| Title |
How can organizations leverage big data to innovate their business models? A systematic literature review |
| ID_Doc |
19544 |
| Authors |
Acciarini, C; Cappa, F; Boccardelli, P; Oriani, R |
| Title |
How can organizations leverage big data to innovate their business models? A systematic literature review |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.technovation.2023.102713 |
| Abstract |
The use of big data has garnered increasing importance in academic research and managerial practice thanks to the benefits it can produce in terms of innovation. However, big data also has drawbacks that have been overlooked so far. Therefore, to ensure the benefits outweigh the costs of big data, and to unlock the full potential of big data in terms of business model innovation, we argue that companies need to have a clear map of all its possible uses. With this aim in mind, we have summarized the current state of scholarship, outlined the uses of big data across different business areas in private and public organizations, and the types of methodologies adopted, and we have suggested future research avenues, building upon our systematic literature review of 311 articles indexed in the Scopus database. In this manner, we contribute to increasing our scientific understanding of the big data phenomenon, and we provide theoretical and practical advice on the possible uses of big data that may allow companies to innovate their business models. |
| Author Keywords |
Big data; Value creation; Value capture; Value delivery; Business model; Business model innovation; Systematic literature review |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000944452400001 |
| WoS Category |
Engineering, Industrial; Management; Operations Research & Management Science |
| Research Area |
Engineering; Business & Economics; Operations Research & Management Science |
| PDF |
https://doi.org/10.1016/j.technovation.2023.102713
|