Search Results (14)

This paper introduces a Mixed Marginal Rates of Substitution (MMRS) approach for analyzing banking efficiency within a linear programming framework. For this purpose, a linear programming model is proposed that efficiently calculates Marginal Rates, revealing how partial input changes affect multiple outputs simultaneously. Applying this methodology to data from the Taiwanese banking system spanning 2010 to 2020 reveals diverse efficiency patterns across financial institutions. The analysis demonstrates that while increased financial inputs generally improve outputs, individual banks exhibit varying sensitivity to these changes. Some institutions were resilient to input fluctuations, while others showed marked sensitivity, particularly in loans and investments. As a result, the proposed MMRS framework provides a robust tool for analyzing indicator relationships within efficient units, offering valuable insights for tailored management strategies and policy formulation in the banking sector. The findings emphasize the importance of institution-specific approaches to enhancing banking efficiency and managing risk effectively, contributing to a more nuanced understanding of economic outcomes in the financial industry. Additionally, symmetry concepts in input–output relationships are suggested as a potential area for future research, offering a possible framework for identifying balanced efficiency patterns among banks. Full article

This study aimed to explore efficiency changes in Taiwan’s banking industry before and after the outbreak of coronavirus disease 2019 (COVID-19) by using the maximum slacks-based measure approach. The data, spanning from 2018 to 2021, categorized banks into three systems: state-owned, private, and foreign. Bank performance was measured from two perspectives: single-period evaluation (assessing bank performance in each year individually) and cross-period evaluation (assessing bank performance from 2018 to 2021 collectively). Inter-temporal changes in bank performance across the three banking systems were analyzed. The results indicated that only foreign banks rebounded rapidly after the COVID-19 outbreak, while the average performance of private banks remained stagnant, and state-owned banks performed worse than before the outbreak. Therefore, it is recommended that state-owned banks develop effective and rapid improvement policies to address major emergencies. Additionally, the study found that inefficiencies in banks were due to excessive input resources and/or failure to achieve the output targets. The input–output gap of inefficient banks was also analyzed, providing learning benchmarks and clear improvement targets that can help these banks formulate practical actions to improve their performance. Full article

Coxsackievirus A24 (CV-A24) is a human enterovirus that causes acute flaccid paralysis. However, a Coxsackievirus A24 variant (CV-A24v) is the most common cause of eye infections. The causes of these variable pathogenicity and tissue tropism remain unclear. To elucidate the phylodynamics of CV-A24 and CV-A24v, we analyzed a dataset of 66 strains using Bayesian phylodynamic approach, along with detailed sequence variation and epistatic analyses. Six CV-A24 strains available in GenBank and 60 CV-A24v strains, including 11 Taiwanese strains, were included in this study. The results revealed striking differences between CV-A24 and CV-A24v exhibiting long terminal branches in the phylogenetic tree, respectively. CV-A24v presented distinct ladder-like clustering, indicating immune escape mechanisms. Notably, 10 genetic recombination events in the 3D regions were identified. Furthermore, 11 missense mutation signatures were detected to differentiate CV-A24 and CV-A24v; among these mutations, the F810Y substitution may significantly affect the secondary structure of the GH loop of VP1 and subsequently affect the epitopes of the capsid proteins. In conclusion, this study provides critical insights into the evolutionary dynamics and epidemiological characteristics of CV-A24 and CV-A24v, and highlights the differences in viral evolution and tissue tropism. Full article

During the 2008 financial crisis, central banks (such as the Fed) adopted a quantitative easing (QE) policy to stimulate their countries’ economies and overcome severe economic and financial recessions. However, apart from stimulating the economy by issuing a substantial amount of currency to purchase long-term bonds and suppress interest rates, QE policy also contributed to a boom in the real estate and construction sectors. Therefore, this study employs data envelopment analysis to measure the business performance (BP) of construction companies, and explore the impact of QE policy on the BP of construction companies, between 2004 and 2015, using hierarchical regression. We also examine the moderating role of the debt ratio on the relationship. Focused on publicly listed construction companies in Taiwan, this research reveals three encouraging findings. Firstly, QE policy indeed enhanced the BP of Taiwanese construction companies. Secondly, performance improvements in construction companies due to QE policy show a time-diminishing trend, suggesting the importance of seizing the initial policy benefits of QE implementation. Lastly, construction companies with appropriate financial leverage may exhibit better BP. These findings can provide valuable insights for relevant government entities and decision-makers in the industry for policy and investment decisions. Full article

