Case Studies
Jan 29, 2018

Assessing the Performance of a California Water Utility Using Two-Stage Data Envelopment Analysis

Publication: Journal of Water Resources Planning and Management
Volume 144, Issue 4

Abstract

Two-stage data envelopment analysis (DEA) methodology was applied in this study to assess the performance of individual districts of a California water utility for calendar year 2014 (CY2014). A bootstrap technique involving the construction of confidence intervals was implemented to overcome the deterministic nature of conventional DEA, and exogenous variables, such as the number of connections and the total annual precipitation in each district, were incorporated into the model to help identify key factors affecting technical efficiency. Two different DEA models were developed to compare the financial and production performance efficiencies of the districts. Although several districts performed weakly from a production perspective, overall the results indicated the strength and high performance of the utility. The findings of this study are expected to provide a useful way to identify the strengths and weaknesses of individual districts and guide subsequent managerial improvement initiatives.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors greatly appreciate the funding provided by the California Water Service Co. for this project. This paper is an extended version of a conference paper originally presented at the ASCE EWRI 2016 & 2017 Conference.

References

Aida, K., Cooper, W., Pastor, J., and Sueyoshi, T. (1998). “Evaluating water supply services in Japan with RAM: A range-adjusted measure of inefficiency.” Omega, 26(2), 207–232.
Ananda, J. (2014). “Evaluating the performance of urban water utilities: Robust nonparametric approach.” J. Water Resour. Plann. Manage., 04014021.
Aragon, Y., Daouia, A., and Thomas-Agnan, C. (2005). “Nonparametric frontier estimation: A conditional quantile-based approach.” Econometric Theory, 21(2), 358–389.
Avkiran, N. (2006). “Productivity analysis in the service sector with data envelopment analysis.” ⟨http://www.users.on.net/∼necmi/financesite/DEA%20Book%203rd%20Edition%202006_AVKIRAN.pdf⟩ (Nov. 28, 2016).
Banker, R. D., Charnes, A., and Cooper, W. W. (1984). “Some models for estimating technical and scale inefficiencies in data envelopment analysis.” Manage. Sci., 30(9), 1078–1092.
Banker, R. D., Cooper, W. W., Seiford, L. M., and Zhu, J. (2011). “Returns to scale in DEA.” Handbook on data envelopment analysis, Springer, New York, 41–70.
Benito, B., Solana, J., and Moreno, M. R. (2014). “Explaining efficiency in municipal services providers.” J. Productivity Anal., 42(3), 225–239.
Berg, S., and Marques, R. C. (2011). “Quantitative studies of water and sanitation utilities: A benchmarking literature survey.” Water Policy, 13(5), 591–606.
Bhattacharyya, A., Harris, R., Narayanan, R., and Raffie, K. (1995). “Technical efficiency of rural water utilities.” J. Agric. Resour. Econ., 20(2), 373–391.
Bowlin, W. F. (1998). “Measuring performance: An introduction to data envelopment analysis (DEA).” J. Cost Anal., 15(2), 3–27.
Byrnes, J., Crase, L., Dollery, B., and Villano, R. (2010). “The relative economic efficiency of urban water utilities in regional New South Wales and Victoria.” Resour. Energy Econ., 32(3), 439–455.
Carvalho, P., and Marques, R. C. (2011). “The influence of the operational environment on the efficiency of water utilities.” J. Environ. Manage., 92(10), 2698–2707.
Carvalho, P., and Marques, R. C. (2016). “Computing economies of scope using robust partial frontier nonparametric methods.” Water, 8(3), 82.
Cazals, C., Florens, J. P., and Simar, L. (2002). “Nonparametric frontier estimation: A robust approach.” J. Econometrics, 106(1), 1–25.
