Rethinking the Sustainability of Industrial Buildings in High-Density Urban Areas: Balancing Adaptability and Public Satisfaction

Abstract

In the context of land scarcity and high-density urban areas, the adaptive reuse of abandoned historical industrial buildings plays a critical role in achieving sustainable development goals. This study proposes a sustainability assessment framework for the adaptive reuse of industrial buildings as exhibition spaces within the context of high-density urban development, addressing multiple dimensions of sustainability, including the building’s physical structure, economic factors, environmental impact, social considerations, and governance. The framework consists of 55 design indexes, categorized into 15 subcategories and 5 main categories. We conducted a survey of experts with experience in high-density urban renewal design and implemented a weighting analysis to identify priority intervention measures for industrial building redevelopment in the era of urban stock. Finally, a fuzzy comprehensive evaluation was carried out on ten cases in Shenzhen where industrial buildings were converted into exhibition spaces over the past 12 years. The findings reveal the following: (1) “Reuse of old architectural spaces” is the most critical category to prioritize, and, at the indicator level, “adaptability and efficiency of building reuse”, “public participation in the renewal process”, “cooperative operation structures”, and “planning vision” are identified as the four key influencing factors. (2) The functional layout, historical value, and richness of public amenities in the transformed industrial buildings have a significant positive impact on the evaluation results, while the building’s construction time and floor area do not significantly affect public post-evaluation. (3) Younger and more highly educated groups tend to view the transformed exhibition spaces as tourist attractions, particularly expressing satisfaction with the repurposing of the Kinwei Brewery and OCAT B10 New Hall, and consider the adaptive reuse of industrial buildings to promote sustainable urban renewal (SUR). This study provides concrete policy recommendations and practical guidance for the adaptive reuse of both new and existing industrial buildings, contributing to the creation of sustainable urban environments.

1. Introduction

As urbanization in China progresses at an accelerated pace, the speed of urban renewal has similarly increased [1]. The expansion of urban centers has resulted in the gradual migration of industrial zones from peripheral areas to the city core. Coupled with policy factors such as industrial restructuring, numerous traditional industrial factories have been compelled to relocate, leading to the abandonment of former industrial sites. In parallel, the repurposing and renovation of existing industrial buildings have become pressing issues of growing concern [2,3]. Taking Shenzhen as a case study, the restructuring and upgrading of the industrial sector have led to the decline of traditional manufacturing industries. Historical industrial buildings, as key components of cultural heritage, hold significant cultural and historical value [4]. These structures not only represent often-overlooked urban resources, but also play a crucial role in fostering social, economic, and cultural vitality [5,6,7]. However, the adaptive reuse of these buildings faces challenges, such as the risk of losing local identity and distinctive features [8,9]. Against the backdrop of limited land resources in high-density cities and the onset of the “stock era”, exploring sustainable adaptive reuse strategies for industrial buildings has become an urgent task.

Over the past decade, there has been a growing interest among experts and government agencies in the adaptive reuse of abandoned buildings, particularly those of historical and cultural significance. In the process of transforming existing industrial buildings, adaptive reuse through functional conversion has emerged as a key strategy for SUR, contributing significantly to the revitalization of historical structures [10]. This approach integrates socio-economic, cultural, and environmental factors to promote community vitality and ensure sustainable development [11]. Adaptive reuse involves converting structurally sound older buildings for new, economically viable purposes, offering a broad solution to sustainability challenges [12]. Potential transformations include residential spaces [13], schools [14], offices [15], commercial spaces [16], museums [17], and exhibition halls [18]. Among these, the conversion of industrial buildings into exhibition halls and museums has gained prominence [19]. These projects not only extend the lifespan of buildings but also preserve community identity [20], reduce waste, stimulate social vitality [21] and tourism [22], and enhance both the functionality and economic value of the buildings [23].

While numerous studies have examined the relationship between adaptive reuse and sustainability, most have focused on specific building characteristics or environmental factors [24,25,26]. Given the current post-industrial developments in China and their impact on various facets of the built environment, there is a pressing need to establish a comprehensive set of sustainability indicators for the adaptive reuse of industrial buildings.

Previous studies have focused on core sustainable development goals, failing to comprehensively cover the broader dimensions. In particular, the adaptability of building structure and functional space plays a crucial role in urban sustainability, especially during the architectural design process [27]. Additionally, many studies concentrate on objective indicators, overlooking a comparative analysis of public participation and subjective experiences. In reality, the public’s subjective experience is essential for assessing adaptive reuse, warranting further investigation. Therefore, this study proposes an evaluation framework for the adaptive reuse of industrial buildings in high-density urban areas, covering multiple dimensions of SUR, including the following five categories: building structure, economic, environmental, social, and governance. Expert assessments, based on their experience in adaptive reuse design, are conducted for each strategy to ensure effective prioritization that addresses real-world challenges. Furthermore, AHP is used to develop the evaluation indicator system. Finally, a comprehensive evaluation approach is employed to gather public feedback on the conversion of ten industrial buildings into exhibition spaces, obtaining subjective assessments. By analyzing the similarities and differences between expert and public evaluations, this study aims to eliminate subjectivity and bias among stakeholders. The results are intended to provide practical, comprehensive guidance for industrial building design in the post-industrial era and assist decision-makers in prioritizing planning indicators. Incorporating public preferences into industrial building design not only improves residents’ health and well-being but also enhances the efficiency of adaptive reuse, aligning with long-term sustainability goals.

