Requirement analysis considering uncertain customer preference for Kansei quality of product

Yamagishi, Kazuko; Seki, Kenichi; Nishimura, Hidekazu

doi:10.1299/jamdsm.2018jamdsm0034

Cited by 13 publications

(12 citation statements)

References 6 publications

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“…However, the weight of the evaluation indexes mainly considers the importance of customer demands, and seldom takes into account the satisfaction degree of customer preferences. For Kansei quality of the product, evaluation grid method and regression analysis method are used to evaluate the customer preference [30]. A way to measure the relative indifference between different characteristics called Fuzzy Indifference Degree (FID) is proposed to select the product closest to their preferences [31].…”

Section: B Customer Demand Analysismentioning

confidence: 99%

Service Satisfaction Evaluation of Customer Preference-Driven Public Warehousing Product Service Systems for Small- and Medium-Sized Enterprises in an Industrial Park

Ding

Zhang

et al. 2019

IEEE Access

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Facing fierce market competitions and fast technological transformation, manufacturing enterprises eagerly aspire to cut down investments in non-core businesses with the low return such as logistics, warehousing, and machine maintenance. In the context of service-oriented manufacturing (SOM), these non-core businesses are expected to be undertaken by third-party service providers in a centralized product + service manner. Supported by SOM principles, public warehousing product-service system (PW-PSS) is defined as integration of public warehouses and related warehousing services (e.g., raw material purchasing, work-in-progress storing/sorting/monitoring, and finished products packaging/distribution) for different manufacturing enterprises in an industrial park (IP). PW-PSS especially benefits for small-and medium-sized enterprises (SMEs) who are suffering from a heavy investment and management burden of self-built warehouses. To well operate the PW-PSS, third-party service providers must improve the service satisfaction degree of customers (i.e., manufacturing enterprises) to attract their continuous cooperation. This paper proposes a service satisfaction evaluation (SSE) method considering customer preferences to ensure the PW-PSS solutions more reliable and reasonable. First, the standard impact loss method is adopted to determine the initial weights of SSE indexes, and then the Kano model is used to adjust the above weights based on the consideration of customer preferences. Second, according to whether an SSE index is profitoriented or cost-oriented, a positive or negative distance is obtained based on a distance average solution method. Finally, an example is given to verify the proposed method. It is expected that SSE can provide a decision-making basis for SMEs in an IP to choose optimal PW-PSS solutions. INDEX TERMS Customer preference, product service system (PSS), public warehouse, service-oriented manufacturing (SOM), service satisfaction evaluation (SSE). QINGTAO LIU received the B.S. degree in mechanical design, manufacturing, and automation from the North China University of Water Resources and Electric Power, Zhengzhou, China, in 2006, and the M.S. and Ph.D. degrees in manufacturing and automation from Chang'an University, Xi'an, China, in 2009 and 2011, respectively, where he is currently a Lecturer with the Department of Manufacturing Automation, School of Construction Machinery. His current research interests include green manufacturing and sustainable manufacturing.

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Section: B Customer Demand Analysismentioning

confidence: 99%

Service Satisfaction Evaluation of Customer Preference-Driven Public Warehousing Product Service Systems for Small- and Medium-Sized Enterprises in an Industrial Park

Ding

Zhang

et al. 2019

IEEE Access

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show abstract

“…In previous research [29], the DBC method has been used, which allows for customers to participate in the process of product design, resulting in modification and adjustment of the product to the customers' requirements. Therefore, in the context of processing and determination of products' quality level, the main methods used have been Kansei (KE) [24,[30][31][32], Quality Function Deployment (QFD) [33][34][35][36], Kano [16,34,37,38], and the Bayesian Network (Naive Bayesian Classifier) [39][40][41][42][43]. These methods were also integrated [31,32,34,38,44].…”

