Uncertainty avoidance,risk tolerance and corporate takeover decisions

In this paper, we examine the role of national culture in corporate takeover decisions, by arguing that managerial risk tolerance (a combination of risk aversion and risk perception), at the national level, is a cultural trait and affects the expected net synergies CEOs require. We propose a theoretical framework that links CEO risk tolerance to the expected net synergies. We empirically show that CEOs of firms located in countries with lower levels of risk tolerance, measured by Hofstede’s (1980, 2001) uncertainty avoidance score, require higher premiums on takeovers, and show that uncertainty avoidance plays a greater role in relatively large takeovers. Additional testing reveals that CEOs from high uncertainty avoiding nations engage less in cross-border/cross-industry takeovers, suggesting that uncertainty avoidance captures more the CEO’s risk perception than his/her risk aversion.     

The Performance Impact of Content and Process in Product Innovation Charters

The significance of product innovation charters (PICs) cannot be overemphasized, as they provide understanding and a tool for setting organizational goals, charting strategic direction, and allocating resources for new product portfolios. In a unique way, a PIC represents a sort of mission statement mutation for new products. With the backdrop of strategy formulation and product innovation literatures, this article investigates the impact of both content specificity within PICs and satisfaction with the PIC formulation process on new product performance in North American corporations. A survey was undertaken among executives knowledgeable about their organization's new product development process. The respondents included chief executive officers, vice presidents, directors, and managers. The findings demonstrate that significant differences exist both in PIC content specificity and process satisfaction between highly innovative and low innovative firms. The study also shows that PIC specificity in terms of the factors mission content and strategic directives positively influences new product performance. Further, the study demonstrates that satisfaction with the process of formulating PICs plays a positive and powerful mediating role in the PIC specificity–performance relationship. The results suggest that product innovation charters, like their mission statement cousins, may be of more value than most managers realize. The study shows that achieving a state of organizational satisfaction with a PIC's formulation process is critical for obtaining better new product performance. Directions for future research also are suggested.     

INSIDER TRADING,REGULATION, AND THE COMPONENTS OF THE BID–ASK SPREAD

In this article we investigate the relation between insider trading regulations and the bid–ask spread. We decompose the spread into its components before and after the enactment of strict new insider trading rules in New Zealand. We find that the enactment led to a significant decrease in the information asymmetry component of the spread, which is observed mainly in illiquid and high prechange information asymmetry companies. These findings are robust to model specification. In addition, we find a decrease in the contribution of information asymmetry to price volatility.     

Dismantling the ivory tower: The influence of networks on innovative output in emerging technologies

In this article we examine how R&D networking affects an organization's innovative output. Using empirical data on 419 research organizations in transgene plant research over a 20-year period, we test several hypotheses relating their sociometric position in an R&D network to their innovative output. Attention is paid to the relative importance of in-house versus collaborative research. Least squares dummy variable models are used to analyze cross-sectional data across different time periods. The results show that (1) an organization's “network embeddedness” positively influences its innovative output; whereas (2) involvement in collaborative R&D has a curvilinear effect on innovative performance.     

A Comparison of State-of-the-Art Classification Techniques for Expert Automobile Insurance Claim Fraud Detection

