Sie können Operatoren mit Ihrer Suchanfrage kombinieren, um diese noch präziser einzugrenzen. Klicken Sie auf den Suchoperator, um eine Erklärung seiner Funktionsweise anzuzeigen.
Findet Dokumente, in denen beide Begriffe in beliebiger Reihenfolge innerhalb von maximal n Worten zueinander stehen. Empfehlung: Wählen Sie zwischen 15 und 30 als maximale Wortanzahl (z.B. NEAR(hybrid, antrieb, 20)).
Findet Dokumente, in denen der Begriff in Wortvarianten vorkommt, wobei diese VOR, HINTER oder VOR und HINTER dem Suchbegriff anschließen können (z.B., leichtbau*, *leichtbau, *leichtbau*).
Das Kapitel geht den Herausforderungen nach, vor denen der Kombinierte Verkehr (KV) steht, wenn es darum geht, die Dienstleistungsqualität und Kosteneffizienz im Vergleich zum Straßen- und Seeverkehr aufrechtzuerhalten. Sie unterstreicht die Notwendigkeit verbesserter Pünktlichkeit, Informationsaustausch und Servicequalität, um den Kundenanforderungen gerecht zu werden, insbesondere aus Branchen wie der chemischen Industrie. Als Lösung für diese Herausforderungen wird das EDICT-Projekt vorgestellt, das sich auf die Verbesserung der digitalen Zusammenarbeit und die Etablierung eines kollaborativen Qualitätsmanagementsystems (cQMS) konzentriert. Das Projekt gliedert sich in drei Arbeitspakete: Verbesserung des Datenaustauschs und der Standardisierung, Einrichtung eines cQMS zur zeitnahen Verzögerungserkennung und -behebung sowie Bereitstellung zusätzlicher Dienstleistungen und Standardisierung von Stammdaten und Kommunikation. In diesem Kapitel wird auch die Bedeutung von Interoperabilität und Zusammenarbeit zwischen verschiedenen Akteuren im KV-Sektor diskutiert. Es schließt mit den erwarteten Ergebnissen des EDICT-Projekts, einschließlich verbesserter Pünktlichkeitsmessung, standardisierter Berichterstattung und verbesserter Interoperabilität, die entscheidend sind, um den KV attraktiver zu machen und zur Ökologisierung des Transportsektors beizutragen.
KI-Generiert
Diese Zusammenfassung des Fachinhalts wurde mit Hilfe von KI generiert.
Abstract
Combined Transport (CT) is one of the most sustainable and safest mode of freight transport in Europe using the advantages of road for the first and last mile and rail for the long-haul journey. The CT chain consists of a comparatively large set of actors and organisation specific rules. Operational issues like a low level of punctuality and related company-specific delay management block efficient quality management and concerted improvement across multiple stakeholders. Under the CEF programme, the European Climate, Infrastructure and Environment Executive Agency (CINEA) co-funded the EDICT project to find pragmatic solutions to ease the connectivity of several existing platforms and to develop standardised master and transaction data to provide a set of interoperable platforms that facilitate the data sharing and interaction between key CT stakeholders. The core innovation is a collaborative Quality Management System (cQMS) that is conceptualised and implemented based on harmonised and improved existing company specific standards for timestamps, delay and cancellation reason codes, and master data. The project partners intend to share a common process design and use a set of interoperable software-as-a-service solutions to improve process and cost efficiency. During the two-year EDICT project lifetime, eight CT stakeholders, under the coordination of the industry association UIRR and consulting partner Consilis, jointly conceptualise, implement, and run a 5-month cQMS demonstrator pilot based on actual operational data.
The project aims to facilitate the digital integration of Road-Rail Terminal Operators, CT Operators, Railway Undertakings and Infrastructure Managers to provide accurate information and ultimately to improve the overall punctuality, reporting and data analysis capabilities, and service quality to door-to-door customers (LSPs and shippers). Thereby, the project contributes to achieve the EU’s policy objectives to increase the share of rail, to push forward the greening of freight transport and contribute to the European mobility data space. The targeted project results lay the foundation for an industry ecosystem solution providing standardised electronic data interchange and sector-wide processes to improve the service quality of regular Combined Transport trains.
