Sustainable Urban Landscape Quality: A User-Perception Framework for Public Space Assessment and Development

Abstract

With rapid urbanization, enhancing the quality of public spaces is critical to residents’ well-being and sustainable urban development. However, user perceptions of these spaces remain insufficiently quantified. This study introduces a perception-based evaluation framework encompassing four dimensions: service, spatial, cultural, and aesthetic. A three-dimensional importance-performance analysis (3-D IPA) model is applied to assess two multifunctional public spaces in Wuhan—the Citizens’ Home (CH) and the Creative World Industrial Park (CWIP)—with the aim of identifying user-prioritized attributes that inform sustainable design interventions. The findings reveal the following: (1) At CH, spatial perception (importance = 3.93; performance = 4.02) received the highest ratings, particularly for openness and ecological pavement, highlighting areas for green infrastructure improvement. (2) At CWIP, cultural perception (importance = 3.75; performance = 3.73) dominated, with a need to enhance the signage systems and cultural integration for greater place identity. (3) Optimization priorities included energy-efficient lighting, entrance enhancements, and recreational layout improvements at CH, and thematic diversity and wayfinding systems at CWIP. (4) The 3-D IPA framework effectively identifies user-perceived priorities and supports experience-driven, resource-conscious spatial improvements. This study provides a user-centered, data-informed approach for evaluating and optimizing urban public spaces, offering practical strategies to align spatial quality with long-term sustainability goals.

1. Introduction

In the context of rapid urbanization, optimizing the landscape environment of urban public spaces has become crucial for improving the quality of life for urban residents. Landscape environments not only facilitate daily activities and promote physical and mental well-being but also contribute to the ecological and aesthetic value of cities [1]. However, in many cases, the landscape design of urban public spaces still fails to adequately address users’ diverse and evolving needs. Therefore, there is a growing recognition that a user-centered, bottom-up strategy is more effective than traditional top-down strategies in responding to these expectations [2,3]. In this context, understanding how users perceive public space environments—including their comfort, safety, attractiveness, and functionality—has become a critical foundation for scientific evaluation and design optimization.

1.1. Construction of Perception Evaluation System for Public Spaces

With the accelerating pace of urbanization, the landscape environment of public spaces has become increasingly crucial in enhancing the livability and sustainability of cities. In recent years, scholars have explored various dimensions of how to effectively assess the landscape quality of urban public spaces through user perception. Perceptual characteristics such as environmental comfort, restorative potential, safety, quietness, spatial openness, and opportunities for social interaction have been widely acknowledged as essential components that influence public experience and health outcomes [4,5]. The research has indicated that evaluation systems often encompass multiple dimensions, including ecology, health, quality of life, economy, aesthetics, and socio-culture aspects. These frameworks propose evaluation criteria that integrate biodiversity, historical and cultural value, and a sense of security to assess the quality of public green spaces [6,7]. Others have emphasized the psychological needs of users, such as naturalness, relaxation, and sociability [8]. Across these various approaches, there is a general consensus on the central role of user perception in the evaluation framework, especially in diverse and functionally complex urban public spaces.

Similarly, domestic studies have reflected this global trend. The recent research in China has not only considered the physical attributes of space but also incorporated user experience and cultural identity as essential perceptual factors. For instance, studies on urban parks and green spaces have proposed multidimensional frameworks that emphasize users’ perceptual experiences and behavioral responses, contributing to a better understanding of how landscape environments support physical and mental well-being [9,10]. Moreover, elements such as safety, microclimate regulation, and recreational function have emerged as critical indicators in landscape quality assessment [11,12]. These studies provide a valuable theoretical foundation for developing evaluation systems that are more responsive to the actual needs of urban public space users.

Despite the growing number of studies focusing on user perception in public spaces, much of the existing research has concentrated on green parks [13,14,15], linear pedestrian spaces [16,17], or commercial streets [18,19], often in isolation. These studies have yielded important insights into individual perceptual dimensions; they lack a comprehensive evaluation framework capable of addressing more complex spatial typologies—particularly outdoor public spaces adjacent to buildings, which often serve overlapping ecological, social, and recreational functions in high-density urban environments. Moreover, few studies have attempted to bridge the gap between perceptual theory and operational evaluation tools that are suitable for such multifunctional spaces.

To address this gap, it is essential to adopt a perceptual evaluation framework that is both multidimensional and adaptable to spatial complexity. While traditional evaluation tools, such as the IPA and KANO models, have proven effective in service and marketing contexts, their application in urban environmental assessment remains limited and predominantly two-dimensional. Consequently, our study aims to explore the potential of integrating an upgraded, 3-D IPA model to capture a more nuanced relationship between user perception and landscape quality in building-dominated public spaces.

1.2. Upgrading of Landscape Evaluation Models: 2-Dimensional IPA; 3-Dimensional IPA

Two-dimensional evaluation models, such as the IPA model [20,21] and the KANO model [22,23], are commonly used in the field of urban environmental evaluation. These models help urban planners and researchers gain a comprehensive understanding of user needs and satisfaction, providing a scientific foundation for improving urban environments.

The IPA model (see Figure 1a), which stands for importance-performance analysis, is widely utilized in marketing as a tool to assess customer satisfaction with services and prioritize service elements [24]. Its most intuitive representation is the Performance Analysis grid, which consists of four quadrants on two axes, as shown in Figure 1a. The vertical axis represents importance, while the horizontal axis represents performance. Each attribute’s importance and performance ratings are plotted as coordinates, with the average scores of both aspects serving as the origin. Elements are then marked on the coordinate axis to determine which areas require priority promotion.

The KANO model (see Figure 1b), also known as the three-factor theory, was proposed by Japanese scholar Noriaki Kano in 1984. This model, grounded in analyzing the contribution of user demand to satisfaction, classifies user needs into three categories: performance-based demands, basic demands, and attractive (B-type) demands [25], as illustrated in Figure 1b. Performance-based demand factors are those for which improvements in service quality lead to a significant increase in user satisfaction, while a decline in service quality leads to a notable decrease in satisfaction. Basic demand elements, on the other hand, do not significantly alter user satisfaction when optimized; however, their deterioration can greatly reduce satisfaction. Charismatic demand elements represent needs that users do not typically consider in their daily experiences. While a reduction in service quality for these factors does not noticeably affect user satisfaction, their optimization can lead to a significant boost in satisfaction.

