| Title |
Is transparency the new green? How business model transparency influences digital service adoption |
| ID_Doc |
62241 |
| Authors |
Trabucchi, D; Patrucco, AS; Buganza, T; Marzi, G |
| Title |
Is transparency the new green? How business model transparency influences digital service adoption |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.technovation.2023.102803 |
| Abstract |
The proliferation of data-driven business models raises privacy concerns, as users often perceive a lack of transparency in how companies use their data. This study explores how business model transparency (and the absence of it) influences users' decisions to adopt a digital service. We propose a model grounded in rational choice theory, tested through multigroup structural equation modeling. Data were collected through a field experiment that exposed users to two different mock-ups characterized by varying levels of transparency related to data usage. The results show that the level of transparency does not directly influence users' willingness to adopt the service. Switching from a transparent to an opaque data-driven business model negatively affects users' willingness to adopt a service. Such findings remark on the users' service adoption decision-making process criteria, which are highly influenced by perceived data usage transparency. Consequently, this study introduces a user perspective on data-driven business models. It conveys to managers the importance of transparency when business models are grounded in data-driven strategies and data exploitation. |
| Author Keywords |
Business model; Transparency; Platforms; Privacy; Digital; Service; Adoption; Business Model Innovation; BMI |
| 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:001028124800001 |
| 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.2023.102803
|