Making Regional Competence Blocs Attractive - On the Critical Role of Entrepreneurship and Firm Turnover in Regional Economic Growth

Radically new technology offers the prospect of a New and high productivity Economy for the industrially advanced economies. These opportunities are rapidly taken advantage of by innovative firms operating across national borders. Rapid globalization, therefore, makes the regional dimension of economic growth increasingly overshadow the national dimension. Economic transformation, furthermore, is also being pushed by a still ongoing (2003) severe recession , forcing previously successful firms to shed resources and making industrial assets available in the market at depressed prices. Technologies embodied in those assets are often globally mobile. Even large regions or nations, however, may lack a sufficiently broad commercialization competence to locally identify, capture and industrialize all free floating technologies. Hence, also previously prosperous regions may risk missing the boat to the New Economy, and history is full of such regional failures. Therefore, even large regional economies will depend on foreign investors, and policy authorities in many industrial regions have initiated policy races both to attract new resources and to shore up the outward flow that might otherwise occur through the intermediation of global companies. The outcome of all this may be the creation of other concentrations of excellence among the rich industrial economies than those created in the wake of the previous industrial revolution some 150 years ago. Being attractive for advanced investments is synonymous to being both internationally competitive and offering a rich supply of complementary industrial services to potential investors. The local capacity (receiver competence) to identify and locally commercialize technological spillovers is always more narrow than the supplies of technology. Competence bloc theory is used to explain and characterize the locally attractive attributes and to demonstrate how they can be enhanced through policy to attract global resources.The Lake Mälar/Baltic region in Sweden is used to clarify how policy action may stem the outward flow by making the region attractive for imports of industrial competence and inward investment emphasizing the need to import industrially competent venture capital to broaden the local receiver competence and to support local new firm establishement based on locally available technology. The Bavaria/Baden- Württemberg (B/W-W) region in Southern Germany is used to illustrate the opposite, namely a region that may possess the broad based capacity to locally reinvest in locally released technologies. For Sweden this amounts to a repeat of the 17th and 18th century industrial policy of Swedish kings to stimulate the foreign immigration of skilled labor, only that this time the purpose is to build new industry for economic growth, not to build an imperial war machine. The dramatic restructuring over markets in Sweden holds the promise, if succesful, to be more innovative than the B/B-W restructuring, but the Swedish case is more risky, not least because of a political unwillingness to introduce the necessary institutional reforms.Competence Bloc theory; Experimentally Organized Economy; Globalization; New Economy; Policy Competition; Regional Industrial Attractor; Social Capital; Venture Capital Competence

Data based identification and prediction of nonlinear and complex dynamical systems

We thank Dr. R. Yang (formerly at ASU), Dr. R.-Q. Su (formerly at ASU), and Mr. Zhesi Shen for their contributions to a number of original papers on which this Review is partly based. This work was supported by ARO under Grant No. W911NF-14-1-0504. W.-X. Wang was also supported by NSFC under Grants No. 61573064 and No. 61074116, as well as by the Fundamental Research Funds for the Central Universities, Beijing Nova Programme.Peer reviewedPostprin

Physically Embedded Genetic Algorithm Learning in Multi-Robot Scenarios: The PEGA algorithm

We present experiments in which a group of autonomous mobile robots learn to perform fundamental sensor-motor tasks through a collaborative learning process. Behavioural strategies, i.e. motor responses to sensory stimuli, are encoded by means of genetic strings stored on the individual robots, and adapted through a genetic algorithm (Mitchell, 1998) executed by the entire robot collective: robots communicate their own strings and corresponding fitness to each other, and then execute a genetic algorithm to improve their individual behavioural strategy. The robots acquired three different sensormotor competences, as well as the ability to select one of two, or one of three behaviours depending on context ("behaviour management"). Results show that fitness indeed increases with increasing learning time, and the analysis of the acquired behavioural strategies demonstrates that they are effective in accomplishing the desired task

