A Study on the Aesthetic Tendency of the YZ Generation in China Toward the Façade Design of Coffee Shop Buildings

Abstract

The number of coffee shops in China is rapidly increasing, and they are becoming a gathering place for young people. In order to enhance their competitiveness, the design of coffee shops has become the core force of competition. To clarify the preferences of young people for coffee shop design, this study takes the most intuitive exposure of consumers to building façades as the starting point. Based on the façade model in the previous research, the façade model was reconstructed through expert group discussions. In total, 80 out of 490 design cases were selected and combined with the reconstructed façade model to construct a questionnaire. Then, a questionnaire survey was conducted on 595 Chinese YZ generation members. The results of the classification summary and post hoc multiple comparison analysis showed that façade design was considered an important factor affecting their choices, and if the façade design met their aesthetic preferences, they would visit the store again. In addition, the aesthetic preferences of the YZ generation for coffee shop façade design, including different façade shapes, contours, visual forms, functional forms, decorative material types, textures, tones, brightness, and color matching methods, are consistent. They prefer the modernist style and pursue more visually stimulating exterior design, and this preference does not differ in terms of generational and gender differences. The differences in aesthetic standards for façades are more reflected in income levels. The YZ generation gave a “like” rating to all façade model contents and cases, but their aesthetic differences in different façade models can still be seen through specific numerical differences.

1. Introduction

The coffee shop industry in China has become one of the emerging fields in the retail industry, and coffee shops are very common in urban areas across the country [1]. In 2023, the scale of China’s coffee industry reached USD 37.12 billion [2], and in the same year, the scale of locally produced tea shops in China reached USD 20.95 billion [3]. According to predictions, the scale of coffee and freshly brewed tea drinks in China is still on the rise, and there is no phenomenon of mutual balance between the two. Their consumer groups often overlap. With the rise in coffee and tea drinking culture in China, especially in big cities, coffee shops have become a new gathering place for young people [4]. Moreover, the younger generation not only pursues the quality of coffee and tea drinks, but also pays attention to the quality of the store environment, decoration style, experience, and service [5].

At the same time, the development of social media has provided effective ways for businesses and brands to attract new customers to their coffee retail business. For example, Starbucks has used social media to influence consumer choices in the Chinese market, not only selling products but also a high-quality lifestyle [6]. Young consumers pursue personalized consumption experiences and hope to express their unique identity and taste by visiting specialty coffee/tea shops (abbreviated as “coffee/tea shops” in subsequent content). Especially for the YZ generation, who grew up with the Internet, they realized the demand for social identity by sharing on social media, which made the Punch in Red Coffee Shop a social currency [7]. This consumption mode has brought about the rise in the culture of taking photos and punching in shops. One of the key points of photography is the environment of the shop, which also makes the design of the shop the key point of improving competitiveness [8]. As the YZ generation has grown, they have gradually become the backbone of social consumption. As a country with a population of about 600 million people in the YZ generation, China’s necessity for research on this group is becoming increasingly prominent.

Visual language, as the most effective form of scientific communication for humans, stimulates visual stimuli to elicit emotional and cognitive responses from consumers toward specific product visual information. It is an important component of brand strategy [9,10,11]. Visual design, as an atmosphere clue, is an important component of the store environment. It enhances the attractiveness of the physical environment, affects customers’ cognitive processes and emotional responses, and increases their willingness to visit [12,13,14]. From the overall perspective of the store, the façade is usually the first and most intuitive architectural feature that consumers come into contact with. Therefore, from a design perspective, the façade is an important aesthetic tool that attracts customers and showcases the corporate image [15]. By incorporating attractive architectural elements into the façade design, consumers’ willingness to enter commercial spaces can be enhanced.

Currently, with the rapid growth of tea shops, the façade design of coffee and tea shops has shown a very diverse trend. In the face of changes in consumer groups, lifestyles, and aesthetic styles, what kind of façade design is attractive to them has become a question worth studying. The purpose of this study is to clarify the frequency of use, selection criteria, and basic evaluation of the façade of coffee shops by YZ in China; clarify the modeling, contour, visual, and functional forms of the façade for the YZ generation; clarify the type and texture of façade decorative materials; clarify the hue, brightness, and color matching method of the façade; clarify the aesthetic preferences for façade decorative elements; and from the perspectives of generation, gender, and income, analyze whether there are differences in their aesthetic preferences for the façade design of coffee shop buildings in terms of modeling form, contour form, visual form, functional form, type and texture of decorative materials, hue, color brightness, color matching methods, and façade decorative elements. If there are aesthetic differences, this study will analyze and explain the specific differences.

2. Literature Review

2.1. Definition and Function of Building Façade

The root of ‘façade’ comes from ‘faces’ or ‘facia’, which, respectively, represent ‘front’ and ‘face’, corresponding to the word ‘appearance’ in English [16]. Therefore, when discussing the ‘façade’ of a building, it usually refers to the side facing the street. And the façade is mainly an intermediary connecting the internal structure of the building and the external world, while also distinguishing between the public and private domains. This identity often corresponds to two different emotions in a façade, namely public responsibility and the expression of self-emotions [17].

In history, there are many names similar to architectural façades, and the ‘Envelope’ is the oldest architectural concept. It refers to the enclosing structure of a building, which is the interface between the external world and the internal space. It divides ownership and restrictions and determines form and image [18]. The concept of ‘Curtain Wall’ mainly originated in the 1970s. It is separate from the load-bearing system of buildings and is an independent frame component, usually suspended between floors [19]. Another term widely used in the mid-20th century was ‘Skin’, which was originally created to distinguish between the cladding and structural ‘skeleton’ of buildings. Recently, it has begun to be associated with the concept of intelligent environmental systems. The difference between ‘Skin’ and façade is that the building façade is the common surface of the building, conveying specific information, while ‘Skin’ is more like a fully enclosed system, which is a component of the building or space [20]. Another related term currently used for building façades is ‘surface’. It not only involves the exterior of the building, but also the edges and boundaries, and it is no longer limited to its physical appearance, but a more complex and multidimensional concept that involves multiple relationships and interactions between the building and its environment [21].

Overall, research on façades is increasingly inclined to consider them as independent themes in architectural design. Once the façade of a building is independent of its structure, it can be replaced more freely like clothing, giving the building a ‘free façade’ [22].

Rob Krier believes that the façade is not designed to truly meet the requirements of internal spatial organization in buildings, but rather to consider the cultural conditions during construction, creating decorative and original architectural elements that can convey the functionality and meaning of the building [17]. With the rethinking of the differences between building structure and decoration, function and decoration, form and façade, façade no longer has the status of a decorative element, but has become an entity in itself [21]. It is a visual representation of the design concepts, usage, procedures, structures, services, or construction processes of a building [23].

Throughout the 20th century, it can be said that building façades have always been experimental and innovative places, and this phenomenon continues to this day, resulting in the construction of a large number of architectural images. As an independent entity, the façade not only showcases the design quality and overall structure of the building surface but also influences the interior design and experience [24], and the façade is crucial for establishing architectural identity [25]. On the one hand, they provide users and passersby with various experiences and visual ideas about the city through visual elements [26]. By using symbolic elements of culture, history, and other aspects in a façade, it can evoke emotional reactions from people [27]. The building façade is a symbol of urban culture and history. As a bridge between the past and the future, it not only affects people’s perception of urban spaces but is also crucial for maintaining the historical identity of the city [28].

In addition, a façade has many practical uses. According to the theory of Knaack, U. et al., a building façade is not only used to define the appearance of a building, but can be used to resist the forces generated by wind loads, support its own weight and the weight of other building components, control the amount of sunlight that penetrates buildings, prevent rainwater infiltration, and provide insulation, cold resistance, and sound insulation [29]. In recent years, the keywords “adaptive”, “responsive”, and “dynamic” in building façades have become increasingly frequent. Some architects believe that future buildings will have façades similar to human skin that can respond to constantly changing environmental conditions.

2.2. The Classification Method of Façade

Carmela Cucuzzella et al. classified building façades since 1950 into three major categories based on their main characteristics, including utilitarian façades, which respond to the structure, environment, and function of the building, formal façades, which define the shape of the building, and image façades, which serve a clear purpose for conveying information and images to the audience [30]. Among them, utilitarian façades include structural façades, which reveal the structural system of the building and display its structural components [31], environmental façades, which adapt to different environmental conditions and respond to changes inside and outside buildings to improve environmental efficiency [32], and functional façades, which focus on clearly demonstrating the internal functions of buildings to the public [33].

Formal façades include material façades, which emphasize the consistency between the façade form and the materials used to construct the façade [34], façades resulting from the exterior design, which are independent of the interior of the building and will not have a significant impact on the interior [35], and tectonic façades, which combine materiality with craftsmanship, technology, and culture to create a specific form [36].

Image façades include symbolic façades, which are decorated with factors related to the surrounding culture, society, and history of the building, or façades that reflect regional history, art, culture, tradition, society, etc. [31], and media façades, which project information to the community through parameterized design, can predict and respond to environmental changes, or serve as a dynamic information interface for urban scale [37].

Another theory of façade classification is that of Mohammad Ghomishi and Mahmud Mohd Jusan, based on Gifford R.’s research, who reduced the number of elements in building façades from 54 to 36 and divided them into six categories. Through quantitative research, they compared the aesthetic preferences of architects and non-architects in residential façade design [38,39]. Its specific classification is as follows.

Wall material: glass cladding, metal cladding, brick, stone, concrete. Wall appearance: reflectance, color uniformity. Wall form: stepped stories, regular stories, articulation, triangles, rectangles, square, polygons, circular, shells. Wall texture: uniformity of smoothness, material smoothness, sharp rounded, horizontal lines, vertical lines. Window size, form and balcony size: window size, vertical or horizontal window, square window, rectangular window, circle window, abstract shapes, window to wall, balcony size. Extra decorations: shading, columns, arches, sculpture, cylindrical shapes, plants.

Another classification method includes Mona Sendi’s, which divides the façades of buildings into pre-modern, modern, and post-modern styles based on their historical architectural styles, and focuses on analyzing relevant cases of postmodern building façades under the influence of digital technology. She believes that new digital tools and technologies have introduced new tools for architects to consider different complex forms of modeling, optimization of complex environments, and manufacturing after design [40].

From relevant research, it can be seen that the classification of building façades is usually based on historical styles, core functions, and architectural elements. This study will make further adjustments based on design case studies and group discussions.

2.3. Related Research on Aesthetic Evaluation of Façades

Environmental design can influence consumer behavior, including patronage, amount of time spent, purchase intention, attitude, loyalty, comfort, and satisfaction [41]. Moreover, shaping a landmark building can also influence consumers’ love for the store and their willingness to revisit [42]. For coffee shops, the sensory value of their brand has a significant impact on consumers’ love for the brand and their loyalty to consuming the brand’s products [43]. These all point to the positive role of design in consumption, and also indicate that grasping consumers’ aesthetic preferences in design is of great significance for enhancing the consumption ability of stores.

Aesthetic research has always been an important topic in the field of architecture, as different physical characteristics of buildings can lead to different aesthetic reactions [44]. Hernan, P. C. et al. found through a comparative study of the aesthetic emotions of Renaissance and contemporary design styles that different design styles have different aesthetic characteristics, comprehension abilities, structural features, and emotional features [45]. The evaluation of aesthetic beauty in architecture mainly depends on the influence of pleasure and admiration emotions [44]. For example, circular curved elements in architectural spaces are interpreted as more pleasant and popular than sharp straight elements [46]. In addition, the number of aesthetic design elements, such as the appearance, shape, materials, and color scheme of a building, has a significant impact on improving user satisfaction [47].

In the narrative of architectural history, a traditional and permanent method is called “style and period”, which is a description of the most unique features of that period [48]. The passage of time also confirms that aesthetic pursuits and changes in lifestyle are effective methods for style differentiation. Research has found that even architecture students’ aesthetic perception of architecture is constrained by the times. According to Cirak Yilmaz, M.’s research, the architectural styles that architecture students are currently farthest from are the eclecticism of the Renaissance and Classical periods. What attracts their attention the most is deconstructivist architecture and their common views on deconstructionism are that it is the most beautiful, impressive, original, and exciting [49].

In addition, the design of different styles of façades can also lead to different opinions, and the style, design, and composition of façades have a significant impact on the complexity, familiarity, excitement, and originality of perceptual dimensions [50,51].

It is not difficult to find from the above research that the aesthetic evaluation of architectural design is a complex content that can be carried out in various ways and from different perspectives. For example, Šafárová K et al. conducted a comparative study on the differences in aesthetic design between architects and non-architects using photographs and Likert scales [52]. Sam et al. conducted a study on the aesthetic appeal and dissemination of architectural heritage photographs using a combination of photographs and the Likert scale [53]. From this, it can be found that the comparison of aesthetics and aesthetic differences can be quantified. The focus of this study is to investigate and quantify the aesthetic preferences of the YZ generation in China toward coffee shop façades by combining photos of representative coffee shop façade designs, and to compare aesthetic differences between generations. Therefore, this study drew on the main methods used in the aforementioned research and adopted the form of the Likert scale to conduct research on dimensions such as ‘like’ and ‘dislike’.

2.4. Theory of Generation Division and Characteristics

A generation is a ‘symbolic community’, the division of which is not based on the number of people, but on their common life experiences, which unify them. This community has no clear time boundaries and can reflect the dynamics of changes in customs, behaviors, and types of actions. The life path of a generation is determined by historical events, changes in education methods, changes in lifestyle, the evolution of relationship systems, and the sum of values and life programs [54].

Generations are typically defined as identifiable groups born during the same period and sharing important life events at key stages of the lifecycle [55]. Generally, the divisions between different generations are determined based on timelines. A common classification of generations includes [56] the Silent or Mature Generation (the Builders) (1925–1946); the Baby Boomers, the Hippies, and the Idealists (1943–1964); Generation X, the Post-Baby Boomers, the TV Generation, and the Latchkey Kids (1961–1981); Generation Y and the Generation of the Millennium, or the Millennials (1978–2000); Generation Z and the Post-Millennials or Centennials (1995–2010); and Generation Alpha, or the Touch-Screeners (2010–).

In addition, both Generation Y and Z are technology-savvy and constantly connected to the Internet [57]. Their main communication tools are online, mostly using handphones [58]. This has also brought about their need for timely and quick access to content [59], which has led to their dependence on social media [60]. In addition, the YZ generation also pursues personalization and innovation, with aesthetic appeal and scarcity being the core factors that stimulate their consumption [61]. They also pay close attention to ecological and social issues and are willing to support brands that align with their values [62].

