Logistics management for the future: the IJLRA framework

ABSTRACT

In this discussion paper, we aim to examine the key issues of logistics management in the Industry 4.0 era by addressing various major challenges. To be specific, we first establish an amended definition of logistics management, highlighting the new elements of cash flow, in both the cyber and physical worlds. We then review the highly relevant selected literature and propose a framework for future logistics management. Our proposed framework includes five critical areas, namely Industry 5.0, Joint-venture, Legal-concerns, Risk management, Automation and artificial intelligence (AI), and hence we call it the ‘IJLRA’ framework. For each area, we identify the major challenges that deserve further analyses. We believe that with proper logistics management under the IJLRA framework, organisations in the supply chain can achieve the crucial goals of logistics – achieving the right time, right place, right quality, and everything right – to satisfy customer needs. Finally, we also propose a future research agenda for logistics management.

KEYWORDS:

• Discussion paper
• logistics
• future
• IJLRA framework
• cyber world

1. Introduction¹

The world is changing. We are no longer living and working in a physical world, but a cyber-physical system. For logistics, we have left the traditional labour-intensive service operations with warehousing, transportation, and inventory, and entered the Industry 4.0 era (Choi et al. 2022) in which automation, intelligence systems, Internet-of-things (IoT) (Rajput and Singh 2022), big data analytics (Choi, Wallace, and Wang 2018), artificial intelligence (AI) (Lim et al. 2022; De Bock et al. 2023), blockchain (Choi 2019), etc., are all widely implemented in all logistics functions. Under the Industry 4.0 era, supply chain visibility, resilience, and efficiency are all enhanced (Bag et al. 2022; Ivanov 2022) with the proper deployment of digital technologies. For example, Walmart has started transforming its warehouse operations with robots to achieve automation (Repko 2023). Kerry logistics has adopted IoT solutions to monitor cargo shipment processes and help transmit critical information about the physical environments of cargos such as temperature to the consignees and shippers.² With the promising applications of all kinds of Industry 4.0 technologies in logistics, the resulting logistics systems will become ‘smarter’ with enhanced information sharing among supply chain members. Quick response operations and optimised resources utilisation can be achieved (Li et al. 2020; Ding et al. 2021). Therefore, smart logistics is more intelligent with the provision of higher levels of accuracy, flexibility, and efficiency than traditional operations (Wang and Sarkis 2021). It is estimated that the market valuation of smart logistics will grow from US$30.6 billion in 2022 to US$201.2 billion in the coming decade.³

Despite changes, one thing remains critical: How to satisfy customer requirements. As a matter of fact, according to the most classic and authoritative definition of logistics management by the Council of Supply Chain Management Professionals (CSCMP), we have the following⁴:

Logistics management is that part of supply chain management that plans, implements, and controls the efficient, effective forward and reverses flow and storage of goods, services and related information between the point of origin and the point of consumption in order to meet customers’ requirements. (Defined by CSCMP).

It is obvious that the functions of logistics management are to deliver products, which can be traditional goods, services, and/or information to the destination at right time, right place, right quality, … and everything right. Ultimately, making customers happy by satisfying what they need. In the future, this definition should still be valid even though we may need to consider more. To be specific, two points should be highlighted, which also relate to the perspective of this discussion paper.

First, the importance of money flow. Nowadays, we have supply chain finance and cash flow is an essential and significant topic in logistics management (Gomm 2010). Supply chain finance generates values to various organisations along the supply chain at an inter-organisational level (Hofmann 2005). By incorporating supply chain finance into logistics management, we can better align financial, product, and information flows within a supply chain. This ultimately yields an optimised work capital (Ali, Gongbing, and Mehreen 2019) and creates a new opportunity of getting loans through the use of Industry 4.0 technology (Choi et al. 2022). However, the old definition does not include this aspect and we propose its inclusion.

Second, there is a need to highlight the importance of both cyber and physical worlds. With the emergence of metaverse and technologies such as digital twins, future logistics management must consider both the cyber and physical worlds together in a coordinated manner. For instance, DHL has applied digital twin technologies in its warehouse to simulate the product flows and warehouse status in real time. The corresponding data will help decision makers to avoid accidents, improve resource allocation, and enhance productivity.⁵ However, Zhang et al. (2022) comment that the actual physical world situation and constraints should be carefully evaluated, and the simulated data should be measurable when the digital twin is used for logistics management. This is definitely revolutionary and would present lots of new challenges to conventional wisdom and traditional know-hows in logistics management.

With respect to the above-mentioned two points, we propose to amend the definition of logistics management as follows.

Logistics management is that part of supply chain management that plans, implements, and controls the efficient, effective forward and reverses flow and storage of goods, services, money and related information between the point of origin and the point of consumption in order to meet customers’ requirements in both the cyber and physical worlds.

This new definition of logistics management is non-trivial as it provides the ground for the field to develop, with special emphases on ‘cash flow’ and the presence of ‘cyber and physical worlds’. In addition, based on this new definition, we know the important directions and can proceed to explore more for future development in logistics management.

In this discussion paper, we follow this amended definition of logistics management and discuss the topic. In the Industry 4.0 era, it is undoubted that many logistics activities will be performed and managed by different disruptive technologies (e.g., IoT, digital twins, and robotics). However, in the existing literature, there is very limited discussion about the key issues and challenges of logistics management that should be addressed carefully in the Industry 4.0 era. This paper contributes by bridging this research gap by reviewing the highly relevant literature and proposing a promising framework for logistics management. A solid future research agenda is also developed. Overall, this study discusses how logistics management should look like and how it should be developed to cater to future challenges.