Technically, several digital platforms are either introduced, modernised or integrated to achieve the best cost-performance ratio and become attractive for a larger group of customers. Piloting 5 regular trains on 3 different TEN-T corridors will serve to learn in practice about benefits and improvement potentials. The evaluation will be used to refine the business model and the adoption strategy to facilitate a future roll-out to become an industry standard. Consequently, not only the CTOs but also the shippers and LSPs will profit from better information transparency on the status of their goods, causes of delays and long-term improvements based on the analysis and elimination of the root causes of disruptions. Thereby, the project and its future roll-out will significantly contribute to a higher attractiveness of Combined Transport and to achieve the declared objectives of the Green Deal, Fit-for-55 and REPowerEU policy initiatives.
1 Quality Management Improvement Needs in Combined Transport
Combined Transport (CT) needs to improve the service quality and costs compared to pure road and maritime shipments. Despite several previous sector and legal initiatives (e.g. UIRR project in 20061) punctuality of trains as one of the main KPIs on quality performance for Combined Transport customers is currently deteriorating. The main causes are driven by (1) major infrastructure disruptions (e.g. Gotthard Base Tunnel incident in 2023), (2) the Russian-Ukrainian war, (3) post-pandemic recovery lags and slow economic recovery in Europe and China, and (4) shortage of locomotive drivers. Major customer groups such as the chemical industry request a long list of improvements in order to enable a more profound shift to rail [1] with punctuality, information and service quality amongst the highest priorities.
A systemic challenge is that CT is a complex transport system that requires many actors to interact seamlessly while building on initially national-oriented little interoperable railway systems still in transition. The EDICT (Electronic Data Interoperability for Combined Transport) project (www.edict-project.eu) aims to address some of these deficits through an improved information exchange, standardisation and improved collaboration processes through facilitating the identification and resolution of quality failures. Previous projects such as ELETA,2 Q-ELETA feasibility study,3 Digital Train 1.0 and 2.0 (all co-funded under the CEF programme) confirmed that improved processes and IT solutions are needed paired with the different stakeholders’ intention to collaborate more intensively. The targeted outcome is a set of enhancements on standardisation areas, processes and interoperable IT applications that increase the competitiveness of CT, and thereby contribute to the carbon reduction of the transport sector that is still difficult to achieve in the near future [1].
Anzeige
Based on the preliminary activities performed in the Digital Train 2.0, EDICT consists of a set of improvement sub-projects grouped into three work packages. Work package 1 focuses on the amended integration of Combined Transport and TAF TSI compliant data exchange improvement on timestamps between Terminal Operators (TOs), CTOs and the railway stakeholders IMs and RUs within Europe. Work package 2 establishes a collaborative Quality Management System (cQMS) to improve the timely identification of delays, their causes and harmonise the processes of identification and delay reconciliation across stakeholder groups. Work package 3 focuses on providing additional services and standardisation of the relevant master data and communication to customers of CT.
Operational issues like the lack of punctuality, lack of supply chain visibility [2] and related company-specific delay management hinder the efficient quality management and concerted improvement across multiple stakeholders. Customer requests for example from the chemical transport industry (ECTA) identify improvement needs related to (1) supply chain visibility, (2) improved interoperability between modes and stakeholders, (3) data sharing and quality (accuracy, timeliness), and (4) missing standardised KPIs and reporting on punctuality and quality [3].
Section 2 focuses on the IT-supported quality improvement and quality assurance identified in the literature on logistics and its implications for the EDICT project. Section 3 presents the preliminary results and Sect. 4 focuses on the targeted final outcomes. The conclusions highlight the hurdles that still exist and further progress areas required to make CT more efficient and attractive to support the greening of European transport, increase the sustainability of businesses towards a zero-emission future and still offer flexible intermodal mobility options.
