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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 (
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
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.
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 connectivity in an innovative joint
distribution system with real-time demand update
Yuan Shi, Meng Chen, Ting Qu, Wei
Liu; Yiji Cai
Use of proximal policy optimization for the joint
replenishment problem
Nathalie Vanvuchelen, Joren Gijsbrechts,
Robert Boute
Synchromodal transportation planning using
travel time information
Hannah Yee, Joren Gijsbrechts, Robert
Orchestrating product provenance story: When
IOTA ecosystem meets electronics supply chain
sabah suhail, Rasheed Hussain, Abid
Khan, Choong Seon Hong
Blockchain-enabled circular supply chain
management: A system architecture for fast
Bill Wang, Wen Luo, Abraham Zhanga,
Zonggui Tian, Zhi Li
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
Peeking into the void: Digital twins for
construction site logistics
Toni Greif, Nikolai Stein, Christoph
Digital twin
Cyber physical system-enabled synchronization
mechanism for pick-and-sort ecommerce order
Xiangtianrui Kong, Xuan Yang, Kelin
Peng, Clyde Zhengdao Li
An investigation into emerging industry 4.0
technologies as drivers of supply chain innovation
in Australia
John L. Hopkins
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
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.
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
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Cisneros-Cabrera, S., Pishchulov, G., Sampaio, P., Mehandjiev, N., Liu, Z., Kununka, S.,
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Derigent, W., Cardin, O., Trentesaux, D., 2020. Industry 4.0: contributions of holonic
manufacturing control architectures and future challenges. Journal of Intelligent
Fahim, P.B.M., An, R., Rezaei, J., Pang, Y., Montreuil, B., Tavasszy, L., 2021. An
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Greif, T., Stein, N., Flath, C.M., 2020. Peeking into the void: Digital twins for construction
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Hopkins, J.L., 2021. An investigation into emerging industry 4.0 technologies as drivers of
supply chain innovation in Australia. Computers in Industry 125, 103323.
Ivanov, D., Dolgui, A., 2020. Viability of intertwined supply networks: extending the supply
chain resilience angles towards survivability. A position paper motivated by COVID-
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Kong, X.T.R., Yang, X., Peng, K.L., Li, C.Z., 2020. Cyber physical system-enabled
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Leal, G., Guédria, W., Panetto, H., 2019. Interoperability assessment: A systematic literature
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Shi, Y., Chen, M., Qu, T., Liu, W., Cai, Y., 2020. Digital connectivity in an innovative joint
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Vanvuchelen, N., Gijsbrechts, J., Boute, R., 2020. Use of Proximal Policy Optimization for
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Wang, B., Luo, C., Zhang, A., Tian, Z., Li, Z., 2020. Blockchain-Enabled Circular Supply
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... The first category includes those studies that review the technologies and standards used in SC data sharing (Nurmilaakso, 2008;Lampathaki et al., 2009;Chituc, 2017;Chituc, 2019). The latter category involves reviewing the implications of data sharing in SCs with regards to I4.0 (Naseem and Yang, 2021;Spanaki et al., 2018), collaboration framework , sustainability (Fritz et al., 2017, ?, ?) and those indicating the recent trends and possible future research (Pan et al., 2021;Ralston et al., 2017;Daneshvar Kakhki and Gargeya, 2019;Frederico, 2021). In Table 1 an exhaustive list of the literature reviews done in the field is presented. ...
... Industry 5.0 and its antecedents Frederico (2021) Use of blockchain for SC transparency and security Hellani et al. (2021) Role of I4.0 in SSCM Naseem and Yang (2021) Interoperability and physical internet in SCs and logistics reviewing papers from 2010-2020 Pan et al. (2021) Big Data analytics in SC and its implications in SC optimization, planning, sustainability, logistics etc. Darvazeh et al. (2020) Comparison of ten industry neutral interoperability frameworks (data standards) ...
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With advances in technologies, data science techniques, and computing equipment, there has been rapidly increasing interest in the applications of reinforcement learning (RL) to address the challenges resulting from the evolving business and organisational operations in logistics and supply chain management (SCM). This paper aims to provide a comprehensive review of the development and applications of RL techniques in the field of logistics and SCM. We first provide an introduction to RL methodologies, followed by a classification of previous research studies by application. The state-of-the-art research is reviewed and the current challenges are discussed. It is found that Q-learning (QL) is the most popular RL approach adopted by these studies and the research on RL for urban logistics is growing in recent years due to the prevalence of E-commerce and last mile delivery. Finally, some potential directions are presented for future research.
