|Title:||The Effect of National Culture and Economic Wealth on Global Software Piracy Rates|
|Author(s):||Moores, T. T.|
|Citation:||Moores, T. T. (2003). The effect of national culture and economic wealth on global software piracy rates. Communications of the ACM, 46(9), 207-215.|
|Link(s):||Definitive , Open Access|
|Key Related Studies:|
|About the Data|
|Data Description:||A sample of 45 countries is derived for which software piracy rates, cultural dimensions scores, and economic wealth data is available. The BSA software piracy study lists 80 countries and seven regions, while the Hofstede sample consists of 50 countries and five regions, with 46 countries in common. The regional data is dismissed since it would be difficult to determine how to combine the data to match one region to another. Finally, the economic data is derived from the World Bank’s World Development Indicators 2001 CD-ROM database. Data is available for all thecountries except Taiwan, thus producing a sample of 45.|
|Data Type:||Secondary data|
|Secondary Data Sources:|
|Data Collection Methods:|
|Data Analysis Methods:|
|Cross Country Study?:||Yes|
|Government or policy study?:||No|
|Time Period(s) of Collection:||
This study will use a sample of 45 countries and data stretching from 1994 to 1999. It will be shown that although there is clearly a cultural component to software piracy, by including a measure of economic wealth into the model it will be shown that the dominant factor still appears to be economic. The development of online auctions, however, has the potential to dismantle these relationships and ignite soaring global software piracy rates over the next few years.
Main Results of the Study
It would appear that increased personal wealth has resulted in a natural decline in software piracy rates throughout the world. The model developed here suggests that as people become richer, they become more individualistic, and the combination of these two effects result in the tendency to buy legal, rather than pirated copies of software, even in countries that traditionally have high software piracy rates.
Furthermore, while vendor organizations such as the BSA and SIIA have a role to play in highlighting and attempting to combat software piracy, the model produced here accounts for more than 80% of the variance, and so, there seems little variance left over to attribute to the efforts of these organizations.
Policy Implications as Stated By Author
Coverage of Study
|Level of aggregation:||Country|
|Period of material under study:||1994-1999|