Cross-Cultural, Cross-Cultural Age and Cross-Cultural Generational Differences in Values between the United States and Japan
Notice bibliographique
Résumé
Executive Summary Many studies have explored cross-cultural, cross-cultural age, and cross-cultural generational differences in values. However, few studies have explored all three constructs in one research study, and even fewer have done so using the Rokeach Value Survey and working adult populations. This study filled in those research gaps by exploring whether there were crosscultural, cross-cultural age and cross-cultural generational differences in values together as constructs in one study between 1,283 United States and 209 Japanese respondents. The hypotheses were supported for cross-cultural (within) differences for 26 of 36 values, cross-cultural age (within) differences for 30 of 36 values and cross-cultural generational (across) differences for 23 of 36 values. The researchers explained the significance of these findings and made recommendations for further research. Introduction The research literature shows that many studies have explored cross-cultural differences, cross-cultural age, or cross-cultural generational differences in values, but few studies have explored all three constructs in one research study. In addition, researchers tend to use college students as the population of convenience to represent the values of adults. Researchers must not only explore cross-cultural or national level differences, but must also go below the national differences to explore cross-cultural age and cross-cultural generational differences in value structures so they can provide more accurate and meaningful information about employee motivation and consumer target to the business community. As DeMooij (1998, p. 3) pointed out, markets are people, not products. There may be global products, but there are no global people. There may be global brands but there are no global motivations for buying those brands. In-depth analysis that goes below the national level of analysis is needed because DeMooij's (1998) research showed that many managers are still trying to motivate employees through the use of money and benefits and marketers continue to develop marketing and advertising campaigns that are focused on values at the national level instead of focusing on the regional, local and individual levels (age and generational) of analysis. Managers and marketers must also move to lower levels of analysis to explore other constructs like cross-cultural age and cross-cultural generational differences in values because of their subsequent impact on attitudes and behavior. One of the most important indicators of attitudes and behavior is value structures, since research has shown that values are the underlying structures that affect attitudes and subsequent behavior (Ajzen, 1988; DeMooij, 1998; Kahle, 1984; Murphy and Andersen, 2003; Reynolds and Olson, 2001; Rokeach, 1979). Review of the literature The researcher's review of the research literature covered over 600 studies between 1977 and 2003 that explored cross-cultural, cross-cultural age and cross-cultural generational differences. Cross-Cultural Research A small sampling of the cross-cultural research literature using the RVS shows that Rokeach (1973) explored value differences between the United States, Australia, Canada and Israel using the Rokeach Value Survey (RVS). The research results suggested that the largest cross-cultural differences were for the terminal values a world at peace and national security and instrumental values ambitious and capable. Rokeach recommended that researchers explore value differences by exploring which values were more important for each culture and by exploring the top five Terminal Values (most important goals in life) and Instrumental Values (behavioral techniques used to obtain terminal value goals) of importance as they would allow researchers to fully explore the similarities and differences between cultures. Munson and Mclntyre's (1978) cross-cultural research suggested that the terminal value social recognition and instrumental value obedient were the only values in the top five of importance for respondents from Thailand, Mexico and the United States. …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».