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Sustainable Tourism and Agriculture Multifunctionality by PAR: A Variable Selection Approach

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Efficiency Measures in the Agricultural Sector

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Abstract

Data Envelopment Analysis (DEA) is a popular non-parametric method used to measure efficiency. It uses linear programming to identify points on a convex hull defined by the inputs and outputs of the most efficient Decision Making Units (DMUs). Two critical elements account for the strength of the DEA approach: (1) no a priori structure is placed on the production process of the firm, and (2) the models can yield a measure of efficiency even with a very small number of data points. The first point is particularly important because the measure of efficiency is based upon the best practice of the DMUs at any of the levels of output observed.

Data envelopment analysis measures efficiency and is very sensitive to the choice of variables for two reasons: the number of efficient DMUs is directly related to the number of variables, and the selection of the variables greatly affects the measure of efficiency when the number of DMUs is few and/or when the number of explanatory variables needed to compute the measure of efficiency is too large. Our approach advises which variables should be included in a DEA model. Hence, a variable selection method is presented for the deterministic DEA approach. First, a definition of different measures of efficiency and the various DEA models used to measure efficiency is provided, and then a variable selection method is proposed. The Azorean agricultural system is used as an example to illustrate the method.

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References

  • Alpert M, Peterson R (1972) On the interpretation of canonical analysis. J Mark Res 30:29–50

    Google Scholar 

  • Banker R (1996) Hypothesis tests using data envelopment analysis. J Product Anal 7(2–3):139–159

    Google Scholar 

  • Banker R, Charnes R, Cooper W (1984a) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078–1092

    Article  Google Scholar 

  • Banker R, Charnes R, Cooper WW (1984b) Equivalence and interpretation of alternative methods for determining returns to scales in data envelopment analysis. Eur J Oper Res 89:473–481

    Article  Google Scholar 

  • Barcikowski R, Stevens J (1975) A Monte Carlo study of the stability of canonical correlations, canonical weights, and canonical variate-variable correlations. Multivar Behav Res 10:353–364

    Article  Google Scholar 

  • Bauernfeind U, Mitsche N (2008) The application of the data envelopment analysis for tourism website evaluation. Inf Technol Tour 10(13):245–257

    Google Scholar 

  • Berger A, Humphrey D (1997) Efficiency of financial institutions: international survey and directions for future research. Eur J Oper Res 98:175–212

    Article  Google Scholar 

  • Boussofiane A, Dyson RG, Thanassoulis E (1991) Applied data envelopment analysis. Eur J Oper Res 52:1–15

    Article  Google Scholar 

  • Brockett PL, Golany B (1996) Using rank statistics for determining programmatic efficiency differences in data envelopment analysis. Manag Sci 42(3):466–472

    Article  Google Scholar 

  • Charnes A, Cooper WW (1985) Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. J Econ 30(1/2):91–107

    Google Scholar 

  • Charnes A, Cooper W, Rhodes E (1978) Measuring the efficiency of decision-making units. Eur J Oper Res 2:429–444

    Article  Google Scholar 

  • Chiang WE, Tsai M-H, Wang LS-M (2004) A DEA evaluation of Taipei hotels. Annal Tour Resear 31(3):712–715

    Article  Google Scholar 

  • Chilingerian J (1995) Evaluating physician efficiency in hospitals: a multivariate analysis of best practices. Eur J Oper Res 80:548–574

    Article  Google Scholar 

  • Cloutier L, Rowley R (1993) Relative technical efficiency: data envelopment analysis and Quebec’s dairy farms. Can J Agric Econ 41:169–176

    Article  Google Scholar 

  • Cooper W, Seiford L, Tone K (2007) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software, 2nd edn. Springer, New York

    Google Scholar 

  • Diaz-Martinez Z, Fernandez-Menendez J (2008) The DEA package, Version 0.1–2, Retrived from http://cran.r-project.org/web/packages/DEA/DEA.pdf

  • Färe R, Grosskopf S, Lovell C (1988) Scale elasticity and scale efficiency. J Inst Theor Econ 144:721–729

    Google Scholar 

  • Fraser I, Cordina D (1999) An application of data envelopment analysis to irrigated dairy farms in northern Victoria, Australia. Agric Syst 59:267–282

