Evaluation of Old Oyo National Park efficiency using DEA Approach

Daniel Jacob; Samuel Onadeko; Imaobong Nelson; Abdul Shotuyo

doi:10.25167/ees.2018.45.12

Opublikowane: 2020-11-18

Tom 18 Nr 1 (45) (2018)

Ocena efektywności Parku Narodowego Old Oyo z użyciem podejścia DEA

Daniel Jacob

, Samuel Onadeko , Imaobong Nelson , Abdul Shotuyo

Economic and Environmental Studies

Dział: Articles

https://doi.org/10.25167/ees.2018.45.12

Abstrakt

Mierzenie efektywności parku narodowego jest trudne ze względu, między innymi, na takie czynniki jak heterogeniczność dostarczonych źródeł (np. dane nt. budżetu, personelu) oraz oczekiwanych rezultatów (np. dochód, przepływ odwiedzających). Gdy tak rzecz wygląda w zarządzaniu obszarem chronionym, w innych dziedzinach podejście może być stosowane z powodzeniem przez wykorzystanie granicznej analizy danych (DEA). DEA ma kilka zalet w porównaniu z innymi technikami gdyż równocześnie wykorzystuje wielorakie heterogeniczne dane wejściowe i wyjściowe w celu określenia które projekty są najskuteczniejsze, które to określa się jako graniczny obszar skuteczności w porównaniu z innymi w zestawie danych. Dlatego też w niniejszym badaniu używa się DEA do oceny skuteczności zarządzania w Parku Narodowym Old Oyo w okresie 2001-2015. Wyniki wskazują, że park ten był efektywnie zarządzany przez 11 i 13 lat, odpowiednio, jeśli idzie o ogólną techniczną oraz czysto techniczną skuteczność w średniej skali efektywności wynoszącej 97%. Również, park ten działał w 80% swojej całkowitej skali produktywności. Te wyniki oraz użycie DEA podkreślają zarówno sukces wykorzystania tej techniki w określaniu skuteczności obszaru chronionego oraz tych czynników, które należy rozważyć przy alokowaniu źródeł przeznaczonych dla projektów realizowanych w Parku.

Słowa kluczowe:

park narodowy, skuteczność, alokacja źródeł, zarządzanie obszarem chronionym

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Zasady cytowania

Jacob, D., Onadeko, S., Nelson, I., & Shotuyo, A. (2020). Ocena efektywności Parku Narodowego Old Oyo z użyciem podejścia DEA. Economic and Environmental Studies, 18(1 (45), 193–210. https://doi.org/10.25167/ees.2018.45.12

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Utwór dostępny jest na licencji Creative Commons Uznanie autorstwa – Użycie niekomercyjne – Na tych samych warunkach 4.0 Międzynarodowe.

Bibliografia

Adejumo, A. A., Amusa, T.O. and Adamu, T.2014.Assessment of Tourists Flow And Revenue Generation In Kainji Lake National Park, Nigeria.Journal Of Research In Forestry, Wildlife And Environmental Volume 6(2): 2141 – 1778
Google Scholar

Apospori, E.; Nikandrou, I.; Brewster, C.; Papalexandris, N. (2008).‘HRM and Organizational Performance in Northern and Southern Europe,’ International Journal of Human Resource Management 19(7), 1187–1207.
Google Scholar

Ayodele, I. A. (2002). Essentials of Tourism Management. Elshaddai Global Ventures Ltd, Ibadan. 90p.
Google Scholar

Balmford, A.; Bresford, J.; Green, J.; Naidoo, R.; Walpole, M; Manica, A. (2009). A Global Perspective on Trends in Nature-Based Tourism. PLoS Biology 7 (6):1-6.
Google Scholar

Banker, R. D.; Cooper, W. W.; Seiford, L. M.; Thrall, R. M.; Zhu, J. (2004). Returns to Scale in Different DEA Models. European Journal of Operational Research, 154(2), 345-362.
Google Scholar

Bhandari, M. (1999). Tourism Raised Problems in Masai Mara National Park Narok, Kenya. Report prepared for APEC, Nepal.14p.
Google Scholar

Bosetti, V.; Locatelli, G. (2006). A Data Envelopment Analysis Approach to the Assessment of Natural Parks’ Economic Efficiency and Sustainability. The Case of Italian National Parks. Sustainable Development 4, No. 4, pp. 277 - 286 DOI: 10.1002/sd.288.
Google Scholar

Bowlin, W. F. (1998). Measuring Performance: An Introduction to Data Envelopment Analysis (DEA). The Journal of Cost Analysis, 15(2), 3-27.
Google Scholar

Cava, P. B.; Junior, A. P. S.; A. M. D. Branco (2016). Evaluation of Bank Efficiency in Brazil: A Dea Approach, Ram, Rev. Adm. Mackenzie, 17(4), 62-84
Google Scholar

Challender, D. W. S.; MacMillan, D. C. (2014). Poaching is More Than an Enforcement Problem. Conservation Letters 7: 484–494
Google Scholar

