Brand Identity of an Ecological Oriented SME

Tämän eksploratiivisen tutkimuksen tarkoituksena on tutkia yrittäjän persoonallisuuden roolia ekologisesti suuntautuneen brändin identiteetin ja assosiaatioiden rakentamisessa. Tutkimus on tehty yrittäjän näkökulmasta, jonka kontekstina ovat pienet ja keskisuuret yritykset. Tämä tutkimus pyrkii laajentamaan ja saamaan ymmärrystä keskeisistä käsitteistä, ja samalla edistämään PK-yrityksiin liittyvää kirjallisuutta. Tämän lisäksi tutkimus tarkastelee mitä assosiaatioita ekologisesti suuntautunut brändi korostaa identiteetissään. Tutkimus suoritettiin tapaustutkimuksena. Laadullista primääridataa kerättiin teemahaastattelemalla yrittäjää, havainnoimalla yhtä case-yrityksen messuosastoa, sekä keräämällä yrittäjän persoonallisuusattribuutteja. Jotta tutkimus saavuttaisi myös datan triangulaation, sekundääristä dataa kerättiin vahvistamaan aiempaa tutkimusta. Yhtenä sekundäärilähteenä toimivat kaksi artikkelia, jotka auttoivat vahvistamaan aiemmin esiin nostetut yrittäjän persoonallisuusattribuutit. Persoonallisuusattribuutteja verrattiin case-yrityksen brändin identiteettiin, jotta yrittäjän persoonallisuuden rooli brändin identiteetin rakentamisessa saataisiin selville. Tulokset osoittivat yhteyden brändin identiteetin ja yrittäjän persoonallisuuden välillä ekologisesti suuntautuneessa case-yrityksessä. Tulokset paljastivat myös joitakin yleisiä assosiaatioita joita luodaan ja vahvistetaan brändin identiteetin eri osa-alueiden avulla.

Modelling ecological values in heterogeneous and dynamic landscapes with geospatial data

Our surrounding landscape is in a constantly dynamic state, but recently the rate of changes and their effects on the environment have considerably increased. In terms of the impact on nature, this development has not been entirely positive, but has rather caused a decline in valuable species, habitats, and general biodiversity. Regardless of recognizing the problem and its high importance, plans and actions of how to stop the detrimental development are largely lacking. This partly originates from a lack of genuine will, but is also due to difficulties in detecting many valuable landscape components and their consequent neglect. To support knowledge extraction, various digital environmental data sources may be of substantial help, but only if all the relevant background factors are known and the data is processed in a suitable way. This dissertation concentrates on detecting ecologically valuable landscape components by using geospatial data sources, and applies this knowledge to support spatial planning and management activities. In other words, the focus is on observing regionally valuable species, habitats, and biotopes with GIS and remote sensing data, using suitable methods for their analysis. Primary emphasis is given to the hemiboreal vegetation zone and the drastic decline in its semi-natural grasslands, which were created by a long trajectory of traditional grazing and management activities. However, the applied perspective is largely methodological, and allows for the application of the obtained results in various contexts. Models based on statistical dependencies and correlations of multiple variables, which are able to extract desired properties from a large mass of initial data, are emphasized in the dissertation. In addition, the papers included combine several data sets from different sources and dates together, with the aim of detecting a wider range of environmental characteristics, as well as pointing out their temporal dynamics. The results of the dissertation emphasise the multidimensionality and dynamics of landscapes, which need to be understood in order to be able to recognise their ecologically valuable components. This not only requires knowledge about the emergence of these components and an understanding of the used data, but also the need to focus the observations on minute details that are able to indicate the existence of fragmented and partly overlapping landscape targets. In addition, this pinpoints the fact that most of the existing classifications are too generalised as such to provide all the required details, but they can be utilized at various steps along a longer processing chain. The dissertation also emphases the importance of landscape history as an important factor, which both creates and preserves ecological values, and which sets an essential standpoint for understanding the present landscape characteristics. The obtained results are significant both in terms of preserving semi-natural grasslands, as well as general methodological development, giving support to science-based framework in order to evaluate ecological values and guide spatial planning.

Bayesian classification of forest ecological type from satellite data

The main objective of this study was todo a statistical analysis of ecological type from optical satellite data, using Tipping's sparse Bayesian algorithm. This thesis uses "the Relevence Vector Machine" algorithm in ecological classification betweenforestland and wetland. Further this bi-classification technique was used to do classification of many other different species of trees and produces hierarchical classification of entire subclasses given as a target class. Also, we carried out an attempt to use airborne image of same forest area. Combining it with image analysis, using different image processing operation, we tried to extract good features and later used them to perform classification of forestland and wetland.

Observations on Software Testing Practice

This thesis investigates factors that affect software testing practice. The thesis consists of empirical studies, in which the affecting factors were analyzed and interpreted using quantitative and qualitative methods. First, the Delphi method was used to specify the scope of the thesis. Secondly, for the quantitative analysis 40industry experts from 30 organizational units (OUs) were interviewed. The survey method was used to explore factors that affect software testing practice. Conclusions were derived using correlation and regression analysis. Thirdly, from these 30 OUs, five were further selected for an in-depth case study. The data was collected through 41 semi-structured interviews. The affecting factors and their relationships were interpreted with qualitative analysis using grounded theory as the research method. The practice of software testing was analyzed from the process improvement and knowledge management viewpoints. The qualitative and quantitativeresults were triangulated to increase the validity of the thesis. Results suggested that testing ought to be adjusted according to the business orientation of the OU; the business orientation affects the testing organization and knowledge management strategy, and the business orientation andthe knowledge management strategy affect outsourcing. As a special case, the complex relationship between testing schedules and knowledge transfer is discussed. The results of this thesis can be used in improvingtesting processes and knowledge management in software testing.

Observations on Software Project Deviations

Software projects have proved to be troublesome to be implemented and as the size of software keeps increasing it is more and more important to follow-up the projects. The proportion of succeeded software projects is still quite low in spite of the research and the development of the project control methodologies. The success and failure factors of projects are known, as well as the project risks but nevertheless the projects still have problems with keeping the schedule and the budget and achieving the defined functionality and adequate quality. The purpose of this thesis was to find out what deviations are there in projects at the moment, what causes them, and what is measured in projects. Also project deviation was defined in the viewpoint of literature and field experts. The analysis was made using a qualitative research approach. It was found out that there are still deviations in software projects with schedule, budget, quality, requirements, documenting, effort, and resources. In addition also changes in requirements were identified. It was also found out that for example schedule deviations can be affected by reducing the size of a task and adding measurements.