Catastrophes, like earthquakes, bring sudden and severe damage, causing fatalities, injuries, and property loss. This often triggers a rapid increase in insurance claims. These claims can encompass various types, such as life insurance claims for deaths, health insurance claims for injuries, and general insurance claims for property damage. For insurers offering multiple types of coverage, this surge in claims can pose a risk of financial losses or bankruptcy. One option for insurers is to transfer some of these risks to reinsurance companies. Reinsurance companies will assess the potential losses due to a catastrophe event, then issue catastrophe reinsurance contracts to insurance companies. This study aims to construct a valuation model for catastrophe reinsurance contracts that can cover claim losses arising from two types of insurance products. Valuation in this study is done using the Fundamental Theorem of Asset Pricing, which is the expected present value of the number of claims that occur during the reinsurance coverage period. The number of catastrophe events during the reinsurance coverage period is assumed to follow a Poisson process. Each impact of a catastrophe event, such as the number of fatalities and injuries that cause claims, is represented as random variables, and modeled using Peaks Over Threshold (POT). This study uses Clayton, Gumbel, and Frank copulas to describe various dependence characteristics between random variables. The parameters of the POT model and copula are estimated using Inference Functions for Margins method. After estimating the model parameters, Monte Carlo simulations are performed to obtain numerical solutions for the expected value of catastrophe reinsurance based on the Fundamental Theorem of Asset Pricing. The expected reinsurance value based on Monte Carlo simulations using Indonesian earthquake data from 1979–2021 is Rp 10,296,819,838.

Research has shown that understanding the fundamental of public support for carbon emission reduction policies may undermine policy formulation and implementation, yet the direction of influence and the transmission mechanism remain unclear. Using data from using data from 1482 questionnaires conducted in Hangzhou, China, this paper has examined a comprehensive model of the factors and paths influencing public support for carbon emission reduction policies, and evaluated the determinants and predictors of policy support regarding individual psychological perceptions, social-contextual perceptions, and perceptions of policy features. The results show that the variables in both the individual psychological perception and social contextual perception dimensions have no significant effect on carbon tax, however, be important constructure in carbon trading; in the policy characteristics perception dimension, both variables have a significant positive effect on both carbon tax and carbon trading, and are also the strongest predictors of policy support for carbon policies. Further evidence suggests that future policies could be more acceptable to residents by strengthening their environmental values, social norms can further arouse residents’ social responsibility to care about climate, and whether the policy is effective or fair to help residents realize the importance of the policy as well as the need for their participation and willingness to dedicate themselves to the mitigation of climate change.

This study explores the complex dynamics of handling augmented reality (AR) data in higher education in the United Arab Emirates (UAE). Although there is a growing interest in incorporating augmented reality (AR) to improve learning experiences, there are still issues in efficiently managing the data produced by these apps. This study attempts to understand the elements that affect AR data management by examining the relationship between the investigated variables: faculty readiness, technological limits, financial constraint, and student engagement on data management in higher education institutions in the UAE, building on earlier research that has identified these problems. The research analyzes financial constraints, technological infrastructure, and faculty preparation to understand their impact on AR data management. The study collected detailed empirical data on AR data management in UAE higher education environments using a quantitative research methods approach, surveys. The reasons for choosing this research method include cost-effectiveness, flexibility in questionnaire design, anonymity and confidentiality involved in the chosen methods. The results of this study are expected to enhance academic discourse by highlighting the obstacles and remedies to improving the efficiency of AR technology data management at higher education institutions. The findings are expected to enlighten decision-making in higher education institutions on maximizing AR technology’s benefits for improved learning outcomes.