2. Selection of Indicators for the Adaptive Reuse of Industrial Buildings as Exhibition Spaces

The adaptive reuse of buildings is increasingly recognized as an effective means of activating urban assets and resources [28,29]. Research has examined its significance from various angles, including from economic, social, environmental, governance, and architectural perspectives [30,31]. These dimensions are interconnected, collectively highlighting the substantial contribution adaptive reuse can make to sustainable development.

As shown in

Table 1. Summary of evaluation indexes for adaptive reuse of industrial buildings.

Year	Country	Subject	Evaluation Index (First Class)	Assessment Method	Refs.
2023	Malaya	This study presents a comprehensive evaluation model, fostering sustainable urban regeneration.	Social, economic, environmental, and methodological.	AHP	[10]
2023	Italy	This study evaluates the most effective intervention strategies.	Social, cultural, financial.	MCDM	[32]
2022	China	This study establishes a satisfaction evaluation model for industrial heritage renewal.	Building regeneration effect, external environment perception, history, culture, and placeness, social influence, economic benefits.	SEM-IPA	[26]
2021	China	This study establishes an evaluation method and proposes an adaptive reuse strategy for historic buildings.	Architectural noumenon, spatial environment, multi-agent.	AHP+SEM	[33]
2020	Iran	This study presents Iran’s industrial heritage and assesses the authenticity criteria of industrial heritage preserved by adaptive reuse.	Historic, contemporary, craftsmanship, people oriented.	Questionnaire Survey	[14]
2019	Greece	This study identifies the key factors that affect local sustainability by using adaptive reuse projects.	Economy, society, environment, culture.	Fuzzy DEMATEL	[27]

, the diversity in research scope has led to varying standards for evaluating adaptive reuse, along with differences in the categories these standards encompass.

The reuse of industrial buildings reduces the consumption of new materials and land while also increasing cultural value through tourism, thereby supporting broader sustainability goals [34,35]. In addition, adaptive reuse projects provide significant socio-economic benefits, including enhanced urban appeal, job creation, and stronger social cohesion.

While adaptive reuse preserves a city’s cultural heritage and enhances its sense of place, such projects may also lead to challenges like gentrification [36]. From a sustainability perspective, the environmental quality and health of urban spaces are critical considerations, with future strategies expected to focus on further improvements in these areas. The relationship between industrial buildings and their surrounding environments reflects the urban form, suggesting that design should optimize not only the buildings themselves but also their surroundings [37]. This includes promoting green spaces, renewable resources, and energy self-sufficiency [38]. Enhancing the flexibility and quality of internal public spaces is also key to balancing urban architecture, ecology, and human interaction.

At the governance level, effective policy and legal frameworks are essential to support adaptive reuse. However, the diversity of public interests and the opacity of decision-making processes often breed distrust [39]. Therefore, it is crucial to coordinate multiple stakeholders to ensure the success of sustainable urban regeneration initiatives [40].

In order to evaluate the ability of industrial building adaptive reuse projects to achieve sustainable development, objective measurement tools are required. In recent years, scholars have proposed various quantitative methods to explore the issues of building adaptability. Currently, indicator-based evaluation methods for adaptive reuse can be categorized into three types: The first type utilizes existing community or urban sustainability indicators, such as the BREEAM-C and LEED-C models, to construct a comprehensive assessment framework suitable for urban regeneration projects [41]. The second type involves assessing specific indicators through various methods, such as the Delphi method [42], the AHP system [43], the MCDM model [44], ANN-based models [45], fuzzy sets [46], the DEMATEL approach [47], or different combinations of the above. The third type employs post-occupancy evaluation (POE) and Importance–Performance Analysis (IPA) models to analyze project satisfaction [48], focusing on human perception and social impact.

Given that the adaptive reuse of industrial buildings for exhibition purposes involves multiple disciplines, the selection of indicators for the evaluation system follows the principles of comprehensiveness, scientific rigor, and practicality, and is based on a thorough review of relevant standards and the literature [49]. The resulting design indicator system for the adaptive reuse of industrial buildings as exhibition spaces includes five major categories, fifteen subcategories, and fifty-five design indexes, as outlined in

Table 2. Evaluation indicators for adaptive reuse of industrial buildings.