Challender, D.; Harrop, S.; MacMillan, D. (2015). Towards Informed and Multi-Faceted Wildlife Trade Interventions. Global Ecology and Conservation 3:129–148.
Google Scholar

Charnes, A.; Cooper, W. W.; Lewin, A. Y.; Seiford, L. M. (1994). Data Envelopment Analysis: Theory, Methodology, and Application. (1st ed.) New York: Springer Science+Business Media, LLC.
Google Scholar

Charnes, A.; Cooper, W.; Rhodes, E. (1978). Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444.
Google Scholar

Charnley, S. (2005) From Nature Tourism to Ecotourism? The Case of the Nerorongoro Conservation Area, Tanzania. Hum Organ 64, 75–88.
Google Scholar

Cooper, W. W.; Seiford, L. M.; Tone, K. (2006). Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References. New York: Springer Science and Business Media, Inc.
Google Scholar

Cooper, W. W.; Seiford, L. M.; Tone, K. (2007). Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software (2nd Ed.). New York: Springer Science & Business Media, LLC.
Google Scholar

Cracolici, M.F. (2005). La Competitività tra Destinazioni Turistiche. Un’Analisi di Destination Benchmarking, PhD Dissertation, Faculty of Economics, University of Palermo, Italy.
Google Scholar

Cracolici, M. F. (2004) Tourist Performance Evaluation: a Novel Approach, Atti XLII Riunione Scientifica della Società Italiana di Statistica, June 2004, Bari.
Google Scholar

Cracolici, M.F., Nijkamp, P. (2006) Competition among Tourist Destination. An Application of Data Envelopment Analysis to Italian Provinces, in Giaoutzi M. and Nijkamp P. (eds.), Tourism and Regional Development: New Pathways, Ashgate, Aldershot, UK.
Google Scholar

Fethi, M.; Pasiouras, F. (2010). Assessing Bank Performance with Operational Research and Artificial Intelligence Techniques: A Survey. European Journal of Operational Research, 204(2), 189-198.
Google Scholar

Fischer, F. (2008). The Importance of Law Enforcement for Protected Areas: Don't Step Back! Be Honest Protect. Pp. 101–103.
Google Scholar

Ginsberg, L. (1997). ̳Training for the Long Haul‘ Computer Shopper 17, pp. 04
Google Scholar

Jackson, G. B.; Wirt, J. G. (1996). Putting Students to Work. Training and Development 50: 58-59
Google Scholar

Jackson, R. H.; Jackson, M. W. (2009). Student Assessment of a semi-directed internship program. Journal of Geography108: 57–67
Google Scholar

Jacob, D. E.; Eniang, E. A.; Nelson, I. U.; U. I. Udoakpan (2015). Vegetation Assessment of Sclater’s Guenon Habitat in Ikot Uso Akpan Forest, Itu, Southeastern Nigeria, Intl. J. of Mol. Ecol. and Conserv. 2(6): 32-38 (doi: 10.5376/ijmec.2015.05.0001)
Google Scholar

Jacob, D. E.; Nelson, I. U. (2015). A Survey of Sclater’s Guenon in Ikot Uso Akpan Community Forest, Itu, Nigeria, Intl. J. of Mol. Ecol. and Conserv. 5(2): 32-38 (doi: 10.5376/ijmec.2015.05.0002)
Google Scholar

Jacob, D. E.; Nelson, I. U.; Udoakapn, U. I.; Etuk, U. B. (2015). Wildlife Poaching in Nigeria National Parks: A Case study of Cross River National Park, International Journal of Molecular Ecology and Conservation 5(4): 1-7 (doi: 10.5376/ijmec.2015.05.0004)
Google Scholar

Jacob, D.E.; A.U. Ogogo (2011). Community Participation in Protected Area Management: A Case Study of Cross River National Park. In: Popoola, L., K. Ogunsanwo and F. Idumah (eds). Forestry in the context of the millennium development goals, Proceeding of the 34th Annual Conference of the Forestry Association of Nigeria held in Osogbo, Osun State, Nigeria. Vol.1 p412-415.
Google Scholar

Jacob, D.E.; Udoakpan U.I.; Nelson, I. U (2013). Issues in Conflict Resolution in Cross River National Park, Southeastern Nigeria. 1st International Conference on Environmental Crisis and its Solution. Scientific and Research Branch, Khouzeslan, Islamic Azad University, Kish Island, Iran, 13th-14th February, 2013. pp 76-82.
Google Scholar

Kruger, O. (2005) The Role of Ecotourism in Conservation: Panacea or Pandora's box? Biodivers Conserv 14, 579–600.
Google Scholar

Kulshreshtha, M.; Parikh, J. K. (2002). Study of Efficiency and Productivity Growth in Opencast and Underground Coal Mining in India: A DEA Analysis. Energy Economics, 24(5), 439-453
Google Scholar

Kumar, S.; Gulati, R. (2008). An Examination of Technical, Pure Technical, and Scale Efficiencies in Indian Public Sector Banks Using Data Envelopment Analysis. Eurasian Journal of Business and Economics 1 (2), 33-69.
Google Scholar

