User-demand-oriented design of restorative seating in urban parks: Using a GT–Kano–AHP–QFD–TOPSIS hybrid model

Abstract

Urban parks are increasingly expected to support rest, relaxation, and restorative perception under accelerating urbanization and everyday stress. However, studies on park seating still lack a systematic pathway for translating user demands into design elements and selecting design alternatives. Taking restorative-oriented wooden seating in urban parks as the object, this study developed a GT–Kano–AHP–QFD–TOPSIS hybrid model. Semi-structured interviews with 30 park users were analyzed using grounded theory. Kano classification was then conducted using 91 valid questionnaires. Twelve experts applied AHP to weight 13 user demand items, which were translated into design elements through QFD. Finally, 17 evaluators rated three design alternatives on a seven-point scale, and TOPSIS was used for ranking. The results showed that seating comfort, ergonomic dimensional optimization, and aesthetic form had the highest weights, at 0.1614, 0.1404, and 0.1321, respectively. Ergonomic dimensions, backrest design, lumbar support, multi-user adaptability, and aesthetic form were identified as priority design elements. Alternative 3 achieved the highest relative closeness coefficient (0.8007), indicating the best overall performance. This study provides a traceable user-oriented decision pathway for wooden park seating design, while its findings reflect perceived preferences rather than clinically or physiologically verified outcomes.

Full Article

User-Demand-Oriented Design of Restorative Seating in Urban Parks: Using a GT–Kano–AHP–QFD–TOPSIS Hybrid Model

Suli Ti  ,^a Ting Yu, ^a,b,* Qitao Wu, ^a and Qing Zhang ^a

Urban parks are increasingly expected to support rest, relaxation, and restorative perception under accelerating urbanization and everyday stress. However, studies on park seating still lack a systematic pathway for translating user demands into design elements and selecting design alternatives. Taking restorative-oriented wooden seating in urban parks as the object, this study developed a GT–Kano–AHP–QFD–TOPSIS hybrid model. Semi-structured interviews with 30 park users were analyzed using grounded theory. Kano classification was then conducted using 91 valid questionnaires. Twelve experts applied AHP to weight 13 user demand items, which were translated into design elements through QFD. Finally, 17 evaluators rated three design alternatives on a seven-point scale, and TOPSIS was used for ranking. The results showed that seating comfort, ergonomic dimensional optimization, and aesthetic form had the highest weights, at 0.1614, 0.1404, and 0.1321, respectively. Ergonomic dimensions, backrest design, lumbar support, multi-user adaptability, and aesthetic form were identified as priority design elements. Alternative 3 achieved the highest relative closeness coefficient (0.8007), indicating the best overall performance. This study provides a traceable user-oriented decision pathway for wooden park seating design, while its findings reflect perceived preferences rather than clinically or physiologically verified outcomes.

DOI: 10.15376/biores.21.4.10366-10407

Keywords: User demands; Urban park; Restorative seating; GT–Kano–AHP–QFD–TOPSIS hybrid model; Restorative design

Contact information: a: Department of Convergence and Art, School of Design, Silla University, Busan 46958, South Korea; b: Department of Interior Design, School of Creative Design, Zhejiang University of Security Technology, Wenzhou, Zhejiang Province, 325000 China;

* Corresponding author: [email protected]

Graphical Abstract

INTRODUCTION

In the post-pandemic period, public mental health pressures and the demand for everyday restorative environments have remained prominent concerns. The World Health Organization reported that, during the first year of the COVID-19 pandemic, the global prevalence of anxiety and depression increased by 25% relative to pre-pandemic levels, indicating the sustained psychosocial burden imposed by public health emergencies (World Health Organization 2022). With rapid urbanization, urban parks have become among the green open spaces most frequently used in residents’ daily lives. They provide essential environmental conditions for rest, short-term stay, social interaction, and relaxation. Previous studies have shown that the quality and accessibility of urban green spaces, together with built-environment characteristics, are closely associated with residents’ mental health and perceived well-being (Fang et al. 2024). Accordingly, improving users’ comfort, relaxation, and perceived restoration through specific facilities in urban parks has become an important topic in healthy-city and public-space design research.

Among the various public facilities in urban parks, seating is a key micro-scale element that links bodily support, duration of stay, and place experience. It provides basic functions such as rest, observation, waiting, and social interaction. Its spatial arrangement, dimensional proportions, material tactility, formal characteristics, color relationships, and integration with the surrounding landscape also shape users’ comfort, perceived safety, sense of affinity, and overall satisfaction. Previous studies have shown that the form, materials, patterns, and spatial order of public seating significantly influence users’ aesthetic evaluations and use experiences (Mohamed 2024). Identifying renewal strategies for public seating based on residents’ needs can further improve the specificity and practical applicability of urban park facility design (Zhang and Sun 2024). Therefore, seating should not be regarded merely as a general resting facility. Rather, it can be understood as a micro-scale medium in urban parks that supports bodily comfort, environmental perception, and restorative experience.

