IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v129y2024i8d10.1007_s11192-024-05108-x.html
   My bibliography  Save this article

Exploring the influence of factors causing stress among doctoral students by combining fuzzy DEMATEL-ANP with a triangular approach

Author

Listed:
  • Shanky Garg

    (Guru Gobind Singh Indraprastha University (GGSIPU))

  • Rashmi Bhardwaj

    (Guru Gobind Singh Indraprastha University (GGSIPU))

Abstract

Besides the highest academic degree with lots of merits post that, getting a Ph.D. and the journey throughout the Ph.D. is not so easy due to which stress and trauma become common among Ph.D. research students. Stress among them can’t be overlooked and is also of major concern as it not only impacts their academic performances but also their mental health, and increases emotional exhaustion. There are many factors that are involved in causing stress among students. Doctoral students are more prone to it as it demands time, selfless effort, and much sacrifice. Moreover, they are in the stage where there are a lot of things going on that distract their minds or sometimes contradict their decisions be it related to their future or to their family, or be it from the institute side. This article mainly deals with analyzing the factors which cause stress, their effects on Ph.D. students, how these factors interrelate with each other, and their percentage share in causing this. Seven dimensions/factors are explored i.e., Institutional Issues, Personal Issues, Supervisor relations, Academic Issues, Fears, Mental Health, and Time Management, which overall depict the entire Doctoral journey. For the analysis of all these dimensions and for finding out the percentage share, a new hybrid method of MCDA (Multi-Criteria Decision Analysis) i.e., fuzzy DEMATEL-ANP with the triangular approach of responses i.e., Optimistic, Pessimistic & Most-Likely is proposed. Performance Analysis and Sensitivity Analysis are done to do the validity check and robustness of the proposed model and by doing this analysis, we identified that the most likely approach in the proposed model is most reliable than the Optimistic and Pessimistic approach due to its non-biased behavior and Supervisor feedback and Uncertain future are the most influential factors and change of city is the least influential one. Moreover, Academic Issues (Poor Writing Skills as well as Publication issues) together with Satisfaction with topic selection during course work period as well as the supervisor's feedback contributes more with weights of 8.1%, 7.7% & 7.5% respectively in causing stress to the doctoral students.

