  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.
