Bao Zhang, Chenpeng Feng, Min Yang, Jianhui Xie and Ya Chen
The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).
Abstract
Purpose
The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).
Design/methodology/approach
Existing studies extend traditional DEA by handling bounded and discrete data based on envelopment models. However, value judgment is usually neglected and fail to be incorporated in these envelopment models. In many cases, there is a need for prior preferences. Using existing DEA approaches as a backdrop, the current paper presents a methodology for incorporating assurance region (AR) restrictions into DEA with bounded and discrete data, i.e. the assurance region bounded discrete (AR-BD) DEA model. Then, the AR-BD DEA model is combined with a context-dependent DEA to obtain an efficiency stratification.
Findings
The authors examine different AR restrictions and calculate efficiency scores of five scenarios of AR restrictions by using the proposed AR-BD DEA model. It shows that AR restrictions have a great impact on the efficiency scores. The authors also identify nine efficient frontiers in total. For each decision-making unit, it could set benchmarks and improve its performance based on each higher efficient frontier.
Originality/value
This paper first evaluates efficiency of gear shaping machines by considering different (bounded and discrete) variable types of data and including AR restrictions. The AR-BD DEA model and context-dependent AR-BD DEA model proposed in this paper further enrich the DEA theory. The findings in this paper certainly provide useful information for both producers and consumers to make smart decisions.
Details
Keywords
Ning Zhang, Xu Haoran, Feng Jiang, Dawei Wang, Peng Chen and Qing Zhang
Based on the theoretical viewpoints of criminal geography and environmental criminology, this research uses spatial multi-criteria decision-making methods. In the process of…
Abstract
Purpose
Based on the theoretical viewpoints of criminal geography and environmental criminology, this research uses spatial multi-criteria decision-making methods. In the process of spatial decision-making and optimization of police resources, researchers fully consider the dynamic application of Geographic Information System (GIS) and the effects of spatial prevention and control.
Design/methodology/approach
Researchers use an integrated method combining Policing Geographic Information System (PGIS) and multi-criteria decision analysis (MCDA). On the one hand, police GIS has an excellent visual data analysis platform and integrated decision support system in data management, spatial analysis, data exploration and regression analysis. On the other hand, through the design of the indicator system, the quantification of indicators, the determination of weights, comprehensive evaluation and sensitivity analysis, MCDA can select the best plan from a large number of alternatives. When joining MCDA, the spatial dimension will bring the research results closer to the real world.
Findings
The study finds that the crime of burglary is affected to a certain extent by the distribution of police forces, the location of police units. Another important finding of this research is the correlation between more precise preventive measures and the crime of burglary.
Originality/value
From a practical point of view, this research would help advance the role of police units and law enforcement agencies in preventing burglary crimes and provide experience for the allocation of regional police resources.