New directions in Stochastic Multicriteria Acceptability Analysis

Decisions taken in modern organizations are often multi-dimensional, involving multiple decision makers and several criteria measured on different scales. Multiple Criteria Decision Making (MCDM) methods are designed to analyze and to give recommendations in this kind of situations. Among the numerous MCDM methods, two large families of methods are the multi-attribute utility theory based methods and the outranking methods. Traditionally both method families require exact values for technical parameters and criteria measurements, as well as for preferences expressed as weights. Often it is hard, if not impossible, to obtain exact values. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods designed to help in this type of situations where exact values are not available. Different variants of SMAA allow handling all types of MCDM problems. They support defining the model through uncertain, imprecise, or completely missing values. The methods are based on simulation that is applied to obtain descriptive indices characterizing the problem. In this thesis we present new advances in the SMAA methodology. We present and analyze algorithms for the SMAA-2 method and its extension to handle ordinal preferences. We then present an application of SMAA-2 to an area where MCDM models have not been applied before: planning elevator groups for high-rise buildings. Following this, we introduce two new methods to the family: SMAA-TRI that extends ELECTRE TRI for sorting problems with uncertain parameter values, and SMAA-III that extends ELECTRE III in a similar way. An efficient software implementing these two methods has been developed in conjunction with this work, and is briefly presented in this thesis. The thesis is closed with a comprehensive survey of SMAA methodology including a definition of a unified framework.

Analysis of Industrial Granular Flow Applications by Using Advanced Collision Models

Granular flow phenomena are frequently encountered in the design of process and industrial plants in the traditional fields of the chemical, nuclear and oil industries as well as in other activities such as food and materials handling. Multi-phase flow is one important branch of the granular flow. Granular materials have unusual kinds of behavior compared to normal materials, either solids or fluids. Although some of the characteristics are still not well-known yet, one thing is confirmed: the particle-particle interaction plays a key role in the dynamics of granular materials, especially for dense granular materials. At the beginning of this thesis, detailed illustration of developing two models for describing the interaction based on the results of finite-element simulation, dimension analysis and numerical simulation is presented. The first model is used to describing the normal collision of viscoelastic particles. Based on some existent models, more parameters are added to this model, which make the model predict the experimental results more accurately. The second model is used for oblique collision, which include the effects from tangential velocity, angular velocity and surface friction based on Coulomb's law. The theoretical predictions of this model are in agreement with those by finite-element simulation. I n the latter chapters of this thesis, the models are used to predict industrial granular flow and the agreement between the simulations and experiments also shows the validation of the new model. The first case presents the simulation of granular flow passing over a circular obstacle. The simulations successfully predict the existence of a parabolic steady layer and show how the characteristics of the particles, such as coefficients of restitution and surface friction affect the separation results. The second case is a spinning container filled with granular material. Employing the previous models, the simulation could also reproduce experimentally observed phenomena, such as a depression in the center of a high frequency rotation. The third application is about gas-solid mixed flow in a vertically vibrated device. Gas phase motion is added to coherence with the particle motion. The governing equations of the gas phase are solved by using the Large eddy simulation (LES) and particle motion is predicted by using the Lagrangian method. The simulation predicted some pattern formation reported by experiment.

Value added logistical support service: logistics cost structure and performance in the new concept. Part 3

The aim of this study is to present an Activity-Based Costing spreadsheet tool for analyzing the logistics costs. The tool can be used both by customer-companies and logistics service providers. The study discusses the influence of different activity models on costs. Additionally this paper discusses about the logistical performance across the total supply chain This study is carried out using ananalytical research approach and literature material has been used for supplementing the concerned research approach. Cost structure analysis was based on the theory of activity-based management. This study was outlined to spare part logistics in machine-shop industry. The outlines of logistics services and logisticalperformance discussed in this report are based on the new logistics business concept (LMS-concept), which has been presented earlier in the Valssi-project. Oneof the aims of this study is to increase awareness of different activity modelson logistics costs. The report paints an overall picture about the business environment and requirements for the new logistics concept.