Charnes, A., Cooper, W., and Rhodes, E. (1978). “Measuring efficiency of decision making units.” Eur. J. Oper. Res., 2(6), 429–444.
Coelli, T., and Walding, S. (2006). “Performance measurement in the Australian water supply industry.” Performance measurement and regulation of network utilities, T. Coelli and D. A. Lawrence, eds., Edward Elgar Publishing, Cheltenham, U.K., 29–62.
Coelli, T. J., Rao, D. S. P., O’Donnell, C. J., and Battese, G. E. (2005). An introduction to efficiency and productivity analysis, Springer Science and Business Media, Berlin.
Daouia, A., and Simar, L. (2007). “Nonparametric efficiency analysis: A multivariate conditional quantile approach.” J. Econometrics, 140(2), 375–400.
Daraio, C., and Simar, L. (2005). “Introducing environmental variables in nonparametric Frontier models: A probabilistic approach.” J. Productivity Anal., 24(1), 93–121.
Daraio, C., and Simar, L. (2007). Advanced robust and nonparametric methods in efficiency analysis. Methodology and applications, Springer, New York.
De Witte, K., and Marques, R. (2010). “Incorporating heterogeneity in non-parametric models: A methodological comparison.” Int. J. Oper. Res., 9(2), 188–204.
Efron, B. (1979). “Bootstrap methods: Another look at the jackknife.” Ann. Stat., 7(1), 1–26.
Ferrier, G. D., and Hirschberg, J. G. (1997). “Bootstrapping confidence intervals for linear programming efficiency scores: With an illustration using Italian banking data.” J. Prod. Anal., 8(1), 19–33.
Ganesan, S. G., García, D. G., Lee, J., and Keck, J. (2017). “A spatio-temporal water mains integrity management program for California.” ASCE World Environmental and Water Resources Congress, ASCE, Reston, VA.
García-Sánchez, I. M. (2006). “Efficiency measurement in Spanish local government: The case of municipal water services.” Rev. Policy Res., 23(2), 355–372.
Gocht, A., and Balcombe, K. (2006). “Ranking efficiency units in DEA using bootstrapping: An applied analysis for Slovenian farm data.” Agric. Econ., 35(2), 223–229.
Guerrini, A., Romano, G., and Campedelli, B. (2013). “Economies of scale, scope, and density in the Italian water sector: A two-stage data envelopment analysis approach.” Water Resour. Manage., 27(13), 4559–4578.
Guerrini, A., Romano, G., Leardini, C., and Martini, M. (2015). “The effects of operational and environmental variables on efficiency of Danish water and wastewater utilities.” Water, 7(7), 3263–3282.
Güngör Demirci, G., and Aksoy, A. (2011a). “Change in optimal pump-and-treat remediation design and costs for different correlation lengths of spatially variable hydraulic conductivity field.” Q. J. Eng. Geol. Hydrogeol., 44(4), 469–480.
Güngör Demirci, G., and Aksoy, A. (2011b). “Variation in time-to-compliance for pump-and-treat remediation of mass transfer-limited aquifers with hydraulic conductivity heterogeneity.” Environ. Earth Sci., 63(6), 1277–1288.
Güngör-Demirci, G., Lee, J., and Keck, J. (2016a). “Performance assessment of a water utility in california.”, ASCE World Environmental and Water Resources Congress, ASCE, Reston, VA.
Güngör-Demirci, G., Lee, J., and Keck, J. (2017). “Performance assessment of a California water utility by data envelopment analysis.” ASCE World Environmental and Water Resources Congress, ASCE, Reston, VA.
Güngör-Demirci, G., Lee, J., Mirzaei, M., and Younos, T. (2016b). “How do people make a decision on bottled or tap water? Preference elicitation with nonparametric bootstrap simulations.” Water Environ. J., 30(3–4), 243–252.
Henningsen, A. (2016). “Package ‘censReg’, version 0.5-22.” ⟨https://cran.r-project.org/web/packages/censReg/index.html⟩ (Dec. 1, 2016).
Jenkins, L., and Anderson, L. (2003). “A multivariate statistical approach to reducing the number of variables in data envelopment analysis.” Eur. J. Oper. Res., 147(1), 51–61.
