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Article

Subjective Impacts on Knowledge Creation Behavior of Enclosed University Campus in China

by
Wanqing Su
1,2,3,
Tianyun Lu
1,2,3,*,
Jianhua Su
4,* and
Menghan Wang
1,2,3
1
School of Architecture, Harbin Institute of Technology, Harbin 150001, China
2
Key Laboratory of Cold Region Urban and Rural Human Settlement Environment Science and Technology, Harbin 150001, China
3
Laboratory of National Territory Spatial Planning and Ecological Restoration in Cold Regions, Harbin 150001, China
4
School of Art, Heilongjiang University, Harbin 150022, China
*
Authors to whom correspondence should be addressed.
Buildings 2023, 13(7), 1702; https://doi.org/10.3390/buildings13071702
Submission received: 23 May 2023 / Revised: 26 June 2023 / Accepted: 27 June 2023 / Published: 3 July 2023
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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Abstract

:
Universities are essential for knowledge creation, and an efficient knowledge creation environment is important. The closed campus approach in China is unique. Almost all students live on campus, which forms the typical teaching + living model. This study aims to determine whether a closed campus is more conducive to knowledge creation and which factors contribute to improving its knowledge creation efficiency. This study uses a cluster analysis, confirmatory factor analysis, and multiple linear regression to explore the relationship between environmental factors and knowledge creation in the common spaces of enclosed university campuses. The findings include that creative behavior is significantly related to physical spaces and humanistic environments, and the latter is more significant. A good atmosphere of academic organization and a relaxed and free environment are necessary to promote academic exchanges. Improving the convenience of a closed campus has a greater impact on academic exchange, while improving the overall satisfaction and comfort has a greater impact on deep thinking. Increased overall satisfaction and convenience also promote thinking coherence. Deep thinking and academic exchange require different environmental characteristics. Meditation requires a better physical space, while scholarly communication needs a better humanistic environment. This study provides theoretical support for building an efficient knowledge creation campus environment.

