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Article
Publication date: 28 June 2018

Shun Chen, Shiyuan Zheng and Hilde Meersman

The occurrence and unpredictability of speculative bubbles on financial markets, and their accompanying crashes, have confounded economists and economic historians worldwide. The…

1398

Abstract

Purpose

The occurrence and unpredictability of speculative bubbles on financial markets, and their accompanying crashes, have confounded economists and economic historians worldwide. The purpose of this paper is to diagnose and detect the bursting of shipping bubbles ex ante, and to qualify the patterns of shipping price dynamics and the bubble mechanics, so that appropriate counter measures can be taken in advance to reduce side effects arising from bubbles.

Design/methodology/approach

Log periodic power law (LPPL) model, developed in the past decade, is used to detect large market falls or “crashes” through modeling of the shipping price dynamics on a selection of three historical shipping bubbles over the period of 1985 to 2016. The method is based on a nonlinear least squares estimation that yields predictions of the most probable time of the regime switching.

Findings

It could be concluded that predictions by the LPPL model are quite dependent on the time at which they are conducted. Interestingly, the LPPL model could have predicted the substantial fall in the Baltic Dry Index during the recent global downturn, but not all crashes in the past. It is also found that the key ingredient that sets off an unsustainable growth process for shipping prices is the positive feedback. When the positive feedback starts, the burst of bubbles in shipping would be influenced by both endogenous and exogenous factors, which are crucial for the advanced warning of the market conversion.

Originality/value

The LPPL model has been first applied into the dry bulk shipping market to test a couple of shipping bubbles. The authors not only assess the predictability and robustness of the LPPL model but also expand the understanding of the model and explain patterns of shipping price dynamics and bubble mechanics.

Details

Maritime Business Review, vol. 3 no. 2
Type: Research Article
ISSN: 2397-3757

Keywords

Available. Content available
Article
Publication date: 24 October 2018

Shiyuan Zheng and Shun Chen

This study aims to propose a theoretical model to characterize the optimal forward freight agreement (FFA) procurement strategies and investigate the determinants of FFA trading…

2136

Abstract

Purpose

This study aims to propose a theoretical model to characterize the optimal forward freight agreement (FFA) procurement strategies and investigate the determinants of FFA trading activities from a new cross-market perspective.

Findings

A two-step model specification is used to empirically test the theoretical results for the Capesize, Panamax and Supramax sectors. It is found that spot demand has a positive relation with FFA trading volume for all three sectors. Moreover, spot demand volatility has a negative relation, while the correlation between spot demand and spot rate has a positive relation with FFA trading volume for the Capesize and Panamax sectors.

Originality/value

The results show that the expected spot demand is scaled by a “quantity premium,” which is the product of a demand covariance term, a demand riskiness term and a demand volatility term. This can be used by the traders in the FFA market to construct their hedging strategies.

Details

Maritime Business Review, vol. 3 no. 3
Type: Research Article
ISSN: 2397-3757

Keywords

Available. Content available
Article
Publication date: 8 August 2018

Emrah Bulut, Okan Duru and T.L. Yip

386

Abstract

Details

Maritime Business Review, vol. 3 no. 2
Type: Research Article
ISSN: 2397-3757

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Article
Publication date: 27 November 2024

Shiyuan Zhang, Xiaoxue Zheng and Fu Jia

The carbon complementary supply chain (CCSC) is a collaborative framework that facilitates internal carbon credit trading agreements among supply chain agents in compliance with…

117

Abstract

Purpose

The carbon complementary supply chain (CCSC) is a collaborative framework that facilitates internal carbon credit trading agreements among supply chain agents in compliance with prevailing carbon regulations. Such agreements are highly beneficial, prompting agents to consider joint investment in emission reduction initiatives. However, capital investments come with inevitable opportunity costs, compelling agents to weigh the potential revenue from collaborative investments against these costs. Thus, this paper mainly explores carbon abatement strategies and operational decisions of the CCSC members and the influence of opportunity costs on the strategic choice of cooperative and noncooperative investment.

Design/methodology/approach

The authors propose a novel biform game-based theoretical framework that captures the interplay of pricing competition and investment cooperation among CCSC agents and assesses the impact of opportunity costs on CCSC profits and social welfare. Besides, the authors also compare the biform game-based collaborative scenario (Model B) to the noncooperative investment scenario (Model N) to investigate the conditions under which collaborative investment is most effective.

Findings

The biform game-based collaborative investment strategy enhances the economic performance of the traditional energy manufacturer, who bears the risk of opportunity costs, as well as the retailer. Additionally, it incentivizes the renewable energy manufacturer to improve environmental performance through renewable projects.

