From network pictures to network insight in solution business – the role of internal communication

Operating in business-to-business markets requires an in-depth understanding on business networks. Actions and reactions made to compete in markets are fundamentally based on managers‘ subjective perceptions of the network. However, an amalgamation of these individual perceptions, termed a network picture, to a common company level shared understanding on that network, known as network insight, is found to be a substantial challenge for companies. A company‘s capability to enhance common network insight is even argued to lead competitive advantage. Especially companies with value creating logics that require wide comprehension of and collaborating in networks, such as solution business, are necessitated to develop advanced network insight. According to the extant literature, dispersed pieces of atomized network pictures can be unified to a common network insight through a process of amalgamation that comprises barriers/drivers of multilateral exchange, manifold rationality, and recursive time. However, the extant body of literature appears to lack an understanding on the role of internal communication in the development of network insight. Nonetheless, the extant understanding on the amalgamation process indicates that internal communication plays a substantial role in the development of company level network insight. The purpose of the present thesis is to enhance understanding on internal communication in the amalgamation of network pictures to develop network insight in the solution business setting, which was chosen to represent business-to-business value creating logic that emphasizes the capability to understand and utilize networks. Thus, in solution business the role of succeeding in the amalgamation process is expected to emphasize. The study combines qualitative and quantitative research by means of various analytical methods including multiple case analysis, simulation, and social network analysis. Approaching the nascent research topic with differing perspectives and means provides a broader insight on the phenomenon. The study provides empirical evidence from Finnish business-to-business companies which operate globally. The empirical data comprise interviews (n=28) with managers of three case companies. In addition the data includes a questionnaire (n=23) collected mainly for the purpose of social network analysis. In addition, the thesis includes a simulation study more specifically achieved by means of agent based modeling. The findings of the thesis shed light on the role of internal communication in the amalgamation process, contributing to the emergent discussion of network insights and thus to the industrial marketing research. In addition, the thesis increases understanding on internal communication in the change process to solution business, a supplier‘s internal communication in its matrix organization structure during a project sales process, key barriers and drivers that influence internal communication in project sales networks, perceived power within industrial project sales, and the revisioning of network pictures. According to the findings, internal communication is found to play a substantial role in the amalgamation process. First, it is suggested that internal communication is a base of multilateral exchange. Second, it is suggested that internal communication intensifies and maintains manifold rationality. Third, internal communication is needed to explicate the usually differing time perspectives of others and thus it is suggested that internal communication has role as the explicator of recursive time. Furthermore, the role of an efficient amalgamation process is found to be emphasized in solutions business as it requires a more advanced network insight for cross-functional collaboration. Finally, the thesis offers several managerial implications for industrial suppliers to enhance the amalgamation process when operating in solution business.

