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Using Data Mining to Improve Decision-Making: Case Study of A Recommendation System Development

Author

Listed:
  • Mydyti Hyrmet

    (1 Universum International College, Faculty of Computer Science, Prishtina, Kosovo)

  • Kadriu Arbana

    (2 SEE University, Faculty of Computer Science, Tetovo, North Macedonia)

  • Pejic Bach Mirjana

    (3 University of Zagreb, Faculty of Economics and Business, Zagreb, Croatia)

Abstract

This study aims to provide a practical perspective on how data mining techniques are used in the home appliance after-sales services. Study investigates on how can a recommendation system help a customer service company that plans to use data mining to improve decision making during its digital transformation process. In addition, study provides a detailed outline on the process for developing and analyzing platforms to improve data analytics for such companies.

Suggested Citation

  • Mydyti Hyrmet & Kadriu Arbana & Pejic Bach Mirjana, 2023. "Using Data Mining to Improve Decision-Making: Case Study of A Recommendation System Development," Organizacija, Sciendo, vol. 56(2), pages 138-154, May.
    • Handle: RePEc:vrs:organi:v:56:y:2023:i:2:p:138-154:n:5
    DOI: 10.2478/orga-2023-0010
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    References listed on IDEAS

    as
    1. Hyrmet Mydyti & Arbana Kadriu, 2021. "The Impact of Chatbots in Driving Digital Transformation," International Journal of E-Services and Mobile Applications (IJESMA), IGI Global, vol. 13(4), pages 88-104, October.
    2. Murali, S. & Pugazhendhi, S. & Muralidharan, C., 2016. "Modelling and Investigating the relationship of after sales service quality with customer satisfaction, retention and loyalty – A case study of home appliances business," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 67-83.
    3. Christopher M. Durugbo, 2020. "After-sales services and aftermarket support: a systematic review, theory and future research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 58(6), pages 1857-1892, March.
    4. Salihu, Armend & Shehu, Visar, 2020. "A Review of Algorithms for Credit Risk Analysis," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 134-146, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    5. Muhammad Syamil Iman Mohd Zain & Safawi Abdul Rahman, 2017. "Challenges of Applying Data Mining in Knowledge Management towards Organization," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 7(12), pages 405-412, December.
    6. F. Tevhide Altekin & Ezgi Aylı & Güvenç Şahin, 2017. "After-sales services network design of a household appliances manufacturer," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 1056-1067, September.
    7. Wiesböck, Florian & Hess, Thomas, 2018. "Understanding the capabilities for digital innovations from a digital technology perspective," Working Papers 1/2018, University of Munich, Munich School of Management, Institute for Information Systems and New Media.
    8. Mirjana Pejić Bach & Tine Bertoncel & Maja Meško & Dalia Suša Vugec & Lucija Ivančić, 2020. "Big Data Usage in European Countries: Cluster Analysis Approach," Data, MDPI, vol. 5(1), pages 1-16, March.
    9. Seyedehfatemeh Golrizgashti & Amir Razavi Hejaz & Kimia Farshianabbasi, 2020. "Assessing after-sales services quality: integrated SERVQUAL and fuzzy Kano's model," International Journal of Services, Economics and Management, Inderscience Enterprises Ltd, vol. 11(2), pages 137-166.
    10. Violeta Sima & Ileana Georgiana Gheorghe & Jonel Subić & Dumitru Nancu, 2020. "Influences of the Industry 4.0 Revolution on the Human Capital Development and Consumer Behavior: A Systematic Review," Sustainability, MDPI, vol. 12(10), pages 1-28, May.
    11. J. Piet Hausberg & Kirsten Liere-Netheler & Sven Packmohr & Stefanie Pakura & Kristin Vogelsang, 2019. "Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis," Journal of Business Economics, Springer, vol. 89(8), pages 931-963, December.
    12. Selimi, Mubarek & Besimi, Adrian, 2019. "A Proposed Model for Stock Price Prediction Based on Financial News," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2019), Rovinj, Croatia, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019, pages 100-107, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    13. Mirjana Pejić Bach & Jasmina Pivar & Božidar Jaković, 2021. "Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees," JRFM, MDPI, vol. 14(11), pages 1-25, November.
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