Should I include country dummies when I combine datasets of 3 countries? I am currently doing the analysis using firm-level data of three countries combining together.
Also, it is a cross-sectional analysis. Therefore, in the regression, I control for industry dummies to account for differential effects in industry level. 

I think I don't need to control for country dummies due to some reasons:
(1) The countries that I use in my analysis share similar characteristics including development level, political, and socio-economic conditions. 
(2) There are only three countries in my analysis.

In this case, I expect that the results will not be affected even though I don't control for country specifics.

However, I am not sure if my idea is appropriate since I cannot find any reference to support it yet.
Therefore, I would like to ask everybody here if you have any idea whether or not country dummies is necessary in my case.

Thank you!
I would advise you to think deeper about your research question first, as this will guide the decision to use country fixed effects. If you would like to exploit cross country variation, for example by studying how the same industry functions differently across countries, then do not use country dummies because it will absorb the variation you want. 

If you want to study a causal relation that is independent of country, then using "within-country" variation (i.e. include country dummies) is the most restrictive approach and will sweep out all fixed country characteristics. Your coefficient will then be identified off deviations from within country means. 

Are you sure that countries are similar across most characteristics in order to defend not using country dummies? It may be hard to defend solving omitted variable bias on those grounds. If you really want to go this route, then include several country covariates as controls.