TOPSIS Enabled Trustworthiness in Crowdsourcing using the Fuzzy Logic-powered Blockchain

With the rapid increase in crowd service workers fueled by broader adaptation of crowd services, the trustworthiness of a crowd service offered by a worker is vital. Evaluating the solutions offered by different workers presents two challenges: (i) selecting the best crowd service alternate and (ii) criteria- level trustworthiness assessment of the selected crowd service. We propose a Crowd Service Trustworthiness (CrowdST) model, which selects the best crowd service alternative using TOPSIS (a multi-criteria decision-making method) and applies a fuzzy logic-based Max-Min Composition method to provide criteria- level trustworthiness assessment. In this way, the crowd service requester's criteria-level requirements can be better catered. Moreover, to further enable trust in the crowd (both requester and worker), we have studied the implications of using CrowdST in a decentralized environment, including gas costs. Our solution provides greater flexibility to all the stakeholders – requesters can get customized crowd service based on their trustworthiness requirements, and crowd service workers can work on the criteria that have a scope for improvements.