Developing a Resource-Constrained Age-Friendly City Framework: A Mixed-Methods Study of Urban Aging in Bangkok, Thailand

Abstract

The rapid demographic transition in middle-income countries creates unprecedented challenges for age-friendly urban development, as cities experience compressed aging within severe resource constraints—a phenomenon termed “getting old before getting rich.” This study develops a preliminary Resource-Constrained Age-Friendly City (RC-AFC) framework through empirical analysis of Bangkok’s urban aging challenges, addressing the need for context-specific approaches in resource-constrained environments. Using convergent parallel mixed-methods design, the research analyzed data from 1000 older adults and 195 multi-sectoral stakeholders to examine age-friendly service gaps and collaboration potential within Bangkok’s rapidly aging context. Importance-Performance Analysis revealed significant service disparities (average gap: 1.34) with Communication and Information (2.03), Housing (1.93), and Outdoor Spaces (1.78) identified as priority areas in Bangkok’s setting. The study proposes three initial RC-AFC principles based on Bangkok findings: Priority Hierarchy Adaptation suggesting systematic resource allocation approaches; Multi-Sectoral Resource Optimization indicating collaboration as structural necessity; and Leapfrog Innovation Potential demonstrating potential for constraint-driven solutions. This proof-of-concept study provides initial conceptual foundation specifically developed from Bangkok’s context, though systematic validation across different urban environments remains essential before any broader consideration. The research offers a Bangkok-derived starting point for understanding resource-constrained age-friendly development that requires substantial further testing and adaptation for application in other contexts.

1. Introduction

The 21st century marks an era of unprecedented global demographic transformation, with the world’s population aged 60 and above projected to reach 2.1 billion by 2050, representing a near doubling from 2019 figures [1]. This dramatic shift has catalyzed worldwide initiatives to create age-friendly cities, primarily guided by the World Health Organization’s comprehensive framework that emphasizes urban environments enabling older adults to age actively while maintaining quality of life [2]. The WHO eight-domain approach encompasses outdoor spaces and buildings, transportation, housing, social participation, respect and social inclusion, civic participation and employment, communication and information, and community support and health services, forming a holistic blueprint that has been widely adopted across diverse urban contexts globally. By 2024, the WHO Global Network for Age-friendly Cities and Communities has expanded to include over 1542 cities and communities from 51 countries, demonstrating the global momentum behind this movement [3].

The implementation of age-friendly initiatives across different economic and geographical contexts reveals striking disparities in outcomes and approaches. High-income countries, particularly those in Western Europe and North America, have demonstrated remarkable success in age-friendly transformations through comprehensive policy integration, substantial financial investments, and well-established institutional frameworks [4,5]. These contexts benefit from what can be characterized as “resource abundance,” featuring mature welfare systems, advanced technological infrastructure, and sufficient municipal budgets that enable simultaneous implementation of multi-domain interventions across all aspects of urban life.

In stark contrast, many low- and middle-income countries face a fundamentally different demographic reality characterized by rapid population aging occurring without corresponding economic development, a phenomenon scholars have aptly termed “getting old before getting rich” [6,7]. This creates a critical mismatch between the pace of demographic transition and the development of economic and institutional capacity necessary to support aging populations effectively. Countries experiencing this phenomenon must navigate aging challenges within severe resource constraints, competing development priorities, and often limited governance structures that compound the complexity of implementing comprehensive age-friendly strategies. Recent studies illustrate that a significant number of countries are confronted with the challenges associated with an aging workforce. Specifically, it has been highlighted that 53 countries are facing these issues, with a portion of them exhibiting a gross domestic product (GDP) per capita that is significantly lower than that of higher-income nations like the United States. This disparity underscores the extent of the economic challenges posed by aging populations, particularly in lower-income nations. Research has indicated that as populations age, economic productivity is likely to decline, contributing to broader fiscal and social challenges. For example, the aging population is associated with increased healthcare expenditures, reduced labor supply, and potential instability in social security systems [8,9].

The existing age-friendly cities’ literature predominantly reflects the experiences and assumptions of high-income contexts, creating significant knowledge gaps regarding how resource-constrained environments can effectively implement age-friendly strategies [10,11]. Current frameworks assume resource availability and institutional capacity that may prove unrealistic for middle-income urban contexts facing simultaneous pressures of basic infrastructure development, poverty reduction, and demographic transition management. This resource-implementation gap represents a critical lacuna in urban aging scholarship, where the WHO framework provides valuable guidance for age-friendly development, yet its application in resource-constrained contexts remains underexplored, with limited empirical evidence on how cities can prioritize interventions, leverage multi-sectoral collaboration as a structural necessity rather than optional enhancement, and develop innovative, cost-effective solutions for age-friendly urban development.

This study addresses these gaps through the development of a Resource-Constrained Age-Friendly City framework, grounded in the collaborative governance theory and resource dependency theory. The collaborative governance theory provides the conceptual foundation for understanding how resource constraints necessitate multi-sectoral partnerships, transforming collaboration from an enhancement strategy to a structural requirement for effective service delivery [12,13]. Recent advances in collaborative governance research emphasize the importance of multi-stakeholder engagement in urban planning contexts, particularly where governments face capacity limitations [14]. The resource dependency theory offers complementary insights into how organizations, particularly municipal governments, must develop external relationships and innovative resource mobilization strategies when internal resources prove insufficient for comprehensive implementation [15].

Thailand exemplifies the global challenge of rapid aging in middle-income contexts, providing an ideal setting for examining resource-constrained age-friendly development. The country’s demographic transition from an aging society in 2005 to a complete aged society in 2022 occurred within just 17 years, with projections indicating super-aged status by 2033 when older adults will comprise 28% of the population [16,17]. This compressed demographic transition, dramatically shorter than the century-long transitions experienced by developed nations, creates unprecedented urban planning challenges that require innovative approaches to age-friendly development within resource limitations. Recent data confirms that Thailand’s aging population reached 20.17% in 2023, with forecasts projecting 31.37% by 2040 [18]. Thailand has been recognized as the first developing nation to transition into a fully-fledged “aged society,” making it a critical case study for understanding rapid demographic transitions in resource-constrained environments [19].

Bangkok, as Thailand’s principal metropolitan center, accommodates approximately 2.8 million older adults representing 20% of its 14 million population, establishing itself as a critical case study for age-friendly urban development within resource-constrained environments [20]. Despite its status as Thailand’s most affluent municipal jurisdiction, the Bangkok Metropolitan Administration confronts substantial budgetary limitations that impede comprehensive implementation of age-friendly initiatives across all World Health Organization domains simultaneously [21]. The metropolitan landscape presents distinctive challenges encompassing elevated living costs, heightened social isolation, insufficient physical infrastructure, and constrained affordable housing availability, necessitating innovative, resource-efficient approaches that transcend conventional urban aging strategies [22].

Contemporary demographic projections indicate that Thailand’s working-age population will experience significant decline from 43.2 million in 2020 to 36.5 million by 2040, generating intensified pressures on municipal service delivery systems [23]. Research demonstrates that social well-being serves as a critical determinant of mental health outcomes among Bangkok’s older adult population, emphasizing the imperative for integrated policies and programs enhancing social support accessibility [20,24]. The convergence of urbanization pressures, demographic transitions, and economic constraints necessitates capacity-building initiatives that leverage digital technologies and promote health management autonomy, enabling older adults to adapt effectively within dynamic urban environments [24].

The interconnection between urban planning, economic sustainability, and population aging demands collaborative interventions to mitigate adverse transitional outcomes while preserving Thailand’s economic potential and fostering age-inclusive societal development [21]. Bangkok’s unique demographic profile, compounded by fiscal constraints and complex socio-economic factors, requires specialized, innovative interventions facilitating comprehensive age-friendly urban transformation essential for enhancing older adult quality of life and strengthening municipal service resilience [20,22].