As a remark, this paper positions itself as a discussion paper or opinion article. It is different from some other original research papers in which the content is all scientifically sound. We do admit hence some sort of subjectivity. However, we do have backups on our proposals with references to the related literature (e.g., a systematic search of the authoritative literature) and real-world practices.

2. Review methodology

In this study, to better understand the current state-of-the-arts research in the field, we conduct a systematic review of the highly relevant journal articles. Following the approach adopted by many prior studies (e.g., Choi and Tana 2022; Xu et al. 2023), we proceed as follows.

Firstly, we search the articles from Web of Science (WoS) and then perform a series of article filtering processes. To be specific, in the first step, we select WoS for retrieving the articles as this is an authoritative database for the peer-refereed scientific journals. In Step 2, we start our article searching process by inputting ‘logistics’ and ‘Industry 4.0’ as the topic. As this study is related to logistics management, we then filter the articles by selecting ‘logistics and supply chain management’. Next, we choose the ‘article’ and ‘early access’ types of documents as these studies are more comprehensive and have a higher level of research rigour than the others (e.g., conference articles). In Step 5, we further consider the publication categories of ‘management’, ‘operations research management science’ (ORMS), ‘business’, and ‘transportation’ as logistics and supply chain management fall into these categories closely. In Step 6, we review articles one by one to determine their relevancy to this study and exclude those review-based articles. To supplement our article searching, we invite an expert (whose expertise is in the field of logistics and supply chain management) to recommend related literature for review. Finally, we review 44 articles that study logistics and supply chain management in the Industry 4.0 era. Figure 1 presents the overview of the article searching and selection process in this study. Figure 2 shows the number of selected publications in each journal in our review.

Figure 1. The article searching and selection process in this study.

Figure 2. The publication numbers of relevant articles in the reviewed journals.

3. Literature review

In this section, we report our examination of each relevant article identified from the process indicated in Figure 1. From the systematic literature review, we find that the selected papers can be classified into five categories, namely Industry 5.0, Joint-venture, Legal-concerns, Risk management, and Automation and artificial intelligence. We discuss them one by one as follows.

Industry 5.0: Logistics management relates to many manual operations. The basic ones, such as moving products manually and driving the trucks in shipping, naturally require labours. For decision making, logistics operations also naturally involve human managers. In the literature, Wehrle et al. (2020) explore how going digitalised in logistics and supply chain systems will affect the related executives. Via a Delphi-based study and using the ‘fuzzy c-means clustering’ method, the authors uncover that ‘digitalization is leading to a strong fusion of SCM executives and digital technologies’. They further discuss the future trend of having clear divisions of job natures and tasks. Miller, Bolumole, and Muir (2021) conduct a comprehensive study towards driver turnover problems. The authors focus on truckload drivers. They uncover how ‘changing industry employment and wages’ would influence the turnover rates of truckload drivers. The findings have relevance to the adoption of digital technologies as this will inevitably affect the industry employment criteria and salaries of workers. Winkelhaus, Grosse, and Glock (2022) investigate via a qualitative study how the transition to Industry 4.0 affects workers. The authors reveal that this transition has a complicated impact on employees and workers. They hence propose that it is critical to enhance the workplace design and highlight the importance of creating the proper work motivation. Loske (2022) studies automated warehousing operations and identifies how the transformation from traditional to new technology-driven operations affects workers’ learning as well as the related job characteristics. The author finds that through real-time data acquired from the automated warehousing systems, the ‘perception–cognition–motor–action cycle for learning by doing tasks’ can be enhanced. The author also shows that the ‘perceived work autonomy and feedback from the picking system’ are related to whether or not workers’ decision making plays a role. Most recently, Sheu and Choi (2023) analytically explore a ‘human-friendly robot-human coordinated order fulfillment scheme’. Using the optimal control theory, the authors theoretically prove how workers can properly work with robotics in logistics systems.

Joint-ventures: Collaborations among supply chain members and logistics service providers are crucial. This also relates to flows of products, services, money, and information. In the literature, related studies include all kinds of collaborations and alliances. For instance, Vanovermeire et al. (2014) argue that horizonal strategic partnerships among logistics companies may lead to efficiency improvement. The authors prove in their study that if the partnering companies adopt flexibility in their operations, their overall operational efficiency can be further improved. Dev, Shankar, and Swami (2020) study circular supply chain management with the consideration of green product diffusion via simulation and statistical approaches. The Industry 4.0 technologies help collect and share real-time information about the reverse logistics activities with the supply chain partners. The authors examine the economic and environmental performances of three different inventory planning policies with and without information sharing. The quantitative results show that the adoption of an inventory planning policy depends on the trade-off between economic and environmental performances. Vural et al. (2020) investigate the potential of adopting Industry 4.0 technologies in reducing the barriers to using intermodal transportation through interviews. Their findings show that the involvement of multiple parties in intermodal transportation will result in different perceptions of Industry 4.0 technologies. This divergency will hinder the digital transformation in the intermodal transportation industry. With digitalisation, the barriers to intermodal transportation can be mitigated if market leaders invest in Industry 4.0 technologies, intermodal transport buyers demand such transport services, and the supply chain is vertically and horizontally integrated. Badraoui, Boulaksil, and Van der Vorst (2022) establish a ‘typology of horizontal logistics collaboration’. To better demonstrate the arguments, the authors conduct a case study on agricultural supply chains and highlight their dynamic nature of them. They also reveal how the features of agricultural supply chains affect the alliance formation and rationales of partner choices. Aloui et al. (2022) explore the impacts brought by collaborations in logistics networks. The authors build an optimisation model and scientifically show the significance of collaborations on both cost minimisation as well as carbon emissions reduction. Similar to Aloui et al. (2022), Wang et al. (2023) conduct an analytical study on how collaboration between shipping companies would affect operational efficiency as well as the environment. One insight is that there are cases in which shipment consolidation would benefit the upstream supply chain partners. This could yield a win-win scenario. Note that the above studies commonly find that joint ventures in the form of collaborations are significant in logistics systems.

