knowledge-based economy (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.

regu- lation and an inadequate legal system), the inefficiency of the market of goods, business sophistication, negative credit rating and low national savings. Serbia’s goal is to obtain a better business environment and increase a demand for domestic products for achieving economic growth. Based on the Europe 2020 WEF Competitiveness Index (The Europe 2020 Competitiveness Report, 2014) Serbia scored 3.46 (scale is from 1 to 7). In order to achieve a better rank and to increase competitiveness Serbia needs to undergo reforms first by establishing institutional capacities in the country, and then by adopting certain policies and devel- opment factors. This is the way to increase productivity and employment that will bring about higher com- petitiveness. Government efforts should be focused on the improvement of institutional capacities, business environment, digital agenda, and education and training. Also, Serbia should address problems, i.e., con- strains such as inefficient government bureaucracy, access to financing, corruption, policy instability and government instability (WEF Europe 2020 Competitiveness Report, 2014). Furthermore, the KBE is achieved at a modest growth rate. The KEI and KI show that Serbia is ranked 49th out of 146 countries. Serbia has highest results in ICT that are considered to be one of the factors that can influence economic growth. A low employment rate of 45% (2013), low allocations in R&D around 1% of GDP (2013), low productivity, in- creased poverty, high public debt (around 70% of GDP, 2014), and fiscal consolidation slow down the achievement of economic development. Serbia needs to continue carrying out the reforms in order to achieve sustainable development and establish knowledge-based economy. In comparison with the EU(28) that itself did not achieve its goals, Serbia is considerably below the EU(28) average and below, or at the same level as the neighbouring countries, Romania and Bulgaria, depending on the indicator.

Afzal, M. N. I., & Lawrey, R. (2012c). A measurement framework for Knowledge- Based Economy (KBE) efficiency in ASEAN: A Data Envelopment (DEA) window approach. International Journal of Business and Management, 7(18), 58-68. [ERA, ABDC indexed]

The scope of knowledge economy policy is vast. It is already functioning in the most developed countries, but the analytical tools and indicators for mapping and meas- uring it’s performance are missing. Ideally, a research- policy agenda should encompass new economic institu- tions and cultures, new technology paradigms and the ICT infrastructure, national and regional innovation sys- tems – and human capital, or the knowledge, skills and other attributes of the workforce (OECD, 1996, 2002). Different KBE assessment methodologies (many of them were not created with intention to assess penetration level of knowledge-based economy elements) have been pre- pared starting from 1962 (F. Maclup, Hepworth, Small, Garfield, 1985; Leontief, 1993; Spencer, 2003; Lande- feld, Fraumeni, 2000; Trewin, 2002; Gera and ec. (1998), Houghton, Sheen, 2000; Dahlman, 2003; Atkinson, 2002 and etc.). Different attempts exist in order to assess the results of knowledge creation and application to eco- nomic, social, political or even cultural spheres of coun- tries. Such possible models are constructed by experts of various international organizations like OECD 2 , World

learning process between different departments within a company, including the department of R&D and University. He also added that bringing innovation from a university classroom to a commercial showroom depends on education, knowledge transfer, R&D linkage, investment in venture capital and ICT communications. Additionally, there are other arguments, such as that put forth by Asheim & Isaksen (2002) who considered the RIS to represent regional clusters which are surrounded by supporting knowledge organisations including universities, research institutes etc. Moreover, Doloreux (2002) argued that the RIS can be conducive to the generation, using the agglomeration concepts and diffusing the knowledge and technology through the interacting interests among formal institutions and other organisations. In short we can say that the theory and concept of RIS arose in the late 1990s based on theory of agglomeration economies, cluster theory and national innovation system. In a knowledge-based economy (KBE), speed and first mover advantage are central aspects of industrial competition. Therefore, information, technology and network economy become the necessary conditions for regional industrial development. Technology-driven competition is technically difficult whilst links with Higher Education Institute (HEIs) enable local industry to grow early and enter the knowledge-based economies. This fulfills the objective of local and national government to develop local high technology clusters. This in turn makes universities the most productive source of skilled human resources and boosts local science park development by creating regional employment. Very few countries in the world successfully implement this theory and become the frontier of a technology driven development phenomenon. Among them, South Korea, Singapore, Taiwan, Hong Kong, Japan, U.S.A, Germany, U.K, and France are the most notable countries. At this point, the question is, how can university or research institute driven science parks work in a regional innovation system for a particular region or country? Let us consider an example. A local firm is innovating a semiconductor technology and a local university’s engineering department partners with this local firm. The partnership is considered an innovative programme, usually administered by the university.

