To alleviate difficulties in writing smart contracts for distributed blockchain applications, as other research, we propose transformation of Business Process Model and Notation (BPMN) models into blockchain smart contracts. Unlike other research, we use Discrete Event Hierarchical State Machine (DE-HSM) multi-modal modeling to identify collaborative trade transactions that need to be supported by the smart contract and describe how the trade transactions, that may be nested, are supported by a transaction mechanism. We describe algorithms to (i) identify the nested trade transactions and to (ii) transform the BPMN model into blockchains smart contracts that include a transaction mechanism to enforce the transactional properties for the identified trade transactions. The developed proof of concept shows that our approach to automated transformation of BPMN models into smart contracts with the support of privacy and cross-chain interoperability is feasible. The thesis examines and evaluates automatically generated alternative transaction mechanisms to support such transactions using three use cases of varying degree of complexity, namely order processing, supply chain management, and a multi-faceted trade use case. The research enriches the academic dialogue on blockchain technology and smart contracts and proposes potential avenues for future research.