Legal-concerns: Logistics systems involve lots of legislative challenges. In the literature, Wong and Yung (2010) study product recalls and the related legislative challenges. The authors propose some ‘green legislation’ schemes for reverse logistics operations. Goel (2018) studies legislation and legal challenges in road transportation. The author makes use of the European context and explores the related ‘legal requirements’ for long-haul transport. The author further discusses the influences brought by the related legal rules. Hansen, Rasmussen, and Lützen (2020) explore energy management-related legislation in maritime operations. Focusing on the ‘Ship Energy Efficiency Management Plan’, the authors explore qualitatively the associated challenges in legislation. The authors further argue that proper goal definitions are crucial for energy efficiency management in shipping operations. Luo and Choi (2022) analytically study the cyber-security challenges in e-supply chains. The authors highlight the roles played by the government and uncover the use of a polarised strategy is optimal. Note that the literature only focuses on legal concerns on traditional logistics systems. In the future, with the emergence and popularity of metaverse, new legal concerns and legislation requirements for logistics management in the cyber-physical world will be a critical issue.

Risk management: Logistics management faces risk. Readers can refer to Choi (2021) for an overview of the recent risk issues in logistics management. The first type is financial risk which is related to the liquidity for daily operations in logistics management. In the related literature, Li and Chen (2019) conduct a case study to examine how supply chain finance affects the third-party logistics (3PL) industry, and they highlight that supply chain finance can help the scale-oriented 3PL gains competitive advantage. Reza-Gharehbagh et al. (2021) study the financing challenges associated with reglobalisation. They take the perspective of the use of ‘crowdfunding’ platform operations. The authors argue that the ‘profit-seeking behavior’ of governments could significantly affect the crowdfunding platform’s performance. They propose that governments should revise the supply chain finance rules by re-prioritising the objectives. Wang et al. (2022) analytically explore different financing scenarios (e.g., the ‘retail-finance mode’) under a competitive market setting. Choi (2022) analytically studies financing in operations for new product development. The author theoretically shows when the use of blockchain-based ‘Initial Coin Offerings’ scheme can benefit the operations.

Another risk that is closely related to logistics management is disruptions. Here, disruptions can be brought by pandemics (such as COVID-19), natural disasters, etc. Lohmer, Bugert, and Lasch (2020) examine the values of using blockchain technology for managing disruption. By applying agent-based simulation, the authors show that blockchain technology is an effective tool to improve supply chain resilience. With blockchain technology, the number of supply chain members who are being affected by the disruption can be reduced. Other benefits include lowered disruption costs and shortened network recovery duration. Sharma et al. (2020) study the agriculture supply chains risks during the COVID-19 pandemic. They build mathematical models and apply multi-criteria decision-making techniques to explore how to build supply chain resilience. Their results show that agriculture supply chains face various challenges (such as supply uncertainty, demand uncertainty, financial, and logistics and infrastructure) caused by the COVID-19 pandemic. On the other hand, Industry 4.0 technologies can be used to create supply chain agility and fulfil dynamic demand requirements. Ali et al. (2022) empirically investigate the role of Industry 4.0 technologies in supply chain disruptions in the food processing industry. By analysing the data collected from surveys, the authors find that supply and demand misalignment, process risks, and transportation risks are the key factors leading to supply chain disruptions. However, the use of Industry 4.0 technologies can reduce the supply and demand misalignment and process risks only, but not the transportation risks. Bag et al. (2021) conduct an empirical study to explore how big data analytical tools affect supply chain resilience during the COVID-19 pandemic in the healthcare industry. Their statistical results demonstrate that big data analytics can help develop supply chain responsiveness and increase supply chain innovation which will eventually lead to a higher level of supply chain resilience during the COVID-19 pandemic. Besides, the collaboration between supply chain partners in terms of logistics and procurement activities can mitigate supply chain risks. Dev et al. (2021) study the inventory and production planning policies in reverse logistics with the consideration of additive manufacturing (AM) technology. The authors apply simulation and statistical approaches and show that AM technology can help reduce the need for inventory for dealing with unexpected disruptions and create supply chain resilience for green product diffusion in the market. Kumar and Singh (2021) identify and prioritise the critical success factors for applying Industry 4.0 technologies in post-disaster logistics coordination. By conducting interviews and applying the AHP techniques, the authors find that the most critical success factor for applying industry 4.0 technologies in humanitarian supply chains is strategic planning which can help facilitate coordination among the organisations in the supply chain. Dash and Dixit (2022) incorporate an institutional framework as well as information and digital technology to develop a disaster supply chain to deal with the COVID-19 pandemic. The authors formulate the objective function as transportation time delay and information response time minimisation and consider various constraints such as capacity. Their proposed framework can facilitate information sharing among different stakeholders, help achieve coordination, and support decision making. Nayal et al. (2022) examine the factors that will motivate AI adoption and explore its impacts on supply chain risk management during the COVID-19 pandemic by conducting statistical tests. Their results show that process issues, information sharing, and supply chain integration are the key elements that drive AI adoption.

