Decision dynamics and landscape approach by individuals and collective groups: the case of Japanese rural land use in agricultural, forest, and boundary areas in an era of population decline

Abstract Establishing a decision-making scheme for multiple land use types in a shrinking society is an urgent and persistent task. In particular, residents and governments face the complexity of cross-sectoral visions over concerned landscapes. This study examined the preference of residents for future visions and the effects of group deliberation in a Japanese rural community to enhance the current understanding of decision and learning processes on cross-sectoral land use types (i.e., agricultural land, forest land, and boundary areas) across ages and groups. This study posed the following questions: (i) what types of interactions do residents find among options on cross-sectoral land uses? and (ii) how do group deliberation influence the individual preferences of residents for land use? In the survey, the residents disclosed their preferences for the prepared visions over three land use types. The survey also enabled the comparison of choices before and after group deliberation. Regarding question (i), the residents’ choice prior to the deliberation demonstrated thematic coherence through land use categories. Smart technology and potential productivity improvement were selected across agriculture and forests. However, regarding question (ii), thematic coherence decreased after the group deliberation. The residents could communicate disagreements during group deliberation and consider the issues relatively independently over land use types, which separately views agriculture lands and forests. The choice after group discussions became increasingly embedded and influenced by residential areas and land ownership of residents. These findings provide unique insights into the group discussion on how individual decisions are affected. In summary, the preferences of cross-sectoral land use types did not converge but tended to diverge.