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Purpose: Recent years have witness the pervasive supply disruptions and their impacts on supply chain performance. It is significant for enterprises to adopt comprehensive measures to cope with supply disruptions. The purpose of this study is to investigate how BI insurance make up the shortage of emergency supply and affect the expected profit of enterprises. Design/methodology: This study develops the penalty cost function on the basic of the financial costs caused by the interruption losses, introduces variables of BI insurance and operational measures, establishes the profit model with BI insurance or not. Findings: Through the proof and analysis, it is demonstrated that BI insurance can mitigate the adverse effect of the increasing cost for expected profit. And this study finds that the value of BI insurance is higher when interruption probability is lower and penalty coefficient is higher. Originality/value: In this study, it is investigated that the impact of business interruption (BI) insurance on supply disruptions and its complementary value against the higher purchase cost of emergency sourcing strategy. BI insurance is an efficient measure for supply interruption and should be adopted correctly to play a role in managing supply disruption risk.

Disruptive events that halt production can have severe business consequences if not appropriately managed. Business interruption (BI) insurance offers firms a financial mechanism for managing their exposure to disruption risk. Firms can also avail of operational measures to manage the risk. In this paper, we explore the relationship between BI insurance and operational measures. We model a manufacturing firm that can purchase BI insurance, invest in inventory, and avail of emergency sourcing. Allowing the insurance premium to depend on the firm's insurance and operational decisions, we characterize the optimal insurance deductible and coverage limit as well as the optimal inventory level. We prove that insurance and operational measures are not always substitutes, and we establish conditions under which they can be complements; that is, insurance can increase the marginal value of inventory and can increase the overall value of emergency sourcing. We also find that the value of insurance is higher for those firms less able to absorb financially significant disruptions. As disruptions become longer but rarer, the value of emergency sourcing increases, and the value of inventory and the value of insurance increase before eventually decreasing. This paper was accepted by Martin Lariviere, operations management.

The aim of this article was to analyze the underwriting dynamics and coverage extent in business interruption insurance, investigating the probability updating process during the pandemic. While the impact of the pandemic on the business insurance market in Brazil has not been quantified, this study fills that gap by identifying the pandemics effects on the business interruption line of business (LOB) and highlighting any policy reformulations. The relevance of this paper is examining how the insurance market perceives and reacts to unpredictable exogenous events, and offering insights into the behavior of economic agents under these conditions. The findings reveal that the pandemic significantly impacted the insurance market, particularly the business interruption LOB. This research provides behavioral evidence that could inform responses to future unexpected adverse events in the insurance sector. We used a two-stage panel data regressions, using official data from the Brazilian insurance market covering Jan/2003-Dec/2023, with a total of 25,333 observations from 180 insurers. The impact of the pandemic on underwriting decisions, premium collection, and claims within business interruption and other LOBs was estimated. During the pandemic, operations in the business interruption LOB and premium revenues showed a gradual decline. Initially, there was a 0.60% increase in claim payments, followed by a stabilization period. The pandemic's impact on the business interruption insurance market deviated from the overall insurance market trend. Evidence of the probability updating phenomenon was observed within this industry.

[...]they could not claim against either their material damage or business interruption ISR insurance sections. Look around, check their security, check their fire protection, check the construction of the buildings and show interest in what the client does and how they do it.\" \"Sometimes an indemnity period is required to cover future exposure, so you have to then look both retrospectively and going forward to give a concise analysis of what the business interruption policy should respond to if there's an insurance event.\" \"Customers need to know there is an underinsurance penalty in the event of a loss if the actual value at the time of the loss is typically more than the percentage allowed in the policy,\" he says.

This study examines whether income distribution in Thailand has a property of scale invariance or self-similarity across years. By using the data on income shares by quintile and by decile of Thailand from 1988 to 2021, the results from 306-pairwise Kolmogorov-Smirnov tests indicate that income distribution in Thailand is statistically scale-invariant or self-similar across years with p-values ranging between 0.988 and 1.000. Based on these empirical findings, this study would like to propose that, in order to change income distribution in Thailand whose pattern had been persisted for over three decades, the change itself cannot be gradual but has to be like a phase transition of substance in physics.