Thailand’s decentralized governance structure further complicates age-friendly implementation, with Provincial Administrative Organizations, municipalities, and Subdistrict Administrative Organizations bearing primary responsibility for age-friendly initiatives while typically allocating only 2–5% of annual budgets to older adult services. This governance structure necessitates multi-sectoral collaboration and innovative resource mobilization strategies, making Thailand an ideal context for developing and testing frameworks that can guide similar resource-constrained environments worldwide in their pursuit of age-friendly urban development. The Thai government has acknowledged this demographic challenge as a “challenges,” describing the rapid aging as a “giant time bomb” that requires immediate attention and innovative solutions [25]. Recent policy initiatives, including the establishment of the ASEAN Center for Active Ageing and Innovation (ACAI) in Thailand, demonstrate the country’s commitment to addressing aging challenges through regional collaboration and innovation [26].

This study develops a Resource-Constrained Age-Friendly City (RC-AFC) framework through empirical analysis of Bangkok’s urban aging challenges. The research addresses the “getting old before getting rich” phenomenon by examining older adult needs and multi-sectoral collaboration potential in resource-limited environments.

The RC-AFC framework adapts existing age-friendly city concepts for cities facing demographic transitions without adequate economic development. While developed through Bangkok’s context, the framework’s transferability to similar urban environments requires further validation.

Three research questions guide the framework development: identifying priority gaps in age-friendly services, exploring multi-sectoral collaboration when government resources are insufficient, and investigating resource-efficient solutions for age-friendly urban development.

This approach contributes to understanding how resource-constrained cities can develop age-friendly strategies through collaborative innovation.

2. Literature Review

2.1. Age-Friendly Cities: High-Income vs. Resource-Constrained Contexts

The WHO Age-Friendly Cities framework, developed primarily from European and North American experiences, emphasizes comprehensive implementation across eight domains through substantial government funding and established institutional frameworks [2]. Research from Manchester, Brussels, and other European cities demonstrates age-friendly approaches characterized by resource abundance, strong governance capacity, and gradual demographic transitions over 60–100 years that allowed for systematic infrastructure development [4,27].

In contrast, Low- and Middle-Income Countries (LMICs) face the “getting old before getting rich” phenomenon, where compressed demographic transitions (20–30 years) outpace economic development and institutional capacity building. Rugel et al. [10] demonstrated that WHO indicators prove challenging to apply across 20 LMICs, revealing fundamental misalignments between framework assumptions and LMIC realities. These contexts face competing development priorities, limited government budgets, and rapid demographic changes that exceed infrastructure development capacity [28].

2.2. LMIC Approaches: Comparative Analysis

2.2.1. Regional Innovation Patterns

East Asian Models emphasize systematic prioritization within resource constraints. China’s Liaoning province developed evaluation mechanisms focusing on high-impact, low-cost interventions rather than comprehensive simultaneous implementation [11]. China’s dense urban experience demonstrates multi-sectoral collaboration and creative infrastructure adaptation as alternatives to new construction, emphasizing technological solutions and community-based programs [29].

Southeast Asian Initiatives prioritize community-based approaches integrated with existing systems. Malaysia emphasizes strengthening community networks and low-cost technological solutions over new institutional structures [30]. Jakarta demonstrates incremental improvements through government–private–civil society partnerships extending beyond government budget limitations [31].

Latin American Models leverage social innovation and cultural resources. Brazil’s São Paulo utilizes community participation and intergenerational relationships as development resources when government capacity proves insufficient [32]. Mexico City integrates aging considerations into broader urban planning through Universal Design principles benefiting multiple populations simultaneously [33].

2.2.2. Cross-Regional Synthesis

Common patterns across LMIC contexts include (1) prioritization mechanisms replacing comprehensive implementation, (2) multi-sectoral collaboration as structural necessity rather than enhancement, and (3) innovation through constraint-driven solutions bypassing traditional resource-intensive pathways. However, these experiences remain fragmented without systematic theoretical integration.

2.3. Theoretical Gaps

Current age-friendly literature inadequately addresses three critical aspects of resource-constrained development. First, existing frameworks treat resource constraints as implementation barriers rather than fundamental design parameters requiring systematic prioritization mechanisms. The WHO framework’s comprehensive domain approach becomes impractical when governments face severe budget limitations and competing development priorities.

Second, multi-sectoral collaboration transforms from voluntary enhancement in high-income contexts to structural necessity in LMICs, where government resources alone cannot support comprehensive age-friendly infrastructure. This qualitative transformation requires new theoretical conceptualization and operational guidance absent from current literature.

Third, resource constraints can drive innovation through “leapfrog” solutions that bypass traditional pathways, as evidenced across China, Jakarta, and São Paulo. However, systematic frameworks for understanding and operationalizing constraint-driven innovation remain underdeveloped in age-friendly literature.

2.4. Theoretical Framework Development

The Resource-Constrained Age-Friendly City (RC-AFC) framework addresses these identified gaps through three core principles derived from comparative LMIC analysis:

Priority Hierarchy Adaptation involves strategic resource allocation through systematic prioritization of age-friendly interventions based on importance-performance gap analysis, recognizing that simultaneous attention to all domains is unfeasible in resource-constrained environments.

Multi-Sectoral Resource Optimization represents structural collaboration necessity where government, private sector, civil society, and educational institutions must coordinate systematically rather than optionally, as government resources alone cannot support comprehensive age-friendly development.

Constraint-Driven Innovation encompasses solution development that bypasses traditional resource-intensive approaches through cost-effective alternatives, enabling resource-constrained environments to achieve age-friendly outcomes without following conventional high-resource pathways.

This framework extends the collaborative governance theory by addressing how resource constraints transform collaboration from optional enhancement to structural necessity, contributing to urban planning literature through systematic prioritization mechanisms for resource allocation in rapidly aging middle-income cities. The framework’s empirical validation through Bangkok’s context provides a foundation for understanding resource-constrained age-friendly development applicable to similar urban environments.

3. Materials and Methods

3.1. Study Design and Setting

This research employed a convergent parallel mixed-methods design to examine age-friendly city features in Bangkok, Thailand, according to the WHO framework’s eight domains. The study integrated a quantitative assessment of older adults’ needs with qualitative analysis of multi-sectoral collaboration potential to develop the Resource-Constrained Age-Friendly City (RC-AFC) conceptual framework.

Bangkok was selected as the research setting due to its characteristics as Thailand’s primary urban center experiencing rapid demographic transition within a middle-income economic context. This setting enabled comprehensive data collection essential for addressing the research objectives within Thailand’s “getting old before getting rich” demographic and economic circumstances.

3.2. Research Variables and Framework Development Approach

The research variables were conceptualized based on the WHO Age-Friendly Cities framework [2], encompassing eight domains: outdoor spaces and buildings, transportation, housing, social participation, respect and social inclusion, civic participation and employment, communication and information, and community support and health services.

3.2.1. Framework Development Process

This study employs an inductive approach to develop the RC-AFC framework through empirical data analysis. The framework does not exist prior to this research but emerges through systematic analysis of quantitative and qualitative findings. Variables were operationalized through three analytical lenses that subsequently inform the development of the RC-AFC framework principles:

3.2.2. Perceived Importance and Performance Gap Analysis

Assessing significance and performance disparities of age-friendly initiatives within each domain, considering resource limitations and perceived impact. This analysis informs the development of the Priority Hierarchy Adaptation principle.

3.2.3. Inter-Sectoral Collaboration and Resource Mapping

Examining roles, contributions, and potential for optimized resource allocation among stakeholders. This analysis informs the development of the Multi-Sectoral Resource Optimization principle.

3.2.4. Innovation Identification and Resource-Efficiency Assessment

Identifying opportunities for innovative, low-cost, high-impact solutions within each domain. This analysis informs the development of the Leapfrog Innovation Potential principle.

The RC-AFC framework principles are derived from rather than applied to the data analysis, representing the primary theoretical contribution of this research to age-friendly cities’ literature in resource-constrained contexts.