Criterion Level	Solution Level	Indicator Level	Refs.
A. Architecture noumenon	A1 Construction safety	A11 Safety of building structure	[50,51,52,53]
		A12 Safety of building functions
	A2 Reuse of the old architectural space	A21 Adaptability and efficiency of building reuse	[26,32,52,54]
		A22 Impact of new functional space on the environment
		A23 Flexibility and efficiency of building reuse
		A24 Rationality of building layout
		A25 Diversity of building functions
		A26 Building density
	A3 Historical and cultural preservation	A31 Integration of old and new developments	[51,55,56]
		A32 Authenticity of industrial heritage
		A33 Restoration and reuse of industrial heritage
		A34 Retaining the original memory of the building
		A35 Reflects local characteristics
		A36 Preservation of complete and distinctive urban interfaces and alleys
		A37 Cultural display windows
	A4 Architectural art	A41 Integrity of original building facades, materials and decorations	[52,53,57,58]
		A42 The beauty of architectural shapes and decorative forms
		A43 Reflecting the level of local construction design and science and technology
		A44 Harmony between old and new architectural styles
B. Environment	B1 Reuse of environmental resources	B11 Reuse of original building materials	[59,60,61]
		B12 Use of renewable energy
		B13 Protection and restoration of surrounding natural resources
		B14 Rainwater management
	B2 Pollution	B21 Air pollution	[58,61,62,63]
		B22 Noise pollution
		B23 Water pollution
	B3 Site traffic	B31 Ease of external transportation	[20,32,48]
		B32 Accessibility of internal transportation
		B33 Recognizability of spatial signage system
		B34 Convenience of site parking on the site
	B4 External environmental quality	B41 Redevelopment of contaminated areas	[26,32]
		B42 Enrichment of public space
		B43 Aesthetics of street space
		B44 Transition and connection between environmental landscape and surrounding buildings
		B45 Diversity of green landscape
C. Society	C1 Social well-being	C11 Number and distribution of public service facilities	[26,50]
		C12 Percentage of public green space
		C13 Completeness of barrier-free facilities
		C14 Diversification of dining and consumption facilities
	C2 Public identity	C21 Social identity	[48,56,64]
		C22 Sense of belonging to the site/sense of place
		C23 Public satisfaction
	C3 Public participation	C31 Public participation in the renewal process	[65,66,67]
		C32 Public participation in venue activities
D. Economics	D1 Economic feasibility	D11 Provides more local employment opportunities	[68,69]
		D12 Attracts investment
		D13 Promotes local economic growth
	D2 Economic vitality	D21 Promotes cultural tourism	[26,64,70]
		D22 Redevelopment of traditional industries
		D23 Enhancement of neighboring property prices
		D24 Optimization of industrial structure
E. Govern	E1 Policy making	E11 Laws and regulations	[16,71]
		E12 Planning vision
	E2 Partnership	E21 Incentives	[64,72,73]
		E22 Cooperative operation structure

.

3. Materials and Methods

3.1. Research Framework

The research framework for this study is illustrated in Figure 1. The first step involves defining the research problem. Through a comprehensive literature review and background analysis, a holistic indicator system for sustainable regeneration in the adaptive reuse of industrial buildings is established. This system encompasses a set of detailed standards, covering five categories: building structure, economy, environment, society, and governance. Each category is further divided into subcategories that address various aspects of adaptive reuse. Subsequently, an expert survey is conducted to determine the weight of each factor. Next, a comprehensive evaluation method is applied to collect public feedback on the transformation of ten industrial buildings into exhibition spaces, capturing subjective assessments. Finally, the evaluation results from both the experts and the public are compared, the challenges encountered in practical transformation cases are analyzed, and strategies for future design modifications are proposed. We initially collect the raw data using “Questionnaire Star” software (v2024), and subsequently analyze the data with “Spasspro” software (v2024) to obtain the final results.

3.2. Sources of Research Cases

The research subject is Shenzhen, a coastal city of Guangdong–Hong Kong–Macao Greater Bay Area. Since the 1980s, Shenzhen has undergone rapid industrial restructuring and urbanization, leading to the relocation of numerous industrial enterprises from the city center to the outskirts, resulting in significant changes to urban functions and spatial structures. With the migration of polluting and labor-intensive industries, many industrial buildings and warehouses have been left vacant, making the transformation of industrial buildings a key issue in urban revitalization strategies [74]. This research examines industrial buildings in Shenzhen that have been converted into exhibition spaces over the past twelve years, analyzing their roles in and impacts on urban revitalization through the investigation of ten transformation projects. The detailed characteristics of the cases are shown in

Table 3. Case characteristics of the typical industrial buildings in Shenzhen city.

Name	Pre-Transformation Function	Building Renewal Time	Overall Floorage (m2)
$X1:ZhiArtMuseum$	Plant workshop	2018	1100
$X2:ShajingVillageHall$	Plant workshop	2020	2500
$X3:WorkshopinBaoanWetlandPark$	Plant workshop	2023	3000
$X4:DachengFlourMill$	Flour mill	2015	33000
$X5:ValueFactory$	Float glass factory	2013	17356
$X6:OCATB10NewHall$	Furniture factory	2022	6109
$X7:KinweiBrewery$	Brewery	2023	12309
$X8:SculptureArtCreativePark$	Plant workshop	2021	3000
$X9:ManjinghuaArtMuseum$	Honghua printing and dyeing factory	2014	3524
$X10:DapengGranary$	Granary	2021	730

.

3.3. Research Data

3.3.1. Research Data on Expert Surveys

The expert survey targeted experts in urban planning, architectural design, and heritage conservation, including Shenzhen municipal government officials, academics, and engineers. This survey was conducted through an online questionnaire from 5 March to 5 May 2024, with three rounds of questionnaire distribution. Each subsequent questionnaire was modified and confirmed based on the feedback from the previous round. Over the course of 12 weeks, a total of 40 questionnaires were distributed, and 21 responses were collected. The questionnaire consisted mainly of sections related to the AHP and sections pertaining to the respondents’ personal information (

Table 4. Information statistics of the Delphi experts.

