Search results

The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

Catastrophic supply chain disruptions can significantly damage the operational and financial performance of firms. While a growing body of literature on supply network structures has studied what influences supply networks' vulnerability to supply chain disruptions and capability to recover from them, it remains unclear how supply network structures change after major supply chain disruptions. We aim to provide an understanding of how these changes occur.

Using a natural experiment approach and supply network data from Factset, this study investigates how firms' supply network structures change after experiencing the catastrophic supply chain disruptions caused by the 2011 Tohoku earthquake and tsunami in Japan. We capture post-earthquake supply network changes using the measures of degree centrality and ego network density.

The results of the analysis suggest that compared to unaffected firms, the affected firms experience changes in their supply network structures tending toward lower complexity measured by in-degree centrality, out-degree centrality and ego network density.

This study contributes to social network theory and the complex adaptive supply network literature by providing empirical evidence of structural changes in supply networks after catastrophic supply chain disruptions. A managerial contribution is made by providing a reflection on why these changes might be occurring and alert firms to the challenges of managing complexity in their supply networks.

The purpose of this paper is to understand which controlling and enabling practices are used, how the numerous supplying partners are managed and how positive network effects are generated in online service triads (multi-sided platform – supplying partners – consumers).

A single representative in-depth case study was conducted to refine theory on managing service triads. The main data source consists of field notes collected by one author, who held a temporary position within the organization. Additional data were collected from observations, internal documents, informal talks and 20 interviews.

The authors found controlling and enabling organizational practices in four main categories on two levels as follows: managing network composition (system level), managing order fulfillment and returns (operations level), category management (both levels) and capability enhancement (both levels).

The authors show that both controlling and enabling practices are present in online service triads. This enables platform owners and supplying partners to share responsibilities for creating positive network effects, i.e. to increase scale, which increases value, which again attracts more suppliers and consumers, which creates more value, etc.

The authors present a range of and controlling and enabling practices that describe how multi-sided platforms can manage numerous supplying partners in an online context.

This study is the first to show that contractual and relational governance is insufficient in service triads in online settings with numerous supplying partners. Further, the authors provide empirical evidence that supply networks continuously adapt over time.

The purpose of this paper is to provide new insights into the reactions and lessons learned with regard to the COVID-19 pandemic in terms of how logistics service providers (LSPs) managed to maintain supply chains resilience and what focus areas have been changed to keep operations functional and uphold financial stability.

Based on data-gathering techniques in interpretive research this study collected primary data via semi-structured interviews, interviewing informants from selected LSPs that operate on a global scale.

The results show that LSPs have built their reactions and actions to the COVID-19 outbreak around five main themes: “create revenue streams,” “enhance operational transport flexibility,” “enforce digitalization and data management,” “optimize logistics infrastructure” and “optimize personnel capacity.” These pillars build the foundation to LSP resilience that enables supply chains to stay resilient during an external shock of high impact and low probability.

The results of this study provide insights into how LSPs have managed the downsides and found innovative ways to overcome operational and financial challenges during the COVID-19 outbreak. As one of the first studies that specially focuses on the role of LSPs during the COVID-19 pandemic, this study categorizes the LSPs’ reactions and provides a “lessons learned” framework from a managerial perspective. From a theoretical perspective, this paper discusses the strategic role of LSPs in supply chain management and thereby extends current supply chain literature with a focus on LSP resilience.

This study focuses to develop a common humanitarian supply chain process model (HSCPM) that enables effective enterprise resource planning (ERP) systems for NGOs, and the study also investigates the role of modularity as a dynamic capability that supports creating such model.

A multifocus group study was performed as part of a larger project, the Frontline Humanitarian Logistics Initiative, aiming to establish a common data model that would serve as the backbone of humanitarian ERP systems. Fourteen international humanitarian organizations (IHOs) participated in the process, reaching a consensus on the structure of the process model.

An HSCPM was proposed based on the consensus reached across IHOs. Four degrees of customization differentiating between “generic,” “tailored,” “specific,” and “unique” processes are presented and discussed.

The findings show modularity applied to process as a mean to create dynamic efficiencies and position the modular process model within the dynamic capabilities framework, supporting supply chain responsiveness and expanding the literature on supply chain management (SCM), dynamic capabilities, and humanitarian logistics.

This research proposes a consensus-based data model, facilitating the advancement of ERP systems in the humanitarian context and lays a foundation for interoperability among ERP systems across diverse IHOs.

First attempt to elucidate the specific characteristics and unique processes defining an HSCPM, this study reached an unprecedented consensus for the humanitarian sector, setting the base toward an industry standard.

The purpose of this paper is to map and analyse the literature from 1989 to 2016 on humanitarian supply chain management (SCM) responding to refugees. This literature review systematically assesses existing literature, thereby highlighting gaps, challenges and directions for future research.

The authors apply a structured content analysis method which has been recognised as a traceable, systematic and reproducible research tool to analyse qualitative and quantitative aspects of existing literature.

The relative scarcity of literature implies that the interface of the fields of Humanitarian SCM and refugees has been rarely addressed. More specifically, the quantitative content analysis highlights a dearth of research that focusses on both fields in a well-balanced manner. In particular, empirical, practice-led studies, as well as research on development aid operations are under-represented. The qualitative analysis finds that further research on logistics models as well as technological innovations is necessary to increase data availability, forecast accuracy and the efficiency of (local) supply network operations during disasters.

