Data Equivalence in Cross-cultural Research: Methods and Tools

Data Equivalence in Cross-cultural Research: Methods and Tools Emmanuel Chéron, Ph.D. 上智大学 SOPHIA UNIVERSITY GRADUATE PROGRAM IN GLOBAL STUDIES International Business/Economics Tokyo

Agenda • Emic/etic controversy • Emic/etic approach implementation steps • Overall framework of data equivalence in cross-cultural research • Equivalence of research topics • Equivalence of data collection • Equivalence of data preparation • Statistical tests of measurement equivalence • Alternative approaches • Conclusion

Emic/etic controversy • Emic school (phonemic): • Attitudes, interests and behavior are unique to each culture • An emic perspective implies an ethnographic research approach with limitations in terms of comparison and generalization

Emic/etic controversy • Etic school (phonetics): • Attitudes and behavior are common across cultures allowing researchers to conduct inter-cultural measurements and comparaisons • Any comparison conducted in international marketing research postulates a valid etic model exposing to a • “pseudo-etic” bias risk (forced etic school) • Validity and reliability of measures between countries need to be checked (a simple internal reliability coefficient such as Cronbach alpha is not enough)

Emic/etic implementation steps • Research steps Culture A Culture B • (native) (foreign) • Start in A • Transfer in B • Discovery of B • Comparison of cultures • Comparison not possible • Comparison possible Emic A Forced Etic Emic B Emic A Emic B Emic B Emic A ` Emic B Emic A Shared Etic

Key point of emic/etic controversy Be aware that cultural contexts between cultures often do not completely overlap Examples of sources of difference: Geographical, climate, demographics, political system, economics, regulations, ethics, cultural, social, religious, distribution Networks and channels, etc.)

Equivalence in cross-cultural research • Equivalence of research topics • Functional, conceptual, category Problem definition • Equivalence of • research methods • collection, stimuli • Equivalence of • research units • definition, selection • Equivalence of administration • timing, interaction Data collection • Equivalence of data • handling • response translation, categories Data preparation • Equivalence of data in cross-cultural research • comparability of data Data analysis • Scalar invariance • relationships of contructs-observed Multi-group SEM (CFA) or Latent trait theory Statistical tests of data equivalence • Metric Invariance • factor loadings correspond • Configural invariance • basic factor patterns correspond

Equivalence of research topics? • Fonctional equivalence: meaning of physical training, • jogging,shopping, of owning certain objects? • Conceptual equivalence: meaning of stimuli (couleurs, • nombres, symboles, objets) • of behavior, gestures, social rituals (graduation, • marriage, funeral ceremonies, gift giving) • Category equivalence: category of objects (beer • as an alcoholic beverage, milk with meals, • hot vs cold continuum of parfumes in France, • meaning of marital status, of a biological mother • in Mali, ranking of professional status)

Key points of problem definition • Danger of self-reference to ones native culture • Importance of cultural understanding

Equivalence of data collection? • Equivalence of research methods • Collection techniques • Stimuli (verbal, visual) • Equivalence of research units • Administrative units (urban, rural) • Consumption unit • Buying decision roles • Equivalence of administration • Comparable timing • Interaction with respondents

Key point of equivalence of data collection Be aware that cross-cultural data equivalence must be balanced with limitations involved in local data collection administration

Equivalence of data handling? • Translation equivalence • Limitation of back-translation and decentering • (Schadenfreude,なつかしいnattsukashii) • Measurement systems equivalence • Currency exchange, purchasing power parity • Physical measurement systems (comparable quality standards) • Equivalence of measurement scale • Equivalence of scoring scale • No-saying and yeah-saying effects • Equivalence of response style • (extreme response style, response range)

Key points of equivalence of data handling Make sure that translations, measurement systems, scoring systems and response styles are equivalent • Baumgartner and Steenkamp (JM, 2001) using GfK survey data on • 11 European countries found an average response style effect of 8% • on the variance of 60 5-point Likert (degree of agreement) scales • When measuring consumer ethnocentrism and health consciouness, • they found a respective effect of 11 to 23% and 12 to 29% depending • on the country • The relative effect size between countries was found smaller than between • scales

Statistical tests of data equivalence? • Configural invariance • Test of the measurement model within culture • Test of cross-cultural configural invariance • Metric Invariance • Test of score equivalence given cross- cultural configural invariance • Scalar Invariance • Test of a common cross-cultural scale origin (partial equivalence?) • Invariance of latent response • Test of cross-cultural equality of parameters of the response probability model of each survey question

Key points of statistical tests of data equivalence The choice of equality constraints may change the test results of scalar invariance Qualitative empirical judgement is still needed to identify invariant items between culture

Alternative approaches • Compare actual cross-cultural buying behavior rather than non-observable survey data • Data mining of sales transaction • Latent class analysis to identify market segments • Cross-cultural comparison of observed response data in experimental setting • Neuromarketing • (Functional Magnetic Resonance Imaging) • 3D Simulation of commercial setting • Eye-tracking

Brand Recognition and Cultural Differences -- Heatmap Data real-time eye-tracking system (Source: JCMR, "Brand recognition and cultural impact, 2005.10") http://www.jmrlsi.co.jp/english/case/jmarket/2006/02_study_examples.html

Conclusion There are many complex requirements for cross- cultural data equivalence when measuring non-observable variables (attitudes, opinions, perceptions) In spite of many refinements available to improve comparison of non-observable variables, observed actual buying behavior and responses to experimental settings offer attractive alternatives

References Baumgartner, Hans and J-B Steenkamp (2001) «Response Styles in Marketing Research: A Cross-National Investigation», Journal of Marketing Research, Vol. 38, May, 143-156. Chéron, Emmanuel and Hideo Hayashi (2001), «The Effect of Respondents'Nationality and Familiarity with a Product Category on the Importance of Product Attributes in Consumer Choice: Globalization and the Evaluation of Domestic and Foreign Products», Japanese Psychological Research, Volume 43, No. 4, 183-194. Chéron, Emmanuel J.; Tetsuo Sugimoto and Hideo Hayashi, (1994), «Usage Frequency and Purchase Motives of Consumer Products: A Comparison between Canada and Japan», Asian Journal of Marketing, Vol. 3, December, 7-20. Chéron, Emmanuel J.; Thomas C. Padgett and Walter A. Woods (1987), «A Method for Cross-Cultural Comparisons for Global Strategies», Journal of Global Marketing, Vol. 1, Nos. 1 & 2, Fall/Winter, 31-51. Laroche, Michel; Linda C. Ueltschy; Shuzo Abe; Mark Cleveland and Peter P. Yannopoulos (2004) «Service Quality Perception and Consumer Satisfaction: Evaluating the role of Culture», Journal of International Marketing, Vol. 12, No. 3, 58-85. Salzberger, Thomas; Rudolf R. Sinkovics and Bodo B. Schlegelmich (1999) «Data Equivalence in Cross-cultural Research: A Comparison of Classic Test Theory and Latent Trait Theory Based Approaches», Australasian Marketing Journal, Vol. 7, No. 2, 23-38. Steenkamp J-B and Hans Baumgartner (1998) «Assessing Measurement Invariance in Cross-National Consumer Research», Journal of Consumer Research, Vol. 25, June, 78-90. Usunier, Jean-Claude and Julie Anne Lee (2005), Marketing Across Cultures, 4/E, Pearson, Prentice Hall Europe. ISBN: 0-273-68529-5.

Data Equivalence in Cross-cultural Research: Methods and Tools