Capital-budgeting decisions using ?crystal ball?

Atkinson, Stanley M.; Kelliher, Charles F.; LeBruto, Stephen M.

doi:10.1016/s0010-8804(97)86579-2

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…The hotel capital budgeting literature has also been extended by more theoretically oriented nonempirical research. Studies conducted in this tradition include Atkinson, Kelliher, and LeBruto (1997), who explored the application of the Monte Carlo simulation model in the context of hotel capital budgeting, and Madanoglu and Olsen (2005), who assessed cost of equity determination models, reviewed their potential lodging industry application, and proposed new approaches to capital budgeting for lodging operations.…”

Section: Literary Context Of Studymentioning

confidence: 99%

Benchmarking Hotel Capital Budgeting Practices To Practices Applied in Non-Hotel Companies

Guilding

Lamminmaki

2007

Journal of Hospitality & Tourism Research

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A survey was conducted to compare hotel capital budgeting practices employed within and outside the hotel sector. It was found that the propensity to inflate investment cash inflow projections outweighs the propensity to deflate cash inflow estimates and the tendency to inflate projected cash inflows is less in the hotel industry. Hotels exhibit a lower level of development with respect to reviewing required rates of return and also applying post-completion audits. Also, NPV and IRR, which are based on discounting approaches, are used to a relatively low degree in the hotel industry and over half the hotels surveyed either exclusively use the payback method (36%) or use no financial investment appraisal method at all (17%). Consistent with prior findings in other industrial sectors, there appears to be a positive relationship between organizational size and use of financial investment appraisal techniques.

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Section: Literary Context Of Studymentioning

confidence: 99%

Benchmarking Hotel Capital Budgeting Practices To Practices Applied in Non-Hotel Companies

Guilding

Lamminmaki

2007

Journal of Hospitality & Tourism Research

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“…Similarly, prognostications presented in probability ranges can be applied to capital budgeting in the hotel industry. Atkinson et al (1997) suggested a software program, Crystal Ball, to address the uncertainty and risks of input variables. Before making a decision for capital budgeting, practitioners have difficulty in estimating future cash flows because traditional methods rely on a point estimation, ignoring the fluctuation caused by uncertainty and risk.…”

Section: How Have These Techniques Been Applied In Other Aspects Of Hmentioning

confidence: 99%

“…Lodging analysts are generally trained to develop projections that conclude with precise figures, that is, point estimates, despite that traditional methods of applying Net Present Value (NPV) and Internal Rate of Return (IRR) analyses do not cover the range of possible results (Atkinson et al, 1997; O’Neill, 2011; Rushmore et al, 2012; Rushmore & O’Neill, 2015). Also, the generally accepted approaches of deriving point estimations have been shown to be based on future projections of a number of economic, demographic, and other factors (Hua et al, 2008; Lee et al, 2016; Nilsson et al, 2002; O’Neill & Carlbäck, 2011) that essentially always deviate from projections.…”

Section: Introductionmentioning

confidence: 99%

Toward Improving Hotel Prognostications Through the Application of Probabilistic Methodologies

O’Neill

Bloom

Sharma

2020

Cornell Hospitality Quarterly

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Existing and generally accepted methodologies for developing projections of future hotel performance have been recently described as “grossly inadequate” and we note they have essentially remained unchanged for decades. Notably, current methodologies result in point estimates of future performance and do not adequately consider the inherent risk in lodging investments. Borrowing from research in other fields, and particularly from the area of finance, we suggest the use of probabilistic, that is, stochastic methodologies. In particular, we recommend hotel investors, operators, and analysts use Monte Carlo simulation. Also, this article provides information regarding why probabilistic methodologies are appropriate and general guidance regarding how to apply such approaches.

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“…An excellent book on computer simulation modeling is the recent publication by Law and Kelton (2000). An example of a mathematical technique used to mimic a probabilistic process within computer simulation is the Monte Carlo method (for a discussion of Monte Carlo simulation and some of its applications, see Atkinson et al , 1997; Field et al , 1997; Sheel, 1995). Some symbolic simulations also utilize alphanumeric data for representation (Race and Brook, 1980).…”

Section: Foundation For Definitionsmentioning

confidence: 99%

Charting the experiential territory

Feinstein

Mann

Corsun

2002

Journal of Management Development

156

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The literature around experiential learning is unclear regarding the similarities and differences among simulation, games, and role play. In order to appropriately evaluate instructional processes, definitional clarity is necessary. In this article, we provide a definitional foundation and classification scheme for the topics of computer simulation, role play, and games. The educational and training outcomes of each are discussed, providing readers the means to determine for themselves, the pedagogical appropriateness of simulation, games, or role play to a given situation.

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Capital-budgeting decisions using ?crystal ball?

Cited by 5 publications

References 6 publications

Benchmarking Hotel Capital Budgeting Practices To Practices Applied in Non-Hotel Companies

Benchmarking Hotel Capital Budgeting Practices To Practices Applied in Non-Hotel Companies

Toward Improving Hotel Prognostications Through the Application of Probabilistic Methodologies

Charting the experiential territory

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