The Licensing of Market Development Rights within Technology Alliances: A Shareholder Value Perspective*

Technology alliances create market development rights that are shared between partners in an alliance relative to codeveloped product technology. Alliance partners will often manage the shared market development rights in a cooperative manner by forming an agreement in which one partner (i.e., the licensor) licenses its market development rights to the other partner in the alliance (i.e., the licensee). The real options and bargaining power literatures provide opposing recommendations regarding whether a licensor creates greater shareholder value by licensing its market development rights to the licensee on a more or less restrictive basis. Empirical analysis of technology alliance contracts reveals that the restrictiveness by which a licensor should license its market development rights to a licensee depends on the licensee's strategic marketing emphasis. Specifically, a licensee will create greater value by following a more restrictive distribution strategy when its partner's marketing strategy emphasizes value creation. Alternatively, a licensee will create greater value when its partner's marketing strategy emphasizes value appropriation by following a less restrictive distribution strategy. From a theoretical perspective, the paper's findings provide early evidence regarding the contribution of marketing strategy toward value creation in technology alliances and help resolve the differing expectations offered by the real options and bargaining power literatures. Managerially, the paper identifies an alliance partner's strategic marketing emphasis as a hitherto unrecognized factor determining when managers should follow a more or less restrictive distribution strategy when licensing marketing development rights within technology alliances.     

Market frictions as building blocks of an organizational economics approach to strategic management

This paper shows that market frictions are fundamental building blocks for an organizational economics approach to strategic management. Various organizational economic approaches (transaction costs, property rights, real options, and resource‐based) have distinctive focal problems and emphasize different combinations of market frictions. A wider recognition of the role of market frictions is useful for three main objectives. First, it helps identify an evolving market‐frictions paradigm in strategic management. Second, it shows how two primary questions in strategy of why firms exist and why some firms outperform others and the three primary strategic goals of cost minimization, value creation, and value capture can be better joined and evaluated. Third, different combinations of market frictions can generate new research questions and advance theory development in the strategic management field. Copyright © 2013 John Wiley & Sons, Ltd.     

Flexibility planning for managing R&D projects under risk

Incorporating managerial flexibility in an innovative R&D project is important, because managers face greater uncertainty in today's competitive and dynamic changing environment. It is essential to bring managerial flexibility into R&D project planning to decrease technical and market risks, while increasing potential market value. The objective of this paper is to develop a flexibility planning methodology based on real option analysis to improve managerial flexibility for R&D projects. The proposed methodology identifies potential risks that may occur during every R&D stage. It also recognizes a cascading option structure to resolve the identified risks, and evaluates and selects adequate options that maximize the potential value of the project. Instead of using a traditional option pricing method, a dynamic programming model that considers multidimensional product performance and market payoff is used to evaluate the R&D project value. Using the proposed methodology, managers can identify future scenarios as a function of their management actions. The proposed flexibility planning methodology can help managers improve managerial flexibility of R&D project and increase the success rate of product launch. A drug development project is used to illustrate the proposed methodology.     

A REAL OPTIONS DESIGN FOR PRODUCT OUTSOURCING

Product outsourcing is recognized as a way to gain flexibility for competitive advantage. We formulate the outsourcing problem using real options. We develop a financial model to assess the option value of product outsourcing. Specifically, we consider a three state-variable problem and use Monte Carlo simulation to estimate the value of the option. This valuation gives decision makers a way to choose the appropriate outsourcing strategy based on an integrated view of the market dynamics. A case example from the apparel manufacturing industry is used to demonstrate the application of real options to value outsourcing flexibility. We show that the inability of classical net present value methods to address dynamics in the market condition leads to an undervaluing of the outsourcing strategy. Numerical results and sensitivity analysis show how the real options approach can be used to give a better view of the long-term value of outsourcing.     

Investment decisions in the wireless industry applying real options

The wireless industry is one of the most capital intensive high-technology industries. This paper applies real options techniques to estimate investments under uncertainty in two new ventures: (a) deferral of the expansion from 2.5G to 3G networks; and (b) expansion of a 2.5G network using Wi-Fi as an alternative technology. The cases are examined and analyzed both qualitatively and quantitatively, using realistic assumptions and parameters. Investment cost, number of subscribers, pricing of services, and risk are at the core of investment decision processing. In both cases, sensitivity analysis of the value of the (real) option considering the above key parameters was conducted, to extrapolate useful findings that should be taken into consideration by the decision makers in wireless companies.     