Despite the importance of the IPA and KANO models in environmental contexts, their limitations have gradually become evident, particularly when addressing complex, multidimensional environmental issues, The 2-D models appear to be insufficient to comprehensively capture the complex relationship between user needs and environmental quality. As a result, scholars have increasingly turned to more sophisticated 3-D models to overcome the limitations inherent in the 2-D model. Lai and Hitchcock [26] developed a three-dimensional model (3-D IPA model) to enhance the accuracy and depth of service quality evaluation by extending the traditional 2-D importance and performance analysis into a three-dimensional space. A service quality study of a luxury hotel in Macau applied the model and provided guidance for specific service optimization measures. In addition, Chia combined the 3-D IPA model with the KANO model to conduct a three-dimensional spatial analysis of YouBike service attributes and proposed optimization strategies to better meet user needs [27]. Although the 3-D IPA model has been widely used in product and service evaluations, its application in urban environmental assessment remains relatively underexplored, especially in the comprehensive evaluation of multidimensional environmental factors, which is still in its early stages.

The introduction of 3-D models into the study of urban landscape environments offers several advantages. Not only does it allow for a more comprehensive capture of the diversity of user perceptions, but it also improves the precision and applicability of evaluations. By incorporating multidimensional perceptual factors such as physiological perception, psychological needs, and cultural identity, 3-D models can significantly enhance the design and optimization of urban landscapes.

1.3. Purpose of the Study

The primary objective of this study is to uncover the dynamic relationship between user needs and environmental factors across different types of public spaces. To achieve this, this study integrates a constructed perception evaluation index system with the 3-D IPA landscape environment quality measurement model, allowing for a comprehensive assessment of the landscape environment in outdoor public spaces within both centralized and decentralized buildings. Based on the assessment results, this study proposes specific 3-D IPA action strategies and optimization recommendations, the research framework see Figure 2.

In addition, this study highlights the central role of user perception in the design of public spaces, arguing that evaluation methods based on user participation can more accurately capture actual needs. This, in turn, provides a more targeted foundation for decision-making in the design and renovation of these spaces. Through this work, this study aims to offer new theoretical perspectives and methods for the landscape optimization of outdoor public spaces in buildings, while also promoting the advancement and application of landscape environmental quality evaluation systems.

2. Materials and Methods

2.1. Study Area

This study selects the Wuhan Citizens’ Home and the Creative World Industrial Park as representative examples for research on outdoor public spaces in Wuhan. These two cases exemplify two distinct types of urban architectural outdoor public spaces: one is a government-oriented, service-driven outdoor space, while the other is a creative industry-focused outdoor space characterized by cultural creativity and multifunctionality (see Figure 3 and Figure 4 and

Table 1. Two categories of public space profiles.

Research Object	Landscape Environment Type	Land Area	Public Space Area (×103 m2)	Building Footprint (×103 m2)	Proportion of Public Space (%)
Citizens’ Home (CH)	Green Space Sculpture Flower Pond Pool	6.701	5.415	1.286	80.80
Creative World Industrial Park (CWIP)		6.420	4.973	1.475	77.46

).

As a large-scale government service complex, the former serves as a key location for citizens to handle various government affairs. Its outdoor space must accommodate multiple needs, including efficient traffic flow, spatial organization, and areas for citizens to rest, wait, and communicate, while reflecting both human-centric design and public accessibility. In contrast, the Creative World Industrial Park integrates functions such as commerce, culture, and office spaces, serving as an important platform for daily activities and social interactions. Its outdoor space is marked by strong openness, communicative interaction, and a cultural atmosphere.

These two spaces differ significantly in terms of geographical location, target populations, spatial organization, and social functions, making them highly representative and complementary. A comparative study of these two spaces will facilitate a comprehensive understanding of the similarities and differences in landscape quality perception and space optimization across different types of urban outdoor public spaces, providing valuable insights for future design and planning practices.

2.2. Environmental Perception Factor Screening and Questionnaire Design

2.2.1. Environmental Perception Factor Screening

This study adopts a comprehensive approach, combining field observations, a literature review, expert interviews, and surveys to preliminarily select the indicators for evaluating the perception of the landscape environment in urban public building outdoor spaces [28,29].

To further optimize and establish the indicator system, expert judgments based on their practical experience were utilized to score the preliminary evaluation indicators, assessing their impact on landscape perception. A questionnaire (

Table A1. The number of experts evaluating the impact degree of each index of landscape environment perception evaluation.

No.	Evaluation Factor	Influence Degree
		Great Impact	Significant Impact	Moderate Impact	Minor Impact	No Impact
1	Identification system guide	6	20	2	2	0
2	Road guidance	6	18	4	2	0
3	The convenience of travel and transportation options	1	20	6	2	1
4	Attractiveness of entrances and exits	2	5	13	6	4
5	Seasonal variation in richness	2	16	10	1	1
6	The richness of landscape spatial types	4	22	4	0	0
7	Site safety and accessibility	3	15	9	2	1
8	The use of permeable floor paving	4	10	13	1	2
9	Road fluency	7	13	8	2	0
10	The cultural nature of landscape decoration	5	16	4	4	1
11	Promotion of culture and history and science education	18	8	2	2	0
12	Cleanliness of the environment	6	2	0	16	6
13	Distribution and quantity of native plants	11	14	5	0	0
14	The openness of the venue	2	18	5	3	2
15	Artistry of public facilities	10	12	8	0	0
16	Overall style coordination	5	2	0	14	8
17	Plant viewing	7	19	0	4	0
18	Landscape night lighting artistic	5	6	0	10	9
19	The completeness of interactive facilities	2	7	0	15	6
20	Privacy of the space	2	22	3	3	0

) was distributed to 30 individuals, including professors, senior engineers, and graduate students from the fields of architecture and landscape architecture at the Hubei University of Technology.

