Product Customer Research Articles

Product family modeling technology for customized cosmetic packaging design based on basic-element theory

BackgroundAs the market demands change, SMEs (small and medium-sized enterprises) have long faced many design issues, including high costs, lengthy cycles, and insufficient innovation. These issues are especially noticeable in the domain of cosmetic packaging design. ObjectiveTo explore innovative product family modeling methods and configuration design processes to improve the efficiency of enterprise cosmetic packaging design and develop the design for mass customization. MethodsTo accomplish this objective, the basic-element theory has been introduced and applied to the design and development system of the product family. ResultsBy examining the mapping relationships between the demand domain, functional domain, technology domain, and structure domain, four interrelated models have been developed, including the demand model, functional model, technology model, and structure model. Together, these models form the mechanism and methodology of product family modeling, specifically for cosmetic packaging design. Through an analysis of a case study on men’s cosmetic packaging design, the feasibility of the proposed product family modeling technology has been demonstrated in terms of customized cosmetic packaging design, and the design efficiency has been enhanced. ConclusionThe product family modeling technology employs a formalized element as a module configuration design language, permeating throughout the entire development cycle of cosmetic packaging design, thus facilitating a structured and modularized configuration design process for the product family system. The application of the basic-element principle in product family modeling technology contributes to the enrichment of the research field surrounding cosmetic packaging product family configuration design, while also providing valuable methods and references for enterprises aiming to elevate the efficiency of cosmetic packaging design for the mass customization product model.

The Impact of Trust and Quality of Electronic Services on Digital Bank Customer Satisfaction with the Bank Image as a Mediator

The COVID-19 pandemic and the development of information technology use in recent years have caused changes in people's behavior patterns and preferences in using digital services. This indirectly encourages the emergence of an accelerating trend of digital transformation in the bank sector in 2022, where banks massively optimize the use of digital technology in both customer products and services. This research is motivated by the development of digital banks which have become a phenomenon in the financial industry in recent years, with the needs of customers who want the speed and flexibility of bank services that are available anywhere and anytime. Customer satisfaction not only supports the survival of the bank, but also the development of the bank. Customer satisfaction in the bank is influenced by many factors such as trust because the bank operates based on the principle of customer trust, the quality of service that must be provided continuously and without interruption, and the image or image of the bank itself. Based on the above phenomenon, this study aims to analyze the role of the bank's image as a mediator of the impact of trust and quality of electronic services on digital bank customer satisfaction. The population of this study is digital bank customers located in DKI Jakarta, with a sample of 190 people. The data analysis method using the Structural Equation Model (SEM) is processed with SmartPLS version 3.29. In this study, it is known that trust does not affect customer satisfaction, the factors that make customers satisfied are the quality of service and the image of the bank.

Implementation of Classification Decision Tree and C4.5 Algorithm in selecting Insurance Products

Every insurance customer will receive a policy card, as a sign that the person is included in the insurance and is obliged to pay the insurance premium, the amount of which has been determined by the company in accordance with the agreement. Premium payments are Insurance's biggest source of income. Unfavorable economic conditions often cause customers not to pay their premiums by the specified time limit, resulting in a delay in completing the recording of premium income. This research aims to find out the right type of insurance product for prospective customers. The research method used is Classification Decision Tree. Classification Decision Tree is a research method used to examine existing facts systematically based on research objects, existing facts to be collected and processed into data, then explained based on theory so that in the end it produces a conclusion. This research is for selecting the right type of insurance product for prospective customers based on the age and income categories of prospective customers. Insurers must be more careful, especially in selecting prospective customers, and in determining the right type of insurance product for prospective customers so that the power in selecting the right type of insurance product for prospective customers is right at the intended target.

