Research Article
Impact of Electronic Services on Customer Satisfaction: The Case of Commercial Bank in Urban Area of Nepal
Dipendra Bikram Sijapati
,
Manamaya Mishra*,
Bishnu Kumar Khadka
Issue:
Volume 12, Issue 1, June 2026
Pages:
1-10
Received:
25 November 2025
Accepted:
7 January 2026
Published:
29 January 2026
Abstract: Electronic banking (e-banking) plays a crucial role in service delivery for emerging economies like Nepal, yet its effects on customer satisfaction remain uneven and context of dependent. It investigates the influence of major e-banking services are ATMs, internet banking, mobile banking, debit cards, credit cards, and electronic fund transfers on the satisfaction levels among customers of commercial banks in urban areas. This paper based on a descriptive research design, selected respondents 188 bank customers in the Kathmandu Valley by using structured questionnaires to collect their experiences and perceptions. Data analysis drew on descriptive statistics to outline usage patterns, Pearson correlations to examine relationships between variables, and multiple regression to assess predictive impacts while controlling confounding factors. The research findings reveal that ATMs and debit cards exert a significant positive effect on customer satisfaction, likely due to their reliability, accessibility, and ease of use in daily transactions. In contrast, internet banking and mobile banking show no statistically significant impact once other services are accounted for. This stems from persistent challenges like inadequate digital infrastructure, frequent connectivity issues, and usability barriers that hinder broader adoption. Credit cards and electronic fund transfers also fall short of strong influence in this setting. Overall, the regression model accounts for 23.8 percent of the variance in satisfaction scores. These results underscore the importance of dependable transaction mechanisms in driving satisfaction. For emerging economies, the paper recommends investments in robust digital infrastructure, enhanced service quality, and targeted customer education programs to overcome barriers and maximize e-banking benefits.
Abstract: Electronic banking (e-banking) plays a crucial role in service delivery for emerging economies like Nepal, yet its effects on customer satisfaction remain uneven and context of dependent. It investigates the influence of major e-banking services are ATMs, internet banking, mobile banking, debit cards, credit cards, and electronic fund transfers on ...
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Research Article
Word Embeddings Network and Transformer Based Part of Speech Tagging for Korean
Pong-Gol You,
Chun-Sik So,
Song-Min Choe,
Yong-Hak Lee,
Chol-Jun O*
Issue:
Volume 12, Issue 1, June 2026
Pages:
11-24
Received:
16 November 2025
Accepted:
9 December 2025
Published:
7 April 2026
DOI:
10.11648/j.ajnna.20261201.12
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Abstract: Korean Part-of-Speech (POS) tagging is different from and more difficult than other languages such as English, Russian and Chinese due to raising issues of Korean word segmentation and analysis of sound-changed morphemes. In this paper we propose a transformer-based Korean POS tagging model, which combines the output vector of a encoder of the transformer with a representational vector of the input word obtained from character-level word embeddings network unlike existing deep learning-based POS tagging models based on BiLSTM. First, in order to perform segmentation of words and changed sound analysis at once, we have designed a model to make a new output sequence of the POS tagging model as a sequence of pairs of strings of morphemes and its POS tags. Second, in order to obtain character-level word representations, word embedding network employing convolution network and highway network are trained. Finally, to make more efficient use of the semantic information of the input word in generating of sequences of POS tagging, we combined the word representation vector obtained from the word-embedding generation network with the output of a encoder of the transformer. According to the experimental results, the proposed model achieves 1.4% performance improvement over the model without incorporating the word representation vector obtained from the word embeddings network, and as a result, the POS tagging accuracy is 96.1%, which is superior to all other compared models including the BiLSTM+CRF model.
Abstract: Korean Part-of-Speech (POS) tagging is different from and more difficult than other languages such as English, Russian and Chinese due to raising issues of Korean word segmentation and analysis of sound-changed morphemes. In this paper we propose a transformer-based Korean POS tagging model, which combines the output vector of a encoder of the tran...
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