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Handbook of Research in International Marketing

Edited by Subhash C. Jain

Presenting the challenges and opportunities ahead, the contributors to this volume critically examine the current status and future direction of research in international marketing. The result of a sustained and lively dialogue among contributors from a variety of cultures, this volume gathers their perspectives and many insights on the revitalization of the field.
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Chapter 8: Measurement Problems in Cross-National Consumer Research: The State-of-the-Art and Future Research Directions

Attila Yaprak


Attila Yaprak INTRODUCTION Comparative study of behavior across cultures has become a fascinating scholarly pursuit in the social sciences. Along this journey, researchers have come across a wide variety of problems they have had to contend with in drawing meaning from their comparisons. For example, they have had to cope with inequalities in the meanings of phenomena across cultural groups, the sometimes inappropriateness of the measurement instruments used across cultures, difficulties in generalizing findings to national or cultural populations of interest, and so forth. Importantly, they have had to learn that their research has to be able to navigate through these barriers while exploring, explaining, and interpreting cross-national similarities and differences in behavior (Craig and Douglas 2000; Mullen 1995; Steenkamp and Baumgartner 1998; Van de Vjver and Leung 1997). Scholars of international marketing, for their part, have discovered that a better understanding of their concepts and constructs, and hence, the advancement of their field as an academic field of inquiry, required that their models and measures had to be psychometrically sound across countries and cultures (Bagozzi and Baumgartner 1994; Steenkamp and Baumgartner 1998). These scholars have had to address, for example, the question of whether the behavioral similarities and differences they were observing in their research across cultures were in fact real. If their observed findings were different than expected (statistical significance was not achieved or the reliability coefficients were low for example), they learned to question whether measurement problems had attenuated their findings;...

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