Research on the Method of Acquiring Customer Individual Demand Based on the Quantitative Kano Model

Du, Laihong; Chen, Hua; Fang, Yadong; Liang, Xiaowei; Zhang, Yujie; Qiao, Yidan; Guo, Zhen

doi:10.1155/2022/5052711

Cited by 9 publications

(10 citation statements)

References 8 publications

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“…Attention to consumer demands can foster a favorable user experience and stimulate sustainable consumer behavior [24,25]. KANO analysis can be a reliable method for analyzing consumer demand in design research [12,41,42,43,44].…”

Section: Resultsmentioning

confidence: 99%

“…The KANO model is a reliable way to observe and analyze the degree of correlation, positive influence, satisfaction and intention between consumers' attitudes toward product demands and consumer behavior. It aids in understanding user requirements by scientifically classifying demands and enhancing the market conversion rate of product value through design [43,44]. This research uses this method to evaluate and classify different consumer demands in e-commerce.…”

Section: Kano Modelmentioning

confidence: 99%

See 1 more Smart Citation

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

2024

KSII TIIS

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Thorough understanding of user demands and formulation of product development strategies are crucial in product design, and can effectively stimulate consumer behavior. Scientific categorization and classification of demands contribute to accurate design development, design efficiency, and success rates. In recent years, e-commerce has become important consumption platforms for smart wearable products. However, there are few studies on product design and development among those related to promoting platform product services and sales. Meanwhile, design strategies focusing on real consumer needs are scarce among smart wearable product design studies. Therefore, an empirical consumer demand analysis method is proposed and design development strategies are formulated based on a categorized interpretation of demands. Using representative smart bracelets from wearable smart products as a case, this paper classifies consumer demands with three methods: big data semantic analysis, KANO model analysis, and satisfaction analysis. The results reveal that analysis methods proposed herein can effectively classify consumer demands and confirm that differences in consumer demand categories have varying impacts on consumer behavior. On this basis, corresponding design strategies are proposed based on four categories of consumer demands, aiming to make product design the leading factor and promote consumer behavior on e-commerce platforms. This research further enriches demand research on smart wearable products on e-commerce platforms, and optimizes products from a design perspective, thereby promoting consumption. In future research, different data analysis methods will be tried to compare and analyze changes in consumer demands and influencing factors, thus improving research on impact factors of product design in e-commerce.

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Section: Resultsmentioning

confidence: 99%

Section: Kano Modelmentioning

confidence: 99%

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

2024

KSII TIIS

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“…Numerous scholars have proposed improved methods for individual or multiple steps in product innovation design. Reference [ 42 ] examined the current needs of users using Kano (S1). References [ 43 , 44 ] utilized mathematical models and algorithms to predict future product demands (S1).…”

Section: Literature Reviewmentioning

confidence: 99%

Product innovation design process combined Kano and TRIZ with AD: Case study

Rong,

Liu,

et al. 2024

PLoS ONE

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In the era of rapid product iteration, companies need simple and effective methods to guide the entire process of product innovation design and enhance their product innovation capabilities. Most research focused on improving one or several steps in the product design process. Although some scholars have proposed methods that guided the entire process, they combined more than three different theories, which increased the difficulty of theoretical learning and the complexity of practical implementation. This paper proposed a product innovation design process composed of three theoretical methods: Kano, Axiomatic Design (AD), and Theory of the Solution of Inventive Problems (TRIZ). This new process guided the entire product design process with fewer theoretical methods, reducing the difficulty of learning and implementation. The paper demonstrated the effectiveness of this method through the design practice of a portable two-wheeled self-balancing vehicle. Additionally, the discussion section explored the method’s potential from the design management perspective.

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“…Abarca Sánchez et al (2022) aim to establish the relationship between loyalty and retention in telecom companies through an exploratory factor analysis and a multiple linear regression modeling. Du et al (2022) proposed a quantitative Kano model to analyze consumer personal demand and achieve a high validity of marketing decisions. Authors recommend providing a personalized proposal for each heterogeneous customer group.…”

Section: Literature Reviewmentioning

confidence: 99%

Customer churn prediction model: a case of the telecommunication market

et al. 2022

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The telecommunications market is well developed but is characterized by oversaturation and high levels of competition. Based on this, the urgent problem is to retain customers and predict the outflow of customer base by switching subscribers to the services of competitors. Data Science technologies and data mining methodology create significant opportunities for companies that implement data analysis and modeling for development of customer churn prediction models. The research goals are to compare different approaches and methods for customer churn prediction and construct different Data Science models to classify customers according to the probability of their churn from the company’s client base and predict potential customers who could stop to use the company’s services. On the example of one of the leading Ukrainian telecommunication companies, the article presents the results of different classification models, such as C5.0, KNN, Neural Net, Ensemble, Random Tree, Neural Net Ensemble, etc. All models are prepared in IBM SPSS Modeler and have a high level of quality (the overall accuracy and AUC ROC are more than 90%). So, the research proves the possibility and feasibility of using models in the further classification of customers to predict customer loyalty to the company and minimize consumer’s churn. The key factors influencing the customer churn are identified and form a basis for future prediction of customer outflow and optimization of company’s services. Implementation of customer churn prediction models will help to maintain customer loyalty, reduce customer outflow and increase business results

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Research on the Method of Acquiring Customer Individual Demand Based on the Quantitative Kano Model

Cited by 9 publications

References 8 publications

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

Identification of Demand Type Differences and Their Impact on Consumer Behavior: A Case Study Based on Smart Wearable Product Design

Product innovation design process combined Kano and TRIZ with AD: Case study

Customer churn prediction model: a case of the telecommunication market

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