Information System ProcessInnovation Adoption, Adaptation, Learning, and Unlearning: A Longitudinal Case Study

This thesis examines the history and evolution of information system process innovation (ISPI) processes (adoption, adaptation, and unlearning) within the information system development (ISD) work in an internal information system (IS) department and in two IS software house organisations in Finland over a 43-year time-period. The study offers insights into influential actors and their dependencies in deciding over ISPIs. The research usesa qualitative research approach, and the research methodology involves the description of the ISPI processes, how the actors searched for ISPIs, and how the relationships between the actors changed over time. The existing theories were evaluated using the conceptual models of the ISPI processes based on the innovationliterature in the IS area. The main focus of the study was to observe changes in the main ISPI processes over time. The main contribution of the thesis is a new theory. The term theory should be understood as 1) a new conceptual framework of the ISPI processes, 2) new ISPI concepts and categories, and the relationships between the ISPI concepts inside the ISPI processes. The study gives a comprehensive and systematic study on the history and evolution of the ISPI processes; reveals the factors that affected ISPI adoption; studies ISPI knowledge acquisition, information transfer, and adaptation mechanisms; and reveals the mechanismsaffecting ISPI unlearning; changes in the ISPI processes; and diverse actors involved in the processes. The results show that both the internal IS department and the two IS software houses sought opportunities to improve their technical skills and career paths and this created an innovative culture. When new technology generations come to the market the platform systems need to be renewed, and therefore the organisations invest in ISPIs in cycles. The extent of internal learning and experiments was higher than the external knowledge acquisition. Until the outsourcing event (1984) the decision-making was centralised and the internalIS department was very influential over ISPIs. After outsourcing, decision-making became distributed between the two IS software houses, the IS client, and itsinternal IT department. The IS client wanted to assure that information systemswould serve the business of the company and thus wanted to co-operate closely with the software organisations.

Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

Automated formulation of optimisation models for steel beam structures

Over 70% of the total costs of an end product are consequences of decisions that are made during the design process. A search for optimal cross-sections will often have only a marginal effect on the amount of material used if the geometry of a structure is fixed and if the cross-sectional characteristics of its elements are property designed by conventional methods. In recent years, optimalgeometry has become a central area of research in the automated design of structures. It is generally accepted that no single optimisation algorithm is suitable for all engineering design problems. An appropriate algorithm, therefore, mustbe selected individually for each optimisation situation. Modelling is the mosttime consuming phase in the optimisation of steel and metal structures. In thisresearch, the goal was to develop a method and computer program, which reduces the modelling and optimisation time for structural design. The program needed anoptimisation algorithm that is suitable for various engineering design problems. Because Finite Element modelling is commonly used in the design of steel and metal structures, the interaction between a finite element tool and optimisation tool needed a practical solution. The developed method and computer programs were tested with standard optimisation tests and practical design optimisation cases. Three generations of computer programs are developed. The programs combine anoptimisation problem modelling tool and FE-modelling program using three alternate methdos. The modelling and optimisation was demonstrated in the design of a new boom construction and steel structures of flat and ridge roofs. This thesis demonstrates that the most time consuming modelling time is significantly reduced. Modelling errors are reduced and the results are more reliable. A new selection rule for the evolution algorithm, which eliminates the need for constraint weight factors is tested with optimisation cases of the steel structures that include hundreds of constraints. It is seen that the tested algorithm can be used nearly as a black box without parameter settings and penalty factors of the constraints.

The effects of potentiallydisruptive technology on business model - a case study of new technologies in ICT industry

This study examines how firms interpret new, potentially disruptive technologies in their own strategic context. The work presents a cross-case analysis of four potentially disruptive technologies or technical operating models: Bluetooth, WLAN, Grid computing and Mobile Peer-to-peer paradigm. The technologies were investigated from the perspective of three mobile operators, a device manufacturer and a software company in the ICT industry. The theoretical background for the study consists of the resource-based view of the firm with dynamic perspective, the theories on the nature of technology and innovations, and the concept of business model. The literature review builds up a propositional framework for estimating the amount of radical change in the companies' business model with two middle variables, the disruptiveness potential of a new technology, and the strategic importance of a new technology to a firm. The data was gathered in group discussion sessions in each company. The results of each case analysis were brought together to evaluate, how firms interpret the potential disruptiveness in terms of changes in product characteristics and added value, technology and market uncertainty, changes in product-market positions, possible competence disruption and changes in value network positions. The results indicate that the perceived disruptiveness in terms ofproduct characteristics does not necessarily translate into strategic importance. In addition, firms did not see the new technologies as a threat in terms of potential competence disruption.

