On analysis of complex network dynamics – changes in local topology

Social networks created based on data gathered in various computer systems are structures that constantly evolve. The nodes and their connections change because they are influenced by the external to the network events.. In this work we present a new approach to the description and quantification of patterns of complex dynamic social networks illustrated with the data from the Wroclaw University of Technology email dataset. We propose an approach based on discovery of local network connection patterns (in this case triads of nodes) as well as we measure and analyse their transitions during network evolution. We define the Triad Transition Matrix (TTM) containing the probabilities of transitions between triads, after that we show how it can help to discover the dynamic patterns of network evolution. One of the main issues when investigating the dynamical process is the selection of the time window size. Thus, the goal of this paper is also to investigate how the size of time window influences the shape of TTM and how the dynamics of triad number change depending on the window size. We have shown that, however the link stability in the network is low, the dynamic network evolution pattern expressed by the TTMs is relatively stable, and thus forming a background for fine-grained classification of complex networks dynamics. Our results open also vast possibilities of link and structure prediction of dynamic networks. The future research and applications stemming from our approach are also proposed and discussed

Surplus Appropriation from R&D and Health Care Technology Assessment Procedures

Given the rapid growth in health care spending that is often attributed to technological change, many private and public institutions are grappling with how to best assess and adopt new health care technologies. The leading technology adoption criteria proposed in theory and used in practice involve so called "cost-effectiveness" measures. However, little is known about the dynamic efficiency implications of such criteria, in particular how they influence the R&D investments that make technologies available in the first place. We argue that such criteria implicitly concern maximizing consumer surplus, which many times is consistent with maximizing static efficiency after an innovation has been developed. Dynamic efficiency, however, concerns aligning the social costs and benefits of R&D and is therefore determined by how much of the social surplus from the new technology is appropriated as producer surplus. We analyze the relationship between cost-effectiveness measures and the degree of surplus appropriation by innovators driving dynamic efficiency. We illustrate how to estimate the two for the new HIV/AIDS therapies that entered the market after the late 1980's and find that only 5% of the social surplus is appropriated by innovators. We show how this finding can be generalized to other existing cost-effectiveness estimates by deriving how those estimates identify innovator appropriation for a set of studies of over 200 drugs. We find that these studies implicitly support a low degree of appropriation as well. Despite the high annual cost of drugs to patients, very low shares of social surplus may go to innovators, which may imply that cost-effectiveness is too high in a dynamic efficiency sense.

Experimental comparison of dynamic tracking performanceof iGPS and laser tracker

External metrology systems are increasingly being integrated with traditional industrial articulated robots, especially in the aerospace industries, to improve their absolute accuracy for precision operations such as drilling, machining and jigless assembly. While currently most of the metrology assisted robotics control systems are limited in their position update rate, such that the robot has to be stopped in order to receive a metrology coordinate update, some recent efforts are addressed toward controlling robots using real-time metrology data. The indoor GPS is one of the metrology systems that may be used to provide real-time 6DOF data to a robot controller. Even if there is a noteworthy literature dealing with the evaluation of iGPS performance, there is, however, a lack of literature on how well the iGPS performs under dynamic conditions. This paper presents an experimental evaluation of the dynamic measurement performance of the iGPS, tracking the trajectories of an industrial robot. The same experiment is also repeated using a laser tracker. Besides the experiment results presented, this paper also proposes a novel method for dynamic repeatability comparisons of tracking instrument

"Trying" to be Entrepreneurial

If we are to understand how entrepreneurial intentions evolve, we must embrace theories reflecting the inherent dynamics of human decision making. While the dominant model of entrepreneurial intentions remains invaluable, capturing the dynamics is necessary to advance our understanding of how intent becomes action. To this end, we offer Bagozzi’s Theory of Trying (TT) as a theory-driven model that assumes a dynamic pathway to intent. Rather than focusing on intentions toward a static target behavior, TT focuses on intentions toward a dynamic goal. To support this perspective, we offer striking new evidence that the emergent intentions process is indeed dynamic.intentions, theory of trying, tipping points, reciprocal causation, entrepreneurship, entrepreneurial cognition

