Browsing by Author "Chen, Mu-Chen"

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A data mining based approach for travel time prediction in freeway with non-recurrent congestion
(2014-06-10)
Li, Chi-Sen
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study integrates three data mining techniques, K-means clustering, decision trees, and neural networks, to predict the travel time of freeway with non-recurrent congestion. By creating dummy variables and identifying important variables, not only is the prediction performance increased without increasing investment in equipment, but also important variables are obtained concerning the important locations of equipment in order to effectively assist public transit agencies with system maintenance. The experimental results for a segment of 36.1 km of National Freeway No. 1, Taiwan, with non-recurrent congestion show that, whether or not the data generated by the Electronic Toll Collection (etc) system is used as input variables, the travel time prediction method developed in this study is able to improve the prediction performance. Meanwhile, the proposed approach also reduces the percentage of samples with mean absolute percentage error (MAPE) > 20%. Furthermore, in this study, important variables are extracted from the decision tree in order to predict the travel time. Finally, the prediction models constructed in accordance with six scenarios are highly accurate due to the low MAPE values, which are from 6% to 9%. (C) 2014 Elsevier B.V. All rights reserved.
A novel process monitoring approach with dynamic independent component analysis
(2010-03-01)
Hsu, Chun-Chin
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Chen, Mu-Chen
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Chen, Long-Sheng
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
A novel process monitoring scheme is proposed to compensate for shortcomings in the conventional independent component analysis (ICA) based monitoring method. The primary idea is first to augment the observed data matrix in order to take the process dynamic into consideration. An outlier rejection rule is then proposed to screen out outliers, in order to better describe the majority of the data. Finally, a rectangular measure is used as a monitoring statistic. The proposed approach is investigated via three cases: a simulation example, the Tennessee Eastman process and a real industrial case. Results indicate that the proposed method is more efficient as compared to alternate methods. Crown Copyright (C) 2009 Published by Elsevier Ltd. All rights reserved.
A Particle Swarm Optimization Approach for Route Planning with Cross-Docking
(2015)
Chen, Mu-Chen
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Hsiao, Yu-Hsiang
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Reddy, Himadeep
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Tiwari, Manoj Kumar
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運輸與物流管理系註：原交通所+運管所
In cross-docking operations, planners need to coordinate the inbound, docking and outbound logistics operations to ensure a smooth flow of goods across the supply chain. The operation management of cross docking is a crucial task with high complexity for the logistics systems. This paper attempts to address the Vehicle Routing Problems (VRPs) of distribution centers with multiple cross-docks for processing multiple products. In this paper, the mathematical model intends to minimize the total cost of operations subjected to a set of time and capacity constraints. Due to high complexity of model, a variant of Particle Swarm Optimization (PSO) with a Self-Learning approach is tailored to solve the VRP. Two test problems are generated and results are obtained.
A study on the relationship between the PDSA cycle of green purchasing and the performance of the SCOR model
(2010)
Hwang, Yeong-Dong
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Wen, Yuan-Feng
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
When environmental problems are the focus, conflicts between the general public and company stakeholders affect both regional and global cooperation prompting conflicts in many areas. As a consequence, various initiatives have been designed and adopted that improve environmental performance while maintaining sustainable development. Green purchasing is applied as a useful tool to mitigate the environmental impacts of consumption and to promote clean production technology. The supply chain operations reference (SCOR) model is proposed by a supply chain council as a standard supply chain performance evaluation model. This model has been widely embraced by many modern organisations. The SCOR model can be applied to analyse supply chain performance in a systematic way. It can also aid in communication among all members in the supply chain, and can assist in the development of a design for a better supply chain network. To further improve the performance of the green purchasing process, which is critical in numerous industries, this study explores the relationship between the plan-do-study-act (PDSA) cycle of green purchasing and the SCOR purchasing/sourcing process and its performance indices/metrics. In this study, those companies which produce Taiwanese green label products are taken as samples. The PDSA cycle of green purchasing and the SCOR model are used to construct a structural equation model (SEM). An SEM analysis is conducted to establish the relationship between the PDSA of green purchasing, the sourcing process, and its performance on the SCOR model. The results of this study provide some suggestions for companies conducting green purchasing.
