The Impact of Wooden Design on User Satisfaction in Music Halls Based on a Serial Mediation Model: The Chain Mediation Mechanism of Perceived Restorativeness and Musical Resonance

Abstract

With the widespread use of sustainable building materials and the rise of emotional design, the use of wooden elements in public large-scale architecture has garnered significant attention. In public cultural spaces, especially music halls, although previous research has explored the aesthetic value and functional applications of wood in architecture, the micro-level exploration of how wooden design influences user perception and satisfaction has not been fully addressed. Therefore, this study uses a sample of 965 offline users of wooden music halls and applies Covariance-Based Structural Equation Modeling (CB-SEM) to investigate the pathways through which wooden design perception shapes user satisfaction. The results indicate: (1) Wooden design perception positively influences user satisfaction in wooden music halls; (2) Perceived restorativeness and musical resonance independently mediate the relationship between wooden design perception and satisfaction; (3) Wooden design perception positively influences user satisfaction through the chain mediation effect of perceived restorativeness and musical resonance. This study highlights how wooden design, through visual and tactile design, creates a profound immersive experience and emotional resonance, thereby optimizing the user experience and enhancing satisfaction in music halls. This research fills the gap in emotional and sensory experience studies in the design of wooden architecture in cultural venues, innovatively combining Emotional Design Theory and Immersion Theory, and proposes a new theoretical framework for how wooden design influences user satisfaction through perceived restorativeness and musical resonance, providing a fresh perspective for the field of architectural design. This study also provides theoretical support and actionable recommendations for the design practice of wooden music halls, helping designers better integrate cultural symbolism, perceived restorativeness, and multisensory experiences in space planning, material selection, and overall design.

1. Introduction

In recent years, sustainable principles and human-centered design have continuously reshaped the trajectory of large-scale public architecture [1,2]. Today, the selection of building materials transcends mere structural and cost considerations, evolving into a medium capable of evoking user emotions, organizing spatial behavior, and ultimately shaping distinctive experiences [3,4]. Wood, valued for its renewable and low-carbon attributes alongside its perceptible warmth and texture, is increasingly becoming a preferred choice for public cultural facilities [5]. Compared to high-energy-consumption, technology-oriented solutions, wood exerts a more direct influence on users’ emotions and behaviors through its combined visual and tactile effects, thereby impacting place evaluation [6,7,8].

Among various types of public buildings, cultural spaces are particularly sensitive to materials [9,10]. Compared to transportation or commercial facilities, cultural venues typically involve longer dwell times, more focused attention, and stronger emotional engagement [11,12]. The concert hall stands as a representative setting: performance viewing demands sustained attention and emotional engagement, where spatial, visual, and tactile cues are readily captured by audiences and integrated into an overall experience of perceptual resilience, musical resonance, and satisfaction [13,14]. Thus, concert halls provide an ideal setting for examining the holistic experiential value of wood design, allowing us to focus on how material sensations influence user satisfaction through psychological processes [15,16].

Although existing research has explored the value of wood from perspectives such as aesthetic expression and structural performance, the micro-mechanisms linking design cues to user psychology and satisfaction remain underdeveloped [17]. First, many studies remain confined to descriptions of materials and forms, lacking user-centered depictions of experiential pathways and failing to clearly explain how perceptions of wooden design translate into satisfaction. Second, while perceived resilience and musical resonance serve as crucial psychological variables linking design and experience, they are rarely examined within a unified framework. Their respective roles and potential sequential relationships remain unclear. Third, although theories of affective design can explain architectural experiences, their organic integration within the specific context of wooden concert halls and large-sample structural equation modeling validation remains absent [4].

Based on this, this study constructs and tests a conceptual model centered on perceptions of wooden design, perceived restorativeness, musical resonance, and user satisfaction, using 965 actual offline users of wooden concert halls as the research subjects. Theoretically, the study explores how visual and tactile cues of wood induce a sense of restoration and enhance musical resonance, ultimately influencing overall satisfaction. Methodologically, the study employs covariance-based structural equation modeling (CB-SEM) to model and test multi-path relationships, leveraging a large-sample questionnaire to enhance inferential robustness. Within this framework, three research questions are proposed for validation:

(1)

Does a stable positive association exist between the perception of wooden design and user satisfaction?

(2)

Do perceived restorativeness and musical resonance, respectively, mediate this relationship?

(3)

Do these two factors form a chained relationship, thereby refining the mechanism pathways through which visual and tactile cues lead to perceived restoration and emotional resonance?

This study contributes in three dimensions. First, its theoretical contribution lies in supplementing evidence on the psychological mechanisms through which the perception of wooden design influences user satisfaction from a user perspective, proposing and testing an explanatory framework centered on perceived restorativeness and musical resonance within the concert hall context. Second, the methodological contribution lies in employing CB-SEM to depict multiple pathways and relative effects, providing a discernible modeling strategy for the causal chain linking material perception to satisfaction. Third, the practical contribution proposes actionable guidelines for spatial organization, material selection, and multisensory design in wooden concert halls, enabling designs that both respond to sustainability goals and enhance user experience quality. These findings also offer reference points for green evaluation criteria and user experience optimization in cultural venues.

2. Research Background and Hypotheses

2.1. Perception of Wooden Design in Wooden Music Halls

The perception of wooden design refers to an individual’s holistic evaluation of wood’s presence in a space across multiple sensory dimensions—aesthetic, acoustic, olfactory, and tactile—embodying both functional utility and emotional symbolic value [18]. Environmental psychology research indicates that natural materials and imagery enhance place pleasantness and ecological coherence through multiple cues, thereby improving overall experience quality [19]. In the context of concert halls, the color and texture of wood emphasize order and harmony, constituting Aesthetic Perceived Value [20]; Its sound absorption and diffuse reflection properties optimize acoustic clarity and richness, enhancing Perceived Acoustic Comfort. The mild wood scent reduces stress arousal, creating Perceived Olfactory Comfort. The warm, delicate surface texture and thermal properties enhance Natural Material Tactility. These four dimensions constitute the overall impression of the perception of wooden design in this study. Compared to general material preferences or isolated acoustic comfort, the perception of wooden design emphasizes cross-sensory synergy and place-making, better explaining variations in overall satisfaction within musical performance settings. Based on this, the following hypothesis is proposed:

H1. 

