Inversion and assimilation methods with applications in geophysical remote sensing

Stratospheric ozone can be measured accurately using a limb scatter remote sensing technique at the UV-visible spectral region of solar light. The advantages of this technique includes a good vertical resolution and a good daytime coverage of the measurements. In addition to ozone, UV-visible limb scatter measurements contain information about NO2, NO3, OClO, BrO and aerosols. There are currently several satellite instruments continuously scanning the atmosphere and measuring the UVvisible region of the spectrum, e.g., the Optical Spectrograph and Infrared Imager System (OSIRIS) launched on the Odin satellite in February 2001, and the Scanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) launched on Envisat in March 2002. Envisat also carries the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, which also measures limb-scattered sunlight under bright limb occultation conditions. These conditions occur during daytime occultation measurements. The global coverage of the satellite measurements is far better than any other ozone measurement technique, but still the measurements are sparse in the spatial domain. Measurements are also repeated relatively rarely over a certain area, and the composition of the Earth’s atmosphere changes dynamically. Assimilation methods are therefore needed in order to combine the information of the measurements with the atmospheric model. In recent years, the focus of assimilation algorithm research has turned towards filtering methods. The traditional Extended Kalman filter (EKF) method takes into account not only the uncertainty of the measurements, but also the uncertainty of the evolution model of the system. However, the computational cost of full blown EKF increases rapidly as the number of the model parameters increases. Therefore the EKF method cannot be applied directly to the stratospheric ozone assimilation problem. The work in this thesis is devoted to the development of inversion methods for satellite instruments and the development of assimilation methods used with atmospheric models.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.

Introducing massively parallel computers into operational weather forecasting

Numerical weather prediction and climate simulation have been among the computationally most demanding applications of high performance computing eversince they were started in the 1950's. Since the 1980's, the most powerful computers have featured an ever larger number of processors. By the early 2000's, this number is often several thousand. An operational weather model must use all these processors in a highly coordinated fashion. The critical resource in running such models is not computation, but the amount of necessary communication between the processors. The communication capacity of parallel computers often fallsfar short of their computational power. The articles in this thesis cover fourteen years of research into how to harness thousands of processors on a single weather forecast or climate simulation, so that the application can benefit as much as possible from the power of parallel high performance computers. The resultsattained in these articles have already been widely applied, so that currently most of the organizations that carry out global weather forecasting or climate simulation anywhere in the world use methods introduced in them. Some further studies extend parallelization opportunities into other parts of the weather forecasting environment, in particular to data assimilation of satellite observations.

On Variational Ensemble Kalman Filtering

The Extended Kalman Filter (EKF) and four dimensional assimilation variational method (4D-VAR) are both advanced data assimilation methods. The EKF is impractical in large scale problems and 4D-VAR needs much effort in building the adjoint model. In this work we have formulated a data assimilation method that will tackle the above difficulties. The method will be later called the Variational Ensemble Kalman Filter (VEnKF). The method has been tested with the Lorenz95 model. Data has been simulated from the solution of the Lorenz95 equation with normally distributed noise. Two experiments have been conducted, first with full observations and the other one with partial observations. In each experiment we assimilate data with three-hour and six-hour time windows. Different ensemble sizes have been tested to examine the method. There is no strong difference between the results shown by the two time windows in either experiment. Experiment I gave similar results for all ensemble sizes tested while in experiment II, higher ensembles produce better results. In experiment I, a small ensemble size was enough to produce nice results while in experiment II the size had to be larger. Computational speed is not as good as we would want. The use of the Limited memory BFGS method instead of the current BFGS method might improve this. The method has proven succesful. Even if, it is unable to match the quality of analyses of EKF, it attains significant skill in forecasts ensuing from the analysis it has produced. It has two advantages over EKF; VEnKF does not require an adjoint model and it can be easily parallelized.