Switching to sustainable products: The role of time, product, and customer characteristics

AbstractAchieving a sustainable economy is one of the primary needs of our time, and sustainable products can play a decisive role in achieving this goal. This article seeks answers about the role of time and product characteristics in the intention to switch to a sustainable product using the example of an everyday product. Drawing from social identity theory, utility maximization and switching theory, the authors propose a conceptual model to examine these questions in a specific market disruption when a product is modified by the same company. The framework focuses on the time‐varying effects of customers' features (brand identification, loyalty, embeddedness) and products' features (perceived value [PV], compliance, switching cost) on switching behavior. The research was carried out using a quasi‐experimental method in three periods. In the first stage, Cox Proportional Hazard Regression was used, and a random‐effects model in the second. Results from longitudinal data of 282 customers during the launch of a new sustainable product show that customer characteristics do not influence the intention to switch. In contrast, the PV and switching costs inhibit the switching behavior, but their effects vary over time. In particular, the effect of the relative PV of the sustainable product on switching will increase over time, but the importance of customer–brand identification also rises. The study has important implications for introducing a sustainable equivalent of an incumbent product of the same brand.

The Influence of Internal and External Factors on the Successful Implementation of 5S Work Culture in Vocational Schools

In the sphere of education, 21st-century skills are becoming increasingly important. The ability to integrate 21st-century skill competencies with workplace cultures is another requirement for vocational institutions. Many companies and industries these days are searching for employees with positive work cultures. Consequently, there is a strong and favorable correlation between workplace culture and student achievement. In addition, there is a strong correlation between students' vocational character and the 5R work culture in vocational schools. Hermawan and Nurdin's (2023) research demonstrates that the 5S work culture assessment tool achieved good content validity and reliability (0.793). Research by Balasundaram et al. (2023), applying the 5S technique can improve customer happiness, product quality, and production efficiency. Additional research by Maulidina and Wijarnaka (2023) demonstrates that work willingness is significantly and favorably impacted by the 5-person work culture by 15.90%. These three studies, however, did not examine the variables that affect the 5S work culture's successful adoption in vocational schools. The primary methodology for the research is qualitative methods; two participants complete Google forms with written interviews and observation techniques. Inductive data analysis was used to process the acquired data. The study's findings indicate that there are both internal and external elements that affect how well 5S work cultures are implemented at vocational schools. The internal factors include 1) a Well-organized curriculum; 2) well-behaved students; and 3) workload distribution. External elements, which are as follows: 1) School Persistence; 2) Industry Support; 3) Community and Parent Participation; and 4) Work Culture Integration Into Daily Practices.

A math-heuristic approach for scheduling the production and delivery of a mobile additive manufacturing hub

This paper investigates an innovative printing-while-delivering paradigm within a mobile additive manufacturing (MAM) hub. Different from the conventional production-first-delivery-second (PFDS) mode, the MAM hub, comprising a 3D printer and a truck, can seamlessly integrate the production and delivery processes. Throughout the delivery process of the MAM hub, the embedded 3D printer within the truck concurrently prints products for customers in batches. This capability significantly diminishes customer dissatisfaction caused by time delays between order placement and product receipt, which requires coordinating the delivery routing of truck and the production scheduling of 3D printer. To tackle this problem, a mixed integer programming model is firstly established to minimize the required time of the MAM hub returning to depot after completing all deliveries. Then, a math-heuristic approach combining the genetic algorithm and branch-and-bound is devised to solve the mathematical model efficiently. The delivery sequence of truck is represented as a chromosome in the genetic algorithm; while, for each delivery sequence, the optimal production scheduling of 3D printer is obtained by branch-and-bound based on the theoretical analysis about the relationship between production and delivery sequences. In the numerical experiments, the proposed math-heuristic algorithm produces results identical to CPLEX solver outcomes in small-scale cases. For larger instances, it outperforms traditional genetic algorithms by 3.39% to 19.54%. The proposed batch printing mode consistently surpasses the non-batch mode by 10% to 25%. Moreover, compared to PFDS, the printing-while-delivering paradigm reduces trip time by over 40%. Finally, we analyze the effects of customer quantity, distribution radius, and printing time on the objective, providing management insights about optimal production and delivery strategy. The research finding not only aids in scheduling the MAM hub but also holds the potential to address other applications characterized by simultaneous production and delivery requirements.