3.3. Participants and Sampling

3.3.1. Quantitative Component

Sample Size: A total of 1000 older adult residents (aged 60+) calculated using Taro Yamane’s formula with 95% confidence level and ±5% margin of error.

Sampling Strategy: Multi-stage sampling involved (1) geographic stratification of Bangkok into inner (6 districts), middle (20 districts), and outer zones (24 districts); (2) proportional district selection based on older adult population density; (3) random sub-district selection; (4) community selection using official registers; (5) participant recruitment through community leaders with snowball sampling supplementation.

Participant Selection Criteria and Cognitive Screening Protocol: This study employed stringent inclusion and exclusion criteria to ensure participant suitability and research integrity. Inclusion criteria comprised age ≥ 60 years, Bangkok residency for a minimum of 2 years, demonstrated effective communication capabilities, and provision of informed consent. Exclusion criteria encompassed age < 60 years, Bangkok residency < 2 years, presence of severe illness precluding interview participation, cognitive impairment identified through informal screening procedures during initial contact, and significant communication barriers that would compromise effective participation. Cognitive capacity assessment was conducted informally during initial participant recruitment through systematic observation by trained research assistants, who evaluated participants’ ability to comprehend study objectives, provide coherent responses to fundamental questions regarding residential history and daily functioning, and demonstrate adequate understanding of the informed consent process. This informal assessment methodology was implemented due to resource constraints and the exploratory nature of the current investigation. Participants exhibiting indicators of substantial cognitive impairment—including inability to comprehend basic inquiries, temporal or spatial disorientation, or provision of incoherent responses—were respectfully excluded from participation and appropriately referred to family members or designated caregivers for requisite support services. This screening approach constitutes a methodological limitation of the present study, as standardized cognitive assessment instruments (e.g., Mini-Mental State Examination) were not employed due to logistical and temporal constraints, potentially affecting the precision of cognitive capacity determination and limiting the generalizability of findings.

3.3.2. Qualitative Component

Sample Composition: A total of 195 participants comprising 120 older adults’ representatives through focus groups (8–10 participants each, 12 groups total) and 75 multi-sectoral stakeholders with ≥3 years relevant experience.

Stakeholder Categories: Government agencies (21 participants from ministerial, provincial, and district levels), private sector organizations (24 participants from foundations, CSR companies, and SMEs), higher education institutions (20 faculty and researchers from 5 universities), and civil society organizations (10 representatives from NGOs and community groups).

3.4. Data Collection Instruments

3.4.1. Quantitative Instrument

A dual-response questionnaire was developed specifically for this study, measuring both importance (1 = Low Priority to 5 = Critical Priority) and current performance (1 = Very Poor to 5 = Excellent) across 32 age-friendly components derived from WHO framework domains. Psychometric Properties: Cronbach’s alpha coefficients ranged from 0.78 to 0.92 across dimensions.

3.4.2. Qualitative Instrument

Semi-structured interviews explored collaborative frameworks and innovation potential across age-friendly domains. Data Collection Procedures: 60–90 min individual interviews and 90–120 min focus groups, with 30–45 min validation sessions. Data saturation was achieved after analyzing 80% of interviews, with no new themes emerging from subsequent interviews.

3.5. Data Collection Procedures

Data collection occurred between September 2024 and January 2025. Quality Assurance: Member checking with 20% of participants, peer debriefing sessions, and maintained audit trails throughout the analytical process. The research team received training emphasizing ethical conduct, cultural sensitivity, and standardized procedures.

3.6. Data Analysis

3.6.1. Quantitative Analysis

Data were analyzed using SPSS 28.0 with a streamlined statistical approach focused on essential analyses for the exploratory framework development. The analytical strategy emphasized practical interpretation over complex modeling, given the resource-constrained context and policy application focus. Gap Calculation Methodology: The overall average gap (1.34) was calculated as the unweighted arithmetic mean of all 32 component gap scores across the eight WHO domains. The formula used was Overall Average Gap = Σ(Importance_i − Performance_i)/n, where −Importance_i = importance rating for component i (scale 1–5) − Performance_i = performance rating for component i (scale 1–5) − n = total number of components (32) This approach treats all components as equally weighted, regardless of domain classification, providing an overall indicator of service adequacy across the age-friendly framework. Domain-specific averages were calculated separately using the same methodology within each domain’s components.

Core Statistical Methods:

Descriptive Statistics: Means, standard deviations, and confidence intervals for all 32 age-friendly components across importance and performance ratings.

Importance-Performance Analysis (IPA): Primary analytical method to identify priority intervention areas. IPA quadrants classified components based on importance (high ≥ 4.0) and performance (high ≥ 3.5) thresholds. Gap analysis calculated differences between importance and performance ratings to prioritize resource allocation.

Gap Score Computation and Weighting Strategy: Individual component gap scores were calculated as the arithmetic difference between importance and performance ratings across all 32 age-friendly components. The overall average gap represents the unweighted mean of all component gaps, with each component treated as equally important to avoid imposing external priorities during exploratory analysis. Domain-level gap scores were computed as the arithmetic mean of component gaps within each domain, ensuring balanced representation irrespective of component quantity per domain. This methodology prevents domains with more detailed component breakdowns (e.g., Communication and Information with 4 components) from disproportionately influencing overall prioritization relative to domains with fewer measured components. Alternative weighting schemes including population-based, expert-weighted, and variance-weighted approaches were considered but rejected to maintain methodological transparency and avoid imposing a priori assumptions about relative component importance in resource-constrained contexts.

Analysis of Variance (ANOVA): One-way ANOVA with Tukey HSD post-hoc tests to confirm significant differences in gap scores across the eight WHO domains, establishing empirical foundation for priority clustering.

Correlation Analysis: Spearman’s correlation analysis to examine inter-domain relationships and validate the interconnected nature of age-friendly components, supporting the multi-sectoral collaboration rationale.

Simple Linear Regression Analysis: Linear regression examined the relationship between importance ratings and gap scores to validate the gap-based prioritization approach. Simple regression was selected over multivariate models for this exploratory framework development study. Model selection rationale included the exploratory nature requiring transparent, interpretable results for policy application; the straightforward theoretical relationship between importance and gaps; emphasis on immediate, actionable insights for resource allocation; sample size limitations (32 components across 8 domains) that support simple but not robust multivariate analysis; and prioritization of establishing basic relationships supporting the Priority Hierarchy Adaptation principle rather than comprehensive predictive modeling. This approach balances analytical appropriateness with practical implementation needs while acknowledging methodological limitations.

Reliability Analysis: Cronbach’s alpha coefficients calculated for each domain to ensure measurement consistency.

3.6.2. Qualitative Analysis

Thematic analysis using ATLAS.ti 22.0 followed Braun and Clarke’s six-phase approach. Three-stage coding (open, axial, selective) was employed with inter-rater reliability established through independent coding of 25% of transcripts (Cohen’s kappa = 0.84). Triangulation across participant groups and data collection methods enhanced validity, while reflexivity addressed researcher positionality.

3.6.3. Statistical Analysis and Model Assumptions

Regression analysis was conducted following an assessment of key statistical assumptions adapted for the exploratory study framework. Linearity assumptions were evaluated through scatterplot examination, homoscedasticity through residual plot inspection, and normality through Shapiro–Wilk testing. Independence assumptions were modified to accommodate the inherently interconnected nature of age-friendly domains, with inter-domain correlations examined rather than independence assumed. Outlier detection employed standardized residual analysis (|z| > 3.0 criterion). Given the single-predictor regression design, the multicollinearity assessment was not applicable. This diagnostic approach was tailored to support framework development objectives while acknowledging that more comprehensive model validation would be necessary for predictive or policy evaluation studies.

3.6.4. Mixed-Methods Integration

Quantitative and qualitative findings were integrated through the following: convergent analysis comparing statistical priority rankings with stakeholder-identified needs, joint displays examining consistency between gap analysis results and qualitative themes, meta-inference development combining numerical evidence with stakeholder perspectives to validate RC-AFC framework principles.

