89 resultados para DYNAMIC FOREST DATA STRUCTURES
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Family businesses are among the longest-lived most prevalent institutions in the world and they are an important source of economic development and growth. Ownership is a key to the business life of the firm and also one main key in family business definition. There is only a little portfolio entrepreneurship or portfolio business research within family business context. The absence of empirical evidence on the long-term relationship between family ownership and portfolio development presents an important gap in the family business literature. This study deals with the family business ownership changes and the development of portfolios in the family business and it is positioned in to the conversation of family business, growth, ownership, management and strategy. This study contributes and expands the existing body of theory on family business and ownership. From the theoretical point of view this study combines insights from the fields of portfolio entrepreneurship, ownership, and family business and integrate them. This crossfertilization produces interesting empirical and theoretical findings that can constitute a basis for solid contributions to the understanding of ownership dynamics and portfolio entrepreneurship in family firms. The research strategy chosen for this study represents longitudinal, qualitative, hermeneutic, and deductive approaches.The empirical part of study is using a case study approach with embedded design, that is, multiple levels of analysis within a single study. The study consists of two cases and it begins with a pilot case which will form a preunderstanding on the phenomenon. Pilot case develops the methodology approach to build in the main case and the main case will deepen the understanding of the phenomenon. This study develops and tests a research method of family business portfolio development focusing on investigating how ownership changes are influencing to the family business structures over time. This study reveals the linkages between dimensions of ownership and how they give rise to portfolio business development within the context of the family business. The empirical results of the study suggest that family business ownership is dynamic and owners are using ownership as a tool for creating business portfolios.
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Glass is a unique material with a long history. Several glass products are used daily in our everyday life, often unnoticed. Glass can be found not only in obvious applications such as tableware, windows, and light bulbs, but also in tennis rackets, windmill turbine blades, optical devices, and medical implants. The glasses used at present as implants are inorganic silica-based melt-derived compositions mainly for hard-tissue repair as bone graft substitute in dentistry and orthopedics. The degree of glass reactivity desired varies according to implantation situation and it is vital that the ion release from any glasses used in medical applications is controlled. Understanding the in vitro dissolution rate of glasses provides a first approximation of their behavior in vivo. Specific studies concerning dissolution properties of bioactive glasses have been relatively scarce and mostly concentrated to static condition studies. The motivation behind this work was to develop a simple and accurate method for quantifying the in vitro dissolution rate of highly different types of glass compositions with interest for future clinical applications. By combining information from various experimental conditions, a better knowledge of glass dissolution and the suitability of different glasses for different medical applications can be obtained. Thus, two traditional and one novel approach were utilized in this thesis to study glass dissolution. The chemical durability of silicate glasses was tested in water and TRIS-buffered solution at static and dynamic conditions. The traditional in vitro testing with a TRISbuffered solution under static conditions works well with bioactive or with readily dissolving glasses, and it is easy to follow the ion dissolution reactions. However, in the buffered solution no marked differences between the more durable glasses were observed. The hydrolytic resistance of the glasses was studied using the standard procedure ISO 719. The relative scale given by the standard failed to provide any relevant information when bioactive glasses were studied. However, the clear differences in the hydrolytic resistance values imply that the method could be used as a rapid test to get an overall idea of the biodegradability of glasses. The standard method combined with the ion concentration and pH measurements gives a better estimate of the hydrolytic resistance because of the high silicon amount released from a glass. A sensitive on-line analysis method utilizing inductively coupled plasma optical emission spectrometer and a flow-through micro-volume pH electrode was developed to study the initial dissolution of biocompatible glasses. This approach was found suitable for compositions within a large range of chemical durability. With this approach, the initial dissolution of all ions could be measured simultaneously and quantitatively, which gave a good overall idea of the initial dissolution rates for the individual ions and the dissolution mechanism. These types of results with glass dissolution were presented for the first time during the course of writing this thesis. Based on the initial dissolution patterns obtained with the novel approach using TRIS, the experimental glasses could be divided into four distinct categories. The initial dissolution patterns of glasses correlated well with the anticipated bioactivity. Moreover, the normalized surface-specific mass loss rates and the different in vivo models and the actual in vivo data correlated well. The results suggest that this type of approach can be used for prescreening the suitability of novel glass compositions for future clinical applications. Furthermore, the results shed light on the possible bioactivity of glasses. An additional goal in this thesis was to gain insight into the phase changes occurring during various heat treatments of glasses with three selected compositions. Engineering-type T-T-T curves for glasses 1-98 and 13-93 were stablished. The information gained is essential in manufacturing amorphous porous implants or for drawing of continuous fibers of the glasses. Although both glasses can be hot worked to amorphous products at carefully controlled conditions, 1-98 showed one magnitude greater nucleation and crystal growth rate than 13-93. Thus, 13-93 is better suited than 1-98 for working processes which require long residence times at high temperatures. It was also shown that amorphous and partially crystalline porous implants can be sintered from bioactive glass S53P4. Surface crystallization of S53P4, forming Na2O∙CaO∙2SiO2, was observed to start at 650°C. The secondary crystals of Na2Ca4(PO4)2SiO4, reported for the first time in this thesis, were detected at higher temperatures, from 850°C to 1000°C. The crystal phases formed affected the dissolution behavior of the implants in simulated body fluid. This study opens up new possibilities for using S53P4 to manufacture various structures, while tailoring their bioactivity by controlling the proportions of the different phases. The results obtained in this thesis give valuable additional information and tools to the state of the art for designing glasses with respect to future clinical applications. With the knowledge gained we can identify different dissolution patters and use this information to improve the tuning of glass compositions. In addition, the novel online analysis approach provides an excellent opportunity to further enhance our knowledge of glass behavior in simulated body conditions.
