We consider a newsvendor setting where the newsvendor elicits a demand forecast from an expert to determine the optimal inventory level for a product. Since the interests of both parties might not be aligned, we propose a proper scoring rule to elicit the expert's forecast that is tailored to the decision problem the newsvendor faces. Under the proposed scoring rule, both the newsvendor's expected profit and the expert's expected payment increase as the expert exerts a higher effort when gathering information to formulate a forecast. Trust issues arise in this setting because the ex post payment the expert receives is contingent on the accuracy of the reported forecast, which in turn depends on a future realized outcome that might be only available to the newsvendor. We show that coding the proposed proper scoring rule as a blockchain-based smart contract allows the newsvendor to signal trustworthiness while, at the same time, inducing the expert to devote more effort in information gathering. Following the design science research framework, we conclude the paper by suggesting a design and a fully functional prototype of a blockchain-based smart contract that implements the proposed tailored proper scoring rule.

我们考虑报摊设置，报摊从专家那里得到需求预测，以确定产品的最佳库存水平。由于双方的利益可能不一致，我们提出了一个适当的评分规则来得出专家的预测，该预测是针对报贩面临的决策问题量身定制的。根据提议的评分规则，随着专家在收集信息以制定预测时付出更大的努力，报贩的预期利润和专家的预期报酬都会增加。在这种情况下会出现信任问题，因为事后专家收到的报酬取决于所报告预测的准确性，而这反过来又取决于可能只有报贩才能获得的未来实现的结果。我们表明，将提议的适当评分规则编码为基于区块链的智能合约，可以让报贩表示可信度，同时诱导专家在信息收集方面投入更多精力。遵循设计科学研究框架，我们通过提出一种基于区块链的智能合约的设计和全功能原型来结束本文，该智能合约实现了所提出的量身定制的适当评分规则。