Browsing by Author "Wang, Chih-Hsuan"

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A market-oriented approach to accomplish product positioning and product recommendation for smart phones and wearable devices
(2015-04-18)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Recently, several global companies start to develop wearable devices like smart watches or smart glasses to avoid market saturation in smart phones, especially when wireless technology was rapidly shifting from the third to the fourth generation. In order to better understand the relative strengths and weaknesses of smart alternatives, this paper presents a market-oriented framework to accomplish product positioning and product recommendation. Initially, correspondence analysis is applied to elicit expert perceptions for conducting product positioning. Then, based on customer preferences, product recommendation can be accomplished in either an unsupervised way (purchase profiles for new products are unavailable) or a supervised manner (for justifying the validity of the proposed recommender system). In particular, analytical hierarchy process is employed to elicit customers\' choices among smart alternatives (treated as prior information or decision labels). In summary, managerial insights are provided as follows: (1) smart phones are good at providing a platform for satisfying home entertainment, (2) smart watches are perceived as auxiliary carriers to accomplish health care and safety monitoring and (3) smart glasses are promising to fulfill industrial operation, logistics service and homeland security.
A novel approach to conduct the importance-satisfaction analysis for acquiring typical user groups in business-intelligence systems
(2016-01-01)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Business intelligence (BI) is a powerful tool to conduct causality analysis and corporate diagnoses since it provides a data-driven approach to link firms\' strategic goals into tactical policies and operational actions. Specifically, BI consists of a series of architectures and techniques like database, data warehousing, and data mining that transform raw data into useful information to provide decision supports. In reality, typical BI user groups involve financial analysts, marketing planners, general managers, field staffs, upstream suppliers, and downstream customers. Inspired by the concept of STP (segmentation-target-positioning) and product family design, BI systems need to be customized to satisfy diverse user groups and tailored to a firm for solving complicated but specific business problems. Consequently, a novel framework is proposed to fulfill the following goals: (1) incorporating user preferences to identify key design features that best fit BI\'s main segments for achieving customer acquisition, (2) transforming user perceptions into quantitative degrees of satisfaction for accomplishing customer retention, and (3) conducting the importance-satisfaction analysis to generate managerial insights for developing next-generation BI systems. (C) 2015 Elsevier Ltd. All rights reserved.
A novel approach to incorporate customer preference and perception into product configuration: A case study on smart pads
(2013-09-01)
Wang, Chih-Hsuan
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Hsueh, One-Zen
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工業工程與管理學系
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Department of Industrial Engineering and Management
This paper proposes a hybrid framework combining AHP (analytical hierarchy process), KM (Kano model), with DEMATEL (decision making trial and evaluation laboratory) to incorporate customer preference and perception into the process of product development. Initially, AHP is applied to respondents to form a basis of market segmentation. Thereafter, with respect to identified segments, AHP and KM are employed to extract customer preference for design attributes (DAs) and customer perception of marketing requirements (MRs), respectively. Finally, by means of DEMATEL, the causal relationships between MRs and DAs are systematically recognized to uncover new ideas of next-generation products. (C) 2013 Elsevier B.V. All rights reserved.
A Novel Framework to Achieve Innovative Product Design and Recommendation for Multi-Functional Tablets: A TRIZ Perspective
(2017-01-01)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Recently, the boundaries between smartphones, tablets and ultrabooks are becoming much more blurred than before. To sustain in a fiercely competitive environment, global brand companies start to design multi-functional products to satisfy diverse consumer requirements. For instance, Asus and Lenovo design Padfones (a smartphone inside) and Yoga Pro3 (a micro-projector inside) to enhance visualization of smartphones and tablets, respectively. Meanwhile, Acer, Sony, and Fuji develop varieties of tablets like Padbooks (pad + keyboard) and Padnotes (pad + stylus pen) to enhance keyboard interface. In this study, a TRIZ (theory of inventive problem solving) based framework is presented to analyze these innovative ideas and indicate how innovative solutions tackle the trade-offs between the improving features and the worsening features. Thereafter, rough set theory (RST) is applied to elicit the causalities between user preferences for ergonomic features and demographic variables. Finally, product recommendation w.r.t. the niche segments can be accordingly achieved.
