IFRS 2 Osakeperusteiset maksut – ylimmän johdon osakeperusteisten palkitsemisjärjestelmien kirjaaminen sekä vaikutus tilinpäätökseen

Tutkimuksen tarkoituksena on pyrkiä selvittämään kansainvälisen tilipäätösstandardin, IFRS 2 Osakeperusteiset maksut, vaikutusta yritysten palkitsemisjärjestelmäkäytäntöihin standardin voimaanastumisesta aina nykyhetkeen saakka. Tarkastelun ensisijaisena pyrkimyksenä on selvittää, miten osakeperusteiset palkitsemisjärjestelmät, kirjataan yritysten tilinpäätöksiin. Tutkimuksessa on myös tarkoitus yritysten tilinpäätösinformaatioiden kautta pyrkiä tuomaan esille osakeperusteisten maksujen tilinpäätöksellinen vaikutus, eli selvittää, millaisia vaikutuksia osakeperusteisten maksujen kirjaamisella on yritysten tunnusluvuille.

IFRS 2 Osakeperusteiset maksut – ylimmän johdon osakeperusteisen palkitsemisjärjestelmien käyttöä selittävät tekijät

Työn tarkoituksena on selvittää, mitkä tekijät vaikuttavat IFRS 2 - standardin mukaisen osakeperusteisen palkitsemisen käyttöön ja sen yleisyyteen sekä mitkä tekijät selittävät IFRS 2 -standardin mukaisen osakeperusteisen palkitsemisen osuutta koko henkilöstökuluista tutkimuksessa esiintyvissä OMX-Nordic pörssin listatuissa Suomen ja Ruotsin large cap - yrityksissä. Työn empiirinen tutkimus toteutetaan laadullisella tutkimuksella, jossa lisäksi käytetään hyväksi regressioanalyysin tuloksia vahvistamaan tutkimuksessa muodostettuja ennakko-oletuksia. Tutkimuksesta kävi ilmi, että IFRS 2 -standardin mukaisen osakeperusteisen palkitsemisen käyttöä selittävät toimitusjohtajan ikä, yrityksen koko sekä yrityksen tutkimus- ja kehitystoiminta. Osakeperusteisen palkitsemisen osuutta yrityksen koko henkilöstökuluista puolestaan selittävät yrityksen velkaantuneisuus, palkitsemistapa sekä toimialan riskisyys.

Share RepurchasePractices in Finland

Tämäntutkimuksen tarkoituksena oli selvittää omien osakkeiden takaisinostoihin liittyviä käytäntöjä Suomessa. Tutkimuksessa selvitettiin ilmoitettujen takaisinostojen syiden ja yritysten todellisen käyttäytymisen suhdetta. Tutkimuksessa tarkasteltiin myös takaisinostoihin liittyviä ylituottoja. Tämä tutkielma on kvantitatiivinen tutkimus, jossa tutkimus perustuu Datastream tietokannasta ja pörssitiedotteista saatuun dataan sekä aikaisempiin tutkimuksiin aiheesta. Tutkimuksen perusteella voidaan todeta, että yritysten ilmoittamat syyt takaisinostoille eivät kerro yritysten todellisista aikeista tai käyttäytymisestä. Ylituottojen tutkimuksen perusteella voidaan todeta, että suurempi takaisinosto-ohjelma ja ennakoimaton takaisinosto aiheuttavat vahvemman positiivisen markkinareaktion.