With the entrance of Generation Z into adulthood and the workforce, Generation Y and Generation Z will become the main force in the workplace and the market. According to statistics, by 2020, Generation Z will make up 20% of the workforce [63], while Generation Y and Generation Z together will occupy almost half of the workplace [54]. It can be seen that the necessity of studying the YZ generation is becoming increasingly prominent.

In order to provide a better basis for comparison and understanding for researchers in the same field, this study has chosen the internationally common generational classification method, rather than the generational classification method specific to China.

3. Methods

To provide a detailed explanation of the specific methods used in this study, we have created a detailed research flowchart, as shown in Figure 1, and combined it with textual explanations to help readers better understand the specific research methods used in this study.

Firstly, this study is divided into three stages. The first stage mainly aims to discover the rise in beverage consumption, which has driven the prosperity of tea-drinking store design. This leads to the question “what kind of tea-drinking store design can better attract consumers?”. Due to the fact that tea-drinking store design is a complex and broad system, in order to further implement research and consider the composition of tea-drinking stores and the importance of commercial space façade in shaping brand image, the research topic has been determined as the exterior façade of the building. On this basis, the core objective of this study has been clarified.

Secondly, based on a clear research objective, this study conducted research on the research models, methods, and findings related to building façades. After forming a certain theoretical foundation, we began to collect façade materials from nearly 10 years of beverage space design cases in tea-drinking stores through a design website. A total of 490 cases were collected. Through horizontal comparison, it can be clearly seen that due to the short time span of the cases, the style of the façade is relatively concentrated. In addition, the focus of this research is on the aesthetic preferences of the Chinese youth group toward façades. Therefore, the analysis model construction focuses on architectural elements such as façade style, form, material, and color. And considering that the style in the case is relatively concentrated, the analysis model of this study will blur the analysis of style. Based on theoretical research and case analysis, we have developed a preliminary analysis model and adjusted it through focus group discussions (FGDs). At the same time, in order to help the sample subjects better understand the questionnaire content, this study considers conducting the survey through a combination of text and images. We also utilized the method of FGD to discuss specific questionnaires and design legends that matched the questions, and exported the complete questionnaire content, as shown in Appendix A. Considering the diversity and complexity of China’s regions, as well as the uncertainty brought about by the mobility of the YZ generation, this study did not include regional surveys in the analysis dimension.

It is worth noting that this questionnaire is divided into six parts. Among them, Q1, Q2, Q3, and Q4 are surveys on the age stage, gender, occupation, and income status of the sample subjects; Q5, Q6, Q7, and Q8 are surveys on the frequency of coffee shops usage, selection criteria, and basic evaluation of the façade of the sample subjects; Q9, Q10, Q11, and Q12, respectively, investigated the design preferences for the façade’s modeling form, contour form, visual form, and functional form; Q13 and Q14 investigated the types of façade decorative materials and design preferences for texture; Q15, Q16, and Q17 researched the hue, color brightness, and color matching preferences of the façade; Q18 investigates the design preferences of façade decorative elements.

Thirdly, after collecting the survey questionnaire, this study will first use reliability and validity analysis methods to verify the authenticity and effectiveness of the questionnaire. Afterward, the basic information of the sample subjects, namely Q1 to Q4 in the questionnaire, was analyzed through frequency analysis. The third step is to use the methods of classification summary and post hoc multiple comparison analysis, taking generation, gender, and monthly income status as prerequisites, to analyze the problems including Q5, Q6, Q7, and Q8, and explain and interpret the results of the analysis. In step four, we use the methods of classification summary and post hoc multiple analysis, taking generation, gender, and monthly income status as prerequisites, analyze the problems including Q9, Q10, Q11, Q12, Q13, Q14, Q15, Q16, Q17, and Q18, and explain and interpret the results of the analysis. In step five, we summarize the results of the questionnaire analysis, provide an introduction, and derive the conclusions of this study.

4. Results

The questionnaire contained 18 topics and 55 items, and the questionnaire answering time was no more than five minutes, which ensured that the information was collected within a reasonable time frame. A total of 528 questionnaires were collected in this research, and in order to ensure the authenticity and validity of the questionnaire results, this study first analyzed the results of the questionnaire for reliability and validity, and the results of the analysis are shown in

Table 1. Reliability statistics (Cronbach’s alpha).

Items	Corrected Item–Total Correlation (CITC)	Cronbach’s Alpha If Item Deleted	Cronbach α
Q1	0.034	0.908	0.907
Q2	0.042	0.908
Q3	−0.062	0.931
Q4	−0.020	0.910
Q5	0.023	0.910
Q6-1	0.620	0.902
Q6-2	0.652	0.901
Q6-3	0.543	0.903
Q6-4	0.633	0.902
Q6-5	0.525	0.903
Q7	0.546	0.903
Q8	0.453	0.904
Q9-1	0.501	0.904
Q9-2	0.455	0.904
Q9-3	0.565	0.903
Q10-1	0.507	0.904
Q10-2	0.571	0.903
Q10-3	0.567	0.903
Q11-1	0.581	0.903
Q11-2	0.605	0.902
Q11-3	0.582	0.903
Q12-1	0.569	0.903
Q12-2	0.530	0.903
Q13-1	0.657	0.901
Q13-2	0.541	0.903
Q14-1	0.535	0.903
Q14-2	0. 546	0.903
Q15-1	0.620	0.902
Q15-2	0.485	0.904
Q16-1	0.584	0.902
Q16-2	0.505	0.904
Q17-1	0.586	0.902
Q17-2	0.544	0.903
Q18-1	0.595	0.902
Q18-2	0.540	0.903

Remarks: Cronbach α (standardized) = 0.921.

and

Table 2. Validity Analysis.

Items	Factor Loadings								Communality (Common Variance)
	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5	Factor 6	Factor 7	Factor 8
Q1	−0.111	0.060	0.073	−0.120	0.231	0.733	−0.062	0.040	0.633
Q2	−0.008	−0.033	0.044	−0.044	−0.024	0.026	0.125	0.871	0.778
Q3	0.003	−0.254	0.182	0.139	−0.127	0.642	0.206	0.004	0.587
Q4	−0.072	−0.082	0.257	−0.027	0.097	−0.770	−0.147	0.012	0.703
Q5	−0.038	−0.018	0.021	0.077	0.055	−0.059	0.822	0.111	0.702
Q6-1	0.465	0.240	0.307	0.229	0.196	−0.045	−0.041	0.007	0.462
Q6-2	0.581	0.103	0.377	0.212	0.220	−0.008	−0.103	0.090	0.602
Q6-3	0.575	0.200	0.063	0.247	0.092	−0.018	−0.122	0.085	0.467
Q6-4	0.596	0.134	0.262	0.295	0.151	−0.037	−0.024	0.021	0.554
Q6-5	0.233	0.162	0.522	0.245	0.141	0.023	−0.209	−0.023	0.478
Q7	0.258	0.449	0.094	0.151	0.406	−0.086	−0.128	0.142	0.509
Q8	0.309	0.383	−0.015	0.101	0.286	−0.061	0.324	0.097	0.452
Q9-1	0.192	0.095	0.565	0.269	0.213	−0.066	0.057	−0.054	0.493
Q9-2	0.521	−0.000	0.158	−0.000	0.413	−0.044	0.050	0.009	0.472
Q9-3	0.266	0.304	0.582	0.062	0.045	0.031	0.126	0.072	0.530
Q10-1	0.259	0.269	0.056	0.421	0.297	−0.056	−0.316	0.259	0.578
Q10-2	0.566	0.297	0.176	0.145	0.007	−0.005	−0.016	−0.048	0.463
Q10-3	0.394	0.456	0.257	−0.003	0.135	−0.023	−0.005	0.022	0.448
Q11-1	0.391	0.259	0.352	0.137	0.132	0.082	−0.106	0.228	0.450
Q11-2	0.459	0.286	0.300	0.124	0.140	0.091	0.058	0.114	0.442
Q11-3	0.262	0.377	0.298	0.188	0.286	0.104	0.105	−0.031	0.440
Q12-1	0.191	0.677	0.105	0.173	0.201	0.009	−0.111	−0.015	0.589
Q12-2	0.229	0.577	0.157	0.182	0.064	−0.056	−0.068	−0.012	0.455
Q13-1	0.563	0.260	0.275	0.272	0.082	−0.071	0.033	−0.034	0.548
Q13-2	0.715	0.236	0.045	−0.016	0.089	0.008	0.059	−0.068	0.585
Q14-1	0.290	0.280	0.152	0.518	−0.012	0.038	−0.006	0.256	0.521
Q14-2	0.392	0.355	0.295	0.276	−0.200	0.108	0.170	0.063	0.528
Q15-1	0.340	0.349	0.254	0.187	0.399	0.061	0.127	−0.044	0.518
Q15-2	0.182	0.220	0.168	0.126	0.718	0.057	0.064	−0.054	0.651
Q16-1	0.364	0.466	0.144	0.226	0.120	−0.005	0.133	0.045	0.455
Q16-2	0.064	0.519	0.245	0.360	0.036	0.007	0.161	−0.003	0.490
Q17-1	0.313	0.482	0.373	0.082	0.091	−0.001	−0.058	−0.115	0.500
Q17-2	0.341	0.408	0.502	−0.137	0.002	−0.085	0.035	0.162	0.588
Q18-1	0.337	0.368	0.143	0.427	0.119	0.029	0.089	−0.031	0.475
Q18-2	0.219	0.210	0.182	0.660	0.187	0.002	0.121	−0.153	0.634
Eigenvalue (Unrotated)	10.956	1.655	1.309	1.143	0.989	0.966	0.900	0.877	-
Explained Variance (Unrotated)	31.302%	4.728%	3.741%	3.266%	2.827%	2.760%	2.572%	2.507%	-
Cumulative Explained Variance (Unrotated)	31.302%	36.030%	39.771%	43.037%	45.864%	48.624%	51.196%	53.703%	-
Eigenvalue (Rotated)	4.644	3.689	2.624	2.080	1.758	1.635	1.240	1.109	-
Explained Variance (Rotated)	13.270%	10.540%	7.497%	5.942%	5.024%	4.672%	3.543%	3.167%	-
Cumulative Explained Variance (Rotated)	13.270%	23.810%	31.307%	37.249%	42.273%	46.946%	50.489%	53.656%	-
KMO	0.960								-
Bartlett's Test of Sphericity	5980.164								-
df	595								-
p value	0.000								-

Note: Blue numbers indicate the absolute value of the loading > 0.4.

. It is worth noting that this questionnaire survey was conducted in compliance with ethical and moral permits.

Table 1 shows that Cronbach’s alpha reliability coefficient is 0.907, which is greater than 0.9, indicating that the data of this study are highly reliable and can be used for further analysis.

In the table above, all research items have commonalities greater than 0.4, indicating that information can be effectively extracted. Additionally, the KMO is 0.960, which is greater than 0.6, indicating the data can effectively extract information. Moreover, the explained variance for the eight factors are 13.270%, 10.540%, 7.497%, 5.942%, 5.024%, 4.672%, 3.543%, and 3.167%, and the cumulative explained variance (rotated) is 53.656%, which is greater than 50%.

4.1. Basic Information of the Research Subjects and Their Basic Understanding of the Façade

After clarifying that the questionnaire had good reliability and validity, this study analyzed the basic information of the subjects who participated in this research through the frequency analysis method, and the results are shown in

Table 3. Frequency analysis of basic information of sample subjects.

Items	Option	Frequency	Percent (%)	Cumulative Percent (%)
Q1: What is the age stage of your birth?	Born between approximately 1980 and 1995 (Generation Y)	354	67.05	67.05
	Born between approximately 1995 and 2010 (Generation Z)	174	32.95	100.00
Q2: What is your gender?	Male	255	48.30	48.30
	Female	273	51.70	100.00
Q3: What is your profession?	Public officials	19	3.60	3.60
	Education positions	32	6.06	9.66
	Medical and health positions	39	7.39	17.05
	Technical and R&D positions	40	7.58	24.62
	Management and administrative positions	42	7.95	32.58
	Sales and Marketing Positions	89	16.86	49.43
	Financial and insurance positions	44	8.33	57.77
	Service and Retail Jobs	43	8.14	65.91
	Creative and artistic positions	29	5.49	71.40
	Freelancing and Self-employment	81	15.34	86.74
	students	52	9.85	96.59
	Other professions (farmers, transportation personnel, etc.)	18	3.41	100.00
Q4: What is your monthly income? (Students can calculate based on monthly living expenses)	Less than 3000 yuan (low income)	52	9.85	9.85
	3000~5000 yuan (lower income)	61	11.55	21.40
	5000~10,000 yuan (middle income)	254	48.11	69.51
	10,000~20,000 yuan (higher income)	115	21.78	91.29
	Over 20,000 yuan (high income)	46	8.71	100.00
Total		528	100.0	100.0

.

From Table 3, it can be seen that among the sample subjects participating in this study, the proportion of Generation Y is 67.05%, and the proportion of Generation Z is 32.95%, indicating that the proportion of Generation Y in the sample is significantly higher than that of Generation Z. In terms of gender, males account for 48.3% and females account for 51.7%, with a relatively even proportion. In terms of occupation, public officials account for 3.60%, education positions account for 6.06%, medical and health positions account for 7.39%, technical and R&D positions account for 7.58%, management and administrative positions account for 7.95%, sales and marketing positions account for 16.86%, financial and insurance positions account for 8.33%, service and retail jobs accounts for 8.14%, creative and artistic positions account for 5.49%, freelancing and self-employment accounts for 15.34%, students account for 9.85%, and other professions (farmers, transportation personnel, etc.) account for 3.41%. From this, it can be seen that among the sample subjects participating in the survey, ‘public officials’ and ‘other professions (farmers, transportation personnel, etc.)’ account for a relatively small proportion, ‘sales and marketing positions’ and ‘freelancing and self-employment’ account for a relatively large proportion, and the proportion of other professions is relatively even. From the perspective of income level, among the sample subjects participating in this survey, the low-income population accounted for 9.85%, the lower-income population accounted for 11.55%, the middle-income population accounted for 48.11%, the higher-income population accounted for 21.78%, and the high-income population accounted for 8.71%. That is to say, nearly 70% of the subjects participating in the survey were in a state of middle income or higher income.

