Direct Loss Research Articles

Acidification of European croplands by nitrogen fertilization: Consequences for carbonate losses, and soil health

Soil acidification is an ongoing problem in intensively cultivated croplands due to inefficient and excessive nitrogen (N) fertilization. We collected high-resolution data comprising 19,969 topsoil (0–20 cm) samples from the Land Use and Coverage Area frame Survey (LUCAS) of the European commission in 2009 to assess the impact of N fertilization on buffering substances such as carbonates and base cations. We have only considered the impacts of mineral fertilizers from the total added N, and a N use efficiency of 60 %. Nitrogen fertilization adds annually 6.1 × 107 kmol H+ to European croplands, leading to annual loss of 6.1 × 109 kg CaCO3. Assuming similar acidification during the next 50 years, soil carbonates will be completely removed from 3.4 × 106 ha of European croplands. In carbonate-free soils, annual loss of 2.1 × 107 kmol of basic cations will lead to strong acidification of at least 2.6 million ha of European croplands within the next 50 years. Inorganic carbon and basic cation losses at such rapid scale tremendously drop the nutrient status and production potential of croplands. Soil liming to ameliorate acidity increases pH only temporarily and with additional financial and environmental costs. Only the direct loss of soil carbonate stocks and compensation of carbonate-related CO2 correspond to about 1.5 % of the proposed budget of the European commission for 2023. Thus, controlling and decreasing soil acidification is crucial to avoid degradation of agricultural soils, which can be done by adopting best management practices and increasing nutrient use efficiency. Regular screening or monitoring of carbonate and base cations contents, especially for soils, where the carbonate stocks are at critical levels, are urgently necessary.

Impact of Climate Change on Infrastructure Resilience and Adaption Strategies

Infrastructure networks have an severe effect by the physical impacts of climate mutability and change, but will also play an crucial role in building resilience to those impacts. Furthermost events explains the extensiveness of this potential exposure. For example, OECD [Organization For Economic And Development ] modelling of the potential impacts of a major flood in Paris found that 30% to 55% of the direct flood damages would be tolerated by the infrastructure sector, while 35% to 85% of business losses were caused by disturbance to the transportation and electricity supply and not by the flood itself. Climate change has very diverse effect on the infrastructure. If the infrastructure will be climate resilient will help to reduce direct losses and reduce the indirect costs of disturbance created by the sudden climate change. New infrastructure should be hierarchic, planned, designed, built and set off in such a way to resist the climate changes that may occur over anytime during their lifetimes. The old Existing infrastructure may need to be rebuilt , or managed differently according to the given climate change. Lastly, additional infrastructure, such as sea walls, will need to be constructed to address the physical impacts of climate change. This additional infrastructure should or may be include traditional infrastructure, such as hard safeguarding and other engineered solutions, as well as natural infrastructure, such as wetlands and other naturally-based solutions. A wide range of actors, both in the public and private sectors, are taking action to strengthen climate resilience. This report highlights appears good practices and remaining challenges across OECD[Organization For Economic And Development] and G20 countries. It provides non-prescriptive guidance to countries as they find the way to enhance resilience in line with their national circumstances and priorities. Key Words: Infrastructures , Climate changes , Resilience , OECD , Challenges , Impacts , Design , Sustainable , Adaptation , Strategies .

THE IMPACT OF CLIMATE CHANGE ON THE RISK-TAKING LEVEL OF CHINESE COMMERCIAL BANKS: EMPIRICAL EVIDENCE FROM CHINESE LOCAL COMMERCIAL BANKS