Reflexive Space. A Constructionist Model of the Russian Reflexive Marker

This study examines the structure of the Russian Reflexive Marker ( ся/-сь) and offers a usage-based model building on Construction Grammar and a probabilistic view of linguistic structure. Traditionally, reflexive verbs are accounted for relative to non-reflexive verbs. These accounts assume that linguistic structures emerge as pairs. Furthermore, these accounts assume directionality where the semantics and structure of a reflexive verb can be derived from the non-reflexive verb. However, this directionality does not necessarily hold diachronically. Additionally, the semantics and the patterns associated with a particular reflexive verb are not always shared with the non-reflexive verb. Thus, a model is proposed that can accommodate the traditional pairs as well as for the possible deviations without postulating different systems. A random sample of 2000 instances marked with the Reflexive Marker was extracted from the Russian National Corpus and the sample used in this study contains 819 unique reflexive verbs. This study moves away from the traditional pair account and introduces the concept of Neighbor Verb. A neighbor verb exists for a reflexive verb if they share the same phonological form excluding the Reflexive Marker. It is claimed here that the Reflexive Marker constitutes a system in Russian and the relation between the reflexive and neighbor verbs constitutes a cross-paradigmatic relation. Furthermore, the relation between the reflexive and the neighbor verb is argued to be of symbolic connectivity rather than directionality. Effectively, the relation holding between particular instantiations can vary. The theoretical basis of the present study builds on this assumption. Several new variables are examined in order to systematically model variability of this symbolic connectivity, specifically the degree and strength of connectivity between items. In usage-based models, the lexicon does not constitute an unstructured list of items. Instead, items are assumed to be interconnected in a network. This interconnectedness is defined as Neighborhood in this study. Additionally, each verb carves its own niche within the Neighborhood and this interconnectedness is modeled through rhyme verbs constituting the degree of connectivity of a particular verb in the lexicon. The second component of the degree of connectivity concerns the status of a particular verb relative to its rhyme verbs. The connectivity within the neighborhood of a particular verb varies and this variability is quantified by using the Levenshtein distance. The second property of the lexical network is the strength of connectivity between items. Frequency of use has been one of the primary variables in functional linguistics used to probe this. In addition, a new variable called Constructional Entropy is introduced in this study building on information theory. It is a quantification of the amount of information carried by a particular reflexive verb in one or more argument constructions. The results of the lexical connectivity indicate that the reflexive verbs have statistically greater neighborhood distances than the neighbor verbs. This distributional property can be used to motivate the traditional observation that the reflexive verbs tend to have idiosyncratic properties. A set of argument constructions, generalizations over usage patterns, are proposed for the reflexive verbs in this study. In addition to the variables associated with the lexical connectivity, a number of variables proposed in the literature are explored and used as predictors in the model. The second part of this study introduces the use of a machine learning algorithm called Random Forests. The performance of the model indicates that it is capable, up to a degree, of disambiguating the proposed argument construction types of the Russian Reflexive Marker. Additionally, a global ranking of the predictors used in the model is offered. Finally, most construction grammars assume that argument construction form a network structure. A new method is proposed that establishes generalization over the argument constructions referred to as Linking Construction. In sum, this study explores the structural properties of the Russian Reflexive Marker and a new model is set forth that can accommodate both the traditional pairs and potential deviations from it in a principled manner.

The key practices of customer portfolio management (CPM) process in the medical and healthcare B2B industry

The goal of this study is to deepen the understanding of the customer portfolio management process. There are many models for the process, and they are not necessarily exclusive of each other. Consequently, the inclusion of many models might even prove out to be beneficial. Other theoretical framework include the current economical situation and its propose on customer portfolio management. With an understanding of the theoretical models as a background, the empirical part of this study compares Finnish multinational medical and healthcare technology companies’ customer portfolio management practices. The empirical research was carried out with theme interviews held with 11 sales and marketing managers or directors from four different companies. The goal was to discover the most essential practices of the process steps in the companies. The result of this study is that there is a lack of systematic customer portfolio management, but most companies are aiming to improve this in the near future. The most essential practices are analysis of sales, communication level, learning, and commitment to strategy of the focal company. Special characteristics of this industry include large business networks that include customers, professional end-users, institutions, universities, researchers, and key opinion leaders. The management and analysis of this comprehensive network has been seen to be extremely important for this industry.

National Library of Finland as Service Centre for libraries, archives, museums and other public sector organisations

Kristiina Hormia-Poutasen esitys KOBV-konferenssissa Berliinissä, Saksassa kesäkuussa 2013.

