Partnering in the Dynamic Environment: The Role of Trust in Asymmetric Technology Partnership Formation

The purpose of this study was to increase the understanding of the role and nature of trust in asymmetric technology partnership formation. In the knowledge-based "learning race" knowledge is considered as a primary source for competitive advantage. In the emerging ICT sector the high pace of technological change, the convergence of technologies and industries as well as the increasing complexity and uncertainty have forced even the largest players to seek cooperation for complementary knowledge and capabilities. Small technology firms need the complementary resources and legitimacy of the large firms to grow and compete in the global market place. Most of the earlier research indicates, however, that partnerships with asymmetric size, managerial resources and cultures have failed. A basic assumption supported by earlier research was that trust is a critical factor in asymmetric technology partnership formation. Asymmetric technology partnership formation is a dynamic and multi-dimensional process, and consequently a holistic research approach was selected. Research issue was approached from different levels: the individual decision-maker, the firm and the relationship between the parties. Also the impact of the dynamic environment and technology content was analyzed. A multitheoretical approach and a qualitative research method with in-depth interviews in five large ICT companies and eight small ICT companies enabled a holistic and rich view of the research issue. Study contributes on the scarce understanding on the nature and evolution of trust in asymmetric technology partnership formation. It sheds also light on the specific nature of asymmetric technology partnerships. The partnerships were found to be tentative and the diverse strategic intent of small and large technology firms appeared as a major challenge. The role of the boundary spanner was highlighted as a possibility to match the incompatible organizational cultures. A shared vision was found to be a pre-condition for individual-based fast trust leading to intuitive decision-making and experimentation. The relationships were tentative and they were continuously re-evaluated through the key actors' sense making of the technology content, asymmetry and the dynamic environment. A multi-dimensional conceptualization for trust was created and propositions on the role and nature of trust for further research are given. The purpose of this study was to increase the understanding of the role and nature of trust in asymmetric technology partnership formation. In the knowledge-based "learning race" knowledge is considered as a primary source for competitive advantage. In the emerging ICT sector the high pace of technological change, the convergence of technologies and industries as well as the increasing complexity and uncertainty have forced even the largest players to seek cooperation for complementary knowledge and capabilities. Small technology firms need the complementary resources and legitimacy of the large firms to grow and compete in the global market place. Most of the earlier research indicates, however, that partnerships with asymmetric size, managerial resources and cultures have failed. A basic assumption supported by earlier research was that trust is a critical factor in asymmetric technology partnership formation. Asymmetric technology partnership formation is a dynamic and multi-dimensional process, and consequently a holistic research approach was selected. Research issue was approached from different levels: the individual decision-maker, the firm and the relationship between the parties. Also the impact of the dynamic environment and technology content was analyzed. A multitheoretical approach and a qualitative research method with in-depth interviews in five large ICT companies and eight small ICT companies enabled a holistic and rich view of the research issue. Study contributes on the scarce understanding on the nature and evolution of trust in asymmetric technology partnership formation. It sheds also light on the specific nature of asymmetric technology partnerships. The partnerships were found to be tentative and the diverse strategic intent of small and large technology firms appeared as a major challenge. The role of the boundary spanner was highlighted as a possibility to match the incompatible organizational cultures. A shared vision was found to be a pre-condition for individual-based fast trust leading to intuitive decision-making and experimentation. The relationships were tentative and they were continuously re-evaluated through the key actors' sense making of the technology content, asymmetry and the dynamic environment. A multi-dimensional conceptualization for trust was created and propositions on the role and nature of trust for further research are given.

Causality and contagion in peripheral EMU public debt markets: a dynamic approach

Our research aims to analyze the causal relationships in the behavior of public debt issued by peripheral member countries of the European Economic and Monetary Union -EMU-, with special emphasis on the recent episodes of crisis triggered in the eurozone sovereign debt markets since 2009. With this goal in mind, we make use of a database of daily frequency of yields on 10-year government bonds issued by five EMU countries -Greece, Ireland, Italy, Portugal and Spain-, covering the entire history of the EMU from its inception on 1 January 1999 until 31 December 2010. In the first step, we explore the pair-wise causal relationship between yields, both for the whole sample and for changing subsamples of the data, in order to capture the possible time-varying causal relationship. This approach allows us to detect episodes of contagion between yields on bonds issued by different countries. In the second step, we study the determinants of these contagion episodes, analyzing the role played by different factors, paying special attention to instruments that capture the total national debt -domestic and foreign- in each country.

