Response Bias, Yea-Saying, and the Double Negative

Arndt, Johan; Crane, Edgar

doi:10.1177/002224377501200212

Cited by 13 publications

(8 citation statements)

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“…14. In an empirical demonstration of this phenomenon, Arndt and Crane (1975) found significant differences in Likert responses to equivalent positively and negatively worded items for 15 of the 20 items in their study. A recent major investigation by Baumgartner and Steenkamp (2001), using items of the typical Likert item type with the attribute intensity in the stem and an agree-disagree response format, found severe "response style" effects, such as acquiescence tendency and mid-point tendency, which altered scale scores by up to 29% and inflated or deflated correlations between scale scores by more than 50% if the two scales had the same bias.…”

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confidence: 86%

The C-OAR-SE procedure for scale development in marketing

Rossiter

2002

International Journal of Research in Marketing

1,921

1,407

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Construct definition, Object classification, Attribute classification, Rater identification, Scale formation, and Enumeration and reporting (C-OAR-SE) is proposed as a new procedure for the development of scales to measure marketing constructs. COARSE is based on content validity, established by expert agreement after pre-interviews with target raters. In C-OAR-SE, constructs are defined in terms of Object, Attribute, and Rater Entity. The Object classification and Attribute classification steps in C-OAR-SE produce a framework (six types of scales) indicating when to use single-item vs. multiple-item scales and, for multiple-item scales, when to use an index of essential items rather than selecting unidimensional items with a high coefficient alpha. The Rater Entity type largely determines reliability, which is a precision-ofscore estimate for a particular application of the scale.

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confidence: 86%

The C-OAR-SE procedure for scale development in marketing

Rossiter

2002

International Journal of Research in Marketing

1,921

1,407

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“…Kalwani and Silk (1982) report that 15.5% of the variation in ratings is attributed to response bias. Typically, respondents may give ratings that are either too easy or too harsh compared with their true psychological state (Arndt and Crane 1975; Dwyer 1980). For this type of bias, the observed ratings and true underlying satisfaction will be related as illustrated by the dotted lines in Figure 1 (for details, see Arnold, Feldman, and Purbhoo 1985).…”

Section: Background and Research Issuesmentioning

confidence: 99%

Satisfaction, Repurchase Intent, and Repurchase Behavior: Investigating the Moderating Effect of Customer Characteristics

Mittal

Kamakura

2001

Journal of Marketing Research

1,702

1,234

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for helpful comments on this article. This manuscript was processed and accepted during the tenure of the previous editor, Russell S. Winer. VIKAS MITTAL and WAGNER A. KAMAKURA*Despite the claim that satisfaction ratings are linked to repurchase behavior, few attempts can be found that relate satisfaction ratings to actual repurchase behavior. This article fills this void by presenting a conceptual model for relating satisfaction ratings and repurchase behavior. The model is based on the premise that ratings observed in a typical customer satisfaction survey are error-prone measures of the customer's true satisfaction, and they may vary systematically on the basis of consumer characteristics. The authors apply the model to a large-scale study of 100,040 automotive customers. Results show that consumers with different characteristics have different thresholds such that, at the same level of rated satisfaction, repurchase rates are systematically different among different customer groups. The authors also find that the nature and extent of response bias in satisfaction ratings varies by customer characteristics. In one group, the response bias is so high that rated satisfaction is completely uncorrelated to repurchase behavior (r = 0). Furthermore, the authors find that, though nonlinear, the functional form relating rated satisfaction to repurchase intent is different from the one relating it to repurchase behavior. Although the functional form exhibits decreasing returns in the case of repurchase intent, it exhibits monotonically increasing returns in the case of repurchase behavior.

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“…In contrast, the buy-response obtained with the DC method refers only to the upper limit of the acceptable price range (Halvorsen and Soelensminde, 1998). This method also facilitates systematic answering, without deep consideration of the question (Arndt and Crane, 1975). Finally, the DC method provides an indirect measure of WTP that is conditional on the price vector used and the assumptions required by the statistical treatment (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Effectiveness of measures assessing response to price information

Desmet

2016

JPBM

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Purpose Questionnaire measures of consumers’ willingness to pay (WTP) and price sensitivity are biased, yet these declarative methods can aid managerial decision-making. Additional choices involve which question formats to use (open-ended or discrete choice) and how many questions (unique versus multiple). This paper aims to inform such choices for online data collection with an empirical evaluation of the size of the bias induced by four methods (price acceptability, price judgements, multiple discrete choices and single discrete choices) in a realistic choice context. Design/methodology/approach An experimental framework collects online data about a staple product whose price should be well known. Price sensitivity, WTP and their confidence intervals are derived from a logistic binary model of acceptability, then ranked to evaluate the size of the bias of each method, relative to an indirect benchmark. Findings Online data collections with self-administrated questionnaires lower respondents’ involvement and create substantial bias; hypothetical methods overestimate WTP and underestimate price sensitivity, especially with methods using unique questions (both discrete choice and price acceptability). Multiple questions (price judgements and repeated random discrete choices) increase attention to price information and reduce the bias. The round price effect also is notable in data collected by open-ended methods. Practical implications To measure declarative WTP and price sensitivity with online data collections, researchers should use a random discrete choices method. Price acceptability questions and split tests are not recommended. Price judgements provide reliable information about consumer reactions to prices, but the strong round price bias is problematic. Originality/value This study adds to marketing and economic literature by comparing actual measurement methods used by firms, rather than hypothetical versions, and offers strong external validity.

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Response Bias, Yea-Saying, and the Double Negative

Cited by 13 publications

References 1 publication

The C-OAR-SE procedure for scale development in marketing

The C-OAR-SE procedure for scale development in marketing

Satisfaction, Repurchase Intent, and Repurchase Behavior: Investigating the Moderating Effect of Customer Characteristics

Effectiveness of measures assessing response to price information

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