Wooden seating in urban parks warrants focused research attention. Compared with public facilities made of metal, concrete, or plastic, wood offers natural texture, warm tactility, strong environmental compatibility, and biophilic qualities. These characteristics allow wooden seating to integrate more effectively into the green landscape context of urban parks (Jasińska et al. 2024; Lin et al. 2024). As a renewable material, wood also has potential advantages in low-carbon performance, repairability, and recyclability when supported by appropriate material selection, structural design, preservative treatment, and maintenance strategies. These properties are consistent with the sustainable development of outdoor public furniture (Hitka et al. 2022). However, existing studies on urban park seating have largely focused on the renewal of general public facilities, aesthetic satisfaction, and spatial arrangement optimization. Less attention has been paid to how the material characteristics of wood contribute to the formation of user demands, the translation of design elements, and the selection of design alternatives. In park seating design oriented toward restorative experience, the tactile, visual, ecological, and maintenance-related properties of wood have not yet been adequately incorporated into a systematic design evaluation framework.

In this study, the term “restorative seating” does not refer to seating with medical or clinical treatment functions. Instead, it denotes wooden seating in urban parks designed to support perceived restoration, psychological comfort, emotional relief, and relaxation. The aim is not to demonstrate that seating directly reduces anxiety or produces clinically verified psychological or physiological outcomes. Rather, the study examines how users perceive seating in terms of safety, comfort, naturalness, affinity, and contextual fit. Research on restorative environments has shown that natural environmental features, perceived spatial safety, and environmental experience can influence individuals’ perceived restoration (Grave et al. 2024). However, a clear translation gap remains between theoretical concepts of restorative environments and furniture-scale design language. Further research is therefore needed to determine how users’ subjective demands for comfort, relaxation, safety, naturalness, and aesthetic quality can be translated into evaluable, comparable, and implementable design elements for wooden seating.

User-oriented design research has increasingly adopted methodological approaches that integrate qualitative identification with quantitative translation. Grounded Theory (GT) is well suited to deriving dimensions of user demand from interview data (Charmaz 2014). The Kano model distinguishes must-be, one-dimensional, and attractive demands, thereby revealing the asymmetric effects of different demand attributes on user satisfaction (Kano et al. 1984; Berger et al. 1993). The Analytic Hierarchy Process (AHP) can be used to determine the relative weights of user demands (Saaty 1980), while Quality Function Deployment (QFD) translates these demands into design elements (Hauser and Clausing 1988; Akao 1990). The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) supports the comprehensive evaluation and ranking of multiple design alternatives (Hwang and Yoon 1981). Previous studies have applied Kano, AHP, and QFD to public facilities, age-friendly environments, and furniture design, demonstrating their effectiveness in complex demand identification and design translation (Liu et al. 2024). However, research on wooden restorative seating in urban parks still lacks an integrated methodological chain that connects user demand identification, demand attribute classification, weight determination, design specification mapping, and comprehensive alternative evaluation.

Beyond the absence of an integrated methodological chain, a conceptual gap also remains in explaining how heterogeneous and subjective user demands are progressively transformed into explicit furniture-design decisions. Existing approaches often address demand identification, prioritization, or design translation as separate analytical tasks. This study therefore treats user-centered furniture design as a staged demand-transformation process linking user expression, demand attributes, priority structures, design specifications, and alternative evaluation.

To address these limitations, this study focused on wooden restorative seating in urban parks and developed a GT–Kano–AHP–QFD–TOPSIS hybrid model. User demand dimensions were first identified through preliminary interviews. The Kano model was then used to classify demand attributes, while AHP was applied to determine the relative weights of user demands. These demands were subsequently translated into design elements through QFD. Finally, TOPSIS was used to comprehensively evaluate and rank the design alternatives. This study aimed to establish a user-demand translation pathway for wooden seating design in urban parks and to provide a methodological reference for restorative-experience-oriented wooden public furniture design. Accordingly, this study addressed the following research questions:

RQ1: What are the core dimensions of user demand for wooden restorative seating in urban parks?

RQ2: How are different user demands prioritized based on Kano attribute classification and AHP-derived weight ranking?

RQ3: How can user demands be translated into actionable design elements for wooden seating, and how can different design alternatives be comprehensively evaluated?

