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Randomized Response Analysis

5. Discussion

5.3. Limitations and future research

Similar to most empirical studies, our research is subject to limitations that represent depar-ture points for fudepar-ture research. Two limitations are of particular interest. First, our empirical research was conducted in the German market, which is one of the four largest markets for recorded music worldwide. Although we do not expect our findings to deviate substantially from other Western markets, piracy behavior is likely to be influenced by country character-istics, such as the existence and enforcement of anti-piracy legislation, economic indicators, and cultural variables. Therefore, it would be interesting to compare our results to other coun-tries or even to extend the framework to explicitly account for country characteristics using a multi-level framework. Second, although we have shown that moral aspects play a crucial role in the formation of piracy and purchase intentions, our research does not provide an in-depth analysis of how moral and emotional appeals can be utilized most effectively, which qualifies as an avenue for future research.

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Tables and figures

Table 1 Pre-study results

Influence on Piracy Intention

Predictors Model 1 Model 2 Model 3 Model 4

Structural parameters

Intercept (β0) –0.708 –1.130 –1.037 –1.283

Questioning technique (RR=1) (δ) 0.575 0.567 0.625 0.595 Main effects

Age (in years) (βage) –0.030 –0.030 –0.032

Gender (female=1) (βgender) –0.127 –0.113 0.083

Impression management (βIM) –0.332

Perceived social undesirability (βSD) –0.620

Perceived legal risk (βrisk) –0.287

Interaction effects

RR x Impression management (βRR, IM) 0.162

RR x Perceived social undesirability (βRR, SD) 0.273

RR x Perceived legal risk (βRR, risk) 0.192

Latent class probability (κ)

Non-adherence (%) 12.0 11.8 11.8 11.8

Notes. Estimates in bold do not contain 0 in their 95% credible interval. All tests are two-sided tests. All predictors are mean-centered. n = 1,601.

Table 2

Simulation study results

Simulated

covariance (ρ) Parameters True values

Baseline model Proposed model

Mean SD RMSE Mean SD RMSE

0.000 γ –0.500 –0.503 0.032 0.028 –0.496 0.156 0.046

β1,2 0.300 0.304 0.035 0.152 0.301 0.084 0.154

ρ 0.000 –0.007 0.153 0.034

0.200 γ –0.500 –0.305 0.032 0.197 –0.486 0.089 0.076

β1,2 0.300 0.196 0.035 0.202 0.287 0.055 0.158

ρ 0.200 0.179 0.084 0.070

0.500 γ –0.500 –0.003 0.032 0.498 –0.493 0.046 0.048

β1,2 0.300 0.052 0.035 0.274 0.297 0.039 0.153

ρ 0.500 0.489 0.036 0.036

0.800 γ –0.500 0.303 0.032 0.803 –0.496 0.022 0.022

β1,2 0.300 –0.101 0.035 0.351 0.297 0.033 0.155

ρ 0.800 0.797 0.010 0.010

1.000 γ –0.500 0.501 0.032 1.001 –0.500 0.000 0.000

β1,2 0.300 –0.200 0.035 0.400 0.292 0.021 0.160

ρ 1.000 1.000 0.000 0.000

Table 3

Item characteristics of piracy and purchase intention items

Discriminations Thresholds

Intention Items αk τ k,1 τ k,2 τ k,3 τ k,4

Piracy Intention Items (θ1i)

Item 1: Download files via BitTorrent 1.611 0.127 0.752 1.302 1.848

Item 2: Download files via other P2P-networks 1.942 0.094 0.722 1.330 1.649 Item 3: Upload/share files via file-sharing networks 2.357 0.141 0.740 1.334 1.708 Item 4: Download files via newsgroups/Usenet 1.933 –0.036 0.631 1.283 1.706 Item 5: Download files via sharehoster or FTP server 1.428 –0.273 0.360 0.955 1.577 Item 6: Upload/share files via sharehoster or FTP server 2.011 0.069 0.682 1.282 1.640 Item 7: Download files via blogs or forums 1.442 –0.182 0.510 1.232 1.750

