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Oil and gas sector has more disruptions regarding its logistics management than any other industry. It is critical to understand which external security threats disrupt the oil and gas supply chain (OGSC). Recently, the time interval between these disruptions became frequent. the purpose of this paper is to identify key logistics elements that lead to such disruptions which would greatly benefit the oil and gas industry in developing more effective mitigation measures and resilient practices in the future.

This research develops the theoretical framework through a critical review of all theories related to resilience, logistics disruptions and mitigation methods in the oil and gas industry. Afterward, semi-structured interviews were conducted with executives in the Egyptian oil and gas industry to develop a conceptual framework. Finally, an empirical study was conducted through questionnaires with managers in the Egyptian oil and gas sector to develop the applied framework.

This research revealed that achieving an elevated level of flexibility, redundancy, visibility and collaboration in the Egyptian OGSC will significantly increase the level of resilience in the sector and consequently help in mitigating probable logistics disruptions.

This research contributes to academia by providing a conceptual framework for the most common logistics disruptions in the Egyptian OGSC and providing practitioners with the best resilience practices that are feasible and effective in mitigating logistics disruptions.

Previous research studied disruptions in OGSC from different perspectives: economic, social, political, technical, safety, legal and environmental perspectives, but no research highlighted the logistics perspective in the Egyptian context, to the best of the authors’ knowledge.

Pricing the shipping surcharge is a major strategic decision for online retailers, and free shipping promotions are becoming more common among online retailers. The purpose of this research is to examine the effect of last mile pricing strategies on customer attraction and retention in the hypercompetitive online retailing industry. Specifically, this paper investigates the effect of partitioning the shipping surcharge on consumer logistics service quality (LSQ) perceptions and, in turn, purchase behavior.

Employing signaling theory and expectation–disconfirmation theory, hypotheses are derived for two specific points in an online purchase scenario: prepurchase and following a logistics disruption. The hypotheses are tested using a scenario-based experiment with manipulations for the level of shipping surcharge partitioning and the presence of a logistics disruption.

The results suggest that partitioned shipping surcharges influence prepurchase expectations of LSQ satisfaction and amplify the negative effects of logistics disruptions. This, in turn, drives the purchase and repurchase intentions.

The findings inform online retailers of the perceptual and behavioral effects of last mile pricing strategies. Specifically, this research demonstrates how and under what conditioning partitioning the shipping surcharge can influence the attraction and retention of online customers.

This study integrates pricing and LSQ research to assess the black box of consumer purchase behavior. This is one of the first studies to empirically contrast the effects of last mile pricing strategies on consumer expectations and perceptions of LSQ.

The purpose of this paper is to examine (1) how the recovery speed using promotional investment and (2) distributed production using additive manufacturing (AM) improve the resilience of the supply chain to manage any disruptions in the diffusion of green products.

The environmental performance, service level performance and economic performance are the measures of interest. These measures are studied through the integration of inventory and production planning (I&PP) of the reverse logistics system and consumer behavior using Bass (1969) model of diffusion of innovation under the paradigm of Industry 4.0 architecture. The Taguchi experimental design framework was used for the simulation analysis.

The adoption patterns based on the Bass model in conjunction with recovery speed and production on AM during the disruption period suggest that there exist tradeoff decisions between various combinations of information-sharing and I&PP policies.

The extensive sensitivity analyses provide real-time support for managerial decisions. Besides the potentials of Industry 4.0 capabilities, the present research suggests paying close attention to the recovery speed in conjunction with the inventory management system.

The integration of consumers' behavior (Bass model) to digital technologies is an additional contribution of the present research toward sustainability issues from the social perspective.

Previous research studies have discussed resilience to manage the ripple effect. However, none of them have addressed the changing scope of resilience to manage the ripple effect caused by the disruption in the diffusion of green products in a reverse logistics setup.

A growing need for global sourcing of business has subjected firms to higher levels of uncertainty and increased risk of supply disruption. Differences in industry and infrastructure make it more difficult for firms to manage supply disruption risks effectively. The purpose of this paper is to extend developing research in this area by addressing gaps within existing literature related to environmental turbulence and uncertainties.

