Search results

The need for flexibility between organisational units is well established in corporate real estate. While the cost of flexibility is rather straightforward to approximate, measuring economical value of the flexibility is not straightforward. The purpose of this paper is to explore how real options analysis can be used for valuing flexibility in a real retrofit investment case, present a research process for valuing the flexibility in the retrofit investment case, and evaluate the empirical usability of real options valuation results compared with traditional discounted cash flow valuation results.

The research is conducted as a case study. A newly introduced real options valuation method, the fuzzy pay-off method is used for analysing data from a Finnish office building retrofit investment case. The major difference in the selected method is that it uses fuzzy set theory instead of probabilistic theory, and the main advantage is the practical applicability, i.e. only three scenarios (minimum, best guess, and maximum) are needed for the valuation of flexibility. In the case, the scenarios are determined using a seven-phase research process that incorporates data available (e.g. rental agreements, building information) to a corporate real estate unit. The research process involves defining vacancy scenarios for rental agreements, transforming them into potential income achievable with flexibility, estimating cost of flexibility, comparing the potential income with the costs, and valuing the real options.

The main finding of this paper is that real options analysis; especially the fuzzy pay-off method can be used for assessing the monetary value of flexibility. The applicability of the fuzzy pay-off method into a practical investment case was found straightforward because assignment of probabilities into different uncertainty scenarios was unnecessary. In the empirical case, it was found that flexibility investments were profitable only when parts of the building instead of the whole building were designed flexible. The present value of the pay-off from flexibility ranged from negative 58/sqm to positive 130/sqm, depending on the tenant.

Real options literature, especially in the real estate and construction sector, has requested for new applications of real options analysis in practical setting. This paper adds to that request with an example of evaluating flexibility in a retrofit investment case. The empirical analysis produced in this paper was perceived valuable by case study investor and can be used as a guidance and motivation for further applications of real options in the industry.

The purpose of this paper is to apply the real option method with fuzzy logic to value the government‐sponsored projects of advanced technology development for strategic selection in an uncertain competitive environment.

For strategic selection of government‐sponsored industrial R&D projects, in this paper, Carlsson and Fúller's model was adopted which employs fuzzy logic to estimate the benefits and costs calculated from various scenarios and utilizes Black‐Scholes‐Merton model. The model of strategic selection is suggested for government R&D with fuzzy real option valuation (FROV) and the portfolio planning model from GE‐Mckinsey matrix as well.

FROV was found to be more appropriate to measure the strategic value than the traditional financial method (net present value, NPV, etc.). When the NPV is ambiguous in deciding whether to go or not to go, for instance, just below zero NPV and high volatility of expected benefit, FROV can offer the additive value of the project reflecting volatility of benefit due to the volatility.

Based on insufficient practical data, this methodology should be verified with various projects and measuring volatility of pay‐off requires precise analysis. In addition, research opportunities are in the stepwise R&D project with fuzzy compound real option.

Many papers on economic analysis of R&D project are focused on NPV or cost‐benefit analysis in the public sector. Several attempts with real option have been conducted in the pharmaceutical field or the aerospace (NASA) industry but are not concerned with the fuzziness of expected benefit. Hence, in this paper, fuzzy logic is added to handle imprecise information on the Black‐Scholes‐Merton model with dividend paying.

The purpose of this study is first to evaluate whether real options analysis (ROA) is suitable for valuing green building certificates, and second to calculate the real option value of a green certificate in a typical office building setting. Green buildings are demonstrated as one of the most profitable climate mitigation actions. However, no consensus exists among industry professionals about how green buildings and specifically green building certificates should be valued.

The research design of the study involves a theoretical part and an empirical part. In the theoretical part, option characteristics of green building certificates are identified and a contemporary real option valuation method is proposed for application. In the empirical part, the application is demonstrated in an embedded multiple case study design. Two different building cases (with and without green certificate) with eight independent cash flow valuations by eight industry professionals are used as data set for eight valuation case studies and analyses. Additionally, cross-case analysis is executed for strengthening the analysis.

The paper finds that green certificates have several characteristics similar to real options and supports the idea of using ROA in valuing a green certificate. The paper also explains how option pricing theory and discounted cash flow (DCF) method deal with uncertainty and what shortcomings of DCF could be overcome by ROA. The results show that a mean real option value of 985,000 (or 8.8 per cent premium to the mean property value) was found for a Leadership in Energy and Environmental Design Platinum certificate in the Finnish property market. The main finding of the paper suggests that the contemporary real option valuation methods are appropriate to assess the monetary value and the uncertainty of a green building certificate.