These frameworks have one common trait in that they all give a basic description of the environment a KBE should possess and claim that a successful KBE should have four core dimensions, namely, knowledge acquisition, knowledge production, knowledge distribution and knowledge utilization. These KBE frameworks were developed to indicate the extent of countries’ knowledge base and implicitly to guide policy. But they have little in theoretical underpinnings and applying them universally across all countries in different regions, at different stages of development and with different institutional, social and economic characteristics may be misleading and result in inappropriate policy responses. In an earlier paper we proposed a framework that clearly distinguishes input-output indicators of a knowledge-based economy under the four core dimensions and attempted to adapt them in a practical policy oriented way for an economy that was attempting to transform from a resource-based to a knowledge-based economy (Afzal and Lawrey 2012a, see also Lee, 2001; Tan, Hooy, Manzoni & Islam 2008 and Karahan, 2011). In a subsequent paper we used the Beta coefficient technique to rank the most important KBE input factors to KBE output factors and examine why the resultant ranking varies across the ASEAN-5 countries namely Indonesia, Malaysia, Singapore, the Philippines and Thailand (Afzal and Lawrey 2012b).

In knowledge intensive economies, effective dissemination and the use of knowledge is of great importance and one of the key determinants for success of national economies that are becoming a hierarchy of strategic networks where the accelerated degree of change creates the need for establishment of network societies [7]. The related ability to join these knowledge and learning networks affects the socio-economic position of indi- vidual members, organizations, and national economies [2]. In fact, the network aspect of the knowledge inten- sive economies came forward with the changes in a traditional linear model of innovation that observed innova- tion as a linear process of discovery stages where scientific research was the initial phase and the driving force behind innovation [8]. In the knowledge-based economy, innovation is a result of interactions between different disciplines and participants, such as organizations, research institutes, academia and science, consumers, product development, manufacturing, engineering, etc. It can assume various forms from basic advancements to existing products, to employing existing technologies to new markets and introducing new technologies to existing mar- kets. Furthermore, productivity and growth are mostly affected by the degree of technological progress and knowledge accumulation capacity [3]. In addition, these knowledge intensive segments of the economy have a tendency to generate increased output and employment growth. In that regards, knowledge and learning net- works act as core mechanisms for efficient knowledge and information dissemination that are preconditioned for long-term economic growth.

Access to funding for startup companies is another important aspect of knowledge-based economies. Technological companies are an important part of knowledge-based economies, and new technology companies require non-financial support and as well as funding. An example is Silicone Valley in the United States which receives both domestic and foreign funding from countries such as Saudi Arabia. As a result, through this funding, many large technology companies and discoveries have emerged. Economic stability is another feature of a knowledge- based economy, and this is due to economic diversity as there are many different industries that contribute to the nations GDP (Hadad, 2017). In contrast, resource-based economies depend on a single or a few commodities that leave the nation’s economy exposed internal and external threats such as the rise in commodity prices. Another reason why knowledge-based economy is usually stable is because firms have access to different government support systems that allow them to grow and expand. An attribute of knowledge-based economy is the increase in the number of high paying high skill jobs, especially in the IT industry. A common trend that has been noticed around the world is the decrease in the number of low skill low wage jobs as more companies are using technology to replace these types of workers. However, the need for highly skilled workers in both the private and public sectors has greatly increased as knowledge has been directly linked with the increase in productivity in both sectors.

Universities and research institutions act as providers of knowledge (ideas, technologies), which is essential to building new economies. Science, as well as lower-level education, contributes to creating a climate conducive to technological progress and innovation. A necessary condition for building a knowledge-based economy is a close link between the research sector and enterprises, especially SME’s. With such an alliance, it is possible to effectively use the knowledge provided by scientific and research infrastructure. A knowledge-based economy behaves differently from an old market economy. In such an economy, information and knowledge are very important. Active use of knowledge is based on its continual development. Organizations have to be prepared for constant innovation and continuous systemization of changes in operation techniques. They should also develop scientific research centers. Ensuring the continuity of innovation processes requires controlling the development of knowledge and its applications at different levels. This is why large organizational systems play a key role in the new economy. Organization of the new economy combines features of free and controlled markets. In the current market economy, the State is involved in the control of the economy. Their task is to create macroeconomic conditions conducive to the development and diffusion of knowledge and maintaining the continuity of the innovation process. However, the dominance of large systems does not mean the disappearance of small businesses. On the contrary, the role of small and medium- sized enterprises is very large. This role will continue to increase with the further development of the service sector.

