Application of Stochastic Linear Programming in Managerial Accounting: Scenario Analysis Approach

• In Event: Data Analysis and Information Systems

Abstract

Firms often need to have an optimal allocation of their capital and operating resources so that their business goals, such as maximizing profits and minimizing costs, can be achieved. In these decision-making processes, managerial accounting issues are integrated with operations management models. With the development of information technologies including Big Data and cloud-based systems, cost accountants are more and more involved in the integration of data analytics and business decision making. This paper focuses on applications of stochastic linear programming (SLP) to managerial accounting issues by providing a theoretical foundation and practical examples. SLP models may have more implications—and broader ones— in industry practice than deterministic linear programing (DLP) models do. SLP models aim at hedging against all scenarios and hence show practical advantages in sensitivity and scenario analysis.

Authors

• Di Wu, Cal State University - Bakersfield

• Ji Li, Cal State University - Bakersfield

• Yong Choi, CSU-Bakersfield