Originality/value

This research contributes significantly by establishing a theoretical framework that integrates the concepts of opportunity costs and biform game theory, offering new insights into the strategic management of carbon emissions within supply chains.

Details

Industrial Management & Data Systems, vol. 125 no. 2
Type: Research Article
ISSN: 0263-5577

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Article
Publication date: 9 January 2025

Debiao Meng, Peng Nie, Shiyuan Yang, Xiaoyan Su and Chengbo Liao

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea…

42

Abstract

Purpose

As a clean and renewable energy source, wind energy will become one of the main sources of new energy supply in the future. Relying on the stable and strong wind resources at sea, wind energy has great potential to become the primary energy. As a critical part of the wind turbine, the gearbox of a wind turbine often bears a large external load. Especially at sea, due to the effects of ocean corrosion, waves and wind, the burden of the wind turbine gearbox is greater, which brings great challenges to its reliability analysis. This study aims to systematically review the reliability research in wind turbine gearboxes and guide future research directions and challenges.

Design/methodology/approach

This study systematically reviews some design requirements and reliability analysis methods for wind turbine gearboxes. Then, it summarizes previous studies on wind load uncertainty modeling methods, including the processing of wind measurement data and the summary of three different classifications of random wind speed prediction models. Finally, existing reliability analysis studies on two major parts of the gearbox are described and summarized.

Findings

First, the basic knowledge of wind turbine gearboxes and their reliability analysis is introduced. The requirements and reliability analysis methods of wind turbine gearboxes are explained. Then, the processing methods of wind measurement data and three different random wind speed prediction models are described in detail. Furthermore, existing reliability analysis studies on two common parts of wind turbine gearboxes, gears and bearings, are summarized and classified, including a summary of bearing failure modes. Finally, three possible future research directions for wind turbine gearbox reliability analysis are discussed, namely, reliability research under the influence of multiple factors on gears, damage indicators of bearing failure modes and quantitative evaluation criteria for the overall dynamic characteristics of offshore wind turbine gearboxes and a summary is also given.

Originality/value

This paper aims to systematically introduce the relevant contents of wind turbine gearboxes and their reliability analysis. The contents of wind speed data processing, predictive modeling and reliability analysis of major components are also comprehensively reviewed, including the classification and principle introduction of these contents.

Details

International Journal of Structural Integrity, vol. 16 no. 1
Type: Research Article
ISSN: 1757-9864

Keywords

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Article
Publication date: 2 January 2024

Xu Li, Zeyu Xiao, Zhenguo Zhao, Junfeng Sun and Shiyuan Liu

To explore the economical and reasonable semi-rigid permeable base layer ratio, solve the problems caused by rainwater washing over the pavement base layer on the slope, improve…

77

Abstract

Purpose

To explore the economical and reasonable semi-rigid permeable base layer ratio, solve the problems caused by rainwater washing over the pavement base layer on the slope, improve its drainage function, improve the water stability and service life of the roadbed pavement and promote the application of semi-rigid permeable base layer materials in the construction of asphalt pavement in cold regions.

Design/methodology/approach

In this study, three semi-rigid base course materials were designed, the mechanical strength and drainage properties were tested and the effect and correlation of air voids on their performance indexes were analyzed.

Findings

It was found that increasing the cement content increased the strength but reduced the air voids and water permeability coefficient. The permeability performance of the sandless material was superior to the dense; the performance of the two sandless materials was basically the same when the cement content was 7%. Overall, the skeleton void (sand-containing) type gradation between the sandless and dense types is more suitable as permeable semi-rigid base material; its gradation is relatively continuous, with cement content? 4.5%, strength? 1.5 MPa, water permeability coefficient? 0.8 cm/s and voids of 18–20%.

Originality/value

The study of permeable semi-rigid base material with large air voids could help to solve the problems of water damage and freeze-thaw damage of the base layer of asphalt pavements in cold regions and ensure the comfort and durability of asphalt pavements while having good economic and social benefits.

Details

International Journal of Structural Integrity, vol. 15 no. 1
Type: Research Article
ISSN: 1757-9864

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Article
Publication date: 23 May 2023

Shiyuan Yang, Debiao Meng, Hongtao Wang, Zhipeng Chen and Bing Xu

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile…

187

Abstract

Purpose

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

Design/methodology/approach

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

Findings

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Originality/value

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

Details

International Journal of Structural Integrity, vol. 14 no. 3
Type: Research Article
ISSN: 1757-9864

Keywords

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Article
Publication date: 15 January 2025

Xumei Lin, Peng Wang, Shiyuan Wang and Jiahui Shen

The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion…

15

Abstract

Purpose

The purpose of this paper is to investigate the accurate monitoring and assessment of steel bar corrosion in concrete based on deep learning multi-sensor information fusion method. The paper addresses the issue of traditional corrosion assessment models relying on sufficient data volume and low evaluation accuracy under small sample conditions.