A Web Services-Based Collaborative Planning, Forecasting, and Replenishment (CPFR) Framework for Managing Spare Parts of Semiconductor Equipment
(2009-11-01)
Chen, Mu-Chen
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Chen, Kai-Ying
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Hsu, Ming-Fu
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Yeh, Cheng-Ta
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運輸與物流管理系註：原交通所+運管所
In a semiconductor foundry, equipment failure has long been recognized as a major cause of unpredicted breakdown which results in an excessive production loss. Equipment maintenance management is one of the essential tasks in semiconductor manufacturing. Due to the prosperity of Internet and IT, e-diagnostics and e-maintenance through the web have become important applications in the semiconductor industry. Web services (WSs) can assist the data integration in heterogeneous e-facturing systems to support faster and remote maintenance functions. In this paper, a WS-based collaborative planning, forecasting and replenishment (CPFR) framework, namely WS-CPFR, is developed to collaboratively manage the logistics activities of spare parts in semiconductor equipment between equipment suppliers and semiconductor factories.
Adaptive Kernel Principal Component Analysis (KPCA) for Monitoring Small Disturbances of Nonlinear Processes
(2010-03-03)
Cheng, Chun-Yuan
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Hsu, Chun-Chin
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
;
Department of Transportation and Logistics Management
The Tennessee Eastman (TE) process, created by Eastman Chemical Company, is a complex nonlinear process. Many, previous studies focus on the detectability of monitoring a multivariate process by using TE process as an example. Principal component analysis (PCA) is a widely used dimension-reduction tool for monitoring multivariate linear process. Recently, the kernel principal component analysis (KPCA) has emerged as all effective method to tackling the problem of nonlinear data. Nevertheless, the conventional KPCA used the sum of squares of latest observations is the monitoring statistics and hence failed to detect small disturbance of the process. To enhance the delectability of the KPCA-based monitoring method, an adaptive KPCA-based monitoring statistic is proposed in this paper. The basic idea of the proposed method is first adopting the multivariate exponentially moving average to predict the process mean shifts and then combining the estimated mean shifts with the extracted components by KPCA to construct the adaptive monitoring statistic. The efficiency of the proposed monitoring scheme is implemented in a simulated nonlinear system and in the TE process. The experimental results indicate that the proposed method outperforms the traditional PCA and KPCA monitoring schemes.
Adopting the Extension of UTAUT Model to Investigate the Determinants of e-book Adoption
(2014-01-01)
Hsu, Chia-Lin
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Chen, Mu-Chen
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Lin, Yu-Hsiang
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Chang, Kuo-Chien
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Hsieh, Ai-Yun
This study aims to examine the key factors affecting users' adoption of e-book by an extension of unified theory of acceptance and use of technology (UTAUT) with environment concern, perceived benefit, and benevolence trust. 343 samples of data were analyzed using a structural equation modeling (SEM). Results showed that user's adoption of e-book is significantly determined by all of the factors.
An effective pricing model for the congestion alleviation of e-commerce logistics
(2019-03-01)
Chen, Mu-Chen
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Wu, Pei-Ju
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Hsu, Yu-Han
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
E-retailers and home delivery companies have struggled with logistics congestion. Hence, this study aims to develop a pricing model for alleviation of congestion in e-commerce logistics. The analytical results reveal that a congestion surcharge mechanism influences the behavior of a home delivery company and e-commerce consumers in terms of early delivery and delayed delivery, cargo volume, and consumers' favorite delivery time. Moreover, e-commerce logistics fees in practice are established by negotiation between e-retailers and home delivery companies. The proposed model can be treated as a reference for e-retailers and home delivery companies to determine appropriate logistics fees. This pioneering study develops a congestion pricing model to deal with congestion problems in e-commerce logistics, which can effectively reflect the impact of various congestion fees on the behavior of e-commerce stakeholders.
An efficient ICA-DW-SVDD fault detection and diagnosis method for non-Gaussian processes
(2016)
Chen, Mu-Chen
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Hsu, Chun-Chin
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Malhotra, Bharat
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Tiwari, Manoj Kumar
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運輸與物流管理系註：原交通所+運管所
Independent Component Analysis (ICA) has been extensively used for detecting faults in industrial processes. While applying ICA to process monitoring, the inability of identifying the important components affect the fault diagnosis ability. For further improving the competence of ICA, this paper proposes an approach integrating ICA, Durbin Watson (DW) criterion and Support Vector Data Description (SVDD) to monitor non-Gaussian process for detecting faults. In the proposed approach, namely ICA-DW-SVDD, ICA is a non-Gaussian information extractor from original variables, DW identifies dominating ICs, and SVDD plays the role of fault detector. This paper also discusses the retracing method to detect original variables causing disturbance in the process. One simulation case and the Tennessee Eastman Process are used to demonstrate the effectiveness of our proposed approach.