This is the first study to argue that option-pricing theory can be used for valuing green building certificates. The identification of the option characteristics of green building certificates and demonstration of the ROA in an empirical case makes questions whether the current mainstream investment analysis approaches are the most suitable methods for valuing green building certificates.

The high expenditures in information technology (IT) and the growing usage that penetrates the core of business have resulted in a need to effectively and efficiently evaluate strategic IT investments in organizations. The purpose of this paper is to propose a novel two‐dimensional approach that determines the deferrable strategy with the most value by maximizing the real option values while minimizing the risks associated with each alternative strategy.

In the proposed approach, first, the deferrable investment strategies are prioritized according to their values using real option analysis (ROA). Then, the risks associated with each investment strategy are quantified using the group fuzzy analytic hierarchy process. Finally, the values associated with the two dimensions are integrated to determine the deferrable IT investment strategy with the most value using a fuzzy preemptive goal programming model.

Managers face the difficulty that most IT investment projects are inherently risky, especially in a rapidly changing business environment. The paper proposes a framework that can be used to evaluate IT investments based on the real option concept. This simple, intuitive, generic and comprehensive approach incorporates the linkage among economic value, real option value and IT investments that could lead to a better‐structured decision process.

In contrast to the traditional ROA literature, the approach contributes to the literature by incorporating a risk dimension parameter. The paper emphasizes the importance of categorizing risk management in IT investment projects since some risk cannot be eliminated.

Real option valuation is capable of accounting for uncertainties in residential development projects but still lacks practical adoption due to limited evidence to support application of the theory in practice. The purpose of this paper is to use option valuation to value staging option embedded in residential projects and compare with results from DCF to determine which of the two methods delivers superior results.

The fuzzy payoff method (FPOM), a real options model that uses scenario planning approach to generate a range of figures, from which a single-numerical value is computed for decision-making.

The results showed that the use of a range of figures was able to represent uncertainties to a higher degree of accuracy than the static DCF. As a result, the FPOM was able to capture about 3 per cent of the value of the project that was missed by the DCF. The staging option offers an opportunity to abandon unprofitable phases of a project, thereby limiting downside losses. Thus, real option models are practically applicable to cases in property sector.

Residential property developers must consider flexibility in financial feasibility evaluation of development because of the embedded value in uncertain property projects. It is important to account for optionality in financial evaluation of property projects for value maximisation.

The FPOM has been used for the first time to evaluate a horizontal phasing of a residential development project.

The principal concern of organization managers in the global rivalry of commerce environment is how to select the project portfolio among available projects. In this matter, organizations should consider the uncertainty intrinsic in the projects regarding an appropriate valuation technique within an optimization framework. In this research, the purpose of this paper is to formulate using a robust optimization algorithm to deal with the complexities and uncertainty inherent in the construction of the project portfolio.

First, a general mathematical formulation is presented, which in compound real options valuation is highlighted. This formulation gives managerial flexibility by correcting the deficiency of traditional discounted cash flow technique that excludes any form of flexibility. Then, considering a limitation on budget of the organization, an integer programming formulation to maximize the n-fold compound options for project portfolio selection is proposed. Finally, a robust optimization model is developed along with the robust combinatorial optimization algorithm, which is effective for solving problems under uncertainty.

Sensitivity analysis showed that projects in later phases of development, having survived several phases of pre-clinical and clinical tests, are worth more because they are more likely to pertain to business. However, the investment costs related to each project during development phases limit the number of projects that a company can bring to their final portfolio. Additionally, the analysis of conservatism level represented how project managers can quite easily determine their risk attitude and the corresponding portfolio composition. From a managerial point of view, the proposed framework is very useful because it requires only financial estimates. Hence, the proposed decision support tool can assist research and development (R&D) project managers in the pharmaceutical industry for making decisions.

The first is the application of the n-fold compound options on portfolio of R&D projects and the employment of compound options value of a project portfolio as an objective function. The second one is a mathematical formulation of these concepts and solving it by the robust combinatorial optimization algorithm. The literature is lacking in the application of the robust combinatorial optimization algorithm to R&D project portfolio selection based on the generalized n-fold compound option model of Cassimon et al. (2004). Every framework from calculation of the n-fold compound option to solving robust combinatorial algorithm is programmed in Matlab software, since it can be used as a business support tool.