1. Introduction

The importance of knowledge creation has been widely valued by countries worldwide. It is the core driving force for social and economic development. Research on knowledge creation has been conducted in the fields of management, sociology, economics, geography, architecture, and urban planning, and several theoretical models have been established. In 1912, Schumpeter formally and systematically proposed the innovation theory from an economic perspective, pointing out that the essence of creation is creative destruction [1]. With the continuous deepening of people’s understanding of innovative thinking, theoretical models related to knowledge creation are also gradually enriched. The creation diffusion theory complements the technology diffusion process in innovation theory [2]. The component models of creativity and innovation in organizations, the theory of induced invention, and the four-stage theory of creativity further expand the connotations of innovation theory [3,4,5]. The motivation for creation comes from technology promotion and demand promotion [6]. Moreover, the three modes of creativity include the visceral mode, ideational mode, and observational mode, which also enrich the innovation theory [7].
The social environment and spatial environment have an impact on knowledge creation. Creativity has social attributes [8]. According to creativity investment theory, environmental factors, including physical, psychological, and social systems, are some of the six essential sources of creativity. Other factors include intelligence, knowledge, the thinking mode, personality, and motivation [9]. At the macro level, there is a spatial imbalance in creation distribution, regional knowledge generation, and creation ability [10,11]. At the micro level, physical space is one of the necessary sources of creation [12]. The workplace directly impacts employees’ work performance and creative focus [13,14,15]. The sharing and openness of places, inter-departmental communication, privacy, noise levels, and having a distraction-free environment affect the innovation space efficiency [16,17]. An efficient innovation space can promote thought fusion, inspiration generation, the socialization of scientific research results, and collaborative learning.
The university is one of the important places for knowledge creation. Creating an efficient and innovative thinking environment is the key to constructing a university campus. Scholars have researched the relationship between the campus environment and students’ subjective feelings and academic performance. Factors such as the physical environment, infrastructure, greenery, and spatial scale are helpful for students’ learning and attention restoration [18,19,20,21]. Regarding the indoor furniture layout, the architectural design also affects the use of space and the satisfaction of teachers and students [22]. The organizational atmosphere, communication within the team, and guidance from mentors are crucial for students’ creativity [23]. In addition to the humanistic environment and physical space, creative behavior is influenced by creative thinking characteristics and individual potential [24], as shown in Figure 1.
Compared with universities in other countries, the Chinese enclosed university campus design is unique. Therefore, it is significant to study the impact mechanism of knowledge creation on closed university campuses in China. The Fang-li system deeply influences the layout mode of Chinese university campuses in ancient China. A Fang-li was a grassroots residential unit in ancient Chinese cities, with enclosed walls and regimented access control, forming a neat and uniform urban structure [25]. The Fang-li system existed as early as the pre-Qin period, reaching its peak in Chang’an City during the Tang dynasties. After the Song Dynasty, the strict management system of Fang-li gradually relaxed, and the Fang-li system finally became a unit for some residential regions or residents to manage [26]. Affected by this, Chinese closed universities differ from Western universities regarding the campus’ functional layout and management. Generally speaking, Chinese universities have clear boundaries and provide dormitories for students, with almost all students concentrated within the campus [27,28], forming a typical campus model of teaching + living areas. The school logistics department provides public services in the university, while other stores are spontaneously formed outside the edge of the campus. In order to solve the dining problem for everyone on campus, there are several large, centralized restaurants covering an area of over 1000 square meters in Chinese universities. However, this campus layout generates significant tidal effects [29], which means the campus space is not fully utilized and affects the efficiency of the campus’ creative activities. Exploring the impact mechanism of China’s closed campus environment on knowledge creation activities and improving overall creation efficiency has become an important research issue.
The existing research has summarized the characteristics of innovation from different perspectives, explored the causes and mechanisms of innovation, and confirmed that social and spatial factors can affect innovation behavior. However, there is a need to clarify how different environmental factors affect innovation behavior. The research on the spatial environment of university campuses has focused more on teaching effectiveness and student needs, with relatively few research results on innovative behavior support and inspiration stimulation. There needs to be more research on the innovative environment of closed university campuses in China. This article uses quantitative research methods such as a cluster analysis, confirmatory factor analysis, and multiple linear regression to study the characteristics of the knowledge creation environment on closed university campuses in China. The focus is on exploring the relationship between the public space, users’ subjective feelings, and knowledge creation behavior, aiming to reveal the essential features of an efficient university public innovation environment.

2. Materials and Methods

2.1. Participants

This study uses the Likert scale and random sampling to explore the environmental factors that affect knowledge creation behavior. The research sites are two campuses of the Harbin Institute of Technology (HIT). HIT is a typical high-level research university in China, ranking 236th in the world ranking of QS in 2022. The disciplines of engineering and technology, material science, computer science and information systems, mathematics, and environmental science at HIT are among the top in the world. Notably, the architecture and built environment disciplines rank in the top 100 worldwide [30].
Here, we analyze the distribution of the Harbin Institute of Technology and its surrounding service facilities through OpenStreetMap data and Gaode data, including catering, public, shopping, life, sports, leisure, and medical care services. Figure 2 shows the density of service facilities per hectare. The figure shows that there are few public service facilities inside the campus, with at most 5 per hectare, and the distribution is uneven. The edge of the school has the most concentrated distribution of off-campus service facilities, at up to 160 per hectare.
The research site includes the library, teaching building, canteen, cafe, study room, classroom, and student union. The sites and the internal environment are shown in Figure 3. To accurately find users’ subjective feelings in the spatial environment, the data were collected by filling out questionnaires on the spot. Undergraduates, postgraduates, doctoral students, and teachers were involved in the survey. The survey was anonymous, and all participants knew the aims of the research and agreed to participate in the survey. According to the local regulations, this investigation did not require ethical approval.

