IDEAS home Printed from https://ideas.repec.org/a/spr/aodasc/v12y2025i5d10.1007_s40745-024-00568-7.html
   My bibliography  Save this article

Determining the Correlation among the Users' Satisfaction and Familiarity with Malay Entrepreneurs Food Delivery Mobile Applications in Malaysia

Author

Listed:
  • Muhamad Redha Iqbal Bin Daud

    (UiTM Selangor PuncakAlam Campus
    KM 20, Lebuhraya Ipoh Lumut)

  • Norhidayah Abdullah

    (UiTM Selangor PuncakAlam Campus)

  • Lovelyna Benedict Jipiu

    (UiTM Selangor PuncakAlam Campus)

Abstract

The rise of mobile technology has significantly transformed numerous aspects of our everyday lives, especially within food delivery services. The investigation aims to explore the food delivery mobile apps (FDMA) satisfaction (SAT) and the influence of familiarity (FAM). Data was gathered from 381 individuals who have experience in using any FDMA services specifically in Shah Alam, Selangor with the aid of online questionnaires. The study findings indicate user satisfaction (US) with FDMA is strongly influenced by the level of familiarity users have with the platform. The research result shows the satisfaction of users with FDMA is strongly linked to how easy they find the platform to use. The research provides a unique contribution by exploring the influence of familiarity on the US with FDMA. Investigating how users' prior experiences and comfort levels impact their satisfaction provides valuable insights for enhancing app design and user experience in the rapidly evolving food delivery industry. The study contributes by elucidating the significant impact of FAM on FDMA satisfaction. This insight aids in refining app design and strategies to enhance user experience. The study suggests optimizing FDMA by prioritizing features that enhance user FAM, ultimately developing higher SAT levels and improving overall user experience. The research findings indicate a notable correlation between the US and the inclination to maintain the usage of FDMA systems.

Suggested Citation

  • Muhamad Redha Iqbal Bin Daud & Norhidayah Abdullah & Lovelyna Benedict Jipiu, 2025. "Determining the Correlation among the Users' Satisfaction and Familiarity with Malay Entrepreneurs Food Delivery Mobile Applications in Malaysia," Annals of Data Science, Springer, vol. 12(5), pages 1431-1462, October.
    • Handle: RePEc:spr:aodasc:v:12:y:2025:i:5:d:10.1007_s40745-024-00568-7
    DOI: 10.1007/s40745-024-00568-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40745-024-00568-7
    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/s40745-024-00568-7?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

    for a different version of it.

