Industry Shock Expectations,Interindustry Linkages,and Merger Waves: Evidence from the Hospital Industry

It is well known that mergers often occur in waves, and this paper develops a new mechanism for merger waves: expectations over industry shocks. We develop a simple test of this explanation and use it to explore the role of expectations in the context of the 1990s hospital merger wave. Managed care such as Health Maintenance Organizations (HMOs) started to become popular in the late 1980s and ultimately became an important player in the health insurance market. Our empirical analysis shows that the expected increase in the popularity of HMOs was partly responsible for the hospital merger wave of the 1990s: hospitals feared that the “innovation” of managed care in the downstream insurance market would penetrate the upstream hospital market and responded to this belief by merging. Our results show the importance of incorporating expectations and interindustry linkages into the understanding of merger waves.     

Consumer rationality and credit card pricing: An explanation based on the option value of credit lines

An option is embedded in credit cards. Since credit cards offer open credit lines, cardholders can borrow at the same terms when they become riskier. This option value raises the zero‐profit card rate. Furthermore, adverse selection occurs if cardholders are better informed about the probability of becoming riskier in the future and borrow more when they become riskier. The adverse selection can limit rate competition and keep the card rate above the zero‐profit card rate. An up‐front fee is not a good alternative because it is also vulnerable to adverse selection. A low introductory card rate is an effective way to avoid the adverse selection problem when asymmetric information is mainly about the change in the borrower's risk profile in the future, as opposed to the riskiness in the present period. Copyright © 2004 John Wiley & Sons, Ltd.     

Functional-coefficient models for nonstationary time series data

This paper studies functional coefficient regression models with nonstationary time series data, allowing also for stationary covariates. A local linear fitting scheme is developed to estimate the coefficient functions. The asymptotic distributions of the estimators are obtained, showing different convergence rates for the stationary and nonstationary covariates. A two-stage approach is proposed to achieve estimation optimality in the sense of minimizing the asymptotic mean squared error. When the coefficient function is a function of a nonstationary variable, the new findings are that the asymptotic bias of its nonparametric estimator is the same as the stationary covariate case but convergence rate differs, and further, the asymptotic distribution is a mixed normal, associated with the local time of a standard Brownian motion. The asymptotic behavior at boundaries is also investigated.     

A multiple group analysis of the training transfer model: exploring the differences between high and low performers in a Korean insurance company

This study suggests an integrative transfer of training model and examines the influence of pre-training performance on the relationship between work environment variables and transfer-related variables. Structural equation modeling was conducted with data collected from 365 Korean employees of a large general insurance firm. They were all participants in a leadership development program. The results of multi-group analyses revealed that the influence of work environment variables on transfer-related variables was moderated by employees' pre-training performance. The findings of the study imply that a more elaborate training transfer model that considers performance not just as an outcome variable, but also as an antecedent variable is required. Also, it is proposed that different strategies should be applied to promote transfer of training based on the employee's level of pre-training performance.     

Value at risk forecasting for volatility index

Forecasts of values at risk (VaRs) are made for volatility indices such as the VIX for the US S&P 500 index, the VKOSPI for the KOSPI (Korea Stock Price Index) and the OVX (oil volatility index) for crude oil funds, which is the first in the literature. In the forecasts, dominant features of the volatility indices are addressed: long memory, conditional heteroscedasticity, asymmetry and fat-tails. An out-of-sample comparison of the VaR forecasts is made in terms of violation probabilities, showing better performance of the proposed method than several competing methods which consider the features differently from ours. The proposed method is composed of heterogeneous autoregressive model for the mean, GARCH model for the volatility and skew-t distribution for the error.     

Corporate governance structure and product market competition

This article assesses the effects of the competitive structure of a product market on a firm’s corporate governance structure. Our model demonstrates that shareholders strategically determine the corporate governance structure, including the manager’s stock ownership and his controlling power over the firm, in order to maximize their utility in the product market competition. We find that the manager’s stock ownership is lower and his controlling power over the firm is higher when the firm’s product is more profitable or when competition within the product market is more severe. The inefficiency of the wealth transfer from shareholders to the manager also affects the corporate governance structure.     

3D simulation technology as an effective instructional tool for enhancing spatial visualization skills in apparel design

The purpose of this study is to explore the effectiveness of 3D simulation technology for enhancing spatial visualization skills in apparel design education and further to suggest an innovative teaching approach using the technology. Apparel design majors in an introductory patternmaking course, at a large Midwestern University in the United States, participated in this study. Three different teaching methods (lecture, 3D simulation instruments, and paper patternmaking) were employed in consecutive instructional phases, within a single day. A short questionnaire devised to assess students’ visualization abilities and overall evaluation on the three different teaching methods was administered to the students after each of the three phases. Overall, students’ abilities to visualize 2D patterns onto a human body were improved by all three teaching methods. The 3D simulation instruments anchored positive effects of training on spatial visualization abilities between lecture and paper patternmaking practices. The results affirm that 3D simulation technology has positive potential as an efficient instructional tool for improving students’ visualization skills in apparel design.     

Information direction, website reputation and eWOM effect: A moderating role of product type

This article examines how the electronic word of mouth (eWOM) information direction (positive vs. negative) and a website's reputation (established vs. unestablished) contribute to the eWOM effect. The article describes a study focusing on the moderating role of the product type (search vs. experience). The results of the experiment show that the eWOM effect is greater for negative eWOM than for positive eWOM, greater for established websites than for unestablished websites, and greater for experience goods than for search goods. The results support the moderating effects of product type on the eWOM information direction-website reputation-eWOM effect relationship. The impact of negative eWOM on the eWOM effect is greater for experience goods than for search goods. Similarly, the impact of website reputation on the eWOM effect is greater for experience goods than for search goods. The findings provide managerial implications for an Internet marketing strategy.     

Location,governance, and strategic determinants of japanese manufacturing investment in the united states

A firm's decision to manufacture abroad depends on location, governance, and strategic factors. Governance factors are firm-specific. In spite of this, most empirical studies of foreign direct investment (FDI) have been conducted at the industry level (making it impossible to look at firm-specific determinants), and only a handful have considered governance, location, and strategic factors simultaneously. This paper is the first large sample study of the determinants of foreign direct investment at the product and firm-level. It examines the impact of location and governance factors, and of four types of strategic interactions, on a Japanese firm's propensity to manufacture in the U.S. The results support the view that foreign direct investment is explained by location, governance, and strategic variables. Economies of scale and trade barriers encourage Japanese FDI in the U.S. The larger a Japanese firm's R & D expenditures, the greater the probability it will manufacture in the U.S., but this is not the case for advertising expenditures. Some strategic factors are also important: Japanese firms with medium domestic market shares have the highest propensity to invest in the U.S. There is evidence of follow-the-leader behavior between firms of rival enterprise groups, but none of ‘exchange-of-threat’ between American and Japanese firms. Japanese investors are also attracted by concentrated and high-growth U.S. industries.