Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation( max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

The development and application of NFTs has gained great attentions. Especially, with the eyes on the potential of Metaverse and Web 3.0, NFTs are regarded as one of the foundational parts of the future internet. The main contribution of NFTs is the innovative solution for creating digital uniqueness through its property of non-fungibility. With this property, the ubiquity caused by replicable data on the current internet can be advanced with NFT-backed uniqueness, which can assist in certifying authenticity, authorship, and possessions of contents, products, and assets online. This has tremendous meaning for the luxury brand industry, which has been struggling with the ubiquity of the internet for years. The emergence of NFTs, however, represents hope and a potential mean to represent scarcity in a digital context. By the use of NFTs, luxury brands’ conservative digital marketing strategies and their ways of production design, marketing, consumer management could be fundamentally changed. This study aims to discuss the NFT marketing strategy from the perspective of luxury brands. Particularly, the study will investigate the desirability strategies in these luxury NFT cases. To do so, the study uses a socio-technical perspective to understand how luxury brands embody the desirability strategy through NFTs, by considering the technical factors of NFTs (i.e., design, issuance, and ecosystem functioning) and social factors of desirability (i.e., exclusivity, rarity, prestige, and creative leadership). The study explores applicable strategy of how to realize luxury desirability through NFT technics. As a result, this study investigates 39 luxury NFT cases from 2021 to 2022, including the NFTs launched by famous luxury brands such as Gucci, Louis Vuitton, Burberry, Dolce & Gabbana, and KARL LAGERFELD. The study showcases three within-case analyses to exhibit vivid examples of NFT innovations. Besides, the study generates a common framework by a complete cross-case analysis. The framework contains three domains and seven dimensions to guide further luxury NFT innovations and contributes to theory development in the field of NFT marketing and branding.

The body of knowledge from psychology has been useful to marketing for understanding consumer minds and behaviors (Jia et al., 2018). Daily activities, such as movie watching, grocery shopping, online shopping, drinking coffee (with friends or alone), and making an in-app purchases on social media, all involve consumption which is affected by the perceptions, attitudes, and behaviors of the decision maker (i.e., consumers). But when the ways in which we sense and interact with the world change, how does it shift our ways of communicating with each other and the processes of forming perceptions, attitudes, and behaviors?

Today, as technology advances and market competition for products intensifies, the product design to improve customer satisfaction by accurately identifying customer needs is emerging as a very important issue for company. Accordingly, the customer-oriented or customer-centered design that maximizes customer satisfaction by grasping and analyzing customer requirements is in the spotlight as an important design theory. In this study, the customer-oriented design is defined as finding the optimal value of design variable with the maximum overall customer satisfaction while minimizing the difference in individual customer satisfaction responded to various customers from multiple product quality characteristics from the perspective of robust design. Therefore, this study presents a new method for modeling the customer preference structure as the different sets of desirability functions for multiple quality characteristics and proposes a new customer-oriented design approach by applying the desirability functions to Taguchi’s robust design process to deal with multi-characteristic design problem. Finally, the proposed method is illustrated with the Kansei engineering design problem of wine glass.

현대 사회가 복잡해지고 기술이 진보하면서 하나의 제품을 설계할 때 단일 특성이 아닌 다 특성을 갖는 제품을 설계하는 것이 요구되고 있다. 다 특성 설계 최적화 문제에서는 설계 변수의 최적값이 특성별로 다르게 되는 현상이 발생하고 이에 따라 하나의 특성에 대한 결과값이 좋아지면 다른 특성에 대한 결과값이 나빠지는 경우에 대해서 trade-off가 필요하다. 따라서 다 특성을 갖는 제품 설계 시 각각의 특성에 대한 성능을 최대화할 수 있는 효율적인 설계 방법의 필요성이 중요한 문제로 떠오르고 있다. 다 특성을 갖는 제품을 설계하는 연구는 오래전부터 중요한 문제로 인식되어 왔는데, 단일 특성에 대해 성능을 최대화하며 강건한 설계를 할 수 있는 다구치 기법과 다기준/다특성 의사 결정 방법인 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey relational analysis), PCA(Principle Component Analysis), Fuzzy Logic System을 통합한 연구들이 진행되어 왔다. 하지만 기존 연구들은 각각의 설계 대안들에 대해 다 특성 결과값에 대한 점수를 통합하여 종합 점수를 비교해 최적의 설계안을 도출할 뿐 설계자의 호감도에 대한 정보는 설계에 반영하지 못한다. 따라서 본 연구에서는 다구치 기법을 기반으로 각각의 특성들에 대한 설계자의 서로 다른 호감도를 함수로써 표현하여 강건성과 함께 설계자의 호감도를 동시에 설계에 반영할 수 있는 방법을 제안한다.

