Measuring museum sustainability in China: a DSR model-driven approach to empower sustainable development goals (SDGs)

In September 2015, the UN adopted the 2030 Agenda establishing 17 SDGs and 169 targets. Culture, heritage, and museums play a strategic role in advancing environmental, social, and economic sustainability. In 2022, ICOM incorporated sustainability into the museum definition, underscoring its relevance. Museums address climate change, pursue carbon neutrality, expand digital access, and advance diversity, equity, accessibility, and inclusion while catalyzing tourism and creative sectors. However, understandings and implementations of sustainability differ significantly across countries and regions. In China, most museums are state-owned, attract very large visitor numbers, and face challenges such as limited professional capacity, uneven regional development, insufficient accessibility for special populations, and a need for stronger social engagement and internal management innovation. To advance sustainability, two core aspects are essential: building deep, long-term relationships with diverse visitors and responding to changing political, social, environmental, and economic contexts with a clear long-term purpose. Research questions: 1) How can a museum define its sustainability strategy in accordance with the UN SDGs and targets? 2) Which indicators should be prioritized from visitor and institutional perspectives to achieve sustainable development? 3) What evaluation framework can translate stakeholder needs into museum sustainability strategies? 4) What evaluation method should be designed to operationalize the framework? The paper proposes and tests a DSR-based framework and a fuzzy QFD evaluation approach with a case study at Zhejiang Natural History Museum.

The literature documents a growing nexus between SDGs and museum practices, including partnerships for quality of life, inclusion and equity, sustainable society, and climate/ecology. Sector bodies (NEMO, ICOMOS) and leading museums have mapped SDG targets and action plans. National systems such as Italy’s NMS embed sustainability indicators into museum evaluation. Scholarship highlights environmental, social, economic, and cultural dimensions of sustainability and posits that sustainable practices support continued stakeholder backing. Regional differences are pronounced; museums must think globally and act locally. The concept of cultural sustainability has matured as a fourth pillar. Post-pandemic constraints elevate challenges related to funding and SDG alignment. Evaluation research has used tools such as SERVQUAL and HISTOQUAL for service quality; broader assessments link museums to urban development, education, innovation, and tourism impacts. Despite qualitative case-rich literature, there is a paucity of quantitative, integrative frameworks that align visitor needs, institutional status, and SDG-guided strategies—particularly in China. This study addresses that gap by operationalizing a DSR-based indicator set and a fuzzy QFD evaluation method.

Framework: The study builds a DSR model for museum sustainability. D (Driving force) captures visitor needs, mapped to seven indicators aligned with Maslow’s hierarchy: D1 convenient and safe facilities; D2 quality offerings; D3 diversified services; D4 positive interactions; D5 attractive exhibitions and education events; D6 abundance and diversity of collections; D7 innovative environment. S (State) captures the status of museum sustainability, defined against China’s Museum Grading Evaluation and Operation Evaluation Standards and refined via interviews, yielding six indicators: S1 professionalism of exhibition and education services; S2 optimizing collection system; S3 intensity of scientific research; S4 standardization of organizational management; S5 extensiveness of cooperation and reciprocity; S6 support of funding policies. R (Response) translates SDG-aligned strategies into 10 indicators across three categories: social awareness (R1 spread environmental protection knowledge; R2 advocate education for sustainable development), cooperative support (R3 enhance collaboration with social forces; R4 inter-institutional cooperation; R5 integrate tourism and development; R6 strengthen international cooperation), and internal reforms (R7 improve resource recycling; R8 enhance sustainable professional capabilities related to heritage; R9 promote social value via public sphere governance; R10 optimize planning and management systems for sustainability). Evaluation approach: A fuzzy QFD model integrates D and S (as criteria) with R (as alternatives). To handle uncertainty, the study employs Fermatean fuzzy (FF) sets. Weighting of criteria combines objective and subjective components using FF-PSI (objective) and FF-SWARA (subjective), aggregated into synthetic weights. The FF-MARCOS method ranks the R strategies within the QFD framework. Empirical design: Case study at Zhejiang Natural History Museum (ZNHM). Data collection included 21 in-depth staff interviews to refine S indicators; three questionnaires: D (visitor needs, 23 items; n=769), S (status, 6 items; n=45 professionals), and expert evaluation of R–(D,S) relationships (ten-level linguistic scale; n=6 experts). Reliability and sampling adequacy: D questionnaire α=0.951; KMO=0.984. S questionnaire α=0.915; KMO=0.867. Analytical steps: 1) Construct D, S, R indicators via DSR and SDG mapping; 2) Collect survey data; 3) Determine D and S weights using FF-PSI-SWARA; 4) Elicit expert judgments on relationships between R and (D,S) in the QFD matrix; 5) Apply FF-MARCOS to prioritize R; 6) Conduct comparative validation against FF-WSM, FF-WPM, FF-WASPAS, and FF-ARAS methods.

