IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i14p8714-d864139.html
   My bibliography  Save this article

Online Platform Customer Shopping Repurchase Behavior Analysis

Author

Listed:
  • Chong Ji

    (College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China)

  • Wenhui Zhao

    (College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China)

  • Hui Wang

    (College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China)

  • Puyu Yuan

    (College of Science, Shenyang Ligong University, Shenyang 110159, China)

Abstract

With the rapid development of the world economy and the progress of modern science and technology, e-commerce has gradually spread to the public. For the online shopping platform, the number of online stores has increased rapidly, especially so in recent years. Mastering the rules of customers’ shopping behavior will help the stores to stand out amidst such a fiercely competitive environment. Taking the cosmetics industry in online shopping as an example, this paper studies the purchase behavior of online platform customers. Through the analysis of order data, it is found that the number of customers’ repurchase times and the corresponding number of people conform to the law of power-law distribution. On this basis, the customer attributes of repurchase behavior are analyzed and demonstrated, and the influences of different factors, such as region, postage, and usage of clients, on the customer repurchase rate and the relationship between the number of orders and the number of days between repurchase are revealed. The analysis results can provide better sustainable operation decision support for online platform operators and improve the overall repurchase rate and benefits of stores.

Suggested Citation

  • Chong Ji & Wenhui Zhao & Hui Wang & Puyu Yuan, 2022. "Online Platform Customer Shopping Repurchase Behavior Analysis," Sustainability, MDPI, vol. 14(14), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8714-:d:864139
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/14/8714/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/14/8714/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mustafa Ozkan & Kemal Cek & Serife Z. Eyupoglu, 2022. "Sustainable Development and Customer Satisfaction and Loyalty in North Cyprus: The Mediating Effect of Customer Identification," Sustainability, MDPI, vol. 14(9), pages 1-13, April.
    2. Thomas Reardon & Ben Belton & Lenis Saweda O. Liverpool‐Tasie & Liang Lu & Chandra S. R. Nuthalapati & Oyinkan Tasie & David Zilberman, 2021. "E‐commerce's fast‐tracking diffusion and adaptation in developing countries," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1243-1259, December.
    3. Tian, Yongge & Wiens, Douglas P., 2006. "On equality and proportionality of ordinary least squares, weighted least squares and best linear unbiased estimators in the general linear model," Statistics & Probability Letters, Elsevier, vol. 76(12), pages 1265-1272, July.
    4. Francisco Diez-Martin & Alicia Blanco-Gonzalez & Camilo Prado-Roman, 2019. "Research Challenges in Digital Marketing: Sustainability," Sustainability, MDPI, vol. 11(10), pages 1-13, May.
    5. Wu, Xingli & Liao, Huchang, 2021. "Modeling personalized cognition of customers in online shopping," Omega, Elsevier, vol. 104(C).
    6. Miluska Murillo-Zegarra & Carla Ruiz-Mafe & Silvia Sanz-Blas, 2020. "The Effects of Mobile Advertising Alerts and Perceived Value on Continuance Intention for Branded Mobile Apps," Sustainability, MDPI, vol. 12(17), pages 1-20, August.
    7. Philipp Brüggemann & Koen Pauwels, 2022. "Consumers’ Attitudes and Purchases in Online Versus Offline Grocery Shopping," Springer Proceedings in Business and Economics, in: Francisco J. Martínez-López & Juan Carlos Gázquez-Abad & Marco Ieva (ed.), Advances in National Brand and Private Label Marketing, pages 39-46, Springer.
    8. M. Goldstein & S. Morris & G. Yen, 2004. "Problems with fitting to the power-law distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 41(2), pages 255-258, September.
    9. Juan He, 2022. "Sustainable Seafood Consumption in Action: Reinvigorating Consumers’ Right to Information in a Borderless Digital World," Journal of International Economic Law, Oxford University Press, vol. 25(1), pages 171-190.
    10. Liang Xiao & Feipeng Guo & Fumao Yu & Shengnan Liu, 2019. "The Effects of Online Shopping Context Cues on Consumers’ Purchase Intention for Cross-Border E-Commerce Sustainability," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    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. Hu Wang & Di Li & Changbin Jiang & Yuxiang Zhang, 2023. "Exploring the Interactive Relationship between Retailers’ Free Shipping Decisions and Manufacturers’ Product Sales in Digital Retailing," Sustainability, MDPI, vol. 15(17), pages 1-19, August.

