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| − | |Name of Study=Zhu, Madnick, Siegel (2008)
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| − | |Author=Hongwei Zhu, Stuart E. Madnick and Michael D. Siegel
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| − | |Title=An Economic Analysis of Policies for the Protection and Reuse of Noncopyrightable Database Contents
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| − | |Year=2008
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| − | |Full Citation=Zhu, Hongwei, Stuart E. Madnick, and Michael D. Siegel. An economic analysis of policies for the protection and reuse of noncopyrightable database contents. Journal of Management Information Systems 25.1 (2008): 199-232.
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| − | |Abstract=The availability of data on the Web and new data extraction technologies have made it increasingly easy to reuse existing data to create new databases and provide value-added services. Meanwhile, database creators have been seeking legal protection for their data, such as the European Union's Database Directive. The legislative development shows that there is significant difficulty in finding the right balance between protecting the incentives of creating publicly accessible databases (including semistructured Web sites) and preserving adequate access to factual data for value-creating activities. We address this issue using an extended spatial competition model that explicitly considers licensing provisions and inefficiencies in policy administration. The results show that, depending on the cost level of database creation, the degree of differentiation of the reuser database, and the efficiency of policy administration, there are different socially beneficial policy choices, such as protecting a legal monopoly, encouraging competition via compulsory licensing, discouraging voluntary licensing, or even allowing free riding. With the appropriate policy in place, both the creators and the reusers should focus on innovation that can increase the variety of databases and create value from database contents.
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| − | |Authentic Link=http://www.tandfonline.com/doi/abs/10.2753/MIS0742-1222250108#.Vwl17aQrLIU
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| − | |Reference=Landes and Posner (1989); Lessig (1998);
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| − | |Plain Text Proposition=The results show that, depending on the cost level of database creation, the degree of differentiation of the reuser database, and the efficiency of policy administration, there are different socially beneficial policy choices, such as protecting a legal monopoly, encouraging competition via compulsory licensing, discouraging voluntary licensing, or even allowing free riding. With the appropriate policy in place, both the creators and the reusers should focus on innovation that can increase the variety of databases and create value from database contents.
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| − | |FundamentalIssue=4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption), 2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?,
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| − | |EvidenceBasedPolicy=A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right),
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| − | |Discipline=L12: Monopoly • Monopolization Strategies, L86: Information and Internet Services • Computer Software, O34: Intellectual Property and Intellectual Capital
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| − | |Intervention-Response=New database regulation will impact all stakeholders in the information economy, in which database creators, data reusers, and the consumers of the creator or reuser database products are the primary ones. One of the important factors to consider in policy formulation is the financial interests in database contents. A creator who invested in creating a database is interested in recouping the investment using the revenues that the database helps to generate. The revenues may be reduced when a free-riding reuser creates a competing database by extracting the contents from the creator's database. Thus, creators would like to have certain means of protecting the contents in their databases. Without adequate protection, the incentives of creating such databases could diminish. On the other hand, overprotection can cause under-utilization of information and make downstream value-added data reuse costly or even impossible. It is important, and often rather difficult, to formulate a policy that reasonably balances the two interests.
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| − | |Description of Data=This study analyses different models of database creation with various levels of openness and protection, using information from previous empirical studies published from 1989 to 2008. The authors examine these models in the light of the EU Database Directive.
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| − | |Data Year=1989 to 2008
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| − | |Data Type=Secondary data
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| − | |Data Source=ECJ;
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| − | |Method of Collection=Quantitative Collection Methods, Quantitative data/text mining, Qualitative Collection Methods, Case Study
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| − | |Method of Analysis=Quantitative Analysis Methods, Quantitative content analysis (e.g. text or data mining)
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| − | |Industry=Software publishing (including video games); Computer programming;
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| − | |Country=European Union; United States;
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| − | |Cross-country=Yes
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| − | |Comparative=Yes
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| − | |Government or policy=No
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| − | |Literature review=Yes
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| − | |Dataset={{Dataset
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| − | |Sample Size=2
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| − | |Level of Aggregation=Models for database creation,
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| − | |Data Material Year=1989-2008
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