Search results

Despite long decades of research studies in the field of urban neighborhood resilience, there are still some unknown dimensions. In this regard, the study aims to develop a new framework for assessment of physical and social resilience at neighborhood level against earthquake.

Accordingly, first all indicators affecting earthquake resilience at neighborhood level have been determined. Subsequently, they have been weighted and prioritized, using analytical hierarchy process technique. One of the neighborhoods of Tehran city in Iran was selected for the case study. Then, four criteria of “robustness,” “redundancy,” “rapidity” and “resourcefulness” were considered as the basis for assessing neighborhood resilience.

It is shown that besides four well-known criteria, four other criteria including “adaptability,” “regularity,” “density” and “efficiency” should also be considered to assess earthquake resilience at neighborhood level. Therefore, a new framework is developed and formulated at this level. Paying attention to all eight criteria, the appropriate interventions to improve resiliency can be addressed.

This study proposes several practical approaches toward the more resilient neighborhoods against earthquakes. By considering the complexity and dynamic characteristics of earthquake resilience, it recommends the implementation of all resilience phases at every neighborhood to increase resilience.

This study proposes a framework in which in addition to physical and tangible indicators of resilience, non-physical and intangible ones are presented. Also, it is shown that besides well-known criteria, other criteria should also be considered using practical and community-based approaches.

Critical infrastructures (CIs) are essential components of the built environment. They ensure the interconnectivity and good operability of any major urban environment. CIs are exposed to several disruptions such as natural events, hazards or threats that may disturb their normal functionality. These disruptions may impact societies not only from a socio-economic perspective but also environmentally. Therefore, ensuring the resilience of CIs is crucial to modern cities. This paper aims to explore the main standards and criteria used to assess the resilience of CIs.

A three-stage systematic review process was adopted to retrieve relevant papers. A total of 44 papers were carefully selected, and the content analysis technique was used to thoroughly analyse the papers.

Results show that researchers’ interest to investigate the assessment criteria of CIs resilience increased after 2004. Further, a total of 28 resilience criteria of CIs were identified, of which the most reported ones are organisational resilience; performance loss, disruption and recovery process; resilience metrics and index; safety, security and risk analysis; societies/communities’ resilience and/or social-equity responsibility; dynamic networks connectivity; resilience through design and structural integrity; and economic resilience.

The findings of this research will serve as a solid foundation for the development of hypothesis for future empirical studies into the development of assessment criteria index for CI resilience. Further, the outcomes will contribute to the ongoing international discussions and debate on the appropriate ways to develop CI resilience.

Project selection is a critical decision for any organization seeking to commission a large-scale construction project. Project selection is a complex multi-criteria decision-making problem with significant uncertainty and high risks. Fuzzy set theory has been used to address various aspects of project uncertainty, but with key practical limitations. This study aims to develop and apply a novel Pythagorean fuzzy sets (PFSs) approach that overcomes these key limitations.

The study is particular to complex project selection in the context of increasing interest in resilience as a key project selection criterion. Project resilience is proposed and considered in the specific situation of a large-scale construction project selection case study. The case study develops and applies a PFS approach to manage project uncertainty. The case study is presented to demonstrate how PFS is applied to a practical problem of realistic complexity. Working through the case study highlights some of the key benefits of the PFS approach for practicing project managers and decision-makers in general.

The PFSs approach proposed in this study is shown to be scalable, efficient, generalizable and practical. The results confirm that the inclusion of last aggregation and last defuzzification avoids the potentially critical information loss and relative lack of transparency. Most especially, the developed PFS is able to accommodate and manage domain expert expressions of uncertainty that are realistic and practical.

The main novelty of this study is to address project resilience in the form of multi-criteria evaluation and decision-making under PFS uncertainty. The approach is defined mathematically and presented as a six-step approach to decision-making. The PFS approach is given to allow multiple domain experts to focus more clearly on accurate expressions of their agreement and disagreement. PFS is shown to be an important new direction in practical multi-criteria decision-making methods for the project management practitioner.

The purpose of this paper is to establish the factors affecting the selection of a suitable partner city for resilience building at the national level.

An exploratory sequential research was adopted using New Zealand as a case study. Data were collected through focus groups and semi-structured interviews and subsequently validated through an online survey.

