IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i10p3997-d357682.html
   My bibliography  Save this article

A Bibliometric Analysis on No-Show Research: Status, Hotspots, Trends and Outlook

Author

Listed:
  • Cheng Wang

    (Institute of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Runhua Wu

    (Institute of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Lili Deng

    (School of Management, Zhejiang University of Technology, Hangzhou 310023, China)

  • Yong Chen

    (Institute of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Yingde Li

    (Institute of Industrial Engineering, Zhejiang University of Technology, Hangzhou 310023, China)

  • Yuehua Wan

    (Institute of Information Resources, Zhejiang University of Technology, Hangzhou 310023, China
    Library, Zhejiang University of Technology, Hangzhou 310023, China)

Abstract

No-show is a thorny issue within the social scope. It not only affects the sustainability of service system operation but also causes heavy irretrievable losses. To maintain and develop the sustainability of service, this paper adopts bibliometric technology to reflect the current status and future prospects about no-show research. And we strive to explore and summarize appointment scheduling methods for no-show problems. The bibliometric analysis was carried out from various aspects including research areas, countries/regions, institutions, journals, authors and author keywords based on papers harvested from Web of Science Core Collection database. The total 1197 papers show that the United States is in a leading position in this field, followed by England and Canada. University of London is the most productive institution with the highest total citations and H-Index. BMC Health Services Research ranks first as the most productive journal, followed by European Journal of Operational Research and Production and Operations Management . Through the analysis of hot articles, we can conclude that how to reduce the impact of no-shows on the sustainability of service systems has become the main research direction. In addition to appointment scheduling, other effective methods are also mentioned. Further study on these methods will be a major research direction in the future.

Suggested Citation

  • Cheng Wang & Runhua Wu & Lili Deng & Yong Chen & Yingde Li & Yuehua Wan, 2020. "A Bibliometric Analysis on No-Show Research: Status, Hotspots, Trends and Outlook," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:10:p:3997-:d:357682
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/10/3997/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/10/3997/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Torres-Salinas, Daniel & Moed, Henk F., 2009. "Library Catalog Analysis as a tool in studies of social sciences and humanities: An exploratory study of published book titles in Economics," Journal of Informetrics, Elsevier, vol. 3(1), pages 9-26.
    2. Zheng Zhang & Bjorn P. Berg & Brian T. Denton & Xiaolan Xie, 2019. "Appointment scheduling and the effects of customer congestion on service," IISE Transactions, Taylor & Francis Journals, vol. 51(10), pages 1075-1090, October.
    3. Du, Huibin & Li, Na & Brown, Marilyn A. & Peng, Yuenuan & Shuai, Yong, 2014. "A bibliographic analysis of recent solar energy literatures: The expansion and evolution of a research field," Renewable Energy, Elsevier, vol. 66(C), pages 696-706.
    4. Janakiram Subramanian & Shaler Stidham & Conrad J. Lautenbacher, 1999. "Airline Yield Management with Overbooking, Cancellations, and No-Shows," Transportation Science, INFORMS, vol. 33(2), pages 147-167, May.
    5. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    6. Tugba Cayirli & Pinar Dursun & Evrim D. Gunes, 2019. "An integrated analysis of capacity allocation and patient scheduling in presence of seasonal walk-ins," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 524-561, June.
    7. Christos Zacharias & Mor Armony, 2017. "Joint Panel Sizing and Appointment Scheduling in Outpatient Care," Management Science, INFORMS, vol. 63(11), pages 3978-3997, November.
    8. Sauré, Antoine & Begen, Mehmet A. & Patrick, Jonathan, 2020. "Dynamic multi-priority, multi-class patient scheduling with stochastic service times," European Journal of Operational Research, Elsevier, vol. 280(1), pages 254-265.
    9. Chen, Hua-Qi & Wang, Xiuping & He, Li & Chen, Ping & Wan, Yuehua & Yang, Lingyun & Jiang, Shuian, 2016. "Chinese energy and fuels research priorities and trend: A bibliometric analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 966-975.
    10. Yoscelina I. Hernandez‐Garcia & José Antonio Chamizo & Mina Kleiche‐Dray & Jane M. Russell, 2016. "The scientific impact of mexican steroid research 1935–1965: A bibliometric and historiographic analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(5), pages 1245-1256, May.
    11. Han, Shuihua & Zhao, Ling & Chen, Kui & Luo, Zong-wei & Mishra, Deepa, 2017. "Appointment scheduling and routing optimization of attended home delivery system with random customer behavior," European Journal of Operational Research, Elsevier, vol. 262(3), pages 966-980.
    12. Angelito Calma & Martin Davies, 2016. "Academy of Management Journal, 1958–2014: a citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 959-975, August.
    13. Nan Liu & Serhan Ziya, 2014. "Panel Size and Overbooking Decisions for Appointment-Based Services under Patient No-Shows," Production and Operations Management, Production and Operations Management Society, vol. 23(12), pages 2209-2223, December.
    14. Kazim Topuz & Hasmet Uner & Asil Oztekin & Mehmet Bayram Yildirim, 2018. "Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network," Annals of Operations Research, Springer, vol. 263(1), pages 479-499, April.
    15. Qu, Xiuli & Peng, Yidong & Shi, Jing & LaGanga, Linda, 2015. "An MDP model for walk-in patient admission management in primary care clinics," International Journal of Production Economics, Elsevier, vol. 168(C), pages 303-320.
    16. Huaqi Chen & Yuehua Wan & Shuian Jiang & Yanxia Cheng, 2014. "Alzheimer’s disease research in the future: bibliometric analysis of cholinesterase inhibitors from 1993 to 2012," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1865-1877, March.
    17. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    18. Jianzhe Luo & Vidyadhar G. Kulkarni & Serhan Ziya, 2012. "Appointment Scheduling Under Patient No-Shows and Service Interruptions," Manufacturing & Service Operations Management, INFORMS, vol. 14(4), pages 670-684, October.
    19. Cheng Wang & Lili Deng & Yi Han, 2018. "Optimal appointment reminder sending strategy for a single service scenario with customer no-show behaviour," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(11), pages 1863-1875, November.
    20. Nan Liu & Serhan Ziya & Vidyadhar G. Kulkarni, 2010. "Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations," Manufacturing & Service Operations Management, INFORMS, vol. 12(2), pages 347-364, September.
    Full references (including those not matched with items on IDEAS)

