A Conceptual Reference Framework for Enterprise Resilience Enhancement

Resilient Roadmap to Minimise the Impact of COVID-19 in the Spanish Enterprises

If something has failed in the management of COVID-19 crisis, this has been the lack of resilience to anticipate, adapt and recover from this event. This paper analyses the impact of COVID-19 in different sectors in Spain, highlighting which ones were more negatively affected by the pandemic after the first COVID-19 wave and which ones created growth and employment during the recovery phase. In this sense, the most negative impacted sectors were culture, tourism and retail while tobacco, pharmaceuticals computer, electronic and optical products sectors pushed the Spanish economy towards recovery. Moreover, the impact of COVID-19 in different aspects such as employment, workers' health, reputation, productivity, among others was also studied. The results reveal that firms invested a lot of time in organising and restructuring work planning to adapt to the new constraints. Finally, based on the findings about the most impacted sectors and the most negatively affected aspects, a set of dimensions and policies are proposed in a roadmap to support the improvement of enterprise resilience capacity to face up to crisis situations such as the one caused by COVID-19.

Business Continuity Training: Educational Programme Proposal

The COVID-19 pandemic has had and is having devastating effects on the health of the population, but also on the economic health of companies and their supply chains. The old paradigms of the commercial and industrial world have been inevitably disrupted: global supply chains have shifted from a system based on efficiency to one oriented towards resilience. Business continuity has become a key activity to be considered in all business processes. Nevertheless, specific studies to train highly qualified professionals in Business Continuity are rare. Therefore, this paper suggests the topics and subjects to be included in a university educational programme proposal to train business continuity managers. This proposal can contribute into building digital education readiness supporting the business continuity manager training, as one of the most important weapons of responsiveness, adaptability, and flexibility to provide companies resilience during next black swan events.

Novel Insights in the Leadership in Business and Economics: A Post-Coronavirus Update

Our world is evolving at an incredibly enormous speed and what was impossible three years ago is now a reality. The concept of leadership and leaders has also undergone profound transformations. Moreover, the recent COVID-19 pandemic caused a digital surge in the ways economic life, business, or education are perceived or conducted. The pandemic proved that small and large businesses, industries, and the whole economies can be suddenly upended by massive technological shifts. Hence, there is a need for a theoretical research update in leadership in business and economics that would bring new insights into this topic and define its place within the context of Sustainable Development Goals (SDGs). Our paper presents the novel insights for the leaders and the leadership concept in business and economics from various approaches and angles of view in the light of the COVID-19 pandemic with a focus on sustainable leadership and organizational resilience. It aims at outlying the theoretical background of leadership in business and economics after the pandemic and bringing up interesting and recent leadership case studies from all around of the world. Moreover, this paper aims as sharing the valuable insights into what it means to be a sustainable leader in business and economics, why leaders are needed, and how to become one. The main criteria of this research and its instrumentation include both the theoretical discussion based on the literature review and analysis and the empirical analysis that supports these theoretical provisions. The paper features an empirical model that assesses how business and economic leaders are searching for new ways of work and personal development during and after the COVID-19 pandemic using the own data from the 400 respondents collected in the Czech Republic and Russia. We found that the pandemic enhanced the emotional creativity of business and economic leaders and made them to invest and engage more into using new digital technologies and fundamentally altering the old ways of managing and governing their respective companies and institutions. Our results might provide valuable food for thought both for academics working on various angles of leadership, as well as for entrepreneurs and businesspeople who want to receive recent updates on the topic of leadership to use them in their daily work.

Knowledge Registration Module Design for Enterprise Resilience Enhancement

The present situation characterized by the coronavirus pandemic has made businesses to be aware about the importance of being resilient to face undesirable impacts like the one caused by this pandemic. One of the constituent capacities of enterprise resilience is the recovery ability to bounce back and restore the operations after disruptions' occurrence. This paper is focused on the recovery perspective of enterprise resilience and its enhancement through knowledge registration. This research proposes the design of the Knowledge Registration Module addressed to the register of valuable information at different knowledge level with the main aim to reuse this piece of information to facilitate the recovery process when the same or an unexpected similar disruptive event occurs. Future research lines will be based on applying the knowledge approach to real cases to study the influence of knowledge management in the enhancement of enterprise resilience.

Deploying Resilience Enablers to Mitigate Risks in Sustainable Fashion Supply Chains

The complex structure of supply chains makes them vulnerable to risk, so enhancing their resilience is an important goal. In particular, fashion supply chain research has identified two important issues that need to be addressed: sustainability and risk. However, investigation of these issues is relatively sparse and has primarily been independent with little combinatory research. Therefore, it is crucial to develop a risk mitigation method that can maximize the resilience of sustainable supply chains for fashion companies. The objective of this study is to develop an integrated quality function deployment approach and to mitigate supply chain risk by deploying resilience capabilities and resilience-enhancing features, thus ultimately providing the fashion industry with a useful approach for the development of resilient, sustainable supply chains. Using a fashion company as an example, the practicability of the proposed approach is verified. To strengthen resilience and thus mitigate key risks, it is found that the most urgent tasks are to reallocate the company’s resources, to carry out the real-time monitoring of risk on the spot, to share the risk responsibility, and to establish an incentive system. When these features are strengthened, agility and adaptability can be improved, and finally, the risks of supplier delays, natural disasters, political instability, and problematic supplier materials with the greatest impact can be alleviated. This study provides a new strategy for the fashion industry for the implementation of resilient, sustainable supply chains to mitigate risks.