In the questionnaire design (Appendix B), five impact levels were defined for each evaluation indicator, ranging from 5 to 1 point, representing the degree from “Great Impact” to “Minor Impact”. The arithmetic mean of the scores provided by all experts for a specific indicator was used to represent its impact on the evaluation of the urban public-building outdoor-space landscape environment. The specific calculation methods are outlined in Formulas (1) and (2).

In Formula (1), $S_j$ represents the impact of the j-th indicator on the evaluation of the landscape environment of urban public buildings, $X_{ij}$ is the score given by the i-th expert for the j-th indicator, and n is the number of experts providing scores. Formula (1) is expressed as follows:

$$S_j={\displaystyle \frac{\sum _{i=1}^n{X}_{ij}}{n}}$$

(1)

In Formula (2), variance is used to measure the dispersion of expert ratings, reflecting whether there are significant differences in expert opinions. The specific calculation formula is as follows:

$$R_i={\displaystyle \frac{\sum _{i=1}^n{\left(X_{ij}-S_{ij}\right)}^2}{n}}$$

(2)

where $R_j$ represents the variance in the ratings for the j-th indicator, indicating the consistency or dispersion of the expert scores.

As shown in

Table A2. Evaluation factors and influence degree of perceived landscape environmental quality.

No.	Evaluation Factor	Influence Degree	Sample Variance
1	Identification system guide	4.00	0.552
2	Road guidance	3.93	0.616
3	The convenience of travel and transportation options	3.60	0.662
4	Attractiveness of entrances and exits	3.57	0.668
5	Seasonal variation in richness	3.45	1.254
6	The richness of landscape spatial types	4.00	0.276
7	Site safety and accessibility	3.57	0.806
8	The use of permeable floor paving	3.67	0.557
9	Road fluency	3.83	0.764
10	The cultural nature of landscape decoration	3.47	0.878
11	Promotion of culture and history and science education	4.40	0.800
12	Cleanliness of the environment	2.53	2.051
13	Distribution and quantity of native plants	4.20	0.510
14	The openness of the venue	3.80	0.629
15	Artistry of public facilities	3.51	0.573
16	Overall style coordination	2.97	1.275
17	Plant viewing	3.21	0.484
18	Landscape night lighting artistic	3.77	0.423
19	The completeness of interactive facilities	2.47	1.568
20	Privacy of the space	2.88	2.147

, some indicators exhibit considerable variation in expert ratings. To ensure the uniformity of expert opinions, this study selected indicators with variance values of less than 1, ensuring greater consistency in expert opinions and enhancing the scientific basis of the selected indicators. Additionally, based on the impact value of each indicator, those with an impact value greater than 2 were selected as the main indicators for evaluating the perception of urban public-building outdoor-space landscape environments.

In conclusion, through these two screening methods, the evaluation indicator system for the urban public-building outdoor-space landscape environment was optimized. This process allowed for the selection of representative indicators and the construction of a scientifically ordered and non-redundant indicator system. Furthermore, semantically repetitive or functionally redundant indicators were merged. For instance, the “Ground Decoration” indicator was removed due to its low importance score, while “Entrance Layout” was integrated into the broader indicator “Entrance Attractiveness”.

Ultimately, this study developed an evaluation indicator system for the landscape environment perception of outdoor public spaces in urban buildings, encompassing the four dimensions of service perception, spatial perception, cultural perception, and aesthetic perception. From these four dimensions, 15 factors influencing the evaluation of the landscape environment of outdoor public spaces in urban buildings were identified, providing a user perception measurement scale (

Table 2. Urban-building outdoor public-space landscape environment user perception scale.

Dimensionality	Environmental Perception Dimension	Serial Number	Environmental Perception Factor
Perceived quality	Service perception	a	Identification system guide
		b	Road guidance
		c	The convenience of travel and transportation options
	Spatial perception	d	Attractiveness of entrances and exits
		e	The richness of landscape spatial types
		f	Site safety and accessibility
		g	The use of permeable floor paving
		h	Road fluency
	Cultural perception	i	The cultural nature of landscape decoration
		j	Promotion of culture and history and science education
		k	Distribution and quantity of native plants
		l	The openness of the venue
	Aesthetic perception	m	Artistry of public facilities
		n	Plant viewing
		o	Landscape night lighting artistic

) for subsequent quantitative evaluation and analysis.

2.2.2. Questionnaire Design

The questionnaire (Appendix C and Appendix D) designed in this study is divided into two sections. The first section gathers basic information about the respondents and their use of the outdoor public spaces, including age, gender, occupation, and travel time, mode, and purpose. The second section focuses on the importance and satisfaction of the respondents with the public-space landscape environmental evaluation indicators. The measurement method used the Likert five-point scale to measure the importance of these perceived factors (1 = “very unimportant”, 5 = “very important”) and their satisfaction (1 = “very dissatisfied”, 5 = “very satisfied”). Demographic characteristics of respondents are presented in Appendix E.

2.3. The 3-Dimensional IPA Methodology

In this study, the explicit and implicit importance matrices suggested by Vavra [30] are applied in urban planning, particularly to evaluate and improve designed landscapes (see Figure 5). Explicit importance refers to the needs and preferences explicitly expressed by users, while implicit importance pertains to factors that although not directly articulated by users, potentially affect their satisfaction. By employing both explicit and implicit importance matrices, this study offers a more comprehensive view of how landscape factors influence user satisfaction, providing a theoretical framework and practical recommendations for urban planning.

Based on the Vavra matrix, the 3D IPA method constructs a cube model consisting of 16 regions (see Figure 6). This model classifies the performance of each factor by calculating the weighted average of explicit importance, implicit importance, and actual performance at the intersections of the cube. The actual performance level is categorized as “very low”, “low”, “high”, or “very high”, as detailed in

Table 3. The 3-D IPA resource allocation.

