Improving Supply Chain Resilience Research Articles

A two-stage capacity reservation contract model with backup sourcing considering supply side disruptions

ABSTRACT To deal with disruption at the supply side, the use of backup suppliers is among the commonly employed strategies. In this research, we derived a dual sourcing model using capacity reservation contracts for a supply chain consisting of a retailer, a primary supplier who may experience disruption, and a reliable backup supplier. This dual sourcing model is a reactive strategy that balances flexibility and redundancy to improve supply chain resilience. The aim of the proposed model is to help find optimal solutions for the reserved capacities of the retailer to the suppliers and the constructed capacities of the suppliers. It has been derived in this research that the above-mentioned reserved/constructed capacities exist uniquely. Sensitivity analyses were also conducted to examine the impact of contract parameters on decision variables. This research contributes to existing knowledge by providing deeper insights into the application of the capacity reservation contract to handle supply disruption.

The metaverse in supply chain knowledge sharing and resilience contexts: An empirical investigation of factors affecting adoption and acceptance

This study develops a conceptual framework based on the unified theory of acceptance and use of technology, the network theory perspective, and metaverse characteristics. Data were gathered through questionnaires from 209 Chinese manufacturers, and covariance-based structural equation modelling was the main approach used. The results indicate that performance expectancy, facilitating conditions, and establishing initial trust amongst supply chain partners can drive behavioural intention with respect to metaverse adoption for knowledge sharing to improve supply chain resilience. In addition, sensory feedback is an important characteristic of the metaverse and has a critical influence on adoption behaviour. Moreover, it has a complementary partial mediation effect on the relationship between establishing initial trust amongst supply chain partners and behavioural intention as well as a full mediating effect on the relationship between the initial trust of supply chain partners and behavioural expectations. Finally, sensory feedback moderates the relationship between behavioural intention and expectancy. Our findings contribute to the literature on metaverse adoption in the context of supply chain resilience.

Robust actions for improving supply chain resilience and viability

It is vital for supply chains (SCs) to survive the dramatic and long-term impacts from severe disruptive events, such as COVID-19 pandemic. SC viability, an extension of SC resilience, is increasingly attracting attention from both academics and practitioners. To improve SC viability, the government can perform a series of costly interventions on SCs. Due to data scarcity on unpredictable disruptive events, especially under the pandemic, the information related to SC partners may not be accurately obtained. In this paper, we investigate a novel SC resilience and viability improving problem under severe disruptive events, in which only the probability intervals of SC partners’ states are known. The problem consists of the selection of appropriate intervention actions, respecting a limited capital budget. The objective is to minimize the worst-case disruption risk of the manufacturer. Specifically, Causal Bayesian Network (CBN) is applied to quantify the SC ripple effects; Do-calculus technique is used to measure the benefits of government intervention actions; and robust optimization is employed to minimize the disruption risk under the worst-case condition. For the problem, a new robust optimization model that combines the CBN and the Do-calculus is constructed. Based on analyses of problem features, an efficient problem-specific branch-and-bound (PS-BAB) algorithm is proposed to solve the problem exactly. Experimental results show the efficiency of our methodology and managerial insights are drawn.

Will the blockchain solve the supply chain resilience challenges? Insights from a systematic literature review

Frequency and severity of supply chain disruptions are increasing, and new solutions for improving supply chain resilience (SCRES) are demanded. Operations managers and scholars place great hopes on recent technological innovations, particularly blockchain technology. However, the current literature lacks a comprehensive review at the intersection of SCRES and blockchain, making it difficult to understand the relations between both fields holistically. This research gap was addressed by systematically analyzing 72 peer-reviewed papers. More specifically, the link between specific blockchain characteristics, SCRES antecedents, and supply chain risk types was explored. The results reveal that visibility and validation are the most relevant blockchain characteristics for improving SCRES. The SCRES antecedents agility, collaboration, and supply chain (re-)engineering can all benefit from blockchain implementation, whereas the effect on risk management culture is widely unexplored. While there is consensus on blockchain’s usability for mitigating security, operational, and supply risks, the effect on demand risks requires further attention. To facilitate the practical implementation of this paper’s results, the findings served as a foundation for discussing SCRES opportunities from well-known blockchain applications such as smart contracts and tracking solutions. Moreover, seven future research avenues and managerial implications are presented.

