Copycat issues and unreliable purchasing agents have challenged cross-border consumption and hurt the brands and online platforms significantly. We explicate a setting in which a platform orders from a brand, then sells and competes with the purchasing agents in an overseas market. Worried about the copycat issues, consumers undertake risk when purchasing from both platforms and agents. The blockchain adoption may help release this uncertainty by purchasing from a platform. We show the values and impacts of this new technology on the platform, brand and consumers. It is interesting to observe that the platform does not always have incentive to adopt blockchain, even if it is costless. In the presence of blockchain, we show that the revenue sharing, two-part tariff and profit sharing contracts can achieve supply chain coordination, but the cost sharing contract fails to do so. In the extended models, we discuss what will happen when the brand decides domestic retail price and the platform links optional information nodes to blockchain.

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At the beginning of the change in bearing condition, the bearing fault features are weak, often drowning in the background noise. It makes difficult to extract weak fault features from the vibration signal. If the fault features cannot be effectively extracted, the diagnostic accuracy will be greatly affected. Under this background, a fault diagnosis framework including two stages of signal enhancement and intelligent fault recognition is proposed in this work. Firstly, use a genetic algorithm to obtain the optimal combination of parameters, upon which the original fault signals are decomposed into intrinsic modal function components. Then, they are transformed into the spectrum signals and inputted into the proposed Bayesian network using dynamic weighted transfer learning (DWTL). This paper uses the DWTL method to set the source domain weight factor and the balance coefficient based on data quantity in different source and target domains.The DWTL method proposed in this paper can improve the fault diagnosis accuracy and effectively avoid the negative transfer phenomenon. An example of rolling bearing fault diagnosis is conducted. The results show that the accuracy of fault diagnosis based on the proposed framework is about 10% higher than that of other fault diagnosis methods. Therefore, the validity and feasibility of the proposed fault diagnosis framework are proved.

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