To clarify the frequency of the Chinese YZ generation going to coffee shops, the main factors for choosing coffee shops, and the basic cognitive status of façade, this study used a categorical summary method to analyze Q5, Q6, Q7, and Q8. To further subdivide the cognitive status of the YZ generation, we classified and summarized them from three aspects: generation, gender, and income status. The results of the generation category analysis are shown in

Table 4. Categorical summary by generation type.

Items	Q1: What Is the Age Stage of Your Birth?		Total
	Generation Y	Generation Z
Q5: Do you often go to tea-drinking stores?	3.740	3.621	3.701
Q6-1: the environment of a tea-drinking store (design, atmosphere, etc.)	4.000	4.040	4.013
Q6-2: brand	3.610	3.690	3.636
Q6-3: price	3.799	3.747	3.782
Q6-4: taste	3.701	3.603	3.669
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	3.797	3.948	3.847
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	3.797	3.816	3.803
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	3.797	3.730	3.775

.

From Table 4, it can be seen that the YZ generation in China “often” goes to coffee shops, while Generation Y goes slightly more frequently than Generation Z. When choosing a coffee shop, Generation Y ranks the importance of various factors as ‘environment of a tea-drinking store’, ‘price’, ‘social evaluation’, ‘taste’, and ‘brand’. The ranking of various factors by Generation Z is ‘environment of a tea-drinking store’, ‘social evaluation’, ‘price’, ‘brand’, and ‘taste’. From this, it can be seen that they all believe that the ‘environment of a tea-drinking store’ is a very important factor, but the difference is that Generation Y values ‘price’ more, while Generation Z values ‘social evaluation’ more. Generation Y values ‘brand’ the least, while Generation Z values ‘taste’ the least. The YZ generation believes that façade design is an important factor influencing their choices. Compared to others, Generation Z performs more prominently. In addition, the YZ generation believes that they will revisit the store again because the façade design meets their aesthetic requirements. In comparison, the trend of Generation Y is more pronounced.

In order to further clarify whether there are significant cognitive differences among the YZ generation regarding the above-mentioned issues, this study analyzed the issues related to Q5, Q6, Q7, and Q8 through post hoc multiple comparative analysis. The analysis results are shown in

Table 5. One-way ANOVA by generation type.

	Q1: What Is the Age Stage of Your Birth? (Mean ± S.D.)		F	p Value
	Generation Y (n = 354)	Generation Z (n = 174)
Q5: Do you often go to tea-drinking stores?	3.74 ± 1.03	3.62 ± 1.12	1.486	0.223
Q6-1: the environment of a tea-drinking store (design, atmosphere, etc.)	4.00 ± 1.02	4.04 ± 1.04	0.180	0.672
Q6-2: brand	3.61 ± 1.16	3.69 ± 1.18	0.543	0.461
Q6-3: price	3.80 ± 1.07	3.75 ± 1.03	0.286	0.593
Q6-4: taste	3.70 ± 1.12	3.60 ± 1.13	0.867	0.352
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	3.80 ± 1.08	3.95 ± 1.05	2.337	0.127
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	3.80 ± 1.05	3.82 ± 1.19	0.037	0.848
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	3.80 ± 1.01	3.73 ± 1.16	0.460	0.498

* p < 0.05 ** p < 0.01.

.

In Table 5, we use ANOVA to study the differences in Q1 across a total of eight items: Q5, Q6-1, Q6-2, Q6-3, Q6-4, Q6-5, Q7, and Q8. The table indicates Q1 do not show significance for Q5, Q6-1, Q6-2, Q6-3, Q6-4, Q6-5, Q7, and Q8 (p > 0.05), indicating that Q1 exhibits consistency with no differences. A post hoc test is not necessary.

According to the data in

Table 6. Categorical summary by gender type.

Items	Q2: What Is Your Gender?		Total
	Male	Female
Q5: Do you often go to tea-drinking stores?	3.600	3.795	3.701
Q6-1: the environment of a tea-drinking store (design, atmosphere, etc.)	3.996	4.029	4.013
Q6-2: brand	3.569	3.700	3.636
Q6-3: price	3.776	3.788	3.782
Q6-4: taste	3.620	3.714	3.669
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	3.831	3.861	3.847
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	3.788	3.817	3.803
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	3.729	3.817	3.775

above, the results of classifying and summarizing from a gender perspective show that women visit coffee shops slightly more frequently than men. When choosing a coffee shop, both men and women rank the importance of various factors such as ‘the environment of a tea-drinking store’, ‘social evaluation’, ‘price’, ‘taste’, and ‘brand’. The difference is that women consider ‘the environment of a tea-drinking store’ to be a very important factor, while men consider ‘the environment of a tea-drinking store’ to be an important factor. Both men and women believe that façade design is an important factor influencing their choices. Compared to others, women exhibit more pronounced behavior. In addition, both men and women believe that they will revisit this store because the façade design meets their aesthetic requirements. By comparison, this tendency is more pronounced among women.

The results of the gender category analysis are shown in Table 6.

In order to further clarify whether there are significant cognitive differences between males and females regarding the above issues, this study analyzed Q5-, Q6-, Q7-, and Q8-related issues through post hoc comparative analysis. The results are shown in

Table 7. One-way ANOVA by gender type.

	Q2: What Is Your Gender? (Mean ± S.D.)		F	p Value
	Male (n = 255)	Female (n = 273)
Q5: Do you often go to tea-drinking stores?	3.60 ± 1.05	3.79 ± 1.06	4.496	0.034 *
Q6-1: the environment of a tea-drinking store (design, atmosphere, etc.)	4.00 ± 1.00	4.03 ± 1.05	0.139	0.710
Q6-2: brand	3.57 ± 1.18	3.70 ± 1.14	1.672	0.197
Q6-3: price	3.78 ± 1.08	3.79 ± 1.04	0.014	0.904
Q6-4: taste	3.62 ± 1.17	3.71 ± 1.08	0.931	0.335
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	3.83 ± 1.08	3.86 ± 1.07	0.099	0.753
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	3.79 ± 1.12	3.82 ± 1.08	0.090	0.765
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	3.73 ± 1.10	3.82 ± 1.02	0.894	0.345

* p < 0.05 ** p < 0.01.

.

In Table 7, we use ANOVA to study the differences in Q2 across a total of eight items: Q5, Q6-1, Q6-2, Q6-3, Q6-4, Q6-5, Q7, Q8. The table indicates that Q2 does not show significance for a total of seven items—Q6-1, Q6-2, Q6-3, Q6-4, Q6-5, Q7, Q8 (p > 0.05)—indicating that Q2 exhibits consistency with no differences. A post hoc test is not necessary. Additionally, Q2 shows significance for a total of one item of Q5 (p < 0.05), indicating differences among the samples of Q2 for Q5; thus, a post hoc test can be conducted. The analysis results are shown in

Table 8. Post hoc multiple comparison by gender type.

	(I) Name	(J) Name	(I) Mean	(J) Mean	D-Value (I-J)	p
Q5: Do you often go to tea-drinking stores?	Male	Female	3.600	3.795	−0.195	0.034 *
Q6-1: the environment of a tea-drinking store (design, atmosphere, etc.)	Male	Female	3.996	4.029	−0.033	0.710
Q6-2: brand	Male	Female	3.569	3.700	−0.131	0.197
Q6-3: price	Male	Female	3.776	3.788	−0.011	0.904
Q6-4: taste	Male	Female	3.620	3.714	−0.095	0.335
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	Male	Female	3.831	3.861	−0.029	0.753
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	Male	Female	3.788	3.817	−0.029	0.765
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	Male	Female	3.729	3.817	−0.087	0.345

* p < 0.05 ** p < 0.01.

.

The ANOVA results indicate that Q2 exhibits differences for Q5. Specifically, the LSD will be conducted; Q2 has a significant difference at the 0.05 level for Q5 (F = 4.496, p = 0.034). The mean for males (3.60) is significantly lower than the mean for females (3.79).

Table 9. Categorical summary by monthly income.

Items	Q4: What Is Your Monthly Income?					Total
	Low Income	Lower Income	Middle Income	Higher Income	High Income
Q5: Do you often go to coffee shops?	3.365	4.164	3.681	3.757	3.435	3.701
Q6-1: the environment of a coffee shop (design, atmosphere, etc.)	4.038	4.197	3.795	4.287	4.261	4.013
Q6-2: brand	3.712	3.590	3.512	3.843	3.783	3.636
Q6-3: price	3.827	3.787	3.736	3.835	3.848	3.782
Q6-4: taste	3.712	3.705	3.618	3.678	3.826	3.669
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	3.923	3.803	3.677	4.148	4.000	3.847
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	3.750	3.951	3.634	4.009	4.087	3.803
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	3.577	4.148	3.713	3.826	3.717	3.775

in the previous text presents the analysis results classified and summarized from the perspective of income status. It is worth noting that the lower-income group in the YZ generation has the highest frequency of visiting coffee shops, almost every day. Except for the middle-income group, all other income groups consider the factor ‘environment of a coffee shop’ to be very important. Besides the middle-income group, all other income groups consider ‘social evaluation’ as the second most important factor, while the middle-income group considers ‘price’ as the second most important factor. In addition, high-income groups and higher-income groups consider façade design to be a very important factor influencing their choices. Lower-income groups believe that they will definitely visit this store again because the façade design meets their aesthetic requirements.

The results of the monthly income category analysis are shown in Table 9.

In order to further clarify whether there are significant cognitive differences among different income groups regarding the above issues, this study analyzed the issues related to Q5, Q6, Q7, and Q8 through post hoc multiple comparative analysis. The results are shown in

Table 10. One-way ANOVA by monthly income.

	Q4: What Is Your Monthly Income? (Mean ± S.D.)					F	p Value
	Low Income	Lower Income	Middle Income	Higher Income	High Income
Q5: Do you often go to tea-drinking stores?	3.37 ± 1.16	4.16 ± 0.84	3.68 ± 1.02	3.76 ± 1.07	3.43 ± 1.20	5.212	0.000 **
Q6-1: the environment of a tea-drinking store (design, atmosphere, etc.)	4.04 ± 1.08	4.20 ± 0.91	3.80 ± 1.12	4.29 ± 0.78	4.26 ± 0.85	6.345	0.000 **
Q6-2: brand	3.71 ± 1.23	3.59 ± 0.90	3.51 ± 1.26	3.84 ± 1.01	3.78 ± 1.19	1.910	0.107
Q6-3: price	3.84 ± 1.18	3.79 ± 0.90	3.74 ± 1.09	3.83 ± 1.06	3.85 ± 0.94	0.258	0.905
Q6-4: taste	3.71 ± 1.21	3.70 ± 1.09	3.62 ± 1.21	3.68 ± 1.00	3.83 ± 0.93	0.387	0.818
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	3.92 ± 1.03	3.80 ± 1.09	3.68 ± 1.16	4.15 ± 0.88	4.00 ± 0.89	4.280	0.002 **
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	3.75 ± 1.25	3.95 ± 0.90	3.63 ± 1.18	4.01 ± 0.92	4.09 ± 0.89	3.675	0.006 **
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	3.58 ± 1.21	4.15 ± 0.87	3.71 ± 1.05	3.83 ± 1.05	3.72 ± 1.13	2.683	0.031 *

* p < 0.05 ** p < 0.01.

.

In Table 10, we use ANOVA to study the differences in Q4 across a total of eight items: Q5, Q6-1, Q6-2, Q6-3, Q6-4, Q6-5, Q7, and Q8. The table indicates that Q4 does not show significance for a total of three items—Q6-2, Q6-3, and Q6-4 (p > 0.05)—indicating that Q4 exhibits consistency with no differences. A post hoc test is not necessary. Additionally, Q4 shows significance for a total of five items—Q5, Q6-1, Q6-5, Q7, Q8 (p < 0.05) —indicating differences among the samples of Q4 for Q5, Q6-1, Q6-5, Q7, and Q8; thus, a post hoc test can be conducted.

The ANOVA results indicate that Q4 exhibits differences for Q5, Q6-1, Q6-5, Q7, and Q8. Specifically, the LSD will be conducted: Q4 has a significant difference at the 0.01 level for Q5 (F = 5.212, p = 0.000). The comparison with significant differences is lower income > low income; middle income > low income; higher income > low income; lower income > middle income; lower income > higher income; lower income > high income. This indicates that the frequency of lower-income groups going to coffee shops is significantly higher than that of other income groups.

Q4 has a significant difference at the 0.01 level for Q6-1 (F = 6.345, p = 0.000). The comparison with significant differences is lower income > middle income; higher income > middle income; high income > middle income. This indicates that the middle-income group is much less concerned about the coffee shop environment than the lower-income group, higher-income group, and high-income group.

Q4 has a significant difference at the 0.01 level for Q6-5 (F = 4.280, p = 0.002). The comparison with significant differences is higher income > lower income; higher income > middle income. This indicates that higher-income groups have a significantly higher recognition of the importance of social evaluation than lower and middle-income groups.

Q4 has a significant difference at the 0.01 level for Q7 (F = 3.675, p = 0.006). The comparison with significant differences is lower income > middle income; higher income > middle income; high income > middle income. This indicates that lower, higher, and high-income groups have a significantly higher level of identification with exterior design as an important factor in choosing a coffee shop compared to the middle-income group.

The specific data results are shown in

Table 11. Post-hoc multiple comparison by monthly income.

