A Classification of Online Music Consumers
Bauer, Hans H.
;
Neumann, Marcus M.
;
Huber, Frank
;
Haber, Tobias E.
Dokumenttyp:
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Präsentation auf Konferenz
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Erscheinungsjahr:
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2005
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Titel einer Zeitschrift oder einer Reihe:
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Proceedings of the ... Annual Conference of the Gesellschaft für Klassifikation e.V.
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Veranstaltungstitel:
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From Data and Information Analysis to Knowledge Engineering : proceedings of the 29th Annual Conference of The Gesellschaft für Klassifikation e.V.
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Veranstaltungsort:
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Magdeburg
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Veranstaltungsdatum:
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March 9-11, 2005
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Sprache der Veröffentlichung:
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Englisch
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Einrichtung:
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Fakultät für Betriebswirtschaftslehre > ABWL u. Marketing II (Bauer 1993-, Em)
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Fachgebiet:
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000 Allgemeines, Wissenschaft
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Abstract:
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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.
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