资源描述
Mining customer knowledge for tourism new product development and customer relationship management Original Research Article
Expert Systems with Applications
In recent years tourism has become one of the fastest growing sectors of the world economy and is widely recognized for its contribution to regional and national economic development. Tourism product design and development have become important activities in many areas/countries as a growing source of foreign and domestic earnings. On the other hand, customer relationship management is a competitive strategy that businesses need in order to stay focused on the needs of their customers and to integrate a customer-oriented approach throughout the organization. Thus, this paper uses the Apriori algorithm as a methodology for association rules and clustering analysis for data mining, which is implemented for mining customer knowledge from the case firm, Phoenix Tours International, in Taiwan. Knowledge extraction from data mining results is illustrated as knowledge patterns, rules, and knowledge maps in order to propose suggestions and solutions to the case firm for new product development and customer relationship management.
Article Outline
1. Introduction
2. The case firm – the Phoenix Tours International
2.1. Background of the case firm
2.2. The new product development procedure of the case firm
3. Methodology
3.1. Research framework
3.2. Questionnaire design and data collection
3.3. Relational database design
3.4. Association rule – Apriori algorithm
3.5. Clustering analysis
4. Research results
4.1. New product development
4.1.1. Travel area – inbound travel (pattern A)
4.1.1.1. Inbound travel association analysis
4.1.1.2. Inbound travel cluster analysis
4.1.2. Travel area – outbound travel – Asia (pattern B)
4.1.2.1. Outbound travel association analysis
4.1.2.2. Outbound travel cluster analysis – Asia area
4.2. Customer relationship management
4.2.1. Travel service
4.2.1.1. Travel service association analysis (pattern C)
4.2.1.2. Travel service cluster analysis
4.2.2. Direct marketing
4.2.2.1. Travel web site usage association analysis (pattern D)
4.2.2.2. Direct marketing cluster analysis
5. Discussion
5.1. In the regard of current market strategy
5.2. In the regard of future market strategy
5.3. In the regard of customer value and satisfaction
5.4. In the regard of new business model
6. Conclusion
Acknowledgements
References
Customer satisfaction driven quality improvement target planning for product development in automotive industry Original Research Article
International Journal of Production Economics
Customer satisfaction targets for vehicle attributes are set at the corporate level with limited consideration of the engineering feasibility and interactions between different product features. This paper presents a comprehensive framework for target planning for customer satisfaction driven quality improvement efforts in the product development process. The proposed framework facilitates a link between corporate decision making and engineering decision making by integrating best practices and structuring technical activities. Potential vehicle attributes are classified and prioritized for further improvement using Kano model and quality function deployment. Customer satisfaction targets are established based on rigorous business analysis and trade-off studies. These targets are converted into objective engineering metrics using regression models. Transfer function equations are developed to provide a link between higher-level product characteristics and lower-level design variables. The mathematical models are formulated as optimization problems to cascade down top-level targets to lower-level elements within given constraints. A case example is presented to demonstrate the proposed methodology.
Article Outline
1. Introduction
2. Target planning process
3. Methodology
3.1. Identify and prioritize improvement opportunities
3.1.1. Customer requirements
3.1.2. Corporate and regulatory requirements
3.1.3. Classification of vehicle attributes
3.1.4. Prioritization of improvement opportunities
3.2. Set attribute-level CS targets
3.3. Establish attribute-level objective metric (measurable) targets
3.4. Target cascading process
3.4.1. Identify critical characteristics
3.4.2. Develop transfer function model
3.4.3. Target cascading
3.4.3.1. Mathematical model
3.4.3.2. Vehicle-level target cascading
3.4.3.3. System-level target cascading
3.4.3.4. Sub-system-level target cascading
3.5. Component-level design optimization
4. Example
4.1. Vehicle-level target cascading model
4.2. System-level target cascading model
4.3. Sub-system-level target cascading model
5. Conclusion
Acknowledgements
References
Managing the trade-off between relationships and value networks. Towards a value-based approach of customer relationship management in business-to-business markets Original Research Article
Industrial Marketing Management
The management of buyer–seller relationships was an early antecedent to the development of customer relationship management (CRM) concepts. Currently, CRM concepts are being challenged by the rise of value networks. Value networks can and, often, do interfere with customer relationships and thereby call for a broader range of concepts to analyze and understand relationship management and the influence of value networks on relationships. This introductory article describes the nature of the problem between relationships and value networks, reviews the current state of research, and describes the contributions of the articles presented in this special issue on CRM in business-to-business markets.