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Modern machine structures are often fabricated by welding. From a fatigue point of view, the structural details and especially, the welded details are the most prone to fatigue damage and failure. Design against fatigue requires information on the fatigue resistance of a structure’s critical details and the stress loads that act on each detail. Even though, dynamic simulation of flexible bodies is already current method for analyzing structures, obtaining the stress history of a structural detail during dynamic simulation is a challenging task; especially when the detail has a complex geometry. In particular, analyzing the stress history of every structural detail within a single finite element model can be overwhelming since the amount of nodal degrees of freedom needed in the model may require an impractical amount of computational effort. The purpose of computer simulation is to reduce amount of prototypes and speed up the product development process. Also, to take operator influence into account, real time models, i.e. simplified and computationally efficient models are required. This in turn, requires stress computation to be efficient if it will be performed during dynamic simulation. The research looks back at the theoretical background of multibody dynamic simulation and finite element method to find suitable parts to form a new approach for efficient stress calculation. This study proposes that, the problem of stress calculation during dynamic simulation can be greatly simplified by using a combination of floating frame of reference formulation with modal superposition and a sub-modeling approach. In practice, the proposed approach can be used to efficiently generate the relevant fatigue assessment stress history for a structural detail during or after dynamic simulation. In this work numerical examples are presented to demonstrate the proposed approach in practice. The results show that approach is applicable and can be used as proposed.
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Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.
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In many industrial applications, such as the printing and coatings industry, wetting of porous materials by liquids includes not only imbibition and permeation into the bulk but also surface spreading and evaporation. By understanding these phenomena, valuable information can be obtained for improved process control, runnability and printability, in which liquid penetration and subsequent drying play important quality and economic roles. Knowledge of the position of the wetting front and the distribution/degree of pore filling within the structure is crucial in describing the transport phenomena involved. Although exemplifying paper as a porous medium in this work, the generalisation to dynamic liquid transfer onto a surface, including permeation and imbibition into porous media, is of importance to many industrial and naturally occurring environmental processes. This thesis explains the phenomena in the field of heatset web offset printing but the content and the analyses are applicable in many other printing methods and also other technologies where water/moisture monitoring is crucial in order to have a stable process and achieve high quality end products. The use of near-infrared technology to study the water and moisture response of porous pigmented structures is presented. The use of sensitive surface chemical and structural analysis, as well as the internal structure investigation of a porous structure, to inspect liquid wetting and distribution, complements the information obtained by spectroscopic techniques. Strong emphasis has been put on the scale of measurement, to filter irrelevant information and to understand the relationship between interactions involved. The near-infrared spectroscopic technique, presented here, samples directly the changes in signal absorbance and its variation in the process at multiple locations in a print production line. The in-line non-contact measurements are facilitated by using several diffuse reflectance probes, giving the absolute water/moisture content from a defined position in the dynamic process in real-time. The nearinfrared measurement data illustrate the changes in moisture content as the paper is passing through the printing nips and dryer, respectively, and the analysis of the mechanisms involved highlight the roles of the contacting surfaces and the relative liquid carrier properties of both non-image and printed image areas. The thesis includes laboratory studies on wetting of porous media in the form of coated paper and compressed pigment tablets by mono-, dual-, and multi-component liquids, and paper water/moisture content analysis in both offline and online conditions, thus also enabling direct sampling of temporal water/moisture profiles from multiple locations. One main focus in this thesis was to establish a measurement system which is able to monitor rapid changes in moisture content of paper. The study suggests that near-infrared diffuse reflectance spectroscopy can be used as a moisture sensitive system and to provide accurate online qualitative indicators, but, also, when accurately calibrated, can provide quantification of water/moisture levels, its distribution and dynamic liquid transfer. Due to the high sensitivity, samples can be measured with excellent reproducibility and good signal to noise ratio. Another focus of this thesis was on the evolution of the moisture content, i.e. changes in moisture content referred to (re)wetting, and liquid distribution during printing of coated paper. The study confirmed different wetting phases together with the factors affecting each phase both for a single droplet and a liquid film applied on a porous substrate. For a single droplet, initial capillary driven imbibition is followed by equilibrium pore filling and liquid retreat by evaporation. In the case of a liquid film applied on paper, the controlling factors defining the transportation were concluded to be the applied liquid volume in relation to surface roughness, capillarity and permeability of the coating giving the liquid uptake capacity. The printing trials confirmed moisture gradients in the printed sheet depending on process parameters such as speed, fountain solution dosage and drying conditions as well as the printed layout itself. Uneven moisture distribution in the printed sheet was identified to be one of the sources for waving appearance and the magnitude of waving was influenced by the drying conditions.