2 Quality Improvements in Complex Logistics Services – Status Quo and Development Needs
2.1 Specific Quality Challenges for Logistics Industry
Quality management standards exist in many industries. The ISO 900x standards family [4] is the basis and is supplemented by many industry-specific standards mainly focusing on the product manufacturing parts such as aviation (ISO 9100), automotive (ISO/TS 16949) or pharma (GMP, GDP). Most of these international standards focus on the manufacturing or distribution of products (e.g. GDP). For the logistics service industry specific standards are developed (e.g. ISO 23354) and for the rail industry the newly updated standard ISO/DIS221634 is officially available since July 2023. As for other service industries, the key challenge is that the expected quality needs to be agreed upon between the service partners in the tolerance zone between desired and adequate quality service levels [5]. One challenge of logistics services is that only part of the total service has physically measurable characteristics where the production-oriented quality measures of manufacturing industries are applicable. The concept of perceived quality [6] as defined by the customer group versus the objective service quality is highly relevant for transport logistics services. The end customer defines the quality standards, and the complex business ecosystem of service providers needs to exchange information and documents, optimise processes and commercial data exchange to meet the customer expectations. These requirements must cascade down from the logistics forwarders to the CTOs, TOs, RUs, and IMs with optionally inspection and shunting yard service providers in between. The classical quality in services (e.g. SERVQUAL service quality measurement model) are for business-to-business services considered as too much focused on functional and process aspects and too little on the technical and outcome perspectives [7].
Anzeige
Quality in logistics services [8] and e-service success [9] are key drivers for logistics success. This correlation has been demonstrated in many papers [7] and a causation is plausible. The significant impacts of facilitating the use of IT systems to positively influence the logistics process service quality and the customer satisfaction via the logistics service outcome quality is shown in Fig. 1.
Fig. 1.
Logistics Service Quality improvements and IT systems use
Logistics Service Quality (LSQ) in recent years is gaining importance. LSQ is equally essential for Logistics Service Providers (LSPs) and customers [10]. In the context of CT, the logistics quality has an additional eminent sector importance through its contribution to the modal shift and greening of freight. In the competition between transport modes not only price but increasingly quality in terms of reliability, correctness and punctuality is a driving factor. In 2023, the Combined Transport sector suffered from lower service quality – especially in the punctuality dimension due to infrastructure outages and fierce price competition that led to a reduced service frequency on some routes.
For an industry-wide solution, a standard set of service quality KPIs and reports were to be agreed between the EDICT project members. With increasing IT-intensity and availability of data that is shared (see European Common Mobility Data Space (COM(2020)789, 2020)) the application of efficient and effective IT solutions to improve services is a relevant factor identified already several decades ago [11] and still requiring improvement.
In this paper we will only address the efforts towards improving the punctuality measurement as key focus of the EDICT project. It defines a set of measures, interorganisational processes and IT changes to increase the service quality of Combined Transport. The IT technical purpose of the EDICT project is to improve the inter-organisational processes, data exchange and IT-integration between stakeholders and other CT IT platforms.
A lack of common data quality [12] and quality understanding in the logistics industry in Europe was identified [8] which prompted to focus on a common definition of “Transport logistics quality (..) as the degree to which the performance of the freight transport operations, across modes in the supply chains, meets stated service criteria and should incorporate the elements of reasonable price, transit time, punctuality, reliability and sustainability” [13].
2.2 Quality Improvement Needs in Combined Transport
Several overview papers on the state and importance of logistics quality were published recently [14]. Bienstock et al. [7] analysed the impact of IT tools and services to increase the quality of logistics services. We slightly adapted their key findings to the context of CT from a customer viewpoint (LSPs or shippers). An industry comparison on centralized aviation quality management has been performed in the Feasibility Study to Rail Collaborative Decision Making (Rail CDM) and several timestamps and principles were transferred to the EDICT solution design where applicable in review workshops with the seven operative business partners of EDICT. The outputs of predecessor projects ELETA, and Digital Train 1.0 and 2.0 were integrated, too. Especially TOs face the lack of easy to use and cost-efficient data exchange and quality management processes. Within the CTOs company-specific approaches were analysed and compared. The desire to improve the standardisation of data exchange and unified quality measurements with a focus on punctuality was guiding the target solution within the EDICT project.