Several factors can impede a country’s transition to a knowledge economy, as demonstrated by the struggle of some countries in the Arab region (i.e. Gulf Coast). From a political perspective, countries with a lack of freedom, good governance, and political commitment will not be able to transfer to a KBE (Osman, 2014). Furthermore, countries with unstable political climates often had leaders who did not prioritize the development of knowledge economies, which resulted in less progress (Osman, 2014). Additionally, the study found that rent-seeking economies such as those which dominated the oil-rich Arab region, struggled to transform into knowledge economies despite significant wealth and economic growth. Though profitable in the short run, economies which rely heavily on one non-renewable resource may fail to develop knowledge economies unless guided by the public sector (Osman, 2014). This problem is reflected in the belief by traditionalists that knowledge is not a tangible product of an economy and only the physical goods it produces matter. It would be in particular quite difficult for the petroleum-products-based economies of the Gulf States to transition to KBEs, especially since they have become rich and powerful due to their oil reserves. However, as those reserves are depleted, the transition to KBEs will become a necessity, as when the oil is gone, the Gulf States will be almost completely without natural resources (Osman, 2014). The United Arab Emirates recognised this some years ago and in 2010 set out its strategic vision to transform its economy to a KBE over the next 11 years. The UAE Vision 2021 states that “Innovation, research, science and

The respondents also stressed that much of their content development was based on trial and error, gauging what worked and what did not work. Writing, filming and editing skills were continuously refined on the job. They depended on the innovative trait of interactive learning by doing, of learning how to create digital media content by creating it. The idea of learning is also associated with sharing information, which is highly lacking in the industry:

networking – network creation, which integrate different kind of companies, oriented around the value chain vector generates rapid economic growth: the speed of technical, human and economic flows amplifies a lot, generating real explosive effects; (6) products value rises exponentially with the value of the market share – the effect of networking leads to a situation in which as bigger as the volume of one kind of product becomes, so its market share is, and its value rises; (7) rising importance of middle levels in the economy – the amplification of volume and complexity of information and knowledge determines the rapid growth of info-intermediaries and of there impact on functioning and performing of the economy; (8) buyers get great power, and sellers get new opportunities – the possibility for the buyers to rapidly obtain the best information they can get just through one “click” confers them a higher possibility to choose and rapidly procure the product / service they need; in the same time, there are some new opportunities for producers and sellers, because, by holding relevant information about markets they know that to produce, at what prices to sell and which are the best market shares; (9) the transaction with goods and services become more and more personalized – rapid and cheap access to information about the specifics of demand reflects into manufacturing and selling of personalized product / services, which determines a substantial diminishing of stocks and of waiting times; (10) availability of any product everywhere – you can order instantly by e-commerce on- line the product you wish and you can get it very fast; so, the gap between the wish to buy and the possibility to do it tends to diminishes to zero in some cases.

Knowledge sharing enables organizations to either create new knowledge by differently combining existing knowledge or to become better at exploiting existing knowledge (Christensen, 2007). In this regards, organizations can create new values to improve development and growth through knowledge sharing and interactions among employees across departments where these values will have a positive effect on producing new products or improving services (Chen, 2009). Coakes (2006) notes that knowledge sharing can help organizations to create, capture, organize, access and use the intellectual asset of the organization in order to provide the user of knowledge with the ability to acquire, document, transfer, and apply the said knowledge. Other significant contributing factors of having employees sharing their knowledge with each other include knowledge sharing allows employees to solve increasingly complex and ambiguous problems and improves decision making at an individual and organizational level. Commitment to sharing stressed many straight forward functional reasons. Among them are to either support the team, to avoid re-inventing the wheel, and to enable others with different expertise to work on a problem, learn from others‟ experiences and improve their own performance (Connelly et al, 2013).