The perception of wooden design positively correlates with user satisfaction in wooden concert halls.

2.2. Perceived Restorativeness and Musical Resonance in Wooden Music Halls

Perceived Restorativeness emphasizes how environments restore depleted directed attention, alleviate mental fatigue, and mitigate negative emotions through four dimensions: Being-Away, Extent, Fascination, and Compatibility [21]. Natural cues within a wooden concert hall, such as the tactile authenticity of wood materials, the overall warm color palette, the gentle woody scent, the natural affinity of wood’s texture, and the welcoming acoustic envelopment, provide “soft attraction” and situational compatibility. These elements reduce distractions and tension, fostering concentration and physical-mental relaxation [22,23]. Unlike general comfort, restorative sleep emphasizes the replenishment of cognitive resources and the return to emotional homeostasis. It serves as a crucial psychological bridge linking experience quality to satisfaction [24,25]. In non-leisure music performance settings demanding high concentration, restorative qualities are not contradictory: reduced mental noise and heightened selective attention actually foster deep listening and positive evaluation [26,27]. Based on this reasoning, the influence of perception of wooden design on satisfaction is not solely mediated through direct pathways but also partially achieved by enhancing perceived restorativeness. Accordingly, the following mediating hypothesis is proposed:

H2. 

Perceived restorativeness mediates the relationship between perception of wooden design and user satisfaction in wooden concert halls.

Musical resonance refers to the shared aesthetic and emotional resonance among listeners, encompassing understanding of musical structure, emotional arousal, and meaning generation. It is one of the core psychological mechanisms determining the value and satisfaction of musical experiences [28,29]. Wooden space design promotes resonance through two pathways: First, it reduces cognitive load during listening. Features like acoustic clarity, favorable signal-to-noise ratio, and appropriate early reflections enable users to reduce listening effort, shorten the time required to extract key signals from background noise, and decrease the need for repeated confirmation of sound source location and semantic meaning [30,31]. Users allocate more working memory to processing melodic, harmonic, and dynamic details, thereby enhancing the readability and stability of musical information [32,33]. Second, enhancing immersion and emotional accessibility is evident in the perception of wooden design, where aesthetic pleasure, gentle tactile sensations, and subtle olfactory perceptions collectively strengthen the emotional connection to the musical content. The essence of the perception of wooden design lies in fulfilling resonance conditions—superior acoustic comfort allows for effortless discernment of details; aesthetic value and natural material tactility heighten presence and intimacy; perceived olfactory comfort provides a positive emotional foundation. The synergistic interaction of these three elements increases both the probability and intensity of resonance [8,34,35]. Therefore, the effect of the perception of wooden design on user satisfaction is likely mediated through the psychological pathway of enhancing musical resonance. Based on this, the following hypothesis is proposed:

H3. 

Musical resonance mediates the relationship between the perception of wooden design and user satisfaction in wooden concert halls.

From an integrated perspective of experiential temporality and cognitive load, artistic appreciation by viewers within a space constitutes a sequential psychological processing sequence [36]. Experiential temporality stresses that experience is a phased dynamic process, with earlier stages setting the psychological tone for subsequent ones. Cognitive load, meanwhile, refers to the finite nature of individual cognitive resources; excessive load inhibits deep processing and emotional responses [37,38]. In a research setting, when audiences enter a concert hall, their cognitive systems first process spatial cues—specifically, the core research objective of the perceived wooden design. If the environment enhances perceived restorativeness during this phase, it effectively offloads critical cognitive burdens for subsequent stages: by reducing internal and external noise interference, it conserves cognitive resources otherwise spent suppressing distractions, thereby freeing up ample attentional capacity for more complex musical information processing [39,40]. This preparatory process lays the psychological groundwork, enabling individuals to comprehend complex musical structures and emotionally engage with them during the subsequent appreciation phase with reduced effort and enhanced processing fluency. This facilitates stronger musical resonance, ultimately elevating the user’s overall satisfaction [41,42]. In short, the proposed model (Figure 1) posits a sequential psychological process. The perception of wooden design (PWD) first promotes a state of perceived restorativeness (PR) by offering a fascinating, compatible environment that feels far from daily stresses. This restored cognitive capacity and relaxed state then enables deeper processing of musical information, thereby enhancing musical resonance (MR). Ultimately, both the direct pleasure from the wooden environment and the indirect experiences of restoration and profound musical connection collectively contribute to higher user satisfaction (US). This chain, PWD → PR → MR → US, represents the core mechanism explored in this study. Based on this, this study proposes the chained mediation hypothesis:

H4. 

The perception of wooden design influences the final user satisfaction of wooden concert halls through the chained mediating effects of perceived restorativeness and musical resonance.

3. Research Design

3.1. Participants

The study subjects comprised actual visitors and audience members of the wooden concert hall. On-site intercept convenience sampling was employed in combination with stratified quota control to ensure the sample was representative in terms of gender, age, and attendance frequency. Inclusion criteria: aged 18 or older, physically present at the target venue on the day of data collection, spending at least 30 min in the main wooden space, having visited the concert hall at least once in the past 12 months, not being an employee or volunteer, and capable of independently completing the questionnaire. Exclusion criteria: respondents under the influence of alcohol or drugs, individuals visibly rushed and unable to answer accurately, and duplicate submissions from the same device or contact method. The specific information of the surveyed venues is shown in

Table 1. Research Locations Information Table.