Several state‐of‐the‐art binary classification techniques are experimentally evaluated in the context of expert automobile insurance claim fraud detection. The predictive power of logistic regression, C4.5 decision tree, k‐nearest neighbor, Bayesian learning multilayer perceptron neural network, least‐squares support vector machine, naive Bayes, and tree‐augmented naive Bayes classification is contrasted. For most of these algorithm types, we report on several operationalizations using alternative hyperparameter or design choices. We compare these in terms of mean percentage correctly classified (PCC) and mean area under the receiver operating characteristic (AUROC) curve using a stratified, blocked, ten‐fold cross‐validation experiment. We also contrast algorithm type performance visually by means of the convex hull of the receiver operating characteristic (ROC) curves associated with the alternative operationalizations per algorithm type. The study is based on a data set of 1,399 personal injury protection claims from 1993 accidents collected by the Automobile Insurers Bureau of Massachusetts. To stay as close to real‐life operating conditions as possible, we consider only predictors that are known relatively early in the life of a claim. Furthermore, based on the qualification of each available claim by both a verbal expert assessment of suspicion of fraud and a ten‐point‐scale expert suspicion score, we can compare classification for different target/class encoding schemes. Finally, we also investigate the added value of systematically collecting nonflag predictors for suspicion of fraud modeling purposes. From the observed results, we may state that: (1) independent of the target encoding scheme and the algorithm type, the inclusion of nonflag predictors allows us to significantly boost predictive performance; (2) for all the evaluated scenarios, the performance difference in terms of mean PCC and mean AUROC between many algorithm type operationalizations turns out to be rather small; visual comparison of the algorithm type ROC curve convex hulls also shows limited difference in performance over the range of operating conditions; (3) relatively simple and efficient techniques such as linear logistic regression and linear kernel least‐squares support vector machine classification show excellent overall predictive capabilities, and (smoothed) naive Bayes also performs well; and (4) the C4.5 decision tree operationalization results are rather disappointing; none of the tree operationalizations are capable of attaining mean AUROC performance in line with the best. Visual inspection of the evaluated scenarios reveals that the C4.5 algorithm type ROC curve convex hull is often dominated in large part by most of the other algorithm type hulls.     

Spatial integration at multiple scales: rice markets in Madagascar

The dramatic increase in the price of rice and other commodities over the past year has generated new interest in how these markets work and how they can be improved. This article uses an exceptionally rich data set to test the extent to which markets in Madagascar are integrated across space at different scales of analysis and to explain some of the factors that limit spatial arbitrage and price equalization within a single country. We use rice price data across four quarters of 2000–2001 along with data on transportation costs and infrastructure availability for nearly 1,400 communes in Madagascar to examine the extent of market integration at three different spatial scales—subregional, regional, and national—and to determine whether non-integration is due to high transfer costs or lack of competition. The results indicate that markets are fairly well integrated at the subregional level and that factors such as high crime rates, remoteness, and lack of information are among the factors limiting competition.     

Structural Models of Factor Demands and Technological Change: An Empirical Assessment of Dynamic Adjustment Specifications for Sectors of the Dutch Economy

In this paper, we combine a translog cost functional form with an adjustment process according to the error correction mechanism to explain the simultaneous determination of factor demands and technological change. To save degrees of freedom in the estimation procedure, we also consider the imposition of restrictions on the matrices of lag parameters and/or the covariance matrix of the disturbances. Using a model selection strategy based on a combination of economic-theoretical considerations and a formal model selection criterion, a model is selected for each of 17 sectors of the Dutch economy. It turns out that, for 14 of the 17 sectors under consideration, a model is chosen that allows the imposition of restrictions with respect to the matrices of lag parameters. A comparison of the present results with those obtained by Lesuis and de Boer reveals that the application of more general dynamic structures leads to results that are more in accordance with economic theory.     

Formation and evolution of buyer-supplier relationships: Conceiving dynamism in actor composition of business networks

This study investigates the tenability of the position that business networks are relatively stable, based on long-lasting inter-firm relationships with limited substitutions of incumbent actors. This is done via a longitudinal analysis on the actor composition evolution with regard to the supplier networks around two car assembly plants. Based on the overall empirical findings, the study concludes that the phenomenon of supplier substitution may be a more widespread reality. Consequently, the article finishes with a series of business implications and recommendations on how to investigate and conceive this matter more thoroughly.     

What Collusion? Unilateral Market Power as a Catalyst for Countercyclical Markups

This paper presents and tests a simple model of competitive and unilateral market power regimes that yields countercyclical markups. Following a decrease in demand in the short run, capacity-constrained firms may have a strong incentive not to lower their prices to the new competitive price. Demand shocks may introduce market power into a previously competitive market. Experimental posted offer markets support this conjecture with complete information on the market structure. With only private information, there appears to be a hysteresis effect concerning supracompetitive prices, i.e., markets with a history of supracompetitive pricing continue to generate supracompetitive prices following demand shocks. However, competitive markets also remain competitive following demand shocks when firms only have private information on costs and capacities.