Open Access to Telecommunications Infrastructure and Digital Services: Competition, Cooperation and Regulation

Open Access, defined as the non-discriminatory access to an upstream bottleneck resource, takes a central role in information and communications technology markets. This thesis investigates the competitive and cooperative interactions in these markets, where firms require access to an essential input resource. Theoretical analyses and experimental evaluations are employed to examine market outcomes under alternative regulatory institutions and voluntary access agreements

Research trends in customer churn prediction: A data mining approach

This study aims to present a very recent literature review on customer churn prediction based on 40 relevant articles published between 2010 and June 2020. For searching the literature, the 40 most relevant articles according to Google Scholar ranking were selected and collected. Then, each of the articles were scrutinized according to six main dimensions: Reference; Areas of Research; Main Goal; Dataset; Techniques; outcomes. The research has proven that the most widely used data mining techniques are decision tree (DT), support vector machines (SVM) and Logistic Regression (LR). The process combined with the massive data accumulation in the telecom industry and the increasingly mature data mining technology motivates the development and application of customer churn model to predict the customer behavior. Therefore, the telecom company can effectively predict the churn of customers, and then avoid customer churn by taking measures such as reducing monthly fixed fees. The present literature review offers recent insights on customer churn prediction scientific literature, revealing research gaps, providing evidences on current trends and helping to understand how to develop accurate and efficient Marketing strategies. The most important finding is that artificial intelligence techniques are are obviously becoming more used in recent years for telecom customer churn prediction. Especially, artificial NN are outstandingly recognized as a competent prediction method. This is a relevant topic for journals related to other social sciences, such as Banking, and also telecom data make up an outstanding source for developing novel prediction modeling techniques. Thus, this study can lead to recommendations for future customer churn prediction improvement, in addition to providing an overview of current research trends.info:eu-repo/semantics/acceptedVersio

Stability and chaos of the duopoly model of Kopel: A study based on symbolic computations

Since Kopel's duopoly model was proposed about three decades ago, there are almost no analytical results on the equilibria and their stability in the asymmetric case. The first objective of our study is to fill this gap. This paper analyzes the asymmetric duopoly model of Kopel analytically by using several tools based on symbolic computations. We discuss the possibility of the existence of multiple positive equilibria and establish necessary and sufficient conditions for a given number of positive equilibria to exist. The possible positions of the equilibria in Kopel's model are also explored. Furthermore, if the duopolists adopt the best response reactions or homogeneous adaptive expectations, we establish rigorous conditions for the existence of distinct numbers of positive equilibria for the first time. The occurrence of chaos in Kopel's model seems to be supported by observations through numerical simulations, which, however, is challenging to prove rigorously. The second objective is to prove the existence of snapback repellers in Kopel's map, which implies the existence of chaos in the sense of Li-Yorke according to Marotto's theorem.Comment: arXiv admin note: substantial text overlap with arXiv:2301.1262

Marketing Modeling for New Products

This thesis addresses the analysis of new or very recent marketing data and the introduction of new marketing models. We present a collection of models that are useful to analyze (1) the optimal launch time of new and dominant technologies, (2) the triggers, speed and timing of new products’ price landings, (3) the consumer heterogeneity that drives substitution patterns present in aggregate data, and (4) the influential locations that drive the diffusion of new technologies. The econometric approaches that we apply are diverse but they are predominantly Bayesian methods. We use Bayesian mixture modelling, Bayesian variable selection techniques, Bayesian spatial models and we put forward a new Bayesian approach for the random coefficient logit model. The data that we analyze consist of unique and large datasets of video-game prices, video-game consoles’ sales, aggregate sales data for consumer products and Google’s online search data