HorizonOptimization Objective *Information EvolutionInformation QualitySystem CharacteristicsScope of Horizontal CollaborationA-Modal BookingEn-route re-SchedulingTruck ToursDeparture/Arrival Schedule
Category 1: Deterministic problems
[42]DSMMIP, BIPA: HAOEc: C, E, DelayOnline. SRDeterministicSocial: networkDTM, STM, TTMXFixedRoad: flexible
[48]Network designMOMIPE: SolverOEc: C; En: CO2; P: TTOnline: D, TT, truck speedDeterministicSocial: networkDTM, STM, TTMFlexRoad: flexible
[40]Perishables goodsIPE: SolverOEn: quality lossOfflineDeterministicSocial: networkDTM; STMXFixedAll: Fixed
[41]Cargo allocationState-space modelA: HAOEc: C; En: EOnline: DDeterministicCooperativeTTMXFixedRoad: flexible
Category 2: Online and stochastic problems
[49]DSGSMMIPA: RLAOEc:POnline: TTS: TTSocial: networkDTM, STM, TTMFixedRoad: flexible
[45]Container schedulingMDPA: ADP-VPIOEc: POnline: D, Resource capacity,S: DSocial: LSPFull: DTM, TTMFixedRoad: flexible
[38]DSGSMMIPA: HSAOEc: POnline: SR, TTS: SR, TTSocial: networkDTM, STM, TTMFixedAll: Flexible
[50]DSSMMIP, BIPA: SAA, PHAOEc: C, E, DelayOnline: SRS: SRSocial: networkDTM, STM, TTMFixedRoad: flexible
[37]SITMIPE: SolverOP: TT,Online: TTS: TTSocial: networkSTMX-All: Flexible
[44]STSSNMIP, MDPA: MH, ADPOEc: COnline: DS: DSocial: networkDTM, STM, TTMXFlexAll: Flexible
[51]DSSMIPA: SolverOEc: COnline: DS: DSocial: network-XFixedRoad: flexible
[43]Service selectionMDPA: ADPOEc: COnline: D, TTS: DSocial: networkDTM, STM, TTMFixedRoad: flexible
[36]DSSMTwo-stageA: GAOEc: POnline: DS: DSocial: networkDTMXFlexAll: Fixed
Category 3: Synchromodality and intermodality comparison
[47]SMT planningMDPE: Back-trackingOEc: COnline: TT, resource capacityS: TT, capacitiesSelfishDTM, STM, TTMXFixedRoad: flexible
[46]Long-distance digital twinSimulationA: Simulation optimizationOEc: C, TT; En: E
P: reliability,
Online: order costs, lead-timeS: order costs, lead-times, TTSelfishLimited: DTM, STMXFlexRoad: flexible
[39]RS-BCRMIPE: CS-BFAAOEc: COnline: DS: DSocial: networkDTM, STM, TTMXFlexRoad: flexible
* Overarching problem: DSM = Dynamic and stochastic matching|DSSM = Dynamic and stochastic matching|DSGSM = Dynamic and stochastic global shipment matching|SITM = Synchronized intermodal traffic management|STSSN = Service and transfer selection problem in a synchromodal network|RS-BCR = Repeated schedule-based cheapest route|* Mathematical model: BIP = Binary integer programming|MOMIP = Multi-objective mixed-integer programming|* Solution method: E = Exact|A = Approximate|HA = Heuristic algorithm|RLA = Reinforcement learning approach| ADP-VPI = Approximate dynamic programming-Value of Perfect Information|SAA = Sample average approximation|PHA = Progressive Hedging Algorithm|GA = Genetic algorithm|CS-BFAA = Capacitated schedule-based flow assignment algorithm|* Optimization Objective: Ec = Economic|En = Environmental|P = Performance|C = Cost|TT = Travel Time|P = Profit|E = Emission|* Information evolution and quality: D = Demand|SR = Spot Request|S = Stochastic.
Table 6. Taxonomy of 2. quantitative dimension: Synchromodal network mapping.
Table 6. Taxonomy of 2. quantitative dimension: Synchromodal network mapping.
Dimension: Synchromodal network mappingAuthorOverarching Problem *Mathematical ModelSolution Method *Planning HorizonOptimization ObjectiveInformation Evolution *Information QualitySystem CharacteristicsScope of Horizontal CollaborationA-Modal Booking En-route re-SchedulingTruck ToursDeparture/Arrival Schedule
Category 4: Synchromodal transshipment location planning
