We develop two models to test hypotheses on the specific impact ofbrand and category characteristics on consumer stock-out responses.Our empirical results show that both characteristics are importantdeterminants. Consumers are more product loyal in hedonic productgroups than in utilitarian...

We propose a consistent utility-based framework to jointly explain a household's decisions on purchase incidence, brand choice and purchase quantity. The approach differs from other approaches, currently available in the literature, as it is able to take into account consumption dynamics. In the...

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specificperiod of time. It is for this purpose that we...

A Forecast Support System (FSS), which generates sales forecasts, is a sophisticated business analytical tool that can help to improve targeted business decisions. Many companies use such a tool, although at the same time they may allow managers to quote their own forecasts. These sales...

Using weekly data on advertising expenditures in various media and response data on awareness, consideration and choice, we test the hierarchy of effects hypothesis. Our empirical results, based on a simultaneous equations model with pooled parameters across brands, suggest that we can reject...

In this paper we empirically investigate various benefits and costs associated with broker characteristics of individuals who operate in the account management system of financial service providers. We narrow our focus to broker positions in two specific task-specific knowledge networks that...

We present a model that integrates the contradicting Burtian and Krackhardtian broker theories to explain effectiveness of brokering for individuals within account management organizations. Using data on a network of 55 individuals in a financial account management organization, we test how...

Market share models for weekly store-level data are useful to understand competitive structures by delivering own and cross price elasticities. These models can however not be used to examine which brands lose share to which brands during a specific period of time. It is for this purpose that we...

A commonly applied modeling tool for the analysis of promotional effects on weekly sales data is a linear regression model. Usually, such a model includes 0/1 dummy variables for promotions, where weeks with a promotion get a value of 1. When these variables are included in a model with...

The authors investigate the impact of direct-response commercials on incoming calls at a national call center. To this end, the authors analyze the data of a fast service for repairs of (parts of) a durable consumption good in Flanders, Belgium. The authors have access to data at the 15 minute...