Skip to main content

Advertisement

SpringerLink
Log in

Efficiency evaluation of urban development in Yazd City, Central Iran using data envelopment analysis

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

Unplanned growth of cities is a matter of concern these days. Lack of attention to proper patterns of urban development has left so many harmful effects on human health and the environment. One of the most effective methods that can be used to measure the efficiency of urban development is data envelopment analysis (DEA). The present study is an attempt to evaluate the performance and efficiency of development of Yazd City using the DEA over the years 1983–2013. In this regard, the ecological factors, affecting the growth of the city of Yazd in the study period, were identified initially. The factors include elevation, slope, aspect, geology, morphology, soil, water quantity, climatic features, and land cover. Next, using variable returns to scale (BCC) based on the output-oriented approach, the efficiency of development of Yazd City was calculated by GAMS software to recognize efficient and inefficient units. Then, Anderson-Peterson (AP) ranking method was used to rank the most efficient units in the development of Yazd City over the study years. The obtained results indicated that the DMUs 2 (1984), 3 (1986), 12 (1994), 15 (1997), 21 (2004), up to 30 (2013) were efficient and introduced as units with proper performance in terms of ecological indicators affecting the urban growth. According to the Anderson-Peterson method, DMU 3 (1986) was recognized as the most efficient unit, ranked the highest (with a score of 1.20319) among the other 30 units in terms of ecological indicators affecting development of the urban growth. The research findings could clarify the strength and weak points of the ecological characteristics of the city. According to which, a comprehensive understanding of the performance of the city could be given to relevant authorities in order to amend inefficient units of urban development or direct the orientation of the city growth toward the most efficient directions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Adhvaryu, B. (2010). Enhancing urban planning using simplified models: SIMPLAN for Ahmedabad, India. Progress in Planning, 37, 113–207.

    Article  Google Scholar 

  • Andersen, P., & Peterson, N. C. (1993). A procedure for ranking efficient unit in DEA. Management Science, 39(10), 1261–1294.

    Article  Google Scholar 

  • Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some methods for estimating technical and inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.

    Article  Google Scholar 

  • Bhattarai, K., & Conway, D. (2010). Urban vulnerabilities in Kathmandu valley, Nepal: visualizations of human/hazard interactions. Journal of Geographic Information System, 2, 63–84.

    Article  Google Scholar 

  • Bobylev, A. V., Bubin, M. N., & Rasskazova, N. S. (2016). The geoecological modelling of small water reservoirs and river catchment areas as a procedure in urban development. Procedia Engineering, 150, 2067–2072.

    Article  Google Scholar 

  • Bowlin, W. F., Charnes, A., Cooper, W. W., & Sherman, H. D. (1985). Data envelopment analysis and regression approaches to efficiency estimation and evaluation. Annals of Operations Research, 2, 113–138.

    Article  Google Scholar 

  • Bray, S., Caggiani, L., & Ottomanelli, M. (2015). Measuring transport systems efficiency under uncertainty by fuzzy sets theory based data envelopment analysis: theoretical and practical comparison with traditional DEA model. Transportation Research Procedia, 5, 186–200.

    Article  Google Scholar 

  • Cascini, L., Bonnard, C., Corominas, J., Jibson, R., & Montero-olarte, J. (2005). Landslide hazard and risk zoning for urban planning and development. In Hungr, Fell, Couture, & Eberhardt (Eds.), Landslide risk management, proceeding of the international conference on landslide risk management, Vancouver, Canada (pp. 199–235). London: A.A. Balkema Publishers, Taylor & Francis Group.

    Google Scholar 

  • Charnes, A., Cooper, W., Golany, B., Seiford, L., & Stutz, J. (1985). Foundation of data envelopment analysis for Pareto-Koopmans efficient empirical production. Journal of Econometrics, 30(1–2), 91–107.

    Article  Google Scholar 

  • Cooper, W. W., Seiford, L. M., & Tone, K. (2000). Data envelopment analysis: a, Comprehensive Text with Models, Application, References and DEA-Solver Software. Boston/Dordrecht/London: Kluwer Academic Publishers.

    Google Scholar 

  • Davidoff, P., & Reiner, T. A. (1973). A choice theory of planning. ED.A. Faludi. In A reader in planning theory (pp. 11–39). Oxford: Pergamon Press.

    Chapter  Google Scholar 

  • Fare, R., Grosskopf, S., & Lovell, C. (1985). The measurement of efficiency of production. Boston: Kluwer Nijhoff.

    Book  Google Scholar 

  • Fu, K. H., Leng, C. H., & Wan Tsou, K. (2014). Analysis of farming environmental efficiency using a DEAModel with undesirable outputs. In APCBEE Procedia, 5th international conference on environmental science and development, ICESD 2014, 10 (pp. 154–158).

    Google Scholar 

  • Golany, B., & Storbeck, J. E. (1999). A data envelopment analysis of the operational efficiency of Bank branches. Interfaces, 29, 14–26.