China’s risk disasters caused by climate change have increased the risk-taking level of China’s commercial banks, posing a threat to the stable development of financial markets. Based on the data from 152 commercial banks in China from 2011 to 2021, this paper uses the fixed effect model to analyze the effect and mechanism of China’s climate change on the risk-taking level of Chinese commercial banks. The main conclusions are as follows. (1) Climate change has significantly improved the risk-taking level of Chinese commercial banks. The results remain significant under the robustness and endogenous tests, such as dealing with endogenous problems, changing variables and adjusting sample intervals. (2) The results of heterogeneity analysis show that under different regions and different types of conditions, the impact of climate change on the risk-taking level of China’s commercial banks is heterogeneous, and the impact is stronger in urban commercial banks and eastern China. (3) The direct economic losses caused by natural disasters caused by climate change affect the risk-taking level of Chinese commercial banks; however, the adjustment of ex ante disaster insurance can weaken the impact of climate change on the risk-taking level of Chinese commercial banks. This paper studies the impact of climate change on the risk-taking level of Chinese commercial banks from the perspective of bank risk-taking level, which is of great significance to enhance the risk prevention awareness of Chinese commercial banks in response to climate change.

Whole value at risk for flood damage estimates through spatial data analysis

Effective disaster risk reduction (DRR) for flooding requires a comprehensive estimate of the whole value at risk (WVAR) to inform appropriate and proportionate mitigation expenditure. Conventional flood risk estimation methods focus on the direct effects of inundation on community value and generally ignore collateral effects on assets and populations outside the flooded area. Consequently, conventional methods tend to underestimate the cost of flooding, leading to an underestimate of the return on DRR investment. Using spatial data analysis in an urban case study for Toronto, Canada, we identify and capture the collateral value at risk (ColVaR) to estimate the WVAR more comprehensively. In our case study, ColVaR (mean estimate) amounts to 70% of direct losses (ColVar = $344 M; direct losses = $475 M CAD), ranging from 20%–150% (ColVar $100–$740 M) when spanning the 90% confidence intervals of our Monte Carlo simulations. Thus, we demonstrate that if the collateral value at risk is ignored, WVAR can be significantly underestimated, potentially leading to reduced disaster risk reduction resource allocations and thereby adding risk exposure for communities. We present an accessible, seven-step process using existing spatial analysis tools and techniques that infrastructure stakeholders and planners can use to estimate ColVaR and better formulate DRR measures for their communities.

Cost of high-level flooding as a consequence of climate change driver?: A case study of China’s flood-prone regions

The extent of flooding in China is more significant than in any other country. Our research reveals that approximately 66 % of China’s landmass is submerged by flooding, affecting about 50 % of the population. Furthermore, the financial toll of flooding now accounts for approximately 1.42 % of the annual gross domestic product (GDP), which is almost 40 times higher than the corresponding figure for the United States. We have observed that Zhengzhou city in Henan province, which faced a devastating flood in 2021, received a significant amount of rainfall, specifically a total of 552.5 mm within a 24-hour period. The floods in Henan province in 2021 caused considerable damage, including impacting nearly 15 million people, resulting in almost 400 deaths, damaging over 10,000 square kilometers of agricultural land, causing almost $19 billion in economic losses, and leading to the collapse of over 35,000 households and damage to various properties. In a similar manner, the significant flooding that occurred in southern China in 2020 impacted approximately 7.1 million individuals across eight provinces and resulted in 54 fatalities, the collapse of 6,700 houses, and incurred a direct economic loss of US$3.33 billion. We found that rainstorms have significantly increased to 10 % in the last 60 years in China. In this paper, we delved into exploring the existing published articles, reports, and government and authoritative legal texts to analyze the causes and impacts of flooding in China’s flood-prone regions and potential mitigation strategies to reduce the repercussions of distressing flood events. We believe this study will help policymakers by providing new insights while formulating policy to reduce the loss caused by high-level flooding.

