Banks In Taiwan Research Articles

Bargibant’s pygmy seahorse Hippocampus bargibanti in Taiwan Bank: hidden biodiversity of Taiwan Strait

During a scientific expedition in the Taiwan Bank in the southern Taiwan Strait in 2021, five pygmy seahorses, measuring between 18.1 mm and 28.3 mm in standard length, were inadvertently collected along with Muricella sea fans. Morphometric measurements of these pygmy seahorse specimens coincided with the previous data on H. bargibanti, but they had a proportionally greater head depth and snout length. Genetically, DNA marker analysis of partial mitochondrial COI sequences confirmed that our specimens belonged to the same lineage as H. bargibanti, with a p-distance of 0.54% among populations. This discovery enhances our knowledge of the limited biodiversity in the Taiwan Bank, which includes a complex geomorphology of both reef banks and sandy substrates, and highlights the importance of strict laws prohibiting fishing with inadequate gear, invasive or illegal fishing, and sand dredging to protect unexplored coral reef biodiversity in the area.

Near-Inertial Oscillations Induced by Winter Monsoon Onset in the Southwest Taiwan Strait

The near-inertial motion in ocean surface currents directly reflects the energy transported by wind towards the surface layer, playing an important role in climate regulation and energy balance. Previous studies have mainly focused on near inertial oscillations (NIOs) induced by tropical cyclones in the Taiwan Strait, with few reports on near inertial oscillations induced by monsoon onset. Using high-frequency radar observations, we detected an amplification of NIOs induced by the winter monsoon onset. While not as strong as NIOs induced by tropical cyclones, the near-inertial current (NIC) induced by winter monsoon onset in the Taiwan Strait has peak speeds reaching up to 5.2 cm/s and explaining up to 0.7% of non-tidal variance. This study presents observational results of NIOs during three monsoon onset events, and analyzes the impact of winds and temperature changes on NIOs. Temporal and spectral analysis reveals that the monsoon onset is the primary driver behind the formation of NIOs. Results indicate that near-inertial kinetic energy is relatively lower in shallower waters, such as the Taiwan Bank, compared to deeper regions. Furthermore, by integrating the air and sea surface temperature from reanalysis products, we have examined the abrupt changes in sea surface temperature (SST) before and after monsoon onset and their correlation with NIOs. The findings suggest that temperature falling favors the intensification of NICs during monsoon onset, and a lack of significant SST changes precludes the triggering of notable NICs. These insights enhance our understanding of the mechanisms driving NIOs and their roles in seawater mixing.

Large-scale geohazards risk of submarine landslides considering the subsea cables vulnerability: A case study from the northern continental slopes of South China Sea

Submarine landslides pose significant threats to subsea cables distributed on the global seabed. However, regional scale risk assessment of landslide geohazards is rarely reported. This study introduces a methodology for regional-scale geohazard risk prediction of submarine landslides, focusing on the northern continental slopes of the South China Sea. Initially, the study employed the infinite-slope method to calculate safety factors for typical submarine slopes. Addressing uncertainties in geotechnical and seismic parameters, Monte Carlo simulations determine slope failure probabilities. Using kriging interpolation, localized failure probabilities are extrapolated to regional scales, establishing a spatiotemporal distribution method for large-scale geohazard susceptibility. Hazard levels are subsequently determined considering the volumes of potential landslides. The density of subsea cables is used as a vulnerability factor to guide the regional-scale assessment of cable vulnerability. Finally, integrating vulnerability with hazard levels provides a comprehensive assessment of landslide-induced large-scale geohazard risks. The findings highlight elevated geohazard risks in the Taiwan Bank slope segment, moderate risks in the Zhujiang Valley and Shenhu slope segments, with lower risks in other areas.

Impacts of El Niño–Southern Oscillation (ENSO) Events on Trophodynamic Structure and Function in Taiwan Bank Marine Ecosystem

Impacts of El Niño–Southern Oscillation (ENSO) Events on Trophodynamic Structure and Function in Taiwan Bank Marine Ecosystem

Mobile payment-banking efficiency nexus—A concise review of the evolution and empirical exploration of the Taiwan banking industry

This paper utilizes an advanced Network Data Envelopment Analysis (DEA) model to examine the impact of mobile payment on the efficiency of Taiwan banking industry. Inheriting the literature, we separate the banking operation process into two stages, namely profitability and marketability. Mobile payment is then considered as the core factor in the second stage. Our paper discovers network DEA model can effectively enhance the analysis of banking industry’s efficiency, and mobile payment has a notable impact on Taiwan banking industry. Regarding the profitability stage, there is only one efficient bank in 2019 and 2022, respectively. These banks also perform better in terms of “mobile payment production”. In the marketability stage, there is also only one bank in 2021 and one bank in 2022, that can reach to unique efficiency score. This indicates many banks attempt to increase earnings per share through investing in mobile payment services. However, the achievement still needs more wait. This leads to the fact that no bank can reach the ultimate overall efficiency. Within our sample, we also find that regarding promoting mobile payment services, Private Banks outperform Government Banks.