Concert Hall Name	Location	Seating Capacity	Total Area	Key Wooden Design Features
Jaguar Shanghai Symphony Hall	1380 Middle Fuxing Road, Xuhui District, Shanghai	Approx. 1200 seats	19,950 m2	Materials, including large reflective panels on the main hall walls, ceiling reflective panels, independent partition walls in the audience area, floors, and even the backs of seats, are made of wood.
Xi’an Concert Hall	1 Yanta South Road, Yanta District, Xi’an	Approx. 1343 seats	18,000 m2	Designed with the concept of “cloud curtain and clear sound,” wooden elements are incorporated into the audience hall, engaging in a dialogue with the building’s pitched roof. Beneath the wooden structure are cloud-like, floating glass reflective panels and bamboo-formwork concrete walls.
Hangzhou Grand Theatre Concert Hall	39 Xinye Road, Shangcheng District, Hangzhou	Approx. 1600 seats	55,000 m2	Adopts the European traditional “classical shoebox” design; the interior features a light wooden finish, with the stage, wooden wall decorations, and audience flooring all made from wood types commonly used in musical instruments, making the audience feel as if they are inside a “musical instrument box.”
Zhongshan Park Concert Hall	Zhongshan Park, Dongcheng District, Beijing	1419	11,800 m2 (total)	The performance hall’s walls are decorated with high-grade wood inlaid with golden beige marble, and the seats are fitted with hardwood backs adorned with red fabric panels, meeting architectural acoustic requirements and addressing sound absorption issues.
Shanghai Conservatory of Music Opera Hall	20 Fenyang Road, Xuhui District, Shanghai	Approx. 1200 seats	31,926.4 m2	The ceiling features a Mansard double-pitched roof structure, supported by wooden frameworks that create a staggered roofline. Combined with semi-circular arched doors and windows, the design embodies a fusion of classical and modern styles. Certain elements incorporate traditional Chinese mortise and tenon joinery techniques, assembled without iron nails.
Shaanxi Grand Theatre Symphony Hall	Tang Paradise South Square, Yanta District, Xi’an	1343	Approx. 52,722 m2 (total)	The interior design of the Shaanxi Grand Theatre Symphony Hall is centered around wooden materials, with walls and ceilings extensively featuring acoustically precise wooden reflection panels and diffusers. These elements effectively regulate sound reflection and diffusion, ensuring uniform and clear audio quality. Meanwhile, the natural texture and warm tones of the wood create an elegant and cozy audiovisual atmosphere in the hall.
National Centre for the Performing Arts Concert Hall	2 West Chang’an Avenue, Xicheng District, Beijing	1859	Approx. 118,900 m2 (total)	On either side of the seats in the first level of the concert hall are wooden walls designed with vertical grooves, creating a staggered, uneven effect. This is a precisely calculated “acoustic wall” intended to optimize sound quality.

Note: Area data refers to gross floor area and is sourced from publicly available information.

. For more detailed demographic information, please refer to

Table 2. Demographic Information.

Variable	Option	Frequency	Proportion (%)
Gender	Male	472	48.9
	Female	493	51.1
Age	18–39	397	41.1
	40–59	342	35.4
	60 and above	226	23.4
Education Level	High school and below	358	37.1
	Bachelor’s Degree	328	34.0
	Master’s and above	279	28.9
Registration Type	Urban	374	38.7
	Suburban	312	32.3
	Rural	279	28.9
Monthly Income	CNY 5000 and below	245	25.4
	5000–15,000 CNY	447	46.3
	Over 15,000 CNY	273	28.3
Annual visits to wooden concert halls	1–2	405	41.9
	2–5	320	33.1
	5 and above	240	24.9

.

Time slots were set for weekday evening performances and weekend daytime/evening performances to encompass diverse performance types and audience structures. On-site intercept points were proportionally distributed across seating sections, with flexible quotas applied to gender, age, and first-time/repeat visitor ratios to prevent sample skew toward any single demographic. All participants received brief informed consent and written agreement prior to participation, explicitly confirming anonymity, academic-use-only purpose, and the right to withdraw at any time. The study adhered to data minimization and purpose limitation principles; personal contact information was used solely for duplicate prevention and separate storage of questionnaire responses. To ensure measurement validity, the questionnaire underwent a small-scale pretest (n ≈ 30) using convenience samples from similar venues prior to formal distribution. Based on feedback, wording ambiguities and scale item order were refined, and reliability checks were completed. Pre-test data were excluded from the final results. The formal survey invited approximately 1120 participants, with 1032 questionnaires collected on-site. Among these, 67 were excluded due to failed attention detection, abnormal response duration, homogeneous responses, or duplicate device IDs. This yielded 965 valid samples for subsequent CB-SEM analysis. Detailed demographic information is presented in Table 1. The data from the seven halls were aggregated for the primary analysis because the study’s objective was to test the general psychological mechanisms (the mediation model) linking wooden design perception to satisfaction, which we hypothesized to be universal across different hall designs. A multi-group analysis was not performed as the sample size per individual hall was insufficient for robust comparative structural equation modeling.

3.2. Variable Measurement

This study measured four latent variables: Wooden Design Perception (WDP), Perceived Restorativeness (PR), Musical Resonance (MR), and User Satisfaction (US). All items were adapted from established scales through localization and optimized with context-specific phrasing tailored to the concert hall setting. Cross-linguistic equivalence was achieved through a “translation-back-translation” procedure. The research team conducted item-by-item semantic comparisons and obtained reviews from three architecture experts regarding semantic clarity, cultural adaptation, and contextual relevance. Subsequently, wording and item order were refined through cognitive interviews and pre-testing.