Managing R&D Content with Web-based KM Software

Työssä tutkittiin tehokasta tietojohtamista globaalin metsäteollisuusyrityksen tutkimus ja kehitys verkostossa. Työn tavoitteena oli rakentaa kuvaus tutkimus ja kehitys sisällön hallintaan kohdeyrityksen käyttämän tietojohtamisohjelmiston avulla. Ensin selvitettiin käsitteitä tietämys ja tietojohtaminen kirjallisuuden avulla. Selvityksen perusteella esitettiin prosessimalli, jolla tietämystä voidaan tehokkaasti hallita yrityksessä. Seuraavaksi analysoitiin tietojohtamisen asettamia vaatimuksia informaatioteknologialle ja informaatioteknologian roolia prosessimallissa. Verkoston vaatimukset tietojohtamista kohtaan selvitettiin haastattelemalla yrityksen avainhenkilöitä. Haastatteluiden perusteella järjestelmän tuli tehokkaasti tukea virtuaalisten projektiryhmien työskentelyä, mahdollistaa tehtaiden välinen tietämyksen jakaminen ja tukea järjestelmään syötetyn sisällön hallintaa. Ensiksi järjestelmän käyttöliittymän rakenne ja salaukset muokattiin vastaamaan verkoston tarpeita. Rakenne tarjoaa työalueen työryhmille ja alueet tehtaiden väliseen tietämyksen jakamiseen. Sisällönhallintaa varten järjestelmään kehitettiin kategoria, profiloitu portaali ja valmiiksi määriteltyjä hakuja. Kehitetty malli tehostaa projektiryhmien työskentelyä, mahdollistaa olemassa olevan tietämyksen hyväksikäytön tehdastasolla sekä helpottaa tutkimus ja kehitys aktiviteettien seurantaa. Toimenpide-ehdotuksina esitetään järjestelmän integrointia tehtaiden operatiivisiin ohjausjärjestelmiin ja ohjelmiston käyttöönottoa tehdastason projektinhallinta työkaluksi.Ehdotusten tavoitteena on varmistaa sekä tehokas tietämyksen jakaminen tehtaiden välillä että tehokas tietojohtaminen tehdastasolla.

Innovation process management of complex consumer products and services in new innovation paradigm – case location based business

Innovation is the word of this decade. According to innovation definitions, without positive sales impact and meaningful market share the company’s product or service has not been an innovation. Research problem of this master thesis is to find out what is the innovation process of complex new consumer products and services in new innovation paradigm. The objective is to get answers to two research questions: 1) What are the critical success factors what company should do when it is implementing the paradigm change in mass markets consumer business with complex products and services? 2) What is the process or framework one firm could follow? The research problem is looked from one company’s innovation creation process, networking and organization change management challenges point of views. Special focus is to look the research problem from an existing company perspective which is entering new business area. Innovation process management framework of complex new consumer products and services in new innovation paradigm has been created with support of several existing innovation theories. The new process framework includes the critical innovation process elements companies should take into consideration in their daily activities when they are in their new business innovation implementing process. Case company location based business implementation activities are studied via the new innovation process framework. This case study showed how important it is to manage the process, look how the target market and the competition in it is developing during company’s own innovation process, make decisions at right time and from beginning plan and implement the organization change management as one activity in the innovation process. In the end this master thesis showed that all companies need to create their own innovation process master plan with milestones and activities. One plan does not fit all, but all companies can start their planning from the new innovation process what was introduced in this master thesis.

Study of ligand-based virtual screening tools in computer-aided drug design

Virtual screening is a central technique in drug discovery today. Millions of molecules can be tested in silico with the aim to only select the most promising and test them experimentally. The topic of this thesis is ligand-based virtual screening tools which take existing active molecules as starting point for finding new drug candidates. One goal of this thesis was to build a model that gives the probability that two molecules are biologically similar as function of one or more chemical similarity scores. Another important goal was to evaluate how well different ligand-based virtual screening tools are able to distinguish active molecules from inactives. One more criterion set for the virtual screening tools was their applicability in scaffold-hopping, i.e. finding new active chemotypes. In the first part of the work, a link was defined between the abstract chemical similarity score given by a screening tool and the probability that the two molecules are biologically similar. These results help to decide objectively which virtual screening hits to test experimentally. The work also resulted in a new type of data fusion method when using two or more tools. In the second part, five ligand-based virtual screening tools were evaluated and their performance was found to be generally poor. Three reasons for this were proposed: false negatives in the benchmark sets, active molecules that do not share the binding mode, and activity cliffs. In the third part of the study, a novel visualization and quantification method is presented for evaluation of the scaffold-hopping ability of virtual screening tools.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Improving Transportation and Warehousing Efficiency with Simulation-Based Decision Support Systems