2.2. Data Analysis

Based on the theory of the spatial structure of the knowledge creation environment [24], this study determines the questionnaire’s overall relationship structure, research elements, and problem setting. This study focuses on the indicators that can reflect the environment and users’ creative behavior. A cluster analysis, confirmatory factor analysis (CFA), and multiple linear regression are used in this research to explore the relationship among the factors of the knowledge creation environment on enclosed university campuses.
The classification of different questions in the questionnaire was achieved using the cluster analysis. The rationality and relevance of each dimension of the questionnaire were verified. Firstly, we standardized the data using z-scores and used the square sum of the dispersion method to cluster the variables [31]. We then performed a cluster analysis of all 20 questions to identify the category attribution of the different questions and to construct new variables to analyze the relationship between the clustering variables.
In this study, we further tested the ability of the model to fit the actual data based on the CFA and measures the correlation between factors [32]. The confirmatory factor analysis was conducted using the five dimensions of deep thinking, communication or leisure, physical space, humanistic environment, and overall feeling. This study also used multiple linear regression to explore the impacts of different factors on creation behavior.

2.2.1. Main Contents

According to the theory of the spatial structure of the knowledge creation environment, knowledge creation behavior mainly includes four aspects: deep thinking, academic exchange, resource acquisition, and knowledge externalization. Closed university campuses have certain limitations in their urban vitality, social equity, innovation, and entrepreneurship, which are not conducive to innovative academic exchange activities [33,34]. This study mainly focuses on two aspects. Table 1 shows the questions from this research.

2.2.2. Data Characteristics

The survey was conducted from September 2021 to June 2022. In total, 1603 questionnaires were collected from two campuses, of which 1566 were valid. The effective rate was 97.7%. In total, 96 teachers, 569 graduate students, and 901 undergraduates were interviewed, including 989 males and 577 females (see Figure 4). Using IBM SPSS statistics 25 software to test the questionnaire results, Cronbach’s α = 0.764, which means the consistency of the scale, was high. Kaiser–Meyer–Olkin’s (KMO) measure of sampling adequacy and Bartlett’s test of sphericity analyzed the validity of the questionnaire. The KMO value was 0.829 (p < 0.05), indicating that the questionnaire had good structural validity.
Cliff’s d-effect test was used to exclude the influence of the sample size on the p-value, with the first semester (September 2021 to January 2022) and second semester (May 2022 to June 2022) used as controls. The results are shown in Table 2. The estimated values are all <0.28, indicating that the results of the two groups of experiments before and after are stable.

3. Results

3.1. The Analysis of Impact Categories of Innovation Activities

3.1.1. Clustering Characteristics of Different Types of Innovation Activities

Similar innovation activities have similar needs for the environment, so in this study we first carried out a cluster analysis of 6 different types of innovation activities. Considering the suitability and stability of the number of groups, the change in inter-group distance within a specific range does not affect the classification results. In this study, we selected an inter-group distance range of 7–9, and the clustering results aggregated the variables into five types. The results are shown in Figure 5.
The results show that cluster 1 is characterized by communication or leisure. This proves that a close relationship exists between academic exchange, chat, and relaxation in enclosed university campuses. Previous qualitative studies have shown that academic exchange often evolves from an informal chat. At the same time, academic exchanges can also play a role in relieving mental tension. Cluster 2 is characterized by deep thinking. The result reflects that interruption significantly influences the meditation and coherence of thinking in enclosed university campuses, affects deep thinking (an essential factor in knowledge creation behavior), and hinders knowledge creation.
Cluster 3 shows the characteristics of a humanistic environment. This shows that the openness and inclusiveness of spaces are conducive to creating an organizational atmosphere, and a relaxed and free atmosphere is an essential feature of the knowledge creation environment. Enclosed university campuses often have a unique organizational atmosphere independent of urban spaces, which provides a friendly humanistic environment for creation. When the overall campus is characterized by the enclosure, the openness of the internal public space becomes an essential factor. Cluster 4 shows the features of the physical space. This clustering reflects the users’ perceptions of the physical space, an essential physical space element. Cluster 5 is characterized by overall feelings. These three factors are the critical elements of the users’ cognition of the environment in enclosed university campuses, and they are of similar importance. A further analysis of the relationships among the five categories found that the physical space and humanistic environment showed aggregation characteristics, which verified that they belong to an environmental variable.