Categories		Percentage (%)
$Institute$	Design agency	36
	Government organization	30.20
	Academia	33.80
$Distributionofresearchfields$	Urban planning	32.56
	Architecture design	47.82
	Urban conservation	19.62
$Workyears$	10–20 yrs	68.58
	20–30 yrs	26.19
	>30 yrs	5.23
$Educationattainment$	Graduate student or above	77.90
	Undergraduate	22.10

).

3.3.2. Research Data on Public

The formal questionnaire distribution employed a combination of online and offline methods, and was conducted over a period of 16 weeks from December 2023 to March 2024. A total of 250 questionnaires were distributed, with 210 valid responses collected. In response to the diversity of the public, statistics were gathered on respondents’ gender, age, occupation, transportation choices, and purpose of visit (

Table 5. Some basic information related to the survey participants.

Categories		Percentage (%)
$Gender$	Male	62
	Female	38
$Age$	Below 30	65
	31–45 years old	24
	46–60 years old	9
	Above 60 years old	2
$Occupation$	General tourist	58
	Local resident	24
	Merchant	15
	Landlord	3
$Choiceoftransportation$	Bus/subway	76
	Cab	12
	By car	9
	Walking	3
$Purposeofvisit$	Visiting the remodeled building	22
	Visiting exhibitions	30
	Sightseeing and photography	41
	Other	7
Points of concern for  industrial building renovation	External open space	8
	Exhibition space	15
	Formal elevation	19
	Leisure experience space	31
	Building structure	5
	Artistic creation, graffiti, logo	22

).

3.4. Research Methodology

3.4.1. Delphi Method

In the 1950s, the Delphi method was initially employed by the RAND Corporation for qualitative forecasting [75]. This method, based on fuzzy mathematical theory, transforms experts’ subjective opinions into quasi-objective data, and represents the evaluation values of indicators with fuzzy numbers. The fuzzy Delphi method achieves research objectives by comprehensively considering the uncertainty and vagueness in expert thinking. Today, the Delphi method is widely applied in the study of historical heritage value assessment [26,76], with its advantages including anonymous voting and avoidance of face-to-face communication, ensuring the confidentiality of collective thought [77]. This study employs the Delphi method to determine the weights of various indicators in the AHP as it is widely used in urban heritage value assessment, and anonymous evaluation helps ensure the authenticity of the data.

3.4.2. Analytic Hierarchy Process (AHP)

The AHP method combines qualitative and quantitative research, utilizing a hierarchical and systematic structure [78]. Its main advantage lies in its hierarchical diagram, which succinctly presents complex multi-objective and multi-level assessments, clearly expressing the relationships between various factors. It is widely applied across different fields due to its practicality and effectiveness in addressing complex decision-making problems [79]. The adaptive reuse of industrial buildings involves multiple dimensions and scales, representing a complex urban system. AHP addresses these complex decision-making issues by constructing a structure that links the main objectives to various levels of indicators [80]. The hierarchical structure model (Figure 2) includes the goal layer, criterion layer, solution layer, and factor layer.

Data validation of the weight calculation of the indicators, including the Consistency Index (CI) and Random Index (RI) tests, which can be used to check the appropriateness of the conclusions of the hierarchical analysis method, can be performed by using Equations (1)–(3).

$$\begin{array}{cc}\hfill CI& ={\displaystyle \frac{{\lambda }_{max}-n}{n-1}}\hfill \end{array}$$

(1)

$$\begin{array}{cc}\hfill RI& ={\displaystyle \frac{{\lambda }_{max,avg}-n}{n-1}}\hfill \end{array}$$

(2)

$$\begin{array}{cc}\hfill CR& ={\displaystyle \frac{CI}{RI\left(n\right)}}<0.1\hfill \end{array}$$

(3)

Here, ${\lambda }_{max}$ denotes the maximum eigenvalue and n represents the number of alternatives. The consistency ratio (CR) should be less than 0.1. However, if the CR is more than 0.1, the evaluation process must be repeated [81].

3.4.3. Fuzzy Comprehensive Evaluation Method

Fuzzy comprehensive evaluation is an application of fuzzy mathematics that utilizes fuzzy transformation and the principle of maximum membership degree to perform a comprehensive assessment of multiple factors [82]. For objects influenced by a small number of factors, a single-layer model is applicable, whereas, for more complex objects affected by multiple factors, two-layer or multi-layer models are used [83]. This study adopts a two-layer fuzzy comprehensive evaluation model as the assessment tool for the adaptive reuse of industrial buildings in Shenzhen. The application steps are as follows:

Step 1. Establish the factor set.

Based on the characteristics of the evaluation index system, the factors in the evaluation relationship are set as follows: U = {$u_1$, $u_2$, $u_3$,…, $u$}. The evaluation factors consist of 55 indicators, arranged in order (Table 4).

