Impact of Demand and Supply in Decision Making for E-Commerce Application

In the rapidly evolving realm of e-commerce, the equilibrium between demand and supply is a linchpin for operational success and financial viability. This abstract encapsulates the core challenge of optimizing decision-making processes within e-commerce applications to navigate the intricate landscape of supply and demand dynamics. With consumer preferences in a state of constant flux and market trends evolving at an unprecedented pace, the challenge lies in comprehending and responding adeptly to these fluctuations. The primary objective is to devise dynamic, analytics-driven decision-making frameworks that empower e-commerce platforms to optimize their demand and supply dynamics, simultaneously ensuring customer satisfaction and sustainable business growth. The stakeholders most affected by the efficacy of these strategies include e-commerce managers, supply chain professionals, and consumers, further emphasizing the urgency and relevance of this issue in the contemporary e-commerce landscape. In the current study, an Analysis of Variance (ANOVA) approach has been used to examine the potential influence of employment on high, moderate, and low levels of demand and supply. ANOVA, or analysis of variance, is a statistical method often used in workforce diversity research. Its purpose is to evaluate if there are statistically significant disparities in a certain outcome variable among various employee groups, as determined by their diversity characteristics.