	(I) Name	(J) Name	(I) Mean	(J) Mean	D-Value (I-J)	p
Q5: Do you often go to tea-drinking stores?	low income	lower income	3.365	4.164	−0.799	0.000 **
	low income	middle income	3.365	3.681	−0.316	0.047 *
	low income	higher income	3.365	3.757	−0.391	0.025 *
	low income	high income	3.365	3.435	−0.069	0.742
	lower income	middle income	4.164	3.681	0.483	0.001 **
	lower income	higher income	4.164	3.757	0.407	0.014 *
	lower income	high income	4.164	3.435	0.729	0.000 **
	middle income	higher income	3.681	3.757	−0.075	0.520
	middle income	high income	3.681	3.435	0.246	0.141
	higher income	high income	3.757	3.435	0.322	0.077
Q6 1: the environment of a tea-drinking store (design, atmosphere, etc.)	low income	lower income	4.038	4.197	−0.158	0.404
	low income	middle income	4.038	3.795	0.423	0.112
	low income	higher income	4.038	4.287	−0.248	0.139
	low income	high income	4.038	4.261	−0.222	0.274
	lower income	middle income	4.197	3.795	0.401	0.005 **
	lower income	higher income	4.197	4.287	−0.090	0.571
	lower income	high income	4.197	4.261	−0.064	0.744
	middle income	higher income	3.795	4.282	−0.492	0.000 **
	middle income	high income	3.795	4.261	−0.466	0.004 **
	higher income	high income	4.287	4.261	0.026	0.882
Q6-2: brand	low income	lower income	3.712	3.590	0.121	0.580
	low income	middle income	3.712	3.512	0.200	0.259
	low income	higher income	3.712	3.843	−0.132	0.496
	low income	high income	3.712	3.783	−0.071	0.762
	lower income	middle income	3.590	3.512	0.078	0.636
	lower income	higher income	3.590	3.843	−0.253	0.169
	lower income	high income	3.590	3.783	−0.192	0.396
	middle income	higher income	3.512	3.843	−0.332	0.011 *
	middle income	high income	3.512	3.783	−0.271	0.146
	higher income	high income	3.843	3.783	0.061	0.764
Q6-3: price	low income	lower income	3.827	3.787	0.040	0.841
	low income	middle income	3.827	3.736	0.091	0.574
	low income	higher income	3.827	3.835	−0.008	0.965
	low income	high income	3.827	3.848	−0.021	0.922
	lower income	middle income	3.787	3.736	0.051	0.737
	lower income	higher income	3.787	3.835	−0.048	0.775
	lower income	high income	3.787	3.848	−0.061	0.768
	middle income	higher income	3.736	3.835	−0.099	0.408
	middle income	high income	3.736	3.848	−0.112	0.511
	higher income	high income	3.835	3.848	−0.013	0.944
Q6-4: taste	low income	lower income	3.712	3.705	0.007	0.975
	low income	middle income	3.712	3.618	0.093	0.587
	low income	higher income	3.712	3.678	0.033	0.860
	low income	high income	3.712	3.826	−0.115	0.617
	lower income	middle income	3.705	3.618	0.087	0.590
	lower income	higher income	3.705	3.678	0.027	0.882
	lower income	high income	3.705	3.826	−0.121	0.583
	middle income	higher income	3.618	3.678	−0.060	0.636
	middle income	high income	3.618	3.826	−0.208	0.251
	higher income	high income	3.678	3.826	−0.148	0.453
Q6-5: social evaluation (online evaluation, friend recommendations, etc.)	low income	lower income	3.923	3.803	0.120	0.549
	low income	middle income	3.923	3.677	0.246	0.128
	low income	higher income	3.923	4.148	−0.225	0.205
	low income	high income	3.923	4.000	−0.077	0.720
	lower income	middle income	3.803	3.677	0.126	0.404
	lower income	higher income	3.803	4.148	−0.345	0.041 *
	lower income	high income	3.803	4.000	−0.197	0.342
	middle income	higher income	3.677	4.148	−0.471	0.000 **
	middle income	high income	3.677	4.000	−0.323	0.058
	higher income	high income	4.148	4.000	0.148	0.424
Q7: Is the façade design of a coffee shop an important factor that influences your choice?	low income	lower income	3.750	3.951	−0.201	0.327
	low income	middle income	3.750	3.634	0.116	0.482
	low income	higher income	3.750	4.009	−0.259	0.154
	low income	high income	3.750	4.087	−0.337	0.126
	lower income	middle income	3.951	3.634	0.317	0.041 *
	lower income	higher income	3.951	4.009	−0.058	0.737
	lower income	high income	3.951	4.087	−0.136	0.521
	middle income	higher income	3.634	4.009	−0.375	0.002 **
	middle income	high income	3.634	4.087	−0.453	0.009 **
	higher income	high income	4.009	4.087	−0.078	0.680
Q8: Would you visit this shop again because the façade design of the coffee shops conforms to your aesthetic preferences?	low income	lower income	3.577	4.148	−0.571	0.004 **
	low income	middle income	3.577	3.713	−0.136	0.399
	low income	higher income	3.577	3.826	−0.249	0.158
	low income	high income	3.577	3.717	−0.140	0.511
	lower income	middle income	4.148	3.713	0.435	0.004 **
	lower income	higher income	4.148	3.826	0.321	0.055
	lower income	high income	4.418	3.717	0.430	0.037 *
	middle income	higher income	3.713	3.826	−0.113	0.339
	middle income	high income	3.717	3.717	−0.005	0.977
	higher income	high income	3.826	3.717	0.109	0.555

* p < 0.05 ** p < 0.01.

.

4.2. Aesthetic Preferences for Façade Design of Coffee Shops

The focus of this section is to describe the aesthetic preferences of the YZ generation in China for the façade design of coffee shops. The analysis of issues including Q9, Q10, Q11, Q12, Q13, Q14, Q15, Q16, and Q17 was mainly conducted through the method of categorical summary. The categorical summary of this stage was also divided by generation, gender, and monthly income status. In order to test whether there are significant differences in aesthetic preferences among different generations, genders, and monthly income levels, the results of the above questions were also analyzed using post hoc multiple comparisons. The specific content is as follows.

4.2.1. The Aesthetic Tendency of China’s YZ Generation Toward Façade Design

The data results classified and summarized by generation category are shown in

Table 12. Categorical summary by generation type.

Items	Q1: What Is the Age Stage of Your Birth?		Total
	Generation Y	Generation Z
Q9-1: Concise, geometric façade	3.997	3.971	3.989
Q9-2: Complex, structurally and formally rich façade	3.927	3.897	3.917
Q9-3: Historic, updated façade design	3.706	3.776	3.729
Q10-1: Completely independent outer contour form	3.938	3.943	3.939
Q10-2: Semi-independent outer contour form	3.684	3.672	3.680
Q10-3: Non independent outer contour form	3.845	3.805	3.831
Q11-1: Completely transparent visual form	3.836	3.908	3.860
Q11-2: Semi-transparent visual form	3.613	3.753	3.659
Q11-3: Completely opaque visual form	3.675	3.799	3.716
Q12-1: Externally equipped with leisure functions	3.624	3.690	3.646
Q12-2: There is no leisure function set externally	3.655	3.615	3.642
Q13-1: Natural-textured materials	3.774	3.667	3.739
Q13-2: Modern-textured materials	3.876	3.874	3.875
Q14-1: Rough-textured materials	3.607	3.626	3.614
Q14-2: Smooth-textured materials	3.579	3.678	3.612
Q15-1: Colorless series	3.619	3.793	3.676
Q15-2: Colored series	3.723	3.937	3.794
Q16-1: Low brightness color scheme	3.593	3.511	3.566
Q16-2: High brightness color scheme	3.777	3.816	3.790
Q17-1: Single color scheme	3.624	3.684	3.644
Q17-2: Multiple color schemes	3.737	3.609	3.695
Q18-1: Natural elements	3.624	3.615	3.621
Q18-2: Popular elements	3.777	3.782	3.778

.

From the data in the table above, it can be seen that the average values of each item fall within the range of greater than 3 and less than or equal to 4. The YZ generation gave a ‘like’ rating to all the contents and cases in the façade model provided in the questionnaire. However, we can still see the specific differences between the façade models and the aesthetic differences in the YZ generation through the specific numerical differences in each content.

Firstly, Q9 is research on the façade’s modeling form. The research results show that the average value of Q9-1 is 3.989, Generation Y is 3.997, and Generation Z is 3.971; the average value of Q9-2 is 3.917, Generation Y is 3.927, and Generation Z is 3.897; the average value of Q9-3 is 3.729, Generation Y is 3.706, and Generation Z is 3.776. This means that the YZ generation’s preference for the façade’s modeling form is ‘concise, geometric façade’ > ‘complex, structurally and formally rich façade’ > ‘historic, updated façade design’. Among them, Generation Y has a higher preference for ‘concise, geometric façade’ and ‘complex, structurally and formally rich façade’ than Generation Z, while Generation Z has a higher preference for ‘historic, updated façade design’ than Generation Y.

Q10 is research on the contour form of the façade. The research results show that the average value of Q10-1 is 3.939, Generation Y is 3.938, and Generation Z is 3.943. The average value of Q10-2 is 3.680, Generation Y is 3.684, and Generation Z is 3.672. The average value of Q10-3 is 3.805, Generation Y is 3.831, and Generation Z is 3.845. This means that the YZ generation’s preference for contour form is ‘completely independent outer contour form’ > ‘non-independent outer contour form’ > ‘semi-independent outer contour form’. Among them, Generation Y has a higher preference for ‘semi-independent outer contour form’ and ‘non-independent outer contour form’ than Generation Z, while Generation Z has a higher preference for ‘completely independent outer contour form’ than Generation Y.

Q11 is research on the visual form of the façade. The research results show that the average value of Q11-1 is 3.860, Generation Y is 3.836, and Generation Z is 3.908. The research results show that the average value of Q11-2 is 3.659, Generation Y is 3.613, and Generation Z is 3.753. The research results show that the average value of Q11-3 is 3.716, Generation Y is 3.675, and Generation Z is 3.799. This means that the YZ generation’s preference for visual form is ‘completely transparent visual form’ > ‘completely opaque visual form’ > ‘semi-transparent visual form’. Among them, Generation Z has higher preferences for ‘completely transparent visual form’, ‘completely opaque visual form’, and ‘semi-transparent visual form’ than Generation Y.

Q12 is research on the functional form of the façade. The research results show that the average value of Q12-1 is 3.646, Generation Y is 3.624, and Generation Z is 3.690. The research results show that the average value of Q12-2 is 3.642, Generation Y is 3.655, and Generation Z is 3.615. It can be seen that Generation Y has a higher preference for ‘there is no leisure function set externally’ than Generation Z, while Generation Z has a higher preference for ‘externally equipped with leisure functions’ than Generation Y.

Secondly, Q13 is a survey on the types of façade decoration materials. The research results show that the average value of Q13-1 is 3.739, followed by 3.774 for Generation Y and 3.667 for Generation Z. The average value of Q13-2 is 3.875, with Generation Y 3.876 and Generation Z 3.874. This means that the YZ generation’s preference for façade decoration material types is ‘modern-textured materials’ > ‘natural-textured materials’. Among them, Generation Y has a higher preference for ‘natural-textured materials’ than Generation Z, while Generation Z has a slightly higher preference for ‘modern-textured materials’ than Generation Y.

Q14 is research on the texture of façade decorative materials. The research results show that the average value of Q14-1 is 3.614, of Generation is Y 3.607, and of Generation Z is 3.626. The average value of Q14-2 is 3.612, with Generation Y at 3.579 and Generation Z at 3.678. It can be seen that Generation Z has higher preferences for both ‘rough-textured materials’ and ‘smooth-textured materials’ than Generation Y. Among them, Generation Y has a higher preference for ‘rough-textured materials’ than ‘smooth-textured materials’, while Generation Z has a higher preference for ‘smooth-textured materials’ than ‘rough-textured materials’.

Thirdly, Q15 is a survey on the preference for façade hue. The research results show that the average value of Q15-1 is 3.676, Generation Y is 3.619, and Generation Z is 3.793. The average value of Q15-2 is 3.794, with Generation Y at 3.723 and Generation Z at 3.937. This means that the YZ generation has a preference for façade hue that is ‘colored series’ > ‘colorless series’, and Generation Z has a higher preference for ‘colored series’ and ‘colorless series’ than Generation Y.

Q16 is a survey on the preference for color brightness of a façade. The research results show that the average value of Q16-1 is 3.566, followed by 3.593 for Generation Y and 3.511 for Generation Z. The average value of Q16-2 is 3.790, with Generation Y 3.777 and Generation Z 3.816. This means that the YZ generation’s preference for the brightness of exterior color is ‘high brightness color scheme’ > ‘low brightness color scheme’. Among them, Generation Y has a higher preference for a ‘low brightness color scheme’ than Generation Z, while Generation Z has a higher preference for a ‘high brightness color scheme’ than Generation Y.

Q17 is a survey on color matching preferences of the façade. The research results show that the average value of Q17-1 is 3.644, followed by 3.624 for Generation Y and 3.684 for Generation Z. The average value of Q17-2 is 3.695, with Generation Y at 3.737 and Generation Z at 3.609. It can be seen that Generation Y has a higher preference for ‘multiple color schemes’ than Generation Z, while Generation Z has a higher preference for ‘single color scheme’ than Generation Y.

Fourthly, Q18 is a survey on design preferences for façade decorative elements. The research results show that the average value of Q18-1 is 3.621, followed by 3.624 for Generation Y and 3.615 for Generation Z. The average value of Q18-2 is 3.778, with Generation Y at 3.777 and Generation Z at 3.782. This means that the YZ generation’s preference for exterior decorative elements is ‘popular elements’ > ‘natural elements’. Among them, Generation Y has a higher preference for ‘natural elements’ than Generation Z, while Generation Z has a higher preference for ‘popular elements’ than Generation Y.

To further clarify whether there are significant differences in the aesthetic preferences of the YZ generation in China regarding various aspects of the façade, this study conducted a further analysis of the above content through post hoc multiple comparisons. The specific analysis results are shown in

Table 13. One-way ANOVA by generation type.