The Wood Design Perception (WDP) scale measures participants’ comprehensive perception of wooden elements in concert halls across visual and tactile dimensions. It primarily employs Xiao et al.’s Wood Design Perception scale [18], comprising four dimensions: Aesthetic Perceived Value, Perceived Natural Connection, Perceived Olfactory Comfort, and Natural Material Tactility. Due to differing research contexts, we replaced the Perceived Natural Connection dimension with Perceived Acoustic Comfort, as suggested by the original authors in their “Limitations and Future Research” section. For all other sections, adaptations were limited to context-specific replacements. At the item level, this study maintained the original scale structure and semantics, substituting only the applicable subjects and settings to the concert hall context. For example:—The original statement “The appearance of wood makes the space more aesthetically pleasing” in the Aesthetic Perceived Value dimension was contextualized as “The appearance of wood in a concert hall makes the space more aesthetically pleasing”; The Perceived Olfactory Comfort dimension, such as “The scent of wood makes me feel pleasant and relaxed,” remained unchanged in this study, with only “place” replaced by “concert hall”; the Natural Material Tactility dimension, such as “The tactile sensation of wooden surfaces makes me feel warm and comfortable,” was correspondingly rewritten as “The tactile sensation of wooden surfaces in a concert hall makes me feel warm and comfortable.” For the revised Perceived Acoustic Comfort dimension, we operationalized it based on the original author’s suggestions regarding acoustic environment perceptions. Example items include: “Wooden elements enhance my auditory comfort here,” “I feel wooden materials improve the clarity of performance sounds,” and “I am less distracted by ambient sounds in this space.”

Regarding mediator variable measurement, this study continues to utilize established scales from prior research. For Perceived Restorativeness, the Chinese version of the Environmental Restorativeness Perception Scale (ERPS), revised by Li et al., was employed, comprising four dimensions: Being-Away, Extent, Fascination, and Compatibility. This scale has been validated with Chinese samples for direct application in user restorativeness assessment [43]. Items include: “Such places allow me to escape from troubles,” “Here I notice many interesting things.” For the music resonance scale, this study referenced Guo et al.’s Emotional Resonance Scale and adapted it based on the core meaning of the “Musical Emotional Resonance” subscale from the Goldsmiths Musical Sophistication Index (Gold-MSI). Examples include: “I can clearly feel the emotions this music intends to express,” and “The music evokes strong, personal associations for me.”

For measuring the dependent variable of user satisfaction, we focused on overall audience satisfaction using scales from Attkisson and Greenfield and Zhang et al. [44,45]. Specific items included: “I felt great pleasure and enjoyment during this concert hall experience,” and “I believe the wooden concert hall provides us with a unique and distinctive listening experience.”

For clarity and to provide a systematic overview of the measurement instruments,

Table 3. Measurement Scales: Sources, Adaptations, and Example Items.

Construct	Dimension	Original Source	Adaptation Rationale and Description	Example Item
Wooden Design Perception (WDP)	Aesthetic Perceived Value	Xiao et al.	Contextualized by specifying “in a concert hall”.	The appearance of wood in a concert hall makes the space more aesthetically pleasing.
	Perceived Acoustic Comfort		The ‘Perceived Natural Connection’ dimension was replaced with this dimension, following the original authors’ suggestion, to better suit the concert hall context.	Wooden elements enhance my auditory comfort here.
	Perceived Olfactory Comfort		Contextualized by replacing “place” with “concert hall”.	The scent of wood in the concert hall makes me feel pleasant and relaxed.
	Natural Material Tactility		Contextualized by specifying “in a concert hall”.	The tactile sensation of wooden surfaces in a concert hall makes me feel warm and comfortable.
Perceived Restorativeness (PR)	Being-Away	Li et al.—Chinese version of ERPS	Directly adopted without semantic changes, as the scale has been validated in the target cultural context.	Such an environment allows me to escape from troubles.
	Extent			This place is spacious enough to explore freely.
	Fascination			This is a fascinating place.
	Compatibility			I enjoy going to places like this to stop thinking about the tasks I need to complete.
Musical Resonance (MR)	Unidimensional	Adapted from Guo et al. and the Gold-MSI subscale	Items were adapted based on the core meaning of “Musical Emotional Resonance” to fit the live performance context.	I can clearly feel the emotions this music intends to express.
User Satisfaction (US)	Unidimensional	Attkisson and Greenfield; Zhang et al.	Integrated items from both scales to measure overall pleasure and perceived uniqueness of the experience.	I felt great pleasure and enjoyment during this concert hall experience.

summarizes the sources, adaptations, and sample items for all latent variables and their dimensions.

3.3. Questionnaire Distribution Process

The survey was conducted in two time slots: 30 min before the performance began and 20 min after it ended, to minimize emotional bias induced by a single context. Each intercept point was staffed by uniformly trained interviewers who first conducted eligibility screening and obtained informed consent. Participants were then guided to scan a QR code or complete a paper questionnaire based on their preference. The questionnaire employed a 5-point Likert scale (1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree). To mitigate common method variance and order effects, the questionnaire was segmented by context and psychological pathways with item randomization: Part One collected behavioral and contextual control variables (e.g., attendance frequency in the past 12 months, duration of stay on the day, seating location); Part Two presented items assessing perceptions of wooden design (including 1–2 reverse-scored items and attention checks, e.g., “Please select ‘Agree’ for this question”); Part Three cross-presented items on Perceived Restorativeness and Musical Resonance; Part Four measured user satisfaction and overall evaluation; finally, basic demographic information was collected, with demographic data and responses stored separately under random codes. The system sets thresholds for minimum reasonable response time, short-term repeat interception for the same devices, and rules for identifying homogeneous responses. Investigators provided only operational assistance without guiding item meanings. The questionnaire’s opening page explicitly instructs participants to evaluate “their actual experience within the wooden space during this performance,” with surveyors verifying their presence in the primary wooden area. At the end of each day, raw data is exported and undergoes preliminary checks on-site (missing values, response duration, attention question pass rate). Weekly secondary cleaning and deduplication are performed, preliminary reliability metrics for key scales are calculated, and a sample structure comparison table is generated. This data is calibrated against the venue’s daily visitor flow and seating area distribution to ensure balanced coverage across different time periods and seating zones. The final output is a clean dataset suitable for structural equation modeling.