Step 2. Determine the set of comments. The weights of the indicators represent the varying impacts on the adaptability of industrial buildings. The weight set W consists of the weights of the 55 indicators, where $W_i$ denotes the weight of the i-th factor. Weights refer to the proportion of each evaluation factor in the evaluation index system based on relative importance. When a weight is assigned to a specific factor, the weight distribution set W can be viewed as a fuzzy set of the set U. Determining the weight of each factor is a core task of the evaluation system. As described in Section 4, we use a fuzzy analytic hierarchy process (FAHP) to determine the weights of the factors and sub-factors in the evaluation index system.

Step 3. Establish the evaluation description set. The set of evaluation opinions is defined as V= $v_1$, $v_2$, $v_3$,…, $v_m$. This study utilizes a four-level evaluation system, with opinions set as V = Excellent, Good, Fair, Poor. To quantify these indicators, we assign corresponding grades on the evaluation forms: V = A, B, C, D.

Step 4. Establish the single-factor evaluation matrix. For each factor in the set U, the membership degree of that factor is calculated based on the evaluation description set. When the evaluation object is judged by the factors $U_i$ in the factor set, the membership degree of that factor in the evaluation description $V_j$ is denoted as $R_{ij}$. Therefore, the fuzzy evaluation set $R_i$ can be expressed by Equation (4):

$$\begin{array}{cc}\hfill R_i& ={\left(r_{ij}\right)}_{n\times m}\hfill \\ & =\left(\begin{array}{cccc}{r}_{11}& r_{12}& \cdots & r_{1m}\\ r_{21}& r_{22}& \cdots & r_{2m}\\ ⋮& ⋮& \ddots & ⋮\\ r_{s1}& r_{s2}& \cdots & r_{sm}\end{array}\right)\hfill \end{array}$$

(4)

In the equation, $r_{ij}$ denotes how much factor $U_i$ belongs to the category defined by comment $v_j$.

Step 5. Determine the factor weights.

The evaluation matrix for the adaptability of industrial buildings represents the relationship between the evaluation factor set U and the evaluation description set V. The evaluation matrix B is a matrix with 5 columns and 55 rows, where each column value corresponds to an indicator in U. Each row’s 1st, 2nd, 3rd, and 4th elements, respectively, represent the membership degrees of Excellent, Good, Fair, and Poor in V. This paper forms the fuzzy comprehensive evaluation set B by summing the product of each factor value and its weight. The weighting set W and the fuzzy evaluation set R are subjected to a fuzzy transformation (as shown in Equation (5)).

$$\begin{array}{cc}\hfill B& =W·R=(b_1,b_2,b_3,\cdots ,b_m)\hfill \end{array}$$

(5)

In the formula, B represents the evaluation results based on all factors in the indicator system U. The k-th element bk signifies the membership degree of the evaluation object concerning the k-th element in the evaluation set. By utilizing the principle of maximum membership degree, a comprehensive evaluation conclusion can be derived.

Step 6. Produce the evaluation result.

Taking $b_i$ as the weight and the evaluation factor $v_j$ as the weighted average, v is the result of the fuzzy comprehensive evaluation that can be calculated by Equation (6). The specific scoring range is shown in

Table 6. Adaptive reuse scores for industrial buildings.

Ranking	Description	Mark
A	Excellent Most indicators fulfill the requirements of the comprehensive fuzzy assessment to a high degree, and the industrial buildings show a high adaptability.	85–100
B	Good. Most indicators fulfill the requirements of the fuzzy comprehensive evaluation, and the industrial buildings have high adaptability.	75–85
C	Fair Some indicators meet the requirements of the fuzzy comprehensive evaluation, and the industrial buildings have a general adaptability.	60–75
D	Poor Most of the indicators of industrial buildings cannot meet the general requirements of the overall fuzzy comprehensive evaluation, and the adaptability of the industrial buildings is poor.	0–60

.

$$\begin{array}{cc}\hfill v& ={\displaystyle \frac{{\sum }_{j=1}^m{b}_j{v}_j}{{\sum }_{j=1}^m{b}_j}}\hfill \end{array}$$

(6)

4. Results

4.1. Results of the AHP Expert Evaluation Form

The adaptive reuse of industrial buildings faces the challenge of a lack of consensus on sustainable development. Therefore, establishing a clear and comprehensive indicator model to monitor the renovation process is crucial. Expert participation in the development of urban heritage indicators plays a key role in the success of sustainable development projects [72]. It is essential to ensure that the indicators meet criteria such as quality, feasibility, policy relevance, and measurability [73]. In this study, based on the Appendix A, the AHP is employed to prioritize the indicators, construct a logical framework, systematize decision-making, and allocate weights to each indicator, as shown in

Table 7. Indicators and weights for industrial building renewal in Shenzhen.