Martins and Caldas discuss the article titled \"Side Effects of the Pandemic: Impacts on the Business Interruption Insurance Market\" by João Vinicius Carvalho and Izadora Gomes. The article evaluates the effects of the COVID-19 pandemic on the business interruption insurance market using data from the Brazilian insurance sector. This pioneering study in Brazil quantifies the impact of this exogenous event on policy underwriting, premium volumes, and claims. The study addresses a critical gap in the literature by employing robust regression models to identify behavioral and economic changes in the sector. Its relevance is indisputable, as it provides empirical evidence and in-depth analyses of an unprecedented phenomenon in the insurance market, making a significant contribution to academic literature and regulatory practice.

Purpose Value chain analyses that help businesses build competitive advantage must include considerations of unpredictable shocks and stressors that can create costly business disruptions. Enriching value chain analysis with considerations of system resilience, meaning the ability to recover and adapt after adverse events, can reduce the imposed costs of such disruptions. Design/methodology/approach The paper provides a perspective on resilience as both an expansion and complement of risk analysis. It examines applications of both concepts within current value chain literature and within supply chain literature that may inform potential directions or pitfalls for future value chain investigations. Established frameworks from the broader field of resilience research are proposed for value chain resilience analysis and practice. Findings The synthesis reveals a need to expand value chain resilience analysis to incorporate phases of system disruption. Current explorations in the literature lack an explicit acknowledgement and understanding of system-level effects related to interconnectedness. The quantification methods proposed for value chain resilience analysis address these gaps. Originality/value Using broader resilience conceptualizations, this paper introduces the resilience matrix and three-tiered resilience assessment that can be applied within value chain analyses to better safeguard long-term business feasibility despite a context of increasing threats.

This paper studies the joint tail behavior of two randomly weighted sums ∑ i =1 m Θ i X i and ∑ j =1 n θ j Y j for some m, n ∈ ℕ ∪{∞}, in which the primary random variables { X i ; i ∈ ℕ} and { Y i ; i ∈ ℕ}, respectively, are real-valued, dependent and heavy-tailed, while the random weights {Θ i , θ i ; i ∈ ℕ} are nonnegative and arbitrarily dependent, but the three sequences { X i ; i ∈ ℕ}, { Y i ; i ∈ ℕ} and {Θ i , θ i ; i ∈ ℕ} are mutually independent. Under two types of weak dependence assumptions on the heavy-tailed primary random variables and some mild moment conditions on the random weights, we establish some (uniformly) asymptotic formulas for the joint tail probability of the two randomly weighted sums, expressing the insensitivity with respect to the underlying weak dependence structures. As applications, we consider both discrete-time and continuous-time insurance risk models, and obtain some asymptotic results for ruin probabilities.

The aim of this paper is to show how qualified investors in cat bonds can offer adequate pandemic business interruption protection in a comprehensive public–private coverage scheme. First, we propose a numerical model to expose how cat bonds can contribute to complement standard re/insurance by improving coverage of cedents even though risks are positively correlated during a pandemic. Second, we introduce double trigger pandemic business interruption cat bonds, which we name PBI bonds, and discuss their precise characteristics to provide efficient coverage. A first trigger should be pulled when the World Health Organization declares a Public Health Emergency of International Concern (PHEIC). The second trigger determines the payout of the bond based on the modelised business interruption losses of an industry in a country. We discuss moral hazard, basis risk, correlation and liquidity issues which are critical in the context of a pandemic. Third, we simulate the life of theoretical PBI bonds in the restaurant industry in France by using data gathered during the COVID-19 pandemic.

An important societal problem is that people underinsure against risks that are unlikely or occur in the far future, such as natural disasters and long-term care needs. One explanation is that uncertainty about the risk of non-reimbursement induces ambiguity averse and risk prudent decision makers to take out less insurance. We set up an insurance experiment to test this explanation. Consistent with the theoretical predictions, we find that the demand for insurance is lower when the nonperformance risk is ambiguous than when it is known and when decision makers are risk prudent. We cannot attribute the lower take-up of insurance to our measure of ambiguity aversion, probably because ambiguity attitudes are richer than aversion alone. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.