Suggested Citation

  • Shanky Garg & Rashmi Bhardwaj, 2024. "Exploring the influence of factors causing stress among doctoral students by combining fuzzy DEMATEL-ANP with a triangular approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(8), pages 4695-4719, August.
  • Handle: RePEc:spr:scient:v:129:y:2024:i:8:d:10.1007_s11192-024-05108-x
    DOI: 10.1007/s11192-024-05108-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-024-05108-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-024-05108-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Levecque, Katia & Anseel, Frederik & De Beuckelaer, Alain & Van der Heyden, Johan & Gisle, Lydia, 2017. "Work organization and mental health problems in PhD students," Research Policy, Elsevier, vol. 46(4), pages 868-879.
    2. Katarina Urošević & Zoran Gligorić & Igor Miljanović & Čedomir Beljić & Miloš Gligorić, 2021. "Novel Methods in Multiple Criteria Decision-Making Process (MCRAT and RAPS)—Application in the Mining Industry," Mathematics, MDPI, vol. 9(16), pages 1-21, August.
    3. Rajput, Shubhangini & Singh, Surya Prakash, 2019. "Connecting circular economy and industry 4.0," International Journal of Information Management, Elsevier, vol. 49(C), pages 98-113.
    4. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    5. Sang-Bing Tsai & Min-Fang Chien & Youzhi Xue & Lei Li & Xiaodong Jiang & Quan Chen & Jie Zhou & Lei Wang, 2015. "Using the Fuzzy DEMATEL to Determine Environmental Performance: A Case of Printed Circuit Board Industry in Taiwan," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-18, June.
    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. Aijun Liu & Yaxuan Xiao & Xiaohui Ji & Kai Wang & Sang-Bing Tsai & Hui Lu & Jinshi Cheng & Xinjun Lai & Jiangtao Wang, 2018. "A Novel Two-Stage Integrated Model for Supplier Selection of Green Fresh Product," Sustainability, MDPI, vol. 10(7), pages 1-23, July.
    2. Li Bai & F. Javier Sendra Garcia & Arunodaya Raj Mishra, 2022. "RETRACTED ARTICLE: Adoption of the sustainable circular supply chain under disruptions risk in manufacturing industry using an integrated fuzzy decision-making approach," Operations Management Research, Springer, vol. 15(3), pages 743-759, December.
    3. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    4. Zarei, Esmaeil & Khan, Faisal & Abbassi, Rouzbeh, 2021. "Importance of human reliability in process operation: A critical analysis," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Sarfaraz Hashemkhani Zolfani & Ramin Bazrafshan & Fatih Ecer & Çağlar Karamaşa, 2022. "The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    6. Paul, Ananna & Shukla, Nagesh & Trianni, Andrea, 2023. "Modelling supply chain sustainability challenges in the food processing sector amid the COVID-19 outbreak," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    7. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).
    8. Martín-García, Jaime & Gómez-Limón, José A. & Arriaza, Manuel, 2024. "Conversion to organic farming: Does it change the economic and environmental performance of fruit farms?," Ecological Economics, Elsevier, vol. 220(C).
    9. Salimi, Negin & Rezaei, Jafar, 2018. "Evaluating firms’ R&D performance using best worst method," Evaluation and Program Planning, Elsevier, vol. 66(C), pages 147-155.
    10. Željko Stević & Irena Đalić & Dragan Pamučar & Zdravko Nunić & Slavko Vesković & Marko Vasiljević & Ilija Tanackov, 2019. "A new hybrid model for quality assessment of scientific conferences based on Rough BWM and SERVQUAL," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 1-30, April.
    11. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
    12. Ravindra Singh Saluja & Varinder Singh, 2023. "Attribute-based characterization, coding, and selection of joining processes using a novel MADM approach," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 616-655, June.
    13. Zheng Yuan & Baohua Wen & Cheng He & Jin Zhou & Zhonghua Zhou & Feng Xu, 2022. "Application of Multi-Criteria Decision-Making Analysis to Rural Spatial Sustainability Evaluation: A Systematic Review," IJERPH, MDPI, vol. 19(11), pages 1-31, May.
    14. Kavitha, S. & Satheeshkumar, J. & Amudha, T., 2024. "Multi-label feature selection using q-rung orthopair hesitant fuzzy MCDM approach extended to CODAS," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 222(C), pages 148-173.
    15. Junli Zhang & Guoteng Wang & Zheng Xu & Zheren Zhang, 2022. "A Comprehensive Evaluation Method and Strengthening Measures for AC/DC Hybrid Power Grids," Energies, MDPI, vol. 15(12), pages 1-20, June.
    16. Hamzeh Soltanali & Mehdi Khojastehpour & Siamak Kheybari, 2023. "Evaluating the critical success factors for maintenance management in agro-industries using multi-criteria decision-making techniques," Operations Management Research, Springer, vol. 16(2), pages 949-968, June.
    17. Yossi Hadad & Baruch Keren & Dima Alberg, 2023. "An Expert System for Ranking and Matching Electric Vehicles to Customer Specifications and Requirements," Energies, MDPI, vol. 16(11), pages 1-18, May.
    18. Syed Abdul Rehman Khan & Arsalan Zahid Piprani & Zhang Yu, 2022. "Digital technology and circular economy practices: future of supply chains," Operations Management Research, Springer, vol. 15(3), pages 676-688, December.
    19. Jen-Jen Yang & Yen-Ching Chuang & Huai-Wei Lo & Ting-I Lee, 2020. "A Two-Stage MCDM Model for Exploring the Influential Relationships of Sustainable Sports Tourism Criteria in Taichung City," IJERPH, MDPI, vol. 17(7), pages 1-16, March.
    20. Vieira, Fabiana C. & Ferreira, Fernando A.F. & Govindan, Kannan & Ferreira, Neuza C.M.Q.F. & Banaitis, Audrius, 2022. "Measuring urban digitalization using cognitive mapping and the best worst method (BWM)," Technology in Society, Elsevier, vol. 71(C).

    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:spr:scient:v:129:y:2024:i:8:d:10.1007_s11192-024-05108-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.