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With the holistic approaches of Industry 4.0, products, services, standards, and application techniques have been improved. This digitalization era has not only impacted the production and service dynamics, but also added advanced dimensions to logistics and supply chain management. According to the current world standards, consumer behavior makes the logistics and supply chain processes more challenging. Especially during the COVID-19 outbreak, logistics and supply chain operations became more crucial for the firms, as most consumers have tended toward online shopping while they are in lockdown. Therefore, the competitive environment today enables firms to adapt the technologies and approaches of Logistics 4.0 and smart/digital supply chain, as they must respond to consumers' demands quickly. Moreover, firms need to have strong relations with their supply chain partners via these technologies. The technologies such as the Internet of Things (IOT), cyber-physical system, Big Data, and cloud computing help to change the fundamentals of logistics and supply chain and improve processes for all industries. This study aims to analyze the transformation of traditional logistics and supply chain activities into Logistics 4.0 and smart/digital supply chain. Primarily, we hope to analyze the existing studies by investigating the concept of Logistics 4.0 within Industry 4.0 dynamics. As firms develop their logistics operations, their supply chain processes will be shaped by the technologies and applications, and this situation also leads us to find out the importance of smart or digital supply chain operations. Discussing the potentials of smart or digital supply chain also lets us to reveal how companies handle their logistics operations during the COVID-19 period.

This study considers the potential of logistics 4.0 for supply chain (SC) optimization in French retail. The authors investigate the implementation of Industry 4.0 technologies to optimize SC performance in the retail sector and SC's role in the digital transformation in supply chain management (SCM).

The authors first carry out a comprehensive bibliographic taxonomy to highlight the different existing digital tools. Based on this, the authors posed three research questions (RQs) and hypotheses to examine the contribution of logistics 4.0 in improving the performance of retail logistics. Then, the authors considered a case study of retail in France based on qualitative and quantitative analysis to answer all the RQs and examine the hypotheses.

The results showed that digital tools such as Cyber Security Systems (CSS), Big Data Analytics (BDA) and Blockchain (BC) technology are the most effective and appropriate tools to optimize the SC performance in retail.

This research work showed that the implementation of these tools in retail can offer several benefits such as improved productivity, optimized delivery times, improved inventory management and secure real-time communication, which leads to improved profitability of the SC.

The study opens a door to develop practical roadmaps for companies that enable smart deliveries based on logistics 4.0.

In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as warehousing are still exploring its applicability, and the technological implementation of this paradigm can become fuzzy. This paper addresses this gap by examining the relationship among influencing factors, barriers, and benefits of Logistics 4.0 technologies in warehousing contexts.

Starting from a Systematic Literature Review (SLR) approach with 56 examined documents published in scientific journals or conference proceedings, a conceptual framework for Logistics 4.0 in warehousing is proposed. The framework encompasses multiple aspects related to the potential adopter’s decision-making process.

Influencing factors toward adoption, achievable benefits, and possible hurdles or criticalities have been extensively analyzed and structured into a consistent picture. Company’s digital awareness and readiness result in a major influencing factor, whereas barriers and criticalities are mostly technological, safety and security, and economic in nature. Warehousing process optimization is the key benefit identified.

This paper addresses a major gap since most of the research has focused on specific facets, or adopted the technology providers’ perspective, whereas little has been explored in warehousing from the adopters’ view. The main novelty and value lie in providing both academics and practitioners with a thorough view of multiple facets to be considered when approaching Logistics 4.0 in logistics facilities.

The study investigates the effect of technological capabilities, organizational capabilities and environmental capabilities on Logistics 4.0 capabilities and also examines the effect of Logistics 4.0 capabilities on firm performance.

The proposed theoretical framework is tested using WarpPLS 6.0 software. We selected samples from the Automotive Component and Allied Manufacturers in South Africa. Initially, we sent the structured questionnaire online using Google forms to 800 potential respondents. After doing follow ups, we received 230 completed survey responses. Further, data preparation is done using established scientific approach and we checked suitability of its use in structural equation modelling. After ensuring all necessary checks are completed, the results are found satisfactory to further proceed with testing of research hypotheses.

