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Article
Publication date: 13 August 2021

Yang Zhao, Jin-Ping Lee and Min-Teh Yu

Catastrophe (CAT) events associated with natural catastrophes and man-made disasters cause profound impacts on the insurance industry. This research thus reviews the impact of CAT…

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Abstract

Purpose

Catastrophe (CAT) events associated with natural catastrophes and man-made disasters cause profound impacts on the insurance industry. This research thus reviews the impact of CAT risk on the insurance industry and how traditional reinsurance and securitized risk-transfer instruments are used for managing CAT risk.

Design/methodology/approach

This research reviews the impact of CAT risk on the insurance industry and how traditional reinsurance and securitized risk-transfer instruments are used for managing CAT risk. Apart from many negative influences, CAT events can increase the net revenue of the insurance industry around CAT events and improve insurance demand over the post-CAT periods. The underwriting cycle of reinsurance causes inefficiencies in transferring CAT risks. Securitized risk-transfer instruments resolve some inefficiencies of the reinsurance market, but are subject to moral hazard, basis risk, credit risk, regulatory uncertainty, etc. The authors introduce some popular securitized solutions and use Merton's structural framework to demonstrate how to value these CAT-linked securities. The hybrid solutions by combining reinsurance with securitized CAT instruments are expected to offer promising applications for CAT risk management.

Findings

The authors introduce some popular securitized solutions and use Merton's structural framework to demonstrate how to value these CAT-linked securities. The hybrid solutions by combining reinsurance with securitized CAT instruments are expected to offer promising applications for CAT risk management.

Originality/value

This research reviews a broad array of impacts of CAT risks on the (re)insurance industry. CAT events challenge (re)insurance capacity and influence insurers' supply decisions and reconstruction costs in the aftermath of catastrophes. While losses from natural catastrophes are the primary threat to property–casualty insurers, the mortality risk posed by influenza pandemics is a leading CAT risk for life insurers. At the same time, natural catastrophes and man-made disasters cause distinct impacts on (re)insures. Man-made disasters can increase the correlation between insurance stocks and the overall market, and natural catastrophes reduce the above correlation. It should be noted that huge CAT losses can also improve (re)insurance demand during the postevent period and thus bring long-term effects to the (re)insurance industry.

Details

China Finance Review International, vol. 11 no. 4
Type: Research Article
ISSN: 2044-1398

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Book part
Publication date: 30 June 2023

Lisa M. Given, Donald O. Case and Rebekah Willson

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Abstract

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Looking for Information
Type: Book
ISBN: 978-1-80382-424-6

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Book part
Publication date: 2 December 2024

Vítor Corado Simões, John Cantwell and Philippe Gugler

Abstract

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The History of EIBA: A Tale of the Co-evolution between International Business Issues and a Scholarly Community
Type: Book
ISBN: 978-1-83608-665-9

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Article
Publication date: 16 July 2021

Zhao Yaoteng and Li Xin

The purpose of this paper is to explore the sustainable development strategy of green finance under the background of big data.

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Abstract

Purpose

The purpose of this paper is to explore the sustainable development strategy of green finance under the background of big data.

Design/methodology/approach

From the perspective of big data, this paper uses quantitative and qualitative analysis methods to judge the correlation among green finance, environmental supervision and financial supervision. Green finance gives the entropy method to calculate the score of green finance and environmental regulation, and establishes the spatial lag model under the double fixed effects of time and space.

Findings

Spatial autocorrelation test shows that economic spatial weight matrix has obvious spatial effect on green innovation. Through the model selection test, the space lag model with fixed time and space is selected. The regression coefficients of green finance, environmental regulation and their interaction are 0.1598, 0.0541 and 0.1763, respectively, which significantly promote green innovation. The regression coefficients of openness, higher education level and per capita GDP are 0.0361, 0.0819 and 0.0686, respectively, which can significantly promote green innovation.

Originality/value

In view of the current situation of large-scale application of big data technology in green innovation of domestic energy-saving and environmental protection enterprises, this paper establishes a fixed time lag evaluation model of green innovation. M-test statistics show that the original hypothesis with no obvious spatial effect is rejected.

Details

Journal of Enterprise Information Management, vol. 35 no. 4/5
Type: Research Article
ISSN: 1741-0398

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Book part
Publication date: 21 July 2022

Ian Ruthven

Free Access. Free Access

Abstract

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Dealing With Change Through Information Sculpting
Type: Book
ISBN: 978-1-80382-047-7

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Article
Publication date: 4 June 2024

Tuan Anh Nguyen and Jamshed Iqbal

Design a novel optimal integrated control algorithm for the automotive electric steering system to improve the stability and adaptation of the system.

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Abstract

Purpose

Design a novel optimal integrated control algorithm for the automotive electric steering system to improve the stability and adaptation of the system.

Design/methodology/approach

Simulation and calculation.

Findings

The output signals follow the reference signal with high accuracy.

Originality/value

The optimal integrated algorithm is established based on the combination of PID and SMC. The parameters of the PID controller are adjusted using a fuzzy algorithm. The optimal range of adjustment values is determined using a genetic algorithm.

