IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v29y2019i2d10.1007_s12525-017-0272-3.html
   My bibliography  Save this article

Smart e-commerce systems: current status and research challenges

Author

Listed:
  • Zhiting Song

    (South China University of Technology)

  • Yanming Sun

    (South China University of Technology)

  • Jiafu Wan

    (South China University of Technology)

  • Lingli Huang

    (South China University of Technology)

  • Jianhua Zhu

    (South China University of Technology)

Abstract

With the ongoing progress in cloud computing, big data analytics (BDA) and other burgeoning technologies, the integration of intelligence and e-commerce systems now makes it possible to build e-commerce systems with enhanced efficiency, reduced transaction costs and smart information-processing patterns. However, despite the fact that smart e-commerce systems (SESs) offer great opportunities to the business field, the development of SESs is still in its infancy. Numerous issues still need to be resolved. To offer a better comprehension of SESs and facilitate future research, this paper first describes the holistic architecture of these systems and analyzes the main enablers underlying the development of SESs in terms of internet of things (IoT), social media, mobile internet, big data analytics and cloud computing. Then, the key challenges and issues pertaining to current SESs are presented, and some possible research directions are also proposed. Finally, the paper presents qualitative and quantitative depictions of SESs from a complex systems perspective, which provides a brand new idea of how to address the current SES issues.

Suggested Citation

  • Zhiting Song & Yanming Sun & Jiafu Wan & Lingli Huang & Jianhua Zhu, 2019. "Smart e-commerce systems: current status and research challenges," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 221-238, June.
  • Handle: RePEc:spr:elmark:v:29:y:2019:i:2:d:10.1007_s12525-017-0272-3
    DOI: 10.1007/s12525-017-0272-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-017-0272-3
    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/s12525-017-0272-3?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Shahriar Akter & Samuel Fosso Wamba, 2016. "Big data analytics in E-commerce: a systematic review and agenda for future research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(2), pages 173-194, May.
    2. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    3. Philip Anderson, 1999. "Perspective: Complexity Theory and Organization Science," Organization Science, INFORMS, vol. 10(3), pages 216-232, June.
    4. Hoyoung Kim & Jinwoo Kim & Yeonsoo Lee, 2005. "An Empirical Study of Use Contexts in the Mobile Internet, Focusing on the Usability of Information Architecture," Information Systems Frontiers, Springer, vol. 7(2), pages 175-186, May.
    5. Ritu Agarwal & Amrit Tiwana, 2015. "Editorial—Evolvable Systems: Through the Looking Glass of IS," Information Systems Research, INFORMS, vol. 26(3), pages 473-479, September.
    6. Declan Butler, 2016. "A world where everyone has a robot: why 2040 could blow your mind," Nature, Nature, vol. 530(7591), pages 398-401, February.
    7. Kietzmann, Jan H. & Hermkens, Kristopher & McCarthy, Ian P. & Silvestre, Bruno S., 2011. "Social media? Get serious! Understanding the functional building blocks of social media," Business Horizons, Elsevier, vol. 54(3), pages 241-251, May.
    8. Kasiri, Leila Agha & Guan Cheng, Kenny Teoh & Sambasivan, Murali & Sidin, Samsinar Md., 2017. "Integration of standardization and customization: Impact on service quality, customer satisfaction, and loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 35(C), pages 91-97.
    9. Lee, In, 2017. "Big data: Dimensions, evolution, impacts, and challenges," Business Horizons, Elsevier, vol. 60(3), pages 293-303.
    10. Scholz, Michael & Dorner, Verena & Schryen, Guido & Benlian, Alexander, 2017. "A configuration-based recommender system for supporting e-commerce decisions," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83360, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    11. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    12. Close, Angeline G. & Kukar-Kinney, Monika, 2010. "Beyond buying: Motivations behind consumers' online shopping cart use," Journal of Business Research, Elsevier, vol. 63(9-10), pages 986-992, September.
    13. Ulrike Baumöl & Linda Hollebeek & Reinhard Jung, 2016. "Dynamics of customer interaction on social media platforms," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(3), pages 199-202, August.
    14. Scholz, Michael & Dorner, Verena & Schryen, Guido & Benlian, Alexander, 2017. "A configuration-based recommender system for supporting e-commerce decisions," European Journal of Operational Research, Elsevier, vol. 259(1), pages 205-215.
    15. Youngjin Yoo & Ola Henfridsson & Kalle Lyytinen, 2010. "Research Commentary ---The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research," Information Systems Research, INFORMS, vol. 21(4), pages 724-735, December.
    16. Scholz, Michael & Dorner, Verena & Schryen, Guido & Benlian, Alexander, 2017. "A configuration-based recommender system for supporting e-commerce decisions," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 85453, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    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. Yin Zhang & Haider Abbas & Yi Sun, 2019. "Smart e-commerce integration with recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 219-220, June.
    2. Sudesh Sheoran & Sanket Vij, 2023. "A Consumer-Centric Paradigm Shift in Business Environment with the Evolution of the Internet of Things: A Literature Review," Vision, , vol. 27(4), pages 431-442, August.
    3. Jean-Éric Pelet & Basma Taieb, 2022. "Context-aware optimization of mobile commerce website interfaces from the consumers’ perspective: Effects on behavioral intentions [Optimisation contextuelle des interfaces de sites Web de commerce," Post-Print hal-04138288, HAL.

