IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v71y2020ics0038012119301715.html
   My bibliography  Save this article

The socio-economic planning of a community nurses programme in mountain areas: A Directional Distance Function approach

Author

Listed:
  • Falavigna, G.
  • Ippoliti, R.

Abstract

This manuscript focuses on the sustainability of a European Union project, funded by the Alpine Space Programme. This project aims to develop an innovative care model based on community nurses to support municipalities in promoting active and healthy ageing. Adopting the Directional Distance Function, our work sets out to propose a specific score able to identify all those municipalities that are inefficient in supporting the ageing process through the coordination of socio-economic interventions. According to the estimated scores, policy makers can make more rational use of the available resources, implementing the innovative treatments where it is most necessary. In this way, the achievements of this European Union project can be maintained for the sake of the next generation, avoiding its collapse as soon as funding shifts to new programmes.

Suggested Citation

  • Falavigna, G. & Ippoliti, R., 2020. "The socio-economic planning of a community nurses programme in mountain areas: A Directional Distance Function approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
  • Handle: RePEc:eee:soceps:v:71:y:2020:i:c:s0038012119301715
    DOI: 10.1016/j.seps.2019.100770
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012119301715
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cheng, Gang & Zervopoulos, Panagiotis D., 2014. "Estimating the technical efficiency of health care systems: A cross-country comparison using the directional distance function," European Journal of Operational Research, Elsevier, vol. 238(3), pages 899-910.
    2. Jose Zofio & Jesus Pastor & Juan Aparicio, 2013. "The directional profit efficiency measure: on why profit inefficiency is either technical or allocative," Journal of Productivity Analysis, Springer, vol. 40(3), pages 257-266, December.
    3. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    4. Cinzia Daraio & Léopold Simar & Paul W. Wilson, 2018. "Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non‐parametric, two‐stage models of production," Econometrics Journal, Royal Economic Society, vol. 21(2), pages 170-191.
    5. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2007. "Environmental production functions and environmental directional distance functions," Energy, Elsevier, vol. 32(7), pages 1055-1066.
    6. Fare, R. & Grosskopf, S. & Hernandez-Sancho, F., 2004. "Environmental performance: an index number approach," Resource and Energy Economics, Elsevier, vol. 26(4), pages 343-352, December.
    7. Cinzia Daraio & Léopold Simar, 2016. "Efficiency and benchmarking with directional distances: a data-driven approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(7), pages 928-944, July.
    8. Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
    9. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    10. Picazo-Tadeo, Andrés J. & Beltrán-Esteve, Mercedes & Gómez-Limón, José A., 2012. "Assessing eco-efficiency with directional distance functions," European Journal of Operational Research, Elsevier, vol. 220(3), pages 798-809.
    11. George France & Francesco Taroni & Andrea Donatini, 2005. "The Italian health‐care system," Health Economics, John Wiley & Sons, Ltd., vol. 14(S1), pages 187-202, September.
    12. Riccardi, R. & Oggioni, G. & Toninelli, R., 2012. "Efficiency analysis of world cement industry in presence of undesirable output: Application of data envelopment analysis and directional distance function," Energy Policy, Elsevier, vol. 44(C), pages 140-152.
    13. Khushalani, Jaya & Ozcan, Yasar A., 2017. "Are hospitals producing quality care efficiently? An analysis using Dynamic Network Data Envelopment Analysis (DEA)," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 15-23.
    14. Halkos, George E. & Tzeremes, Nickolaos G., 2013. "A conditional directional distance function approach for measuring regional environmental efficiency: Evidence from UK regions," European Journal of Operational Research, Elsevier, vol. 227(1), pages 182-189.