    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. Murtaza Nasir & Nichalin Summerfield & Ali Dag & Asil Oztekin, 2020. "A service analytic approach to studying patient no-shows," Service Business, Springer;Pan-Pacific Business Association, vol. 14(2), pages 287-313, June.
    2. Christos Zacharias & Tallys Yunes, 2020. "Multimodularity in the Stochastic Appointment Scheduling Problem with Discrete Arrival Epochs," Management Science, INFORMS, vol. 66(2), pages 744-763, February.
    3. Tunçalp, Feray & Güneş, Evrim D. & Örmeci, E. Lerzan, 2024. "Modeling strategic walk-in patients in appointment systems: Equilibrium behavior and capacity allocation," European Journal of Operational Research, Elsevier, vol. 313(2), pages 587-601.
    4. Song-Hee Kim & Ward Whitt & Won Chul Cha, 2018. "A Data-Driven Model of an Appointment-Generated Arrival Process at an Outpatient Clinic," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 181-199, February.
    5. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    6. Kılıç, Hakan & Güneş, Evrim Didem, 2024. "Patient adherence in healthcare operations: A narrative review," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    7. Tugba Cayirli & Pinar Dursun & Evrim D. Gunes, 2019. "An integrated analysis of capacity allocation and patient scheduling in presence of seasonal walk-ins," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 524-561, June.
    8. Miao Bai & Bjorn Berg & Esra Sisikoglu Sir & Mustafa Y. Sir, 2023. "Partially partitioned templating strategies for outpatient specialty practices," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 301-318, January.
    9. Li Luo & Ying Zhou & Bernard T. Han & Jialing Li, 2019. "An optimization model to determine appointment scheduling window for an outpatient clinic with patient no-shows," Health Care Management Science, Springer, vol. 22(1), pages 68-84, March.
    10. Kazim Topuz & Timothy L. Urban & Robert A. Russell & Mehmet B. Yildirim, 2024. "Decision support system for appointment scheduling and overbooking under patient no-show behavior," Annals of Operations Research, Springer, vol. 342(1), pages 845-873, November.
    11. Paola Cappanera & Filippo Visintin & Carlo Banditori & Daniele Feo, 2019. "Evaluating the long-term effects of appointment scheduling policies in a magnetic resonance imaging setting," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 212-254, March.
    12. Bowen Pang & Xiaolei Xie & Feng Ju & James Pipe, 2022. "A dynamic sequential decision-making model on MRI real-time scheduling with simulation-based optimization," Health Care Management Science, Springer, vol. 25(3), pages 426-440, September.
    13. Van-Anh Truong, 2015. "Optimal Advance Scheduling," Management Science, INFORMS, vol. 61(7), pages 1584-1597, July.
    14. Yong-Hong Kuo & Hari Balasubramanian & Yan Chen, 2020. "Medical appointment overbooking and optimal scheduling: tradeoffs between schedule efficiency and accessibility to service," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 72-101, March.
    15. Oualid Jouini & Saif Benjaafar & Bingnan Lu & Siqiao Li & Benjamin Legros, 2022. "Appointment-driven queueing systems with non-punctual customers," Queueing Systems: Theory and Applications, Springer, vol. 101(1), pages 1-56, June.
    16. Cai, Yun & Song, Haiqing & Wang, Shan, 2024. "Managing appointment-based services with electronic visits," European Journal of Operational Research, Elsevier, vol. 315(3), pages 863-878.
    17. Guo, Hainan & Xie, Yue & Jiang, Bowen & Tang, Jiafu, 2024. "When outpatient appointment meets online consultation: A joint scheduling optimization framework," Omega, Elsevier, vol. 127(C).
    18. Ruiwei Jiang & Siqian Shen & Yiling Zhang, 2017. "Integer Programming Approaches for Appointment Scheduling with Random No-Shows and Service Durations," Operations Research, INFORMS, vol. 65(6), pages 1638-1656, December.
    19. Imran, Muhammad & Haglind, Fredrik & Asim, Muhammad & Zeb Alvi, Jahan, 2018. "Recent research trends in organic Rankine cycle technology: A bibliometric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 552-562.
    20. Aditya Shetty & Harry Groenevelt & Vera Tilson, 2023. "Intraday dynamic rescheduling under patient no-shows," Health Care Management Science, Springer, vol. 26(3), pages 583-598, September.

    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:jsusta:v:12:y:2020:i:10:p:3997-:d:357682. 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.