Exploring the influence of fintech patents on operation efficiency and market efficiency in Taiwan's commercial banking sector‐meta entropy dynamic two‐stage DDF model

AbstractThis paper presents a meta entropy dynamic two‐stage DDF model, incorporating significant patents in financial technology (fintech) into the analysis to examine the operational and market efficiencies of banks in Taiwan, providing new insights for research on banking performance and government policy. The results show the following. (1) The most efficient bank is Cathay Financial, while the bottom three are First Financial, E.SUN Financial, and Hua Nan Financial. (2) Financial holding companies (FHCs) outperform non‐FHCs in both operational and market stages. (3) The number of patents has a positive impact on the market stage efficiency of banks.

An exploration of operational efficiency, market efficiency, and sustainable development in the banking industry

AbstractSustainable development is the primary goal of the current global economic transformation. The banking industry, as an intermediary institution within the financial system, not only serves as a crucial foundation for national economic development but also plays a key role in the global transition to sustainability and a low‐carbon economy. Banks can leverage the influence of financing to direct funds towards sustainable ventures and simultaneously develop green financial products, guiding ordinary consumers to make more environmentally friendly choices. How the banking industry can effectively improve operational efficiency while considering sustainable development is one of the key focuses of ongoing development in the banking sector. The main aim of this study is to incorporate the aspect of sustainable development into the evaluation of operational efficiency, aligning with the goals of corporate sustainable development. It allows for an analysis of how decision‐makers in the banking industry can adjust resources to maintain stable and sustainable profitability while promoting sustainable development. This study selected 13 financial holding banks and 19 non‐financial holding banks in Taiwan as research subjects, covering the period from 2016 to 2021. Utilizing a meta assurance regions (AR) parallel dynamic two‐stage slacks‐based measure model with “operational stage” and “market and sustainability parallel stage,” the research explores the efficiency performance of banks considering sustainable development. It examines the differences in efficiency performance at various stages among different types of banks. The research findings are as follows: (1) among the banking industry in Taiwan, operational stage efficiency ranks the highest, followed by sustainable stage efficiency, while market stage performance lags behind. (2) Financial holding banks outperform non‐financial holding banks on average in operational stage, market stage, and sustainable stage efficiency. (3) Fubon Financial, TFH, CATHAY HOLDINGS, and SKFH are benchmark performers among financial holding banks. (4) Non‐financial holding banks exhibit a higher average technical gap ratio compared to financial holding banks, indicating that non‐financial holding banks have fewer inefficient areas to improve. However, the technical efficiency of both groups of banks approaches each other over the years. (5) In the sustainable stage, financial holding banks demonstrate superior environmental indicators and corporate treatment efficiency compared to non‐financial holding banks.

THE FACILITATORS AND INHIBITORS OF CUSTOMER ADOPTION OF PURE INTERNET BANKING: TRUST TRANSFER AND STATUS QUO BIAS

ABSTRACT There are three pure Internet banks in Taiwan and Line Bank accounts for more than 90% market share of pure Internet banking. In addition, despite the increasing viability of pure Internet banking, customers continue using existing banking services and results in only 10.16% of all kinds of banking services. To explore why consumers prefer one bank over others and why consumers hesitate to adopt pure Internet banking, this study considers status quo bias (habitual usage) and trust transfer in the context of LINE Bank, a company that provides its customers with comprehensive pure Internet banking services. We also theorize that intimacy with service personnel leads to the habitual usage of existing banking services, and trust in the LINE app and trust in LINE Pay affect customers’ trust in LINE Bank. We also suggest that habitual usage can also reduce trust and moderates the relationship between trust in LINE Bank and usage intention. Survey data from 403 active LINE Pay and Line app users confirm that both trust in the LINE app and trust in LINE Pay exhibit positive effects on trust in LINE Bank, which in turn positively affects usage intention. In addition, intimacy enhances habitual usage, which has a negative effect on trust in LINE Bank, has a direct and negative effect on usage intention, and at the same time adversely moderates the relationship between trust in LINE Bank and usage intention.