Robotics in Food Manufacturing Industry in the Industry 4.0 Era

Robotics is used in food manufacturing in multiple processes. Prominent existing applications are: preparation of soil, seeding, water sprinklers, harvest controlling, cutting the harvests, food extractions, processing, packaging, loading/unloading, food warehouse operations, and food retail operations. Robots enhancements in Industry 4.0 framework have enabled cognitive and collaboration capabilities related to dynamics, kinematics, self-diagnostics, and self-control. Robots can identify and change their robotic hands as per process requirement. Robotics in food manufacturing is used to improve food quality and hygiene, increasing quality and its consistency, improving process performance, improving production rate and productivity, production reconfigurability, improving supply chain resilience and responsiveness, improving food traceability, reducing food loss and wastage, and improving workplace safety. Industry 4.0 allows robotic cyber physical systems (RCPS), HMI interfacing with robots through augmented reality thus ensuring remote real time precision monitoring and control of field robots. Robots with attached cameras with machine learning for image visualization analytics can ensure quality assurance and control of food products during all the stages of the food manufacturing logistics. The key drivers for adopting robotics in food manufacturing are cloud manufacturing, Internet of Things (attached with robotic controller cards), virtual reality simulations, augmented reality for HMI controls, additive manufacturing in food processing, integration of Industry 4.0 systems (IoT with blockchains, edge computing, big data analytics, and machine learning), and autonomous automation software. Robotics in food manufacturing using Industry 4.0 capabilities is a positive change. However, there are ethical and financial challenges. Increased usage of robotics can affect employment of food harvesting and manufacturing workers in developed as well as developing economies. Further, economics of using robotics in food manufacturing is not yet justified in developing nations given the high initial costs and prolonged time to break even. Overall, robotics in food manufacturing using Industry 4.0 has many technical and production advantages but ethical and financial viability is an ongoing research domain.

Uncertainties affecting the offsite construction supply chain resilience: a systematic literature review

Purpose This paper aims to synthesise the latest literature on supply chain operations of offsite manufacturing in the construction industry to identify and evaluate the uncertainties at each stage of the offsite construction supply chain (OSC-SC) to compile contributions to knowledge and thereby determine the future research directions to improve supply chain resilience (SCR). Design/methodology/approach The study was conducted as a systematic literature review. In total, 99 peer-reviewed journal papers published between 2015 and mid-2022 were shortlisted and analysed through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Findings The bibliometric analysis revealed that the research focusing on supply chain issues and developing best practices in offsite construction adopt case study approaches to investigate the research problems comprehensively. The content analysis revealed the lack of up-to-date knowledge in the construction workforce regarding OSC; low preparedness for the changes brought by the SC uncertainties; the lack of a proper procurement model for OSC; lack of end-to-end visibility of the supply chain to identify uncertainties and lack of national or government standards on OSC-SC, as some of the key problems instigating the identified the uncertainties. Originality/value This study clarifies the current knowledge by systematically presenting uncertainties at each stage of the OSC-SC. Moreover, it provides a framework and proposes that future research should focus specifically on individual/team, organisational, supply chain/network and sector/national/supranational levels to improve SCR.

The Resilience of the Renewable Energy Electromobility Supply Chain: Review and Trends

Electromobility has been crucial in mitigating transport emissions and meeting reduction targets. From this context, this literature review’s main objective is to analyze the resilience of the electromobility supply chain that integrates renewable energy sources. This literature review focuses on the resilience of the electromobility supply chain and how it can incorporate renewable energy sources. The central argument is that the success of the supply chain depends on its ability to resist, adapt, and recover from disruptions that affect operations. We comprehensively review current knowledge in three stages: identifying critical components of resilience, highlighting challenges and opportunities for risk mitigation, establishing strategic alliances, and synthesizing vital issues, trends, and emerging areas that require further research. The findings emphasize the importance of improving supply chain resilience for sustainable transportation and environmental preservation under five guidelines: emergency preparedness, monitoring and evaluation, sustainable practices, maintenance of essential services, and prevention of operational disruptions.

Collaborative emergency adaptation for ripple effect mitigation in intertwined supply networks

AbstractFor the first time, the ripple effect is examined in the setting of an intertwined supply network. Through simulations, we model the disruption propagation in supply chains having common suppliers. We explore conditions under which a collaborative coordination of re-purposed capacities and shared stocks can help mitigate the ripple effect and improve recovery performance. As a result, we conceptualize the notion of collaborative emergency adaptation contributing to development of “network-of networks” and viability perspective in supply chain resilience management. We illustrate our approach with anyLogistix simulations and deduce some generalized theoretical and managerial insights on how and when a collaborative emergency adaptation can be implemented and help improve supply chain resilience and viability.

