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.

Statistical modelling of extreme rainfall in Madeira Island

Extreme rainfall events have triggered a significant number of flash floods in Madeira Island along its past and recent history. Madeira is a volcanic island where the spatial rainfall distribution is strongly affected by its rugged topography. In this thesis, annual maximum of daily rainfall data from 25 rain gauge stations located in Madeira Island were modelled by the generalised extreme value distribution. Also, the hypothesis of a Gumbel distribution was tested by two methods and the existence of a linear trend in both distributions parameters was analysed. Estimates for the 50– and 100–year return levels were also obtained. Still in an univariate context, the assumption that a distribution function belongs to the domain of attraction of an extreme value distribution for monthly maximum rainfall data was tested for the rainy season. The available data was then analysed in order to find the most suitable domain of attraction for the sampled distribution. In a different approach, a search for thresholds was also performed for daily rainfall values through a graphical analysis. In a multivariate context, a study was made on the dependence between extreme rainfall values from the considered stations based on Kendall’s τ measure. This study suggests the influence of factors such as altitude, slope orientation, distance between stations and their proximity of the sea on the spatial distribution of extreme rainfall. Groups of three pairwise associated stations were also obtained and an adjustment was made to a family of extreme value copulas involving the Marshall–Olkin family, whose parameters can be written as a function of Kendall’s τ association measures of the obtained pairs.