The objective of this paper is to assess the relative efficiencies of ASEAN-5 countries in their development of knowledge-based economies (KBEs) during the period 2005-2010. The KBE concept was first used by the Organization for Economic Co-operation and Development (OECD) describing it as an economy which is directly based on the production, distribution and use of knowledge and information. Subsequently, the Asia Pacific Economic Cooperation forum (APEC) and the World Bank Institute (WBI), along with the OECD, extended the concept and developed frameworks to compare the status of the knowledge base of different economies. These frameworks identify four core dimensions: knowledge acquisition, production, distribution and utilization, and use many structural and qualitative variables in their analysis. But none of the current methodologies explicitly divide the KBE indicators under these four core dimensions or measure the efficiency with which knowledge inputs are transformed to knowledge outputs. This paper attempts to fill the gap in existing literature by building a policy-focused KBE framework, selecting appropriate indicators from the existing OECD and WBI KBE frameworks and assessing the relative input-output efficiencies of the ASEAN-5 countries in the development of their KBEs over time. For this purpose we use the linear programming application of Data Envelopment (DEA) Window Analysis. The DEA/Window scores allow the comparison of the relative performance of each country regarding each dimension of KBE. The importance of this study, however, is not so much the immediate result which highlights comparative efficiencies, but rather that DEA/Window is a workable model which can take the study of KBE further in investigating the contributory factors of KBE.

The purpose of this paper is to build a policy focused knowledge-based economy (KBE) framework based on the OECD KBE definition in order to identify the KBE factors in the Association of South East Asian Nations (ASEAN) region. The paper utilises the Beta coefficient technique which allows us to rank the most important KBE input factors to KBE output factors. After identifying KBE input-output factors, following the Australian Bureau of Statistics KBE framework assumptions, standardized beta coefficients are used to assess how many standard deviations a dependent variable will change, per standard deviation increase in the predictor variable. Standardization of the coefficient is usually done to answer the question of which of the independent variables have greater effects on the dependent variable in a multiple regression analysis, when the variables are measured in different units. Data are mostly collected from secondary sources such as the World Bank's World Development Indicators and the International Institute for Management Development's World Competitive Yearbook. The results show Singapore is the best performer in knowledge acquisition, production and distribution and the Philippines is the best performer in knowledge utilization. Indonesia, on the other hand, shows weak performance in almost all the KBE dimensions. The lessons from the success of Singapore and the Philippines for weak performance countries in KBE are to improve the efficiency of FDI inflows, to optimise the use of research and development expenditure, to increase the secondary school enrolment ratio and finally to increase the interaction between academia and industry, which facilitates the creation and commercial use of knowledge. This paper provides empirical evidence to rank the important KBE input factors that gives governments some insight on where to focus investment in order to become a successful KBE.

Purpose The purpose this study is to investigate national innovation systems (NIS) using Porter’s Diamond model (PDM) by examining the five founding member nations of the Association of South East Asian Nations (ASEAN) namely Indonesia, Malaysia, Philippines, Singapore and Thailand, for the period 2010-2014 (WCY 2015, WDI 2015). Design/methodology/approach PDM of competitiveness helps us understanding a nation’s competitive position in world trade. In exploring the empirical relationship between NISs and PDM, a non-parametric approach has been applied using the Malmquist Productivity Index (MPI). This study focused on representing the PDM in a simplified manner and endeavored to understand NIS more rigorously through PDM. The study has used several innovation input-output variables to investigate the efficiency and productivity of the countries concerned. The accuracy of the study has been enhanced by the use of MPI. Findings PDM is found efficacious in the practice and strengthening of NIS in the context of these countries’ competitiveness. This study found unchanged Total Factor Productivity (TFP) for Philippines, Singapore and Thailand; that is technological progress is yet to be obtained. Indonesia lags both in technical and technological progress. On the other hand, Malaysia is found to be over-using the existing input-output factors of NIS. Originality/value Many authors have attempted to measure competitiveness and NIS separately in the context of ASEAN or other South-East Asian countries. However, as yet, no empirical investigation has been conducted to assess the competitiveness of a nation by applying NIS-based analysis according to PDM.

The purpose of this study is to evaluate the performance and change in the technical as well as technological efficiency in the total factor productivity of the 34 food processing industries in Malaysia, and to investigate the changes in their efficiency from 2009 to 2010 by applying two recent methods of data analysis, namely order-m and Malmquist productivity index. The results show that almost all industries have experienced an efficient technological contribution in their respective production functions, but there are wide dissimilarities in the technical efficiency of the organic composition of each industry. Also, there are variations in the change in efficiency scores from 2009 to 2010.

Energy prices in Brunei are highly subsidised and have not changed for over twenty years. Electricity is priced at approximately B$0.06 (US$0.044) per kWh and petrol (gasoline) varies from B$0.36 (US$0.26) per litre for regular to a maximum of B$0.53 (US$0.38) per litre for premium unleaded. With oil and natural gas prices at relatively high historical levels and the government attempting to reduce its influence on the economy and promote privatisation, the increasing size of the subsidies has come to the attention of policy makers. This paper considers likely market prices for energy in Brunei given current institutions and infrastructure and discusses issues associated with removal of the subsidies in this unique economy.