A Deep-Reinforcement-Learning-Based Digital Twin for Manufacturing Process Optimization

In the context of Industry 4.0 and smart manufacturing, production factories are increasingly focusing on process optimization, high product customization, quality improvement, cost reduction, and energy saving by implementing a new type of digital solutions that are mainly driven by Internet of Things (IoT), artificial intelligence, big data, and cloud computing. By the adoption of the cyber–physical systems (CPSs) concept, today’s factories are gaining in synergy between the physical and the cyber worlds. As a fast-spreading concept, a digital twin is considered today as a robust solution for decision-making support and optimization. Alongside these benefits, sectors are still working to adopt this technology because of the complexity of modeling manufacturing operations as digital twins. In addition, attempting to use a digital twin for fully automatic decision-making adds yet another layer of complexity. This paper presents our framework for the implementation of a full-duplex (data and decisions) specific-purpose digital twin system for autonomous process control, with plastic injection molding as a practical use-case. Our approach is based on a combination of supervised learning and deep reinforcement learning models that allows for an automated updating of the virtual representation of the system, in addition to an intelligent decision-making process for operational metrics optimization. The suggested method allows for improvements in the product quality while lowering costs. The outcomes demonstrate how the suggested structure can produce high-quality output with the least amount of human involvement. This study shows how the digital twin technology can improve the productivity and effectiveness of production processes and advances the use of the technology in the industrial sector.

Evaluating the Ranking of Performance Variables in Flexible Manufacturing System through the Best-Worst Method

Flexible Manufacturing Systems (FMSs) provide a competitive edge in the ever-evolving manufacturing landscape, offering the agility to swiftly adapt to changing customer demands and product lifecycles. Nevertheless, the complex and interconnected nature of FMSs presents a distinct challenge: the evaluation and prioritization of performance variables. This study clarifies a conspicuous research gap by introducing a pioneering approach to evaluating and ranking FMS performance variables. The Best-Worst Method (BWM), a multicriteria decision-making (MCDM) approach, is employed to tackle this challenge. Notably, the BWM excels at resolving intricate issues with limited pairwise comparisons, making it an innovative tool in this context. To implement the BWM, a comprehensive survey of FMS experts from the German manufacturing industry was conducted. The survey, which contained 34 key performance variables identified through an exhaustive literature review and bibliometric analysis, invited experts to assess the variables by comparing the best and worst in terms of their significance to overall FMS performance. The outcomes of the BWM analysis not only offer insights into the factors affecting FMS performance but, more importantly, convey a nuanced ranking of these factors. The findings reveal a distinct hierarchy: the “Quality (Q)” factor emerges as the most critical, followed by “Productivity (P)” and “Flexibility (F)”. In terms of contributions, this study pioneers a novel and comprehensive approach to evaluating and ranking FMS performance variables. It bridges an evident research gap and contributes to the existing literature by offering practical insights that can guide manufacturing companies in identifying and prioritizing the most crucial performance variables for enhancing their FMS competitiveness. Our research acknowledges the potential introduction of biases through expert opinion, delineating the need for further exploration and comparative analyses in diverse industrial contexts. The outcomes of this study bear the potential for cross-industry applicability, laying the groundwork for future investigations in the domain of performance evaluation in manufacturing systems.