3 Results and Discussion
One key challenge was to identify the degree of collaboration achievable between competitors. The provision of the project guidance towards collaboration and sustain the commitment to deliver a common solution with partial funding is instrumental to change mindsets towards solving challenges collaboratively to improve logistics quality and performance. Complementary, the orientation towards common objectives needs to be tracked and broken down in the project lifetime plus the success monitored to avoid operative day-to-day tasks to weaken momentum.
3.1 Solution Design Challenges
The solution design challenge the EDICT project partners faced was to overcome several hurdles together and to agree upon a common process, data exchange and IT solution architecture:
1.
Company-specific punctuality measurement and reason code harmonization challenges
2.
Avoid the ‘blame & shame’ game between two supply chain players via a conflict reducing reconciliation facilitation process
3.
Avoid company focused or only bilateral relationship regulations for common challenges to materialise (see [8])
4.
Overcome the distributed benefits challenge [9] where partners are not equally benefiting from a change without readjusting the boundary conditions
Together with the project partners the insight was reached that total efficiency, cost savings and global quality improvement goals are only achievable through enhanced collaboration based on a common IT application (cQMS).
3.2 Business Ecosystem Design for Interoperability
Interoperability of organisations, processes, and data [15] within the regulatory environment builds on extending the conceptual interoperability to organisational units including the business ecosystem interoperability level required for CT [16] (see Fig. 2). The need arises from the decentralised interorganisational and multi-stakeholder nature of the CT business [17, 18]. Additionally, modularity and complementarity are design principles for both Business Ecosystems (BE) such as for CT [19] and the cQMS complemented by standardisation and interoperability. The full set of interoperability levels needs to be addressed for successful BE-wide transformations such as the CT sector with mutual adjustment needs on all levels to increase competitiveness with other transport modes.
Fig. 2.
Interoperability levels to be covered for collaborative processes and IT architectures
The partial transformation of CT with at minimum 6 different stakeholder types can be best understood with an underlying BE view (see [18, 20]). The CT innovation area requires co-opetition between competitors and co-creation to agree on common future processes, interoperable standards and IT services. The role of the orchestrator fostering open innovation [21] is temporarily performed by Consilis and UIRR in the project context. Business ecosystems transformation including all stakeholders is complex and time consuming [22, 23]. The total scope can be visualised in the Business Ecosystem Transformation framework applied to other large-scale transformations [15, 24].
The need to collaborate is not only given by the multi-stakeholder structure but also to achieve process efficiency, customer-orientation and IT efficiency driven. Identifying different reason codes per bilateral customer-supplier relationship is time consuming and inefficient. Avoiding different coding systems per customer-supplier relationship is a key driver to strive for a standard. The project developed together with seven combined transport actors harmonised timestamps and a two-level delay reason and train cancellation coding system. The purpose of these emerging standards is to ease the harmonised classification of a disruption and the corresponding reporting system. The cQMS provides the standardised information basis to identify delays compared to the scheduled train run as well as documenting and analysing the causes.
The following data exchange gaps required to be closed as pre-requisites to meet the punctuality assessment and improvement tasks:
Identifiable stakeholders (e.g. CTO to be introduced into the TAF TSI legal framework) (see TAF TSI handbook)
List of common delay reason and cancellations codes related to CT operations (to be introduced as well in the TAF TSI Regulation)
Definition and improvement of a standard message format to exchange the relevant information between all actors and IT platforms
Provide a process for the clarification of the main causes of delays to facilitate the dispute resolution (reconciliation process)
3.3 Solution Elements
The design and specification phase of the 10 subcomponents of the project has been completed. Their conceptual interplay is visualised in Fig. 3. The internal interdependencies are more complex on a detailed level which increases the need to motivate and align the project partners to dedicate sufficient resources and priorities for a two-year transformation project.