Tuning cell motility : roles of nestin and vimentin in cancer cell invasion and motility

The cytoskeleton is a key feature of both prokaryotic and eukaryotic cells. Itis comprised of three protein families, one of which is the intermediate filaments (IFs). Of these, the IFs are the largest and most diverse. The IFs are expressed throughout life, and are involved in the regulation of cell differentiation, homeostasis, ageing and pathogenesis. The IFs not only provide structural integrity to the cell, they are also involved in a range of cellular functions from organelle trafficking and cell migration to signalling transduction. The IFs are highly dynamic proteins, able to respond and adapt their network rapidly in response to intra- and extra- cellular cues. Consequently they interact with a whole host of cellular signalling proteins, regulating function, and activity, and cellular localisation. While the function of some of the better-known IFs such as the keratins is well studied, the understanding of the function of two IFs, nestin and vimentin, is poor. Nestin is well known as a marker of differentiation and is expressed in some cancers. In cancer, nestin is primarily described as is a promoter of cell motility, however, how it fulfils this role remains undefined. Vimentin too is expressed in cancer, and is known to promote cell motility and is used as a marker for epithelial to mesenchymal transition (EMT). It is only in the last decade that studies have addressed the role that vimentin plays in cell motility and EMT. This work provides novel insight into how the IFs, nestin and vimentin regulate cell motility and invasion. In particular we show that nestin regulates the cellular localisation and organisation of two key facilitators of cell migration, focal adhesion kinase and integrins. We identify nestin as a regulator of extracellular matrix degradation and integrin-mediated cell invasion. Two further studies address the specific regulation of vimentin by phosphorylation. A detailed characterisation study identified key phosphorylation sites on vimentin, which are critical for proper organisation of the vimentin network. Furthermore, we show that the bioactive sphingolipids are vimentin network regulators. Specifically, the sphingolipids induced RhoA kinasedependent (ROCK) phosphorylation at vimentin S71, which lead to filament reorganisation and inhibition of cell migration. Together these studies shed new light into the regulation of nestin and vimentin during cell motility.

Network connectance and autonomy analyses of the photosynthetic apparatus in tropical tree species from different successional groups under contrasting irradiance conditions

Biological systems are complex dynamical systems whose relationships with environment have strong implications on their regulation and survival. From the interactions between plant and environment can emerge a quite complex network of plant responses rarely observed through classical analytical approaches. The objective of this current study was to test the hypothesis that photosynthetic responses of different tree species to increasing irradiance are related to changes in network connectances of gas exchange and photochemical apparatus, and alterations in plant autonomy in relation to the environment. The heat dissipative capacity through daily changes in leaf temperature was also evaluated. It indicated that the early successional species (Citharexylum myrianthum Cham. and Rhamnidium elaeocarpum Reiss.) were more efficient as dissipative structures than the late successional one (Cariniana legalis (Mart.) Kuntze), suggesting that the parameter deltaT (T ºCair - T ºCleaf) could be a simple tool in order to help the classification of successional classes of tropical trees. Our results indicated a pattern of network responses and autonomy changes under high irradiance. Considering the maintenance of daily CO2 assimilation, the tolerant species (C. myrianthum and R. elaeocarpum) to high irradiance trended to maintain stable the level of gas exchange network connectance and to increase the autonomy in relation to the environment. On the other hand, the late successional species (C. legalis) trended to lose autonomy, decreasing the network connectance of gas exchange. All species showed lower autonomy and higher network connectance of the photochemical apparatus under high irradiance.

LVDC power distribution system: computational modelling

In the doctoral dissertation, low-voltage direct current (LVDC) distribution system stability, supply security and power quality are evaluated by computational modelling and measurements on an LVDC research platform. Computational models for the LVDC network analysis are developed. Time-domain simulation models are implemented in the time-domain simulation environment PSCAD/EMTDC. The PSCAD/EMTDC models of the LVDC network are applied to the transient behaviour and power quality studies. The LVDC network power loss model is developed in a MATLAB environment and is capable of fast estimation of the network and component power losses. The model integrates analytical equations that describe the power loss mechanism of the network components with power flow calculations. For an LVDC network research platform, a monitoring and control software solution is developed. The solution is used to deliver measurement data for verification of the developed models and analysis of the modelling results. In the work, the power loss mechanism of the LVDC network components and its main dependencies are described. Energy loss distribution of the LVDC network components is presented. Power quality measurements and current spectra are provided and harmonic pollution on the DC network is analysed. The transient behaviour of the network is verified through time-domain simulations. DC capacitor guidelines for an LVDC power distribution network are introduced. The power loss analysis results show that one of the main optimisation targets for an LVDC power distribution network should be reduction of the no-load losses and efficiency improvement of converters at partial loads. Low-frequency spectra of the network voltages and currents are shown, and harmonic propagation is analysed. Power quality in the LVDC network point of common coupling (PCC) is discussed. Power quality standard requirements are shown to be met by the LVDC network. The network behaviour during transients is analysed by time-domain simulations. The network is shown to be transient stable during large-scale disturbances. Measurement results on the LVDC research platform proving this are presented in the work.