It is observed that technological capabilities, organizational capabilities and environmental capabilities show significant effect on Logistics 4.0 capabilities. However, the outcome of technological capabilities and environmental capabilities on Logistics 4.0 capabilities (ß = 0.27) is found stronger than organizational capabilities. Logistics 4.0 capabilities shows significant effect on firm performance.

It is important that the sustainability goals are aligned with Logistics 4.0 strategies. Managers need to increase focus towards development of Logistics 4.0 dynamic capabilities that enhance agility and responsiveness in the supply chain. Managers should check the financial performance and market conditions continuously to further review logistics performance as this can influence the overall firm performance.

This study advances the literature on Logistics 4.0 applications in operations management by investigating the key links such as Logistics 4.0 capability development and firm performance.

This study aims to provide a measurement model, and the underlying constructs and items, for Logistics 4.0 in manufacturing companies. Industry 4.0 technology for logistics processes has been termed Logistics 4.0. Logistics 4.0 and its elements have seen varied conceptualizations in the literature. The literature has mainly focused on conceptual and theoretical studies, which supports the notion that Logistics 4.0 is a relatively young area of research. Refinement of constructs and building consensus perspectives and definitions is necessary for practical and theoretical advances in this area.

Based on a detailed literature review and practitioner focus group interviews, items of Logistics 4.0 for manufacturing enterprises were further validated by using a large-scale survey with practicing experts from organizations located in Central Europe, the Northeastern United States of America and Northern Thailand. Exploratory and confirmatory factor analyses were used to define a measurement model for Logistics 4.0.

Based on 239 responses the exploratory and confirmatory factor analyses resulted in nine items and three factors for the final Logistics 4.0 measurement model. It combines “the leveraging of increased organizational capabilities” (factor 1) with “the rise of interconnection and material flow transparency” (factor 2) and “the setting up of autonomization in logistics processes” (factor 3).

Practitioners can use the proposed measurement model to assess their current level of maturity regarding the implementation of Logistics 4.0 practices. They can map the current state and derive appropriate implementation plans as well as benchmark against best practices across or between industries based on these metrics.

Logistics 4.0 is a relatively young research area, which necessitates greater development through empirical validation. To the best of the authors knowledge, an empirically validated multidimensional construct to measure Logistics 4.0 in manufacturing companies does not exist.

The purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.

The factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).

The prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.

Indian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.

The novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.

Global trade depends on more complex, prolonged and larger port systems, where port logistics is a backbone for such operations. Ports are responsible for transferring more than 80 percent of the global trade. Port logistics are prone to being risk-oriented. The study proposes a model to study various port logistics barriers and their associated risks for emerging economies in the Industry 4.0 era.

The study develops a framework by integrating the fuzzy set theory, the evidential reasoning approach and the expected utility theorem for identifying the severity value of port logistics barriers under the Industry 4.0 era for emerging economies and prioritize them based on various perspectives. The study identifies multiple risks associated with the barriers, and intensity-based categorization of the risks is performed for risk profiling.

The study reveals that poor infrastructure, nonsupportive policy ecosystem, and lack of research and development are the top barriers that need immediate attention. A new approach has been proposed that changes the importance of perspectives, and 192 analytical experiments were done to study the changing behavior of barriers. The study also presents various types of risks associated with the selected barriers.

In future studies, other barriers can be discovered and studied to develop such models. To cover the entire spectrum of possibilities, belief degrees of the barriers could be used to study the barriers instead of changing the weights.

This study presents a quantification model to prioritize the barriers based on environmental, economic and operational perspectives. Further, the model helps create scenarios for decision-makers to improve port logistics performance and achieve sustainability. The study identifies various risks associated with port logistics barriers and allows decision-makers to take proactive actions.

This study contributes significantly to the literature on port logistics by developing a framework for determining the severity of the barriers in the Industry 4.0 era for emerging economies. Further, the study pinpoints various risks associated with port logistics, and risk profiling is carried out.

