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Universal dimensions of individuals' perception: Revisiting the operationalization of warmth and competence with a mixed-method approach

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  • Halkias, Georgios
  • Diamantopoulos, Adamantios

Abstract

A dynamic and growing body of marketing literature draws from the Stereotype Content Model's (SCM) dimensions, warmth and competence, to describe individuals' perception of various market-related stimuli (e.g., salespeople, employees, products) and predict their influence on subsequent behavior. However, the operationalization of these fundamental dimensions in empirical marketing research has been inconsistent and problematic, hindering comparability of findings across studies and limiting the overall usefulness of warmth–competence in relevant research. Using a mixed-method approach, the present paper scrutinizes the warmth–competence dimensions in order to validate and optimize their measurement. Through seven studies using different methodologies and metrics, we identify a set of trait items that (a) capture perceptions of warmth and competence consistently across a variety of impression formation settings, and (b) display strong psychometric properties. Our findings offer a parsimonious approach that promotes the consistent operationalization of warmth and competence across marketing studies and enables the integration of empirical findings, both of which are crucial requirements for meta-analytic investigations, replication studies, and integrative reviews.

Suggested Citation

  • Halkias, Georgios & Diamantopoulos, Adamantios, 2020. "Universal dimensions of individuals' perception: Revisiting the operationalization of warmth and competence with a mixed-method approach," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 714-736.
    • Handle: RePEc:eee:ijrema:v:37:y:2020:i:4:p:714-736
    DOI: 10.1016/j.ijresmar.2020.02.004
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    Cited by:

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    3. Zouhui Ji & Yaping Yang & Xinfang Fan & Yuting Wang & Qiang Xu & Qing-Wei Chen, 2021. "Stereotypes of Social Groups in Mainland China in Terms of Warmth and Competence: Evidence from a Large Undergraduate Sample," IJERPH, MDPI, vol. 18(7), pages 1-21, March.
    4. Tao Liu & Kewei Shi & Lingli Hu & Yuqing Liu & Yunyao Liu, 2023. "A New Instrument for Measuring Customers’ Perceptions of Service Warmth: A Big Data and Machine Learning Approach," SAGE Open, , vol. 13(4), pages 21582440231, December.
    5. Yang, Yikai & Zheng, Jiehui & Yu, Yining & Qiu, Yiling & Wang, Lei, 2024. "The role of recommendation sources and attribute framing in online product recommendations," Journal of Business Research, Elsevier, vol. 174(C).
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    7. Barbarossa, Camilla & Buzeta, Cristian & De Pelsmacker, Patrick & Moons, Ingrid, 2022. "Foreign company misconduct and how consumers’ punitive intent is influenced by country stereotypes and the perceived similarity between the foreign country and the home country," International Business Review, Elsevier, vol. 31(5).
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