Kalman Filtering in Online Paper Quality Assessment

Controlling the quality variables (such as basis weight, moisture etc.) is a vital part of making top quality paper or board. In this thesis, an advanced data assimilation tool is applied to the quality control system (QCS) of a paper or board machine. The functionality of the QCS is based on quality observations that are measured with a traversing scanner making a zigzag path. The basic idea is the following: The measured quality variable has to be separated into its machine direction (MD) and cross direction (CD) variations due to the fact that the QCS works separately in MD and CD. Traditionally this is done simply by assuming one scan of the zigzag path to be the CD profile and its mean value to be one point of the MD trend. In this thesis, a more advanced method is introduced. The fundamental idea is to use the signals’ frequency components to represent the variation in both CD and MD. To be able to get to the frequency domain, the Fourier transform is utilized. The frequency domain, that is, the Fourier components are then used as a state vector in a Kalman filter. The Kalman filter is a widely used data assimilation tool to combine noisy observations with a model. The observations here refer to the quality measurements and the model to the Fourier frequency components. By implementing the two dimensional Fourier transform into the Kalman filter, we get an advanced tool for the separation of CD and MD components in total variation or, to be more general, for data assimilation. A piece of a paper roll is analyzed and this tool is applied to model the dataset. As a result, it is clear that the Kalman filter algorithm is able to reconstruct the main features of the dataset from a zigzag path. Although the results are made with a very short sample of paper roll, it seems that this method has great potential to be used later on as a part of the quality control system.

Simulating the performance of paper machine control

The topic of this thesis is the simulation of a combination of several control and data assimilation methods, meant to be used for controlling the quality of paper in a paper machine. Paper making is a very complex process and the information obtained from the web is sparse. A paper web scanner can only measure a zig zag path on the web. An assimilation method is needed to process estimates for Machine Direction (MD) and Cross Direction (CD) profiles of the web. Quality control is based on these measurements. There is an increasing need for intelligent methods to assist in data assimilation. The target of this thesis is to study how such intelligent assimilation methods are affecting paper web quality. This work is based on a paper web simulator, which has been developed in the TEKES funded MASI NoTes project. The simulator is a valuable tool in comparing different assimilation methods. The thesis contains the comparison of four different assimilation methods. These data assimilation methods are a first order Bayesian model estimator, an ARMA model based on a higher order Bayesian estimator, a Fourier transform based Kalman filter estimator and a simple block estimator. The last one can be considered to be close to current operational methods. From these methods Bayesian, ARMA and Kalman all seem to have advantages over the commercial one. The Kalman and ARMA estimators seems to be best in overall performance.

NADPH-Dependent Thioredoxin System In Regulation of Chloroplast Functions

Photosynthesis, the process in which carbon dioxide is converted into sugars using the energy of sunlight, is vital for heterotrophic life on Earth. In plants, photosynthesis takes place in specific organelles called chloroplasts. During chloroplast biogenesis, light is a prerequisite for the development of functional photosynthetic structures. In addition to photosynthesis, a number of other metabolic processes such as nitrogen assimilation, the biosynthesis of fatty acids, amino acids, vitamins, and hormones are localized to plant chloroplasts. The biosynthetic pathways in chloroplasts are tightly regulated, and especially the reduction/oxidation (redox) signals play important roles in controlling many developmental and metabolic processes in chloroplasts. Thioredoxins are universal regulatory proteins that mediate redox signals in chloroplasts. They are able to modify the structure and function of their target proteins by reduction of disulfide bonds. Oxidized thioredoxins are restored via the action of thioredoxin reductases. Two thioredoxin reductase systems exist in plant chloroplasts, the NADPHdependent thioredoxin reductase C (NTRC) and ferredoxin-thioredoxin reductase (FTR). The ferredoxin-thioredoxin system that is linked to photosynthetic light reactions is involved in light-activation of chloroplast proteins. NADPH can be produced via both the photosynthetic electron transfer reactions in light, and in darkness via the pentose phosphate pathway. These different pathways of NADPH production enable the regulation of diverse metabolic pathways in chloroplasts by the NADPH-dependent thioredoxin system. In this thesis, the role of NADPH-dependent thioredoxin system in the redox-control of chloroplast development and metabolism was studied by characterization of Arabidopsis thaliana T-DNA insertion lines of NTRC gene (ntrc) and by identification of chloroplast proteins regulated by NTRC. The ntrc plants showed the strongest visible phenotypes when grown under short 8-h photoperiod. This indicates that i) chloroplast NADPH-dependent thioredoxin system is non-redundant to ferredoxinthioredoxin system and that ii) NTRC particularly controls the chloroplast processes that are easily imbalanced in daily light/dark rhythms with short day and long night. I identified four processes and the redox-regulated proteins therein that are potentially regulated by NTRC; i) chloroplast development, ii) starch biosynthesis, iii) aromatic amino acid biosynthesis and iv) detoxification of H₂O₂. Such regulation can be achieved directly by modulating the redox state of intramolecular or intermolecular disulfide bridges of enzymes, or by protecting enzymes from oxidation in conjunction with 2-cysteine peroxiredoxins. This thesis work also demonstrated that the enzymatic antioxidant systems in chloroplasts, ascorbate peroxidases, superoxide dismutase and NTRC-dependent 2-cysteine peroxiredoxins are tightly linked up to prevent the detrimental accumulation of reactive oxygen species in plants.