	Q1: What Is the Age Stage of Your Birth? (Mean ± S.D.)		F	p
	Generation Y (n = 354)	Generation Z (n = 174)
Q9-1: Concise, geometric façade	4.00 ± 0.94	3.97 ± 0.95	0.088	0.767
Q9-2: Complex, structurally and formally rich façade	3.93 ± 1.04	3.90 ± 0.96	0.102	0.750
Q9-3: Historic, updated façade design	3.71 ± 1.19	3.78 ± 1.12	0.414	0.520
Q10-1: Completely independent outer contour form	3.94 ± 0.96	3.94 ± 0.94	0.003	0.958
Q10-2: Semi-independent outer contour form	3.68 ± 1.17	3.67 ± 1.09	0.011	0.916
Q10-3: Non independent outer contour form	3.84 ± 1.07	3.80 ± 1.04	0.167	0.683
Q11-1: Completely transparent visual form	3.84 ± 1.05	3.91 ± 0.99	0.569	0.451
Q11-2: Semi-transparent visual form	3.61 ± 1.14	3.75 ± 1.16	1.724	0.190
Q11-3: Completely opaque visual form	3.68 ± 1.15	3.80 ± 1.08	1.411	0.235
Q12-1: Externally equipped with leisure functions	3.62 ± 1.17	3.69 ± 1.12	0.373	0.541
Q12-2: There is no leisure function set externally	3.66 ± 1.15	3.61 ± 1.16	0.143	0.706
Q13-1: Natural-textured materials	3.77 ± 1.11	3.67 ± 1.21	1.027	0.311
Q13-2: Modern-textured materials	3.88 ± 1.11	3.87 ± 1.19	0.000	0.984
Q14-1: Rough-textured materials	3.61 ± 1.16	3.63 ± 1.04	0.034	0.855
Q14-2: Smooth-textured materials	3.58 ± 1.15	3.68 ± 1.20	0.841	0.360
Q15-1: Colorless series	3.62 ± 1.21	3.79 ± 1.12	2.551	0.111
Q15-2: Colored series	3.72 ± 1.11	3.94 ± 1.11	4.327	0.038 *
Q16-1: Low brightness color scheme	3.59 ± 1.23	3.51 ± 1.23	0.531	0.474
Q16-2: High brightness color scheme	3.78 ± 1.14	3.82 ± 1.06	0.144	0.705
Q17-1: Single color scheme	3.62 ± 1.15	3.68 ± 1.17	0.311	0.577
Q17-2: Multiple color schemes	3.74 ± 1.11	3.61 ± 1.22	1.459	0.228
Q18-1: Natural elements	3.62 ± 1.19	3.61 ± 1.18	0.007	0.932
Q18-2: Popular elements	3.78 ± 1.10	3.78 ± 1.15	0.002	0.963

* p < 0.05 ** p < 0.01.

.

In the table, we use ANOVA to study the differences in Q1 across a total of 23 items: Q9-1, Q9-2, Q9-3, Q10-1, Q10-2, Q10-3, Q11-1, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q14-1, Q14-2, Q15-1, Q15-2, Q16-1, Q16-2, Q17-1, Q17-2, Q18-1, and Q18-2. The table indicates Q1 does not show significance for a total of 22 items—Q9-1, Q9-2, Q9-3, Q10-1, Q10-2, Q10-3, Q11-1, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q14-1, Q14-2, Q15-1, Q16-1, Q16-2, Q17-1, Q17-2, Q18-1, and Q18-2 (p > 0.05)—indicating Q1 exhibits consistency with no differences. A post hoc test is not necessary. Additionally, Q1 shows significance for a total of one item of Q15-2 (p < 0.05), indicating differences among the samples of Q1 for Q15-2; thus, a post hoc test can be conducted. The specific analysis results are shown in

Table 14. Post hoc test (multiple comparison) by generation type.

	(I) Name	(J) Name	(I) Mean	(J) Mean	Difference (I-J)	p Value
Q9-1: Concise, geometric façade	Generation Y	Generation Z	3.997	3.971	0.026	0.767
Q9-2: Complex, structurally and formally rich façade	Generation Y	Generation Z	3.927	3.897	0.030	0.750
Q9-3: Historic, updated façade design	Generation Y	Generation Z	3.706	3.776	−0.070	0.520
Q10-1: Completely independent outer contour form	Generation Y	Generation Z	3.938	3.943	−0.005	0.958
Q10-2: Semi-independent outer contour form	Generation Y	Generation Z	3.684	3.672	0.011	0.916
Q10-3: Non independent outer contour form	Generation Y	Generation Z	3.845	3.805	0.040	0.383
Q11-1: Completely transparent visual form	Generation Y	Generation Z	3.836	3.908	−0.072	0.451
Q11-2: Semi-transparent visual form	Generation Y	Generation Z	3.613	3.753	−0.140	0.190
Q11-3: Completely opaque visual form	Generation Y	Generation Z	3.675	3.799	−0.124	0.235
Q12-1: Externally equipped with leisure functions	Generation Y	Generation Z	3.624	3.690	−0.065	0.541
Q12-2: There is no leisure function set externally	Generation Y	Generation Z	3.655	3.615	0.040	0.706
Q13-1: Natural-textured materials	Generation Y	Generation Z	3.774	3.667	0.107	0.311
Q13-2: Modern-textured materials	Generation Y	Generation Z	3.876	3.874	0.002	0.984
Q14-1: Rough-textured materials	Generation Y	Generation Z	3.607	3.626	−0.019	0.855
Q14-2: Smooth-textured materials	Generation Y	Generation Z	3.579	3.678	−0.099	0.360
Q15-1: Colorless series	Generation Y	Generation Z	3.619	3.793	−0.174	0.111
Q15-2: Colored series	Generation Y	Generation Z	3.723	3.937	−0.214	0.038 *
Q16-1: Low brightness color scheme	Generation Y	Generation Z	3.593	3.511	0.082	0.474
Q16-2: High brightness color scheme	Generation Y	Generation Z	3.777	3.816	−0.039	0.705
Q17-1: Single color scheme	Generation Y	Generation Z	3.624	3.684	−0.060	0.577
Q17-2: Multiple color schemes	Generation Y	Generation Z	3.737	3.609	0.128	0.228
Q18-1: Natural elements	Generation Y	Generation Z	3.624	3.615	0.009	0.932
Q18-2: Popular elements	Generation Y	Generation Z	3.777	3.782	−0.005	0.963

* p < 0.05 ** p < 0.01.

.

The ANOVA results indicate that Q1 exhibits differences from Q15-2. Specifically, the LSD will be conducted: Q1 has a significant difference at the 0.05 level for Q15-2 (F = 4.327, p = 0.038), and the mean of Generation Y (3.72) is significantly lower than the mean of Generation Z (3.94). This means that Generation Z has a significantly higher preference for colored façades than Generation Y.

4.2.2. The Aesthetic Tendencies of Different Genders in Facade Design Among the YZ Generation in China

The data results classified and summarized by gender category are shown in

Table 15. Categorical summary by gender type.

Items	Q2: What Is Your Gender?		Total
	Male	Female
Q9-1: Concise, geometric façade	3.988	3.989	3.989
Q9-2: Complex, structurally and formally rich façade	3.890	3.941	3.917
Q9-3: Historic, updated façade design	3.643	3.810	3.729
Q10-1: Completely independent outer contour form	3.894	3.982	3.939
Q10-2: Semi-independent outer contour form	3.651	3.707	3.680
Q10-3: Non independent outer contour form	3.808	3.853	3.831
Q11-1: Completely transparent visual form	3.788	3.927	3.860
Q11-2: Semi-transparent visual form	3.616	3.700	3.659
Q11-3: Completely opaque visual form	3.710	3.722	3.716
Q12-1: Externally equipped with leisure functions	3.647	3.645	3.646
Q12-2: There is no leisure function set externally	3.663	3.623	3.642
Q13-1: Natural-textured materials	3.753	3.725	3.739
Q13-2: Modern-textured materials	3.890	3.861	3.875
Q14-1: Rough-textured materials	3.510	3.711	3.614
Q14-2: Smooth-textured materials	3.537	3.681	3.612
Q15-1: Colorless series	3.682	3.670	3.676
Q15-2: Colored series	3.824	3.766	3.794
Q16-1: Low brightness color scheme	3.514	3.615	3.566
Q16-2: High brightness color scheme	3.757	3.821	3.790
Q17-1: Single color scheme	3.655	3.634	3.644
Q17-2: Multiple color schemes	3.624	3.762	3.695
Q18-1: Natural elements	3.604	3.637	3.621
Q18-2: Popular elements	3.788	3.769	3.778

.

According to the table above, firstly, for Q9-1, the average value for males is 3.988 and for females is 3.989. For Q9-2, it is 3.890 for males and 3.941 for females. For Q9-3, it is 3.643 for males and 3.810 for females. From this, it can be seen that women have higher preferences for ‘concise, geometric façade’, ‘complex, structurally and formally rich façade’, and ‘historic, updated façade design’ than men.

For Q10-1, the average value for males is 3.894 and for females is 3.982. For 10-2, the male is 3.651 and the female is 3.707. For Q10-3, it is 3.808 for males and 3.853 for females. From this, it can be inferred that women have higher preferences for ‘completely independent outer contour form’, ‘non-independent outer contour form’, and ‘semi-independent outer contour form’ than men.

For Q11-1, the average value for males is 3.788 and for females is 3.927. For Q11-2, it is 3.616 for males and 3.700 for females. For Q11-3, it is 3.710 for males and 3.722 for females. From this, it can be seen that women have higher preferences for ‘completely transparent visual form’, ‘completely opaque visual form’, and ‘semi-transparent visual form’ than men.

For Q12-1, the average value is 3.647 for males and 3.645 for females. For Q12-2, it is 3.663 for males and 3.623 for females. It can be inferred that men have a higher preference for ‘there is no leisure function set externally’ and ‘externally equipped with leisure functions’ than women.

Secondly, for Q13-1, the average value for males is 3.753 and for females is 3.725. For Q13-2, it is 3.890 for males and 3.861 for females. It can be inferred that men have a higher preference for ‘modern-textured materials’ and ‘natural-textured materials’ than women.

For Q14-1, the average value for males is 3.510 and for females is 3.711. For Q14-2, it is 3.537 for males and 3.681 for females. It can be inferred that women have a higher preference for ‘rough-textured materials’ and ‘smooth-textured materials’ than men.

Thirdly, for Q15-1, the average value for males is 3.682 and for females is 3.670. For Q15-2, it is 3.824 for males and 3.766 for females. It can be inferred that men have a higher preference for ‘colored series’ and ‘colorless series’ than women.

For Q16-1, the average value for males is 3.514 and for females is 3.615. For Q16-2, it is 3.757 for males and 3.821 for females. It can be inferred that women have a higher preference for ‘high brightness color scheme’ and ‘low brightness color scheme’ than men.

For Q17-1, the average value for males is 3.655 and for females is 3.634. For Q17-2, it is 3.624 for males and 3.762 for females. From this, it can be inferred that men prefer a ‘single color scheme’, while women prefer ‘multiple color schemes’.

Fourthly, for Q18-1, the average value for males is 3.604 and for females is 3.637. For Q18-2, it is 3.788 for males and 3.769 for females. From this, it can be inferred that men prefer ‘popular elements’, while women prefer ‘natural elements’.

To further clarify whether there are significant differences in the aesthetic preferences of the Chinese YZ generation toward various aspects of façade content at the gender level, this study conducted further analysis of the above content through post hoc multiple comparisons. The specific analysis results are shown in

Table 16. One-way ANOVA by gender type.

	Q2: What Is Your Gender? (Mean ± S.D.)		F	p
	Male (n = 255)	Female (n = 273)
Q9-1: Concise, geometric façade	3.99 ± 0.97	3.99 ± 0.92	0.000	0.992
Q9-2: Complex, structurally and formally rich façade	3.89 ± 1.02	3.94 ± 1.01	0.335	0.563
Q9-3: Historic, updated façade design	3.64 ± 1.22	3.81 ± 1.12	2.679	0.102
Q10-1: Completely independent outer contour form	3.89 ± 0.96	3.98 ± 0.94	1.124	0.290
Q10-2: Semi-independent outer contour form	3.65 ± 1.16	3.71 ± 1.13	0.317	0.573
Q10-3: Non independent outer contour form	3.81 ± 1.11	3.85 ± 1.00	0.246	0.620
Q11-1: Completely transparent visual form	3.79 ± 1.04	3.93 ± 1.02	2.397	0.122
Q11-2: Semi-transparent visual form	3.62 ± 1.20	3.70 ± 1.10	0.700	0.403
Q11-3: Completely opaque visual form	3.71 ± 1.13	3.72 ± 1.12	0.014	0.904
Q12-1: Externally equipped with leisure functions	3.65 ± 1.22	3.64 ± 1.10	0.001	0.981
Q12-2: There is no leisure function set externally	3.66 ± 1.20	3.62 ± 1.11	0.158	0.691
Q13-1: Natural-textured materials	3.75 ± 1.16	3.73 ± 1.13	0.077	0.782
Q13-2: Modern-textured materials	3.89 ± 1.12	3.86 ± 1.15	0.088	0.766
Q14-1: Rough-textured materials	3.51 ± 1.17	3.71 ± 1.07	4.238	0.040 *
Q14-2: Smooth-textured materials	3.54 ± 1.20	3.68 ± 1.13	2.014	0.156
Q15-1: Colorless series	3.68 ± 1.23	3.67 ± 1.14	0.014	0.907
Q15-2: Colored series	3.82 ± 1.12	3.77 ± 1.11	0.357	0.550
Q16-1: Low brightness color scheme	3.51 ± 1.28	3.62 ± 1.19	0.898	0.344
Q16-2: High brightness color scheme	3.76 ± 1.13	3.82 ± 1.11	0.428	0.513
Q17-1: Single color scheme	3.65 ± 1.15	3.63 ± 1.16	0.044	0.833
Q17-2: Multiple color schemes	3.62 ± 1.18	3.76 ± 1.11	1.926	0.166
Q18-1: Natural elements	3.60 ± 1.22	3.64 ± 1.15	0.105	0.746
Q18-2: Popular elements	3.79 ± 1.13	3.77 ± 1.11	0.038	0.846

* p < 0.05 ** p < 0.01.

.

In the table, we use ANOVA to study the differences in Q2 across a total of 23 items: Q9-1, Q9-2, Q9-3, Q10-1, Q10-2, Q10-3, Q11-1, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q14-1, Q14-2, Q15-1, Q15-2, Q16-1, Q16-2, Q17-1, Q17-2, Q18-1 and Q18-2. The table indicates Q2 do not show significance for a total of 22 items—Q9-1, Q9-2, Q9-3, Q10-1, Q10-2, Q10-3, Q11-1, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q14-2, Q15-1, Q15-2, Q16-1, Q16-2, Q17-1, Q17-2, Q18-1 and Q18-2 (p > 0.05)—indicating that Q2 exhibits consistency with no differences. A post hoc test is not necessary. Additionally, Q2 shows significance for a total of one item of Q14-1 (p < 0.05), indicating differences among the samples of Q2 for Q14-1; thus, a post hoc test can be conducted. The specific analysis results are shown in

Table 17. Post hoc test (multiple comparison) by gender type.

