1. Limited sample size: The small size of the architectural research community and the limited availability of data can make it difficult to draw robust conclusions from quantitative research in architecture.
2. Difficulty in measuring subjective variables: Variables like aesthetic value, user behavior, and experience are difficult to quantify and measure systematically in architecture.
3. Lack of standardization: There is a lack of standardization in the measurement tools and data collection techniques used in architectural research.
4. Time-consuming data collection: Collecting data in architecture can be time-consuming due to the complex nature of architectural projects and the involvement of different stakeholders.
5. Limited availability of data: Many architectural projects are unique and do not have a large dataset, which can limit the scope and generalizability of research findings.
6. Complexity of data analysis: Analyzing architectural data can be a challenge due to the complexity and multidisciplinary nature of the field.
7. Ethical concerns: There can be ethical concerns related to data privacy and the use of data in architectural research, particularly when it involves human subjects or sensitive information.
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