Controlling new product R&D projects

New products are critical to the success of most corporations. But managing the R&D projects that produce new products has proven to be a risky and tricky business. Theorists and practitioners claim that one of the major obstacles to higher new product output is the ‘tight’ control practices found in large corporations. The conventional wisdom argues that, to correct this, firms need to find ways ‘to loosen-up.’ But is that all there is to it? This article presents five findings for effectively controlling new product R&D projects. These findings emerged at the conclusion of an empirical research investigation into the formal and informal control practices that business unit managers use to control various new product R&D situations. The article concludes with several recommendations for those managers who want to control their new product R&D projects better.     

Spatial Models in Marketing

Marketing science models typically assume that responses of one entity (firm or consumer) are unrelated to responses of other entities. In contrast, models constructed using tools from spatial statistics allow for cross-sectional and longitudinal correlations among responses to be explicitly modeled by locating entities on some type of map. By generalizing the notion of a map to include demographic and psychometric representations, spatial models can capture a variety of effects (spatial lags, spatial autocorrelation, and spatial drift) that impact firm or consumer decision behavior. Marketing science applications of spatial models and important research opportunities are discussed. This paper is based upon the discussions of the Spatial Models in Marketing seminar at the Sixth Invitational Choice Symposium, June 2004. Eric T. Bradlow, Bart Bronnenberg and Gary J. Russell served as co-chairs of the session.     

The Popperian Legacy in Economics: Confusion and beyond

Summary The book ThePopperian Legacy in Economics (editor Neil de Marchi, Cambridge University Press, 1988) is recommended as a well-composed overview of different approaches to economic methodology, the struggle of economists with the attractions and frustrations of Popper's methodology of falsification, and attempts to strike out in new directions. The overall result is confusion, but a confusion which is worth taking note of and which offers both a challenge and some hints for a search for progress. Part two of the article attempts to take up that challenge.     

The contribution of manufacturing to shortening design cycle times

Shortening design cycle times, without increasing design costs or sacrificing quality has become an important management goal. In this paper, we will provide a short overview of the literature on shortening design cycle times. Building on this, we want to establish how manufacturing and the manufacturing/R&D interface can contribute to shorter development cycle times. The European Manufacturing Futures database will be used to test some of the literature findings on a sample of large European Manufacturers.     

How Applicable is the Dominant Firm Model of Price Leadership?

In this paper, we examine the usefulness of the dominant firm model of price leadership to serve as a benchmark for organizing behavior in laboratory markets. This well established model, whose origins can be traced back over a hundred years, has been recently applied to such landmark antitrust cases as Standard Oil and Alcoa and more recently to the analysis of deregulated markets for electric power. Our results indicate that in posted offer markets the dominant firm quite often produces more than the model's benchmark and sometimes at much greater prices. With sealed offer auction rules and a low elasticity of fringe supply, the dominant firm produces the theoretical output at a price greater than the prediction. However, with a high elasticity of fringe supply, the dominant firm produces more output over a wide range of prices that includes the predicted price.     

Generalizations of the KPSS-test for stationarity

We propose automatic generalizations of the KPSS-test for the null hypothesis of stationarity of a univariate time series. We can use these tests for the null hypotheses of trend stationarity, level stationarity and zero mean stationarity. We introduce the asymptotic null distributions and we determine consistency against relevant nonstationary alternatives. We compare the properties of the tests with those of other proposed tests for stationarity. Monte Carlo simulations support the relevance of the tests when an autoregressive process with large positive autocorrelations is likely under the null hypothesis.     

Private fiat money with many suppliers

A dynamic rational expectations model of money is used to investigate whether a Nash equilibrium of many firms, each supplying its own brand-name currency, will optimally deflate their currencies in Friedman's (1969) sense. The optimal deflation does arise under an open loop dynamic structure, but the equilibrium breaks down under a more realistic feedback control structure.