Actual Performance (X)	Implicit Importance (Y)	Explicit Importance (Z)	Three-Factor Theory	Original IPA Approach	Resource Allocation
Very high	High	High	Performance	Keep	Keep
Very high	Low	High	Basic	Keep	Reduce
Very high	High	Low	Excitement	Reduce	Keep
Very high	Low	Low	Performance	Reduce	Reduce
High	High	High	Performance	Keep	Keep
High	Low	High	Basic	Keep	Slightly reduce
High	High	Low	Excitement	Reduce	Low Priority
High	Low	Low	Performance	Reduce	Reduce
Low	High	High	Performance	Improve	Improve
Low	Low	High	Basic	Improve	Low Priority
Low	High	Low	Excitement	Low Priority	Keep/Improve
Low	Low	Low	Performance	Low Priority	Low Priority
Very low	High	High	Performance	Improve	Improve
Very low	Low	High	Basic	Improve	Improve
Very low	High	Low	Excitement	Low Priority	Keep/Significantly improve *
Very low	Low	Low	Performance	Low Priority	Low Priority

Note: * depends on the availability of the resources.

. Based on these analytical results, this study proposes corresponding 3-D IPA action strategies.

For performance-based factors, for those with high explicit and implicit importance, the current performance should be maintained and further optimized to enhance user satisfaction. For the basic factors—those with high explicit importance and low implicit importance—if their performance exceeds expectations, it is recommended to adjust to a reasonable average level to avoid over-optimization. Conversely, if performance is poor, priority should be given to meeting the basic needs of users. Excitatory factors—those with lower explicit importance but higher implicit importance—should be classified as “low priority” but the focus should be on improving performance, particularly if these factors have a high potential to enhance user satisfaction. In cases of limited resources, it is advised that planners prioritize improving the performance of performance-based factors while ensuring a reasonable allocation of resources and selectively investing in the optimization of excitatory factors.

In this study, explicit importance was measured through self-statements, while implicit importance was assessed using relative measures. Following the guidelines of Lai and Hitchcock, factor satisfaction was treated as the independent variable, and overall satisfaction as the dependent variable for analysis. Considering that multiple regression analysis may overemphasize the attributes with large coefficients and underestimate the implicit importance of other attributes, partial correlation analysis was used in this study. Partial correlation analysis can independently evaluate the direct relationship between each perceived factor and overall satisfaction, avoiding the bias that may be brought by multiple regression analysis, and can more accurately quantify the influence of independent variables on dependent variables when dealing with multiple attributes.

2.4. Data Collection

The data for this study were collected using the Questionnaire for Evaluation of Perception of Landscape Environment in Outdoor Public Space of Buildings in Wuhan City, which was surveyed in two time periods using online and offline methods. The first phase of the survey was conducted from May 7 to 27 2024, targeting users who visited or had visited the Wuhan Citizens’ Home (CH). A total of 175 questionnaires were distributed, and 165 valid responses were collected, yielding an effective recovery rate of 94.3%. The second phase of the survey took place from 12 to 22 July 2024, at the Creative World Industrial Park (CWIP). In this phase, 200 questionnaires were distributed, with 175 valid responses recovered, resulting in an effective recovery rate of 87.5%. Overall, this study collected a total of 340 valid questionnaires.

3. Results

3.1. Construct Reliability and Validity

The reliability (

Table A3. Reliability test.

Index	Citizens’ Home (CH)		Creative World Industrial Park (CWIP)
	Cronbach’s Alpha	Number of terms	Cronbach’s Alpha	Number of terms
Explicit importance	0.887	15	0.930	15
Actual performance	0.919	15	0.948	15

) and validity (

Table A4. Validity test.

KMO and Bartlett Tests		Citizens’ Home (CH)		Creative World Industrial Park (CWIP)
		Explicit Importance	Actual Performance	Explicit Importance	Actual Performance
KMO sample appropriateness measure		0.911	0.944	0.948	0.962
Bartlett Sphericity test	Approximate Chi-squared value	793.915	1076.585	1313.398	1673.434
	Degree of freedom	105	105	105	105
	Significance	0.000	0.000	0.000	0.000

) of the evaluation of the landscape environment’s perception in the outdoor public space of CH and CWIP were thoroughly examined and analyzed. The Cronbach’s α values for both the significance and satisfaction of the evaluation indicators exceeded 0.8, indicating that the data are highly reliable and stable. Additionally, the KMO values for both samples were above 0.8, demonstrating good sample validity. The results of Bartlett’s test revealed a significant correlation between the variables, with a significance of sig = 0.000 < 0.05. These findings provide strong support for the continued analysis of this dataset.

3.2. Actual Performance, Explicit Importance and Implicit Importance

This study quantified the “explicit importance” of 15 landscape factors, with values ranging from 3.69 to 4.02 and a mean of 3.79. The “implicit importance” was measured by examining the relationship between satisfaction with these factors and overall satisfaction, with values ranging from 0.372 to 0.508 and a mean of 0.377. Additionally, the “actual performance” values for these factors ranged from 3.58 to 4.09, with a mean of 3.88. These three mean values form the core intersections of the three-dimensional IPA cube. To further analyze the actual performance, the values were classified into the following four categories: “very high”, “high”, “low”, and “very low”, with distinction points set at 3.96, 3.84, and 3.71, respectively.

Table 4. The 3-D IPA results for all outdoor public spaces in buildings (n = 340).

