Using Different Probability Distributions for Managerial Accounting Technique: The Cost-Volume-Profit Analysis
Hassan A. Said · Journal of Business and Accounting · 2016
(ProQuest: ... denotes formulae omitted.)INTRUDUCTIONThe use of cost-volume-profit (CVP) analysis has application not only in the manufacturing sector but also for financial services entities (Basu et al. 1994). Despite a considerable research literature progress on CVP analysis, that has accumulated since the seminal contribution of Jaedicke and Robichek (1964), this advancement has been almost entirely unheeded by textbooks authors of accounting and finance. Like all financial models, CVP, is based on a set of simplifying assumptions that reduce the complexity of input and output variables to make decision making more tractable. To understand a financial model and its usefulness, its assumptions and their role in a decision must be understood. According to Horngren and Foster (2010), the basic CVP model is subject to ten essential assumptions and limiting conditions: behavior of costs and revenues is linear, selling prices are constant, prices of production inputs are constant, all costs can be categorized into their fixed and variable elements, total fixed costs remain constant, total variable costs are proportional to volume, efficiency and productivity are constant, the model involves a constant sales mix or a single product, revenues and costs are being compared over a unit-volume base, and volume is the only driver of costs. Learning the basic deterministic CVP model is fortunate for students, but an understanding of the generalization of the model to uncertainty situations and relaxing some of its limiting conditions is an added improvement. A CVP model that incorporated uncertainty would hence provide a good entry point into the essential but challenging topic of decision-making under uncertainty. Virtually all real-world business decisions take place under conditions of uncertainty, and that at least some modest degree of familiarity with analytical approaches to decision-making under uncertainty could well benefit the future business leaders. The seminal application of uncertainty to the CVP model was first introduced by Jaedicke and Robichek using the basic CVP equation:... (1)Where Z = Profit, Q = Unit Sales, P = Price/Unit, V =Variable Cost/unit, F= Total Fixed CostVarious statistical distributions has been investigated perilously such as normal (Jaedicke and Robichek, here after JR, (1964)), log normal (Hilliard and Leitch (1975)) and several distribution-free methods such as the Tchebycheff Inequality (Buzby (1974)), model sampling (Liao (1975), and Kottas and Lau (1978)), and additional improvements are examined to the CVP model such as multiproduct (Johnson and Simik (1971), and cost of capital and degree of operating leverage (Guidry, Horrigan and Craycraft (1998)), all have been employed by these and other authors (Shih (1979), and Yunker and Yunker (2003) and Banker, Dyzalov, and Plehn-Dujowich (2014)) to analyze the demand uncertainty, cost behavior and the random behavior of profits. The application of these works was largely confined to the assessment of probability distribution of profit and the calculations of their central tendency (mean) and spread (variance) to identify the best' choice among alternative measures of profit.Thus far, this extensive literature has been virtually ignored by managerial and cost accounting authors, e.g., Garrison, Noreen, and Brewer (2011), Zimmerman (2013), Warren, Reeve, and Duchac (2014), and their reluctance to undertake CVP models under uncertainty may be attributed to the diversity and complexity of the research literature, i.e., multi-product, multiple uncertainty sources, the assumption that demand exceeds, equals, or less than production sales, use of the basic accounting CVP model versus economic demand relating quantity sold to price and/or unit cost functions. The CVP analysis is expected to be complicated, connecting as it does to various concepts from economics and mathematical statistics. However, Bhimani, et al. …