# II.2. Choosing a suitable blockchain The blockchain that supports the platform is important as it influences functionality and usability. We have studied the possibility of choosing Steem as a social blockchain for this purpose. This blockchain was not suitable as we have noticed a number of trends and concerns so we collected responses from users to know what the main problems are. The Steem blockchain does not correspond to our requirements and does not meet our objectives because it has some limitations that are noticeable as follows: #### 1) Complicated usability. The users need to manage a lot of private keys and 3 different tokens. The registration process is also unintuitive and long. #### 2) Low quality and diversity of content. The posts on Steem are all original content from non-professional vloggers and contributors. They are focused on the blockchain community and don’t have widespread appeal. #### 3) Unsuitable economic parameters The mass adoption of the economic model is hindered by unfair reward distribution, token illiquidity, short monetization window and limits on voting. #### 4) Concerns on scalability The Steem blockchain already had 400 decentralized applications the last time we checked. This in addition to no customization and low bandwidth can lead to slow performance. Our team agreed to use Smart chain & Avalon framework to develop and test a new blockchain. The blockchain that we created was named VLOCITY to reflect its high performance, speed and functionality. It is a second generation social blockchain like Avalon that has new advancements and improvements. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://whitepaper.vlokr.us/ii.2.-choosing-a-suitable-blockchain.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.