IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i19p8029-d421147.html
   My bibliography  Save this article

Implementation for Comparison Analysis System of Used Transaction Using Big Data

Author

Listed:
  • Byungjoon Park

    (Computer Science and Engineering, Sejong University, Seoul 04997, Korea)

  • Hasung Kim

    (IT College, Suwon University, Seoul 04997, Korea)

  • Byeongtae Ahn

    (Liberal & Arts College, Anyang University, Gyeonggi-do 13992, Korea)

Abstract

With the recent increase in used trading sites that support used trading, users want to find various information in real time, and the development of the Internet consists of direct and indirect connections between businesses and consumers. This change created a new type of C2C (Commerce to Commerce) transaction. However, each used trading site has its own characteristics, making it difficult to standardize one. Therefore, in this paper, we construed a system that provides the user’s used transaction data in real time and provides the desired information quickly. In this paper, we developed the crawler system needed to develop an integrated transaction system for second-hand goods through Internet e-commerce transactions, defined morphological analyzers, and described the service that users can employ in the web environment by using the system developed in the paper.

Suggested Citation

  • Byungjoon Park & Hasung Kim & Byeongtae Ahn, 2020. "Implementation for Comparison Analysis System of Used Transaction Using Big Data," Sustainability, MDPI, vol. 12(19), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8029-:d:421147
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/19/8029/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/19/8029/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Robert J. Gordon, 2000. "Does the "New Economy" Measure Up to the Great Inventions of the Past?," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 49-74, Fall.
    2. Conboy, Kieran & Mikalef, Patrick & Dennehy, Denis & Krogstie, John, 2020. "Using business analytics to enhance dynamic capabilities in operations research: A case analysis and research agenda," European Journal of Operational Research, Elsevier, vol. 281(3), pages 656-672.
    3. Carlsson, Bo, 2004. "The Digital Economy: what is new and what is not?," Structural Change and Economic Dynamics, Elsevier, vol. 15(3), pages 245-264, September.
    4. Barker, Theresa J. & Zabinsky, Zelda B., 2011. "A multicriteria decision making model for reverse logistics using analytical hierarchy process," Omega, Elsevier, vol. 39(5), pages 558-573, October.
    5. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    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. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.
    2. Koen W. de Bock & Kristof Coussement & Arno De Caigny & Roman Slowiński & Bart Baesens & Robert N Boute & Tsan-Ming Choi & Dursun Delen & Mathias Kraus & Stefan Lessmann & Sebastián Maldonado & David , 2023. "Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda," Post-Print hal-04219546, HAL.
    3. Lucian Croitoru, 2016. "Are We Systematically Wrong when Estimating Potential Output and the Natural Rate of Interest?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 128-151, June.
    4. Lingzhang Kong & Jinye Li, 2022. "Digital Economy Development and Green Economic Efficiency: Evidence from Province-Level Empirical Data in China," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    5. Karl Whelan, 2002. "Computers, Obsolescence, And Productivity," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 445-461, August.
    6. Ahn, Sanghoon, 2003. "Technology Upgrading with Learning Cost," CEI Working Paper Series 2003-21, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    7. Jonathan Temple, 2002. "The Assessment: The New Economy," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 18(3), pages 241-264.
    8. Hashmat Khan & Marjorie Santos, 2002. "Contribution of ICT Use to Output and Labour-Productivity Growth in Canada," Staff Working Papers 02-7, Bank of Canada.
    9. Liu, Weihua & George Shanthikumar, J. & Tae-Woo Lee, Paul & Li, Xiang & Zhou, Li, 2021. "Special issue editorial: Smart supply chains and intelligent logistics services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    10. Orlando Gomes, 2007. "Investment in organizational capital," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 107-113.
    11. Bussolo Maurizio & de Hoyos Rafael E. & Medvedev Denis & van der Mensbrugghe Dominique, 2012. "Global Growth and Distribution: China, India, and the Emergence of a Global Middle Class," Journal of Globalization and Development, De Gruyter, vol. 2(2), pages 1-29, January.
    12. Kiley, Michael T., 2001. "Computers and growth with frictions: aggregate and disaggregate evidence," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 55(1), pages 171-215, December.
    13. Gebhard Flaig, 2001. "Gibt es einen »New-Economy-Effekt« auf das amerikanische Produktionspotential?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 54(05), pages 16-21, October.
    14. Alberto Chilosi, 2014. "The Economic System as an End or as a Means, and the Future of Socialism: An Evolutionary Viewpoint," Palgrave Studies in the History of Economic Thought, in: Riccardo Bellofiore & Ewa Karwowski & Jan Toporowski (ed.), Economic Crisis and Political Economy, chapter 1, pages 10-28, Palgrave Macmillan.
    15. Yao Zhao & Xuena Kong & Mahmood Ahmad & Zahoor Ahmed, 2023. "Digital Economy, Industrial Structure, and Environmental Quality: Assessing the Roles of Educational Investment, Green Innovation, and Economic Globalization," Sustainability, MDPI, vol. 15(3), pages 1-24, January.
    16. Pang, Jifang & Liang, Jiye, 2012. "Evaluation of the results of multi-attribute group decision-making with linguistic information," Omega, Elsevier, vol. 40(3), pages 294-301.
    17. Dale W. Jorgenson & Mun S. Ho & Kevin J. Stiroh, 2008. "A Retrospective Look at the U.S. Productivity Growth Resurgence," Journal of Economic Perspectives, American Economic Association, vol. 22(1), pages 3-24, Winter.
    18. Szalavetz, Andrea, 2002. "Az informatikai szektor és a felzárkózó gazdaságok [The informatics sector and the advancing economies]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 794-804.
    19. Ran, Qiying & Yang, Xiaodong & Yan, Hongchuan & Xu, Yang & Cao, Jianhong, 2023. "Natural resource consumption and industrial green transformation: Does the digital economy matter?," Resources Policy, Elsevier, vol. 81(C).
    20. Teresa Serra & Barry K. Goodwin & José M. Gil & Anthony Mancuso, 2006. "Non‐parametric Modelling of Spatial Price Relationships," Journal of Agricultural Economics, Wiley Blackwell, vol. 57(3), pages 501-522, 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:19:p:8029-:d:421147. 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.