Unbundling dynamic capabilities for inter-organizational collaboration

Purpose The purpose of this paper is to explore two distinct subsets of dynamic capabilities that need to be deployed when pursuing innovation through inter-organizational activities, respectively, in the contexts of broad networks and specific alliances. The authors draw distinctions and explore potential interdependencies between these two dynamic capability reservoirs, by integrating concepts from the theoretical perspectives they are derived from, but which have until now largely ignored each other – the social network perspective and the dynamic capabilities view. Design/methodology/approach The authors investigate nanotechnology-driven R&D activities in the 1995–2005 period for 76 publicly traded firms in the electronics and electrical equipment industry and in the chemicals and pharmaceuticals industry, that applied for 580 nanotechnology-related patents and engaged in 2,459 alliances during the observation period. The authors used zero-truncated Poisson regression as the estimation method. Findings The findings support conceptualizing dynamic capabilities as four distinct subsets, deployed for sensing or seizing purposes, and across the two different inter-organizational contexts. The findings also suggest potential synergies between these subsets of dynamic capabilities, with two subsets being more macro-oriented (i.e. sensing and seizing opportunities within networks) and the two other ones more micro-oriented (i.e. sensing and seizing opportunities within specific alliances). Practical implications The authors show that firms differ in their subsets of dynamic capabilities for pursuing different types of inter-organizational, boundary-spanning relationships (such as alliances vs broader network relationships), which ultimately affects their innovation performance. Originality/value The authors contribute to the growing body of work on dynamic capabilities and firm-specific advantages by unbundling the dynamic capability subsets, and investigating their complex interdependencies for managing different types of inter-organizational linkages. The main new insight is that the “linear model” of generating more innovations through higher inter-firm collaboration in an emerging field paints an erroneous picture of how high innovation performance is actually achieved

Population–reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population–reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population–reaction model. We also show that population–reaction models can be applied to various ecological concepts, such as predator–prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms

Examining emerging ICT's adoption in SMEs from a dynamic process approach

Purpose – This paper aims to advance information and communication technologies (ICT) adoption research and practice by examining and understanding the emerging ICT adoption in small and medium enterprises (SMEs) from a dynamic process perspective using actor-network theory (ANT). Design/methodology/approach – This study employs a qualitative approach to investigate how services SMEs are constantly engaging in ICT adoption for improving business performance. Two rounds of interviews were conducted with 26 interviewees. Data collected from the unstructured and semi-structured interviews were analysed to understand the dynamic adoption process, actors involved and their interactions. Findings – The findings reveal the recursive and dynamic nature of the emerging ICT adoption process and the constant interactions and negotiations of various actors. Underpinned by the key concepts of ANTand validated by the empirical data, a framework is developed to depict the stages of dynamic process of emerging ICT adoption, the actors involved and the associated key activities. Research limitations/implications – Qualitative research is interpretive in nature and the size of the sample used is limited. These limitations require caution for the generalization of the findings. The framework can be further validated across a wider population using mixed methods combining qualitative and quantitative approaches. Practical implications – Emerging ICT adoption has moved from a simple adopters’ participation process to involving various actors that constantly interact and influence the process. SMEs manager can be influenced by and influence the technology advancement. As a result, SMEs need constantly interact with various human and non-human actors to keep up with the new ICT development and benefit from the emerging opportunities. Originality/value – The research focuses on the emerging ICT adoption in SMEs from the dynamic process perspective using ANT. It advances ICT adoption research and practice by developing a framework to depict the dynamic and interactive nature of ICT adoption process, and the actors involved and their interactions in the adoption process. Keywords Adoption, Technology adoption, Actor-network theory, Small- and medium-sized enterprises (SMEs) Paper type Research pape