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This editorial introduces this Special Issue on advances in research on digital interoperability and trans-formation in logistics and supply chain management. Eleven high-quality and original research works from both researchers and practitioners in the area have been selected to compose this Special Issue.This editorial first introduces the scientific context relevant to the Special Issue, then presents each of the eleven papers. From these papers, this editorial identifies several interesting prospective works, which are finally presented.
Digital interoperability and transformation in logistics and supply chain
management: editorial
Shenle Pana,*, Damien Trentesauxb, Duncan McFarlanec, Benoit Montreuild, Eric Ballota,
George Q. Huange
To cite this article:
Shenle Pan, Damien Trentesaux, Duncan McFarlane, Benoit Montreuil, Eric Ballot, George Q. Huang
(2021) Digital interoperability and transformation in logistics and supply chain management: Editorial,
Computers in Industry, Volume 129, 103462 (https://doi.org/10.1016/j.compind.2021.103462)
a MINES ParisTech, PSL Research University, CGS -Centre de gestion scientifique, i3 UMR CNRS 9217, 60 Bd
St Michel 75006 Paris, France
b LAMIH UMR CNRS 8201, Université Polytechnique Hauts-de-France, 59313 Valenciennes cedex 9, France
c Institute for Manufacturing, University of Cambridge, 17 Charles Babbage Road, Cambridge CB3 0FS, United
Kingdom
d Physical Internet Center, Supply Chain & Logistics Institute, H. Milton Stewart School of Industrial & Systems
Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
e HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering , The
University of Hong Kong, Hong Kong, PR China
Abstract: This editorial introduces this Special Issue on advances in research on digital interoperability
and transformation in logistics and supply chain management. Eleven high-quality and original research
works from both researchers and practitioners in the area have been selected to compose this Special
Issue. This editorial first introduces the scientific context relevant to the Special Issue, then presents
each of the eleven papers. From these papers, this editorial identifies several interesting prospective
works, which are finally presented.
Keywords: Digital interoperability, Digital transformation, Logistics, Supply Chain Management,
Editorial, Special issue.
1. Context
To surf on the wave of digitalization, companies are keen to improve digital interoperability
through the digital transformation process. Digital interoperability is the ability to achieve quick,
seamless, secure, and reliable data and information exchange between companies (Pan et al.,
2021). The ability is of particular importance in the area of logistics and supply chain
management (LSCM) which stresses the importance of cross-organizational and cross-
functional collaboration for strategic planning and operation management. Although digital
transformation is well underway in this area, companies are still struggling to find efficient and
effective solutions and approaches to enhance the digital interoperability, especially at large-
scale level (Leal et al., 2019).
The practical need for enhancing digital interoperability in LSCM has been particularly
witnessed in the COVID-19 pandemic. A large number of issues regarding resilience and
viability of the contemporary supply chain have been highlighted, most of which are pointedly
related to the problem of digital interoperability, such as supplier’s information viability and
sharing, logistics service provider’s operational information availability, end-to-end supply
chain mapping and monitoring. At the beginning of the outbreak in early 2020, these issues
were even more obvious to the companies (or those having suppliers) located in the quarantined
areas. This can be attributed to the presence of information silos, i.e., the isolated information
and data owned by individual companies or systems. Due to the lack of fast and reliable
communication among the silos, information sharing is very limited. One of the goals of digital
interoperability is to interconnect these information silos such that information can be
exchanged in efficient and effective way with privacy preservation.
On the other hand, recent research has suggested the need to consider not just supply chains but
supply networks. New relevant paradigms include intertwined supply networks (Ivanov and
Dolgui, 2020) and Physical Internet (Montreuil, 2011; Ballot et al., 2014), which advocate
horizontal and vertical collaborations based on the interconnection of the existing logistics
networks for sharing the logistics resources and services involved. Likewise, in accordance with
the Industry 4.0 principles such as plug-and-play and the systems of systems, recent approaches
used in digital logistics systems modeling also put emphasis on the interconnectivity of systems
(including objects, information entities, etc.). Among them, for example, Cyber-physical
systems, semantics and ontology, and digital twins are the most investigated recently (Derigent
et al., 2020). For all these new approaches and paradigms, digital interoperability is a key to
success that makes company-to-company, network-to-network, or system-to-system
communication possible and reliable.