Enhancing absorptive capacity in a non-research and development. An action research approach to converting individual observations into organisational awareness

The ability to recognize potential knowledge and convert it into business opportunities is one of the key factors of renewal in uncertain environments. This thesis examines absorptive capacity in the context of non-research and development innovation, with a primary focus on the social interaction that facilitates the absorption of knowledge. It proposes that everyone is and should be entitled to take part in the social interaction that shapes individual observations into innovations. Both innovation and absorptive capacity have been traditionally related to research and development departments and institutions. These innovations need to be adopted and adapted by others. This so-called waterfall model of innovations is only one aspect of new knowledge generation and innovation. In addition to this Science–Technology–Innovation perspective, more attention has been recently paid to the Doing–Using–Interacting mode of generating new knowledge and innovations. The amount of literature on absorptive capacity is vast, yet the concept is reified. The greater part of the literature links absorptive capacity to research and development departments. Some publications have focused on the nature of absorptive capacity in practice and the role of social interaction in enhancing it. Recent literature on absorptive capacity calls for studies that shed light on the relationship between individual absorptive capacity and organisational absorptive capacity. There has also been a call to examine absorptive capacity in non-research and development environments. Drawing on the literature on employee-driven innovation and social capital, this thesis looks at how individual observations and ideas are converted into something that an organisation can use. The critical phases of absorptive capacity, during which the ideas of individuals are incorporated into a group context, are assimilation and transformation. These two phases are seen as complementary: whereas assimilation is the application of easy-to-accept knowledge, transformation challenges the current way of thinking. The two require distinct kinds of social interaction and practices. The results of this study can been crystallised thus: “Enhancing absorptive capacity in practicebased non-research and development context is to organise the optimal circumstances for social interaction. Every individual is a potential source of signals leading to innovations. The individual, thus, recognises opportunities and acquires signals. Through the social interaction processes of assimilation and transformation, these signals are processed into the organisation’s reality and language. The conditions of creative social capital facilitate the interplay between assimilation and transformation. An organisation that strives for employee-driven innovation gains the benefits of a broader surface for opportunity recognition and faster absorption.” If organisations and managers become more aware of the benefits of enhancing absorptive capacity in practice, they have reason to assign resources to those practices that facilitate the creation of absorptive capacity. By recognising the underlying social mechanisms and structural features that lead either to assimilation or transformation, it is easier to balance between renewal and effective operations.

On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Virulence properties of Aggregatibacter actinomycetemcomitans biofilm and characterisation of its putative cytokine exploitation

Biofilms are surface-attached multispecies microbial communities that are embedded by their self-produced extracellular polymeric substances. This lifestyle enhances the survival of the bacteria and plays a major role in many chronic bacterial infections. For instance, periodontitis is initiated by multispecies biofilms. The phases of active periodontal tissue destruction and notably increased levels of proinflammatory mediators, such as the key inflammatory mediator interleukin (IL)-1beta, are typical of the disease. The opportunistic periodontal pathogen Aggregatibacter actinomycetemcomitans is usually abundant at sites of aggressive periodontitis. Despite potent host immune system responses to subgingival invaders, A. actinomycetemcomitans is able to resist clearance attempts. Moreover, some strains of A. actinomycetemcomitans can generate genetic diversity through natural transformation, which may improve the species’ adjustment tothe subgingival environment in the long term. Some biofilm forming species are known to bind and sense human cytokines. As a response to cytokines, bacteria may increase biofilm formation and alter their expression of virulence genes. Specific outer membrane receptors for interferon-γ or IL-1β have been characterised in two Gram-negative pathogens. Because little is known about periodontal pathogens’ ability to sense cytokines, we used A. actinomycetemcomitans as a model organism to investigate how the species responds to IL-1beta. The main aims of this thesis were to explore cytokine binding on single-species A. actinomycetemcomitans biofilms and to determine the effects of cytokines on the biofilm formation and metabolic activity of the species. Additionally, the cytokine’s putative internalisation and interaction with A. actinomycetemcomitans proteins were studied. The possible impact of biofilm IL-1beta sequestering on the proliferation and apoptosis of gingival keratinocyte cells was evaluated in an organotypic mucosa co-culture model. Finally, the role of the extramembranous domain of the outer membrane protein HofQ (emHofQ) in DNA binding linked to DNA uptake in A. actinomycetemcomitans was examined. Our main finding revealed that viable A. actinomycetemcomitans biofilms can bind and take up the IL-1β produced by gingival cells. At the sites of pathogen-host interaction, the proliferation and apoptosis of gingival keratinocytes decreased slightly. Notably, the exposure of biofilms to IL-1beta caused their metabolic activity to drop, which may be linked to the observed interaction of IL-1beta with the conserved intracellular proteins DNA binding protein HU and the trimeric form of ATP synthase subunit beta. A Pasteurellaceaespecific lipoprotein, which had no previously determined function, was characterized as an IL-1beta interacting membrane protein that was expressed in the biofilm cultures of all tested A. actinomycetemcomitans strains. The use of a subcellular localisation tool combined with experimental analyses suggested that the identified lipoprotein, bacterial interleukin receptor I (BilRI), may be associated with the outer membrane with a portion of the protein oriented towards the external milieu. The results of the emHofQ study indicated that emHofQ has both the structural and functional capability to bind DNA. This result implies that emHofQ plays a role in DNA assimilation. The results from the current study also demonstrate that the Gram-negative oral species appears to sense the central proinflammatory mediator IL-1beta.

