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Li, Z.-Q., Hu, S.-y., Wang, J.-h., Yu, H.-l., Fu, X.-H., Yang, J.-h., Li, L.-M., Li, S., and Zhu, W.-k. (2024). “Functional requirements and design strategy of E-sports chair based on the KANO model,” BioResources 19(3), 4679-4697.

Abstract

A design strategy was developed, based on the KANO model, for health-centric and sustainable e-sports chair products. Specifically, this study investigated the functional requirements of e-sports chairs using interviews and questionnaires to guide their subsequent design. The functional requirements of the e-sports chair were evaluated using the KANO model. In addition, a satisfaction coefficient was introduced to optimize the traditional KANO model and to obtain the functional requirement classification of the e-sports chair. The sensitivity coefficient was used to evaluate whether the e-sports chair functions attract users. The research results show that users have clear functional requirements for e-sports chairs, and there is a significant correlation between satisfaction and sensitivity. Moreover, the adjustability and air permeability of the e-sports chair greatly improves user satisfaction, and the non-difference function can simplify the process by reducing production costs. This research develops a hierarchical model of demand for e-sports chairs and categorizes the results by essential, one-dimensional, attractive, non-differentiated, and sensitivity requirements. Furthermore, the main attributes of user preferences for e-sports chairs are explored, which provides a certain theoretical basis for the subsequent design and production of e-sports chairs.


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Functional Requirements and Design Strategy of E-sports Chair Based on the KANO Model

Ze-Qun Li,a,1 Sun-yue Hu,a,1 Jin-huan Wang,b Hui-ling Yu,c Xiao-Han Fu,a Jun-hui Yang,a Lu-Ming Li,a,* Song Li,a,* and Wen-kai Zhu a,*

A design strategy was developed, based on the KANO model, for health-centric and sustainable e-sports chair products. Specifically, this study investigated the functional requirements of e-sports chairs using interviews and questionnaires to guide their subsequent design. The functional requirements of the e-sports chair were evaluated using the KANO model. In addition, a satisfaction coefficient was introduced to optimize the traditional KANO model and to obtain the functional requirement classification of the e-sports chair. The sensitivity coefficient was used to evaluate whether the e-sports chair functions attract users. The research results show that users have clear functional requirements for e-sports chairs, and there is a significant correlation between satisfaction and sensitivity. Moreover, the adjustability and air permeability of the e-sports chair greatly improves user satisfaction, and the non-difference function can simplify the process by reducing production costs. This research develops a hierarchical model of demand for e-sports chairs and categorizes the results by essential, one-dimensional, attractive, non-differentiated, and sensitivity requirements. Furthermore, the main attributes of user preferences for e-sports chairs are explored, which provides a certain theoretical basis for the subsequent design and production of e-sports chairs.

DOI: 10.15376/biores.19.3.4679-4697

Keywords: KANO model; E-sports chair; Functional requirement; Design strategy

Contact information: a: College of Chemistry and Materials Engineering, Zhejiang A&F University, Hangzhou 311300, China; b: Sunon Technology Co., LTD, Hangzhou 311200, China; c: College of Intelligent Science and Engineering, Yantai Nanshan University, Yantai 265713, China;

* Corresponding authors: llm@zafu.edu.cn, 20090013@zafu.edu.cn, wenkai0814@zafu.edu.cn; 1. These authors contributed equally to this work.

