Understanding Illegal Music Downloading in the UK: A Multi-Attribute Model
Journal of Research in Interactive Marketing, Vol. 5, No. 1, 2011
Posted: 9 May 2011 Last revised: 19 Jun 2014
Date Written: March 1, 2011
Abstract
Purpose – This study aims to examine the role of product attributes, applying the multi-attribute model, on consumers' decisions to download digital music via unauthorised sources in the UK.
Design/methodology/approach – The data were collected through an online survey. Consumer choice was measured through three sets of questions built on Likert scales to identify individuals' evaluation of importance placed on the eight attributes, when making a choice, and level of satisfaction with those, both for purchasing and downloading. Two logistic regression models are developed using background characteristics and responses to these three sets of questions. The consumer choice between purchasing digital music and downloading through unauthorised channels was analysed in regards to eight product-specific attributes.
Findings – The results show that illegal downloaders expect a similar utility from both channels, while others tend to have a more positive attitude towards their chosen channel (i.e. purchasing). Background characteristics such as age, gender, education, and income show some relevance to the choice of music downloading channel. Regarding the importance attributed to and satisfaction from the eight product attributes, security of the source, variety of available music, quality, copyright, and legitimacy of the source are found to be significant in determining the choice.
Practical implications – This study is likely to guide digital music providers in designing their marketing plans using key attributes and consumer perceptions.
Originality/value – This is a rare study of downloading behaviour in the UK using a mixed population sample which is not dominated by students. Findings question the weight of price in decision making.
Keywords: Consumer Behaviour, Copyright Law, Crimes, Decision Making, Internet, Music
JEL Classification: M30, M39
Suggested Citation: Suggested Citation