On a Certain Research Gap in Big Data Mining for Customer Insights
The main purpose of this paper is to provide a theoretically grounded discussion on big data mining for customer insights, as well as to identify and describe a research gap due to the shortcomings in the use of the temporal approach in big data analyzes in scientific literature sources. This articl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/15/6993 |
| _version_ | 1797525765381685248 |
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| author | Maria Mach-Król Bartłomiej Hadasik |
| author_facet | Maria Mach-Król Bartłomiej Hadasik |
| author_sort | Maria Mach-Król |
| collection | DOAJ |
| description | The main purpose of this paper is to provide a theoretically grounded discussion on big data mining for customer insights, as well as to identify and describe a research gap due to the shortcomings in the use of the temporal approach in big data analyzes in scientific literature sources. This article adopts two research methods. The first method is the systematic search in bibliographic repositories aimed at identifying the concepts of big data mining for customer insights. This method has been conducted in four steps: search, selection, analysis, and synthesis. The second research method is the bibliographic verification of the obtained results. The verification consisted of querying the Scopus database with previously identified key phrases and then performing trend analysis on the revealed Scopus results. The main contributions of this study are: (1) to organize knowledge on the role of advanced big data analytics (BDA), mainly big data mining in understanding customer behavior; (2) to indicate the importance of the temporal dimension of customer behavior; and (3) to identify an interesting research gap: mining of temporal big data for a complete picture of customers. |
| first_indexed | 2024-03-10T09:18:38Z |
| format | Article |
| id | doaj.art-3745e3ac1de24ea9a58937a79baeea7d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:18:38Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-3745e3ac1de24ea9a58937a79baeea7d2023-11-22T05:22:43ZengMDPI AGApplied Sciences2076-34172021-07-011115699310.3390/app11156993On a Certain Research Gap in Big Data Mining for Customer InsightsMaria Mach-Król0Bartłomiej Hadasik1Department of Business Informatics, University of Economics in Katowice, ul. 1 Maja 50, 40-287 Katowice, PolandDepartment of Business Informatics, University of Economics in Katowice, ul. 1 Maja 50, 40-287 Katowice, PolandThe main purpose of this paper is to provide a theoretically grounded discussion on big data mining for customer insights, as well as to identify and describe a research gap due to the shortcomings in the use of the temporal approach in big data analyzes in scientific literature sources. This article adopts two research methods. The first method is the systematic search in bibliographic repositories aimed at identifying the concepts of big data mining for customer insights. This method has been conducted in four steps: search, selection, analysis, and synthesis. The second research method is the bibliographic verification of the obtained results. The verification consisted of querying the Scopus database with previously identified key phrases and then performing trend analysis on the revealed Scopus results. The main contributions of this study are: (1) to organize knowledge on the role of advanced big data analytics (BDA), mainly big data mining in understanding customer behavior; (2) to indicate the importance of the temporal dimension of customer behavior; and (3) to identify an interesting research gap: mining of temporal big data for a complete picture of customers.https://www.mdpi.com/2076-3417/11/15/6993customercustomer insighte-commercebig databig data miningtemporal approach |
| spellingShingle | Maria Mach-Król Bartłomiej Hadasik On a Certain Research Gap in Big Data Mining for Customer Insights Applied Sciences customer customer insight e-commerce big data big data mining temporal approach |
| title | On a Certain Research Gap in Big Data Mining for Customer Insights |
| title_full | On a Certain Research Gap in Big Data Mining for Customer Insights |
| title_fullStr | On a Certain Research Gap in Big Data Mining for Customer Insights |
| title_full_unstemmed | On a Certain Research Gap in Big Data Mining for Customer Insights |
| title_short | On a Certain Research Gap in Big Data Mining for Customer Insights |
| title_sort | on a certain research gap in big data mining for customer insights |
| topic | customer customer insight e-commerce big data big data mining temporal approach |
| url | https://www.mdpi.com/2076-3417/11/15/6993 |
| work_keys_str_mv | AT mariamachkrol onacertainresearchgapinbigdataminingforcustomerinsights AT bartłomiejhadasik onacertainresearchgapinbigdataminingforcustomerinsights |