The brain decade in debate: I. Neurobiology of learning and memory

This article is a transcription of an electronic symposium in which some active researchers were invited by the Brazilian Society for Neuroscience and Behavior (SBNeC) to discuss the last decade's advances in neurobiology of learning and memory. The way different parts of the brain are recruited during the storage of different kinds of memory (e.g., short-term vs long-term memory, declarative vs procedural memory) and even the property of these divisions were discussed. It was pointed out that the brain does not really store memories, but stores traces of information that are later used to create memories, not always expressing a completely veridical picture of the past experienced reality. To perform this process different parts of the brain act as important nodes of the neural network that encode, store and retrieve the information that will be used to create memories. Some of the brain regions are recognizably active during the activation of short-term working memory (e.g., prefrontal cortex), or the storage of information retrieved as long-term explicit memories (e.g., hippocampus and related cortical areas) or the modulation of the storage of memories related to emotional events (e.g., amygdala). This does not mean that there is a separate neural structure completely supporting the storage of each kind of memory but means that these memories critically depend on the functioning of these neural structures. The current view is that there is no sense in talking about hippocampus-based or amygdala-based memory since this implies that there is a one-to-one correspondence. The present question to be solved is how systems interact in memory. The pertinence of attributing a critical role to cellular processes like synaptic tagging and protein kinase A activation to explain the memory storage processes at the cellular level was also discussed.

Development of an Ecology-Oriented Software-Defined Networking Framework

ICT contributed to about 0.83 GtCO2 emissions where the 37% comes from the telecoms infrastructures. At the same time, the increasing cost of energy has been hindering the industry in providing more affordable services for the users. One of the sources of these problems is said to be the rigidity of the current network infrastructures which limits innovations in the network. SDN (Software Defined Network) has emerged as one of the prominent solutions with its idea of abstraction, visibility, and programmability in the network. Nevertheless, there are still significant efforts needed to actually utilize it to create a more energy and environmentally friendly network. In this paper, we suggested and developed a platform for developing ecology-related SDN applications. The main approach we take in realizing this goal is by maximizing the abstractions provided by OpenFlow and to expose RESTful interfaces to modules which enable energy saving in the network. While OpenFlow is made to be the standard for SDN protocol, there are still some mechanisms not defined in its specification such as settings related to Quality of Service (QoS). To solve this, we created REST interfaces for setting of QoS in the switches which can maximize network utilization. We also created a module for minimizing the required network resources in delivering packets across the network. This is achieved by utilizing redundant links when it is needed, but disabling them when the load in the network decreases. The usage of multi paths in a network is also evaluated for its benefit in terms of transfer rate improvement and energy savings. Hopefully, the developed framework can be beneficial for developers in creating applications for supporting environmentally friendly network infrastructures.

The influence of high cable penetration in distribution networks on earth fault currents and the operation of relay protection.