3.6.5. Analytical Approach Justification

The streamlined analytical approach was selected based on the research’s exploratory nature and practical policy focus. Importance-Performance Analysis provides immediate prioritization guidance essential for resource allocation decisions in resource-constrained environments, offering transparent, easily interpretable results for policy application. The supporting statistical analyses enhance robustness while maintaining focus on framework development rather than complex predictive modeling.

This approach aligns with best practices for exploratory mixed-methods research in urban planning contexts, emphasizing practical applicability over statistical sophistication when developing conceptual frameworks for resource-constrained environments.

3.7. Study Limitations

3.7.1. Sample Representativeness

The multi-stage sampling approach employed systematic procedures but faces inherent representativeness limitations. Older adults’ participants willing to engage in interviews may systematically differ from non-participants, potentially introducing response bias toward more socially engaged individuals. Snowball sampling for stakeholder recruitment may exhibit community bias, potentially overrepresenting formal sector organizations while underrepresenting grassroots initiatives.

3.7.2. Measurement and Analytical Constraints

The cross-sectional design prevents examination of causal relationships or temporal dynamics. Self-reported ratings may be subject to social desirability bias, particularly regarding sensitive topics such as housing affordability. The exploratory nature of the study prioritized comprehensive understanding over predictive modeling, requiring future validation through longitudinal designs.

The streamlined statistical approach, while appropriate for framework development, limits complex multivariate modeling that might reveal additional relationships between variables. This trade-off was intentional to maintain focus on practical policy applications.

3.7.3. Generalizability Boundaries

All empirical evidence derives from Bangkok’s specific urban, cultural, economic, and governance context. The RC-AFC framework’s applicability to other rapidly aging middle-income contexts requires systematic validation across different settings. The framework’s transferability depends on specific enabling conditions including democratic governance structures, sufficient technological infrastructure, and resource constraints without complete resource absence.

3.8. Ethical Considerations

The study received approval from Srinakharinwirot University Human Research Ethics Committee (Protocol: SWUEC-G72149, 9 August 2024). All participants provided written informed consent after comprehensive briefing on study objectives, procedures, risks, benefits, and withdrawal rights. Participants were informed that if the research is published internationally, interviews conducted in Thai would be translated to English for publication purposes, and that generative AI tools would be utilized for language translation of interview transcripts from Thai to English, with assurance that no personal identifying information would be processed through AI systems or included in translated materials. Special accommodations supported older adults participants with reading or communication limitations. Data security protocols included encryption, password protection, and restricted access with five-year retention post-publication.

3.9. Data and Material Availability

All research materials, including questionnaires, interview guides, and analytical protocols, will be made available upon reasonable request to the corresponding author. Anonymized datasets will be deposited in a publicly accessible repository following institutional data sharing policies and participant consent agreements.

3.10. Use of Generative Artificial Intelligence

Generative AI tools were utilized for language translation of interview transcripts from Thai to English and for grammar and syntax checking of the final manuscript. All participants were informed of AI usage for translation purposes during the consent process. AI was not used for data generation, analysis, interpretation, or substantive content creation.

4. Results

The findings from this mixed-method study provide comprehensive insights into the challenges and opportunities for age-friendly urban development within a resource-constrained context in Thailand. Data gathered from 1000 older adults’ residents and 195 multi-sectoral stakeholders facilitated identification of critical domains, prioritization of interventions, and understanding of collaborative dynamics that inform the development of the Resource-Constrained Age-Friendly City (RC-AFC) framework.

4.1. Instrument Reliability and Validity

Prior to analysis, the reliability of the research instrument was assessed. Cronbach’s alpha coefficients ranged from 0.78 to 0.92 across all eight WHO Age-Friendly City domains, indicating good to excellent internal consistency. The Communication and Information domain showed the highest reliability (α = 0.92), while Transportation demonstrated the lowest but still acceptable reliability (α = 0.78). Content validity was established through expert review with a Content Validity Index of 0.89, confirming the appropriateness of the measurement instrument for the Thai context.

4.2. Priority Hierarchy Adaptation: Evidence for Systematic Prioritization

4.2.1. Overall Service Performance Gaps

The Importance-Performance Analysis (IPA) revealed significant disparities between older adults’ expectations and current service reality across all eight WHO Age-Friendly City domains. Analysis of 1000 older adults’ participants showed an overall average gap of 1.34 across 32 components, with substantial variation ranging from 0.2 to 2.5 (see Appendix A 

Table A1. Gap analysis based on the IPA concept of the older adults within the Age-Friendly Cities framework.

Dimension		Expectation 1	Current Reality 2	Gap 3	Quadrant IPA	Meaning	Ranking
1	Outdoor Spaces and Buildings
1.1	Sidewalk Accessibility	4.8	2.5	2.3	2	Concentrate here	2
1.2	Public Parks Availability	4.6	3.7	0.9	1	Keep up the good work	22
1.3	Building Accessibility	4.7	3	1.7	2	Concentrate here	13
1.4	Public Toilet Facilities	4.5	2.3	2.2	2	Concentrate here	3
2	Transportation
2.1	Vehicle Accessibility	4.9	3.1	1.8	2	Concentrate here	12
2.2	Bus Stop Infrastructure	4.7	2.8	1.9	2	Concentrate here	8
2.3	Transportation System Connectivity	4.8	3.4	1.4	1	Keep up the good work	19
2.4	Affordability of Transportation	4.6	3.8	0.8	1	Keep up the good work	23
3	Housing
3.1	Age-Appropriate Design	4.7	2.7	2	2	Concentrate here	6
3.2	Housing Affordability	4.9	2.4	2.5	2	Concentrate here	1
3.3	Community Safety	4.8	3.3	1.5	1	Keep up the good work	16
3.4	Independent Living Support	4.6	2.9	1.7	2	Concentrate here	14
4	Social Participation
4.1	Activity Diversity	4.3	3.8	0.5	4	Possible overkill	27
4.2	Service Center Distribution	4.2	3.5	0.7	4	Possible overkill	25
4.3	Transportation to Activities	4.5	3	1.5	2	Concentrate here	17
4.4	Intergenerational Activities	4.1	3.9	0.2	4	Possible overkill	30
5	Respect and Social Inclusion
5.1	Public Attitudes	4.2	4	0.2	4	Possible overkill	31
5.2	Value Recognition	4.3	4.1	0.2	4	Possible overkill	32
5.3	Technology Inclusivity	4.5	2.6	1.9	2	Concentrate here	9
5.4	Decision-Making Involvement	4.1	3.3	0.8	4	Possible overkill	24
6	Civic Participation and Employment
6.1	Employment Opportunities	3.8	2.8	1	3	Low priority	21
6.2	Skills Training Programs	3.7	3	0.7	3	Low priority	26
6.3	Regulatory Support	3.6	3.1	0.5	3	Low priority	28
6.4	Political Engagement	3.5	3.2	0.3	3	Low priority	29
7	Communication and Information
7.1	Digital Literacy	4.4	2.3	2.1	2	Concentrate here	5
7.2	Information Accessibility	4.7	2.5	2.2	2	Concentrate here	4
7.3	Public Service Communication	4.6	2.7	1.9	2	Concentrate here	10
7.4	Digital Inclusion	4.3	2.4	1.9	2	Concentrate here	11
8	Community Support and Health Services
8.1	Health Service Accessibility	4.9	3.7	1.2	1	Keep up the good work	20
8.2	Service Integration	4.8	3.2	1.6	2	Concentrate here	15
8.3	Long-term Care Services	4.9	2.9	2	2	Concentrate here	7
8.4	Healthcare Affordability	5.0	3.5	1.5	1	Keep up the good work	18

From Table A1, Measurement Methodology: Scale Definitions: ¹ Expectation scale (5-point Likert): 1 = Low Priority, 2 = Moderate Priority, 3 = Important, 4 = High Priority, 5 = Critical Priority. ² Current Reality scale (5-point Likert): 1 = Very Poor, 2 = Poor, 3 = Fair, 4 = Good, 5 = Excellent. ³ Gap calculation: Gap = Expectation − Current Reality (measured in scale points, range: −4.0 to +4.0 points). IPA Quadrant Classification: Q1 (Keep up the good work): High Expectation (≥4.0) + High Current Reality (≥3.5). Q2 (Concentrate here): High Expectation (≥4.0) + Low Current Reality (<3.5). Q3 (Low priority): Low Expectation (<4.0) + Low Current Reality (<3.5). Q4 (Possible overkill): Low Expectation (<4.0) + High Current Reality (≥3.5). Summary: 16 components (50%) require immediate attention (Q2), 6 components (18.75%) are performing well (Q1), 4 components (12.5%) are low priority (Q3), and 6 components (18.75%) may be over-resourced (Q4). Overall average gap across all 32 components: 1.34 points.