The purpose of this study is to gain a better understanding of the impacts of Logistics 4.0 initiatives (focusing on automated warehousing systems) on the economic, environmental and social dimensions of firms' sustainability performance. To achieve this objective, a new framework for the assessment of sustainable warehousing in the 4.0 era is developed.

The framework, developed via the item-objective congruence index, Q-sort method and interviews with experts, is employed to assess performance changes through management interviews in two warehousing companies after the implementation of automation technologies.

Most aspects of both companies' sustainability performance are considerably improved (e.g. productivity, accuracy, air emission, worker safety and supply chain visibility); however, the outcome for some criteria might be worsened or improved depending on each company's solutions and strategies (e.g. increasing electricity bills, maintenance costs and job losses).

The findings provide insight into the effective implementation of warehousing technologies. The proposed framework is also a valid and reliable instrument for sustainability assessment for warehousing operators, which companies can utilise for self-assessment.

This paper contributes to establishing a body of literature that explores the previously unclarified effects of Logistics 4.0 on firms' sustainability performance. The proposed framework, which captures critical concerns of corporate sustainability and technological adaptation, is also the first of its kind for warehouse performance assessment.

Technology is the lifeline for the logistics industry, and it has been immensely disrupted by the emerging blockchain technology. This paper has two main objectives. The first is to explore how the current blockchain technology can be implemented in the logistics industry with the aim of improving logistic services amongst the network of logistics service providers (LSPs). The second is to propose the development of a blockchain model for the small and medium logistics service supply chain.

A prototype blockchain-based logistics system has been created and tested in a case study with a real logistics company. The primary technologies for developing a blockchain model on the Hyperledger platform as well as how the system is designed based on the logistics service flow are explained.

The study has resulted in the successful implementation of the proposed prototype blockchain-based logistics system. In particular, the case company has managed to fully utilise the developed tracking and tracing system. Whilst utilising the prototype, the participants have been able to fulfil their responsibilities in an effective manner. The performance of LSPs has improved following the World Bank Logistics Performance Index (LPI) criteria.

This paper contributes to current research in the application of blockchain technologies in the domain of logistics and the supply chain to progress LSPs towards Logistics 4.0. The current frameworks for Logistics 4.0 and how blockchain as a disruptive technology revolutionises logistic services are reviewed. In addition, this paper highlights the benefits of blockchain technology that LSPs can leverage to further improve their performance based on the LPI criteria.

This study illustrates the experience of scholar–practitioner collaboration for data-driven decision-making through the problematic of optimizing facility locations and minimizing logistics costs for La Palette Rouge (LPR) of Portugal.

The authors used a mixed mixed-method approach involving (1) a quantitative exploratory analysis of big data, which applied analytics and mathematical modeling to optimize LPR's logistics network, and (2) an illustrative case of scholar–practitioner collaboration for data-driven decision-making.

The quantitative analysis compared more than 20 million possible configurations and proposed the optimal logistics structures. The proposed optimization model minimizes the logistics costs by 22%. Another optimal configuration revealed that LPR can minimize logistics costs by 12% through closing one of its facilities. The illustrative description demonstrates that well-established resource-rich multinational enterprises do not necessarily have the in-house capabilities and competencies to handle and analyze big data.

The mathematical modeling for optimizing logistics networks demonstrates that outcomes are readily actionable for practitioners and can be extended to other country and industry contexts with logistics operations. The case illustrates that synergistic relationships can be created, and the opportunities exist between scholars and practitioners in the field of Logistics 4.0 and that scientific researcher is necessary for solving problems and issues that arise in practice while advancing knowledge.

The study illustrates that several Logistics 4.0 challenges highlighted in the literature can be collectively addressed through scholar–practitioner collaborations. The authors discuss the implications of such collaborations for adopting virtual and augmented reality (AR) technologies and to develop the capabilities for maximizing their benefits in mature low-medium technology industries, such as the food logistics industry.