Comparison of Abundance and Structure of Larval Fish Assemblages between Autumn and Spring in the Waters Surrounding Taiwan Bank, Western North Pacific

The fluctuations in both time and space of larval fish assemblages in relation to hydrographic characteristics in the waters surrounding Taiwan Bank were studied in October 2021 (autumn) and March 2022 (spring). Throughout the study period, we identified a total of 149 taxa of fish larvae, encompassing 96 genera and 71 families. Engraulis japonicus, Diaphus slender type, unidentified Gobiidae, Apogon sp., unidentified Clupeidae, and Benthosema pterotum were the six dominant taxa and together constituted 47.39% of the total catch. There were no notable temporal variations observed in the abundance of fish larvae, but the species number of fish larvae was greater in spring than in autumn. Significant variations in species composition were observed between the different cruises, and the cluster analysis unveiled a distinct temporal structure of the assemblages of fish larvae. The dynamics of the prevailing currents induced by seasonal monsoons contribute significantly to the transportation of fish larvae. The distribution of fish larvae showed a good association with hydrographic characteristics, where seawater temperature and salinity emerged as the primary explanatory factors influencing the composition of larval fish assemblages in the waters surrounding Taiwan Bank. While the increased influx of nutrients from upwelling ensures abundant food availability, the hydrographic conditions may not be suitable for every fish larva.

Predicting default risk bancassurance using GMDH and dce-GMDH neural network models

Purpose This study aims to develop a novel approach for predicting default risk in bancassurance, which plays a crucial role in the relationship between interest rates in banks and premium rates in insurance companies. The proposed method aims to improve default risk predictions and assist with client segmentation in the banking system. Design/methodology/approach This research introduces the group method of data handling (GMDH) technique and a diversified classifier ensemble based on GMDH (dce-GMDH) for predicting default risk. The data set comprises information from 30,000 credit card clients of a large bank in Taiwan, with the output variable being a dummy variable distinguishing between default risk (0) and non-default risk (1), whereas the input variables comprise 23 distinct features characterizing each customer. Findings The results of this study show promising outcomes, highlighting the usefulness of the proposed technique for bancassurance and client segmentation. Remarkably, the dce-GMDH model consistently outperforms the conventional GMDH model, demonstrating its superiority in predicting default risk based on various error criteria. Originality/value This study presents a unique approach to predicting default risk in bancassurance by using the GMDH and dce-GMDH neural network models. The proposed method offers a valuable contribution to the field by showcasing improved accuracy and enhanced applicability within the banking sector, offering valuable insights and potential avenues for further exploration.

Do Bank Funding Diversity and Bank Lending Affect Net Interest Margins? Evidence From Asia Markets Before and During the Covid-19 Pandemic

This paper investigates how bank funding diversity and lending affect bank performance, especially during the Covid-19 pandemic. We employ the Generalized Method of Moments to analyze unbalanced panels of commercial banks in China, Taiwan, and Vietnam. The empirical results show that a percentage increase in bank funding diversity and bank lending in the sample negatively affects profitability. In contrast, the results are mixed in each country due to different market microstructures. While holding diversified funding strengthens bank profitability during the pandemic, increasing lending activities dampers the bank’s performance. Finally, this research has important implications for bank managers and regulators to develop sustainable banking performance in emerging markets, especially during pandemics.

Nonlinear Dynamic Analysis of Seafloor Pressure Time Series with and without Internal Waves

Ocean internal wave as a nonlinear process oscillates within ocean interior rather than the surface. Internal waves have significant influences on the transport of material, energy and even global climate. The generation, transmission and attenuation of internal wave play a significant role in the ocean dynamics owing to the exchange of the energy within each process. In this paper, reduced complexity of seafloor pressure time series induced by internal wave in the southern Taiwan bank has been investigated using nonlinear dynamic analysis. Cao method has been used to distinguish between the pressure signal with internal wave and the random signal without internal wave. The reconstructed phase spaces and correlation dimensions of the time series with and without internal wave are compared. Internal wave leads the seafloor pressure time series to produce a more regular phase space reconstruction and more low dimensional dynamics. Our study suggests that nonlinear dynamic analysis could be a valuable and promising method in real-time ocean internal wave detection.

Does violation of regulations hurt firm value enhanced: Evidence from Taiwan banking industry?

