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Technologies continue to disrupt logistics and freight transport (known as smart logistics), but their impacts on smart city sustainability is underinvestigated. Drawing on technology, organisation and environment (TOE) perspective, the objective of this study is to empirically investigate the hierarchical effects of smart logistics on smart city sustainable dimensions (i.e. environmental, social and economic).

The study used cross-sectional survey to collect data from urban transporters, warehouse managers, retailers and information technology (IT) managers in Australia. Data were analysed using structural equation modeling (SEM) to test the hypothesised relationship between constructs of smart logistics and smart city sustainable performance.

The findings reveal that information and communications technologies (ICTs) use and IT capability (ITC) have positive and significant effects on smart logistics. Technology-enabled smart logistics have an immediate positive effect on smart city environment, which in turn has positive impacts on social and economic performance.

The study informs managers that smart logistics equipped with freight transport telematics can improve smart city environment through enhanced tracking and tracing of goods movement. The improved environmental stewardship is likely to support social and economic performance.

Smart city research remains primarily theoretical and focussed on concerns surrounding sustainable growth amid urbanisation and digitalisation. City logistics and urban freights play key role in smart city economic growth, but vehicular pollution pose social and environmental challenges. Technology-assisted smart logistics are likely to improve smart city sustainable performance but yet to find how they affect each other.

This study explores the influencing factors on organizational efficiency of the smart logistics ecological chain, and designs the corresponding theoretical framework to guide the practice of enterprises

A multi-case study method is adopted in this study. It includes four companies A, B, C and D in China as the case study objects, collects data through enterprise survey and uses the combination of open coding and spindle coding to process the data. By testing the reliability and validity, the theoretical framework is summarized.

First, organizational efficiency in smart logistics ecological chains is directly related to their service and technology innovation capability. Second, symbiotic relationships, information sharing and customer demand affect the efficiency of smart logistics multi-case ecological chains by influencing their service capacity; their technological innovation capability regulates the mechanism of influence. Third, technological innovation in smart logistics ecological chains positively impacts their service capabilities. Improving technological innovation capability can enhance logistics service capabilities.

According to the characteristics of smart logistics, the theoretical framework about organizational efficiency of smart logistics ecological chain is constructed, which fills the research gap and can provide interesting perspectives for the future research related to the smart logistics ecological chain. At the same time, the findings can also help enterprises to better build the smart logistics ecological chain in practice.

Nowadays, companies have required new alternatives and strategies to handle environmental sustainability difficulties, primarily as ecological and social awareness has grown. In this context, the aim is to determine the green transportation indicators in companies with corporate identity and logistics activities at the international level in Giresun, Ordu, Gümüshane, Artvin, Rize, and Trabzon in the Eastern Black Sea Region in Turkey. At the same time, the study contributes to providing an effective and applicable solution to decision-making problems involving the assessment of green transportation indicators and smart network strategies in the logistics sector, which is a critical sector for countries. The purpose of this paper is to address these issues.

This study aims to propose a model for the selection of smart network strategy and to determine the criteria weights used in green transportation indicators, and establish an ideal smart network strategy. In achieving the outlined goals of the study, the authors believe that the model proposed in the study will draw the focus to green logistics which will aid the environmental, economic and social efforts of businesses and governments through the provision of efficient use of scarce resources, which will, in turn, ensure that we leave a sustainable environment for future generations and businesses enjoy a competitive advantage. At the same time, different smart network strategies and green transportation indicators in companies show the success rate of social, economic and environmental indicators in green logistics practices. In addition to providing innovative, reliable and sustainable transportation systems, smart network strategies are critical for businesses to create cost advantages. Through the green transportation indicators and smart network strategies selection model outlined in this study, it is clear that the contribution will not only be limited to businesses, as the society and governments will also benefit from the important indicators on sustainability, as well as the protection of the environment and nature.

According to the findings, “economic indicators” is the essential green transportation indicator in logistics companies with a corporate identity and worldwide transportation operations. Besides, the “mixed access model strategy” is the most appropriate smart network strategy in logistics firms with corporate identity and worldwide transportation activities. Currently, it is possible to assume that logistics organizations prefer to profit from all smart network strategies in terms of cost optimization and competitiveness rather than from just one. The study, on the other hand, which is a road map that will help sustainability practices in the logistics sector due to green transportation, also examines the similarities and differences of green transportation practices in companies in the relevant sector and to what extent they can be reflected. As a result, the study provides a practical road map for selecting green transport indicators and a smart network strategy process for the logistics industry.

This study examined logistics companies with a corporate identity and international transportation activities in provinces in the Eastern Black Sea Region such as Ordu, Giresun, Trabzon, Rize, Artvin and Gümüshane. Novel picture fuzzy level based weight assessment (PF-LBWA) and picture fuzzy combined compromise solution (PF-CoCoSo) methods are developed to solve the decision-making problem.

The research article's primary purpose is to understand the advancements in urban logistics and allied fields over time along with a consideration of its enabling technologies.

An initial review is used to build a keyword vocabulary, combinations of which were then applied to the Scopus, ScienceDirect, Emerald Insights, the Web of Science (WOS), Elsevier, Taylor and Francis, Wiley, Inderscience, Springer, Google Scholar and IEEE Xplore for extracting academic publication collection. The first part includes bibliometric analysis; network analysis is done based on the finally selected 645 papers (only those articles include either of the keywords mentioned above in title, abstract, and keywords). The second part conducts a review of the existing literature review studies (only 21 literature review studies out of 645 articles). The last one discusses the advancement in the topics based on the selected research articles.