The standardisation of the data exchange and CT-compatible list of timestamps has been achieved (WP1) and the specification of the cQMS and the tender process is completed (WP2). The cQMS is in its configuration process and the testing of the collaborative solution with live data starts in December 2023. The chosen solution was the best fit from 4 short-listed providers. The winning company offers an existing Software-as-a-Service (SaaS) solution for CT. Due to the complex BE, the choice was made for a hybrid agile design method to be able to deliver in time and reduce the time to provide a working pilot. A two-phase roll-out was chosen to reduce complexity, implementation risk and give all cQMS demonstrator partners and involved IT platforms sufficient time to prepare their interfaces, standards, and mapping activities.
The cQMS is based on harmonised and improved existing company specific standards for timestamps, delay and cancellation reason codes, their reconciliation as well as digital, harmonised reporting, and master data exchange via several IT platforms.
Central alignment instruments were the ‘AS IS’ and’TO BE’ process modelling with each partner to identify if a common approach is feasible within the project constraints. Due to a high degree of similarity the partners agreed to a common future process flow and interface standards.
The second key alignment activity was the BE-wide IT architecture design (see Fig. 4). The selection of messages, the IT platforms to be used and the conversion activities between the IT platforms were salient prerequisites towards implementation planning. Both the process design and the IT architecture were required to explore the appropriate degree of change the project members were able to collectively commit to.
Thirdly, the specification and alignment of the first set of delay reason codes and cancellation codes within the project partners as well as an extended group of terminals was required to establish the foundation for the harmonised reporting system.
Fourthly, the selection of master data and transaction data elements throughout the project partners and the migration paths towards the common set was required to simplify the final solution and reduce the costs and efforts to implement and maintain the solution.
Lastly, the interoperability of platforms is a central element to increase the efficiency of the data exchange capabilities between the relevant players. Figure 4 highlights the 5 relevant IT platforms that need to interchange messages to record the timetables, timestamps, reason and cancellation codes with the respective stakeholders. The integrated solutions are (1) KV4.0 as central data hub, (2) cQMS as centralized information collection, delay processing and reporting platform, (3) RNE TIS for information exchange with the IMs and RUs, and the (4) UIRR master data service platform to synchronise ILU codes, location codes etc. according to TAF TSI standards, and (5) the CESAR Next CT customer communication platform. The long-term target should be to establish interoperable digital services that facilitate the shift-to-rail for all business ecosystem stakeholders similar to efforts initiated in the rail-based passenger transport environment [25].
3.4 Expected Final EDICT Results
The tender process resulted in the selection of Simply Deliver as SaaS platform provider and the interoperability of several existing IT platforms. The project enables the exchange of standardised information via EDIGES (rail-road transport) and TAF TSI (rail transport) standards.
In the cause of the project several replanning processes were required due to time and resource constraints that were not foreseeable at the conception phase. Despite these extra hurdles the partners are motivated to deliver meaningful results to improve the data exchange, quality measurement, and improvement potentials.
3.5 Limitations and Future Development and Research Needs
The following improvement areas are identifiable before the final results are produced on the assumption that no unknown and unsurmountable hurdles may occur during the remaining project phase:
1.
Adoption of status, reason code and message standards, processes and IT services by more sector stakeholder types (e.g. RUs, LSPs and consignors)
2.
Direct involvement of other partners to enhance the business ecosystem through enabling the roll-out to more CT stakeholders within Europe and Central Asia (long-term view)
3.
Faster reaction to disruptions by functional enhancements towards exception and prevention management
4.
Interface modernisation and migration to renewed platforms to reduce interfacing costs (e.g. REST APIs)
5.
Quality improvement measures to identify and manage collaborative quality improvement projects and identify measures within the common cQMS
6.
Explore the extension of scope (e.g. document exchange and electronic freight transport information (eFTI) compliance (EU 2020/1056)
The above-mentioned future development directions will be assessed after the final outcome of the live demo and the evaluation of the data quality, user acceptance and cQMS project assessment.