EXPERIMENTAL

This study adopted the Double Diamond Model as its overall framework. Through the four stages of “discover, define, develop, and deliver,” the design process was organized into two consecutive diamond structures: problem exploration and demand definition, followed by design development and outcome delivery (Design Council 2005). The first diamond focuses on exploring and defining the problem space. It uses divergent research to comprehensively identify relevant issues, followed by convergent analysis to clarify key user demands. The second diamond focuses on generating and implementing solutions. It involves screening, prioritizing, and translating multiple design possibilities into an implementable design alternative. The model emphasizes the continuity and systematic logic of design research, from “identifying the right problem” to “developing an appropriate solution.” It therefore aligns well with the user-demand-oriented objective of restorative seating design in urban parks.
The methodological sequence was determined by the progressive transformation of information required in user-centered furniture design rather than by simply combining multiple analytical techniques. GT was positioned first because the relevant user-demand criteria were not assumed in advance and therefore needed to be inductively derived from users’ situated experiences. Once the demand set had been established, the Kano model was used to distinguish the asymmetric effects of different demand attributes on satisfaction, thereby providing a structured basis for screening and organizing the demands before weighting. AHP was then applied because Kano classification identifies demand types but does not determine their relative priority within the design decision process. The resulting weights were subsequently introduced into QFD, which translated prioritized user demands into actionable design elements and technical characteristics. Finally, TOPSIS was applied after the design criteria, their weights, and the design alternatives had been established, allowing the alternatives to be compared according to their overall proximity to the weighted ideal solution. Thus, each method addresses a limitation left by the preceding stage and provides the necessary input for the next stage.

Compared with single-stage decision-making approaches that begin with predefined evaluation criteria or focus primarily on weighting or alternative ranking, the present sequence is more suitable for this study because the initial user-demand structure itself was unknown and required qualitative exploration before quantitative decision analysis. No single method used in the framework independently covers demand elicitation, satisfaction-attribute classification, priority weighting, design translation, and alternative selection. The integrated sequence was therefore selected to preserve traceability from raw user expressions to final scheme evaluation, rather than to claim universal superiority over other decision-making methods. Importantly, the integration is operational rather than merely procedural: the Kano-screened demand set forms the basis of the AHP hierarchy, the AHP-derived weights enter the QFD relationship matrix and subsequent alternative evaluation, and the QFD-prioritized design elements guide the generation and refinement of the design alternatives evaluated by TOPSIS.

Building on the logic of the Double Diamond Model, this study developed a GT–Kano–AHP–QFD–TOPSIS hybrid research pathway by integrating Grounded Theory, the Kano model, the Analytic Hierarchy Process, Quality Function Deployment, and TOPSIS. The pathway establishes a sequential information-transfer process in which the output of each analytical stage serves as the input to the next, progressing from demand discovery and classification to prioritization, design translation, and alternative evaluation. As shown in Fig. 1, the research framework comprises four interconnected stages.

In the Discover stage, GT is used to identify user demands from qualitative data. In the Define stage, the Kano model classifies demand attributes and AHP establishes their relative priorities. In the Develop stage, QFD translates prioritized user demands into actionable design elements and supports the development of design alternatives. In the Deliver stage, TOPSIS evaluates and ranks the alternatives. Thus, the output of each stage serves as the input to the next, forming a traceable pathway from user-demand identification to design translation and alternative selection.

Fig. 1. Overview of the research workflow

User Demand Acquisition Based on Grounded Theory

Expert workshops: Semi-structured interview framework

GT emphasizes the iterative integration of data collection and analysis. Once the research direction has been clearly defined, the interview guide should remain open, flexible, and revisable, rather than being fully fixed before the study begins (Charmaz 2014; Foley et al. 2021). Before conducting formal interviews with park users, this study reviewed relevant literature on restorative environments, urban public spaces, public seating design, and user demand translation. The review results were used to identify preliminary issues related to restorative seating in urban parks. Two rounds of interdisciplinary expert workshops were then organized. Experts in landscape design, environmental design, industrial design, environmental psychology, and public facility design participated in the discussions. The workshops focused on three main issues: the key problems of urban park seating in real-use contexts; the core characteristics that distinguish restorative seating from general park seating; and the ways in which users’ subjective experiences, including relaxation, perceived safety, privacy, sense of belonging, and perceived closeness to nature, could be transformed into research dimensions suitable for interviewing, coding, and design translation. This process did not replace user interviews. Instead, it helped clarify the scope of the interviews, refine the wording of the questions, and reduce the risk that the interview guide would be too broad or misaligned with the research objectives.

Table 1. Semi-Structured Interview Guide

After expert discussion and multiple rounds of revision, this study developed a semi-structured interview framework for restorative seating in urban parks (Kalender et al. 2023). The framework comprises five dimensions. The first dimension addresses use contexts and behavioral characteristics, including the time, location, activity state, and mode of stay associated with park visits and seating use. The second dimension concerns functional needs and spatial adaptation, including requirements for comfort, safety, shading, dimensional suitability, accessibility, and ease of use. The third dimension focuses on perceived restoration and emotional experience, including users’ perceptions of relaxation, safety, privacy, companionship, and emotional relief while using the seating. The fourth dimension examines environmental perception and landscape relationships, including the relationship between seating and tree shade, waterscapes, pathways, quiet areas, and the surrounding natural environment. The fifth dimension concerns design preferences and expectations for improvement, including preferences regarding materials, colors, forms, sense of enclosure, and additional functions. This interview framework provided the basis for subsequent open coding, axial coding, Kano demand classification, AHP-based weight calculation, and QFD-based design translation. The detailed interview questions are presented in Table 1.