	(I) Name	(J) Name	(I) Mean	(J) Mean	Difference (I-J)	p Value
Q9-1: Concise, geometric façade	Male	Female	3.988	3.989	−0.001	0.992
Q9-2: Complex, structurally and formally rich façade	Male	Female	3.890	3.941	−0.051	0.563
Q9-3: Historic, updated façade design	Male	Female	3.643	3.810	−0.166	0.102
Q10-1: Completely independent outer contour form	Male	Female	3.894	3.982	−0.088	0.290
Q10-2: Semi-independent outer contour form	Male	Female	3.651	3.707	−0.056	0.573
Q10-3: Non independent outer contour form	Male	Female	3.808	3.853	−0.046	0.620
Q11-1: Completely transparent visual form	Male	Female	3.788	3.927	−0.139	0.122
Q11-2: Semi-transparent visual form	Male	Female	3.616	3.700	−0.084	0.403
Q11-3: Completely opaque visual form	Male	Female	3.710	3.722	−0.012	0.904
Q12-1: Externally equipped with leisure functions	Male	Female	3.647	3.645	0.002	0.981
Q12-2: There is no leisure function set externally	Male	Female	3.663	3.623	0.040	0.691
Q13-1: Natural-textured materials	Male	Female	3.753	3.725	0.028	0.782
Q13-2: Modern-textured materials	Male	Female	3.890	3.86	0.029	0.766
Q14-1: Rough-textured materials	Male	Female	3.510	3.711	−0.201	0.040 *
Q14-2: Smooth-textured materials	Male	Female	3.537	3.681	−0.144	0.156
Q15-1: Colorless series	Male	Female	3.682	3.670	0.012	0.907
Q15-2: Colored series	Male	Female	3.824	3.766	0.058	0.550
Q16-1: Low brightness color scheme	Male	Female	3.514	3.615	−0.102	0.344
Q16-2: High brightness color scheme	Male	Female	3.757	3.821	−0.064	0.513
Q17-1: Single color scheme	Male	Female	3.655	3.634	0.021	0.833
Q17-2: Multiple color schemes	Male	Female	3.624	3.762	−0.138	0.166
Q18-1: Natural elements	Male	Female	3.604	3.637	−0.033	0.746
Q18-2: Popular elements	Male	Female	3.788	3.769	0.019	0.846

* p < 0.05 ** p < 0.01.

.

The ANOVA results indicate that Q2 exhibits differences for Q14-1. Specifically, the LSD will be conducted:

Q2 has a significant difference at the 0.05 level for Q14-1 (F = 4.238, p = 0.040). The mean of males (3.51) is significantly lower than the mean of females (3.71). This means that men have a significantly lower preference for rough-textured façades compared to women.

4.2.3. The Aesthetic Preferences of Different Monthly Income Groups in China’s YZ Generation Toward Façade Design

The results of classifying and summarizing monthly income categories are shown in

Table 18. Categorical summary by monthly income type.

Items	Q4: What Is Your Monthly Income?					Total
	Low Income	Lower Income	Middle Income	Higher Income	High Income
Q9-1: Concise, geometric façade	4.038	4.000	3.846	4.200	4.174	3.989
Q9-2: Complex, structurally and formally rich façade	3.942	3.885	3.811	4.043	4.196	3.917
Q9-3: Historic, updated façade design	3.692	3.803	3.638	3.896	3.761	3.729
Q10-1: Completely independent outer contour form	4.077	3.902	3.819	4.078	4.152	3.939
Q10-2: Semi-independent outer contour form	3.769	3.754	3.547	3.826	3.848	3.680
Q10-3: Non independent outer contour form	3.731	4.115	3.701	4.043	3.761	3.831
Q11-1: Completely transparent visual form	3.962	4.000	3.748	3.948	3.957	3.860
Q11-2: Semi-transparent visual form	3.846	3.918	3.480	3.783	3.783	3.659
Q11-3: Completely opaque visual form	3.865	3.918	3.587	3.887	3.565	3.716
Q12-1: Externally equipped with leisure functions	3.500	3.951	3.551	3.861	3.391	3.646
Q12-2: There is no leisure function set externally	3.404	3.967	3.535	3.791	3.696	3.642
Q13-1: Natural-textured materials	3.692	3.984	3.575	3.878	4.022	3.739
Q13-2: Modern-textured materials	3.750	4.197	3.752	4.026	3.891	3.875
Q14-1: Rough-textured materials	3.654	3.754	3.531	3.748	3.500	3.614
Q14-2: Smooth-textured materials	3.673	3.902	3.551	3.696	3.283	3.612
Q15-1: Colorless series	3.692	4.098	3.567	3.583	3.935	3.676
Q15-2: Colored series	3.731	4.033	3.720	3.852	3.804	3.794
Q16-1: Low brightness color scheme	3.442	3.902	3.535	3.609	3.326	3.566
Q16-2: High brightness color scheme	3.673	3.984	3.720	3.913	3.739	3.790
Q17-1: Single color scheme	3.673	3.934	3.453	3.774	3.957	3.644
Q17-2: Multiple color schemes	3.481	3.951	3.539	3.922	3.891	3.695
Q18-1: Natural elements	3.519	3.967	3.520	3.678	3.696	3.621
Q18-2: Popular elements	3.788	3.902	3.732	3.783	3.848	3.778

.

According to the table above, firstly, for Q9-1, the average value for low income is 4.038, the average value for lower income is 4.000, the average value for middle income is 3.846, the average value for higher income is 4.200, and the average value for high income is 4.174. For Q9-2, the low income is 3.942, the lower income is 3.885, the middle income is 3.811, the higher income is 4.043, and the high income is 4.196. For Q9-3, the low income is 3.692, the lower income is 3.803, the middle income is 3.638, the higher income is 3.896, and the high income is 3.761. From this, it can be seen that the preferences for ‘concise, geometric façade’, ‘complex, structurally and formally rich façade’, and ‘historic, updated façade design’ are more positive for both higher-income and high-income groups, while the middle-income group shows the least positive behavior.

For Q10-1, the average low income is 4. 077, the average for lower income is 3.902, the average for middle income is 3.819, the average for higher income is 4.078, and the average for high income is 4.152. For Q10-2, the low income is 3.769, the lower income is 3.754, the middle income is 3.547, the higher income is 3.826, and the high income is 3.848. For Q10-3, the low income is 3.731, the lower income is 4.115, the middle income is 3.701, the higher income is 4.043, and the high income is 3.761. From this, it can be seen that for ‘completely independent outer contour form’ and ‘semi-independent outer contour form’, their preferences are more positive toward high-income groups and higher-income groups, while the preference for ‘non-independent outer contour form’ is more positive for lower-income and high-income groups. The middle-income group shows the least positive preference for ‘completely independent outer contour form’, ‘semi-independent outer contour form’, and ‘non-independent outer contour form’.

For Q11-1, the average for low income is 3.962, the average for lower income is 4.000, the average for middle income is 3.748, the average for higher income is 3.948, and the average for high income is 3.957. For Q11-2, the low-income group is 3.846, the lower-income group is 3.918, the middle-income group is 3.480, the higher-income group is 3.783, and the high-income group is 3.783. For Q11-3, the low income is 3.865, the low income is 3.918, the middle income is 3.587, the high income is 3.887, and the high income is 3.565. From this, it can be seen that preferences for ‘completely transparent visual form’ and ‘semi-transparent visual form’ are more positive for lower-income and low-income groups, while preferences for ‘completely opaque visual form’ are more positive for lower-income and higher-income groups. For ‘completely transparent visual form’ and ‘semi-transparent visual form’, the preference for middle-income groups is the least positive, while for ‘completely opaque visual form’, the preference for high-income groups is the least positive.

For Q12, the average for low income is 3.500, the average for lower income is 3.951, the average for middle income is 3.551, the average for higher income is 3.861, and the average for high income is 3.391. For Q12-2, the low income is 3.404, the lower income is 3.967, the middle income is 3.535, the higher income is 3.791, and the high income is 3.696. From this, it can be seen that preferences for ‘externally equipped with leisure functions’ and ‘there is no leisure function set externally’ are more positive for both low-income and high-income groups; ‘externally equipped with leisure functions’ shows the least positive preference for high-income groups, while ‘there is no leisure function set externally’ shows the least positive preference for low-income groups.

Secondly, for Q13-1, the average for low income is 3.692, the average for lower income is 3.984, the average for middle income is 3.575, the average for higher income is 3.878, and the average for high income is 4.022. For Q12-2, the low income is 3.750, the lower income is 4.197, the middle income is 3.752, the higher income is 4.026, and the high income is 3.891. From this, it can be seen that the preference for ‘natural-textured materials’ is more positive among high-income and lower-income groups, while the middle-income group shows the least positive behavior. The preference for ‘modern-textured materials’ is more positive among lower-income and higher-income groups, while low-income groups show the least positive behavior.

For Q14-1, the average for low income is 3.654, the average for lower income is 3.754, the average for middle income is 3.531, the average for higher income is 3.748, and the average for high income is 3.500. For Q12-2, the low income is 3.673, the lower income is 3.902, the middle income is 3.551, the higher income is 3.696, and the high income is 3.285. From this, it can be seen that the preferences of ‘rough-textured materials’ and ‘smooth-textured materials’ are more positive for lower-income and higher-income groups, while high-income groups show the least positive behavior.

Thirdly, for Q15-1, the average for low income is 3.692, the average for lower income is 4.098, the average for middle income is 3.567, the average for higher income is 3.583, and the average for high income is 3.935. For Q12-2, the low income is 3.731, the lower income is 4.033, the middle income is 3.720, the higher income is 3.852, and the high income is 3.804. From this, it can be seen that the preference for ‘colorless series’ is more positive among lower-income and high-income groups, while the middle-income group shows the least positive preference. The preference for ‘colored series’ is more positive for both lower-income and higher-income groups, while it is also least positive for middle-income groups.

For Q16-1, the average for low income is 3.442, the average for lower income is 3.902, the average for middle income is 3.535, the average for higher income is 3.609, and the average for high income is 3.326. For Q16-2, the low income is 3.673, the lower income is 3.984, the middle income is 3.720, the higher income is 3.913, and the high income is 3.739. From this, it can be seen that preferences for ‘low brightness color scheme’ and ‘high brightness color scheme’ are more positive for both lower-income and higher-income groups; ‘low brightness color scheme’ shows the least positive preference for high-income groups, while ‘high brightness color scheme’ shows the least positive preference for low-income groups.

For Q17-1, the average for low income is 3.673, the average for lower income is 3.934, the average for middle income is 3.453, the average for higher income is 3.774, and the average for high income is 3.957. For Q17-2, the low income is 3.481, the lower income is 3.951, the middle income is 3.539, the higher income is 3.922, and the high income is 3.891. From this, it can be seen that the preference for a ‘single color scheme’ is more positive for high-income and lower-income groups, while the middle-income group shows the least positive preference. The preference for ‘multiple color schemes’ is more positive among lower-income and higher-income groups, while low-income groups show the least positive behavior.

Thirdly, for Q18-1, the average for low income is 3.519, the average for lower income is 3.967, the average for middle income is 3.520, the average for higher income is 3.678, and the average for high income is 3.6969. For Q18-2, the low income is 3.788, the lower income is 3.902, the middle income is 3.732, the higher income is 3.783, and the high income is 3.848. From this, it can be seen that preferences for ‘natural elements’ and ‘popular elements’ are more positive toward lower-income and high-income groups. The preference for ‘natural elements’ is least positive for low-income groups, while the preference for ‘popular elements’ is least positive for middle-income groups.

To further clarify whether there are significant differences in the aesthetic preferences of the YZ generation in China regarding various aspects of the façade at the monthly income level, this study conducted a further analysis of the above content through post hoc multiple comparisons. The specific analysis results are shown in

Table 19. One-way ANOVA by monthly income type.

	Q4: What Is Your Monthly Income? (Mean ± S.D.)					F	p
	Low Income (n = 52)	Lower Income (n = 61)	Middle Income (n = 254)	Higher Income (n = 115)	High Income (n = 46)
Q9-1: Concise, geometric façade	4.04 ± 0.88	4.00 ± 0.86	3.85 ± 0.98	4.20 ± 0.89	4.17 ± 0.95	3.438	0.009 **
Q9-2: Complex, structurally and formally rich façade	3.94 ± 0.94	3.89 ± 0.80	3.81 ± 1.06	4.04 ± 1.06	4.20 ± 0.88	2.047	0.087
Q9-3: Historic, updated façade design	3.69 ± 1.26	3.80 ± 1.11	3.64 ± 1.26	3.90 ± 1.04	3.76 ± 0.90	1.054	0.379
Q10-1: Completely independent outer contour form	4.08 ± 0.95	3.90 ± 0.91	3.82 ± 1.00	4.08 ± 0.85	4.15 ± 0.87	2.547	0.039 *
Q10-2: Semi-independent outer contour form	3.77 ± 1.10	3.75 ± 1.11	3.55 ± 1.24	3.83 ± 0.99	3.85 ± 0.92	1.736	0.141
Q10-3: Non independent outer contour form	3.73 ± 1.09	4.11 ± 0.91	3.70 ± 1.12	4.04 ± 0.93	3.76 ± 0.99	3.460	0.008 **
Q11-1: Completely transparent visual form	3.960 ± 1.10	4.00 ± 0.91	3.75 ± 1.07	3.95 ± 0.94	3.96 ± 1.03	1.478	0.208
Q11-2: Semi-transparent visual form	3.85 ± 1.18	3.92 ± 1.02	3.48 ± 1.21	3.78 ± 1.04	3.78 ± 1.11	3.160	0.014 *
Q11-3: Completely opaque visual form	3.87 ± 1.16	3.92 ± 0.95	3.59 ± 1.22	3.89 ± 1.00	3.57 ± 1.00	2.457	0.045 *
Q12-1: Externally equipped with leisure functions	3.50 ± 1.06	3.95 ± 1.01	3.55 ± 1.20	3.86 ± 1.08	3.39 ± 1.22	3.310	0.011 *
Q12-2: There is no leisure function set externally	3.40 ± 1.21	3.97 ± 1.02	3.54 ± 1.21	3.79 ± 1.10	3.70 ± 1.01	2.846	0.024 *
Q13-1: Natural-textured materials	3.69 ± 1.28	3.98 ± 1.02	3.57 ± 1.20	3.88 ± 1.00	4.02 ± 1.06	3.207	0.013 *
Q13-2: Modern-textured materials	3.75 ± 1.22	4.20 ± 0.93	3.75 ± 1.20	4.03 ± 1.01	3.89 ± 1.10	2.679	0.031 *
Q14-1: Rough-textured materials	3.65 ± 1.01	3.75 ± 0.96	3.53 ± 1.15	3.75 ± 1.15	3.50 ± 1.22	1.123	0.345
Q14-2: Smooth-textured materials	3.67 ± 1.23	3.90 ± 1.03	3.55 ± 1.19	3.70 ± 1.12	3.28 ± 1.19	2.233	0.064
Q15-1: Colorless series	3.69 ± 1.06	4.10 ± 1.00	3.57 ± 1.23	3.58 ± 1.16	3.93 ± 1.22	3.280	0.011 *
Q15-2: Colored series	3.73 ± 1.12	4.03 ± 0.91	3.72 ± 1.14	3.85 ± 1.12	3.80 ± 1.15	1.102	0.355
Q16-1: Low brightness color scheme	3.44 ± 1.23	3.90 ± 1.01	3.54 ± 1.29	3.61 ± 1.15	3.33 ± 1.32	1.784	0.131
Q16-2: High brightness color scheme	3.67 ± 1.08	3.98 ± 1.01	3.72 ± 1.16	3.91 ± 1.00	3.74 ± 1.27	1.221	0.301
Q17-1: Single color scheme	3.67 ± 1.22	3.93 ± 1.00	3.45 ± 1.21	3.77 ± 1.03	3.96 ± 1.09	4.020	0.003 **
Q17-2: Multiple color schemes	3.48 ± 1.34	3.95 ± 1.04	3.54 ± 1.20	3.92 ± 0.93	3.89 ± 1.06	3.935	0.004 **
Q18-1: Natural elements	3.52 ± 1.21	3.97 ± 105	3.52 ± 1.25	3.68 ± 1.13	3.70 ± 1.05	1.989	0.095
Q18-2: Popular elements	3.79 ± 1.11	3.90 ± 0.93	3.73 ± 1.18	3.78 ± 1.07	3.85 ± 1.17	0.337	0.853

* p < 0.05 ** p < 0.01.