Flexible Multibody Simulation Approach in the Dynamic Analysis of Bone Strains Activity

The objective of this study is to show that bone strains due to dynamic mechanical loading during physical activity can be analysed using the flexible multibody simulation approach. Strains within the bone tissue play a major role in bone (re)modeling. Based on previous studies, it has been shown that dynamic loading seems to be more important for bone (re)modeling than static loading. The finite element method has been used previously to assess bone strains. However, the finite element method may be limited to static analysis of bone strains due to the expensive computation required for dynamic analysis, especially for a biomechanical system consisting of several bodies. Further, in vivo implementation of strain gauges on the surfaces of bone has been used previously in order to quantify the mechanical loading environment of the skeleton. However, in vivo strain measurement requires invasive methodology, which is challenging and limited to certain regions of superficial bones only, such as the anterior surface of the tibia. In this study, an alternative numerical approach to analyzing in vivo strains, based on the flexible multibody simulation approach, is proposed. In order to investigate the reliability of the proposed approach, three 3-dimensional musculoskeletal models where the right tibia is assumed to be flexible, are used as demonstration examples. The models are employed in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model is developed using the actual geometry of the subject’s tibia, which is obtained from 3 dimensional reconstruction of Magnetic Resonance Images. Inverse dynamics simulation based on motion capture data obtained from walking at a constant velocity is used to calculate the desired contraction trajectory for each muscle. In the forward dynamics simulation, a proportional derivative servo controller is used to calculate each muscle force required to reproduce the motion, based on the desired muscle contraction trajectory obtained from the inverse dynamics simulation. Experimental measurements are used to verify the models and check the accuracy of the models in replicating the realistic mechanical loading environment measured from the walking test. The predicted strain results by the models show consistency with literature-based in vivo strain measurements. In conclusion, the non-invasive flexible multibody simulation approach may be used as a surrogate for experimental bone strain measurement, and thus be of use in detailed strain estimation of bones in different applications. Consequently, the information obtained from the present approach might be useful in clinical applications, including optimizing implant design and devising exercises to prevent bone fragility, accelerate fracture healing and reduce osteoporotic bone loss.

Determination of Rod and Cone Influence to the Early and Late Dynamic of the Pupillary Light Response.

PURPOSE: This study aims to identify which aspects of the pupil light reflex are most influenced by rods and cones independently by analyzing pupil recordings from different mouse models of photoreceptor deficiency. METHODS: One-month-old wild type (WT), rodless (Rho-/-), coneless (Cnga3-/-), or photoreceptor less (Cnga3-/-; Rho-/- or Gnat1-/-) mice were subjected to brief red and blue light stimuli of increasing intensity. To describe the initial dynamic response to light, the maximal pupillary constriction amplitudes and the derivative curve of the first 3 seconds were determined. To estimate the postillumination phase, the constriction amplitude at 9.5 seconds after light termination was related to the maximal constriction amplitude. RESULTS: Rho-/- mice showed decreased constriction amplitude but more prolonged pupilloconstriction to all blue and red light stimuli compared to wild type mice. Cnga3-/- mice had constriction amplitudes similar to WT however following maximal constriction, the early and rapid dilation to low intensity blue light was decreased. To high intensity blue light, the Cnga3-/- mice demonstrated marked prolongation of the pupillary constriction. Cnga3-/-; Rho-/- mice had no pupil response to red light of low and medium intensity. CONCLUSIONS: From specific gene defective mouse models which selectively voided the rod or cone function, we determined that mouse rod photoreceptors are highly contributing to the pupil response to blue light stimuli but also to low and medium red stimuli. We also observed that cone cells mainly drive the partial rapid dilation of the initial response to low blue light stimuli. Thus photoreceptor dysfunction can be derived from chromatic pupillometry in mouse models.

Geographic assignment of seabirds to their origin: combining morphology, genetics and biogeochemical analyses

