For any sequence of RVs X1,...,Xn the following holds: E[max{X1, ..., Xn}] >= max{E[X1], ..., E[Xn]} (*) Proof. We have that max{X1, ..., Xn} >= Xi for all i. Thus, this holds in expectation as well, i.e. E[max{X1, ..., Xn}] >= E[Xi] for all i. Since this holds for all i, it holds for … Continue reading The expectation of the maximum of RVs is greater or equal to the maximum of the expectations
Forums and gamifying innovation
Very nice article mentioning Q&A forums similar to my paper idea: Morgan and Wang (CMR 2010) - Tournaments for Ideas See also this Article. https://en.wikipedia.org/wiki/Yahoo!_Answers https://en.wikipedia.org/wiki/Google_Answers
Research tournaments are Tullock contests and hence WTA is optimal
A classic paper of "research tournaments" by Fullerton and McAfee (1999) assumes a single prize (by design). Hoppe-Wewetzer and Wagener (2019) show that a Fullerton–McAfee "research tournament" with multiple prizes is strategically equivalent to a (nested) multi-prize Tullock contest. Given that it is known that Tullock contests are strategically equivalent to "effort+noise" contests with Gumbel … Continue reading Research tournaments are Tullock contests and hence WTA is optimal
Several MBA MOOCs from the top US business schools
OR conference in Dublin: 23rd-26th June 2019
If you are into OR and Optimization this is a conference opportunity to visit Dublin: https://www.euro2019dublin.com/ See also: https://www.youtube.com/watch?v=LECA5vtOaWQ
Marketplace Innovation Workshop 2019
The INFORMS Revenue Management & Pricing Conference will be held at Stanford Graduate School of Business on June 6–7, 2019. The conference will be held in conjunction with the Marketplace Innovation Workshop, which will take place on June 4–5, 2019. Deadline for full papers: 18 February 2019. More details at: https://www.rmp2019.org/
Internal innovation contests
I am aware of this recent paper on the topic but today I realized someone actually wrote a book/thesis on this topic recently as well. This is a downloadable chapter. Case Study Developing Innovative Solutions Through Internal Crowdsourcing (MIT SMR 2017)