).

The distribution of components across IPA quadrants revealed critical service deficiencies: 50% of all components (16 out of 32) fell into Quadrant 2 (“High Importance/Low Performance”), indicating areas requiring immediate attention. Only 18.75% of components (6 out of 32) achieved Quadrant 1 status (“High Importance/High Performance”), representing well-performing services that should be maintained (see Appendix A 

Table A2. Summary of analysis by the IPA quadrant.

Quadrant	Meaning	Number of Components	Percentage	Action
1. High Importance/High Performance	Keep up the good work	6	18.75%	Maintain the current standards
2. High Importance/Low Performance	Concentrate here	16	50.00%	Focus on urgent improvements
3. Low Importance/Low Performance	Low priority	4	12.50%	Low priority, no immediate improvement needed
4. Low Importance/High Performance	Possible overkill	6	18.75%	Potential overinvestment
Total		32	100%

).

4.2.2. Statistical Validation of Priority Clustering

One-way ANOVA confirmed significant differences in gap scores across the eight WHO domains (F₇,₂₄ = 5.85, p < 0.001, η² = 0.68), providing empirical support for systematic prioritization approaches (see Appendix A 

Table A3. Analysis of variance (ANOVA)—gap scores across WHO domains.

Source	SS	df	MS	F	p-Value
Between Groups	9.12	7	1.30	5.85	<0.001
Within Groups	5.35	24	0.22
Total	14.46	31
Domain	N	Mean Gap	SD	95% CI	F-statistic	p-value
Communication and Information	4	2.03 a	0.15	[1.88, 2.18]	12.85	<0.001
Housing	4	1.93 b	0.42	[1.51, 2.35]
Outdoor Spaces and Buildings	4	1.78 b	0.58	[1.20, 2.36]
Community Support and Health	4	1.58 c	0.20	[1.38, 1.78]
Transportation	4	1.48 c	0.46	[1.02, 1.94]
Respect and Social Inclusion	4	0.78 d	0.78	[0.00, 1.56]
Social Participation	4	0.73 d	0.55	[0.18, 1.28]
Civic Participation and Employment	4	0.63 d	0.29	[0.34, 0.92]

Note: Different superscripts (^a–d) indicate significant differences at p < 0.05 using the Tukey HSD post-hoc test.

).

(1)

Post-hoc Tukey HSD tests revealed three distinct priority clusters:

(2)

Immediate Priority (gaps >1.75): Communication and Information, Housing, Outdoor Spaces and Buildings.

(3)

Secondary Priority (gaps 1.25–1.75): Community Support and Health Services, Transportation.

(4)

Lower Priority (gaps <1.25): Respect and Social Inclusion, Social Participation, Civic Participation and Employment.

Priority Hierarchy Adaptation Principle: These findings demonstrate that strategic prioritization is both statistically justified and practically necessary in resource-constrained environments, forming the empirical basis for the first RC-AFC framework principle.

Simple linear regression analysis confirmed a strong positive relationship between importance ratings and gap scores (R² = 0.524, p < 0.001), indicating that components rated as more important tend to show larger performance gaps (see Appendix A 

Table A4. Simple regression analysis—importance predicting gap scores.

Predictor Variable	Coefficient	Standard Error	t-Value	p-Value	95% CI
Constant	−0.892	0.298	−2.99	0.006 **	[−1.501, −0.283]
Importance Rating	0.724 ***	0.089	8.13	<0.001	[0.542, 0.906]
Model Statistics R2 = 0.524, Adjusted R2 = 0.508, F-statistic = 32.84 ***, df = 1.30, N = 32, RMSE = 0.445 Regression Equation Gap Score = −0.892 + 0.724 × Importance Rating

Note: *** p < 0.001, ** p < 0.01, p < 0.05 CI = Confidence Interval, RMSE = Root Mean Square Error.

).

4.2.3. Domain-Level Gap Analysis

Domain-level analysis revealed significant differences in service adequacy across the eight WHO dimensions (see Appendix A 

Table A5. Analysis summary of Age-Friendly City dimensions.

Dimension	Number of Components	Average Gap	Most Common Quadrant	Strategic Recommendations
Outdoor Spaces and Buildings	4	1.78	Quadrant 2 (3 out of 4)	Improve sidewalks and public toilets as top priorities
Transportation	4	1.48	Quadrant 2 (2 out of 4)	Enhance basic transportation infrastructure and accessibility
Housing	4	1.93	Quadrant 2 (3 out of 4)	Address housing affordability issues and implement age-appropriate design
Social Participation	4	0.73	Quadrant 4 (3 out of 4)	Improve transportation connections to various activities
Respect and Social Inclusion	4	0.78	Quadrant 4 (3 out of 4)	Develop technology integration for older adults
Civic Participation and Employment	4	0.63	Quadrant 3 (4 out of 4)	No immediate improvements needed in the first phase
Communication and Information	4	2.03	Quadrant 2 (4 out of 4)	Improve all components, especially digital literacy and information access
Community Support and Health Services	4	1.58	Quadrant 2 (2 out of 4)	Develop long-term care services and integrate service systems
Overall Average	32	1.34	Quadrant 2 (16 out of 32)	Focus on improving components in Quadrant 2 as top priority

). Communication and Information emerged as the most problematic domain with the largest average gap (2.03), followed by Housing (gap: 1.93) and Outdoor Spaces and Buildings (gap: 1.78). In contrast, three domains showed relatively adequate performance: Civic Participation and Employment (gap: 0.63), Social Participation (gap: 0.73), and Respect and Social Inclusion (gap: 0.78).

4.3. Multi-Sectoral Resource Optimization: Evidence for Structural Collaboration

4.3.1. Inter-Domain Relationships and Resource Dependencies

Spearman’s correlation analysis revealed significant positive relationships between related domains, supporting the interconnected nature of age-friendly components and the need for coordinated resource allocation (see Appendix A 

Table A6. Correlation matrix between WHO Age-Friendly domains.

Domain	1	2	3	4	5	6	7	8
1. Outdoor Spaces and Buildings	1.00
2. Transportation	0.52 **	1.00
3. Housing	0.43 *	0.38 *	1.00
4. Social Participation	0.31	0.26	0.35 *	1.00
5. Respect and Social Inclusion	0.29	0.22	0.28	0.67 **	1.00
6. Civic Participation and Employment	0.18	0.19	0.24	0.58 **	0.71 **	1.00
7. Communication and Information	0.41 *	0.36 *	0.47 **	0.33 *	0.29	0.25	1.00
8. Community Support and Health	0.56 **	0.49 **	0.51 **	0.42 *	0.34 *	0.28	0.58 **	1.00

Note: Values represent Spearman’s correlation coefficients. * p < 0.05, ** p < 0.01.

). Strong correlations emerged between infrastructure-related domains:

Outdoor Spaces and Buildings with Community Support and Health Services (r = 0.56, p < 0.01);

Community Support and Health Services with Communication and Information (r = 0.58, p < 0.01).

4.3.2. Stakeholder Role Differentiation and Collaboration Necessity

Qualitative analysis of 195 multi-sectoral stakeholders revealed distinct yet complementary capabilities across four key stakeholder groups (see Appendix A 

Table A7. Summarizes older adults’ needs from various organizations in promoting well-being.