Green consumption by design: interaction experiences and customization intentions

PurposeThis study investigated the impacts of the interaction experiential customization (IEC) mode on consumers' information processing fluency and green customization intention (GCI) as well as the moderating effect of consumers' self-construal.Design/methodology/approachThis study conducted an online field experiment, questionnaire study and between-subjects laboratory experiment to test the hypotheses.FindingsIt was found that IEC had a significant positive effect on consumers' GCI. Moreover, consumer retrieval processing fluency played a partial mediating role in the relationship between IEC and GCI. In addition, consumers' self-construal moderated the “IEC? Three dimensions of processing fluency” relationships.Practical implicationsThe results emphasized the importance of IEC in influencing consumers' consumption intention in a green customization setting and have some practical implications, that is, companies have the opportunity to use appropriate digital choice architecture designs, which can enhance consumer processing fluency when promoting eco-friendly products in the customized consumption process, especially for independent consumers.Originality/valueThis study focused on the customization design on consumers' GCI and explained the mechanism of impact of IEC on improving consumers' processing fluency and GCI in a product customization setting based on the fluency theory. In addition, this study investigated the moderating effect of consumers' self-construal (independent vs interdependent) on their significant different information processing modes for low-carbon choices.

Pelaksanaan Promosi Digital Menggunakan Media Blog Pada UMKM di Kelurahan Sumurwelut Kecamatan Lakarsantri Kota Surabaya

The implementation aims to investigate and analyze the application of digital promotion using blog media for UMKM in Sumurwelut Village, Lakarsantri District, Surabaya City. Through a qualitative approach and case study design, this study explores the extent to which UMKM in the village use blogs as a digital promotion tool. The results indicate that UMKM have generally adopted digital promotion strategies through blogs with content involving product descriptions, customer reviews, special offers, and industry-related articles. UMKM that are active in creating high-quality content through blogs experience a significant increase in visibility and sales. Supporting factors include a good understanding of the blog platform, the involvement of UMKM owners, and creativity in presenting content. Technical obstacles, and lack of understanding of the benefits of digital promotion are the main obstacles. The positive response from consumers to digital promotion through blogs shows increased trust, and a tendency to interact further. These findings provide deep insights into the effectiveness of digital promotion in UMKM and refer to recommendations for the development of better digital promotion strategies, including increasing UMKM' understanding of the potential of digital promotion and optimizing interaction with consumers through blog platforms. It is expected that this internship will make a significant contribution to stakeholders, including UMKM, local governments, and UMKM supporting institutions, in supporting UMKM business growth in the digital era.

Product Development in Crowdfunding: Theoretical and Empirical Analysis

Problem definition: Crowdfunding goes beyond raising funds. Entrepreneurs often use crowdfunding to solicit feedback from customers to improve their products and may therefore prefer to launch their crowdfunding campaigns using basic versions of their products with fewer features. However, customers may not be persuaded by a campaign if the product appears to be underdeveloped. In view of this tradeoff, a key question for entrepreneurs is how much to develop a product before launching a crowdfunding campaign. Methodology/results: Analyzing a game-theoretical model and testing its predictions empirically, we study (1) how the development level of a product at campaign launch, measured by the initial number of product features, influences whether customers will make comments that help entrepreneurs improve the product; (2) whether entrepreneurs continue to improve the product during the campaign; and (3) whether the campaign is successful. We show that, as the number of product features at campaign launch increases, the likelihood that customers will make comments and that the product will be improved during the campaign first increases but then decreases. Furthermore, the likelihood of campaign success first increases but then decreases with the number of product features at campaign launch. Finally, by analyzing the interactions between customer feedback, product improvement, and campaign success, we show that customer feedback motivates entrepreneurs to improve the product during the campaign. Moreover, entrepreneurs should take account of the initial number of features and customer feedback when improving the product, because otherwise product improvements can harm campaign success. Managerial implications: Our study provides practical insights on how entrepreneurs can use crowdfunding to aid product development and improvement. Specifically, entrepreneurs should avoid overdeveloping their products before crowdfunding campaigns because, as well as decreasing the chance of campaign success, this could hinder their ability to save development costs (e.g., market research costs) through involving customers in product development. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.0344 .

