Assessing the economic ripple effect of flood disasters in light of the recovery process: Insights from an agent-based model.

To assess the economic ripple effect, this study integrates agent-based modeling (ABM) with a multiregional input-output (MRIO) table to develop an assessment model that considers capacity recovery process. The intermediate and final demands in the MRIO table are used to describe the agents' interdependence. Survival analysis is used to construct capacity rate curves. By defining the first- and second-order ripple effects, ABM is used to capture the ripple process in days. To conduct a case study, the service and retail sectors in Enshi in Hubei, China, are selected as disaster-affected sectors (they were severely affected by the July 17, 2020 flood disaster). The main findings are as follows: (1) With the first-order ripple effect, the losses caused by service and retail are concentrated within Enshi. Enshi's final demand, construction, and raw materials manufacturing sectors as well as Wuhan's construction sector are seriously affected. (2) With the second-order ripple effect, the losses caused by the service and retail sectors expand, forming a prominent industrial ripple chain: "service (retail)-raw materials manufacturing-construction." (3) The direct and indirect losses caused by the service sector are more significant than those caused by the retail sector. However, the loss ratio of the service sector is smaller than that of the retail sector because of its sound industrial structure and strong resilience. Hence, the indirect losses caused by different sectors are not entirely determined by their direct losses; instead, they are also related to the degree of perfection of the structures of different sectors.

Diffusion of White-Hat Botnet Using Lifespan with Controllable Ripple Effect for Malware Removal in IoT Networks.

Self-propagating malware has been infecting thousands of IoT devices and causing security breaches worldwide. Mitigating and cleaning self-propagating malware is important but challenging because they propagate unpredictably. White-hat botnets have been used to combat self-propagating malware with the concept of fight fire-with-fire. However, white-hat botnets can also overpopulate and consume the resource of IoT devices. Later, lifespan was introduced as a self-destruct measure to restrain white-hat botnets' overpopulation, but unable to change based on real-time situations. This paper proposes a method for diffusing white-hat botnets by controlling lifespan. The main contribution of this paper is that the method uses a dynamic lifespan that increases and decreases based on the congregation's situation of the self-propagating malware and white-hat botnets. The method tackles the problem of overpopulation of white-hat botnets since they can self-propagate by controlling the ripple effect that widens the white-hat botnet's diffusion area but suppresses the number of white-hat botnets to achieve a 'zero-botnet' situation. The effectiveness in reducing the overpopulation rate was confirmed. The experiment result showed that the ripple effect could reduce the number of white-hat botnets in the network by around 80%, depending on different control parameters.

A simulation-based approach for assessing regional and industrial flood vulnerability using mixed-MRIO model: A case study of Hubei Province, China.

Given the unstoppable forces behind regional economic integration trends, damages from a flood disaster in a specific area will influence correlative cities through industrial linkages and make economic systems more vulnerable. Assessing urban vulnerability is an essential part of flood prevention and mitigation, and also a hot topic of recent research. Therefore, this study (1) constructed a mixed multiregional input-output (mixed-MRIO) model to explore ripple effects on other regions and sectors when production in a flooded area is constrained, and (2) applied this model to characterize the economic vulnerability of cities and sectors in Hubei Province, China by simulation. First, various hypothetical flood disaster scenarios are simulated to reveal the ripple effects of different events. The composite vulnerability is assessed by analyzing economic-loss sensitivity rankings across scenarios. Then, the model is applied to the case of a 50-year return period flood that occurred in Enshi City, Hubei Province, on July 17, 2020 to empirically verify the usefulness of such a simulation-based approach in evaluating vulnerability. The results indicate vulnerability is higher in Wuhan City, Yichang City, and Xiangyang City and for three manufacturing sector types: livelihood-related manufacturing, raw materials manufacturing, and processing and assembly manufacturing. Such cities and industrial sectors with high vulnerability will significantly benefit from prioritization in flood management.

A dynamic approach to supply chain reconfiguration and ripple effect analysis in an epidemic.