    Article  Google Scholar 

  • Gifi A (1990) Nonlinear multivariate analysis. Wiley, Chichester

    Google Scholar 

  • Gimenez-Garcia VM, Martínez-Parra JL, Frank P (2007) Improving resource utilization in multi-unit networked organizations: the case of a Spanish restaurant chain. Tour Manag 28:262–270

    Article  Google Scholar 

  • Golany B, Roll Y (1989) An application procedure for DEA. Technion-Israel Institute of Technology, Israel

    Google Scholar 

  • Hallam D, Machado F (1996) Efficiency analysis with panel data – a study of Portuguese dairy farms. Eur Rev Agric Resou Econ 23(1):79–93

    Article  Google Scholar 

  • Hughes A, Yaisawarng S (2004) Sensitivity and dimensionality tests of DEA efficiency scores. Eur J Oper Res 154:419–422

    Article  Google Scholar 

  • Jaforullah M, Whiteman J (1999) Scale efficiency in the New Zealand dairy industry: a non-parametric approach. Aust J Agric Resour Econ 43(4):523–541

    Article  Google Scholar 

  • Jenkins L, Anderson M (2003) A multivariate statistical approach to reducing the number of variables in data envelopment analysis. Eur J Oper Res 147:51–61

    Article  Google Scholar 

  • Levine M (1977) Canonical analysis and factor comparison, vol 6, Quantitative applications in the social sciences series. Sage Publications, Thousand Oaks

    Google Scholar 

  • Lewin A, Morey R, Cook T (1982) Evaluating the administrative efficiency of courts. Omega 10(4):401–411

    Article  Google Scholar 

  • Lovell C (1993) Production frontier and productive efficiency. In: Fried HO, Lovell CAK, Schmidt SS (eds) The measurement of productive efficiency-techniques and applications. Oxford University Press, Oxford, pp 3–67

    Google Scholar 

  • Marianna S, David A, Peter J, Andrew L (2004) ICT paradox lost? A stepwise DEA methodology to evaluate technology investments in tourism settings. J Trav Resear 43(2):180–192

    Article  Google Scholar 

  • Marote E, Silva E (2002) Análise Dinâmica da Eficiência das Explorações Leiteiras da Ilha Terceira. XII Congresso de Zootecnia. November

    Google Scholar 

  • Marote E, Silva E (2011) Importância dos Subsídios na Eficiência das Explorações Leiteiras da Terceira. Revista de Ciências Agrárias, pp 161–170

    Google Scholar 

  • Noncheva V, Mendes A, Silva E (2009) An approach to variable aggregation in efficiency analysis. In: Classification, forecasting, data mining, international book series information science & computing. Suppl Int J Inf Technol Knowl 3(8):97–104

    Google Scholar 

  • Noncheva V, Mendes A, Silva E (2012) Azorean agriculture efficiency by PAR. In: Mendes A, Silva E, Santos J (eds) Efficiency measures in the agricultural sector, with applications. Springer, Dordrecht, pp 53–72

    Google Scholar 

  • Norman M, Stoker B (1991) Data envelopment analysis: the assessment of performance. Wiley, Chichester

    Google Scholar 

  • Nunamaker T (1985) Using data envelopment analysis to measure the efficiency of non-profit organizations: a critical evaluation. Manag Decis Econ 6(1):50–58

    Article  Google Scholar 

  • OECD – Organisation for Economic Co-Operation and Development (2001) Environmental indicators for agriculture methods and results. Executive summary. Retrived from http://www.oecd.org/greengrowth/sustainableagriculture/1916629.pdf.

  • Pastor JT, Ruiz I-S (2002) A statistical test for nested radial DEA models. Oper Res 50(4):728–735

    Article  Google Scholar 

  • Rodriguez M, Gómez E, Lorente J (2004) Rural multifunctionality in Europe. The concepts and policies. 90th AEEA Seminar

    Google Scholar 

  • Salinas-Jimenez J, Smith P (1996) Data envelopment analysis applied to quality in primary health care. Ann Oper Res 67:141–161

    Article  Google Scholar 

  • Sigala M, Airey D, Jones P, Lockwood A (2004) ICT paradox lost? A stepwise DEA methodology to evaluate technology investments in tourism settings. J Travel Res 43:180–192