GRAPHICAL ABSTRACT

KANO graphical abstract

INTRODUCTION

In recent years, the e-sports field has developed rapidly and globally, and the number of active users has grown exponentially. As a result, this activity has been recognized as a sport by the International Olympic Committee and the Asian Olympic Committee in 2018 (Seo 2013). E-sports has also developed rapidly in China. According to recent statistics, the number of e-sports users in China has exceeded 500 million in 2021, making it one of the main forms of public entertainment (Zhao et al. 2020). At the same time, products related to e-sports continue to emerge; among them, e-sports chairs have become an important and popular product. E-sports chairs are ergonomic chairs designed and produced by combining the technology of racing chairs with ergonomic principles suitable for computer work (Li and Zhang 2021). Owing to their specialized seating properties, e-sports chairs are typically designed with better wrap-around support and with a wide range of colors that can match different trendy styles and form personalized color schemes that blend in with their surroundings (Du et al. 2022). In addition, many e-sports chair designs currently use wooden construction, giving them excellent environmental performance and an attractive appearance. Therefore, e-sports chairs built with wooden components are expected to achieve better user satisfaction, gaming success, and comfort. Furthermore, the ergonomic comfort provided by e-sports chairs has not only led people to use them for recreational gaming, but also to replace traditional office chairs as the primary seating option for professional work. This integration of leisurely relaxation into the work process has expanded the usage scenarios for e-sports chairs. Consequently, both domestic and international researchers have gradually begun to delve into the design and research of e-sports chairs. For example, Yang and Wu (2021) analyzed the overall comfort of commonly used e-sports chair brands through the induction and summarization method and produced a more comfortable e-sports chair style. Wang and Lv (2022) started with common e-sports occupational diseases, based on ergonomics, combined with traditional Chinese medicine acupoints, and improved the design of e-sports chairs to stimulate the back acupoints effectively when leaning back, thereby achieving the effect of relieving pain and promoting health. Yin and Fang (2021) analyzed the effects of sitting posture and duration on user psychology based on ergonomic principles and improved the front, side, and back of existing e-sports chairs through streamlined design to make them more compatible with users’ physiological and psychological needs. Gutierrez et al. (2019) proposed an e-sports chair design with an arm support system aimed at guiding the scapula to the proper position, thus improving the user posture. The research conclusions of scholars show that adjustability, comfort, and appearance are the main research attributes in the design of e-sports chairs. Adjustability enables users to adapt to different seating postures; comfort can enable users to maintain a comfortable seating posture for a long time without fatigue, ensuring their physical health; and appearance can make users look more professional and improve their psychological comfort.

Data shows that the size of China’s esports market exceeded 165 billion yuan in 2021, and it is expected to reach 218.6 billion yuan by 2024, an increase of 32.5%. However, with the increasing competition in the e-sports chair market, existing products are of uneven design quality and suffer from serious homogenization. Apart from differences in appearance and color, their functional structure is largely the same, and additional features are lacking, making it difficult to meet the personalized needs of users (Tseng 2020). Furthermore, e-sports often require maintaining a seated position for extended periods, potentially resulting in significant health damage (Yang et al. 2024). This presents new requirements for e-sports chair design and materials. In response to current market demand, a new design strategy is needed to meet the health and sustainability requirements of the product, bringing innovation and vitality to e-sports chair design.

The KANO model is a well-known cognitive model developed by Noriaki Kano, a famous management scientist from the Tokyo Institute of Technology (Materla et al. 2019; Liu and Li 2020). It accurately reflects the non-linear relationship between customer quality, attributes, performance, and overall satisfaction, and is primarily used for analyzing and acquiring user requirements. It is an essential tool for designers in the early research stages (Shan et al. 2022). Wu et al. (2024) integrated the KANO model into the innovative design of bamboo furniture, transforming subjective user needs into more rigorous indicators of demand using the KANO model, thus addressing the product’s design positioning issues. Wang and Zhou (2023) conducted a comprehensive study involving desktop research, user journey mapping, and user interviews to capture the needs of their target users. Subsequently, they employed the KJ method for hierarchical analysis. Following this, they utilized the KANO model to cluster user requirements, thus revealing distinct categories and priority rankings. Finally, by integrating the KANO model with the QFD model, they constructed a comprehensive model of requirements and features from which they extracted crucial design elements for in-depth development. Many people have applied the KANO model to household products (Li and Wang 2023), industrial products (Qi et al. 2023), souvenirs (Tama et al. 2015), and other products, demonstrating the wide-ranging application of the KANO model in improving design. In this study, the KANO model evaluation method was used to obtain the design requirements for e-sports chairs. The satisfaction coefficient and sensitivity coefficient were used to optimize the model, and a series of design principles for e-sports chairs that promote health and sustainability were proposed based on the research results, providing theoretical support for the improvement of e-sports chair design.

EXPERIMENTAL

Research Methodology

This study developed a health-centric and sustainable design strategy for the development of e-sports chair products based on the KANO model (Fig. 1).

Fig. 1. Research method of e-sports chair product design strategy

The e-sports chair product design strategy includes four levels: requirement acquisition, requirement analysis, evaluation, and guidance level. The requirement acquisition level obtains users’ design requirements for e-sports chairs through methods such as questionnaire surveys and interviews, and it establishes the requirement hierarchy of e-sports chairs based on this. Then, at the requirement analysis level, a Likert bidirectional requirement questionnaire is designed according to the hierarchical model to obtain user evaluation indicators based on the KANO model. At the evaluation level, the satisfaction coefficient and sensitivity coefficient are used to optimize the KANO model, realizing the classification of e-sports chair product requirements and importance ranking. Finally, design principles are determined to develop innovative design strategies for e-sports chair products.