3.1.2. Verification Test

This part mainly discusses the confirmatory factor analysis results for the five cluster categories, and the load factors are shown in Table 3. The results show that the measurement items of each factor are at the significance level of 1%. Each dimension has a good measurement relationship. The analysis of the average common factor variance extraction (AVE) and the model’s combined reliability (CR) shows that the model’s convergence validity is ideal. The mean variance extraction of all factors is higher than 0.4, and the combined reliability CR values are higher than 0.6. The discriminant validity of the scale is ideal. Each fitting index is close to the ideal value, which indicates that the model has good adaptability, as shown in Table 4.

3.2. The Influence of Environmental Factors on Behaviors and Feelings

To further explore the specific impact of each cluster category on creation behavior in enclosed university campuses, a Spearman rank correlation analysis was used for the five clustering categories to determine their relationship, as shown in Figure 6.

3.2.1. Environmental Factors and Overall Feelings

The results show that both the humanistic environment and physical space significantly influence the users’ overall feelings of teachers and students in enclosed university campuses (>0.5), showing a positive correlation. The influence of the physical space (0.572) is more significant than that of the humanistic environment (0.507). People are more likely to have direct subjective feelings about the physical space, such as whether the temperature is appropriate, whether the light is bright, whether it is noisy, and whether there is any odor. The feelings about the humanistic environment come from the people or things around them. A friendly and relaxed environment can improve the users’ comfort and satisfaction.

3.2.2. Environmental Factors and Creative Behavior

The multiple linear regression of the creative behavior, physical space, and humanistic environment shows the relationships between the three elements in enclosed university campuses. Creative behavior is significantly related to the physical space and the humanistic environment, and the humanistic environment’s effect (0.391) on creative behavior is more significant than the physical space (0.166). This result is consistent with the previous research results on the five elements of creation; that is, there is a strong correlation between the humanistic environment and creative behavior and a weak correlation between the physical space and creative behavior [24].
As shown in Figure 6, for deep thinking, the influence of the physical space (0.595) is more significant than that of the humanistic environment (0.213), indicating that deep thinking requires a better physical environment. In enclosed university campuses, meditation is more affected by the acoustic, light, and thermal conditions and odors, while the influence of the humanistic environment is relatively weak.
Field observations can also support this conclusion. Libraries, study rooms, and other spaces are quiet, bright, and odorless. Such places attract users to learn, read, and think quietly, although these people who study together are probably not familiar with each other.
The correlation between communication and leisure and the physical space is not significant. When the users communicate and relax, a quieter environment is not better. Conversely, they prefer an environment with background sound, such as a cafe with music. The humanistic environment has a more significant impact on communication and leisure (0.351). For example, users are more willing to communicate in an academic atmosphere. Therefore, the users need a high-quality humanistic environment for communication or leisure.
The research on enclosed university campuses finds that most library and study room users’ study quietly. At the same time, the discussions in cafes and the student union are not, indicating that chat and academic exchanges can tolerate a worse physical environment.
This study also compared the data for teachers and students (including undergraduate and graduate students) and analyzed the impacts of environmental factors on their innovative behavior (see Table 5).
Consistent with the above results, the overall feeling is more influenced by the material space than the human environment. Both the teacher and student require a better physical environment when they meditate, and the human environment more influences students’ communication and leisure behavior than the physical space. However, the correlation between the teachers’ communication and leisure activities and environmental factors is insignificant. This research has found that teachers are more willing to share their innovative thinking with people from different backgrounds and prefer to expand their thinking range through academic exchanges. This kind of communication is often not limited to formal occasions but also occurs in informal situations, reducing the demand for environmental quality. Due to their relatively limited knowledge accumulation, students need a certain amount of environmental pressure to focus their attention, thereby requiring good environmental element quality.

