A Classification of Online Music Consumers

Bauer, Hans H. ; Neumann, Marcus M. ; Huber, Frank ; Haber, Tobias E.

Dokumenttyp: Präsentation auf Konferenz
Erscheinungsjahr: 2005
Veranstaltungstitel: From Data and Information Analysis to Knowledge Engineering : proceedings of the 29th Annual Conference of The Gesellschaft für Klassifikation e.V.
Veranstaltungsort: Magdeburg
Veranstaltungsdatum: March 9-11, 2005
Sprache der Veröffentlichung: Englisch
Einrichtung: Fakultät für Betriebswirtschaftslehre > ABWL u. Marketing II (Bauer Em)
Fachgebiet: 000 Allgemeines, Wissenschaft
Abstract: Companies in the music industry increasingly aim to develop the potential of the internet to enhance their business activities. However, at the same time they are facing massive threats with their traditional distribution system, due to free of charge supply of music provided by peer-to-peer-systems. The initial point of this survey is the traditionally low customer orientation of the music industry. Recently developed music on demand services provide a number of advantages for consumers over traditional music suppliers and can, simultaneously, initiate and optimise comprehensive communication and transaction processes. These music on demand services can be the strategic path for the music industry to establish long lasting and profitable customer relationships, assuming they manage to generate a true added value for their customers. It is the goal of this study to identify benefit generating elements of a potential music on demand service. In a survey of actual and potential online-music consumers (n = 1127), preference structures according to "virtual music" are evaluated for music consumers, using an Adaptive Conjoint Analysis. In a second step, central benefit dimensions are developed in an exploratory factor analysis and compared to existing supplier's offers. Results show that existing web sites to not suit customer needs as required. Furthermore, it is the goal of this study to analyse how the consumers can be classified based on their preferences, identified in the conjoint analysis. For this purpose, a hierarchical cluster analysis was performed which identified four different consumer segments. A second cluster analysis, allowed another benefit segmentation, looking at the extracted benefit dimensions and analysing their relevance for the actual userinterfaces of music online suppliers. In this cluster analysis, four consumer segments could be identified. Results show that consumers appreciate seven identified benefit dimensions, which can be used a guideline for web site's design. Based on the results, management oriented customer satisfactions analysis can be implemented easily.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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Bauer, Hans H. ; Neumann, Marcus M. ; Huber, Frank ; Haber, Tobias E. (2005) A Classification of Online Music Consumers. [Präsentation auf Konferenz]

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