Criterion Level	W	Solution Level	W	R	Indicator Level	W	R
A.  Architecture  noumenon	0.317	A1  C. S.	0.51	11	A11 Safety of building structure	0.033	3
					A12 Safety of building functions	0.018	4
		A2  Reuse in the old architectural space	0.12	1	A21 Adaptability and efficiency of building reuse	0.035	1
					A22 Impact of the new functional space on the environment	0.017	5
					A23 Flexibility and efficiency of building reuse	0.034	2
					A24 Rationality of building layout	0.011	10
					A25 Diversity of building functions	0.009	11
					A26 Building density	0.014	7
		A3 Historical and cultural preservation	0.09	4	A31 Integration of old and new developments	0.027	4
					A32 Authenticity of industrial heritage	0.006	13
					A33 Restoration and reuse of industrial heritage	0.016	6
					A34 Retaining the original memory of the building	0.009	11
					A35 Reflects local characteristics	0.013	8
					A36 Preservation of complete and distinctive urban interfaces and alleys	0.011	10
					A37 Cultural display windows	0.008	12
		A4  Architectural art	0.056	8	A41 Integrity of original building facades, materials, and decorations	0.017	5
					A42 The beauty of architectural shapes and decorative forms	0.012	9
					A43 Reflecting the level of local construction design and science and technology	0.013	8
					A44 Harmony between old and new architectural styles	0.014	7
B.  Environment	0.198	B1 Reuse of environmental resources	0.04	13	B11 Reuse of original building materials	0.001	7
					B12 Use of renewable energy	0.008	9
					B13 Protection and restoration of surrounding natural resources	0.015	3
					B14 Rainwater management	0.007	10
		B2 Pollution	0.039	14	B21 Air pollution	0.019	1
					B22 Noise pollution	0.006	11
					B23 Water pollution	0.014	4
		B3 Site traffic	0.052	10	B31 Ease of external transportation	0.001	7
					B32 Accessibility of internal transportation	0.015	3
					B33 Recognizability of spatial signage system	0.014	4
					B34 Convenience of site parking on the site	0.013	5
		B4 External environmental quality	0.067	6	B41 Reconstruction of contaminated area	0.009	8
					B42 Enrichment of public space	0.016	2
					B43 Aesthetics of street space	0.012	6
					B44 Transition and connection between environmental landscape and surrounding buildings	0.016	2
					B45 Diversity of green landscape	0.014	4
C. Society	0.217	C1 Social well-being	0.064	7	C11 Number and distribution of public service facilities	0.018	5
					C12 Percentage of public green space	0.021	7
					C13 Completeness of barrier-free facilities	0.014	4
					C14 Diversification of dining and consumption facilities	0.011	8
		C2 Public identity	0.056	9	C21 Social identity	0.016	6
					C22 Sense of belonging to the site/sense of place	0.022	3
					C23 Public satisfaction	0.018	5
		C3 Public participation	0.097	3	C31 Public participation in the renewal process	0.061	1
					C32 Public participation in the venue activities	0.036	2
D. Economics	0.086	D1 Economic feasibility	0.036	15	Provides more local employment opportunities	0.013	2
					D12 Attracts investment	0.011	4
					D13 Promotes local economic growth	0.012	3
		D2 Economic vitality	0.05	12	D21 Promotes the tourism industry	0.015	1
					D22 Redevelopment of traditional industries	0.012	3
					D23 Enhancement of neighboring property prices	0.001	5
					D24 Optimization of industrial structure	0.013	2
E. Governance	0.182	E1  Policy making	0.079	5	E11 Laws and regulations	0.027	4
					E12 Planning vision	0.052	2
		E2  Partnership	0.103	2	E21 Incentives	0.041	3
					E22 Cooperative operation structure	0.062	1

where “C. S.” is short for “construction safety”.

. This approach is particularly effective for addressing the complex issues involved in the reuse of historical buildings and helps to minimize decision-making bias.

4.2. Evaluation Results for Adaptive Reuse of Industrial Buildings in Shenzhen

Figure 3, Figure 4 and Figure 5 summarize the weighted results of the indicator system for the adaptive reuse of industrial buildings in the context of Shenzhen’s high-density urban development. This chart illustrates the relative assessment weights across three categories. The “building structure adaptability” (A) category holds the highest weight at 0.317, followed by the “social dimension” (C) with a weight of 0.217. The “environmental dimension” (B) ranks third, with a weight of 0.198. The importance of building entity adaptability lies in its direct impact on structure, material recyclability, and lifespan. These factors determine the feasibility and economic viability of the renovation. The high weight of the social dimension underscores the critical role of public participation, cultural heritage, and social cohesion in modern urban renewal. Although the environmental dimension ranks third, its position is expected to improve in the future, particularly in the context of deepening sustainable development and the need to address climate change and resource scarcity. The scientific establishment of these weights not only provides a basis for the current study but also guides policymakers in prioritizing and directing planning efforts in practical applications.

In the dimension of building entity adaptability, the adaptability and efficiency of building reuse (A21) have the highest weight (0.035), indicating that flexible and efficient use of space is paramount in adaptive reuse. As urban functions evolve, the importance of historical building preservation in urban renewal is increasing, with heritage being considered holistically alongside other urban elements. Mixed land development is an effective strategy for addressing land resource scarcity and promoting sustainable development.

In the social dimension, public participation in venue activities (C32) carries the highest weight (0.061), highlighting the importance of the public in urban renewal. However, the traditional top-down renewal model often neglects the needs of various stakeholders, leading to issues such as a lack of spatial justice and the disruption of community networks [84]. Although the government attempts to encourage public participation through announcements and hearings, these are mostly forms of “informing” rather than “empowering”, leaving the public with limited influence in decision-making [73].

In the environmental dimension, air pollution (B21) holds the highest weight (0.019). Restoring old buildings not only optimizes land use but also reduces construction pollution, minimizes material consumption, and promotes sustainable development [85]. Additionally, the redevelopment of polluted areas and the conservation of natural resources also deserve attention.

In the economic dimension, promoting the tourism economy (D21) carries the highest weight (0.015). The adaptive reuse of industrial buildings not only provides new cultural experiences but also becomes one of the driving forces of economic growth by boosting the tourism industry [86].

In the governance dimension, the importance of collaborative structures (E22) ranks highest. In recent years, multi-agency collaborations or “joint partnerships” have become a key advantage in urban renewal. In China, local governments shoulder a significant portion of the renewal responsibilities, making efficient coordination mechanisms and approval processes crucial for the participation of non-governmental entities [87].

4.3. A Post-Evaluation Analysis of Ten Industrial Buildings Converted into Exhibition Spaces from the Perspective of Diverse Public Stakeholders

The fuzzy comprehensive evaluation method is adopted to calculate the adaptive values of the AHP evaluation indicators (building entities, society, environment, governance, and economy) of 10 industrial buildings converted into exhibition halls. The adaptive values of transforming industrial buildings into exhibition halls mostly range between 60 and 75, with 70% of the industrial buildings rated as A and B based on the score range. From the results of the factor-level weight calculations, it can be seen that the functionality of the building after renovation has a significant impact on the adaptability of industrial buildings. The diversified functions within the renovated exhibition spaces, along with well-developed surrounding facilities, contribute to the high adaptability scores, allowing them to fully realize the potential of cultural networks in SUR.

The results of the field research indicate that the public has a high level of recognition for the transformation of industrial buildings into exhibition spaces, with 84% of respondents believing that they hold significant value. Most people feel that the renovated buildings can meet urban cultural needs and compensate for shortcomings in public cultural construction. Among the 10 cases, the Jinwei Brewery and OCAT Shenzhen B10 New Museum received the highest audience favorability due to their diversified functions, accounting for 24.1% and 19.7%, respectively (Figure 6). The Dapeng Fortress Granary is popular for its rich cultural atmosphere and historical memories, while the Value Factory and Oyster Lake Cultural and Creative Museum are recognized for their industrial cultural ambiance and the blend of old and new. In contrast, the Zhimei Art Museum lacks industrial memory and has a single-exhibition format; the Manjinghua Art Museum and Sculpture Art Creative Park are located in remote areas with insufficient supporting facilities; and the Dacheng Flour Mill has an outdated space and incomplete renovations, leading to lower favorability.

5. Discussion

Using the above methods, we have established the weight of evaluation criteria for the adaptive reuse of industrial buildings in high-density urban areas and determined the assessment scores for real-world case projects. In this section, we discuss the differentiated analysis of expert-assigned weights compared to public preference scores. Additionally, we provide practical recommendations for application and policy making to encourage the adoption of these strategies in both adaptive reuse projects and new constructions, aiming to enhance their sustainability.

5.1. Common Problems and Analysis

5.1.1. Several Types of Functional Supporting Services for the Exhibition Buildings

In the expert post-evaluation, greater emphasis is placed on the “adaptability and efficiency of building reuse” (A21), whereas visitors tend to prioritize the “flexibility and efficiency of building reuse” (A23). This divergence stems from the experts’ focus on design considerations, in contrast to the public’s greater concern for spatial perception. Furthermore, an analysis of the functional composition of the ten renovated buildings reveals that venues with a more diverse range of functions, such as the B10 Hall and Kinwei Brewery, are more popular, as shown in Figure 7. However, in practice, many renovation projects primarily concentrate on the layout of exhibition halls, often neglecting the integration of complementary functions. This imbalance leads to a lower level of functional completeness in the final design.

5.1.2. Homogeneous External Environment

In terms of external environmental quality (B4), issues relating to insufficient and monotonous design are common, and are mainly characterized by a lack of variety in green space configurations, monotonous spatial layouts, and neglect of pedestrian pathways, resting areas, and public facilities, which fail to meet the diverse needs of users. With the exception of Jinwei Brewery and OCAT B10, the other cases generally lack leisure design in external spaces, without considering temporary resting areas and facilities. Additionally, many designs fall short in addressing local climate conditions, natural landscapes, and social culture, leading to poor harmony with the surrounding environment. These limitations in external environment design affect the interaction between the buildings and their surroundings, diminishing the overall vibrancy and appeal of the overall spaces and failing to provide users with a rich sense of experience.

5.1.3. Creating the Exhibition Atmosphere

More than half of the cases neglected the design of leisure spaces, with the renovated exhibition buildings lacking consideration for the human-centered needs of visitors, as architects overly emphasized the purity of exhibition spaces. In the limited instances where leisure spaces were incorporated, relaxing environments were primarily achieved through the integration of seating areas and multifunctional steps. Among them, the Manjinghua Art Museum and Jinwei Brewery are typical examples, successfully shaping diverse leisure scenarios.

5.2. Suggestions for the Adaptive Reuse of Buildings

Dimensionality of building entities: In the process of the adaptive reuse of industrial buildings as exhibition spaces, the diversification of functional types significantly enhances the potential for varied spatial use, thereby increasing the flexibility and comprehensive service capacity of the building [13]. Furthermore, for buildings with moderate historical and cultural value, representative components and elements (such as materials, beams, columns, walls, and door frames) can be retained and transformed in conjunction with new exhibition spaces [88]. In the case of buildings with lower historical and cultural value, new cultural symbols can be introduced through graffiti, signage, and other means to reflect the spirit of the times.

Environmental dimension: While enhancing the internal space of the building, attention is also given to the sustainable and cyclical use of external environmental resources [89]. For industrial buildings with significant historical and cultural value, a preservation approach focused on intangible culture is typically adopted, treating the whole building as a display object to continue the legacy of industrial civilization. Meanwhile, by incorporating natural elements such as greenery, water features, and sculptures, a microclimatic effect is created. Design strategies such as material differentiation, the creation of stepped levels, the addition of corridors, and the integration of unique forms contribute to the formation of transitional spaces between indoor and outdoor areas [90]. These design approaches not only meet the functional requirements of exhibition buildings but also enhance the sense of place and sustainable usability of the building.

Economic dimension: By retaining and reusing existing building materials, not only is the generation of construction waste and the project’s carbon footprint reduced, but the historical memory and industrial cultural characteristics of the building are also conveyed. In addition, the reuse of materials must consider both technical feasibility and safety to ensure the physical properties, durability, and compatibility of these materials with the new functional spaces [59].

Social dimension: Enhancing urban residents’ connection to the adaptive reuse of industrial buildings is vital for advancing sustainable urban development and preserving cultural heritage. Achieving this requires increasing public awareness of the importance of industrial heritage. Educational and outreach initiatives can help deepen understanding of its historical, cultural, and environmental value. By fostering such awareness, communities will be better equipped to recognize and appreciate the significance of industrial buildings in the context of urban regeneration.

Governance dimension: Collaboration among multiple stakeholders is widely recognized as a key strategy for advancing urban renewal. To facilitate this, it is recommended to establish an integrated system that brings together various stakeholders [73]. This system should include the strengthening of laws and regulations, the implementation of incentives and constraints for private investors, and expert evaluation and guidance, as well as active participation and feedback from urban residents. Such an approach would foster a collaborative management framework that involves all relevant parties [91].

This study has the following limitations: (1) The reliability of the Delphi technique depends on the feedback from experts. Due to differences in expertise, experience, geographical location, and domain knowledge among the experts, the reliability and validity of the data may be at risk. Although the findings are supported by statistical analysis and the literature, varying opinions from different experts could lead to different research inputs. To reduce bias, future studies are recommended to expand the sample size and increase the number of respondents. (2) The evaluation indicators selected in this study are based on the characteristics of industrial buildings in Shenzhen, and the evaluation methods are applicable to urban industrial buildings in similar conditions. Future research could explore the impact of adaptive reuse of industrial buildings on urban development by broadening the geographic scope and research subjects, incorporating different demographic and economic backgrounds.

6. Conclusions

In the context of land scarcity and high-density urban areas, the adaptive reuse of abandoned historical industrial buildings has become an inevitable trend in future architectural development, with repurposing for exhibition spaces being one of the most common functional choices. This study proposes an evaluation indicator system for the adaptive reuse of industrial buildings as exhibition spaces, encompassing five major categories, fifteen subcategories, and fifty-five design indexes. To objectively and quantitatively assess these strategies, an expert survey was conducted, and a weight analysis was performed to identify priority interventions in the context of urban renewal and the existing building stock.

Based on this framework, we conducted a fuzzy comprehensive evaluation of ten industrial buildings in Shenzhen that were transformed into exhibition spaces over the past 12 years. We also compared the expert rankings with public satisfaction assessments. The findings are as follows: (1) Among the categories assessed, “reuse in the old architectural space” emerged as the most critical factor. At the indicator level, “adaptability and efficiency of building reuse”, “public participation in the renewal process”, “cooperative operational structures”, and “planning vision” were identified as the four key influencing factors. (2) The functional layout, historical value, and richness of public facilities in the renovated projects had a significant positive impact on the evaluation results, whereas the construction period and building area of the industrial buildings showed no decisive effect on public post-evaluation. (3) Younger and more educated groups tended to view exhibition halls as tourist attractions, particularly expressing satisfaction with the transformations of Kinwei Brewery and OCAT B10 New Hall, and view the adaptive reuse of industrial buildings as exhibition spaces as a key contributor to SUR.

This study is innovative in its development of a comprehensive evaluation model which compares expert assessments with public satisfaction. By doing so, it provides actionable recommendations for policymakers to more effectively allocate resources in the post-industrial era. The proposed indicator system not only supports the creation of relevant standards, but also enhances public awareness of the adaptive reuse of industrial buildings. Ultimately, it contributes to the development of healthier, more sustainable living environments and offers valuable insights for improving urban renewal outcomes in similar economic contexts.