Title: Business strategies in Darknet marketplaces. Subtitle: An attempt to model competition in the framework of Economic Complexity.

What are the sources of competitive advantages of vendors in an economy of purely rational and anonymous agents? Hereafter, throughout to the case study of Darknet markets, we attempt to develop a new model of competitive advantage that brings together knowledge of strategic management and economic complexity theories. Over the last five years, researches in the field of Darknet marketplaces have been started and a partial light has been shed over the mystery of the illegal e-commerce. Ultimately, as a first approximation, a Darknet market can be defined as a virtual tripartite network of anonymous vendors, products and customers. In this context, the Darknet market constitutes a good approximation of an economy of purely rational and anonymous agents, with limited contacts and relationships, based only on economic exchange. In other words, the first approximation of a "textbook economy". Given such a general opportunity, it is legitim to question if is it possible to develop an economy of agents who do not directly trust and know each other? Moreover, if it's that the case, what are the attributes that make some vendors develop a competitive advantage despite their anonymity? In this Master's Thesis, we indagate such questions through an innovative methodology that merges together literature of strategic management and economic complexity theories. Barney’s model of sustained competitive advantage states that different vendors in the same market can reach different performance levels and that these differences in performance are driven by the resources that vendors possess. More in details, we show that these ideas at the vendor level closely align with Hidalgo & Haussman’s theory of capabilities, which considers the set of different products as the source of competitive power at the national level. Hence, reshaping Barney’s model into the Hidalgo & Haussman theory of capabilities, we are able to propose an analysis of our Darknet dataset, and more generally, of our "textbook economy”. Starting from these arguments, in order to tackle the analysis quantitatively, we developed a generalization of the Fitness-Complexity Algorithm of Pietronero et al. Namely, we proposed a new metric over a tripartite network of vendors, products, and customers, that considers the ability to diversify over a heterogeneous set of customers as the ultimate resource of vendors’ competitiveness. Results show a clear correlation between the so-defined vendors'fitness and the vendors' revenues, in support of the informativeness of the new metric. Concluding, we attempted to describe the sources of competitive advantages of a general textbook economy, throughout the case study of Darknet markets. In order to do so, we connected literature of strategic management and economic complexity and we introduced a successful tripartite generalization of the Fitness-Complexity Algorithm which quantifies the competitiveness of vendors. Our contribution is thus twofold: not only we have successfully analyzed the strategic dynamics of vendors in the Darknet markets, but, starting from this stimulus we have been able to develop a broader approach that enlarges the applicability of the economic complexity theories to an individual level, and, potentially, could successfully uncover this fitter-gets-richer phenomenon in many other tripartite competitive systems.