This study investigates the impact of penalties, including sanctions, corrections, and fine payments, on firm value within the context of the banking industry on the Taiwan Stock Exchange (TWSE) from 2017 to 2021. Utilizing data from the Financial Supervisory Commission, we employ rigorous statistical methods, such as multiple regression and Petersen regression models, to discern whether these punitive measures affect firm performance. Intriguingly, our findings indicate that firms subject to financial sanctions and penalties in Taiwan experience an improvement in their firm value, challenging the conventional belief that such penalties erode value. We propose that this unexpected outcome may be attributed to the potential gains derived from expanding business activities, even in violation of banking regulations, outweighing the associated regulatory costs. By shedding light on this under-researched aspect of the literature, our study contributes to a broader understanding of how regulatory penalties impact firm value in the banking industry, thereby providing regulatory authorities with practical insights.

Forecasting vault cash with an extreme value long short-term memory network

Effective cash management is key in banking operations and has implications for cost control, customer service, and risk management. As transactions become more diverse, manual forecasting methods have become inadequate for accurate vault cash forecasting, which involves extensive data analysis. To address this challenge, the banking industry has adopted FinTech tools based on big data and deep learning for various client services. These methods are generally accurate but perform poorly in cases with extreme events, for which data are scarce. In this study, we propose a time series prediction model with long short-term memory and an attention mechanism that effectively predicts the presence of extreme values. We applied extreme value theory to define the extreme value loss for extreme situations and use a sliding window to process time series data. The enhanced extreme value loss function in our model yields improved prediction accuracy for time series data.We evaluated the proposed model against previous methods in evaluation experiments on data from three branches of a commercial bank in Taiwan, where the vault cash data of each exhibited extreme values. The proposed model was highly accurate: it had a lower mean absolute percentage error and higher trend accuracy than competing methods on a majority of time series, and it was also more accurate in predicting extreme values in time series data.

Upwelling impact and lateral transport of dissolved PAHs in the Taiwan Strait and adjacent South China Sea

The spatial distribution and depth profile of dissolved polycyclic aromatic hydrocarbons (PAHs) were investigated in the western Taiwan Strait (TWS) and northeastern South China Sea (SCS) during the southwest monsoon for a comprehensive study of spatial distribution, potential sources, upwelling, and lateral PAHs transport flux to assess the impacts of oceanic processes. The concentrations of ∑14PAHs were 33 ± 14 ng L−1 and 23 ± 11 ng L−1 in western TWS and northeastern SCS, respectively. A minor difference in potential sources in different areas was shown in principle component analysis results, which illustrated mixed sources (petrogenic and pyrogenic) in western TWS and petrogenic sources in northeastern SCS. An “enrichment in surface or deep but depletion in medium water” distribution pattern of PAHs depth profile during summertime was observed in Taiwan Bank, which was potentially influenced by the upwelling. The greatest lateral ∑14PAHs transport flux was found along the Taiwan Strait Current area (43.51 g s−1), followed by those along South China Sea Warm Current and Guangdong Coastal Current areas. Though the oceanic response to PAHs varied relatively slowly, the ocean current was a less-dominant pathway for PAHs exchange between the SCS and the East China Sea (ECS).

Oceanic and ecological response to native Typhoons Cempaka and Lupit (2021) along the northern South China Sea continental shelf: comparison and evaluation of global and regional Operational Oceanography Forecasting Systems

The Global Operational Oceanography Forecasting System from the Mercator Ocean (MO) and the regional South China Sea Operational Oceanography Forecasting System (SCSOFSv2) were compared and evaluated using in situ and satellite observations, with a focus on the oceanic and ecological response to two consecutive native typhoons, Cempaka and Lupit, that occurred in July–August 2021. Results revealed a better simulation of the chlorophyll a (Chla) structure by SCSOFSv2 and a better simulation of the temperature profile by MO in the Pearl River Estuary. In addition, SCSOFSv2 sea surface temperature (SST) and MO Chla variations corresponded well with observations along the northern SCS shelf. Simulated maximum SST cooling was larger and 2–3 days earlier than those observations. Maximum Chla was stronger and led the climatological average by 2 days after the typhoon passage. Typhoon-induced vertical variations of Chla and NO3 indicated that different Chla bloom processes from coastal waters to the continental shelf. Discharge brought extra nutrients to stimulate Chla bloom in coastal waters, and model results revealed that its impact could extend to the continental shelf 50–150 km from the coastline. However, bottom nutrients were uplifted to contribute to Chla enhancement in the upper and middle layers of the shelf. Nutrients transported from the open sea along the continental slope with the bottom cold water could trigger Chla enhancement in the Taiwan Bank. This study suggests considering strong tides and waves as well as regional dynamics to improve model skills in the future.

