An experimental analysis on the effect of lowering prices of original software in determining demand for pirated software Essay

1 - An experimental analysis on the effect of lowering prices of original software in determining demand for pirated software Essay introduction. DESIGN

a.) Hypothesis

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This study is based on the general hypothesis that there is a level of price, still significantly higher than the price of pirated software wherein consumers would select original software despite it still being more expensive than pirated software. Specifically, this study sought to determine the truth of the following sub-hypotheses:

Consumers still prefer pirated software over original software even if original software is reduced in price.
There is no significant difference in the sales of software in four key locations.
There is no significant difference in the sales of software using four different pricing schemes.
b.) Experimental Design

This study aimed to collect input data obtained from key locations which will be set up to provide consumers with the knowledge that both original and pirated software are being offered to them. The data input was sales results from repeated trials on several key locations of the experiment. The data was processed statistically to obtain subject demographics and other pertinent details which would result to the output that answers the question as posted in the sub-hypotheses leading to the conclusion of the main hypothesis. This framework can be described by the proceeding theoretical flowchart.

Last

Sub-hypothesis?

Output:

Answer to first sub-hypothesis

YES

Conclusion of main Hypothesis

END

2. METHOD

a.) Design

This design considered the factor of lowering prices of original software against the sales of pirated and original software in four key locations within the city proper. This identified the price gradation and key locations as independent variables while the sales of software in the said locations according to the different price gradations was considered the dependent variable.

b.) Dependent Variable

The dependent variable was measured by obtaining the number of pirated software sold and the number of original software sold in each of the four key locations according to each of four trials using different prices for the original software.

c.) Independent Variables

The key locations were selected according to areas within the city proper where selling of pirated software is rampant. These were selected to exclude other factors such as fear of being caught buying pirated material from affecting the results of this study. The prices were determined first by the original price, second by a small 20% decrement from the original price which is usually offered during sales, third by a considerable 50% decrement from the original price and last by a 70% decrement from the original price which is still triple the price of a pirated copy. Each trial will have a stock of 100 pirated software and 100 original software. The software offered was only one undisclosed title in order to prevent factors of supply and demand from affecting the study.

d.) Subjects

The subjects were the local consumers of pirated software found in the four key locations. There was no specific number of subjects required but the evaluator selling the software stayed inside the vicinity during business hours to get as many subjects as possible. The subjects likely ranged widely in demographics. They were motivated by the opportunity of obtaining up-to-date popular software in the market.

e.) Task

The task of the evaluator involved advertising the product to the pool of potential customers, explaining the difference of the prices and taking orders. The evaluator also jotted down demographic profiles of customers.

f.) Experimental Procedures

The experiment proceeded in detail according to the following timetable.

Day 1: Sales experiment in locations A B C and D using standard pirated price for pirated software and original software.

Day 2: Sales experiment in locations A B C and D using standard pirated price for pirated software and 20% off the standard price of original software.

Day 3: Sales experiment in locations A B C and D using standard pirated price for pirated software and 50% off the standard price of original software.

Day 4: Sales experiment in locations A B C and D using standard pirated price for pirated software and 70% off the standard price of original software.

The data analysis pack of M.S. Excel was used to make the necessary statistical calculations for the gathered data.

3. RESULTS

a.) Sample Data Set

Table 1: Demographic Profile

Gender:

Age:

Male
487

Below 15
172

Female
532

15 – 18
432

Above 18
415

Highest Educational Attainment

Basic Education
210

Secondary Education
411

Higher Education
398

Table 2:

Day 1 data
Price of Original: 100%

Sales
Location
Pirated
Original
A
47
2
B
35
1
C
28
1
D
33
1

Table 3:

Day 2 data
Price of Original: 80%

Sales
Location
Pirated
Original
A
38
11
B
48
13
C
27
5
D
30
14

Table 4:

Day 3 data
Price of Original: 50%

Sales
Location
Pirated
Original
A
11
49
B
8
57
C
12
38
D
15
42

Table 5:

Day 4 data
Price of Original: 30%

Sales
Location
Pirated
Original
A
4
55
B
3
54
C
1
43
D
2
42

b.) Results

            i.) Descriptive Statistics

Table 6: Descriptive Summary
Mean
Median
Standard Deviation

Pirated
35.75
34
8.057087977
Day 1
Original
1.25
1
0.5

Total
18.5
15
19.18332609

Pirated
35.75
34
9.394147114
Day 2
Original
10.75
12
4.031128874

Total
23.25
20.5
14.94513777

Pirated
11.5
11.5
2.886751346
Day 3
Original
46.5
45.5
8.346656017

Total
29
26.5
19.58133222

Pirated
2.5
2.5
1.290994449
Day 4
Original
48.5
48.5
6.952217872

Total
25.5
23
25.01999201

Location A
27.125
24.5
22.21606562

Location B
27.375
24
23.73025495

Location C
19.375
19.5
16.79232393

Location D
22.375
22.5
16.63848808

            It can be seen from both the mean and median values of table 6 as supported by figures 2 – 5 that a gradual shifting trend from patronage of pirated software to original can be seen from day 1 to day 4. Moreover, the standard deviations of each sample seem to indicate normality of the data. Out of the four days, day 3 exhibited the highest total mean sales while day 4 exhibited the highest mean original software sales and day 1 the highest mean pirated software sales. Normality is less observed from the data as grouped by key location, which indicates the expected fluctuating trend of sales in the four key locations during the four days. Location B has the highest mean sales while location C had the least.

            ii.) Inferential Statistics

The MS Excel data analysis tool pack was used to compute for the required inferential results.

Table 7: Data Summary for 2-way ANOVA
Location
A
B
C
D
Day 1
49
36
29
34
Day 2
49
61
32
44
Day 3
60
65
50
57
Day 4
59
57
44
44

A two –way ANOVA was selected to treat the sales across four locations and in four days (see Table 7) to determine homogeneity of the data and the level of bias per location, per day.

The absolute value of the computed F-value of 2.23 is less than the Critical Value of 2.68 at a 95% confidence level. Thus, there is no significant difference in the sales of software across the four key locations in the four experimentation days.

A set of paired T-test at a 95% confidence level with critical value 1.63 was performed on each set of pirated software sales against original software sales on each of the four experimentation days to determine whether there is a significant difference in the sales of pirated software to that of original software on each of the pricing conditions. The results are summarized in table 8 below:

Table 8: T-test Summary

Days
Absolute T-value
Difference
Day 1
11.23
Significant
Day 2
7.21
Significant
Day 3
13.25
Significant
Day 4
18.14
Significant

As shown in table 8, there is a significant difference in the sales of pirated software to that of original software in each of the four experimentation days. Going back to the data gathered in tables 2-5, this means that the sales of pirated software was significantly greater in Day 1 and Day 2 than  that of original software. It also means that the sales of original software were significantly greater than sales of pirated software in Day 3 and Day 4.

4. CONCLUSIONS

It can be concluded that there is a reliable level of normality as based on the two-way ANOVA test used for table 7 with regards to the four key locations and the four experimentation days. Thus, we can conclude that the total sales of software do not vary significantly during those four days in those four key locations. This answers the last two sub-hypotheses and gives way for the answering of the first.

The subsequent paired t-tests performed on original software sales against pirated software sales on each of the four experimentation days revealed that there is a significant difference in the sales on each of the days. If we inspect the mean sales of each of the items, we can conclude that a 100% and 80% priced original software would fare much less in the market than a normally priced pirated software. However, a 50% to 30% priced original software would fare a lot better than pirated software, despite the price of original software still being much higher than that of the pirated software even at the experimental reductions.

The main conclusion can therefore be substantiated that there is a level of price, still significantly higher than the price of pirated software wherein consumers would select original software despite it still being more expensive than pirated software. This indicates a significant demand for original software, that consumers still prefer original to pirated software if only the prices were a cheaper though not necessarily nor closely as cheap as pirated software.

There are several limitations regarding the conclusions that can be drawn from this study. Firstly, the conclusions are only limited to the data gathered in the four key locations. Although these locations are justifiably the best possible venues for the experiment since they have the best possibility of obtaining subjects, further studies should be conducted on locations in other cities or provinces. The study was also constrained with just one software title to offer to the subjects. This may have been limiting since there is a wide array of software genres that are being pirated. Further studies should be conducted to include most if not all of the major genres so that the trends can be verified for the patrons according to genres as well. Also, further pricing methods in between the methods selected for this experimental study should also be explored in the interest of defining a better price for original software that may be recommended to software manufacturers as a means to curtail the demand for piracy. Further studies should be conducted to obtain a more secure market for original software. This study acknowledged both the intellectual property rights of the original software manufacturers, the royalty rights for the developers and the consumer rights for fair pricing. This study has proven to a limited extent that it is possible to obtain a compromise from the consumer side with regards to the pricing of original software. Original software developers would do well to take this compromise into consideration and conduct their own studies on the material feasibility and relative profitability of giving in to such compromises from their consumers. Finally, this paper acknowledges that piracy is a crime that should not be condoned, but makes the assumption that its solution cannot merely be found in stricter laws in as much as its prevalence is widespread and its sources near-impossible to catch. Thus, this study has begun to propose a more economic solution with the hope that further development of such an idea would lead to the solution of the software piracy problem.

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