It is in this context that digital interoperability has gained increasing attention in LSCM, from
both researchers and practitioners in the area. Considering the recent challenges placed on
today’s logistics systems, as well as the new opportunities empowered by the disruptive
technologies, new research questions and issues that merit more attention are put forward.
2. The current research focus
This Special Issue aims to advance the research on digital interoperability in LSCM, by
collecting the high-quality and original research works from both researchers and practitioners
in the area, and by raising new research questions. The scope is wide enough to incorporate the
most relevant contributions including development and application of concepts and solutions,
disruptive technologies and techniques investigation, state-of-the-art or survey studies, etc.
The Special Issue particularly encourages the cutting-edge solutions that foster logistics and
supply chain collaboration at large-scale level. The solutions and the related issues that are
investigated by the papers included in this Special Issues are summarized in Table 1. The
solutions can be grouped in four main categories that are hereinafter discussed, as displayed in
Figure 1.
Title
Authors
Solution
An approach and decision support tool for
forming Industry 4.0 supply chain collaborations
Sonia Cisneros-Cabrera, Grigory
Pishchulov, Pedro Sampaio, Nikolay
Mehandjiev, Zixu Liu, Sophia Kununka
Digital
platform
Digital connectivity in an innovative joint
distribution system with real-time demand update
Yuan Shi, Meng Chen, Ting Qu, Wei
Liu; Yiji Cai
Data-driven
planning
Use of proximal policy optimization for the joint
replenishment problem
Nathalie Vanvuchelen, Joren Gijsbrechts,
Robert Boute
Machine
Learning
Synchromodal transportation planning using
travel time information
Hannah Yee, Joren Gijsbrechts, Robert
Boute
Data-driven
planning
Orchestrating product provenance story: When
IOTA ecosystem meets electronics supply chain
space
sabah suhail, Rasheed Hussain, Abid
Khan, Choong Seon Hong
Blockchain
Blockchain-enabled circular supply chain
management: A system architecture for fast
fashion
Bill Wang, Wen Luo, Abraham Zhanga,
Zonggui Tian, Zhi Li
Blockchain
An information architecture to enable track-and-
trace capability in Physical Internet ports
Patrick Fahim, Yusong Pang, Jafar
Rezaei, Lorant Tavasszy, Rowoon An,
Benoit Montreuil
API
Peeking into the void: Digital twins for
construction site logistics
Toni Greif, Nikolai Stein, Christoph
Flath
Digital twin
Cyber physical system-enabled synchronization
mechanism for pick-and-sort ecommerce order
fulfilment
Xiangtianrui Kong, Xuan Yang, Kelin
Peng, Clyde Zhengdao Li
CPS
An investigation into emerging industry 4.0
technologies as drivers of supply chain innovation
in Australia
John L. Hopkins
Empirical
study
Digital interoperability in logistics and supply
chain management: state-of-the-art and research
avenues towards Physical Internet
Shenle Pan, Damien Trentesaux, Duncan
McFarlane, Benoit Montreuil, Eric
Ballot, George Q. Huang
Landscape
analysis
Table 1. Papers included in this Special Issue.
Figure 1. The four main categories of solutions presented in the Special Issue.