.

In the table, we use ANOVA to study the differences in Q4 across a total of 23 items: Q9-1, Q9-2, Q9-3, Q10-1, Q10-2, Q10-3, Q11-1, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q14-1, Q14-2, Q15-1, Q15-2, Q16-1, Q16-2, Q17-1, Q17-2, Q18-1, and Q18-2. The table indicates that Q4 does not show significance for a total of 11 items—Q9-2, Q9-3, Q10-2, Q11-1, Q14-1, Q14-2, Q15-2, Q16-1, Q16-2, Q18-1, and Q18-2 (p > 0.05)—indicating that Q4 exhibits consistency with no differences. A post hoc test is not necessary. Additionally, Q4 shows significance for a total of 12 items—Q9-1, Q10-1, Q10-3, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q15-1, Q17-1, and Q17-2 (p < 0.05)— indicating differences among the samples of Q4 for Q9-1, Q10-1, Q10-3, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q15-1, Q17-1, and Q17-2; thus, a post hoc test can be conducted. The specific analysis results are shown in

Table 20. Post hoc test (multiple comparison) by monthly income type.

	(I) Name	(J) Name	(I) Mean	(J) Mean	D-Value (I-J)	p
Q9-1: Concise, geometric façade	low income	lower income	4.038	4.000	0.038	0.827
	low income	middle income	4.038	3.846	0.192	0.177
	low income	higher income	4.038	4.200	−0.162	0.301
	low income	high income	4.038	4.174	−0.135	0.474
	lower income	middle income	4.000	3.846	0.154	0.249
	lower income	higher income	4.000	4.200	−0.200	0.177
	lower income	high income	4.000	4.174	−0.174	0.341
	middle income	higher income	3.846	4.200	−0.354	0.001 **
	middle income	high income	3.846	4.174	−0.327	0.029 *
	higher income	high income	4.200	4.174	0.026	0.837
Q9-2: Complex, structurally and formally rich façade	low income	lower income	3.942	3.885	0.057	0.765
	low income	middle income	3.942	3.811	0.131	0.394
	low income	higher income	3.942	4.043	−0.101	0.549
	low income	high income	3.942	4.196	−0.253	0.216
	lower income	middle income	3.885	3.811	0.074	0.607
	lower income	higher income	3.885	4.043	−0.158	0.323
	lower income	high income	3.885	4.196	−0.310	0.116
	middle income	higher income	3.811	4.043	−0.232	0.041 *
	middle income	high income	3.811	4.196	−0.385	0.018 *
	higher income	high income	4.043	4.196	−0.152	0.388
Q9-3: Historic, updated façade design	low income	lower income	3.692	3.803	−0.111	0.615
	low income	middle income	3.692	3.638	0.055	0.759
	low income	higher income	3.692	3.896	−0.203	0.298
	low income	high income	3.692	3.761	−0.069	0.772
	lower income	middle income	3.803	3.639	0.165	0.321
	lower income	higher income	3.803	3.896	−0.092	0.618
	lower income	high income	3.803	3.761	0.042	0.853
	middle income	higher income	3.638	3.896	−0.258	0.050
	middle income	high income	3.638	3.761	−0.123	0.511
	higher income	high income	3.896	3.761	0.135	0.509
Q10-1: Completely independent outer contour form	low income	lower income	4.077	3.902	0.175	0.325
	low income	middle income	4.077	3.819	0.258	0.073
	low income	higher income	4.077	4.078	−0.001	0.993
	low income	high income	4.077	4.152	−0.075	0.694
	lower income	middle income	3.902	3.819	0.083	0.539
	lower income	higher income	3.902	4.078	−0.177	0.238
	lower income	high income	3.902	4.152	−0.251	0.174
	middle income	higher income	3.819	4.078	−0.259	0.015 *
	middle income	high income	3.819	4.152	−0.333	0.028 *
	higher income	high income	4.078	4.152	−0.074	0.653
Q10-2: Semi independent outer contour form	low income	lower income	3.769	3.754	0.015	0.944
	low income	middle income	3.769	3.547	0.222	0.200
	low income	higher income	3.769	3.826	−0.057	0.765
	low income	high income	3.769	3.848	−0.079	0.733
	lower income	middle income	3.754	3.547	0.207	0.202
	lower income	higher income	3.754	3.826	−0.072	0.689
	lower income	high income	3.754	3.848	−0.094	0.673
	middle income	higher income	3.547	3.826	−0.279	0.030 *
	middle income	high income	3.547	3.848	−0.301	0.100
	higher income	high income	3.826	3.848	−0.022	0.913
Q10-3: Non independent outer contour form	low income	lower income	3.731	4.115	−0.384	0.052
	low income	middle income	3.731	3.701	0.030	0.851
	low income	higher income	3.731	4.043	−0.313	0.074
	low income	high income	3.731	3.761	−0.030	0.887
	lower income	middle income	4.115	3.707	0.414	0.006 **
	lower income	higher income	4.115	4.043	0.071	0.667
	lower income	high income	4.115	3.761	0.354	0.084
	middle income	higher income	3.701	4.043	−0.343	0.004 **
	middle income	high income	3.701	3.761	−0.060	0.720
	higher income	high income	4.043	3.761	0.283	0.122
Q11-1: Completely transparent visual form	low income	lower income	3.962	4.000	−0.038	0.843
	low income	middle income	3.962	3.748	0.214	0.172
	low income	higher income	3.962	3.948	0.014	0.936
	low income	high income	3.962	3.957	0.005	0.981
	lower income	middle income	4.000	3.748	0.252	0.086
	lower income	higher income	4.000	3.948	0.052	0.748
	lower income	high income	4.000	3.957	0.043	0.828
	middle income	higher income	3.748	3.948	−0.200	0.084
	middle income	high income	3.748	3.957	−0.208	0.206
	higher income	high income	3.948	3.957	−0.009	0.961
Q11-2: Semi-transparent visual form	low income	lower income	3.846	3.918	−0.072	0.739
	low income	middle income	3.846	3.480	0.366	0.036 *
	low income	higher income	3.846	3.783	0.064	0.739
	low income	high income	3.846	3.783	0.064	0.784
	lower income	middle income	3.918	3.480	0.438	0.007 **
	lower income	higher income	3.918	3.783	0.135	0.454
	lower income	high income	3.918	3.783	0.135	0.544
	middle income	higher income	3.480	3.783	−0.302	0.019 *
	middle income	high income	3.480	3.783	−0.302	0.099
	higher income	high income	3.783	3.783	0.000	1.000
Q11-3: Completely opaque visual form	low income	lower income	3.865	3.918	−0.054	0.803
	low income	middle income	3.865	3.587	0.279	0.102
	low income	higher income	3.865	3.887	−0.022	0.908
	low income	high income	3.865	3.565	0.300	0.186
	lower income	middle income	3.918	3.587	0.331	0.038 *
	lower income	higher income	3.918	3.887	0.031	0.861
	lower income	high income	3.918	3.565	0.353	0.107
	middle income	higher income	3.587	3.887	−0.300	0.017 *
	middle income	high income	3.587	3.565	0.021	0.905
	higher income	high income	3.887	3.565	0.322	0.100
Q12-1: Externally equipped with leisure functions	low income	lower income	3.500	3.951	−0.451	0.037 *
	low income	middle income	3.500	3.551	−0.051	0.769
	low income	higher income	3.500	3.861	−0.361	0.060
	low income	high income	3.500	3.391	0.109	0.639
	lower income	middle income	3.951	3.551	0.400	0.015 *
	lower income	higher income	3.951	3.861	0.090	0.620
	lower income	high income	3.951	3.391	0.560	0.013 *
	middle income	higher income	3.551	3.861	−0.310	0.016 *
	middle income	high income	3.551	3.391	0.160	0.384
	higher income	high income	3.861	3.391	0.470	0.019 *
Q12-2: There is no leisure function set externally	low income	lower income	3.404	3.967	−0.563	0.010 **
	low income	middle income	3.404	3.535	−0.132	0.451
	low income	higher income	3.404	3.791	−0.387	0.044 *
	low income	high income	3.404	3.696	−0.292	0.209
	lower income	middle income	3.967	3.535	0.432	0.009 **
	lower income	higher income	3.967	3.791	0.176	0.333
	lower income	high income	3.967	3.696	0.272	0.226
	middle income	higher income	3.535	3.791	−0.256	0.048 *
	middle income	high income	3.535	3.696	−0.160	0.384
	higher income	high income	3.791	3.696	0.096	0.633
Q13-1: Natural-textured materials	low income	lower income	3.692	3.984	−0.291	0.174
	low income	middle income	3.692	3.575	0.118	0.497
	low income	higher income	3.692	3.878	−0.186	0.327
	low income	high income	3.692	4.022	−0.329	0.152
	lower income	middle income	3.984	3.575	0.409	0.012 *
	lower income	higher income	3.984	3.878	0.105	0.558
	lower income	high income	3.984	4.022	−0.038	0.863
	middle income	higher income	3.575	3.878	−0.303	0.018 *
	middle income	high income	3.575	4.022	−0.447	0.014 *
	higher income	high income	3.878	4.022	−0.143	0.469
Q13-2: Modern-textured materials	low income	lower income	3.750	4.197	−0.447	0.036 *
	low income	middle income	3.750	3.752	−0.002	0.991
	low income	higher income	3.750	4.026	−0.276	0.143
	low income	high income	3.750	3.891	−0.141	0.536
	lower income	middle income	4.197	3.752	0.445	0.006 **
	lower income	higher income	4.197	4.026	0.171	0.340
	lower income	high income	4.197	3.891	0.305	0.166
	middle income	higher income	3.752	4.026	−0.274	0.031 *
	middle income	high income	3.752	3.891	−0.139	0.441
	higher income	high income	4.026	3.891	0.135	0.493
Q14-1: Rough-textured materials	low income	lower income	3.654	3.754	−0.100	0.636
	low income	middle income	3.654	3.531	0.122	0.474
	low income	higher income	3.654	3.748	−0.094	0.617
	low income	high income	3.654	3.500	0.154	0.499
	lower income	middle income	3.754	3.531	0.223	0.165
	lower income	higher income	3.754	3.748	0.006	0.972
	lower income	high income	3.754	3.500	0.254	0.247
	middle income	higher income	3.531	3.748	−0.216	0.087
	middle income	high income	3.531	3.500	0.031	0.861
	higher income	high income	3.748	3.500	0.248	0.206
Q14-2: Smooth-textured materials	low income	lower income	3.673	3.902	−0.229	0.298
	low income	middle income	3.673	3.551	0.122	0.491
	low income	higher income	3.673	3.696	−0.023	0.907
	low income	high income	3.673	3.283	0.390	0.097
	lower income	middle income	3.902	3.551	0.350	0.035 *
	lower income	higher income	3.902	3.696	0.206	0.263
	lower income	high income	3.902	3.283	0.619	0.007 **
	middle income	higher income	3.551	3.696	−0.144	0.269
	middle income	high income	3.551	3.283	0.269	0.150
	higher income	high income	3.696	3.283	0.413	0.042 *
Q15-1: Colorless series	low income	lower income	3.692	4.098	−0.406	0.067
	low income	middle income	3.692	3.567	0.125	0.482
	low income	higher income	3.692	3.583	0.110	0.575
	low income	high income	3.692	3.935	−0.242	0.307
	lower income	middle income	4.098	3.567	0.531	0.002 **
	lower income	higher income	4.098	3.583	0.516	0.006 **
	lower income	high income	4.098	3.935	0.164	0.475
	middle income	higher income	3.567	3.583	−0.016	0.905
	middle income	high income	3.567	3.935	−0.368	0.051
	higher income	high income	3.583	3.935	−0.352	0.085
Q15-2: Colored series	low income	lower income	3.731	4.033	−0.302	0.151
	low income	middle income	3.731	3.720	0.010	0.952
	low income	higher income	3.731	3.852	−0.121	0.514
	low income	high income	3.731	3.804	−0.074	0.744
	lower income	middle income	4.033	3.720	0.312	0.049 *
	lower income	higher income	4.033	3.852	0.181	0.306
	lower income	high income	4.033	3.804	0.228	0.293
	middle income	higher income	3.720	3.852	−0.132	0.293
	middle income	high income	3.720	3.804	−0.084	0.638
	higher income	high income	3.852	3.804	0.048	0.805
Q16-1: Low brightness color scheme	low income	lower income	3.442	3.902	−0.459	0.048 *
	low income	middle income	3.442	3.535	−0.093	0.619
	low income	higher income	3.442	3.609	−0.166	0.418
	low income	high income	3.442	3.326	0.116	0.640
	lower income	middle income	3.902	3.535	0.366	0.037 *
	lower income	higher income	3.902	3.609	0.293	0.133
	lower income	high income	3.902	3.326	0.576	0.017 *
	middle income	higher income	3.535	3.609	−0.073	0.596
	middle income	high income	3.535	3.326	0.209	0.288
	higher income	high income	3.609	3.326	0.283	0.188
Q16-2: High brightness color scheme	low income	lower income	3.673	3.984	−0.311	0.141
	low income	middle income	3.673	3.720	−0.047	0.780
	low income	higher income	3.673	3.913	−0.240	0.199
	low income	high income	3.673	3.739	−0.066	0.770
	lower income	middle income	3.984	3.720	0.263	0.099
	lower income	higher income	3.984	3.913	0.071	0.690
	lower income	high income	3.984	3.739	0.244	0.263
	middle income	higher income	3.720	3.913	−0.193	0.125
	middle income	high income	3.720	3.739	−0.019	0.917
	higher income	high income	3.913	3.739	0.174	0.372
Q17-1: Single color scheme	low income	lower income	3.673	3.934	−0.261	0.225
	low income	middle income	3.673	3.453	0.220	0.205
	low income	higher income	3.673	3.774	−0.101	0.597
	low income	high income	3.673	3.957	−0.283	0.220
	lower income	middle income	3.934	3.453	0.482	0.003 **
	lower income	higher income	3.934	3.774	0.161	0.375
	lower income	high income	3.934	3.957	−0.022	0.921
	middle income	higher income	3.453	3.774	−0.321	0.013 *
	middle income	high income	3.453	3.957	−0.504	0.006 **
	higher income	high income	3.774	3.957	−0.183	0.359
Q17-2: Multiple color schemes	low income	lower income	3.481	3.951	−0.470	0.028 *
	low income	middle income	3.481	3.539	−0.059	0.734
	low income	higher income	3.481	3.922	−0.441	0.020 *
	low income	high income	3.481	3.891	−0.411	0.074
	lower income	middle income	3.951	3.539	0.411	0.011 *
	lower income	higher income	3.951	3.922	0.029	0.871
	lower income	high income	3.951	3.891	0.060	0.788
	middle income	higher income	3.539	3.922	−0.382	0.003 **
	middle income	high income	3.539	3.891	−0.352	0.053
	higher income	high income	3.922	3.891	0.030	0.878
Q18-1: Natural elements	low income	lower income	3.519	3.967	−0.448	0.045 *
	low income	middle income	3.519	3.520	−0.000	0.998
	low income	higher income	3.519	3.678	−0.159	0.421
	low income	high income	3.519	3.696	−0.176	0.461
	lower income	middle income	3.967	3.520	0.448	0.008 **
	lower income	higher income	3.967	3.678	0.289	0.123
	lower income	high income	3.967	3.696	0.272	0.239
	middle income	higher income	3.520	3.678	−0.159	0.233
	middle income	high income	3.520	3.696	−0.176	0.353
	higher income	high income	3.678	3.696	−0.017	0.933
Q18-2: Popular elements	low income	lower income	3.788	3.902	−0.113	0.593
	low income	middle income	3.788	3.732	0.056	0.742
	low income	higher income	3.788	3.783	0.006	0.975
	low income	high income	3.788	3.848	−0.059	0.794
	lower income	middle income	3.902	3.732	0.169	0.290
	lower income	higher income	3.902	3.783	0.119	0.503
	lower income	high income	3.902	3.848	0.054	0.806
	middle income	higher income	3.732	3.783	−0.050	0.690
	middle income	high income	3.732	3.848	−0.116	0.520
	higher income	high income	3.783	3.848	−0.065	0.739

