Browsing by Author "Chang, Ai-Che"

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Clustering analysis prioritization of automobile logistics services
(2010)
Trappey, Charles V.
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Trappey, Amy J. C.
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Chang, Ai-Che
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Huang, Ashley Y. L.
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管理科學系
Purpose - The purpose of this paper is to provide a clustering approach to segment supply chain partners in the automobile industry and prioritize services offered by third party logistics service (3PL) providers. Design/methodology/approach - In total, 98 automobile and auto-parts manufacturers are surveyed to identify service needs, preferences, and outsourcing commitments. By applying a two-stage clustering approach combined with Ward's minimum-variance method and the K-means algorithm, the logistics companies prioritize their services to better satisfy groups of customers with specific preferences. Findings - Four distinctive groups of manufacturers are identified using the two-stage clustering approach. The clusters separate logistic preferences and outsourcing patterns of after market parts suppliers, original equipment service parts suppliers, original equipment manufacturer parts suppliers, and tier one car makers. The paper finds that distribution and delivery services hold the highest percentage of services outsourced among the manufacturers. Originality/value - This paper models logistic services as customizable services and develops a data system methodology to define the profiles of automobile manufacturers and their preferred logistic services. Through the analysis of service preferences and clustering, the paper identifies the key logistic services that can be customized for members of the automobile supply chain. A case is provided which demonstrates how a logistics company can provide customized service designs for specific target markets and customers.
Deriving Competitive Foresight Using an Ontology-Based Patent Roadmap and Valuation Analysis
(2019-04-01)
Trappey, Amy J. C.
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Trappey, Charles, V
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Chang, Ai-Che
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Li, Jason X. K.
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交大名義發表
An ontology-based patent roadmap and valuation analysis approach provides competitive foresights for a corporation's associated patent portfolios and the underlying business processes. To demonstrate the methodology and computer supported analysis system, the patent portfolios of two global smart e-retailers are compared. The patents in each company's portfolio are text mined and categorized based on the smart retailing ontology schema. Both cases' text mining results are plotted as patent portfolio roadmaps, linking patents to innovation categories, commercial applications, and business process models. The three-dimensional (3-D) patent valuation analysis method provides foresights of the companies' competitive advantages related to "patent scope" (PS), "patent importance" (PI), and "patent innovation" (PIN). The research implements a computer supported system to provide evidence how companies utilize patent portfolios as key strategies for protecting business related intellectual properties (IPs) while implementing sustainable and competitive business processes.
Global Logistic Management for Overseas Production Using a Bulk Purchase 4PL Model
(2013-01-01)
Trappey, Amy J. C.
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Trappey, Charles V.
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Chang, Ai-Che
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Lee, W. T.
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Cho, Hsueh-Yi
In order to improve the quality of the components supplied by key suppliers and delivered to the final assembly sites overseas efficiently and timely, a new logistics business model and assessment analysis are proposed using services provided by fourth-party logistics (4PL) companies. In the research, a Petri Net process modeling approach is adopted to construct the model and identify the current bottlenecks discovered in the as-is (existing) logistic processes. According to the benefits of the proposed e-logistics information system and its to-be process improvement, total operating time and total operating costs can be reduced 41% and 21% respectively. The global logistics information platform is built to enhance the logistics management efficiency of manufacturers with multi-national operations for improving their global competitiveness.
The Improved Global Supply Chain Material Management Process Framework for One-Stop Logistic Services
(2015-01-01)
Hsu, Abby P. T.
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Chang, Ai-Che
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Trappey, Amy J. C.
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Trappey, Charles V.
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Lee, W. T.
This research focuses on the material procurement process improvement of a manufacturer under one-stop logistic services and proposes a to-be process offering a vendor-managed inventory (VMI) and information integration services provided by one-stop logistic services providers (1SLP) for shortening the procurement and manufacturing lead time, and enhancing the information flow accuracy and transparency. The 1SLP is an integrator that assembles the resources, capabilities, and technologies of supply chain networks to design and implement comprehensive logistic solutions. The research develops the 1SLP process framework by dividing the service scope into four service models. We use a case example to demonstrate the improved process. The case company is a leading manufacturer in producing projectors for the global market. The current material procurement process causes long lead times, delays the manufacturing process, and does not integrate all information in the supply chain. In the to-be model, a 1SLP incorporated model 2 services and provides a VMI warehouse as a value-added service and integrated information platform to ensure the buyer\'s inventory level and implements appropriate logistics optimization for efficient delivery. The AnyLogic Simulation Software is used to model the current and the to-be business processes. The comparison between the as-is and the to-be models demonstrates that the improved material procurement process increases the current process\'s efficiency under the one-stop services without impeding product availability to the target market.