Pulling together: Does supplier digital transformation affect customer risk‐taking capability?

AbstractThis study explores the impact of supplier digital transformation on customer risk‐taking capability and further explores its impact mechanism in China using A‐share listed companies from 2010 to 2020. The empirical results indicate that the supplier digital transformation mechanism test has a significant and positive impact on the risk‐taking capability of customers. They reveal that supplier digital transformation improves the risk‐taking capability of customers by easing customer financing constraints and driving customer product innovation. Additionally, the results of the heterogeneity test indicate that supply chain relationships play a moderating role in the impact of supplier digital transformation on customer risk‐taking.

Exploring Shopper Psychographic Characteristics From a Human Ecosystem Perspective: A Proposed Typology of Millennial Luxury Consumers

An enhanced understanding of millennial luxury consumers is needed for luxury retailers to develop loyalty strategies and foster business success. Guided by the human ecosystem framework, the objective of this research was to classify millennial luxury consumers into a shopper typology based on shopper psychographic characteristics to provide an understanding of their shopping motivations and behaviors regarding luxury goods. Two studies were conducted. Semistructured interviews of millennial luxury consumers in Study 1, analyzed through interpretive analysis, resulted in 11 major themes or shopper psychographic characteristics. An online survey to a larger sample of millennial luxury consumers in Study 2 was then employed. Reliability and validity testing confirmed the 11 psychographic characteristics and latent profile analyses revealed a four-class shopper typology. Findings provide retail industry executives with in-depth information on customer profiles which includes shopping and product preferences, motivations, and customer expectations that was previously absent in the literature.

PENINGKATAN PELANGGAN PADA PT. TELKOMSEL SUMBAWA MELALUI PENERAPAN STRATEGI RELATIONSHIP MARKETING

This study aims to know the effect of relationship Marketing on increasing the number of customers at PT. Telkomsel Sumbawa. The type of study used in this study was associative approach which aims to determine the relationship between variables and verify whether a variable causes the variable to change or not. The type of data used in this study was quantitative data in the form of scoring results of respondents' answers regarding the object under study. This quantitative data was obtained directly from the original source, namely research respondents who were collected using a research instrument in the form of a questionnaire. The number of samples used as respondents in this study was 100 people who were selected using accidental sampling techniques. The data that has been collected was processed using the SPSS application to be studied using simple linear regression analysis techniques, partial hypothesis testing (t test), and determinant coefficient test (R2). The results of this study showed the relationship marketing had a positive and significant effect on increasing the number of customers at PT. Telkomsel Sumbawa. The effect of relationship marketing on increasing the number of customers at PT. Telkomsel Sumbawa was 36.1%, while the remaining of 63.9% was affected by other variables outside this study, such as product quality, service quality and customer satisfaction.

Web-Based Sales Information System in One of The Cash Shops Using the Business to Customer Method

Science and information technology's rapid and sophisticated progress motivates humans to generate novel solutions that facilitate easy and speedy information acquisition. Consumer behavior has experienced a substantial transformation in the present digital age. Many people opt for Internet purchasing due to the ease, accessibility, and flexibility it provides. The fashion industry is not immune to this phenomenon, as internet retailers are gaining popularity as a preferred method for buying clothing and accessories. Online retailers offer advantages such as convenient access to product catalogs, the ability to purchase at any time and from any location, and a broader selection of options. This offers a substantial opportunity for fashion retailers to access a larger pool of potential customers and enhance their market dominance. The sales process in a particular fashion store now depends on a traditional system involving direct transactions at the physical store and maintaining sales data through paper documents. This technique encounters multiple impediments that must be surmounted. A significant challenge is the limited accessibility to clients beyond the geographical confines of the physical business. In addition, using paper documents to manage sales data also needs to be improved in efficiency and accuracy. The method is laborious and prone to human errors. As inferred from the background description, the author's objective is to develop a web-based sales information system for a fashion retailer utilizing the business-to-customer approach. This system will streamline the sales process and aid in managing sales data, encompassing product data, customer data, and transactions. The system development will utilize the PHP programming language and the MySQL database, widely employed in online development. The research methodologies encompass literature review, observation, and interviews. The chosen approach for system development is Object-Oriented Software Engineering (OOSE), which utilizes Unified Modeling Language (UML) for system modeling. This includes using various diagrams such as use case, activity, sequence, and class diagrams. Hence, the sales information system is anticipated to offer a more efficient resolution for carrying out sales procedures and enhancing data administration promptly, safely, and precisely. Implementing this strategy will enable the fashion store to expand its consumer base, particularly among individuals located beyond the geographical reach of the actual store, thereby improving overall business performance.