Recent Storms in Nordic countries were a reason of long power outages in huge territories. After these disasters distribution networks' operators faced with a problem how to provide adequate quality of supply in such situation. The decision of utilization cable lines rather than overhead lines were made, which brings new features to distribution networks. The main idea of this work is a complex analysis of medium voltage distribution networks with long cable lines. High value of cable’s specific capacitance and length of lines determine such problems as: high values of earth fault currents, excessive amount of reactive power flow from distribution to transmission network, possibility of a high voltage level at the receiving end of cable feeders. However the core tasks was to estimate functional ability of the earth fault protection and the possibility to utilize simplified formulas for operating setting calculations in this network. In order to provide justify solution or evaluation of mentioned above problems corresponding calculations were made and in order to analyze behavior of relay protection principles PSCAD model of the examined network have been created. Evaluation of the voltage rise in the end of a cable line have educed absence of a dangerous increase in a voltage level, while excessive value of reactive power can be a reason of final penalty according to the Finish regulations. It was proved and calculated that for this networks compensation of earth fault currents should be implemented. In PSCAD models of the electrical grid with isolated neutral, central compensation and hybrid compensation were created. For the network with hybrid compensation methodology which allows to select number and rated power of distributed arc suppression coils have been offered. Based on the obtained results from experiments it was determined that in order to guarantee selective and reliable operation of the relay protection should be utilized hybrid compensation with connection of high-ohmic resistor. Directional and admittance based relay protection were tested under these conditions and advantageous of the novel protection were revealed. However, for electrical grids with extensive cabling necessity of a complex approach to the relay protection were explained and illustrated. Thus, in order to organize reliable earth fault protection is recommended to utilize both intermittent and conventional relay protection with operational settings calculated by the use of simplified formulas.

Rheological and structural evaluations of commercial italian salad dressings

The emulsion stability, composition, structure and rheology of four different commercial italian salad dressings manufactured with traditional and light formulations were evaluated. According to the results, the fat content ranged from 8% (w/w) (light) to 34% (w/w) (traditional), the carbohydrate concentration varied between 3.8% (w/w) (traditional) and 14.4% (w/w) (light) and the pH was between 3.6-3.9 for all samples. The microscopic and stability analyses showed that the only stable salad dressing was a light sample, which had the smallest droplet size when compared with the other samples. With respect to the rheological behaviour, all the salad dressings were characterized as thixotropic and shear thinning fluids. However, the stable dressing showed an overshoot at relatively low shear rates. This distinct rheological behavior being explained by the differences in its composition, particularly the presence of a maltodextrin network.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

The Role Of Social Networks In New Venture Internationalization: Case Of Russian And Finnish Firms

The purpose of current master thesis research is to investigate the role of social networks in internationalization of Russian and Finnish firms. Literature review of existing empirical researches on the topic is conducted in order to identify the gap, which is fulfilled by empirical research of 4 Russian and 1 Finnish firm that have established international operations no later than 8 years since their foundation. In-depth semi-structured interviews have shown that business network has been an influencing factor in firms’ internationalization and that even if social network is not the driver of internationalization, it becomes important when a company has established international presence and is working on its enlargement. The study has both theoretical and practical contribution by contributing to research of Russian and Finnish firms’ internationalization and by showing examples of successful foreign market entry of companies from different industries. General practical implication of current thesis is that it shows the efficient ways of entrepreneurs’ social network usage in business development in international scope.

Properties and Algorithms of the KCube Graphs

The KCube interconnection topology was rst introduced in 2010. The KCube graph is a compound graph of a Kautz digraph and hypercubes. Compared with the at- tractive Kautz digraph and well known hypercube graph, the KCube graph could accommodate as many nodes as possible for a given indegree (and outdegree) and the diameter of interconnection networks. However, there are few algorithms designed for the KCube graph. In this thesis, we will concentrate on nding graph theoretical properties of the KCube graph and designing parallel algorithms that run on this network. We will explore several topological properties, such as bipartiteness, Hamiltonianicity, and symmetry property. These properties for the KCube graph are very useful to develop efficient algorithms on this network. We will then study the KCube network from the algorithmic point of view, and will give an improved routing algorithm. In addition, we will present two optimal broadcasting algorithms. They are fundamental algorithms to many applications. A literature review of the state of the art network designs in relation to the KCube network as well as some open problems in this field will also be given.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.