A decision support model for the selection of nanotechnology with good performance and necessity

Nanotechnologies are being developed rapidly and driving economic growth. Among so many nanotechnology alternatives, selecting a nanotechnology with good performance and necessity is important and difficult. In this study, we propose a decision support model composed of AHP/DEA-AR(analytic hierarchy process/data envelopment analysis-assurance region) and AHP(analytic hierarchy process)rating method to evaluate nanotechnologies accurately and systematically. The proposed model evaluates performance of nanotechnology alternatives by AHP/DEA-AR and necessity of nanotechnology alternatives by AHP rating method, and calculates each alternative's combined score by adding each alternative's performance value and necessity value. The alternative with the highest combined score is selected as nanotechnology with good performance and necessity. In this study, we select 6 criteria for selecting nanotechnology with good performance and necessity. Experts rate nanotechnology alternatives in terms of the 6 criteria. The 6 criteria are classified as criteria for performance and criteria for necessity, R&D capability, ease of production, marketability and technical extension are criteria for performance. Urgency and government support are criteria for necessity. To evaluate the performance of nanotechnology alternatives, we normalize the ratings to criteria for performance first,then, we use AHP pairwise comparison to set AR (assurance region) for using DEA-AR. After setting AR, we employ DEA-AR to evaluate performance of nanotechnololgy alternatives. The evaluation result is performance value (DEA score). To assess the necessity of nanotechnology alternatives, we use AHP rating method instead of AHP pairwise comparison, because the number of alternatives is large, so the pairwise comparison is impracticable. The assessment result is necessity value (AHP score). We add a nanotechnology alternative's DEA score and AHP score to get the alternative's combined score. After calculating each nanotechnology alternative's combined score, we rank the combined scores from the largest to lowest. At last, we select the nanotechnology alternative with the highest combined score as the nanotechnology with good performance and necessity. A case of nanotechnology is used to illustrate the proposed model. The result shows that the proposed model provides a systematical and objective evaluation to alternatives and is a reasonable method for nanotechnology selection.