Material Selection in Green Design: A Method Combining DEA and TOPSIS

In order to rationalize material selection in green design, this study presents an attempt to combine the methods of generalized Data Envelopment Analysis (DEA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By establishing a green material index system, the G-CCR model of generalized DEA was first used to select effective materials from the candidate samples, and TOPSIS was then used to sort the effective suppliers. The combined DEA/TOPSIS model helps to rank the materials by quality, and then integrate both the merits ofG-CCR model and the key characteristics of TOPSIS. The results of this study showed that the combined DEA/TOPSIS model can screen and exclude materials with poor performance when selecting wood for the furniture industry. Therefore, the combined model that is presented in this study provides a more rational and evidentiary basis for material selection in green design.

Efficiency Aggregation in Generalized Network Data Envelopment Analysis with Slacks-Based Measure Based on Sample Units

By using sample units (SUs), the generalized data envelopment analysis (DEA) method can evaluate the efficiency of decision making unit (DMU) through different reference sets, but the existing models are radial models, and the DMU is treated as a black box, rarely taking the operations of the internal divisions into account. This paper proposes a generalized network slacks-based measure (SBM) approach based on the SUs. First, the generalized network SBM approach for a basic two-stage structure is proposed. This paper considers the intermediate products in calculating the divisional efficiency for each DMU. Overall efficiency of DMU is a weighted average of the divisional efficiency. The weight of each division does not need to be given in advance. Since the DMUs set and SUs set are not necessarily the same, this paper proposes an improved generalized network SBM approach for a basic two-stage structure to solve the problem that the original model may be infeasible. Then, the approach for basic two-stage structure is extended to general multi-stage structure. Finally, an example is given to show the practicability of the generalized network SBM approach.

A Computation Methods for Analysis on the Effect of Stock Market and its Application

As a barometer of the macroeconomic of a country and an important part of the capital market, stock market has attracted increasing and highlighted attention. As is well-known, Chinese stock market is known as 'policy market', however, the issue about whether the stock market is really influenced by these policies is always an important and hot topic. In this paper, by using generalized data envelopment analysis, an analysis on the effect of the new policies carried out in May 2012 is provided based on closing price, Tobin Q, circulation market value, turnover rate, and return on assets. Based on the above results, it can show the effect of stock market policies on Chinese Economy.