Forecasting the green behaviour level of Chinese enterprises: A conjoined application of the autoregressive integrated moving average (ARIMA) model and multi-scenario simulation

Liping Wang, Longjun Chen, Shucen Jin and Chuang Li

Technology in Society, 2025, vol. 81, issue C

Abstract: Enterprises' green behaviour level (EGBL) is an important reflection of a country's green development progress. Gaining foresight into the future trends of EGBL can provide a roadmap for achieving national carbon peak and carbon neutrality ('dual carbon') goals. However, existing research has primarily focused on the factors influencing corporate green behaviour and their potential impacts, whereas predictive studies on EGBL remain underexplored. To address this research gap, this study first combines the characteristics of sustainable development of enterprises and develops a more comprehensive Chinese EGBL evaluation system from 26 evaluation indicators including five positive dimensions and one negative dimension. And then it calculates EGBL based on panel data from 828 industrial enterprises between 2010 and 2020. Subsequently, the study develops the Autoregressive Integrated Moving Average model (ARIMA) and scenario analysis models to conduct a comprehensive, multilevel forecast of the EGBL. The prediction results of EGBL based on the ARIMA model show that: Whether in 2030 or 2060, the EGBL in the middle reaches of the Yangtze River is the highest, and the EGBL in the northeast region is the lowest. The EGBL of state-owned enterprises was higher than that of non-state-owned enterprises. In terms of industry, EGBL ranks highest to lowest in the high-tech, manufacturing, energy, and resource industries. The results of the prediction of EGBL based on the scenario analysis method showed that regardless of the scenario, the overall trend of EGBL continued to increase. In similar scenarios, the evolution of environmental regulations and technological progress from slow to medium growth has a limited effect on EGBL. Only if environmental regulations and technological progress develop rapidly can a significant increase in EGBL be achieved. A cross-scenario analysis shows that for certain environmental regulations and technological progress, the gap in the EGBL caused by changes in economic growth, industrial structure and the degree of urbanisation is relatively small. Therefore, environmental regulations and technological progress are important factors contributing to differences in EGBL. Finally, based on the above prospective analysis, this study identified possible future development paths to improve EGBL in different regions of China.

Keywords: Enterprise green behaviour; ARIMA model; Scenario analysis; Time series; Predictive research (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:81:y:2025:i:c:s0160791x25000156

DOI: 10.1016/j.techsoc.2025.102825

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