		Actual Performance (X)			Implicit Importance (Y)		Explicit Importance (Z)			Three-Factor Theory	IPA Strategy	Resource Allocation
		Mean	S.D.	Level	Coefficient	Level	Mean	S.D.	Level
SEP	a	3.76	1.134	L	0.372	L	3.69	1.244	L	Performance	Low Priority	Low Priority
	b	3.92	1.087	H	0.288	L	3.57	1.358	L	Performance	Reduce	Reduce
	c	4.01	1.010	VH	0.382	H	3.77	1.197	L	Excitement	Reduce	Keep
SPP	d	3.76	1.273	L	0.448	H	4.02	1.074	H	Performance	Improve	Improve
	e	3.68	1.330	VL	0.402	H	3.94	0.994	H	Performance	Improve	Improve
	f	4.09	1.003	VH	0.397	H	3.78	1.248	L	Excitement	Reduce	Keep
	g	4.07	1.084	VH	0.344	L	3.81	1.149	H	Basic	Reduce	Reduce
	h	3.87	1.128	H	0.261	L	3.59	1.364	L	Performance	Reduce	Reduce
CUP	i	3.58	1.345	VL	0.345	L	3.91	0.981	H	Basic	Improve	Improve
	j	3.69	1.338	VL	0.504	H	4.01	1.039	H	Performance	Improve	Improve
	k	3.91	1.068	H	0.370	L	3.60	1.352	L	Performance	Reduce	Reduce
	l	4.00	1.085	VH	0.298	L	3.70	1.268	L	Performance	Reduce	Reduce
AEP	m	3.98	1.052	VH	0.417	H	3.75	1.253	L	Excitement	Reduce	Keep
	n	3.82	1.275	L	0.508	H	3.88	1.097	H	Performance	Improve	Improve
	o	4.07	0.991	VH	0.320	L	3.84	1.272	H	Basic	Keep	Reduce
Large mean		3.88			0.377		3.79

Remark: SEP—service perception; SPP—spatial perception; CUP—cultural perception; AEP—aesthetic perception.

provides the values for explicit importance, implicit importance, and actual performance.

3.3. Analysis of Actual Performance, Explicit Importance Evaluation of Four Perceived Dimensions

Table 5. The 3-D IPA results in four dimensions.

	Actual Performance (X)		Implicit Importance (Y)		Explicit Importance (Z)		Three-Factor Theory	IPA Strategy	Resource Allocation
	Mean	Level	Mean	Level	Mean	Level
CH
SEP	3.98	VL	0.407	L	3.65	L	Performance	Reduce	Low priority
SPP	4.02	VH	0.426	L	3.93	H	Basic	Keep	Reduce
CUP	3.87	H	0.391	L	3.87	H	Basic	Improve	Keep
AEP	4.05	VH	0.434	L	3.90	H	Basic	Keep	Reduce
CWIP
SEP	3.82	L	0.492	H	3.70	L	Excitement	Low priority	Keep/Improve
SPP	3.77	L	0.458	H	3.73	L	Excitement	Low priority	Keep/Improve
CUP	3.73	L	0.528	H	3.75	L	Excitement	Low priority	Keep/Improve
AEP	3.97	VH	0.474	H	3.65	L	Excitement	Reduce	Keep

Remark: SEP—service perception; SPP—spatial perception; CUP—cultural perception; AEP—aesthetic perception.

presents the 3-D IPA results for the four dimensions of user perception of the landscape environment in outdoor public spaces within buildings. In CH, the dimensions of “spatial perception”, “cultural perception”, and “aesthetic perception” are classified as basic factors, while the “service perception” dimension is categorized as a performance factor. For basic factors, it is recommended to either “maintain” or “reduce” existing measures. For the “service perception” dimension, a “low priority” action is recommended. In CWIP, all four dimensions are classified as excitatory factors. For these excitatory factors, the recommended action strategy is to either “keep” or “improve” their performance.

By comparing two types of outdoor public spaces, CH and CWIP, this study analyzes the results of the evaluation of the actual performance and apparent importance of each factor in the following four perceptual dimensions: service perception, spatial perception, cultural perception, and aesthetic perception (see

Table 6. The 3-D IPA results of CH (n = 165).

		Actual Performance (X)			Implicit Importance (Y)		Explicit Importance (Z)			Three-Factor Theory	IPA Strategy	Resource Allocation
		Mean	S.D.	Level	Coefficient	Level	Mean	S.D.	Level
SEP	Aa	3.93	1.009	H	0.475	H	3.52	1.391	L	Excitement	Reduce	Low Priority
	Ab	3.95	1.002	H	0.438	H	3.56	1.394	L	Excitement	Reduce	Reduce
	Ac	4.05	0.939	VH	0.307	L	3.87	1.149	H	Basic	Keep	Keep
SPP	Ad	3.92	1.220	H	0.411	H	4.15	1.049	H	Performance	Keep	Improve
	Ae	4.05	1.066	VH	0.354	L	3.99	0.934	H	Basic	Keep	Improve
	Af	4.22	0.906	VH	0.343	L	3.92	1.142	H	Basic	Keep	Keep
	Ag	4.26	0.840	VH	0.552	H	3.99	1.099	H	Performance	Keep	Reduce
	Ah	3.94	1.010	H	0.472	H	3.59	1.370	L	Excitement	Reduce	Reduce
CUP	Ai	3.67	1.313	VL	0.314	L	3.96	0.910	H	Basic	Improve	Improve
	Aj	4.15	1.287	H	0.406	H	4.06	1.080	H	Performance	Keep	Improve
	Ak	3.87	1.089	H	0.365	L	3.55	1.386	L	Performance	Low Priority	Reduce
	Al	3.90	1.198	H	0.477	H	4.13	0.951	H	Performance	Keep	Reduce
AEP	Am	3.96	1.067	H	0.487	H	3.86	1.136	H	Performance	Keep	Keep
	An	4.05	1.181	VH	0.317	L	3.84	1.081	H	Basic	Keep	Improve
	Ao	4.15	0.960	VH	0.497	H	3.99	1.140	H	Performance	Keep	Reduce

Remark: SEP—service perception; SPP—spatial perception; CUP—cultural perception; AEP—aesthetic perception. A—Citizens’ Home (CH).

and

Table 7. The 3-D IPA results of CWIP (n = 175).

		Actual Performance (X)			Implicit Importance (Y)		Explicit Importance (Z)			Three-Factor Theory	IPA Strategy	Resource Allocation
		Mean	S.D.	Level	Coefficient	Level	Mean	S.D.	Level
SEP	Ba	3.60	1.222	VL	0.463	H	3.86	1.138	H	Performance	Improve	Improve
	Bb	3.90	1.165	H	0.469	H	3.58	1.328	L	Excitement	Reduce	Low priority
	Bc	3.97	1.074	VH	0.546	H	3.67	1.237	L	Excitement	Reduce	Keep
SPP	Bd	3.90	1.086	H	0.545	H	3.61	1.308	L	Excitement	Reduce	Low priority
	Be	3.61	1.355	VL	0.453	H	3.89	1.048	H	Performance	Improve	Improve
	Bf	3.96	1.074	H	0.455	H	3.65	1.330	L	Excitement	Reduce	Low priority
	Bg	3.89	1.248	H	0.407	H	3.65	1.174	L	Excitement	Reduce	Low priority
	Bh	3.80	1.227	L	0.423	H	3.58	1.362	L	Excitement	Low	Keep/Improve
CUP	Bi	3.50	1.372	VL	0.512	H	3.87	1.045	H	Performance	Priority	Improve
	Bj	3.97	0.999	VH	0.543	H	3.58	1.379	L	Excitement	Improve	Keep
	Bk	3.95	1.049	H	0.590	H	3.65	1.322	L	Excitement	Reduce	Low priority
	Bl	3.87	1.187	H	0.468	H	3.51	1.308	L	Excitement	Reduce	Low priority
AEP	Bm	4.00	1.039	VH	0.491	H	3.64	1.348	L	Excitement	Low	Keep
	Bn	3.92	1.014	H	0.443	H	3.60	1.402	L	Excitement	Priority	Low priority
	Bo	4.00	1.017	VH	0.498	H	3.70	1.374	L	Excitement	Reduce	Keep

Remark: SEP—service perception; SPP—spatial perception; CUP—cultural perception; AEP—aesthetic perception; B—Creative World Industrial Park (CWIP).

).

In the service perception dimension, CH outperforms CWIP in the factors of “identification system guide”, “road guidance”, and “the convenience of travel and transportation options”. The factor “the convenience of travel and transportation options” obtained the highest explicit importance score (3.87), indicating that users really like how the outdoor public spaces are designed at CH. Conversely, the factor “identification system guide” obtained the lowest score (3.52), suggesting that users place less importance on this orientation service. In contrast, CWIP shows more evenly distributed scores across the service perception factors. Users consider “identification system guide” and “the convenience of travel and transportation options” to be highly important. However, the actual performance of the “identification system guide” is poor, indicating that the users’ experiences with this feature fall short of their expectations. In the spatial perception dimension, CH performs better overall, particularly in factors such as “attractiveness of entrances and exits”, “the richness of landscape space types”, “site safety and accessibility”, and “the use of permeable floor paving”, all of which are significant factors. Despite CWIP’s high score for the importance of “the richness of landscape space types”, its actual performance score is low (3.61), signaling that users still have high expectations for a diverse range of spaces and features that have not yet been fully met. In the cultural perception dimension, both CH and CWIP users agree on the importance of “the cultural nature of landscape decoration” in cultural landscape design. However, the actual performance of this factor is lacking, suggesting that users’ expectations for the cultural aspect of the landscape have not been fulfilled. Meanwhile, the performance of other related factors is better, and users’ satisfaction with these elements is generally higher, indicating that the cultural and activity-oriented aspects of the public space design are generally well received. In the aesthetic perception dimension, both CH and CWIP users gave high ratings to factors such as the art of public facilities, plant viewing, and landscape night lighting. This suggests that in terms of aesthetics, the design of public spaces is generally well-regarded. Particularly in the areas of landscape night lighting and plant viewing, users perceive significant aesthetic value, which enhances the overall attractiveness of the landscape.

3.4. The 3-D IPA Analysis of Four Perceptual Dimensions

3.4.1. The 3-D IPA of Service Perception Dimensions

The 3-D IPA model analysis of the service perception dimension (see Figure 7) indicates that the optimal strategies for improving the landscape environment quality of the outdoor public space at CH are provision of an “identification system guide” and “road guidance”, which fall into the Low Priority quadrant, indicating that they require no immediate action. In contrast, “the convenience of travel and transportation options” is recommended to adopt a reduction strategy; while maintaining basic travel convenience for the public, it is advisable to minimize planning and design inputs in this dimension to enhance the overall cost-efficiency. Compared to the CH, the “identification system guide” of the CWIP needs to be “improved” to make the service functions better, like identification. Conversely, “road guidance” remains a low priority, while “the convenience of travel and transportation options” should remain unchanged.

3.4.2. The 3-D IPA of Spatial Perception Dimensions

In the 3-D IPA model analysis of spatial perception dimensions (see Figure 8), the “attractiveness of entrances and exits” and “the use of permeable floor paving” should stay the same in the CH. “Road fluency” adopts a “low priority” action strategy; “the richness of landscape spatial types” and “site safety and accessibility” should be reduced to meet the needs of the public and maintain the quality of their landscape space. In contrast, in the CWIP, “the richness of landscape spatial types” and “road fluency” should be adopted as “improve” strategies. We regard the remaining three factors as “low priority” and recommend their moderate optimization.

3.4.3. The 3-D IPA of Cultural Perception Dimensions

For the CH in the 3-D IPA model analysis of cultural perception dimensions (see Figure 9), it is indicated that “the cultural nature of landscape decoration” needs to “improve”. It also indicates that “promotion of culture and history and science education”, and the “openness of venue” should be “kept” to meet the needs of the residents for cultural activities. At the same time, the “distribution and quantity of native plants” should be moderately “reduced”, so as to reduce the planning and design input in this area on the premise of satisfying the public’s regional cultural experience. In contrast, in the CWIP, “the distribution and quantity of native plants” and “the openness of the venue” are regarded as “low priority”. The “promotion of culture and history and science education” should be maintained at the current level; the same “improve” strategy should be adopted for “the cultural nature of landscape decoration” to further strengthen the cultural aspects of outdoor public spaces in decentralized buildings.