    References listed on IDEAS

    as
    1. repec:plo:pntd00:0007987 is not listed on IDEAS
    2. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, 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. Govinda Prasad Dhungana & Arun Kumar Chaudhary & Ramesh Prasad Tharu & Vijay Kumar, 2025. "Generalized Alpha Power Inverted Weibull Distribution: Application of Air Pollution in Kathmandu, Nepal," Annals of Data Science, Springer, vol. 12(5), pages 1691-1715, October.
    2. Heba Soltan Mohamed & M. Masoom Ali & Haitham M. Yousof, 2023. "The Lindley Gompertz Model for Estimating the Survival Rates: Properties and Applications in Insurance," Annals of Data Science, Springer, vol. 10(5), pages 1199-1216, October.
    3. Roberto Moro-Visconti & Salvador Cruz Rambaud & Joaquín López Pascual, 2023. "Artificial intelligence-driven scalability and its impact on the sustainability and valuation of traditional firms," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    4. Mansoureh Beheshti Nejad & Seyed Mahmoud Zanjirchi & Seyed Mojtaba Hosseini Bamakan & Negar Jalilian, 2024. "Blockchain Adoption in Operations Management: A Systematic Literature Review of 14 Years of Research," Annals of Data Science, Springer, vol. 11(4), pages 1361-1389, August.
    5. Amaal Elsayed Mubarak & Ehab Mohamed Almetwally, 2024. "Modelling and Forecasting of Covid-19 Using Periodical ARIMA Models," Annals of Data Science, Springer, vol. 11(4), pages 1483-1502, August.
    6. Xueyan Xu & Fusheng Yu & Runjun Wan, 2023. "A Determining Degree-Based Method for Classification Problems with Interval-Valued Attributes," Annals of Data Science, Springer, vol. 10(2), pages 393-413, April.
    7. Qinghua Zheng & Chutong Yang & Haijun Yang & Jianhe Zhou, 2020. "A Fast Exact Algorithm for Deployment of Sensor Nodes for Internet of Things," Information Systems Frontiers, Springer, vol. 22(4), pages 829-842, August.
    8. Prashant Singh & Prashant Verma & Nikhil Singh, 2022. "Offline Signature Verification: An Application of GLCM Features in Machine Learning," Annals of Data Science, Springer, vol. 9(6), pages 1309-1321, December.
    9. Elham Shamsinejad & Touraj Banirostam & Mir Mohsen Pedram & Amir Masoud Rahmani, 2025. "A Review of Anonymization Algorithms and Methods in Big Data," Annals of Data Science, Springer, vol. 12(1), pages 253-279, February.
    10. Hui Zheng & Peng LI & Jing HE, 2022. "A Novel Association Rule Mining Method for Streaming Temporal Data," Annals of Data Science, Springer, vol. 9(4), pages 863-883, August.
    11. Sankalp Loomba & Madhavi Dave & Harshal Arolkar & Sachin Sharma, 2024. "Sentiment Analysis using Dictionary-Based Lexicon Approach: Analysis on the Opinion of Indian Community for the Topic of Cryptocurrency," Annals of Data Science, Springer, vol. 11(6), pages 2019-2034, December.
    12. Mathew P. M. Ashlin & P. G. Sankaran & E. P. Sreedevi, 2025. "Semiparametric Regression Analysis of Panel Count Data with Multiple Modes of Recurrence," Annals of Data Science, Springer, vol. 12(2), pages 571-590, April.
    13. Muhammed Navas Thorakkattle & Shazia Farhin & Athar Ali khan, 2022. "Forecasting the Trends of Covid-19 and Causal Impact of Vaccines Using Bayesian Structural time Series and ARIMA," Annals of Data Science, Springer, vol. 9(5), pages 1025-1047, October.
    14. Bo Li & Guangle Du, 2024. "Reaction Function for Financial Market Reacting to Events or Information," Annals of Data Science, Springer, vol. 11(4), pages 1265-1290, August.
    15. Tousifur Rahman & Partha Jyoti Hazarika & M. Masoom Ali & Manash Pratim Barman, 2022. "Three-Inflated Poisson Distribution and its Application in Suicide Cases of India During Covid-19 Pandemic," Annals of Data Science, Springer, vol. 9(5), pages 1103-1127, October.
    16. Monowar Wadud Hridoy & Mohammad Mizanur Rahman & Saadman Sakib, 2024. "A Framework for Industrial Inspection System using Deep Learning," Annals of Data Science, Springer, vol. 11(2), pages 445-478, April.
    17. Vrushabh Gada & Madhura Shegaonkar & Madhura Inamdar & Sharath Dinesh & Darshan Sapariya & Vedant Konde & Mahesh Warang & Ninad Mehendale, 2022. "Data Analysis of COVID-19 Hospital Records Using Contextual Patient Classification System," Annals of Data Science, Springer, vol. 9(5), pages 945-965, October.
    18. Showkat Ahmad Lone & Intekhab Alam & Ahmadur Rahman, 2023. "Statistical Analysis Under Geometric Process in Accelerated Life Testing Plans for Generalized Exponential Distribution," Annals of Data Science, Springer, vol. 10(6), pages 1653-1665, December.
    19. Yanke Bao & Ying Wang, 2022. "Factor Space: The New Science of Causal Relationship," Annals of Data Science, Springer, vol. 9(3), pages 555-570, June.
    20. Manoj Verma & Harish Kumar Ghritlahre & Surendra Bajpai, 2023. "A Case Study of Optimization of a Solar Power Plant Sizing and Placement in Madhya Pradesh, India Using Multi-Objective Genetic Algorithm," Annals of Data Science, Springer, vol. 10(4), pages 933-966, August.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:aodasc:v:12:y:2025:i:5:d:10.1007_s40745-024-00568-7. 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.