Analysis methods: Ranking methods

 

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Paper
1.
How to Kiss? (Keep it simple, stupid)
Olivier L. Aron, ESOMAR, Fragrances Conference, New York, May 2005
The paper describes a specific philosophy and a new methodology for conducting fragrance market research, i.e., TEST NOMADE™. The better understanding of the rationale and merits of this methodology a ...

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Read: 19 times
Paper
2.
An Insightful Comparison of Brands on an Arbitrary Ordinal Scale
Zvi Gilula and Benjamin Yakir, International Journal of Market Research, Vol. 40, No. 3, 1998
The ability to rank brands or services from 'best' to 'worst' is a well-known marketing need. The current methodology for doing so is at best ad hoc; it involves some arbitrary techniques and is not g ...

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Read: 7 times
Paper
3.
Unconventional wisdom: remove 'that's how we've always conducted research' from your vocabulary
Terry Grapentine, Market Research Abstract from: Marketing Research, Fall 2006, Vol 18, No 3, pp 27-31, , (full text not available on WARC.com)
The paper suggests that today’s pressures can compel researchers to conduct research using traditional methodologies and approaches, without assessing other factors and more recent changes. In particu ...

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Paper
4.
An extended paradigm for measurement analysis of marketing constructs applicable to panel data
Hans Baumgartner and Jan-Benedict E.M. Steenkamp, Market Research Abstract from: Journal of Marketing Research, Vol XLIII, No 3, August 2006, pp 431-442, , (full text not available on WARC.com)
The authors propose extensions to the current scale development paradigm, including by a model which separates stable and transient sources of variation, and by an exploration of whether error affects ...

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Paper
5.
Leveraging missing ratings to improve online recommendation systems
Yuanping Ying, Fred Feinberg and Michel Wedel, Market Research Abstract from: Journal of Marketing Research, Vol XLIII, No 3, August 2006, pp 355-365, , (full text not available on WARC.com)
‘Product recommendation systems’ are increasingly important to the network economy, leveraging customers’ prior product ratings to generate subsequent suggestions. The authors discuss increasing data ...

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