CVP under uncertainty and the manager's utility function

Kim, Sangphill; Abdolmohammadi, Mohammad J.; Klein, Lawrence A.

doi:10.1007/bf00367499

Cited by 9 publications

(4 citation statements)

References 8 publications

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“…Kim et al [32] incorporate the utility function of the decision maker into the CVP model. The authors argue that decisionmakers (managers) are trying their best to maximize their utility when they make decision on the investment in risky assets.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Assume Q and C following Gamma distribution, Q ∼ Gamma (q shape , q scale C ∼ Gamma c shape , c scale where q shape and c shape are shape parameters of random variable Q and C, and q scale and c scale are scale parameters of random variable Q and C. Per Appendix A, the moment generating function of function of W gam is m n W gam = 1 q scale c scale n Γ q shape + n Γ q shape Γ c shape + n Γ c shape (29) Using (24), the first moment is m 1 W gam = 1 q scale c scale 1 Γ q shape + 1 Γ q shape Γ c shape + 1 Γ c shape (30) which simplifies to m 1 W gam = q shape c shape. q scale c scale (31) Similarly, the second moment is (32) which simplifies to m 2 W gam = 1 q scale c scale 2 q shape q shape + 1 c shape c shape + 1 .…”

Section: Casementioning

confidence: 99%

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A Generalized Stochastic Cost–Volume–Profit Model

Liang

Guiffrida

Liu³

et al. 2021

Systems

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Cost–volume–profit (CVP) analysis is a widely used decision tool across many business disciplines. The current literature on stochastic applications of the CVP model is limited in that the model is studied under the restrictive forms of the Gaussian and Lognormal distributions. In this paper we introduce the Mellin Transform as a methodology to generalize stochastic modeling of the CVP problem. We demonstrate the versatility of using the Mellin transform to model the CVP problem, and present a generalization of the CVP model when the contribution margin and sales volume are both defined by continuous random distributions.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Casementioning

confidence: 99%

A Generalized Stochastic Cost–Volume–Profit Model

Liang

Guiffrida

Liu³

et al. 2021

Systems

View full text Add to dashboard Cite

show abstract

“…Since the seminal contribution of Jaedicke and Robichek in 1964, a substantial literature has accumulated in accounting, economics, management, and decision science periodicals on the subject of stochastic CVP analysis. Some of the more recent contributors to this literature include Brockett et al (1984Brockett et al ( , 1987, Lau and Lau (1987), Chung (1990Chung ( , 1993, Kim et al (1996), Chan and Wong (1999), and Yunker (2001). Numerous models have been proposed and examined: single-product versus multi-product, single uncertainty source versus multiple uncertainty sources, the assumption that production equals sales versus differentiation of the production quantity from the sales quantity, specification of the decision question simply as produce-not produce versus determination of a quantity to produce and/or a price to set, use of the fundamental CVP equation alone versus the addition of 'economic' functions relating quantity sold to price and/or unit cost to quantity produced, and so on and so forth.…”

Section: Introductionmentioning

confidence: 99%

Pricing training and development programs using stochastic CVP analysis

Yunker

Schofield

2005

Manage Decis Econ

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This paper sets forth, analyzes and applies a stochastic cost-volume-profit (CVP) model specifically geared toward the determination of enrollment fees for training and development (T+D) programs. It is a simpler model than many of those developed in the research literature, but it does incorporate one advanced component: an 'economic' demand function relating the expected sales level to price. Price is neither a constant nor a random variable in this model but rather the decision-maker's basic control variable. The simplicity of the model permits analytical solutions for five 'special prices': (1) the highest price which sets breakeven probability equal to a minimum acceptable level; (2) the price which maximizes expected profits; (3) the price which maximizes a Cobb-Douglas utility function based on expected profits and breakeven probability; (4) the price which maximizes breakeven probability; and (5) the lowest price which sets breakeven probability equal to a minimum acceptable level. The model is applied to data provided by the Center for Management and Professional Development at the authors' university. The results suggest that there could be a significant payoff to fine-tuning a T+D provider's pricing strategy using formal analysis. Copyright © 2005 John Wiley & Sons, Ltd.

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“…Kottas and Lau [34]; Ismail and Lauderbeck[35]; Constantinides, Ijiri and Leitch[36]; Barry, Velez-Arocho and Welch[37]; Lau and Lau[38]; Kim, Abdolmohammadi and Klein[39]; and Yunker[31,42].…”

mentioning

confidence: 99%

Assessment of business value from services re-use on SOA-based e-business platform

Kryvinska

Strauß

Auer

et al. 2010

Proceedings of the 12th International Conference on Information Integration and Web-Based Applications &Amp; Services

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The top drivers for SOA adoption include the expectation of greater reuse in existing and newly-built Web services, business flexibility, simplification and speed of integration. So, in order to maximize the intended benefits of service-oriented architecture (SOA) implementation, organizations need to develop a wellarticulated SOA quality strategy to promote trust and reuse. However, the shift to this strategy does not come easy and cheap. Building an effective SOA platform requires tight integration between new and existing product categories, and it may require large investments. For this reason, conventional investment valuation methods need to be combined with other modern techniques to reflect SOA's long-term strategic investment nature, the inherent uncertainty and the managerial discretion. Some emerging value-based analytical methodologies have started to be developed extensively under the umbrella concept of Business Value Analysis (BVA). Thus, in this paper, we apply modified CVP/BEP method developed under the BVA umbrella for the evaluation of SOA projects, in particular for the services reuse related.

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CVP under uncertainty and the manager's utility function

Cited by 9 publications

References 8 publications

A Generalized Stochastic Cost–Volume–Profit Model

A Generalized Stochastic Cost–Volume–Profit Model

Pricing training and development programs using stochastic CVP analysis

Assessment of business value from services re-use on SOA-based e-business platform

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