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An Alternative Approach to the Measurement of Emotional Attachment
Author(s) -
Jiménez Fernando R.,
Voss Kevin E.
Publication year - 2014
Publication title -
psychology and marketing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.035
H-Index - 116
eISSN - 1520-6793
pISSN - 0742-6046
DOI - 10.1002/mar.20700
Subject(s) - nomological network , construct (python library) , psychology , scale (ratio) , discriminant validity , construct validity , social psychology , set (abstract data type) , criterion validity , cognitive psychology , psychometrics , developmental psychology , computer science , internal consistency , physics , quantum mechanics , programming language
Emotional attachment (EA)—the emotional bond connecting an individual with a specific target—has been identified as an important construct within the marketing domain. Despite all the research, there is no consensus on how the construct should be measured. A major factor contributing to this confusion is that current definitions and, consequently, scales of EA focus on describing reactions toward specific referents of attachment rather than on capturing the extent of emotion an individual feels; hence, hindering construct validity. In this article, the authors scrutinized the concept validity of EA. After defining the construct, scale development procedures were followed to propose an alternative one‐dimensional scale that reflects the abstract nature of EA. Three studies support the scale's reliability as well as the discriminant, convergent, criterion, and nomological validity of the measure. The studies tested the scale under different marketing contexts. Moreover, by employing the new measure, the findings showed that EA and self‐concept maintenance (SCM) are related, yet different constructs. Specifically, the results showed that these constructs interact to predict willingness to pay (WTP) for a brand such that when SCM is low, WTP is predicted by EA. However, when self‐concept is high, the effect of EA on WTP is not that strong. This new scale will help researchers extend research on EA to a broader set of contexts, explore the relationship between EA and related constructs, develop nomological networks, and prevent the confounding of terms.