3.3. The Influence of the Environment and Feelings on Innovation Behavior

3.3.1. The Effect of Holistic Experiences on Creative Behavior

This research covers the relationships among six types of different creative behaviors and three types of overall feelings using a multiple linear regression, as shown in Table 6. The residual analysis of the relationships among all elements shows that the residual of the factors conforms to a normal distribution, and the explanation rate is high.
It was found that overall convenience (p < 0.001, B = 0.281) had a more significant impact on academic exchange, while the satisfaction level (p = 0.44) and overall comfort (p = 0.83) had no significant influence on it. This shows that an environment with high convenience can promote academic exchanges. Inside the enclosed university campuses, the places providing various services are few and centralized. Moreover, the campus scale is often too large, which makes the convenience level insufficient.
The satisfaction level (p = 0.003, B = 0.235) and overall comfort (p = 0.016, B = 0.199) had a more significant impact on meditation, while overall convenience had no significant impact on it (p = 0.41). Therefore, a comfortable and high-satisfaction environment should be provided for deep thinking in enclosed university campuses.
Further investigation shows that improvements in satisfaction level (p < 0.001, B = 0.280) and overall convenience (p = 0.007, B = 0.202) can also promote the coherence of thinking, while the overall convenience (p = 0.004, B = 0.223) has a significant influence on interruptions. The reason is that in a more convenient space, the users’ various needs can be met in time, reducing the possibility of interrupted thoughts, which is also an essential feature of the service facility distribution of enclosed university campuses.

3.3.2. The Sensitivity of Different Innovation Behaviors to Environmental Factors

To explore how different creation behaviors are affected by the surrounding campus environment, this research also covers the relationships between six kinds of different creative behaviors and the physical space and humanistic environment, as shown in Table 7. The residual analysis is consistent with the normal distribution and the explanation rate is high.
The results show that a humanistic environment (p < 0.001, B = 0.368) has a more significant impact on academic exchange, while physical space (p = 0.118) has no significant impact on academic exchange. For chat and relaxation, the influence of a humanistic environment is significantly positively correlated and the influence of physical space is significantly negatively correlated. In an enclosed university campus, places such as libraries, cafes, and common rooms have high-quality physical environments, and people’s willingness to communicate in libraries is far less than in cafes. The results explain that this phenomenon is because when users are in a tranquil environment, they feel worried that their conversation may interfere with others, reducing their willingness to talk. In the common room in the department, users are often familiar with each other and they feel relaxed in it, which leads to the evolution from informal chats to academic exchanges.
For deep thinking, the physical space (p < 0.001, B = 0.597) greatly influences meditation, while the humanistic environment (p = 0.169) has no evident influence on meditation. Both the physical space (p < 0.001, B = 0.335) and humanistic environment (p = 0.070, B = 0.131) impact the coherence of thinking, and the impact of physical space is more significant than that of the humanistic environment. Therefore, high-quality physical space should be provided for deep thinking.
The relationship between different creative behavior and environmental factors in the enclosed university campuses has been studied, as shown in Table 8. It shows that whether a space is suitable for academic exchange in the public spaces of enclosed university campuses mainly depends on the organization atmosphere (p < 0.001, B = 0.325) and the free feeling (p = 0.009, B = 0.210). A friendly environment is more suitable for communication and discussion to inspire creativity. The free feeling focuses more on the users’ controllability of space and whether the users feel at ease. A high degree of free feeling in the space is more suitable for academic exchanges.
Among the four physical space factors, acoustics and odors are the main influencing factors, especially in meditation. This result shows that a pungent environment hinders one’s deep thinking, and noise can interfere with learning and cause annoyance [35]. Studies on olfactory–auditory interactions have shown that sound and odor will affect each other’s subjective evaluation, joyous sound and odor will improve each other’s subjective evaluation, and negative sound and odor have the opposite effect [36].