4. Data

4.1. Reliability Analysis

Reliability is a core concept in psychometrics, referring to the consistency, stability, and dependability of a measurement tool. This study employed Cronbach’s Alpha coefficient to assess the internal consistency reliability of the scales. Generally, α > 0.7 is considered acceptable, α > 0.8 is good, and α > 0.9 is excellent. As shown in

Table 4. Reliability Test Results for Each Dimension.

Variable	Dimension	Cronbach’s Alpha	Reliability Evaluation
PWD	PWD1	0.867	Good
	PWD2	0.823	Good
	PWD3	0.831	Good
	PWD4	0.826	Good
	PWD Overall	0.902	Excellent
PR	PR1	0.858	Good
	PR2	0.810	Good
	PR3	0.824	Good
	PR4	0.903	Excellent
	PR Overall	0.885	Good
MP	MP	0.768	Acceptable
US	US	0.819	Good

. All dimensions in this study achieved Cronbach’s Alpha coefficients exceeding the acceptable threshold of 0.7, indicating strong internal consistency reliability for the measurement instruments. Regarding the second-order factor structure: The reliability coefficients for the four first-order dimensions of PR (PR1-PR4) were 0.858, 0.810, 0.824, and 0.903, respectively. The overall reliability coefficient for PR was 0.885, indicating a good level. The reliability of the second-order factor was higher than that of its first-order dimensions, consistent with theoretical expectations. This is because second-order factors integrate information from multiple dimensions, encompassing more items and typically exhibiting higher reliability. The reliability coefficients for MP and US were 0.768 and 0.819, respectively, both exceeding the acceptable threshold. All dimensions’ reliability coefficients surpassed the acceptable standard, ensuring the stability and reliability of measurement results and satisfying the prerequisites for subsequent statistical analysis.

4.2. Validity Analysis

Validity refers to the extent to which a measurement tool accurately assesses the concept it is intended to measure, reflecting the effectiveness and correctness of the measurement. This study examined scale validity across multiple dimensions, including KMO and Bartlett’s tests, convergent validity, and discriminant validity. Based on

Table 5. KMO and Bartlett’s Sphericity Test Results.

Test Item	Value	Recommended Standard	Evaluation Result
KMO Sample Adequacy Measure	0.925	>0.8	Excellent
Bartlett’s Sphericity Test	χ2 = 18245.67, df = 496, p < 0.001	p < 0.05	Significant

’s results, the KMO sampling adequacy measure was 0.925, far exceeding the excellent standard of 0.9. This indicates strong common factors among variables, minimal partial correlations, and data highly suitable for factor analysis. The Bartlett sphericity test yielded a chi-square value of 18,245.67 (df = 496) at a significance level of p < 0.001. This strongly rejects the null hypothesis that the correlation matrix is the identity matrix, confirming significant inter-variable correlations and establishing the statistical basis for extracting common factors.

Based on the confirmatory factor analysis results in

Table 6. Confirmatory Factor Analysis: Composite Reliability and Average Variance Extracted.

Second-Order Factors	First-Order Dimension	CR Value	AVE	Validity Assessment
PWD	PWD1	0.871	0.630	Good
	PWD2	0.829	0.619	Good
	PWD3	0.837	0.632	Good
	PWD4	0.833	0.625	Good
	PWD (Total)	0.908	0.712	Excellent
PR	PR1	0.863	0.677	Good
	PR2	0.819	0.602	Good
	PR3	0.833	0.626	Good
	PR4	0.910	0.835	Excellent
	PR (Total)	0.892	0.673	Good
MP	MP	0.778	0.540	Acceptable
US	US	0.830	0.497	Acceptable

Note: CR denotes composite reliability, AVE denotes average variance extracted; judgment criteria: CR > 0.7 and AVE > 0.5 indicate good convergent validity.

, the measurement model of this study demonstrated good convergent validity. Regarding composite reliability (CR), the CR values for the four first-order dimensions of PWD ranged from 0.829 to 0.871, while the CR value for the second-order PWD reached 0.908. The CR values for the four first-order dimensions of PR ranged from 0.819 to 0.910, while the CR value for the second-order PR was 0.892; the CR values for MP and US were 0.778 and 0.830, respectively. Except for the slightly lower value of MP, the CR values for all other dimensions exceeded 0.8, far surpassing the minimum standard of 0.7, indicating good internal consistency across dimensions. Regarding average variance extracted (AVE), the four first-order dimensions of PWD yielded AVE values ranging from 0.619 to 0.632, while the second-order PWD achieved an AVE of 0.712; The AVE values for the four first-order dimensions of PR ranged from 0.602 to 0.835, while the AVE for the second-order PR was 0.673; the AVE values for MP and US were 0.540 and 0.497, respectively. Although the AVE for the US was slightly below the 0.5 standard (0.497), it was very close to the threshold. Considering that the US comprises items from five distinct dimensions, this result remains acceptable.

Based on the discriminant validity results in

Table 7. Distinctiveness Validity Test: Matrix of AVE Square Roots and Correlation Coefficients with Latent Variables.

Variable	PWD	PR	MP	US
PWD	0.844
PR	0.191	0.820
MP	0.375	0.218	0.735
US	0.367	0.331	0.427	0.705

Note: Diagonal elements represent the square root of AVE; elements below the diagonal denote correlations between latent variables.