4 Conclusions
Early results are the aligned set of timestamps, delay reason and cancellation codes for the identification of disruptions in the supply chain and to assure a TAF TSI compliant information exchange between CT stakeholders. Furthermore, an extension of the communication with CT customers via the updated CESAR Next platform has been achieved. These efforts should contribute to fostering CT attractiveness to shift to rail by contributing to increased stability, punctuality and reliability for customers through facilitated information exchange, quality management process enabling, and eased interoperability.
Future research is required to accelerate the adoption and further refinement of the established and newly created standards (e.g. CT reason and cancellation codes). The harmonization and extension of the nucleus to include both LSPs and shippers is part of the way forward and the integration of higher automation in the classification as well as enhanced exception and prevention processes are natural development phases. This targeted achievement and future larger scale impact relies on the incentives, positive results, and the willingness to collaborate with the existing and potential future partners of the cQMS.
Key learnings are that further improvement and alignment of processes between different stakeholder groups takes time and a BE coordination which was performed by UIRR with the support of Consilis is instrumental. First successful steps have been made. More effort to increase the interoperability of processes and information systems is required to improve the competitive position of CT in areas where the access is available and the service offering is possible. The EDICT project and especially cQMS show a path to improve the service quality with punctuality as one of the key deficits of CT if compared to pure road or sea freight and road shipments. The contribution to a larger shift to rail and CT can be significant if the outcome of the project is successful and widely adapted in the future. The first implemented steps on a longer BE transformation roadmap that not only require processes and IT improvements but also further asset availability and standardisation improvements towards a greener transport future in compliance with the Green Deal and REPowerEU targets.
5 Methods Applied
Participatory action research [26] is well suited for complex and sometimes messy situations often uncovered in complex logistics and supply chain settings [27]. It is a fitting qualitative research method to innovate, reality test and learn from new or adapted artefacts. It is positively applied to logistics context to innovate processes in a small business ecosystem [28]. Consilis conducted as-is and to-be process and IT architecture improvement interventions as well as master data and transaction data workshops with all four companies to identify the change needs and common process requirements. Research methods applied used multiple sources of evidence collection [29] such as online plus physical workshops, document studies, and meetings that were transcribed to identify key themes. The constructs were presented and discussed with representatives of different functions of the four company participants and additional UIRR association members. The identified hurdles were resource constraints and other projects that were prerequisites to the agreed-upon changes corroborated by unplannable external events with significant business impact outside the sphere of influence of the core CT stakeholders.
A mix of qualitative research methods [30, 31] are used to innovate current practice with solution elements present in other comparable industries (e.g. aviation) or established in a few companies only. The objective of the demonstrator is to identify the suitability of the chosen processes, standards and IT architecture. With the real-life insights and single loop plus double loop learning the adoption strategy for the future roll-out to a wider scope will be crafted, if successful.
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Q-ELETA feasibility study was a sub-project under Digital Train 2.0 CEF co-financed. It analysed the quality management system of European Combined Transport operations coordinated by UIRR (2021).
Hoyle, D.: ISO 9000 - Quality Systems Handbook: updated for the ISO 9001:2015 standard, 7th edn. Routledge, New York (2018)
5.
Zeithaml, V.A., Berry, L.L., Parasuraman, A.: The Nature and Determinants of Customer Expectations of Service. Academy of Marketing Science, 1–12 (1993)
6.
Zeithaml, V.A.: Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. J. Mark. 52(July), 2–22 (1988)CrossRef
7.
Bienstock, C.C., Royne, M.B., Sherrell, D., Stafford, T.F.: An expanded model of logistics service quality: Incorporating logistics information technology. Int. J. Prod. Econ. 113(1), 205–222 (2008)CrossRef
8.
Milorad Kilibarda, M.A.V.P.: Research in logistics service quality. Transport 35(2), 224–235 (2020)
9.
Klueber, R.G.: Frameworks and Models to Identify and Increase the Success Potential of E-Services. Ph.D., University of Surrey, School of Management, Guildford, UK (2005).
