Fuzzy Kano Model Research Articles

Classification of traditional cultural elements in temple street festivals using the fuzzy Kano model

This study aims to explain consumers’ expectations regarding the culture of temple streets and cultivates an identity system for local culture. The Kano model with fuzzy linguistic concepts was applied to the field observation of temple street festivals and the semi-structured interviews of local cultural directors, scholars of cultural centres, government officials, and cultural industry operators with data on traditional cultural elements. The findings show that “Religious temples”, “Custom activities and events”, “Local cultural industries”, and “Specialty and gourmet food” have a symmetrical impact on both satisfaction and dissatisfaction in proportion to the extent of traditional cultural element fulfilment. “Local stories” do not increase overall satisfaction if traditional cultural elements are exceeded but cause dissatisfaction if they are not fulfilled. Moreover, outer “Tangible”, middle “Behavioural”, and inner “Intangible” factors of attractive, one-dimensional, must-be quality transformed into contemporary image designs are amiably illustrated. These results provide a direction for managing satisfaction and a performance guideline for each activity in the process of creating temple street experiences that can increase satisfaction and reduce dissatisfaction.

手机购物顾客满意度的关键影响因素研究

智能手机的普及使得手机购物消费群扩充迅速，了解顾客满意度的关键影响因素对改善移动电子商务企业服务水平的意义重大。首先利用R型系统聚类优化出手机购物顾客满意度的影响因素；其次基于模糊Kano模型并结合熵值法进行属性分类；最后找出影响顾客满意度的关键因素。研究表明：魅力属性因素是提升顾客满意度的关键，如晒单信息、本地化服务、WIFI环境、利用碎片化时间等；期望属性因素是降低顾客不满的关键，如支付安全、账户安全、个人隐私等。 With the prevalence of mobile commerce and the rapid expansion of consumer groups, it is significant to explore critical factors of consumer satisfaction in mobile commerce, which can improve the service quality. Firstly, R-type hierarchical clustering was used to optimize typical factors, which affected customer satisfaction of shopping by mobile phone. Then, attributive classification of factors was conducted based on the fuzzy Kano model combined with the entropy method. And finally found the critical factors for improving customer satisfaction and reducing customer dissatisfaction. The research shows that the shared information, local service, WIFI environment and the use of fragmented time are attractive attributes which can improve customer satisfaction rapidly. Payment security, account security and personal privacy belong to one dimensional attributes, they are key factors to reduce customer satisfaction.

Integrating fuzzy Kano model with importance-performance analysis to identify the key determinants of customer retention for airline services

The global economic recession as well as emerging low-cost carriers have led to declining revenues for worldwide airlines. A novel framework is presented to seek critical service attributes (SAs) that can enhance customer satisfaction and customer retention. Initially, fuzzy Kano model is employed to capture customer perceptions of SAs and convert them into quantitative degrees of customer satisfaction. Then, multiple regression and logistic regression are used to extract the weights of SAs and identify the key SAs for forecasting customer retention, respectively. Finally, the importance-performance analysis is conducted to offer managerial insights. Furthermore, support vector machine is used to justify the validity of customer retention. In summary, the main contributions are described as follows: (1) capturing passenger perceptions of airline services, (2) indicating which SAs should be improved first to enhance passenger satisfaction, and (3) using the identified key predictors to forecast customer retention.

Integration of fuzzy theory into Kano model for classification of service quality elements: A case study in a machinery industry of China

Purpose: The purpose of study is to meet customer requirements and improve customer satisfaction that aims to classify customer requirements more effectively. And the classification is focused on the customer psychology. Design/methodology/approach: In this study, considering the advantages of Kano model in taking into account both customer’s consuming psychology and motivation, and combining with fuzzy theory which is effective to cope with uncertainty and ambiguity, a Kano model based on fuzzy theory is proposed. In view of the strong subjectivity of traditional Kano questionnaires, a fuzzy Kano questionnaire to classify the service quality elements more objectively is proposed. Furthermore, this study will also develop a mathematical calculation performance according to the quality classification of fuzzy Kano model. It’s more objective than traditional Kano model to realize the service quality elements classification. With this method, the accurate mentality can be fully reasonable reflected in some unknown circumstances. Finally, an empirical study in Xuzhou Construction Machinery Group Co., Ltd, the largest manufacturing industry in China, is showed to testify its feasibility and validity. Findings: The calculation results indicate that the proposed model has good performance in classifying customer requirements. With this method, the accurate mentality can be fully reasonable reflected in unknown circumstances and it is more objective than traditional Kano model to classify the service quality elements. Originality/value: This study provides a method to integrate fuzzy theory and Kano model, and develops a mathematical calculation performance according to the quality classification of fuzzy Kano model.

Providing a way to Recognize Bank Customers' needs Effectively based on Clustering Techniques, the Fuzzy TOPSIS and Kano Model: A Case Study in Bank of Qarzollhassaneh Mehr Iran in Khuzestan

The service organizations and especially banks as economic units attempt to get customers’ expectations and needs. But one of the main challenges of bank managers is how to get a framework to classify customers and recognize their needs in order to provide better services. The present study aim is to provide a model to recognize the bank customers’ needs effectively and classify them through three ways-clustering, fuzzy TOPSIS, Kano model to supply better services. The questionnaire is used to get data, population included 384 clients of contribution bank of Mehr Iran in Khuzestan and 5 cluster of customers were selected as sample through Weka software and experts’ perspectives. Then, clusters were classified by Fuzzy TOPSIS and clients ‘expectations were determined through satisfaction model of Kano. The results showed that this model may use in most service organizations especially in banks, so it caused to make satisfaction, loyalty and recognize the customers’ needs and more competition.

