Optimal modularity: a demonstration of the evolutionary advantage of modular architectures

Modularity is an important concept in evolutionary theorizing but lack of a consistent definition renders study difficult. Using the generalized NK-model of fitness landscapes, we differentiate modularity from decomposability. Modular and decomposable systems are both composed of subsystems, but in the former, these subsystems are connected via interface standards, while in the latter, subsystems are completely isolated. We derive the optimal level of modularity, which minimizes the time required to globally optimize a system, both for the case of two-layered systems and for the general case of multi-layered hierarchical systems containing modules within modules. This derivation supports the hypothesis of modularity as a mechanism to increase the speed of evolution. Our formal definition clarifies the concept of modularity and provides a framework and an analytical baseline for further research.     

A complex systems methodology to transition management

There is a general sense of urgency that major technological transitions are required for sustainable development. Such transitions are best perceived as involving multiple transition steps along a transition path. Due to the path dependent and irreversible nature of innovation in complex technologies, an initial transition step along some preferred path may cut off paths that later may turn out to be more desirable. For these reasons, initial transition steps should allow for future flexibility, where we define flexibility as robustness regarding changing evidence and changing preferences. We propose a technology assessment methodology based on rugged fitness landscapes, which identifies the flexibility of initial transition steps in complex technologies. We illustrate our methodology by an empirical application to 2,646 possible future car systems.

Modeling Marketing Dynamics by Time Series Econometrics

This paper argues that time-series econometrics provides valuable tools and opens exciting research opportunities to marketing researchers. It allows marketing researchers to advance traditional modeling and estimation approaches by incorporating dynamic processes to answer new important research questions. The authors discuss the challenges facing time-series modelers in marketing, provide an overview of recent methodological developments and several applications, and highlight fruitful areas for future research. This discussion is based on the First Annual Conference on Modeling Marketing Dynamics by Time Series Econometrics at the Tuck School of Business at Dartmouth, Hanover, New Hampshire, USA on September 16–17, 2004.Insights from the First Annual Conference, Tuck School of Business at DartmouthThis revised version was published online in May 2005 with a corrected cover date.     

Same place,same knowledge – same people? The geography of non-patent citations in Dutch polymer patents

It has long been argued that geographic co-location supports knowledge spillovers. More recently, this argument has been challenged by showing that knowledge spillovers mainly flow through social networks, which may or may not be localized at various geographic scales. We further scrutinize the conjecture of geographically bounded knowledge spillovers by focusing on knowledge flows between academia and industry. Looking into citations to non-patent literature (NPL) in 2385 Dutch polymer patents, we find that citation lags are shorter on average if Dutch rather than foreign NPLs are cited. However, when excluding individual and organizational self-citations, geographically proximate NPLs no longer diffuse faster than foreign NPLs. This suggests that knowledge is not ‘in the air’ but transferred by mobile individuals and/or direct university–industry collaboration. Our findings moreover suggest an important role of international conferences in the diffusion of recent scientific knowledge.     

Models in evolutionary economics and environmental policy: Towards an evolutionary environmental economics

In this paper we review evolutionary economic modelling in relation to environmental policy. We discuss three areas in which evolutionary economic models have a particularly high added value for environmental policy-making: the double externality problem, technological transitions and consumer demand. We explore the possibilities to apply evolutionary economic models in environmental policy assessment, including the opportunities for making policy-making endogenous to environmental innovation. We end with a critical discussion of the challenges that remain.     

Are private banks more efficient than public banks?

We study whether bank efficiency is related to bank ownership in Russia. We find that foreign banks are more efficient than domestic private banks and, surprisingly, that domestic private banks are not more efficient than domestic public banks. These results are not driven by the choice of production process, the bank's environment, management's risk preferences, the bank's activity mix or size, the econometric approach, or the introduction of deposit insurance. The policy conclusion is that the efficiency of the Russian banking system may benefit more from increased levels of competition and greater access of foreign banks than from bank privatization.