Entropic risk analysis by a high level decision support system (e-FDSS) for construction SMEs

The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects.

Factors affecting regional SMEs progression to Digital Business Ecosystems

SMEs are widely recognized as an important driving force of economic growth, yet, their uptake of ICT is still very low. Tosupport SMEs ICT adoption and to foster regional development, in 2000, the Lisbon Strategy on the Information Society andKnowledge-based economy created a vision for 2010 towards the creation of the European Digital Business Ecosystems(DBE). This paper is positioned within that context and reports upon a project involving 6000 SMEs whose aim was tosupport ICT adoption and to encourage SME networks through the creation of a Regional Business Portal. The papere xplores factors affecting the regional SMEs participating in the DBE. An in-depth longitudinal case study approach was adopted and multiple sources of evidence were used. Many factors affecting SMEs progression to DBE were identified:including people and organization, environmental, diffusion networks, technological, regional and time factors

Organic certification, export market access and the impacts of policy: Bayesian estimation of avocado smallholder “times-to-organic certification” in Michoacán Mexico

This study analyzes organic adoption decisions using a rich set of time-to-organic durations collected from avocado small-holders in Michoacán Mexico. We derive robust, intrasample predictions about the profiles of entry and exit within the conventional-versus-organic complex and we explore the sensitivity of these predictions to choice of functional form. The dynamic nature of the sample allows us to make retrospective predictions and we establish, precisely, the profile of organic entry had the respondents been availed optimal amounts of adoption-restraining resources. A fundamental problem in the dynamic adoption literature, hitherto unrecognized, is discussed and consequent extensions are suggested.

Catchment phosphorous losses: an export coefficient modelling approach with scenario analysis for water management

This paper presents the development of an export coefficient model to characterise the rates and sources of P export from land to water in four reservoir systems located in a semi-arid rural region in southern of Portugal. The model was developed to enable effective management of these important water resource systems under the EU Water Framework Directive. This is the first time such an approach has been fully adapted for the semi-arid systems typical of Mediterranean Europe. The sources of P loading delivered to each reservoir from its catchment were determined and scenario analysis was undertaken to predict the likely impact of catchment management strategies on the scale of rate of P loading delivered to each water body from its catchment. The results indicate the importance of farming and sewage treatment works/collective septic tanks discharges as the main contributors to the total diffuse and point source P loading delivered to the reservoirs, respectively. A reduction in the total P loading for all study areas would require control of farming practices and more efficient removal of P from human wastes prior to discharge to surface waters. The scenario analysis indicates a strategy based solely on reducing the agricultural P surplus may result in only a slow improvement in water quality, which would be unlikely to support the generation of good ecological status in reservoirs. The model application indicates that a reduction of P-inputs to the reservoirs should first focus on reducing P loading from sewage effluent discharges through the introduction of tertiary treatment (P-stripping) in all major residential areas. The fully calibrated export coefficient modelling approach transferred well to semi-arid regions, with the only significant limitation being the availability of suitable input data to drive the model. Further studies using this approach in semi-arid catchments are now needed to increase the knowledge of nutrient export behaviours in semi-arid regions.

Stream water quality and nutrient export in the Slapton Catchments

A weekly programme of water quality monitoring has been conducted by Slapton Ley Field Centre since 1970. Samples have been collected for the four main streams draining into Slapton Ley, from the Ley itself and from other sites within the catchment. On occasions, more frequent sampling has been undertaken during short-term research projects, usually in relation to nutrient export from the catchment. These water quality data, unparalleled in length for a series of small drainage basins in the British Isles, provide a unique resource for analysis of spatial and temporal variations in stream water quality within an agricultural area. Not surprisingly, given the eutrophic status of the Ley, most attention has focused on the nutrients nitrate and phosphate. A number of approaches to modelling nutrient loss have been attempted, including time series analysis and the application of nutrient export and physically-based models.