Article Outline
1. Value networks—A challenge for business-to-business relationships
2. Value creation through cooperation—The evolution of cooperative buyer–seller relationships in the realm of business-to-business markets
3. Directions for relationship concepts
3.1. Value networks—The challenges for relationship management
3.2. Towards a common understanding of relationship concepts
3.3. Relationship-focused strategies in a network context
3.4. Managing the customer interaction in a multiple channel network
3.5. Knowledge management for network positioning
4. The road ahead
Acknowledgements
References
Vitae
A new mixed integer linear programming model for product development using quality function deployment Original Research Article
Computers & Industrial Engineering
Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product development, determining the fulfillment levels of design requirements (DRs) is crucial during QFD optimization. However, in real world applications, the values of DRs are often discrete instead of continuous. To the best of our knowledge, there is no mixed integer linear programming (MILP) model in which the discrete DRs values are considered. Therefore, in this paper, a new QFD optimization approach combining MILP model and Kano model is suggested to acquire the optimized solution from a limited number of alternative DRs, the values of which can be discrete. The proposed model can be used not only to optimize the product development but also in other applications of QFD such as quality management, planning, design, engineering and decision-making, on the condition that DR values are discrete. Additionally, the problem of lack of solutions in integer and linear programming in the QFD optimization is overcome. Finally, the model is illustrated through an example.
Article Outline
1. Introduction
2. Literature review
2.1. Optimization methods in QFD literature
2.2. Kano model in QFD literature
3. A new approach to QFD optimization
3.1. Kano model
3.2. Proposed MILP model
4. Illustration
4.1. Constructing the HOQ
4.2. Optimizing the development problem
5. Conclusion and discussion
Appendix A
References
Virtual product experience and customer participation—A chance for customer-centred, really new products Original Research Article
Technovation
This paper demonstrates how customers can be virtually integrated into a company's innovation process. New interaction tools allow companies to gain valuable input from customers via the Internet. First, we explain why too closely listening to customers may turn out to be problematic for the development of real new products. The KANO model shows that it is difficult for customers to express their latent needs as well as those which are taken for granted. New virtual interaction tools and virtual product experiences help to overcome these problems and enable customers to transfer their explicit and implicit knowledge to innovation teams. How to apply virtual interaction tools and how to virtually integrate customers into the innovation process in practice is illustrated in detail in the AUDI case study. Our case study findings show that virtual customer integration provides valuable input for new product development. This paper introduces virtual customer integration as a new means of coming up with customer-centred, really new products.
Article Outline
1. Introduction
2. Customers’ problems to articulate their needs
3. The virtual product experience
4. Concept of virtual customer integration
5. Virtual customer integration at AUDI
6. Management considerations of virtual customer integration
7. Discussion
References
Vitae
9,641 articles found for: pub-date > 2003 and tak(((WLAN product promotion) or (WLAN Customer Support) or (Specifications discussions) or (cooperative development) or (customer problems) or solutions) and ((Network IC) or Development or (Driven Development Project) or (Windows driver development and maintenance) or (WLAN chip verification)))
Customer interactivity and new product performance: Moderating effects of product newness and product embeddedness Original Research Article
Industrial Marketing Management
Using AHP and TOPSIS approaches in customer-driven product design process Original Research Article
Computers in Industry
Network-on-Chip design and synthesis outlook Original Research Article
Integration, the VLSI Journal
Identifying issues in customer relationship management at Merck-Medco Original Research Article
Decision Support Systems
A methodology to generate a belief rule base for customer perception risk analysis in new product development Original Research Article
Expert Systems with Applications
Research highlights
► A novel method to generate belief rule base for risk analysis in new product development is developed. ► A new way to quantify the influence of antecedent attributes on the consequence is proposed. ► Biases and inconsistencies can be reduced by the method during the belief rule base generation process. ► A case regarding customer perception risk analysis is then studied using the method proposed in the paper.