Lindsey, P. A.; Alexander, R.; Mills, M. G. L.; Romanãch, S.; Woodroffe, R. (2007). Wildlife Viewing Preferences of Visitors to Protected Areas in South Africa: Implications for the Role of Ecotourism in Conservation. Journal of Ecotourism, 6(1):19-33.
Google Scholar

Liu, S. (2009). Slacks-Based Efficiency Measures for Predicting Bank Performance. Expert Systems with Applications, 36(2), 2813-2818
Google Scholar

Macedo, M. A.; Barbosa, A. T. (2009). Eficiência no sistema bancário brasileiro: uma análise do desempenho de bancos de varejo, atacado, middle-market e financiamento utilizando DEA. Revista de Informação Contábil (RIC), 3(3), 1-24.
Google Scholar

Macoris, L.; Salgado, A. P. Jr.; Falsarella, E., Jr. (2015). The Different Approaches of Banking Efficiency: A Meta-Analysis. Proceedings of the International Conference on Data Envelopment Analysis. Braunschweig, Germany, 13.
Google Scholar

Meduna, A. J.; Amusa, T.O.; Ogunjinmi, A. A.; Ibeun, J. S. (2005). Environmental Friendly Tourism in Nigeria: A Case Study of Nigerian National Park Service. Nigerian Journal of Forestry 35 (1): 36-43.
Google Scholar

Ogogo, A. U.; A. A. Nchor; D. E. Jacob (2010). Challenges of Buffer Zone Management in Cross River National Park, Southeastern Nigeria. Journal of Research in Forestry, Wildlife and Environment 2(2): 156-163
Google Scholar

Périco, A.; Rebelatto, D. N.; Santana, N. B. (2008). Eficiência bancária: os maiores bancos são os mais eficientes? Uma análise por envoltória de dados. Gest. Prod., 15(2), 421-431.
Google Scholar

Raab, R. L.; Lichty, R. W. (2002). Identifying Subareas that Comprise a Greater Metropolitan Area: The Criterion of County Relative Efficiency. Journal of Regional Science, 42(3), 579-594.
Google Scholar

Renz, T. (2015). The Transition from an Unpaid, Unprotected Internship Model. WWW document, http://www.the-wagnerreview.org/2015/04/the-transition-from-an-unpaid-unprotectedinternship-model/
Google Scholar

Pai, J. T.; W. Liao; D. Hu. (2017). Research on Eco-efficiency of Industrial Parks in Taiwan. Proceedings of 2017 International Conference of Asian-Pacific Planning Societies, 20pp.
Google Scholar

Rusielik, R.; W, Zbaraszewski. (2014). The Efficiency of Scientific and Tourism Activity of Polish National Parks with use DEA method. Economic and Environmental Studies 14 (3 (31)), 283-297
Google Scholar

Saha, A.; Ravisankar, T. (2000). Rating of Indian commercial banks: a DEA approach. European Journal of Operational Research, 124(1), 187-203.
Google Scholar

Sánchez, L.E., Croal, P. (2012). Environmental impact assessment, from Rio-92 to Rio + 20 and beyond. Ambiente and Sociedade 15, 41–54
Google Scholar

Sathye, M. (2003). Efficiency of banks in a developing economy: The case of India. European Journal of Operational Research, 148(3), 662-671.
Google Scholar

Sovilla, E. S. (1998). Co-op’s Odyssey. ASSEE Prism 7: 18–23
Google Scholar

Soysal-Kurt, H. (2017). Measuring Tourism Efficiency of European Countries by Using Data Envelopement Analysis, European Scientific Journal 13(10): 1857 – 7881
Google Scholar

Thanassoulis, E. (2003). Introduction to the Theory and Application of Data Envelopment Analysis: A Foundation Text with Integrated Software (2nd ed.). New York: Springer
Google Scholar

Toloo, M. ; Nalchigar, S. (2009). A New Integrated DEA Model for Finding Most BCC-Efficient DMU. Applied Mathematical Modelling 33(1): 597-604
Google Scholar

Tranquilli, S.; Abedi-Lartey, M.; Abernethy, K.; Amsini, F.; Asamoah, A.; Balangtaa, C.; et al. (2014) Protected Areas in Tropical Africa: Assessing Threats and Conservation Activities. PLoS ONE 9(12): e114154. https://doi.org/10.1371/journal.pone.0114154
Google Scholar

Wanke, P.; Barros, C.; Faria, J. (2015). Financial Distress Drivers in Brazilian Banks: A Dynamic Slacks Approach. European Journal of Operational Research, 240(1), 258-268
Google Scholar

Yang, Y.; Zhao, J. (2009), Study on Commercial Bank Credit Risk based on AGA and Camel Rating System., Knowledge Discovery and Data Mining, pp. 562-565.
Google Scholar

Yu, Z.; Chen, H.; Liu, J.; Zhang, H.; Yan, Y.; Zhu, N.; Guo, Y.; Yang, B.; Chang, Y.y Dai, F.; et al. (2014). Various Applications of TALEN and CRISPR/Cas9-mediated Homologous Recombination to Modify the Drosophila genome. Biol Open. 3:271–280.
Google Scholar