Section: Introductionmentioning

confidence: 99%

“…These methods were also integrated [31,32,34,38,44]. The use of the Kansei method (KE) [24,[30][31][32] included determination of the psychology of customers, and then matching customers to Kansei words. This method was integrated with the QFD method to precisely determine both quantitative (technical) and qualitative (emotional) requirements [31,44].…”

Section: Introductionmentioning

confidence: 99%

“…Following this literature review, it was concluded that previous research has determined the required number of customers [17][18][19][20][21][22][23]; furthermore, customers' expectations have been obtained and processed to determine the quality level of products (for example: [24,25,30,34,35,38]). Methods to forecast or predict the quality level of products have also been implemented [27,33,36].…”

Section: Introductionmentioning

confidence: 99%

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A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations

Siwiec

Pacana

2021

Sustainability

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The main factor that conditions the success of organizations is the development of products oriented toward customer satisfaction. An additional attribute of organizations is the use of sustainable development rules. The use of these rules and the simultaneous desire to create high-quality products encourage organizations to apply different methods to, for example, eliminate waste. This study aimed to develop a method to determine the research sample size required to predict a product’s quality level, taking into account current customers’ expectations. This method was developed by modifying a procedure to determine the research sample size as part of the calculated estimator of the mean value in the general population. Based on the concept of product sustainability development, the goal of the developed method was to determine the number of potential customers (respondents) needed to provide product requirements, which were then processed and used to predict the quality level of the product. This method was applied to simultaneously test a number of hypotheses, determine the test power, and detect statistically significant differences for several relationships of the sample sizes and the test power. This was achieved using universal hypotheses and the popular alternative-punctual (MAP) method. Testing of the proposed method showed that it was able to predict the quality level of products based on current expectations of customers.

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“…Liu et al [29] used EGM of Miryoku engineering and fuzzy QFD to explore the design elements of a typical culture and creative product. Yamagishi et al [30] carried out EGM of Miryoku engineering to increase the robustness of the Kansei quality and maximize customer satisfaction for consumer electronic products. Conducting qualitative EGM interviews with high-involvement groups can record and summarize the semantic structure of expert logic from the actual behavior cases of users through pairwise comparison of various features.…”

Section: Introductionmentioning

confidence: 99%

Combining Grey Relationship Analysis and Neural Network to Develop Attractive Automobile Booth Design

Kang

2020

Computational Intelligence and Neuroscience

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Miryoku engineering is a design concept based on customer preferences, with the goal of creating attractive products or spaces. However, traditional Miryoku engineering faces two main issues: (1) the upper Kansei factor ranks the weights by the number of mentions, but it does not represent the importance of customers; (2) the mapping connection between the upper Kansei factor and the lower specific conditions adopts a statistical analysis method, which easily leads to the omission of key information. With the development of computer-based artificial intelligence, it repeatedly simulates human thinking with simple calculation rules, which has the advantages of fewer errors and faster speed. Therefore, on the three-level evaluation grid diagram platform established by Miryoku engineering, this paper first uses grey relationship analysis to comprehensively evaluate the priority order of Kansei words. Secondly, for the key Kansei factors, a morphological deconstruction table that connects the original reasons and specific conditions is established. Orthogonal design is used to screen representative combinations of design elements and create sample models by using the 3D software. Finally, the neural network was used to establish a mapping function between the key Kansei factors and the representative product design elements, and based on this, the most perceptually attractive product design was discovered. As a case study, the automobile booth was used to validate the effectiveness of the proposed method and significantly improve exhibitor design decisions and attendees’ satisfaction.

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Requirement analysis considering uncertain customer preference for Kansei quality of product

Cited by 13 publications

References 6 publications

Service Satisfaction Evaluation of Customer Preference-Driven Public Warehousing Product Service Systems for Small- and Medium-Sized Enterprises in an Industrial Park

Service Satisfaction Evaluation of Customer Preference-Driven Public Warehousing Product Service Systems for Small- and Medium-Sized Enterprises in an Industrial Park

A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations

Combining Grey Relationship Analysis and Neural Network to Develop Attractive Automobile Booth Design

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