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Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/111943
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| Title: | A review of data monetization: Strategic use of big data |
| Authors: | 陳春龍
Liu, Chien Hung
Chen, Chuen Lun |
| Contributors: | 資訊管理學系 |
| Date: | 2015-12 |
| Issue Date: | 2017-08-14 15:36:10 (UTC+8) |
| Abstract: | In this data-rich big data age, industries are capable to collect data that could not be imagined before. Many industries today are now thinking of how to better use these data assets properly to generate value, either for internal or external purpose. Data monetization is adopted as one of strategies used to create additional stream of revenue from the discovery, capture, storage, analysis, dissemination, and use of that data. It gains in popularity among different industries. The three research question s of interest to this study are: (1) what does data monetization mean to business; (2) what are types of data monetization and industries currently use; (3) how to initiate a data monetization strategy. To address these questions, this study did a comprehensive review of prior research from academia as well as from industry. This study clarifies and defines the data monetization, presents the synthesis of use cases learned from other industries as well as provides guiding principles of how to start with data monetization. The contributions of this study are twofold. First, this paper contributes to industry communities that start to explore opportunities of creating value from their data assets but lack of directions and how to. Second, this study contributes to raise awareness of academic communities over the potential of big data monetization research and the opportunities in further discussing the converging information system and strategy domain. |
| Relation: | Proceedings of the International Conference on Electronic Business (ICEB), 2015-January, 40-46
15th International Conference on Electronic Business, ICEB 2015; Hyatt Regency Hotel, CUHKSha Tin; Hong Kong; 6 December 2015 到 10 December 2015; 代碼 118797 |
| Data Type: | conference |
| Appears in Collections: | [資訊管理學系] 會議論文
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