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Hypothetical Model Structure
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The high demand for educated workers in various jobs has created opportunities for secondary school graduates to advance their studies. Increased intellectual and expertise is the basis for better employment opportunities and higher salaries. Students studying in another city need a place to live and supplies. Housing needs are often not provided b...
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Context 1
... was meant to obtain the appropriate variables and indicators in the study area. The structured hypothetical model was proposed to assess the impact of studentification, as shown in Figure 2. The model can be developed as input for studentification research in other areas according to based on their local conditions. ...
Citations
... These community changes often have five major dimensions, which include social, cultural, physical (environmental), economic, and institution and governance [9,10]. Situmorang et al. [11] posited that socially, studentification leads to structural gentrification and segregation. Culturally, the social clusters or concentrations of youths with shared students' culture, lifestyle, and consumption practices lead to the introduction of new sub-cultures in the area. ...
... All ES within each criterion were summed up to obtain the criteria score (CS) using Equation (11) [94]. ...
Globally, most higher educational institutions can no longer house their students within their campuses due to the increased number of enrolments and the unavailability of land for spatial expansion, especially in urban areas. This leads to studentification which negatively impacts university towns. Developing resilience against the negative impacts of studentification will make university towns more sustainable. However, there is no existing community resilience index designed for that purpose. Thus, this study develops a composite resilience index for university towns, using Akoka, a university town in Lagos, Nigeria, as a case study. The composites of the index were determined by prioritizing online user-generated content mined from Twitter between 1 January 2010 and 31 December 2021 using artificial intelligence, while the elements of resilience and risk reduction were developed through the Delphi and analytic hierarchy process. The research outcomes showed that the physical, economic, social, and cultural criteria subjected to comparisons represented ≥70% of the total weights. These criteria made up the outcome indicators, while the integrated community-based risk reduction program model was adopted for the process indicators. Both outcome and process indicators formed the localized composite resilience index for Akoka, Lagos, Nigeria. This proposed composite resilience index would help the town to assess and build resilience against the negative impacts of studentification and provide a methodology for other university towns to create theirs using similar methods.
... Studentification leads to urban changes over time. According to Smith [20] and Situmorang et al. [21] these changes have five key dimensions: social, cultural, physical, economic, and governance. Socially, studentification leads to structural gentrification and This study gives a global overview of university towns' challenges due to studentification beyond the housing issues often discussed in the literature. ...
... Studentification leads to urban changes over time. According to Smith [20] and Situmorang et al. [21] these changes have five key dimensions: social, cultural, physical, economic, and governance. Socially, studentification leads to structural gentrification and segregation. ...
University towns face many challenges in the 21st century due to urbanization, increased student population, and higher educational institutions’ inability to house all their students on-campus. For university towns to be resilient and sustainable, the challenges facing them must be assessed and addressed. To carry out community resilience assessments, this study adopted a novel methodological framework to harness the power of artificial intelligence and social media big data (user-generated content on Twitter) to carry out remote studies in six university towns on six continents using Text Mining, Machine Learning, and Natural Language Processing. Cultural, social, physical, economic, and institutional and governance community challenges were identified and analyzed from the historical big data and validated using an online expert survey. This study gives a global overview of the challenges university towns experience due to studentification and shows that artificial intelligence can provide an easy, cheap, and more accurate way of conducting community resilience assessments in urban communities. The study also contributes to knowledge of research in the new normal by proving that longitudinal studies can be completed remotely.
Harapan Kita Heart Hospital and Dharmais Cancer Hospital are national scale hospitals in Indonesia, are central hospitals with the most complete service facilities for heart disease and cancer. these two hospitals are referral centers for patients from various provinces and cities throughout Indonesia. There are various levels of care needed, patients must be accompanied by family or relatives at the time of treatment. For this reason, patients need a place to live around these two hospitals. The purpose of this study is to identify residential areas around Harapan Kita Heart Hospital and Dharmais Cancer Hospital, as well as identify land use suitability with the DKI Jakarta RDTR 2022. The study location is RT01 and RT 08, RW 06 and RW 09, South Bamboo City Village, Palmerah District, West Jakarta City, which is directly adjacent to the two hospitals. Descriptive analysis was used to determine the changes that occurred based on in-depth interviews with 30 study respondents who were boarding house owners or guards. The results showed a change in residential form by 80% from a onestory house to a 2.3-storey building, with the Basic Building Coefficient and Building Floor Coefficient not in accordance with the DKI Jakarta RDTR 2022.