User interviews: Identifying explicit and latent demands for restorative seating in urban parks

Field investigations were conducted in representative urban parks in China, with two parks in Wenzhou, Zhejiang Province, selected as primary study sites: Sanyang Wetland Urban Park in Ouhai District and Ma’anchi Urban Park in Lucheng District. Respondents were recruited through a combination of on-site random interception and purposive sampling. The inclusion criteria were as follows: participants had visited urban parks within the past year, had actual experience using park seating, and were able to clearly describe their perceptions of seating use contexts, satisfaction, pain points, and expectations for restorative experience. To improve the relevance of the data, priority was given to users who visited parks frequently and regularly used park seating. The interviews continued until no new substantive concepts emerged during open coding, indicating that theoretical saturation had been reached. In total, 30 park users were interviewed. Their demographic characteristics are presented in Table 2. The interview transcripts were analyzed through open coding, axial coding, and selective coding to identify the core user demands for restorative seating in urban parks. These findings provided the basis for subsequent Kano classification, AHP-based weighting, and QFD-based design translation.

Data collection and organization

Formal interviews were conducted with 30 participants between January 10 and March 12, 2026. This sample size was considered adequate to capture users’ experiences with urban park seating across different use scenarios. Semi-structured interviews were conducted using both online and offline methods. Each interview lasted 7 to 16 min, with an average duration of approximately 13 min. All interviews were audio-recorded and fully transcribed, providing the primary dataset for subsequent GT coding and analysis.

Participation in the interviews, questionnaires, AHP expert evaluations, and design-alternative evaluations was entirely voluntary. All participants received a Participant Information Sheet and provided informed consent before participation. Participants involved in the semi-structured interviews additionally consented to audio recording and transcription. Interview recordings, transcripts, questionnaire responses, expert judgments, and design-evaluation data were handled confidentially. Personally identifying information was removed during data processing, and anonymized data were used for analysis and reporting. Access to the research data was restricted to the research team.

Semantic coding

Open coding is the initial stage of GT analysis. Its purpose is to conceptualize raw textual data, identify analytically meaningful semantic units from participants’ responses, and extract initial concepts. In this study, NVivo 15.0 was used to conduct sentence-by-sentence review and open coding of the semi-structured interview transcripts. To improve the objectivity and reliability of the coding results, three researchers independently completed the initial coding.

Table 2. Demographic Characteristics of Semi-structured Interview Respondents

Table 3. Open Coding Results Based on Grounded Theory

Concept labels and category assignments were then standardized through comparison, discussion, and cross-checking, resulting in a relatively stable initial conceptual system.

A total of 41 initial concepts, labeled a1–a41, and 16 categories, labeled A1–A16, were identified. During axial coding, these categories were further integrated into five main categories, labeled B1–B5. During selective coding, two core categories were ultimately extracted: C1, sensory interaction experience, and C2, environmental symbiotic efficacy. Based on these results, a theoretical model of user demands for urban park seating was constructed, as shown in Table 3.

Theoretical saturation test

GT is an iterative process in which concepts are generated from raw data through theoretical sampling, constant comparison, and repeated category integration. By continuously comparing and analyzing each data source, researchers identify emerging concepts and categories and use them to refine the theoretical framework. Theoretical saturation is reached when subsequent data no longer generate new concepts, categories, or relationships (Hennink and Kaiser 2022).

In this study, three-level coding of the interview data from 30 respondents yielded 41 initial concepts. By the time coding reached the 25^th respondent, all newly added statements could be incorporated into the existing category system, and no new concepts or categories emerged. This indicated that the basic conditions for theoretical saturation had been met. To enhance the completeness and rigor of the analysis, the research team continued coding the remaining five interviews. As no additional concepts or categories were identified, the theoretical analysis was confirmed to have reached a high level of saturation.

User Demand Classification Based on the Kano Model

Scale and questionnaire design

Based on the Kano model of user demand analysis, this study developed a questionnaire to classify the user-demand attributes of restorative seating in urban parks (Cavacece et al. 2025). The questionnaire adopted the classical paired functional–dysfunctional question format of the Kano model. A total of 16 user-demand attributes were evaluated. For each attribute, respondents answered one functional question concerning their reaction when the feature was present and one dysfunctional question concerning their reaction when the feature was absent (Kano et al. 1984; Berger et al. 1993).

For both the functional and dysfunctional questions, respondents selected one of five categorical Kano response options: (1) “I dislike it that way,” (2) “I can live with it that way,” (3) “I am neutral,” (4) “It must be that way,” and (5) “I like it that way.” The numerical values from 1 to 5 were used only as category codes for data entry and did not represent a five-point Likert scale. Each pair of functional and dysfunctional responses was classified according to the standard Kano evaluation matrix into Attractive (A), One-dimensional (O), Must-be (M), Indifferent (I), Reverse (R), or Questionable (Q). For each user-demand attribute, the frequencies of the six Kano categories were calculated across the 91 valid questionnaires, and the category with the highest response frequency was used as the final Kano classification.

