A co-utility approach to the mesh economy: the crowd-based business model

We explore the mesh economy applications of co-utility, a new concept describing self-enforcing and mutually beneficial interactions among self-interested agents. We show that the crowdsourcing market is naturally co-utile (without additional incentives). Furthermore, we analyze the investment crowdfunding industry and propose solutions that can neutralize the fear and mistrust effects underlying its market in order to make it strictly co-utile. Up on our analysis under the co-utility framework, we corroborate that collaboration is always rationally sustainable, as long as the system is co-utile and that all co-utile outcomes are Pareto-optimal; but not all Pareto-optimal outcomes are co-utile. In addition, reciprocity and hybridity equilibrium are compatible with co-utility in specific cases at which they provide Pareto-optimal outcomes. This methodology of analysis within the framework of co-utility can be extended beyond the crowd-based business models and promises to significantly contribute to economic theory.     

Disclosure risk assessment in statistical microdata protection via advanced record linkage

The performance of Statistical Disclosure Control (SDC) methods for microdata (also called masking methods) is measured in terms of the utility and the disclosure risk associated to the protected microdata set. Empirical disclosure risk assessment based on record linkage stands out as a realistic and practical disclosure risk assessment methodology which is applicable to every conceivable masking method. The intruder is assumed to know an external data set, whose records are to be linked to those in the protected data set; the percent of correctly linked record pairs is a measure of disclosure risk. This paper reviews conventional record linkage, which assumes shared variables between the external and the protected data sets, and then shows that record linkage—and thus disclosure—is still possible without shared variables.