Difference between revisions of "Zhang (2012)"
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|Source={{Source | |Source={{Source | ||
|Name of Study=Zhang (2012) | |Name of Study=Zhang (2012) | ||
| − | |Author=Zhang, | + | |Author=Zhang, L.; |
|Title=Intellectual Property Strategy and the Long Tail: Evidence From the Recorded Music Industry | |Title=Intellectual Property Strategy and the Long Tail: Evidence From the Recorded Music Industry | ||
|Year=2012 | |Year=2012 | ||
|Full Citation=Zhang, L. (2014). Intellectual Property Strategy and the Long Tail: Evidence From the Recorded Music Industry. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515581 | |Full Citation=Zhang, L. (2014). Intellectual Property Strategy and the Long Tail: Evidence From the Recorded Music Industry. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515581 | ||
| − | |Abstract=Digitization has impacted firm profitability in many media industries by lowering the cost of copying and sharing creative works. I examine the impact of digital rights management (DRM) - a prevalent strategy used by firms in media industries to address piracy concerns - on music sales. I exploit a natural experiment, where different labels remove DRM from their entire catalogue of music at different times, to examine whether relaxing an album's sharing restrictions increases sales. Using a large sample of albums from all four major record labels, I find that removing DRM increases digital music sales by 10% but relaxing sharing restrictions does not impact all albums equally. It increases the sales of lower-selling albums (i.e., the | + | |Abstract=Digitization has impacted firm profitability in many media industries by lowering the cost of copying and sharing creative works. I examine the impact of digital rights management (DRM) - a prevalent strategy used by firms in media industries to address piracy concerns - on music sales. I exploit a natural experiment, where different labels remove DRM from their entire catalogue of music at different times, to examine whether relaxing an album's sharing restrictions increases sales. Using a large sample of albums from all four major record labels, I find that removing DRM increases digital music sales by 10% but relaxing sharing restrictions does not impact all albums equally. It increases the sales of lower-selling albums (i.e., the "long tail") significantly (30%) but does not benefit top-selling albums. These results suggest that the optimal strength of copyright depends on the distribution of products in firms' portfolio. |
| + | |Authentic Link=http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515581 | ||
|Link=http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515581 | |Link=http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515581 | ||
| − | |Reference= | + | |Reference=Schumpeter (1934);Anderson (2006);Peitz and Waelbroeck (2006);Brynjolfsson, Hu, and Simester (2011); |
| − | |Plain Text Proposition=* | + | |Plain Text Proposition=* Removing DRM increases record sales by 10% and increases sales more in the long tail of the distribution, meaning that less well known artists gain the most from removing DRM. * This suggests that lowering search costs facilitates discovery and thus increases album sales. Of non mainstream artists. Removing DRM had little effect on well established artists.* The author notes that this strategy could also increase total consumer welfare by introducing songs to new people who otherwise wouldn't know of them. * The author also notes that the results might be different for other copyright industries outside of the music industry. |
| − | * This suggests that lowering search costs facilitates discovery and thus increases album sales. Of non mainstream artists. | + | |FundamentalIssue=2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?,5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media) |
| − | Removing DRM had little effect on well established artists. | + | |EvidenceBasedPolicy=A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right),F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness) |
| − | * The author notes that this strategy could also increase total consumer welfare by introducing songs to new people who otherwise wouldn't know of them. | ||
| − | * The author also notes that the results might be different for other copyright industries outside of the music industry. | ||
| − | |FundamentalIssue=2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?, 5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media) | ||
| − | |EvidenceBasedPolicy=A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right), F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness) | ||
|Discipline=O33: Technological Change: Choices and Consequences • Diffusion Processes, O34: Intellectual Property and Intellectual Capital | |Discipline=O33: Technological Change: Choices and Consequences • Diffusion Processes, O34: Intellectual Property and Intellectual Capital | ||