The authors test the model using data collected from 253 senior managers and directors in the Thai beverage industry using advanced statistical techniques to explore the relationship between representations of supply disruption risk and uncertainty.

The results show that both magnitude and probability of risk impact on the disruption risk, but the probability of loss is a dominant determinant. The authors also find that demand uncertainty and quality uncertainty affect the risk perception of purchasing managers, and are related to the magnitude of disruption risk, rather than the frequency of occurrence. Interestingly, the results show that quality uncertainty negatively impacts on the severity of disruption risk.

The construct validity of demand uncertainty was under the required threshold, intimating the need for further construct development.

The framework provides managers with direction on how to formulate and target their disruption risk management strategies. The work also allows practitioners to critical reflect on implicit risk management strategies they may already employ and their effectiveness.

The paper identifies key antecedents of supply disruption risk and tests them within a novel industrial context of the beverage industry and a novel national context of Thailand.

Logistics capability is an important enabler of supply chain resilience (SCR). However, few studies have analyzed the underlying influence mechanism of logistics capability on SCR in extreme conditions, such as those of the COVID-19 pandemic. The purpose of this study is to increase understanding of the role of logistics capabilities in constituting a resilient supply chain.

Drawing upon the dynamic capability perspective and contingency theory, the proposed conceptual framework aims to demonstrate the relationship between a firm's logistics capabilities and SCR. Furthermore, the conceptual framework is illustrated by empirical evidence from a case study of a Chinese manufacturing company, which focuses on extracting practical lessons from the COVID-19 pandemic.

The findings suggest that digitalization, innovativeness, and modularization comprise potential mediating pathways for firm logistics capability to affect SCR and government policies, risk management culture, trust and cooperation moderate the effect positively. The potential associations are identified and elucidated by detecting the corresponding strategies and practices of a Chinese manufacturer that performed well amid the COVID-19 pandemic.

This study provides specific guidelines for logistics managers to enhance SCR during the COVID-19 pandemic. Seeing SCR as a dynamic capability, the framework is also instructive for manufacturers, supply chain members, and policymakers to achieve the sustained competitive advantage of supply chains.

The findings expand the understanding of enhancing SCR in a logistics approach. The empirical validation of propositions in the case study reveals a new vista for research on SCR.

Presently, Indian sectors are manifesting a higher level of interdependency and making the economy more vulnerable to human-caused and natural disasters. COVID-19 pandemic creates a devastating effect on the world economy. The Indian economy was expected to lose around ₹ 32,000 crores every day during the first 21 days of complete lockdown. This motivates to conduct the research on how the COVID-19 pandemic affects the port logistics sector and how the effects of COVID-19 on port logistics propagate to other sectors owing to its interconnectedness and affect the economy of the country.

The purpose of the study is analyze how perturbation in one sector can affect the system of interdependent sectors and it is done with interdependency analysis. It uses Wassily Leontief’s inoperability input-output model (IIM) and interval programming (IP) to develop a framework. IP is used to address situations where assumptions are not valid because of uncertainties associated with disruptive events.

The model helps in describing how the effect of the COVID-19 pandemic in port logistics can propagate owing to the interconnectedness across other sectors. The model uses the latest five-year data available on the Organisation for Economic Co-operation and Development database. It uses metrics like inoperability and economic loss to study the consequences of COVID-19 pandemic on various sectors. This study also presents the ranking of the affected sectors based on their inoperability and economic loss

In the future study, other techniques like dynamic evolution, multiplex network analysis, analytical hierarchy process, pinch analysis, stochastic evolution and pinch graph could be integrated with input-output (I-O) modelling. Integrated stochastic evolution with an I-O model allows capturing the likelihood of the events; it includes probability distributions instead of point estimates for scenario parameters. Methods like dynamic evolution and multiplex network analysis can be introduced in future work to shed lights on interdependency among the sector, which could potentially provide additional insights for transport policy formulations.

This study discusses the theory, methodology and application of the IIM-IP model in the domain of port logistics. The developed IIM-IP model helps decision-makers to manage risk in port logistics. Firstly, it studies how different sectors are interconnected with each other. Secondly, it helps in identifying the most vulnerable sectors based on economic loss and inoperability. Thirdly, it provides the ranking of the sectors based on their economic losses.