Improving supply chain resilience through investment in flexibility and innovation

This study examines how a firm can improve its resilience to respond effectively to supply chain disruptions through investment in flexibility and innovation. There are several approaches and conceptualizations of flexibility and innovation in the operations and supply chain management literature. Nevertheless, how flexibility and innovation can enhance an organisational response to disruptions has not received much attention. We extend the research in supply chain resilience by investigating the relationships between flexibility, innovation, and resilience under disruption risk. The findings show that innovation and flexibility have a positive impact on resilience. A numerical example based on these relationships shows significant differences between optimum values of objective functions when we have high disruption risk versus low disruption risk imposed on the system. By developing a novel multi-objective mixed-integer linear programming, the findings reveal that disruption risks affect resilience and firms’ ROI, so investing in improvements in flexibility and innovation decreases the impact of disruptions.

The future of industry 4.0 and supply chain resilience after the COVID-19 pandemic: Empirical evidence from a Delphi study

The COVID-19 pandemic has caused major supply chain disruptions and unveiled the pressing need to improve supply chain resilience (SCRES). Industry 4.0 (I4.0) is a promising lever; however, its future in supply chain risk management (SCRM) is highly uncertain and largely unexplored. This paper aims to evaluate I4.0′s potential to improve SCRES in a post-COVID-19 world. Based on current literature and multiple workshops, 13 future projections on potential I4.0 application areas in SCRM were developed. A two-round Delphi study among 64 SCRM experts with digital expertise was conducted to evaluate and discuss the projections regarding their probability of occurrence until 2030, their impact on SCRES, and their desirability. A fuzzy c-means algorithm was applied to cluster the projections based on the expert assessments. The expert evaluations led to three clusters on I4.0 application in SCRM: Four projections on generating data, increasing visibility, and building digital capabilities received considerable approval and are reliable to improve SCRES in 2030. Four projections enabling data sharing and processing were predominantly supported and demonstrated realization potential for 2030. Finally, five projections that require major supply network adaptations were deemed unlikely to improve SCRES in 2030. This paper answers several research calls by presenting empirical evidence on the pathway of I4.0 implementation in SCRM following the COVID-19 pandemic. Moreover, it evaluates a holistic set of technologies and indicates prioritization potentials to achieve SCRES improvements.

The impact of procurement digitalization on supply chain resilience: empirical evidence from Finland

PurposeThe purpose of this study is to investigate the role of procurement digitalization in reducing uncertainty in the supply chain (SC) and how it relates to mitigating SC risks and improving SC resilience (SCRES).Design/methodology/approachBased on survey data collected from the procurement functions of 147 Finnish firms, this study conceptualizes data analytics, information sharing and procurement process digitalization as drivers of procurement digitalization and investigates their impact on SC risk management and SCRES by using partial least squares path modeling.FindingsProcurement digitalization through data analytics and digital process maturity requires effective information sharing among SC partners and SC risk management to be able to improve SCRES. Procurement digitalization increases information-processing capacities and reduces uncertainty in the SC.Originality/valueThis study contributes to the understanding on the relationships between procurement digitalization and SCRES.

Considering region risks and mitigation strategies in the supplier selection process for improving supply chain resilience

This study applies combinations of mitigation strategies (including multi-region supplier, multi-sourcing, reserved inventory, and alternative shipment) in supplier selection, taking into account two types of disruptions: a decline in supplier capacity and transportation failure. This study adopts a two-phase decision-making model to formulate a resilient supplier selection process, supported by suitable mitigation strategies. The first phase selects the main supplier process using the augmented ε-constrained and analytic hierarchy process method to find the maximum supplier performance on resilient-sustainable criteria and minimum supplier location risk. The second phase implements mitigation strategies when allocating orders to the main suppliers using linear programming to find how many units to order at the lowest procurement costs. Eight strategy combinations are utilized in the numerical study with several regional disruption scenarios. This study shows that by combining strategies, the company may minimize its reliance on backup suppliers while improving the supply chain resilience, collaboration with main suppliers, and service level. The findings demonstrate the strategy combination's effectiveness in terms of economic benefits, reduced lost sales, and decreased variability of orders to main suppliers.