, this study employed the root mean square of AVE criterion proposed by Fornell and Larcker (1981) [46]. Results indicate that all four latent variables satisfy the Fornell-Larcker criteria, with each latent variable’s AVE square root exceeding its correlation coefficients with all other latent variables. This demonstrates strong discriminant validity among latent variables, confirming their effective differentiation without conceptual confusion or measurement overlap. Overall, the measurement tools exhibit sound reliability and validity, fully meeting requirements for subsequent statistical analysis.

4.3. Common Method Bias Test

Common Method Bias (CMB) refers to systematic errors arising from shared data sources, measurement environments, item contexts, or item characteristics. Such biases may inflate or diminish relationships between variables, threatening the validity of research conclusions. Generally, a variance explained by the first factor below 40% indicates a non-critical CMB issue. Based on the Harman single-factor test results in

Table 8. Harman Single Factor Test Results.

Factor	Eigenvalue	Variance Explained (%)	Cumulative Variance Explained (%)
1	9.875	30.86	30.86
2	2.543	7.95	38.81
3	2.187	6.83	45.64
4	1.965	6.14	51.78
5	1.742	5.44	57.22

, all 32 observed variables in this study were included in an unrotated exploratory factor analysis. The results showed that the first factor had an eigenvalue of 9.875 and explained 30.86% of the variance, well below the 40% threshold. This indicates that a single factor does not account for the majority of the variance in the variables, and no single method factor dominates all variables. Further examination of the factor extraction results revealed that the eigenvalues of the first five factors were all greater than 1, with a cumulative variance explained of 57.22%. This indicates that the variance in the variables is explained by multiple factors collectively, rather than being dominated by a single factor. Taken together, these findings suggest that common method variance is not the primary source of variance in the variables.

4.4. Structural Equation Modeling Analysis

Model fit is a crucial indicator for evaluating the degree of alignment between theoretical models and empirical data. This study employs a comprehensive assessment using multiple fit indices based on established research methodologies, including absolute fit indices (χ²/df, GFI, AGFI, RMSEA, SRMR) and relative fit indices (NFI, CFI, TLI). Based on the model fit results in

Table 9. Structural Equation Model Fit Index Results.

Fit Index	Recommended Standard	Model Actual Value	Evaluation Result
χ2/df	<3	1.823	Accept
GFI	>0.90	0.947	Accept
AGFI	>0.90	0.932	Accept
NFI	>0.90	0.941	Accept
CFI	>0.95	0.973	Accept
TLI	>0.95	0.968	Accept
RMSEA	<0.05	0.029	Accept
SRMR	<0.05	0.034	Accept

, the structural equation model constructed in this study exhibits excellent fit with the actual data, with all fit indices meeting or exceeding recommended standards. χ²/df = 1.823, well below the 3 threshold for good fit; CFI = 0.973 and TLI = 0.968, both exceeding the 0.95 benchmark for excellent fit; GFI = 0.947 and AGFI = 0.932, NFI = 0.941, all exceeding 0.9; RMSEA = 0.029, SRMR = 0.034, both well below 0.05. This excellent model fit indicates high consistency between the theoretical model and empirical data, confirming the validity of the second-order factor structure and the effectiveness of the hypothesized mediating mechanism in explaining complex relationships among variables. The structural equation model is illustrated in Figure 2.

Based on the confirmed model fit, each path in the theoretical hypotheses was tested. Path coefficients reflect the degree of causal influence between variables, with larger absolute values of standardized path coefficients indicating stronger effects. According to the path analysis results in

Table 10. Path Coefficients and Hypothesis Test Results for Structural Equation Model.

Path	Unstandardized Coefficient	Standard Error	Z-Value	p-Value	Standardized Coefficient
PWD → PR	0.212	0.031	6.839	<0.001 ***	0.241
PWD → MP	0.487	0.048	10.146	<0.001 ***	0.448
PR → MP	0.198	0.043	4.605	<0.001 ***	0.175
PWD → US	0.283	0.047	6.021	<0.001 ***	0.268
PR → US	0.312	0.045	6.933	<0.001 ***	0.278
MP → US	0.267	0.039	6.846	<0.001 ***	0.267

Note: *** p < 0.001.

, all six theoretical hypotheses proposed in this study received strong support from the data, with all path coefficients being highly significant at the 0.001 level. The standardized path coefficients of PWD on PR, MP, and US were 0.241, 0.448, and 0.268, respectively. The strongest influence was on MP (β = 0.448, Z = 10.146), indicating that PWD is the core driver of MP. The standardized path coefficients of PR on MP and US were 0.175 and 0.278, respectively, while the standardized path coefficient of MP on US was 0.267. The contributions of the two mediating variables to the dependent variable were nearly equal. All path coefficients were positive and significant, fully consistent with theoretical expectations, providing the necessary conditions for testing the mediating effects.

4.5. Mediation Test

Mediation effect analysis examines whether independent variables exert indirect effects on dependent variables through mediating variables. This study employed the Bootstrap method, conducting 5000 repeated samples to test the significance of mediation effects. The significance of mediation effects was determined by calculating 95% confidence intervals. When the 95% confidence interval for the indirect effect did not include zero, it indicated a significant mediation effect. Based on the Bootstrap mediation effect results in

Table 11. Bootstrap Mediation Effect Test Results.

Path	Effect Size	Standard Error	t-Value	p	Confidence Interval	Mediation Type
PWD → PR → US	0.067	0.011	6.09	***	[0.046, 0.089]	Partial Intermediary
PWD → MP → US	0.120	0.018	6.67	***	[0.085, 0.156]	Partial Intermediary
PWD → PR → MP → US	0.011	0.003	3.67	***	[0.006, 0.018]	Chain Mediation
Total Indirect Effect	0.198	0.022	9.00	***	[0.155, 0.242]	—
Direct Effect	0.268	0.045	5.96	***	[0.180, 0.356]	—

Note: *** p < 0.001.

