The Numbers That Matter

The core drivers.

Four numbers, tested on real adults rather than the usual student sample. Every one of them held up. Here is what each path actually says.

H1 · strong

-0.29

Moral Intensity
→ Attitude

H2 · moderate

-0.22

Moral Intensity
→ Intention to Pirate

H3 · moderate

-0.20

Perceived Technical Risk
→ Attitude

H4 · primary

+0.47

Attitude
→ Intention to Pirate

01 · Path by Path

What each number really means.

Read each coefficient like a dial. A bigger number, positive or negative, means a stronger pull on the outcome.

Moral Intensity → Attitude

-0.29

The biggest lever on how people feel about piracy. When the harm to others lands, attitudes harden against it.

Moral Intensity → Intention to Pirate

-0.22

Moral weight also tugs directly on what people actually plan to do, even after attitude is accounted for.

Perceived Technical Risk → Attitude

-0.20

Fear of malware, data theft, and broken hardware reshapes how the whole act gets judged.

Attitude → Intention to Pirate

+0.47

Once an attitude is locked in, it is by far the strongest predictor of whether someone actually pirates.

02 · What Drives Attitude

Each driver in the model was measured with a proper validated scale, not a single throwaway question. Here is what they actually capture.

Impact on society

Moral Intensity

Magnitude of consequences
The total damage piracy does to music, film, and software industries.
Probability of effect
How likely that damage actually reaches creators and companies.
Temporal immediacy
How fast the damage hits: an instant blow versus slow long-term decline.

Singhapakdi et al. (1996); Jones (1991)

Impact on the pirate

Perceived Technical Risk

Software piracy risk
Catching a nasty virus or hidden malware from the file you just downloaded.
Data security threat
Hackers walking off with your private files, accounts, and saved passwords.
Physical damage
Destructive payloads that can actually fry parts of your computer.

Framed as a tech cost, not a legal one