IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i3p1805-d742611.html
   My bibliography  Save this article

The Online Ordering Behaviors among Participants in the Oklahoma Women, Infants, and Children Program: A Cross-Sectional Analysis

Author

Listed:
  • Qi Zhang

    (School of Community and Environmental Health, Old Dominion University, Norfolk, VA 23529, USA)

  • Kayoung Park

    (Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA 23529, USA)

  • Junzhou Zhang

    (Department of Marketing, Montclair State University, Montclair, NJ 07043, USA)

  • Chuanyi Tang

    (Department of Marketing, Old Dominion University, Norfolk, VA 23529, USA)

Abstract

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is a nutrition assistance program in the United States (U.S.). Participants in the program redeem their prescribed food benefits in WIC-authorized grocery stores. Online ordering is an innovative method being pilot-tested in some stores to facilitate WIC participants’ food benefit redemption, which has become especially important in the COVID-19 pandemic. The present research aimed to examine the online ordering (OO) behaviors among 726 WIC households who adopted WIC OO in a grocery chain, XYZ (anonymous) store, in Oklahoma (OK). These households represented approximately 5% of WIC households who redeemed WIC benefits in XYZ stores during the study period, which was 1 July to 31 December 2020. This period was during the COVID-19 pandemic but after the temporary lockdown in Oklahoma had been lifted. Descriptive statistics were estimated for WIC OO households’ adoption behaviors and their orders. The Cox proportional hazard model and zero-truncated negative binomial regression were applied to examine the relationship between participants’ socio-demographics and the length of time between 1 July 2020, and their first OO, as well as the number of WIC online orders. About 80% of these online orders were picked up without any changes. Minority households had a significantly longer time before adopting their first OO (hazard ratio (HR) < 1, p < 0.001), while households with a child or a woman participant, or more participants, had a shorter time before adopting OO (HR > 1, p < 0.05). Non-Hispanic black households had a fewer number of OOs than non-Hispanic white households (B = −0.374, p = 0.007). OO adoption varied across socio-demographics. More efforts are needed to ensure equal access and adoption of WIC OO.

Suggested Citation

  • Qi Zhang & Kayoung Park & Junzhou Zhang & Chuanyi Tang, 2022. "The Online Ordering Behaviors among Participants in the Oklahoma Women, Infants, and Children Program: A Cross-Sectional Analysis," IJERPH, MDPI, vol. 19(3), pages 1-11, February.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:3:p:1805-:d:742611
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/3/1805/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/3/1805/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, January.
    2. Driediger, Fabian & Bhatiasevi, Veera, 2019. "Online grocery shopping in Thailand: Consumer acceptance and usage behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 224-237.
    3. Mohammad Al Nawayseh & Wamadeva Balachandran, 2012. "Online Grocery Shopping in Developing Countries: Jordanian Consumers as Case Study," International Journal of Social Ecology and Sustainable Development (IJSESD), IGI Global, vol. 3(3), pages 1-14, July.
    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. Hodges, Leslie & Toossi, Saied & Todd, Jessica E. & Ryan-Claytor, Cayley, 2024. "The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC): Background, Trends, and Economic Issues, 2024 Edition," Economic Information Bulletin 341637, United States Department of Agriculture, Economic Research Service.

    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. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    2. Riccardo (Jack) Lucchetti & Luca Pedini, 2020. "ParMA: Parallelised Bayesian Model Averaging for Generalised Linear Models," Working Papers 2020:28, Department of Economics, University of Venice "Ca' Foscari".
    3. Landry, Craig E. & Shonkwiler, J. Scott & Whitehead, John C., 2020. "Economic Values of Coastal Erosion Management: Joint Estimation of Use and Existence Values with recreation demand and contingent valuation data," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    4. Mónica Moreno-Gutiérrez & Víctor Hernández-Trejo & Ramón Valdivia-Alcalá & Judith Juárez-Mancilla & Plácido Roberto Cruz-Chávez & Ulianov Jakes-Cota, 2024. "Linking Tourist Willingness to Pay and Beach Management: A Travel Cost Analysis for Balandra Marine Park, Mexico," Tourism and Hospitality, MDPI, vol. 5(4), pages 1-20, October.
    5. Ghosh, Prasenjit & Rong, Jian & Khanna, Madhu & Wang, Weiwei & Miao, Ruiqing, 2017. "Have They Gone with the Wind? Indirect Effects of Wind Turbines on Bird Abundance," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258100, Agricultural and Applied Economics Association.
    6. Mullahy, John, 2024. "Analyzing health outcomes measured as bounded counts," Journal of Health Economics, Elsevier, vol. 95(C).
    7. Michel Beine & Ilan Noy & Christopher Parsons, 2021. "Climate change, migration and voice," Climatic Change, Springer, vol. 167(1), pages 1-27, July.
    8. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    9. D M Zimmer, 2023. "The effect of food stamps on fibre intake," Economic Issues Journal Articles, Economic Issues, vol. 28(2), pages 71-86, September.
    10. Jasna Atanasijević & Miloš Božović, 2016. "Exchange Rate as a Determinant of Corporate Loan Defaults in a Euroized Economy: Evidence from Micro-Level Data," Eastern European Economics, Taylor & Francis Journals, vol. 54(3), pages 228-250, May.
    11. Syed Muhammad All-E-Raza Rizvi & Marie-Ange Véganzonès-Varoudakis, 2019. "Economic, social, and institutional determinants of domestic conflict in fragile States," Working Papers hal-02340977, HAL.
    12. Kyriakos Drivas & Constantine Iliopoulos, 2017. "An Empirical Investigation in the Relationship Between PDOs/PGIs and Trademarks," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(2), pages 585-595, June.
    13. J. M. C. Santos Silva & Silvana Tenreyro, 2022. "The Log of Gravity at 15," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(3), pages 423-437, September.
    14. Vidhura Tennekoon, 2017. "Counting unreported abortions: A binomial-thinned zero-inflated Poisson model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 36(2), pages 41-72.
    15. Holger Breinlich & Dennis Novy & J. M. C. Santos Silva, 2024. "Trade, Gravity, and Aggregation," The Review of Economics and Statistics, MIT Press, vol. 106(5), pages 1418-1426, September.
    16. Rik L. Rozendaal & Herman R. J. Vollebergh, 2021. "Policy-Induced Innovation in Clean Technologies: Evidence from the Car Market," CESifo Working Paper Series 9422, CESifo.
    17. Oliver Westerwinter, 2021. "Transnational public-private governance initiatives in world politics: Introducing a new dataset," The Review of International Organizations, Springer, vol. 16(1), pages 137-174, January.
    18. Geoffroy Enjolras & Philippe Madiès, 2020. "The role of bank analysts and scores in the prediction of financial distress: Evidence from French farms," Economics Bulletin, AccessEcon, vol. 40(4), pages 2978-2993.
    19. Xu Wang & Xiaobo Zhang & Zhuan Xie & Huang Yiping, 2016. "Roads to Innovation: Firm-Level Evidence from China," Working Papers id:11121, eSocialSciences.
    20. Bono, Pierre-Henri & David, Quentin & Desbordes, Rodolphe & Py, Loriane, 2022. "Metro infrastructure and metropolitan attractiveness," Regional Science and Urban Economics, Elsevier, vol. 93(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:gam:jijerp:v:19:y:2022:i:3:p:1805-:d:742611. 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.