The Six Pillars of Knowledge Economics

The purpose of this paper is to extend our earlier work on the contributions to the mini-track on Knowledge Economics at the Hawaii International Conference on System Sciences (HICSS). In the present work, we analyze 16 contributions from 2012 to 2016 and based on our analysis, we propose the Six Pillars of Knowledge Economics framework. The proposed framework articulates that six elements are essential to generate knowledge outputs: Innovation Capability, Leadership, Human Capital, Information Technology Resources, Financial Resources, and Innovation Climate. Additional major findings are that organizations are the most common unit of analysis, while the individual level is hardly considered. Journals represent the major source of citations. Conference proceedings were less cited, though more current. We recommend major conferences to be indexed by services like Scopus and provide open access to peer-reviewed proceedings

Utilizing rapid prototyping 3D printer for fabricating flexographic PDMS printing plate

Recently printed electronic field is significantly growth. Printed electronic is to develop electrical devices by printing method. Conventional printing method that has been studied for this kind of printed electronic such as flexographic, micro contact printing, screen printing, gravure and ink jet. In flexographic and microcontact printing, a printing plate is used to transfer the designed and desired pattern to substrate through conformed contact. Therefore printing plate is play a big role in this area. Printing plate making by photopolymer which used in flexographic have limitation in achieving a micro-scale of pattern size. However, printing plate of microcontact printing have an advantages in producing micro, even nano-scale size by PDMS (Polydimethylsiloxane). Hence, rapid prototyping 3D printer was used for developing a PDMS micro-scale printing plate which will be used in reel to reel (R2R) flexographic due to high speed, low cost, mass production of this type of printing process. The flexibility of 3D printer in producing any shape of pattern easily, contributed the success of this study. A nickel plating and glass etching master pattern was used in this study too as master pattern mould since 3D printer has been reached the micro size limitation. The finest multiple solid line array with 1mm width and 2mm gap pattern of printing plate was successfully fabricated by 3D printer master mould due to size limitation of the FDM (Fused Deposition Modeling) 3D printer nozzle itself. However, the micro-scale multiple solid line array of 100micron and 25micron successfully made by nikel platting and glass etching master mould respectively. Those types of printing plate producing method is valueable since it is easy, fast and low cost, used for micro-flexographic in printed electronic field or biomedical application

Applying a Comprehensive Neo-Schumpeterian Approach to Europe and its Lisbon Agenda

The paper shows that Comprehensive Neo-Schumpeterian Economics (CNSE) is an adequate theoretical approach accompanying the enforcement of the aims of the Lisbon Agenda. The CNSE approach is based on the principle of innovation and the idea of future orientation penetrating all spheres of economics which can be summarized in three domains of economic life: industry, finance and public sector, the 3-pillars of CNSE. The CNSE approach is applied to an empirical study of 18 OECD countries using a three step procedure: In a first step country patterns of pillars are identified in a cluster analysis. This gives a fine grained picture of institutional and structural set-ups for the countries under study. In a second step within the pillar clusters a performance analysis is exercised in order to rank the countries. Because of the similarities of countries within a cluster this comparative analysis can be done whereas for countries belonging to different clusters this comparison would lead to wrong conclusions. In a final step as a crude representation of macro-economic performance the cluster composition is sorted by the average growth rates of the economies. This allows a first correlation of pillar composition and growth performance.Lisbon Agenda, Comprehensive Neo-Schumpeterian Economics, European Country Patterns, future-oriented indicator-based model

KBE frameworks and their applicability to a resource-based country: The case of Brunei Darussalam

Knowledge is generally considered to be one of the most important drivers of economic growth. The difference between a knowledge-based economy (KBE) and a resource-based one is that in the former, the main competition between individuals, firms, and countries is the ability to innovate. Other forms of competition, for example through pricing strategies and access to resources, become secondary. Generally, knowledge is information combined with technology that dramatically increases its impact when shared. Organizations such as the Organization for Economic Cooperation and Development (OECD), Asia Pacific Economic Cooperation Forum (APEC), Australian Bureau of Statistics (ABS) and the World Bank Institute (WBI) have developed different KBE frameworks to indicate the extent of countries' knowledge base and implicitly to guide policy. But these frameworks 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 this paper we propose a framework that clearly distinguishes input-output indicators of a knowledge-based economy under four important dimensions: knowledge acquisition, knowledge production, knowledge distribution and knowledge utilization, and attempt to adapt them in a practical policy oriented approach for an economy like Brunei Darussalam, which is attempting to transform from a resource-based to a knowledge-based economy

Ratings and rankings: Voodoo or Science?