Item 8: Rip files from audio streams 0.827 –0.530 0.238 1.192 2.279

Item 9: Rip files from video streams 0.826 –1.054 –0.373 0.586 1.609

Item 10: Obtain files via instant messaging or email 1.024 –0.835 –0.143 0.741 1.745 Item 11: Obtain files via media storage devices 0.820 –1.993 –1.268 0.056 1.245 Item 12: Share files via instant messaging, email or storage devices 0.885 –1.595 –0.902 0.240 1.396 Item 13: Use VPN services for privacy protection 1.081 –0.359 0.427 1.316 2.059

Item 14: Purchase counterfeit CDs 0.743 –0.035 0.772 1.827 3.134

Item 15: Purchase unlicensed MP3s 0.847 –0.437 0.445 1.489 2.465

Item 16: Sell unlicensed music for a profit 1.144 0.578 1.270 1.852 2.677

Purchase Intention Items (θ2i)

Item 1: Purchase likelihood 1.928 –1.519 –1.144 0.583 0.138

Item 2: Purchase frequency 1.813 –1.319 –0.642 0.045 0.756

Item 3: Usage of paid channels for music consumption 0.820 –1.479 –0.752 0.090 1.045 Item 4: Usage share of paid channels (most music consumption) 1.484 –1.158 –0.592 0.002 0.784 Item 5: Usage share of paid channels (all music consumption) 1.190 –0.874 –0.273 0.392 1.054

Item 6: Spending intention 1.965 –1.572 –1.150 –0.423 0.394

Item 7: Spending intention compared with others 1.326 –0.908 –0.120 0.645 1.265 Item 8: Spending intention as part of disposable income 0.884 –0.647 0.593 1.582 2.361

Item 9: Spending amount (planned) 0.795 –1.224 –0.479 0.352 1.304

n = 3,246

Table 4

Posterior predictive check and agreement with piracy items under DQ and RR

Piracy Intention Items

Percentage Agreement obs. DQ est. DQ est. RR

Item 1: Download files via BitTorrent 2.2% 2.1% 3.0%

Item 2: Download files via other P2P-networks 1.2% 1.5% 2.3%

Item 3: Upload/share files via file-sharing networks 1.3% 1.1% 1.8%

Item 4: Download files via newsgroups/Usenet 2.0% 1.7% 2.6%

Item 5: Download files via sharehoster or FTP server 4.6% 5.0% 7.2%

Item 6: Upload/share files via sharehoster or FTP server 2.0% 1.3% 2.4%

Item 7: Download files via blogs or forums 3.0% 2.9% 4.3%

Item 8: Rip files from audio streams 6.8% 7.5% 10.3%

Item 9: Rip files from video streams 12.8% 14.3% 19.4%

Item 10: Obtain files via instant messaging or email 9.0% 9.9% 13.7%

Item 11: Obtain files via media storage devices 20.0% 22.9% 30.3%

Item 12: Share files via instant messaging, email or storage devices 17.3% 18.8% 25.3%

Item 13: Use VPN services for privacy protection 3.5% 4.1% 5.8%

Item 14: Purchase counterfeit CDs 3.7% 4.3% 5.9%

Item 15: Purchase unlicensed MP3s 4.3% 5.0% 6.9%

Item 16: Sell unlicensed music for a profit 1.7% 1.4% 2.0%

Notes. Agreement are responses 4: “agree” or 5: “strongly agree”. Obs. DQ = observed percentage in the direct questioning group, est. DQ/est. RR = estimated percentage under the proposed model in the direct questioning and randomized response group, respectively. n = 3,246

Table 5

Posterior mean estimates of the antecedents of piracy and purchase intentions

Model 1 Model 2

Predictor

Piracy Intention

Purchase Intention

Piracy Intention

Purchase Intention

Structural Parameters

Intercept (β0) –1.109 0.288 –1.041 0.467

Question technique (RR = 1) (δ) 0.401 0.426 Control variables

Age (in years) (β1) –0.008 –0.012 –0.015 –0.012 Gender (female = 1) (β2) 0.070 –0.314 0.075 –0.317

