IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i18p3349-d915772.html
   My bibliography  Save this article

Exploring Knowledge Trajectories of Accounting Information Systems Using Business Method Patents and Knowledge Persistence-Based Main Path Analysis

Author

Listed:
  • Yoonki Rhee

    (Newcastle University Business School, Newcastle University, Newcastle upon Tyne NE1 4SE, UK
    Department of Information Systems, Hanyang University, Seoul 04763, Korea)

  • Sejun Yoon

    (Department of Information Systems, Hanyang University, Seoul 04763, Korea)

  • Hyunseok Park

    (Department of Information Systems, Hanyang University, Seoul 04763, Korea)

Abstract

In this paper, the development trajectory of accounting information systems was analyzed using business method patents and main path analysis based on knowledge persistence. Knowledge persistence-based main path analysis can dramatically minimize the complexity of a knowledge network without omission of the dominant knowledge flows, and so it is a suitable selection for analyzing the business method patents on accounting information systems. The main findings from the empirical results are as follows: the empirical results show that accounting information system patents were developed along with the software patent of knowledge injected from the outside. Bookkeeping/accounting and taxation systems expanded from the basic calculation, storage, and payment technique to scalability to other techniques and functions in more complex situations. This research has found that technological advancement has facilitated and been supporting the development of accounting information system over the years, as shown in the patents filed under business solutions. There is a clear indication of the growing complexity of those patents, signifying the moves/advancement of corporate business information systems from financial accounting-oriented systems to more complex ERP systems.

Suggested Citation

  • Yoonki Rhee & Sejun Yoon & Hyunseok Park, 2022. "Exploring Knowledge Trajectories of Accounting Information Systems Using Business Method Patents and Knowledge Persistence-Based Main Path Analysis," Mathematics, MDPI, vol. 10(18), pages 1-22, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:18:p:3349-:d:915772
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/18/3349/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/18/3349/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Won Sang Lee & So Young Sohn, 2017. "Identifying Emerging Trends of Financial Business Method Patents," Sustainability, MDPI, vol. 9(9), pages 1-21, September.
    2. Roberto Fontana & Alessandro Nuvolari & Bart Verspagen, 2009. "Mapping technological trajectories as patent citation networks. An application to data communication standards," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 18(4), pages 311-336.
    3. Mun, Changbae & Yoon, Sejun & Raghavan, Nagarajan & Hwang, Dongwook & Basnet, Subarna & Park, Hyunseok, 2021. "Function score-based technological trend analysis," Technovation, Elsevier, vol. 101(C).
    4. Bart Verspagen, 2007. "Mapping Technological Trajectories As Patent Citation Networks: A Study On The History Of Fuel Cell Research," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 93-115.
    5. Kanellou, Alexandra & Spathis, Charalambos, 2013. "Accounting benefits and satisfaction in an ERP environment," International Journal of Accounting Information Systems, Elsevier, vol. 14(3), pages 209-234.
    6. Rui Li & Tamy Chambers & Ying Ding & Guo Zhang & Liansheng Meng, 2014. "Patent citation analysis: Calculating science linkage based on citing motivation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(5), pages 1007-1017, May.
    7. Pao-Long Chang & Chao-Chan Wu & Hoang-Jyh Leu, 2010. "Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 5-19, January.
    8. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
    9. Arianna Martinelli & Önder Nomaler, 2014. "Measuring knowledge persistence: a genetic approach to patent citation networks," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 623-652, July.
    10. Bhupatiraju, Samyukta & Nomaler, Önder & Triulzi, Giorgio & Verspagen, Bart, 2012. "Knowledge flows – Analyzing the core literature of innovation, entrepreneurship and science and technology studies," Research Policy, Elsevier, vol. 41(7), pages 1205-1218.
    11. Schilling, Melissa A. & Green, Elad, 2011. "Recombinant search and breakthrough idea generation: An analysis of high impact papers in the social sciences," Research Policy, Elsevier, vol. 40(10), pages 1321-1331.
    12. Nakamura, Hiroko & Suzuki, Shinji & Sakata, Ichiro & Kajikawa, Yuya, 2015. "Knowledge combination modeling: The measurement of knowledge similarity between different technological domains," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 187-201.
    13. Al-Sayed, Mahmoud & Dugdale, David, 2016. "Activity-based innovations in the UK manufacturing sector: Extent, adoption process patterns and contingency factors," The British Accounting Review, Elsevier, vol. 48(1), pages 38-58.
    14. Shortridge, Rebecca Toppe & Smith, Pamela A., 2009. "Understanding the changes in accounting thought," Research in Accounting Regulation, Elsevier, vol. 21(1), pages 11-18.
    15. Chih-Yao Chang & Kuo-Ping Lin, 2020. "Developing Support Vector Machine with New Fuzzy Selection for the Infringement of a Patent Rights Problem," Mathematics, MDPI, vol. 8(8), pages 1-16, August.
    16. von Wartburg, Iwan & Teichert, Thorsten & Rost, Katja, 2005. "Inventive progress measured by multi-stage patent citation analysis," Research Policy, Elsevier, vol. 34(10), pages 1591-1607, December.
    17. Yawei Qi & Wenxiang Peng & Neal N. Xiong, 2020. "The Effects of Fiscal and Tax Incentives on Regional Innovation Capability: Text Extraction Based on Python," Mathematics, MDPI, vol. 8(7), pages 1-19, July.
    18. Martinelli, Arianna, 2012. "An emerging paradigm or just another trajectory? Understanding the nature of technological changes using engineering heuristics in the telecommunications switching industry," Research Policy, Elsevier, vol. 41(2), pages 414-429.
    19. Mun, Changbae & Kim, Yongmin & Yoo, Donghyun & Yoon, Sejun & Hyun, Heesu & Raghavan, Nagarajan & Park, Hyunseok, 2019. "Discovering business diversification opportunities using patent information and open innovation cases," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 144-154.
    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. Kuan, Chung-Huei, 2024. "Integrating prior field knowledge as key documents with main path analysis utilizing key-node path search," Journal of Informetrics, Elsevier, vol. 18(3).
    2. Ba, Zhichao & Ma, Yaxue & Cai, Jinyao & Li, Gang, 2023. "A citation-based research framework for exploring policy diffusion: Evidence from China's new energy policies," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    3. Chung-Huei Kuan & Ssu-Yu Liao, 2024. "Assessing main paths by uncovering their coverage with key-node path search," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6629-6657, November.