Integrating Real Options with Managerial Cash Flow Estimates

This article presents a real options model that fits managerial cash flow estimates (optimistic, likely, and pessimistic projections) to a continuous geometric Brownian motion (GBM) cash flow process with changing growth and volatility parameters. The cash flows and the value of a project are correlated to a traded asset, so the real option is priced under the risk-neutral measure with a closed-form solution. The analysis is extended to a sequential compound call option for investments over multiple periods. If the project is correlated to the market, then some of the risk may be mitigated by a delta-hedging strategy. A numerical example shows that the effect of the correlated asset on the real option value is significant, and the relationship between the volatility of the project and the real option value is not analogous to the typical relationship found in financial option pricing. Integrating the expertise and industry knowledge of management, this approach makes possible a more rigorous estimation of model inputs for real option pricing.     

The Impact of Volatility on Firms Holding Growth Options

“Abuses of real option valuation were partly behind the ramping and subsequent deramping of the 2000 internet techno bubble. No one ever got to eat the free lunch these real option 'theorists' promised. No one ever will; no one ever could.” (Mayor 2001, 53) Growth options contribute to over 95% of the market value of Internet stocks such as Amazon.com, America Online, and eBay. Finance theory often promotes market volatility as being desirable for investors holding financial options. Is volatility also desirable for firms holding growth options? While many argue that it is, this paper presents a simple example illustrating that increasing volatility can destroy growth option value, especially for firms holding “quality” growth options.     

Timing the Start of Material Substitution Projects: Creating Switching Options under Volatile Material Prices

Firms developing new products often face the challenge of making investment decisions under uncertain input–cost conditions due to the price volatilities of the materials they use. These decisions need to be made long before the final products are launched on the market. Therefore, firms that invest in the opportunity to switch materials in a timely manner will have the flexibility to react to material price changes and realize competitive advantages. However, volatile material prices may also cause a firm to delay investment. Using real‐options reasoning, this paper studies the influence of input‐cost fluctuations on the timing decision to start new product development (NPD) and thus create the follow‐on opportunity to later replace an existing product. A model that combines waiting and switching options to derive influencing factors of the flexibility value that triggers the investment is developed and tested on a sample of material substitution projects from manufacturing firms. The results show how price uncertainty of the new and the old material, their joint price development, the expected project duration, and competitive preemption are related to the propensity to delay the start of NPD. The findings provide new insights on how timing in adopting materials can be used to hedge exposure to volatile material prices. The insights are relevant for adopters and producers of new materials, as well as for policy makers who strive for supporting the diffusion of new materials.     

Paying attention to real options

The strategy literature is increasingly focused on the need to create dynamic capabilities to respond with innovative product offerings in 'hypercompetitive' environments. The real options approach offers hope for managers facing such threatening environments by highlighting methods to hold options on a variety of possible future states, thereby reducing risk without bearing all the costs. However, extant real options literature, stemming from rational-based financial assumptions, does not consider attention as a limited resource. Real options are valued on the assumption that management can exploit the flexibility inherent in projects, and so require management attention to obtain their full theoretical value. This paper brings attentional constraints to bear on the real options framework and describes a conceptual framework that illustrates the real option value realization process.     

Dark Fiber Valuation

Valuation of dark fiber has recently generated controversy, sparked particularly by the large sums booked for swaps of dark fiber between companies. One of the issues raised is valuation: i.e., what is the value of an asset that generates no revenue now and may do so at some unknown point in the future but only after investment, in an uncertain business climate, and where prices are dropping? The picture is further complicated because the result of investing to bring the asset to market (i.e. lighting the fiber) changes the supply and demand conditions of the market itself and hence invalidates price predictions. A realistic and consistent valuation methodology is necessary for increasingly cautious companies, auditors, and investors. In this paper we describe such a valuation methodology for dark fibre based on real options. Publicly available bandwidth price services start to make this practical by providing market price information. For dark fibre valuation the real option to be valued are the lighting decisions. We specifically include the effect on the market of adding new capacity by using the price-elasticity of demand within the stochastic price process itself, conditional on lighting decisions. Prices are generally volatile and decreasing with time. The evolution of lighting costs and maintenance are included in the valuation. The real options technique used here is novel in that it combines economic and market factors explicitly with mathematical finance to arrive at a valuation and optimal decisions. We found that the optimal lighting riming and capacity decisions to depend on many of the factors included in the analysis with no simple triggers: the details really matter.     