Economic burden attributable to hospital-acquired infections among tumor patients from a large regional cancer center in Southern China

To evaluate the economic loss of hospital-acquired infections (HAIs) among tumor patients so as to help policymakers to allocate health care resources and address the issue. We conducted a retrospective, 1:1 matched case-control study in a large region cancer hospital between January 1 and December 31, 2022. The economic burden was estimated as the median of the 1:1 pair differences of various hospitalization fees and hospital length of stay (LOS). In this study of 329 matched pairs, the patients with HAIs incurred higher hospitalization cost (ie, $16,927) and experienced longer hospital LOS (ie, 22 days), compared to the non-HAI groups. The extra hospitalization cost and the prolonged hospital LOS caused by HAIs were $4,919 and 9 days, respectively. Accordingly, the direct nonmedical economic loss attributable to HAI was approximately $478 to 835 per case. Furthermore, the increment of hospitalization costs varied by sites of infection, types of tumors, and stratum of age. HAIs lead to the increment of direct economic burden and hospital LOS in tumor patients. Our findings highlight the importance of implementing effective infection control measures in hospitals to reduce the financial burden on tumor patients.

Assessment of typhoon disaster loss based on the factor analysis-random forest model

Typhoon disasters in China’s coastal areas pose significant challenges for disaster prevention and mitigation, urban planning and national economic construction. This study aims to address the problem of incomparable disaster assessment indicators and low prediction accuracy of machine learning for small sample data. It establishes an index system based on the practical disaster investigation classification standards, which ensures data sources and uniformity. It also proposes a combination algorithm of factor analysis-random forest regression for direct economic loss prediction, which improves the typhoon disaster losses prediction. The results show that the optimized model has higher accuracy than single decision tree model, random forest model and factor analysis-decision tree model. The factor analysis method verifies the importance of influencing factors, which indicates that China faces great risks of coastal floods caused by super typhoons. The combination regression model can predict disaster losses reasonably, providing effective technical support for typhoon disaster assessment and management.

Persistence of Basal Ganglia Oscillatory Activity During Tremor Attenuation by Movement in Parkinson's Disease Patients.

One of the characteristics of parkinsonian tremor is that its amplitude decreases with movement. Current models suggest an interaction between basal ganglia (BG) and cerebello-thalamo-cortical circuits in parkinsonian tremor pathophysiology. We aimed to correlate central oscillation in the BG with electromyographic activity during re-emergent tremor in order to detect changes in BG oscillatory activity when tremor is attenuated by movement. We performed a prospective, observational study on consecutive parkinsonian patients who underwent deep brain stimulation surgery and presented re-emergent tremor. Coherence analysis between subthalamic nucleus/globus pallidus internus (STN/GPi) tremorous activity measured by microrecording (MER) and electromyogram (EMG) from flexor and extensor wrist muscles during rest, posture, and re-emergent tremor pause was performed during surgery. The statistical significance level of the MER-EMG coherence was determined using surrogate data analysis, and the directionality of information transfer between BG and muscle was performed using entropy transfer analysis. We analyzed 148 MERs with tremor-like activity from 6 patients which were evaluated against the simultaneous EMGs, resulting in 296 correlations. Of these, 26 presented a significant level of coherence at tremor frequency, throughout rest and posture, with a complete EMG stop in between. During the pause, all recordings showed sustained MER peaks at tremor frequency (±1.5 Hz). Information flows preferentially from BG to muscle during rest and posture, with a loss of directionality during the pause. Our results suggest that oscillatory activity in STN/GPi functionally linked to tremor sustains firing frequency during re-emergent tremor pause, thus suggesting no direct role of the BG circuit on tremor attenuation due to voluntary movements. © 2024 International Parkinson and Movement Disorder Society.