In addition, adopting AI can enhance supply chain risk management. Rehman and Ali (2022) first identify and rank resilience strategies. They then investigate the risks that are the most severe, very likely to occur, and have the longest recovery time in the healthcare supply chains. The authors apply multi-criteria decision-making techniques and find that the use of Industry 4.0 technologies, multiple sourcing, risk identification, and agility are all important strategies for building resilient healthcare supply chains. Akan (2023) analyses the logistics process in maritime logistics industry by applying the as-is and to-be models in the business process management framework. The author conducts a case study and demonstrates that the proposed business process management framework is an effective tool to help maritime logistics organisations to build resilience. Molinaro et al. (2022) examine the importance of ‘supply base concentration’. They counterintuitively obtain one finding that ‘developing technologies to share information with suppliers may be counterproductive in driving efficiency’. Similar to Molinaro et al. (2022)’s focus on ‘concentration’, Liu et al. (2023) explore how to redesign logistics and supply chain systems in the presence of COVID-19 pandemic. The authors focus their attention on several critical concentration dimensions in the supply chain (i.e. ‘supplier, customer, product, and region’) and discuss how each concentration dimension is affected by the COVID-19 pandemic. Zhou, Wang, and Yang (2023) study the impacts of using digital technologies in logistics and supply chains on the associated risk derived from the COVID-19 pandemic. They empirically show that digitalisation would positively influence the ‘3Rs’ (i.e. responsiveness, resilience, and restoration) in supply chains. Cardoso, Fontainha, and Leiras (2023) report a literature review on how logistics and supply chains can be better prepared when facing disasters. Most recently, Xu et al. (2023) investigate the operational strategies to achieve 3Rs in global supply chains facing the COVID-19 pandemic. By considering the specific actions taken by leading enterprises, they build the conceptual framework for this purpose. Note that risk management can also extend to other domains such as health risk (Guo and Choi 2023). Overall, risk management is definitely one critical area in logistics.

Automation and artificial intelligence (AI): In the Industry 4.0 era, logistics systems not only become more automated, but also more intelligent. In fact, nowadays, digital technologies, such as blockchain (Liu et al. 2022) and cloud computing, are widely applied in logistics management (Tang and Veelenturf 2019; Lim, Xiong, and Wang 2021; 2022). For instance, Yavas and Ozkan-Ozen (2020) study the transition of logistics management from the traditional one which only has automation to an intelligent ‘logistics 4.0’. Baştuğ et al. (2020) investigate the value of using Industry 4.0 technologies in the port industry via a case study approach. With the use of Industry 4.0 technologies (including port community systems, cyber-physical systems, IoTs, and big data), automation in the port processes can be achieved, which is a crucial component for generating cost savings in port activities. Ma et al. (2020) analytically analyse the optimal pricing and inventory planning decisions of freshness-keeping services offered under the cap-and trade policy. The authors consider the role of Industry 4.0 for supply chain decentralisation and self-regulation. Their findings reveal that the third-party logistics service providers will put more effort to keep the product fresh for the products with a higher quantity elasticity. Yetkin Ekren (2021) studies how to properly design an ‘autonomous vehicle-based storage and retrieval system’ (AVS/RS) warehouse with the objective of minimising both the average cycle time and energy consumption for each transaction. By using simulation and statistical approaches, the author shows that the warehouse should be designed with more aisles but fewer tiers. Henríquez, de Osés, and Marín (2022) conduct interviews and a case study to examine how the Industry 4.0 technologies shape the ‘smart port’ model. They find that the Industry 4.0 technologies and the market pull towards their execution by seaports are positively associated. The authors also argue that government regulation should be considered and studied carefully as it will affect the business innovation model being adopted in the seaports. Lei et al. (2023) propose a decision-making mechanism for allocating production and logistics-integrated tasks in smart factories in a coordinated manner by using the reinforcement learning method. The authors demonstrate that their proposed reinforcement learning model outperforms the centralised scheduling system in terms of the ‘production logistics integrated tasks allocation’ in the smart factories when the orders are dynamic and ‘small-batch’.