[52]SLTPMIPE: SolverSEc: COfflineDeterministicSocial: LSPTTMN/AN/AN/AN/A
[62]TLAPTwo stageA: PHAS-TP: max. transportation utilityOfflineS: transshipment capacitiesSocial: networkTTMN/AN/AN/AN/A
Category 5: Synchromodal transportation revenue management
[54]Cargo fare class mixMarkov ChainA: Greedy TEc: POfflineS: DSocial: networkLimited: DTM, STMXFixedFixed
[53]Cargo fare class mixMIPE: SolverTEc: revenueOfflineS: DSelfishNoneXFixedFixed
Category 6: Transport mode schedule und tour determination
[63]DSSM & Resource schedulTwo stage & IPA: SAA OEc: COnline: D, capacityS: D, capacityLimitedLimited: DTM, STMXFixedFlexible
[55]Cargo allocation and vehicle routing State-space commodity flowE: SolverOEc: COnline: TT, resource capacityS: TTSocial: networkDTM, STM, TTMFlexRoad: flexible
[56]PDPTMIPA: ALNSOEc: C; En: CO2Online: TTS: DSocial: networkDTM, STM, TTMFlexFlexible
[57]Online order assignment IPE: SolverOEc: COnline: D, AAS: D, AASelfishDTM, STMFlexFlexible
[64]Network design IPE: Solver O-TEc: COfflineDeterministicSelfishNoneXFlexRoad: flexible
[65]SMT replanning MIPE: SolverOEc: COnline: D, TT shipment release timeDeterministicSocial: networkDTM, STM, TTMFixedFlexible
[58]Network resource scheduleIPE: SolverOEc: COfflineDeterministicSocial: LSPDTMXFixedFlexible
Category 7: Decentralized decision-making
[59]Resource scheduleMIPE: SolverOEc: COnline: D, costDeterministicLimitedLimited: DTM, STMXFixedFlexible
[66]Inland vessel coordination CP, MIPE: Solver
A: LNS
OP: EfficiencyOfflineDeterministicAllLimited to full: STM, TTMN/AX-Flexible
[61]Dynamic traffic assignment SimulationA: Greedy OEc: COnline: TTS: TTLimited, selfishDTM, STM, TTMX✓/XFlexRoad: flexible
[60]Cooperative model predictive container flow control SimulationA: ALR, ADMMO-TEc: COnline: D, resource capacityDeterministicCooperativeLimited: DTM, STM, TTMX-Road: flexible
* Overarching problem: SLTP = Single-commodity multi-period synchronized Location Transshipment Problem|TLA = Stochastic multi-period Transshipment Location-Allocation Problem|CP = Constraint Programming|* Solution method: (A)LNS = (Adaptive) Large Neighborhood Search|ALR = Augmented Lagrange Relaxation|ADMM = Alternating Direction Method of Multipliers|* Information evolution: AA = Appointment approval.
Table 7. Taxonomy of 3. quantitative dimension: Synchromodal transportation application.
Table 7. Taxonomy of 3. quantitative dimension: Synchromodal transportation application.
3. Dimension: Synchromodal transportation applicationAuthorOverarching Problem *Mathematical ModelSolution MethodPlanning HorizonOptimization ObjectiveInformation EvolutionInformation QualitySystem CharacteristicsScope of Horizontal CollaborationA-Modal BookingEn-route re-SchedulingTruck ToursDeparture/Arrival Schedule
Category 8: Digital planning tools for synchromodal transportation
[67]MCMCFMIPE: SolverOP: flexibility, robustness, customer satisfactionOfflineS: TT, handling timesN/AFull: DTM, STM, TTMFlexibleRoad: flexible
[68]Maritime pattern extraction SimulationA: GAOEc: C, TT; En: EOnline: vessel position dataS: Ship waypointsCooperativeN/AN/AN/AN/AN/A
[71]SMT cargo allocation MIPE: SolverOEc: C, TTOfflineDeterministicSocial: networkNoneXFlexibleFixed
[35]Exceptional Handling & Real-time switching N/A*N/A*OEc: C, TT, fuel consumptionOnline: TT, CDeterministicSelfishN/AXN/AN/A
[72]Multi-objective k-shortest path SimulationA: Sequential heuristicOEc: C; En: CO2;P: reliabilityOnline: SRS: TTSocial: networkFull: DTM, STM, TTMFixedRoad: flexible
Category 9: Synchromodal transportation with Supply Chain focus
