Developing a system for assessing the costs associated with different procurement routes in the construction industry

In developing techniques for monitoring the costs associated with different procurement routes, the central task is disentangling the various project costs incurred by organizations taking part in construction projects. While all firms are familiar with the need to analyse their own costs, it is unusual to apply the same kind of analysis to projects. The purpose of this research is to examine the claims that new ways of working such as strategic alliancing and partnering bring positive business benefits. This requires that costs associated with marketing, estimating, pricing, negotiation of terms, monitoring of performance and enforcement of contract are collected for a cross-section of projects under differing arrangements, and from those in the supply chain from clients to consultants, contractors, sub-contractors and suppliers. Collaboration with industrial partners forms the basis for developing a research instrument, based on time sheets, which will be relevant for all those taking part in the work. The signs are that costs associated with tendering are highly variable, 1-15%, depending upon what precisely is taken into account. The research to date reveals that there are mechanisms for measuring the costs of transactions and these will generate useful data for subsequent analysis.

Developing a system for assessing the costs associated with different procurement routes in the construction industry

In developing techniques for monitoring the costs associated with different procurement routes, the central task is disentangling the various project costs incurred by organizations taking part in construction projects. While all firms are familiar with the need to analyse their own costs, it is unusual to apply the same kind of analysis to projects. The purpose of this research is to examine the claims that new, ways of working such as strategic alliancing and partnering bring positive business benefits. This requires that costs associated with marketing, estimating, pricing, negotiation of terms, monitoring of performance and enforcement of contract are collected for a cross-section of projects under differing arrangements, and from those in the supply, chain from clients to consultants, contractors, subcontractors and suppliers. Collaboration with industrial partners forms the basis for developing a research instrument, bused on time sheets, which will be relevant for all those taking part in the work. The signs are that costs associated with,with tendering are highly variable, 1-15%, depending upon what precisely, is taken into account. The research to date reveals that there are mechanisms for measuring the costs of transactions and these will generate useful data for subsequent analysis.

Geoadditive models for regional count data: an application to industrial location

We propose a geoadditive negative binomial model (Geo-NB-GAM) for regional count data that allows us to address simultaneously some important methodological issues, such as spatial clustering, nonlinearities, and overdispersion. This model is applied to the study of location determinants of inward greenfield investments that occurred during 2003–2007 in 249 European regions. After presenting the data set and showing the presence of overdispersion and spatial clustering, we review the theoretical framework that motivates the choice of the location determinants included in the empirical model, and we highlight some reasons why the relationship between some of the covariates and the dependent variable might be nonlinear. The subsequent section first describes the solutions proposed by previous literature to tackle spatial clustering, nonlinearities, and overdispersion, and then presents the Geo-NB-GAM. The empirical analysis shows the good performance of Geo-NB-GAM. Notably, the inclusion of a geoadditive component (a smooth spatial trend surface) permits us to control for spatial unobserved heterogeneity that induces spatial clustering. Allowing for nonlinearities reveals, in keeping with theoretical predictions, that the positive effect of agglomeration economies fades as the density of economic activities reaches some threshold value. However, no matter how dense the economic activity becomes, our results suggest that congestion costs never overcome positive agglomeration externalities.