This research discussed the advancement of the urban logistics and allied field, key academic forums and key researchers. It is evident from the analysis that the research related to key emerging themes like implementing innovative concepts and sustainability; application of green technologies; data collection, visualization, monitoring and sharing; and automatic logistic systems are still in the nascent stage. However, these research areas gained momentum in the recent past.

Urban logistics are essential and play a crucial role for such rapidly growing cities to function. Despite playing a vital role, urban ecosystem logistics is often neglected in formal urban planning. Hence, as a response to customer and business demand, private entities regularly invest in new technologies and solutions. Since such investments are toward profits, various environmental, social and economic challenges arise.

This research investigates the advancements in urban logistics toward smart, sustainable reforms in developing enabling technologies and markets. The obtained research articles are subjected to bibliometric, descriptive, network and content analysis to present a rundown of advancements, relationships and trends in emerging research gaps.

Today, the transport industry is facing increasing demands on reducing both the environmental impact and cost of freight transports. Another demand, coming from the end consumers, is the demand for ecological accountability, so‐called ecological foot‐printing, meaning that the emission of every freight movement is distributed to the freight. Previous research shows that transport planning, system integration and control are some of the key factors to achieve more sustainable transport setups. One of the major obstacles preventing these factors is the complexity of international supply chains, with several involved actors. Smart Freight is a holistic concept, integrating transport management and state‐of‐the‐art technologies for freight tracking and vehicle monitoring, in order to enable improved management and accountability of freight transportation. The purpose of this research is to explore how Smart Freight can be used to control, track and reduce the environmental impact of goods transportation. This research is based on two in‐depth case studies and a demonstration prototype of one of the studied transport setups. An extensive amount of data was collected between 2006 and 2008 through interviews, video filming, document studies, physical travel with the freight flows, seminars, prototype building, literature and desktop studies. The result of this research highlights the weaknesses in today’s control of transport operations and presents a model for how Smart Freight enables a more environmentally friendly and accountable transport system.

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.

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.

Smart manufacturing is the prime gripper for the transformation and upgrading of the manufacturing industry. Smart manufacturing systems (SMSs) largely determine how smart manufacturing evolves in technical and organizational dimensions and how it realizes values in products, production or services. SMSs are growing rapidly and receiving tons of attention from academic research and industrial practice. However, the development of SMSs is still in its fancy, and many issues wait to be identified and solved, such as single point failures, low transparency and ineffective resource sharing. Blockchain, an emerging technology deriving from Bitcoin, is competent to aid SMSs to conquer troubles due to its decentralization, traceability, trackability, disintermediation, auditability and etc. The purpose of this paper is to investigate the blockchain applications in SMSs, seek out the challenges faced by blockchain-enabled SMSs (BSMSs) and provide referable research directions and ideas.

A comprehensive literature review as a survey is conducted in this paper. The survey starts by introducing blockchain concepts, followed by the descriptions of a literature review method and the blockchain applications throughout the product life cycle in SMSs. Then, the key issues and challenges confronting BSMSs are discussed and some possible research directions are also proposed. It finally presents qualitative and quantitative descriptions of BSMSs, along with some conclusions and implications.

The findings of this paper present a deep understanding about the current status and challenges of blockchain adoption in SMSs. Furthermore, this paper provides a brand new thinking for future research.

This paper minutely analyzes the impacts that blockchain exerts on SMSs in view of the product life cycle, and proposes using the complexity science thinking to deal with BSMSs qualitatively and quantitatively, including tackling the current major problems BSMSs face. This research can serve as a foundation for future theoretical studies and enterprise practice.

The purpose of this paper is to present a conceptual model that defines the essential components shaping the new Digital Supply Chains (DSCs) through the implementation and acceleration of Industry 4.0.

The scope of the present work exposes a conceptual approach and review of the key literature from 1989 to 2019, concerning the evolution and transformation of the actors and constructs in logistics and Supply Chain Management (SCM) by means of examining different conceptual models and a state-of-the-art review of Industry 4.0’s concepts and elements, with a focus on digitization in supply chain (SC) processes. A detailed study of the constructs and components of SCM, as defined by their authors, resulted in the development of a referential and systematic model that fuses the inherent concepts and roles of SCM, with the new technological trends directed toward digitization, automation, and the increasing use of information and communication technologies across logistics global value chains.

Having achieved an exploration of the different conceptual frameworks, there is no compelling evidence of the existence of a conceptual SCM that incorporates the basic theoretical constructs and the new roles and elements of Industry 4.0. Therefore, the main components of Industry 4.0 and their impact on DSC Management are described, driving the proposal for a new conceptual model which addresses and accelerates a vision of the future of the interconnectivity between different DSCs, grouped in clusters in order to add value, through new forms of cooperation and digital integration.

This research explores the gap in the current SCM models leading into Industry 4.0. The proposed model provides a novel and comprehensive overview of the new concepts and components driving the nascent and current DSCs. This conceptual framework will further aid researchers in the exploration of knowledge regarding the variables and components presented, as well as the verification of the newly revealed roles and constructs to understand the new forms of cooperation and implementation of Industry 4.0 in digitalized SCs.

The purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability.

Nineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions.

The five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance.

Researchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories.

Compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.