Digital platform: Digital platform can be seen an online platform that consists of information
systems, interfaces and engines for the users to collect, exchange and search information. It
could be web-based or mobile application-based marketplaces for BtoB, BtoC or CtoC markets
(B for business, C for consumer). As per its advantages especially for ecosystem development,
digital platform has been considered as a powerful tool of digital transformation, which also
assists the interoperability among companies connected to the ecosystem. However, several
issues must be dealt with in order to ensure the effectiveness and efficiency, for example, data
format and integration, privacy preservation, information system architecture, searching and
matching engine and algorithms design. These issues are particularly crucial for large-scale
multi-party supply chain and logistic collaboration, as demonstrated by (Cisneros-Cabrera et
al., 2021). From a practical point of view, the authors design a digital platform as a decision
making tool for matching demands and supplies from companies in manufacturing. On the
demand side, companies post Call for Tenders with specific requirements; on the supply side,
suppliers publish their capabilities available. As the platform is ontology based, the devised
matching algorithm is able to efficiently and effectively match the demands and supplies. The
interoperability is therefore enhanced for multi-party at large-scale.
Data-driven solution design, planning, modeling and control: The decision-making processes
in LSCM have been conventionally and primarily supported by Operations Management &
Operations Research (OM/OR) fields. Moreover, purely data-driven approaches have also
shown the great potential to assist in the processes, such as using real-time information for
dynamic planning, exploiting historical data for forecasting, etc. This can be considered as a
reorientation of some of the traditionally mathematical approaches to OM/OR. For example,
Yee et al. (2021) suggest to use cargos’ real-time travel information in synchromodal
transportation planning. The results denote that real-time information may help optimize modal
choice by minimizing the total transportation and overtime delivery costs. Likewise, Shi et al.
(2020) investigate the importance of real-time demand update in joint distribution systems, i.e.,
horizontal collaboration among shippers. They propose an architecture of digital connectivity
for the dynamic joint distribution system, in order to collect and communicate synchronously
and continuously data from customers, shippers, logistics platforms, etc., for the purpose of
route optimization. More recently, the application of Machine Learning technique in logistics
industry has further fundamentally altered the conventional approaches, enabling more efficient
and visionary decision-making process. In the work of (Vanvuchelen et al., 2020), the authors
experiment proximal policy optimization (PPO) algorithms in joint replenishment schemes,
which is an optimization method in the domain of deep reinforcement learning. The results of
their experiments show that, whatever at small- or large-scale, the suggested PPO algorithm
outperforms the conventional heuristic methods for joint replenishment decision making. It
means the algorithm can eventually facilitate the coordination in cooperative logistics schemes,
especially at large-scale. This first work should encourage more research on the applications of
AI in the area of LSCM.
Blockchain and API: To alleviate some critical issues related to data sharing, e.g., data tracking,
traceability, trustability, and privacy preservation, Blockchain or API (Application
programming interface) based disruptive solutions have been put forward. For example, the
blockchain technology is being growingly investigated in LSCM for the traceability of material,
responsibility or data, e.g., Wang et al. (2020) use it for tracing the reuse of materials for circular
supply chain management in fast fashion, and Suhail et al. (2020) suggest IOAT blockchain to
ensure trustworthy data for tracing product provenance from raw material to end of life. Further,
the technology of Smart Contracts based on blockchain is also receiving increasing attentions,
especially for automating processes and exchanges, like services procurement and payment.
APIs are also used to simplify and secure data exchange, as shown in the case of track-and-
trace capability in Physical Internet ports done by (Fahim et al., 2021). Besides, API is also the
key technology to provides blockchain with information from the outside world, in other words,
to connect blockchain to other data bases. As the research on Blockchain in the area of LSCM
is still in its infancy, a number of issues still need to be addressed, such as scalability, typology
(open, private or consortium), time- and cost-effectiveness, and sustainability of the technology.
Digital twin and Cyber-physical systems: One outcome of the digital transformation in many
industries is that physical object and its lifecycle can now be sharped in the digital world, thanks
to the advancement of IoT and sensing technologies. The virtual counterpart, namely Digital
twin, can then be used to handle the very complex problems, such as product design, real-time
status monitoring, maintenance scheduling, new value creation, etc. In addition, cyber-physical
systems (CPS) that integrate technologies of sensor, computing and communication are
primarily used to intertwine physical and cyber worlds for the purpose of controlling the objects.