4. Discussion

4.1. Meditation, Communication, and Knowledge Creation

Many studies have confirmed that the environment can affect individual behaviors [37]. The structural cognitive theory of the knowledge creation environment [24] further clarifies the influence mechanism between knowledge creation behavior and the environment. Based on this, this paper puts forward research hypotheses and obtains consistent measurement results.
The structural cognitive theory of knowledge creation environments posits that creative thinking is a form deep thinking and requires the thinker to go through a gradual process from shallow to deep, which is also an essential process of knowledge understanding and reprocessing. Because new knowledge is easily forgotten, a sudden interruption will seriously impact the innovation process. Therefore, reducing interference and maintaining the continuity of deep thinking is very important. This study further found that although the physical space and humanistic environment can affect the continuity of thinking, the impact of the physical space is more significant. Meditation is an independent personal behavior that does not rely on the support of a pleasant humanistic environment. Instead, meditation prefers a stranger society, which can reduce the interference of greeting each other. A sudden noise in the physical environment can directly interfere with meditation.
This study also further proves that academic exchanges are gradual and urgent. Academic exchanges are often transformed from small talk or informal communication. Therefore, a friendly and relaxing humanistic environment can promote conversation better. Academic exchange and a humanistic environment show a significant positive correlation. In a tranquil public environment, it is not easy to ensure the privacy of the conversation. Moreover, it is difficult to completely relax because the users may be worried about disturbing others. To meet the urgent characteristics of academic exchanges, we should separate meditation and communication spaces and make them adjacent. In this way, we can provide a high-quality physical space for meditation and a comfortable humanistic environment for communication.

4.2. A Closed Campus Leads to a Lack of Weak Relationships in the Social Network of Knowledge Creation

Individual creativity is often contained in the social network formed by interpersonal interactions [38]. A knowledge creation network can be described by its network size, relationship strength, and network centrality. According to the frequency of interactions between individuals, intimacy, and trust, it can be divided into strong and weak network relationships [39]. Strong relational networks are more conducive to building trusting relationships to acquire in-depth and complex knowledge. In contrast, weak relational networks are more conducive to developing heterogeneous and external knowledge, which is equally important for knowledge creation. Therefore, the knowledge network has become an important “situational variable” of organizational creativity [8,40].
This study confirmed that academic communication and leisure have a close cluster relationship, whereby the physical space plays a vital role in informal communication and convenience significantly impacts academic communication activities [41]. Coffee shops, fast food restaurants, bars, and other businesses provide suitable physical spaces. They often have characteristics of openness, leisure, and convenience, which are important weak relationship network nodes. However, the management mode of the enclosed campus model in China hinders the development of leisure businesses such as fast food restaurants and bars inside the campus. The quantity, density, and accessibility of leisure businesses are affected, resulting in the lack of a weak relationship network on the campus. However, people’s unplanned face-to-face communication and knowledge sharing are indispensable for innovative organizations [42]. Convenient, shared, and attractive places promote informal communication behavior. Accessible coffee, printing services, comfortable seats, etc., provide opportunities for unexpected encounters between colleagues, prompting people to stay and talk there [43].

5. Conclusions

This study reveals the impact mechanism of the physical space, cultural environment, and overall subjective feelings of users on the deep thinking, academic exchange, and other knowledge creation behaviors of closed university campus users, which help guide the construction of efficient knowledge creation on university campuses.
Although closed campuses enhance people’s sense of security, they also weaken the overall convenience, significantly affecting academic exchange activities in knowledge creation. However, informal chatting, relaxation, and academic exchange require better convenience support. People’s knowledge creation behavior is significantly correlated with both the physical space and humanistic environment, and the impact of the humanistic environment is greater than that of the physical space. The environmental characteristics required for peaceful thinking and academic exchange are different. Deep thinking in innovation requires a better physical space, while academic exchange and leisure require a better humanistic environment. Simply improving the environmental quality of the physical space cannot better promote academic exchange. Therefore, while maintaining the quality of an enclosed campus’ physical space, more attention should be paid to creating an academic atmosphere suitable for communication and providing more diverse public rest spaces.
Although the indicators of overall satisfaction and overall comfort on campus have little impact on academic exchange activities, they have a more significant impact on meditation. The improvement of overall satisfaction and overall convenience can also significantly affect the coherence of thinking in knowledge creation. Therefore, improving the convenience of various service facilities and the comfort of the environment is of positive significance for improved satisfaction and innovation efficiency.

