Have a personal or library account? Click to login
Using Data Mining to Improve Decision-Making: Case Study of A Recommendation System Development Cover

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

Organizacija
Volume 56 (2023): Issue 2 (May 2023)
By:
Open Access
|May 2023

References

  1. Altekin, F. T., Aylı, E., & Şahin, G. (2017). After-sales services network design of a household appliances manufacturer. Journal of the Operational Research Society, 68(9), 1056-1067. DOI:<a href="https://doi.org/10.1057/s41274-016-0142-y." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1057/s41274-016-0142-y.</a>
    Search in Google ScholarBack to article
  2. Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlstrom, P., Henke, N. and Trench, M. (2017). Artificial intelligence: the next digital frontier?. McKinsey Global Institute, pp.1-80.
    Search in Google ScholarBack to article
  3. Bumblauskas, D., Nold, H., Bumblauskas, P., & Igou, A. (2017). Big data analytics: transforming data to action. Business Process Management Journal, pp.703-720. DOI: <a href="https://doi.org/10.1108/BPMJ-03-2016-0056." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1108/BPMJ-03-2016-0056.</a>
    Search in Google ScholarBack to article
  4. Capozzoli, A., Cerquitelli, T., and Piscitelli, M. S. (2016). Enhancing energy efficiency in buildings through innovative data analytics technologies. Next Generation Platforms for Intelligent Data Collection; Dobre, C., Xhafa, F., Eds, 353-389. DOI: <a href="https://doi.org/10.1016/B978-0-12-803663-1.00011-5." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1016/B978-0-12-803663-1.00011-5.</a>
    Search in Google ScholarBack to article
  5. Chen, W. J., Kamath, R., Kelly, A., Lopez, H. H. D., Roberts, M., & Yheng, Y. P. (2015). Systems of insight for digital transformation: Using IBM operational decision manager advanced and predictive analytics. IBM Redbooks.
    Search in Google ScholarBack to article
  6. Deloitte, L. (2018). Digital maturity model achieving digital maturity to drive growth. In Presentation of Deloitte, TM Forum Digital Maturity Model, Feb.
    Search in Google ScholarBack to article
  7. Durugbo, C. M. (2020). After-sales services and aftermarket support: a systematic review, theory and future research directions. International Journal of Production Research, 58(6), 1857-1892. DOI: <a href="https://doi.org/10.1080/00207543.2019.1693655." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1080/00207543.2019.1693655.</a>
    Search in Google ScholarBack to article
  8. Dušanka, D., Darko, S., Srdjan, S., Marko, A., & Teodora, L. (2017). A comparison of contemporary data mining tools. In XVII International Scientific Conference on Industrial Systems (pp. 150-155). Retrieved from: https://www.iim.ftn.uns.ac.rs/is17/papers/27.pdf.
    Search in Google ScholarBack to article
  9. Eremina, Y., Lace, N., & Bistrova, J. (2019). Digital maturity and corporate performance: The case of the Baltic states. Journal of open innovation: technology, market, and complexity, 5(3), 54. DOI: <a href="https://doi.org/10.3390/joitmc5030054." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.3390/joitmc5030054.</a>
    Search in Google ScholarBack to article
  10. Felch, V., Asdecker, B., & Sucky, E. (2019). Maturity models in the age of Industry 4.0–Do the available models correspond to the needs of business practice?. Proceedings of the 52nd Hawaii International Conference on System Sciences (pp. 5165–5174). DOI: <a href="https://doi.org/10.24251/HICSS.2019.620." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.24251/HICSS.2019.620.</a>
    Search in Google ScholarBack to article
  11. Galetsi, P., Katsaliaki, K., & Kumar, S. (2020). Big data analytics in health sector: Theoretical framework, techniques and prospects. International Journal of Information Management, 50, 206-216. DOI: <a href="https://doi.org/10.1016/j.ijinfomgt.2019.05.003." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1016/j.ijinfomgt.2019.05.003.</a>
    Search in Google ScholarBack to article
  12. Gimpel, H., Hosseini, S., Huber, R., Probst, L., Röglinger, M., & Faisst, U. (2018). Structuring digital transformation: a framework of action fields and its application at ZEISS. Journal of Information Technology Theory and Application (JITTA), 19(1), 3. Retrieved from: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1726&context= jitta.