    Article  Google Scholar 

  • Hassan, M. M., & Nazem, M. N. I. (2016). Examination of land use/land cover changes, urban growth dynamics, and environmental sustainability in Chittagong city, Bangladesh. Environment, Development and Sustainability, 18(3), 697–716.

    Article  Google Scholar 

  • Hegazy, I., & Kaloop, M. (2015). Monitoring urban growth land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), 117–124.

    Article  Google Scholar 

  • Huang, J., & Liu, Y. (2011). The assessment of regional vulnerability to natural disasters in China. International Journal of Disaster Risk Science, 2(2), 41–48.

    Article  Google Scholar 

  • Jenny, A., & Ericson, A. (2006). A participatory approach to conservation in the Calakmul biosphere reserve, Campeche, Mexico. Landscape Urban Plan, 74(3–4), 242–266.

    Google Scholar 

  • Krishna Veni, K., Rajesh, R., & Pugazhendhi, S. (2012). Development of decision making model using integrated AHP and DEA for vendor selection. Procedia Engineering, 38, 3700–3708.

    Article  Google Scholar 

  • Li, F., Liu, X., Hu, D., Wang, R., Yang, W., Li, D., et al. (2009). Measurement indicators and an evaluation approach for assessing urban sustainable development: a case study for China’s Jining city. Landscape and Urban Planning, (90(3–4), 134–142.

  • Li, C. H., Li, N., Wu, L. C., & Hu, A. J. (2013). A relative vulnerability estimation of flood using data envelopment analysis in the Dongting Lake region of human. Natural Hazards and Earth System Sciences, 13, 1723–1734.

    Article  Google Scholar 

  • Liu, J., Ding, F. Y., & Lall, V. (2000). Using data envelopment analysis to compare suppliers for supplier selection and performance improvement. Supply Chain Management: An International Journal, 5(3), 143–150.

    Article  Google Scholar 

  • Liu, Y., Song, Y., & Arp, H. (2012). Examination of relationship between urban form and urban eco-efficiency in China. Habitat International, 36(1), 171–177.

    Article  Google Scholar 

  • Markovits-Somogy, R. (2011). Ranking efficient and inefficient decision making units in data envelopment analysis. International Journal for Traffic and Transport Engineering, 1(4), 245–256.

    Google Scholar 

  • Merwe, V. D., & Hendrik, J. (1997). GIS-aided land evaluation and decision-making for regulating urban expansion: a south African case study. Geo Journal, 43(2), 135–151.

    Google Scholar 

  • Neto, S. (2016). Water governance in an urban age. Utilities Policy, In Press, Corrected Proof.

  • Pardalos P. M., & Resende, M.G.C. (2002). Handbook of applied optimization. Oxford University Press.

  • Pauleit, S., Ennos, R., & Golding, Y. (2005). Modeling the environmental impacts of urban land use and cover change—a study in Merseyside, UK. Landscape Urban Plane, 71(2–4), 295–310.

    Article  Google Scholar 

  • Rizk, H. I., & Rashed, K. M. (2015). Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1, 117–124.

    Google Scholar 

  • Ryngnga, P. K., & Ryntathiang, B. B. L. (2013). Dynamics of land use land cover for sustainability: a case of Shillong, Meghalaya, India. International Journal of Scientific & Technology Research, 2(3), 235–239.

    Google Scholar 

  • Serrao-Neumann, S., Renouf M., Kenway, S.J., & Low Choy, D. (2017). Connecting land-use and water planning: prospects for an urban water metabolism approach. Cities, 60, Part B, 13–27

  • Sueyoshi, T., & Yuan, Y. (2015). China’s regional sustainability and diversified resource allocation: DEA environmental assessment on economic development and air pollution. Energy Economics, 49, 239–256.

    Article  Google Scholar 

  • Yu, Y., & Wen, Z. (2010). Evaluating China’s urban environmental sustainability with data envelopment analysis. Ecological Economics, 69(9), 1748–1755.

    Article  Google Scholar 

  • Zhang, T. (2000). Land market forces and Government’s role in sprawl. Cities, 17(2), 123–135.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Environmental Science, Faculty of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Amanehalsadat Pouriyeh, Nematollah Khorasani & Parvin Farshchi

  2. Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Farhad Hosseinzadeh Lotfi

Authors
  1. Amanehalsadat Pouriyeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nematollah Khorasani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Farhad Hosseinzadeh Lotfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Parvin Farshchi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nematollah Khorasani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pouriyeh, A., Khorasani, N., Hosseinzadeh Lotfi, F. et al. Efficiency evaluation of urban development in Yazd City, Central Iran using data envelopment analysis. Environ Monit Assess 188, 618 (2016). https://doi.org/10.1007/s10661-016-5548-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-016-5548-0

Keywords

Search

Navigation