Structuring innovation funnels for R&D projects under uncertainty

An innovative R&D project that creates a great business opportunity usually involves high technological and market uncertainty. It is easy to see that developing only one solution approach in the R&D project is too risky. The selectionism or the parallel development strategy can be applied to construct an innovation funnel that increases the flexibility to hedge against the uncertainty. However, little research has been devoted to selection of which alternative solution approaches should be included for the innovation funnel. This research aims to develop a simulation-based methodology that can help R&D managers evaluate and construct an innovation funnel containing promising alternative approaches for a novel R&D project to maximize project profit, while minimizing downside risk within an allowable loss. A new risk measure based on the concept of conditional value-at-risk from the finance literature is defined to evaluate the project downside risk. An example of drug development project is used to illustrate the proposed methodology. We recommend that firms should improve their capabilities on market research, concept screening, and R&D efficiency for taking full advantages of selectionism.     

The Effects of Environmental Turbulence on New Product Development Strategy Planning

Managers need guidance on how to cope with turbulent environments in order to improve corporate performance. Research on environmental turbulence has suggested that firms adopt a less centralized, more organic structure in dynamic, uncertain environments. Little work has been done specifically, however, on how environmental turbulence affects strategy planning for new product development (NPD). In this article, we specify a baseline model with firm innovativeness, market orientation and top management risk taking as antecedents to NPD speed and corporate strategic planning; these in turn are modeled as antecedents to NPD program (not project) performance. Two conceptualizations of the role of environmental turbulence are examined: (1) that market turbulence and technological turbulence are additional direct antecedents to NPD program performance; and (2) that the baseline model is moderated by turbulence (that is, that the strengths of the paths differ depending on levels of turbulence). A cross-sectional survey methodology including four diverse industries [automotive, electronics, publishing, and manufacturing/research and development (R&D) laboratories] was used to test the hypotheses. The latter conceptualization is supported. In particular, the paths from innovativeness to strategic planning and from risk taking to NPD speed are significantly greater in highly turbulent environments. A set of managerial recommendations and implications are provided. First, managers must recognize the possible improvements in new product performance by actively including NPD personnel in corporate strategic planning and also by involving corporate planners in NPD activities. Second, managers also should recognize that turbulent environments heighten the need to make risky investments, and sometimes, risky decisions; risk-taking decisions ought to be encouraged in such environments.     

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.     

Business R&;D and the Interplay of R&;D Subsidies and Product Market Uncertainty

This paper examines the effect of product market uncertainty and government research and development (R&D) subsidies on firm-level R&D investment. Using a sample of German manufacturing firms, we find that product market uncertainty reduces R&D investment and government R&D subsidies increase R&D investment. Moreover, our results indicate that R&D subsidies mitigate the effect of product market uncertainty on R&D investment. These findings suggest that public policies aimed at increasing business R&D investment can achieve this objective by reducing the degree of uncertainty in the product market.      

R&D project selection and scheduling for organizations facing product obsolescence

Research and development is very crucial in an organization that faces rapid product obsolescence. Our thesis is that R&D project scheduling and resource planning should be born out of the optimum product launch plan which, in turn, should be in adherence to the growth rate targeted by the organization. Such an approach would ensure that the R&D activities of the organization are in tune with the Organization's goals. The absence of such coordinated R&D planning would hamper the productivity and profitability of the organization. This paper attempts to develop a methodology and model that would enable the streamlining of R&D project schedule. A real life case application has also been illustrated.     

Evaluating growth options as sources of value for pharmaceutical research projects