The review suggests a number of areas in need of future research, proposes possibilities of collaborations between different actors and provides a research agenda for Humanitarian SCM in the context of refugees.

This review is the first to analyse the literature on Humanitarian SCM related to refugees.

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

This paper aims to study the religious tourism supply chain and understand and introduce resilience across the same to mitigate post-pandemic disruptions.

In this manuscript, a systematic literature review has been done to identify the gaps in the religious tourism supply chain, which gives adequate revenue to India but not studied yet. The identified gap shaped this study's objectives and research questions and guided the authors to devise a theoretical framework for the religious tourism supply chain.

The key findings of this research paper led to identifying both threats and opportunities for the religious tourism supply chain, which has been into existence and caused many disasters in the past. As pandemic Covid-19 shut the doors of these religious destinations for extended periods, it became necessary for governments, state authorities and private parties to think and devise the post unlock operating processes for this supply chain. This thinking directed the authors to create a framework for the smooth flow of people and other services across this supply chain. The collaborative efforts of all the stakeholders at various levels can realize the actual working of the suggested framework. A stagewise set of processes has been proposed to understand the resilience across the religious tourism supply chain and reduce disruptions.

Covid-19 pandemic has devastated the world economies and disrupted the supply chains of all sectors. The paper elaborates the need for cohesive efforts to introduce resilience across humanitarian supply chains and phase-wise processes to reduce the disruptions caused by various disasters. These systematic efforts will familiarize the readers with the need for resilience across the religious tourism supply chain. Still, it would also assist in generating revenue for the Indian government and reviving the economy soon.

The trade of religious tourism adds a significant contribution to the Indian economy in terms of revenue, employment, visibility of culture and destination, etc. The Covid-19 pandemic has immensely disrupted the tourism sector supply chain, resulting in huge losses (FICCI report 2020). The introduction and implementation of resilience across the religious tourism supply chain can diminish the losses and assist in reviving the economy soon. Construct of resilience across the religious tourism supply chain has not been studied yet. This manuscript contributes to identifying post-pandemic challenges across the religious tourism supply chain and ways to integrate resilience to reduce disruptions caused by disasters.

This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities of accomplishing tasks are highly dependent on the effective information sharing among intelligent subjects within the networks. Hence, proposing an adaptive information-sharing approach can help improve the performance of crowd networks on accomplishing tasks that are assigned to them.

This paper first introduces the factors that affect effectiveness of information-sharing pattern: the network topology, the resources owned by intelligent subjects and the degree of information demand. By analyzing the correlation between these factors and the performance of crowd networks, an Adaptive Information Sharing Approach for Crowd Networks (AISCN approach) is proposed. By referring to information needed for accomplishing the historical tasks that are assigned to a crowd network, the AISCN approach can explore the optimized information-sharing pattern based on the predefined composite objective function. The authors implement their approach on two crowd networks including bee colony and supply chain, to prove the effectiveness of the approach.

The shared information among intelligent subjects affects the efficiency of task completion in the crowd network. The factors that can be used to describe the effectiveness of information-sharing patterns include the network topology, the resources owned by intelligent subjects and the degree of information demand. The AISCN approach used heuristic algorithm to solve a composite objective function which takes all these factors into consideration, so that the optimized information-sharing pattern can be obtained.

This paper introduces a set of factors that can be used to describe the correlation between information-sharing pattern and performance of crowd network. By quantifying such correlation based on these factors, this paper proposes an adaptive information-sharing approach which can explore the optimized information-sharing pattern for a variety of crowd networks. As the approach is a data-driven approach that explores the information-sharing pattern based on the network’s performance on historical tasks and network’s characteristics, it is adaptive to the dynamic change (change of incoming tasks, change of network characteristics) of the target crowd network. To ensure the commonality of the information-sharing approach, the proposed approach is not designed for a specific optimization algorithm. In this way, during the implementation of the proposed approach, heuristic algorithms can be chosen according to the complexity of the target crowd network.

The COVID-19 pandemic and recent disruptive events are affecting firms’ operations and supply chain networks on a large scale, causing disturbances in supply, demand, production and logistics activities. Although supply chain resilience (SCR) research has received large attention in recent years, the purpose of this paper is to offer an original contribution by exploring how complex configurations and interactions between SCR strategies and capacities can lead to resilience.

This study investigates the configurations of SCR strategies and capacities using a fuzzy-set qualitative comparative analysis.

First, the findings reveal different SCR strategy configurations through the lens of absorptive, reactive and restorative capacities to achieve resilience. Second, this study applies the contingent resource-based view (CRBV) perspective to interpret how organizations can achieve resilience before, during and after a disruptive event. Third, it offers an analysis of different groups of organizations, based on the adoption of different SCR strategies and capacities.

This study identifies a set of equifinal SCR strategies and capacity configurations that can be implemented to cope with a disruptive event and lead to resilience. It also enriches the research addressing the consecutive phases of SCR investments, developing the CRBV perspective. In our results, five solutions describe organizations that invest in absorptive capacities, representing an ex ante readiness.