Transportation and warehousing are large and growing sectors in the society, and their efficiency is of high importance. Transportation also has a large share of global carbondioxide emissions, which are one the leading causes of anthropogenic climate warming. Various countries have agreed to decrease their carbon emissions according to the Kyoto protocol. Transportation is the only sector where emissions have steadily increased since the 1990s, which highlights the importance of transportation efficiency. The efficiency of transportation and warehousing can be improved with the help of simulations, but models alone are not sufficient. This research concentrates on the use of simulations in decision support systems. Three main simulation approaches are used in logistics: discrete-event simulation, systems dynamics, and agent-based modeling. However, individual simulation approaches have weaknesses of their own. Hybridization (combining two or more approaches) can improve the quality of the models, as it allows using a different method to overcome the weakness of one method. It is important to choose the correct approach (or a combination of approaches) when modeling transportation and warehousing issues. If an inappropriate method is chosen (this can occur if the modeler is proficient in only one approach or the model specification is not conducted thoroughly), the simulation model will have an inaccurate structure, which in turn will lead to misleading results. This issue can further escalate, as the decision-maker may assume that the presented simulation model gives the most useful results available, even though the whole model can be based on a poorly chosen structure. In this research it is argued that simulation- based decision support systems need to take various issues into account to make a functioning decision support system. The actual simulation model can be constructed using any (or multiple) approach, it can be combined with different optimization modules, and there needs to be a proper interface between the model and the user. These issues are presented in a framework, which simulation modelers can use when creating decision support systems. In order for decision-makers to fully benefit from the simulations, the user interface needs to clearly separate the model and the user, but at the same time, the user needs to be able to run the appropriate runs in order to analyze the problems correctly. This study recommends that simulation modelers should start to transfer their tacit knowledge to explicit knowledge. This would greatly benefit the whole simulation community and improve the quality of simulation-based decision support systems as well. More studies should also be conducted by using hybrid models and integrating simulations with Graphical Information Systems.

The role of advance payments in working capital management and profitability

The objective of this thesis is to study the role of received advance payments in working capital management by creating a new measurement and to study the relationship between advance payments and profitability. The study has been conducted using narrative literature review and quantitative research methods. The research was made analyzing 108 companies listed in Helsinki Stock Exchange. The results indicate that 68 % of the studied companies are receiving advance payments and the average cycle time for received advance payments is 13 days. A new key figure is created to include received advance payments into the calculation of working capital. Received advance payments shorten the working capital cycle, by 13 days, when they are used in the calculation. The role of advance payments is not as significant as the role of receivables and inventories but advance payments may have a larger role than payables if the company is receiving noticeable amounts of advance payments. There are three branches where companies are receiving more advance payments than average companies. The branches are project business and ICT and publishing sectors. There is a negative correlation between profitability and advance payments based on the results of this study.

A simulation model of the optimal maintenance strategy: conceptual agent-based approach

In this Master’s thesis agent-based modeling has been used to analyze maintenance strategy related phenomena. The main research question that has been answered was: what does the agent-based model made for this study tell us about how different maintenance strategy decisions affect profitability of equipment owners and maintenance service providers? Thus, the main outcome of this study is an analysis of how profitability can be increased in industrial maintenance context. To answer that question, first, a literature review of maintenance strategy, agent-based modeling and maintenance modeling and optimization was conducted. This review provided the basis for making the agent-based model. Making the model followed a standard simulation modeling procedure. With the simulation results from the agent-based model the research question was answered. Specifically, the results of the modeling and this study are: (1) optimizing the point in which a machine is maintained increases profitability for the owner of the machine and also the maintainer with certain conditions; (2) time-based pricing of maintenance services leads to a zero-sum game between the parties; (3) value-based pricing of maintenance services leads to a win-win game between the parties, if the owners of the machines share a substantial amount of their value to the maintainers; and (4) error in machine condition measurement is a critical parameter to optimizing maintenance strategy, and there is real systemic value in having more accurate machine condition measurement systems.

Creating an open-books implementation framework for a maintenance-related value-based life-cycle model

This study is a qualitative action research by its nature with elements of personal design in the form of a tangible model implementation framework construction. Utilized empirical data has been gathered via two questionnaires in relation to the arranged four workshop events with twelve individual participants. Five of them represented maintenance customers, three maintenance service providers and four equipment providers respectively. Further, there are two main research objectives in proportion to the two complementary focusing areas of this thesis. Firstly, the value-based life-cycle model, which first version has already been developed prior to this thesis, requires updating in order to increase its real-life applicability as an inter-firm decision-making tool in industrial maintenance. This first research objective is fulfilled by improving appearance, intelligibility and usability of the above-mentioned model. In addition, certain new features are also added. The workshop participants from the collaborating companies were reasonably pleased with made changes, although further attention will be required in future on the model’s intelligibility in particular as main results, charts and values were all reckoned as slightly hard to understand. Moreover, upgraded model’s appearance and added new features satisfied them the most. Secondly and more importantly, the premises of the model’s possible inter-firm implementation process need to be considered. This second research objective is delivered in two consecutive steps. At first, a bipartite open-books supported implementation framework is created and its different characteristics discussed in theory. Afterwards, the prerequisites and the pitfalls of increasing inter-organizational information transparency are studied in empirical context. One of the main findings was that the organizations are not yet prepared for network-wide information disclosure as dyadic collaboration was favored instead. However, they would be willing to share information bilaterally at least. Another major result was that the present state of companies’ cost accounting systems will definitely need implementation-wise enhancing in future since accurate and sufficiently detailed maintenance data is not available. Further, it will also be crucial to create supporting and mutually agreed network infrastructure. There are hardly any collaborative models, methods or tools currently in usage. Lastly, the essential questions about mutual trust and predominant purchasing strategies are cooperation-wise important. If inter-organizational activities are expanded, a more relational approach should be favored in this regard. Mutual trust was also recognized as a significant cooperation factor, but it is hard to measure in reality.