Smart electric meters play a pivotal role in making energy systems decarbonized and automating the energy system. Smart electric meters denote huge business opportunities for both public and private companies. Utility players can manage the electricity demand more efficiently whereas customers can monitor and control the electricity bill through the adoption of smart electric meters. The study examines the factors affecting the adoption intention of smart electric meters in Indian households. This study draws a roadmap that how utility providers and customers can improve the smart electric meters adoption. The study has five independent variables (performance expectancy, effort expectancy, social influence, environmentalism, and hedonic motivation) and one dependent variable (adoption intention). The sample size for the study is four hundred and sixty-two respondents from Delhi and the National Capital Region (NCR). The data was analysed using structural equation modelling (SEM). The results of this study have confirmed that performance expectancy, environmentalism, and social influence have a significant impact on the intention of adopting smart electric meters. Therefore, utility providers can improve their strategies to attract more customers to adopt smart electric meters by focusing more on the performance of smart electric meters and by making them environmentally friendly. This research offers meaningful insights to both customers and utility providers to make energy systems decarbonized and control energy consumption.

Purpose: The paper aims to study the methodology and functional of Internal Audit (IA) during the transition to remote working methods necessitated by the COVID-19 pandemic crisis period. Design/methodology/approach: Data are collected over a sample of 352 internal audit departments in retail SMEs distributed in the Gulf Cooperation Council (GCC) region. The six variables are measured using a reflective model. An exploratory factor analysis is applied to gauge the measurement model’s validity and reliability. Findings: The research findings revealed that internal auditing within the Kingdom of Saudi Arabia (KSA) and the Qatari retail sector is not sufficiently advanced. The focus of internal auditing primarily revolves around compliance audits rather than performance audits, thereby limiting their degree of agility and strategy which negatively affects the IA methodology. Conversely, for the United Arab Emirates (UAE) retail companies the research hypotheses were validated showing an IA functions evolution, an IA reassurance and IA agility that are conducted throughout a remote working and a strategic design that affect positively IA working methodology. Originality: The originality impregnates by the fact that reviews of traditional audit working methods were updated and shaped according to the deficiencies that couldn’t be identified during a pre COVID-19 period. A traditional audit plan may not work in this situation. The originality of the study consists of estimating IA methodological review through an agile approach that provides internal reassurance and risk attenuation.

Overwhelming studies unanimously agreed that preservation of the environment is a central climax in the discourse of green banking. There is a growing interest in exploring green banking practices for fostering financial inclusion, economic growth and sustainable development as part of Vision 2030 in Saudi Arabia. There are insufficient studies that examine this in the context of Saudi Arabia. This study aims at exploring the potential of green banking in order to attain sustainable banking and financial inclusion in achieving vision 2030in the country. Qualitative content analysis is used as a methodology of the study. Data were gathered through different sources such as: Web of Science (WOS), related journals, newspapers, published references, research papers, library sources and environmental organizations reports. It is indicated that green banking initiatives can be instrumental in fostering sustainable economic and environmental development in the Kingdom. The paper highlighted various activities of green banking such as: renewable and clean energy, financing green agriculture/food security, high-quality infrastructure among others. Nonetheless, some impediments to the green banking practices such as: risks facing green banks, poor quality of financial services among others are also mentioned in this paper. The paper proffers solutions to the challenges impeding green banking practices. In conclusion, the financial and banking industries in Saudi Arabia has been proving reform of the sector through greening economy. It is there suggested that the stakeholders and policymakers should provide efficient and effective technical, operational legal frameworks for enhancing green economy in achieving Vision 2030 in the country.

The progress of a country can be directly related to the education level of its countrymen. Over a time period, the internet has become a game changer for the world of disseminating education. From 2000 onwards, the scale of online courses has increased manyfold. The main reason for this growth in online learning can be attributed to the flexibility in course delivery and scheduling. Through this study, the authors analyzed the challenges in adopting Online degree programs in higher education in management in India. The authors used Focus Group discussions, semi-structured interviews, and in-depth interviews to collect the data from the various stakeholders. Thematic analysis was used to analyze the responses. Considering the challenges and constraints in India, the authors proposed a sustainable model for implementation. Based on the viewpoints of the different stakeholders, the authors find that online degrees can be instrumental in bringing inclusivity in higher education. There are obvious constraints like a lack of IT infrastructure, the inexperience of faculty in online pedagogy, and the need for more expertise in the administration of online programs by existing universities. However, using SWAYAM as a platform can overcome most of these constraints, as it reduces the burden on individual universities. Hence, the authors proposed models where SWAYAM (technology platform) and Universities (academic partners) can come together to provide a sustainable education model.