Some studies specifically focus on a particular technology in logistics and supply chain management. For the use of blockchain technology, it has been widely examined in the logistics management literature (Dutta et al. 2020; Chan, Choi, and De la Torre 2023). Sternberg, Hofmann, and Roeck (2021) empirically study the challenges and major barriers hindering the deployment of blockchain for logistics and supply chain systems. One core insight identified by the authors is that the ‘adoption and integration decision of one supply chain actor recursively affects the adoption and integration decisions of the other supply chain actors’. Choi and Tana (2022) construct a conceptual framework, called the ‘Intra–Inter-Organizational Framework’, for the use of blockchain in logistics systems. The authors also reveal the critical success factors for the proper deployment of blockchain technology in logistics under the proposed framework. Xiong and Xue (2023) examine the application of blockchain to tackle the challenges of information asymmetry in materials shipping. The authors construct evolutionary gaming models to derive the ‘stable evolutionary strategies’ for the problem. For other technologies, Ivanov, Dolgui, and Sokolov (2022) explore the use of digital platforms for logistics and supply chain operations. The authors develop a novel concept called ‘Supply Chain-as-a-Service’ and propose the use of cloud computing technologies to achieve it. They further point out that the core features of cloud-based logistics systems are closely related to ‘dynamic service composition with dynamically changing buyer/supplier roles’ with the use of Industry 4.0 technologies. Friedrich, Lange, and Elbert (2022) investigate 3D printing logistics and supply chain systems. The authors conduct a multi-case analysis to uncover ‘why and how’ 3D printing affects the commonly seen ‘make-or-buy’ decision. In a recent study, Srinivas, Ramachandiran, and Rajendran (2022) report an insightful review of the ‘autonomous robot-driven deliveries’. The authors also discuss critical research opportunities in this emerging topic.

We summarise the reviewed literature in the above five major areas, including the specific topics covered and the core findings, in Table 1.

Table 1. Summary of the reviewed literature

Issues	Topics addressed in the literature	Findings
Industry 5.0	To discuss the impacts of digitalisation on executives (Wehrle et al. 2020), truckload driver turnover (Miller, Bolumole, and Muir 2021), worker’s job satisfaction and learning (Winkelhaus, Grosse, and Glock 2022; Loske 2022) and robot-human coordination mechanism (Sheu and Choi 2023).	Impacts on humans should be considered. Limited discussions on logistics and supply chain operations in Industry 5.0.
Joint-ventures	To reveal how the collaborations affect operational efficiency (Vanovermeire et al. 2014), cost and environmental sustainability (Aloui et al. 2022; Wang et al. 2023). To present how the alliance and partner choices are shaped and determined (Badraoui, Boulaksil, and Van der Vorst 2022) To examine the performances of different inventory planning policies with and without partnership on information sharing for green product management (Dev, Shankar, and Swami 2020). To uncover the obstacles to intermodal transportation operations and highlight the importance of collaboration (Vural et al. 2020).	Benefits, impacts, and forms of collaboration should be well explored before implementation. Very few studies explore the design of the optimal collaboration scheme.
Legal-concerns	To study the legislation challenges for reverse logistics operations (Wong and Yung 2010), road transportation (Goel 2018), and energy management (Hansen, Rasmussen, and Lützen 2020). To investigate the cybersecurity challenges (Luo and Choi 2022).	New legislation and government policy are needed for achieving different purposes such as sustainability and cybersecurity. With more applications of disruptive technologies in the real-world, it is important to conduct in-depth studies on cyberspace, such as cybersecurity and e-commerce.
Risk management	To examine the financial risks of 3PL (Li and Chen 2019), crowdfunding platform (Reza-Gharehbagh et al. 2021), new product development (Choi 2022), and under different financing scenarios (Wang et al. 2022). To explore different issues under disruption, including supplier integration (Molinaro et al. 2022), logistics and supply chain system design (Kumar and Singh 2022; Dash and Dixit 2022; Liu et al. 2023), responsiveness, resilience and restoration (Lohmer, Bugert, and Lasch 2020; Bag et al. 2021; Akan 2023; Sharma et al. 2020; Zhou, Wang, and Yang 2023), and measure and strategy (Ali et al. 2022; Dev et al. 2021; Nayal et al. 2022; Rehman and Ali 2022; Cardoso, Fontainha, and Leiras 2023; Xu et al. 2023).	Disruptions brought by pandemics and extreme weather create huge challenges. Supply chain finance is a timely topic. However, supply chain finance, including all kinds of innovative financing models, is under-explored.
Automation and artificial intelligence (AI)	To examine the challenges (Sternberg, Hofmann, and Roeck 2021) and critical success factors (Choi and Tana 2022) of executing blockchain for logistics and supply chain systems. To study the use of various technologies to overcome information asymmetry problem (Xiong and Xue 2023), support the logistics and supply chain operations (Baştuğ et al. 2020; Yetkin Ekren 2021; Henríquez, de Osés, and Marín 2022; Lei et al. 2023; Ivanov, Dolgui, and Sokolov 2022; Srinivas, Ramachandiran, and Rajendran 2022), ‘make-or-buy’ decision (Friedrich, Lange, and Elbert 2022), and inventory planning decision (Ma et al. 2020).	The uses of disruptive technologies in supporting logistics and supply chain systems are essential in the future. Sustainability is one of the focuses of organisations. However, limited study examines how to make use of technologies (e.g., AI) to assess environmental and social sustainability performances.

4. The IJLRA framework

In Section 3, we have identified five key categories which we believe to be critical. Recall that the five categories are Industry 5.0, Joint-venture, Legal-concerns, Risk management, and Automation and artificial intelligence. The short form of these five categories, based on the initials of them, is IJLRA. In this section, we further elaborate on several major challenges under each category that deserve scholars’ and industrialists’ in-depth investigation and establish the respective IJLRA framework.