Composite indicators aggregate a set of variables using weights which are understood to reflect the variables' importance in the index. In this paper we propose to measure the importance of a given variable within existing composite indicators via Karl Pearson's `correlation ratio'; we call this measure `main effect'. Because socio-economic variables are heteroskedastic and correlated, (relative) nominal weights are hardly ever found to match (relative) main effects; we propose to summarize their discrepancy with a divergence measure. We further discuss to what extent the mapping from nominal weights to main effects can be inverted. This analysis is applied to five composite indicators, including the Human Development Index and two popular league tables of university performance. It is found that in many cases the declared importance of single indicators and their main effect are very different, and that the data correlation structure often prevents developers from obtaining the stated importance, even when modifying the nominal weights in the set of nonnegative numbers with unit sum.Comment: 28 pages, 7 figure

Maintenance Strategies to Reduce Downtime Due to Machine Positional Errors

Manufacturing strives to reduce waste and increase Overall Equipment Effectiveness (OEE). When managing machine tool maintenance a manufacturer must apply an appropriate decision technique in order to reveal hidden costs associated with production losses, reduce equipment downtime competently and similarly identify the machines’ performance. Total productive maintenance (TPM) is a maintenance program that involves concepts for maintaining plant and equipment effectively. OEE is a powerful metric of manufacturing performance incorporating measures of the utilisation, yield and efficiency of a given process, machine or manufacturing line. It supports TPM initiatives by accurately tracking progress towards achieving “perfect production.” This paper presents a review of maintenance management methodologies and their application to positional error calibration decision-making. The purpose of this review is to evaluate the contribution of maintenance strategies, in particular TPM, towards improving manufacturing performance, and how they could be applied to reduce downtime due to inaccuracy of the machine. This is to find a balance between predictive calibration, on-machine checking and lost production due to inaccuracy. This work redefines the role of maintenance management techniques and develops a framework to support the process of implementing a predictive calibration program as a prime method to supporting the change of philosophy for machine tool calibration decision making. Keywords—maintenance strategies, down time, OEE, TPM, decision making, predictive calibration

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

European Regional Space Classification Regarding Smart Growth Level

The paper presented classification results including European regional space positional statistics regarding advancement and smart growth level in NUTS 2 regions. Regional smart growth covers three pillars: innovation, creativity (Knowledge Based Economy) and smart specialization illustrated by characteristics available in Eurostat data resources. These qualities constituted the basis for constructing aggregate measures for specific pillars and also for the purposes of regional classification. The results of obtained classes were assessed in an overall European space, in groups of regions distinguished in line with integration processes chronology and also in capital regions and these including the country capital, as well as in the system of Polish regions.Strategia Europa 2020, jako sukcesor Strategii Lizbońskiej, jest wizją społecznej gospodarki rynkowej dla Europy XXI wieku, obejmującą trzy powiązane priorytety: 1/ rozwój inteligentny: rozwój gospodarki opartej na wiedzy i innowacji; 2/ rozwój zrównoważony: wspieranie gospodarki efektywniej korzystającej z zasobów, bardziej przyjaznej środowisku i bardziej konkurencyjnej; 3/ rozwój sprzyjający włączeniu społecznemu: wspieranie gospodarki o wysokim poziomie zatrudnienia, zapewniającej spójność społeczną i terytorialną. W pracy przedstawiono wyniki klasyfikacji ze statystykami pozycyjnymi europejskiej przestrzeni regionalnej ze względu na stopień zaawansowania i poziom inteligentnego rozwoju w regionach szczebla NUTS 2. Rozwój inteligentny regionów uwzględnia trzy filary: innowacyjność, kreatywność (Gospodarka Oparta na Wiedzy) i inteligentną specjalizację ilustrowane charakterystykami znajdującymi się w zasobach informacyjnych Eurostatu. Cechy te stanowiły podstawę do konstrukcji miar agregatowych dla określonych filarów, a także do klasyfikacji regionów. Wyniki uzyskanych podziałów oceniono w całej europejskiej przestrzeni regionalnej, w grupach regionów wydzielonych zgodnie z chronologią procesów integracji, a także w regionach stołecznych i zawierających stolicę oraz w układzie regionów polskich

New resonance approach to competitiveness interventions in lagging regions: the case of Ukraine before the armed conflict

Regional competitiveness is considered to be an alternative basis for the determination of regional interventions. However, the composite competitiveness indicator is quite sensitive to the weights of sub-indicators, no matter what methodology is being used. To avoid this uncertainty in the determination of regional interventions, we proposed a new non-compensatory resonance approach that is focused on the hierarchical coincidence between weaknesses of NUTS 1 and NUTS 2 regions measuring the extensive and intensive components of competitiveness. Such a coincidence, being perceived as a resonance effect, is supposed to increase the effectiveness of interventions triggering synergetic effects and stirring up local regional potentials. The components of competitiveness are obtained through synthesising DEA methodology and Hellwig's index, correspondingly focusing on the measurement of technical efficiency and resource level. In analysing Ukrainian regions, no correlation between resonance interventions and the composite competitiveness indicator or GDP per capita was found, pointing toward a completely different direction in resonance approach. In western Ukraine, the congestion of six NUTS 2 regions was defined as a homogeneous area of analogous resonance interventions focused on improving business efficiency.Web of Science171562

Sustainability ranking of desalination plants using Mamdani Fuzzy Logic Inference Systems

As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability