Boundary decisions of the firm: make, buy, cooperate

Firms are not atomistic hierarchies only linked with one another at arm’s-length distance in markets. Instead, a myriad of long-lived, highly cooperative relationships between suppliers and customers are pervasively found in the B2B world. And it is within those enmeshed relationships and networks that the co-evolution of capabilities and business specialisms is brought about and developed. If that is the actual ‘topography’ of the business landscape, then the coordination of economic activities in general, and the boundary decisions of each and every firm in particular, are unlikely to be reduced to a (dual) choice between ‘making’ or ‘buying’. Inter-firm cooperation is in itself a third governance structure, in alternative to the hierarchical and the market modes of coordination. And, what is also equally important to note, it is through the make-or-buy-or-cooperate decisions that the (embedded) firm is able to change its nature and scope, redefine its (fuzzy) boundaries, and thus adapt to an ever-changing business setting.

Markets-as-networks theory: a review

This paper exposes the development of markets-as-networks theory from formal inception in the mid-1970s until 2010 state-of-the-art, en route presenting its historical roots. This largely European-based theory challenges the conventional, dichotomous view of the business world as including firms and markets, arguing for the existence of relational governance structures (the so-called ‘‘interfirm cooperation’’) in addition to hierarchical and transactional ones.

Using Neo4J geospatial data storage and integration

Online geographic-databases have been growing increasingly as they have become a crucial source of information for both social networks and safety-critical systems. Since the quality of such applications is largely related to the richness and completeness of their data, it becomes imperative to develop adaptable and persistent storage systems, able to make use of several sources of information as well as enabling the fastest possible response from them. This work will create a shared and extensible geographic model, able to retrieve and store information from the major spatial sources available. A geographic-based system also has very high requirements in terms of scalability, computational power and domain complexity, causing several difficulties for a traditional relational database as the number of results increases. NoSQL systems provide valuable advantages for this scenario, in particular graph databases which are capable of modeling vast amounts of inter-connected data while providing a very substantial increase of performance for several spatial requests, such as finding shortestpath routes and performing relationship lookups with high concurrency. In this work, we will analyze the current state of geographic information systems and develop a unified geographic model, named GeoPlace Explorer (GE). GE is able to import and store spatial data from several online sources at a symbolic level in both a relational and a graph databases, where several stress tests were performed in order to find the advantages and disadvantages of each database paradigm.