An integrated approach to organizational resilience: a quality perspective

PurposeThe main components of resiliency, including resilience capacities, resilience activities and resilience measures, are identified, extracted and redefined by designing their ontologies. The integrated model is developed by adapting the PDCA (plan, do, check and act) model to resilience management and implementing the developed concepts in the model.Design/methodology/approachThis study uses systems theory to define the main concepts discussed in the literature on resilience. This study then uses systems engineering theory and a resource-based view of the firm to develop an integrated framework to demonstrate how a resilient firm operates.FindingsThe revised terminologies and the integrated model address the current theoretical issues in the literature, and they also provide a reference model for practical implementation of resilience management at the firm level. Also, the integrated model addresses the role of innovation in resilience management.Originality/valueThe study examines the concept of resilience form a quality perspective and also examines how resilience and innovation are related.

Resilience Assessment: A Performance-Based Importance Measure

The resilience of a system can be considered as a function of its reliability and recoverability. Hence, for effective resilience management, the reliability and recoverability of all components which build up the system need to be identified. After that, their importance should be identified using an appropriate model for future resource allocation. The critical infrastructures are under dynamic stress due to operational conditions. Such stress can significantly affect the recoverability and reliability of a system‘s components, the system configuration, and consequently, the importance of components. Hence, their effect on the developed importance measure needs to be identified and then quantified appropriately. The dynamic operational condition can be modeled using the risk factors. However, in most of the available importance measures, the effect of risk factors has not been addressed properly. In this paper, a reliability importance measure has been used to determine the critical components considering the effect of risk factors. The application of the model has been shown through a case study.

Evidence of the adaptive market hypothesis in shares traded by B3 listed banking companies

PurposeThe authors aim to verify the indicators that influence the efficiency reported by Brazilian listed financial companies.Design/methodology/approachThe sample consists of companies in the financial segment that have shares traded in B3, comprising nine institutions from 2000 to 2018 were selected. The authors adopted the regression model with unbalanced panel data to analyze the data. The dependent is the efficiency, which the authors calculated using Hurst Exponent. As independent variables, we used the sector-specific indicators: earnings management, banking resilience, management efficiency, and profitability. The authors controlled the models by size and type of control.FindingsThe findings indicate that the efficiency of financial companies' securities is affected by aspects related to management, resilience, and efficiency in administration. The lower the earnings management, the greater the banking resilience, the efficiency in the management of resources, and the efficiency of stock prices of these companies. These results show that efficiency is affected by intrinsic factors of the entities, corroborating the hypothesis that markets adapt, among others, to institutional factors.Originality/valueMany users of financial institutions understand whether their stock prices reflect the information provided by accounting. The findings are original because they provide evidence that institutional factors affect the efficiency of companies in the Brazilian financial segment.

Resilience and Situational Awareness in Critical Infrastructure Protection: An Indicator-Based Approach

The paper proposes a concept enabling quantitative assessment of resilience in critical entities developed in the European projects SmartResilience and InfraStress. The concept aims at combining simple communication-related advantages of simplified assessments results (such as “resilience very high” or “resilience very low”) with the advantages of the in-depth assessments (e.g. analysis of multiple sensor data). The paper describes the main elements of the innovative, indicator-based concept, starting with the “resilience cube” at the top, and continuing with the multi-level, hierarchical, indicator-based assessment methodology. The concept allows analyzing and assessing different aspects of practical resilience management. One can assess the resilience level of an entity at a given point in time, monitor their resilience level over time and benchmark it. One can also model and analyze the functionality of a system during a particular (threat) scenario, as well as stress-test it. The same methodology allows to optimize investment in improving resilience (e.g. in further training, in equipment, etc.), in a transparent and intuitive way. A resilience indicator database (over 4,000 indicators available) and a suite of tools (primarily developed within SmartResilience and InfraStress projects) and a repository of over 20 application cases and 300 scenarios, support application of the methodology. The concept has been discussed and agreed with over 50 different organizational stakeholders and is being embedded into the new ISO 31050 standard currently under development. Its “life-after-the-project” will be ensured by the dedicated “resilience rating initiative (ERRA)”. Although the concept and the tool in the form of the “ResilienceTool” were developed primarily for the resilience assessment of critical infrastructure (the “smart” ones in particular), they can be used for resilience assessment of other systems and through the extension of the, already initiated, implementation of AI techniques (machine learning) to make the ResilienceTool even more versatile and easier to use in the future.

Prioritization of hazards for risk and resilience management through elicitation of expert judgement

Risk assessment in communities or regions typically relies on the determination of hazard scenarios and an evaluation of their impact on local systems and structures. One of the challenges of risk assessment for infrastructure operators is how to identify the most critical scenarios that are likely to represent unacceptable risks to such assets in a given time frame. This study develops a novel approach for prioritizing hazards for the risk assessment of infrastructure. Central to the proposed methodology is an expert elicitation technique termed paired comparison which is based on a formal mathematical technique for quantifying the range and variance in the judgements of a group of stakeholders. The methodology is applied here to identify and rank natural and operational hazard scenarios that could cause serious disruption or have disastrous effects to the infrastructure in the transnational Øresund region over a period of five years. The application highlighted substantial divergences of views among the stakeholders on identifying a single ‘most critical’ natural or operational hazard scenario. Despite these differences, it was possible to flag up certain cases as critical among the natural hazard scenarios, and others among the operational hazards.

A Global Supply Network Design Model: A Resilient Management Approach

We propose a design model for creating a resilient supply network applicable for local and global markets. It addresses the ineffectiveness and failure of existing supply network that resulted current economic, food and hospital supply crisis during this ongoing COVID 19 Pandemic situation. The research includes resilience creation approach for the known previously experienced as well as unknown and unforeseen disruption situations. This research considers resilience management-based steps and methods covered in the literature to building abilities of supply networks for absorption, adaptation and recovery for containing disruptions that have severe negative effect on supply chain operations and society. The research studies the options for including SC intermediaries to take the role of supply agent or supply contractors (SCON) to manage supply of items when traditional/classical supply networks known to us were almost inoperative or ineffective to fulfill buyer requirements during this COVID 19 like pandemic situations. A numerical example is solved for illustrating applicability of the model.

A comparison of hazard analysis methods capability for safety requirements generation

A safety-critical system comprising several interacting and software-intensive systems must be carefully analyzed to detect whether new functional requirements are needed to ensure safety. This involves an analysis of the systemic properties of the system, which addresses the effect of the interaction between systems and system parts. The paper compares two hazard analysis methods, which are often considered well-suited for such software-intensive systems: the Functional Hazard Analysis (FHA) and Systems-Theoretic Process Analysis (STPA). The focus is on the selection and improvement of the best methods, based on the lesson learned from the comparison of FHA and STPA. The analyses cover the hazard analysis processes, systemic properties, and the criteria of requirements. The paper concludes that STPA is the better choice over FHA. Insights are obtained to align both STPA and FHA methods with the broader topic on risk management, that is, hazard analysis method improvement, cautionary thinking, uncertainty management, and resilience management.