The Anchor Contraction Effect in International Marketing Research

Langhe, Bart de; Puntoni, Stefano; Fernandes, Daniel; Osselaer, Stijn van

doi:10.1037/e621072012-159

Cited by 13 publications

(22 citation statements)

References 24 publications

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“…Finally, the calibrated sigma method may also be applicable in other contexts where different groups of respondents tend to show different response patterns regardless of content, for instance, situations where native speakers versus non-native speakers may attach different meanings to the same response category labels used in the same language (de Langhe, et al, 2011;Harzing, 2006;Weijters, et al, in press). …”

Section: Discussionmentioning

confidence: 99%

“…The most obvious domain of application of the method is in survey research involving multiple languages, where researchers are well aware of the issue of differential scale usage and where there is an active research tradition aiming to address this issue (de Langhe, et al, 2011;Weijters, et al, 2013;Weijters, Puntoni, & Baumgartner, in press). Here, the calibrated sigma method is especially useful when comparing Likert-type data in different languages, including samples that share the same nationality but use a different language, a common situation in marketing research (Holmqvist & Van Vaerenbergh, 2013;Van Vaerenbergh & Holmqvist, 2014;Weijters, et al, in press).…”

Section: Discussionmentioning

confidence: 99%

“…First, if only the endpoints are labeled, they are comparatively more salient and less ambiguous than the other response categories, which should encourage greater endorsement of the endpoints (Weijters, Cabooter, & Schillewaert, 2010). Second, the labels of the endpoints in the endpoint-labeled condition are less intense and therefore more likely to be endorsed (de Langhe, Puntoni, Fernandes, & van Osselaer, 2011). The SNI scale generally has a mean below the midpoint (Bearden, et al, 1989), because consumers typically do not believe that their behaviors are influenced by others (Bearden, et al, 1989;Gopinath & Nyer, 2009).…”

Section: Study 3: Empirical Application Of the Calibrated Sigma Methomentioning

confidence: 99%

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The calibrated sigma method: An efficient remedy for between-group differences in response category use on Likert scales

Weijters

Baumgartner

Geuens

2016

International Journal of Research in Marketing

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The authors propose a procedure, labeled the calibrated sigma method, which is designed to correct for between-group differences in endorsement likelihood of response categories that are unrelated to the content of the items. The method is especially useful in cross-cultural research where group differences may reflect variation in scale usage rather than substantive differences. However, the procedure is also relevant in other situations, for example, when different data collection modes or different experimental manipulations affect respondents' perception of the meaning of the scale labels. The calibrated sigma method uses information derived from heterogeneous control items (calibration items) to reweight the responses to substantive items in a group-specific way. The advantages of the calibrated sigma method are that it avoids the arbitrariness in the assignment of particular numerical values to response categories; that it is compatible with the linear model, which is used by most marketing researchers; and that it does not require the use of complex nonlinear models involving the estimation of many additional measurement model parameters. The authors validate the calibrated sigma method on a simulated cross-linguistic data set pertaining to 12 different languages; an empirical data set collected from respondents of the same nationality but from two different language groups; and an experimental data set consisting of responses to two different response scale formats. The findings demonstrate that the proposed procedure controls for artefactual scale use differences across groups but does not eliminate substantive differences. It is particularly efficient for marketing research agencies, panel providers and other marketing researchers who analyze surveys involving multiple language groups, different scale formats, multiple modes of data collection, or different manipulations affecting the meaning of the response category labels.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Study 3: Empirical Application Of the Calibrated Sigma Methomentioning

confidence: 99%

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The calibrated sigma method: An efficient remedy for between-group differences in response category use on Likert scales

Weijters

Baumgartner

Geuens

2016

International Journal of Research in Marketing

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“…It is likely that the intensity of the category labels affects response behavior under at least some circumstances, and it is also possible that intensity and familiarity have complementary effects on respondents' endorsement of the endpoint categories (i.e., the intensity and familiarity hypotheses need not be mutually contradictory). For example, the recent research of de Langhe et al (2011) supports the relevance of label intensity in emotion research. In an interesting series of studies, these authors show that when respondents verbalize emotional reactions in a non-native language, they express systematically more intense emotions than when they respond in their native language.…”

Section: Limitations and Future Researchmentioning

confidence: 99%

“…In emotion assessment, special symbols have been developed (sad, neutral and smiling faces, for example) to avoid translation problems (de Langhe et al 2011). However, these symbols are typically content-specific (e.g., designed to measure emotional valence) and it is not clear which symbols could be used to express degrees of agreement without the need to explain and label the symbols with words (which would in turn suffer from differences in wording familiarity).…”

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confidence: 99%

The Effect of Familiarity with the Response Category Labels on Item Response to Likert Scales

Weijters¹,

Geuens²,

Baumgartner³

2013

J Consum Res

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When Cheap Isn't the Same as Not Expensive: Generic Price Terms and Their Negations

2018

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Generic price terms such as cheap, not expensive, not cheap, and expensive are used frequently in marketing, but little is known about how consumers interpret them. In typical consumer contexts, in which lower prices are preferred, we find that not cheap means essentially the same as expensive (i.e., not cheap = expensive). In contrast, not expensive does not mean the same as cheap, in that cheap is associated with lower prices (i.e., cheap < not expensive). As an implication, in a consumer survey we find different response distributions for rating scales that are anchored with endpoint labels of not expensive versus expensive as compared to cheap versus expensive or cheap versus not cheap (the latter two are equivalent). Furthermore, although cheap is associated with lower prices than not expensive, this does not necessarily translate into higher preferences for options that are described as cheap (vs. not expensive), because cheap may also evoke negative quality perceptions. Finally, we demonstrate an interesting reversal in the way price terms are interpreted: when higher prices are preferred, cheap is equal to not expensive (i.e., cheap = not expensive), whereas not cheap is associated with lower prices than expensive (i.e., not cheap < expensive).

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The Anchor Contraction Effect in International Marketing Research

Cited by 13 publications

References 24 publications

The calibrated sigma method: An efficient remedy for between-group differences in response category use on Likert scales

The calibrated sigma method: An efficient remedy for between-group differences in response category use on Likert scales

The Effect of Familiarity with the Response Category Labels on Item Response to Likert Scales

When Cheap Isn't the Same as Not Expensive: Generic Price Terms and Their Negations

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