Assessing Management Measures in Large-Scale Residential Facilities: An SNS-Driven Evaluative Approach

Abstract

This research proposes a novel approach to assess management measures in large-scale residential facilities using resident-exclusive Social Networking Services (SNS) data. The study develops a three-domain model (“User-Subjective-Objective”) adapted from Wada's “Value-Function-Activity-Entity” model to analyze resident interactions and behaviors within the SNS environment (M. Wada, 2021). The methodology consists of three main components: modeling the resident exclusive SNS (S. Tsugawa, 2020), clustering users based on their browsing behaviors (Y. Yamaguchi, S. Yamamoto and T. Sato, 2013) and developing a framework for quantitatively assessing management measures. The study employs Hierarchical Clustering Analysis to group users based on their temporal browsing patterns and introduces a method to evaluate management measures through “degree of interest fulfillment.” The research applies this methodology to a case study in the Tokyo Metropolitan Area, analyzing SNS data from 495 users over a one-year period, complemented by survey responses from 78 residents. The results demonstrate the effectiveness of the approach in identifying distinct user clusters and evaluating different management measures, such as “House Reform” and “Mix Bazaar” initiatives. The findings highlight the value of integrating SNS data analysis into residential facility management (A. Kobayashi, et al., 2022), offering a more dynamic and responsive approach to understanding resident needs and evaluating management strategies' effectiveness.