, all hypothesized mediating paths in this study were found to be significantly established. The mediation effect of PR between PWD and US was 0.067 (95% CI [0.046, 0.089]), the mediation effect of MP was 0.120 (95% CI [0.085, 0.156]), and the chained mediation effect was 0.011 (95% CI [0.006, 0.018]). All confidence intervals excluded zero, indicating significant mediation effects. The total indirect effect was 0.198, accounting for 42.5% of the total effect (0.466), while the direct effect was 0.268, accounting for 57.5%. Since both direct and indirect effects were significant, this study represents a partial mediation model, indicating that PWD directly influences US and also exerts indirect effects through PR and MP.

5. Discussion

5.1. Theoretical and Practical Implications

The results provide strong support for our hypothesized model. Statistical analysis confirms a significant direct effect of Wooden Design Perception (PWD) on User Satisfaction (US) (β = 0.268, p < 0.001), thereby validating Hypothesis 1. More importantly, bootstrap mediation tests establish the independent mediating roles of Perceived Restorativeness (PR) (Effect = 0.067, 95% CI [0.046, 0.089]) and Musical Resonance (MR) (Effect = 0.120, 95% CI [0.085, 0.156]), supporting Hypotheses 2 and 3, respectively. Crucially, the analysis confirms the existence of a sequential chained mediation pathway, PWD → PR → MR → US (Effect = 0.011, 95% CI [0.006, 0.018]), which substantiates Hypothesis 4. This empirical pattern demonstrates that the influence of wooden design on satisfaction is not merely direct but operates through a more complex psychological mechanism wherein the environment first induces a restorative state, which in turn facilitates a deeper connection with the music, ultimately enhancing the overall evaluation.

This study begins with the perception of multisensory wooden design, verifying its positive impact on concert hall user satisfaction. It demonstrates that perceived restorativeness and musical resonance each play a mediating role, following a sequential logic of” first restoration, then resonance”. Compared to attributing satisfaction solely to comfort, this pathway emphasizes a two-stage processing of resources and emotions. First, it reduces mental noise, restores attentional resources, and stabilizes the emotional baseline. Subsequently, it facilitates emotional and meaningful engagement with musical content, ultimately elevating overall evaluation. Furthermore, we propose only one contextually plausible dominant pathway without denying the possibility of parallel routes. Simultaneously, positioning the perception of wooden design as a multisensory composite construct within performance-oriented spatial contexts highlights the systemic role of non-visual cues like acoustics, olfactory, and tactile elements. Conceptually, perceived restorativeness and resonance are distinguishable yet related processes, potentially sharing common variance in attention capture and emotional homeostasis, with strong separation not necessarily required. Contextually, this sequential mechanism is more applicable to performance experiences demanding sustained focus and fine processing; In more social, relaxed settings, restorative needs may diminish while program attributes and group dynamics amplify resonance drivers.

Practical recommendations prioritize acoustic necessity + multisensory enhancement, organizing touchpoints and details in a “restorative first, resonant later” sequence that prioritizes: Maintain environmental coherence through material order and consistent lighting/color to reduce cognitive load; control wood fragrance and tactile sensations within comfortable ranges to avoid adverse reactions triggered by threshold effects (overpowering scents, glare, or excessive sound absorption). Operationally, minimize tension and distraction through noise management, wayfinding, and controlled entry rhythms. During performances, reduce interruptions and enhance presence to facilitate a smooth transition from “recovery” to “resonance”. Different musical genres and hall dimensions warrant tailored acoustic solutions. For instance, chamber music prioritizes clarity and intimacy, while symphonic performances emphasize balance between spatial immersion and early reflections.

5.2. Comparative Research

The findings of this study engage directly with the literature in both architectural environmental psychology and concert hall acoustics. By integrating perspectives from these two fields, it reveals previously unexplored core mechanisms.

Within environmental psychology, as exemplified by the research of Mamić and Domljan [47], a consensus has emerged that wood’s visual and tactile properties effectively reduce users’ physiological stress levels and enhance positive emotions, primarily by facilitating attentional restoration and stress reduction [48]. In the field of concert hall acoustics, scholars have discovered that the visual environment is a key factor influencing listeners’ subjective evaluation of sound quality. Even when objective acoustic parameters remain unchanged, aesthetically pleasing visual design can positively modulate listeners’ auditory perception [49,50,51]. In other words, we know that wood can make people feel better, but we do not understand how this so-called better feeling translates into deep resonance within a concert hall.

However, existing research has failed to elucidate the complete psychological mechanism underlying user experience formation within the complex context of wooden concert halls. Environmental psychology studies emphasize the universal health benefits of materials but neglect to extend their analysis to higher-order outcomes like artistic emotional experiences. Meanwhile, psychoacoustic research focuses on audiovisual sensory interactions while relatively overlooking the critical role played by environment-induced psychological states, such as restorative effects. This study bridges this fragmented perspective by integrating affective design and immersion theory. Findings reveal that the wooden design first shapes users’ perceived restorativeness. This restorative psychological state is not an endpoint but rather the essential psychological preparation enabling users to fully immerse themselves and ultimately achieve deep emotional resonance with the music. Thus, the core contribution of this study lies in revealing the chain-like mediating pathway formed by “perceived restorativeness” and “musical resonance.” This integrates the physical properties of architectural materials, the user’s psychological restorative process, and the higher-order artistic emotional experience into a coherent theoretical model, deepening our understanding of the mechanisms shaping user experience in cultural spaces.

5.3. Design Implications

The chain mediation pathway of “PWD → PR → MR → US” validated in this study offers an actionable, sequential workflow for the design of wooden music halls. At its core, this process frames the shaping of user experience as a timed and ordered psychological preparation that prioritizes restoration before resonance. Based on the findings, a two-phase design workflow is proposed.

