What particular measure to use? Multiple regression or MANOVA? I've been doing a research paper - 
Effects of Workplace Bullying on Employees' Productivity,
Self-Confidence and Self-Esteem.  So I have 1 IV (Workplace bullying) and 3 DVs. what can I use to interpret it?  
Another thing: if it's MANOVA, can I execute it without having to use factors? 
 A: You have three outcomes and one input variable, you can't use multiple regression. Peter has clearly explained, you need to choose between three simple regression (taking one output at a time) or MANOVA (Multivariate regression).
Regression techniques to be used, if the output is continuous: 


*

*Single input & single output - Simple regression  (If input
categorical, use dummy variable or go for t-test/ANOVA)

*Multiple inputs & single output - Multiple regression  (If input(s)
categorical, use dummy variable(s) or go for ANCOVA)

*Single input & multiple outputs - Multivariate regression 

*Multiple inputs & multiple outputs - Multiple multivariate
regression 
And if the outcome is categorical, then it becomes classification problem. Different methods can be used like logistic regression, discriminant analysis etc.
A: Whether you want a) MANOVA b) Multivariate regression or c) several OLS regressions d) something else depends on what you want to test and the nature of the data. If you are interested in relationships among the three dependent variables (DV) as well as between the DVs and the single independent variable (IV) you want either MANOVA or multivariate regression (the latter not to be confused with multiple regression, which has one DV and more than one IV). 
ANOVA and regression are really the same model, but the ANOVA/MANOVA terminology is usually used when your independent variable is categorical and the regression/multivariate regression when the IV is numeric/continuous.
You also have to consider the nature of the DV: All the above assume it is continuous. If it is not, then you probably want some form of logistic regression. 
A: IV is independent variable, DV stands for dependent variable (output). So in this case you indeed have one independent (input/cause) variable: the amount of bullying and 3 outcome variables which are studies (i.e. Productivity, Self-Confidence and Self-Esteem). A regression analysis should be applied to test for effects.
MANOVA would be used to test multiple groups and although your question does not clearly state this, I am going to assume you have one group of persons on which measured the amount of IV and tested all 3 DVs, so MANOVA is not the thing you need.
In this case you could also choose to test for correlations between variables instead of using a regression technique, i.e. to correlate the IV with the 3 DVs, although now you use these variables as random variables. 
A: We do regression when we are interested in prediction
And there is multivariate linear regression technique
However we use Manova when we are interested to study the effect of independent variables on the dependent variables I.e. whether there is an effect or no and what is the cause of the effect.