The financial value of research projects is difficult to assess because they are highly uncertain. Often, the result is either an overly conservative approach to strategic innovation, based on net present value analyses, or an overly aggressive approach based on optimistic qualitative portfolios. R&D project evaluation requires recognizing threats as well as opportunities from uncertain events, and incorporating flexibility in managerial action in response to them. Real options pricing analysis is a widely discussed tool for evaluating such managerial flexibility. The limitation of options pricing lies in its requirement for complete financial markets, in which a replicating asset can be found that reproduces (or, at least, is correlated with) the project’s payoffs in all possible states of the world. However, the major risks of research projects are typically project specific and cannot be replicated in external markets. In this situation, a decision tree is a better tool to represent managerial options during execution of the project, and to evaluate its value. A decision tree is equivalent to options pricing for risks that can be priced in the financial markets (if trading of securities is explicitly included), and moreover, it can incorporate risks and flexibility that are not traded in financial markets. Using decision trees, we demonstrate a quantitative evaluation of compound growth options from research at BestPharma, a large international pharmaceutical company. A growth option is a future opportunity that may arise from a current R&D investment. The growth option may not be related to the primary purpose of the R&D project, or not even be directly foreseeable. Kester (1984) has argued that growth options may account for a large part of project value. BestPharma faced the problem of choosing among several strategic research initiatives. They developed a decision tree representation of the projects, which helped to provide transparency about project value and strategic options. Most importantly, carefully thinking through the tree helped to identify growth options, represented by additional branches in the tree, and to quantify that they represented major sources of value.     

Assessing R&D quality in rehabilitation technology development. The case of Roessingh Research and Development

This paper presents a framework for describing and evaluating the links between the design of the R&D function, its context and its performance. As a first step towards the development of a quality assurance system, this framework was used to assess R&D quality performance at a privatized R&D unit connected to a rehabilitation centre (Roessingh Research and Development). The results suggest that the framework is a useful instrument for managers to identify and understand the strengths and weaknesses of the R&D function, both with respect to its present, operational (quality) performance as well as its strategic flexibility, i.e. its readiness to adapt to, anticipate, or even create future (quality) performance requirements. The paper concludes with managerial implications with regard to the choice of an appropriate quality assurance system for Roessingh R&D, thus illustrating briefly how the framework can be used to apply ISO/BS quality standards (which are aimed at product development) in more fundamental R&D.     

The influence of voluntarily disclosed qualitative information

We examine the voluntary disclosure of qualitative information about actions involving governmental agencies and managerial intentions or beliefs in R&D project announcements in The Wall Street Journal. Our analysis indicates that information regarding government approval and managerial intentions/beliefs voluntarily disclosed in R&D project announcements interacts with industry/firm variables to provide significant incremental explanatory power in both the innovation and commercialization stages of R&D projects. Our data also indicate that the biggest impact is from managerial intentions, especially an intent to increase market share when coupled with being a larger firm. Copyright © 2000 John Wiley & Sons, Ltd.     

R&D in markets with network externalities

This paper studies the consequences of network externalities on R&D rivalry between an incumbent firm and a potential entrant. In the model, all differences between the R&D projects chosen in market equilibrium and the socially best projects are solely due to network externalities. From a welfare perspective, the incumbent chooses a too risky and the entrant a too certain R&D project. Rothschild and Stiglitz's mean preserving spread criterion is used as a measure of risk. Adoption of a new standard is more likely in equilibrium than in the social optimum.     

REAL OPTION MODELS FOR MANAGING MANUFACTURING SYSTEM CHANGES IN THE NEW ECONOMY

The manufacturing environment is becoming increasingly dynamic with upsurges in electronic-commerce, supply chain management, forecasting, and procurement and resource planning. It also includes trends toward more process data acquisition and analysis, shorter production runs, and more stringent quality requirements. These drivers lead to an opportunity for companies to collect and use information to identify changes that will affect their manufacturing systems. In conjunction with an industry partner who produces home fashion products, we developed a case-study that highlights four major manufacturing transitions: new product introduction; moving a product from research and development (R&D) to commercialization: new plant location; and starting or restarting production of existing products. These types of changes cross many levels of the operation - including the product level, plant level, and organizational level - and typically present significant operational challenges. We use this case-study to motivate the theoretical and applied research needed to support a real option framework for system changes in manufacturing. The key elements of our framework are to quantify manufacturing changes, develop a real option model for these activities, value the options to identify the best scenarios, and integrate these elements so that we can monitor and manage the overall process. The advantage of this approach is that it allows us to directly incorporate a market driven perspective, tying the manufacturing operations with the organizational economic goals.     