The study confirmed that the criteria for selecting partner cities for collaboration and knowledge sharing on resilience were similarity of hazards, geographic proximity, city resources and priorities, resilience performance, city size and demographics, previous relationship, willingness to collaborate and similar industries.

The findings of this paper will help guide cities that are interested in developing national-level resilience partnerships through the process of selecting the most suitable partner cities.

Despite the existence of international intercity resilience networks, there is a lack of information on the criteria affecting the selection of suitable resilience partner cities at the national level. This paper addresses this gap and offers informed decision-making criteria for cities to consider.

Community resilience decides a lot on a city's ability to withstand an external shock. It has evolved naturally from a bounce-back approach to a more robust and meaningful bounce-forward process. The study explores gaps found in community resilience and finds that criteria specific to different disasters are absent.

The study uses a multi-criteria decision analysis technique, fuzzy Delphi, to select criteria. Derivation of the initial list of criteria was from a pilot study, a focus group discussion and other literature studies which was followed by the fuzzy Delphi survey.

After two rounds of fuzzy Delphi analysis, the consensus among 65 experts resulted in selecting 125 sub-sub-criteria within seven criteria. Findings show that many criteria previously not discussed in other pieces of literature project high fuzzy scores such as “availability of drinking water post-disaster” and “cracking down fake news spreaders by the police”. In addition, positive cooperation between political and religious institutions have proven to expedite disaster recovery.

The future scope also includes weighing the selected criteria using analytical hierarchy process (AHP).

Policymakers in the disaster management domain can use the study findings in implementing effective disaster mitigation strategies.

The selection of criteria is based on the community resilience shown by the Kerala community during the floods of 2018 and 2019 (in Kerala). Measures demonstrated by the community need to be studied, which will help foster disaster mitigation better in future scenarios.

Selecting the optimal supplier is a challenging managerial decision that involves several dimensions that vary over time. Despite the considerable attention devoted to this issue, knowledge is required to be updated and analyzed in this field. This paper reveals new opportunities to advance supplier selection (SS) research from a multidimensional perspective. Moreover, this study aims to formalise SS knowledge to enable the appropriate selection of sustainable, resilient and circular criteria.

This study is developed in two stages: first, a systematic literature review is conducted to select relevant papers. Descriptive and thematic analyses are employed to analyze criteria, solving approaches and case studies. Second, a criterion knowledge-based framework is developed and validated by experts to be implemented as ontology using Protégé software.

Evaluating the viability of suppliers need further studies to integrate other criteria and to align SS objectives with research advancement. Artificial intelligence tools are needed to revolutionize and optimize the traditional techniques used to solve this problem. Literature lucks frameworks for specific sectors. The proposed ontology provides a consistent criteria knowledge base.

For academics, the results of this study highlight opportunities to improve the viable SS process. From a managerial perspective, the proposed ontology can assist managers in selecting the appropriate criteria. Future works can enrich the proposed ontology and integrate this knowledge base into an information system.

This study contributes to promoting knowledge about viable SS. Capitalizing the knowledge base of criteria in a computer-interpretable manner supports the digitalization of this critical decision.

Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave.

This paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted.

The result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave.

The research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC.

The proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC.

The COVID-19 pandemic has showcased the lack of resilience found in the global value chains (GVCs) of multinational enterprises (MNEs). Existing evidence shows that MNEs have only recently and slowly started recovering and attempting to rebuild the resilience of their GVCs. This paper analyzes the challenges/inhibitors faced by MNEs in building their resilience through their GVCs.

A four-stage hybrid model was used to identify the interrelationship among the identified inhibitors and to distinguish the most critical ones by ranking them. In the first stage, we employed a modified total interpretive structural modeling (m-TISM) approach to determine the inter-relationship among the inhibitors. Additionally, we identified the inhibitors' driving power and dependency by performing a matrix multiplication applied to classification (MICMAC) analysis. In the second stage, we employed the Pythagorean fuzzy analytic hierarchy process (PF-AHP) method to determine the weight of the criteria. The next stage followed, in which we used the Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method to rank the inhibitors. Finally, we performed a sensitivity analysis to determine the robustness of the framework we had built based on the criteria and inhibitors.

We find business sustainability to have the highest importance and managerial governance as the most critical inhibitor hindering the path to resilience. Based on these insights, we derive four research propositions aimed at strengthening the resilience of such GVCs, followed by their implications for theory and practice.

