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This study aims to clarify the following research questions: to what extent do people consider natural disaster risks as important for residential selection? what personal demographics and attitudes toward natural disaster risks are associated with the relative importance of natural disasters for residential selection? and to what extent do the associated personal attributes influence the relative importance of natural disasters for residential selection?

An internet-based survey was performed to collect 2,000 responses from residents of Osaka Prefecture, Japan, to gauge people’s relative importance of safety against natural disasters regarding residential preference. The obtained results were analysed using two types of statistical analysis, specifically chi-square test and multivariable logistic regression analyses.

It was found that 37.3% of the respondents in Osaka Prefecture, Japan, considered the “safety against natural disasters” relatively important when selecting a residential location. The statistical analysis also demonstrated that those having a relatively higher level of disaster awareness and preparedness were 1.41 times more likely to prefer to live in a place that is safer from natural disasters. Thus, it was suggested that disaster education aimed at raising the level of people’s disaster awareness could be effective to increase the number of people who choose to live in a safer place from natural disasters.

Living in an area that is safer from natural disasters can effectively minimize human and property damage. Recently, several measures have been taken in Japan to guide people to live in a safer place. The clarification of the extent to which people consider natural disaster risks as important for residential selection and the understanding of the categories of the people who are likely to do so is important to develop more effective natural disaster measures; however, there has been less attention on such investigation. Therefore, this study conducted an internet-based survey and examined it.

Culture is increasingly recognized as a key component of local development, but this attention is largely focused on large cities. This paper aims to focus on the ways in which the innovative, participatory action-research (PAR) methods of IdeaLabs and community intervention workshops are used by two projects with solidarity economy enterprise (SEE) participants to activate place-based cultural resources for local development in small communities.

An in-depth reflexive analysis undertaken by researchers involved in the two projects, taking a feminist ethics of care perspective, demonstrates the ways in which these two PAR methods promote local development with the goal of fighting against the economic, social and cultural degradation of small cities and rural areas.

The PAR methods used by the two projects examined stimulate place-based local development initiatives through collaboration and knowledge co-production among participants and researchers. The projects go beyond an instrumental view of the use of culture and the arts for local development to innovate and demonstrate new methodologies for more participatory approaches.

This paper addresses a gap in social economy literature, presenting methods that can be used in PAR projects to catalyse the use of culture as a local development tool by local SEEs.

The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size, which is one of the essential issues in qualitative research. The fuzzy logic model is proposed to determine the sample size in qualitative research.

Considering the structure of the problem in the present study, the proposed fuzzy logic model will benefit and contribute to the literature and practical applications. In this context, ten variables, namely scope of research, data quality, participant genuineness, duration of the interview, number of interviews, homogeneity, information strength, drilling ability, triangulation and research design, are used as inputs. A total of 20 different scenarios were created to demonstrate the applicability of the model proposed in the research and how the model works.

The authors reflected the results of each scenario in the table and showed the values for the sample size in qualitative studies in Table 4. The research results show that the proposed model's results are of a quality that will support the literature. The research findings show that it is possible to develop a model using the laws of fuzzy logic to determine the sample size in qualitative research.

The model developed in this research can contribute to the literature, and in any case, it can be argued that determining the sample volume is a much more effective and functional model than leaving it to the initiative of the researcher.