摘要：The World Development Report of 1999 has drawn attention to the fact that knowledge is not evenly distributed within countries, regions or urban areas. This has been described as the existence of a “knowledge gap” or, in relation to the ICT backbone of a knowledge system, as the “digital divide”. It is then proposed to close these gaps by appropriate development policies. So far most studies have tried to show the narrowing or widening of knowledge gaps by using indicators, as provided by the KAM (knowledge assessment methodology) data base of the World Bank Institute, like number of researchers per million population, investment in R&D (research and development) as percentage of GDP and other indicators. In most cases these data have measured knowledge gaps between countries or regions, without paying closer attention to the geographical distribution of knowledge assets as well as the existence of knowledge gaps within countries, provinces or cities. We intend to close this particular “knowledge gap” by providing a methodology to show and measure the geographical distribution of knowledge related assets, people or organizations, which we have referred to as “epistemic landscapes”. This paper is thus designed to discuss the methodology of creating knowledge maps and analyzing epistemic landscapes. Data and maps from ongoing research in the Mekong Delta in Vietnam1 We define epistemic landscapes in a geographical sense, i.e. we refer to the spatial distribution of knowledge assets within a predefined region (Evers 2008). The concept is not yet standard social science terminology. We are using the term “epistemic” in line with “epistemic culture”, the culture of knowledge production, as coined by Karin Knorr-Cetina (Knorr-Cetina 1999). The term “epistemic” has been used in different contexts. One line of argument refers back to Bacon and 18th-century 'encyclopaedism' and defines an epistemic landscape as depicting a synthesis of knowledge (Wernick 2006). In Weisberg and Muldoon’s study a single epistemic landscape corresponds to the research topic that engages a group of scientists. Agent based modelling with NetLogo software is used to model the changing epistemic landscape according to research strategies of participating scientists (Weisberg and Muldoon 2007). Conceptually distance rather than Euclidean distance is shown in graphs, similar to those used to illustrate social networks. In our study we follow a different path and focus on the development strategies of governments, strategic groups, firms, research institutes and their success in shaping the epistemic landscape of a region. The allocation of human and financial resources creates knowledge assets which are geographically distributed and can be measured, mapped and made to depict the contours of an epistemic landscape. are used to illustrate various methodological issues and to show examples of maps and graphs. As discussed elsewhere (Evers 2008), knowledge landscapes are formed by knowledge clusters, knowledge hubs and the distribution of knowledge assets. Following the work of Porter on the competitive advantage of nations (Porter 2003; Porter 1990) there has been an upsurge of research and data collection on industrial clusters (Sölvell 2009). These studies usually assume that modern industrial clusters are centres of innovation and therefore desirable. Our concept of knowledge landscapes is less value laden and intends to show the spatial distribution of knowledge. Which type of knowledge landscape optimizes intellectual or industrial output remains a question to be decided by further empirical research.