Industry 5.0: Industry 5.0 represents a transformative business environment in which disruptive technologies and human labour work in a coordinated way. In this paradigm, logistics management is human-centric, with a strong emphasis on environmental sustainability and supply chain resilience (Saldanha-da-Gama 2022; Grosse 2023). Human factors are critical in future logistics systems, but they are under-explored. These human factors include autonomy, rights, and dignity. When integrating these human factors into business operations, a major challenge arises: How can workers be empowered by disruptive technologies (Mcloughlin 2023) without compromising their autonomy, rights, and dignity? In addition, organisations have to carefully rethink the proper approaches and strategies to address environmental sustainability and supply chain resilience simultaneously. They must determine the effective ways to achieve optimal solutions that balance these two aspects.

Joint-ventures: According to Deloitte, the primary reason for forming joint-venture is to share the operating cost and investment.⁶ Joint-ventures allow partners to collaborate in various forms and foster a dynamic business relationship. However, partners in the joint-venture may have different perspectives on strategic adoption, which can present challenges. Investing in technologies and training is very costly and should be perceived as long-term projects. Thus, determining how to form collaborative relationships that yield mutual benefits from technological investment becomes a complex task. Moreover, the management of the financial flows is one key element in the logistics and supply chain systems and these money flows exist not only in the physical world but also in the cyber world. How to manage the money flows in joint-venture in highly complex logistics and supply chain systems is crucial.

Legal concerns: The digitalisation and the popularity of e-commerce have created an opportunity for fraudulent activities. Cybercrime has emerged as the most severe problem from the perspective of executives all around the world. It is reported that about 32% of small organisations have experienced cybercrime and such percentage is even higher for larger organisations.⁷ In this context, it is important to explore ways to govern logistics systems in the intertwined physical and cyber worlds. To be specific, it is crucial to establish proper rules and legislation frameworks that address cyber-security within logistics systems which can help organisations maintain the integrity of their operations while safeguarding their digital assets and customer data.

Risk management: Over the past decade, organisations have been facing various disruptions, including natural disasters, pandemic, and trade wars. Under these adverse situations, we have observed that logistics networks are disrupted, demand for commodities is more robust, and freight costs rise substantially. Therefore, the optimal design of logistics and supply chain systems under different disruptions deserves further analysis. On the other hand, organisations have to maintain healthy financial liquidity to cope with the challenges encountered in a dynamic and uncertain business environment. Thus, the exploration and establishment of innovative financial models in the real world are crucial. Understanding how to properly design these models will generate valuable insights for future preparedness.

Automation and AI: The use of Industry 4.0 technologies (e.g., blockchain, AI and robotics, IoT) can facilitate automation in production, real-time information sharing, and forecasting. Given the wide range of technologies available in the Industry 4.0 era, selecting the optimal technology from various options is a critical yet under-explored aspect of logistics management. Furthermore, in the future, logistics and supply chain operations will be more data driven. Organisations are able to collect massive amounts of data (e.g., customer’s personal data) which is sensitive and difficult to manage. The ethical and operational challenges associated with the use AI of in logistics and supply chain systems need to be carefully considered and addressed to ensure a responsible and effective use of these technologies.

From the above discussions, we can see that there are many challenges under each issue which are crucial for future logistics management. These challenges arise mainly because of the huge changes in logistics management driven by digital technologies. Of course, the development of human civilisations with more emphasis on human welfare plays a role, too. By addressing the challenges discussed above, logistics management can achieve in a larger scope of sustainability, operate in a more competitive manner, and attain a higher level of efficiency. On the other hand, resilience can be established to deal with the disruption caused by the dynamic and uncertain external business environment. Overall, organisations can develop competitive advantages and build higher capability to satisfy customers’ needs at right time, right place, right quality, and ‘everything right’.

We present Table 2 to summarise the major challenges and factors under the IJLRA framework. We further depict the framework in Figure 3.

Figure 3. The IJLRA framework.

Table 2. The major challenges and factors under the IJLRA framework.

Issues	Meaning	Major Challenges	Major factors
I	Industry 5.0	How to empower the workers by using disruptive technologies? How to achieve environmental sustainability and supply chain resilience simultaneously and generate optimal solutions?	Emphasis on human factors. Sustainable social welfare.
J	Joint-ventures	Investing in technologies and training is very costly and should be perceived as long-term decisions. How to manage the money flows in joint-venture in highly complex logistics and supply chain systems?	Achieving all-win. Cash flow management.
L	Legal concerns	Digitalisation and the use of e-commerce create an opportunity for fraud. How to govern logistics systems in the physical-cyber world?	Legislation for the physical-cyber world. Cyber-security.
R	Risk management	What is the optimal design of logistic and supply chain systems under different disruptions? How to maintain healthy financial liquidity to cope with the challenges in a dynamic and uncertain business environment?	Disruptions. Financing.
A	Automation and AI	Wide range of technologies available in Industry 4.0 era. How to select the optimal technology? How to manage those huge amounts of sensitive data being collected?	Choices of technologies. Ethics with AI.

5. Future research agenda

From the reviewed literature as well as our proposed IJLRA framework, a few important issues have been proposed. In this section, we discuss them in more detail and propose the respective future research directions.

