Florida Households’ Expected Responses to Hurricane Hazard Mitigation Incentives

This study tested a series of models predicting household expectations of participating in hurricane hazard mitigation incentive programs. Data from 599 households in Florida revealed that mitigation incentive adoption expectations were most strongly and consistently related to hazard intrusiveness and risk perception and, to a lesser extent, worry. Demographic and hazard exposure had indirect effects on mitigation incentive adoption expectations that were mediated by the psychological variables. The results also revealed differences in the factors affecting mitigation incentive adoption expectations for each of five specific incentive programs. Overall, the results suggest that hazard managers are more likely to increase participation in mitigation incentive programs if they provide messages that repeatedly (thus increasing hazard intrusiveness) remind people of the likelihood of severe negative consequences of hurricane impact (thus increasing risk perception).     

ON FRAGILE GROUNDS: A REPLICATION OF “ARE MUSLIM IMMIGRANTS DIFFERENT IN TERMS OF CULTURAL INTEGRATION?”

This study is a replication of “Are Muslim Immigrants Different in terms of Cultural Integration?” by Alberto Bisin, Eleonora Patacchini, Thierry Verdier and Yves Zenou, published in the Journal of the European Economic Association, 6, 445–456, 2008. Bisin et al. (2008) report that they have 5,963 observations in their study. Using their empirical setup, we can only identify 1,901 relevant observations in the original data. After removing missing values we are left with 818 observations. We cannot replicate any of their results and our estimations yield no support for their claims.     

Reducing Customer Dissatisfaction: How Important is Learning to Reduce Service Failure?

As service failures are inevitable, firms must be prepared to recover and learn from service failures. Yet, the majority of customers are still dissatisfied with the way firms resolve their complaints. Can learning to reduce service failures reduce customer dissatisfaction, and to what extent are such reductions sustainable? Previous research showed that organizational learning curves for customer dissatisfaction (i) follow a U‐shaped function of operating experience and (ii) are heterogeneous across firms. In this paper, I tease out where the U‐shaped learning‐curve effect and learning‐curve heterogeneity originate: service failure or customers' propensity to complain with a third party given the occurrence of a service failure. Using quarterly data for nine major US airlines over 11 years, I find that the U‐shaped learning‐curve effect and the learning‐curve heterogeneity originate in the propensity to complain. In the long term, reductions in service failure did not translate in sustainable reductions in customer dissatisfaction. Customers' propensity to complain eventually went up. Managing the propensity to complain provides more opportunity for a firm to distinguish itself from competitors.     

The Surgical Scheduling Problem: Current Research and Future Opportunities

This paper reviews the general problem of surgical scheduling. We organize the literature based on the time frame or planning horizon of the schedule into six categories: capacity planning, process reengineering/redesign, the surgical services portfolio, procedure duration estimation, schedule construction, and schedule execution, monitoring, and control. We survey past work and suggest topics for potential future research in each of those areas.     

Nonparametric Instrumental Regression

The focus of this paper is the nonparametric estimation of an instrumental regression function ϕ defined by conditional moment restrictions that stem from a structural econometric model E[Y−ϕ(Z)|W]=0, and involve endogenous variables Y and Z and instruments W. The function ϕ is the solution of an ill‐posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyzes identification and overidentification of this model, and presents asymptotic properties of the estimated nonparametric instrumental regression function.     

Bayesian locally optimal design of knockout tournaments

The elimination or knockout format is one of the most common designs for pairing competitors in tournaments and leagues. In each round of a knockout tournament, the losers are eliminated while the winners advance to the next round. Typically, the goal of such a design is to identify the overall best player. Using a common probability model for expressing relative player strengths, we develop an adaptive approach to pairing players each round in which the probability that the best player advances to the next round is maximized. We evaluate our method using simulated game outcomes under several data-generating mechanisms, and compare it to random pairings, to the standard knockout format, and to two variants of the standard format.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.