The COVID-19 pandemic has illustrated the unprecedented challenges of ensuring the continuity of operations in a supply chain as suppliers' and their suppliers stop producing due the spread of infection, leading to a degradation of downstream customer service levels in a ripple effect. In this paper, we contextualize a dynamic approach and propose an optimal control model for supply chain reconfiguration and ripple effect analysis integrated with an epidemic dynamics model. We provide supply chain managers with the optimal choice over a planning horizon among subsets of interchangeable suppliers and corresponding orders; this will maximize demand satisfaction given their prices, lead times, exposure to infection, and upstream suppliers' risk exposure. Numerical illustrations show that our prescriptive forward-looking model can help reconfigure a supply chain and mitigate the ripple effect due to reduced production because of suppliers' infected workers. A risk aversion factor incorporates a measure of supplier risk exposure at the upstream echelons. We examine three scenarios: (a) infection limits the capacity of suppliers, (b) the pandemic recedes but not at the same pace for all suppliers, and (c) infection waves affect the capacity of some suppliers, while others are in a recovery phase. We illustrate through a case study how our model can be immediately deployed in manufacturing or retail supply chains since the data are readily accessible from suppliers and health authorities. This work opens new avenues for prescriptive models in operations management and the study of viable supply chains by combining optimal control and epidemiological models.

Typhoon eye effect versus ripple effect: the role of family size on mental health during the COVID-19 pandemic in Pakistan.

BACKGROUND: The recent outbreak of COVID-19 has impacted adversely upon the mental health of millions of people worldwide. Impacts on the mental health conditions and the associated predictors relating to adults in Pakistan, the fifth most populous country in the world, during the COVID-19 remain understudied. Our aim was to investigate distress, anxiety, and overall mental health and their associated predictors among Pakistani adults in this pandemic. We specifically examine mental health issues based on the distance from the epicenter, (a predictor that has revealed opposing evidence in other countries) based on the theories of typhoon eye effect and ripple effect. The sample consisted of 601 adults who were surveyed online about 2.5 months into the outbreak across Pakistan with varying distances from the epicenter of COVID-19 of Karachi. RESULTS: The results showed that 9.2 and 19.0% of the participants surpassed the cut-off criteria for distress and anxiety disorders, respectively. Overall, the distance from the epicenter positively predicted the mental health of adults in Pakistan, and family size negatively moderated this effect. The distance from the epicenter negatively predicted distress and anxiety disorders for adults in large families, which are quite common in Pakistan. CONCLUSION: The evidence of the study interestingly finds that the prediction of the mental health of people by their distance from the epicenter depends on family size. The evidence of this study can help to provide initial indicators for mental health care providers to screen vulnerable groups in Pakistan, a populous country that continues struggling to cope with the COVID-19 pandemic.

A whole system approach to increasing children's physical activity in a multi-ethnic UK city: a process evaluation protocol.

BACKGROUND: Engaging in regular physical activity requires continued complex decision-making in varied and dynamic individual, social and structural contexts. Widespread shortfalls of physical activity interventions suggests the complex underlying mechanisms of change are not yet fully understood. More insightful process evaluations are needed to design and implement more effective approaches. This paper describes the protocol for a process evaluation of the JU:MP programme, a whole systems approach to increasing physical activity in children and young people aged 5-14 years in North Bradford, UK. METHODS: This process evaluation, underpinned by realist philosophy, aims to understand the development and implementation of the JU:MP programme and the mechanisms by which JU:MP influences physical activity in children and young people. It also aims to explore behaviour change across wider policy, strategy and neighbourhood systems. A mixed method data collection approach will include semi-structured interview, observation, documentary analysis, surveys, and participatory evaluation methods including reflections and ripple effect mapping. DISCUSSION: This protocol offers an innovative approach on the use of process evaluation feeding into an iterative programme intended to generate evidence-based practice and deliver practice-based evidence. This paper advances knowledge regarding the development of process evaluations for evaluating systems interventions, and emphasises the importance of process evaluation.

OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications.