Describing innovative business models and evaluating their wealth potential – Cases Stora Enso and E-bay

Tutkimuksen tavoitteena oli analysoida liiketoimintamalleihin liittyviä teorioita ja erilaisten mallien pohjalta rakentaa selkeä teoria, jota yritykset voivat käyttää määritellessään ja analysoidessaan liiketoimintamalleja. Tutkimuksen kohteena olleet yritykset voitiin jaotella sisäisesti fokusoituneisiin ja ulkoisesti suuntautuneisiin. Jaottelun pohjalta oli mahdollista tehdä johtopäätöksiä koskien liiketoimintamallien potentiaalia. Tutkimus oli luonteeltaan kvalitatiivinen. Tutkimuksen tuloksena on liiketoimintamallien rakentamiseen ja analysointiin sopiva työkalu, jota voidaan käyttää yrityksen strategisessa suunnittelussa.

The Business Models of Telecommunications Equipment Manufacturers. Case: Cisco Systems.

Tutkielman tavoitteena oli tarkastella telekommunikaatiolaitevalmistajien liiketoimintamalleja. Tutkielma jakaantuu teoreettiseen ja empiiriseen osaan. Teoreettinen osa keskittyy lähinnä liiketoimintamallin käsitteen määrittelyyn. Olemassa olevien määritelmien, sekä liiketoimintamallin käsitteeseen läheisesti liittyvien termien, pohjalta luotiin liiketoimintamallille uusi malli. Tutkielman empiirinen osa keskittyy case-yritys Cisco Systemsin liiketoimintamallin määrittelyyn ja kehityksen kuvaamiseen. Liiketoimintamallin kehitystä seurattiin kahden vuoden ajalta perehtymällä lähinnä yrityksen lehdistötiedotteisiin, artikkeleihin ja muuhun julkiseen materiaaliin. Ciscon lisäksi empiirisessä osassa tutkittiin kahdeksan muun laitevalmistajan liiketoimintamallien kehitystä. Empiirisen osan päätavoitteena oli selvittää, miten telekommunikaatiolaitevalmistajien liiketoimintamallit kehittyvät nyt ja tulevaisuudessa.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Business Models of Packaging Machinery Manufacturers – Case Study

The goal of the study was to find a proper frame to understand business models and study business models of the chosen companies in packaging machinery manufacturing. Good practices and tips are searched from business models which have helped companies to success. Packaging industry’s future is also examined in front of different kinds of changes and the influence which they have on machinery manufacturer’s business models. In the theory part business models’ history and the best frame suitable for this study are presented. The chosen case companies have been discussed according to the frame, and they have been compared to each other to point out the differences. The good practices noticed in companies and according to information from other sources, new business model has been constructed including things that should be noticed while constructing a new business model. The information sources of this study where interviews, annual reports, companies presentations and web pages. The type of study was an interpretative case study.

Analysis of outliers in electricity spot prices with exampleof New England and New Zealand markets

Electricity spot prices have always been a demanding data set for time series analysis, mostly because of the non-storability of electricity. This feature, making electric power unlike the other commodities, causes outstanding price spikes. Moreover, the last several years in financial world seem to show that ’spiky’ behaviour of time series is no longer an exception, but rather a regular phenomenon. The purpose of this paper is to seek patterns and relations within electricity price outliers and verify how they affect the overall statistics of the data. For the study techniques like classical Box-Jenkins approach, series DFT smoothing and GARCH models are used. The results obtained for two geographically different price series show that patterns in outliers’ occurrence are not straightforward. Additionally, there seems to be no rule that would predict the appearance of a spike from volatility, while the reverse effect is quite prominent. It is concluded that spikes cannot be predicted based only on the price series; probably some geographical and meteorological variables need to be included in modeling.

New design of the frame for a permanent magnet generator

This thesis introduces a search for a new design of the frame for a permanent magnet generator mounted at a windmill. The objective of this work is to offer new design ideas for the stator frame - new concepts for connecting stator core to stator frame in a generator. Desired aims of new design concepts are: simplification of the structure production; decrease of material use; use of standard components; light weight of construction and etc. Thesis contains several new possible designs for the stator frame structure. Also, it has a list of possible connection concepts, which can be used to join the stator to the frame. All new ideas are described and compared according to its match to the desired purposes of the work. New design concepts are modeled using modern software. The main part of the Thesis contains several approximate computer models of the current and new offered constructions, description of loads and stress in the current stator frame. It has evaluation of the most important stress and load characteristics. The final design is a result of all previous research. It has a description of a new frame structure and joining concept for it. This structure matched main aims of work, but it does not have detailed design with dimensions and check calculations of the frame and welds. Thesis gives representation about design search, evaluation and comparison of new concepts of generator structure. Also, it gives general representation of renewable energy technology, knowledge about windmill turbines and its contents.