International R&D project evaluation by multinational corporations in the electronics and IT industry of Singapore

This paper explores a number of variables associated with the evaluation of international R&D projects by multinational corporations (MNCs) in the electronics and IT industry of Singapore. Empirical analysis of the data collected from R&D managerial executives suggests a series of considerations in relation to their R&D investments. It is desirable if R&D can create a potential impact on the growth of their regional and international businesses. In considering the risks associated with an R&D project, a balance approach would be appropriate when demanding a return on investment. In particular, the consistence with customer demands, the achievement of time‐based competitiveness, the training of R&D manpower and the development of conducive innovation environments are fundamental to the success of international R&D projects.     

System modeling of the R&D domain through the object–process methodology: a practical tool to help R&D satisfy its customers' needs

Research and Development is an intricate process involving a host of challenging technological frontiers. This paper presents a practical tool to help R&D personnel satisfy the needs of customers by a systematic evaluation of R&D performance. To establish a sound methodology for R&D performance evaluation, we employ the object-process analysis (OPA) part of the object–process methodology. Using OPA, we gradually expose the constituents of the R&D system, its environment and the interaction between them. Through this systematic top-down refinement, we provide a comprehensive generic view of the R&D domain. The framework presented in the paper allows the user to describe, order, and inter-relate the issues that R&D managers should consider when managing, evaluating and planning R&D. As the approach addresses structure and behaviour in a unified, integrated manner, the analysis provides insights into both the static and dynamic aspects of the R&D domain and establishes a solid basis for its enterprise modeling.     

Problems faced by R&D managers in Canadian federal government laboratories

The paper conducts a critical review of the problems faced by middle to first-line managers in managing R&D in Canadian government laboratories. The data come from the published literature, interviews with R&D managers, and information obtained from government employees undergoing training as R&D managers.
The problems are numerous and serious. They arise from a multiplicity of causes related to underfunding and bureaucratic management practices that do not allow for the special nature of R&D. Hiring freezes, staff reductions, travel restrictions and reductions in training budgets are all consequences of underfunding, resulting in an aging workforce and technological obsolescence. Bureaucratic administration rules set by central agencies constrain the freedom of R&D managers to manage effectively, and limit low-level participation in policy-making and planning. The result is that too many management posts are filled by under-achieving scientists and engineers, with resultant consequences for originality and efficiency.
The authors believe that the only cure is to undertake proper funding, recognise the special operational needs of R&D management, and select managers for managerial ability in addition to technical competence.     

R&D as an option on market introduction

Discounted cash flow methods for making R&D investment decisions cannot properly capture the option value in R&D. Since market and technology uncertainties change expectations about the viability of many new products, the value of projects is frequently adjusted during the R&D stages. Capturing the adjustment in expectations has an option value that may significantly differ from the Net Present Value of R&D projects. However, there are no historic time series for estimating the uncertainty of the value of R&D projects. As a result, the standard Black and Scholes model for financial option valuation needs to be adjusted. The aim of this paper is to report the application of a particular option pricing model for setting the budget of R&D projects. The option value of the model captures jumps or business shifts in market or technology conditions. The approach originates from applying current insight into the valuation of R&D projects to the field of multimedia research at Philips Corporate Research. This way, the gap between real option theory and R&D practice is further diminished.     

The case for a real options approach to ex-ante cost-benefit analyses of agricultural research projects

The United States Agency for International Development (USAID), like many other development agencies and donors, increasingly emphasizes evidence-based programming. This requires assessments of project performance at all stages of implementation, comprising ex-ante impact assessment, monitoring and evaluation, and ex-post attribution of outcomes. Ex-ante impact assessment, in particular, involves performing Cost-Benefit Analysis (CBA) to determine the Expected Net Present Value (ENPV) of the project in question. Unfortunately, the traditional ENPV approach has proven inadequate for dealing with uncertainty in the timing of investments and flexibility in future decision making. This is especially relevant for Research and Development (R&D) projects which require several stages of product development and multiple rounds of testing prior to releasing final products. As a consequence, the real-options approach to CBA has increasingly been used to evaluate private sector R&D projects. This paper advocates for the adoption of the real options approach in the evaluation of public investments in agricultural research, and illustrates its practical utility with an assessment conducted by USAID to determine the economic viability of a proposed project to develop improved varieties of critical food security crops in Uganda.     

