Hypotheses Testing

Environmental Change (Network Scale +,

Piracy Rate -)

Productivity Change of

the Music Industry Performances of

Individual Firms (Sales +, Labor -,

Capital -) 1. New technology

2. Lawsuit effect 3. Business model

innovation

Frontier Shift

Technical Efficiency Change

In order to provide new evidences for the performance, that different strategic decisions working upon the music industry, this research will test four hypotheses listed further.

H1: The copyright-protection-lacking digital music technologies, such as MP3 and P2P, are negative related to the productivity of music firms.

H2: Filing a lawsuit against piracy makes a positive impact on the productivity of music firms.

H3: Launching a brand-new business model is positive related to the productivity of music firms.

H4: Launching a new business model do more impact on the productivity than filing a lawsuit against piracy.

The Tobit regressions again and Mann-Whitney rank test will be applied, in this section, to test these hypotheses separately. Hypotheses one, two, and three will employ Tobit models with dummy variables, which representing different event periods, and hypothesis four will employ Mann-Whitney rank test for testing.

The Tobit models, model (7) to model (15), will test the influence of different business strategic events, including new digital technologies, lawsuits, and new business model, on the Malmquist indices. The empirical results of these Tobit models are computed by EViews 3.0 computer program.

In the point of view of the whole music industry, the empirical results of the Tobit regression for Malmquist Indices with the different business strategies are listed on Table 11 to Table 13 below.

Table 11 Regression Analysis on MPI in Music Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 12 Regression Analysis on TEC in Music Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 13 Regression Analysis on FS in Music Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

In the scope of whole music industry, several findings are reveled on Table 11 to Table 13. The Tobit model with the first dummy variable, which reflects the influence of lawsuits, finds out that filing lawsuits against piracy can enhance the productivity significantly, and therefore hypothesis two in our research, filing a lawsuit against piracy makes a positive impact on the productivity of music firms,

is confirmed. Furthermore this improvement is mainly caused by the forward shit of efficiency frontier, representing the improvement of external environment in whole music industry, instead of the technical efficiency change. Similarly, The Tobit model with the third dummy variable, which reflects the MP3 and P2P affections, finds out that MP3 and P2P technologies may impair the productivity significantly, and therefore hypothesis one in our research, the copyright-protection-lacking digital music technologies are negative related to the productivity of music firms, is confirmed. Furthermore this deterioration is mainly caused by the backward shit of efficiency frontier, representing the deterioration of external environment in whole music industry, and does much more affection than the benefits of technical efficiency improvement. However when our Tobit model is taken the second dummy variable, which reflects the influence of Apple’s new iTunes business model, into consideration, an insignificant result is derived, and the hypothesis three in our research is failed to verified.

In order to know why the hypothesis three is failed to verified, the sub-industries, such as music retailing, music publishing, and music production industry, are tested separately in our research further to get more detail information about the mechanism that strategic events, especially the Apple related events, effecting the performance of music industry. These results are shown from Table 14 to Table 22 following. First of all, the empirical results of the Tobit regression for Malmquist Indices, with the different business strategies, in music retailing industry are listed on Table 12 below.

Table 14 Regression Analysis on MPI in Music Retailing Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 15 Regression Analysis on TEC in Music Retailing Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 16 Regression Analysis on FS in Music Retailing Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

In the scope of music retailing industry, findings reveled on Table 14 to Table 16 are basically consisting with the previous findings of the whole music industry listed on Table 11 to Table 13. The digital technologies do a negative influence on productivity and lawsuits positively in contrast. However, the productivity of music retailing industry is significantly worsened in the period of Apple’s iTunes

business model launching. This finding can be interpreted as that the Apple’s iTunes business model provided a new, but legal, way for music transactions, and ate the market share of inherent music retailers away.

Next, the empirical results of the Tobit regression for Malmquist Indices, with the different business strategies, in music publishing industry are listed on Table 17 to Table 19 below.

Table 17 Regression Analysis on MPI in Music Publishing Industry

Equations (7) (8) (9)

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 18 Regression Analysis on TEC in Music Publishing Industry

Equations (10) (11) (12)

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 19 Regression Analysis on FS in Music Publishing Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

In the scope of music publishing industry, results of Tobit models confirm again that MP3 and P2P technologies affect badly on the music publishers.

Moreover, the Apple’s iTunes business model is confirmed significantly doing goods for the technical efficiency change, and has contributions to the internal

Also, the empirical results of the Tobit regression for Malmquist Indices, with the different business strategies, in music production industry are listed on Table 20 to Table 22 below.

Table 20 Regression Analysis on MPI in Music Production Industry

Equations (7) (8) (9)

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 21 Regression Analysis on TEC in Music Production Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Table 22 Regression Analysis on FS in Music Production Industry

The coefficient, t-value, and p-value (in parentheses) are given for each variable.

