Post on 18-Nov-2014
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MBA 512 – Business Research & Design
Jason Giomboni and John Mullisky
Electronic Media Piracy
Legal vs. illegal use of content
Introduction Media – any form of electronic content used for
entertainment or education. Piracy – illegal downloading of software content
without payment.
Why perform the survey? John and myself have decades of experience in
the IT field and wanted to determine the percentage of media actually paid for.
We feel that all electronic media should be paid for based on the amount of time, resources and creative ability put into its development.
COD Example
ExplorationHypothesis Statement : People with less experience in life
based on education or work experience are more willing to download media content without payment.
Research Question: Do people with less education and/or work experience
download more electronic media content without payment for the content?
Relevant Factors: Age Income Education Work Experience Download Tendencies
Data Collection Survey: 21 Questions
Demographic: Gender, Education, Income, Work Experience, Computer Skill Level
Content: Movies, Music, Television, Adult, Software, Games
Behavior: Payment, Penalties, Guilt Survey Format:
Multiple ChoiceSingle ResponseMultiple ResponsesPayment RangesText Fields
Data Collection Target Audience:
Users of electronic devices that download electronic content.
Sample Size: 50 respondents Sampling Plan:
Email coworkers, friends and familyFacebook – sent to our friends and asked them
to send to their friends (random sample). Summary of Respondents:
Sent over one hundred and fifty emails and Facebook requests
50 Responses
Data Collection
Method of Administration:Created online survey (form) through
Google DocsWe couldn’t use Best Buy because of
solicitation policy
Data Collection - Education Breakdown
High School or Below - 7 14%Trade or Certificate -1 2%Associates -7 14%Bachelor -10 20%Graduate and Above -25 50%
Current level of education completed:
Data Collection - Income Breakdown
< $25,000 - 7 14%$25,001 to $45,000 -8 16%$45,001 to $60,000 -13 26%$60,001 to $75,000 -7 14%> $75,001 -15 30%
Income Level:
Level of computer/technology skills:
17
2
6
25
Level of computer skillsIntermediate to Advanced users make up a large ma-
jority of the sample
Advanced
Beginner
Expert
Intermediate
Focused on reaching users of technology so this sample re-flects the skill set of the popu-lation that are users of tech-nology
Data Collection – Computer Skill Level
Type of hardware used
The majority of the respondents used the most widely available tools to download content.
Type of content by gender
Gender Music Games Movies Adult Software Television
Female 17 7 5 0 7 5Male 27 13 14 9 18 12
Analysis Summary Probability – identify probabilities for illegal
content downloads for various user classifications
One sample t-test – Test our data against a hypothesized value to see if the data is a likely representation of population
Two sample t-test – Test to see if our hypothesis is correct
Regression analysis – if the model is valid and if a relation ship exist
Content UsersProbabilities – User will pay for their content We used a pivot table to group the data
to determine the probability 12 out of 50 respondents pay for all their
downloaded content – 12/50 = 24% 25 out of 50 respondents pay for some
or none of their content – 25/50 = 50%
Another question ask if the users always paid for content the total number of yes responses was 16 – not 12
Content UsersProbabilities – User will pay for their content 6 out of 20 female respondents pay for all their
downloaded content – 6/20 = 30% 8 out of 20 female respondents pay for some
or none of their content – 8/20 = 40%
Content UsersProbabilities – User will pay for their content 6 out of 30 male respondents pay for all their
downloaded content – 6/30 = 20% 17 out of 30 male respondents pay for some or
none of their content – 17/30 = 56.6%
Males are least likely to pay for all of their downloaded content and more
likely to not pay for their content
Total - All Total - Some/None
Male - All Male - Some/None
Female - All Female - Some/None
0
10
20
30
40
50
60
Probabilty of paying for content
Probabilty of paying for content
Probabilities for the level of experience users paying for content
Advanced - Pay
Advanced - No pay
Beginner - Pay
Beginner - No Pay
Expert - Pay Expert - No Pay
Intermediate - Pay
Intermediate - No Pay
0%
20%
40%
60%
80%
100%
120%
35%
65%
0%
100%
17%
83%
36%
64%
Probabilty of always paying for content
Probabilty
Beginner – not enough users to indicate this is trendAdvanced and Intermediate are compared about equalExpert – See an increase in not always paying – may know more ways of getting illegal content
Number of device users by number of users who pay for content Probabilities
MP3 – 34% Smart Phone –
32% Laptop/PC –
25% iPad – 0% Game Console –
27% DVD/BluRay –
40%MP3 Player Smart Phone Laptop/PC iPad Game
ConsoleDVD/Blu-Ray
Player
0
5
10
15
20
25
30
35
40
45
50
One Sample Proportion t-test Tested to see if illegal download lead to
future purchases – Asked this question explicitly in the survey.
One Sample Proportion t-test Tested to see if level of work experience
affected the rate of illegal download. greater then 5 years of experience vs less than 5 years of experience.
Two Sample proportion test Do people with advanced degrees less
likely to illegally download content?
Reason given for illegal downloading
Reason # of Respondents
Why pay for it when you can get it for free somewhere else?
15
Needed it for school/work
8
Cost of paying too high 22
Can't find store to purchase it
5
Regression Test – Multiple Variable Dependent variable – Do you always
pay for your downloaded media/content?
Independent variables – Current Income, Years of work experience, Education Level, Level of computer skills, Frequency of downloading
Analysis Conclusion Does piracy lead to future purchases of
content? Probabilities indicate yes greater then 60% of the time.
Does having work experience greater then five years affect how likely a person is to download content illegally? No – equally likely with limited and greater experience
Are people with advance degrees less likely to download content illegally? No – equally likely with lower and advanced education
Analysis Conclusion Does income affect payment for content?
No – equally likely with low and high income
Do high frequency users pay for less content? No – equally likely between low and high frequency down loaders
Regression – Model is not valid and cannot identify relationship between variables
Conclusion There is a trend not to pay for all the content a
person may download, with a majority of males only paying for some if the content
Counter this with the analyst indicating future purchases from originally pirated content
Did not identify any survey data or analysis indicating that different levels of salary, education or work experience has a strong relationship with predicting content piracy
Impact – We have to answer our hypothesis question with a NO People with less education, lower salary or work
experience do not download more content illegally than those with higher levels of salary, work experience or education
Survey Improvements Execution: Phrasing the questions with
the method of analysis in mind – result in cleaner data with less transformation
Improve on the ability to obtain results from target audience – relied on “pass it along” methods to ensure we achieved a broad based response pool
Identify industry data for comparison – we had a broad definition of content – prevented comparison to available data
Future Research Possibilities We gathered data on the price a respondent would
be willing to pay for the content they downloaded. Interesting to see if this could be used to predict prices for content.
Follow up study – approximately 2/3rd of respondents indicated that an illegal download would lead to future purchase from the content owner – if this could be verified it may provide a means of marketing your content and “legalizing” content download