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.

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 Each chapter contains rigorous academic theory, including a synthesis of the recent literature as well as key historical references, applied contextualization and recent research results, making it an excellent resource for practitioners.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.

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.

Inventors can commercialize innovative products by themselves and simultaneously license the technology to other firms. The licensee may cannibalize sales of the licensor, but this can be compensated by gains from royalties. We show in this paper how licenses can be used strategically to speed up the new product diffusion process in two instances of markets: (i) a market with strong Intellectual Property Rights (IPR), and (ii) a market with weak IPR holder and pirate rivals. The main findings suggest that licensing is a beneficial strategy for a licensor in the context of strong IPR, because licensor benefits from the royalties, the advertising investment and positive word-of-mouth effects by licensees. We compare this result with a weak IPR context, where piracy speeds up the product diffusion but this does not compensate IPR holder for the sales loss effect who is willing to license to get some royalties. However, pirates do not generally find interesting the licensing agreement. We present a comparative statics analysis based on numerical simulation.

This paper presents an algorithm for approximating the solution of deterministic/stochastic continuous-time growth models based on the Euler's equation and the transversality conditions. The main issue for computing these models is to deal efficiently with the boundary conditions associated. This approach is a wavelets-collocation method derived from the finite-iterative trapezoidal approach. Illustrative examples are given. JEL classification codes: C63.

We discuss how trade-in rebates can be used to manage product multigenerational innovation diffusion waves, and study the optimal behavior of the firm controlling the prices and rebates associated to product upgrades. We show how this strategy accelerates the diffusion and can lead to profit increments of about 5%. The strategy is profitable even when the rebate subsidizes the upgrades entirely.