An Analysis of Theoretical Construction of Tenant Satisfaction Models for Long-Term Rental Apartments

This study centers on an in-depth discussion of the long-stay apartment tenant satisfaction model, which is constructed and validated by comprehensively applying a variety of modeling methods. In the research process, the latent variables of the long-stay apartment tenant satisfaction model are first identified by summarizing domestic and international satisfaction models. At the same time, based on marketing theory and the theory of inconsistent expectations, structural equation modeling (SEM) was constructed to describe the relationship between the latent variables, and specific models were built to verify the relevant assumptions through regression analysis. When determining the observation variables, we refer to ACSI, ECSI and other models, set the observation variables in combination with the characteristics of long-term rental apartments, and determine their weights by using the hierarchical analysis method (AHP). In addition, Combach α, compositional reliability, average refinement variance and other indicators are applied to test the reliability and validity, and the overall model fit is examined. The results of the study show a strong correlation between the latent variables and provide a clear direction of improvement for long term rental apartment companies.

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Publication Details

Journal
Mathematical Modeling and Algorithm Application
Published
2025-04-25
DOI
https://doi.org/10.54097/eqtkd338
Primary Topic
Place Attachment and Urban Studies
Type
article
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article

An Analysis of Theoretical Construction of Tenant Satisfaction Models for Long-Term Rental Apartments

Yue Li
Mathematical Modeling and Algorithm Application
Place Attachment and Urban Studies
article

An Analysis of Theoretical Construction of Tenant Satisfaction Models for Long-Term Rental Apartments

Yue Li
article en

Abstract

This study centers on an in-depth discussion of the long-stay apartment tenant satisfaction model, which is constructed and validated by comprehensively applying a variety of modeling methods. In the research process, the latent variables of the long-stay apartment tenant satisfaction model are first identified by summarizing domestic and international satisfaction models. At the same time, based on marketing theory and the theory of inconsistent expectations, structural equation modeling (SEM) was constructed to describe the relationship between the latent variables, and specific models were built to verify the relevant assumptions through regression analysis. When determining the observation variables, we refer to ACSI, ECSI and other models, set the observation variables in combination with the characteristics of long-term rental apartments, and determine their weights by using the hierarchical analysis method (AHP). In addition, Combach α, compositional reliability, average refinement variance and other indicators are applied to test the reliability and validity, and the overall model fit is examined. The results of the study show a strong correlation between the latent variables and provide a clear direction of improvement for long term rental apartment companies.

Mathematical Modeling and Algorithm ApplicationVol. 4(3)
Openalex Percentile: Top 87%
Place Attachment and Urban Studies
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An Analysis of Theoretical Construction of Tenant Satisfaction Models for Long-Term Rental Apartments — Yue Li · Mathematical Modeling and Algorithm Application (2025) | TGRS Research Map | TGRS