Essays on Networks and Firm Relations
This dissertation contains three essays that study relationships among firms. Firms connect to each other via direct and indirect relationships. A network describes these relationships as linkages among firms. This dissertation empirically studies the roles of firms in networks, in particular the incentives firms face when forming linkages with each other.
Chapter 1 studies the structure of supplier-buyer networks of U.S. tech firms from 2003 to 2014. For each year, a supplier-buyer network describes which firms supply to which firms, and equivalently, which firms buy from which firms. I identify four firms - Apple, Dell, IBM, and Microsoft - as the most significant firms in the supplier-buyer networks. Using a community detection method, I find that these four firms each belongs to a different community of firms, indicating that they are closely linked to distinct groups of firms. On the other hand, the four communities, each associated with one of the four firms, are composed of firms in similar industry sectors. These suggest that there exists a certain degree of exclusivity in supplier-buyer relationships of the four firms. Moreover, I rank their significance in the network using measures of centrality and modular centrality, where the latter accounts for the community structure. I find that IBM was by far the most significant firm, both as a supplier and a buyer, until 2010. However, the centrality of Microsoft grew and surpassed IBM in 2014. Furthermore, the growth of Apple's centrality over the years is remarkable.
Chapter 2 describes the relationships among U.S. credit card issuers, hotel chains, and airlines. These firms operate loyalty programs, in which customers may earn points by making purchases. Moreover, they form partnerships with other firms so that the points can be transferred to the loyalty programs of partner firms. Via such transfer partnerships, customers may redeem the points for not only the goods and services offered by the firm but also those offered by the partner firms. Thus, the set of partners possessed by a firm is an important marketing tool, and it has an incentive to form partnerships with a select set of firms, as a means of competition. Chapter 2 also describes the data collection procedure, which contains annual observations on transfer partnerships among 3 credit card issuers, 7 hotel chains, and 43 airlines and quarterly observations on their firm-level characteristics from 2014 to 2018.
Chapter 3 utilizes the aforementioned data set to study the formation of transfer partnerships. After describing transfer partnerships among firms as a directed network, I exploit variations in transfer partnerships and characteristics of firms over time to study how major U.S. credit card issuers choose their airline partners. Partnerships between credit card issuers and hotel chains and partnerships among airlines are taken as given because these partnerships are typically determined by long-term contracts and hence little variation is observed in the data. Recognizing that characteristics of firms, the set of other partners possessed by a credit card issuer (i.e., complementarity of potential partnership to existing set of partners), the set of partners possessed by its partner hotel chains (i.e., indirect partnerships), and the set of partners possessed by other credit card issuers (i.e., partnerships of competitors) may affect the choice of a partner, this chapter uses a sequential network formation model to describe the partnership formation process. A key feature is that the state of the network affects partnership formation. A difficulty is that the order of events - the timeline through which partnerships were formed, rejected, or modified - is not fully observed. I use Markov Chain Monte Carlo to sample the order of events and to estimate model parameters. The result indicates that a credit card issuer tends to favor an airline partner that complements its other airline partners, is a partner of another credit card issuer, and is a partner of its hotel chain partner.