3.4.4. The 3-D IPA of Aesthetic Perception Dimensions

To make the landscape environment better, the 3-D IPA model looks at the aesthetic perception dimension (see Figure 10). It shows that the CH and CWIP use a “keep” strategy for “artistry of public facilities” and “landscape night lighting artistic”. This indicates that these two factors can meet the basic needs of users at the current level, and there is no need for substantial optimization. For “plant viewing”, CH uses the “Reduce” strategy, which means that this factor does somewhat affect users’ aesthetic needs, but the current performance is satisfactory enough that it does not need a lot of extra resources to be improved. In contrast, CWIP uses the “low priority” strategy, which means this factor does not affect users’ aesthetic needs as much and can be moderately optimized without using too many resources.

4. Discussion

This study builds on the previous research by looking into how to improve the quality of the landscape environment for the four main perception factors of service perception, spatial perception, cultural perception, and aesthetic perception in the outdoor public spaces of CH and CWIP (see in

Table 8. Optimization recommendations for the outdoor public space landscape environments of CH and CWIP.

Dimensionality	Environmental Perception Factor	3-D IPA Resource Allocation		Landscape Quality Improvement Suggestions
		CH	CWIP	CH	CWIP
Service perception	Identification system guide	Low priority	Improve	(1) Establish a uniform and clear signage system (2) Increase auxiliary facilities such as voice guidance and touch-screen guides
	Road guidance	Low priority	Low priority	(1) Use of green belts, ground material changes, and ground markings (2) Constructing an online network service cloud platform applet
	The convenience of travel and transportation options	Reduce	Keep	Maintaining easy access to transportation modes for travel
Spatial perception	Attractiveness of entrances and exits	Keep	Low priority	Keeping entrances and exits attractive	(1) Adding distinctive lands-cape elements or cultural markers (2) Installation of small sitting areas or information display walls
	The richness of landscape spatial types	Reduce	Improve	Reduced complexity of entrance space design	(1) Increase the division of multi-functional areas, such as recreational areas, play areas, garden areas, etc. (2) Introduce abundant vegetation
	Site safety and accessibility	Reduce	Low priority	Maintenance of existing site accessibility design and regular inspection and maintenance	Increase the installation of accessible ramps, accessible parking lots
	The use of permeable floor paving	Keep	Low priority	Maintaining the utilization of permeable paving on the ground	(1) Adopt permeable paving materials (2) Adding pervious paving type landscaping
	Road fluency	Low priority	Keep/ Improve	(1) Simplify road layout (2) Add intelligent guidance
Cultural perception	The cultural nature of landscape decoration	Improve	Improve	(1) Adding sculptures and other works by local artists (2) Shaping landscape vignettes using regional materials and traditional crafts
	Promotion of culture and history and science education	Keep	Keep	Maintaining the cultural atmosphere and character of the premises
	Distribution and quantity of native plants	Reduce	Low priority	Reduce the planting of overly complex flower types and plant more varieties that are suited to the local climate and soil	Follow the natural growth pattern and use different levels of plant configuration
	The openness of the venue	Keep	Low priority	Keeping event venues open and flexible
Aesthetic perception	Artistry of public facilities	Keep	Keep	Maintain artistic design of public facilities
	Plant viewing	Reduce	Low priority	Capitalize on the ornamental value of ornamental garden plants	(1) Select multi-seasonal plant species (2) Create interactive plant viewing experiences
	Landscape night lighting artistic	Keep	Keep	Maintain the artistic and visual appeal of the landscape nightscape

).

4.1. Service Perception Dimension Optimization Recommendations

The 3-D IPA analysis reveals that both in the CH and CWIP, “identification system guide” and “road guidance” are classified into the low-priority quadrants, indicating that users place less importance on these factors. This may be due to users’ familiarity with the space or the inherent clarity of the original spatial structure. In particular, at CWIP, being a creative industrial park, users are more inclined to navigate the space independently and rely less on formal guidance systems.

Nevertheless, it remains essential to improve inclusiveness and efficiency. A unified visual language, such as intuitive symbols, color coding, and digital guidance tools, is recommended. Additionally, considering the needs of the elderly and visually impaired, barrier-free guidance methods, including voice broadcasting and touch screens, should be incorporated. This strategy aligns with Stessens et al.’s [7] emphasis on spatial identifiability in green spaces and supports the urban system design principles proposed by Firmansyah et al. [8].

4.2. Spatial Perception Dimension Optimization Recommendations

The importance of “the richness of landscape space types” is rated as moderate in the CH but is considered highly important in CWIP. This suggests that user expectations vary based on the nature of the space: in the CH, which functions as a government building, users prefer simple, function-oriented spaces. In contrast, users of CWIP, a creative industrial park, place greater emphasis on the diversity and openness of spaces to accommodate creative work and social interaction. Therefore, CH should avoid overdesign and focus on simplifying the design, using durable, low-maintenance materials, clear path systems, and multifunctional spatial layouts [31]. On the other hand, CWIP can enhance the variability of space and artistic expression, creating attractive social spaces such as shaded rest areas or small event platforms. These strategies align with the view that “spatial clarity contributes to the efficiency of use”, as proposed by Gavrilidis et al. [1], and support the conclusion that “spatial stratified structure can meet diverse perceptual expectations”, as emphasized by Qi et al. [14].

Regarding the “attractiveness of entrances and exits” at CWIP, it is recommended that the design of these areas be further optimized to enhance their visual guidance and functionality. For example, entrances and exits can be made more prominent by incorporating characteristic landscape elements or cultural markers, transforming them into key visual nodes in the space and increasing their appeal to users. Additionally, multifunctional areas, such as small seating arrangements or information display walls, can be added around the entrances to further enhance their utility and capacity for gathering crowds. These improvements would contribute to the accessibility, mobility, interactivity, and overall attractiveness of the space.

