The role of consumer networks in firms' multi-characteristics competition and market-share inequality

We develop a location analysis spatial model of firms' competition in multi-characteristics space, where consumers' opinions about the firms' products are distributed on multilayered networks. Firms do not compete on price but only on location upon the products' multi-characteristics space, and they aim to attract the maximum number of consumers. Boundedly rational consumers have distinct ideal points/tastes over the possible available firm locations but, crucially, they are affected by the opinions of their neighbors. Proposing a dynamic agent-based analysis on firms' location choice we characterize multi-dimensional product differentiation competition as adaptive learning by firms' managers and we argue that such a complex systems approach advances the analysis in alternative ways, beyond game-theoretic calculations.Comment: 33 pages, 5 figure

The role of networks in firms’ multi-characteristics competition and market-share inequality

We develop a location analysis spatial model of firms’ competition in multi-characteristics space, where consumers’ opinions about the firms’ products are distributed on multilayered networks. Firms do not compete on price but only on location upon the products’ multi-characteristics space, and they aim to attract the maximum number of consumers. Boundedly rational consumers have distinct ideal points/tastes over the possible available firm locations but, crucially, they are affected by the opinions of their neighbors. Our central argument is that the consolidation of a dense underlying consumers’ opinion network is the key for the firm to enlarge its market-share. Proposing a dynamic agent-based analysis on firms’ location choice we characterize multi-dimensional product differentiation competition as adaptive learning by firms’ managers and we argue that such a complex systems approach advances the analysis in alternative ways, beyond game-theoretic calculations

The role of networks in firms’ multi-characteristics competition and market-share inequality

We develop a location analysis spatial model of firms’ competition in multi-characteristics space, where consumers’ opinions about the firms’ products are distributed on multilayered networks. Firms do not compete on price but only on location upon the products’ multi-characteristics space, and they aim to attract the maximum number of consumers. Boundedly rational consumers have distinct ideal points/tastes over the possible available firm locations but, crucially, they are affected by the opinions of their neighbors. Our central argument is that the consolidation of a dense underlying consumers’ opinion network is the key for the firm to enlarge its market-share. Proposing a dynamic agent-based analysis on firms’ location choice we characterize multi-dimensional product differentiation competition as adaptive learning by firms’ managers and we argue that such a complex systems approach advances the analysis in alternative ways, beyond game-theoretic calculations

Information Diffusion on Social Networks

In this thesis we model the diffusion of information on social networks. A game played on a specific type of graph generator, the iterated local transitivity model, is examined. We study how the dynamics of the game change as the graph grows, and the relationship between properties of the game on a graph initially and properties of the game later in the graph’s development. We show that, given certain conditions, for the iterated local transitivity model it is possible to predict the existence of a Nash equilibrium at any point in the graph’s growth. We give sufficient conditions for the existence of Nash Equilibria on star graphs, cliques and trees. We give some results on potential games on the iterated local transitivity model. Chapter 2 provides an introduction to graph properties, and describes various early graph models. Chapter 3 describes some models for online social networks, and introduces the iterated local transitivity model which we use later in the thesis. In Chapter 4 various models for games played on networks are examined. We study a model for competitive information diffusion on star graphs, cliques and trees, and we provide conditions for the existence of Nash Equilibria on these. This model for competitive information diffusion is studied in detail for the iterated local transitivity model in Chapter 5. We discuss potential games in Chapter 6 and their existence on the iterated local transitivity model. We conclude with some suggestions on how to extend and develop upon the work done in this thesis