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The effective management of industry/university research linkages has always been a challenge — for both partners. Moreover, a greater understanding is required for the role that these partners can play in developing strong linkages between them, particularly through mechanisms such as liaison offices and technology parks. This paper will examine the role of such mechanisms for the case of Greece. Basing on interviews with individuals in technology transfer process between academia and industry, it will examine the role and function of Academic Liaison Offices and Technology Transfer Units. Moreover, the development of effective strategies which is a matter for serious concern will be proposed in order to bridge the gap between them. Finally, the addressed model, such as a combined bridge linking both partners is to promote the liaison between the two and to overcome the traditional university structures which have not been designed for technology transfer purposes but for research and education only.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The study shows that three organizational capabilities jointly influence an organization’s business model innovation and, subsequently, business performance.

The briefing saves busy executives, strategists, and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The purpose of this study is to investigate how an environmental management system (EMS) might affect the environmental product innovation propensity of a firm through its influence on two factors shaping the knowledge process: the human capital management practices of training and development and the organisational context.

To test the study’s hypotheses, an empirical analysis was carried out on 262 companies drawn from 16 developed European markets included in the S&P Europe 350 Dow Jones index over the years 2005-2015.The authors adopted regression analysis by using the ordinary least squares and the binary logit econometric models.

Consistently with the study’s predictions, results show that for organisational contexts characterised by the presence of family owners, the EMAS-certified EMS reveals as a significant moderating factor that positively influences their approach to the knowledge management tools for the improvement of the workforce cognitive capabilities, with a significant impact on the firm’s openness towards green product innovation. On the contrary, the ISO 14001-certified EMS tends not to stimulate such proactive behaviour, in both family and non-family firms.

The findings suggest that an EMS can stimulate the knowledge exploration in the environmental protection field. To this end, top managers should overcome the bureaucratic vision of an EMS and conceive it as a knowledge management tool able to support the learning evolution of the organisation through an effective commitment to human capital management policies of training and development.

Drawing from social identity and institutional theories, this is the first study – to the best of the authors’ knowledge – that theorises and tests why the adoption of an EMS might stimulate the knowledge advancement of the organisation in a different way, especially in peculiar organisational contexts of family firms where the identity overlap between the family and the firm tends to affect the knowledge management process.

The purpose of this paper is twofold: first, to validate the global competitiveness project (GCP) framework in the Brazilian context; second, to describe the competitiveness levels on a sample of Brazilian firms, searching for heterogeneities of size, age and industry.

The study used the theoretical-empirical GCP framework, comprising the dimensions: human capital, product, domestic market, networks, technology, decision-making, competitive strategy, marketing, internationalization and online presence (Lafuente, Szerb and Rideg, 2016; Lafuente et al., 2019) and applied descriptive statistics, correlation analysis, confirmatory factor analysis and cluster analysis, on a survey data set of 55 Brazilian firms from different sizes, ages and industries.

The GCP framework was found robust, reliable and useful in emerging economies as the Brazilian. Three clusters of competitiveness were identified. Heterogeneities were detected in knowledge-intensive business services results. This work allows a better understanding of competitiveness through the identification and measurement of dimensions, which can help managers to identify/audit capacities to plan/improve firm performance.

Findings may support managers to identify, estimate and manage their competitiveness pillars, and thus increase their competitiveness levels with a focus on strategic long-term goals.

This paper contributes to knowledge production in two ways: to the validation of the framework in the Brazilian scenario and the understanding of the dynamics of competitiveness of firms.

This study aims to propose a computationally efficient framework for multi-objective optimization (MO) of antennas involving nested kriging modeling technology. The technique is demonstrated through a two-objective optimization of a planar Yagi antenna and three-objective design of a compact wideband antenna.

The keystone of the proposed approach is the usage of recently introduced nested kriging modeling for identifying the design space region containing the Pareto front and constructing fast surrogate model for the MO algorithm. Surrogate-assisted design refinement is applied to improve the accuracy of Pareto set determination. Consequently, the Pareto set is obtained cost-efficiently, even though the optimization process uses solely high-fidelity electromagnetic (EM) analysis.