Sustainable social welfare: Logistics is a crucial part of supply chain management. A supply chain is a complex system which in general includes a lot of parties. How to employ logistics to achieve the concept of sustainable social welfare (Choi et al. 2022) becomes critical. In this context, sustainable social welfare encompasses human welfare (e.g., human rights, privacy, and ethics), company benefits, and environmental impacts. The European Commission (2021) has addressed the significance of human and environmental sustainability issues under Industry 5.0 in which business enterprises will transform to be more ‘sustainable, human-centric and resilient’. For example, in the manufacturing industries with the use of disruptive technologies, worker welfare aspects such as fair wages, worker’s diversity, worker’s empowerment, and a safe working environment should be considered.⁸ This approach can be observed in real-world practice by the Factory2Fit project which provides ‘worker-centered solutions’ to its business clients. The project emphasises the involvement and empowerment of workers in designing work processes in smart factories.⁹ On the other hand, workers will receive feedback on their work performance and well-being. This enhances factory operations through the use of disruptive technologies while worker welfare is also well-respected in daily business operations. In order to achieve the goal of sustainable social welfare, a totally new concept of management and consensus among supply chain agents as well as governments is necessary. This is super challenging and future research should be conducted to examine how this goal can be achieved, or at least ‘close-to achieve’. Furthermore, in the future, it is essential to investigate the performance of logistics management with a focus on human-centric scenarios in the Industry 5.0 era. In other words, it is pertinent to explore the human-machine collaboration mechanism and examine how to optimise the operations with a multi-objective focus on human, sustainability, and resilience.

Legal challenges in cyber-physical logistics systems: In the rapidly evolving cyber-physical world, numerous novel challenges are emerging. For instance, how to control the Non-Fungible Token (NFT) based trading and how to protect corporate benefits when the cyber-world is involved are all practical and important topics. Some of the traditional challenges such as corruption (Hu, Wagner, and Shou 2023), misinformation and fake news (Chatterjee, Chaudhuri, and Vrontis 2023), and taxation may appear in different formats in the cyber world. Governments all around the world are delving into this legal domain and considering appropriate legislative policies. In Taiwan, for example, a new anti-money laundering (AML) regulation has been enacted in 2021 to oversee cryptocurrency exchanges and related trading activities. Currently, there are 24 crypto platforms that are in compliance with the AML Control Act (Sinclair 2023). In addition, as internet technologies facilitate rapid dissemination of information globally, governments are striving to overcome the spread of misinformation through legislations (Mrazik and Remenik 2022). For example, the Australian government has introduced new laws to ensure tech-driven companies adhere to the misinformation and disinformation code of practice such as preventing the distribution of misleading content through spam and bots (Samios 2022). In terms of taxation, the Indian government has implemented significant regulations to tax incomes generated from virtual digital assets (VDAs), including crypto asset, NFTs, and tokens, which can be traded or exchanged among parties. Specifically, the trading of crypto assets and NFT is subject to a 30% tax rate (Chadha and Prasad 2022). Similarly, the UK government has also established a taxation policy for Decentralized Finance (Defi) related activities, such as lending and staking.¹⁰ We believe that to provide scientifically sound support to policy makers, further research into legal challenges, legislative frameworks, and supportive schemes associated with cyber-physical logistics systems should be conducted in the future.

Globalisation or the other way round: Joint-ventures in logistics and supply chain systems involve not only globalisation but also regional political challenges. Furthermore, disruptions and tensions are created by global crises such as COVID-19 pandemics and trade wars. For example, the Russia-Ukraine war has severely affected the supply chain systems, leading to port closures, cargo delays, product shortages, increased fuels and shipping costs, and soaring warehouse costs due to the increased demand for containers on the East Coast.¹¹ In response to these challenges, in Europe, the European Chips Act has been introduced to address semiconductor shortages. It is widely anticipated that this will stimulate significant growth in the European Battery Alliance and foster collaboration among organisations to develop a more competitive battery industry (Simchi-Levi and Haren 2022). On the other hand, businesses have also explored the potential manufacturing sites to mitigate the risk of over-reliance on a single manufacturing base (Wong 2022). To overcome all these disruptions caused by the ever-changing global business environment, it is reported that many organisations plan to adopt reshoring strategies. For example, Schneider Electric has decided to establish new manufacturing facilities in North America¹² and BishopSound has relocated its speakers’ components production to the North of England (Handley 2023). Under reshoring strategies, the use of local production and local sourcing (Choi 2013) can enable businesses to respond rapidly to market changes and meet local demand. The associated risk management challenges are timely and require innovative solutions to overcome. It is hence interesting to explore the optimal mechanisms for sharing benefits and risks through joint venture, as well as the new operational decisions under reshoring.

AI ethics: Artificial Intelligence (AI) is a double-edged sword. The recent development of ChatGPT, a chatbot developed by an American startup OpenAI, has generated huge buzz (Chui, Roberts, and Yee 2022). Launched in 2022, ChatGPT utilised machine learning techniques and is properly trained by having distinctive data and text from various Internet sources to produce intelligent, ‘human-like’ responses and solutions to a specific problem.¹³ As AI systems become increasingly sophisticated, they can enhance decision-making in logistics management in terms of both speed and accuracy. However, AI also presents challenges related to human welfare and ethics issues.¹⁴ The emergence of ChatGPT has caused serious concern about job loss, particularly for those repetitive and routine tasks. For instance, ChatGPT could potentially replace programmers or website designers by performing standard computer coding (Cerullo 2023) and automatically generating websites (Mitchell 2023) without human intervention. It is estimated that ChatGPT could completely change the labour market and replace 20% of the labour force (Waugh 2023). Another concern associated with the application of ChatGPT in industries relates to privacy and security. Since the chatbot generates responses from the inputs provided (e.g., any databases from internet sources), it will potentially threaten the privacy and security of individuals and enterprises as the detailed information and user identities can be traced. Many experts have then raised their concerns about the potential misuse of such technology by the general public (Tang 2023). Thus, such powerful AI chatbot like ChatGPT should be used responsibly and in a controllable manner, and regulation is deemed essential (Simon 2023). In addition, it is also worth our further investigation to examine the situation in which AI technologies (e.g., ChatGPT) are suitable to support logistics services. For future research, we argue that to avoid having devastating effects on human welfare, it is urgent to impose proper control on the use and development of AI. However, it is easier said than done as there are definitely all kinds of tricks behind the scenes.

