The shopping behavior of time-sensitive consumers has been modeled as an economic model of choice. Consumers are said to balance the costs of time spent commuting to the store and in the store with storage costs and other nontime costs of shopping. In so doing, these consumers tend to minimize their overall costs. Propositions are developed and tested using this economic model of shopping. The model is extended beyond time sensitivity to include deal proneness; further propositions are developed and tested using the extended model. The empirical results support the derived models.

The authors present a methodology that measures improvement in customer satisfaction scores when those scores are already high and the production process is slow and thus does not generate a large amount of useful data in any given time period. The authors used these techniques with data from a midsized rehabilitation institute affiliated with a regional, nonprofit medical center. Thus, this article functions as a case study, the findings of which may be applicable to a large number of other healthcare providers that share both the mission and challenges faced by this facility. The methodology focused on 2 factors: use of the unique characteristics of panel data to overcome the paucity of observations and a dynamic benchmarking approach to track process variability over time. By focusing on these factors, the authors identify some additional areas for process improvement despite the institute's past operational success.

A wide variety of techniques are used to assess the development of survey-based scales. The majority of these techniques focus on the quality of information characterized by the scale. Aside from very rudimentary measures such as response rates and sample sizes, very few empirical techniques are available to measure the quantity of information contained in a scale. This article conducts an exploratory empirical analysis to assess whether information entropy can be useful for measuring the quantity of information in a scale’s development. If the quantity of information in the scale significantly increases (decreases) with the addition of the survey item, researchers may consider retaining (discarding) that item in the scale. The study was conducted within the context of a natural experiment that occurred at a major amateur sporting event in 2018. Customer satisfaction was assessed using a survey whose core questions have been assessed repeatedly over time. The most recent survey contained a previously validated empathy scale, with two items contained in the base measure. Six additional items were added to this base empathy measure. The quantity of information provided (as measured by information entropy) is calculated for each set of scale items. Statistical analysis indicates that, when adding the behavioral, cognitive, and affective scales to the two-item base scale, the quantity of information available increased. However, most of the increase in information quantity was attributable to three survey items, one item from each of the behavioral, cognitive, and affective domains. These findings suggest that information entropy may indeed be a useful quality control tool for survey scale development.

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