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Interoperability is playing an increasing role for today's logistics and supply chain management (LSCM) because of the trends of cooperation or coopetition. Especially, digital interoperability concerning data or information exchange becomes a key enabler for the next evolutions that will massively rely upon digitalization, artificial intelligence, and autonomous systems. The notion of Physical Internet (PI) is one such evolution, an innovative worldwide logistic paradigm aimed at interconnecting and coordinating logistics networks for efficiency and sustainability. This paper investigates how digital interoperability can help interconnect logistics and supply networks as well as the operational solutions for sustainable development, and examines the new challenges and research opportunities for digital interoperability under the PI paradigm. To this end, we study the most relevant technologies for digital interoperability in LSCM, via a bibliometric analysis based on 208 papers published during 2010-2020. The results reveal that the present state-of-the-art solutions of digital interoperability are not fully aligned with PI requirements and show new challenges, research gaps and opportunities that need further discussion. Accordingly, several research avenues are suggested to advance research and applications in this area, and to achieve interconnection in logistics and supply networks for sustainability.
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Synchromodal transportation planning is defined by the possibility to re-route shipments to alternative transportation modes at intermediate terminals based on real-time information about the shipment in transit. We present a synchromodal decision support model to determine the optimal modal choice for a single shipment in a multimodal network that is characterized by stochastic travel times. The model is formulated as a Markov decision process and allows adaptations to the modal choice based on real-time information on the travel time. Our formulation trades off transportation and late delivery penalty costs, and captures the value of synchromodal planning. We demonstrate the use of our model in a numerical case study, where we evaluate synchromodal against static intermodal transportation planning. The latter does not allow real-time adjustments to the modal choice. Compared to intermodality, synchromodal planning has most value when the penalty for late delivery is high and transportation services are more frequent.
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Deep reinforcement learning has been coined as a promising research avenue to solve sequential decision-making problems, especially if few is known about the optimal policy structure. We apply the proximal policy optimization algorithm to the intractable joint replenishment problem. We demonstrate how the algorithm approaches the optimal policy structure and outperforms two other heuristics. Its deployment in supply chain control towers can orchestrate and facilitate collaborative shipping in the Physical Internet.
The Physical Internet (PI), a new vision for the future of the global freight transport and logistics system, describes a geographical hierarchy of interconnected networks of networks, from the urban, to the national, the continental, and the global level. Like today, in PI the maritime ports will fulfil roles as continental and global hubs. Differently than ports today, however, decisions to split and bundle cargo across ships and other modes will not be made solely on the basis of long-term agreements by ports, but rather ever more dynamically and in real-time, aiming to reconsolidate shipments within the port area. This implies a need to reconsider the currently used information systems (ISs), and to gain understanding of future requirements to satisfy their needs. We exploit a design science research (DSR) approach to shape these requirements. Among the many components of future ISs, we study ports’ track-and-trace (T&T) capability. The proposed information architecture (IA) enables to integrate T&T capability in PI ports by means of information carried on PI containers into the logistics chain via an open interface platform, which also supports interoperability among the various actors’ ISs. The design is based on the Reference Architecture Model for Industry 4.0 (RAMI 4.0). This model supports the analysis of PI ports in key dimensions along with hierarchical logistics entities, which could be used as a blueprint for IAs of PI ports, globally. We provide insights into the approach’s applicability by means of the illustrative case of Teesport, located in Northeast England (United Kingdom).
Industry 4.0 technologies, process digitalisation and automation can be applied to support the formation of supply chain collaborations in manufacturing. Underpinned by information and communication technologies, collaborations of independent companies can dynamically pool production capacities and capabilities to jointly react to new business opportunities. These collaborations may involve a wide range of enterprises with different sizes and scope that individually would not be able to tender for such new business opportunities. To form these collaborative teams, assistive processes and technologies can underpin the effort towards exploring the tender requirements, unbundling the tender into smaller tasks and finding a suitable supplier for each task. In this paper, we present an approach and a tool to support decision making concerning forming supply chain collaborations in Industry 4.0. The approach proposed is unique in integrating industry domain ontologies, assistive human-computer interaction tools and multi-criteria decision support techniques to form team compositions speeding-up the collaboration process whilst maximising the chances of forming a viable team to fulfil the tender requirements. We also show evaluation results involving stakeholders from the supply chain function pointing to the effectiveness of the proposed solution, available online as a demo¹.
As supply chains recover from the impact of COVID-19, a sudden acceleration of interest in digitalization and automation is expected, as firms increasingly look towards digital technologies as sources of innovation in the wake of an extreme disruption. The purpose of this study is to utilize the experience of supply chain practitioners, to ascertain the current level of adoption of a number of key Industry 4.0 technologies, understand what preparatory measures are being taken by firms to ensure they are digitally-ready to utilise Industry 4.0 technologies, recognise how and where these technologies are likely impact supply chains, and investigate whether organisational size is a factor in technology adoption. This empirical study utilises primary data from a descriptive survey of supply chain practitioners working across a range of industry sectors and different stages in the supply chain. Whilst the findings from this research indicate that some Industry 4.0 technologies are still in the early stages of adoption, amongst Australian supply chain organisations, they clearly show which technologies are anticipated to have the greatest impact, what sectors that impact will most likely occur in, and which specific improvements they are expected to drive. Larger firms were found to be more digitally-ready than smaller firms, and a number of significant gaps were identified between expected impact and expected investment, meaning little spend is currently projected for certain technologies that are expected to have a significant impact.
