Encounter Satisfaction in E‐tailing: Are the Relationships of Order Fulfillment Service Quality with its Antecedents and Consequences Moderated by Historical Satisfaction?

This study focuses on whether historical satisfaction with an e‐tailer (HSat) moderates baseline relationships in order fulfillment service quality models. HSat is defined as satisfaction with the e‐tailer spanning all transactions except the current encounter. Encounter satisfaction (ESat) is defined as the consumer's satisfaction with the current transaction. In the baseline model, four order fulfillment service quality (OFSQ) dimensions managerially relevant to consumer e‐tailing are examined: timeliness, availability, condition, and billing accuracy. The baseline structural model results support that OFSQ dimensions impact ESat, which in turn predicts two key consequences—repurchase intention and word‐of‐mouth. Adaptation theory is used to model the role of HSat, while controlling for transaction recency, vendor familiarity, and competitive pricing. HSat is shown to have pervasive main and interaction effects upon all baseline model relationships. These moderation effects have great managerial relevance. For example, the results illustrate a phenomenon similar to the service recovery paradox, wherein when a negative service encounter is followed by a highly positive service recovery event, previously dissatisfied consumers, as compared to previously satisfied consumers, respond with higher levels of current satisfaction. For managers, this finding is encouraging because policies that create highly positive events for consumers can thus supersede past negative experiences. Our results show however that HSat cannot be completely superseded by current OFSQ or current ESat.     

Longitudinal Analysis of Inhibitors of Manufacturer Delivery Performance

This article examines demand, manufacturing, and supply factors proposed to inhibit manufacturer delivery execution. Extant research proposes many factors expected to harm delivery performance. Prior cross‐sectional empirical research examines such factors at the plant level, generally finding factors arising from dynamic complexity to be significant, but factors arising from detail complexity to be insignificant. Little empirical research examines the factors using product‐level operating data, which arguably makes more sense for analyzing how supply chain complexity factors inhibit delivery. For purposes of research triangulation, we use longitudinal product‐level data from MRP systems to examine whether the factors inhibit internal manufacturing on time job rates and three customer‐oriented measures of delivery performance: product line item fill rates, average delivery lead times, and average tardiness. Our econometric models pool product line item data across division plants and within distinct product families, using a proprietary monthly dataset on over 100 product line items from the environmental controls manufacturing division of a Fortune 100 conglomerate. The data summarize customer ordering events of over 900 customers and supply chain activities of over 80 suppliers. The study contributes academically by finding significant detail complexity inhibitors of delivery that prior studies found insignificant. The findings demonstrate the need for empirical research using data disaggregated below the plant‐level unit of analysis, as they illustrate how some factors previously found insignificant indeed are significant when considered at the product‐level unit of analysis. Managers can use the findings to understand better which drivers and inhibitors of delivery performance are important.     

A course for clinical trial personnel in clinical study designs, randomization, allocation schedules, and interactive response systems

This continuing education course for professionals involved in all areas of clinical trials integrates concepts related to the role of randomization in the scientific process. The course includes two interactive lecture and discussion sections and a workshop practicum. The first interactive lecture introduces basic clinical trial issues and statistical principles such as bias, blinding, randomization, control groups, and the importance of formulating clear and discriminating clinical and statistical hypotheses. It then focuses on the most commonly used clinical study designs and the corresponding patient randomization schemes. The second interactive lecture focuses on the implementation of randomization of patients and drug supply through allocation and component ID schedules. The workshop practicum, conducted in small groups, enables students to apply the lecture concepts to real clinical studies. Flexibility was built into the workshop practicum materials to allow the course content to be customized to specific audiences, and the interactive lecture sessions can be stretched to cover more advanced topics according to class interest and time availability.     