    Search in Google ScholarBack to article
  13. Golrizgashti, S., Hejaz, A. R., & Farshianabbasi, K. (2020). Assessing after-sales services quality: integrated SERVQUAL and fuzzy Kano’s model. International Journal of Services, Economics and Management, 11(2), 137-166. DOI: <a href="https://doi.org/10.1504/IJSEM.2020.10031218." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1504/IJSEM.2020.10031218.</a>
    Search in Google ScholarBack to article
  14. Guzovski, M.., Smoljić, M.., & Martinčević, I. . (2022). Creating Value for Clients using a Holistic Approach in Banking Marketing.   ENTRENOVA - ENTerprise REsearch InNOVAtion, 8(1), 80–90. DOI: <a href="https://doi.org/10.54820/entrenova-2022-0008." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.54820/entrenova-2022-0008.</a>
    Search in Google ScholarBack to article
  15. Hausberg, J. P., Liere-Netheler, K., Packmohr, S., Pakura, S., & Vogelsang, K. (2019). Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis. Journal of Business Economics, 89(8), 931-963. DOI: <a href="https://doi.org/10.1007/s11573-019-00956-z." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/s11573-019-00956-z.</a>
    Search in Google ScholarBack to article
  16. Ikenna, O., Ifeanyi, N., Justina, R., Nnamdi, N., Anuli, U., & Paul, N. (2014). Review of data mining as a tool for organisation’s growth and productivity. IJCSMC, 9(3), 284-290. Retrieved from: https://ijcsmc.com/docs/papers/ September2014/V3I9201433.pdf.
    Search in Google ScholarBack to article
  17. Jadhav, S. D., & Channe, H. P. (2016). Comparative study of K-NN, naive Bayes and decision tree classification techniques. International Journal of Science and Research (IJSR), 5(1), 1842-1845. Retrieved from: https://www.ijsr.net/archive/v5i1/NOV153131.pdf.
    Search in Google ScholarBack to article
  18. Jintana, J., Sopadang, A., & Ramingwong, S. (2021). Idea selection of new service for courier business: The opportunity of data analytics. International Journal of Engineering Business Management, 13, 18479790211042191. DOI: <a href="https://doi.org/10.1177/18479790211042191." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1177/18479790211042191.</a>
    Search in Google ScholarBack to article
  19. Jovic, A., Brkic, K., & Bogunovic, N. (2014, May). An overview of free software tools for general data mining. In 2014 37th International convention on information and communication technology, electronics and microelectronics (MIPRO) (pp. 1112-1117). IEEE. DOI: <a href="https://doi.org/10.1109/MIPRO.2014.6859735" target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1109/MIPRO.2014.6859735</a>
    Search in Google ScholarBack to article
  20. Kaur, K., & Dhiman, S. (2016). Review of data mining with Weka tool. International Journal of Computer Sciences and Engineering, 4(8), 41-44. Retrieved from: https://www.ijcseonline.org/pub_paper/IJCSE-01768.pdf.
    Search in Google ScholarBack to article
  21. Lundkvist, E. (2014). Decision tree classification and forecasting of pricing time series data. Master’s Degree Project. KTH, School of Electrical Engineering (EES), Automatic Control. Retrieved from: http://www.diva-portal.org/smash/get/diva2:746332/fulltext01.pdf.
    Search in Google ScholarBack to article
  22. Morakanyane, R., Grace, A. A., & O’reilly, P. (2017). Conceptualizing Digital Transformation in Business Organizations: A Systematic Review of Literature. Bled eConference, 21, 428-444. DOI: <a href="https://doi.org/10.18690/978-961-286-043-1.30." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.18690/978-961-286-043-1.30.</a>
    Search in Google ScholarBack to article
  23. 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, 30, 67-83. DOI: <a href="https://doi.org/10.1016/j.jretconser.2016.01.001." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1016/j.jretconser.2016.01.001.</a>
    Search in Google ScholarBack to article
  24. Mydyti, H. (2021b). Data Mining Approach Improving Decision-Making Competency along the Business Digital Transformation Journey: A Case Study–Home Appliances after Sales Service. Seeu Review, 16(1), 45-65. DOI: <a href="https://doi.org/10.2478/seeur-2021-0008." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2478/seeur-2021-0008.</a>
    Search in Google ScholarBack to article
  25. Mydyti, H. (2022). Data Mining Approach Improving Decision-Making Competency Along the Business Digital Transformation Journey. [Unpublished doctoral thesis dissertation]. Faculty of Computer Sciences, SEE University, North Macedonia.
