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In the last decade, we have witnessed companies investing in financially and laboriously expensive enterprise information technologies (EITs) that unify the internal and external supply chains for the purpose of gaining strategic advantages. As performance metrics data resulting from such investments are beginning to emerge, both practitioners and researchers are taking a critical look at whether these systems indeed produced the benefits proclaimed by their proponents at the pre‐implementation stages. In this context, the well‐managed appraisal, design, operation, and auditing of EITs within the ambit of organizational goals become significant. Provides a conceptual discussion on: a framework outlining a recommended decision process; a categorization of factors that must be considered during the process; and a summary of techniques and tools for the evaluation of those factors.

This paper aims to present an impact analysis in the educational dimension of the European Institute of Innovation and Technology (EIT) and specifically on its “knowledge and innovation community” (KIC), focused on the information and communications technology sector named “EIT Digital” in the university field.

After reviewing the current situation on education in ICT-related engineering and the need to address new professional profiles and/or complement the current ones to increase the value of the new professionals in a globalised society, the principles behind the EIT model are analysed, taking the experience accumulated in EIT Digital as a basis for discussion at master level.

The conceptual framework on “what” and “how” of the EIT described from the educational perspective constituted sound bases for ensuring the value of the EIT KICs as drivers for institutional innovation and structural reform. As the practical experience of Universidad Politécnica de Madrid (UPM) shows, the policy experimentation space provided by EIT Digital has acted as an internal transformation driver for European universities. It has played a key role to accelerate structural reforms once partner universities assumed the need of modifying or reinterpreting “any internal regulation to participate better in the EIT”.

This analysis is used as a basis for the design of an institutional agenda of education transformation in the rest of the UPM where the innovation and entrepreneurship vision is inserted into the technical education to give future professionals the tools and capacities to serve as catalyser agents of the innovation system.

The purpose of this paper is to highlight the potential of innovation platforms to realise SDGs targets by focussing in sustainable innovation process related to infrastructure and industrialisation.

Analysis of different policy documents, reports as well as a series of interviews and participatory processes run in 2016–2017 of the EIT Regional Innovation Scheme programme to prototype a knowledge triangle integration (KTI) index.

Preliminary findings show that EIT Climate-KIC operates as an innovation platform that mobilise resources to increases capabilities for climate innovation.

The paper contributes to a better understanding of the complexity of the efforts needed to tackle climate innovation regarding resource mobilisation for KTI processes by focussing on how platforms work in a bottom-up way.

Mechanisms and processes that consolidate local knowledge and strengthen relational assets with regards to climate innovation are important for the realisation of some of the 169 targets of the 2030 Agenda.

During the Paris Convention, Korean Government made commitment to curb carbon emission by 37 percent by the year of 2030. Since then there has been constant debate, both in media and academia, as to whether attempts to reduce carbon emission would spell the concomitant economic slowdown. The purpose of this paper is to build a Computable General Equilibrium (CGE) model to see the effects of emission decrease on Korea economy.

To answer the above question, we build a comprehensive framework to gauge the economic impact of Paris Convention through the lens of Computable General Equilibrium (CGE) model using Armington and Melitz model.

Contrary to conventional wisdom, Korea’s economic performance in terms of welfare remains robust when the carbon emission is reduced. Broadly speaking, Korea’s welfare does not contract significantly in part due to expansion at the export market. For instance, the energy intensive industry (EIT) is affected most directly from the Paris Convention commitment and yet it experiences growth in export. On the contrary, the authors find that the general economic impact on Korea’s output is negative. The additional experiment using Melitz model shows that as the carbon reduction is enforced, both the number and the average productivity of the exporting firms increase in the EIT sector, which the authors refer in the paper as the “Melitz Effect.”

This paper shows that what can be occurred in Korean industries by emission decrease commitment.

One byproduct from restricting carbon emission is the surge in the electricity price. This is due to the fact that industries have to shift away from traditional fuels such as oil to electricity for energy. Therefore the authors propose that industrial policies aimed at balancing electricity price should accompany the plan to reduce carbon emission.

For Korean economy, the effects of emission reduction is researched using Armington and Melitz model at the same time. Especially, this is the first research case using the Melitz model in this Korean topic.

The aim of this paper is to introduce and to evaluate the performance of a multiple frequency complex impedance reconstruction for fabric-based EIT pressure sensor. Pressure mapping is an important and challenging area of modern sensing technology. It has many applications in areas such as artificial skins in Robotics and pressure monitoring on soft tissue in biomechanics. Fabric-based sensors are being developed in conjunction with electrical impedance tomography (EIT) for pressure mapping imaging. This is potentially a very cost-effective pressure mapping imaging solution in particular for imaging large areas. Fabric-based EIT pressure sensors aim to provide a pressure mapping image using current carrying and voltage sensing electrodes attached on the boundary of the fabric patch.

Recently, promising results are being achieved in conductivity imaging for these sensors. However, the fabric structure presents capacitive behaviour that could also be exploited for pressure mapping imaging. Complex impedance reconstructions with multiple frequencies are implemented to observe both conductivity and permittivity changes due to the pressure applied to the fabric sensor.

Experimental studies on detecting changes of complex impedance on fabric-based sensor are performed. First, electrical impedance spectroscopy on a fabric-based sensor is performed. Secondly, the complex impedance tomography is carried out on fabric and compared with traditional EIT tank phantoms. Quantitative image quality measures are used to evaluate the performance of a fabric-based sensor at various frequencies and against the tank phantom.