International supply chains can be severely disrupted by failures in international logistics processes. Therefore, an understanding of international logistics risks, or causes of failure, how these may interact with each other and how they can be mitigated are imperatives for the smooth operation of international supply chains. The purpose of this paper is to specifically investigate the interactions between international logistics risks within the prevailing structures of international supply chains and highlights how these risks may be inter-connected and amplified. A new dynamic supply chain logistics risk analysis model is proposed which is novel as it provides a holistic understanding of the risk event interactivity.

The paper applies interpretive structural modelling to data collected from a survey of leading supply chain practitioners, in order to analyse their perspectives of risk elements and interactions. The risk elements and their contextual relationship were derived empirically through the use of focus groups and subsequent Delphi study. The two stages of the research rely on experts’ views on risk events and clusters and the level of interactions among those clusters.

A key finding of this research is that supply chain practitioner’s perception of risk consists of inter-connected four levels: value streams risks; information and relationship risks; risks in international supply chain activities; and external environment. In particular, since level 2 risk creates feedback loops of risks, risk management at level 2 can dampen the amplification effect and the strength of the interactions.

Several managerial implications are drawn. First, the research guides managers in the identification and evaluation of risk events which can impact the performance of their international logistics supply chain operations. Second, evidence is presented that supports the proposition that the relationships with trading partners and LSPs, and the degree of logistics information exchange, are critical to prevent, or at least mitigate, logistics risks which can substantially affect the responsiveness of the international supply chain.

The main contribution to knowledge that this study offers to the literature on supply chain risk management is the development of a supply chain logistics risk analysis model which includes both risk elements and interactions. The research demonstrates the importance of taking into account risk interactions in the process of identification and evaluation of risk events.

The purpose of this paper is to identify how the relationship between inbound logistics (IL) activities and elements of resilience (EoR) can contribute to organisational resilience.

Two in-depth case-based studies were conducted in the dairy industry. After identifying EoR and IL activities through a systematic literature review, relationships among them have been empirically discussed in six groups (emerged content analysis results): supplier and response capability; transportation; security; quick response to disruption; logistics management; trust and knowledge.

A framework was developed describing the contribution of these six groups to organisational resilience by highlighting and discussing three aspects: rigidity of the hierarchy, type of relationship and geographical dispersion. These aspects emerged from the process of content analysis and are related to the companies’ characteristics.

The proposed framework can assist managers to decide which group of EoR and IL activities they should prioritise, depending on the company’s characteristics and needs.

Although some studies have discussed the IL contribution to generating resilience in companies, none of them have explored in detail the relationship between EoR and IL activities, and their contribution to organisational resilience. The proposed framework shows the contribution of the EoR to three different organisational aspects.

As the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.

A causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.

The result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.

In this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.

The present study aims to assess the role of supply chain resilience as an operational excellence approach to deal with disruptions caused by coronavirus pandemic in the food supply chain of an agri-food supply firm.

The case study method was used to analyse the disruptions faced by the agricultural food supply chain during the pandemic. The study applies a dynamic capability theory as a foundation to develop a contextualised resilience framework for agri-food supply chain to achieve operational excellence. The case has been analysed by using situation-actor-process (SAP) and learning-action-performance (LAP) framework.

The SAP aspect of framework points that the flexibility amongst actors for a resilient agriculture supply chain worsened due to the lockdown measures post COVID-19. The LAP aspect of framework suggests how resilience can be built at the supply, demand and logistics end through various proactive and reactive practices such as collaboration, coordination, ICT and ground-level inputs. Lack of commitment and inadequate support from top management towards supply chain resilience are also observed as significant challenges to maintain operational excellence during the pandemic.

One of the major implications of the study is that a mix of capabilities rather than a single capability can be the most appropriate way for making the supply chain resilient to maintain operational excellence during the pandemic. However, the sources of disruptions need to be duly recognised to derive the best-contextualised resilience framework for agri-food supply chains.

The development of a contextualised research framework as well as research propositions for analysing supply chain resilience are the major contribution of this study.