Keck, J. C., and Lee, J. (2015). “A new model for industry-university partnership.” J. AWWA, 107(11), 84–90.
Khezrimotlagh, D. (2015). “How to deal with numbers of decision making units and variables in data envelopment analysis.” ⟨https://arxiv.org/pdf/1503.02306⟩ (Feb. 23, 2017).
Kneip, A., Simar, L., and Wilson, P. W. (2003). “Asymptotics for DEA estimators in non-parametric Frontier models.”, Interuniversity Attraction Pole, Belgian Science Policy Office, Brussels, Belgium.
LeBlanc, D. C. (2004). Statistics: Concepts and applications for science, Vol. 2, Jones and Bartlett Learning, Burlington, MA.
Lee, J. (2016). “Residential water demand analysis in a low income ratepayer assistance program in California, US.” Water Environ. J, 30(1–2), 49–61.
Marques, R. C., Berg, S., and Yane, S. (2014). “Nonparametric benchmarking of Japanese water utilities: Institutional and environmental factors affecting efficiency.” J. Water Resour. Plann. Manage., 562–571.
Mbuvi, D., De Witte, K., and Perelman, S. (2012). “Urban water sector performance in Africa: A step-wise bias-corrected efficiency and effectiveness analysis.” Util. Policy, 22(Sep), 31–40.
Mirzaei, M., et al. (2015). “Uncertainty analysis for extreme flood events in a semi-arid region.” Nat. Hazards, 78(3), 1947–1960.
Pinto, F. S., Simões, P., and Marques, R. C. (2017). “Water services performance: Do operational environment and quality factors count?” Urban Water J., 14(8), 773–781.
Renzetti, S., and Dupont, D. (2009). “Measuring the technical efficiency of municipal water suppliers: The role of environmental factors.” Land Econ., 85(4), 627–636.
Simar, L., and Wilson, P. W. (2000). “A general methodology for bootstrapping in non-parametric frontier models.” J. Appl. Stat., 27(6), 779–802.
Simar, L., and Wilson, P. W. (2007). “Estimation and inference in two-stage, semi-parametric models of production processes.” J. Econometrics, 136(1), 31–64.
Simm, J., and Besstremyannaya, G. (2015). “Package ‘rDEA’, version 1.2-4.” ⟨https://cran.r-project.org/web/packages/rDEA/index.html⟩ (Jun. 24, 2016).
Storto, C. L. (2013). “Are public-private partnerships a source of greater efficiency in water supply? Results of a non-parametric performance analysis relating to the Italian industry.” Water, 5(4), 2058–2079.
Tziogkidis, P. (2012). Bootstrap DEA and hypothesis testing, Cardiff Business School, Cardiff, U.K.
Wagner, J. M., and Shimshak, D. G. (2007). “Stepwise selection of variables in data envelopment analysis: Procedures and managerial perspectives.” Eur. J. Oper. Res., 180(1), 57–67.
Wijesiri, M., Viganò, L., and Meoli, M. (2015). “Efficiency of microfinance institutions in Sri Lanka: A two-stage double bootstrap DEA approach.” Econ. Modell., 47, 74–83.
Zschille, M., and Walter, M. (2012). “The performance of German water utilities: A (semi)-parametric analysis.” Appl. Econ., 44(29), 3749–3764.

Information & Authors

Information

Published In

Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 144Issue 4April 2018

History

Received: Mar 7, 2017
Accepted: Oct 10, 2017
Published online: Jan 29, 2018
Published in print: Apr 1, 2018
Discussion open until: Jun 29, 2018

Permissions

Request permissions for this article.

Authors

Affiliations

Gamze Güngör-Demirci, Ph.D. [email protected]
Postdoctoral Research Associate, Dept. of Civil and Environmental Engineering, San José State Univ., San José, CA 95192. E-mail: [email protected]
Juneseok Lee, Ph.D., M.ASCE [email protected]
P.E.
Associate Professor, Dept. of Civil and Environmental Engineering, San José State Univ., San José, CA 95192 (corresponding author). E-mail: [email protected]
Jonathan Keck, Ph.D., M.ASCE [email protected]
P.E.
Manager of Special Projects, California Water Service Company, 1720 N. First St., San José, CA 95112. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share