A novel framework to evaluate programmable logic controllers: a fuzzy MCDM perspective
(2016-04)
Wang, Chih-Hsuan
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Wu, Hui-Shan
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工業工程與管理學系
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Department of Industrial Engineering and Management
A programmable logic controller (PLC) is a real-time system operated in severe conditions such as high/low temperatures or tough environments with excessive electrical noise. In particular, a PLC is designed to connect and control multiple mechatronic devices such as facility sensors and actuators and thus the issue of selecting/assessing PLC suppliers is critically important to achieve automatic process control and facility monitoring. In reality, various MCDM (multi-criteria decision making) composed of MADM (multi-attribute) and MODM (multi-objective) based schemes are frequently adopted to tackle the problem of supplier selection. Nevertheless, most of them have the following demerits: (1) the causal dependences between main criteria (or associate attributes) are rarely considered (2) a large number of pairwise comparisons are usually required to conduct the evaluation process. Consequently, a novel framework combining fuzzy DEMATEL, fuzzy AHP, with fuzzy Delphi is proposed to overcome the aforementioned shortcomings. Without requiring tedious pairwise comparisons, the importance weights of main criteria (associated attributes) and the performance scores of PLC vendors are systematically fused into the whole evaluation process. Furthermore, an industrial example is demonstrated to assist PLC practitioners in assessing the top three suppliers, such as SIEMENS (31 %), Allen-Bradley (22 %) and Mitsubishi (13 %).
Apply robust segmentation to the service industry using kernel induced fuzzy clustering techniques
(2010-12-01)
Wang, Chih-Hsuan
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交大名義發表
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工業工程與管理學系
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National Chiao Tung University
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Department of Industrial Engineering and Management
To understand customers' characteristics and their desire is critical for modern CRM (customer relationship management). The easiest way for a company to achieve this goal is to target their customers and then to serve them through providing a variety of personalized and satisfactory goods or service. In order to put the right products or services and allocate resources to specific targeted groups, many CRM researchers and/or practitioners attempt to provide a variety of ways for effective customer segmentation. Unfortunately, most existing approaches are vulnerable to outliers in practice and hence segmentation results may be unsatisfactory or seriously biased. In this study, a hybrid approach that incorporates kernel induced fuzzy clustering techniques is proposed to overcome the above-mentioned difficulties. Two real datasets, including the WINE and the RFM, are used to validate the proposed approach. Experimental results show that the proposed approach cannot only fulfill robust classification, but also achieve robust segmentation when applied to the noisy dataset. (C) 2010 Elsevier Ltd. All rights reserved.
Association rule mining and cognitive pairwise rating based portfolio analysis for product family design
(2019-04-01)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Changing customer needs coupled with rapid technology advances has boosted stronger requirements for a greater variety of consumer electronics. This trend has forced global companies to reconsider their product-positioning strategies. To reduce design cost and shorten the time to market, portfolio analysis for product family design is usually adopted to acquire diverse but related market applications. This study presents a novel framework to implement product differentiation and product configuration. Initially, association rule mining is used to capture user perceptions to identify the significant portfolios of hedonic attributes. Secondly, cognitive pairwise rating is conducted to elicit user preferences for utilitarian attributes (UAs). Finally, the Technique for Order Preference by Similarity to Ideal Solution is used to prioritize the optimal portfolios of UAs. Experiment results show that keyboard interface, body material, and screen size are the most concerned HAs for differentiating the product family while CPU performance is the most important UA for configuring padbooks, ultrabooks and notebooks. In summary, this research allows companies to effectively and efficiently incorporate user perceptions or preferences into the entire decision-making process.
Combining balanced scorecard with data envelopment analysis to conduct performance diagnosis for Taiwanese LED manufacturers
(2016)
Wang, Chih-Hsuan
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Chien, Yu-Wei
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工業工程與管理學系
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Department of Industrial Engineering and Management
Light emitting diode (LED) is a popular component to replace the traditional lighting source or advertising sign display. In 2014, high-brightness LED has a strong growth in backlight display, mobile appliances, automotive devices and outdoor illumination. However, emerging technologies in compound materials, epitaxying, packaging and new entrants result in a scale-based economy and intensively competitive environment. Inspired by the concept of business analytics, this paper proposes a novel framework to conduct corporate diagnosis for Taiwanese LED manufacturers: (1) balanced scorecard is fused with data envelopment analysis to address the impact of operational efficiency on performance outcomes, (2) financial and non-financial indicators are incorporated into the process of performance measurement, (3) the intricate causalities between key performance indicators (KPIs) and multiple outcomes (i.e. earnings per share and return on equity) are captured and (4) managerial insights are provided to indicate adaptive adjustment on significant KPIs. More importantly, a data-set comprising representative Taiwanese LED companies spanned from 2010 to 2014 is used to justify the validity of the proposed framework.
Combining fuzzy AHP and fuzzy Kano to optimize product varieties for smart cameras: A zero-one integer programming perspective
(2014-09-01)
Wang, Chih-Hsuan
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Wang, Juite
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工業工程與管理學系
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Department of Industrial Engineering and Management
In an era of global customization, dominating the majority market with a single product has become increasingly difficult and almost impossible for most companies. In contrast, they must provide various product varieties that attract diverse customers, particularly when acquiring distinct market segments. In practice, however, most companies cannot effectively reduce the gap between customer requirements and design characteristics, although this impacts the profitability and future growth of companies. Meanwhile, companies often get stuck in the trade-offs between enhancing product varieties and controlling manufacturing costs. Accordingly, this paper proposes a hybrid framework that combines fuzzy analytical hierarchy process (AHP), fuzzy Kano model with zero-one integer programming (ZOIP) to incorporate customer preferences and customer perceptions into the decision-making process of product configuration. Specifically, fuzzy AHP is used to extract customer preferences for core attributes while fuzzy Kano model is utilized to elicit customer perceptions of optional attributes. Finally, by virtue of ZOIP, the optimal product varieties ( smart cameras) for distinct segments are determined by maximizing overall customer utility (OCU) and taking a firm\'s pricing policy into account. (C) 2014 Elsevier B.V. All rights reserved.
Combining multiple correspondence analysis with association rule mining to conduct user-driven product design of wearable devices
(2016-03)
Wang, Chih-Hsuan
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Nien, Su-Hau
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工業工程與管理學系
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Department of Industrial Engineering and Management
In recent years, the popularity of smart phones has boomed the emergence of wearable devices like wristband, smart watch, and sport watch since these devices are portable to record human body information, synchronize information with smart phones, and conduct real-time monitoring of physical condition. However, a recent survey indicates that near 70% respondents are not interested in buying Apple\'s new iWatch although the marketplace is full of competing alternatives like Samsung\'s Gear fit, LG\'s G watch, and Sony\'s SW3. In this study, a novel framework combining multiple correspondence analysis (MCA), association rule mining (ARM), with K nearest neighbor (KNN) is proposed to help brand companies address the following issues: (1) using MCA to explore the latent relationships between users\' demographic profiles, user perceptions of design attributes, and user preferences for wearable devices, (2) using ARM to identify key design attributes that can best configure a specific alternative to achieve effective product differentiation (positioning), (3) using KNN to accomplish efficient product selection (recommendation). More importantly, hundreds of consumers are surveyed to justify the validity of the presented framework. (C) 2015 Elsevier B.V. All rights reserved.