Based on these technologies, digital interoperability can be achieved among objects (or systems,
companies). In the literature, intralogistics is currently the main field of application. The authors
in (Greif et al., 2020) apply digital twin concept on the silos in construction sites; and they
prove that the developed digital silo twins can offer new business values as well as supports for
silo dispatch and replenishment decisions. Another common application is related to logistics
platform, since smart (or intelligent) objects are now being employed in intralogistics systems,
for example, industrial wearables, AGVs (automated guided vehicles), AMRs (autonomous
mobile robots), autonomous vehicles. Kong et al. demonstrate in their paper (Kong et al., 2020)
that integrating smart objects and CPS modelling may become an efficient and effective
solution for pick-and-sort operations in ecommerce fulfilment centers. These works showcase
the capability of digital twin and Cyber-physical systems in LSCM, especially to handle the
high complexity of decision-making and control.
It is worth mentioning that two papers in the Special Issue are putting focus on the digital
interoperability research landscape rather than on specific solutions. Pan et al. (2021) provide
a comprehensive bibliometric analysis on the stat-of-the-arts solutions for digital
interoperability in LSCM. The research trends, as well as new challenges raised by recent
paradigms such as Physical Internet are discussed. Some future research avenues are also
pointed out in order to advance the research. In another paper (Hopkins, 2021), the author
applies empirical methods to investigate how emerging industry 4.0 technologies drive the
SCM innovations, the digitalization and the inter-company connectivity.
3. Discussion
Since digital interoperability is an emerging research topic in the area of LSCM, this Special
Issue with the included contributions should encourage more research on the topic. Several
research questions can be discussed here.
First, the solutions discussed above could be further industrialized and deployed in real-life
world, especially for large-scale multi-party logistics systems. It is foreseeable that some design
issues must be addressed beforehand.
Second, this Special Issue also reveals the significance of interdisciplinary approaches to the
research topic, involving operations research, data science, computer science, information
system management, software and hardware engineering, as well as systems and organizational
theory. It is believed that this axis will attract more attention in the future.
Third, as shown by the studies above, data-driven and digital twin-driven approaches have the
great potential to enhance system-to-system, object-to-object, or object-to-context
interoperability. Data-driven approaches include Big data analytics, data mining, machine
learning, graph database etc.; and digital twin-driven approaches are for example semantics and
ontology, cyber-physical systems, holonic systems, etc. The research on the application of such
approaches in LSCM has just begun.
Last, blockchain and especially smart contract technologies are being considered as an enabler
of automated processes and autonomous (self-organizing) systems. But one main issue is the
interconnection and dynamic interaction among such processes and systems so that real-time
information could considered and communicated. Recent concepts like Oracle (e.g., Chainlink)
show the potential to deal with the issue, but more research on the proof of efficiency of
applications in LSCM are still appealing.
With the development of the above-mentioned technologies, this emerging research field will
also have to consider organizational questions related to adoption and the transformational
potential of such technologies implemented at large-scale level by companies involved in
supply networks in general.
Acknowledgement
First of all, we should express our sincere thanks to the authors and the anonymous reviewers
who have greatly contributed to this Special Issue. We thank the authors for their high-quality
and original scientific contributions, and the reviewers for their valuable time and support given
to the double-blind peer review process, that are especially precious during the pandemic
outbreak in 2020. Last but not least, we are grateful to the Computers in Industry editorial board
and office, especially the current Editor-in-chief Professor Bernard Grabot and the current
editorial manager for Special Issues Dr. Nick Szirbik, for their precious advice and trust on
the guest editors. It is with their support of utmost importance that this Special Issue come to
fruition.
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