An Information‐Processing Approach for Evaluating In‐Store Retail Operational Design Strategies

We develop a model to evaluate retail store operational design strategies using an information‐processing perspective of organizational design. We propose that three model constructs pertaining to in‐store shopper task uncertainty—the product mix complexity, the service production complexity, and the product mix changeover—create shopper encounter information requirements (IR). These requirements can be met using specific retail service operational design choices for managing shopper encounters, namely, designing layouts for self‐service (SS) and providing employees with task empowerment (TE). The model is then operationalized using a two‐stage approach to develop new multi‐item, measurement scales. The psychometric properties and predictive validity of the scales and model are then confirmed by using structural equation modeling with survey data from 175 merchandise retail store managers. We find that our model can be generically applied across the retail industry to understand how shopper encounter IR motivate retailer store design choices and can be used to determine whether to design stores for SS or to provide store employees with TE. We then evaluate the efficacy of the studied store design choices on customer delivery satisfaction, and offer some suggestions for future research.     

On the validity of MAPE as a measure of population forecast accuracy

The mean absolute percent error (MAPE) is the summary measure most often used for evaluating the accuracy of population forecasts. While MAPE has many desirable criteria, we argue from both normative and relative standpoints that the widespread practice of exclusively using it for evaluating population forecasts should be changed. Normatively, we argue that MAPE does not meet the criterion of validity because as a summary measure it overstates the error found in a population forecast. We base this argument on logical grounds and support it empirically, using a sample of population forecasts for counties. From a relative standpoint, we examine two alternatives to MAPE, both sharing with it, the important conceptual feature of using most of the information about error. These alternatives are symmetrical MAPE (SMAPE) and a class of measures known as M-estimators. The empirical evaluation suggests M-estimators do not overstate forecast error as much as either MAPE or SMAPE and are, therefore, more valid measures of accuracy. We consequently recommend incorporating M-estimators into the evaluation toolkit. Because M-estimators do not meet the desired criterion of interpretative ease as well as MAPE, we also suggest another approach that focuses on nonlinear transformations of the error distribution.     

Substrate reinforcement and dialectal differences in Melanesian Pidgin

Stabilization of a new contact language involves a process of levelling, or the reduction of variants. One of the factors influencing which grammatical variants are retained in the process is substrate reinforcement – the existence in the substrate languages of a congruent structure with a similar function. This article illustrates substrate reinforcement in the development of the three current dialects of Melanesian Pidgin. First, evidence of earlier variability is presented and the sociolinguistic conditions that later led to greater stability are described. Second, five grammatical features that differentiate the dialects are examined. For each feature, it is shown first that at least two variants were previously in use. Then evidence is presented illustrating correspondence between the particular variant retained in the dialect and a feature of the substrate languages of that geographic area. Differing substrates reinforced different variants, and this accounts for these dialectal differences.     

The nature and effectiveness of program models for adolescents at risk of entering the formal child protection system

This article compares rationales and outcome research for five areas of programming for adolescents: adolescent competence and skill development programs, family- and parent-focused programs, social integration programs, multiple component programs, and neighborhood transformation programs. The article examines program evidence for maltreated teens as well as teens coping with a variety of other challenges. The study uses a framework based on common developmental challenges and risk factors for adolescents to select and review programs.     

Evaluating Population Forecast Accuracy: A Regression Approach Using County Data

Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places. Using decennial census data from 1900 to 2000 for 2,482 counties in the US, we construct a large number of county population forecasts and calculate forecast errors for 10- and 20-year horizons. Then, we develop and evaluate several alternative functional forms of regression models relating population size and growth rate to forecast accuracy; investigate the impact of adding several other explanatory variables; and estimate the relative contributions of each variable to the discriminatory power of the models. Our results confirm several findings reported in previous studies but uncover several new findings as well. We believe regression models based on data for individual places provide powerful but under-utilized tools for investigating the determinants of population forecast accuracy.     

Assessing Uncertainty in Small Area Forecasts: State of the Practice and Implementation Strategy

Forecasts are needed for everyday decisions and must be in the form of numbers. Yet forecasts invariably turn out to be different than the numbers that actually occur. Yet, most producers of forecasts only present a deterministic view of the future in the form of point predictions. However, the presence of uncertainty is inherent in management or policy decisions and there is often concern that benefits are overstated and risks are understated. Such concerns are difficult to address by providing only point forecasts with no assessment of their uncertainty. Having a better understanding of uncertainty can enhance the usefulness of forecasts and make the work of forecasting agencies an even more valuable product for planners, policy makers, and the public. The purpose of this paper is twofold. First, it presents an overview of the current state-of-the-practice is assessing forecast uncertainty. Second, it offers a guidelines and options for implementing and building uncertainty into small area forecasting processes. There are options for assessing forecasting uncertainty that can and should be implemented by most, if not all, producers of forecasts.