Longline fisheries, oil spills, and offshore wind farms are some of the major threats increasing seabird mortality at sea, but the impact of these threats on specific populations has been difficult to determine so far. We tested the use of molecular markers, morphometric measures, and stable isotope (δ15N and δ13C) and trace element concentrations in the first primary feather (grown at the end of the breeding period) to assign the geographic origin of Calonectris shearwaters. Overall, we sampled birds from three taxa: 13 Mediterranean Cory's Shearwater (Calonectris diomedea diomedea) breeding sites, 10 Atlantic Cory's Shearwater (Calonectris diomedea borealis) breeding sites, and one Cape Verde Shearwater (C. edwardsii) breeding site. Assignment rates were investigated at three spatial scales: breeding colony, breeding archipelago, and taxa levels. Genetic analyses based on the mitochondrial control region (198 birds from 21 breeding colonies) correctly assigned 100% of birds to the three main taxa but failed in detecting geographic structuring at lower scales. Discriminant analyses based on trace elements composition achieved the best rate of correct assignment to colony (77.5%). Body measurements or stable isotopes mainly succeeded in assigning individuals among taxa (87.9% and 89.9%, respectively) but failed at the colony level (27.1% and 38.0%, respectively). Combining all three approaches (morphometrics, isotopes, and trace elements on 186 birds from 15 breeding colonies) substantially improved correct classifications (86.0%, 90.7%, and 100% among colonies, archipelagos, and taxa, respectively). Validations using two independent data sets and jackknife cross-validation confirmed the robustness of the combined approach in the colony assignment (62.5%, 58.8%, and 69.8% for each validation test, respectively). A preliminary application of the discriminant model based on stable isotope δ15N and δ13C values and trace elements (219 birds from 17 breeding sites) showed that 41 Cory's Shearwaters caught by western Mediterranean long-liners came mainly from breeding colonies in Menorca (48.8%), Ibiza (14.6%), and Crete (31.7%). Our findings show that combining analyses of trace elements and stable isotopes on feathers can achieve high rates of correct geographic assignment of birds in the marine environment, opening new prospects for the study of seabird mortality at sea.

Validation of plant dynamic model by online and laboratory measurements – a tool to predict online COD loads out of production of mechanical printing papers

COD discharges out of processes have increased in line with elevating brightness demands for mechanical pulp and papers. The share of lignin-like substances in COD discharges is on average 75%. In this thesis, a plant dynamic model was created and validated as a means to predict COD loading and discharges out of a mill. The assays were carried out in one paper mill integrate producing mechanical printing papers. The objective in the modeling of plant dynamics was to predict day averages of COD load and discharges out of mills. This means that online data, like 1) the level of large storage towers of pulp and white water 2) pulp dosages, 3) production rates and 4) internal white water flows and discharges were used to create transients into the balances of solids and white water, referred to as “plant dynamics”. A conversion coefficient was verified between TOC and COD. The conversion coefficient was used for predicting the flows from TOC to COD to the waste water treatment plant. The COD load was modeled with similar uncertainty as in reference TOC sampling. The water balance of waste water treatment was validated by the reference concentration of COD. The difference of COD predictions against references was within the same deviation of TOC-predictions. The modeled yield losses and retention values of TOC in pulping and bleaching processes and the modeled fixing of colloidal TOC to solids between the pulping plant and the aeration basin in the waste water treatment plant were similar to references presented in literature. The valid water balances of the waste water treatment plant and the reduction model of lignin-like substances produced a valid prediction of COD discharges out of the mill. A 30% increase in the release of lignin-like substances in the form of production problems was observed in pulping and bleaching processes. The same increase was observed in COD discharges out of waste water treatment. In the prediction of annual COD discharge, it was noticed that the reduction of lignin has a wide deviation from year to year and from one mill to another. This made it difficult to compare the parameters of COD discharges validated in plant dynamic simulation with another mill producing mechanical printing papers. However, a trend of moving from unbleached towards high-brightness TMP in COD discharges was valid.

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.

Literature review on permanent magnet generators design and dynamic behavior

This paper is a literature review which describes the construction of state of the art of permanent magnet generators and motors constructing and discusses the current and possible application of these machines in industry. Permanent magnet machines are a well-know class of rotating and linear electric machines used for many years in industrial applications. A particular interest for permanent magnet generators is connected with wind mills, which seem to be becoming increasingly popular nowadays. Geared and direct-driven permanent magnet generators are described. A classification of direct-driven permanent magnet generators is given. Design aspects of permanent magnet generators are presented. Permanent magnet generators for wind turbines designs are highlighted. Dynamics and vibration problems of permanent magnet generators covered in literature are presented. The application of the Finite Element Method for mechanical problems solution in the field of permanent magnet generators is discussed.

Generalized three-sided assignment markets: consistency and the core

A class of three-sided markets (and games) is considered, where value is generated by pairs or triplets of agents belonging to different sectors, as well as by individuals. For these markets we analyze the situation that arises when some agents leave the market with some payoff To this end, we introduce the derived market (and game) and relate it to the Davis and Maschler (1965) reduced game. Consistency with respect to the derived market, together with singleness best and individual anti-monotonicity axiomatically characterize the core for these generalized three-sided assignment markets. These markets may have an empty core, but we define a balanced subclass, where the worth of each triplet is defined as the addition of the worths of the pairs it contains. Keywords: Multi-sided assignment market, Consistency, Core, Nucleolus. JEL Classification: C71, C78