An Extended Sustainable Supply Chain Framework Integrating Market Uncertainties for Demand Forecasting

ABSTRACT

The emergence of an extended sustainable supply chain (ESSC) has highlighted the importance of incorporating sustainable consumer behavior into supply chain decision‐making. However, existing studies consider consumer behavior as a qualitative consideration, while demand uncertainty is modeled as an exogenous market disturbance. Thus, limited attention has been given to understanding how dynamic consumer behavior generates demand uncertainty within ESSC. To address this gap, this study develops a generalized mathematical modeling framework that conceptualizes demand uncertainty as an endogenous outcome of sustainable consumer behavior. Specifically, balking and repurchasing behavior are explicitly incorporated into the demand generation process. An ordinary differential equation‐based framework is proposed to capture the demand dynamics. Moreover, a gamma‐distributed random variable is introduced to represent uncertainty arising from behavioral fluctuations. Further, using the Laplace transformation technique, a closed‐form analytical solution is derived from which multiple demand models are developed using different cumulative distribution functions. The proposed models are validated on real‐world sales datasets from the automotive and electronics sectors. To identify the most suitable demand model, a hybrid AHP‐G‐TODIM multicriteria decision‐making framework is employed. AHP‐G is utilized to determine the criteria weights and TODIM for ranking alternatives. The findings demonstrate the significance of consumer behavior in shaping demand uncertainty and provide a quantitative approach for analyzing customer‐driven demand dynamics. The study contributes to the ESSC literature by establishing an analytical relationship between sustainable consumer behavior and demand uncertainty, thereby supporting more effective forecasting and supply chain decision‐making.