Combining rough set theory with fuzzy cognitive pairwise rating to construct a novel framework for developing multi-functional tablets
(2018-01-01)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
To survive in a fiercely competitive market, global companies must effectively capture user requirements, perceptions, and preferences and efficiently convert them into attractive product design and development. Compared to functional or technical features, affective or ergonomic features can exert more influence on satisfying diverse consumers and accommodating a product to a wide range of usage. In practice, a quantitative approach to transform vague user perceptions of affective features into innovative products is necessary. In this study, a novel framework is proposed to help practitioners achieve the following goals. Initially, Kansei engineering (KE) is integrated with the theory of inventive problem solving (TRIZ) to accomplish systematic innovation. Secondly, to accomplish product planning, rough set theory (RST) is used to derive decision rules that can relate user perceptions to demographic variables (i.e. age, gender, and occupation). Finally, to accomplish product recommendation, fuzzy cognitive pairwise rating (FCPR) is applied to quantify user preference. In summary, the presented framework is effective to construct a product platform for developing innovative tablets and efficient to derive insightful decision rules for targeting the ad-hoc user groups.
Demand forecasting and financial estimation considering the interactive dynamics of semiconductor supply-chain companies
(2019-12-01)
Wang, Chih-Hsuan
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Chen, Jen-Yu
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工業工程與管理學系
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Department of Industrial Engineering and Management
Demand forecasting and financial estimation are two critical issues in supply chain management. Traditional forecasting techniques are either based on historical data (time-series) or causal predictors (regression). Although numerous schemes have been proposed, most cannot accommodate the time-lag causalities between the predictors and the outcome and the interactive dynamics of the supply-chain members. This research presents a novel framework to highlight the following issues: (1) Time-series models are constructed to accommodate product volatility and conduct demand forecasting. (2) Vector autoregression is used to capture the interactive dynamics of the supply-chain members to conduct financial estimation. (3) Regression methods are applied to conduct sensitivity analyses that can measure the impact on the sales revenue of a firm by increasing or decreasing a specific predictor. Experimental results demand forecast for consumer products can successfully predict the sales revenues of chip-design firms. For chip manufacturers and packaging and testing (P&T) firms, interactive dynamics can be competition (one suffers from the growth of the other) or cooperation (a win-win scenario). If one is strong and the other is weak (asymmetric relationship), the dynamics is cooperative. If two firms perform almost equivalently, the dynamics is competitive.
Facilitating customer involvement into the decision-making process of concept generation and concept evaluation for new product development
(2012-01-01)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Facilitating customer involvement into the decision-making process of concept generation and concept evaluation plays a vital role to achieve successful new product development. In particular, customer-preference based market segmentation could offer numerous business synergies, such as: (1) learning which product attributes are most critical to distinct segments, (2) identifying niche segments to assist an enterprise in generating design concepts, (3) helping product managers better predict customers\' desires to effectively implement promotion plans for future market opportunities. In this study, a novel framework which integrates conjoint analysis with Kano model is proposed to address the aforementioned issues. By virtue of conjoint analysis, customer preference is initially formulated through their perceived importance degrees of critical attributes and the entire market is segmented accordingly. Thereafter, with respect to distinct segments, conjoint analysis is employed again to extract customer utilities of critical attributes while Kano model is used to elicit customer delight/disgust of optional attributes, respectively. Finally, a real case study on generating and evaluating various design alternatives of a smart-phone is demonstrated to validate our proposed approach.