Our findings contribute to the extant literature by uncovering key inhibitors that act as barriers to MNEs. We link out our findings with a number of propositions that we derive, which may be considered for implementation by MNEs and could help them endow their GVCs with resilience.

This paper aims to identify, classify and rank the contributing factors to financial resilience.

The present study is of a mixed-method and significant contributing factors have been identified after analyzing and reviewing the literature on resilience and financial resilience. These factors were classified and ranked using the analytic hierarchy process method. This paper operationalizes the concept of financial resilience.

The study results show that consistency in production and sales, access to a reliable supply chain, management ability to environmental adaptability, regional dimension and social support from the government’s side are among the determining factors in financial resilience at the market level. Some elements such as flexibility, risk identification, income, foreign exchange benefits, innovation in presenting goods and services, firm size and responsiveness of partners and beneficiaries inside and outside the organization are among the leading contributing factors at the organization level and management manner. Finally, the staff’s efficiency in using organization resources, shareholder staff and learning culture in the organization are among the main contributing factors to financial resilience under the staff’s influence.

The study results may give managers direction to evaluate companies’ resilience, especially in the emerging economy; besides, it improves the literature on the topic.

The increasing risk of natural disasters is challenging humanitarian actors to create resilient disaster management systems. However, the role of the private sector in disaster management operations (DMOs) is not as prominent as the role played by (inter)governmental agencies. This article aims to investigate the relationship of collaboration and resilience in disaster management supply networks (DMSNs).

Supply network resilience criteria were defined as robustness, flexibility, velocity and visibility based on the literature review. DMSN capabilities were identified characterising each resilience criterion through the development of the Collaboration–Resilience (COLRES) Analysis Framework for DMSNs. This theoretical model was then applied to an empirical case study in the Philippines using semi-structured interviews for data gathering.

A total of 46 cross-sector collaboration activities were identified across four disaster management phases and linked to the resilience criteria. A causal analysis of each collaboration activity and its outcome was conducted to identify relationships between collaboration types and resilience constructs. Based on these results, patterns were identified, and dependencies between collaboration and resilience were defined. Collective DMSN resilience (DMSNRES) enabled by existing cross-sector collaboration activities was evaluated against a future disaster scenario to identify resilience gaps. These gaps were used to recognise new cross-sector collaboration opportunities, thereby illustrating the continuous process of resilience building.

This research provides new insights on how private sector is involved within a DMOs through collaboration with the government and other NGOs. It augments existing literature on private sector involvement in DMOs where common perception is that the sector is only involved in short-term response and recovery activities. This study finds that the private sector can be operationally involved not just in post-disaster activities, but also in mitigation and preparation phases as well. This then sets a new baseline for further research on private sector involvement within DMOs. As this study provided a novel framework to analyse collaboration activities and its impact to DMSN resilience, future work could be done by applying the model to further cases such as other countries'. DMSNs, or to more specific contexts such as inter-organisational collaborations rather than big sectors. A more detailed assessment method against a future disaster will prove relevance for the model in providing practical insights on how resilience can be built in DMSNs.

This research proposed a novel DMSN collaboration-resilience (COLRES) model (Figure 11) to analyse existing processes in preparation for specific disasters. Practitioners may be able to use this model with the goal of identifying resilience gaps to fill and continuously improve their processes. The model also provides practitioners the lens to improve processes with the perspective on collaboration to complement government and NGO efforts and expertise with those of the private sector. For the private sector perspective, this research provides new insights on how they can be more involved with the community to provide more sustainable and long-term contributions to the society.

With disasters becoming more complex and frequent by the day and as humanitarian actors focus on improving their expertise, the need for every piece of the society to contribute to disaster risk reduction is continuously intensified. This research shows that each sector of the society can take part in disaster management operations to reduce unpredictability, lives impacted and increase speed of response and recovery. Each sector of the society can be of great contribution not only during post-disaster response and recovery but also during pre-disaster mitigation and preparedness phase. As such, this research echoes the call for everyone to be involved in disaster risk reduction and mitigation as a way of life.

This research ultimately finds that cross-sector collaboration builds resilience in DMSNs through capacity building, redundancy sourcing, information reliability and logistics responsiveness. This study shows that the private sector is able to go beyond existing short-term partnerships by participating in the 46 collaboration activities identified across four disaster management phases in order to build resilience in DMSNs.