“Why share in uncertain conditions?” Factors of individual level knowledge sharing in offshoring cases

The objective of this Master’s Thesis was to research factors influencing and enhancing individual level knowledge sharing in offshore projects which often involve uncertainty of the knowledge provider’s own future. The purpose was to understand why individuals are willing to share their knowledge under these kinds of circumstances. In addition the goal was to identify obstacles to interpersonal knowledge sharing in order to understand how to mitigate their influence. The research was conducted as a qualitative multiple case study in a global IT company, and the data was gathered using semi-structured personal theme interviews within two different offshore projects. In order to a gain a wider perspective on the matter, some management representatives were interviewed as well. Data was analysed with the inductive content analysis method. Results of the study indicate that individuals are willing to share their knowledge despite of uncertainty if they are motivated, if they are provided with opportunities to do so, and if they have skills, competence and experience to share their knowledge. A strong knowledge sharing culture in the organization or team also works as a strong incentive for individual level knowledge sharing. The findings suggest that even under uncertain conditions it is possible to encourage people to share their knowledge if uncertainty can be decreased to a bearable level, a robust and personal connection and relationship between the knowledge provider and acquirer can be created and suitable opportunities for knowledge sharing are provided. In addition, based on the results the support and commitment of management and HR in addition to favourable environmental circumstances play an essential role in building a bridge between the knowledge provider and acquirer in order to create a virtual environment and space for knowledge sharing: Ba.

Production Quality Analysis of Special Elevator Cars Based on Six Sigma Approach

Project scope is to utilize Six Sigma DMAIC approach and lean principles to improve production quality of the case company. Six Sigma tools and techniques are explored through a literature review and later used in the quality control phase. The focus is set on the Pareto analysis to demonstrate the most evident development areas in the production. Materials that are not delivered to the customer or materials that damaged during transportation comprise the biggest share of all feedbacks. The goal is set to reduce these feedbacks by 50 %. Production observation pointed out that not only material shortages but also over-production is a daily situation. As a result, an initial picking list where the purchased and own production components can be seen, is created, reduction of over- and underproduction and material marking improvement are seen the most competitive options so that the goal can be reached. The picking list development should still continue to make sure that the list can be used not only in the case study but also in the industrial scale. The reduction of material missing category can be evaluated reliably not sooner than in few years because it takes time to gather the needed statistical information.

Variable-speed-drive-based detection methods for problems in fluid handling systems

Fluid handling systems account for a significant share of the global consumption of electrical energy. They also suffer from problems, which reduce their energy efficiency and increase life-cycle costs. Detecting or predicting these problems in time can make fluid handling systems more environmentally and economically sustainable to operate. In this Master’s Thesis, significant problems in fluid systems were studied and possibilities to develop variable-speed-drive-based detection methods for them was discussed. A literature review was conducted to find significant problems occurring in fluid handling systems containing pumps, fans and compressors. To find case examples for evaluating the feasibility of variable-speed-drive-based methods, queries were sent to industrial companies. As a result of this, the possibility to detect heat exchanger fouling with a variable-speed drive was analysed with data from three industrial cases. It was found that a mass flow rate estimate, which can be generated with a variable speed drive, can be used together with temperature measurements to monitor a heat exchanger’s thermal performance. Secondly, it was found that the fouling-related increase in the pressure drop of a heat exchanger can be monitored with a variable speed drive. Lastly, for systems where the flow device is speed controlled with by a pressure measurement, it was concluded that increasing rotational speed can be interpreted as progressing fouling in the heat exchanger.