Distributed coordination of self-organizing mechanisms in communication networks

The fast development of the Self-Organizing Network (SON) technology in mobile networks renders the problem of coordinating SON functionalities operating simultaneously critical. SON functionalities can be viewed as control loops that may need to be coordinated to guarantee conflict free operation, to enforce stability of the network and to achieve performance gain. This paper proposes a distributed solution for coordinating SON functionalities. It uses Rosen's concave games framework in conjunction with convex optimization. The SON functionalities are modeled as linear Ordinary Differential Equation (ODE)s. The stability of the system is first evaluated using a basic control theory approach. The coordination solution consists in finding a linear map (called coordination matrix) that stabilizes the system of SON functionalities. It is proven that the solution remains valid in a noisy environment using Stochastic Approximation. A practical example involving three different SON functionalities deployed in Base Stations (BSs) of a Long Term Evolution (LTE) network demonstrates the usefulness of the proposed method.Comment: submitted to IEEE TCNS. arXiv admin note: substantial text overlap with arXiv:1209.123

Recognizing the Importance of an Understanding of Autopoietic and Complexity Theories Within the Electronic Commerce Model for Competitive Advantage

Traditionally, management has viewed the organization as a very mechanistic, linear system characterized by a simple and predictable cause and effect. However, complexity theory brings to management an organic, nonlinear, and holistic way of viewing organizational systems. Within the business context in general and the electronic commerce model in specific, the selfproducing and self-organizing nature of the organization combined with the interaction between the autonomous agents of the system, produces emerging patterns and an intrinsic order that flies in the face of the traditional problem-solving techniques. The application of the autopoietic and complexity theories to the virtual systems that exist within the electronic commerce model can assist business management in understanding the nature of the unpredictable, dynamic forces continuously driving forward the dynamics of these New Economy systems. The focus of this research will center on: · identifying the interactive nature of complexity theory within the electronic commerce model;· understanding the virtual society of the electronic commerce model as being functionally differentiated into autonomous autopoietic subsystems, or “meaning worlds” (Teubner & Willke, 1997), which can influence each other only indirectly; · accepting that functional differentiation, complexity theory, and autopoiesis mean it is no longer possible to direct and control these virtual social systems to move along the traditionally predetermined paths through interventions from external systems, such as external entities, business alliances, internal customers, or external customers; · appreciating the creative dynamism unleashed through complexity theory and the autopoietic processes in which the new hyper-extended communication acts to produce new artificial structures within the electronic commerce model that have dynamics of their own and can self-reproduce and self-regulate through autopoiesis; · being aware that these social autopoietics do not give primacy either to the individual or the collective within the virtual social system, but to the emergent new hyper-extended communication system which results from discourses involving the dynamic systemic structures and real people. Hypothesized outcomes of this research also include a better understanding of the emergent behavior of the systems within the electronic commerce model. The application of the autopoietic and complexity theories to these virtual systems can be positively related to organizational success that comes from the networked combinations of freely acting agents. Competitive advantages can be maximized and organizational missions can be achieved though an understanding and application of complexity and autopoietic theories

A Black Hole Attack Model for Reactive Ad-Hoc Protocols

Net-Centric Warfare places the network in the center of all operations, making it a critical resource to attack and defend during wartime. This thesis examines one particular network attack, the Black Hole attack, to determine if an analytical model can be used to predict the impact of this attack on ad-hoc networks. An analytical Black Hole attack model is developed for reactive ad-hoc network protocols DSR and AODV. To simplify topology analysis, a hypercube topology is used to approximate ad-hoc topologies that have the same average node degree. An experiment is conducted to compare the predicted results of the analytical model against simulated Black Hole attacks on a variety of ad-hoc networks. The results show that the model describes the general order of growth in Black Hole attacks as a function of the number of Black Holes in a given network. The model accuracy maximizes when both the hypercube approximation matches the average degree and number of nodes of the ad-hoc topology. For this case, the model falls within the 95% confidence intervals of the estimated network performance loss for 17 out of 20 measured scenarios for AODV and 7 out of 20 for DSR