The final questionnaire comprised 16 paired Kano items across five major user-demand dimensions, forming the demand-classification system for restorative seating in urban parks. A schematic representation of the paired functional and dysfunctional Kano questionnaire is shown in Fig. 2.

Fig. 2. Schematic representation of the paired functional and dysfunctional Kano questionnaire

Data collection

To broaden the range of perspectives included in the Kano survey, data were collected through both online and offline channels. The offline survey was conducted from March 13 to April 19, 2026, in selected urban park spaces. With on-site guidance from the research team, structured questionnaires were distributed to actual park users, including family groups, leisure visitors, and individual visitors. A total of 50 offline questionnaires were distributed, of which 27 valid responses were obtained.

The online survey primarily targeted design-related practitioners and researchers, including landscape designers, product designers, and scholars in related fields. A total of 100 online questionnaires were distributed, and 64 valid responses were obtained. In total, the combined online and offline survey yielded 91 valid responses. The use of the two recruitment channels enabled the study to incorporate both park-user and professional perspectives, thereby broadening the range of viewpoints considered in the Kano demand classification. The combined sampling strategy was intended to broaden the range of perspectives rather than to achieve statistical representativeness of the broader urban park user population.

Reliability and validity tests

Reliability and validity analyses were conducted in SPSS 27.0 using the collected questionnaire data to assess the measurement quality and structural adequacy of the scale. Internal consistency was first evaluated using Cronbach’s α coefficient. The overall scale yielded a Cronbach’s α value of 0.903, exceeding the commonly accepted threshold of 0.90 (Hair et al. 2014). This result indicates excellent internal consistency and supports the suitability of the data for further analysis.

The Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity were then used to assess sampling adequacy and the appropriateness of the data for factor analysis. The KMO value was 0.773, exceeding the recommended threshold of 0.70 (Hair et al. 2014). Bartlett’s test of sphericity was statistically significant (p < 0.05), indicating sufficient correlations among the variables.

These results confirm that the user demand scale for restorative seating in urban parks has good reliability and validity. The dataset therefore provides a reliable empirical basis for subsequent Kano classification and multidimensional demand structure analysis.

Table 4. Analysis of Kano Results

To quantify the effects of different functional attributes on user satisfaction, this study calculated the satisfaction impact coefficient (SI) and dissatisfaction impact coefficient (DSI) for each indicator based on the Kano classification matrix. SI measures the extent to which the presence of a given function enhances user satisfaction, whereas DSI reflects the degree of user dissatisfaction caused by the absence of that function (Berger et al. 1993). The calculation formulas are as follows,

where A denotes attractive demand, O denotes one-dimensional demand, M denotes must-be demand, and I denotes indifferent demand.

As shown in Table 4, different restorative demand attributes varied substantially in their contributions to satisfaction and dissatisfaction. A higher SI value indicates that the presence of a function more strongly enhances users’ restorative experience and spatial satisfaction. A lower, more negative DSI value indicates that the absence of the function is more likely to generate dissatisfaction and weaken the spatial experience. For example, seating experience, ergonomic comfort support, and appearance and form contribute strongly to satisfaction enhancement. In contrast, facility safety, cleaning, and maintenance are more closely associated with must-be demands, and their absence would substantially reduce the user experience. As shown in Fig. 3, A4, A7, and A14 are classified as indifferent demands. Overall, the Kano model effectively identifies differences among demand levels for restorative seating in urban parks. These findings provide an important basis for subsequent functional prioritization, design optimization, and refined public space renewal. Therefore, the three indifferent demand items were excluded from the subsequent AHP analysis.

Fig. 3. Better-worse analysis results

AHP-Based Calculation and Ranking of User Demand Weights

Construction of the hierarchical structure model

Before calculating AHP weights, this study decomposed user demands for restorative seating in urban parks into a hierarchical structure based on the preceding Kano classification results. A three-level AHP model was constructed, comprising the goal layer, criterion layer, and sub-criterion layer. The goal layer was defined as “core user demands for restorative seating in urban parks.” The criterion layer included three Kano demand types with clear effects on user satisfaction: must-be demands (M), one-dimensional demands (O), and attractive demands (A). Indifferent demands (I) and reverse demands (R) were excluded from the subsequent weighting analysis because they provide limited support for establishing effective design priorities.

The sub-criterion layer comprised 13 representative functional demands identified through the Kano analysis: facility safety, cleaning and maintenance, all-day use, multi-user adaptation, ergonomic dimensional optimization, armrest support, lumbar support, backrest optimization, seating experience, landscape adaptation, multi-functionality, auxiliary module expansion, and appearance and form, as shown in Fig. 4. This hierarchical structure established a clear correspondence between user demand attributes and specific design evaluation indicators, providing the basis for constructing judgment matrices, calculating weights, and conducting consistency tests.

