[800 Words; 5 Minute Read] Research methodology often incorporates case studies, and it is important to outline case study epistemological merits and limitations. Firstly, the case study approach allows integration with the causal drivers operating at various geographies. Here in this article, I focus largely at the city and sub-city scale such as the neighbourhood scale as defined by an administrative authority. In doing so, it can be argued that the case study method allows investigators to retain the holistic and meaningful characteristics of real-life events such as individual life cycles and neighbourhood change. Furthermore, case study methods are encouraged when studying complex interaction of phenomenon such as community organization at the neighbourhood scale (Yin, 2017).

Challenges to this approach involve the difficulty of placing case studies in context that in turn increases the amount of explanatory and causality variables. For instance, it can be argued that the inclusion of context creates more variables than data points, the richness of study needing multiple data sources of evidence, and the need for analysis strategies even if all the relevant variables are quantitative (Yin, 2017).

Despite these challenges, once placed in some context the use of case studies in this type of research can aid in illuminating neighbourhood issues such as economic decline and growth. If case studies used in research are directed at smaller scale geographies, neighbourhood scales may be appropriate. Neighbourhoods can be aggregated to conceptualise case study areas such as city, city-region, regional, national, global, and policy areas scales where different sets of governance structures and policy areas operate.

Research could focus on inter-neighbourhood analysis at the city-scale case of a city as defined by its administrative local authority boundary. City boundaries contain neighbourhoods formed by political-geographies developed in relation to the census. Census ‘off the shelf’ neighbourhood boundaries are used with a view to further explore whether they can be related to other neighbourhood boundaries (e.g. super output areas in the United Kingdom; block geographies in the United States; and mesh blocks in New Zealand). Neighbourhoods contained within a city case can be analysed in order to explore variable relationships using data sets accessed from city and national administrative organisations.

Databases can be interrogated by looking at certain variables, such as the dependant variable of house prices being used to draw statistical findings in relation to other independent variables that make up ‘global’ city results for all neighbourhood cases at the small scale census level. Further, the specific intra-neighbourhood case studies (i.e. within a single neighbourhood boundary) can be identified and selected through exploratory regression scatterplots that plot a census geography using a house price dependent indicator against other independent indicators such as tenure and educational attainment.

Those small scale geographies with lower than expected price for properties against neighbourhood characteristics can then be used to pinpoint neighbourhoods for Intra-interrogation. This intra-neighbourhood case study selection method provides a more objective selection of neighbourhoods using outliers of the ‘normal’ (line of best fit) housing market in a city-scale case. Once the neighbourhood cases are selected, inter-neighbourhood analysis such as geographical and temporal weighted regression can be carried out between neighbourhoods to provide a city-scale case study.

Once a neighbourhood has been selected, intra-neighbourhood case study analysis can then be carried out within the selected case studies using secondary longitudinal house price change, comparing descriptive statistics (between neighbourhood cases and comparison to wider district and city averages), drawing on primary interview findings, fieldwork, focus groups, and attendance at meetings. The intra-neighbourhood case studies are used to tease out more qualitatively any further neighbourhood drivers of say decline and growth. Including spatial patterns and temporal dynamics.

Specific intra-neighbourhood findings can then be used: (a) to add weight to the statistical and Geographic Information Science (GISc) findings by confirming or rejecting them; and (b) to further enrich the results by providing findings that may have fallen short due to data limitations. In analysing spatial policy, the intra-neighbourhood case selections could be partly formed via parameters such as location in the spatially targetted policy area.

Looking to the future, research into small scale geographical analysis opens up the opportunity to more deeply analyse policy and neighbourhood drivers and dynamics elsewhere. For instance, if looking at neighbourhoods in decline or growth, they could be contextually compared as ‘shrinking’ or ‘growing’ case cities that share the more structural characteristics of industrial decline or technological boom. It should be stressed that these wider cases in other policy areas and cities need to be carefully considered in their use for direct comparative analysis given the path dependencies. A path dependency is a path with which policies and cities have evolved over very specific and different historical and spatial context.

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