Diss. Göteborg : Göteborgs universitet, 2005.

Originally presented as the author's doctoral thesis to the European Business School, Oestrich-Winkel. / Description based on print version record. Includes bibliographical references and index.

Originally presented as the author's doctoral thesis to the European Business School, Oestrich-Winkel. / Description based on print version record. Includes bibliographical references (p. [345]-353) and index.

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xii, 144 p.; also includes graphics (some col.). Includes bibliographical references (p. ). Available online via OhioLINK's ETD Center

Originally presented as the author's doctoral thesis to the European Business School, Oestrich-Winkel. / Includes bibliographical references and index.

Originally presented as the author's doctoral thesis to the European Business School, Oestrich-Winkel. / Description based on print version record. Includes bibliographical reference (p. [345]-353) and index.

Assignment (MComm)--University of Stellenbosch, 2006. / Bibliography. Also available via the Internet.

The developments of new technologies for commercial aviation involve significant risk for technologists as these programs are often driven by fixed assumptions regarding future airline needs, while being subject to many uncertainties at the technical and market levels. To prioritize these developments, technologists must assess their economic viability even though standard methods used for capital budgeting are not well suited to handle the overwhelming uncertainty surrounding such developments. This research proposes a framework featuring real options to overcome this challenge. It is motivated by three observations: disregarding the value of managerial flexibility undervalues long-term research and development (R&D) programs; windows of opportunities emerge and disappear and manufacturers can derive significant value by exploiting their upside potential; integrating competitive aspects early in the design ensures that development programs are robust with respect to moves by the competition. Real options analyses have been proposed to address some of these points but the adoption has been slow, hindered by constraining frameworks. A panel of academics and practitioners has identified a set of requirements, known as the Georgetown Challenge, that real options analyses must meet to get more traction amongst practitioners in the industry. In a bid to meet some of these requirements, this research proposes a novel methodology, cross-fertilizing techniques from financial engineering, actuarial sciences, and statistics to evaluate and study the timing of technology developments under uncertainty. It aims at substantiating decision making for R&D while having a wider domain of application and an improved ability to handle a complex reality compared to more traditional approaches. The method named FLexible AViation Investment Analysis (FLAVIA) uses first Monte Carlo techniques to simulate the evolution of uncertainties driving the value of technology developments. A non-parametric Esscher transform is then applied to perform a change of probability measure to express these evolutions under the equivalent martingale measure. A bootstrap technique is suggested next to construct new non-weighted evolutions of the technology development value under the new measure. A regression-based technique is finally used to analyze the technology development program and to discover trigger boundaries which help define when the technology development program should be launched. Verification of the method is performed on several canonical examples and indicates good accuracy and competitive execution time. It is applied next to the analysis of a performance improvement package (PIP) development using the Integrated Cost And Revenue Estimation method (i-CARE) developed as part of this research. The PIP can be retrofitted to currently operating turbofan engines in order to mitigate the impact of the aging process on their operating costs. The PIP is subject to market uncertainties, such as the evolution of jet-fuel prices and the possible taxation of carbon emissions. The profitability of the PIP development is investigated and the value of managerial flexibility and timing flexibility are highlighted.The developments of new technologies for commercial aviation involve significant risk for technologists as these programs are often driven by fixed assumptions regarding future airline needs, while being subject to many uncertainties at the technical and market levels. To prioritize these developments, technologists must assess their economic viability even though standard methods used for capital budgeting are not well suited to handle the overwhelming uncertainty surrounding such developments. This research proposes a framework featuring real options to overcome this challenge. It is motivated by three observations: disregarding the value of managerial flexibility undervalues long-term research and development (R&D) programs; windows of opportunities emerge and disappear and manufacturers can derive significant value by exploiting their upside potential; integrating competitive aspects early in the design ensures that development programs are robust with respect to moves by the competition. Real options analyses have been proposed to address some of these points but the adoption has been slow, hindered by constraining frameworks. A panel of academics and practitioners has identified a set of requirements, known as the Georgetown Challenge, that real options analyses must meet to get more traction amongst practitioners in the industry. In a bid to meet some of these requirements, this research proposes a novel methodology, cross-fertilizing techniques from financial engineering, actuarial sciences, and statistics to evaluate and study the timing of technology developments under uncertainty. It aims at substantiating decision making for R&D while having a wider domain of application and an improved ability to handle a complex reality compared to more traditional approaches. The method named FLexible AViation Investment Analysis (FLAVIA) uses first Monte Carlo techniques to simulate the evolution of uncertainties driving the value of technology developments. A non-parametric Esscher transform is then applied to perform a change of probability measure to express these evolutions under the equivalent martingale measure. A bootstrap technique is suggested next to construct new non-weighted evolutions of the technology development value under the new measure. A regression-based technique is finally used to analyze the technology development program and to discover trigger boundaries which help define when the technology development program should be launched. Verification of the method is performed on several canonical examples and indicates good accuracy and competitive execution time. It is applied next to the analysis of a performance improvement package (PIP) development using the Integrated Cost And Revenue Estimation method (i-CARE) developed as part of this research. The PIP can be retrofitted to currently operating turbofan engines in order to mitigate the impact of the aging process on their operating costs. The PIP is subject to market uncertainties, such as the evolution of jet-fuel prices and the possible taxation of carbon emissions. The profitability of the PIP development is investigated and the value of managerial flexibility and timing flexibility are highlighted.

