Covering both quantitative and qualitative methods, this book examines the breadth of modern market research methods for upper level students across business schools and social science faculties. Modern and trending topics including social networks, machine learning, big data, and artificial intelligence are addressed and real world examples and case studies illustrate the application of the methods. This text examines potential problems, such as researcher bias, and discusses effective solutions in the preparation of research reports and papers, and oral presentations. Assuming no prior knowledge of statistics or econometrics, discrete chapters offer a clear introduction to both, opening up the quantitative methods to all students. Each chapter contains rigorous academic theory, including a synthesis of the recent literature as well as key historical references, applied contextualization and recent research results, making it an excellent resource for practitioners. Online resources include extensive chapter bibliographies, lecture slides, an instructor guide and extra extension material and questions.
The planning of promotions and other marketing events frequently requires manufacturers to make decisions about the optimal duration of these activities. Yet manufacturers often lack the support tools for decision making. We assume that customer decisions at the aggregated level follow a state-dependent Markov process. On the basis of the expected economic return associated with dynamic response to stimuli, we determine the ideal length of marketing events using dynamic programming optimization and apply the model to a complex promotion event. Results suggest that this methodology could help managers in the publishing industry to plan the optimal duration of promotion events.
Historically, the U.S. advertising industry has been experiencing enormous movements as a result of rapid advances in the media technology and the business cycle. In this paper, we study the historical behavior of the U.S. advertising industry, correcting for inflation. We find that the introduction of new media cause structural breaks in the mean growth rates of advertising expenditure for the incumbent media. In addition, we find that random components of media advertising spending follow a long-term equilibrium where the cross-elasticities across newer and older media can show substitution or complementarity patterns depending on the type of audience. We examine the influence of the economic conditions on the aggregated advertising expenditure, and on each media spending. We also measure the impact of the recent takeoff in mobile advertising.
This paper studies the impact and effectiveness of a type of non-price promotion often used in the European periodical magazines industry to stimulate sales, in which a value pack is sold containing the magazine issue plus another product. Magazines are sold simultaneously with and without promotion at different prices, and promotions are serialized by fractioning the additional product across different issues of the magazine. We find that promoted magazines contemporarily cannibalize non-promoted sales; but this loss is compensated by a medium term increase of non-promoted sales. These results show that this sales promotion strategy is an effective way to diminish the decline rate of periodical sales.
The experimental design literature has produced a wide range of algorithms optimizing estimator variance for linear models where the design-space is finite or a convex polytope. But these methods have problems handling nonlinear constraints or constraints over multiple treatments. This paper presents Newton-type algorithms to compute exact optimal designs in models with continuous and/or discrete regressors, where the set of feasible treatments is defined by nonlinear constraints. We carry out numerical comparisons with other state-of-art methods to show the performance of this approach.
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