In order to explore the potential influence of new mobile payment services on the Ephesus model developed by Kao and Hwang (2008), we investigated the relative performance of 19 Taiwanese banks from 2018 to 2021. The network efficiency was divided into two parts: management efficiency and profitability efficiency. Only one bank achieved total efficiency from 2019 to 2021. The stage efficiencies showed increments during the first three years (2018–2020), but they declined in 2021. Most banks had low efficiency in the management stage and high efficiency in the profitability stage, suggesting that there are weaknesses in the management of physical resources but high awareness that mobile payment services can be exploited to achieve high profitability. Our results prove that mobile payment is a potential and profitable new service that Taiwanese banks should take advantage of. Comparing the results between the CCR model and the NDEA model, we observed that the NDEA model has more explanatory power, as it provides insight into the internal structure of the working process of Taiwanese banks. Full article

This opinion article discusses the factors that attract children and teens to athletic careers. The most important attribute for the making of athletes is polished sports talent, followed by psychological, environmental, and incentive factors. Our laboratory studies a red blood cell (RBC) type called GP.Mur, which is rare in most parts of the world besides Southeast Asia. Intriguingly, the prevalence of the GP.Mur blood type is relatively high among Taiwanese elite athletes. The highest frequency of the GP.Mur blood type worldwide is found among Taiwan’s Ami people (88–95% from hospital blood bank surveys in the 1980s). Though the Ami constitute only 0.6–0.8% of the Taiwanese population, from records of national track-and-field games in the past century, 10–60% of the medalists were Ami. Biologically, GP.Mur expression supports blood CO₂ metabolism, which may have implications for athleticism. As many of our study subjects are elite college athletes with the GP.Mur blood type, we contemplated their upbringings and career dilemmas, especially during the difficult COVID-19 pandemic. Beyond individual sports talent, the pandemic particularly tests personal characteristics and socioeconomic support for becoming an athlete. Full article

The purpose of the study is to investigate whether bank diversification influences borrowing firms’ financial constraints on investment decisions. It also analyzes whether the different dimensions of bank diversification could alleviate financial constraints to firm investment. Further, the role of bank diversification in achieving firm financial sustainability is explored. By applying the Two-step System GMM, this study examines the effect of changes in bank diversification on financial constraints to borrowing firm investment in a reduced-form investment model with a sample of 810 listed firms in Taiwan over the period 1997–2019. The empirical findings indicate that firms are financially constrained as well as there being a positive relationship between cash flow and investment among Taiwanese listed firms. Additionally, bank diversification significantly reduces the investment-cash flow sensitivity of firms, suggesting that bank diversification mitigates the financial constraints to borrowing firms. Moreover, the multi-diversification of a bank compared to single-diversification will have greater impact on mitigating the firms’ financial constraints on investment. Thus, bank diversification strategies are proposed in a bank-based financial system, leading to the easing of the borrowing firms’ financial constraints to investments. Full article

Financial distress prediction is crucial in the financial domain because of its implications for banks, businesses, and corporations. Serious financial losses may occur because of poor financial distress prediction. As a result, significant efforts have been made to develop prediction models that can assist decision-makers to anticipate events before they occur and avoid bankruptcy, thereby helping to improve the quality of such tasks. Because of the usual highly imbalanced distribution of data, financial distress prediction is a challenging task. Hence, a wide range of methods and algorithms have been developed over recent decades to address the classification of imbalanced datasets. Metaheuristic optimization-based artificial neural networks have shown exciting results in a variety of applications, as well as classification problems. However, less consideration has been paid to using a cost sensitivity fitness function in metaheuristic optimization-based artificial neural networks to solve the financial distress prediction problem. In this work, we propose ENS_PSONN_cost and ENS_CSONN_cost: metaheuristic optimization-based artificial neural networks that utilize a particle swarm optimizer and a competitive swarm optimizer and five cost sensitivity fitness functions as the base learners in a majority voting ensemble learning paradigm. Three extremely imbalanced datasets from Spanish, Taiwanese, and Polish companies were considered to avoid dataset bias. The results showed significant improvements in the g-mean (the geometric mean of sensitivity and specificity) metric and the F1 score (the harmonic mean of precision and sensitivity) while maintaining adequately high accuracy. Full article