Identifying and Characterizing New Ingredients in vitro for Prebiotic and Synbiotic use

The endogenous microbiota, constituting the microbes that live inside and on humans, is estimated to outnumber human cells by a factor of ten. This commensal microbial population has an important role in many physiological functions, with the densest microbiota population found in the colon. The colonic microbiota is a highly complex and diverse bacterial ecosystem, and a delicate balance exists between the gut microbiota and its host. An imbalance in the microbial ecosystem may lead to severe symptoms in and also beyond the gastrointestinal tract. Due to the important role of the gut microbiota in human health, means of its modification have been introduced in the dietary concepts of pro-, pre- and synbiotics. Prebiotics, which are usually carbohydrates, strive to selectively influence beneficial microbes resident in the colon with the aim of modifying the composition and functionality of the commensal microbial population towards a purportedly healthier one. The study of prebiotic effects on colonic micro-organisms is typically done by using human faecal material, though this provides relatively little information on bacterial populations and metabolic events in different parts of the colon. For this reason, several in vitro models have been developed to investigate the gut microbiota. The aim of this doctoral thesis was to screen through some of the promising prebiotic candidates, characterize their effects on the microbiota through the use of two in vitro methods (pure microbial cultures and a colon simulator model) and to evaluate their potential as emerging prebiotics or synbiotics when combined with the probiotic Bifidobacterium lactis . As a result of the screening work and subsequent colon simulation studies, several compounds with promising features were identified. Xylo-oligosaccharides (XOS), which have previously already shown promise as prebiotic compounds, were well fermented by several probiotic Bifidobacterium lactis strains in pure culture studies and in the following simulation studies utilizing the complex microbiota by endogenous B. lactis Another promising compound was panose, a trisaccharide belonging to isomalto-oligosaccharides (IMO) that also was also able to modify the microbiota in vitro by increasing the number of beneficial microbes investigated. Panose has not been widely studied previously and therefore, this thesis work provided the first data on panose fermentation in mixed colonic microbiota. Galacto-oligosaccharide (GOS) is an established prebiotic, and it was studied here in conjunction with another potential polygosaccharide polydextrose (PDX) and probiotic B. lactis Bi-07. In this final study, the synbiotics including GOS were more effective than the constituting pro- or prebiotics alone in modulating the microbiota composition, thus indicating a synergy resulting from the combination. The results obtained in this in vitro work can be, and have already been, utilized in product development aimed at the nutritional modification of the human colonic microbiota. Some of the compounds have entered the human clinical intervention phase to nvestigate in more detail the prebiotic and synbiotic properties seen in these in vitro studies.

Some advances in mathematical models for preference relations

Preference relations, and their modeling, have played a crucial role in both social sciences and applied mathematics. A special category of preference relations is represented by cardinal preference relations, which are nothing other than relations which can also take into account the degree of relation. Preference relations play a pivotal role in most of multi criteria decision making methods and in the operational research. This thesis aims at showing some recent advances in their methodology. Actually, there are a number of open issues in this field and the contributions presented in this thesis can be grouped accordingly. The first issue regards the estimation of a weight vector given a preference relation. A new and efficient algorithm for estimating the priority vector of a reciprocal relation, i.e. a special type of preference relation, is going to be presented. The same section contains the proof that twenty methods already proposed in literature lead to unsatisfactory results as they employ a conflicting constraint in their optimization model. The second area of interest concerns consistency evaluation and it is possibly the kernel of the thesis. This thesis contains the proofs that some indices are equivalent and that therefore, some seemingly different formulae, end up leading to the very same result. Moreover, some numerical simulations are presented. The section ends with some consideration of a new method for fairly evaluating consistency. The third matter regards incomplete relations and how to estimate missing comparisons. This section reports a numerical study of the methods already proposed in literature and analyzes their behavior in different situations. The fourth, and last, topic, proposes a way to deal with group decision making by means of connecting preference relations with social network analysis.