- Indicator priorities for ZNHM: • Driving forces (visitors’ needs) ranked with innovative environment and diversified services at the top (Table 6 shows highest weights: D7 0.104; D3 0.0884), followed by quality offerings (D2 0.0784), positive interactions (D4 0.0673), abundance and diversity of collections (D6 0.0619), convenient and safe facilities (D1 0.0541), and attractive exhibitions and education events (D5 0.0519). • State indicators (institutional status) prioritized optimizing the collection system (S2, weight 0.1076), professionalism of exhibitions and education services (S1, 0.0841), and support of funding policies (S6, 0.0832), followed by organizational management (S4, 0.0791) and cooperation and reciprocity (S5, 0.0728); scientific research (S3) ranked lower in the presented table. - Sustainability strategies (R) prioritization: Using the proposed FF-PSI-SWARA-MARCOS-based QFD model, social awareness strategies were top: R1 spreading environmental protection knowledge (weight 2.5336) and R2 advocating education on sustainable development (2.4572). Internal reforms emphasizing social value and governance followed: R9 promoting social value through public sphere governance (2.2854), R8 enhancing sustainable professional capabilities related to heritage (2.2427), and R10 optimizing planning and management for sustainability (2.2053). Next were R6 strengthening international cooperation (2.1954), R4 improving inter-institutional cooperation (2.1415), R3 enhancing collaboration with social forces (2.1009), R7 improving resource recycling (2.0559), and R5 integrating local tourism and development (1.5232). - Strategic implications for ZNHM: Significant opportunities include updating and digitizing the collection system, enhancing the professionalism of exhibitions and education programs, and securing funding policies. ZNHM’s sustainability efforts should prioritize social awareness (R1–R2), then internal reforms around social value, governance, and professional capabilities (R9, R8, R10), with international cooperation as a subsequent step. - Model validation: Comparative analysis with FF-WSM, FF-WPM, FF-WASPAS, and FF-ARAS produced broadly consistent ranking patterns, supporting the feasibility and validity of the proposed QFD approach.

The study addresses the research questions by linking visitor needs (D) and institutional status (S) to SDG-aligned strategies (R) within a unified DSR-QFD framework, operationalized with Fermatean fuzzy multi-criteria methods. This bridges qualitative insights and quantitative evaluation, enabling museums to translate stakeholder needs into prioritized sustainability strategies. For ZNHM, the findings underscore that enhancing social awareness through environmental knowledge dissemination and education for sustainable development offers the strongest leverage, while internal reforms that strengthen social value, governance, and professional capacities are the next priority. These results align with the museum’s mission and China’s emphasis on sustainable development, offering a clear pathway for planning and resource allocation. The approach provides a mechanism to evaluate the orientation and extent of sustainability efforts—an area previously underdeveloped in China’s museum policy landscape—supporting evidence-based decision-making, transparency, and alignment with SDGs. By demonstrating operability and reliability (high α and KMO values) and showing consistency with alternative MCDM methods, the study contributes a replicable, data-driven template for museums to assess and advance sustainability in context-sensitive ways.

This paper develops and validates a DSR-based evaluation framework and a fuzzy QFD evaluation method (FF-PSI-SWARA-MARCOS) for measuring museum sustainability in China. The framework integrates visitor needs (D), institutional status (S), and SDG-aligned strategies (R), enabling museums to prioritize actions systematically. Empirical application at ZNHM indicates that social awareness strategies should be the primary focus, followed by internal reforms that highlight social value, governance, and professional capacity, with international cooperation as a subsequent priority. Practically, ZNHM should update its collection system, elevate professionalism in exhibitions and education, and strengthen funding mechanisms. The study advances quantitative evaluation in a field dominated by qualitative approaches and offers a reference model for Chinese museums. Future research will apply the framework across diverse museum types and regions, refine indicator weights dynamically, and expand stakeholder participation to enhance generalizability and robustness.

- Single-case focus on a natural history museum limits generalizability across museum types and regions. - Small expert panel (n=6) for R–(D,S) relationships may constrain robustness of linguistic judgments. - Some reported tables show minor inconsistencies; further replication would solidify rankings. - Cross-sectional design; sustainability indicators and priorities are dynamic and may shift over time, necessitating periodic re-weighting and reassessment. - Cultural and institutional specificities in China (e.g., predominantly state-owned museums) may limit direct transferability to other governance contexts.