    Search in Google ScholarBack to article
  26. Mydyti, H., & Kadriu, A. (2021a, August). Data Mining Approach Improving Decision-Making Competency Along the Business Digital Transformation Journey: A Literature Review. In International Conference for Emerging Technologies in Computing (pp. 129-146). Springer, Cham. DOI: <a href="https://doi.org/10.1007/978-3-030-90016-8_9." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/978-3-030-90016-8_9.</a>
    Search in Google ScholarBack to article
  27. Mydyti, H., & Kadriu, A. (2021c). The Impact of Chatbots in Driving Digital Transformation. International Journal of E-Services and Mobile Applications (IJESMA), 13(4), 88-104. DOI: <a href="https://doi.org/10.4018/IJESMA.2021100106." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.4018/IJESMA.2021100106.</a>
    Search in Google ScholarBack to article
  28. Nguyen, B., Nguyen, V. H., & Ho, T. (2021). Sentiment analysis of customer feedbacks in online food ordering services. Business Systems Research: International journal of the Society for Advancing Innovation and Research in Economy, 12(2), 46-59. DOI: <a href="https://doi.org/10.2478/bsrj-2021-0018." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2478/bsrj-2021-0018.</a>
    Search in Google ScholarBack to article
  29. Orfanidis, P. (2018). Prominence of big data in the digital transformation era. [Unpublished master thesis dissertation]. School of Economics, Business Administration & Legal Studies, Thessaloniki – Greece. Retrieved from: https://core.ac.uk/download/pdf/236205144.pdf.
    Search in Google ScholarBack to article
  30. Othman, B. A., Harun, A., De Almeida, N. M., & Sadq, Z. M. (2020). The effects on customer satisfaction and customer loyalty by integrating marketing communication and after sale service into the traditional marketing mix model of Umrah travel services in Malaysia. Journal of Islamic Marketing, 12(2), 363-388. DOI: <a href="https://doi.org/10.1108/JIMA-09-2019-0198." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1108/JIMA-09-2019-0198.</a>
    Search in Google ScholarBack to article
  31. Palmer, A., Jiménez, R., & Gervilla, E. (2011). Data mining: Machine learning and statistical techniques. Knowledge-Oriented Applications in Data Mining, Prof. Kimito Funatsu (Ed.), 373-396. DOI: <a href="https://doi.org/10.5772/13621." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.5772/13621.</a>
    Search in Google ScholarBack to article
  32. Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of retailing, 64(1), 12-40. Retrieved from: https://psycnet.apa.org/record/1989-10632-001.
    Search in Google ScholarBack to article
  33. Pejić Bach, M., Bertoncel, T., Meško, M., Suša Vugec, D., & Ivančić, L. (2020a). Big data usage in european countries: Cluster analysis approach.   Data, 5(1), 25. DOI: <a href="https://doi.org/10.3390/data5010025." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.3390/data5010025.</a>
    Search in Google ScholarBack to article
  34. Pejić Bach, M., Pivar, J., & Jaković, B. (2021). Churn management in telecommunications: Hybrid approach using cluster analysis and decision trees. Journal of Risk and Financial Management, 14(11), 544. <a href="https://doi.org/10.3390/jrfm14110544." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">https://doi.org/10.3390/jrfm14110544.</a>
    Search in Google ScholarBack to article
  35. Pejić Bach, M., Topalović, A., & Turulja, L. (2022). Data mining usage in Italian SMEs: an integrated SEM-ANN approach. Central European Journal of Operations Research, 1-33. DOI: <a href="https://doi.org/10.1007/s10100-022-00829-x." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/s10100-022-00829-x.</a>
    Search in Google ScholarBack to article
  36. Pejić Bach, M., Dumičić, K., Žmuk, B., & Ćurlin, T. (2020b). Data mining approach to internal fraud in a project-based organization. International Journal of Information Systems and Project Management, 8(2), 81-101. DOI: <a href="https://doi.org/10.12821/ijispm080204." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.12821/ijispm080204.</a>
    Search in Google ScholarBack to article
  37. Pejić Bach, M., Pivar, J., & Krstić, Ž. (2019). Big data for prediction: patent analysis–patenting big data for prediction analysis. In  Big Data Governance and Perspectives in Knowledge Management  (pp. 218-240). IGI Global. DOI: <a href="https://doi.org/10.4018/978-1-5225-7077-6.ch010." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.4018/978-1-5225-7077-6.ch010.</a>
    Search in Google ScholarBack to article
  38. Phorncharoen, I. (2020). Influence of market orientation, learning orientation, and innovativeness on operational performance of real estate business. International Journal of Engineering Business Management, 12, 1847979020952672. DOI: <a href="https://doi.org/10.1177/1847979020952672." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1177/1847979020952672.</a>
    Search in Google ScholarBack to article
  39. Prabhu, C. S. R., Chivukula, A. S., Mogadala, A., Ghosh, R., & Livingston, L. M. (2019). Big data analytics. In Big data analytics: systems, algorithms, applications (pp. 1-23). Springer, Singapore. DOI: <a href="https://doi.org/10.1007/978-981-15-0094-7." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/978-981-15-0094-7.</a>
    Search in Google ScholarBack to article
  40. Ragab, A. H. M., Noaman, A. Y., Al-Ghamdi, A. S., & Madbouly, A. I. (2014, June). A comparative analysis of classification algorithms for students college enrollment approval using data mining. In Proceedings of the 2014 Workshop on Interaction Design in Educational Environments (pp. 106-113). DOI: <a href="https://doi.org/10.1145/2643604.2643631." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1145/2643604.2643631.</a>
    Search in Google ScholarBack to article
  41. Ramya, N., Kowsalya, A., & Dharanipriya, K. (2019). Service quality and its dimensions. EPRA International Journal of Research & Development, 4(2). Retrieved from: https://eprajournals.com/IJSR/article/1196.