Design/methodology/approach

A multi-sensor integrated corrosion monitoring equipment for reinforced concrete is designed to detect corrosion parameters such as corrosion potential, current, impedance, electromagnetic signal and steel bar stress, as well as environmental parameters such as internal temperature, humidity and chloride ion concentration of concrete. To overcome the small amount of monitoring data and improve the accuracy of evaluation, an improved Siamese neural network based on the attention mechanism and multi-loss fusion function is proposed to establish a corrosion evaluation model suitable for small sample data.

Findings

The corrosion assessment model has an accuracy of 98.41%, which is 20% more accurate than traditional models.

Practical implications

Timely maintenance of buildings according to corrosion evaluation results can improve maintenance efficiency and reduce maintenance costs, which is of great significance to ensure structural safety.

Originality/value

The corrosion monitoring equipment for reinforced concrete designed in this paper can realize the whole process of monitoring inside the concrete. The proposed corrosion evaluation model for reinforced concrete based on Siamese neural network has high accuracy and can provide a more accurate assessment model for structural health testing.

Details

Anti-Corrosion Methods and Materials, vol. 72 no. 2
Type: Research Article
ISSN: 0003-5599

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Article
Publication date: 5 July 2022

Debiao Meng, Shiyuan Yang, Chao He, Hongtao Wang, Zhiyuan Lv, Yipeng Guo and Peng Nie

As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex…

768

Abstract

Purpose

As an advanced calculation methodology, reliability-based multidisciplinary design optimization (RBMDO) has been widely acknowledged for the design problems of modern complex engineering systems, not only because of the accurate evaluation of the impact of uncertain factors but also the relatively good balance between economy and safety of performance. However, with the increasing complexity of engineering technology, the proposed RBMDO method gradually cannot effectively solve the higher nonlinear coupled multidisciplinary uncertainty design optimization problems, which limits the engineering application of RBMDO. Many valuable works have been done in the RBMDO field in recent decades to tackle the above challenges. This study is to review these studies systematically, highlight the research opportunities and challenges, and attempt to guide future research efforts.

Design/methodology/approach

This study presents a comprehensive review of the RBMDO theory, mainly including the reliability analysis methods of different uncertainties and the decoupling strategies of RBMDO.

Findings

First, the multidisciplinary design optimization (MDO) preliminaries are given. The basic MDO concepts and the corresponding mathematical formulas are illustrated. Then, the procedures of three RBMDO methods with different reliability analysis strategies are introduced in detail. These RBMDO methods were proposed for the design optimization problems under different uncertainty types. Furtherly, an optimization problem for a certain operating condition of a turbine runner blade is introduced to illustrate the engineering application of the above method. Finally, three aspects of future challenges for RBMDO, namely, time-varying uncertainty analysis; high-precision surrogate models, and verification, validation and accreditation (VVA) for the model, are discussed followed by the conclusion.

Originality/value

The scope of this study is to introduce the RBMDO theory systematically. Three commonly used RBMDO-SORA methods are reviewed comprehensively, including the methods' general procedures and mathematical models.

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Article
Publication date: 5 May 2020

Jiahong He

With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the…

738

Abstract

Purpose

With the analysis of the causes of corruption, this study aims to investigate specific anti-corruption measures that can be implemented to reform the political system and the social climate of China.

Design/methodology/approach

This study examines 97 severe corruption cases of high-ranking officials in China, which occurred between 2012 and 2015. As this insinuates that both institutional and social corruption are major problems in China, the analysis delves into multiple facts of corruption, including different types, four primary underlying causes, and suggestions regarding the implementation of three significant governmental shifts that focus on investigation, prevention tactics and legal regulations.

Findings

China’s corruption is not only individual-based but also it has developed into institutional corruption and social corruption. Besides human nature and instinct, the causes of corruption can be organised into four categories, namely, social customs, social transitions, institutional designs and institutional operations. For the removed high-ranking officials, the formation of interest chains was an important underlying cause behind their corruption.

Originality/value

This study makes a significant contribution to the literature because this study provides a well-rounded approach to a complex issue by highlighting the significance of democracy and the rule of law as ways to regulate human behaviour to combat future corruption.

Details

Journal of Financial Crime, vol. 27 no. 3
Type: Research Article
ISSN: 1359-0790

Keywords

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