The relative effects of different dimensions of traditional cultural elements on customer product satisfaction

It is increasingly important to account for cognizance of local cultural elements during the product design process. The relationship between traditional cultural elements and customer satisfaction was explored in this study. A Continuous Fuzzy Kano Model was used to analyze the effects of different cultural elements on user satisfaction. And a design practice was carried out to verify the results. Twenty-four cultural product cases were identified and investigated. We developed a scale questionnaire to examine the cases, and identified and categorized the relevant cultural elements. This study identifies the importance for product designers of individual cultural elements, and ascertains which dimension of cultural elements better satisfies user requirements. Relevance to industryThis information is very relevant for designers and developers as it helps them to identify important cultural elements and estimate their effects on the user's satisfaction of products.

A Decision-Making Method for Improving Logistics Services Quality by Integrating Fuzzy Kano Model with Importance-Performance Analysis

In resources limited circumstances, seeking relationship between customer satisfaction and logistics service performance is meaningful for the development of logistics companies. Therefore, it is crucial for logistics companies to understand that logistics service quality attributes can increase satisfaction and their improvement priorities can help make better decisions. Thus, the identification of logistics service quality attributes importance and their contributions on improving customer satisfaction have become more necessary to logistics companies success. Considering traditional Kano model classification is subjective, the contribution of this study is, therefore, to integrate fuzzy Kano model with importance-performance analysis to address the shortcomings with using these two methods separately. What’s more, constructing a decision-making method can help logistics companies determine the priority of logistics service quality attributes. Finally, an empirical study on customer satisfaction was undertaken. The feasibility and effectiveness of this method had been verified.

A Method to Forecast the Dynamics of Express Delivering Quality Elements Classification Based on GM(1,1) Model

Aiming at solving the problem of forecasting the dynamics of express delivering quality elements classification, the paper proposed a novel method integrating Kano model with GM(1,1) model which is effective to perform fitting prediction. An approach of fuzzy questionnaires to modify Kano questionnaires which considered as subjective is suggested, and the GM (1,1) model is used to estimate and predict data according to the quality classification of fuzzy Kano model. An empirical study in express industry is provided to testify its feasibility and validity.

Combining fuzzy AHP and fuzzy Kano to optimize product varieties for smart cameras: A zero-one integer programming perspective

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.

Incorporating customer satisfaction into the decision-making process of product configuration: a fuzzy Kano perspective

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.

A novel integrated model to increase customer satisfaction

This paper proposes a novel model encompassing the Kano model (KM), fuzzy theory, and Taguchi method (TM) to precisely define customer requirements and increase customer satisfaction. Therefore, the proposed model has the following capabilities: (1) defining the true requirements of customers, (2) quantifying customer satisfaction, (3) organizing possible solutions or proposals for products, and (4) analyzing product feasibility. In addition, we validated the proposed model with a case study of media player appearances, attempting to compare the design outcome of our proposed model, TM + fuzzy Kano model (TMFKM), with other models. A test session was attended by 32 students aged 16–18 who rated their experience with these media players. The results, analyzed by the ANOVA and Scheffe tests, show that the TMFKM is more suitable for product design than competing methods in enabling designers to precisely quantify user needs, analyze product feasibility, and increase user satisfaction.

Sustainability assessment of an automotive organisation using fuzzy Kano's model

Sustainable development is the development that meets the needs of the present generation without compromising the ability of future generations to meet their own needs. Sustainability assessment is an important part of the decision process in organisations. Sustainability is difficult to define or measure because it is a complex concept. To assess the sustainability level of an organisation, a unique attempt has been made using fuzzy-based Kano model based on the stakeholders' satisfaction. The Kano model is a customer satisfaction assessment tool that must be precise, and it is incorporated with fuzzy logic because it has the capability to replicate the human perceptions. In this context, the approach is used to assess the sustainability by using the stakeholders' satisfaction for different criteria and it provides information regarding improvement in sustainability.

Quality function deployment implementation based on Fuzzy Kano model: An application in PLM system

Product lifecycle management (PLM), a strategic business system allows more effective communication among different groups at dispersed locations to share ideas and access information needed for developing new products and executing innovative processes. The main function of PLM is to develop an attractive system which ensures customer satisfaction. Therefore, one of the important topics of the PLM system developments is to take customer requirements into consideration. Quality function deployment (QFD) has been widely used for numerous years; it is one of the structured methodologies that are used to translate customer needs into specific quality development. However, in the traditional QFD approach, each element’s interdependence and customer requirements are usually not systematically treated. Additionally, the Kano model can effectively classify customer demand attributes, but to make Kano model more objective in the course of weighing, we have also included Fuzzy mode in our discussion. This study presents an integrative approach by incorporating the Kano model with Fuzzy mode into the matrix of QFD and adjusting customer requirement weights. This approach can fulfill two objectives, First, through the Kano model with the Fuzzy mode, it will not only discriminate out options for the required attributes in much more breadth but also simultaneously render the discretions on the linguistic implications much more accurate with the aid of the ambiguous questionnaire response method. Second, combining the Kano model and QFD, can not only provide a new way to optimize the product design but can also enhance customer satisfaction and loyalty, and minimize dissatisfaction. The proposed methods can be useful to both practitioners and researchers. To illustrate our findings, we have incorporated an example which suggests that the proposed approach can contribute to the creation of attractive PLM attributes and PLM innovation.