Is There a Size-Induced Market Failure in Skills Training?

A skilled and educated workforce can support the competitiveness of enterprises of all sizes. However, smaller firms may face greater challenges in developing human capital. We explore differences between smaller and larger firms in offering skills training and in hiring workers with more formal education. Drawing on a dataset of enterprises in five Asian countries, we find major size-based differences in education and training. While smaller firms train less, they also are less inclined to view an inadequately skilled workforce as a major constraint on their operations. It may be that smaller firms are content to occupy niches in a low-skills equilibrium. Our empirical results do offer the possibility, however, that a size-induced market failure in skills training may coexist with a lower regard for skills. The policy implications are not only that governments can reduce the costs for firms to train, but also that micro and small firms need to be sensitized to the benefits of skills upgrading

A multi-agent-based evolution model of innovation networks in dynamic environments

An innovation network can be considered as a complex adaptive system with evolution affected by dynamic environments. This paper establishes a multi-agent-based evolution model of innovation networks under dynamic settings through computational and logical modeling, and a multi-agent system paradigm. This evolution model is composed of several sub-models of agents' knowledge production by independent innovations in dynamic situations, knowledge learning by cooperative innovations covering agents' heterogeneities, decision-making for innovation selections, and knowledge update considering decay factors. On the basis of above-mentioned sub-models, an evolution rule for multi-agent based innovation network system is given. The proposed evolution model can be utilized to simulate and analyze different scenarios of innovation networks in various dynamic environments and support decision-making for innovation network optimization

Relevancy between corporations and clans: ideologies behind corporate law

postprin

Relevancy between corporations and clans: ideologies behind corporate law

postprin

The innovation network as a complex adaptive system: flexible multi-agent based modeling, simulation and evolutionary decision making

The literature rarely considers an innovation network as a complex adaptive system. In this paper, theories of complex adaptive systems research are employed to model and analyze intra-organization networks, inter-organization networks as well as their interaction mechanisms in the whole innovation context, with a conceptual framework proposed and presented. Flexible multi-agent based modeling, smart simulation, self-survival and adaptive intelligent software agents, expert systems, analytic hierarchy process, hybrid decision support approach, and statistical methods are integrated to deal with the innovation network problem and support evolutionary decision making in the open and dynamic environments

Gate-controllable spin-battery

We propose a gate-controllable spin-battery for spin current. The spin-battery consists of a lateral double quantum dot under a uniform magnetic field. A finite DC spin-current is driven out of the device by controlling a set of gate voltages. Spin-current can also be delivered in the absence of charge-current. The proposed device should be realizable using present technology at low temperature.Comment: 3 pages, 3 figures, accepted by Appl. Phys. Let