Peer review is already evolving. Increasingly academics discover their papers via search engines (Google, Google Scholar), and social platforms (blogs, email, arXiv, Academia.edu, Twitter). The usage of these channels as discovery channels for research shows that the metrics that drive those channels are doing a good job at expert curation - i.e. surfacing good content.
On Google Scholar, it's citation counts that drive the ranking, and therefore the discovery process. This is the "crowd review" process I talked about in the post. With social platforms, it's recommendations from friends and colleagues that drive the discovery process. This is the "social review" process I talked about in the post.
In the pre-web days, people used to walk down to their libraries to read the latest edition from a particular journal. In those days, the journals did drive a lot of the discovery process. Nowadays, pretty much all discovery of research papers happens on the web, and most of the discovery is via channels such as search, and recommendations from colleagues over social & communication platforms.
You are right to think about the incentive systems that drive different kinds of peer review. In the case of the social review process, you want to share good recommendations with your friends, not bad ones (this is why Twitter and Facebook work as discovery channels). In the case of the crowd review process, you want to cite good works that your work genuinely built on, not bad work.