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In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated.

By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions.

The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole.

Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system.

This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.

The authors provide a comprehensive study on systemic risk of the banking sectors in the ASEAN-6 countries. In particular, they investigate the systemic risk dynamics and determinants of 49 listed banks in the region over the 2000–2018 period.

The authors employ the market-based SRISK measure of Brownlees and Engle (2017) to investigate the systemic risk of the ASEAN-6's banking sectors.

The authors find that the regional systemic risk fluctuates significantly and currently at par or higher level than that of the recent global financial crisis. Systemic risk is generally associated with banks that have bigger size, more traditional business models, lower quality in their loan portfolios, less profitable and with lower market-to-book values. However, these relationships vary significantly between ASEAN countries.

The research focuses on the systemic risk of ASEAN-6 countries. Therefore, the research results may lack generalizability to other countries.

The authors’ empirical evidence advocates the use of capital surcharges on the systemically important financial institutions. Although the region has been pushing to higher financial integration in recent years, the authors encourage the regional regulators to account for the idiosyncratic characteristics of their banking sectors in designing effective macroprudential policy to contain systemic risk.

This paper provides the first study on the systemic risk of the ASEAN-6 region. The empirical evidence on the drivers of systemic risk would be of interest to the regional regulators.

This paper sheds light on the impact of market risk measures on systemic risk. Market risk, which is captured by the volatility of stock market returns, is also decomposed into systematic and idiosyncratic risks.

The author uses the five-factor asset pricing model and systemic risk methodologies to derive market and systemic risk measures, respectively. Using a sample of 2,667 US banks for over 30 years and employing panel data estimation techniques, the author tests the said relationship.

It is shown that idiosyncratic risk can surge systemic risk, while systematic risk plays a less important role. Results survive a battery of tests, including different systemic risk measures, controlling causality and interacting with bank size, market fear and crisis periods.

These findings call for regulatory intervention, especially for large banks with high idiosyncratic risk.

This is the first paper that provides a more granular picture of the relationship between market and systemic risk from the US banking industry for more than 30 years.

The purpose of this paper, builds on previous studies that explored the research patterns over 15 years, is to consider the current status of the integration of Lean and Six Sigma. More specifically, this research addresses whether Lean and Six Sigma are stronger together and explores the reasons why Lean researchers and practitioners may be less likely to integrate Six Sigma in their work.

The research utilises a survey of 25 established and respected academics and practitioners from 16 countries. The questionnaire is analysed using a direct content approach and coded in NVivo.

The findings suggest that challenges may lie in the perception and understanding of statistics as well as short-term rather than long-term focus on improvement. The findings also suggest that academics and practitioners believe that Lean Six Sigma has developed over time and will continue to develop and improve as a methodology rather than being replaced with a new methodology.

The survey has a sample size of 25, albeit all respondents are established and very experienced practitioners and academics.

For organisations that are introducing or refreshing their continuous improvement initiatives, this research identifies some of the challenges and provides the opportunity to address them to maximise the opportunities for success and sustainability.

The value of this paper is that it further addresses the debate over the integration of Lean and Six Sigma for many organisations which still employ Lean alone, but beyond this it explores how they will continue to develop and whether they are a permanent edition to the quality management landscape or a transition to something else.

An increasing literature focuses on how Demand Responsive Transport (DRT) may contribute to improve public transport. However, qualitative studies about whether such services contribute to social inclusion are lacking. The aim is therefore to understand how citizens experience DRT services.

For this purpose, we compare the different local public transport solutions in three rural municipalities in Norway. One case represents a conventional public transport service with a school bus that is open for all. The two other cases represent DRT solutions with different characteristics in terms of how extensive the services are. The data are qualitative, gathered via interviews and focus groups.

We find that who the users are and their patterns of use differ between the cases. The more extensive the service is, the more popular it is – even to the extent that leisure clubs adapt their start and end times to the public transport routes. Moreover, the evidence suggests that door-to-door transport is crucial for the ability of many people of older age to travel.

The need for door-to-door services means that flexibility has to be incorporated into DRT schemes with fixed bus stops, if the aim is to cover all citizens.

The insights about how not only the users themselves experience different transport services, but also their relations, provide added value. Finally, we argue that, given among others the dispersion of transport responsibilities on different political levels and sectors, the DRT services have not been successful in solving efficiency issues.

The aim of this study is to determine the fracture behavior of wool felt and fabric based epoxy composites and their responses to electromagnetic waves.

Notched and unnotched tensile tests of composites made of wool only and hybridized with a glass fiber layer were carried out, and fracture behavior and toughness at macro scale were determined. They were exposed to electromagnetic waves between 8 and 18 GHz frequencies using two horn antennas.