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This study examines the use of di erent features derived from remotely sensed data in segmentation of forest stands. Surface interpolation methods were applied to LiDAR points in order to represent data in the form of grayscale images. Median and mean shift ltering was applied to the data for noise reduction. The ability of di erent compositions of rasters obtained from LiDAR data and an aerial image to maximize stand homogeneity in the segmentation was evaluated. The quality of forest stand delineations was assessed by the Akaike information criterion. The research was performed in co-operation with Arbonaut Ltd., Joensuu, Finland.
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This thesis examined both domestic and international forest investment options for a Finnish non-industrial private forest investor. The focus was on forest-based investment instruments. The influence of movements of currency exchange rates on foreign returns were also taken into account. Annual data from 1995 to 2011 was used. The main portfolio optimization model in this study was the Mean-Variance model but the results were also validated by using the Value at Risk and Expected Shortfall models. In addition, the exchange rate risk hedging was established by using one-week-maturity forward contracts. The results suggested that 75 % of the total wealth should be invested in Finnish private forests and the rest, 25 %, to a US REIT, in this case Rayonier. With hedging, the total return on the portfolio was 7.21 % (NIPF 5.3%) with the volatility of 6.63 % (NIPF 7.9%). Taxation supported US investments in this case. As a conclusion, a Finnish private forest investor may, as evidenced, benefit in diversifying a portfolio using REITs in the US.
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This study focuses on the relationship between organizational network competence and the internationalization process of small- and medium sized enterprises (SMEs). Over recent decades, the global business environment has become increasingly conducive to internationalization of small firms. A central facilitating factor in the process has been the emergence of networked business relationships between internationalizing firms. Research on SME internationalization has found that certain types of structures and dynamics of business networks allow SMEs access to the resources they need to enter foreign markets. This consequently means that their internationalization often becomes to depend on the networks they are embedded in. However, research so far has mostly ignored the possibility that the organizational ability to develop and manage business network relationships, network competence, may be a major underlying factor in determining how well SMEs can leverage their network relationships to enter foreign markets and consequently may determine in large part how successful their internationalization process turns out to be. This study aims to respond to those gaps, by empirically examining how the development of network competence in internationalizing SMEs influences the internationalization outcomes that they can expect, and how such network competence is conceptualized and developed. Using a mixed methods approach, survey data collected from 298 Finnish SMEs across five industry sectors is first used to examine how levels of network competence are related to internationalization propensity of SMEs and their subsequent international performance, growth and profitability as internationally operating firms. In order to illustrate in more detail the ways in which network competence is conceptualized and how it develops during the internationalization process of an SME, qualitative data from internationally operating Finnish SMEs are used. Longitudinal interview data of an internationalizing Finnish SME is accompanied by data gathered through a series of semistructured interviews of Finnish and Russian managers involved in mutual business relationship dyads. Structurally, this thesis examines the research issue as an article-based dissertation, consisting of five journal and conference publications. Three of these publications are based on the quantitative data, and the remaining two apply the qualitative interview data. The results find several aspects where network competence has a positive influence on the success of internationalizing SMEs, how it develops and what it entails conceptually in this context. Quantitatively, the level of network competence is found to have a positive relationship to various internationalization outcomes, including the propensity of SMEs to enter foreign markets and on their subsequent international performance, their growth and their profitability. Additionally, the positive relationship is divided between the relationship-specific and cross-relational dimension of network competence, in that the influence of the former is relevant for the propensity to internationalize, while the latter is for the growth and profitability of the already internationalized SMEs. Qualitatively, the results suggest, firstly, that the development process of network competence does not necessarily precede the start of the internationalization process, but may occur through a gradual learning process alongside it. And secondly, the results also imply that the conceptualization of network competence by Finnish managers of internationally operating Finnish SMEs is structurally distinct from that of their culturally distinct partner managers in Russia. This study contributes to the literature on SME internationalization in several ways. Firstly, it introduces operationalized organizational competencies to the literature on internationalization of SMEs, which has so far mainly examined the influence of business