Effect of Inventory Information Discrepancy in a Drop‐Shipping Supply Chain

This article investigates the impact of information discrepancy between a drop‐shipper and an online retailer on the drop‐shipping supply chain performance. The inventory information misalignment between them contributes to the failure of order fulfillment and demand satisfaction, and hence the associated penalties are incurred. In this article, we first analyze the penalties of ignoring such information discrepancy on both the drop‐shipper and the online retailer. We then assess the impact of information discrepancy on both parties when the drop‐shipper understands the existence of the information discrepancy but is not able to eliminate the errors. The numerical experiments indicate that both parties can have significant amount of the percentage cost reductions if the information discrepancy can be eliminated, and the potential savings are substantial especially when the errors have large variability. Furthermore, we observe that the online retailer is more vulnerable to information discrepancy than the drop‐shipper, and the drop‐shipper is likely to suffer from the online retailer's underestimation of the physical inventory level more than the problem of its overestimation. Moreover, even if eliminating errors is not possible, both parties could still benefit from taking the possibility of errors into consideration in decision making.     

Coherence principles in interval‐based dose finding

This paper studies the notion of coherence in interval‐based dose‐finding methods. An incoherent decision is either (a) a recommendation to escalate the dose following an observed dose‐limiting toxicity or (b) a recommendation to deescalate the dose following a non–dose‐limiting toxicity. In a simulated example, we illustrate that the Bayesian optimal interval method and the Keyboard method are not coherent. We generated dose‐limiting toxicity outcomes under an assumed set of true probabilities for a trial of n=36 patients in cohorts of size 1, and we counted the number of incoherent dosing decisions that were made throughout this simulated trial. Each of the methods studied resulted in 13/36 (36%) incoherent decisions in the simulated trial. Additionally, for two different target dose‐limiting toxicity rates, 20% and 30%, and a sample size of n=30 patients, we randomly generated 100 dose‐toxicity curves and tabulated the number of incoherent decisions made by each method in 1000 simulated trials under each curve. For each method studied, the probability of incurring at least one incoherent decision during the conduct of a single trial is greater than 75%. Coherency is an important principle in the conduct of dose‐finding trials. Interval‐based methods violate this principle for cohorts of size 1 and require additional modifications to overcome this shortcoming. Researchers need to take a closer look at the dose assignment behavior of interval‐based methods when using them to plan dose‐finding studies.     

Passing Encounters East and West: Comparing Japanese and American Pedestrian Interactions

This study examined the microinteractions of pedestrians in Japan and in the United States as they walked past a confederate. Specifically, the effects of culture, condition (avoid, look-only, and look plus smile) and sex of confederate on glances, smiles, nods, and greetings by passing pedestrians were examined in a field study on over 1000 participants. The hypotheses of (1) lower responsiveness in Japanese pedestrians than in American pedestrians and (2) increased responsiveness as a function of condition were supported in a series of log-linear analyses of pedestrian glances, smiles, nods, and greetings. Both of these main effects were, however, qualified by Culture X Condition interactions on smiles, nods, and greetings, with the large condition effects present in the American pedestrians, but absent in the Japanese pedestrians. The results are discussed in terms of the functions of glances, smiles, nods, and greetings in these brief encounters and how differing cultural norms affect Japanese and American responsiveness. Finally, the limitations of this study and the broader utility of this research paradigm are discussed.

An Application of Markov Chain Analysis to the Game of Squash*

If the score in a squash game is tied late in the game, one player has a choice of how many additional points (from a prespecified set of possibilities) are to be played to determine the winner. This paper constructs a Markov chain model of the situation and solves for the optimal strategy. Expressions for the optimal strategy are obtained with a symbolic algebra computer package. Results are given for both international and American scoring systems. The model and analysis are very suitable for educational purposes. The resulting Markov chain is small enough that it can be easily presented in a classroom setting, yet the model is sufficiently complex that algebraic manipulation is nearly hopeless. The final results illustrate the power of the combination of mathematical and computer modeling applied to a problem of practical interest.     

Temporary Employment Contracts and Household Income

Social Indicators Research - It is widely accepted that temporary jobs tend to be associated with low pay which, in turn, will have negative consequences for household income. Evidence in support...     

Generalized Reflexive Responding and Cross-Modal Tactile Transfer of Stimulus Function in Children with Autism

We sought to evaluate the efficacy of successive matching training for establishing generalized reflexive matching across 4 children with autism. In Experiment 1, differential reinforcement with delay fading was efficacious in establishing “yes” and “no” matching and nonmatching responses in 2 participants when 2 identical or nonidentical picture stimuli were presented. In addition, emergent visual–visual reflexive relational responses were observed using novel picture stimuli in a transfer test phase. In Experiment 2, differential reinforcement alone was efficacious in establishing matching and nonmatching responses in the other 2 participants when 2 identical or nonidentical objects were presented. Transfer to identical objects presented through touch (i.e., tactile discrimination) was additionally observed for both participants. Procedures in the study were adapted from the PEAK Relational Training System to aid in clinical replication, and the translational results have implications for language training with individuals with autism.     

Explaining individual differences in infant visual sensory seeking

Individual differences in infants’ engagement with their environment manifest early in development and are noticed by parents. Three views have been advanced to explain differences in seeking novel stimulation. The optimal stimulation hypothesis suggests that individuals seek further stimulation when they are under‐responsive to current sensory input. The processing speed hypothesis proposes that those capable of processing information faster are driven to seek stimulation more frequently. The information prioritization hypothesis suggests the differences in stimulation seeking index variation in the prioritization of incoming relative to ongoing information processing. Ten‐month‐old infants saw 10 repetitions of a video clip and changes in frontal theta oscillatory amplitude were measured as an index of information processing speed. Stimulus‐locked P1 peak amplitude in response to checkerboards briefly overlaid on the video at random points during its presentation indexed processing of incoming stimulation. Parental report of higher visual seeking did not relate to reduced P1 peak amplitude or to a stronger decrease in frontal theta amplitude with repetition, thus not supporting either the optimal stimulation or the processing speed hypotheses. Higher visual seeking occurred in those infants whose P1 peak amplitude was greater than expected based on their theta amplitude. These findings indicate that visual sensory seeking in infancy is explained by a bias toward novel stimulation, thus supporting the information prioritization hypothesis.     

Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, stored in public repositories. We review applications of a variety of empirical Bayes methods to several well‐known model‐based prediction methods, including penalized regression, linear discriminant analysis, and Bayesian models with sparse or dense priors. We discuss “formal” empirical Bayes methods that maximize the marginal likelihood but also more informal approaches based on other data summaries. We contrast empirical Bayes to cross‐validation and full Bayes and discuss hybrid approaches. To study the relation between the quality of an empirical Bayes estimator and p, the number of variables, we consider a simple empirical Bayes estimator in a linear model setting. We argue that empirical Bayes is particularly useful when the prior contains multiple parameters, which model a priori information on variables termed “co‐data”. In particular, we present two novel examples that allow for co‐data: first, a Bayesian spike‐and‐slab setting that facilitates inclusion of multiple co‐data sources and types and, second, a hybrid empirical Bayes–full Bayes ridge regression approach for estimation of the posterior predictive interval.