Project valuation in the pharmaceutical industry: a comparison of least‐squares Monte Carlo real option valuation and conventional approaches

Least‐squares Monte Carlo simulation (LSM) is a promising new technique for valuing real options that has received little or no attention in the pharmaceutical industry. This study demonstrates that LSM can handle complex valuation situations with multiple uncertainties and compounded American‐type options. The limited application of real option valuation (ROV) in the pharmaceutical industry is remarkable, given the importance of accurate project valuation in an industry that requires large investments in high‐risk projects with long pay‐back periods, which is furthermore suffering from ever‐increasing development costs and shrinking profit margins. The LSM model developed in this study is constructed as an extension of a discounted cash flow model that should be familiar to economists active in the pharmaceutical industry. A number of pharmaceutical projects have been evaluated using LSM ROV, binominal real option valuation and expected net present value techniques. The different results yielded by these methods are explained in terms of differences in risking assumptions and ability to capture the value of flexibility. The analysis provides a framework to introduce the basic concepts of real option pricing to a non‐specialist audience. The LSM model illustrates the potential for real‐life commercial assessment as the versatility of the technique allows for an easy customisation to specific business problems.     

A BETTER UNDERSTANDING OF WHY NPV UNDERVALUES MANAGERIAL FLEXIBILITY

The Real Options paradigm addresses the valuation of managerial flexibility in capital budgeting. Despite the great strides achieved by researchers in this field, many financial analysts have chosen not to adopt this new paradigm due to a lack of comfort with the approach and the mathematical complexity of the valuation models. This article shows how some projects with real options can be valued using simple and familiar tools-discounting expected cash flows after adjusting the discount rate. Unless the discount rate is adjusted to account for the impact of real options on risk, a traditional net present value (NPV) analysis misses the value of flexibility. By narrowing the gulf between Real Options analysis and more familiar tools, the weighted average discount rate (WADR) approach introduced in this paper may help novices better understand die Real Options paradigm, which subsequently may gain the wider acceptance it deserves. Though the WADR approach is practical only for simple real options, comfort with the approach may encourage analysts to pursue more advanced and robust real option valuation techniques for more complex applications.     

Pricing real growth options when the underlying assets have jump diffusion processes: the case of R&D investments

Numerous previous studies have demonstrated that research and development (R&D) investments can be evaluated by a real growth options approach. However, few studies have constructed evaluating models which consider the important R&D characteristics, including uncertainty regarding the project value, investment cost, and jump diffusion processes. The contribution of this study is not only to derive a model for evaluating R&D investments to conform to these key characteristics of R&D activities but also to build a real option pricing method that is more general than comparative important models, such as the theoretical papers of Black and Scholes (1973), Merton (1976), and Fischer (1978), and the application paper of Brach and Paxson (2001). This study also presents sensitivity analyses which illustrate the dynamic relationship between the real growth option value and the project value, investment cost, and main jump parameters. Hopefully, the results of this study can provide a useful reference for managers, and help them make better evaluations of R&D investments.     

Optimal exploration investments under price and geological‐technical uncertainty: a real options model

This article develops a real options model for valuing natural resource exploration investments (e.g. oil or copper) when there is joint price and geological‐technical uncertainty. After a successful several‐stage exploration phase, there is a development investment and an extraction phase. All phases are optimized contingent on price and geological‐technical uncertainty.
Several real options are considered. There are flexible investment schedules for all exploration stages and a timing option for the development investment. Once the mine is developed, there are closure, opening and abandonment options for the extraction phase. Our model maintains a relatively simple valuation structure by collapsing price and geological‐technical uncertainty into a one‐factor model.
We apply the model to a copper exploration prospect and find that a significant fraction of total project value is due to the operational, development and exploration options available to project managers.     