Customer Product Choice: The Effect of Product Quality on Relative price and Price fairness and their implication on Customer Product Choice

This study examines the influence of product quality on individuals' perceptions of relative prices and price justice, as well as the potential consequences for consumer decision-making in product selection. This study employs robust statistical analysis to get insights into customers' decision-making processes when purchasing products and selecting brands, particularly about product attributes and pricing. The study employed a non-parametric Structural Equation Modeling PLS technique, which involved a sample of 100 consumers who had previously consumed cigarette goods in the urban area of Bandung. The questionnaire was distributed through social media platforms, utilizing a Google Form link. The employed sample method is convenience sampling, wherein clients are requested to complete a structured questionnaire that has been supplied. The poll encompassed inquiries about participants' perceptions regarding the quality of the product, its comparable pricing, and the appropriateness of the price. The survey data were subjected to rigorous statistical analysis, encompassing several analytical techniques such as regression analysis and hypothesis testing. The study's findings indicate that a product's quality plays a substantial role in shaping consumers' evaluations of comparable prices and perceptions of price justice. Consumers tend to make product selections predicated upon their subjective quality assessment, shaping their perception of the product's price. The presence of excellent product quality can mitigate price barriers, as customers exhibit a greater propensity to pay elevated costs for things they believe to possess superior quality. Furthermore, this study demonstrates that comparable costs and the perception of price justice influence consumer product choices. This condition highlights the significance of prudent pricing within a company's marketing strategy, whereby competitive and equitable pricing can catalyze consumers to opt for specific products. However, a further noteworthy discovery is that the relative pricing and price reasonableness factors do not influence customers' brand preferences. This condition suggests that when considering the choice of a brand, several elements, such as brand image, individual preferences, or distinctive brand characteristics, may exert a more significant impact. The correlation between product and brand compatibility plays a significant part in consumers' decision-making process when it comes to selecting a brand. The findings of this study offer significant implications for businesses in enhancing their marketing and pricing strategies. Furthermore, they contribute to a more comprehensive comprehension of consumer decision-making processes within the product and brand choices framework. In order to achieve success in a competitive and dynamic business climate, it is imperative to possess a comprehensive comprehension of the various elements that impact consumer decision-making.

Implementasi Augmented Reality untuk Aplikasi Media Promosi Produk Mebel Jepara Berbasis Android

Jepara Regency is known as one of the centres of furniture production in Indonesia thanks to its distinctive wooden crafts. Many furniture industries in this area have adopted the strategy of marketing through catalogues as a promotional medium, but with the rapid popularity of smartphone use, the use of social media as a marketing tool for furniture products has also increased. This has resulted in marketing through catalogues of furniture products via social media becoming commonplace and less effective. The ineffectiveness of catalogue media is because it has limitations that can only convey information in the form of images, while the selection of furniture products requires design considerations according to customer preferences. With problems arising related to the effectiveness of furniture marketing strategies, innovation is needed in product visualisation. The proposed solution is to use Augmented Reality (AR) technology on promotional media. Augmented Reality (AR) is a technology that combines digital information with the user's environment in real-time. In this research, an Android-based furniture promotion application is developed with the Extreme Programming method that utilizes AR technology to visualise furniture product designs in 3D and is designed using the Unified Modelling Language (UML). It is expected that this application can increase interest and facilitate customers in finding furniture products, as well as support the furniture industry in promoting its products.

