Blockchain technology has evolved as a promising means to transform data management models in many domains including healthcare, agricultural research, tourism domains etc. In the research community, a usable blockchain-based system can allow users to create a proof of ownership and provenance of the research work, share research data without losing control and ownership of it, provide incentives for sharing and give users full transparency and control over who access their data, when and for what purpose. The initial adoption of such blockchain-based systems is necessary for continued use of the services, but their user acceptance behavioral model has not been well investigated in the literature. In this paper, we take the Technology Acceptance Model (TAM) as a foundation and extend the external constructs to uncover how the perceived ease of use, perceived usability, quality of the system and perceived enjoyment influence the intention to use the blockchain-based system. We based our study on user evaluation of a prototype of a blockchain-based research data sharing framework using a TAM validated questionnaire. Our results show that, overall, all the individual constructs of the behavior model significantly influence the intention to use the system while their collective effect is found to be insignificant. The quality of the system and the perceived enjoyment have stronger influence on the perceived usefulness. However, the effect of perceived ease of use on the perceived usefulness is not supported. Finally, we discuss the implications of our findings. Keywords-TAM, behavior model, blockchain, smart contract, data sharing, privacy, perceived ease of use, perceived usefulness, quality of system, perceived enjoyment, behavioral Intention

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We propose a new platform for user modeling with blockchains that allows users to share data without losing control and ownership of it and applied it to the domain of travel booking. Our new platform provides solution to three important problems: ensuring privacy and user control, and incentives for sharing. It tracks who shared what, with whom, when, by what means and for what purposes in a verifiable fashion. The paper presents a case study of applying the framework for a hotel reservation system as one of the enterprise nodes of Multichain which collects users' profile data and allows users to receive rewards while sharing their data with other travel service providers according to their privacy preferences expressed in smart contracts. The user data from the repository is converted into an open data format and shared via stream in the blockchain so that other nodes can efficiently process and use the data. The smart contract verifies and executes the agreed terms of use of the data and transfers digital tokens as a reward to the user. The smart contract imposes double deposit collateral to ensure that all participants act honestly. The paper also presents a performance evaluation of the new platform by analyzing latency and memory consumption with selected three test-scenarios and measuring the transaction cost for smart contracts deployment. The results show that the node responded quickly in all our cases with a befitting transaction cost.

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Currently, there is no universal method to track who shared what, with whom, when and for what purposes in a verifiable way to create an individual incentive for data owners. A platform that allows data owners to control, delete, and get rewards from sharing their data would be an important enabler of user data-sharing. We propose a usable blockchain-and smart contracts-based framework that allows users to store research data locally and share without losing control and ownership of it. We have created smart contracts for building automatic verification of the conditions for data access that also naturally supports building up a verifiable record of the provenance, incentives for users to share their data and accountability of access. The paper presents a review of the existing work of research data sharing, the proposed blockchain-based framework and an evaluation of the framework by measuring the transaction cost for smart contracts deployment. The results show that nodes responded quickly in all tested cases with a befitting transaction cost.