    15. Roberto Ippoliti & Isabella Allievi & Greta Falavigna & Pasquale Giuliano & Floriana Montani & Paola Obbia & Silvia Rizzi & Giuliana Moda, 2018. "The sustainability of a community nurses programme aimed at supporting active ageing in mountain areas," International Journal of Health Planning and Management, Wiley Blackwell, vol. 33(4), pages 1100-1111, October.
    16. Mattsson, Pontus & Tidanå, Claes, 2019. "Potential efficiency effects of merging the Swedish district courts," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 58-68.
    17. Picazo-Tadeo, Andres J. & Reig-Martinez, Ernest & Hernandez-Sancho, Francesc, 2005. "Directional distance functions and environmental regulation," Resource and Energy Economics, Elsevier, vol. 27(2), pages 131-142, June.
    18. Falavigna, Greta & Ippoliti, Roberto & Manello, Alessandro & Ramello, Giovanni B., 2015. "Judicial productivity, delay and efficiency: A Directional Distance Function (DDF) approach," European Journal of Operational Research, Elsevier, vol. 240(2), pages 592-601.
    19. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    20. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    21. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    22. Fare, Rolf & Grosskopf, Shawna, 2004. "Modeling undesirable factors in efficiency evaluation: Comment," European Journal of Operational Research, Elsevier, vol. 157(1), pages 242-245, August.
    23. De Vos, Pol & Orduñez-García, Pedro & Santos-Peña, Moisés & Van der Stuyft, Patrick, 2010. "Public hospital management in times of crisis: Lessons learned from Cienfuegos, Cuba (1996-2008)," Health Policy, Elsevier, vol. 96(1), pages 64-71, June.
    24. Daraio, Cinzia & Simar, Leopold & Wilson, Paul, 2018. "Central limit theorems for conditional efficiency measures and tests of the ‘separability’ condition in non-parametric, two-stage models of production," ISBA Reprints (ISBA - Institute of Statistics, Biostatistics and Actuarial Sciences) 2018023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    25. W. Briec, 1997. "A Graph-Type Extension of Farrell Technical Efficiency Measure," Journal of Productivity Analysis, Springer, vol. 8(1), pages 95-110, March.
    26. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    27. Zhang, Yue-Jun & Chen, Ming-Ying, 2018. "Evaluating the dynamic performance of energy portfolios: Empirical evidence from the DEA directional distance function," European Journal of Operational Research, Elsevier, vol. 269(1), pages 64-78.
    28. Greta Falavigna & Roberto Ippoliti & Alessandro Manello, 2013. "Hospital organization and performance: a directional distance function approach," Health Care Management Science, Springer, vol. 16(2), pages 139-151, June.
    29. Giovanni Fattore & Aleksandra Torbica, 2006. "Inpatient reimbursement system in Italy: How do tariffs relate to costs?," Health Care Management Science, Springer, vol. 9(3), pages 251-258, August.
    30. Kazley, Abby Swanson & Ozcan, Yasar A., 2009. "Electronic medical record use and efficiency: A DEA and windows analysis of hospitals," Socio-Economic Planning Sciences, Elsevier, vol. 43(3), pages 209-216, September.
    31. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    32. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    33. Falavigna, Greta & Ippoliti, Roberto & Ramello, Giovanni B., 2018. "DEA-based Malmquist productivity indexes for understanding courts reform," Socio-Economic Planning Sciences, Elsevier, vol. 62(C), pages 31-43.
    34. Aparicio, Juan & Pastor, Jesus T. & Vidal, Fernando, 2016. "The directional distance function and the translation invariance property," Omega, Elsevier, vol. 58(C), pages 1-3.
    35. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    36. Casagranda, Ivo & Costantino, Giorgio & Falavigna, Greta & Furlan, Raffaello & Ippoliti, Roberto, 2016. "Artificial Neural Networks and risk stratification models in Emergency Departments: The policy maker's perspective," Health Policy, Elsevier, vol. 120(1), pages 111-119.
    Full references (including those not matched with items on IDEAS)

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:71:y:2020:i:c:s0038012119301715. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Haili He). General contact details of provider: http://www.elsevier.com/locate/seps .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.