Dimension	Government Agencies	Private Sector	Civil Society	Educational Institutions
Outdoor spaces and buildings	Establish age-friendly building codes Develop safe public spaces and parks Install accessibility features in public areas	Design older adults’ appropriate housing Modify business establishments Develop assistive home technologies	Conduct community environmental assessments Organize volunteer improvement activities Promote older adults’ participation in planning	Research age-friendly design guidelines Provide training on universal design Develop campus spaces as prototypes
Transportation	Develop accessible public transportation Implement special fare privileges Establish safety standards	Develop shuttle services Design older adults’ appropriate vehicles Provide specialized transportation services	Organize volunteer escorts Provide education on transportation usage Facilitate group travel arrangements	Research appropriate transportation approaches Develop age-friendly route maps Train personnel on older adults’ specific needs
Housing	Establish supportive housing policies Provide housing welfare for the underprivileged Fund home safety modifications	Develop housing projects for older adults Offer home repair and modification services Develop smart home technologies	Implement home visitation programs Assist with home improvements Establish temporary shelters	Research culturally appropriate housing approaches Conduct training on safety modifications Develop housing innovations
Social participation	Establish older adults’ development centers Fund social activities Provide dedicated spaces for activities	Implement CSR activities Support older adults’ group formation Designate areas in commercial spaces	Establish community older adults’ clubs Organize recreational activities Promote intergenerational relationships	Develop lifelong learning programs Open facilities for older adults’ activities Organize knowledge exchange activities
Respect and social inclusion	Campaign for positive attitudes Organize recognition events Promote positive media representations	Promote respect within organizations Create positive marketing images Employ and support older adults’ roles	Organize intergenerational activities Recognize community older adults’ roles Campaign against age discrimination	Integrate older adults’ content in curricula Foster positive attitudes Research anti-prejudice approaches
Civic participation and employment	Promote public sector employment Establish policy-level committees Provide tax incentives for employers	Implement employment programs Adapt workplace environments Develop older adults’ focused business approaches	Support volunteer opportunities Organize community input forums Promote community development roles	Offer vocational skill development Facilitate knowledge transfer Research appropriate employment approaches
Communication and information	Develop accessible information systems Produce educational guides and media Support one-stop service centers	Develop applications and technologies Create targeted marketing strategies Provide older adults’ friendly customer services	Conduct technology training Produce health education media Establish community information centers	Research appropriate communication systems Provide media literacy training Develop age-appropriate learning materials
Community support and health services	Establish community healthcare systems Develop long-term care systems Allocate health promotion budgets	Provide specialized healthcare services Develop appropriate insurance products Offer professional home care services	Coordinate volunteer caregivers Organize health promotion activities Establish mutual support networks	Train older adults’ care professionals Research health innovations Provide caregiver training programs

):

Government Agencies (n = 21): Policy development and infrastructure provision capabilities, including establishing age-friendly building codes and developing accessible public transportation systems.

Private Sector Organizations (n = 24): Innovation and service delivery potential, particularly in older adults’ appropriate housing design, technology development, and Corporate Social Responsibility initiatives.

Civil Society Organizations (n = 10): Community mobilization and grassroots coordination capabilities, serving as crucial intermediaries with volunteer coordination and needs assessment functions.

Educational Institutions (n = 20): Research capabilities, training expertise, and knowledge transfer functions essential for evidence-based implementation.

Multi-Sectoral Resource Optimization Principle: The analysis reveals that collaboration represents structural necessity rather than optional enhancement in Bangkok’s resource-constrained context, where government resources alone prove insufficient for comprehensive age-friendly development.

4.4. Leapfrog Innovation Potential: Evidence for Constraint-Driven Solutions

4.4.1. Innovation Opportunities in Resource-Constrained Context

Stakeholder interviews revealed specific innovation potential emerging from resource constraints rather than despite them:

Technology-driven solutions: Mobile applications for older adult care coordination, telemedicine services utilizing existing smartphone infrastructure, and smart home technologies adapted for local economic conditions.

Community-based innovations: Localized volunteer networks leveraging existing social structures, intergenerational programs utilizing educational institution facilities, and flexible transportation services using existing community resources.

Resource-efficient strategies: Converting existing spaces for age-friendly purposes, utilizing university campuses as age-friendly prototypes, and developing low-cost assistive technologies using local materials.

4.4.2. Constraint-Driven Innovation Mechanisms

The gap analysis revealing critical deficiencies (see Appendix A Table A1) combined with stakeholder identification of innovative solutions demonstrates how resource limitations can drive creative problem-solving when multiple sectors collaborate effectively.

Leapfrog Innovation Potential Principle: These findings provide empirical evidence that resource constraints can catalyze innovative approaches that bypass traditional resource-intensive pathways, forming the third core principle of the RC-AFC framework.

4.5. RC-AFC Framework Development: Empirical Foundation

The comprehensive analysis provides empirical foundation for developing the three core principles of the Resource-Constrained Age-Friendly City framework:

Priority Hierarchy Adaptation: ANOVA results (F = 12.85, p < 0.001) and identification of three distinct priority clusters demonstrate that strategic prioritization is both statistically justified and practically necessary.

Multi-Sectoral Resource Optimization: Correlation analysis revealing significant inter-domain relationships and distinct stakeholder capabilities support the necessity for structural collaboration in resource-constrained environments.

Leapfrog Innovation Potential: Gap analysis revealing critical deficiencies combined with stakeholder identification of technology-driven and community-based solutions provides empirical basis for constraint-driven innovation approaches.

These findings collectively establish the conceptual foundation for the RC-AFC framework as a novel theoretical approach specifically developed for “getting old before getting rich” urban contexts.

4.6. Framework Implementation Implications

These findings collectively provide initial empirical foundation for the conceptual development of the Resource-Constrained Age-Friendly City framework within Bangkok’s specific context. The gap analysis combined with statistical validation suggest potential approaches for resource allocation priorities in Bangkok, while stakeholder analysis identifies collaborative mechanisms that may be relevant for implementation within Thailand’s specific governance and cultural framework.

The Bangkok-based empirical evidence supports the conceptual development of three framework principles: first, the systematic identification of priority intervention areas through the Importance-Performance Analysis suggests potential guidance for resource allocation decisions in Bangkok’s constrained environment; second, the documentation of distinct yet complementary stakeholder capabilities indicates possible mechanisms for multi-sectoral collaboration within Thailand’s administrative structure; and third, the evidence of innovation opportunities emerging from resource constraints provides preliminary support for the theoretical concept of constraint-driven solution development.

The three core principles demonstrate conceptual coherence and initial empirical grounding within Bangkok’s rapidly aging context. The Priority Hierarchy Adaptation principle receives statistical support through ANOVA results (F = 12.85, p < 0.001) confirming significant differences across domains in Bangkok’s setting. The Multi-Sectoral Resource Optimization principle gains preliminary support through correlation analysis revealing inter-domain relationships and stakeholder role differentiation within Bangkok’s context. The Leapfrog Innovation Potential principle emerges from Bangkok-specific service gaps and locally-identified innovation opportunities, providing initial conceptual foundation for constraint-driven approaches.

However, the framework represents Bangkok-specific conceptual development requiring systematic validation before any broader application. The empirical evidence establishes conceptual foundation specifically for Bangkok’s context—characterized by democratic governance structures, moderate technological infrastructure, middle-income economic status, and organized stakeholder ecosystems—but provides no evidence for applicability elsewhere. Systematic validation research across different urban contexts remains absolutely essential before considering practical application in other settings.

The findings establish a Bangkok-derived conceptual framework that contributes to age-friendly cities’ literature through context-specific empirical analysis. Any consideration for application in other rapidly aging urban contexts requires independent empirical validation, careful assessment of contextual compatibility, and systematic adaptation of framework principles to local conditions rather than direct transfer of Bangkok-derived approaches.