Incorporating customer satisfaction into the decision-making process of product configuration: a fuzzy Kano perspective
(2013-11-15)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
In an era of global customisation, buyers continuously benefit from the flexibility of selecting their desired options when making decisions on purchasing. Most manufacturing companies, however, need to balance the trade-offs between enhancing product variety and controlling manufacturing cost. In order to fulfil the goal of market-oriented product development, customer satisfaction needs to be well incorporated into the decision-making process of product configuration. Therefore, a hybrid framework is presented to address two critical issues in new product development: customer satisfaction and product configuration. In the beginning, fuzzy Kano model is employed to elicit customer perception of product attributes and extract customer satisfaction. Consecutively, information entropy is used for deriving the important weights of product attributes. Lastly, by means of Technique for Order Preference by Similarity to Ideal Solution, competing design alternatives are efficiently prioritised and configured. In particular, a case study on configuring varieties of smart pads is demonstrated to justify the validity of the proposed framework. With consideration of and the pricing policies of multi-segments, a systematic framework to effectively bridge customer satisfaction and product configuration is offered for the academics and industrial practitioners.
Incorporating the concept of systematic innovation into quality function deployment for developing multi-functional smart phones
(2017-05-01)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Smartphone has been recognized as one of the most powerful mobile carriers because of its portability, multiple functions, and wireless connectivity. However, the market shares of mobile phones have been intensively fluctuating because many brand companies like Nokia or Motorola have been merged. In order to brainstorm innovative ideas, this paper incorporates the theory of inventive problem solving (TRIZ) into quality function deployment (QFD) to address the following issues: (1) a smartphone is characterized by marketing requirements (MRs) and technical attributes (TM), (2) engineering conflicts among TM are tackled by TRIZ, (3) user preferences for MRs are extracted to form a basis of market segmentation, (4) user perceptions of TAs are captured to identify significant features with regard to the ad-hoc segments. More importantly, numerous industrial examples including Sony's QX series, Samsung's K-zoom, Nokia's Lumia 1020, Asus's Zenfone zoom, Asus's Padfone series, LG's G flex, Samsung's galaxy beam, and Lenovo's Yoga Tablet 2 are illustrated to validate this research. In brief, this study does not only provide a way to handle engineering conflicts in designing smartphones but also help product planners generate innovative alternatives for acquiring the ad-hoc niche segments. (C) 2016 Elsevier Ltd. All rights reserved.
Integrating affective features with engineering features to seek the optimal product varieties with respect to the niche segments
(2017-08-01)
Wang, Chih-Hsuan
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Chin, Hsin-Tze
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工業工程與管理學系
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Department of Industrial Engineering and Management
In recent years, the popularity of smart phones substantially leads to poor sales of the low-end digital cameras. One of the most astounding industry news is Kodak's bankruptcy in 2011 although Kodak was a pioneer in the field of digital still cameras. In reality, not only functional capability but also affective design can influence user purchase intentions on consumer electronics. In this paper, both affective features (AFs), and engineering features (EFs) are considered to achieve successful product planning. In particular, two critical issues are addressed: (1) market partitioning and (2) product differentiation. Initially, Kansei engineering is employed to capture user attitude toward AFs. Then, a classification tree is constructed to carry out effective market partitioning. Secondly, correspondence analysis is applied to capture user perceptions of EFs for identifying the core features that best characterize distinct market segments. Finally, VIKOR (VIseICriterijumska Optimizacija I Kompromisno Resenje) ranldng is conducted to prioritize various product portfolios to accomplish product differentiation. In summary, the presented framework can help industrial practitioners transform diverse customer requirements into attractive alternatives while keep controllable manufacturing costs. (C) 2016 Elsevier Ltd. All rights reserved.
Integrating conjoint analysis with quality function deployment to carry out customer-driven concept development for ultrabooks
(2013-11-01)
Wang, Chih-Hsuan
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Shih, Chih-Wen
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工業工程與管理學系
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Department of Industrial Engineering and Management
A hybrid framework integrating conjoint analysis (CA) with quality function deployment (QFD) is presented to incorporate customer preferences into the process of product development. In particular, the proposed framework constitutes two sequential phases, namely, concept generation based on CA and prototype evaluation based on QFD. In addition, product features are characterized by customer requirements (CRs) and functional attributes (FAs). By means of DEMATEL (Decision Making and Trial Laboratory), the impacts of FAs on CRs are systematically identified to visualize their causalities. Instead of utilizing FAs, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is employed to assess potential prototypes in terms of CRs. (C) 2013 Elsevier B.V. All rights reserved.
