Pet Industry Analysis Based on Multiple Linear Regression and ARIMA Models

This paper systematically analyzes the market dynamics of the pet industry in China and globally based on multiple linear regression and ARIMA models. First, for the Chinese market, this paper constructs an optimized ridge regression model by analyzing the urbanization trend and market size of major pet types, revealing the significant impact of urbanization and other factors on market size. Second, a multiple linear regression model is used to predict the growth trend of China's pet consumption market in the next three years, taking into account four major influencing factors. Next, the paper analyzes the global pet market and uses the ARIMA model to forecast future pet food demand, and inputs this forecast into a multiple linear regression model to further predict the trend of global pet food demand, finding that the market will peak in 2026. The innovation of this study is the combination of multiple regression and time series analysis methods, which can more accurately assess the future development trend of the pet industry and provide data support for industry decision-making.

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Publication Details

Published
2025-06-28
DOI
https://doi.org/10.1109/icipca65645.2025.11138787
Citations
1
Primary Topic
Environmental Quality and Pollution
Type
article
Field-Weighted Citation Impact
1.72
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article

Pet Industry Analysis Based on Multiple Linear Regression and ARIMA Models

Feng Shen, Yueqing Zhao, Ruiting Shen
1 citations
Environmental Quality and Pollution
1.72
article

Pet Industry Analysis Based on Multiple Linear Regression and ARIMA Models

Feng Shen, Yueqing Zhao, Ruiting Shen
article en
1 citations

Abstract

This paper systematically analyzes the market dynamics of the pet industry in China and globally based on multiple linear regression and ARIMA models. First, for the Chinese market, this paper constructs an optimized ridge regression model by analyzing the urbanization trend and market size of major pet types, revealing the significant impact of urbanization and other factors on market size. Second, a multiple linear regression model is used to predict the growth trend of China's pet consumption market in the next three years, taking into account four major influencing factors. Next, the paper analyzes the global pet market and uses the ARIMA model to forecast future pet food demand, and inputs this forecast into a multiple linear regression model to further predict the trend of global pet food demand, finding that the market will peak in 2026. The innovation of this study is the combination of multiple regression and time series analysis methods, which can more accurately assess the future development trend of the pet industry and provide data support for industry decision-making.

Nanjing University of Information Science and Technology (CN)
Openalex Percentile: Top 14%
Environmental Quality and Pollution
1.72
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Pet Industry Analysis Based on Multiple Linear Regression and ARIMA Models — Feng Shen, Yueqing Zhao, et al. · (2025) | TGRS Research Map | TGRS