    Search in Google ScholarBack to article
  42. Rogić, S., Kašćelan, L., & Pejić Bach, M. (2022). Customer Response Model in DirectMarketing: Solving the Problem of Unbalanced Dataset with a Balanced Support Vector Machine. Journal of Theoretical and Applied Electronic Commerce Research, 17(3), 1003-1018. DOI: <a href="https://doi.org/10.3390/jtaer17030051." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.3390/jtaer17030051.</a>
    Search in Google ScholarBack to article
  43. Rokach, L., & Maimon, O. (2005). Decision trees. In Data mining and knowledge discovery handbook (pp. 165-192). Springer, Boston, MA. DOI: <a href="https://doi.org/10.1007/0-387-25465-X_9." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/0-387-25465-X_9.</a>
    Search in Google ScholarBack to article
  44. Rudnick, M., Riezebos, J., Powell, D. J., & Hauptvogel, A. (2020). Effective after-sales services through the lean servitisation canvas. International Journal of Lean Six Sigma. DOI: <a href="https://doi.org/10.1108/IJLSS-07-2017-0082." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1108/IJLSS-07-2017-0082.</a>
    Search in Google ScholarBack to article
  45. Sadiku, N., Adebo, O., & Musa, M. (2018). Big data in business. International Journal of Advanced Research in Computer Science and Software Engineering, 8(1), 160-162. Retrieved from: https://www.researchgate.net/publication/323595185_big_data_in_business.
    Search in Google ScholarBack to article
  46. Saeed, T. (2020). Data Mining for Small and Medium Enterprises: A Conceptual Model for Adaptation. Intelligent Information Management, 12(5), 183-197. DOI: <a href="https://doi.org/10.4236/iim.2020.125011." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.4236/iim.2020.125011.</a>
    Search in Google ScholarBack to article
  47. Salihu, A., & Shehu, V. (2020). A Review of Algorithms for Credit Risk Analysis. ENTRENOVA - ENTerprise REsearch InNOVAtion, 6(1), 134–146. Retrieved from https://hrcak.srce.hr/ojs/index.php/entrenova/article/view/13445
    Search in Google ScholarBack to article
  48. Schwertner, K. (2017). Digital transformation of business. Trakia Journal of Sciences, 15(1), 388-393. Retrueved from: http://tru.uni-sz.bg/tsj/TJS_Suppl.1_Vol.15_2017/65.pdf.
    Search in Google ScholarBack to article
  49. Selimi, M., & Besimi, A. (2019). A Proposed Model for Stock Price Prediction Based on Financial News. ENTRENOVA - ENTerprise REsearch InNOVAtion, 5(1), 68–75. Retrieved from https://hrcak.srce.hr/ojs/index.php/entrenova/article/view/13732
    Search in Google ScholarBack to article
  50. Sharma, B. R., Kaur, D., & Manju, A. (2013). Review on data mining: its challenges, issues and applications. International Journal of Current Engineering and Technology, 3(2), 695-700. Retrieved from: https://inpressco.com/wp-content/uploads/2013/06/Paper85695-700.pdf.