An empirical analysis of the antecedents of e-satisfaction and e-loyalty: focusing on the role of flow and its antecedents
(2013-06-01)
Hsu, Chia-Lin
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Wu, Cou-Chen
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Many previous studies have identified that flow is a constructive construct for explaining consumer behaviors in the context of computer-mediated environments. Success in websites is dependent on their ability to create opportunities for consumers to experience flow. However, relatively little research has been conducted to understand how that flow forms (i.e., antecedents of flow) and impacts subsequently (i.e., consequences of flow). Thus, this research contributes in integrating the technology acceptance model (TAM), flow theory, and regulatory fit theory to investigate the unique role of flow for understanding the antecedents and consequences of flow. The results showed that perceived ease of use, perceived usefulness and regulatory fit exhibited significant positive effects on flow, and additionally the results indicated that regulatory fit has the strongest effect on flow. The results also confirmed that flow, perceived ease of use and perceived usefulness significantly affect e-satisfaction, which in turn affects e-loyalty, and additionally the results indicated that flow is the strongest determinant of e-loyalty. Important implications of these findings are discussed and directions for future research are also provided.
Apply Ensemble Empirical Mode Decomposition to Discover Time Variants of Metro Station Passenger Flow
(2017-01-01)
Chen, Mu-Chen
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Chen, Long-Sheng
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Wei, Yu
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This paper applies both Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) to extract the EMD and EEMD components from a data set of passenger flows of a station in the metro system, and illustrates the time variants of short-term passenger flow for this data sets. The results indicate that the extracted meaningful EEMD components reveal a more unique pattern than the extracted meaningful EMD components. The patterns of these EEMD components of passenger flow in the metro system are more specific and can be explained more easily for management purposes.
Applying a Kansei engineering-based logistics service design approach to developing international express services
(2015-01-01)
Chen, Mu-Chen
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Chang, Kuo-Chien
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Hsu, Chia-Lin
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Xiao, Jia-Hau
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運輸與物流管理系註：原交通所+運管所
Purpose - To obtain a competitive advantage in the logistics market, international express companies should design services to stimulate customers\' usage intention by understanding customers\' affective perceptions (or in Japanese, Kansei) of the service offerings. Thus, the purpose of this paper is to analyze the relationships among the service elements of international express, customer Kansei perceptions, and intentions to use the service, to provide new ideas for the design of international express services (IESs). Design/methodology/approach - By using Kansei engineering approach, customers\' Kansei perceptions related to elements of IES are first determined, and the logistic regression technique is then used to analyze three constructed models based on the relationships among the service elements of international express, customers\' Kansei perceptions, and usage intention. Findings - Accordingly, five critical service elements that correspond to four vital Kansei words related to usage intention were obtained based on cross-comparisons of the results of three models. The findings have important implications for international express managers, in that the priorities in designing services should be those service elements that favorably elicit certain Kansei perceptions among customers and effectively lead to customers\' usage intention in the pre-purchase phase. Moreover, some important missing Kansei perceptions further derived from customers\' real service experiences in the post-purchase stage should be incorporated into future design considerations. Originality/value - This study incorporated customers\' Kansei perceptions into the procedure of IES design. By understanding the service elements and feelings that customers deem important, international express companies can improve the content of existing services and strengthen the design of new services to increase customers\' behavioral intentions.
