Multimarket competition and business strategy

Multimarket competition abounds in the real world. Globalization of competition (triad rivalry) and economic integration of communities (European integration) contribute to the intensification of multimarket competition. The fact that firms meet in many markets has implications for rivalry. This paper introduces five key elements of multimarket competition and illustrates their working and influence by applying game-theoretic reasoning. By way of illustration the case of the artificial sweetening industry is discussed.Professor H.W. de Jong and M. van Wegberg are gratefully acknowledged for their valuable comments. Of course, the usual disclaimer applies.     

Financial Constraints and Other Obstacles: are they a Threat to Innovation Activity?

Summary  In this paper we examine the importance of financial and other obstacles to innovation in the Netherlands using statistical information from the CIS 3.5 innovation survey. We report results on the effect of these obstacles on the firms’ decision to abandon, prematurely stop, seriously slow down, or not to start an innovative project. These results are compared with those from other studies in the Netherlands and other countries. We end with a discussion of policy measures that have been taken to overcome, or at least attenuate these obstacles, such as R&D tax incentives, venture capital financing and policy mix packages.      

Het wetsvoorstel tot afschaffing der Jachtwet

Sneek, December 1873     

Introducing errors in progress ratios determined from experience curves

Progress ratios (PRs) derived from historical data in experience curves are used for forecasting development of many technologies as a means to model endogenous technical change in for instance climate–economy models. These forecasts are highly sensitive to uncertainties in the progress ratio. As a progress ratio is determined from fitting data, a coefficient of determination R² is frequently used to show the quality of the fit and accuracy of PR. Although this is instructive, we recommend using the error σ_PR in PR, which can be directly determined from fitting the data. In this paper we illustrate this approach for three renewable energy technologies, i.e., wind energy, bio-ethanol, and photovoltaics.