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This paper uses an analytical model to examine when it makes sense to provide incentives to innovators to adopt a new product. The model allows for separate segments of innovators and imitators, each of which follows a Bass-type diffusion process. Interestingly "seeding" the market is optimal for a limited range of situations and these do not appear to include those where there is a downturn in sales (chasm) as sales move from the first to the second segment. Research has frequently identified different segments of adopters of new products. Categorizations include innovators vs imitators (Bass, 1969; Rogers, 1995; Mahahan et al., 1990; Im et al., 2003), technophiles vs "normal" people, and business vs consumer users. Further, considerable effort has gone into studying the influence of members of the first group on the second. This paper focuses on when, if ever, it makes sense for a manufacture of a new product to "seed" the market by subsidizing a few early adopters to speed the adoption process. The paper builds on earlier work by Kalish and Lilien (1983) which focused on the impact of widely available government subsidies on the adoption of socially desirable innovations (i.e. alternative energy sources) as well as the work of Jain et al. (1995). Unlike that work, we concentrate on providing subsidies (here free goods) to selective individuals in the context of a model which allows for separate segments of innovators and imitators and nests the standard Bass (1969) model. ; Publicado

In this work, we develop a new model for competition in markets with differentiated products. In addition, we present a consumer model designed to produce a flexible nonlinear inverse demand system that resembles the classical Multinomial Logit model, and discuss several extensions. We characterize firms competition in quantities based on the inverse demand system. The model is applied to the Spanish newspaper industry. This is a highly competitive two-sided market whose revenues are generated from sales and to a larger extent from advertising driven by its circulation. We then characterize the Perfect Equilibrium by conditional moment conditions, and estimate the parameters using the Generalized Method of Moments ; Research funded by two research projects, S-0505/TIC-0230 by the Comunidad de Madrid and ECO20011-30198 by MICINN agency of Spanish Government

Historically US Media channels have competed to attract advertising expenditure from marketing. This has been a fierce battle, where, every few years, incumbents have been shattered by the introduction of a new media such as TV, Yellow Pages, Cable and the Internet. In this paper we will analyze and discuss the dynamic trend in advertising expenditure for ten different advertising media channels in the U.S., by estimating the long-term equilibrium between these time series, and their equilibrium cross-elasticities. We will also analyze how they are related to the business cycle, both at the aggregated level and specifically for each media. To this end, it is crucial to consider simultaneously the impact of new media introductions over the incumbents, estimating the potential effects of structural changes. Both, the introduction effects and the long-term equilibrium relationship between two media can be very different. In particular, we will study the influence of the Internet ; Research funded by two research projects, S-0505/TIC-0230 by the Comunidad de Madrid and ECO2011-30198 by MICINN agency of Spanish Government

The quality of Conjoint Analysis estimations heavily depends on the alternatives presented in the experiment. An efficient selection of the experiment design matrix allows more information to be elicited about consumer preferences from a small number of questions, thus reducing experimental cost and respondent's fatigue. The statistical literature considers optimal design algorithms (Kiefer, 1959), and typically selects the same combination of stimuli more than once. However in the context of conjoint analysis, replications do not make sense for individual respondents. In this paper we present a general approach to compute optimal designs for conjoint experiments in a variety of scenarios and methodologies: continuous, discrete and mixed attributes types, customer panels with random effects, and quantile regression models. We do not compute good designs, but the best ones according to the size (determinant or trace) of the information matrix of the associated estimators without repeating profiles as in Kiefer's methodology. We handle efficient optimization algorithms to achieve our goal, avoiding the use of widespread ad-hoc intuitive rules. ; Research funded by two research projects, S-0505/TIC-0230 by the Comunidad de Madrid and ECO2011-30198 by MICINN agency of Spanish Government

Customer Relationship Management generally uses the value of customers to allocate marketing budget. But marketing interventions generally change the customer behavior, turning upside-down the customers ranking based on their initial valuations and making the budget allocation suboptimal. Rational Managers should allocate the marketing budget to maximize the expected net present value of future profits drawn from each customer, simultaneously planning mass marketing interventions and direct marketing effort on each individual. This is a large dimensional Stochastic Dynamic Program, which cannot be easily solved due to the curse of dimensionality. This paper propose a new decomposition algorithm to alleviate the curse of dimensionality in SDP problems, which allows forward-looking firms to allocate the marketing budget optimizing the CLV of their customer base, simultaneously using customized and mass marketing interventions ; Research funded by two research projects, S-0505/TIC-0230 by the Comunidad de Madrid and ECO20011-30198 by MICINN agency of Spanish Government

Sales uncertainty is a central problem for marketing management. Marketers tend to focus on expected sales, rather than short-term time-varying oscillations. With long supply-chain streams, the Bullwhip effect can turn retail sales volatility into a major problem for upstream companies. While it has been recognized that conditional expected sales change through time (for a review see Dekimpe and Hanssens, 2000), marketers have not yet started to modeling explicitly time variation of sales' conditional variances. In this paper we focus on this issue, modeling and forecasting time-varying retail sales and marketing mix volatility and their crossed effects within brand, and between competitive brands. We analyze up to 6 product categories sold by Dominick's Finer Foods, finding volatility and co-volatilities in all of them. We discuss managerial implications for brand management and competitive strategy ; Research funded by two research projects, by the Comunidad de Madrid and the Spanish Government

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. ; Research funded by two research projects, by the Comunidad de Madrid and the Spanish Government

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. ; Research funded by two research projects, by the Comunidad de Madrid and the Spanish Government

Display advertising is traded in a complex market with multiple sides and intermediaries, where advertisers are exposed to several forms of potentially fraudulent behavior. Intermediaries often claim to implement measures to detect fraud but provide limited information about those measures. Advertisers are required to trust that self-regulation efforts effectively filter out low-quality ad impressions. In this article, we propose an approach for tracking key display impression metrics by embedding a light JavaScript code in the ad to collect the necessary information to help detect fraudulent activities. We explain these metrics using the campaign cost per thousand (CPT) and the number of impressions per publisher. We test the approach through six display ad campaigns. Our results provide a counterargument against the industry claim that it is effectively filtering out display fraud and show the utility of our approach for advertisers. ; This work is partly supported by the European Union through SMOOTH (786741) and PIMCITY (871370); the European Social Fund through Ramón y Cajal (RYC-2015-17732); and the Spanish Ministry of Economy and Competitiveness through ECO2015-67763-R and PGC2018-096083-B-I00 projects.