Characterization of Leaf-Type Ferredoxin-NADP+ Oxidoreductase (FNR) Isoforms in Arabidopsis thaliana

Life on earth is based on sunlight, which is captured in chemical form by photosynthetic reactions. In the chloroplasts of plants, light reactions of photosynthesis take place at thylakoid membranes, whereas carbon assimilation reactions occur in the soluble stroma. The products of linear electron transfer (LET), highly-energetic ATP molecules, and reducing power in the form of NADPH molecules, are further used in the fixation of inorganic CO2 molecules into organic sugars. Ferredoxin-NADP+ oxidoreductase (FNR) catalyzes the last of the light reactions by transferring electrons from ferredoxin (FD) to NADP+. In addition to LET, FNR has been suggested to play a role in cyclic electron transfer (CET), which produces ATP without the accumulation of reducing equivalents. CET is proposed to occur via two putative routes, the PGR5- route and the NDH-route. In this thesis, the leaf-type FNR (LFNR) isoforms LFNR1 and LFNR2 of a model organism, Arabidopsis thaliana, were characterized. The physiological roles of LFNRs were investigated using single and double mutant plants. The viability of the single mutants indicates functionality of both isoforms, with neither appearing to play a specific role in CET. The more severe phenotype of low-temperature adapted fnr2 plants compared to both wild-type (WT) and fnr1 plants suggests a specific role for LFNR2 under unfavorable growth conditions. The more severe phenotype of the fnr1 x fnr2 (F1 generation) plants compared to single mutants reflects down-regulated photosynthetic capacity, whereas slightly higher excitation pressure indicates mild over-excitation of electron transfer chain (ETC). However, induction of CET and various photoprotective mechanisms enable adaptation of fnr1 x fnr2 plants to scarcity of LFNR. The fnr1 fnr2 plants (F2 generation), without detectable levels of LFNR, were viable only under heterotrophic conditions. Moreover, drought stress induced acceleration of the rate of P700 + re-reduction in darkness was accompanied by a concomitant up-regulation of the PGR5-route specific components, PGR5 and PGRL1, demonstrating the induction of CET via the PGR5-route. The up-regulation of relative transcriptional expression of the FD1 gene indicates that the FD1 isoform may have a specific function in CET, while no such role could be defined for either of the LFNR isoforms. Both the membrane-bound and soluble LFNR1 and LFNR2 each appear as two distinct spots after 2D-PAGE with different isoelectric points (pIs), indicating the existence of post-translational modifications (PTMs) which do not determine the membrane attachment of LFNR. The possibility of phosphorylation and glycosylation PTMs were excluded, but all four LFNR forms were shown to contain acetylated lysine residues as well as alternative N-termini. N-terminal acetylation was shown to shift the pI of both LFNRs to be more acidic. In addition, all four LFNR forms were demonstrated to interact both with FD1 and FD2 in vitro