    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. Suyuan Luo & Tsan‐Ming Choi, 2022. "E‐commerce supply chains with considerations of cyber‐security: Should governments play a role?," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2107-2126, May.
    2. Park, YoungSoo & Sim, Jeongeun & Kim, Bosung, 2022. "Online retail operations with “Try-Before-You-Buy”," European Journal of Operational Research, Elsevier, vol. 299(3), pages 987-1002.
    3. Davazdahemami, Behrooz & Kalgotra, Pankush & Zolbanin, Hamed M. & Delen, Dursun, 2023. "A developer-oriented recommender model for the app store: A predictive network analytics approach," Journal of Business Research, Elsevier, vol. 158(C).
    4. Zhang, Junhui & Balaji, M.S. & Luo, Jun & Jha, Subhash, 2022. "Effectiveness of product recommendation framing on online retail platforms," Journal of Business Research, Elsevier, vol. 153(C), pages 185-197.
    5. Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2019. "Cross-efficiency evaluation in data envelopment analysis based on prospect theory," European Journal of Operational Research, Elsevier, vol. 273(1), pages 364-375.
    6. Ghasemaghaei, Maryam & Calic, Goran, 2019. "Does big data enhance firm innovation competency? The mediating role of data-driven insights," Journal of Business Research, Elsevier, vol. 104(C), pages 69-84.
    7. Bernd Heinrich & Marcus Hopf & Daniel Lohninger & Alexander Schiller & Michael Szubartowicz, 2022. "Something’s Missing? A Procedure for Extending Item Content Data Sets in the Context of Recommender Systems," Information Systems Frontiers, Springer, vol. 24(1), pages 267-286, February.
    8. Gupta, Mukul & Kumar, Pradeep, 2020. "Recommendation generation using personalized weight of meta-paths in heterogeneous information networks," European Journal of Operational Research, Elsevier, vol. 284(2), pages 660-674.
    9. K. Coussement & K. W. Bock & S. Geuens, 2022. "A decision-analytic framework for interpretable recommendation systems with multiple input data sources: a case study for a European e-tailer," Annals of Operations Research, Springer, vol. 315(2), pages 671-694, August.
    10. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    11. Leogrande, Angelo, 2021. "The Destruction of Price-Representativeness," MPRA Paper 111239, University Library of Munich, Germany.
    12. Correa, Juan C. & Garzón, Wilmer & Brooker, Phillip & Sakarkar, Gopal & Carranza, Steven A. & Yunado, Leidy & Rincón, Alejandro, 2019. "Evaluation of collaborative consumption of food delivery services through web mining techniques," Journal of Retailing and Consumer Services, Elsevier, vol. 46(C), pages 45-50.
    13. Nguyen Anh Khoa Dam & Thang Le Dinh & William Menvielle, 2019. "A systematic literature review of big data adoption in internationalization," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 182-195, September.
    14. Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    15. Amit Kumar Gupta & Harshit Goyal, 2021. "Framework for implementing big data analytics in Indian manufacturing: ISM-MICMAC and Fuzzy-AHP approach," Information Technology and Management, Springer, vol. 22(3), pages 207-229, September.
    16. Liedong, Tahiru Azaaviele & Rajwani, Tazeeb & Lawton, Thomas C., 2020. "Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    17. Gianluca Vitale & Sebastiano Cupertino & Angelo Riccaboni, 2020. "Big data and management control systems change: the case of an agricultural SME," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 123-152, April.
    18. Alshawawreh, Ali Ra’Ed & Liébana-Cabanillas, Francisco & Blanco-Encomienda, Francisco Javier, 2024. "Impact of big data analytics on telecom companies' competitive advantage," Technology in Society, Elsevier, vol. 76(C).
    19. Czakon, Wojciech & Mania, Karolina & Jedynak, Monika & Kuźniarska, Aneta & Choiński, Michał & Dabić, Marina, 2024. "Who are we? Analyzing the digital identities of organizations through the lens of micro-interactions on social media," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    20. Vakeel, Khadija Ali & Fudurić, Morana & Malthouse, Edward C., 2021. "Extending variety seeking to multi-sided platforms: Impact of new retailer listing," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).

    More about this item

    Keywords

    Smart e-commerce systems; Big data analytics; Cloud computing; Internet of things; Complex systems;
    All these keywords.

    JEL classification:

    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

    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:elmark:v:29:y:2019:i:2:d:10.1007_s12525-017-0272-3. 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.