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Identifying E-Commerce Processes Ιs Key to Sustainable Automation Using AI

Author

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  • Katarzyna Ragin-Skorecka
  • Karolina Grobelna
  • Filip Nowak

Abstract

Purpose: This study focuses on the analysis of the transformation of e-commerce processes from the AS IS model to TO BE, in particular on the application of artificial intelligence (AI) and global identification standards such as GTIN. The study aims to identify key areas and data in e-commerce that have the potential to implement modern IT solutions supporting sustainable development. The work fills the gap in the literature, taking into account both the aspects of process automation and the challenges related to the transparency and ethics of AI in e-commerce. Design/Methodology/Approach: The study is based on a qualitative research approach, including a systematic literature review and process analysis using BPMN 2.0 notation. The existing order and delivery process (AS IS) within the Allegro platform was analysed, identifying areas requiring improvement. Then, the TO BE model was developed, taking into account the use of AI and GTIN standards. The analysis process was supported by an expert method, which ensures the replicability of the results and their practical application in various e-commerce environments. Findings: The study found that integrating AI and GTIN standards significantly improves operational efficiency and sustainability of e-commerce processes. AI supports the automation of key stages, such as generating quotes, optimizing inventory management, and dynamically adjusting prices, which shortens order fulfilment times and increases their accuracy. GTIN enables interoperability of systems, eliminating manual errors and streamlining the exchange of information between process participants. At the same time, challenges related to the ethical use of AI were identified, including the need to ensure transparency of algorithms and the protection of customer data. Practical Implications: The results of the study have direct application in optimizing e-commerce processes, especially in the context of sustainable development. Automation and standardization of data can support companies in improving operational efficiency, increasing the quality of customer service and reducing costs. Recommendations on the responsible implementation of AI and transparency of algorithms can be valuable advice for decision-makers and industry practitioners. Originality/Value: The study provides an innovative perspective on integrating AI into e-commerce processes, especially in the context of sustainable development. The combination of automation, global identification standards and an ethical approach distinguishes the work from existing studies. The results expand knowledge on the practical application of AI in e-commerce and emphasize the importance of sustainable and responsible strategies in a dynamically developing sector.

Suggested Citation

  • Katarzyna Ragin-Skorecka & Karolina Grobelna & Filip Nowak, 2024. "Identifying E-Commerce Processes Ιs Key to Sustainable Automation Using AI," European Research Studies Journal, European Research Studies Journal, vol. 0(Special A), pages 621-633.
    • Handle: RePEc:ers:journl:v:xxvii:y:2024:i:speciala:p:621-633
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    References listed on IDEAS

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    1. Ransome Epie Bawack & Samuel Fosso Wamba & Kevin Daniel André Carillo & Shahriar Akter, 2022. "Artificial intelligence in E-Commerce: a bibliometric study and literature review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 297-338, March.
    2. Laith T. Khrais, 2020. "Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce," Future Internet, MDPI, vol. 12(12), pages 1-14, December.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    E-commerce; business process; artificial intelligence; BPMN; sustainability.;
    All these keywords.

    JEL classification:

    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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