<p>With the increased role of local authorities in creating cultural policy, gathering information on how successful and sustainable local heritage conservation programs are established will be very valuable in crafting future policies. This dissertation investigated the development of local government heritage conservation policies in the City of San Fernando, Pampanga in the Philippines in order to determine (1) predictors of community support for heritage conservation policy – why communities support heritage conservation policy and what characteristics or elements of communities lead them to support heritage conservation policies, (2) factors that lead to the adoption and implementation of heritage conservation policies or policy drivers of heritage conservation policy, and (3) given the deeper understanding of community support and policy drivers, the relationship between these predictors and drivers with heritage conservation policy management and sustainability. It did this by being cognizant of the lack of homogeneity across communities, with actors, factors, contexts, and nuances specific to each community.</p><p>Implementing two component studies, the dissertation used mixed methods, which interprets and integrates information drawn from the combined strength of both quantitative and qualitative data, following the convergent design (Creswell and Plano Clark, 2018; Harrison et al., 2020) and guided by the Rigorous Mixed Methods framework (Harrison, Reilly and Creswell, 2020). This first study used a self-administered online survey to collect data from stakeholders and ordinary residents of the City of San Fernando, Pampanga which was analyzed using Structural Equation Modelling (SEM). In the second study, guided by the naturalist paradigm (Guba and Lincoln, 1982; Lincoln and Guba, 1985), transcripts of semi-structured interviews conducted by City Tourism and Investment Promotion Office (CTIPO) were coded and analyzed using the grounded theory approach. It combined several coding approaches, specifically a blended approach (Skjott Linneberg, and Korsgaard, 2006), with the the Gioia Methodology (Gioia et al., 2012) and Ünlü-Qureshi instrument (Qureshi and Ünlü, 2020)</p> <p>The integration of qualitative and quantitative data and results was guided by the dimensions of the mixed methods research integration trilogy (Fetters and Molina-Azorin, 2017). The dissertation identified predictors for community support for heritage conservation policy, policy drivers of the heritage conservation policy process, and the relationship between these predictors and drivers and within the heritage conservation policy process and produced three models: (1) predictors of community support for local heritage conservation policy, (2) heritage conservation policy drivers, and (3) managerial implications for heritage conservation policy sustainability, and a framework for heritage conservation, management, and sustainability. The data suggested that in the case of San Fernando, (1) knowledge and awareness, (2) sense of belonging and attachment, (3) place image and community identity, and (4) evaluation of value are predictors of support for heritage conservation policies, with evaluation of value as a mediator for the first three. It also identified two major policy drivers: (1) good governance, and (2) heritage consciousness, and six specific policy drivers: (1) understanding the dynamics of heritage conservation, (2) addressing program sustainability, (3) stakeholder integration in the policy process, (4) appreciation of process-oriented governance, (5) manifesting pride and attachment, and (6) awareness of long-term outcomes of policies, that serve as factors leading to the adoption and implementation of heritage conservation policies. The predictors and policy drivers were incorporated into a single framework for heritage conservation policy management and sustainability.</p>