Author Contributions

Conceptualization, W.S. and J.S.; methodology, W.S. and J.S.; software, T.L.; validation, M.W.; formal analysis, T.L.; investigation, T.L. and M.W.; resources, W.S. and J.S.; data curation, T.L.; writing—original draft preparation, T.L. and M.W.; writing—review and editing, W.S. and J.S.; visualization, T.L.; supervision, W.S. and J.S.; project administration, W.S. and J.S.; funding acquisition, W.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Fundamental Research Funds for Central Universities, grant No.XNAUEA5750000120, entitled “Research on Green Campus and Surrounding Space Planning Based on Sustainable Development”; the Graduate Education and Teaching Reform Project of Harbin Institute of Technology, grant 21HX0303, entitled “Collaborative Mechanism of University Social Spatial Planning for Knowledge Innovation”; and the Harbin Science and Technology Plan Project, grant 2022STQZXKT0, entitled “Harbin Special project for the construction of innovation and entrepreneurship ecosystem around Harbin University”.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study.

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Buildings 13 01702 g001 550
Figure 1. Theory of the social–spatial structure of knowledge creation: (a) structure of five core categories and twenty-two keywords; (b) links among five core categories.
Figure 1. Theory of the social–spatial structure of knowledge creation: (a) structure of five core categories and twenty-two keywords; (b) links among five core categories.
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Figure 2. Distribution of the enclosed university and surrounding service facilities.
Figure 2. Distribution of the enclosed university and surrounding service facilities.
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Figure 3. The sites and the internal environment: (a) library (150 m2); (b) teaching building (135 m2); (c) cafe (200 m2); (d) classroom (60 m2); (e) student union (495 m2); (f) canteen (500 m2).
Figure 3. The sites and the internal environment: (a) library (150 m2); (b) teaching building (135 m2); (c) cafe (200 m2); (d) classroom (60 m2); (e) student union (495 m2); (f) canteen (500 m2).
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Figure 4. An analysis of the respondents’ identities.
Figure 4. An analysis of the respondents’ identities.
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Figure 5. Dendrogram of the cluster analysis.
Figure 5. Dendrogram of the cluster analysis.
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Figure 6. Correlations between the five core categories. Note: ** p < 0.01.
Figure 6. Correlations between the five core categories. Note: ** p < 0.01.
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Table
Table 1. Contents of the questionnaire.
Table 1. Contents of the questionnaire.
ContentsIndexAims
Basic information of respondentsGender, identity, monthly consumption.To understand the influence of users’ characteristics on subjective sound evaluation.
The respondents’ overall feelings about various spaces on campusSatisfaction level, overall comfort, overall convenience.To understand users’ overall evaluation of spaces.
Respondents’ evaluation of physical spaces and humanistic environments in different spacesSubjective feelings of acoustics, light, odors, and thermal condition; subjective feelings of organization atmosphere, openness, free feeling, and interruption.To understand users’ feelings about environmental factors.
Appropriateness of creative behavior in different spacesSuitability for deep thinking, academic exchange, relaxation, and leisure.To understand the influence of different environmental factors on creative behavior.
Table
Table 2. Cliff’s d effect size test.
Table 2. Cliff’s d effect size test.
NameEstimateLevel
Satisfaction level0.21153858Small
Overall comfort0.10968866Negligible
Convenience0.141583Small
Acoustic0.2055972Small
Light0.15698241Small
Thermal condition0.18421053Small
Odors0.13277785Small
Organization atmosphere0.14197209Small
Openness0.10902278Negligible
Free feeling0.12937568Small
Chat−0.14230898Small
Academic exchange−0.14742884Small
Relaxation0.02084955Negligible
Meditation0.09954368Negligible
Coherence of thinking0.13920575Small
