Encouraging a Spatial Perspective in Third Sector Studies: Exploratory Spatial Data Analysis and Spatial Regression Analysis

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Geographic space or location is an important aspect of many research topics in the third sector. Methodological advances...     

Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts

High levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, but the exact nature of the dose-response relationship is less well understood. To investigate this relationship, data were assembled from six longitudinal birth cohort studies examining the effects of PAE on cognitive outcomes from early school age through adolescence. Structural equation models (SEMs) are a natural approach to consider, because of the way they conceptualise multiple observed outcomes as relating to an underlying latent variable of interest, which can then be modelled as a function of exposure and other predictors of interest. However, conventional SEMs could not be fitted in this context because slightly different outcome measures were used in the six studies. In this paper we propose a multi-group Bayesian SEM that maps the unobserved cognition variable to a broad range of observed outcomes. The relation between these variables and PAE is then examined while controlling for potential confounders via propensity score adjustment. By examining different possible dose-response functions, the proposed framework is used to investigate whether there is a threshold PAE level that results in minimal cognitive deficit.     

Measuring the Benefit of Offering Auxiliary Services: Do Bag‐Checkers Differ in Their Sensitivities to Airline Itinerary Attributes?

When firms evaluate their service system design choices, there is typically more uncertainty surrounding the value that a particular auxiliary service provides than there is on the cost of providing that service. To help inform this decision, we propose an approach where we compare the relative value of the segment of passengers who use an auxiliary service to the relative value of the segment that does not use it. We demonstrate this approach for a typical auxiliary service common to the airline industry. In 2008, most US airlines implemented checked baggage fee policies to decrease their costs by reducing the number of customer service agents needed in the check‐in and baggage handling processes. The success of this change has led to a current debate at many of these airlines on whether to make further staffing cuts in these areas, essentially making it even less attractive for passengers to check their baggage. Our proposed methodology helps answer whether passengers who continue to check bags in today's baggage‐fee era are more or less valuable than passengers who do not check bags. We explore this question empirically by examining, through a stated preference survey, if a history of checking or not checking bags can be used to segment passengers based on how their itinerary choices are influenced by common airline service attributes (on‐time performance, itinerary time, number of connections, airfare, and schedule delay). Contrary to the opinions of some top airline executives, we find that the passengers who continue to check bags at airlines that charge baggage fees are generally less sensitive to differences in three of these important service attributes and are less likely to switch airlines when a competing airline improves its offerings along these dimensions. Thus, airlines that charge for checked bags should consider improving the customer experience for their bag‐checking passengers, as they represent a potentially more valuable segment class to the airline.