A linear model-based test for the heterogeneity of conditional correlations

Current methods of testing the equality of conditional correlations of bivariate data on a third variable of interest (covariate) are limited due to discretizing of the covariate when it is continuous. In this study, we propose a linear model approach for estimation and hypothesis testing of the Pearson correlation coefficient, where the correlation itself can be modeled as a function of continuous covariates. The restricted maximum likelihood method is applied for parameter estimation, and the corrected likelihood ratio test is performed for hypothesis testing. This approach allows for flexible and robust inference and prediction of the conditional correlations based on the linear model. Simulation studies show that the proposed method is statistically more powerful and more flexible in accommodating complex covariate patterns than the existing methods. In addition, we illustrate the approach by analyzing the correlation between the physical component summary and the mental component summary of the MOS SF-36 form across a fair number of covariates in the national survey data.     

A two-sample empirical likelihood ratio test based on samples entropy

Powerful entropy-based tests for normality, uniformity and exponentiality have been well addressed in the statistical literature. The density-based empirical likelihood approach improves the performance of these tests for goodness-of-fit, forming them into approximate likelihood ratios. This method is extended to develop two-sample empirical likelihood approximations to optimal parametric likelihood ratios, resulting in an efficient test based on samples entropy. The proposed and examined distribution-free two-sample test is shown to be very competitive with well-known nonparametric tests. For example, the new test has high and stable power detecting a nonconstant shift in the two-sample problem, when Wilcoxon’s test may break down completely. This is partly due to the inherent structure developed within Neyman-Pearson type lemmas. The outputs of an extensive Monte Carlo analysis and real data example support our theoretical results. The Monte Carlo simulation study indicates that the proposed test compares favorably with the standard procedures, for a wide range of null and alternative distributions.     

Psychopathology in pathological gamblers seeking treatment

High rates of psychiatric symptoms have been reported in pathological gamblers. This study of psychiatric comorbidity in pathological gamblers is the first to use structured psychiatric interviews assessing DSM-III-R Axis I and II disorders. The Structured Clinical Interview for DSM III-R (SCID-P, SCID-II) was administered to 40 (25 male, 15 male) pathological gamblers seeking outpatient treatment in Minnesota for gambling, and 64 (41 male, 23 female) controls. High lifetime rates of Axis I (92%) but not Axis II (25%) psychopathology were found in pathological gamblers as compared to controls. No differences between male and female gamblers were found in rates of affective, substance use or personality disorders. Females had higher rates of anxiety disorders and histories of physical/sexual abuse. Possible associations between psychiatric disorders and pathological gambling are discussed along with gambler typologies and implications for future research.The authors wish to gratefully acknowledge the assistance of: Gary Christenson, M.D., Carol Peterson, Ph.D., William Meller, M.D., Thomas Mackenzie, M.D.     

Reports of childhood sexual abuse by adolescents and young adults: stability over time

The consistency of childhood sexual abuse (CSA) reporting was explored in this study. Two-hundred seventeen adolescents and young adults (ages 14-24) enrolled in urban health care clinics completed self-report questionnaires assessing CSA and other problem behaviors at enrollment and at 7 months. Results indicated that the stability of CSA self-report at two time points was poor (58% consistent nonreporters of CSA, 20% consistent reporters, 22% inconsistent reporters). Consistent and inconsistent reporters were differentiated on risk measures. Adolescents who endorsed more items from the CSA scale were five times more likely to be consistent reporters. In sum, adolescent CSA reporting was quite inconsistent over time. Using multi-item scales and assessing CSA at two time points enhances accuracy of reporting.     

Family composition preferences in a developing culture: The case of Taiwan, 1973

Abstract As fertility comes increasingly under voluntary control in a developing society, it can be argued that individual desires or preferences about children will become more salient and more significant for eventual fertility. Hence, the study of preferences is increasingly important as contraceptive use is extended and results in decreasing the number of unwanted births.(1) Further changes in fertility then depend on changes in preferences. The assumption is that people will at least try to achieve the families they want, if the means to do so are available. The fact that contraception is used at all is some evidence of the soundness of this assumption, although it should be recognized that family size desires operate in a complex of preferences, under varying degrees of conflict and control. To expect a one-to-one relationship between attitudes or preferences and overt behaviour would be simplistic.