Integrating correspondence analysis with Grey relational model to implement a user-driven STP product strategy for smart glasses
(2016-10)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
To enhance customer retention and customer acquisition, product differentiation, product configuration and product recommendation are of importance to help firms implement segmentation-targeting-positioning strategies. In reality, however, user perceptions of product features are usually vague and diverse by individuals. Consequently, for a manufacturer, learning an efficient way to balance the trade-offs between satisfying customer needs and optimizing product varieties has become much more challenging than before. In order to overcome the aforementioned difficulty, this paper presents a novel framework to assist firms in determining the optimal product varieties of smart glasses with consideration of diverse requirements of three distinct segments (i.e. home entertainment, medical healthcare, and industry service). In particular, correspondence analysis is employed to indicate which product attributes best characterize a specific segment for achieving product differentiation. Then, by means of Grey relational model, the top three priorities with regard to three segments are systematically identified for conducting product configuration. Lastly, Bayes theorem is utilized to assign a potential buyer to his/her most similar segment for accomplishing unsupervised product recommendation.
Integrating decision tree with back propagation network to conduct business diagnosis and performance simulation for solar companies
(2016-01-01)
Wang, Chih-Hsuan
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Chuang, Jia-Jien
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工業工程與管理學系
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Department of Industrial Engineering and Management
Solar energy is a natural, clean, and inexhaustible resource to help the earth solve its energy crisis and reduce the air pollution caused by coal, nuclear, and gas electricity plants. Solar heating, solar photovoltaics, and solar thermal electricity can contribute to solving some of the most urgent problems the world faces. Despite the anti-dumping tariff and the anti-subsidy policy negatively impacting solar companies in Taiwan and China, solar cells are facing strong recovery of market growth in 2015. However, fierce competition in terms of cost and quality has resulted in a series of corporate acquisitions or bankruptcies since 2012. Inspired by the concept of business intelligence, a balanced scorecard (BSC) based framework is proposed to address the following issues: (1) How to identify key performance indicators (KPIs) that influence outcomes? (2) How to guide the lagging group to benchmark with the leading group (business diagnosis)? (3) How to adjust the significant KPIs to improve outcomes (what-if simulation)? In particular, classification and regression tree (fused with logistic regression) and back propagation neural network (fused with multiple regression) are adopted to provide managerial insights for worldwide solar companies. Furthermore, support vector machine (regression) is used to justify the validity of the presented framework. (C) 2015 Elsevier B.V. All rights reserved.
Integrating Kansei engineering with conjoint analysis to fulfil market segmentation and product customisation for digital cameras
(2015-04-18)
Wang, Chih-Hsuan
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工業工程與管理學系
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Department of Industrial Engineering and Management
Diverse customer desires coupled with technological advances have forced companies to manufacture products with ultimate performance, low cost, high quality and much shorter time-to-market. Recently, the popularity of smart phones has given rise to seriously declined product sales of digital cameras. In this paper, a two-phase framework is presented to offer decision supports on developing next-generation cameras. In the phase of market segmentation, Kansei engineering is employed to capture customer perceptions of affective features. Then, rough set theory is conducted to generate decision rules for partitioning the whole market into the consumer segment and the professional segment, respectively. In the phase of product customisation, conjoint analysis is applied to extract customer preferences for functional features. Furthermore, Grey relational analysis is conducted to select the top three varieties with regard to two distinct segments. In particular, this paper is capable to help brand companies or camera manufacturers better capture customer perceptions and preferences for digital cameras, effectively perform market segmentation (based on affective features) and efficiently conduct product customisation (based on functional features).