Cross-cultural differences in the adoption of social media
Published on Jan 21, 2019in Journal of Research in Interactive Marketing
· DOI :10.1108/JRIM-10-2017-0092
As social media have become very popular and an integral part of the world economy in recent years, identifying factors that influence consumers’ attitudes toward social media sites has become a major goal of many researchers in academia and industry. This paper aims to identify factors that predict consumers’ attitudes and intentions toward usage of Instagram, a relatively new social media tool. In addition, it examines the role of an important dimension of culture – individualism vs collectivism –to determine cultural influences on the adoption of social media in the USA (i.e. an individualistic culture) and Kuwait (i.e. a collectivist culture).,Data were collected from a convenience sample of undergraduate business and MBA students from Kuwait and the USA. To validate the measures for the constructs depicted in the conceptual model, the authors conducted an exploratory factor analysis using all items. They then conducted a confirmatory factor analysis to further evaluate the adequacy and validity of the measurement model. They also tested the hypotheses using structural equation modeling (SEM).,Out of the nine hypotheses that were tested for significance, the SEM results indicated that seven hypotheses were significant. The results indicated a non-significant result between perceived critical mass is not a predictor of perceived usefulness and social influence to attitude.,The current study has some limitations that need to be recognized and can be used as guidelines for future research. First, college students represent only a portion of online users and may impact the external validity of our study. Hence, a more diverse sample with a broader range of ages, incomes, education levels, cultures and national origins would be advisable. Second, this study featured a dynamically continuous innovation (Instagram) rather than a discontinuous innovation. Third, other factors can be carried out to see other variables other than those described in this study to predict consumer’s attitude and intention to use the social media.,Cultural characteristics such as individualism/collectivism would seem to be potentially useful when segmenting countries. The results of the current study indicate that the modified model is applicable to a cross-national group of social media users. This study demonstrates the impact of cultural characteristics on various technology adoption. Hence, managers must be aware that countries can be grouped according to the type of cultural effect within each. Each social media category, clusters can be formed consisting of countries that are expected to have similar usage patterns based on technological capability and social norms. By understanding the factors that influence each cluster of countries, firms can design customized social media programs.,This research provides valuable information to better understand the consumers’ attitudes and intentions toward the emerging social media landscape. Indeed, the popularity of social media has greatly changed the way in which people communicate in today’s world. In particular, Instagram has gradually become a major communication media for both social and business purposes. This research shed light into the factors that influence intentions to adopt social media across different cultures. It empirically examines the role of culture – individualism vs collectivism – by using two samples (i.e. Kuwait and the USA) to determine cultural influences on the adoption of social media in different cultures.,Using data drawn from Kuwait and US samples, this current study draws upon the theory of reasoned action (Fishbein and Ajzen, 1975) and the technology acceptance model (Davis, 1989). The results of the analysis indicate that the modified model is applicable to a cross-national group of social media users. Moreover, this study demonstrates the impact of cultural characteristics on various technology adoption constructs in the model.