six subsectors in the production sector of the economy: i) education, ii) research and development (R&D), iii) artistic creation, iv) information technology, v) information services and vi) communication media. In general, Machlup highlighted the significance of knowledge production for economic growth through competition, sharing and diffusion in modern economics and has stimulated subsequent research into the knowledge economy framework. For instance in 1974 Hayek in his Nobel Prize lecture (The Pretence of Knowledge) said “people learn by doing and acquire new knowledge through the competitive market process. Therefore, the competitive market process, from the Austrian perspective, has led to beneficial interaction among market participants. This process, over time, reduces ignorance to manageable levels for economic agents, promotes the discovery of knowledge that was not previously available and could contribute to economic growth” (in Lin, 2006, p.326). The emphasis on free markets is very important for the Austrian School and was in contrast to the Keynesian approach that was dominant at the time of Schumpeter’s work. The basic premise of Hayek and others of the Austrian School is that the economy is too complex to model but can be explained through systematic verbal argument, and the free market economy will automatically move to a more knowledge-based economy. Research continues on the knowledge economy in an attempt to measure knowledge in KBEs by the new growth theory economists led by Romer (1986), Lucas (1988) and others (Lin, 2006). The core argument of KBE researchers is that investing in knowledge can increase the productive capacity of the other factors of production as well as transform them into new products and processes. The other key feature of the theory is that knowledge leads to increasing returns to scale in production. Conventional production functions assume diminishing returns to scale, where marginal costs increase. However in knowledge-intensive products, the fixed costs of production are large, but the variable costs of production are small (Lee, 2001). Since then, KBE research has developed to today’s modern KBE frameworks as detailed later in the paper (Cader, 2008). KBE research transcends disciplinary boundaries and researches from a sociological and cultural perspective also make valuable contributions to the study of transition. For example, Evers (2003) studied the social and cultural preconditions as well as consequences in reaching the stage of a knowledge society for Malaysia and Indonesia.

Understanding the role of knowledge in the knowledge economy – as production factor and mixed public good – or in the knowledge–based society – as fundamental tool and mechanism for thei[r]

Based on the presented results of analysis it can be summarized that there is a relationship between knowledge support and knowledge development in organizations; organizations does support knowledge transfer (H0) but there are some promising areas of knowledge development in the organizations. The strongest and most signifi cant statistical areas which affect knowledge development in organizations are based on cooperation and communication, hence the organizational culture, as mentioned by Kumaraswamy and Chitale (2012), Stahl et al. (2012) and Senge (2006). Another important area supporting knowledge transfer in an organization is relationships. This area has also been mentioned in research undertaken by Bozionelos (2006), Hezlett and Gibson (2007) and Singh et al. (2009). Based on other similar research (Carter & Donohue, 2012; Shen & Hall, 2009; van Dam, 2007), the authors have also suggested the necessity of working with coaches and mentors in order to work with knowledge and ensure its transfer. This area has not been utilized in most of the studied organizations. It is also necessary to educate and develop employees with regard to their work, social values and behavior – each employee is an individual with a different perception and personality (Loke et al., 2012).

7 Human Capital Theory and Human Resource Development 60 Strategies for the Future 65 The 'knowledge-based economy' KBE 65 The Asian model 70 The neo-liberal model 75 80 Conclusion CHAPT[r]

The relevance of knowledge-based organization concept in our country ensues from its involvement in the progress towards informational society – society of knowledge – which is a prerequisite for long-lasting growth. Over the last years, education in knowledge-based economy has played an increasingly important role since more and more organizations are concerned with knowledge and technology transfer in the economy by means of scientific, technical sites and parks.

Knowledge Based Engineering system is a usage of proper computer software for obtaining and recycling knowledge on a product and process in a most integrated way. Therefore, it is especially beneficial in the event where the design is constantly develop. As stated by (Skarka 2007), creation of a good project depends largely on creativity of the designer himself. In other words, in order to have a good project, it is advised to devote, in optimal solution, much more that 20% of designing time for creative actions.

Moreover, globalization is a fundamentally microeconomic phenomenon, driven by the strategies and behaviour of firms. In a global strategy the comparative advantages of each nation, state or location are no longer considered separately. Comparative advantages are determined by a firm’s objectives – e.g. low production costs, new markets for standardized or differentiated products, access to new technologies or know-how. Hence, comparative advantages, advantages of location, will vary according to the firm’s global strategy. Nations, states and locations need to attend to the development of a coherent set of advantages, and find a niche in the global economy which attracts the type of economic activity they want to foster. Attending to the generic business environment is necessary, but no longer sufficient.