    Article  Google Scholar 

  • Silva E, Santos C (2007) Eficiência nos Sistemas de Produção Pecuária nos Açores. APDEA Congress, Vila Real

    Google Scholar 

  • Silva E, Arzubi A, Berbel J (1996) An application of data envelopment analysis (DEA) in Azores dairy farms. New Medit 3:39–43

    Google Scholar 

  • Silva E, Arzubi A, Berbel J (2004) An application of data envelopment analysis (DEA) in Azores dairy farms. New Medit 3:39–43

    Google Scholar 

  • Simar L (1996) Aspects of statistical analyses in DEA-type frontier models. J Product Anal 7:177–186

    Article  Google Scholar 

  • Simar L, Wilson P (2008) Statistical interference in nonparametric frontier models: recent developments and perspectives. In: Fried H, Lovell CAK, Schmidt S (eds) The measurement of productive efficiency and productivity change. Oxford University Press, New York

    Google Scholar 

  • SREA (2007a) Estudo sobre os Turistas que visitam os Açores. 2005 – 2006. Região Autónoma dos Açores/ed. Serviço Regional de Estatística dos Açores

    Google Scholar 

  • SREA (2007b) Anuário Estatístico dos Açores, 2007. Região Autónoma dos Açores/ed. Serviço Regional de Estatística dos Açores

    Google Scholar 

  • Stevens J (1986) Applied multivariate statistics for the social sciences. Erlbaum, Hillsdale

    Google Scholar 

  • Suhariyanto K (1999) Productivity growth efficiency and technical changes in Asian agriculture: a Malmquist index analysis. PhD thesis, University of Reading

    Google Scholar 

  • Sungsoo P (2007) DEA application for the tourist satisfaction management. Tour Anal 12:201–211

    Article  Google Scholar 

  • Valdmanis V (1992) Sensitivity analysis for DEA model: an empirical example using public vs. NEP hospitals. J Public Econ 48:185–205

    Article  Google Scholar 

  • Venâncio F, Silva E (2004) A Eficiência de Exploração Agro-pecuárias dos Açores: uma abordagem paramétrica. XIV Jornadas Luso Espanholas de Gestão Científica

    Google Scholar 

  • Wilson PW (2005) FEAR 1.0: a software package for frontier efficiency analysis with R, Retrieved from http://business.clemson.edu/Economic/faculty/wilson/courses/bcn/papers/fear.pdf

Download references

Acknowledgments

This work has been partially supported by Direcção Regional da Ciência e Tecnologia of Azores Government through the project M.2.1.2/l/009/2008.

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Authors and Affiliations

  1. CEEAplA, Departamento de Matemática, Universidade dos Açores, Rua da Mãe de Deus, 9500-801, Ponta Delgada, Açores, Portugal

    Armando B. Mendes

  2. CEEAplA, Faculty of Mathematics and Informatics, University of Plovdiv, “PaisiiHilendarski”, Plovdiv, Bulgaria

    Veska Noncheva

  3. CEEAplA, Departamento de Ciências Agrárias, Universidade dos Açores, Rua Capitão João de Ávila, 9700-042, Angra do Heroísmo, Açores, Portugal

    Emiliana Silva

Authors
  1. Armando B. Mendes
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  2. Veska Noncheva
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  3. Emiliana Silva
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Corresponding author

Correspondence to Armando B. Mendes .

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Editors and Affiliations

  1. , Mathematics, Azores University, Mãe de Deus, Ponta Delgada, 9501-801, Portugal

    Armando B. Mendes

  2. , Agricultural Sciences Department, University of Azores, Rua Capitão João de Ávila, Angra do Heroísmo, 9700-042, Portugal

    Emiliana L. D. G. Soares da Silva

  3. , Mathematics, Escola de Ciências e Tecnologia, R. Romão Ramalho 59, Évora, 7000-671, Portugal

    Jorge M Azevedo Santos

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Mendes, A.B., Noncheva, V., Silva, E. (2013). Sustainable Tourism and Agriculture Multifunctionality by PAR: A Variable Selection Approach. In: Mendes, A., L. D. G. Soares da Silva, E., Azevedo Santos, J. (eds) Efficiency Measures in the Agricultural Sector. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5739-4_10

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