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This study aims to align the objectives of key stakeholders by developing an integrated framework for high-impact natural disaster risk management. High-impact natural disasters have emerged as one of the most challenging policy issues.

The authors have applied the thematic text analysis for analysing the list of questions essential to develop an integrated framework. For theory, the authors have used the theoretical framework of collaborative governance.

The current work explains how to identify key stakeholders. Furthermore, it describes the framework to fit stakeholders' actions into the actionable components of risk management. Additionally, this framework also helps the firms that fall under the category of the industries “in the proximity of risks” and “the support industries” in modifying their role in the context of natural disaster risk.

The limitation of this framework is that the authors relied on commonly occurring natural disaster risks to develop the framework. Therefore, risk-specific aspects are less likely to be thoroughly covered in this framework. However, this limitation is not directly impacting the goal of this study. Additionally, in the future more comprehensive framework with the additional element in the existing framework can overcome these limitations.

The findings of the study offer insights that can be useful for policymakers in developing various preventive strategies. Managers can use the results and align their objectives with policy goals.

Socially, if communities try to design local risk management strategies, this framework would be helpful.

This study illustrates the role of objective alignment in high-impact risk management. This study is crucial in extending current knowledge on high-impact natural disaster risk management.

The US-China trade war has brought forth the problem of balance of trade not only for them, but also for many other economies in the world. However, all the commodity segments are not equally affected and thus, the segment-wise trade analysis of commodities can bring up many valuable insights, vital for policy formulation process. Despite this, existing literature barely covered this aspect as a focal research. Therefore, this chapter has carried out segment-wise analysis of commodity classes popular in international trade discussions for the United States and China since the trade dispute intensified between them. In this chapter, we have built an argument around three commodity-segments which are popular in international trade studies namely, the raw material segment, semi-finished goods segment, and finished goods segments. While doing this analysis, we majorly focused on monopolistic power of economies in different commodity segments. We found that while in the segment of raw material, mostly cost is driving the trade, in the finished goods segment, variety and innovations are the key drivers that can boost trade by discovering new consumption spaces.

Education transmits knowledge and abilities that are essential for any society’s socioeconomic progress. It improves the quality of life by providing both individuals and civilizations with several advantages. In this regard, women’s education is critical as they spend longer time with children than men. Despite the fact that education plays an immense role in overall wellbeing of society, in India, there are fewer educational opportunities available to young women than to young men. The gender bias that persists in Indian education and professional training is evident even in the richest countries in the world. In this regard, this study focuses on this intergenerational transmission of knowledge from the mother to her progenies in Karimganj District of Assam using the data from the household level primary survey. This study examines mothers’ educational profiles and ascertains the extent to which their education influence their children’s educational attainments. The results show that woman’s education has a direct role in enhancing the overall welfare of children and, thus, indirectly improves the economic status of the family. The results provide definite causal connections between a mother’s education and children’s educational attainment.

The systematic risks related to credit financing has received significant attention in the academic domain during and after any financial crisis. However, the role of insurance has not been adequately studied in the context of crises. The extant literature also shows that the scale of credit financing depends upon the availability of credit insurance and on the policy orientation. Past evidence shows that demand for credit insurance was significantly high during the crisis period. Therefore, this chapter proposes to study the role of various combinations of these two aspects near the period of crisis. The findings of this chapter are based on the outcomesof previous research articles on these topics. The research articles are gathered from various online databases for the years 2000–2014 for the G7 economies. This chapter has alsoincluded facts from contextual policy documents on monetary and fiscal policies where it finds them necessary. Broadly, this chapter describes the role of policies when two mutually dependent industries interact and adversely impact market equilibrium.

A new framework to support the national and local capacity building plan for disaster risk management (DRM) in Cameroon is presented. For the past 30 years, after the general re-organisation of the civil protection department, capacity building programmes for DRM has been solely carried out for and by the Ministry of Territorial Administration and the Department of Civil Protection. The exclusion of businesses, civil society and community participation, among others, has been the main obstacle to capacity building programmes undertaken for DRM. The paper aims to discuss these issues.

Based on interviews conducted among 200 informants by means of a process of participatory monitoring and evaluation as well as a duo capacity building workshop for DRM held in August 2017 in Yaoundé, this paper evaluated existing capacity building programmes for DRM in Cameroon.

Findings show that the greater portion of government representatives within the public administration lack capacity to address DRM initiatives at the local and national levels of governance. While recommending DRM programmes as a necessity for integration within civil administrative curriculum, this paper proposes six elements to address capacity building gaps for DRM in Cameroon.

The results demonstrate critical gaps in capacity building aimed at DRM, especially where single ministry or department monopolises DRM. The findings provide the government with a useful tool to review its national strategy for a disaster reduction policy and the drawing up of a national intervention plan.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs).

This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms.

The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age.

The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.