Fig. 4. Hierarchical analysis model of user demands

Construction of the judgment matrix and weight calculation

After establishing the hierarchical structure model, 12 experts were invited to conduct pairwise comparisons of the indicators using the Saaty 1–9 scale (Saaty 1980). The expert panel comprised professionals with backgrounds in landscape design, industrial/product design, and visual/environmental design. Experts were selected based on their professional or academic experience in furniture design, public-facility design, environmental design, ergonomics, or related user-centered design fields, as well as their familiarity with design evaluation and multi-criteria decision-making. Only individuals with relevant professional practice, research, or teaching experience were included to ensure that the judgments reflected both design expertise and the characteristics of urban public seating. (Saaty 1980). Based on this approach, the judgment matrix was defined as follows:

According to Eq. 3, the judgment matrix for the criterion layer of user demands for restorative seating in urban parks was first constructed (Table 5).

Table 5. Judgment Matrix for the Standard Layer

Using Eqs. 4 through 7, the corresponding relative weights were calculated. Following the same procedure, judgment matrices were constructed for the 13 functional attributes at the sub-criterion level, and their local weights were computed (Table 6). The global weight of each functional attribute was then obtained by multiplying its local weight by the weight of the corresponding criterion, followed by normalization. Based on the resulting weights, all indicators were ranked according to their priority.

Table 6. Sub-Criterion Level Judgment Matrix

AHP Results

As shown in Fig. 5, the weights of user demands for restorative seating in urban parks exhibited a clear hierarchical structure. The top ten indicators were ranked as follows: seating experience O7 (0.1614), ergonomic dimensional optimization O3 (0.1404), appearance and form A4 (0.1321), backrest optimization O6 (0.1157), lumbar curve support O5 (0.0896), armrest support for body structure O4 (0.0783), facility safety M1 (0.0708), auxiliary functional module expansion A3 (0.0589), enhanced multifunctionality A2 (0.0423), and cleaning and maintenance M2 (0.0354).

Among these indicators, seating experience, ergonomic dimensional optimization, and appearance and form ranked as the top three. This indicates that users prioritize immediate, stable, and comfortable usage experiences. Seating comfort and anthropometric compatibility determine whether users can remain seated for extended periods. In contrast, appearance and form influence users’ willingness to approach the seating, as well as spatial recognition and emotional perception.

Backrest optimization, lumbar curve support, and armrest support ranked fourth to sixth, indicating that the comfort of restorative seating is not determined solely by the seat surface. Instead, it depends on an integrated bodily support system composed of the seat surface, backrest, lumbar region, and armrests. Although facility safety and cleaning and maintenance ranked lower than comfort-related indicators, they remain fundamental requirements for public facilities and must be ensured in terms of structural load-bearing stability, edge protection, weather resistance, corrosion prevention, drainage performance, and ease of maintenance.

Fig. 5. Ranking results of user demand hierarchical analysis

Auxiliary functional module expansion and enhanced multifunctionality are considered value-added experiential factors. They can improve usability and contextual adaptability but should not replace basic seating functionality. Overall, the design of restorative seating in urban parks should prioritize seating experience and ergonomic dimensional optimization as core considerations, emphasize backrest, lumbar, and armrest support as key structural components, enhance visual appeal through natural and harmonious form design, and ensure comfort and restorative perception through adequate safety, maintenance, and moderate functional expansion.

As shown in Fig. 5, the results indicate that the identified user demands differ in their relative priority for the design of restorative seating in urban parks. Higher-priority demands are primarily associated with perceived seating comfort, safety, usability, and experiential value. Addressing these demands in subsequent design development may contribute to more favorable user evaluations of the proposed seating. However, the present study did not directly assess changes in actual usage frequency or public-space service performance, and these outcomes require further validation using physical prototypes and real-world deployment.

Consistency verification

Consistency testing was conducted to evaluate the validity of the judgment matrices. After deriving weights from each level of the judgment matrices, a consistency check was performed to assess the logical consistency of expert judgments and to ensure the statistical validity of the resulting weight system (Saaty 1980). First, the maximum eigenvalue (λ_max) was computed using the eigenvector method, as shown below:

A CR value below 0.1 is generally considered acceptable, indicating satisfactory consistency (Saaty 1980). This suggests that the experts’ judgments are sufficiently consistent and that the derived weights provide a reliable basis for subsequent decision-making (Padilla-Garrido et al. 2014).

Table 7. Consistency Test Results

As shown in Table 7, the consistency test results indicated that the CR value of the criterion-level judgment matrix was 0.033. The CR values of the sub-criterion-level judgment matrices for must-be, one-dimensional, and attractive demands were 0.000, 0.049, and 0.030, respectively. All CR values are below the 0.1 threshold, indicating satisfactory consistency across all judgment matrices. This demonstrates that the derived weights are reliable and further confirms the logical robustness and methodological validity of the evaluation system, supporting its use in subsequent user demand weight analysis.

