Knowledge Management, Culture and Development: Value Creation in National Economies

The paper investigates relations among dimensions of national culture, inclusion in the knowledge economy, sustainable development, intellectual capital and competitiveness, covering countries from a convenience sampling,... [ view full abstract ]

The paper investigates relations among dimensions of national culture, inclusion in the knowledge economy, sustainable development, intellectual capital and competitiveness, covering countries from a convenience sampling, depending on the availability of variables for comparative testing.
Based on the premise that it would be up to the public administration to promote a harmonious context from which the various actors could create value — economic, social and environmental —the following analytical frameworks are used: (i) culture as mental programming (Hofstede 1994; Trompenaars, 2003); knowledge as a promoter of development (K4D - World Bank, 2010); (iii) sustainable economic welfare / well-being (Cobb and Daly in 1989, 1989; CSLS, 1998); and (iv) intellectual capital of nations (Edvinsson, & Lin 2004), (v) global competitiveness (World Economic Forum, 2014).
Early findings indicate that there are significant interdependencies between dimensions of culture and fundamentals of the entry of countries in the Knowledge Economy. Also point to positive interaction of culture and extent of welfare/well-being. The associations among indicators of competitiveness and intellectual capital with the other variables are still in process.
The findings thus far reinforces the need for public administration, seeking to cross boundaries, objectively recognize cultural traits for policy formulation, adoption of practices and service delivery before benchmarks foreign management models — reinforcing Guerreiro Ramos (1996 ) on the sociological reduction path as a postcolonial engagement without loss of scientific objectivity.
The study used variables obtained from secondary data, adopting univariate and multivariate treatment, which allowed categorizing the observations in clusters and establish correlations.
The main limitation relates to non-availability of long time series for the variables and use of them on different times to compose relationship analysis. In this sense, we could not verify the existence of path dependence and the results can’t be considered predictive.