networking on the internationalization process without having such an organizational viewpoint. Furthermore, this study provides a multi-level analysis of the determinants of successful SME internationalization, by examining various strategic and performance outcomes across the process. These results also contribute to the literature on organizational strategy of internationalizing SMEs, by clarifying how different dimensions of business networking may be optimal in different phases of the internationalization process. Conceptually, the results of this study contribute to the literature on competence development and SME internationalization, by illustrating how the development process of network competence may occur during internationalization process. Thus, they also contribute to the discussion on how SMEs are able to influence the dynamics and structures of their business networks over time. Finally, this study contributes to the literature on the role of culture in the internationalization process, by implying that the cultural background of the manager of the SME may determine whether business networking and network competence is seen as an organizational-level or an individual level capability. The study also includes some additional contributions to the literature on dynamic capabilities in strategic management, and on that of strategic business networks. These include further clarifying the exact nature and tangibility of dynamic capabilities, and being one of the first studies to introduce constructs from both dynamic capabilities and business network literature to the field of international entrepreneurship. And finally, the study also has some contribution on the two streams of literature, in illustrating how both dyadic and network-level capabilities may be relevant, depending on the current strategic goals and market position of the firm. Keywords: network competence, internationalizatio
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.
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Recently, due to the increasing total construction and transportation cost and difficulties associated with handling massive structural components or assemblies, there has been increasing financial pressure to reduce structural weight. Furthermore, advances in material technology coupled with continuing advances in design tools and techniques have encouraged engineers to vary and combine materials, offering new opportunities to reduce the weight of mechanical structures. These new lower mass systems, however, are more susceptible to inherent imbalances, a weakness that can result in higher shock and harmonic resonances which leads to poor structural dynamic performances. The objective of this thesis is the modeling of layered sheet steel elements, to accurately predict dynamic performance. During the development of the layered sheet steel model, the numerical modeling approach, the Finite Element Analysis and the Experimental Modal Analysis are applied in building a modal model of the layered sheet steel elements. Furthermore, in view of getting a better understanding of the dynamic behavior of layered sheet steel, several binding methods have been studied to understand and demonstrate how a binding method affects the dynamic behavior of layered sheet steel elements when compared to single homogeneous steel plate. Based on the developed layered sheet steel model, the dynamic behavior of a lightweight wheel structure to be used as the structure for the stator of an outer rotor Direct-Drive Permanent Magnet Synchronous Generator designed for high-power wind turbines is studied.
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Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.
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This doctoral dissertation explores the intra-organizational dynamics of a strategic renewal process. The main research question is how the pursuit of change and organizational inertia co-exist, intertwine, and collide in organizational cognition and capabilities during the strategic renewal. It is a comprehensive study on how organizational capabilities, organizational cognition, and structure enhance and inhibit change. Theoretically, the study is positioned in the modern tradition of strategy research, using the dynamic capability view and the organizational and managerial cognition research tradition as the main theoretical frames. Empirically, the study is a longitudinal case study of the Finnish Broadcasting Company (Yle), following the organizational changes during the years of 2011-1014. The analysis is based on both quantitative and qualitative data, which was collected during the research process using surveys, interviews, and archives. The main theoretical contribution is the application of the two theoretical approaches in one study. Empirically, the study contributes to operationalization of the concepts related to the dynamic capability view and organizational cognition, in a media context that is going through drastic changes due to digitalization. Furthermore, the case of a public broadcasting company extends the application of the theoretical concepts to the context of public management. The results suggest that renewal is a complex process, in which an organization’s perceptions intertwine with the strategic actions and decision-making. The change evolves pathdependently: the past experiences, routines, and organizational structures tend to dictate the future visions, desires, and actions. The study also reveals how the public nature of an organization adds to the tensions between change and organizational inertia, and hampers the decision-making. The doctoral dissertation consists of six research papers, each of which explores the phenomenon under study from a different perspective.