I used Bartle's 4 types as a starting ground
to brainstorm possible underlying motivations. Bartle elaborates
on these 4 types in his paper - Hearts,
Clubs, Diamonds, Spades: Players Who Suit Muds.
Here is a brief summary of Bartle's 4 Types:
- Achievers are driven by in-game goals,
usually some form of points gathering - whether experience
points, levels, or money.
- Explorers are driven to find out
as much as they can about the virtual construct - including
mapping its geography and understanding the game mechanics.
- Socializers use the virtual construct
to converse and role-play with their fellow gamers.
- Killers use the virtual construct
to cause distress on other players, and gain satisfaction
from inflicting anxiety and pain on others.
Bartle weaves a fairly elaborate model on
how these different types interact with other, as well as
how the balance of these different types will cause drifts
to occur in the player base. While elegant and cleverly modeled,
Bartle's types were not constructed from empirical data, but
rather, from a long discussion among MUD wizards.
One problem with such a just-so model is that
the 4 types may overlap. For example, it may be the case that
most Achievers are Explorers, because to advance in levels
quickly, one has to know about the game mechanics. Another
problem is that the types may not be well-constructed, and
may include unnecessary traits and exclude important traits.
For example, perhaps the Achiever scale should be based upon
a desire for power rather than points accumulation. Or perhaps,
mapping geography is not that important to most Explorers
who are actually much more interested in the game mechanics.
The problem of employing a just-so model is
that it becomes self-fulfilling. If a questionnaire is constructed
such that a respondent has to choose between being an Achiever
or an Explorer, then the end result will be a dichotomy where
none may exist to begin with. It would be like asking - Do
you prefer pizza or ice-cream?
Nevertheless, Bartle's preliminary model
serves as a good starting point, and gives us a foundation
on which to understand underlying motivations, as well as
a model to test against empirical data.