Search results

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

This study examines the relationship between multi-layer supply chain flexibility (MSCF) and Supply chain resilience (SCR). Further, it looks at the moderating effect of environmental dynamism (ED) and supply chain risks (SCRI) on the relationship between MSCF and SCR.

Executives from the pharmaceutical, agri-food, electronics, automobile and textile industries were invited to complete a self-administered questionnaire. We received feedback from a total of 302 participants. Prior to conducting the primary analysis, we addressed the potential for nonresponse bias and verified the assumptions of homoscedasticity and normal distribution of the data. The reliability and validity of the constructs were established through confirmatory factor analysis. Structural equation modelling is employed for the purpose of conducting hypothesis testing.

The results demonstrate a notable influence of MSCF on SCR, particularly in settings characterized by high levels of ED and SCRI. The study highlights the importance of flexibility in multiple aspects of the supply chain to build resilience against a range of disruptions and uncertainties.

The study presents the fundamental role of Multi-Layer Flexibility in building up SCR. The results of this study reinforce the existing literature and offers empirical evidence for how ED, SCRI moderates the influence between MSCF to SCR. These results offer valuable information to both supply chain specialists and researchers for building comprehensive strategy to bring resilience in supply chains.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

This study aims to present a methodology and a system to support the technical and managerial issues involved in anomaly detection within the reverse logistics process of an e-commerce company.

A case study approach is used to document the company’s experience, with interviews of key stakeholders and integration of obtained evidence with secondary data.

The paper presents an algorithm and a system to support a more efficient and smart management of reverse logistics based on a set of anticipatory actions, and continuous and automatic monitoring of returned goods. Improvements are described in terms of a number of key performance indicators.

The analysis and the developed system need further applications and validations in other organizational contexts. However, the research presents a roadmap and a research agenda for the reverse logistics transformation in Industry 4.0, by also providing new insights to design a multidimensional performance dashboard for reverse logistics.

The paper describes a replicable experience and provides checklists for implementing similar initiatives in the domain of reverse logistics, in the aim to increase the company’s performance along four key complementary dimensions, i.e. time savings, accuracy, completeness of data analysis and interpretation and cost efficiency.

The main novelty of the study stays in carrying out a classification of anomalies by type and product category, with related causes, and in proposing operational recommendations, including process monitoring and control indicators that can be included to design a reverse logistics performance dashboard.

During the supply chain disruptions caused by COVID-19, logistics service providers (LSPs) have invested heavily in innovations to enhance their supply chain resilience capabilities. However, only little attention has been given so far to the nature of these innovative capabilities, in particular to what extent LSPs were able to repurpose capabilities to build supply chain resilience. In response, using the concept of exaptation, this study identifies to what extent LSPs have discovered and utilized latent functions to build supply chain resilience capabilities during a disruptive event of high impact and low probability.

This conceptual paper uses a theory building approach to advance the literature on supply chain resilience by delineating the relationship between exaptation and supply chain resilience capabilities in the context of COVID-19. To do so, we propose two frameworks: (1) to clarify the role of exaptation for supply chain resilience capabilities and (2) to depict four different exaptation dimensions for the supply chain resilience capabilities of LSPs.

We illustrate how LSPs have repurposed original functions into new products or services to build their supply chain resilience capabilities and combine the two critical concepts of exploitation and exploration capabilities to identify four exaptation dimensions in the context of LSPs, namely impeded exaptation, configurative exaptation, transformative exaptation and ambidextrous exaptation.

As one of the first studies linking exaptation and supply chain resilience, the framework and subsequent categorization advance the understanding of how LSPs can build exapt-driven supply chain resilience capabilities and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the repurposing of capabilities.

Sailing toward sustainability is becoming the strategic focus of shipping firms. Drawing on organizational information processing theory (OIPT) and the theory of planned behavior (TPB), we investigated the impact of digital transformation (DT) on shipping firms’ sustainable management performance and the boundary conditions guiding this relationship.

The authors examined the hypotheses by employing hierarchical linear modeling on two-wave time-lagged data from 189 shipping firm employees in China.

The results suggest that a shipping firm’s DT is positively associated with its sustainable management performance and that the relationship is strengthened by having better cross-functional and customer coordination mechanisms. Furthermore, our three-way interaction analyses show that while injunctive norms in a shipping firm’s networks can strengthen the contingency roles of both cross-functional and customer coordination mechanisms, descriptive norms alone significantly influence customer coordination.

Drawing on organizational information processing and planned behavior theories, the present research provides new insights into leveraging DT for sailing toward sustainable success. Moreover, this study extends the current understandings of the boundary conditions of the relationship between DT and sustainable management performance by showing the two-way and three-way interaction effects of coordination mechanisms and subjective norms. The findings of the present research can be utilized as effective strategies for promoting sustainable management performance.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.

As China’s e-commerce and cross-border e-commerce rapidly develop, the cross-border e-commerce supply chain exhibits characteristics of globalized development scale, collaborative multiparty participation, streamlined management processes, digitalized production and trade and flexible strategic choices. It tends toward data-driven intelligence, interoperable information collaboration, personalized order responses, sustainable supply chain management and secure blockchain technology. These characteristics and trends provide critical references for businesses, governments and investors.

In response to issues such as inconsistent legal regulations, imbalanced logistics and transportation, imperfect payment settlements and opaque supply chains.

It is recommended to take measures to strengthen cooperation and communication, optimize logistics, reduce customs clearance difficulties, reinforce safeguard measures and promote sustainable development, collectively fostering the healthy growth of cross-border e-commerce.

With the rapid development of cross-border e-commerce, green and low-carbon initiatives have become a significant trend in this sector. The cross-border e-commerce supply chain refers to the mechanism that reduces environmental impacts and enhances resource efficiency from manufacturers to consumers. It primarily involves manufacturers, e-commerce platforms, logistics companies and payment and settlement processes. The cross-border e-commerce supply chain is gradually becoming a highlight in China’s foreign trade, supporting the concept of “buying globally and selling globally” and connecting the “world’s factory” with the “world’s market.”

This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

In recent years, technological advancement has played a crucial role in the growth of emerging economies. However, as with any novel technological development, there are often concerns and hesitations surrounding its implementation. This study aims to investigate the factors influencing blockchain adoption and usage. Thereby evaluating its impact on supply chain performance.

This is a deductive research based on the modified form unified theory of acceptance and use of technology, which is a persuasive model that has been used in numerous studies on the acceptance and usage of information technology systems. For this study, valid data was collected from 129 management-level supply chain professionals and policymakers working in diverse manufacturing industries. The collected data was used for testing hypotheses by deploying the structural equation modeling technique.

The findings of this study reveal that facilitating conditions and technology readiness highly are key influencers for organizations to implement this disruptive technology. Moreover, blockchain adoption and usage can significantly enhance supply chain performance.

Blockchain technology is a novel and promising disruptive technology that industries are looking forward to adopting and using. For the policymakers and supply chain strategists working in a developing country, this study offers a comprehensive viewpoint on the swift acceptance and usage of blockchain technology to facilitate supply chain operations.