知名上市集成电路设计公司-，苏州工业园区长期策略合作的集成电路设计公司，延续半导体以人为本的经营理念，在中国设立集成电路设计公司，以开创中国半导体产业蓬勃发展为愿景，跃升世界第一流集成电路设计公司为永续经营目标。
微电子成立于2001年12月，位处苏州工业园区，总投资额美金1750万元，以集成电路设计为主要业务，主要产品为芯片。本着以人为本，企业与员工共同成长的信念，目前集成电路研发人员已占公司总人数的80%以上，同时，每位研发人员在进公司后，公司随即对其进行为期3个月至半年的集成电路设计教育训练，而后再以on—job training方式，让同仁透过学习获得成长，由此显见公司对于产品研发方面的重视程度。未来，在中国半导体产业蓬勃发展的基础上，微电子将致力于半导体集成电路的研发、芯片的销售与集成电路设计人才的培育，以期在全球半导体产业上占有一席之地。
Influences of customer preference development on the effectiveness of recommendation strategies Original Research Article
Electronic Commerce Research and Applications
Most previous studies on recommendation agents have been restricted to the problems of uncovering customer preferences during the process of understanding customers. However, studies on consumer psychology have indicated that customer preferences are often unstable and developed over time. Therefore, we assert that it is necessary to observe the degree to which customer preferences are developed since effectiveness of recommendations is affected by customers’ preference development. This study presents a scheme to identify the status of customers’ preference development and analyzes the influences of customer preference development on the effectiveness of various recommendation strategies.
Article Outline
1. Introduction
2. Theoretical background of customer preference development
2.1. Two perspectives of customer preference
2.2. Customer preference development
2.2.1. Dimensions of customer preference development
2.2.2. Customer segmentation by preference development
3. Research model and hypotheses
3.1. Research model: recommendation strategies and customer preference development
3.2. Hypotheses
4. Experimental design
4.1. Overview
4.2. Step 1: data collection and participants invitation
4.2.1. Movie dataset
4.2.2. Participants
4.3. Step 2: preference assessments
4.4. Step 3: measurement of preference development
4.4.1. Stability
4.4.2. Self-insight
4.5. Step 4: customer segmentation by preference development
4.6. Step 5: recommendation by various strategies and evaluation
4.6.1. Details of recommendation strategies
4.6.1.1. Recommendation by average opinion
4.6.1.2. Recommendation by expert opinion
4.6.1.3. Recommendation by collaborative filtering
4.6.1.4. Recommendation by content-based filtering
4.6.2. Evaluation metrics for recommendation performance
5. Results
6. Discussion
6.1. Theoretical discussion
6.2. Practical implications
7. Conclusion
Acknowledgements
Appendix A. Detailed explanation for recommendation by collaborative filtering
Appendix B. Detailed explanation for recommendation by content-based filtering
References
Practices and functions of customer reference marketing — Leveraging customer references as marketing assets Original Research Article
Industrial Marketing Management
Enabling through life product-instance management: Solutions and challenges Original Research Article
Journal of Network and Computer Applications
Optimizing product assortment under customer-driven demand substitution Original Research Article
European Journal of Operational Research
工作项目：
1，从事芯片的系统设计开发和验证；
2，负责芯片固件程序的编写；
3，负责解决芯片开发和验证过程遇到的问题；
4，帮助解决客户的需求和遇到的问题；
工作经验：
1，有USB/PCIE，记忆卡开发经验优先；
2，熟悉芯片开发流程和芯片设计开发原理；
3，熟练掌握C语言编程；
4，了解数字电路和模拟电路原理；
其他要求：
1，很好的工作有主动性；
2，很好的工作合作性；
3，很快的学习能力和解决问题的能力；
A process-oriented multi-agent system development approach to support the cooperation-activities of concurrent new product development Original Research Article
Computers & Industrial Engineering
Enabling content-based publish/subscribe services in cooperative P2P networks Original Research Article
Computer Networks
Developing integrated solu
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