Adjusting Choice Models to Better Predict Market Behavior

The emergence of Bayesian methodology has facilitated respondent-level conjoint models, and deriving utilities from choice experiments has become very popular among those modeling product line decisions or new product introductions. This review begins with a paradox of why experimental choices should mirror market behavior despite clear differences in content, structure and motivation. It then addresses ways to design the choice tasks so that they are more likely to reflect market choices. Finally, it examines ways to model the results of the choice experiments to better mirror both underlying decision processes and potential market choices. Co-chairs. Author order is alphabetical.     

The impact of M&A and joint ventures on the value of IT and non-IT firms

This paper aims to study and provide empirical evidence on the impact of mergers and acquisitions (M&A) and joint ventures on the value of IT and non-IT firms. Using the event study methodology, we investigate the effect of such strategic alliance announcements on firm value in a sample of 170 firms. The results show that such strategic alliance announcements create significant gains in firm value. When the sample is divided into IT and non-IT firms, we find stronger support for positive impact on gains in firm value among non-IT firms than among IT firms. We also find that the smaller strategic alliance partners perform better than their larger partners. However, we fail to find any significant difference in impact on firm value between merger/acquisition and joint venture announcements. This work was supported by the research fund of Hanyang University (HY-2004). JEL Classification L1 · G14 · G34     

Net Asset Value Discounts for Asian-Pacific Real Estate Companies: Long-Run Relationships and Short-Term Dynamics

This study investigates the time series behavior of real estate company net asset value discount/premium (NAVDISC) in eight Asian-Pacific securitized real estate markets from 1995 to 2003. We postulate that if there is a stable NAVDISC for real estate companies in the long-run, then there should be a long-run cointegrating relation between their stock prices (Ps) and net asset values (NAVs). Employing panel data cointegration econometrics that comprises three approaches; panel unit root test, heterogeneous panel cointegration test and dynamic panel error-correction modeling (ECM), we find that long run NAVDISCs persist in individual Asian-Pacific securitized real estate markets and the regional market. All the NAVDISCs exhibit mean reversion and that the respective disequilibrium errors fluctuate around the mean values. Moreover, NAV is an important factor that statistically explains the price variations in real estate stock prices regardless of their speed of mean-reversion in the NAV discount /premium.     

Determinants of technology licensing: the case of licensors

This paper empirically analyzes the behavior of technology licensors using a large dataset of US‐traded companies. The stock of technological knowledge of the licensor, this company's prior exposure to licensing, the rate of growth of its primary sector, the strength of IPR protection, and the nature of the technology are found to be important determinants of the propensity to sell technology through nonexclusive licenses. Smaller firms in industries with ‘simpler’ technologies tend to sell technology through exclusive licenses more than others. In contrast, larger firms in industries dealing with more ‘complex’ technologies engage relatively more in cross licensing. Copyright © 2006 John Wiley & Sons, Ltd.     

Hybrid knowledge integration using the fuzzy genetic algorithm: prediction of the Korea stock price index

This paper proposes the hybrid knowledge integration mechanism using the fuzzy genetic algorithm for the optimized integration of knowledge from several sources such as machine knowledge, expert knowledge and user knowledge. This mechanism is applied to the prediction of the Korea stock price index. Machine knowledge is generated by applying neural networks to technical indicators, while expert knowledge and user knowledge are generated from the evaluations of external factors that affect the stock market. Cooperative knowledge is generated from the weighted sum of these sources using a genetic algorithm. Experimental results show that the hybrid mechanism can provide more accurate and less ambiguous results. It means that this mechanism is useful in integrating knowledge from multiple sources for an unstructured environment such as the stock market. Copyright © 2004 John Wiley & Sons, Ltd.     

Alternative transportation modes in an urban land use model: A general equilibrium approach

This paper presents and analyzes a general equilibrium transportation demand model. The model was applied to hypothetical cities with populations of 1 and 2 million. Data and coefficients for those cities were obtained from existing metropolitan areas of equivalent sizes. A subway system is found to be uneconomical in the hypothetical city with one million population and with an average population density of 4400 per square mile. However, it is found to be economical and desirable for the hypothetical city with two million population and with an average density of 6900 per square mile.     

Stochastic reserve changes and expansion of bank credit: The case of additional risks

In this paper we examine the effects of introducing additional risks to the Orr-Mellon-Cooper model on the asymptotic behavior of bank credit expansion, and derive monetary policy implications therefrom. Our model of additional risks corrects a loss of generality existing in the Orr-Mellon-Cooper model. It shows that the local solution for optimal credit expansion is the global solution, regardless of the parameters of the reserve loss functions, when the default risk is introduced. The analysis further points out necessary conditions to determine the direction of credit changes caused by a monetary injection under uncertainty.     

An alternative model for fair share allocation of lower income housing

A linear programming model was developed and presented for fair-share allocation of lower income housing as an alternative to existing heuristic models. The model is applied for the Middlesex County region in pursuit of a regional fair-share of lower income housing needs for the year 1975 for each township in the county. The results are presented and compared with those of the Court's allocation, held by the Superior Court of New Jersey in May 1976 for the Middlesex County region.