* p < 0.05 ** p < 0.01.

.

The ANOVA results indicate that Q4 exhibits differences for Q9-1, Q10-1, Q10-3, Q11-2, Q11-3, Q12-1, Q12-2, Q13-1, Q13-2, Q15-1, Q17-1, and Q17-2. Specifically, the LSD will be conducted.

Q4 has a significant difference at the 0.01 level for Q9-1 (F = 3.438, p = 0.009). The comparison with significant differences is higher income > middle income; high income > middle income. This indicates that both higher-income and high-income groups have a significantly higher preference for a ‘concise, geometric façade’ than the middle-income group.

Q4 has a significant difference at the 0.05 level for Q10-1 (F = 2.547, p = 0.039). The comparison with significant differences is higher income > middle income; high income > middle income. This indicates that both higher-income and high-income groups have a significantly higher preference for ‘completely independent outer contour form’ than the middle-income group.

Q4 has a significant difference at the 0.01 level for Q10-3 (F = 3.460, p = 0.008). The comparison with significant differences is lower income > middle income; higher income > middle income. This indicates that both lower-income and higher-income groups have a significantly higher preference for ‘non-independent outer contour form’ than the middle-income group.

Q4 has a significant difference at the 0.05 level for Q11-2 (F = 3.160, p = 0.014). The comparison with significant differences is low income > middle income; lower income > middle income; higher income > middle income. This indicates that the low-income, lower-income and higher-income groups have a significantly higher preference for ‘semi-transparent visual form’ than the middle-income group.

Q4 has a significant difference at the 0.05 level for Q11-3 (F = 2.457, p = 0.045). The comparison with significant differences is lower income > middle income; higher income > middle income. This indicates that both lower-income and higher-income groups have a significantly higher preference for a ‘completely opaque visual form’ than the middle-income group.

Q4 has a significant difference at the 0.05 level for Q12-1 (F = 3.310, p = 0.011). The comparison with significant differences is lower income > low income; lower income > middle income; lower income > high income; higher income > middle income; higher income > high income. This indicates that the lower-income group has a significantly higher preference for ‘externally equipped with leisure functions’ than the low-income, middle-income, and high-income groups. The preference of high-income groups for ‘externally equipped with leisure functions’ is significantly higher than that of middle- and high-income groups.

Q4 has a significant difference at the 0.05 level for Q12-2 (F = 2.846, p = 0.024). The comparison with significant differences is lower income > low income; higher income > low income; lower income > middle income; higher income > middle income. This indicates that lower- and higher-income groups have a significantly higher preference for ‘there is no leisure function set externally’ than low- and middle-income groups.

Q4 has a significant difference at the 0.05 level for Q13-1 (F = 3.207, p = 0.013). The comparison with significant differences is lower income > middle income; higher income > middle income; high income > middle income. This indicates that lower-income, higher-income, and high-income groups have significantly higher preferences for ‘natural-textured materials’ than the middle-income group.

Q4 has a significant difference at the 0.05 level for Q13-2 (F = 2.679, p = 0.031). The comparison with significant differences is lower income > low income; lower income > middle income; higher income > middle income. This indicates that lower-income groups have a significantly higher preference for ‘modern-textured materials’ than low and middle-income groups. The preference of high-income groups for ‘modern-textured materials’ is significantly higher than that of middle-income groups.

Q4 has a significant difference at the 0.05 level for Q15-1 (F = 3.280, p = 0.011). The comparison with significant differences is lower income > middle income; lower income > higher income. This indicates that the lower-income group has a significantly higher preference for ‘colorless series’ than the middle- and higher-income groups.

Q4 has a significant difference at the 0.01 level for Q17-1 (F = 4.020, p = 0.003). The comparison with significant differences is lower income > middle income; higher income > middle income; high income > middle income. This indicates that lower-income, higher-income, and high-income groups have significantly higher preferences for a ‘single color scheme’ than the middle-income group.

Q4 has a significant difference at the 0.01 level for Q17-2 (F = 3.935, p = 0.004). The comparison with significant differences is lower income > low income; higher income > low income; lower income > middle income; higher income > middle income. This indicates that the preferences of lower- and higher-income groups for ‘multiple color schemes’ are significantly higher than those of low- and middle-income groups.

5. Discussion

Firstly, according to research data, the YZ generation in China frequently visits coffee shops, with the current Generation Y being more frequent. In addition, the YZ generation is very concerned about the environment of coffee shops. Moreover, they not only consider the façade as an important factor in choosing a coffee shop but also revisit the store due to a façade that meets their aesthetic preferences. This is more evident in Generation Y. This result indicates that the design of coffee shop façades can not only attract consumers, but also influence their willingness to visit, which is consistent with the research findings of Orth U. R. et al. [15,42], and this theory is also applicable to the YZ generation in China.

In addition, the frequency of YZ generation visiting coffee shops, selection criteria, and basic evaluations of the façade are basically consistent. At the gender level, YZ generation consumers of different genders have similar criteria for choosing coffee shops and basic evaluations of their appearance. However, there are significant differences in the frequency of women visiting coffee shops compared to men. From the perspective of income level, there are significant differences in the frequency of coffee shop visits, selection criteria, and basic evaluation of the façade among the YZ generation with different income levels. The research results also indicate that there is a significant difference in the perception of coffee shop façades between the lower-income and middle-income groups in the YZ generation.

Secondly, the data results show that the YZ generation exhibits a common preference for multiple design dimensions, especially in pursuing simple geometric forms in façade design and high-brightness color schemes, which differs from the style that architecture students are more concerned about [49]. In addition, the YZ generation exhibits slight differences in certain specific elements: Generation Y prefers non-independent contours, no external leisure functions, natural materials, low brightness, and façades decorated with natural elements, while Generation Z prefers completely independent, transparent lines of sight, external leisure functions, different material textures, high brightness, and façades decorated with popular elements. From this, it can also be seen that compared to Generation Z, Generation Y prefers relatively simple, stable, and natural façades; Generation Z prefers relatively complex, lively, and modern façades. The core content that distinguishes the YZ generation is age. This aesthetic difference reflects whether it is caused by long-term exposure to specific design styles or whether aesthetic changes occur with age. To address this issue, we hope to conduct more in-depth qualitative research on the Chinese Generation Y in future studies.

Thirdly, at the gender level, the YZ generation has consistent preferences for the model form, visual form, material type, color system, brightness, and decorative elements of exterior façades. Among them, women have higher preferences for model form, contour form, line of sight form, material texture, brightness, decorative element types, and multi-color color matching methods than men. It can be seen that women are more sensitive to the appearance of design and attach more importance to the aesthetic and aesthetic value of façade design [64], and men have a higher preference for functional types, material types, color series, and single color façade forms than women, which shows that men pay more attention to technical and functional characteristics, and their preferences are also more concise [65]. This conclusion can also be explained from the perspective of gender perception differences in visual elements. Women have a more detailed perception of color and light when entering architectural spaces, while men are more sensitive to the combination of geometric shapes and forms [66]. In addition, this conclusion is consistent with the viewpoint proposed by A et al. that “men generally prefer symmetrical and less complex architectural appearances, while women may have a higher tolerance for complexity” [67].

Fourthly, from the perspective of income, the aesthetic differences in façade design caused by income disparities among the YZ generation are significant, especially in terms of aesthetic differences in the contour form, line of sight form, functional type, material type, and color matching method of the façade. Among them, lower-income and higher-income groups gave more positive evaluations, while middle-income and low-income groups gave more negative evaluations. The lower-income group has the most positive evaluation of various design contents, while the middle-income group has the least positive evaluation. This result cannot verify the notion that higher economic levels place greater emphasis on design aesthetics as demonstrated in relevant research [68]. As for why there are significant aesthetic differences in the design of façades between the lower and middle-income groups in China’s YZ generation, more targeted research is needed to explain and clarify.

Fifthly, based on the theoretical framework and data results of this study, we believe that relevant enterprises, brands, and designers can consider using modernist style as the foundation when designing the façade of coffee shop buildings, adding visual stimulation and popular decorative elements to the façade. For example, by using simple geometric forms, constructing independent contours, ensuring transparent façade views, and adding some popular elements on the basis of modern-textured materials, such designs will be more favored by the Chinese youth group.

6. Conclusions

Firstly, from the perspectives of generation and gender, there is a certain degree of uniformity in the basic understanding and selection criteria of coffee shops, as well as aesthetic preferences for façade design among the YZ generation in China. This discovery is helpful and traceable for designers and brands to shape a coffee shop façade that is accepted by the YZ generation. From a historical perspective, a long-term relatively fixed and unified aesthetic is an important foundation for style formation. For the YZ generation in China, the unity of their aesthetic preferences can serve as an important basis for promoting style formation.

Secondly, the Chinese YZ generation has a preference for simple geometric forms of façades, completely independent façade contours, fully transparent façades, and façades with modern material textures, indicating a clear modernist tendency in their aesthetics. And their preference for color schemes, high brightness, multi-color combinations, and façades with added popular elements also indicates their pursuit of a lively and visually stimulating façade.

Thirdly, the results of the data show that there is no significant difference in the cognitive and aesthetic preferences of Chinese YZ generation consumers toward the façade of coffee shops at the generational and gender levels. The differences in their cognitive and aesthetic preferences are more reflected in their income level. This provides us with a good reference standard when conducting related research and design, that is, to explore more about the aesthetic conditions of design under different income levels.

Fourthly, from the research results, it can also be seen that the evaluation of coffee shop façade design by the Chinese YZ generation is more positive for lower-income, higher-income, and high-income groups, while the evaluation of middle-income and low-income groups is less positive. This result is of certain reference value for enterprises, brands, and designers when designing a targeted coffee shop façade with a clear understanding of the target consumer’s income status. The model and results of this study are valuable. In addition, the results of this study can also indirectly indicate that research related to the YZ generation and design can be conducted from the perspective of income level.

Fifthly, among various income groups, the middle-income group and the lower-income group are two very special groups. The lower-income group is the group that gives more positive evaluations of various content, while the middle-income group is the group that gives more negative evaluations of various content. Why do they display such evaluation results? How do we better enhance the attractiveness of external faces to them? Which of the currently displayed content is more appealing to them, which is not, and which designs are not presented in this study that are attractive to them? These questions are interesting and worthy of further research, and they are also important directions for future research in this study.

It is worth noting that the data results of this study were developed within the framework of this research, and modifications to the framework may result in fluctuations in the data results. In addition, this study considers the diversity and cultural complexity of China’s regions, and lists regions as dimensions for analysis. Due to the influence of geography and culture, there may also be differences in aesthetic preferences within specific regions. This is also the main limitation of this study.

In summary, this study fills the gap in the aesthetic preferences of Chinese youth toward the façade design of coffee shop buildings, and we hope that the results of this study can provide valuable guidance for relevant enterprises, brands, and designers in constructing the façade design of coffee shops. We hope to expand this impact and value through further in-depth research in the future.