Browsing by Author "Yang, Keng-Chieh"

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Applying Artificial Neural Network to Predict Semiconductor Machine Outliers
(2013)
Yang, Keng-Chieh
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Yang, Conna
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Chao, Pei-Yao
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Shih, Po-Hong
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經營管理研究所
Advanced semiconductor processes are produced by very sophisticated and complex machines. The demand of higher precision for the monitoring system is becoming more vital when the devices are shrunk into smaller sizes. The high quality and high solution checking mechanism must rely on the advanced information systems, such as fault detection and classification (FDC). FDC can timely detect the deviations of the machine parameters when the parameters deviate from the original value and exceed the range of the specification. This study adopts backpropagation neural network model and gray relational analysis as tools to analyze the data. This study uses FDC data to detect the semiconductor machine outliers. Data collected for network training are in three different intervals: 6-month period, 3-month period, and one-month period. The results demonstrate that 3-month period has the best result. However, 6-month period has the worst result. The findings indicate that machine deteriorates quickly after continuous use for 6 months. The equipment engineers and managers can take care of this phenomenon and make the production yield better.
Assessing how service quality, airline image and customer value affect the intentions of passengers regarding low cost carriers
(2012-05-01)
Yang, Keng-Chieh
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Hsieh, Tsui-Chuan
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Li, Hendrik
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Yang, Chyan
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資訊管理與財務金融系註：原資管所+財金所
This paper uses simple structural equation modelling to investigate relationships between service quality, airline image, customer value and behavioural intentions for passengers to fly on low cost carriers. In particular it focuses on flier's expectations of the types of services that they can enjoy. The analysis indicates that service quality has a significant positive effect on customer value, airline image and behavioural intentions, but that airline image does not itself significantly influence behavioural intentions. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.
Consumer attitudes toward online video advertisement: YouTube as a platform
(2017-01-01)
Yang, Keng-Chieh
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Huang, Chia-Hui
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Yang, Conna
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Yang, Su Yu
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資訊管理與財務金融系註：原資管所+財金所
Purpose - Online video advertisement is a wide-ranging phenomenon on the internet that provides huge opportunities for business enterprises. The revenues of website service providers come primarily from advertisement. However, it is rare to find research focusing on consumer attitudes toward online video advertisement. This study aims to investigate consumer attitudes toward advertisement while they are watching online videos on YouTube. Design/methodology/approach - The paper followed Brackett and Carr's (2001) Web Advertising Attitudes Model and combined it with the theory of reasoned action (TRA) and the flow theory. This study investigates consideration of the factors affecting attitudes toward advertisement and the influence on shopping intention and purchase behavior. Findings - The findings indicate that entertainment, informativeness, irritation and credibility have a shopping influence on purchase attitudes. Flow, on the other hand, does have an influence on shopping intention and purchase behavior. The discussion and conclusion have been further discussed. Originality/value - This study provides a comprehensive model for online video advertisement. This model was based on Brackett and Carr's model, combining the users and gratifications theory, TRA and flow theory to develop an online video advertisement model. Researchers can consider this model as a framework and use it to capture a more complete picture of the relevant phenomena in their works.
Improving the search process through ontology-based adaptive semantic search
(2007)
Yang, Chyan
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Yang, Keng-Chieh
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Yuan, Hsu-Chieh
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Purpose - The purpose of this research is to describe an efficient search methodology to help improve the search results in the top portion of a lengthy search list. When facing a lengthy search list, people often limit themselves to the top ten items on the list, even though there may be more useful information after the top ten items. Design/methodology/approach - This study proposes an ontology-based adaptive semantic search to significantly improve the search experience. To capture the semantic difference of search terms, naive ontology is used to store the relationship among terms. Before a search term is processed by the search engine Lucene, the related words of the search term are selected from ontology structures to form new query phrases in the process of query expansion. The weighting of the expanded query phrases is dynamically learned by observing the users' clicking behaviors. Findings - Research results show that with the aid of ontology the average precision rate of all cases is dramatically higher than the precision rate for the default search result. Even in the worst cases, in some situations, this ontology is still close to the precision rate for the default search result. Originality/value - This paper shows how it is possible to improve the precision rate of items retrieved after a search and thus avoid information overload.
The link between state-of-mind and individuals' willingness to adopt and continue using smartphones
(2018-01-01)
Shih, Po-Hong
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Yang, Keng-Chieh
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Yang, Chyan
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資訊管理與財務金融系註：原資管所+財金所
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Department of Information Management and Finance
Purpose Although numerous studies have examined factors that influence smartphone acceptance and use, few have analyzed cognitive age. This study aims to use the unified theory of acceptance and use of technology (UTAUT) to test two models to analyze the moderating effect of cognitive age. This research offers relevant suggestions among different cognitive age groups. Design/methodology/approach A questionnaire survey was conducted to collect research data in Taiwan and the UTAUT model was used. Model 1 ensures all four antecedent constructs among digital natives (those under 34 years old). Model 2 divides the digital immigrants into two groups to test the influence of cognitive age on the behaviors of smartphone use. This study tests Model 1 using AMOS 20 to examine the measurement and structural model and validates Model 2 using partial least squares (PLSs). Findings In Model 1, the digital natives have sufficient confidence to accept a new technology with ease and little effort owing to most educational resources and the widespread internet. Group 1 in Model 2 reveals that the behavior of digital immigrants is similar to that of digital natives. For Group 2 in Model 2, they tend to infer that skills or tasks they associate with having higher value are more difficult to learn. Originality/value This study provides another dimensional result for different cognitive age groups and it has to consider not only chronological age but also cognitive age in user behavior. The result can enrich the theoretical perspective on technology adoption and use behavior via cognitive age, which is a significant and important self-related factor that can help predict technology adoption and use behavior.
Urban and rural differences Multilevel latent class analysis of online activities and e-payment behavior patterns
(2013)
Hsieh, Tsui-Chuan
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Yang, Keng-Chieh
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Yang, Conna
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Yang, Chyan
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經營管理研究所
Purpose - The purpose of this article is to investigate urban and rural differences for online activities and e-payment behavior patterns. Design/methodology/approach - This study applied the MLCA model to investigate Internet usage patterns from 11 online applications among 10,909 Taiwan residents in 25 different regions. Findings - The results showed that online behavior patterns exhibited regional differences, as the regional segments affected the individual segments of different use patterns. For instance, the urban area comprised a higher proportion of members who were accustomed to internet applications and skilled in online shopping by using a credit card. The rural area made up a higher proportion of members who only occasionally used online services. Moreover, rural region residents used other payment methods (excluding credit cards) more often than urban region residents. As expected, users' personal characteristics also dictated the online behavior-pattern. For instance, people with higher-level income spent relatively more money for online shopping and often used various internet applications than others. Practical implications - The findings herein should help Internet service providers form an applicable guideline for developing service strategies of higher service satisfaction regarding products and users' needs. Originality/value - This study implemented a multilevel latent class model to investigate online behavior patterns that exhibited urban and rural differences, with the goal of providing service providers an understanding and mastery of their target users.