Call for Papers

CfP special issue on "The cultural impact in platform competition"

No longer accepting submissions

Guest Editors


User-generated content (UGC) has been widely utilized in the cross-cultural context with the globalization of online platform portals. For this special issue, we define UGC as what consumers post online including consumer product reviews at sites like Amazon and Yelp, posts on social media such as Facebook and Twitter, blogs, pictures, and images found in the online environment. The diversity of global consumers’ cultural backgrounds both enriches the utility of UGC on multi-national social media platforms and increases the complexity of platform competition strategy (Alt & Zimmermann, 2019). While some studies reported cross-cultural created differences in ethnic restaurant reviews (Chik et al., 2016; Nakayama & Wan, 2019b), we are still in the early stage of understanding how cross-cultural influences are transpiring on the broader spectrum of UGC, such as how to channel their influence as a differential factor into service or product recommendation and customization in platform competition. Thus, empirical investigations are needed to explore innovative methods and frameworks on the cultural data analytics of UGC as well as on the integration of cultural factors into platform competition strategies. In this special issue, we encourage submissions that apply a cross-disciplinary perspective beyond the extant national culture frameworks, such as Hofstede (Hofstede, 1980; Minkov & Hofstede, 2012) and intercultural communication (Gudykunst, 2005).

Central issues and topics

Today, global social media platforms such as Facebook and Yelp are accessible not only via PC and smartphone but also via automobiles and an increasing number of IoT devices. Such platforms constantly collect and analyze UGC, then interpret them into recommendation or customized products and services back into the platform. Though this process has been replicated across the globe in different languages by ecommerce portals, they are more or less applying the same algorithms and standard practices across platforms. However, consumers from different countries are not a monolithic group. Their cultural backgrounds heavily influence their preferences, usage, and evaluation of products and services. Globally standardized recommendation and customization algorithms without incorporating culture elements could contribute or directly lead to strategic failures, such as the exit of the Chinese market by Amazon (Liao, 2019). Meanwhile, recent studies found consumers with different cultural backgrounds place different emphases on food quality, waiter service, ambiance, and price fairness in their reviews (Nakayama & Wan, 2018, 2019a). In other words, comparable Yelp five-star sushi restaurants in Tokyo and New York could be different because Japanese and US reviewers have different emphasis on evaluation attributes. Failure to account for cross-cultural differences on the provided ratings may also distort the information content of UGC for firms and customers (Stamolampros et al., 2019).

Today’s economy is driven strongly by optimizing the product mix to the target consumer profiles on a global scale. When cultural factors influence the consumer in the evaluation of products and services, we should expect such influence being properly utilized, presented, and informed to other consumers through recommendation systems, widgets on social media outlets, and review websites. With the big data analytical methods being systematically used in the cross-cultural perspective of UGC to help analyze such influence (Akter & Wamba, 2016), we expect future studies would not only identify cultural influence but also measure them quantitatively. We encourage submissions that apply a cross-disciplinary perspective on the cultural impact of UGC with topics such as:

  • Theoretical frameworks to analyze national culture influence on UGC
  • Cultural induced textual/sentimental characteristics of UGC
  • Sentiment analyses of UGC across national, regional or ethnic cultures
  • Cross-cultural analyses of UGC for subjective goods such as hospitality products and services
  • Diversity of UGC reactions and consumers’ cultural background
  • Review summarization strategy considering cultural variations of UGC
  • Adaption strategy of UGC across national, regional or ethnic cultures into platform competition
  • Biases in social media due to national, regional or ethnic cultures
  • Review of national, regional or ethnic cultural impact on UGC
  • Algorithm design in digital platforms considering cultural factors
  • Culture in designing recommendation and review systems
  • Management of platform content and functionalities in different cultures
  • Analyses of the competitive impact of cultural issues in digital platforms
  • Cross-cultural differences on the effect of UGC on corporate performance
  • Antecedents of the credibility of UGC in different cultures
  • Firm responses to negative UGC across national, regional or ethnic cultures


Electronic Markets is a Social Science Citation Index (SSCI)-listed journal (IF 3.553 in 2018) in the area of information systems. We encourage original contributions with a broad range of methodological approaches, including conceptual, qualitative and quantitative research. Please also consider position papers and case studies for this special issue. All papers should fit the journal scope (for more information, see and will undergo a double-blind peer-review process. Submissions must be made via the journal’s submission system and comply with the journal's formatting standards. The preferred average article length is approximately 8,000 words, excluding references. If you would like to discuss any aspect of this special issue, you may either contact the guest editors or the Editorial Office.


Akter, S., & Wamba, S. F. (2016). Big data analytics in E-commerce: a systematic review and agenda for future research. Electronic Markets, 26(2), 173–194. doi: 10.1007/s12525-016-0219-0

Alt, R., & Zimmermann, H.-D. (2019). Electronic Markets on platform competition. Electronic Markets, 29(2), 143–149. doi:10.1007/s12525-019-00353-y

Chik, A., Vásquez, C., & Vasquez, C. (2016). A comparative multimodal analysis of restaurant reviews from two geographical contexts. Visual Communication, 16(1), 3–26. doi: 10.1177/1470357216634005

Gudykunst, W. B. (2005). Theorizing about intercultural communication. Sage.

Hofstede, G. (1980). Culture’s consequences: International differences in work-related values. London: Sage.

Liao, S. (2019). Amazon admits defeat against Chinese e-commerce rivals like Alibaba and - The Verge. The Verge. Accessed 30 December 2019

Minkov, M., & Hofstede, G. (2012). Hofstede’s fifth dimension: New evidence from the World Values Survey. Journal of cross-cultural psychology, 43(1), 3–14.

Nakayama, M., & Wan, Y. (2018). Is culture of origin associated with more expressions? An analysis of Yelp reviews on Japanese restaurants. Tourism Management, 66. doi: 10.1016/j.tourman.2017.10.019

Nakayama, M., & Wan, Y. (2019a). Cross-Cultural Examination on Content Bias and Helpfulness of Online Reviews?: Sentiment Balance at the Aspect Level for a Subjective Good. In HICSS 52 (Vol. 6, pp. 1154–1163).

Nakayama, M., & Wan, Y. (2019b). The cultural impact on social commerce: A sentiment analysis on Yelp ethnic restaurant reviews. Information and Management. doi: 10.1016/

Stamolampros, P., Korfiatis, N., Kourouthanassis, P., & Symitsi, E. (2019). Flying to Quality: Cultural Influences on Online Reviews. Journal of Travel Research, 58(3).496-511. doi: 10.1177/0047287518764345