Assessment of meat preservation methods used by retailers and the estimation of direct economic losses associated with meat spoilage in Kenya

Meat spoilage reduces the meat quality and the revenue from the meat industry. This study assessed the direct impact of ineffective meat preservation methods on economic loss among meat retailers in the Dagoretti region of Nairobi, Kenya. A cross-sectional survey was conducted in 87 butcheries and 9 supermarkets from low, middle, and high-income areas using a systematic sampling technique. The meat losses were measured by kilograms of spoilt meat and associated financial cost was estimated. Descriptive and Inferential statistics were used to establish the significance of the association between preservation and demographic factors. A correlation analysis was used to estimate the strength of the relationship between the factors. The study revealed that most of meat handlers heavily relied on refrigeration methods (73%) for storing meat, and 27% hung meat at room temperature due to the high cost of electricity and deep freezers. Furthermore, it revealed that each meat retail business lost 2.3 kg (1.0-3.0 kg) on average per week, which indicates financial losses of USD 11.5 (Range 5.0-15.0 USD) per week or USD 598 (Range USD 260-790) per year. These losses were mainly associated with moisture loss (49%) and microbial spoilage (22%). Poor storage and meat handling practices were blamed for spoilt meat. Meat retailers reported fly menace disturbing their business. It’s recommended that the government implement policies to reduce electricity bills and enhance the adoption of refrigeration methods, while industry stakeholders should facilitate initiatives for public awareness on appropriate methods of meat preservation. Additionally, retail cut meat products on display should be wrapped with permeable film to reduce moisture loss. Further study is needed for a comprehensive analysis of direct economic losses segregated by meat types and preservation forms.

The Effect of Magnetic Anisotropy on the Computed Specific Total Loss in Electrical Steel

Grain-oriented (GO) electrical steel (ES) laminates are still very important in industrial applications due to their remarkable crystallographic properties. Cores of large electrical machines and transformers are built from ES. The performances of these devices are significantly influenced by the properties of ES. The improvement of ES properties has been the subject of considerable research for many years. The phenomenon of magnetic anisotropy is highly non-linear, and it should be taken into account by the designers of magnetic circuits. The article proposes a modified model for calculating the angular properties of specific total loss of ES. The modeling takes into account the isotropic component (from classic eddy currents) and the anisotropic component, which is the sum of hysteresis and excess losses. For the directional loss modeling, the Boltzmann function was used. An analysis of the dependency of model coefficients on the frequency is presented.

Результаты лабораторно-полевых испытаний процесса глубокорыхления глубокорыхлителем РВН-3

Sunflower harvesting is the final stage in its cultivation; it is the most labor-intensive and responsible operation, as it requires a lot of labor and the availability of specialized equipment. Important factors influencing the quality indicators of sunflower harvesting are the timing of harvesting and the technical means used. The optimal time for sunflower harvesting occurs when the seed moisture content is 12-14%; at this humidity, as a rule, self-shedding of the seeds does not occur. Reducing direct losses of sunflower seeds behind a combine harvester largely depends on the harvesting equipment used. Currently, there are a large number of them, they have different designs, but not all of them meet agricultural requirements. The article presents the test results of sunflower harvesting devices PRP-8 and PRP-12. Keywords: HARVESTING, HARVEST, SUNFLOWER, HARVESTER, MOUNTED HARVESTING ADAPTERS, ENERGY EQUIPMENT, TECHNOLOGICAL PROCESS

Prioritising climate adaptation options to minimise financial and distributional impacts of water supply disruptions

Climate-related disruptions to water supply infrastructure services incur direct financial losses to utilities (e.g. to repair damaged assets) and externalise a societal cost to domestic customers due to additional costs that they may incur (e.g. to acquire water from alternative sources). The latter often represents an uncompensated social burden, which should be properly accounted for in investment planning. Here we present a new framework for quantifying direct financial risks burdened by utilities and alternative water purchase losses incurred by domestic customers, including those in low-income groups, during flood- and drought-induced utility water supply disruptions. This framework enables the comparison of benefit-cost ratios of a portfolio of flood protection and leakage reduction for water supply systems across the island of Jamaica. A system-level optioneering analysis allows the identification of the optimal adaptation option per system. We estimate that 34% of systems would benefit from flood defences and 53% would benefit from leakage reduction to adaptation to droughts. The benefit that could be achieved by implementing all system optimised adaptation options is estimated to be 720 million Jamaican dollars per year on average, representing a substantial saving for the utility and its customers, including low-income customers. We identify options that offer strong synergies between economic and equity objectives for both types of adaptation option. The proposed framework is established to support the business case for climate adaptation in the water supply sector and to prioritise across flood and drought mitigation options. We take a first step towards mainstreaming equity considerations in water supply sector optioneering frameworks by estimating the contribution of adaptation options towards reducing household costs for low-income customers.