Applying big data analytics to support Kansei engineering for hotel service development
(2019-02-04)
Chen, Mu-Chen
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Hsiao, Yu-Hsiang
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Chang, Kuo-Chien
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Lin, Ming-Ke
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運輸與物流管理系註：原交通所+運管所
Purpose Leisure and tourism activities have proliferated and become important parts of modern life, and the hotel industry plays a necessary role in the supply for and demand from consumers. The purpose of this paper is to develop guidelines for hotel service development by applying a service development approach integrating Kansei engineering and text mining. Design/methodology/approach The online reviews represent the voice of customers regarding the products and services. Consumers' online comments might become a key factor for consumers choosing hotels when planning their tourism itinerary. With the framework of Kansei engineering, this paper adopts text mining to extract the sets of Kansei words and hotel service characteristics from the online contents as well as the relationships among Kansei words, service characteristics and these two sets. The relationships are generated by using link analysis, and then the guidelines for hotel service development are proposed based on the obtained relationships. Findings The results of the present research can provide the hotel industry a comprehensive understanding of hotels' customers opinions, and can offer specific advice on how to differentiate one's products and services from competitors' in order to improve customer satisfaction and increase hotels' performance in the end. Finally, this study finds out the service development guidelines to meet customers' requirements which can provide suggestions for hotel managers. The implications both for academic and industry are also drawn based on the obtained results. Originality/value Now, in the internet era, consumers can comment on their hotel living experience directly through the internet. The large amount of user-generated content (UGC) provided by consumers also provides chances for the hospitality industry to understand consumers' opinions through online review mining. The UGC with consumers' opinions to hotel services can be continuously collected and analyzed by hoteliers. Therefore, this paper demonstrates how to apply the hybrid approach integrating Kansei engineering and online review mining to hotel service development.
Applying Kansei Engineering and data mining to design door-to-door delivery service
(2018-06-01)
Yeh, Cheng-Ta
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
This study proposes a service design approach integrating Kansei Engineering and a data mining technique, in which Kansei Engineering is an ergonomic approach of customer-oriented product/service development and can translate the users' subjective perceptions into a design specifications. The integrated approach collects customers' relevant perceptual vocabulary and service properties based on the Kansei Engineering procedure. Subsequently, it quantifies the relationship among service properties, perceptual responses and usage intention through the data mining technique using a decision tree. A case of door-to-door delivery (D2DD) service is adopted to demonstrate that the proposed approach can incorporate the customers' feelings into the process of service design or improvement and illustrate that the decision tree is suitable to be integrated with Kansei Engineering. The analytical results show the influence of a combination of different service properties (resp. perceptual responses) on a perceptual response (resp. usage intention). It is found that the combinations of crucial perceptual responses result in positive (resp. negative) usage intention and the property combinations result in these crucial perceptual responses. Accordingly, the D2DD service provider can improve or create its service based on the research findings.
Applying Kansei engineering to design logistics services - A case of home delivery service
(2015-07-01)
Chen, Mu-Chen
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Hsu, Chia-Lin
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Chang, Kuo-Chien
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Chou, Man-Chi
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運輸與物流管理系註：原交通所+運管所
Home delivery service (HDS) has grown fast in recent years because more and more customers engage in Internet and television shopping. Moreover, due to the rising competition in the HDS sector, service providers need to put more concentration on the continual improvement and differentiation of service to maintain the competitive advantage. After experiencing the current services, customers are always expecting the new ones. Thus, the idea of new service design never ends. Designers always have to insight into the real feelings of customers so that they could design the new service, which is able to meet customers\' expectation. Kansei engineering is a means to transform real voices of customers into the product and service design. This method is able to quantify the relationship between feelings represented by simple words and design elements. In this study, the Partial Least Square (PLS) is used to analyze the relationships between the real feelings of customers and characteristics of HDS. Finally, this study combines those characteristics, which are strongly related to important feelings, to obtain the original idea of new design of HDS. Relevance to industry: As stated in this abstract, our study offers an exemplification on applying Kansei engineering to design service in service industries. Specifically, along with the application of Kansei engineering, the research findings offer a technique for service design of service industries. (C) 2015 Elsevier B.V. All rights reserved.
Applying loss aversion to assess the effect of customers' asymmetric responses to service quality on post-dining behavioral intentions: An empirical survey in the restaurant sector
(2010-12-01)
Chang, Kuo-Chien
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Chen, Mu-Chen
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Hsu, Chia-Lin
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Using the loss aversion concept, this paper attempts to investigate the relationship between service quality and customers' post-dining behavioral intentions in the restaurant sector. Incorporating the DINESERV instrument, the results gained from a Chinese chain restaurant indicate that a decrease in service quality from the reference point (customer's expectation) will decrease the perceived service value and customer satisfaction, but that an increase in service quality may not have significant effects on these two behavioral constructs. Moreover, the behavior-related causal relationships underlying service quality suggest that perceived service value and attitudinal loyalty succeed in acting as mediating variables within the model. (C) 2009 Elsevier Ltd. All rights reserved.