[70]Multimodal dual sourcing MIPE: SolverOEc: COnline: D, lead-timesS: D, lead-timesSelfishFull: DTM, STM, TTMXFixedFixed
[69]Dynamic inventory replenishment IPE: simulation-optimizationOEc: COnline: DS: DSelfishNoneXXFixedRoad: flexible
[73]SMT network design MIPE: SolverSEn: E, C, energy consumption OfflineDeterministicLimitedN/AXXN/AN/A
* Overarching problem: MCMCF = Minimum Cost Multi-Commodity Flow problem.
Table 8. Fields of future research on synchromodality.
Table 8. Fields of future research on synchromodality.
Field of DevelopmentOpen Research Fields
Business
Differentiated investigation of the effects of SMT on the cost development of individual cost units and transport actors in comparison to currently used multimodal concepts.
Conceptual design and modelling of a centralized entity with a focus on profit and loss sharing mechanisms as well as more realistic SMT pricing strategies, considering spot requests, demand variations, and cannibalization effects between fare classes.
Further investigation on determining the tasks of a platform organizing SMT and whether an existing actor or an additional player will manage it.
Determination of which overall goals a platform for organizing an SMT network pursues.
Legal
Determination of which legal barriers impede the requested horizontal collaboration and how these can be overcome.
Clarification of liability, data security, and insurance issues of a-modal booking and real-time switching.
Technological/Physical
Investigation on how the connectivity of loading units can be established through IoT technology.
Impact of infrastructure interoperability issues on anticipated en-route real-time switching.
Investigation of which loading units are best suited to be used in SMT.
Mathematical Modeling
Consideration of larger SMT networks in numerical experiments, consisting of multiple transshipment points and transport corridors offering several transport modality alternatives.
Elaboration of a model incorporating transport modalities using alternative fuels or engines (e.g., electric trucks, Methanol-powered barges).
Consideration of truck driver shortages.
Modelling based on data from SMT real-life applications.
Analysis and quantification of cost and travel time effects of SMT shipments facing short-duration disruptions.
Awareness and implementation
Expansion of existing serious gaming methods and expansion of their application among employees are directly affected by process changes induced by SMT.
Further investigation and verification of existing results regarding conditions and compensations under which shippers agree to a-modal booking.
Further investigation and verification of existing results regarding the implementation challenges of individual SMT characteristics differentiated by cultural and legal conditions.
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Rentschler, J.; Elbert, R.; Weber, F. Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research. Sustainability 2022, 14, 13269. https://doi.org/10.3390/su142013269

AMA Style

Rentschler J, Elbert R, Weber F. Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research. Sustainability. 2022; 14(20):13269. https://doi.org/10.3390/su142013269

Chicago/Turabian Style

Rentschler, Johannes, Ralf Elbert, and Felix Weber. 2022. "Promoting Sustainability through Synchromodal Transportation: A Systematic Literature Review and Future Fields of Research" Sustainability 14, no. 20: 13269. https://doi.org/10.3390/su142013269

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