Molecular Mechanisms and Interactions in Regulation of Photosynthetic Reactions

In photosynthesis, light energy is converted to chemical energy, which is consumed for carbon assimilation in the Calvin-Benson-Bassham (CBB) cycle. Intensive research has significantly advanced the understanding of how photosynthesis can survive in the ever-changing light conditions. However, precise details concerning the dynamic regulation of photosynthetic processes have remained elusive. The aim of my thesis was to specify some molecular mechanisms and interactions behind the regulation of photosynthetic reactions under environmental fluctuations. A genetic approach was employed, whereby Arabidopsis thaliana mutants deficient in specific photosynthetic protein components were subjected to adverse light conditions and assessed for functional deficiencies in the photosynthetic machinery. I examined three interconnected mechanisms: (i) auxiliary functions of PsbO1 and PsbO2 isoforms in the oxygen evolving complex of photosystem II (PSII), (ii) the regulatory function of PGR5 in photosynthetic electron transfer and (iii) the involvement of the Calcium Sensing Receptor CaS in photosynthetic performance. Analysis of photosynthetic properties in psbo1 and psbo2 mutants demonstrated that PSII is sensitive to light induced damage when PsbO2, rather than PsbO1, is present in the oxygen evolving complex. PsbO1 stabilizes PSII more efficiently compared to PsbO2 under light stress. However, PsbO2 shows a higher GTPase activity compared to PsbO1, and plants may partially compensate the lack of PsbO1 by increasing the rate of the PSII repair cycle. PGR5 proved vital in the protection of photosystem I (PSI) under fluctuating light conditions. Biophysical characterization of photosynthetic electron transfer reactions revealed that PGR5 regulates linear electron transfer by controlling proton motive force, which is crucial for the induction of the photoprotective non-photochemical quenching and the control of electron flow from PSII to PSI. I conclude that PGR5 controls linear electron transfer to protect PSI against light induced oxidative damage. I also found that PGR5 physically interacts with CaS, which is not needed for photoprotection of PSII or PSI in higher plants. Rather, transcript profiling and quantitative proteomic analysis suggested that CaS is functionally connected with the CBB cycle. This conclusion was supported by lowered amounts of specific calciumregulated CBB enzymes in cas mutant chloroplasts and by slow electron flow to PSI electron acceptors when leaves were reilluminated after an extended dark period. I propose that CaS is required for calcium regulation of the CBB cycle during periods of darkness. Moreover, CaS may also have a regulatory role in the activation of chloroplast ATPase. Through their diverse interactions, components of the photosynthetic machinery ensure optimization of light-driven electron transport and efficient basic production, while minimizing the harm caused by light induced photodamage.

PK-yrityksen omistajanvaihdos tietojohtamisen näkökulmasta – tiedon jakaminen ja absorptiivinen kapasiteetti

PK-yritysten omistajanvaihdokset koskettavat vuoteen 2020 mennessä Suomessa noin 250000 ihmistä. Yhteiskunnan kannalta on tärkeää, että vaihdokset onnistuvat ja yritykset säilyttävät kilpailukykynsä, pystyvät kehittymään, kasvamaan kannattavasti ja työllistämään lisää henkilökuntaa. Työn tavoitteena on ymmärtää ja selittää PK-yrityksen omistajanvaihdosta tietojohtamisen näkökulmasta. Tutkimus toteutettiin vertailevana tapaustutkimuksena. Aineisto kerättiin puolistrukturoiduilla teemahaastatteluilla. Luopujan hiljaisen tiedon ja jatkajan yritykseen tuoman uuden tiedon onnistunut hyödyntäminen on oleellista PK-yritysten omistajanvaihdosten onnistumisessa. Luopujan hiljaisen tiedon siirtäminen jatkajalle ylläpitää yrityksen kilpailukykyä. Jatkajan yritykseen tuoma uusi tieto puolestaan voi laukaista tiedon hankinnan, sulattamisen, muokkaamisen ja hyödyntämisen prosessin, jonka kautta yrityksen kilpailukykyä voidaan parantaa tehostamalla prosesseja tai parantamalla tuotteita ja palveluita. Yksilöiden välinen tiedon jakaminen, siirtäminen ja rakentaminen ovat prosesseja, jotka kasvattavat yrityksen absorptiivistä kapasiteettiä tehostamalla tiedon sulattamista ja muuntamista. Tätä kautta voidaan osaltaan selittää omistajanvaihdokseen liittyviä riskejä ja mahdollisuuksia.