It sounds like you should read a textbook on correlation and regression. One that is highly recommended and might have examples that are relevant to your own field is Correlation and Regression Applications for Industrial Organizational Psychology and Management by Bobko.

What type of multivariate data analysis should I use for my dissertation project?

From the above explanation - If your conceptual framework only consists of IVs & DV and the questionnaires are adopted from previous empirical research, perhaps you can use multiple regression analysis. However, if your conceptual framework adapted / enhanced from previous theoretical frameworks / theories & you are conducting an exploratory research, perhaps you can do an exploratory factor analysis among your IVs' 40 items first to see any significant factors emerging so that you can use those factors as your IVs in the multiple regression analysis.

According to your question it sounds look like the multiple regression, because the dependent variable has 1 category, which has no order involve in these categories, so the best option is to use multiple regression.

Han Ping Fung, if the 8 independent variables do come from pre-established scales, I would hesitate to put those 40 variables into an Exploratory Factor Analysis, given the kind of confusion that can arise with doing EFA on so many variables. I certain would consider a Confirmatory Factor Analysis, but I think the person asking the question is a relative beginner with regard to this kind of analysis, so I would try to start with something as simple as possible.

In addition to David L Morgan's recommendation, I would recommend reading, "Applied Statistics: From Bivariate Through Multivariate Techniques," by Warner, Rebecca (Becky) M. (Margaret). Chapters 13 - 23 provide in-depth descriptions of multivariate analysis on a introductory level. It's a read, re-read, read again type of book, but I always end up going back to it for guidance on how to conduct these types of analyses and why. The introductions to each type of analysis give you examples of when you would use them, why, if you can based on your types of variables, the assumptions for each statistic, and so much more. It is very insightful.