Design Requirement Transformation Based on QFD

Mapping and analysis of user demands and design elements

After completing the ranking of user demand weights for restorative seating in urban parks, this study applied the Quality Function Deployment (QFD) method to construct a relationship matrix between user demands and design elements. The core function of QFD is to translate user demands into operational technical characteristics that can be implemented in design practice. It further employs the House of Quality model to evaluate the correlation strength between user demands and design elements, thereby providing a structured basis for subsequent design generation and optimization (Hauser and Clausing 1988; Akao 1990).

Based on the AHP results, this study identified high-priority requirements—including seating experience, ergonomic dimensional optimization, backrest optimization, lumbar curve support, armrest structural support, and facility safety—as key inputs for the QFD analysis. In addition, a literature review combined with the Delphi method was used to further refine and translate user demands into corresponding design elements.

First, a literature review approach was employed to preliminarily identify design elements related to restorative seating in urban parks. The technical conditions, materials, functionality, and aesthetic attributes of urban furniture directly influence the comfort, attractiveness, and user evaluation of public spaces (Grabiec et al. 2022). In addition, restorative spatial characteristics in urban parks significantly affect users’ perceived psychological restoration (Grave et al. 2024). Public seating design requires a structured integration of user demands, ergonomic performance, environmental sustainability, and design evaluation (Chang et al. 2025). Furthermore, research on furniture dimensional optimization indicates that decisions regarding furniture size not only affect functional performance but are also closely associated with structural integrity, material efficiency, and aesthetic proportion (Jasińska et al. 2024). Studies on wooden chair structures further demonstrate that variations in user body weight and anthropometric parameters influence structural component design. Accordingly, public seating must adequately account for load-bearing safety and structural reliability (Hitka et al. 2022). Furniture form, line quality, and stylistic characteristics can significantly influence users’ emotional responses, thereby providing a theoretical foundation for the aesthetic design and emotional perception of restorative seating (Lin et al. 2024).

Based on the results of the literature review above, this study further employed the Delphi method to conduct expert evaluation and refinement of the initially derived design elements (Linstone and Turoff 1975). The expert panel consisted of professionals from industrial design, product design, ergonomics, environmental design, and public facility design. It included four university faculty members specializing in industrial or product design, four industrial designers with experience in public facilities or furniture design, and two researchers in environmental design or public space design.

The expert evaluation focused on the necessity and operability of each design element, its degree of alignment with user demands, its applicability in urban park contexts, and the presence of redundancy or conceptual overlap. A total of three rounds of Delphi consultation were conducted to validate and refine the design elements until expert opinions converged, resulting in a finalized set of design elements for subsequent QFD House of Quality analysis. Based on the literature review and Delphi-based refinement, the final mapping between user demands and design elements is presented in Table 8.

Construction of the QFD house of quality for restorative seating in urban parks

Based on the user demand importance values derived from the AHP analysis and the established mapping between user demands and design elements of restorative seating in urban parks, a Quality Function Deployment (QFD) House of Quality was constructed, as shown in Fig. 6.

In this model, user demands and their corresponding weights are placed on the left side of the House of Quality, while design elements are positioned at the top. The relationships between user demands and design elements are then evaluated and quantified, enabling a systematic translation of user demands into design elements. Relationship strengths are classified into three levels: strong correlation is assigned a value of 5 and marked with “●”; moderate correlation is assigned a value of 3 and marked with “○”; weak correlation is assigned a value of 1 and marked with “△”; and no significant relationship is left unassigned.

Table 8. User–Design Element Mapping for Park Seating

The technical importance of each design element was calculated by multiplying the weight of each user demand by the corresponding relationship strength and summing the results. The calculation formula is as follows:

where D_j denotes the technical importance of the j-th design element, W_i represents the comprehensive weight of the i-th user demand, R_ij denotes the correlation coefficient between the i-th user demand and the j-th design element, and n is the total number of user demands.

Based on the resulting technical importance values, the design elements were further prioritized, providing a basis for subsequent structural optimization, functional configuration, material selection, and form design of restorative seating in urban parks.

Fig. 6. Quality house

QFD results analysis

Based on the user demand weights and the user demand–design element relationship matrix, this study calculated the technical importance of 13 design elements. These elements were then classified into first-, second-, and third-level design priorities, as shown in Table 9. The results indicate that the design focus of restorative seating in urban parks is not the simple aggregation of multiple functions. Instead, it reflects a systematic response centered on bodily comfort, postural support, public safety, and contextual adaptability. First-level design elements primarily determine the core user experience of the seating system. Second-level design elements mainly enhance tactile comfort, usability, and safety performance. Third-level design elements primarily support environmental adaptability, maintenance and renewal, and long-term service performance. Therefore, subsequent design development should prioritize the implementation of first- and second-level design elements, while treating third-level elements as supporting constraints integrated into the overall optimization framework.