Fast quasi-null-filling of radiation patterns for multiple solutions generation

Here we present an improved, rapid method for filling quasi-nulls in symmetrical radiation patterns synthesized by equispaced linear arrays, leading to the generation of multiple solutions. Considering the polynomial representation of the pattern, this null-filling is achieved by displacing the roots radially off the unit circle, keeping a constant displacement. This allows analyzing how the potential solutions vary with the quasi-uniform filling and the associated directivity loss. This method is based on the Cardano-Vieta relations, which link the coefficients of a complex Schelkunoff polynomial with its roots. As examples of application, we have considered a 20/100 element Dolph-Chebyshev pattern, with a spacing between the elements λ/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda / 2$$\\end{document}, side lobe level of − 20/− 28 dB and three inner sidelobes at − 40/− 50 dB.

How climate change is damaging the US ski industry

ABSTRACT Since the mid-twentieth century, warming in mountain regions has outpaced the global rate, with important regional implications for snowpacks and the ski industry. Recent climate litigation by communities in the State of Colorado signals the need to assess how observed changes in climate may have damaged the ski industry. This study presents a novel application of the SkiSim2.0 ski operations model at 226 ski areas across 4 US regional ski markets to assess what the ski industry could have looked like if post-1970s anthropogenic climate change had not occurred. Relative to 1960–1979, modelled average ski seasons (with snowmaking) in the 2000–2019 period have shortened between 5.5 and 7.1 days. National direct economic losses associated with lost skier visits and increased snowmaking costs are estimated at US$252 million annually. For the 2050s, regional ski seasons are projected to shorten between 14–33 days (low emissions) and 27–62 days (high emissions). The associated national direct economic losses range from US$657 to 1352 million annually. Climate change is an evolving business reality for the US ski industry. The economic damage already done is clear and the extent of future damages is dependent on the success of Paris Climate Agreement.

The first year’s impact of the full-scale war on Ukrainian business

The relevance of the research is stipulated by the need to analyse the impact of military operations on the economic environment of Ukraine, in particular on business, constituting a significant part of the Ukrainian economy. The purpose of the article was to study the first year’s impact of the full-scale war in Ukraine on the state of Ukrainian business, to identify the main challenges and opportunities faced by business during the war, and to provide recommendations for stabilizing the economic environment in Ukraine. Methods of secondary information analysis have been used to obtain a generalized picture of the impact of military operations on Ukrainian business by analysing the reports of international and Ukrainian organizations. Statistical analysis has become the basis for evaluating dynamics and key economic indicators. The state of Ukrainian business during the Russian-Ukrainian war has been analysed. The impact of the conflict on business has been studied and recommendations for stabilizing the economic environment in Ukraine have been provided. The dynamics of gross domestic product from 2013 to 2022 and the negative impact of the war on the economy have been analysed. The ways of business adaptation to new conditions, direct losses of the industrial sector and new opportunities for business during the war have been studied. State aid measures to support business and strategic directions for overcoming the crisis and restoring the economy after the war have been described. The results of the study give evidence of a significant negative impact of the Russian-Ukrainian war on Ukrainian business, which is traced in a fall in gross domestic product, a decrease in the level of investment, an increase in unemployment and infrastructure destruction. The proposed recommendations and development strategies include the need to strengthen state support for business, stimulate investment, reform the economy to diversify and increase its resistance to external shocks. The recommendations are the result of scientific analysis and can serve as a basis for practical application by enterprises during the war and after its end