The Role of Relational Capital in Anti-Crisis Measures Undertaken by Companies—Conclusions from a Case Study

The aim of this article was to present the results of empirical research conducted in enterprises of all sizes operating in Poland and Central Europe. The study focused on the impact of relational capital on the prevention of and intervention in the event of a crisis in a company. The author assumes that there is a link between a company’s relational capital and its susceptibility to crisis phenomena. The research carried out allowed different conclusions to be drawn. It turns out that the studied companies were characterized by a high level of relational capital. Their internal relational capital—particularly the relations between employees and company owners—was especially important to them. Relations of the surveyed companies with external stakeholders were also important. In response to the question about the role of relational capital in anti-crisis measures undertaken by companies, it appears that the relational capital of the companies surveyed allowed them, in their opinion, to avoid many crisis situations. Thanks to the right attitudes of the surveyed companies’ stakeholders, they have often managed to avoid crises. This situation also applies to the recent crisis caused by COVID-19.

Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming

In today’s volatile business arena, companies need to be resilient to deal with the unexpected. One of the main pillars of enterprise resilience is the capacity to anticipate, prevent and prepare in advance for disruptions. From this perspective, the paper proposes a mixed-integer linear programming (MILP) model for optimising preparedness capacity. Based on the proposed reference framework for enterprise resilience enhancement, the MILP optimises the activation of preventive actions to reduce proneness to disruption. To do so, the objective function minimizes the sum of the annual expected cost of disruptive events after implementing preventive actions and the annual cost of such actions. Moreover, the algorithm includes a constraint capping the investment in preventive actions and an attenuation formula to deal with the joint savings produced by the activation of two or more preventive actions on the same disruptive event. The management and business rationale for proposing the MILP approach is to keep it as simple and comprehensible as possible so that it does not require highly mathematically skilled personnel, thus allowing top managers at enterprises of any size to apply it effortlessly. Finally, a real pilot case study was performed to validate the mathematical formulation.

Sustaining Enterprise Operations and Productivity during the COVID-19 Pandemic: “Enterprise Effectiveness and Sustainability Model”

The research explores key factors impacting enterprise operational sustainability and the ability to transcend adversity during different stages of a crisis, such as the COVID-19 pandemic. The current study draws from the Theory of Crisis Management Teams, the Stakeholder Theory, and the Distributed Cognition Theory to build an “Enterprise Effectiveness and Sustainability Model during Pandemic.” Existing theoretical background joint with contemporary success case studies helped to identify the essential aspects and strategies enterprises should employ to survive and thrive during crisis and post-crisis. We have conceptualized an innovative approach to COVID-19 from the perspective of organizational characteristics, operations, digital transformation, and financial planning. The findings suggest that enterprises having distributed leadership, workforce and adaptive culture sustain business operations during a pandemic. Furthermore, resilient enterprises allow for more informed and decentralized decision-making. Prosperous organizations leverage Internet and Communication Technology (ICT) and integrate Intranet, social media, and online communication platforms into their daily business routines, as this helps to establish trust and build bonds with employees, stakeholders, and customers during and post-crisis. Finally, balancing between the stockpiling of resources and resiliency is crucial in anticipation of a crisis. Therefore, we conclude that enterprises with financial contingency plans sustain their business operations during a pandemic.

Distributed Manufacturing of Open Source Medical Hardware for Pandemics

Distributed digital manufacturing offers a solution to medical supply and technology shortages during pandemics. To prepare for the next pandemic, this study reviews the state-of-the-art of open hardware designs needed in a COVID-19-like pandemic. It evaluates the readiness of the top twenty technologies requested by the Government of India. The results show that the majority of the actual medical products have some open source development, however, only 15% of the supporting technologies required to produce them are freely available. The results show there is still considerable research needed to provide open source paths for the development of all the medical hardware needed during pandemics. Five core areas of future research are discussed, which include (i) technical development of a wide-range of open source solutions for all medical supplies and devices, (ii) policies that protect the productivity of laboratories, makerspaces, and fabrication facilities during a pandemic, as well as (iii) streamlining the regulatory process, (iv) developing Good-Samaritan laws to protect makers and designers of open medical hardware, as well as to compel those with knowledge that will save lives to share it, and (v) requiring all citizen-funded research to be released with free and open source licenses.

Failure Prediction Model Using Iterative Feature Selection for Industrial Internet of Things

This paper presents a failure prediction model using iterative feature selection, which aims to accurately predict the failure occurrences in industrial Internet of Things (IIoT) environments. In general, vast amounts of data are collected from various sensors in an IIoT environment, and they are analyzed to prevent failures by predicting their occurrence. However, the collected data may include data irrelevant to failures and thereby decrease the prediction accuracy. To address this problem, we propose a failure prediction model using iterative feature selection. To build the model, the relevancy between each feature (i.e., each sensor) and the failure was analyzed using the random forest algorithm, to obtain the importance of the features. Then, feature selection and model building were conducted iteratively. In each iteration, a new feature was selected considering the importance and added to the selected feature set. The failure prediction model was built for each iteration via the support vector machine (SVM). Finally, the failure prediction model having the highest prediction accuracy was selected. The experimental implementation was conducted using open-source R. The results showed that the proposed failure prediction model achieved high prediction accuracy.