In this paper, we use the multi-stage network slacks-based measure model under uncertainty to evaluate the performance of Taiwanese financial holding companies (FHCs) from 2007 to 2012. We conceptualize the value creation process to be a two-stage framework, as the profitability and the marketability stages with a serial-linkage relationship, in order to solicit more information from the value creation process of FHCs. Under this framework, the profitability stage can be further divided into banking, insurance, and securities profitability sub-stages. In addition, we further extend the proposed model mentioned above to not only incorporate the NPLs as the undesirable output in the banking profitability stage but also use the fuzzy set approach to process its uncertainty. Results indicate that the discriminatory ability of our model is higher when we simplify the variables in the model specification. We also find that all Taiwanese FHCs in that particular period were “inefficient performers”, which is mainly attributed to the weak profitability performance, especially in banking service. We postulate that the global financial crisis, the US subprime crisis in particular, had a negative effect on the value creation performance of Taiwanese FHCs; however, they gradually recovered and improved their performance after the crisis. Full article

Tables are an important element in a document and can express more information with fewer words. Due to the different arrangements of tables and texts, as well as the variety of layouts, table detection is a challenge in the field of document analysis. Nowadays, as Optical Character Recognition technology has gradually matured, it can help us to obtain text information quickly, and the ability to accurately detect table structures can improve the efficiency of obtaining text content. The process of document digitization is influenced by the editor’s style on the table layout. In addition, many industries rely on a large number of people to process data, which has high expense, thus, the industry imports artificial intelligence and Robotic Process Automation to handle simple and complicated routine text digitization work. Therefore, this paper proposes an end-to-end table detection model, U-SSD, as based on the object detection method of deep learning, takes the Single Shot MultiBox Detector (SSD) as the basic model architecture, improves it by U-Net, and adds dilated convolution to enhance the feature learning capability of the network. The experiment in this study uses the dataset of accident claim documents, as provided by a Taiwanese Law Firm, and conducts table detection. The experimental results show that the proposed method is effective. In addition, the results of the evaluation on open dataset of TableBank, Github, and ICDAR13 show that the SSD-based network architectures can achieve good performance. Full article

Glycophorin hybrids such as GP.Mur are common in Southeast Asians. In Taiwan, clinically significant alloantibodies to the GP.Mur phenotype are the most important issue in blood banks. A large-scale screening of glycophorin hybrids in the Taiwanese population is urgently needed to ensure transfusion safety. Four clones of human hybridomas that secrete anti-Mi^a, anti-MUT, and anti-Mur were established by fusing human B-lymphocytes and myeloma cells (JMS-3). The specificity of each monoclonal antibody (MoAb) was characterized. Three MoAbs were applied on an Automated Pretransfusion Blood Testing Analyzer (PK7300/PK7400) for donor screening. Genotyping was performed to determine the detailed subgrouping of glycophorin hybrids. Four MoAbs are IgM antibodies. Anti-Mi^a (377T) binds to ⁴⁶DXHKRDTYA⁵⁴, ⁴⁸HKRDTYAAHT⁵⁷ peptides, and anti-Mi^a (367T) binds to ⁴³QTNDXHKRD⁵¹ peptides (X indicates T, M, or K). Anti-Mur is reactive with ⁴⁹KRDTYPAHTA⁵⁸ peptides. Anti-MUT is reactive with ⁴⁷KHKRDTYA⁵⁴. A total of 78,327 donors were screened using three MoAbs, and 3690 (4.71%) were GP.Mur, 20 (0.025%) were GP.Hut, and 18 (0.022%) were GP.Vw. When the Mi^a antigen was introduced as routine screening, the frequency of Mi(a+) among blood donors in Taiwan was 4.66% (67,348/1,444,541). Mi^a antigen was implemented as a routine blood testing, and the results were labeled on all red blood cell (RBC) units. Full article