Research Process

Acquisition of e-sports chair design requirements

The functional requirements of the e-sports chair are similar to those of office chairs, aimed at preventing occupational diseases caused by long-term sitting and enabling users to use them more comfortably and for longer periods. In this study, the design requirements of e-sports chairs were discussed through interviews and questionnaires in the requirement acquisition layer. The specific implementation process was as follows:

The relevant questions for the e-sports chair interview were determined by visiting the extensive e-sports chair market in the Zhejiang Province, China and by conducting user surveys. Based on the suggestions obtained from the interview, the requirement questionnaire focused on the seven main unit components of the e-sports chairs’ structural composition, including the seat cushion, backrest, armrest, headrest, lumbar support, footrest, chair legs, and overall requirements, to explore the needs of the functional aspects of each unit component and ultimately determine the design requirements of the e-sports chair (Fig. 2 and Supporting Information).

Fig. 2. Sample e-sports chair demand questionnaire

The data gathered from the design requirements of the e-sports chair directly supported the hierarchical requirements. The investigation of functional elements in e-sports chairs entailed the distribution of 47 questionnaires, yielding 43 valid responses. Subsequently, a total of 22 design prerequisites for e-sports chairs were identified and systematically categorized to establish the hierarchical requirements of these chairs. This included three requirements for the cushion, four requirements for the backrest, seven requirements for the armrest, two requirements for the headrest, two requirements for the lumbar support, one requirement for the footrest, two requirements for the chair legs, and one requirement for overall optimization (Table 1).

Table 1. Research Results of Esports Chair Design Function Requirements

According to the research results shown in Table 1, the main functional requirements of the design of e-sports chairs included adjustability and breathability of the seats. Except for the footrest and chair legs, users expressed the demand for adjustability in parts of the e-sports chair that directly contact the human body. The adjustment method was multi-dimensional and conformed to the changes in human body movement, which reflected more rigorous requirements for ergonomic products from the users. In terms of breathability, users hoped that the seat, backrest, and armrests, which were in closest contact with the human body, had good breathability. However, most of the current e-sports chair products on the market use leather as the covering material, which shows that existing products cannot meet this requirement very well.

Analysis of requirements hierarchy

According to the KANO model, a Likert five-level bidirectional survey questionnaire was designed based on the identified design requirements for the e-sports chair (Vaez Shahrestani et al. 2020). The questionnaire contained the 22 functional requirements listed in Table 1. A separate survey was conducted for each functional requirement, with each question including two aspects: “having this function” and “missing this function.” The questionnaire answer options were set to 5 points, where 1 point indicated a very dissatisfied response to the questionnaire description, whereas 5 points indicated a very satisfied response to the questionnaire description (Fig. 3 and Supporting Information) (Yu et al. 2021; Xiong et al. 2023). Respondents rated the described situations based on their level of satisfaction.

Fig. 3. Example of Likert’s bidirectional needs questionnaire

The KANO model survey garnered a total of 776 valid responses, all of which were characterized by impartial and objective evaluations from the participants. After the collection of Likert bidirectional survey questionnaire, the scoring results of the positive and negative questions were entered into the KANO evaluation model, and the intersection point of satisfaction ratings for “having this function” and “missing this function” was used as the attribute of the demand type for each function (Table 2) (Li et al. 2022).

Table 2. KANO Evaluation Model

The traditional KANO model can simply classify product requirements based on their frequency of occurrence (Yin et al. 2022). However, according to the classification shown in the evaluation model table, other requirement types only appeared when users selected extremely satisfied or extremely dissatisfied options; otherwise they were classified as indifferent requirement types (Ma et al. 2019). Therefore, according to the traditional KANO model classification, the frequency of indifferent requirement types was higher than that of other types (Wang et al. 2019).

To address this issue, this study optimized the traditional KANO model by introducing a consumer satisfaction coefficient to further confirm the requirement types. The formula for calculating the satisfaction coefficient is as follows,

SI = (A+O)/(A+O+M+I) (1)

DSI = -(O+M)/(A+O+M+I) (2)

where SI represents the satisfaction coefficient, and DSI represents the dissatisfaction coefficient.