Specifically, the top five first-level design elements in terms of technical importance are ergonomic dimensional optimization DP5 (2.5796), backrest optimization DP8 (1.8421), appearance and form DP13 (1.8335), lumbar curve support DP7 (1.7899), and multi-user adaptation DP4 (1.7891). These results indicate that seat height, seat depth, backrest angle, lumbar support, visual affinity, and adaptability to diverse user groups constitute the core control factors in restorative seating design. Seating experience DP9 (1.7687), armrest structural support DP6 (1.4571), facility safety DP1 (1.1259), and enhanced multifunctionality DP11 (0.9817) constitute the second-level design elements.

Table 9. Design Elements Sorting Table

These primarily address contact comfort, sit-to-stand assistance, structural safety, and lightweight functional extension. All-day use DP3, auxiliary functional module expansion DP12, landscape adaptation DP10, and cleaning and maintenance DP2, although lower in technical importance, remain essential factors influencing long-term usability and spatial adaptability in public environments. Overall, the QFD results establish a hierarchical design priority pathway for restorative seating in urban parks: “anthropometric control → body support optimization → natural and affinity-oriented form design → multi-user adaptability → safety and maintenance assurance.”

RESULTS AND DISCUSSION

Design Alternatives for Restorative Seating in Urban Parks

Based on the results of user demand weight ranking and the QFD House of Quality analysis, the core user demands for restorative seating in urban parks were derived in this study. Design optimization was primarily focused on high-weight factors, which included seating experience, ergonomic dimensional optimization, appearance and form, backrest optimization, lumbar curve support, armrest structural support, and facility safety. These requirements were subsequently translated into actionable and implementable product design elements. During the design process, priority was given to first-level design elements that are directly associated with bodily comfort, postural support, safe use, and emotional relaxation. Secondary design elements, such as multifunctional features and modular expansion, were selectively incorporated to enhance usability. However, excessive functional integration was avoided to prevent dilution of the fundamental resting function of the seating system.

Wood was selected as the primary material owing to its natural texture, warm tactile quality, and relatively low visual impact (Grabiec et al. 2022; Hitka et al. 2022; Lin et al. 2023; Jasińska et al. 2024). It can be effectively integrated into vegetation, pathways, and surrounding landscape elements within urban parks, thereby contributing to the creation of a natural, welcoming, and psychologically soothing resting environment. Compared with metal or stone materials, wood provides a softer tactile experience and is less likely to generate extreme thermal sensations (e.g., excessive cold or heat) under varying climatic conditions, thereby enhancing user comfort during contact and seating. In addition, wood exhibits favorable machinability, which enables ergonomic seat, backrest, and lumbar support forms to be achieved through processes such as bending, joining, chamfering, and surface shaping. When high-quality wood treated for anti-degradative, moisture resistance, and weather resistance is used, both outdoor durability and structural safety can be ensured, and maintenance efficiency is also improved. Therefore, wood not only satisfies the functional requirements of restorative seating in urban parks but also enhances its natural character, emotional affinity, and landscape integration performance.

A restorative seating design scheme for urban parks was developed, targeting multiple user groups and aiming to enhance seating comfort, physical relaxation, perceived safety, and usage frequency in park environments. To efficiently and systematically translate user demands into implementable therapeutic design alternatives, a data-driven hybrid design workflow was developed and implemented. In this workflow, the reasoning capabilities of large AI language models (ChatGPT and Gemini) were integrated with image generation and editing technologies based on OpenAI GPT Image 2 and Google Gemini Nano Banana. These tools were embedded into the Quality Function Deployment (QFD) analysis process (Choudhury et al. 2025). The proposed workflow was designed to address systemic limitations in traditional public furniture design, particularly semantic loss in requirement translation and geometric distortion in design visualization. It was further used to support concept expansion, prompt optimization, and iterative refinement of visual design schemes. The resulting set of restorative seating concepts for urban parks is presented in Fig. 7.

Fig. 7. Design alternatives for restorative seating in urban parks

Rather than pursuing the accumulation of complex functions, the design alternatives were developed to prioritize bodily comfort, postural support, safety, environmental coordination, and long-term maintenance. The proposed dimensional, tactile, structural, and formal strategies are expected to support perceived comfort and usability, while their actual effects on restorative experience and real-world performance require validation through physical prototyping and field-based evaluation.

Through continuous iterative refinement, multiple candidate prototypes of restorative seating for urban parks were developed, and an initial dataset of design alternatives was established (Fig. 7). The design content of the restorative seating for urban parks is presented in Table 10.

On this basis, three design alternatives with high overall alignment were selected based on evaluation criteria, including functional coverage, alignment with restorative-oriented requirements, and solution completeness. These three schemes were further developed along three distinct optimization pathways: ergonomic support, interactive multi-user adaptability, and support for perceived restoration. Collectively, they represent the phased core outcomes of this study on restorative seating design in urban parks.

Table 10. Design Content of Restorative Seating in Urban Parks