The paper demonstrates for the first time the useful information on pressure mapping imaging from the permittivity component of fabric EIT. Multiple frequency EIT reconstruction reveals spectral behaviour of the fabric-based EIT, which opens up new opportunities in exploration of these sensors.

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

Electrical impedance measurement and imaging are techniques that are widely used in a range of applications. Electro‐conductive knitted structure is a major new development in wearable computing. The purpose of this paper is to carry out a preliminary investigation of applying electrical impedance analysis to predict the behavior of electro‐conductive knitted structure. This can potentially pave the way for a low‐cost solution for pressure mapping imaging.

Electrical impedance tomography (EIT) has been used as a mapping technique for deformation imaging in conductive knitted fabric. EIT is an imaging system used to generate a map of electrical conductivity. Pressure and deformation mapping scanner is being developed based on electrical conductivity imaging of the conductive area generated in a fabric. The results are presented using these new sensors with various deformations.

Experimental results show the feasibility of qualitative deformation imaging. In particular, it is promising that multiple deformations can be mapped using the proposed technique. The paper also demonstrates preliminary results regarding quantitative pressure and deformation mapping using EIT technique.

The results presented in the paper are laboratory‐based experiments for proof of principle and will be evaluated in specific application areas in future.

The paper shows, for the first time, detection of multiple pressure points as well as quantifying the pressure map using the new imaging sensor. The sensor proposed here can be used for robotic touch sensing application, as well as some biomechanical observations.

In the context of electrical impedance tomography (EIT), this paper aims to evaluate limitations of estimating conductivity or resistivity, as well as the improvements achieved with the use of an alternate description of the solution space, the logarithmic conductivity.

A quantitative analysis is performed, solving the inverse EIT problem by using the Gauss–Newton and non-linear conjugate gradient methods for a numerical phantom of 15 elements. A property of symmetry is studied for the direct EIT problem for a phantom of 385,601 elements.

Solving the inverse EIT problem in logarithmic conductivity is more robust to the initial guess, as solutions are kept within physical bounds (conductivity positiveness). Also, convergence is faster and less dependent on the final values of the estimates.

Logarithmic conductivity provides an advantageous description of the solution space for the EIT inverse problem. Similar estimation problems might be subject to analogous conclusions.

This study provides a novel analysis, quantitatively comparing the effect of different variables to solve the inverse EIT problem.

This paper aims to examine the current thoughts on knowledge management (KM) and to develop a metaphor to combine these thoughts in a new way that effectively conveys the different types of knowledge and ways of managing it.

The literature on the transition of data to knowledge is reviewed. A popular paradigm in KM states that data are integrated to create information and information is integrated to create knowledge. This paradigm is represented as a pyramid‐shaped hierarchy with knowledge at the top, information in the middle, and data on the bottom. Why this paradigm is a simplistic and limited view of knowledge and KM is discussed.

The “explicit islands in a tacit sea (EITS)” metaphor is explained and discussed in the context of knowledge and knowledge management (KM).

The EITS metaphor more accurately and completely describes knowledge in the context of KM. The practical implications of this metaphor are its flexibility and transparency of the transitional actions that affect the evolution of data to knowledge.

The EITS metaphor is an evolution of the prevailing frameworks and removes the apparent limitations in earlier frameworks. The paper provides a paradigm shift in the discussion of KM.

This study aims to discuss science governance in Europe and the network of associated nonprofit institutions. The authors posit that this network, which comprises both (partial) learning organizations and non-learning organizations, has been observed to postpone taking up “responsibility” as an issue in science governance and funding decisions.

This paper discusses the challenge of learning and policy implementation within the European science governance system. By exploring how learning on responsible innovation (RI) in this governance system can be provoked, it addresses the question how Senge’s insights in organizational learning can clarify discourses on and practices of RI and responsibility in research. This study explores the potential of a new organizational form, that of Social Labs, to support learning on Responsible Research and Innovation (RRI) in standing governance organizations.

This study concludes that Social Labs are a suitable format for enacting the five disciplines as identified by Senge, and a Social Lab may turn into a learning organization, be it a temporary one. Responsibility in research and innovation is conducive for learning in the setting of a Social Lab, and Social Labs act as intermediary organizations, which not merely pass on information among actors but also actively give substantive shape to what they convey from a practice-informed, normative orientation.

This empirical work on RRI-oriented Social Labs therefore suggests that Social Lab–oriented temporary, intermediary learning organizations present a promising form for implementing complex normative policies in a networked, nonhierarchical governance setting.

Based on this research funding and governance organizations in research, policy-makers in other domains may take up and create such intermediary organizations to aid learning in (science) governance.

This research suggests that RRI-oriented Social Labs present a promising form for implementing complex normative policies, thus integrate learning on and by responsible practices in various governance settings.

European science governance is characterized by a network of partial Learning Organization (LOs) and Non-Learning Organization (nLOs) who postpone decision-making on topics around “responsibility” and “solving societal challenges” or delegate authority to reviewers and individual actors, filtering possibilities for collaborative transformation toward RRI. social lab (SLs) are spaces that can address social problems or social challenges in an open, action-oriented and creative manner. As such, they may function as temporary, intermediary LOs bringing together diverse actors from a specific context to work on and learn about issues of science and society where standing organizations avoid doing so. Taken together, SLs may offer temporary organizational structures and spaces to move beyond top-down exercise of power or lack of real change to more open, deliberative and creative forms of sociopolitical coordination between multiple actors cutting across realms of state, practitioners of research and innovation and civil society. By taking the role of temporary LOs, they may support existing research and innovation organizations and research governance to become more flexible and adaptive.