Today, as technology advances and market competition for products intensifies, the design to improve product satisfaction by accurately identifying customer requirements is emerging as a very important problem for company. Accordingly, Customer-Oriented Design, that maximizes customer satisfaction by grasping and analyzing customer requirements, is in the spotlight as an important design theory. In this study, Customer- Oriented Design is defined as finding the optimal value of the design variable with the maximum overall customer satisfaction while minimizing the difference in individual customer satisfaction responded to various customers from multiple product quality characteristics from the perspective of robust design. Therefore, in this work, we present a new method for generating a Desirability Function for each quality characteristic to deal with the multi characteristic parameter design with multiple quality characteristics. And we propose a new Customer-Oriented Design methodology that applies these Desirability Functions to Taguchi’s parameter design process.

In a sheet metal forming process, fracture and wrinkle are the most difficult task in new parts launching. The variation in process condition generates the fracture and wrinkle fluctuation. The fracture and wrinkle are very sensitive to the process conditions, then the main effects of the design variables cannot be obtained from the standard mean analysis. Therefore, in order to minimize the fracture and wrinkle in parts of automobile, a special method to counterpart is required. In this study, a new design method to achieve the optimal in the sheet metal forming process is proposed. The effectiveness of the proposed methods is shown with an example of the parts of fracture and wrinkle.

The optimization of dewatering and impregnation soaking (DIS) process for a concentrated Aloe vera product was investigated using Taguchi method in combination with desirability function analysis. Polyethylene glycol (PEG) as osmotic agent was adopted, and soaking temperature (T), immersion time (t), PEG concentration (C), PEG molecular weight (MW), and thickness of Aloe vera leaf slice (x) were selected as affecting variables. L16 (45) orthogonal array was designed by Taguchi method with four parameters such as water loss, solid gain, glucomannan, and anthraquinone contents as objective functions. An overall quality index was transformed from individual objective functions, and was optimized finally. The optimal setting for maximum overall desirability was obtained at 55oC (T), 2 hr (t), 40% w/v (C), 0.5 cm (x), and 4,000 Da. (MW). The obtained overall desirability was 0.7842. The order of affecting factors was T>C>x>MW≈x>t and the experimental results under optimum condition were similar to the prediction of an overall desirability of 0.8384. Also, it was found that the optimized DIS condition could be reproduced for a minimally processed Aloe vera product with high quality.

Quality design methodologies have received constituent attention from a number of researchers and practitioners for more than twenty years. Specially, the quality design for drug products must be carefully considered because of the hazards involved in the

This paper presents the optimization steps with weight and importance of estimated characteristic values in the multiresponse surface analysis(MRA). The research introduces the shape parameter of individual desirability function for relaxation and tighening of specification bounds. The study also proposes the combinded desirability function using arithmetic, geometric and harmonic means considering the measurement unit and numerical pattern.

Purpose: The purpose of this study was to prove the influence of method biases of social desirability on the sequential process of basic psychological needs → motivation → flow and emotion, suggested in HMIEM. Methods: This study conducted a questionnaire survey with 307 high school athletes. Structural Equation Model was employed to look into the scale of common method biases induced by social desirability. Results: As a result, a, b, and c, each of which is factor loading prior to control of social desirability, were .76, .80, and -.31, as shown in figure 2. Each factor loading after control of social desirability (shown in table 2) fell to .43, .56, and -.18. With regard to the SMC of each latent variable prior to control, the SMC of motivation was 57.5%, that of flow 63.5%, and that of emotion 9.8%. However, after control, motivation's SMC remarkably fell to 18.5%, flow's to 31.2%, and emotion's to 3.2%. Conclusion: Therefore, social desirability, one of common method biases, influenced the research model.