Interruption0.14976338Small
Negligible: |estimate| < 0.11; small: 0.11 ≤ |estimate| < 0.28; medium: 0.28 ≤ |estimate| < 0.43; large: |estimate| ≥ 0.43.
Table
Table 3. Evaluation of the model.
Table 3. Evaluation of the model.
VariablesStandardization CoefficientPAVEStandard Estimation Coefficient
Communication or leisure
Chat0.952-0.6740.85
Academic exchange 0.7110.000 ***
Relaxation0.660.000 ***
Deep thinking
Meditation0.84-0.6140.82
Coherence of thinking0.6380.000 ***
Interruption0.8070.000 ***
Physical spaces
Acoustic0.819-0.5110.803
Light0.6090.000 ***
Thermal condition0.660.000 ***
Odors0.7250.000 ***
Humanistic environments
Organization atmosphere0.799-0.410.664
Openness0.4410.000 ***
Free feeling0.6280.000 ***
Overall feeling
Satisfaction level0.637-0.4850.737
Overall comfort 0.7210.000 ***
Convenience 0.7220.000 ***
Note: *** p < 0.001.
Table
Table 4. The fitting index of the model.
Table 4. The fitting index of the model.
IndexX2/DOFRMSRMRGFICFINFINNFI
Criterion<3<0.10<0.05>0.9>0.9>0.9>0.9
Value3.3640.1070.0530.8060.8530.8060.812
Table
Table 5. Spearman’s nonparametric rank correlation test.
Table 5. Spearman’s nonparametric rank correlation test.
IdentitySpearman Rank Correlation Coefficient
Student Overall
feeling		Communication and leisureDeep
thinking
Physical space0.482 **0.069 **0.435 **
Humanistic environment0.454 **0.300 **0.164 **
Teacher Overall
feeling		Communication & leisureDeep
thinking
Physical space0.600 **0.2610.856 **
Humanistic environment0.488 *0.4370.666 **
Note: ** p < 0.01, * p < 0.05.
Table
Table 6. Standardized regression coefficient table of different creative behaviors and overall feelings.
Table 6. Standardized regression coefficient table of different creative behaviors and overall feelings.
IndependentVariableR2
Satisfaction LevelOverall ComfortConvenience
Chat−0.093−0.0410.158 *0.021
Relaxation0.0140.180 **0.159 **0.091
Academic exchange0.063−0.0190.281 ***0.091
Meditation0.235 ***0.199 **0.0620.173
Interruption0.1090.1330.223 ***0.145
Coherence of thinking0.280 ***0.0610.202 ***0.200
Note: *** p < 0.001. ** p < 0.01. * p < 0.05.
Table
Table 7. Standardized regression coefficient table of different creative behaviors and environmental factors.
Table 7. Standardized regression coefficient table of different creative behaviors and environmental factors.
IndependentVariableR2
Physical SpaceHumanistic Environment
Chat−0.390 ***0.382 ***0.162
Relaxation−0.139 *0.443 ***0.159
Academic exchange −0.1170.368 ***0.109
Meditation0.597 ***−0.0900.315
Interruption0.600 ***−0.115 *0.310
Coherence of thinking0.335 ***0.131 *0.169
Note: *** p < 0.001. * p < 0.05.
Table
Table 8. Standardized regression coefficient table of different creative behaviors and specific environmental factors.
Table 8. Standardized regression coefficient table of different creative behaviors and specific environmental factors.
IndependentVariableR2
AcousticsLightThermal ConditionOdorsOrganization AtmosphereOpennessFree Feeling
Chat−0.333 ***0.064−0.001−0.289 ***0.299 ***−0.0410.282 ***0.162
Relaxation−0.146 *0.117−0.091−0.1230.460 ***0.0510.0920.159
Academic exchange −0.0660.026−0.140−0.0240.325 ***−0.0590.210 ***0.109
Meditation0.518 ***−0.050−0.0630.380 ***−0.0610.056−0.165 **0.315
Interruption0.491 ***0.036−0.168 **0.407 ***−0.054−0.139 **−0.0240.310
Coherence of thinking0.336 ***−0.029−0.059 **0.191 **0.0590.131 *−0.0500.169
Note: *** p < 0.001; ** p < 0.01; * p < 0.05.
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Su, W.; Lu, T.; Su, J.; Wang, M. Subjective Impacts on Knowledge Creation Behavior of Enclosed University Campus in China. Buildings 2023, 13, 1702. https://doi.org/10.3390/buildings13071702

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Su W, Lu T, Su J, Wang M. Subjective Impacts on Knowledge Creation Behavior of Enclosed University Campus in China. Buildings. 2023; 13(7):1702. https://doi.org/10.3390/buildings13071702

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Su, Wanqing, Tianyun Lu, Jianhua Su, and Menghan Wang. 2023. "Subjective Impacts on Knowledge Creation Behavior of Enclosed University Campus in China" Buildings 13, no. 7: 1702. https://doi.org/10.3390/buildings13071702

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