Chapter 1 Estimating Directional Returns to Scale in DEA
1.1 Introduction
1.2 Classical RTS in DEA framework
1.3 Directional SE and directional RTS
1.4 Measurement of directional RTS
1.5 A case study
1.6 Conclusions
Chapter 2 Data Envelopment Analysis in the Absence of Convexity: Specifying Efficiency Status and Estimating Returns to Scale
2.1 Introduction
2.2 Preliminaries and literature review
2.3 Methodology
2.4 Most productive scale size
2.5 Illustrative examples
2.6 Conclusions and future extensions
Chapter 3 Institutional Change and Optimal Size of Universities
3.1 Introduction
3.2 Background and theory
3.3 Data and identification strategy
3.4 Results
3.5 Discussions and conclusions
Chapter 4 A Study on Directional Returns to Scale
4.1 Introduction
4.2 Methodology
4.3 Analysis of directional RTS and directional congestion effect
4.4 Conclusions and discussions
Chapter 5 Directional Congestion in the Framework of Data Envelopment Analysis
5.1 Introduction
5.2 Primary approaches to congestion measurement
5.3 Definitions of directional congestion
5.4 Measurement of directional congestion
5.5 A case study
5.6 Conclusions
Chapter 6 Integer Data in DEA: Illustrating the Drawbacks and Recognizing Congestion
6.1 Introduction
6.2 Classical congestion
6.3 Karimi et al.'s (2016) congestion approach
6.4 The drawbacks of the PEIC
6.5 Recognizing congestion with both negative and/or non-negative continuous and integer data
6.6 Graphical illustration of our proposed approach
6.7 Numerical example
6.8 Empirical application
6.9 Concluding remarks and possible extensions
Chapter 7 Negative Data in DEA: Recognizing Congestion and Specifying the Least and the Most Congested Decision-Making Units
7.1 Introduction
7.2 Implications of congestion and negative data in DEA
7.3 The proposed congestion approach
7.4 Specifying the strongly and weakly most congested DMUs in the presence of negative data
7.5 Ranking of the congested DMUs in the presence of negative data
7.6 Numerical example
7.7 Empirical application
7.8 Conclusions and future extensions
Chapter 8 Estimating Capacity Utilization of Chinese Manufacturing Industries
8.1 Introduction
8.2 Literature review
8.3 Methodology and indicators
8.4 Empirical results
8.5 Conclusions and discussions
Chapter 9 Measuring the Chinese Regional Production Potential Using A Generalized Capacity Utilization Indicator
9.1 Introduction
9.2 Literature review
9.3 Generalized capacity utilization indicator
9.4 Empirical study:Chinese regions
9.5 Conclusions and discussions
Chapter 10 Estimating Capacity Utilization of Chinese State Farms
10.1 Introduction
10.2 Literature review
10.3 Methodology
10.4 Results and policy implication
10.5 Conclusions
Chapter 11 Measuring the Capacity Utilization of the 48 Largest Iron and Steel Enterprises in China
11.1 Introduction
11.2 Literature review
11.3 Notation and models
11.4 Dataset and input and output variables
11.5 Empirical results
11.6 Conclusions and discussions
