IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i2p605-d479097.html
   My bibliography  Save this article

Degrees of Shortage and Uncovered Ratios for Long-Term Care in Taiwan’s Regions: Evidence from Dynamic DEA

Author

Listed:
  • Kuo-Feng Wu

    (Department of Nurse-Midwifery and Women Health, National Taipei University of Nursing and Health Science, Taipei City 112303, Taiwan)

  • Jin-Li Hu

    (Institute of Business and Management, National Yang Ming Chiao Tung University, Taipei City 10044, Taiwan)

  • Hawjeng Chiou

    (College of Management, National Taiwan Normal University, No. 162, Section 1, Heping E. Rd., Taipei City 10610, Taiwan)

Abstract

The government is facing the country’s aging population and low birth rate have led to a severe shortage of its healthcare workforce in Taiwan after 2003. In order to explore the status of the country’s degree of long-term care shortage and uncovered ratio, this research uses the Push-Pull-Mooring (PPM) theory to explain long-term care efficiency during 2010–2019 in each city and county. We collect longitudinal-sectional data for 2010–2019 from the Ministry of Health and Welfare’s Department of Statistics for 22 administrative regions in Taiwan in each year and employ dynamic data envelopment analysis (DEA) to evaluate the overall technical efficiency and the disaggregate output insufficiency to explain the research results. The main findings are as follows: (1) Cities near the capital Taipei have the highest degree of shortages in long-term caregivers and high uncovered ratios of people who need long-term care. (2) Presently, there is no demand to increase the number of long-term care institutions in Taiwan. (3) The government should introduce new long-term care certificates through national examinations in order to develop a stronger professional workforce in this field.

Suggested Citation

  • Kuo-Feng Wu & Jin-Li Hu & Hawjeng Chiou, 2021. "Degrees of Shortage and Uncovered Ratios for Long-Term Care in Taiwan’s Regions: Evidence from Dynamic DEA," IJERPH, MDPI, vol. 18(2), pages 1-17, January.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:2:p:605-:d:479097
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/2/605/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/2/605/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. María Dolores Ruiz-Fernández & José Manuel Hernández-Padilla & Rocío Ortiz-Amo & Cayetano Fernández-Sola & Isabel María Fernández-Medina & José Granero-Molina, 2019. "Predictor Factors of Perceived Health in Family Caregivers of People Diagnosed with Mild or Moderate Alzheimer’s Disease," IJERPH, MDPI, vol. 16(19), pages 1-14, October.
    2. Jin-Li Hu & Ming-Chung Chang & Hsin-Jung Chung, 2020. "Projecting the Target Quantity of Medical Staff in Taiwan’s Administrative Regions by the Theory of Carrying Capacity," IJERPH, MDPI, vol. 17(9), pages 1-16, April.
    3. 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.
    4. Jin-Li Hu & Tzu-Pu Chang, 2016. "Total-Factor Energy Efficiency and Its Extensions: Introduction, Computation and Application," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 45-69, Springer.
    5. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    6. Lai, Jung-Yu & Wang, Juite, 2015. "Switching attitudes of Taiwanese middle-aged and elderly patients toward cloud healthcare services: An exploratory study," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 155-167.
    7. Alice Tran & Kim-Huong Nguyen & Len Gray & Tracy Comans, 2019. "A Systematic Literature Review of Efficiency Measurement in Nursing Homes," IJERPH, MDPI, vol. 16(12), pages 1-18, June.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Chien-Hsun, 2023. "Taiwan’s Rapidly Aging Population: A Crisis in the Making?," MPRA Paper 116543, University Library of Munich, Germany.
    2. Cheng-En Wu & Kai Way Li & Fan Chia & Wei-Yang Huang, 2022. "Interventions to Improve Physical Capability of Older Adults with Mild Disabilities: A Case Study," IJERPH, MDPI, vol. 19(5), pages 1-11, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    2. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    3. Yu-Chuan Chen & Yung-Ho Chiu & Tzu-Han Chang & Tai-Yu Lin, 2023. "Sustainable Development, Government Efficiency, and People’s Happiness," Journal of Happiness Studies, Springer, vol. 24(4), pages 1549-1578, April.
    4. Bao-Ngoc Tong & Cheng-Ping Cheng & Lien-Wen Liang & Yi-Jun Liu, 2023. "Using Network DEA to Explore the Effect of Mobile Payment on Taiwanese Bank Efficiency," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    5. Yung‐ho Chiu & Tai‐Yu Lin & Tzu‐Han Chang & Yi‐Nuo Lin & Shih‐Yung Chiu, 2021. "Prevaluating efficiency gains from potential mergers and acquisitions in the financial industry with the Resample Past–Present–Future data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(2), pages 369-384, March.
    6. Necmi Avkiran & Alan McCrystal, 2014. "Intertemporal analysis of organizational productivity in residential aged care networks: scenario analyses for setting policy targets," Health Care Management Science, Springer, vol. 17(2), pages 113-125, June.
    7. Zhicheng Lai & Lei Li & Zhuomin Tao & Tao Li & Xiaoting Shi & Jialing Li & Xin Li, 2023. "Spatio-Temporal Evolution and Influencing Factors of Ecological Well-Being Performance from the Perspective of Strong Sustainability: A Case Study of the Three Gorges Reservoir Area, China," IJERPH, MDPI, vol. 20(3), pages 1-25, January.
    8. Aparicio, Juan & Kapelko, Magdalena, 2019. "Accounting for slacks to measure dynamic inefficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 278(2), pages 463-471.
    9. Huang, Shwu-Huei & Yu, Ming-Miin & Huang, Ya-Ling, 2022. "Evaluation of the efficiency of the local tax administration in Taiwan: Application of a dynamic network data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    10. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    11. Alperovych, Yan & Amess, Kevin & Wright, Mike, 2013. "Private equity firm experience and buyout vendor source: What is their impact on efficiency?," European Journal of Operational Research, Elsevier, vol. 228(3), pages 601-611.
    12. Liang-Han Ma & Jin-Chi Hsieh & Ying Li & Yung-Ho Chiu, 2021. "Evaluating Efficiency Change in Taiwan’s Financial Industry," SAGE Open, , vol. 11(2), pages 21582440211, April.
    13. Sebastian Cuadros & Yeny E. Rodríguez & Javier Contreras, 2020. "Dynamic Data Envelopment Analysis Model Involving Undesirable Outputs in the Electricity Power Generation Sector: The Case of Latin America and the Caribbean Countries," Energies, MDPI, vol. 13(24), pages 1-20, December.
    14. Wang, Qian & Ren, Shuming, 2022. "Evaluation of green technology innovation efficiency in a regional context: A dynamic network slacks-based measuring approach," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    15. Zhen Shi & Shijiong Qin & Yung-ho Chiu & Xiaoying Tan & Xiaoli Miao, 2021. "The impact of gross domestic product on the financing and investment efficiency of China’s commercial banks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-23, December.
    16. Fang-Rong Ren & Ze Tian & Yu-Ting Shen & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Energy, CO 2 , and AQI Efficiency and Improvement of the Yangtze River Economic Belt," Energies, MDPI, vol. 12(4), pages 1-17, February.
    17. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    18. Qian Wang & Jinbao Yang & Yung‐ho Chiu & Tai‐Yu Lin, 2020. "The impact of digital finance on financial efficiency," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(7), pages 1225-1236, October.
    19. Iveta Repkova, 2013. "Estimation of Banking Efficiency in the Czech Republic: Dynamic Data Envelopment Analysis," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 4, pages 261-275, December.
    20. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.

    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:gam:jijerp:v:18:y:2021:i:2:p:605-:d:479097. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.