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

In the scope of music production industry, results show that the influences of strategic events are mainly taking place on the changes of technical efficiency, which represent the affections on internal factors of individual music producers.

The digital technologies do a negative influence, and lawsuits do a positive influence on TEC indices. In addition, the Apple’s iTunes business model worsens

the TEC index of music publishers significantly for the shrinking of interests sharing. According to the empirical results of these sub-industries, from Table 14 to Table 22, the reason of insignificance in our third hypothesis test can be concluded that new business model like iTunes may stimulate the reallocation of interests. Therefore some inherent companies will take the advantages, and some be eliminated from this industry at the same time.

Finally all the empirical results above, from Table 11 to Table 22, are summarized on Table 23.

Table 23 Summary of the Empirical Results

Events MPI TEC FS

MP3 & P2P －*** ＋** －***

Lawsuits ＋*** －** ＋***

Whole Music

Industry Apple Online

Music Store － ＋ －

MP3 & P2P － ＋** －***

Lawsuits ＋** － ＋***

Music Retailing

Industry Apple Online

Music Store －* － －***

MP3 & P2P ＋ －*** －*

Lawsuits － ＋ ＋

Music Publishing

Industry Apple Online

Music Store ＋ ＋* －

MP3 & P2P ＋ －** －

Lawsuits －* ＋*** ＋

Music Production

Industry Apple Online

Music Store ＋ －* －

***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

According to the results of Tobit models in the whole scope of music industry, in brief, hypotheses one and two in this research are confirmed, meaning that digital music technologies are negative related and filing a lawsuit against piracy is positive related to the productivity change of music industry. Hypothesis one is confirmed by the Tobit model with the third dummy variable, and evidences show that the MP3 and P2P technologies may significantly impair the productivity. On the other hand, the hypothesis two is confirmed by the Tobit model with the first

the productivity with 99 percent significant level. However based on the whole scope of music industry Tobit models, hypothesis three in our research is failed to verify. This outcome means that launching a new business model like Apple’s iTunes Music Store is not necessary for the improvement of productivity in every music related industries. Further investigation in particular music related industry, accordingly, are used to find out the reason of the fail validation in hypothesis three. Evidences show that productivities of music retailers and producers are significantly worsened in the period of Apple’s iTunes business model launching, and productivities of music publishers are improved in such period. Hence the reason of insignificance in our third hypothesis test is concluded as a relocation of interests happened while the Apple’s iTunes business model launching: some industries are benefited from this change, but some are not.

In the last part of this section, hypothesis four, launching a new business model do more impact on the productivity than filing a lawsuit against piracy, will be tested. The Mann-Whitney rank tests are used to compare medians of Malmquist productivity indices between two independent events groups, filing lawsuits and Apple’s iTunes business model launching, on the basis of nonparametric analysis. SPSS computer program reports the normal approximation to the U statistics and the p-values for two-sided tests on Table 24.

Table 24 Mann-Whitney Tests in Malmaquist Indices for Different Business Strategies

Ranks

Group N Mean Rank Sum of Ranks

iTunes 51 78.53 4005.00

Lawsuits 130 95.89 12466.00 MPI

Total 181 - -

iTunes 51 100.43 5122.00

Lawsuits 130 87.30 11349.00 TEC

Total 181 - -

iTunes 51 62.27 3176.00

Lawsuits 130 102.27 13295.00

FS

Total 181 - -

Test Statistics

Test Variables MPI TEC FS

Mann-Whitney U 2679.000 2834.000 1850.000 Wilcoxon W 4005.000 11349.000 3176.000

Z -2.006 -1.517 -4.620

Asymp. Sig.

(2-tailed) .045** .129 .000***

1. The Mann-Whitney U statistic displayed in the table is the smaller of these two values. (In this research U1 is smaller)

2. Grouping variable represented the events that Apple iTunes Online Music Store launching, and the RIAA filing lawsuits against Napster respectively.

3. The negative Z statistics indicate that the rank sums are lower than their expected values.

4. ***, **, and * indicate significant levels at 10%, 5%, and 1%, respectively.

Results of the two-tails Mann-Whitney tests appear significance, p-values are smaller than 0.05, in the MPI and FS indices, and the Z statistics for every tests have negative signs. Therefore the single tail null hypothesis, filing a lawsuit against piracy do no more impact on the productivity than launching a new business model, is rejected as the rejection of two tails hypothesis, and the four hypothesis in our research is confirmed as a contrary result consequently. Besides the productivity vantage of filing lawsuits against piracy is mainly coming from the superior improvement of frontier shift, implying the lawsuits may cause a greater improvement of external environment. These findings reinforce the importance of filing lawsuits against piracy in a harsh circumstance.