4.3. Cultural Perception Dimension Optimization Recommendations

To optimize “the cultural nature of landscape decoration”, both CH and CWIP can adopt similar strategies to enhance the cultural connotation of their landscapes. It is recommended that landscape vignettes incorporate more cultural elements, such as the work of local artists, sculptures depicting the area’s history, or the use of local building materials and traditional crafts [32]. For instance, CH can reflect government culture through educational and public-oriented landscape sculptures and historical signage, while CWIP can integrate multicultural elements to create a more inclusive cultural expression space.

In terms of plant configuration, CH should simplify plant types to reduce maintenance complexity, whereas CWIP can adopt a layered planting structure to enhance both ecological and visual diversity. This strategy aligns with Gao et al. [9], who emphasized that “localized plant design facilitates ecological and cultural synergy”, and echoed Tzoulas et al. [33], who highlighted the role of green infrastructure in carrying both ecological and social significance. Furthermore, Zhao et al. [18] and Jiang and Liu [19] also underscored that embedding cultural narratives into spatial layouts can significantly enhance users’ cultural engagement and sense of belonging.

Regarding the optimization of “distribution and quantity of native plants”, CH should reduce overly complex flower plantings and prioritize species adapted to the local climate and soil conditions. This approach not only helps create a uniform and natural landscape effect but also reduces maintenance costs and complexity. In contrast, CWIP should follow the natural growth patterns of plants and avoid the over-concentration of any single species. By strategically configuring trees, shrubs, groundcovers, and other plants, CWIP can achieve a more natural and rich landscape effect [33]. For example, in walkway or plaza areas, a moderate density of low groundcover plants can be used, while areas requiring shade could feature sparse trees or large shrubs. This plant configuration enhances ecological diversity and better meets the functional needs of the space.

In terms of “promotion of culture, history, and science education”, as well as “the openness of the venue”, it is recommended to maintain the existing design principles. The enhancement of cultural and historical aspects can be achieved through the combination of spatial layout and landscape design [34], such as reinforcing the sense of history and cultural depth through cultural signs, historical sculptures, or display walls. The openness of the activity venue should focus on maintaining flexibility, allowing the space to be adjusted for various uses. The layout and arrangement of facilities should be planned to facilitate smooth functioning for a wide range of activities. This will make public spaces more interactive and functional.

4.4. Aesthetic Perception Dimension Optimization Recommendations

Regarding the design of the “artistry of public facilities” and “landscape night lighting artistry”, both CH and CWIP have achieved commendable design results. However, in terms of “plant viewing”, CH users tend to favor seasonal variation and structural aesthetics, while CWIP users prefer informal, multisensory experiences. To enhance the viewing experience, it is recommended to incorporate diverse plant forms, seasonal color contrasts, and perceptible landscaping elements (such as aromatic or touchable herbaceous plants), particularly around walkways and gathering areas. This approach aligns with the conclusion by Van Den Berg et al. [15] that “sensory-rich green spaces have greater restorative effects” and resonates with Pasha and Shepley’s [32] research on how “multi-sensory garden design promotes emotional connections”.

4.5. Study Limitations and Future Research Directions

While this study provides actionable strategies, several limitations should be acknowledged. First, the research is based on two representative sites in Wuhan, which may not fully reflect broader patterns across different urban regions. Although the CH and CWIP respectively, further case studies are needed for more comprehensive generalization. Second, while the questionnaire was carefully designed based on perception dimensions, the sample size and demographic scope were limited. Future research should aim to expand participant diversity and explore longitudinal changes in user perception. Third, this study did not explicitly analyze the impact of climatic factors on spatial perception, such as heat stress or rainfall. Future studies could investigate how environmental design (e.g., shading, paving, and ventilation) mitigates climate-related discomfort and influences space usage.

5. Conclusions

This study uses both the 3-D IPA model and an evaluation index system based on perception theory to obtain a full picture of how satisfied people are with the landscape environment in the public outdoor areas in CH and CWIP. The results of this study show that the 3-D IPA model can provide an effective evaluation method for users’ landscape preferences in outdoor public spaces, and at the same time, provide direct quantitative evaluation and empirical support for landscape perception theory and sustainable urban development practices. Based on the results, this study proposes specific optimization suggestions for each index that align with sustainability principles. The main conclusions and insights of this study are as follows:

(1)

Through a 3-D IPA analysis of the CH and CWIP, this study reveals the differences in user perceptions of these two architectural spaces. The CH sees its users particularly focused on the functional, accessible, and safe aspects of the space, with aesthetic perception being secondary, as users prioritize the artistic and visual effects of the landscape. In contrast, CWIP’s users place greater importance on cultural perception, especially regarding the cultural value of landscape elements and the openness of activity spaces. Space perception ranks second, with users emphasizing the diversity, rational layout, and accessibility of the landscape. Both service perception and aesthetic perception are relatively less significant. These findings provide valuable insights for developing more sustainable, user-centered urban spaces.

(2)

Based on the results of the 3-D IPA analysis, the CH should prioritize optimizing the convenience of transportation, particularly by improving the design of entrances and traffic guidance functions to promote sustainable mobility. In addition, landscape design should focus on enhancing the environmental benefits and aesthetic appeal of permeable paving, which contributes to urban water management and climate resilience, while avoiding excessive investment in identification systems and road guidance functions. For CWIP, the focus should be on improving the diversity of landscape spaces and the smoothness of roads, while optimizing the cultural expression of landscape elements to enhance social sustainability and community engagement.

(3)

In addition to the optimization recommendations for the CH and CWIP, this study also provides optimization references for the outdoor public spaces of other similar building types. First, the differences between spatial types and user needs should be fully understood. Second, the optimization plan should address multiple dimensions, not limited to functionality and accessibility, but also considering the improvement of aesthetics, cultural elements, and service facilities. Finally, designers should integrate the 3-D IPA model’s comprehensive evaluation method and based on the characteristics of different spatial types and user needs, flexibly adjust design elements to ensure that, while enhancing the functionality of the space, the diverse perceptual needs of users are also met.