Using System Dynamics Analysis for Performance Evaluation of IoT Enabled One-Stop Logistic Services
(2014)
Hsu, Abby P. T.
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Lee, W. T.
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Trappey, Amy J. C.
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Chang, Ai-Che
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Trappey, Charles V.
This research focuses on a methodology applying Internet of Things (IoT) technology and enabling the material procurement process improvement of a manufacturer. The one-stop logistic service provider (1SLP) is an integrator that assembles the resources, capabilities, and technologies of supply chain networks to design and implement comprehensive logistic service solutions. This research develops the IoT enabled 1SLP process framework and uses a case example to demonstrate the improved process with a system dynamic (SD) assessment. The current material procurement process of the case requires excessive operation times and the related data do not integrate with the supply chain related information. The 1SLP offers to-be (improved) logistics support incorporating IoT to shorten the operational time and enhance the information flow accurately and transparently. For the SD assessment, the results show that the to-be model improves the IoT process efficiency with the IoT when benchmarked with the as-is current processes.
Using System Dynamics Analysis for Performance Evaluation of IoT Enabled One-Stop Logistic Services
(2015-01-01)
Hsu, Abby P. T.
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Lee, W. T.
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Trappey, Amy J. C.
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Chang, Ai-Che
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Trappey, Charles V.
This research focuses on a methodology applying Internet of Things (IoT) technology and enabling the material procurement process improvement of a manufacturer. The one-stop logistic service provider (1SLP) is an integrator that assembles the resources, capabilities, and technologies of supply chain networks to design and implement comprehensive logistic service solutions. This research develops the IoT enabled 1SLP process framework and uses a case example to demonstrate the improved process with a system dynamic (SD) assessment. The current material procurement process of the case requires excessive operation times and the related data do not integrate with the supply chain related information. The 1SLP offers to-be (improved) logistics support incorporating IoT to shorten the operational time and enhance the information flow accurately and transparently. For the SD assessment, the results show that the to-be model improves the IoT process efficiency with the IoT when benchmarked with the as-is current processes.
Using Web Mining and Perceptual Mapping to Support Customer-Oriented Product Positions and Designs
(2016)
Trappey, Amy J. C.
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Trappey, Charles V.
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Chang, Ai-Che
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Chen, Luna W. L.
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管理科學系
In recent years, many e-commerce websites provide consumer feedback functions and social networks, allowing customers to share their purchasing and usage experiences online. Companies collect and analyze information from customers\' reviews through the platform to understand the customers impressions of the products they purchased. Online customer reviews has been widely regarded as an important source of information influencing customers buying decisions. In addition, online customer reviews help companies to redesign their products with key features that better positions to target customers in promising market sectors. This research uses online customer reviews as the business intelligence (BI) corpus. After determining the source webpage of customer reviews, a web crawler is needed to collect customer review text. Afterwards, computer-assisted text mining, clustering analysis, and perceptual mapping are applied to develop a formal methodology to compare similar products in a given domain. In this research, the consumer electronic sector is studied. Mobile phone customer reviews are web crawled, collected, mined, and analyzed. The study assists mobile phone manufacturers to understand the voice of customers in both positive and negative perspectives of post-purchasing experiences. The customer-preferred product functions, hardware/software/app features, and price positions, as key business intelligence, are derived for new product designs and market launches.
Web Mining Customer Perceptions to Define Product Positions and Design Preferences
(2020-04-01)
Chang, Ai-Che
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Trappey, Charles, V
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Trappey, Amy J. C.
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Chen, Luna W. L.
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交大名義發表
E-commerce provides a global platform supporting product transactions through the consumer purchase lifecycle including communications of perceived satisfaction and dissatisfaction. The customer feedback functions and social networks of many e-commerce websites allow for the creation of extremely large databases that can be mined to model the customers' perceptions toward online purchases. This research uses online customer reviews as the business intelligence corpus to help companies redesign products that better satisfy consumer preferences and differentiate their product offerings. After identifying the specific webpages of customer reviews, a web crawler collects review text. Computer-supported text mining, cluster analysis, and perceptual mapping are combined as a systematic analytic approach to compare products in a given domain. The study assists phone manufacturers to understand the positive and negative perceptions of customers related to their post-purchase experiences. The customer-preferred product functions, features, and price positions provide valuable strategic intelligence for new product designs and market differentiation.