Improving supply chain resilience from the perspective of information processing theory

PurposeSupply chain resilience (SCR) has attracted much attention in the context of the high uncertainty caused by the coronavirus disease 2019 (COVID-19), local regional conflicts and natural disasters. Based on information processing theory (IPT), this study investigates the role of supply chain information processing capability in enhancing SCR through supply chain governance (SCG), under different conditions of environmental uncertainty.Design/methodology/approachThe hypothetical model is tested by using hierarchical regression on the primary samples collected from the Chinese manufacturing industry.FindingsThe results indicate that supply chain information processing capability has a significant positive effect on SCR. Also, SCG plays a mediating role between supply chain information processing capability and SCR. Furthermore, environmental uncertainty positively moderates the effect of supply chain information acquisition and supply chain information analysis on relational governance. However, environmental uncertainty only positively moderates the effect of supply chain information analysis on contractual governance.Originality/valueThis is the first study to explain the effect of information processing capability on SCR from the supply chain perspective, while also exploring the mediating role of SCG between SCR and supply chain information processing capacity, based on IPT.

Resilient Supply Chain Framework for Semiconductor Distribution and an Empirical Study of Demand Risk Inference

Supply chain uncertainty is high due to low information transparency in the upstream and downstream, long lead time for supply chain planning, short product life cycles, lengthy production cycle time, and continuous technology migration. The construction and innovation of the new program of supply the chain faces huge challenges. This study aims to propose a smart resilient supply chain framework with a decision-making schema through the plan-do-check-act management cycle. It can enhance supply chain resilience and strengthen industrial competitiveness. Moreover, an empirical study of demand forecast and risk inference for semiconductor distribution is conducted as a validation. Through demand pattern clustering and forecasting for historic customer order behaviors, the demand status of each customer is classified, and an optimal planning solution is released to support decision-making. The result has shown the practical viability of the proposed approach to drive collaborative efforts in enhancing demand risk management to improve supply chain resilience. The proposed forecast model performs better than all four benchmark models, and the revised recall of the proposed risk reference model shows high accuracy in all demand risk levels. As supply chain resilience is about to be reconstructed due to the industrial revolution, a government and industry alliance should follow the resilient supply chain blueprint to gradually make the manufacturing strategy a technology platform in the Industry 4.0 era.

Big data and supply chain resilience: role of decision-making technology

PurposeAs global supply chains continue to develop, uncertainty grows and supply chains are frequently threatened with disruption. Although big data technology is being used to improve supply chain resilience, big data technology's role in human–machine collaboration is shifting between “supporters” and “substitutes.” However, big data technology's applicability in supply chain management is unclear. Choosing appropriate big data technology based on the enterprise's internal and external environments is important.Design/methodology/approachThis study built a three-factor structural model of the factors “management support,” “big data technology adoption” and “supply chain resilience”. Big data technology adoption was divided into big data-assisted decision-making technology (ADT) and big data intelligent decision-making technology (IDT). A survey was conducted on more than 260 employees from supply chain departments in Chinese companies. The data were analyzed through structural equation modeling using Analyze of Moment Structures (AMOS) software.FindingsThe study's empirical results revealed that adopting both ADT and IDT improved supply chain resilience. The effects of both types of big data were significant in low-dynamic environments, but the effect of IDT on supply chain resilience was insignificant under high-dynamic environments. The authors also found that government support had an insignificantly effect on IDT adoption but significantly boosted ADT adoption, whereas management support factors promoted both ADT and IDT adoption.Originality/valueBy introducing two types of big data technology from the perspectives of the roles in human–machine collaborative decision-making, the research results provide a theoretical basis and management implications for enterprises to reduce the supply chain risk of enterprises.

Let’s talk about bad experiences instead of forgetting them: An empirical study on the importance of memory for supply chain disruption management

Few studies have been concerned about the role of previous knowledge in supply chain disruption management. Based on the premise that supply chain resilience and robustness impact supply chain performance, this paper aims to expand this knowledge by conceptually and empirically establishing the role of supply chain memory for supply chain disruption management performance. A survey receiving 290 valid responses was conducted with supply chain managers. Quantitative data were analyzed with structural equation modeling. In addition, a mixed-methods approach was conducted to validate and explore the quantitative results. This paper contributes to theory and practice showing that experience, familiarity, and knowledge about dealing with disruptions improve supply chain resilience and robustness efficiency. The moderation effect of memory reveals that high memory leverages the impact of supply chain resilience on supply chain performance. Moreover, it brings important insights into the impact of robustness on supply chain performance since it is conditional to memory levels. The full model was able to explain 37.19% of supply chain performance.

