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The purpose of this paper is to develop artificial neural networks (ANNs) allowing us to simulate the local thermal insulation of clothing protecting against cold on a basis of the characteristics of materials and design solutions used.

For this purpose, laboratory tests of thermal insulation of clothing protecting against cold as well as thermal resistance of textile systems used in the clothing were performed. These tests were conducted with a use of thermal manikin and so-called skin model, respectively. On a basis of results gathered, 12 ANNs were developed that correspond to each thermal manikin’s segment besides hands and feet which are not covered by protective clothing.

In order to obtain high level of simulations, optimization measures for the developed ANNs were introduced. Finally, conducted validation indicated a very high correlation (above 0.95) between theoretical and experimental results, as well as a low error of the simulations (max 8 percent).

The literature reports addressing the problem of modeling thermal insulation of clothing focus mainly on the impact of the degree of fit and the velocity of air movement on thermal insulation properties, whereas reports dedicated to modeling the impact of the construction of clothing protecting against cold as well as of diverse material systems used within one design of clothing on its thermal insulation are scarce.

The purpose of this paper is to compare morphological and physical features of three kinds of materials intended for the insulating layer in the clothing protecting against cold – high-bulk non-woven, goose down (GD) and duck down (DD).

Comparison of thermal performance of developed textile systems with the non-woven, GD and DD content was based on basic biophysical properties related to comfort sensations of the user such as thermal resistance, water vapor resistance and air permeability. In this study, light microscopy and scanning electron microscopy methods were employed to visualize the surface and internal structure of non-woven, GD and DD samples.

The paper indicates the advantages and disadvantages of each of selected insulating material. For the down samples, significantly higher thermal resistance in a dry state than for the non-woven samples can be achieved. Meanwhile, textile systems with the non-woven provide lower value of water vapor resistance. The selected textile systems for the research were characterized by a comparable air permeability.

This paper allows for an evaluation of high-bulk non-woven, DD and GD samples in terms of providing optimal thermal performance in clothing protecting against cold.

The purpose of this paper is to analyze the impact of design solutions used in clothing on the thermal resistance of the material systems from which the clothing is made, design solutions used in clothing on its thermal insulation and clothing size on its thermal insulation properties.

This study involved laboratory tests of clothing protecting against cold and textile systems used in this type of garment using a “skin model” test stand and a thermal manikin.

Analysis of the results obtained from tests carried out showed that the design solutions used in a garment can model its local and overall insulation. It was found that using a bib in trousers has a dominant influence on the thermal properties of clothing. An important parameter is also the use of a hood, as well as the length of the jacket. No significant effect of other structural solutions, such as jacket fastening, pockets and reflective tapes, on the thermal performance of the clothing set was noted.

Although the reports available in the literature pay a lot of attention to the impact of the design of clothing protecting against cold on its thermal performance, most of the presented research results relate to the aspects of fit, whereas the analyses of the effects of other aspects of garment construction on thermal properties are lacking. Therefore, the analysis of the impact of design solutions used in clothing on its thermal insulation properties is a key original factor of this paper.

The outbreak of the coronavirus pandemic (COVID-19) has severely disrupted businesses around the world. To address the impact of operational and strategic business disruptions, this paper contributes to the practice of a firm's management in terms of identifying the determinants of organizational resilience (OR) and creating a hierarchical model of the potential sources of a firm's adaptive capability.

A novel research framework integrating Pareto analysis, grey theory and total interpretive structural modeling (TISM) has been applied to, first, identify the sources of a company's resilience and, second, to determine contextual relations among these sources of OR.

The findings of the survey highlight three primary sources that allow companies to build companies' resilience: access to financial resources, digitization level and supply chain (SC) collaboration. The authors' model shows that resilience cannot be viewed as a particular feature but rather as a dynamic intertwined network of different co-dependent sources.

The proposed hierarchical model indicates that the most crucial sources of company's resilience in the recent pandemic are access to financial resources, digitization level and SC collaboration.

The study takes an original investigation on cognitive grounds, touching on the problem of firms' resilience to the unique nature of the crisis caused by the COVID-19 pandemic. The study also represents one of the few attempts to use integrated Pareto analysis, grey theory and TISM to examine this critical area of firm management.

Brexit has caused a visible disruption to the established and accepted web of rules governing European markets. Our study, based on a survey of Polish firms operating in the UK market, aims to identify Polish firms’ perceptions of Brexit and select characteristics of groups of firms exhibiting similar perceptions of uncertainty. The perception of uncertainty itself was measured along two separate dimensions – uncertainty about future arrangements between the EU and the UK and uncertainty about institutional agility in the UK. The results are analyzed using the cluster method. The findings identify three types of firms that we have named as alarmist, the concerned, and the oasis of peace, within which the largest group are companies that view Brexit as a non-significant threat (the oasis of peace), unlike the other two groups (alarmist and the concerned). Those perceived differently are mostly firms having larger size, greater involvement into the British market and longer-term experience in that market.

Crises are often studied in international business (IB) research as the external “context” for business strategies, but firms can also be active participants in the unfolding of crises. The study of crises in IB could benefit greatly from studying the role of multinational enterprises (MNEs) as active participants, rather than as mere passive actors, responding to exogenous events. History shows that IB crises typically unfold partially as exogenous processes, and partly as the result of MNE strategies. A multilevel and longitudinal approach to studying crises in IB is clearly necessary. This chapter considers the extent to which smaller events that preceded the present crisis – since 1989 – point to systemic problems in global governance. It also defines five overlapping lenses through which future IB studies can further create relevant insights on how to deal with crises: historic, macro, meso, micro and exogenous. The chapter finally serves as an introduction to the whole Progress in International Business Research volume by indicating the relevance of all parts and chapters that follow.