This paper critically evaluates the dominant discourse of academic marketing management which is held to be capable of structuring practice. In addressing this issue and the concerns of the marketing as practice track, this paper draws on critical theory, discourse analysis, and social constructionism. The latter involved carrying out two groups of in depth interviews with marketing managers. T...

Background:Social marketing emphasizes the use of commercial marketing concepts and their application for social purposes and also the change of voluntary behavior in a non-profit manner. The main purpose of this study is to examine the effectiveness of social marketing on changing the physical activity of the elderly. Second, this study seeks to determine the extent to which Andreasonchr('39')...

The role of database marketing (DBM) has become increasingly important for organisations that have large databases of information on customers with whom they deal directly. At the same time, DBM models used in practice have increased in sophistication. This paper examines a systemic view of DBM and the role of analytical techniques within DBM. It extends existing process models to develop a sys...

Validation issues have received little attention by agent-based modelers in marketing research. In this paper we provide a definition of validation relevant for this community of modelers. Using the foundation of a history-friendly model for simulation calibration (Malerba, et al., 1999), we demonstrate how conjoint analyses can be used to instantiate and calibrate an agent-based marketing mode...

Marketers acquire information on customers from various sources, creating large databases. To use this information effectively, they need to estimate binary response models (e.g., Bult and Wansbeek 1995) in high-dimensions, i.e. in the presence of numerous exogenous variables. This task entails serious challenges of computation, identification, and statistical inference. Because of computationa...

Digital marketing has brought in enormous capture of consumer data. In quantitative marketing, researchers have adopted structural models to explain the (dynamic) decision process and incentives of consumers. However, due to computational burdens, structural models have rarely been applied to big data. Machine learning algorithms that perform well on big data, however, hardly have any theoretic...

Random utility (RU) models are well-established methods for describing discrete choice behavior. Recently, there has been a strong upsurge in interest driven by advances in data gathering and estimation technology. This review paper describes the principles and issues, and develops a taxonomy of three major families of models. The paper summarizes and classifies the different approaches. The ad...