This thesis studies two optimization problems: the optimization of a staffing policy assuming non stationary Poisson demand, and exponential travel and job times, and the optimization of investment decisions with an investment lag. In the staffing policy optimization, we solve a novel time-dynamic Hamilton-Jacobi-Bellman equation that models jobs as a Poisson jump process. The model gives the employer the flexibility to control the number of staff hired by two factors: the cost of hiring and the effect of delay. We have solved the optimal staffing policy problem using different approaches, which are compared. We produce accurate numerical results for different parameters, and discuss the advantages and disadvantages of each approach. Moreover, we have solved a staffing problem for a national utility company, using a standard linear programming approach, which is compared with our methods. In addition to the Poisson jump process, we extend the model to treat a continuous job model, and two locations model that is extendible to a larger network problem. In the investment lag problem, we use a mixture of numerical methods including finite difference and body fitted co-ordinates to form a robust and stable numerical scheme which is applied to solve the investment lag problem for a geometric Brownian motion presented in the paper by Bar-Ilan and Strange (1996). The problem is to calculate the optimal price to invest in a project that have a time lag period between the decision to invest and production, and the optimal price to mothball the project. The method presented in this thesis is more flexible as we compare it with the previous results, and solves the problem for different stochastic processes, such as Cox-Ingersoll-Ross model, which does not have analytic solution.

The development of new infrastructure invariably requires massive capital investments, take many years to design and deliver, and are expected to operate for several decades. During delivery and operational lifetime, the functional requirements are likely to change. To make the assets economically adaptable to foreseeable changes, sizeable investments in design flexibility may be required upfront. Under uncertainty about the future and tight budgets, multi-stakeholder teams must trade-off additional investments in flexibility with more affordable investments in rigid designs at risk of costly adaptation. How to help project teams bridge their divergences and coalesce their views of the world into a project strategy is the core question at the heart of this research. After reviewing the limitations of current practice and theory in the management of capital projects, this study turns to real options reasoning. By definition, investments in design flexibility can be equated with buying options: if the future resolves favourably, the options can be exercised to adapt the design economically. To advance theory and practice on capital design for evolvability, this study combines case-based with experimental work. First, an exploratory study reveals that, despite using options thinking, project teams find real options mathematical models inadequate to support mundane design decisions. A subsequent study on design practices at Network Rail shows the difficulties of designing for evolvability become amplified with multiple stakeholders. With asymmetry in capabilities, knowledge, and power to influence decisions, multi-stakeholder teams systematically resort to a combination of informal options thinking and ‘money talks’ to resolve concept design. Tensions flare up whenever stakeholders demanding investments in design flexibility cannot fund them. These findings suggest that a formal procedure to design for evolvability can offer a superior approach at front-end strategizing. To test this proposition, this research develops an original proof-of-principle of a formal design for evolvability framing that cross-fertilizes literature on project risk management and real options theory with insights from the fieldwork. It also develops a two-group experiment – grounded on fine-grained empirical data from a real-world rail station project – to compare the performance of the experimental and control groups in terms of effectiveness, efficiency, and satisfaction. The results show that a formal design for evolvability framing can improve front-end strategizing. As project teams become more efficient, they have more time to effectively resolve the design for evolvability strategy. Importantly, teams are unlikely to reject attempts to formalize the decision-making process. The study also shows that a formal design for evolvability strategy can improve the accountability of decision-makers for investments in design flexibility. Final considerations discuss the generalizability and limitations of these insights, and future directions.