The impact of neutral beam parameters on current drive and neutron yield in DEMO-FNS tokamak

DEMO-FNS (DEMO Fusion Neutron Source) will be a hybrid reactor designed to combine fusion and fission technologies. In a hybrid reactor the power is mainly produced by a fission blanket which is exposed to the neutron flux generated by confined fusion plasma used as a Fusion Neutron Source (FNS). The steady-state operation of the FNS is easier to achieve as compared to pure fusion reactors, allowing the FNS to be more compact. The DEMO-FNS will produce 40 MW of fusion power. The neutral beam injectors (NBI) are designed to provide a steady state plasma heating, rotation, fueling, current drive and neutron generation in DEMO-FNS. Four injector units will deliver 30 MW power in deuterium with energy Eb = 500 keV. The NBI concept and main components are inspired from ITER HNBI design implementing acceleration of negative ions with their neutralization on gas.The high density of injected power in DEMO-FNS leads to a very specific operation scenario with ahigher ratio of high-energy ions in the plasma with respect to conventional tokamaks, where the mainpart of neutron flux will result from fusion between hot-tail ions and relatively coldbackground. The current drive and neutron yield produced by the tangentially injected beam in asteady-state operation are strongly affected by magnetic configuration and plasma kineticprofiles. The fast ions deposition and performance in plasma are limited by the losses associatedwith the neutral beam shape and aiming. The main channels of direct beam losses includeshine-through losses, as well as fast ion orbital losses. The detailed evaluation of NB parametersand geometry effects is a necessary step of scenario optimization.BTR code (Beam Transmission or, in earlier versions, Beam Transmission with Reionization) is intended for injector beamlines study, and BTR detailed beam model can be also applied to perform a detailed analysis of beam losses and performance in plasma. The analysis of beam in plasma shows the ways towards higher values of beam driven current (NBCD) and neutral yield; the beam-in-plasma behaviour can be tuned for a given tokamak configuration. The NB tracing model workflow is implemented in the BTOR suite (Beam in TORoids). The results for DEMO-FNS are compared with the NBI performance in ITER tokamak, as both machines are beam-driven and implement a similar NBI concept.

Large-scale serological survey on Mycobacterium avium subsp. paratuberculosis infection in sheep and goat herds in Sicily, Southern Italy.

Paratuberculosis (PTB) is a worldwide chronic, contagious enteric disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) mainly affecting ruminant species. PTB is a WOAH-listed disease with direct and indirect economic losses in the livestock sector, negative impact on animal welfare and significant public health concerns. In spite of this, MAP prevalence in small ruminants is still unknown and the prevalence appears to be underestimated in many countries. The aim of this study is providing a first large-scale serological survey on MAP infection in small ruminants in Sicily, a region of Southern Italy with the 11.3 and 8.9% Italian national heritage of sheep and goats, respectively. For this purpose, we analyzed a total of 48,643 animals reared in 439 flocks throughout Sicily. MAP seroprevalence was estimated both at herd-level and animal-level within breeds reared in all the nine sampled provinces. Our results revealed a high overall apparent prevalence at herd-level of 71.8% in sheep and 60.8% in goat farms with an animal-level prevalence of 4.5 and 5.1% in sheep and goats, respectively. Significant statistical differences were found between the provinces and within the breeds both in sheep and goats. Our study provides the first large-scale serological survey on PTB infection in small ruminants in Sicily and showed a high prevalence of disease depending to the species, breed and province. This study represents the first step to better understand the MAP epidemiology in a typical Mediterranean breeding context, suggesting the need of in-depth study on the herds risk factors, including the eventual presence of candidate genes for resistance/susceptibility to PTB in native breeds.