The Taiwanese government has encouraged bank privatization and the establishment of financial holding companies to improve banking sustainability and consolidate banks, insurance companies, and securities firms. It is important for bank decision makers to set policies that lead to sustainable development. However, the literature remains unclear about the types of banks that achieve greater business sustainability. This paper aims to (1) identify the criteria that affect banks’ business sustainability and (2) determine the most sustainable types of banks. This study uses a hybrid multiple-criteria decision-making approach on eighteen financial criteria for twenty-five Taiwanese listed banks with data from 2012 to 2016. The results show that non-performing loan ratio is the most critical factor. In addition, financial holding companies outperformed non-financial holding companies. Financial holding companies with insurance companies as their largest subsidiaries performed best. Private banks exceeded state-owned banks in sustainability. The results lead to two implications. First, banks should value risk over profitability and diversify financial products. Second, the government should continue to privatize banks. These findings suggest that bank managers implement an enterprise resource planning (ERP) system with a master plan, framework, and guidelines to help them track bank performance indicators to ensure sustainability. Full article

Individual microcredit loans involve large quantities and small amounts and necessitate rapid approval, therefore making simple and fast application approvals rather critical. Creditors must evaluate clients’ credit status and default risk within the shortest time when determining whether to approve or decline their applications, preventing overdue responses that negatively impact bank profits and management practices, and could trigger domestic financial crises. This study investigates client credit quality criteria, focusing on the expert opinions of bank managers. The decision-making trial and evaluation laboratory method is adopted to enable a comparison and analysis of the similarities and differences in how banks evaluate their clients’ character, ability, financial capability, and collateral. Based on causality and correlations among the criteria, we also identify the core problems and key improvement criteria in the evaluation system. Through survey results of professional managers from Taiwanese banks, this study uses the DEMATEL method to compare the differences in bank evaluation methods based on the four dimensions of clients’ character, ability, pockets, and collateral, as well as the corresponding 14 criteria. In order to improve the reliability and usefulness in bank client credit risk assessment, the assessment dimensions and indicators of bank client credit risk assessment are first discussed; second, the causal relationship and degree of mutual influence between different dimensions and criteria are researched and assessed; in the end, the paper discusses how to improve the function and the benefits of bank client credit risk assessment. Full article

Canine parvovirus type 2c (CPV-2c) emerged in 2000 and is known for causing a more severe disease than other CPV-2 variants in puppies. In 2015, the emerging CPV-2c variant was isolated in Taiwan and it subsequently became the predominant variant. To trace the evolution of Taiwanese CPV-2c, we compared complete VP2 genes of CPV-2c from Taiwan and sequences obtained from GenBank. The evolutionary rate of CPV-2c was estimated to be 4.586 × 10⁻⁴ substitutions per site per year (95% highest posterior density (HPD) was 3.284–6.076 × 10⁻⁴). The time to the most recent common ancestor (TMRCA) dated to 1990 (95% HPD: 1984–1996) and 2011 (95% HPD: 2010–2013) for the CPV-2c variant and Taiwanese isolates, respectively. The CPV-2c variant isolated from Taiwan was clustered with CPV-2c from China. This phylogenetic clade began to branch off in approximately 2010 (95% HPD was 3.823–6.497). Notably, two unique mutations of Taiwanese CPV-2c were found, Q383R and P410L. In summary, this is the first report on the genome evolution of CPV-2c in Taiwan, revealing that this CPV-2c variant shares a common evolutionary origin with strains from China. The demographic history inferred by the Bayesian skyline plot showed that the effective population of CPV-2c increased until 2006 and then slowly declined until 2011. Full article