10.
Mentzer, J.T., Flint, D.J., Hult, T.M.: Logistics service quality as a segment-customized process. J. Mark. 65, 82–104 (2001)CrossRef
11.
Prahalad, C.K., Krishnan, M.S.: The new meaning of quality in the information age. Harvard Bus. Rev. 77(5) 109–118 (1999)
12.
Fu, Q., Easton, J.M.: Understanding data quality: ensuring data quality by design in the rail industry. In: IEEEE International Conference on Big Data (BIGDATA), pp. 3792–2799, Boston, MA (2017)
13.
Islam, D.M., Zunder, T.H.: The necessity for a new quality standard for freight transport and logistics in Europe. Eur. Transp. Res. Rev. 6, 397–410 (2014)CrossRef
14.
Arbelen, G., Kaya, T.: Assessment of logistics service quality: a qualitative approach. J. Shipp. Trade 14(6) (2021)
15.
Kher, R., Sooklal, A., Nair, A.S., Anand, J., Klüber, R.: Effective International Partnership For Health And Wellbeing: Interoperable, Holistic, Integrative. T20, New Dehli (2023)
16.
Tok, A., Diallo, S.Y., Turnitsa, C.D.: Applying the levels of conceptual interoperability model in support of integratability, interoperability, and composability for system-of-systems engineering. J. Syst. Cybernet. Inform. 5(5) (2007)
17.
Jacobides, M.G., Tae, C.J.: Kingpins, Bottlenecks, and Value Dynamics within a Sector. Organ. Sci. 26(3), 889–907 (2015)CrossRef
18.
Hannah, D.P., Eisenhardt, K.M.: Origins and Outcomes of Firm Strategy in Nascent Ecosystems. Standford University, Stanford (2015)
19.
Jacobides, M.G., Cennamo, C., Gawer, A.: Towards a theory of ecosystems. Strategic Manag. J. 2255–2276 (2018)
20.
Lewrick, M.: Business Ökosystem Design. Vahlen, Munich (2021)
21.
Stadler, C., Hautz, J., Matzler, K., von den Eichen, S.F.: Open Strategy - Mastering Disruption from Outside the C-Suite. MIT Press, Cambridge, MA (2021)CrossRef
22.
Kranasios, S., Breidbach, C., Mann, G.: Orchestrating the digital transformation of a business ecosystem. Strategic Inf. Syst. (2022)
23.
Fuller, J., Jacobides, M.G., Reeves, M.: The Myths and Realities of Business Ecosystems. MIT SMR Frontiers / Research Highlight, Boston (2019)
24.
Nair, A.S., Klüber, R.: Digital contact tracing interoperability: balancing privacy and public health concerns to fight COVID-19. Diplomatic Courier, 25 September (2020)
25.
Ferreira, M., Castro, J.M., Perras, A., Mili, S.: Shift2Rail IP4: building an interoperable mobility ecosystem at a European scale. Transp. Res. Procedia (2022)
26.
Argyris, C., Schön, D.A.: Participatory action research and action science compared: a commentary. Am. Beh. Sci. 32, 612–623 (1989)CrossRef
27.
Näslund, D.: Logistics needs qualitative research - especially action research. Int. J. Phys. Distrib. Logist. Manag. 32(5), 321–228 (2002)CrossRef
28.
van Lange, P., Pijper, G., de Vries, P., Brazier, F.: Participatory design of participatory systems for sustainable collaboration: exploring its potential in transport and logistics. Sustainability 15, 1–43 (2023)
29.
Yin, R.K.: Case Study Research and Applications: Design and Methods, 6th edn. Sage Publications, Los Angeles (2017)
30.
Miles, M.B., Huberman, M.A.: Qualitative Data Analysis: An Expanded Sourcebook, 2nd edn. Sage Publications, Thousand Oaks (1994)
ISO: Railway applications - Railway quality management system - ISO 9001:2015 and specific requirements OFR application in the railway sector, ISO (2022)