DIY:企业组织分析的另一个视角

本文从用户DIY的角度出发 ,认为产品的模块性是这个消费模式得以实现的条件 ;产品模块性促成了企业组织的模块性。企业组织的模块性能够很好地适应用户的DIY需求 ,因而能够很好地解决市场的不确定性问题。企业组织模块性对于不确定性的作用可以刻画为一种实期权 ,因而组织模块化将产生期权价值     

Modeling the Korean Chonsei Lease Contract

Chonsei is a unique Korean lease contract in which the tenant pays an up–front deposit, typically about 40 to 80% of the value of the property, with no requirement for periodic rent payments. At the contract maturation, the landlord then returns the nominal value of the deposit. Since there is no legal obligation on the part of the landlord to deposit the money in an escrow account, the principal default risk associated with the chonsei contract falls on the tenant. We discuss the development and popularity of this contractual agreement in the context of the public policy initiatives, historical and institutional settings surrounding the Korean housing and housing finance market. We develop a contingent–claims model that recognizes the compound options embedded in the chonsei contract. Theoretical predictions are confirmed by an empirical analysis using monthly data from 1986 to 2000. Our analysis shows that the chonsei contract is an indigenous market response to economic conditions prevalent in Korea.     

A robust methodology for setting tariffs

Pricing new or existing services is a challenge in the current state of the communications industry, with new industrial structures, fast technical change and varying degrees of competition and regulation. Basically the industry is newly immature, with few good models for, and little data on, the behaviour of consumers or competitors. In this paper we describe the development of a robust methodology for the determination of prices, able to cater for some of the sources of uncertainty in the real world, such as market behaviour. By robust, we mean the ability to re-use the basic model with relatively little change if, for example, the underlying sub-model of consumer behaviour is changed from cost minimising to risk averse, or the basis of pricing is changed from value to cost.     

Making real options work for practitioners: a generic model for valuing R&D projects

We propose a generic valuation framework for the appraisal of R&D projects based on real option theory. The added value of this approach is the presentation of a model that was implemented in a manner that allows corporate decision makers to use real options in an intuitive and standardized way. The project valuation procedure is separated into three main phases: project modeling, data and input collection, and result generation and analysis. The project model represents the structure of the real world R&D project with its investments, expected results, and decisions that need to be taken conditionally on the outcomes of research activities. The project model is represented in the form of a decision tree, where different research results or taken decisions lead to new branches. In this way, every possible situation the project can pass through can be represented. Uncertainties are separated into market uncertainties (e.g., market prices) and project specific, private uncertainties (e.g. uncertainty of research results). For both uncertainties, event trees are constructed which are then combined and merged with the above mentioned decision tree in order to represent the value evolution of the R&D project under given decisions and uncertainties. For every possible state of the project the real option value is calculated. By creating multidimensional trees, a multitude of decision steps and various kinds of real options (e.g., continue, expansion, switch, abandonment) can be modeled. The calculation complexity for the decision trees is given. From the tree structure we can calculate the real option value of starting an R&D project, i.e., the value of undertaking the first investment and thus acquiring the subsequent decision opportunities given by the completion of the first research effort. Furthermore, the optimal exercise strategy is derived from the decision tree. The exercise strategy gives the manager the possibility to have an a priori overview of where an R&D project may lead to, which decisions need to be taken in which circumstances, and when the project needs to be stopped in order not to generate losses. In an in‐depth case study we use an illustrative R&D project to set up and discuss the three phases of project modeling in the real options framework: building the multidimensional decision tree, input generation, and calculation of the real option value as well as the optimal strategy for the R&D project.     

Toward a behavioral theory of real options: Noisy signals,bias, and learning

Research Summary: We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback learning theory that considers uncertain current asset values (contemporaneous uncertainty). This enables us to incorporate behavioral bias in the feedback learning process underlying the option execution/termination decision. The resulting computational model suggests that firms that inappropriately account for contemporaneous uncertainty and are subject to learning biases may experience substantial downside risk in undertaking real options. Moreover, contrary to the standard option result, greater uncertainty may decrease option value, making commitment to an investment path more effective than remaining flexible. Managerial Summary: Executives recognize the need to make uncertain investments to grow their business while mitigating downside risk. The analogy between financial options and real corporate investments provides an appealing method to consider the practical challenge of such investment decisions. Unfortunately, the “real options” analogy seems to break down in practice. We identify how a second form of uncertainty confounds real options intuition, leading managers to overestimate the value of uncertain investments. We present a behavioral real options model that accounts for both forms of uncertainty and suggest how uncertainty interacts with behavioral bias in the option execution/termination decision. Our model facilitates assessment of the conditions under which investments in uncertain opportunities are usefully considered as real options, and provides a means to evaluate their attractiveness.