scholarly journals Efficiency Evaluation for Smart Grid Management Based on Stochastic Frontier Model and Data Envelope Analyses Model

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Yu Xiaobao ◽  
Tan Zhongfu ◽  
Chen Kangting ◽  
Ju Liwei ◽  
He Puyu
Keyword(s):  
Smart Grid ◽  
Information Needs ◽  
Evaluation Model ◽  
Stochastic Frontier ◽  
Allocative Efficiency ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Stochastic Frontier Model ◽  
Influence Parameter

For the technical and allocative efficiency evaluation of smart grid, this paper has proposed two methods. One is based on Data Envelopment Analysis and another is based on Stochastic Frontier Model. Among them, the former considered the dynamics of smart grid development and development dynamics is the influence parameter. The latter analyzed self-duality between the Cobb-Douglas production function and cost function; then, it deduced the smart grid resources optimization allocative efficiency evaluation model which can avoid price information needs of input factor in conventional allocative efficiency evaluation. The validity and rationality of the two methods are verified by a case study.

scholarly journals Efficiency Analysis of Lignite Mining Operations Using Production Stochastic Frontier Modeling

Mining ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 100-111
Author(s):  
Ioannis E. Tsolas
Keyword(s):  
Environmental Performance ◽  
Stochastic Frontier ◽  
Data Envelopment ◽  
Significant Determinant ◽  
Mining Operations ◽  
Public Power ◽  
Lignite Mining ◽  
Long Period ◽  
Lignite Mine

This paper proposes a stochastic frontier model for measuring both technical and environmental performance at the mine level by using a translog production function. The Kardia Field opencast lignite mine of the Greek Public Power Corporation (PPC), S.A. is the topic of the case study. Efficiency ratings are derived over a long period of time using annual operating data, and in addition, the determinants of inefficiency are established by means of the technical inefficiency effects model. In the light of the results, there is a strong correlation between technical and environmental efficiency; the results are validated by those produced by data envelopment analysis (DEA). In addition, the stripping ratio is identified as the statistically significant determinant of performance. The proposed framework could be used as an instrument to measure the efficiency of lignite mining operations and to identify the drivers of performance.

scholarly journals Evaluation of the technical efficiency in the production of National Cocoa in the main cantons of the province of Guayas

2021 ◽  
Vol 25 (110) ◽  
pp. 14-22
Author(s):  
Martha Bucaram Levarone ◽  
Francisco Quinde Rosales ◽  
Joy Mayorga Ramos ◽  
Martha Bueno Quinonez
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Stochastic Frontier ◽  
Allocative Efficiency ◽  
Productive Efficiency ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Frontier Analysis ◽  
Simon Bolivar ◽  
Non Parametric

