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Optimal resource allocation in survey designs

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  • Calinescu, Melania
  • Bhulai, Sandjai
  • Schouten, Barry

Abstract

Resource allocation is a relatively new research area in survey designs and has not been fully addressed in the literature. Recently, the declining participation rates and increasing survey costs have steered research interests towards resource planning. Survey organizations across the world are considering the development of new mathematical models in order to improve the quality of survey results while taking into account optimal resource planning. In this paper, we address the problem of resource allocation in survey designs and we discuss its impact on the quality of the survey results. We propose a novel method in which the optimal allocation of survey resources is determined such that the quality of survey results, i.e., the survey response rate, is maximized. We demonstrate the effectiveness of our method by extensive numerical experiments.

Suggested Citation

  • Calinescu, Melania & Bhulai, Sandjai & Schouten, Barry, 2013. "Optimal resource allocation in survey designs," European Journal of Operational Research, Elsevier, vol. 226(1), pages 115-121.
    • Handle: RePEc:eee:ejores:v:226:y:2013:i:1:p:115-121
    DOI: 10.1016/j.ejor.2012.10.046
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    References listed on IDEAS

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    1. Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
    2. Bretthauer, Kurt M. & Ross, Anthony & Shetty, Bala, 1999. "Nonlinear integer programming for optimal allocation in stratified sampling," European Journal of Operational Research, Elsevier, vol. 116(3), pages 667-680, August.
    3. Kurt M. Bretthauer & Bala Shetty, 1995. "The Nonlinear Resource Allocation Problem," Operations Research, INFORMS, vol. 43(4), pages 670-683, August.
    4. Patriksson, Michael, 2008. "A survey on the continuous nonlinear resource allocation problem," European Journal of Operational Research, Elsevier, vol. 185(1), pages 1-46, February.
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    Cited by:

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    2. Chun Asaph Young & Schouten Barry & Wagner James, 2017. "JOS Special Issue on Responsive and Adaptive Survey Design: Looking Back to See Forward – Editorial: In Memory of Professor Stephen E. Fienberg, 1942–2016," Journal of Official Statistics, Sciendo, vol. 33(3), pages 571-577, September.
    3. Lynn, Peter, 2013. "Targeted response inducement strategies on longitudinal surveys," Understanding Society Working Paper Series 2013-02, Understanding Society at the Institute for Social and Economic Research.
    4. Roger Tourangeau & J. Michael Brick & Sharon Lohr & Jane Li, 2017. "Adaptive and responsive survey designs: a review and assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 203-223, January.
    5. McCarthy Jaki & Wagner James & Sanders Herschel Lisette, 2017. "The Impact of Targeted Data Collection on Nonresponse Bias in an Establishment Survey: A Simulation Study of Adaptive Survey Design," Journal of Official Statistics, Sciendo, vol. 33(3), pages 857-871, September.
    6. Eltinge John L. & Biemer Paul P. & Holmberg Anders, 2013. "A Potential Framework for Integration of Architecture and Methodology to Improve Statistical Production Systems," Journal of Official Statistics, Sciendo, vol. 29(1), pages 125-145, March.
    7. Burger Joep & Perryck Koen & Schouten Barry, 2017. "Robustness of Adaptive Survey Designs to Inaccuracy of Design Parameters," Journal of Official Statistics, Sciendo, vol. 33(3), pages 687-708, September.

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