Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.

Analytiikan hyödyntäminen asiakkuuksien johtamisessa

Yrityksiltä vaaditaan yhä enemmän tietoa päätöksenteon tueksi asiakkuuksien johtamisen yhteydessä. Analytiikan hyödyntäminen tehostaa päätöksentekoa ja auttaa muuttamaan asiakastiedon pääomaksi. Tämän tutkimuksen tarkoituksena oli tutkia millaisia hyötyjä analytiikka mahdollistaa yritysten asiakkuuksien johtamisen tueksi. Tutkimus toteutettiin laadullisena tapaustutkimuksena. Kohdeyritykseksi valittiin media-alan yritys. Tutkimukseen osallistui seitsemän henkilöä kohdeyrityksen myynnin ja markkinoinnin johdon sekä esimies- ja asiantuntijatehtävistä. Tutkimusmenetelmänä käytettiin teemahaastattelua. Tutkimustulosten mukaan analytiikka oli mahdollistanut myyntiä edistäviä ja kannattavuutta parantavia toimenpiteitä, joita toteutettiin asiakkuuksien johtamisen eri vaiheissa. Analytiikka asiakkuuksien johtamisen tukena oli kohdeyrityksessä kuitenkin vielä uudehko asia, jossa nähtiin olevan merkittäviä mahdollisuuksia asiakastiedon parempaan hyödyntämiseen.

Sosiaalisen pääoman verkostotutkimus kohdeyrityksessä

Tässä sosiaalisen pääoman verkostotutkimuksessa tarkastellaan valitun rahoitusalalla toimivan kohdeyhtiön sosiaalisen verkoston rakennetta. Työn tavoitteena on määritellä kohdeorganisaation sosiaalinen verkosto ja löytää avainhenkilöt, jotka ovat keskeisiä organisaation toiminnalle ja tiedonjakamiselle. Näiden tunnistettujen roolien kautta pyritään selvittämään miten yritykset laajemmin voivat hyödyntää yritysten epämuodollista sosiaalista verkostoa yleensä tiedon jakamisessa. Tuloksilla pyritään myös hakemaan tukea sille miten sosiaalista epämuodollista verkostoa voidaan hyödyntää silloin kun organisaatio on muutostilassa. Työ on laadullinen tutkimus jota tuetaan numeerisella aineistolla joka on kerätty verkostokyselyllä. Pääasiallinen aineisto tutkimukselle kerättiin teemahaastatteluilla. Empiirinen aineisto kerättiin verkostoanalyysillä koko kohdeyhtiön henkilökunnalle lähetetyllä kyselyllä. Tästä johdettuna luotiin sosiaalisen verkosto kartta ja analysoitiin tulokset. Tuloksien avulla löydettyjä havaintoja käytettiin teemahaastatteluiden pohjana varsinaiselle tutkimukselle. Haastateltavat henkilöt edustivat organisaation eri yksiköitä ja ammattiryhmiä. Tutkimuksen tulokset osoittavat sen, että kohdeyrityksen sosiaalisen verkoston rakenne poikkeaa tyypillisestä muodollisesta organisaatiorakenteesta huomattavasti. Tutkimuksessa havaittiin selkeitä avainhenkilöitä joiden roolit korostuvat organisaation toiminnalle oleellisina tietoväylinä. Näiden avainhenkilöiden kautta haetaan tietoa ja apua päätöstentekoon organisaation kaikilla tasoilla. Tutkimus osoittaa myös sen, että sosiaalisen pääoman kasvaessa oikeaa tietoa osataan hakea oikeasta paikasta nopeammin ja tehokkaammin epämuodollisia reittejä pitkin. Tunnistamalla avainhenkilöt organisaatiossa, yritykset pystyvät vaikuttamaan tiedonkulkuun myös silloin kun yritys on muutostilassa. Vaikuttamalla ja kommunikoimalla myös epäformaalien verkostojen kautta yrityksien on helpompi muokata toimintatapojaan muutoksien yhteydessä.