A comparative analysis of the technical efficiency in the production of national cocoa among the main producing cantons of the province of Guayas was carried out. For this, the study was based on an analysis with inductive reasoning and empirical-analytical paradigm, through the elaboration of surveys to 361 UPA's in the cantons of: Milagro, San Jacinto de Yaguachi, El Empalme, Alfredo Baquerizo Moreno, Naranjal and Simón Bolívar; these data served as the basis for the elaboration of the Data Envelopment Analysis (DEA) model. The results show that on average, the Simón Bolívar canton is the canton with the highest technical efficiency, with 50% of the total UPAs surveyed in the range of 70% and 99% effectiveness. Finally, regarding the observed averages of allocative efficiency, it can be concluded that Jujan has the highest average with 75%. Keywords: Technical and Allocative Efficiency, National Cocoa, Enveloped Data Analysis, Non Parametric Method. References [1]M. Naranjo., «Un Puerto en busca de una Nación, Guayaquil y la idea fundacional del Ecuador como país,» de Seminario Internacional Poder, Política y Repertorios de la Movilización Social en el Ecuador Bicentenario, Quito, 2009. [2]S. C. Mogro, V. Andrade-Díaz y D. P.-. Villacís, «Posicionamiento y eficiencia del banano, cacao y flores del Ecuador en el mercado mundial,» Revista Ciencia UNEMI, vol. 9, nº 19, pp. 48-53, 2016. [3]M. Vassallo, Diferenciación y agregado de valor en la cadena ecuatoriana del cacao, Quito: Editorial IAEN, 2015. [4]M. Pigache y S. Bainville, Cacao tipo ‘Nacional’ vs. Cacao CCN51: ¿Quién ganará el partido?, Quito: Ird Editions, 2007. [5]M. Chiriboga, Jornaleros, grandes propietarios y exportación cacaotera, Quito: Universidad Andina Simón Bolívar, 2013. [6]A. Acosta., Breve Historia Económica del Ecuador, Quito: Editora Nacional, 2006. [7]M. Espinoza y Y. Arteaga., «Diagnóstico de los Procesos de Asociatividad y la Producción de Cacao en Milagro y sus sectores aledaños,» Revista Ciencia UNEMI, vol. 8, nº 14, pp. 105-112, 2015. [8]E. Romero, M. Fernández, J. Macías y K. Zúñiga, «Producción y comercialización del cacao y su incidencia en el desarrollo socioeconómico del cantón Milagro,» Revista Ciencia UNEMI, vol. 9, nº 17, pp. 56-64, 2016. [9]e. I. I. d. C. A. Ministerio de Agricultura y Ganadería, La Agroindustria en el Ecuador. Un diagnóstico integral, Quito: IICA, 2006. [10]R. Rodríguez, M. Brugiafreddo y E. Raña., «Eficiencia técnica en la agricultura familiar: Análisis envolvente de datos (DEA) versus aproximación de fronteras estocásticas (SFA),» Nova Scientia, vol. 9, nº 18, pp. 342-370, 2017. [11]A. Resti., «Evaluating the cost-efficiency of the Italian banking system: what can be learned from the joint application of parametric and non-parametric techniques,» Journal of Banking & Finance, vol. 21, nº 2, pp. 221-250, 1997. [12]T. Coelli y S. Perelman, «A Comparison Of Parametric And Non-Parametric Distance Functions: With Application To European Railways,» European Journal Of Operational Research, vol. 117, nº 2, pp. 326-339, 1999. [13]B. Iráizoz, M. Rapún y I. Zabaleta., «Assessing the technicalb efficiency of horticultural production in Navarra, Spain,» Agricultural Systems, vol. 78, nº 3, pp. 387-403, 2003. [14]K. Sharma, S. Ping y H. Zaleski., «Productive efficiency of the swine industry in Hawaii,» Research Series, vol. 77, pp. 1-24, 1996. [15]D. Tingley, S. Pascoe y L. Coglan, «Factors affecting technical efficiency in fisheries: Stochastic Production Frontier versus Data Envelopment Analysis approaches,» Fisheries Research, vol. 73, nº 3, pp. 363-376, 2005. [16]H. Johansson, «Technical, allocative and economic efficiency in Swedish dairy farms: the Data Envelopment Analysis versus the Stochastic Frontier Approach,» de Poster background paper prepared for presentation at the XIth International Congress of the European Association of Agricultural Economists (EAAE), Copenhagen, 2005. [17]F. Madau, «Technical and scale efficiency in the Italian Citrus Farming: A comparison between Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) Models,» Munich Personal RePEc Archive (MPRA), vol. 41403, nº 18, pp. 1-25, 2012. [18]E. A. S. d. Pedro, Nivel de competitividad y eficiencia de la producción ganadera, Córdoba: Tesis doctoral. Departamento de Producción Animal, 2013. [19]F. Bacon, Novum Organum, Londres, 1620. [20]Seminario Metodología de la Investigación, Bogota: Facultad de Ciencias Económicas, Universidad Nacional de Colombia, 2015.  

Two-Stage Data Envelopment Analysis Efficiency of Indian General Insurance Companies

2021 ◽  
pp. 097215092110476
Author(s):  
Ram Pratap Sinha
Keyword(s):  
Data Envelopment Analysis ◽  
Asset Management ◽  
Evaluation Model ◽  
Insurance Companies ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Two Stage ◽  
Network Dea ◽  
Second Stage ◽  
General Insurance

The present study compares efficiency-related performance of 15 Indian general insurance companies using a two-stage efficiency evaluation model. Efficiency evaluation has been made for the span 2009–2010 to 2017–2018 using network DEA (data envelopment analysis). The results indicate that the in-sample private sector general insurance companies outcompeted the public sector insurers with regard to first-stage activity (premium mobilization), while the reverse was observed in terms of the second-stage activity (asset management and provision of claim benefits). The study also carried out regression of efficiency scores on several contextual variables. The results indicate that ownership is an influential contextual variable in both stages of productivity while solvency significantly impacts efficiency in the second stage.

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