Difference between revisions of "Balducci (2009)"
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|Name of Study=Balducci (2009) | |Name of Study=Balducci (2009) | ||
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|Abstract=Using survey data on cultural consumption by about 650 university students, this article proposes a market segmentation and some "rule-of-thumb" managerial implications for the music industry. The aim is to show how technological innovation impacts on the structure of consumer preferences. Consumption behaviours, listening habits and musical preferences are explained by a large number of variables. Nevertheless it is possible to reduce this overload of information into two common factors (using "factor analysis"). "Cluster analysis" is accordingly used to group the students-consumers. The findings are then deepened in light of an econometric analysis. The analysis shows that the new digital technologies (for example "file sharing") may be harmful for the music industry only within one specific group of consumers. New technologies can instead promote music consumption (especially of live music) by the other categories of consumers. By investing in music knowledge and enjoyment, it is possible to induce consumers to buy digital music legally from authorized sites. | |Abstract=Using survey data on cultural consumption by about 650 university students, this article proposes a market segmentation and some "rule-of-thumb" managerial implications for the music industry. The aim is to show how technological innovation impacts on the structure of consumer preferences. Consumption behaviours, listening habits and musical preferences are explained by a large number of variables. Nevertheless it is possible to reduce this overload of information into two common factors (using "factor analysis"). "Cluster analysis" is accordingly used to group the students-consumers. The findings are then deepened in light of an econometric analysis. The analysis shows that the new digital technologies (for example "file sharing") may be harmful for the music industry only within one specific group of consumers. New technologies can instead promote music consumption (especially of live music) by the other categories of consumers. By investing in music knowledge and enjoyment, it is possible to induce consumers to buy digital music legally from authorized sites. | ||
|Authentic Link=http://www.rivisteweb.it/doi/10.1427/30395 | |Authentic Link=http://www.rivisteweb.it/doi/10.1427/30395 | ||
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|FundamentalIssue=4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption), | |FundamentalIssue=4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption), | ||
|EvidenceBasedPolicy=A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right), | |EvidenceBasedPolicy=A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right), | ||
|Discipline=L82: Entertainment • Media, O33: Technological Change: Choices and Consequences • Diffusion Processes, Z11: Economics of the Arts and Literature | |Discipline=L82: Entertainment • Media, O33: Technological Change: Choices and Consequences • Diffusion Processes, Z11: Economics of the Arts and Literature | ||
+ | |Description of Data=The dataset was derived from a survey administered to a sample of 634 university students at the Universit‡ Politecnica delle Marche and the Rimini campus of the Universiti di Bologna during April and May 2007. Ancona and Rimini are towns comparable in terms of population size. They are also situated in the same geographical area (central Italy). The mean age was 20.4 (with a median age of 20); 73% of the students were 19 or 20 years old,9.7% were 21, and 4.4% were aged over 23. | ||
+ | |Data Year=April to May 2007 | ||
|Data Type=Primary data | |Data Type=Primary data | ||
− | |Method of Collection=Survey Research (qualitative; e.g. consumer preferences) | + | |Method of Collection=Survey Research (qualitative; e.g. consumer preferences), Survey Research (quantitative; e.g. sales/income reporting) |
− | |Method of Analysis=Cluster analysis | + | |Method of Analysis=Cluster analysis, Textual Content Analysis |
|Industry=Sound recording and music publishing; | |Industry=Sound recording and music publishing; | ||
+ | |Country=Italy; | ||
|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=University students, | ||
+ | |Data Material Year=2007 | ||
}} | }} | ||
}} | }} |
Latest revision as of 12:56, 22 October 2016
Contents
Source Details
Balducci (2009) | |
Title: | Music or hi-tech lovers? Inferring into the determinants of music consumption |
Author(s): | Balducci, F. |
Year: | 2009 |
Citation: | Balducci, F. (2009). Music or hi-tech lovers? Inferring into the determinants of music consumption. Rivista italiana degli economisti, 14(2), 361-0. |
Link(s): | Definitive |
Key Related Studies: | |
Discipline: | |
Linked by: |
About the Data | |
Data Description: | The dataset was derived from a survey administered to a sample of 634 university students at the Universit‡ Politecnica delle Marche and the Rimini campus of the Universiti di Bologna during April and May 2007. Ancona and Rimini are towns comparable in terms of population size. They are also situated in the same geographical area (central Italy). The mean age was 20.4 (with a median age of 20); 73% of the students were 19 or 20 years old,9.7% were 21, and 4.4% were aged over 23. |
Data Type: | Primary 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
Using survey data on cultural consumption by about 650 university students, this article proposes a market segmentation and some "rule-of-thumb" managerial implications for the music industry. The aim is to show how technological innovation impacts on the structure of consumer preferences. Consumption behaviours, listening habits and musical preferences are explained by a large number of variables. Nevertheless it is possible to reduce this overload of information into two common factors (using "factor analysis"). "Cluster analysis" is accordingly used to group the students-consumers. The findings are then deepened in light of an econometric analysis. The analysis shows that the new digital technologies (for example "file sharing") may be harmful for the music industry only within one specific group of consumers. New technologies can instead promote music consumption (especially of live music) by the other categories of consumers. By investing in music knowledge and enjoyment, it is possible to induce consumers to buy digital music legally from authorized sites.
Main Results of the Study
Policy Implications as Stated By Author
Coverage of Study
Datasets
Sample size: | 634 |
Level of aggregation: | University students |
Period of material under study: | 2007 |