The COVID-19 pandemic unveils unforeseen and unprecedented fragilities in supply chains (SC). A primary stressor of SCs and their subsequent shocks derives from disruption propagation (i.e., the ripple effect) through related networks. In this paper, we conceptualize current state and future research directions on the ripple effect for pandemic context. We scrutinize the existing OR (Operational Research) studies published in international journals dealing with disruption propagation and structural dynamics in SCs. Our study pursues two major contributions in relation to two research questions. First, we collate state-of-the-art research on disruption propagation in SCs and identify a methodical taxonomy along with theories displaying their value and applications for coping with the impacts of pandemics on SCs. Second, we reveal and systemize managerial insights from theory used for operating (adapting) amid a pandemic and during times of recovery, along with becoming more resistant to future pandemics. Streamlining the literature allowed us to reveal several new research tensions and novel categorizations and classifications. The outcomes of our study show that methodical contributions and the resulting managerial insights can be categorized into three levels, i.e., network, process, and control. Our analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions. Our findings depict how the existing OR methods can help coping with the ripple effect at five pandemic stages (i.e., Anticipation; Early Detection; Containment; Control and Mitigation; and Elimination) following the WHO classification. The outcomes and findings of our study can be used by industry and researchers alike to progress the decision-support systems guiding SCs amid the COVID-19 pandemic and toward recovery. Suggestions for future research directions are offered and discussed.

Ripple effect in the supply chain network: Forward and backward disruption propagation, network health and firm vulnerability.

A local disruption can propagate to forward and downward through the material flow and eventually influence the entire supply chain network (SCN). This phenomenon of ripple effect, immensely existing in practice, has received great interest in recent years. Moreover, forward and backward disruption propagations became major stressors for SCNs during the COVID-19 pandemic triggered by simultaneous and sequential supply and demand disruptions. However, current literature has paid less attention to the different impacts of the directions of disruption propagation. This study examines the disruption propagation through simulating simple interaction rules of firms inside the SCN. Specifically, an agent-based computational model is developed to delineate the supply chain disruption propagation behavior. Then, we conduct multi-level quantitative analysis to explore the effects of forward and backward disruption propagation, moderated by network structure, network-level health and node-level vulnerability. Our results demonstrate that it is practically important to differentiate between forward and backward disruption propagation, as they are distinctive in the associated mitigation strategies and in the effects on network and individual firm performance. Forward disruption propagation generally can be mitigated by substitute and backup supply and has greater impact on firms serving the assembly role and on the supply/assembly networks, whereas backward disruption propagation is normally mitigated by flexible operation and distribution and has bigger impact on firms serving the distribution role and on distribution networks. We further analyze the investment strategies in a dual-focal supply network under disruption propagation. We provide propositions to facilitate decision-making and summarize important managerial implications.

Ensuring sustainability in the reverse supply chain in case of the ripple effect: A two-stage stochastic optimization model.

The devastating impact of the ripple effect increases the importance of the reverse supply chain (RSC) design to ensure sustainability in the long-term. That being the case, in this study, a two-stage stochastic mixed-integer optimization model is proposed to design an RSC network under uncertainty sourcing from the ripple effect (i.e. external side of RSC) by considering the environmental and economic dimensions of sustainability. The environmental and economic disruptions of the ripple effect are represented by the increase in the carbon emission levels and the distance of roads, and the decrease in the capacity of facilities, respectively. Accordingly, a set of scenarios is considered based on the disruption levels (low- and high-impact) in case of the ripple effect. Furthermore, an α -reliability constraint is integrated into the model to further analyze the occurrence of scenarios. The model allows us to make integrated operational and strategic decisions by placing an emphasis on the carbon emission levels (i.e. environmental dimension) and the total cost (i.e. economic dimension). To obtain some remarkable insights, the proposed model is validated through computational experiments based on data extracted from a real case. The computational results show that the ripple effect increases the emission level and total cost up to 40%. For this reason, it suggested that the regulations regarding WEEE (Waste Electrical and Electronic Equipment) should be prepared by considering sustainability in the entire RSC network. Besides, it is realized that the centralized distribution strategy leads to a more resilient RSC network design.

The Use of Ripple Effect Mapping to Understand Successes of the SC Pregnancy Assistance Fund: A Participatory Evaluation Approach.