Building responsive and resilient supply chains: Lessons from the COVID‐19 disruption

Building responsive and resilient supply chains: Lessons from the <scp>COVID</scp>‐19 disruption

COLLABORATIVE APPROACH TO FLEXIBILITY, VISIBILITY AND VELOCITY IN SUPPLY CHAINS: A MULTI-GROUP ANALYSIS

Most studies focus on developed economies when investigating resilience, creating a gap in research in developing countries. This study addresses two literature gaps by examining supplier collaboration's effect on supply chain flexibility, visibility, and velocity in an African business environment and assessing the relevance of company size to this relationship. This study used a descriptive design. The population and sample were 1332 and 264 respectively. 219 questionnaire copies informed the analysis and it was performed using percentages and a structural equation model. The study reveals that resource sharing is the most effective strategy for improving supply chain resilience and collaboration practices are most effective for supply chain flexibility. Organisations pursuing supply chain resilience can implement resource-sharing and information-sharing strategies to yield resilience. Additionally, managers must note that supplier collaboration may not yield similar results across all resilience performance measurements. Medium-scale firms must focus on information sharing to improve supply chain flexibility.

Viable Supply Chain Management toward Company Sustainability during COVID-19 Pandemic in Malaysia

Since the pandemic first appeared in early 2020, the manufacturing industry across the globe has experienced a decline. Concerns regarding public health were present at the start of the new decade, and as the pandemic reached its peak in March 2020, manufacturers all over the world were forced to contend with high demand, reduced workforce requirements, subsequent lockdowns, and major disruptions to their supply chains to prevent the global spread of the pandemic. No research has been done on the interaction of these variables because the idea of VSCM is still relatively new, particularly in Malaysia’s manufacturing industry. The purpose of this study is to present management researchers with a novel idea for coping with a pandemic situation in today’s business environment. Furthermore, the purpose of this research is to determine VSCM practices that contribute to company sustainability so that such future incidents can be controlled and revamped. The report also advocated a VSCM framework to improve supply chain resilience and sustainability. This study’s objective is to analyze the relationship between viable supply chain management (VSCM) practices and company sustainability for manufacturing companies in Malaysia during the COVID-19 pandemic. 197 respondents from Malaysian manufacturing companies were surveyed using a quantitative approach. Using PLS-SEM analysis, all surveys are examined. As a result, the direct relationship between VSCM and company sustainability has demonstrated a significant positive effect. The implication of this study is to strengthen the viability and reliability of viable supply chain management and contribute further to the COVID-19 outbreak’s impact on company sustainability. Moreover, a successful supply chain model would guarantee that manufacturers are compelled to respond swiftly to safeguard and support their employees and maintain operations that are critical lifelines for consumers and communities.

Dynamic digital capabilities and supply chain resilience: The role of government effectiveness

Organizations in recent times are increasingly investing in building supply chain resilience following disruptions due to natural disasters, geo-political crises, and pandemics. A lack of government support has exacerbated the disruption to supply chains in some regions of the world. The positive influence of digitalization on social inclusion, government accountability, and creating a more open environment is well understood. Despite this, different countries have shown varying degrees of digital responsiveness during the pandemic as they attempted to deal with the effects of various COVID strains. The influence of government policies on the supply chain has not been examined in the literature so far and, hence, to address this research gap, we examine the interaction effect of government support effectiveness i.e., tax credits, interest deferral, digital investment, soft loans on dynamic capabilities i.e., digital adaptabilities and digital agilities and on supply chain resilience, using a multi-method approach. To understand how digital adaptability and agility improve supply chain resilience, we conducted 13 semi-structured interviews. Additionally, we pretested our measurement instrument using qualitative semi-structured interviews to validate our hypothesized relationships. We collected data at a specific point of time using a survey-based instrument (N = 203) to address our research questions. Based on data analyses of both the qualitative and survey-based data, our findings indicate that digital adaptability is an important driver of digital agility. Furthermore, the results indicate that government effectiveness is crucial to enhancing supply chain resilience by enhancing digital adaptability and agility. Our research makes some useful contributions to the dynamic capability view by enhancing theoretical understanding, of the role of government in building digital capabilities in uncertain times, to improve supply chain resilience. It also bridges the research gaps between macro and micro perspectives, as identified by management scholars. Lastly, we noted the weaknesses and limitations in the study and therefore we have offered multiple research directions forward, that could help researchers to further develop our current work.