    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. Fang Han & Sejun Yoon & Nagarajan Raghavan & Hyunseok Park, 2022. "Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics," Sustainability, MDPI, vol. 14(5), pages 1-19, March.
    2. Mun, Changbae & Yoon, Sejun & Raghavan, Nagarajan & Hwang, Dongwook & Basnet, Subarna & Park, Hyunseok, 2021. "Function score-based technological trend analysis," Technovation, Elsevier, vol. 101(C).
    3. Kuan, Chung-Huei & Huang, Mu-Hsuan & Chen, Dar-Zen, 2018. "Missing links: Timing characteristics and their implications for capturing contemporaneous technological developments," Journal of Informetrics, Elsevier, vol. 12(1), pages 259-270.
    4. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    5. Huenteler, Joern & Ossenbrink, Jan & Schmidt, Tobias S. & Hoffmann, Volker H., 2016. "How a product’s design hierarchy shapes the evolution of technological knowledge—Evidence from patent-citation networks in wind power," Research Policy, Elsevier, vol. 45(6), pages 1195-1217.
    6. Alessandri, Enrico, 2023. "Identifying technological trajectories in the mining sector using patent citation networks," Resources Policy, Elsevier, vol. 80(C).
    7. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    8. Arianna Martinelli & Önder Nomaler, 2014. "Measuring knowledge persistence: a genetic approach to patent citation networks," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 623-652, July.
    9. Adam B. Jaffe & Gaétan de Rassenfosse, 2017. "Patent citation data in social science research: Overview and best practices," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(6), pages 1360-1374, June.
    10. Huang, Ying & Li, Ruinan & Zou, Fang & Jiang, Lidan & Porter, Alan L. & Zhang, Lin, 2022. "Technology life cycle analysis: From the dynamic perspective of patent citation networks," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    11. Huenteler, Joern & Schmidt, Tobias S. & Ossenbrink, Jan & Hoffmann, Volker H., 2016. "Technology life-cycles in the energy sector — Technological characteristics and the role of deployment for innovation," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 102-121.
    12. Kuan, Chung-Huei & Chen, Dar-Zen & Huang, Mu-Hsuan, 2020. "The overlooked citations: Investigating the impact of ignoring citations to published patent applications," Journal of Informetrics, Elsevier, vol. 14(1).
    13. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
    14. Junmo Kim & Juneseuk Shin, 2018. "Mapping extended technological trajectories: integration of main path, derivative paths, and technology junctures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1439-1459, September.
    15. John S. Liu & Louis Y. Y. Lu & Mei Hsiu-Ching Ho, 2019. "A few notes on main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 379-391, April.
    16. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    17. Lai, Kuei-Kuei & Chen, Yu-Long & Kumar, Vimal & Daim, Tugrul & Verma, Pratima & Kao, Fang-Chen & Liu, Ruirong, 2023. "Mapping technological trajectories and exploring knowledge sources: A case study of E-payment technologies," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    18. Shih-Chang Hung & John S. Liu & Louis Y. Y. Lu & Yu-Chiang Tseng, 2014. "Technological change in lithium iron phosphate battery: the key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 97-120, July.
    19. Epicoco, Marianna & Oltra, Vanessa & Maïder Saint, Jean, 2014. "Knowledge dynamics and sources of eco-innovation: Mapping the Green Chemistry community," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 388-402.
    20. Song-Chia Hsu & Kai-Ying Chen & Chih-Ping Lin & Wei-Hao Su, 2022. "Knowledge Development Trajectories of Crime Prevention Domain: An Academic Study Based on Citation and Main Path Analysis," IJERPH, MDPI, vol. 19(17), pages 1-20, August.

    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:jmathe:v:10:y:2022:i:18:p:3349-:d:915772. 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.