Segmentation of Wheat Lodging Areas from UAV Imagery Using an Ultra-Lightweight Network

Crop lodging is an important cause of direct economic losses and secondary disease transmission in agricultural production. Most existing methods for segmenting wheat lodging areas use a large-volume network, which poses great difficulties for annotation and crop monitoring in real time. Therefore, an ultra-lightweight model, Lodging-U2NetP (L-U2NetP), based on a novel annotation strategy which crops the images before annotating them (Crop-annotation), was proposed and applied to RGB images of wheat captured with an unmanned aerial vehicle (UAV) at a height of 30 m during the maturity stage. In the L-U2NetP, the Dual Cross-Attention (DCA) module was firstly introduced into each small U-structure effectively to address semantic gaps. Then, Crisscross Attention (CCA) was used to replace several bulky modules for a stronger feature extraction ability. Finally, the model was compared with several classic networks. The results showed that the L-U2NetP yielded an accuracy, F1 score, and IoU (Intersection over Union) for segmenting of 95.45%, 93.11%, 89.15% and 89.72%, 79.95%, 70.24% on the simple and difficult sub-sets of the dataset (CA set) obtained using the Crop-annotation strategy, respectively. Additionally, the L-U2NetP also demonstrated strong robustness in the real-time detection simulations and the dataset (AC set) obtained using the mainstream annotation strategy, which annotates images before cropping (Annotation-crop). The results indicated that L-U2NetP could effectively extract wheat lodging and the Crop-annotation strategy provided a reliable performance which is comparable with that of the mainstream one.

ТРАНСФОРМАЦІЯ БІЗНЕС-МОДЕЛЕЙ ПІДПРИЄМСТВ В УМОВАХ ВІЙНИ

The purpose of the study is to determine the impact of changes in the micro and macro environment on business during a full-scale war and directions for modifying business models that ensure the survival and development of business structures. The methodological basis of the research is А. Osterwalder's and I. Pigneur’s approach to business modeling. In the study it was determined that the war caused the emergence of new consumer segments. There are displaced persons, the state or volunteers, consumers with specific needs due to the special circumstances created by the war. As a result of changes in the demographic, socio-economic characteristics of society, business must rethink the characteristics of existing market segments. The value proposition can be modified taking into account the growth of national self-awareness, an increase in psychological stress, and changes in consumer priorities in wartime conditions. Problems with the organization of physical movement of goods increase the relevance of e-commerce. There is a need to review the channels and quality of communications to attract consumers to form long-term relationships with them, because consumers are more particular about the content and timeliness of messages from sellers during a war. Review of key segments, value proposition prompts to make changes to the range of goods and services that ensure incomes, sales organization, payment methods. An increase in the cost of resources, primarily raw materials, direct loss of property, a decrease of availability of financial resources, and the loss of human capital during the war causes the need to review the priority of resources for the company, and the search for new ways of attracting them. Determination of key types of activities is carried out under the influence of adjustment of consumer segments and available resources. Since many businesses lose the ability to fulfill previously obligations, companies need to look for new key partners, and the increase in the price of resources and the drop in client incomes increases the urgency of cost optimization.

Pandemic‐induced De‐urbanization in Indonesia: Urban and Rural Impacts

In Indonesia, the negative health impact of COVID‐19 and the initial, direct loss of employment have been largest in urban, not rural areas. But the second‐round effects on labor markets have been very different. They have included a huge, empirically documented migration of newly unemployed urban workers from urban to rural areas, in urgent search of employment, food, and safety from the pandemic. We call this “de‐urbanization.” It placed the migrating workers in economic competition with the least skilled agricultural workers, expanding their numbers by almost 8%. By increasing the supply of unskilled farm labor, de‐urbanization depressed farm workers' real wages. Because the demand for farm labor is inelastic, the total wage income of these workers, aggregated across all unskilled farm laborers, declined. The households relying on this source of income are by far Indonesia's poorest. Similar outcomes may occur in other pandemic‐affected developing countries with large agricultural sectors.