Valuation of R&D real American sequential exchange options

Valuation of R&D real American sequential exchange options requires specifying the pattern of R&D expenditures and the stochastic process of the eventual R&D project. We model the stages of R&D expense and then the ultimate discovery (and the development cost for the discovery) using real sequential (compound) exchange option models. We study E_Commerce R&D, so the timing is relatively short‐term, with initial R&D, a second phase of R&D, and a final development phase, when the project values are realized. We use proxies from the financial markets for expected project value and cost volatilities (and correlation). Then the real option valuation is based on an approximate American sequential exchange option.     

The nature of NPD and role flexibility of R&D/marketing in a fast growing high‐tech setting

This study investigated the mutual learning process between marketing and R&D in the context of the information and communications technology industry. The relationship between product newness and role flexibility of R&D/marketing was examined via correlation analysis and multiple regression against a stratified sample of 171 new products. The results showed that different aspects of product newness are associated in a different way to role flexibility of R&D/marketing. Management should therefore be aware of such differences when planning their product development portfolio so that effective integration between R&D and marketing can be achieved.     

Networks and the Decision to Persist with Underperforming R&D Projects

Drawing on aspiration level theory and the networks literature, this paper develops a model toward decision makers' persistence with underperforming R&D projects based on the perceived properties of their personal network. The assumption is that positive feedback from network partners motivates persistence, and that this effect is multiplied when the decision makers' network is larger and denser, when network ties are predominantly strong, and when communication frequency within the network is high. The model is tested by a field experiment and conjoint methodology. Analysis of 1632 persistence decisions nested within 51 scientists responsible for R&D projects reveals that more positive feedback enhances persistence of underperforming R&D projects, and that this effect becomes stronger with increasing network size, network density, and communication frequency. These findings extend the project management literature by focusing on the social environment of the decision maker as one so far neglected factor in empirical studies on persistence decisions. Moreover, this study is among the first to investigate contingency relationships between feedback received from network partners and network structure. Finally, while most studies have emphasized that individuals and organizations can profit from their engagements in social networks, this paper suggests a potential dark side of networks by showing that networks can encourage decision makers to persist with their investment in an underperforming—and potentially failing—project. These results can help project managers involved in networking activities to better understand the effects of these activities on their decision policies, and thus draw better and more accurate decisions. Second, this study provides insights into how organizational strategy with respect to dissemination of R&D results and involvement of the organization's R&D managers in the scientific community influences the persistence of underperforming R&D projects, and thereby the organization's R&D expenditures. This can assist top managers to design financial controls and allocate financial resources to managers of underperforming R&D projects in line with the organization's networking strategy.     

Cost Reduction,Competitive Pressure and Firms' Optimal R&D Strategies in a Duopolistic Industry

This paper deals with a duopolistic industry where firms are engaged in cost-reducing R&D activity in order to maximize their market shares. Firms' R&D competition is characterized as a dynamic noncooperative feedback game where the optimal strategies are affected by the extra-industry R&D activity and the degree of intra-industry spillovers. Numerical simulations highlight the importance of the assumptions on the firms' absorptive capacity (to exploit external knowledge) in determining the optimal levels of firms R&D investrnents.     

The path of R&D efficiency over time

In this paper we investigate the pattern of R&D efficiency in terms of the number of product innovations achieved by firms over time. Using a panel dataset of Spanish manufacturing firms for the period 1990–2006, we follow the innovative performance of R&D active firms and observe that innovation rates change over firms' R&D histories. To explain these facts we propose a model that explicitly acknowledges the twofold composition of firms' R&D expenditures, comprising spending on both physical capital for R&D projects and payments to researchers. We regard this latter component of R&D as a source for dynamic returns to firms' R&D investments. Consequently firms' innovation outcomes clearly depend on how long they have been investing in R&D and also on whether there have been any interruptions in the temporal sequence of R&D activities. Our results suggest that R&D activities exhibit dynamic returns that are positive but at a decreasing rate, and that interruptions in R&D engagement reduce R&D efficiency.