4.7. SDG 11 Contribution Assessment

The comprehensive analysis provides preliminary empirical support for the three core principles of the Resource-Constrained Age-Friendly City framework:

Priority Hierarchy Adaptation: ANOVA results (F = 12.85, p < 0.001) (see Appendix A Table A3) and the identification of three distinct priority clusters demonstrate that strategic prioritization is both statistically justified and practically necessary.

Multi-Sectoral Resource Optimization: Correlation analysis revealing significant inter-domain relationships (see Appendix A Table A6) and distinct stakeholder capabilities support the theoretical necessity for structural collaboration.

Leapfrog Innovation Potential: The gap analysis revealing critical deficiencies (see Appendix A Table A1) combined with stakeholder identification of technology-driven solutions provide an empirical basis for constraint-driven innovation approaches.

5. Discussion

5.1. Framework Development and Theoretical Contributions

5.1.1. Positioning Within LMIC Age-Friendly Literature

The Resource-Constrained Age-Friendly City (RC-AFC) framework addresses identified gaps in LMIC age-friendly literature through systematic empirical analysis within Bangkok’s middle-income urban context. In contrast to existing approaches that adapt high-income frameworks for LMIC settings, the RC-AFC framework emerges inductively from resource-constrained empirical realities, offering conceptual foundation specifically designed for “getting old before getting rich” contexts.

Comparative analysis positions the RC-AFC framework within broader LMIC age-friendly approaches while highlighting distinct contributions. Similar to China’s Liaoning province model [11], the RC-AFC framework emphasizes systematic prioritization mechanisms for resource allocation decisions. However, the Bangkok-derived framework provides more detailed empirical foundation for multi-sectoral collaboration as structural necessity rather than optional enhancement, addressing gaps identified in Chinese top-down approaches.

The framework’s Leapfrog Innovation principle aligns with Hong Kong’s emphasis on technological solutions and creative infrastructure adaptation [29], while extending theoretical understanding of how resource constraints can drive innovation rather than merely limiting implementation options. In contrast to Hong Kong’s density-focused approach, Bangkok’s findings suggest broader applicability to middle-income urban contexts with moderate rather than extreme space constraints.

5.1.2. Theoretical Contributions to Collaborative Governance

The RC-AFC framework extends the collaborative governance theory by demonstrating how resource constraints transform collaboration from optional enhancement to structural necessity within Bangkok’s democratic governance context. This contribution addresses theoretical gaps identified across LMIC age-friendly literature, where existing frameworks inadequately conceptualize collaboration imperatives in resource-constrained environments.

In contrast to Brazil’s community-participation model [32] or Mexico City’s integration approach [33], Bangkok’s findings provide systematic empirical evidence for distinct stakeholder roles and complementary capabilities essential for resource optimization. The framework’s Multi-Sectoral Resource Optimization principle offers a more structured approach to collaboration coordination than informal community-based models documented elsewhere in LMIC literature.

However, the framework’s collaborative governance contributions remain Bangkok-specific and require systematic validation across different cultural, institutional, and economic contexts before broader theoretical generalization. The democratic governance prerequisite may limit applicability to LMIC contexts with different political systems or institutional arrangements.

5.1.3. Innovation Theory Extensions

The Leapfrog Innovation Potential principle contributes preliminary understanding of constraint-driven solution development within middle-income urban contexts, addressing theoretical gaps identified in comparative LMIC literature. In contrast to deterministic innovation models that assume resource availability, the Bangkok-derived principle suggests that constraints can catalyze creative problem-solving when combined with systematic multi-sectoral collaboration.

This theoretical contribution aligns with broader innovation literature emphasizing resource constraints as potential drivers of creativity, while providing specific application to age-friendly urban development contexts. The framework’s innovation principle offers more systematic theoretical foundation than ad-hoc innovation examples documented across LMIC cities, though empirical validation remains limited to Bangkok’s specific technological and institutional context.

5.1.4. Limitations of Comparative Positioning

The RC-AFC framework’s positioning within LMIC age-friendly literature faces significant limitations requiring explicit acknowledgment. Bangkok’s democratic governance structures, organized stakeholder ecosystems, and moderate technological infrastructure create enabling conditions that may not exist in other LMIC contexts. The framework’s transferability to cities with different political systems, institutional arrangements, or resource severity remains empirically untested.

Additionally, the framework development relies on specific cultural acceptance of systematic prioritization and multi-sectoral coordination that may not translate across different cultural contexts within LMIC settings. The emphasis on formal stakeholder coordination may prove inappropriate for contexts emphasizing informal community networks or different governance traditions.

Comparative analysis reveals the RC-AFC framework as one possible approach to resource-constrained age-friendly development rather than a universal solution for LMIC contexts. Systematic validation across cities with comparable demographic, economic, and governance characteristics remains absolutely essential before considering broader theoretical or practical applications.

5.1.5. Multi-Sectoral Collaboration Insights

The distinct yet complementary roles identified across stakeholder groups provide empirical support for Multi-Sectoral Resource Optimization principles within Bangkok’s governance context. In contrast to high-income contexts where Torku et al. (2020) [34] found that collaboration serves a supplementary role, this study reveals collaboration as structural necessity when government resources alone prove insufficient for comprehensive development. The identification of current collaboration gaps—including lack of standardized communication protocols and insufficient data sharing mechanisms—supports Handler’s (2014) [35] emphasis on comparative evaluation tools assessing both process and outcome indicators.

5.1.6. Innovation Potential Validation

The technology-based and community-based innovation opportunities identified align with broader literature on urban innovation in resource-constrained environments. The potential for “leapfrog” solutions using mobile applications, telemedicine, and community networks supports theoretical frameworks suggesting that constraints can drive innovation, though implementation effectiveness requires systematic testing as noted by the World Bank [36] urban development strategy emphasizing systematic testing across different contexts.

5.2. Implications for Policy and Practice

5.2.1. Bangkok-Specific Implementation Guidance

The dimensional priority framework provides preliminary evidence-based guidance for resource allocation in Bangkok’s rapidly aging context. The identification of Communication and Information, Housing, and Outdoor Spaces as immediate priorities offers direction for policy development, though practitioners should understand the framework’s exploratory status requiring validation before large-scale implementation.

5.2.2. Collaboration Framework Development

The stakeholder role analysis provides a foundation for developing formal collaboration protocols within Bangkok’s governance structure, addressing identified gaps in multi-sectoral coordination specific to Thailand’s administrative and cultural context. The findings suggest potential for unified strategic planning platforms and shared resource pools, though implementation requires careful attention to cultural appropriateness and local governance structures.

5.3. Study Limitations and Validity Considerations

5.3.1. Methodological Limitations

This study represents an initial conceptualization rather than a validated implementation model. The reliance on Importance-Performance Analysis rather than more sophisticated analytical approaches reflects practical constraints in exploratory research but limits theoretical validation, consistent with Davern et al. [37] argument for “more clearly defined scope of actions” in age-friendly research.

The cross-sectional design prevents the examination of causal relationships or temporal dynamics, particularly significant given Thailand’s rapid demographic transition. Priority rankings may not remain stable as aging intensifies and economic conditions evolve, requiring longitudinal validation studies. The framework’s progression toward a validated implementation tool requires a systematic research agenda including controlled pilot testing, longitudinal outcome assessment, and replication studies across comparable middle-income urban contexts.

5.3.2. Bangkok-Specific Boundary Conditions

The framework’s applicability depends on specific enabling conditions present in Bangkok including democratic governance structures, sufficient technological infrastructure, cultural acceptance of systematic prioritization, and middle-income economic status with resource constraints without complete resource absence. These boundary conditions require explicit testing across different contexts before broader application.

5.4. Future Research Directions

5.4.1. Validation Research Priority

The progression from an exploratory framework to a validated implementation approach requires systematic research across multiple domains: (1) Implementation Validation: Pilot testing of RC-AFC principles through controlled interventions in comparable middle-income cities; (2) Outcome Validation: Longitudinal studies measuring age-friendly characteristic improvements; and (3) Contextual Validation: Replication studies across diverse middle-income urban contexts including cities in Malaysia, Indonesia, and the Philippines.

