You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: Supply chain performance models: A literature review on approaches, techniques, and criteria 
Chapter Title:  Wong and Wong 
1. Abstract of Cited Paper (BIB001):  Purpose – The purpose of this paper is to investigate the efficiency levels of the decision‐making units within the public hospital laboratories in using their supply chain towards meeting the satisfaction of doctors.Design/methodology/approach – Data were collected from two senior laboratory administrators and 30 doctors of two hospital laboratories in Malaysia using two sets of structured questionnaires, which comprised of two dimensions, i.e. doctor satisfaction dimension (DSD) and supply chain inputs (SCI). The dimensions of DSD and SCI were developed and that SCI has been relabeled as hospital laboratory inputs (HLI) to suit the nature of current study. The resulting data were positioned on an importance‐performance matrix. By using the data envelopment analysis software, the efficient frontier for both hospital laboratories was calculated under different scenarios.Findings – Results reveal that one of the laboratories satisfies doctors efficiently using the present levels of HLI for each scenario wh... 
2. Abstract of Cited Paper (BIB002):  Supply chain (SC) performance evaluation is a complex decision-making problem involving various criteria under uncertainty situations. This paper studies the supply chain performance evaluation of a furniture manufacture industry in the southwest of China. We identify the main uncertainty factors affecting evaluation process, and then model and analyze them using our rough data envelopment analysis (RDEA) models. We create rough DEA by integrating classical DEA and rough set theory. The solution approach of rough DEA is discussed and employed to evaluate the supply chain network operation efficiency of the furniture manufacture industry. Then we give a practical example to illustrate the efficacy and efficiency of the rough DEA model and show how decision-making is improved by the insights the rough DEA model provides. 
3. Abstract of Cited Paper (BIB003):  Performance evaluation is of great importance for effective supply chain management. The foundation of efficiency evaluation is to faithfully identify the corresponding production possibility set. Although a lot of researches have been done on supply chain DEA models, the exact definition for supply chain production possibility set is still in absence. This paper defines two types of supply chain production possibility sets, which are proved to be equivalent to each other. Based upon the production possibility set, a supply chain CRS DEA model is advanced to appraise the overall technical efficiency of supply chains. The major advantage of the model lies on the fact that it can help to find out the most efficient production abilities in supply chains, by replacing or improving inefficient subsystems (supply chain members). The proposed model also directly identifies the benchmarking units for inefficient supply chains to improve their performance. A real case validates the reasonableness and acceptability of this approach.

Literature Review:
In another paper, gave motivation of using DEA in addressing supply chain benchmarking. The authors first reviewed problems in supply chain benchmarking, existing tools used in benchmarking, problems in existing tools and then justified that DEA can be used as a benchmarking tool for supply chain performance measurement. Abu BIB002 investigated the efficiency levels of the decision-making units within the public hospital laboratories in using their supply chain towards meeting the satisfaction of doctors. For this purpose DEA method was applied to monitor the performance of decision-making units with respect to doctors' satisfaction and determining areas and ways that warrant improvement. BIB004 considered that the performance of a supply chain is attributed to two main factors: the performances of all supply chain members, and the cooperation and harmony of its members. The authors defined two types of supply chain production possibility sets and based upon those, proposed a supply chain constant return to scale DEA model to appraise the overall technical efficiency of supply chains. BIB003 created rough DEA by integrating classical DEA and rough set theory for SC performance evaluation under uncertainty situations. In their paper, DEA is employed to evaluate the performance of supply chain. The authors addressed that the main virtue of DEA is that it can be used to measure efficiency when there are multiple inputs and outputs. To depict rough uncertain environment, the authors employed rough set theory proposed by Pawlak and rough variable proposed by BIB001 to deal with the rough uncertainty phenomena in real world. Parkan and Wang (2007) applied two non-parametric performance measurement methods, DEA and operational competitiveness rating analysis (OCRA), on the basis of the framework of  , to measure the performance of a supply chain over a number of time periods. These two performance measurement methods, DEA and OCRA, were used to aggregate the metric scores of a supply chain in a number of periods so as to obtain overall ratings that gauge the supply chain's relative overall performance during those periods.