6. Concluding remarks

Motivated by many changes in the world, the role and development of logistics management for the future all require our deeper considerations.

In this discussion paper, we first establish a new definition of logistics management, which is an amended version of the classic definition by CSCPM. In the new definition, we highlight the presence of two new elements, namely cash flow, and the existence of both the cyber and physical worlds.

After that, we systematically review the highly relevant literature and identify various key issues that should be addressed carefully. Based on the reviewed literature and our proposed new definition of logistics management, we discuss and establish the IJLRA framework, which includes several areas, namely Industry 5.0, joint-venture, legal-concerns, risk management, automation and artificial intelligence (AI), and the related major factors.

We argue that through proper logistics management under the IJLRA framework, organisations in the supply chain can well-achieve the goals of logistics – achieving the right time, right place, right quality, and everything right – to satisfy customer requirements in both the cyber and physical worlds. Finally, we propose a solid future research agenda, which aims at inspiring further studies on the topic.

This paper has some limitations which we would like to admit and highlight here. First, this is a discussion paper which mainly shows our opinions and comments on the topic. Even though our arguments are supported by and partially based on the reviewed literature and observed real-world practices, we do admit that there is a substantial level of subjectivity. Second, we do not intend to make an exhaustive review of the related literature in ‘every outlet’ (e.g., we have excluded the articles published in conferences and book chapters). Besides, to be more focused, our review is concentrated on the WoS categories of ‘business’, ‘operations research management science’, ‘management’, and ‘transportation’. So, some studies in other disciplines may not be covered in this review.

Acknowledgements

The authors thank our assistants Koei Yuen and Yandy Wong for their clerical assistance during the preparation of this paper. This discussion paper is written to celebrate the 25th Anniversary of International Journal of Logistics Research and Application. We sincerely thank the editors Professor Ming Lim and Professor Weihua Liu for their kind invitation to us to contribute to this special issue. We wish ‘International Journal of Logistics Research and Application’ will continue to be an impactful and successful journal in logistics. Happy anniversary!

Disclosure statement

No potential conflict of interest was reported by the author.

Funding

Hau-Ling Chan’s research is partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (RGC Project No. UGC/FDS24/B01/21).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials.

Notes

1 We sincerely thank the editors and reviewers for their critical and helpful comments on this discussion paper.

2 https://meantime.global/news/kerry-logistics-introduces-iot-solution-to-global-supply-chain-with-smart-sensor/ (accessed 6 July 2023)

3 https://www.persistencemarketresearch.com/market-research/smart-logistics-market.asp (accessed 21 February 2023)

4 https://cscmp.org/CSCMP/Educate/SCM_Definitions_and_Glossary_of_Terms.aspx (accessed 15 February 2023)

5 https://www.dpdhl.com/en/media-relations/press-releases/2019/dhl-supply-chain-partners-tetra-pak-implement-first-digital-twin-warehouse-asia-pacific.html (accessed 6 July 2023)

6 https://www2.deloitte.com/content/dam/Deloitte/fr/Documents/finance/Publications/Etude_Joint_Venture_juillet%202010.pdf (accessed 10 July 2023)

7 https://www.pwc.com/gx/en/forensics/gecsm-2022/pdf/PwC%E2%80%99s-Global-Economic-Crime-and-Fraud-Survey-2022.pdf (accessed 10 July 2023)

8 https://op.europa.eu/en/publication-detail/-/publication/468a892a-5097-11eb-b59f-01aa75ed71a1/ (accessed 20 February 2023)

9 https://factory2fit.eu/about-the-project/ (accessed 20 February 2023)

10 https://www.gov.uk/government/consultations/call-for-evidence-the-taxation-of-decentralised-finance-involving-the-lending-and-staking-of-cryptoassets/the-taxation-of-decentralised-finance-involving-the-lending-and-staking-of-cryptoassets-call-for-evidence (accessed 21 February 2023)

11 https://www.gep.com/blog/mind/russia-ukraine-war-logistics-impact (accessed 6 July 2023)

12 https://www.businesswire.com/news/home/20211110006019/en/Schneider-Electric-to-Invest-and-Build-Three-New-Manufacturing-Plants-in-North-America (accessed 6 July 2023)

13 https://op.europa.eu/en/publication-detail/-/publication/468a892a-5097-11eb-b59f-01aa75ed71a1/ (accessed 21 February 2023)

14 https://www.forbes.com/sites/qai/2023/02/01/what-is-chatgpt-how-ai-is-transforming-multiple-industries/?sh=aedf9d6728ef (accessed 21 February 2023)