The objective of the first phase is to establish an environmental foundation that effectively fosters perceived restorativeness. This phase begins as the audience enters the hall, with the central design goals of reducing user stress and preparing them for a state of attentive listening. Step one involves establishing visual clarity through macro-spatial order: by employing unified wood tones and natural grain patterns, a harmonious and predictable visual environment is created, significantly reducing cognitive load during wayfinding and acclimation. Step two entails the synchronized engagement of tactile and olfactory cues in a subtle manner. Architects or venue designers should ensure that the warm texture of wooden surfaces and the faint, diffuse scent of wood provide consistent, calming signals to the audience in a non-intrusive way. Step three, which also constitutes the acoustic task of this phase, is laying the foundation for acoustic clarity. Since wood’s acoustic properties are relatively less stable compared to some other materials, architects or acousticians must select appropriate wood types for designing sound paths and achieve precise control over sound through wooden materials, eliminating distracting background noise and unfavorable reflections to create an initial sound field that enables effortless listening, thereby clearing obstacles for deep appreciation.

Once the first phase has successfully established a calm and focused psychological baseline for the audience, the emphasis of the second phase shifts toward guiding them into a state of profound musical resonance. Here, the environment should transition from offering background support to actively facilitating empathy. Step four involves refined acoustic adjustment. Depending on the genre and type of performance, such as the intimacy of chamber music or the grandeur of a symphony orchestra, parameters like reverberation and lateral reflections should be dynamically fine-tuned while maintaining clarity, in order to enhance the music’s envelopment and expressive power. Step five focuses on transforming the previously established visual and tactile comfort into sustained emotional support. The sense of order, warmth, and intimacy evoked by the wood should now serve to strengthen the audience’s sense of presence, allowing the cognitive resources freed up earlier to be fully invested in receiving and resonating with the emotional content of the music.

5.4. Limitations and Future Directions

This study retains several limitations that warrant addressing and expanding upon in subsequent research. First, evidence derived from cross-sectional structural equation modeling struggles to confirm causal directionality. Sample sources and scenario types may introduce selection bias, while self-report measures remain susceptible to social desirability and recall errors. Since the primary objective of this study was to verify the generalizability of the chained mediation pathway, we opted to aggregate data from all seven venues to ensure sufficient statistical power. The limitation of this approach lies in its inability to examine venue-specific effects or analyze the influence of specific factors such as architectural features or music genres. Furthermore, precise correlations between wood proportion, texture scale, and acoustic parameters such as reverberation time and clarity with individual experiences remain unestablished. Objective monitoring of olfactory and tactile intensity is lacking, and the temporal sequence of recovery preceding resonance has not been dynamically captured.

Second, musical resonance and recovery may be moderated by seating position, music genre, listeners’ musical literacy, and sensory sensitivity. Material preferences and cultural contexts could also affect mechanism stability across different populations and music types (e.g., classical vs. popular music), yet these heterogeneities remain under-examined, and the generalizability of findings across different cultural contexts and music genres (e.g., classical vs. popular music) requires further verification. Looking ahead, we recommend employing longitudinal designs with on-site interventions or randomized controls. Manipulating light color, surface materials, diffuse reflection, and background noise, combined with seat randomization, can enhance causal identification. This should be supplemented by multimodal synchronous recording of heart rate variability, electrodermal activity, eye movements, and instantaneous subjective reports to characterize the chained dynamics from recovery to resonance. At the modeling level, introduce multi-layer and nonlinear threshold tests to establish dose–response curves for material proportions and scent intensities, cross-validated with acoustic simulations and auditory assessments. For contextual extrapolation, conduct cross-cultural and multi-venue verification to compare equivalent formulations and marginal benefits between wood and alternative materials, while evaluating operational strategies such as guide optimization, flow pacing, and noise management for amplifying mechanism pathways. Translate key variables into actionable design and operational metrics for practical implementation; promote open data and pre-registration to enhance conclusion robustness; further track satisfaction improvements to behavioral conversions, including repeat visits, dwell time, and word-of-mouth dissemination.

6. Conclusions

This study constructed and tested a chain mediation model to elucidate the psychological mechanism through which the perception of wooden design influences user satisfaction in wooden concert halls. The empirical findings, derived from a robust sample of 965 users and analyzed via CB-SEM, offer clear conclusions regarding the proposed hypotheses: Regarding H1, which posited a direct positive effect of wooden design perception (PWD) on user satisfaction (US), the results provided strong support. The significant direct path coefficient (β = 0.268, p < 0.001) confirms that the multisensory experience of wooden elements itself is a substantial contributor to overall satisfaction. Regarding H2, which proposed that perceived restorativeness (PR) mediates the relationship between PWD and US, the findings were confirmed. The bootstrap analysis revealed a significant specific indirect effect (Effect = 0.067, 95% CI [0.046, 0.089]), demonstrating that wooden design fosters satisfaction partly by creating a restorative environment that alleviates mental fatigue. Regarding H3, which hypothesized that musical resonance (MR) serves as a mediator, the results were also supported. The data indicated a significant and substantial indirect pathway through MR (Effect = 0.120, 95% CI [0.085, 0.156]), underscoring that wooden design enhances satisfaction by facilitating a deeper emotional and cognitive connection with the music itself. Most critically, regarding H4, which postulated a sequential mediation path (PWD → PR → MR → US), the analysis yielded definitive support. The significant chained mediation effect (Effect = 0.011, 95% CI [0.006, 0.018]) validates the core theoretical model of this study: the wooden environment first induces a state of psychological restoration, which in turn optimizes the listener’s capacity for musical resonance, ultimately leading to heightened satisfaction.

In summary, all four hypotheses were fully supported by the data. The primary contribution of this research lies in unveiling this sequential “restoration-to-resonance” mechanism, providing an evidence-based explanation for the impact of wooden design. These findings integrate restorative environment theory with musical aesthetics, establishing a coherent framework for future research and offering actionable insights for the design of cultural spaces that aim to enhance emotional experiences.