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Combining Quantitative Methods and Grounded Theory for Researching E-Reverse Auctions

Authors: Andrea Lösch;

Combining Quantitative Methods and Grounded Theory for Researching E-Reverse Auctions

Abstract

Even though many authors claim that e-reverse auctions (e-RAs) are detrimental to the effective building and management of buyer-supplier relationships (Emiliani and Stec 2004), not much is known about how specific characteristics of e-RAs may contribute to such negative effects on buyer-seller relations (Jap 2003). This study sets out not only to provide a first investigation of context, participants' information behaviour, and buyer-supplier relationships in e-RAs, but also to illustrate new methods for theory building in the e-RA and information systems domain. Following a grounded-theory approach, a comprehensive online questionnaire was developed (Losch and Lambert 2006) based on the critical review of the literature and the results of a preceding exploratory study (Losch 2005). Usable responses were received from 89 buyers and 54 suppliers, including both users and non-users of e-RAs. The data were analyzed using a novel approach to quantitative analysis based on suggestions by Glaser (1994). The results indicate that e-RAs have fewer negative effects on buyer-supplier relationships than currently assumed. They also show how context and the participants' information behaviour correlate with buyer-supplier relationships, thus providing first suggestions for a better management of e-RAs. The paper also thus provides a first illustration of how quantitative methodology might be usefully applied to information systems research, an area which is dominated by the use of qualitative methodology.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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