    Search in Google ScholarBack to article
  51. Sima, V., Gheorghe, I. G., Subić, J., & Nancu, D. (2020). Influences of the industry 4.0 revolution on the human capital development and consumer behavior: A systematic review. Sustainability, 12(10), 4035. DOI: <a href="https://doi.org/10.3390/su12104035." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.3390/su12104035.</a>
    Search in Google ScholarBack to article
  52. Tangirala, S. (2020). Evaluating the impact of GINI index and information gain on classification using decision tree classifier algorithm. International Journal of Advanced Computer Science and Applications, 11(2), 612-619. DOI: <a href="https://doi.org/10.14569/IJACSA.2020.0110277." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.14569/IJACSA.2020.0110277.</a>
    Search in Google ScholarBack to article
  53. Telegescu, T. (2018, May). IT in the workspace–The need for digital transformation. In Proceedings of the International Conference on Business Excellence (Vol. 12, No. 1, pp. 952-965). DOI: <a href="https://doi.org/10.2478/picbe-2018-0085." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2478/picbe-2018-0085.</a>
    Search in Google ScholarBack to article
  54. Topalović, A., & Azzini, A. (2020). Data mining applications in SMEs: an Italian perspective.   Business Systems Research: International journal of the Society for Advancing Innovation and Research in Economy, 11(3), 127-146. DOI: <a href="https://doi.org/10.2478/bsrj-2020-0031." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.2478/bsrj-2020-0031.</a>
    Search in Google ScholarBack to article
  55. ur Rehman, M. H., Yaqoob, I., Salah, K., Imran, M., Jayaraman, P. P., & Perera, C. (2019). The role of big data analytics in industrial Internet of Things. Future Generation Computer Systems, 99, 247-259. DOI: <a href="https://doi.org/10.1016/j.future.2019.04.020." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1016/j.future.2019.04.020.</a>
    Search in Google ScholarBack to article
  56. Valdez-de-Leon, O. (2016). A digital maturity model for telecommunications service providers. Technology innovation management review, 6(8). DOI: <a href="https://doi.org/10.22215/timreview/1008." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.22215/timreview/1008.</a>
    Search in Google ScholarBack to article
  57. Vivekananth, P., & Baptist, A. (2015). An analysis of big data analytics techniques. International Journal of Engineering and Management Research (IJEMR), 5(5), 17-19. Retrieved from: https://www.academia.edu/41448400/An_Analysis_of_Big_Data_Analytics_Techniques.
    Search in Google ScholarBack to article
  58. West, D. M., & Allen, J. R. (2018). How artificial intelligence is transforming the world. Report. April, 24, 2018.
    Search in Google ScholarBack to article
  59. Wickramasinghe, V., & Mathusinghe, K. (2016). After-sales services of home appliances: evidence from S ri Lanka. International Journal of Consumer Studies, 40(1), 115-124. DOI: <a href="https://doi.org/10.1111/ijcs.12229." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1111/ijcs.12229.</a>
    Search in Google ScholarBack to article
  60. Wiesböck, F., & Hess, T. (2018). Understanding the capabilities for digital innovations from a digital technology perspective (No. 1/2018). Arbeitsbericht. Retrieved from: https://www.dmm.bwl.uni-muenchen.de/download/ epub/mreport_2018_01.pdf.
    Search in Google ScholarBack to article
  61. Williams, C., Schallmo, D., Lang, K., & Boardman, L. (2019). Digital maturity models for small and medium- sized enterprises: a systematic literature review. In ISPIM Conference Proceedings (pp. 1-15). The International Society for Professional Innovation Management (ISPIM). Retrieved from: https://publications.hs-neu-ulm.de/1518/.
    Search in Google ScholarBack to article
  62. Zain, M. S. I. M., & Rahman, S. A. (2017). Challenges of applying data mining in knowledge management towards organisation. International Journal of Academic Research in Business and Social Sciences, 7(12), 405-412.DOI: <a href="https://doi.org/10.6007/IJARBSS/v7-i12/3621." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.6007/IJARBSS/v7-i12/3621.</a>
    Search in Google ScholarBack to article
  63. Ziyadin, S., Suieubayeva, S., & Utegenova, A. (2019, April). Digital transformation in business. In International Scientific Conference “Digital Transformation of the Economy: Challenges, Trends, New Opportunities” (pp. 408-415). Springer, Cham. DOI: <a href="https://doi.org/10.1007/978-3-030-27015-5_49." target="_blank" rel="noopener noreferrer" class="text-signal-blue hover:underline">10.1007/978-3-030-27015-5_49.</a>
    Search in Google ScholarBack to article
DOI: https://doi.org/10.2478/orga-2023-0010 | Journal eISSN: 1581-1832 | Journal ISSN: 1318-5454
Journal RSS Feed
Language: English
Page range: 138 - 154
Submitted on: Feb 6, 2023
Accepted on: May 8, 2023
Published on: May 29, 2023
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
Keywords:
Digital transformation,
Data mining,
Decision tree algorithm,
Decision-making,
Home appliances after-sales services
Related subjects:
Business and economics,
Business management,
Management, organization, corporate governance

© 2023 Hyrmet Mydyti, Arbana Kadriu, Mirjana Pejic Bach, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Previous articleVolume 56 (2023): Issue 2 (May 2023)Next article