You are to be commended for examining whether the assumptions underlying your initial linear regression model were satisfied. There are better ways to model data in which the outcome variable is a fraction between 0 an 1.
Two standard ways to model such outcomes with regression are beta regression and logistic regression. This answer describes the differences between them and provides links that show how to implement them. Beta regression is most appropriate when the fraction is continuous. In your case, where the outcome variable is discrete (the ratio of the number of sponsors that are in a creative industry to the total number of sponsors, for each sponsored event), logistic regression is probably a better choice.
Although logistic regression is typically used with a binary outcome variable, this answer shows how to proceed with situations like yours where for each case you have counts of "successes" (creative-industry sponsors) and "failures" (other sponsors) for each sponsored event. Logistic regression will also take into account the number of sponsors in each case; one would expect an event with more sponsors to provide more information about the relationship between creative-industry sponsorship and the nature of the event (as modeled in your other predictor variables).