The optimization cost is dramatically reduced for the proposed framework as compared to other state-of-the-art frameworks. The initial Pareto set is identified more precisely (its span is wider and of better quality), which is a result of a considerably smaller domain of the nested kriging model and better predictive power of the surrogate.

The proposed technique can be generalized to accommodate low- and high-fidelity EM simulations in a straightforward manner. The future work will incorporate variable-fidelity simulations to further reduce the cost of the training data acquisition.

The fast MO optimization procedure with the use of the nested kriging modeling technology for approximation of the Pareto set has been proposed and its superiority over state-of-the-art surrogate-assisted procedures has been proved. To the best of the authors’ knowledge, this approach to multi-objective antenna optimization is novel and enables obtaining optimal designs cost-effectively even in relatively high-dimensional spaces (considering typical antenna design setups) within wide parameter ranges.

The purpose of this paper is to exploit a database of pre-existing designs to accelerate parametric optimization of antenna structures is investigated.

The usefulness of pre-existing designs for rapid design of antennas is investigated. The proposed approach exploits the database existing antenna base designs to determine a good starting point for structure optimization and its response sensitivities. The considered method is suitable for handling computationally expensive models, which are evaluated using full-wave electromagnetic (EM) simulations. Numerical case studies are provided demonstrating the feasibility of the framework for the design of real-world structures.

The use of pre-existing designs enables rapid identification of a good starting point for antenna optimization and speeds-up estimation of the structure response sensitivities. The base designs can be arranged into subsets (simplexes) in the objective space and used to represent the target vector, i.e. the starting point for structure design. The base closest base point w.r.t. the initial design can be used to initialize Jacobian for local optimization. Moreover, local optimization costs can be reduced through the use of Broyden formula for Jacobian updates in consecutive iterations.

The study investigates the possibility of reusing pre-existing designs for the acceleration of antenna optimization. The proposed technique enables the identification of a good starting point and reduces the number of expensive EM simulations required to obtain the final design.

The proposed design framework proved to be useful for the identification of good initial design and rapid optimization of modern antennas. Identification of the starting point for the design of such structures is extremely challenging when using conventional methods involving parametric studies or repetitive local optimizations. The presented methodology proved to be a useful design and geometry scaling tool when previously obtained designs are available for the same antenna structure.

A novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios.

The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels that render good initial designs, as well as an initial estimate of the antenna response sensitivities. Subsequent design refinement is realized using an iterative prediction-correction loop accommodating the discrepancies between the actual and target design specifications.

The presented framework is capable of yielding optimized antenna designs at the cost of just a few full-wave electromagnetic simulations. The practical importance of the iterative correction procedure has been corroborated by benchmarking against gradient-only refinement. It has been found that the incorporation of problem-specific knowledge into the optimization framework greatly facilitates parameter adjustment and improves its reliability.

The proposed approach can be a viable tool for antenna optimization whenever a certain number of previously obtained designs are available or the designer finds the initial effort of their gathering justifiable by intended re-use of the procedure. The future work will incorporate response features technology for improving the accuracy of the initial approximation of antenna response sensitivities.

The proposed optimization framework has been proved to be a viable tool for cost-efficient and reliable antenna optimization. To the knowledge, this approach to antenna optimization goes beyond the capabilities of available methods, especially in terms of efficient utilization of the existing knowledge, thus enabling reliable parameter tuning over broad ranges of both operating conditions and material parameters of the structure of interest.

The purpose of this study is to investigate contemporary changes in the education system. In particular, an analysis of the mechanisms of coordination and communication involved in the process can show how different geographical factors with different relational mechanisms may contribute to the creation of a new academic entrepreneurship.

The authors propose a methodology with two-step approach. In the first part of the paper, they use a theoretical approach to carry out a longitudinal study of academic literature on the topics of “entrepreneurial university,” “academic entrepreneurship” and “spin-off organizations.” In the second part, they use cross-database analysis to theorize the main aspects of recent developments in higher education in Italy. To this end, the authors use three public and open-access databases on spin-offs, universities and higher education institutions and incubators in Italy.

