This paper presents an integrated set of innovation taxonomies for firms and sectors. It discards the practice of representing industries by some average behaviour, instead characterising them by the distribution of diverse innovation modes at the firm level. The theoretical focus is on (i)...

Statistical cluster techniques are applied in the development of two new taxonomies of manufacturing industries. The first focuses on the distinction between exogenous, location dependent comparative cost advantages, such as the relative abundance of capital or labour, and endogenously created...

Much emphasis on the sectoral perspective in economics originates in the observation of the diverse and contingent nature of competitive behaviour, where a firm's performance depends on the capability to match its organisation and strategy to the technological, social and economic restrictions...

The problem of selecting a clustering algorithm from the myriad of algorithms has been discussed in recent years. Many researchers have attacked this problem by using the concept of admissibility (e.g. Fisher and Van Ness, 1971, Yadohisa, et al., 1999). We propose a new criterion called the...

This paper discusses the admissibility of agglomerative hierarchical clustering algorithms with respect to space distortion and monotonicity, as defined by Yadohisa et al. and Batagelj, respectively. Several admissibilities and their properties are given for selecting a clustering algorithm....