Uncertainties in residential property investment performance require that real estate assets are designed in a flexible manner to respond to impacts of market dynamics. Though estimating the cost of flexibility is straightforward, assessing the economic value of flexibility is not. The purpose of this study is to explore the potential practical application of real option analysis to determine the economic value of a switching output flexibility embedded in a residential property investment in Australia. The study involves the exploration of an optimal strategy for investment in a residential development through real option analysis and valuation of a mixed use investment.

The real option valuation model developed by McDonald and Siegel (1986) is adopted for the evaluation because the switching output flexibility is likened to a perpetual American call option with dividend payout.

Through real option analysis, the economic value of switching output flexibility of the mixed use building was determined to be higher than the initial upfront costs. Moreover, a payoff of about $4million was determined to be the value of the switching output flexibility, therefore justifying upfront investments in flexibility as an uncertainty and risk management tool.

This application is an important demonstration of the practical use of options pricing techniques (real options analysis) and delivers further evidence needed to support the adoption of real option valuation in practice. Flexibility can also enhance risks and uncertainty management in residential property investment better than the adjustment of discount rates.

There is limited evidence on the use of real options techniques for the valuation of switching output flexibility in practice, and this comes as an original application; both the case study and data are all initial applications of switching flexibility in the Australian property market.

A new method to solve zero‐sum two‐person games with imprecise values in their matrices of pay‐offs is suggested. The natural lack of precision generated by the use of fuzzy numbers in a fuzzy game requires the use of subjective criteria by the players in the resolution model. We apply a ranking function, the Average Value, which allows the decision makers to take into account their subjectivity. The use of this function raises again the solution of the fuzzy game when two criteria, one for each player, are used.

The paper aims to introduce a novel concept to solve the bi-level multi-criteria nonlinear fractional programming (BL-MCNFP) problems. Bi-level programming problem (BLPP) is rigorously flourished and studied by several researchers, which deals with decentralized decisions by comprising a sequence of two optimization problems, namely upper and lower-level problems. However, on the other hand, many real-world decision-making problems involve multiple objectives with fraction aspects, called fractional programming problems that reflect technical and economic performance.

This paper introduces a VIKOR (“VlseKriterijumska Optimizacija I Kompromisno Resenje”) approach to solve the BL-MCNFP problem. In this approach, an aggregating function based on L_P metrics is formulated on the basis of the “closeness” scheme from the “ideal” solution. The three steps perform the solution process: First, a new concept is attempted to minimize and maximize of the numerators and denominators from their respective ideal solutions and anti-ideal values simultaneously. Second, for each level, the K-dimensional objective space of each level is converted to a one-dimensional space by an aggregating function. Third, to obtain the final solution, all levels are combined into single-level model where the decision variables of upper levels are interrelated with other levels through fuzzy strategy-based linear and nonlinear membership functions.

The effectiveness of the proposed VIKOR is demonstrated by numerical examples, where the reported results affirm that the extended VIKOR method provides superior results in comparison with the same methods in the literature, and it is a good alternative to BL-MCNFP problems.

In terms of the assistance-based right decision, a parametric analysis for the weight of the majority is provided to exhibit a wide range of compromise solutions for the decision-maker.

The purpose of this paper is to demonstrate how managerial estimates of long-term market price trends can be included into investment analysis of metal mining. The inclusion of subjective market information with a new cycle reverting price process is proposed.

Subjective managerial estimates are included into stochastic metal price modeling by defining separately the following parameters of each price cycle phase: approximated length, approximated long-term price level and volatility. An net present value-based investment analysis model is applied together with Monte Carlo simulation.

It is plausible to combine managerial estimates about metal price trends and cycles with stochastic modeling for shorter term and to include the information into investment analysis. The results show that the difference between the proposed process and the commonly used mean reverting process is remarkable in terms of decision-making implications.

The proposed method allows the inclusion of more relevant information into the metal price modeling used in mining investment analysis. Results suggest that the cyclical nature of metal prices affects project value of metal mining projects, and it should be considered when making irreversible investment decisions. The proposed method can be generalized for any cyclical processes.