PEMANFAATAN CHAT GPT OPEN AI TERHADAP ANALISIS DAN STRATEGI DALAM MENINGKATKAN PERFORMA PENJUALAN PRODUK SECARA DIGITAL

The rapid development of technology can produce several new innovations that are beneficial to society such as ChatGPT Open AI. ChatGPT is an artificial language model developed by OpenAI, an artificial intelligence technology company. GPT stands for "Generative Pre-trained Transformer", which refers to the model architecture used in the creation of ChatGPT. The method used in this research is a qualitative method. The results showed that the utilization of ChatGPT allows businesses to be able to conduct in-depth analysis of customer data and product reviews, help identify new problems and opportunities that have not been seen before, assist businesses in developing more targeted and personalized marketing strategies, enable businesses to provide fast and responsive responses to customer inquiries, businesses can quickly identify problems that may occur with the product, This allows for faster repairs and improvements, which in turn can increase customer satisfaction. By utilizing the analysis conducted with ChatGPT, businesses can enter a continuous cycle of improvement. Findings and feedback can be continuously processed to improve products and marketing strategies, ultimately supporting long-term sales growth. Although ChatGPT has a lot of potential, the software has limitations. Understanding the context and human interpretation remains critical to making the right decisions. In addition, ethics in data collection and use must also be prioritized. With awareness and understanding, utilizing ChatGPT in digital product sales analysis and strategy can significantly contribute to achieving business goals.

Integrated triangular fuzzy KE-GRA-TOPSIS method for dynamic ranking of products of customers’ fuzzy Kansei preferences

As society evolves, companies produce more homogeneous products, shifting customers’ needs from functionality to emotions. Therefore, how quickly customers select products that meet their Kansei preferences has become a key concern. However, customer Kansei preferences vary from person to person and are ambiguous and uncertain, posing a challenge. To address this problem, this paper proposes a TF-KE-GRA-TOPSIS method that integrates triangular fuzzy Kansei engineering (TF-KE) with Grey Relational Analysis (GRA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Firstly, a Kansei evaluation system is constructed based on KE and fuzzy theory. A dynamic triangular fuzzy Kansei preference similarity decision matrix (TF-KPSDM) is defined to quantify customer satisfaction with fuzzy Kansei preferences. Secondly, dynamic objective weights are derived using Criteria Importance Though Intercrieria Correlation (CRITIC) and entropy, optimized through game theory to achieve superior combined weights. Thirdly, the GRA-TOPSIS method utilizes the TF-KPSDM and combined weights to rank products. Finally, taking the case of Kansei preference selection for electric bicycles, results indicate that the proposed method robustly avoids rank reversal and achieves greater accuracy than comparative models. This study can help companies dynamically recommend products to customers based on their Kansei preferences, increasing customer satisfaction and sales.

Promotion by KOL and Acquaintances in Differentiated Products: By the Case of Nintendo Switch

Nintendo, founded in 1889, is a Japanese company mainly engaged in the development of electronic game hardware and software and is the pioneer of the modern electronic game industry. Nintendo Corporation is headquartered in Kyoto City, Japan. Nintendo has sold more than 2 billion copies of its software worldwide, created some of the most famous characters in the history of gaming, such as Mario, and created some of the most classic games in the history of gaming, such as The Legend of Zelda.According to Pu Yamauchi, the head of the game department, it is known that Nintendo strives to be a paradise for game artists. Nintendo believes that people who develop great games should be artists, not technicians, and therefore should be given enough freedom. That's why the Switch is so innovative today. This paper mainly focuses on the analysis of Nintendo's customer characteristics and product characteristics and puts forward corresponding marketing strategies and cures.