I did hierarchical regression analysis on my data due to having interaction effects in my research model.

2. Although the Beta value for ZSC_X_CS is significant, its positive sign is against the hypothesis! it's supposed to have a negative sign according to the literature & also logic! How should i treat this hypothesis? Accept? Reject? Partially accept?!!!

TQ.

R2 increased from .695 in model1 (main effect only) to .734 in model2 (main &interaction effects)(sig. F change = .000). All the assumptions for the regression analysis have been met. I have two problems with the "coefficients" table:
1. As u can see in the table, the insignificant beta value of ZSC in model1 became significant in model2! Is it ok? I'm confused! Which value should i consider to reject/accept the related hypothesis? B of model1 (which rejects the hypothesis) or 2 (which confirms it!!)?