Applying loss aversion to investigate service quality in logistics A moderating effect of service convenience
(2010)
Hsu, Chia-Lin
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Chen, Mu-Chen
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Chang, Kuo-Chien
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Chao, Chuang-Min
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運輸與物流管理系註：原交通所+運管所
Purpose - Using the concept of loss aversion, this paper aims to investigate the relationship between service quality and customer loyalty in the home delivery industry. The second purpose of this paper is to investigate the moderating effect of service convenience in the relationship between service quality and customer loyalty. Furthermore, this paper attempts to demonstrate the existence of a moderating effect either on the service quality loss (SQLOSS)-customer loyalty link, or on the service quality gain (SQGAIN)-customer loyalty link, or on both. Design/methodology/approach - In this paper, the research model and hypotheses are constructed through a literature review. Data are collected by a questionnaire survey, and the adapted SERVQUAL scale is taken as the measurement instrument. Structural equation modeling is adopted to confirm the above relationships. Findings - From the results come the finding that a loss in service quality has a greater effect on customer loyalty than that of a SQGAIN in the home delivery industry. This paper also proves that the relationship between service quality and customer loyalty is moderated by service convenience. Originality/value - This paper demonstrates the effect of asymmetric response of service quality on customer loyalty.
Applying Neural Networks to Detect the Failures of Turbines in Thermal Power Facilities
(2009)
Chen, Kai-Ying
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Chen, Long-Sheng
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Chen, Mu-Chen
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Lee, Chia-Lung
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運輸與物流管理系註：原交通所+運管所
Due to the growing demand on electricity, how to improve the efficiency of equipment has become one of the critical issues in a thermal power plant. Related works reported that efficiency and availability depend heavily on high reliability and maintainability. Recently, the concept of e-maintenance has been introduced to reduce the cost of maintenance. In e-maintenance systems, the intelligent fault detection system plays a crucial role for identifying failures. Machine learning techniques are at the core of such intelligent systems and can greatly influence their performance. Applying these techniques to fault detection makes it possible to shorten shutdown maintenance and thus increase the capacity utilization rates of equipment. Therefore, this work applies Back-propagation Neural Networks (BPN) to analyze the failures of turbines in thermal power facilities. Finally, a real case from a thermal power plant is provided to evaluate the effectiveness.
Applying Quality Function Development to Develop the Home Delivery Service Model for Specialty Foods in Traditional Market
(2012-01-01)
Chen, Mu-Chen
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Hsu, Chia-Lin
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Lee, Ying-Yi
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Although a few studies have been done to investigate the issue of new service development (NSD) in an emerging market, it is deficiency in the development of home delivery service (HDS) for specialty foods in traditional market. Thus, this study takes a Taiwan\'s HD companies as a subject and uses quality function deployment (QFD) to develop the home delivery service model based on NSD model. In the area of voice of customer (VOC), the results reveal that e-shoppers put emphasis on the security of personal information and trading mechanism. As for HDS for specialty foods in traditional market, customers pay attention to the speed of delivery service, freshness of foods and quick responses from HD companies when any problems happen during delivery. Furthermore, in the area of voice of engineering (VOE), the main suggestions for improvement are training staff, setting up a brand, and strengthening system effectiveness and information safety.
Applying the Kano model and QFD to explore customers' brand contacts in the hotel business: A study of a hot spring hotel
(2011)
Chang, Kuo-Chien
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Chen, Mu-Chen
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運輸與物流管理系註：原交通所+運管所
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Department of Transportation and Logistics Management
Brand contacts are a variety of elements about how customers come into contact with a brand and how they communicate their values about it to other potential customers. For the sake of cost and efficiency, brand contacts can be investigated not only from a customer perspective but also from that of the service provider. This paper thus attempts to integrate the Kano model and quality function deployment (QFD) to explore brand contact elements. The results gained from an empirical study of a hot spring hotel indicate that customers' perceptions about contact elements are mostly classified into one-dimensional and must-be attributes by the Kano model. The proposed approach contributes to the creation of attractive contact elements that have an enormous potential to further increase customer satisfaction and differentiate competitors. Moreover, along with the 10 technical characteristics obtained by the integrated approach, the customers' contact experiences are displayed through the brand contact priority grid, both of which provide references for future hotel business development. Lastly, atmosphere-oriented brand contacts dominate customers' brand perceptions more than others, in that they lessen customers' sense of risk and uncertainty toward product/service offerings. A discussion of the findings including managerial implications is also presented in this paper.