OBJECTIVES: The South Carolina Pregnancy Assistance Fund (SCPAF) funded four counties to increase the amount, quality, and awareness of services for young parents; increase educational attainment among expectant and parenting youth; reduce the number of repeat teen pregnancies among youth; and improve parenting skills. The purpose of this paper is twofold: (1) to describe our application of the Ripple Effect Mapping (REM) technique as an innovative evaluation strategy to gather perspectives from SCPAF stakeholders and (2) to share key findings generated by participants in REM sessions on the perceived success of local SCPAF community collaboratives. METHODS: REM, an innovative evaluation strategy, was used to gather perspectives from SCPAF stakeholders. Five REM sessions were conducted with 52 participants. REM sessions included partner interviews and collective development of visual maps to illustrate stakeholder perspectives of program successes. Visual maps, as well as transcripts of discussions, were analyzed using an inductive approach. RESULTS: Stakeholders reported that the connections to resources, supports, and services provided through SCPAF had the potential to alter the life trajectories of expectant and parenting teens (EPT). Stakeholders also described that SCPAF fostered growth in collaboration among partners and reduced duplication of services in funded communities CONCLUSIONS FOR PRACTICE: This paper describes how an innovative evaluation strategy was used to provide a space for stakeholders to dialogue, synthesize their experiences, and construct a collective narrative of key program successes. This paper also illustrates how such approaches can be applied to complex community initiatives.

Ripple Effects of the Communities Preventing Childhood Obesity Project.

This research examines the practice of community coaching within coalitions in the Communities Preventing Childhood Obesity project. A quasi-experimental design was used in seven Midwestern states. Each state selected two rural, low-income communities with functioning health coalitions. Coalitions were randomly assigned to be intervention or comparison communities. After 4 years of the coaching intervention, ripple effect mapping served as one method for examining the coalitions' work that may affect children's weight status. A research team from each state conducted ripple effect mapping with their two coalitions, resulting in 14 ripple maps. Community capitals framework and the social-ecological model were used for coding the items identified within the ripple maps. A quantitative scoring analysis determined if differences existed between the intervention and comparison coalitions in terms of the activities, programs, funding, and partnerships for social-ecological model score (e.g., individual, community, policy levels), community capitals score, and ripples score (e.g., number of branches formed within the maps). All scores were higher in intervention communities; however, the differences were not statistically significant (p > .05). Assessing community assets, such as availability of a community coach, is necessary in order to decide whether to deploy certain resources when designing health promotion strategies.

The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation.

How should managers take into account the propagation of supply chain disruptions and risks (i.e. the ripple effect) when they design their inventory policies? For over 60 years, various extensions and applications to the popular newsvendor model have been suggested, where cost/profit are often the focal objective. We propose a new version of the traditional single-period newsvendor model - the "Rippled Newsvendor" - with supply chain severity (i.e. risk propagation) as the primary objective while taking into account network structure. Our model considers exogenous and endogenous risk(s) of disruption while exploring the tension between under-supply and "wear-and-tear" (i.e system breakdown). To model the intricacies of this trade-off whilst minimizing the potential spread of risk, we leverage a Bayesian Network whereby the conditional probability distributions are functions of the inventory ordering decisions. We use a simulation study to understand the nature of our objective function as well as to gain insight into the potential optimal ordering policies of this new model. Furthermore, the simulation seeks to understand how the various factors in our system impact total risk severity, and if they do so in different ways. Our simulations indicate that local exogenous risk is of greater importance than non-local exogenous risk. Furthermore, we show that the type of risk, as well as the structural characteristics of the supply chain and inventory system, impact risk severity differently.

Bayesian networks for supply chain risk, resilience and ripple effect analysis: A literature review.

In the broad sense, the Bayesian networks (BN) are probabilistic graphical models that possess unique methodical features to model dependencies in complex networks, such as forward and backward propagation (inference) of disruptions. BNs have transitioned from an emerging topic to a growing research area in supply chain (SC) resilience and risk analysis. As a result, there is an acute need to review existing literature to ascertain recent developments and uncover future areas of research. Despite the increasing number of publications on BNs in the domain of SC uncertainty, an extensive review on their application to SC risk and resilience is lacking. To address this gap, we analyzed research articles published in peer-reviewed academic journals from 2007 to 2019 using network analysis, visualization-based scientometric analysis, and clustering analysis. Through this study, we contribute to literature by discussing the challenges of current research, and, more importantly, identifying and proposing future research directions. The results of our survey show that further debate on the theory and application of BNs to SC resilience and risk management is a significant area of interest for both academics and practitioners. The applications of BNs, and their conjunction with machine learning algorithms to solve big data SC problems relating to uncertainty and risk, are also discussed.

Use of a knowledge broker to establish healthy public policies in a city district: a developmental evaluation.