Income (β3) –0.017 0.096 –0.016 0.096

Music taste (independent) (β4) 0.010 0.142 0.106 0.141 Costs of piracy

Legal costs (β5) –0.075 –0.037 –0.084 –0.037

Moral costs (β6) –0.185 0.231 –0.179 0.230

Search costs (β7) 0.041 0.049 0.038 0.049

Technical costs (β8) –0.025 0.007 –0.025 0.007

Learning costs (β9) 0.030 0.003 0.023 0.003

Utility of piracy

Social utility (β10) 0.293 –0.014 0.387 –0.014

Anti-industry utility (β11) 0.158 0.013 0.164 0.012

Economic utility (β12) 0.003 0.019 0.002 0.020

Devaluation utility (β13) 0.065 –0.318 0.064 –0.317 Price of legitimate alternatives (β14) –0.032 –0.105 –0.033 –0.105 Lack of legitimate alternatives (β15) 0.017 –0.155 0.016 –0.155

Sampling utility (β16) 0.224 0.003 0.315 0.002

Question technique interactions

RR x Age (βRR, age) 0.008

RR x Music taste (βRR, taste) –0.135

RR x Social utility (βRR, social) –0.137

RR x Sampling utility (βRR, sampling) –0.127 Notes. Estimates in bold do not contain 0 in their 95% credible interval. All tests are two-sided tests. All predictors are mean-centered. The prior variances of θ1i and θ2i are set equal to 1 to fix the scale. n = 3,246.

Table 6

Influence of piracy intentions on purchase intentions and purchase behaviors

Influence on Purchase Intentionsa (n = 3,246)

Influence on Purchase Behaviors (n = 1,652)

Model 1 Model 2 Model 3 Model 4

Predictor

Piracy Intention

Purchase Intention

Piracy Intention

Purchase Intention

Piracy Intention

Purchase Behavior

Piracy Intention

Purchase Behavior Controlling for …

social desirability?b yes yes yes yes

endogeneity?c no yes no yes

Structural Parameters

Intercept (β0) –0.947 –.0269 –0.923 0.080 –0.534 1.601 –0.786 1.753

Question technique (δ) 0.407 0.409 0.495 0.491

Piracy Intention

Main effect (γ) –0.107 –0.171 –0.084 –0.120

Interaction effect (βDQ, piracy)b 0.090 0.151 0.007 0.029

Latent class probability (λ)

Main effect (βNP) 0.219 0.223

Non-purchasers (%) 10.1 10.1

a We only report coefficients that are related to the effect of piracy intentions on purchase intentions because the remaining predictor effects exhibit a high degree of stability across models.

b The difference in magnitude of the γ-parameter between the experimental groups is inferred by including an interaction term between the group indicator (DQ = 1) and the piracy intention main effect in the purchase regression equations. For example, the effect size of 0.090 in Model 1 indicates that γ = –0.017 under DQ.

c In models 1 and 3 with uncorrelated errors, we specify independent normal priors for the piracy and purchase constructs and define another independent predictor variable for piracy intentions.

Notes. Estimates in bold do not contain 0 in their 95% credible interval. All tests are two-sided tests. All predictors are mean-centered.

Table 7 Summary of effects

Purchase intentions Positive effect

• Moral costs Search costs

Income

Music taste (independent)

No effect

Legal costs Technical costs

Learning costs

Economic utility

Social utility

Anti-industry utility

Sampling utility

Negative effect

Age Price of alternatives

Lack of alternatives

Gender (female)

Devaluation utility

Negative effect No effect Positive effect Piracy intentions

Figure 1

Framework of the antecedents and consequences of piracy and purchase intentions

Notes. Piracy intentions are measured with direct questioning and randomized response using a between-subjects design. The effect of consumer intentions on purchase behavior is tested on a sub-sample using data from a longitudinal survey that was conducted subsequent to the main study.

Figure 2

Randomized response mechanism

Figure 3

Category response functions (a) Item 1

(b) Item 10

Figure 4

Probability distribution under proposed randomized response scheme

Note. The randomization device does not have to produce outcomes that are uniformly distributed, since the sampling design is integrated in the model. For example, when more forced “strongly agree” responses are in-structed, the model will expect on average more “strongly agree” responses

Appendix

Appendix 1: Survey items, descriptive statistics and procedural instructions