The satisfaction coefficient SI reflects the increase in user satisfaction with this function, which is the proportion of attractive requirements (A) and one-dimensional requirements (O) in the overall demand. The larger the value, the more the user’s satisfaction increases with this function, indicating a high level of desire for this function. Contrarily, the dissatisfaction coefficient DSI reflects the decrease in user satisfaction without this function, which is the proportion of one-dimensional requirements (O) and must-be requirements (M) in the overall demand. The dissatisfaction coefficient is usually negative, and the larger the absolute value, the more the user’s satisfaction decreases when missing this function, indicating a high level of requirement for this function, which is essential to achieving customer satisfaction (Haber et al. 2020; Jin et al. 2022; Liu et al. 2024). Based on this, this study also introduces the sensitivity coefficient to determine the user’s sensitivity to the functional requirements (Zhu et al. 2023a).

The sensitivity calculation formula is given in Eq. 3,

(3)

where ω represents the sensitivity coefficient, and the closer its value is to 1, the higher the sensitivity of the functional requirement to users, indicating a higher level of demand.

RESULTS AND DISCUSSION

Analysis of the KANO Model Results

To understand the impact of customer satisfaction and dissatisfaction on the demand types of e-sports chairs, the index coefficients of each demand item were calculated using Eqs. 1 and 2 based on the results of the Likert two-way questionnaire survey. Using the satisfaction index SI value as the horizontal axis and the dissatisfaction index DSI value as the vertical axis, and taking the average value as the critical line of the horizontal and vertical axes, a scatter plot of the demand satisfaction level of e-sports chair products was plotted in four-quadrants (Fig. 4) (Chen et al. 2021).

Fig. 4. Four-quadrant scatter plot of satisfaction coefficient for e-sports chairs

From Fig. 4, the 22 indicators of e-sports chair requirements exhibited a linear distribution in the second and fourth quadrants, with an R² value of 0.5666 and a good fitting degree (Wang 2022). This trend showed that users have a clear attitude towards the e-sports chair functional requirements proposed in this study; that is, the satisfaction level increased with the presence of the function and decreased with the absence of the function in a positive correlation.

Examining the quadrants, the first quadrant included three functional indicators, Q8, Q19, and Q22. The points in this quadrant had high SI values and low absolute DSI values, indicating that having these functions significantly increased user satisfaction, but the absence of these functions did not affect user satisfaction, which belonged to the attractive requirements (A). The second quadrant included eight functional indicators, Q6, Q9-Q14, and Q21. The points in this quadrant had low absolute values of both SI and DSI, indicating that whether these functions were present or not had a small impact on user satisfaction, which belonged to the indifferent requirements (I). The third quadrant only included one functional indicator, Q1. The points in this quadrant had low SI values and high absolute DSI values, indicating that users were not concerned whether they have this function, but the absence of this function had a significant impact on their satisfaction, which belonged to the requirements (M). The fourth quadrant included ten functional indicators, Q2-Q7, Q15—Q18, and Q20. The points in this quadrant had high absolute values of both SI and DSI, indicating that whether these functions were present or not had a significant impact on user satisfaction. Having these functions can greatly increase user satisfaction, while the absence of these functions can greatly reduce user satisfaction, which belongs to the one-dimensional requirements (O).

Analysis of Satisfaction and Sensitivity of Design Requirements

According to the survey questionnaire, the satisfaction and sensitivity coefficients were calculated (Table 3). Users were more sensitive to the adjustability of the e-sports chair. Several functions related to the adjustment of the e-sports chair, such as Q4, Q15, and Q17, had higher sensitivity coefficients, indicating that users hoped that the e-sports chair could be more flexible in adapting to people with different body sizes and sitting habits. This multi-adjustable design made the e-sports chair closer to the definition of ergonomics and more comfortable to use. Q3 and Q7 were ranked third and fifth, respectively, indicating that users were also very concerned about the breathability of the e-sports chair.

Good breathability can provide users with a more comfortable experience when using e-sports chair products. The excellent breathability of the seat cushion and backrest helped the skin ventilate and perspire, making it more comfortable to sit for a long time, while reducing the breeding of bacteria and mites, and maintaining the product material clean and tidy. The sensitivity coefficients of the three attractive requirements (A) functions, Q22, Q19, and Q8, were all in the middle of the ranking results, indicating that users had a mixed attitude towards these functions. The sensitivity coefficients of various functions in the indifferent requirements (I) were relatively low, indicating that users are less concerned about these functions.

Table 3. Functional Demand Satisfaction Coefficient and Sensitivity Coefficient of E-sports Chair