BACKGROUND: Public health is to a large extent determined by non-health-sector policies. One approach to address this apparent paradox is to establish healthy public policies. This requires policy makers in non-health sectors to become more aware of the health impacts of their policies, and more willing to adopt evidence-informed policy measures to improve health. We employed a knowledge broker to set the agenda for health and to specify health-promoting policy alternatives. This study aimed at gaining in-depth understanding of how this knowledge broker approach works. METHODS: In the context of a long-term partnership between the two universities in Amsterdam and the municipal public health service, we employed a knowledge broker who worked part-time at a university and part-time for an Amsterdam city district. When setting an agenda and specifying evidence-informed policy alternatives, we considered three individual policy portfolios as well as the policy organization of the city district. We evaluated and developed the knowledge broker approach through action research using participant observation. RESULTS: Our knowledge brokering strategy led to the adoption of several policy alternatives in individual policy portfolios, and was especially successful in agenda-setting for health. More specifically, health became an issue on the formal policy agenda as evidenced by its uptake in the city district's mid-term review and the appointment of a policy analyst for health. Our study corroborated the importance of process factors such as building trust, clearly distinguishing the knowledge broker role, and adequate management support. We also saw the benefits of multilevel agenda-setting and specifying policy alternatives at appropriate policy levels. Sector-specific responsibilities hampered the adoption of cross-sectoral policy alternatives, while thematically designed policy documents offered opportunities for including them. Further interpretation revealed three additional themes in knowledge brokering: boundary spanning, a ripple effect, and participant observation. CONCLUSIONS: The employment of a knowledge broker who works simultaneously on both agenda-setting for health as well as the specification of health-promoting policy alternatives seems to be a promising first step in establishing local healthy public policies. Future studies are needed to explore the usefulness of our approach in further policy development and policy implementation.

Collective Sensemaking and Healthcare Workers' Ripple Effect Influencing Vaccine Hesitancy in West Michigan.

The social efficacy of vaccines has been a central concern around COVID-19 vaccine uptake rates. As partners on the Vaccinate West Michigan Coalition, we conducted a rapid ethnographic assessment project among adults living in West Michigan. Three case studies are presented to convey the nuanced context around decisions with a focus on the influence of fear, trust, and the ripple effect of healthcare workers' (HCW) beliefs around vaccines. While HCWs' attitudes and beliefs influence their patients, the unique contribution of this study is its focus on how HCWs' perceptions influence friends and family members.

Creating musical life reviews with older people: a community case study.

Older people living in their homes might experience growing loneliness, detachment from their social environment, and decreased functional ability. In this community case study, we report on a project we initiated to enhance the functional ability of older people by creating musical life reviews (MLR) with them. We connected seven of our music therapy graduates (MT) to older people living in the neighborhood across the street from campus. MTs were first trained to work by a protocol for creating MLRs with older people, developed by the authors of this article. They then worked with older people from the neighborhood for 10 one-on-one sessions, on personally tailored MLRs. MTs kept on meeting in weekly group supervision sessions, thus learning from each other- and forming a community of their own. Participants expressed their high satisfaction with the process and reported that their MLRs became increasingly important to them. Most of them were interested in taking their MLR one step ahead, and playing it to family and/or friends, and, as part of the process, planned a personal event to do this. Further, two big community events were initiated by participants and MTs. To conclude, we show how the community project enhanced the functional ability of those participating in it. We also point at possible challenges and recommendations for further implementation of the project.

Brownfields to Healthfields: A Retrospective Ripple Effect Mapping Evaluation in Three Rural Communities.

The environments in which we live influence our health behaviors and outcomes. The redevelopment of brownfields sites to health-promoting land uses may provide an array of benefits to individuals and communities, but these impacts can be particularly difficult to assess in rural communities using traditional evaluation approaches. This participatory evaluation aimed to explore the impacts of redeveloping rural brownfield sites into health-promoting land uses. Using a facilitated workshop-based Ripple Effects Mapping process, we evaluated three rural brownfields redevelopment sites across Appalachian portions of EPA Region 3 (mid-Atlantic). Adult members (n=32) of these communities participated in guided reflection on the redevelopment and subsequent impacts. Data were constructed as digital mind maps, then coded to the Community Capitals Framework by two authors coding independently. Member checking was conducted with representative workshop participants. Commonly cited impacts were site improvements, facilitation of social and physical activity, and engaging community identity. The most discussed community capitals were social and built; the least discussed capitals were natural and political. Rural brownfield redevelopment targeting physical activity provides the added benefit of engaging an array of community capitals, ultimately strengthening communities on the whole. Future directions for brownfield redevelopment evaluation are discussed.

