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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
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    References listed on IDEAS

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    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. Lee, In, 2017. "Big data: Dimensions, evolution, impacts, and challenges," Business Horizons, Elsevier, vol. 60(3), pages 293-303.
    3. 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.
    4. Philip Anderson, 1999. "Perspective: Complexity Theory and Organization Science," Organization Science, INFORMS, vol. 10(3), pages 216-232, June.
    5. 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).
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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).
    16. 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.
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    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. 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.
    3. 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.

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    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

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