| − | |Intervention-Response=Could be useful for companies to take the results into account and depending on their portfolio | + | |Intervention-Response=Could be useful for companies to take the results into account and depending on their portfolio either use or not use DMR. |
| − | |Description of Data=Data covers music sold between January 1992 and June 2012. | + | |Description of Data=Data covers music sold between January 1992 and June 2012. Dataset contains monthly data of the number of albums sold through traditional outlets like retail chains and digital albums. |
|Data Year=January 1992 – June 2012 | |Data Year=January 1992 – June 2012 | ||
|Data Type=Secondary data | |Data Type=Secondary data | ||
| − | |Data Source=Nielsen SoundScan; Billboard Chart; | + | |Data Source=Nielsen SoundScan;Billboard Chart; |
|Method of Collection=Quantitative Collection Methods, Quantitative data/text mining | |Method of Collection=Quantitative Collection Methods, Quantitative data/text mining | ||
|Method of Analysis=Quantitative Analysis Methods, Descriptive statistics (counting; means reporting; cross-tabulation), Multivariate Statistics, Regression Analysis | |Method of Analysis=Quantitative Analysis Methods, Descriptive statistics (counting; means reporting; cross-tabulation), Multivariate Statistics, Regression Analysis | ||
| Line 28: | Line 25: | ||
|Cross-country=No | |Cross-country=No | ||
|Comparative=No | |Comparative=No | ||
| + | |Government or policy=No | ||
| + | |Literature review=No | ||
| + | }} | ||
| + | |Dataset={{Dataset | ||
| + | |Sample Size=634 | ||
| + | |Level of Aggregation=Artist | ||
| + | |Data Material Year=1992-2012 | ||
| + | }}{{Dataset | ||
| + | |Sample Size=5,864 | ||
| + | |Level of Aggregation=Album | ||
| + | |Data Material Year=1992-2012 | ||
}} | }} | ||
| − | |||
}} | }} | ||
Latest revision as of 08:20, 3 June 2020
Contents
Source Details
| Zhang (2012) | |
| Title: | Intellectual Property Strategy and the Long Tail: Evidence From the Recorded Music Industry |
| Author(s): | Zhang, L. |
| Year: | 2012 |
| Citation: | Zhang, L. (2014). Intellectual Property Strategy and the Long Tail: Evidence From the Recorded Music Industry. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2515581 |
| Link(s): | Definitive , Open Access |
| Key Related Studies: | |
| Discipline: | |
| Linked by: | Belleflamme and Peitz (2014) |
| About the Data | |
| Data Description: | Data covers music sold between January 1992 and June 2012. Dataset contains monthly data of the number of albums sold through traditional outlets like retail chains and digital albums. |
| Data Type: | Secondary data |
| Secondary Data Sources: | |
| Data Collection Methods: | |
| Data Analysis Methods: | |
| Industry(ies): | |
| Country(ies): | |
| Cross Country Study?: | No |
| Comparative Study?: | No |
| Literature review?: | No |
| Government or policy study?: | No |
| Time Period(s) of Collection: |
|
| Funder(s): | |
Abstract
Digitization has impacted firm profitability in many media industries by lowering the cost of copying and sharing creative works. I examine the impact of digital rights management (DRM) - a prevalent strategy used by firms in media industries to address piracy concerns - on music sales. I exploit a natural experiment, where different labels remove DRM from their entire catalogue of music at different times, to examine whether relaxing an album's sharing restrictions increases sales. Using a large sample of albums from all four major record labels, I find that removing DRM increases digital music sales by 10% but relaxing sharing restrictions does not impact all albums equally. It increases the sales of lower-selling albums (i.e., the "long tail") significantly (30%) but does not benefit top-selling albums. These results suggest that the optimal strength of copyright depends on the distribution of products in firms' portfolio.
Main Results of the Study
- Removing DRM increases record sales by 10% and increases sales more in the long tail of the distribution, meaning that less well known artists gain the most from removing DRM. * This suggests that lowering search costs facilitates discovery and thus increases album sales. Of non mainstream artists. Removing DRM had little effect on well established artists.* The author notes that this strategy could also increase total consumer welfare by introducing songs to new people who otherwise wouldn't know of them. * The author also notes that the results might be different for other copyright industries outside of the music industry.
Policy Implications as Stated By Author
Could be useful for companies to take the results into account and depending on their portfolio either use or not use DMR.
Coverage of Study
Datasets
| Sample size: | 634 |
| Level of aggregation: | Artist |
| Period of material under study: | 1992-2012 |
| Sample size: | 5,864 |
| Level of aggregation: | Album |
| Period of material under study: | 1992-2012 |