Microplastics are transferred by soil fauna and regulate soil function as material carriers.

The ecotoxicological effects of microplastics, a new and widespread ecosystem pollutant, have been extensively reported. However, it remains unclear whether soil fauna transfer microplastics and whether migration behaviours influence subsequent ecological functions in terrestrial ecosystems. We investigated the transfer patterns of microplastics and their adsorbed substances by soil animals (the springtail, Folsomia candida) and the effect of the transfer on the decomposition of soil organic matter through a standardized cotton strip assay. The results showed that springtails had a strong ability to transfer microplastics into the soil. The adsorbed nutrient (nitrogen; N), pollutant (cadmium; Cd), and green fluorescent Escherichia coli (GFP-E. coli) were also transferred with the microplastics. In addition, cotton strip decomposition was accelerated when the microplastics adsorbed N, but the adsorption of Cd decreased decomposition. These ecological effects were particularly strong for small microplastics. Microplastic transfer regulated soil bacterial communities, promoting the growth of Ascomycota fungi and inhibiting that of Basidiomycota, leading to cotton strip decomposition. Thus, microplastic pollution may occur at one site, but microplastics can be transferred anywhere in terrestrial ecosystems by soil animals and adsorb other substances, including nutrients and pollutants, that affect ecosystem function. Therefore, more studies on the migration behaviour of microplastics are necessary.

A dataset on declared tax evasion attitudes of students and entrepreneurs from Poland under the slippery slope framework.

The datasets included in this article come from a survey carried out on a group of Polish students and self-employed entrepreneurs and were originally created for studies on tax behaviour under the slippery slope framework. The slippery slope framework explains the role of extensive power execution and building trust in the tax administration in enhancing either enforced or voluntary tax compliance accordingly [1]. Students of economics, finance, and management at the Faculty of Economic Sciences and the Faculty of Management at the University of Warsaw were surveyed in two rounds, in 2011 and 2022, using paper-based questionnaires handed to them personally. Entrepreneurs were invited to fill in online questionnaires in 2020. Questionnaires were filled in by self-employed individuals from the Kuyavia-Pomerania, Lower Silesia, Lublin, and Silesia Province. The datasets provide 599 records for students and 422 observations for entrepreneurs. The purpose of collecting these data was to analyse the attitudes of the mentioned social groups towards tax compliance and tax evasion under the slippery slope framework along two dimensions: trust in authorities and power of authorities. The sample was selected because students in these fields are the most likely to become entrepreneurs, so the study sought to capture the potential behavioural change that is taking place. Each questionnaire consisted of three parts, a description of a fictitious country (Varosia) in one of four scenarios: (1) high trust-high power; (2) low trust-high power; (3) high trust-low power; (4) low trust-low power, 28 questions including manipulation checks on trust in authorities and power of authorities, intended tax compliance, voluntary tax compliance, enforced tax compliance, intended tax evasion, tax morale and the perceived similarity between Varosia and Poland, and finally two questions on gender and age of respondents. The data presented are particularly useful for policymakers in shaping tax policy and economists in analyses regarding taxation. Researchers may be interested in reusing the provided datasets for comparative research in other social groups, regions, and countries.

Supply chain disruptions and resilience: a major review and future research agenda.

Our study examines the literature that has been published in important journals on supply chain disruptions, a topic that has emerged the last 20 years, with an emphasis in the latest developments in the field. Based on a review process important studies have been identified and analyzed. The content analysis of these studies synthesized existing information about the types of disruptions, their impact on supply chains, resilience methods in supply chain design and recovery strategies proposed by the studies supported by cost-benefit analysis. Our review also examines the most popular modeling approaches on the topic with indicative examples and the IT tools that enhance resilience and reduce disruption risks. Finally, a detailed future research agenda is formed about SC disruptions, which identifies the research gaps yet to be addressed. The aim of this study is to amalgamate knowledge on supply chain disruptions which constitutes an important and timely as the frequency and impact of disruptions increase. The study summarizes and builds upon the knowledge of other well-cited reviews and surveys in this research area.