Trustworthy data is the fuel for ensuring transparent traceability, precise decision-making, and cogent coordination in the Supply Chain (SC) space. However, the disparate data silos act as a trade barrier in orchestrating the provenance of the product lifecycle; starting from the raw materials to end products available for customers. Besides product traceability, the legacy SCs face several other problems including data validation, data accessibility, security, and privacy issues. In this regard, Blockchain – an advanced Distributed Ledger Technology (DLT) works well to address these challenges by linking fragmented and siloed SC events in an immutable audit trail. However, the underlying challenges with blockchain such as scalability, inability to access off-line data, vulnerability to quantum attacks, and high transaction fees necessitate a new solution to overcome the inefficiencies of the current blockchain design. In this regard, IOTA (the third generation of DLT) leverages a Directed Acyclic Graph (DAG)-based data structure in contrast to linear data structure of blockchain to address such challenges and facilitate a scalable, quantum-resistant, and miner-free solution for the Internet of Things (IoT). After realizing the crucial requirement of traceability and considering the limitations of blockchain in SC, in this work, we propose a provenance-enabled framework for the Electronics Supply Chain (ESC) through a permissioned IOTA ledger. To that end, we construct a transparent product ledger based on trade event details along with time-stamped SC processes to identify operational disruptions or counterfeiting issues. We further exploit the Masked Authenticated Messaging (MAM) protocol provided by IOTA that allows the SC players to procure distributed information while keeping confidential trade flows, ensuring restrictions on data retrieval, and facilitating the integration of fine-grained or coarse-grained data accessibility. Our experimental results show that the time required to construct secure provenance data aggregated from multiple SC entities takes 3 s (on average) for a local node and 4 s for a remote node, which is justifiable. Furthermore, we perform experiments on Raspberry Pi 3B to verify that the estimated energy consumption at resource-constrained devices is tolerable while implementing the proposed scheme.
Circular supply chain management is required for firms to transition from a linear make-use-dispose economic model to a more sustainable circular economy. However, it faces the critical challenge of tracing the reuse of materials over multiple life cycles involving a variety of stakeholders. Blockchain technology can help manage the complexities of circular supply chain management. This paper takes the first step in developing a system architecture of blockchain-enabled circular supply chain management in the fast-fashion industry. The system architecture was validated by two experts in blockchain technology and supply chain management. Managerial implications are discussed for implementing blockchain technology to advance the circular economy agenda.
Construction is one of the least-digitized industries in the economy. To rein in the rising costs of building activities, digital transformation is one of the pillars that industry leaders rely on. A case in point are logistics processes which are characterized by very limited visibility and inefficient organization. To progress beyond this current state of the art, we conceptualize the idea of a lightweight digital twin for non-high-tech industries. In collaboration with a leading supplier of building materials, we explore the opportunities offered by digital silo twin capabilities. Focusing on fill level monitoring we identify diverse opportunities for generating informational, automational and transformational business value. Leveraging new information sources for the redesign of core business processes drastically increases the complexity of operational decision-making. To tap into these opportunities, we design and implement a decision support system for silo dispatch and replenishment activity.
A joint distribution system based on digital connectivity to share logistics resources constitutes an innovative method of intelligent logistics. In general, O2O deliverymen are subjected to delivery capacity imbalances in different hours—peak hours and off-peak hours in particular—throughout the day. To solve the insufficient capacity problem in peak hours and the idle capacity problem in off-peak hours of O2O deliverymen, this paper introduces an innovative digital connectivity enabled B2C and O2O joint distribution system. In this system, all pickup and delivery nodes of both B2C and O2O orders are interconnected through the Physical Internet. In response to the dynamic arrivals of O2O orders, this paper develops a center dispatching system to collect and schedule the real-time logistics information via digital connectivity. An improved savings algorithm is proposed to support the real-time routing optimization of deliverymen. By making a comparative analysis with the traditional separate distribution mode, this paper proves the effectiveness of the joint distribution system. Results show that it outputs better optimization with larger order sizes, the same B2C and O2O order proportions as well as longer lengths of O2O time window. With the benefit of the digital connectivity, the joint distribution system contributes to providing real-time logistics services with high efficiency and reducing carbon emissions to realize sustainability. The prospect of this system exhibits the potential for use in richly varied delivery services, most notably meal delivery in urban areas.