Big Datan liiketoiminnalliset mahdollisuudet ja haasteet

Tämän kandidaatintutkielman tarkoituksena oli selvittää minkälaisia liiketoiminnallisia mahdollisuuksia ja haasteita Big Dataan ja sen ominaispiirteisiin liittyy, ja miten Big Data määritellään nykyaikaisesti ja ajankohtaisesti. Tutkimusongelmaa lähestyttiin narratiivisen kirjallisuuskatsauksen keinoin. Toisin sanoen tutkielma on hajanaisen tiedon avulla koostettu yhtenäinen katsaus nykytilanteeseen. Lähdeaineisto koostuu pääosin tieteellisistä artikkeleista, mutta käytössä oli myös oppikirjamateriaalia, konferenssijulkaisuja ja uutisartikkeleja. Tutkimuksessa käytetyt akateemisen kirjallisuuden lähteet sisälsivät keskenään paljon samankaltaisia näkemyksiä tutkimusaihetta kohtaan. Niiden perusteella muodostettiin kaksi taulukkoa havaituista mahdollisuuksista ja haasteista, ja taulukoiden rivit nimettiin niitä kuvaavien ominaispiirteiden mukaan. Tutkimuksessa liiketoiminnalliset mahdollisuudet ja haasteet jaettiin viiteen pääkategoriaan ja neljään alakategoriaan. Tutkimus toteutettiin liiketoiminnan näkökulmasta, joten siinä sivuutettiin monenlaisia Big Datan teknisiä aspekteja. Tutkielman luonne on poikkitieteellinen, ja sen avulla pyritään havainnoimaan tämän hetken yhtä uusinta tietojenkäsittelykäsittelytieteiden termiä liiketoiminnallisessa kontekstissa. Tutkielmassa Big Dataan liittyvillä ominaispiirteillä todettiin olevan mahdollisuuksia, jotka voitiin jaotella korrelaatioiden havaitsemisen perusteella markkinoiden tarkemman segmentoinnin mahdollisuuksiin ja päätöksenteon tukena toimimiseen. Reaaliaikaisen seurannan mahdollisuudet perustuvat Big Datan nopeuteen ja kokoon, eli sen jatkuvaan kasvuun. Ominaispiirteisiin liittyvät haasteet voidaan jakaa viiteen kategoriaan, joista osa liittyy toimintaympäristöön ja osa organisaation sisäiseen toimintaan.

Social media in the purchasing of knowledge-intensive business services

The purpose of this thesis was to understand how industrial buyers utilize social media in the purchasing of knowledge-intensive business services. By combining theories from past research a theoretical framework was formed to visualize the role of the social media at the different stages of the purchasing process. The subject was approached from the industrial buyers’ perspective instead of the knowledge-intensive business firm. The research was conducted using two qualitative research methods: interviews and netnography. The selected interviewees have been involved in the decision-making unit for purchasing knowledge-intensive business services. Additionally all of them are using various social media. Based on the interviews social media is used merely to support decision-making. Some of the interviewees had also shared their own experiences about the service and collaboration with the service provider with other social media users. Based on the interviews two social media were chosen for closer examination. The findings from netnography support the results from the interviews. The outcome of knowledgeintensive business services is dependable of the professionals. Therefore the information is used during decision-making process to confirm the formed image of the service, and the professionals of the service provider. Information obtained from social media complements information provided by the supplier. Even though the interviewees had not themselves used social media to find information about the service during search process, finding from netnography suggest it to exist. Industrial buyers ask other users’ opinions and experience about the services, and receive recommendations to them. Some recommendations are given publicly, but more discreet information is shared in private conversations. Observations in social media show that industrial buyers might be exposed to triggers to promote problem recognition as well. Companies share news and successful customer cases through their social media profiles, which might affect the industrial buyers, but to confirm this requires further research. The industrial buyers’ use of social media during different purchasing processes of knowledgeintensive business services can be conceptualize based on the findings. This helps companies to create right content to their social media pages, and encourage professionals to develop their networks in social media.

Suomalaisen PK-yrityksen etabloitumisen kompleksisuus Venäjälle

Tässä diplomityössä perehdytään suomalaisten pk - yritysten kansainvälistymisen kompleksisuuteen Venäjälle. Tutkimuksen pääkohderyhmänä ovat Etelä-Karjalaiset kone – ja metallialan pienet ja keskisuuret yritykset. Tutkimuksessa selvitettiin myös Pietarin alueen suurten metalliyritysten etabloitumishalukkuutta Suomeen. Työn tavoitteena on tuottaa informaatiota kansainvälisen liiketoiminnan päätöksenteon tueksi. Työn tarkoituksena on myös selvittää lukijalle kansainvälistymiseen liittyvän kompleksisuuden ja yrityksen resurssien välistä yhteyttä. Työn yhtenä tuotoksena luotiin yksinkertainen malli, joka omalta osaltaan selittää haastavalle liiketoiminta-alueelle etabloitumista tavoittelevan yrityksen kokemaa kompleksisuutta ja sen yhteyttä yrityksen resursseihin.

A decision support system for selective cleaning

[Abstract]

Technology selection and group decision support systems: Case studies on supporting strategic technology selection processes

