Application of stochastic linear programming in managerial accounting

Di Wu, Yong Choi and Ji Li

International Journal of Accounting & Information Management, 2020, vol. 28, issue 1, 184-204

Abstract: Purpose - This paper aims to focus 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 programming (DLP) models do. Design/methodology/approach - This paper introduces both DLP and SLP methods. In addition, continuous and discrete SLP models are explained. Applications are demonstrated using practical examples and simulations. Findings - This research work extends the current knowledge of SLP, especially concerning managerial accounting issues. Through numerical examples, SLP demonstrates its great ability of hedging against all scenarios. Originality/value - This study serves as an addition to building a cumulative tradition of research on SLP in managerial accounting. Only a few SLP studies in managerial accounting have focused on the development of such an instrument. Thus, the measurement scales in this research can be used as the starting point for further refining the instrument of optimization in managerial accounting.

Keywords: Scenario analysis; Data analytics; Deterministic linear programming; Stochastic linear programming (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijaimp:ijaim-12-2018-0148

DOI: 10.1108/IJAIM-12-2018-0148

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