    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. Gillespie, Colin S., 2015. "Fitting Heavy Tailed Distributions: The poweRlaw Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 64(i02).
    2. Fenner, Trevor & Levene, Mark & Loizou, George, 2010. "Predicting the long tail of book sales: Unearthing the power-law exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2416-2421.
    3. Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011. "Optimal combination forecasts for hierarchical time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
    4. Rezvanian, Alireza & Meybodi, Mohammad Reza, 2015. "Sampling social networks using shortest paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 254-268.
    5. Zoltán Lakner & Brigitta Plasek & Gyula Kasza & Anna Kiss & Sándor Soós & Ágoston Temesi, 2021. "Towards Understanding the Food Consumer Behavior–Food Safety–Sustainability Triangle: A Bibliometric Approach," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    6. Rafael González-Val, 2012. "A Nonparametric Estimation of the Local Zipf Exponent for all US Cities," Environment and Planning B, , vol. 39(6), pages 1119-1130, December.
    7. Yuqin Sun & Rong Ke & Yongge Tian, 2014. "Some overall properties of seemingly unrelated regression models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 103-120, April.
    8. Rafael González-Val, 2021. "The Probability Distribution of Worldwide Forest Areas," Sustainability, MDPI, vol. 13(3), pages 1-19, January.
    9. Paulo Rita & Ricardo F. Ramos, 2022. "Global Research Trends in Consumer Behavior and Sustainability in E-Commerce: A Bibliometric Analysis of the Knowledge Structure," Sustainability, MDPI, vol. 14(15), pages 1-20, August.
    10. Rafael González‐Val, 2019. "Historical urban growth in Europe (1300–1800)," Papers in Regional Science, Wiley Blackwell, vol. 98(2), pages 1115-1136, April.
    11. Kayenaat Bahl & Ravi Kiran & Anupam Sharma, 2023. "Scaling Up Banking Performance for the Realisation of Specific Sustainable Development Goals: The Interplay of Digitalisation and Training in the Transformation Journey," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    12. repec:igg:jamtr0:v:4:y:2022:i:1:p:1-19 is not listed on IDEAS
    13. Marcus Berliant & Hiroki Watanabe, 2015. "Explaining the size distribution of cities: Extreme economies," Quantitative Economics, Econometric Society, vol. 6(1), pages 153-187, March.
    14. Tomson Ogwang, 2011. "Power laws in top wealth distributions: evidence from Canada," Empirical Economics, Springer, vol. 41(2), pages 473-486, October.
    15. Klabunde, Anna, 2014. "Computational Economic Modeling of Migration," Ruhr Economic Papers 471, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    16. Minzhe Yi & Zihao Huang & Yuxiang Yu, 2022. "Creating a Sustainable E-Commerce Environment: The Impact of Product Configurator Interaction Design on Consumer Personalized Customization Experience," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    17. Ogwang, Tomson, 2013. "Is the wealth of the world’s billionaires Paretian?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 757-762.
    18. Fenner, Trevor & Levene, Mark & Loizou, George, 2005. "A stochastic evolutionary model exhibiting power-law behaviour with an exponential cutoff," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 641-656.
    19. Einar Erlingsson & Simone Alfarano & Marco Raberto & Hlynur Stefánsson, 2013. "On the distributional properties of size, profit and growth of Icelandic firms," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 57-74, April.
    20. Seung-hye Jung & Joon-ho Kim & Ha-na Cho & Hae-won Lee & Hyun-ju Choi, 2021. "Brand Personality of Korean Dance and Sustainable Behavioral Intention of Global Consumers in Four Countries: Focusing on the Technological Acceptance Model," Sustainability, MDPI, vol. 13(20), pages 1-19, October.
    21. Branca Barbosa & José Duarte Santos, 2023. "Bibliometric Study on the Social Shopping Concept," Administrative Sciences, MDPI, vol. 13(10), pages 1-21, 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:14:y:2022:i:14:p:8714-:d:864139. 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.