It is not merely a chat: Transforming chatbot affordances into dual identification and loyalty

Artificial intelligence (AI)-powered service chatbot functionality is changing to more effectively connect with customers in the era of digital marketing. As such, an understanding of how to enhance user perceptions and behaviors through interface design has become crucial. Using affordance actualization theory and social identity theory as a theoretical lens, this study explored how chatbot affordances affect consumer brand loyalty. Data were collected from 369 respondents who had at least one conversation with AI chatbots from a predetermined list of banks in Taiwan; the collected data were then analyzed using structural equation modeling. The results revealed that anytime–anyplace connectivity, information association, visibility, and interactivity affordances provided by chatbots positively influenced chatbot exploitation, which in turn affected perceived brand competence and perceived brand warmth. Furthermore, perceived brand competence influenced customer–chatbot identification and customer–brand identification, whereas brand warmth influenced customer–brand identification. Customer–chatbot identification also influenced brand loyalty both indirectly—through customer–brand identification—and directly. These findings are useful for assisting managers in various industries in the application of AI technologies to implement digital transformation strategies and improve customer services.

The Impact of Corporate Social Responsibility Practices on Customer Value Co-Creation and Perception in the Digital Context: A Case Study of Taiwan Bank Industry

The rapid development of digitalization has introduced greater variability and trust-related risks to the banking industry. Enhancing customers’ perception of value co-creation with banks is a critical issue that requires attention. This study aims to explore the impact and mechanism of a bank’s social responsibility practices on its customers’ value co-creation in the digital context. A cross-level analysis model was developed and analyzed based on in-depth surveys of 30 bank managers and 262 valid customers. The results reveal that (1) CSR practices have no impact on customer value co-creation in the digital context; (2) CSR practices have a positive impact on customers’ perception of a company’s social responsibility; (3) customers’ perception of a company’s social responsibility has a positive impact on customer value co-creation; and (4) customers’ perception plays a mediating role between CSR practices and customer value co-creation. Although corporate social responsibility is becoming increasingly important in the current digital economy, our study found that it does not necessarily lead to more customer value co-creation. Banks must enable customers to perceive their CSR practices in order to foster value co-creation. This study has important implications for banking practitioners seeking to strengthen their social responsibility practices and create value with their customers in the digital era.

A Principal Component Analysis of Digital Banking Development in Taiwan

Abstract In Taiwan, the digitalization of banks has imparted a future trend and a national financial technology (FinTech) policy. This paper aims to study which factors will affect the promotion of digital banking amongst digital accounts. Categorically, we applied the principal components analysis (PCA) method to analyze and identify the main factors of digital banking development. In addition, this study used three years of data from 2017 to 2020 since the data were relatively comprehensive and included all the large financial holding companies (15 in total) in Taiwan. The empirical findings can briefly be summarized as follows: a bank that wants to promote digital accounts must start with a credit card since that is what digital finance must be bound to. They also need to let people know that digital accounts have many advantages, such as no deposit limits or interest-free cross-bank withdrawals. There are a few crucial factors that need to be considered, including the number of free transfers, the card in force, active cards, and the number of free withdrawals. If banks effectively promote and attract people to apply for digital accounts, it could strongly contribute to the development of digital banking in Taiwan. JEL classification numbers: C45, G10. Keywords: Financial technology, Digital banking, Digital account, Principal components analysis.

High-Precision Inversion of Shallow Bathymetry under Complex Hydrographic Conditions Using VGG19—A Case Study of the Taiwan Banks

Shallow bathymetry is important for ocean exploration, and the development of high-precision bathymetry inversion methods, especially for shallow waters with poor quality, is a major research aim. Synthetic aperture radar (SAR) image data benefit from a wide coverage, high measurement density, rapidity, and low consumption but are limited by low accuracy. Alternatively, multibeam data have low coverage and are difficult to obtain but have a high measurement accuracy. In this paper, taking advantage of the complementary properties, we use SAR image data as the content map and multibeam images as the migrated style map, applying the VGG19 neural network (optimizing the loss function formula) for bathymetric inversion. The model was universal and highly accurate for bathymetric inversion of shallow marine areas, such as turbid water in Taiwan. There was a strong correlation between bathymetric inversion data and measured data (R2 = 0.8822; RMSE = 1.86 m). The relative error was refined by 9.22% over those of previous studies. Values for different bathymetric regions were extremely correlated in the region of 20–40 m. The newly developed approach is highly accurate over 20 m in the open ocean, providing an efficient, precise shallow bathymetry inversion method for complex hydrographic conditions.