First, issues relating to the formation and best practices of entrepreneurial universities are discussed, based on the works of researchers from 25 countries. Second, a hypothesis is put forward to suggest that the organizational model of entrepreneurial university affects microeconomic competitiveness. Third, a case study of Italian spin-off organizations suggests that the number of incubators and spin-offs, and the type of academic knowledge, all directly affect the entrepreneurial university.

This paper aims to examine the role of the university in the modern economic system. The originality of this investigation lies in its ability to offer a picture and first analysis of the main actors and of the entrepreneurial university system.

A technique for accelerated design optimization of antenna input characteristics is developed and comprehensively validated using real-world wideband antenna structures. Comparative study using a conventional trust-region algorithm is provided. Investigations of the effects of the algorithm control parameters are also carried out.

An optimization methodology is introduced that replaces finite differentiation (FD) by a combination of FD and selectively used Broyden updating formula for antenna response Jacobian estimations. The updating formula is used for directions that are sufficiently well aligned with the design relocation that occurred in the most recent algorithm iteration. This allows for a significant reduction of the number of full-wave electromagnetic simulations necessary for the algorithm to converge; hence, it leads to the reduction of the overall design cost.

Incorporation of the updating formulas into the Jacobian estimation process in a selective manner considerably reduces the computational cost of the optimization process without compromising the design quality. The algorithm proposed in the study can be used to speed up direct optimization of the antenna structures as well as surrogate-assisted procedures involving variable-fidelity models.

This study sets a direction for further studies on accelerating procedures for the local optimization of antenna structures. Further investigations on the effects of the control parameters on the algorithm performance are necessary along with the development of means to automate the algorithm setup for a particular antenna structure, especially from the point of view of the search space dimensionality.

The proposed algorithm proved useful for a reduced-cost optimization of antennas and has been demonstrated to outperform conventional algorithms. To the authors’ knowledge, this is one of the first attempts to address the problem in this manner. In particular, it goes beyond traditional approaches, especially by combining various sensitivity estimation update measures in an adaptive fashion.

The purpose of this study is to propose a framework for expedited antenna optimization with numerical derivatives involving gradient variation monitoring throughout the optimization run and demonstrate it using a benchmark set of real-world wideband antennas. A comprehensive analysis of the algorithm performance involving multiple starting points is provided. The optimization results are compared with a conventional trust-region (TR) procedure, as well as the state-of-the-art accelerated TR algorithms.

The proposed algorithm is a modification of the TR gradient-based algorithm with numerical derivatives in which a monitoring of changes of the system response gradients is performed throughout the algorithm run. The gradient variations between consecutive iterations are quantified by an appropriately developed metric. Upon detecting stable patterns for particular parameter sensitivities, the costly finite differentiation (FD)-based gradient updates are suppressed; hence, the overall number of full-wave electromagnetic (EM) simulations is significantly reduced. This leads to considerable computational savings without compromising the design quality.

Monitoring of the antenna response sensitivity variations during the optimization process enables to detect the parameters for which updating the gradient information is not necessary at every iteration. When incorporated into the TR gradient-search procedures, the approach permits reduction of the computational cost of the optimization process. The proposed technique is dedicated to expedite direct optimization of antenna structures, but it can also be applied to speed up surrogate-assisted tasks, especially solving sub-problems that involve performing numerous evaluations of coarse-discretization models.

The introduced methodology opens up new possibilities for future developments of accelerated antenna optimization procedures. In particular, the presented routine can be combined with the previously reported techniques that involve replacing FD with the Broyden formula for directions that are satisfactorily well aligned with the most recent design relocation and/or performing FD in a sparse manner based on relative design relocation (with respect to the current search region) in consecutive algorithm iterations.

Benchmarking against a conventional TR procedure, as well as previously reported methods, confirms improved efficiency and reliability of the proposed approach. The applications of the framework include direct EM-driven design closure, along with surrogate-based optimization within variable-fidelity surrogate-assisted procedures. To the best of the authors’ knowledge, no comparable approach to antenna optimization has been reported elsewhere. Particularly, it surmounts established methodology by carrying out constant supervision of the antenna response gradient throughout successive algorithm iterations and using gathered observations to properly guide the optimization routine.