5.4.2. Methodological Advancements

Future research should employ established quality assessment frameworks including Risk of Bias Assessment and Evaluation of Certainty of Evidence tools to enhance validation quality [38]. Advanced mixed-methods approaches combining quantitative outcome measurement with qualitative process evaluation can provide comprehensive understanding of implementation mechanisms.

5.4.3. Cross-Cultural Testing

Systematic replication across comparable middle-income cities including Kuala Lumpur, Ho Chi Minh City, and Manila should employ standardized instruments while allowing for context-specific adaptations to test framework transferability and identify necessary modifications.

5.5. Bangkok’s Context and Implementation Implications

The RC-AFC framework addresses challenges specific to Bangkok’s urban aging context while providing conceptual foundation for similar rapidly aging middle-income cities. The framework’s emphasis on systematic prioritization, multi-sectoral collaboration, and innovation potential provides theoretical foundation for policy development in comparable contexts.

However, the framework requires careful adaptation to different governance systems, cultural contexts, and economic conditions. The approach should be viewed as an adaptable framework requiring systematic modification for local contexts while maintaining core principles addressing resource constraints.

5.6. SDG 11 Implementation Implications

The RC-AFC framework findings, while developed through age-friendly city methodology, offer contextual insights that may inform SDG 11 implementation strategies within Bangkok’s specific urban context. However, direct SDG indicator measurement was beyond this study’s scope, and the connections presented here represent analytical interpretation rather than empirical validation.

Conceptual Connections to SDG 11 Targets

SDG Target 11.1 (Adequate Housing): Bangkok’s significant gaps in Housing Affordability (2.5 points) and Age-Appropriate Design (2.0 points) among older adults may reflect broader housing adequacy challenges relevant to SDG 11.1 objectives. While this study did not measure indicators 11.1.1 (slum populations) or 11.1.2 (housing adequacy) directly, the prioritization of housing-related interventions in resource-constrained contexts aligns conceptually with the SDG 11.1 emphasis on affordable, adequate housing for vulnerable populations.

SDG Target 11.2 (Sustainable Transport): The identification of Vehicle Accessibility (1.8 points) and Bus Stop Infrastructure (1.9 points) as priority areas suggests potential overlap with SDG indicator 11.2.1 concerning convenient public transport access. However, older adults’ mobility needs, as measured in this study, differ substantially from general population transport accessibility requirements measured in official SDG assessments.

SDG Target 11.3 (Sustainable Urbanization): The relatively adequate performance in Civic Participation and Employment (0.63 points gap) combined with the Multi-Sectoral Resource Optimization principle may indicate existing participatory mechanisms relevant to SDG indicator 11.3.2 (participatory planning structures). Nevertheless, age-friendly participation mechanisms do not necessarily translate to city-wide participatory planning systems required for SDG measurement.

Analytical Limitations and Methodological Divergence

The fundamental methodological differences between this age-friendly city study and SDG 11 indicator measurement create significant interpretive constraints. SDG 11 indicators require city-wide quantitative data (population percentages, spatial measurements, accessibility ratios), while this study employed perception-based Importance-Performance Analysis among older adults specifically. These represent fundamentally different analytical approaches addressing different research questions.

Furthermore, the target population specificity limits SDG relevance. While older adults’ experiences may serve as indicators of broader urban challenges, their specific needs and perceptions cannot substitute for comprehensive urban population assessment required by SDG frameworks. The geographic scope limitation to Bangkok’s older adult communities precludes generalization to city-wide SDG implementation requirements.

Policy Integration Considerations

Despite methodological limitations, the RC-AFC framework’s emphasis on systematic prioritization and multi-sectoral collaboration offers potential complementary approaches to SDG 11 implementation in resource-constrained contexts. The Priority Hierarchy Adaptation principle may inform SDG target prioritization when cities face competing development demands, while Multi-Sectoral Resource Optimization approaches could support the collaborative governance mechanisms essential for sustainable urbanization objectives.

However, these remain conceptual connections requiring empirical validation through dedicated SDG-specific research. The framework’s contribution to SDG 11 implementation should be viewed as providing contextual insights for older adult-inclusive urban planning rather than direct SDG indicator assessment or substitution.

Research Recommendations

Future research examining SDG 11 implementation in contexts similar to Bangkok should consider the following:

(1)

Dedicated SDG indicator measurement using official methodologies across all urban population groups.

(2)

Integration of age-friendly considerations into broader SDG assessment frameworks.

(3)

Systematic evaluation of resource-constrained approaches to SDG target prioritization.

(4)

Cross-validation studies examining relationships between age-friendly city indicators and broader urban sustainability metrics.

This study’s primary value for SDG 11 discourse lies in demonstrating approaches to systematic prioritization and collaborative resource optimization rather than providing direct SDG indicator data or assessment methodologies.

6. Conclusions

This research presents the Resource-Constrained Age-Friendly City (RC-AFC) framework as a preliminary conceptual approach specifically designed for “getting old before getting rich” urban contexts. The study provides initial empirical foundation for three core principles—Priority Hierarchy Adaptation, Multi-Sectoral Resource Optimization, and Leapfrog Innovation Potential—through comprehensive analysis of older adults’ needs and stakeholder collaboration potential in Bangkok.

6.1. Key Findings and Contributions

This research presents the Resource-Constrained Age-Friendly City (RC-AFC) framework as a preliminary conceptual approach specifically designed for “getting old before getting rich” urban contexts, using Bangkok as an empirical case study. The study provides an initial foundation for three core principles through comprehensive analysis of older adults’ needs and stakeholder collaboration potential within Bangkok’s specific context.

The research identifies significant gaps between older adult expectations and current age-friendly services (average gap: 1.34) in Bangkok, with Communication and Information, Housing, and Outdoor Spaces requiring immediate priority attention. The study reveals distinct yet complementary roles across government, private sector, civil society, and educational institutions within Bangkok’s governance structure.

6.2. Practical Implications for Bangkok’s Context

The dimensional priority framework provides preliminary evidence-based guidance for resource allocation in Bangkok’s rapidly aging context. The identification of specific intervention priorities and stakeholder roles offers a foundation for policy development within Thailand’s administrative and cultural framework.

6.3. Research Status and Future Requirements

This study represents proof-of-concept for Bangkok’s context rather than proof-of-effectiveness, providing a foundation for future validation research rather than immediate implementation guidance. The framework’s progression toward a validated implementation tool requires a systematic research agenda including controlled pilot testing in comparable settings, cross-cultural replication, and longitudinal outcome assessment.

Practitioners and policymakers should understand the framework’s exploratory status requiring a systematic validation before practical application at scale. The study’s primary contribution lies in developing a theoretically-grounded and empirically-informed starting point for validated approaches to age-friendly city development in resource-constrained contexts similar to Bangkok.

6.4. Contribution to Global Understanding

As middle-income countries worldwide face compressed demographic transitions similar to Thailand, the RC-AFC framework addresses challenges requiring innovative approaches to urban aging. The framework provides a conceptual foundation developed from Bangkok’s experience for addressing similar challenges across comparable contexts, though systematic adaptation and validation remain essential for broader application.

The research demonstrates potential for transforming resource constraints from implementation barriers into innovation catalysts within middle-income urban contexts, contributing to broader sustainable development objectives while maintaining focus on practical implementation feasibility in resource-limited environments comparable to Bangkok.

6.5. SDG 11 Implementation Context

The RC-AFC framework contributes to the SDG 11 implementation by providing evidence-based prioritization mechanisms developed specifically for Bangkok’s rapidly aging middle-income context. The framework’s innovative approach to resource-constrained age-friendly development supports multiple SDG 11 targets while addressing the specific challenges of the “getting old before getting rich” demographic transition experienced by Bangkok and similar cities.