Details

Engineering Computations, vol. 41 no. 4
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 28 November 2019

Tingting Zhao, Y.T. Feng and Yuanqiang Tan

The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing…

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Abstract

Purpose

The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing characterising system based on principal component analysis (PCA) to quantitatively reveal some fundamental features of spherical particle packings in three-dimensional.

Design/methodology/approach

Gaussian quadrature is adopted to obtain the volume matrix representation of a particle packing. Then, the digitalised image of the packing is obtained by converting cross-sectional images along one direction to column vectors of the packing image. Both a principal variance (PV) function and a dissimilarity coefficient (DC) are proposed to characterise differences between different packings (or images).

Findings

Differences between two packings with different packing features can be revealed by the PVs and DC. Furthermore, the values of PV and DC can indicate different levels of effects on packing caused by configuration randomness, particle distribution, packing density and particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach.

Originality/value

Develop an alternative novel approach to quantitatively characterise sphere packings, particularly their differences.

Details

Engineering Computations, vol. 37 no. 3
Type: Research Article
ISSN: 0264-4401

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Book part
Publication date: 7 December 2020

Tyler Wry and Rodolphe Durand

Our editorial argues that categories theory can be advanced by embracing heuristics research, and the insight that audiences often evaluate items based on multiple valued…

Abstract

Our editorial argues that categories theory can be advanced by embracing heuristics research, and the insight that audiences often evaluate items based on multiple valued criteria. Thus, rather than building on extant theory – which suggests that categories embody specific evaluative criteria, or that audiences operate according to a set “theory of value” – the authors argue that hybrids research would benefit from attending to the underlying processes that actors use to weigh and balance the diverse considerations that guide their decisions. The authors define and discuss three commonly used heuristics (satisficing, lexicographic preferences, and elimination by aspects), and show how these might lead audiences to support different types of hybrid entities.

Details

Organizational Hybridity: Perspectives, Processes, Promises
Type: Book
ISBN: 978-1-83909-355-5

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Article
Publication date: 22 April 2022

Lijun Shang, Qingan Qiu, Cang Wu and Yongjun Du

The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product…

153

Abstract

Purpose

The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability during the warranty period. By extending the proposed warranty to the consumer's post-warranty maintenance model, besides the authors investigate two kinds of random maintenance policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating depreciation expense depending on working time, the cost rate is constructed for each random maintenance policy and some special cases are provided by discussing parameters in cost rates. Finally, sensitivities on both the proposed warranty and random maintenance policies are analyzed in numerical experiments.

Design/methodology/approach

The working cycle of products can be monitored by advanced sensors and measuring technologies. By monitoring the working cycle, manufacturers can design warranty policies to ensure product reliability performance and consumers can model the post-warranty maintenance to sustain the post-warranty reliability. In this article, the authors design a limited number of random working cycles as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability performance during the warranty period. By extending a proposed warranty to the consumer's post-warranty maintenance model, the authors investigate two kinds of random replacement policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating a depreciation expense depending on working time, the cost rate is constructed for each random replacement and some special cases are provided by discussing parameters in the cost rate. Finally, sensitivities to both the proposed warranties and random replacements are analyzed in numerical experiments.

Findings

It is shown that the manufacturer can control the warranty cost by limiting number of random working cycle. For the consumer, when the number of random working cycle is designed as a greater warranty limit, the cost rate can be reduced while the post-warranty period can't be lengthened.

Originality/value

The contribution of this article can be highlighted in two key aspects: (1) the authors investigate early warranties to ensure reliability performance of the product which executes successively projects at random working cycles; (2) by integrating random working cycles into the post-warranty period, the authors is the first to investigate random maintenance policy to sustain the post-warranty reliability from the consumer's perspective, which seldom appears in the existing literature.

Details

Journal of Quality in Maintenance Engineering, vol. 29 no. 2
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 23 December 2024

Jiaqi Liu, Jialong Jiang, Mingwei Lin, Hong Chen and Zeshui Xu

When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are…

12

Abstract

Purpose

When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are difficult to achieve a balance between rating prediction accuracy and complexity. Therefore, the purpose of this paper is to propose an accurate and effective model to predict users’ ratings of products for the accurate recommendation of products to users.

Design/methodology/approach

First, we introduce an attention mechanism that dynamically assigns weights to user preferences, highlighting key interaction information and enhancing the model’s understanding of user behavior. Second, a fold embedding strategy is employed to segment user interaction data, increasing the information density of each subset while reducing the complexity of the attention mechanism. Finally, a masking strategy is integrated to mitigate overfitting by concealing portions of user-item interactions, thereby improving the model’s generalization ability.

Findings

The experimental results demonstrate that the proposed model significantly minimizes prediction error across five real-world datasets. On average, the evaluation metrics root mean square error (RMSE) and mean absolute error (MAE) are reduced by 9.11 and 13.3%, respectively. Additionally, the Friedman test results confirm that these improvements are statistically significant. Consequently, the proposed model more accurately captures the intrinsic correlation between users and products, leading to a substantial reduction in prediction error.

Originality/value

We propose a novel collaborative filtering model to learn the user-item interaction matrix effectively. Additionally, we introduce a fold embedding strategy to reduce the computational resource consumption of the attention mechanism. Finally, we implement a masking strategy to encourage the model to focus on key features and patterns, thereby mitigating overfitting.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

Keywords

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