The keratin and lignin layer on the surface of the wool felt caused lower values to be obtained compared to the mechanical values given by pure epoxy. However, the use of wool felt in the symmetry layer of the laminated composite material provided higher mechanical values than the composite with glass fiber in the symmetry layer due to the mechanical interlocking it created. The use of wool in fabric form resulted in an increase in the modulus of elasticity, but no change in fracture toughness was observed. As a result of the electromagnetic analysis, it was also seen in the electromagnetic analysis that the transmittance of the materials was high, and the reflectance was low throughout the applied frequency range. Hence, it was concluded that all of the manufactured materials could be used as radome material over a wide band.

Sheep wool is an easy-to-supply and low-cost material. In this paper, it is presented that sheep wool can be evaluated as a biocomposite material and used for radome applications.

The combined evaluation of felt and fabric forms of a natural and inexpensive reinforcing element such as sheep wool and the combined evaluation of fracture mechanics and electromagnetic absorption properties will contribute to the evaluation of biocomposites in aviation.

An aircraft engine control system consists of a large scale of control parameters and variables because of the complex structure of aero-engine. Monitoring and adjusting control variables and parameters such as detecting, isolating and reconfiguring the system faults/failures depend on the controller design. Developing a robust controller is based on an accurate mathematical model.

In this study, a small-scale turboprop engine is modeled. Simulation is carried out on MATLAB/Simulink for design and off-design operating conditions. Both steady-state and transient conditions (from idle to maximum thrust levels) are tested. The performance parameters of compressor and turbine components are predicted via trained Neuro-Fuzzy model (ANFIS) based on component maps. Temperature, rotational speed, mass flow, pressure and other parameters are generated by using thermodynamic formulas and conservation laws. Considering these calculated values, error calculations are made and compared with the cycle data of the engine at the related simulation conditions.

Simulation results show that the designed engine model’s simulation values have acceptable accuracy for both design and off-design conditions from idle to maximum power operating envelope considering cycle data. The designed engine model can be adapted to other types of gas turbine engines.

Different from other literature studies, in this work, a small-scale turboprop engine is modeled. Furthermore, for performance prediction of compressor and turbine components, ANFIS structure is applied.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

This paper aims to understand empirically how shares of standard and premium private label (PL) products affect a retailer’s marketing mix decisions toward national brands (NBs).

Using a comprehensive store-level data set covering 52 categories and 130 stores of two retailer chains during 2003-2009, this paper examines how shares of standard and premium PLs affect retailer marketing strategies for NB retail prices, promotions and product assortments. The empirical analysis uses a simultaneous equations model estimated by the generalized method of moments approach and controls for endogeneity between PL shares and NB decisions and potential confounding variables including consumer, manufacturer and retailer factors.

Standard PL shares are associated positively with NB retail prices and negatively with NB promotions and assortments. In contrast, premium PL shares are associated positively with NB retail prices, promotions and assortments.

The results indicate that retailers make strategic NB decisions through multitier PLs. Specifically, the evidence suggests that retailers use standard and premium PLs differently in promotion and assortment decisions toward NBs. NB manufacturers need to be cognizant of the increasing marketing power of retailers through their multitier PLs.

Prior research has mainly focused on the role of PLs as a strategic weapon to gain power in the channel and its impact on NB pricing decisions in a single PL context. After accounting for potential confounding factors (retailer, consumer and manufacturer) and endogeneity, the authors find empirical evidence that retailers appear to leverage standard and premium PLs differently in some marketing mix decisions toward NB. In particular, the results reveal PL performance to be a determinant of retailer NB assortment decisions.

This study aims to develop the governing differential equation and to analyze the free vibration of a rotating non-uniform beam having a flexible root and setting angle for variations in operating conditions and structural design parameters.

Hamiltonian principle is used to derive the flapwise bending motion of the structure, and the governing differential equations are solved numerically by using differential quadrature with satisfactory accuracy and computation time.

The results obtained by using the differential quadrature method (DQM) are compared to results of previous studies in the open literature to show the power of the used method. Important results affecting the dynamics characteristics of a rotating beam are tabulated and illustrated in concerned figures to show the effect of investigated design parameters and operating conditions.

The principal novelty of this paper arises from the application of the DQM to a rotating non-uniform beam with flexible root and deriving new governing differential equation including various parameters such as rotary inertia, setting angle, taper ratios, root flexibility, hub radius and rotational speed. Also, the application of the used numerical method is expressed clearly step by step with the algorithm scheme.