Book reviews

Strategic Leaning in Action Tony Grundy London, McGraw-Hill, 1994, 218 pp. ISBN 0-07-707825-X.

The Knowledge-creating Company Ikujiro Nonaka & Hirotaka Takeuchi Oxford, Oxford University Press, 1995, 382pp, £24.95 (hbk), ISBV 0-19-509269-4.

The Challenge of the 21st Century: Managing Technology and Ourselves in a Shrinking World Harold A. Linstone with Ian I Mitroff Albay, Ny, State University of New York Press, 1994, 406 pp, $19.95 (hbk) ISBN0-7914-1949-5.

Practical Steps for Aligning Information Technology with Business Strategies: How to Achieve a Competitive Advantage Bernard H. Boar New York, John Wiley, 1995, 241 pp, ISBN 0-471-07637-6.

Strategic Innovation: An International Casebook on Strategic Management Charles Baden-Fuller & Martyn Pitt (Eds) London, Routledge, 1996, 461 pp, £16.95 (pbk), ISBN 0-451-12870-6.     

Learning rational expectations: The finite state case

This paper is devoted to the question of whether traders can learn rational expectations from repeated observations of market data in a stationary environment with finitely many exogenous states of the world. The learning problem is placed in the context of an iterative adjustment process which achieves equilibrium if traders have rational expectations. The main result is that even if traders begin with no knowledge of their environment, there exists an estimation procedure which converges to rational expectations when the environment satisfies a certain regularity condition. The regularity condition is shown to be generic.     

How to reduce your inventory: a real world case study

This case study describes the use of a performance analysis system at the Safety Products Division of Mine Safety Appliances Company, which contributed to the reduction of excess inventories by more than $8,000,000 during the first two years of implementation.     

END‐OF‐DAY PRICING IN THE U.S. TREASURY MARKET: A COMPARISON OF GovPX AND THE FEDERAL RESERVE BANK OF NEW YORK

We compare end‐of‐day indicative U.S. Treasury prices from GovPX and the Federal Reserve Bank of New York (FRBNY). We find that the two sources rarely quote identical prices, and differences are not simply due to noise or rounding. The average bid price differential is 2 cents for notes and bonds, but it is only ¹/₁₀ of 1 cent for bills. Bid‐ask spreads in both sources appear to be largely artificial and contain limited information. Finally, we find that the end‐of‐day indicative FRBNY bid prices are closer to true intraday GovPX market quotes than end‐of‐day indicative quotes provided by GovPX itself.     

A layered United States Universal Service Fund for an everything-over-IP world

Support through the United States Federal Universal Service Fund for high-cost areas has been principally defined in terms of telephone service. Fund growth due to increases in wireless lines and implicit support for broadband infrastructure has created an untenable situation, and fundamental reform is expected. The cause underlying this growth is convergence between the telephone network, wireless networks, the Internet, and cable networks. This convergence will pose additional serious long-term challenges to the fund. This paper proposes a restructuring of the high-cost funds based on a layered model. Both contributions and distributions are focused on network infrastructure, without distinction between voice and broadband. The proposal uses a new definition of communication services to guarantee technology neutrality, and includes service area reform and cost efficiency measures. This layered approach repositions the fund for future converged networks.     

A Cross-Validity Comparison of Conjoint Analysis and Choice Models at Different Levels of Aggregation

Several (ratings-based) conjoint analysis and experimental choice (choice-based conjoint) models are compared on their ability to predict both aggregate choice shares among the sample and individual choices in an availability validation task. While there was a weak relationship between validations at the individual and aggregate levels, several models stand out. In general, models capturing individual differences validated well at both the individual and aggregate level. The hierarchical Bayes choice and conjoint models validated particularly well.Among choice models, the hierarchical Bayes choice model had the highest aggregate and individual level-validations. It was followed by the hybrid and seven segment latent segment choice models. Overall, the highest validating ratings-based conjoint model was the hierarchical Bayes model. However, the seven segment latent segment conjoint model produced better aggregate choice share validations than any other conjoint model. These results indicate that validations can be improved either by using benefit segment models and/or merging different types of data to estimate more individualized models.In most cases, rescaling improved the ratings-based, but not the choice-based choice share validations. This suggests that one might adjust for differences between ratings and choice tasks before making choice share predictions.     

Attribute Range Effects in Binary Response Tasks

This paper investigates attribute range effects in binary response conjoint analysis tasks. We investigate a long-standing conjecture that the regression estimates of attributes in choice tasks are influenced by a researcher's selected range of attribute levels across choice sets. Specifically, we examine the effect(s) of varying attribute ranges systematically over two ranges of levels (1=wide range, 2=levels in the middle of the wide range) in a public bus choice context. A master 2³ design is used to vary the range (i.e., wide, middle) of three numerical attributes (fare, service and time). In each of the eight master range conditions a 2³ factorial creates bus profiles, and a ninth condition is added to test for response non-linearity. Our results suggest that attribute range impacts attribute main effects to a small degree, yet exhibit substantial and systematic effects on attribute interactions and model goodness-of-fit. Implications of these results for practical design of academic and commercial choice-based conjoint analysis tasks are discussed.