The objective of the dissertation is to increase understanding and knowledge in the field where group decision support system (GDSS) and technology selection research overlap in the strategic sense. The purpose is to develop pragmatic, unique and competent management practices and processes for strategic technology assessment and selection from the whole company's point of view. The combination of the GDSS and technology selection is approached from the points of view of the core competence concept, the lead user -method, and different technology types. In this research the aim is to find out how the GDSS contributes to the technology selection process, what aspects should be considered when selecting technologies to be developed or acquired, and what advantages and restrictions the GDSS has in the selection processes. These research objectives are discussed on the basis of experiences and findings in real life selection meetings. The research has been mainly carried outwith constructive, case study research methods. The study contributes novel ideas to the present knowledge and prior literature on the GDSS and technology selection arena. Academic and pragmatic research has been conducted in four areas: 1) the potential benefits of the group support system with the lead user -method,where the need assessment process is positioned as information gathering for the selection of wireless technology development projects; 2) integrated technology selection and core competencies management processes both in theory and in practice; 3) potential benefits of the group decision support system in the technology selection processes of different technology types; and 4) linkages between technology selection and R&D project selection in innovative product development networks. New type of knowledge and understanding has been created on the practical utilization of the GDSS in technology selection decisions. The study demonstrates that technology selection requires close cooperation between differentdepartments, functions, and strategic business units in order to gather the best knowledge for the decision making. The GDSS is proved to be an effective way to promote communication and co-operation between the selectors. The constructs developed in this study have been tested in many industry fields, for example in information and communication, forest, telecommunication, metal, software, and miscellaneous industries, as well as in non-profit organizations. The pragmatic results in these organizations are some of the most relevant proofs that confirm the scientific contribution of the study, according to the principles of the constructive research approach.

Are Evaluation of ICTs Investment Using Decision Support Systems:Case Applications from Distributor's and End User's Perspective Group Decision

The evaluation of investments in advanced technology is one of the most important decision making tasks. The importance is even more pronounced considering the huge budget concerning the strategic, economic and analytic justification in order to shorten design and development time. Choosing the most appropriate technology requires an accurate and reliable system that can lead the decision makers to obtain such a complicated task. Currently, several Information and Communication Technologies (ICTs) manufacturers that design global products are seeking local firms to act as their sales and services representatives (called distributors) to the end user. At the same time, the end user or customer is also searching for the best possible deal for their investment in ICT's projects. Therefore, the objective of this research is to present a holistic decision support system to assist the decision maker in Small and Medium Enterprises (SMEs) - working either as individual decision makers or in a group - in the evaluation of the investment to become an ICT's distributor or an ICT's end user. The model is composed of the Delphi/MAH (Maximising Agreement Heuristic) Analysis, a well-known quantitative method in Group Support System (GSS), which is applied to gather the average ranking data from amongst Decision Makers (DMs). After that the Analytic Network Process (ANP) analysis is brought in to analyse holistically: it performs quantitative and qualitative analysis simultaneously. The illustrative data are obtained from industrial entrepreneurs by using the Group Support System (GSS) laboratory facilities at Lappeenranta University of Technology, Finland and in Thailand. The result of the research, which is currently implemented in Thailand, can provide benefits to the industry in the evaluation of becoming an ICT's distributor or an ICT's end user, particularly in the assessment of the Enterprise Resource Planning (ERP) programme. After the model is put to test with an in-depth collaboration with industrial entrepreneurs in Finland and Thailand, the sensitivity analysis is also performed to validate the robustness of the model. The contribution of this research is in developing a new approach and the Delphi/MAH software to obtain an analysis of the value of becoming an ERP distributor or end user that is flexible and applicable to entrepreneurs, who are looking for the most appropriate investment to become an ERP distributor or end user. The main advantage of this research over others is that the model can deliver the value of becoming an ERP distributor or end user in a single number which makes it easier for DMs to choose the most appropriate ERP vendor. The associated advantage is that the model can include qualitative data as well as quantitative data, as the results from using quantitative data alone can be misleading and inadequate. There is a need to utilise quantitative and qualitative analysis together, as can be seen from the case studies.

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.

Improving strategic decision-making with simulation based decision support systems

Combating climate change is one of the key tasks of humanity in the 21st century. One of the leading causes is carbon dioxide emissions due to usage of fossil fuels. Renewable energy sources should be used instead of relying on oil, gas, and coal. In Finland a significant amount of energy is produced using wood. The usage of wood chips is expected to increase in the future significantly, over 60 %. The aim of this research is to improve understanding over the costs of wood chip supply chains. This is conducted by utilizing simulation as the main research method. The simulation model utilizes both agent-based modelling and discrete event simulation to imitate the wood chip supply chain. This thesis concentrates on the usage of simulation based decision support systems in strategic decision-making. The simulation model is part of a decision support system, which connects the simulation model to databases but also provides a graphical user interface for the decisionmaker. The main analysis conducted with the decision support system concentrates on comparing a traditional supply chain to a supply chain utilizing specialized containers. According to the analysis, the container supply chain is able to have smaller costs than the traditional supply chain. Also, a container supply chain can be more easily scaled up due to faster emptying operations. Initially the container operations would only supply part of the fuel needs of a power plant and it would complement the current supply chain. The model can be expanded to include intermodal supply chains as due to increased demand in the future there is not enough wood chips located close to current and future power plants.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Decision support systems in wood procurement. A Review

Summary

A Local DLP-GIS-LP system for geographically decentralized wood procurement planning and decision making

Summary