A Mathematical Approach to Supply Complexity Management Efficiency Evaluation for Supply Chain

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This study investigates the difference in service efficiency based on establishing entity and outsourcing in 847 public libraries in Korea. The public libraries were categorized into three types based on establishing entity and outsourcing, where Type 1 libraries are those established and directly managed by the Office of Education under the central government, Type 2 libraries are established and directly managed by local governments, and Type 3 libraries are established by local governments and their operations are outsourced. Each library type was analyzed and compared using data envelopment analysis (DEA), and results found that public libraries established by local governments are more efficient than those established by the central government, while outsourcing operations improved the efficiency of public libraries. Further analysis of the projection point and excess quantity of input showed that the main cause of inefficiency for Type 1 libraries is the library area, and for Types 2 and 3, the number of periodicals. This study provides guidelines for the sustainable performance of public library services based on the factors of foundation and operational patterns.

Section: Efficiency Scorementioning

confidence: 99%

Efficiency Analysis of Public Library Services Based on Establishing Entity and Outsourcing

Kim

Choi

2020

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“…Data envelopment analysis (DEA) makes use of linear programming to analyze the relative efficiency within a specific group, and has been applied in various areas of study since its introduction by Charnes et al [23]. Charnes et al [23] delineated that the ratio of the weighted sum outputs to the weighted sum of inputs of each decision-making unit (DMU) for evaluation cannot exceed 1, and defined DEA as a linear programming technique that aims to maximize the ratio of the weighted sum of outputs, assuming the condition that the weights of each input and output factor are greater than 0 [24]. The degree of inefficiency in the input-to-output ratio is most commonly analyzed in terms of ranking using the Charnes-Cooper-Rhodes (CCR) model or the further-developed Banker-Charnes-Cooper (BCC) model.…”

Section: Data Envelopment Analysis and Malmquist Indexmentioning

confidence: 99%

Do Shifts in Renewable Energy Operation Policy Affect Efficiency: Korea’s Shift from FIT to RPS and Its Results

Park

Kim

2018

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South Korea's new and renewable energy (NRE) policy experienced a drastic shift from the Feed-in Tariff (FIT) to the Renewable Portfolio Standard (RPS) in 2012. This study looks at the changes in the efficiency of NRE policy in this transition through DEA (Data Envelopment Analysis) and MI (Malmquist Index) methods, using investment for NRE technology development and for NRE dissemination as input factors and the number of firms, the number of employees, and the volume of NRE power generation as output factors. The results show a temporary drop in efficiency in 2012 during the transition period for the NRE industry as a whole. However, apart from those energy types with ulterior factors, the implementation of RPS increased the technical change (TC) of most NRE types. Furthermore, the findings highlight that, among South Korea's three focal NRE industries-photovoltaic, wind power, and fuel cell energies-only fuel cell energies showed an increase in efficiency over time. South Korea's policy shifts from FIT to RPS and the resulting effects on NRE policy's efficiency provide a useful reference and guideline for government decision-making on NRE policy changes.

“…The process to estimate the efficiency of the BCC model using bootstrap DEA follows that outlined by Simar and Wilson [41] and Kim and Kim [43]:…”

Section: Bootstrap Deamentioning

confidence: 99%

Driving Sustainable Competitive Advantage in the Mobile Industry: Evidence from U.S. Wireless Carriers

Kim¹,

Kim²,

Kang³

2016

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Abstract:In light of the growing importance of data network quality in the wireless industry, this study analyzes and compares efficiencies in management, service quality, network quality, and market in the 4G Long Term Evolution (LTE) wireless industry. For this purpose, a bootstrap data envelopment analysis (DEA) model using representative U.S. wireless carriers as decision making units (DMUs) was designed and conducted, with further verification through the Mann-Whitney U and Wilcoxon W test, to examine the differences in efficiency distribution. The results indicate that, in terms of efficiency distribution, network quality efficiency and market efficiency belongs to the same group as that which has high management efficiency. Based on these results, this paper suggests implications and strategic guidelines for wireless carriers for improvement in management efficiency.