Examining cultural effects on distributed decision-making processes using keyword analysis and data mining techniques
This empirical study employes a keyword analysis and text mining technique using the Provalis mixed methods research suite to examine the following research question: 'What is the impact of cultural context on decision-making processes in global virtual teams (GVTs) of transnational civil society?' Our approach to cultural context is primarily driven by Hall's (1976) theory of high vs. low context dimensions and Hofstede's (1980, 2001, 2005) five dimensional framework for analysing culture. Our four-stage conceptual model of decision-making draws on Zakaria (2006), Kingdon (1995), Adler (2002) and Guss (2002). We further explore this model of culture and decision making with data from a four-year public email archive (2002--2005) of the GVT of transnational civil society involved in UN World Summit on Information Society (WSIS). From a methodological perspective, we find that for our explicit cultural variables (gender and region), keyword content analysis and data mining techniques are powerful tools to unlock massive datasets. In contrast, for our implicit cultural variables (high-context and low context communication styles and cultural values), these techniques were not yet as helpful.