Activityscape Mapping: Consumer Activity Systems as Service Context

Activity systems are the cognitively linked groups of activities that consumers carry out as a part of their daily life. The aim of this paper is to investigate how consumers experience value through their activities, and how services fit into the context of activity systems. A new technique for illustrating consumers’ activity systems is introduced. The technique consists of identifying a consumer’s activities through an interview, then quantitatively measuring how the consumer evaluates the identified activities on three dimensions: Experienced benefits, sacrifices and frequency. This information is used to create a graphical representation of the consumer’s activity system, an “activityscape map”. Activity systems work as infrastructure for the individual consumer’s value experience. The paper contributes to value and service literature, where there currently are no clearly described standardized techniques for visually mapping out individual consumer activity. Existing approaches are service- or relationship focused, and are mostly used to identify activities, not to understand them. The activityscape representation provides an overview of consumers’ perceptions of their activity patterns and the position of one or several services in this pattern. Comparing different consumers’ activityscapes, it shows the differences between consumers' activity structures, and provides insight into how services are used to create value within them. The paper is conceptual; an empirical illustration is used to indicate the potential in further empirical studies. The technique can be used by businesses to understand contexts for service use, which may uncover potential for business reconfiguration and customer segmentation.

Impact of agricultural market liberalization on food security in developing countries : a comparative study of Kenya and Zambia

This research investigates the impacts of agricultural market liberalization on food security in developing countries and it evaluates the supply perspective of food security. This research theme is applied on the agricultural sector in Kenya and in Zambia by studying the role policies played in the maize sub-sector. An evaluation of selected policies introduced at the beginning of the 1980s is made, as well as an assessment of whether those policies influenced maize output. A theoretical model of agricultural production is then formulated to reflect cereal production in a developing country setting. This study begins with a review of the general framework and the aims of the structural adjustment programs and proceeds to their application in the maize sector in Kenya and Zambia. A literature review of the supply and demand synthesis of food security is presented with examples from various developing countries. Contrary to previous studies on food security, this study assesses two countries with divergent economic orientations. Agricultural sector response to economic and institutional policies in different settings is also evaluated. Finally, a dynamic time series econometric model is applied to assess the effects of policy on maize output. The empirical findings suggest a weak policy influence on maize output, but the precipitation and acreage variables stand out as core determinants of maize output. The policy dimension of acreage and how markets influence it is not discussed at length in this study. Due to weak land rights and tenure structures in these countries, the direct impact of policy change on land markets cannot be precisely measured. Recurring government intervention during the structural policy implementation period impeded efficient functioning of input and output markets, particularly in Zambia. Input and output prices of maize and fertilizer responded more strongly in Kenya than in Zambia, where the state often ceded to public pressure by revoking pertinent policy measures. These policy interpretations are based on the response of policy variables which are more responsive in Kenya than in Zambia. According the obtained regression results, agricultural markets in general, and the maize sub-sector in particular, responded more positively to implemented policies in Kenya, than in Zambia, which supported a more socialist economic system. It is observed in these results that in order for policies to be effective, sector and regional dimensions need to be considered. The regional and sector dimensions were not taken into account in the formulation and implementation of structural adjustment policies in the 1980s. It can be noted that countries with vibrant economic structures and institutions fared better than those which had a firm, socially founded system.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.

The politics of forest bureaucracy as a subject of comparative studies.

XVIII IUFRO World Congress, Ljubljana 1986.

Mapping Road Infrastructure in Developing Countries Applying Remote Sensing and GIS - The Case of the Taita Hills, Kenya

Road transport and infrastructure has a fundamental meaning for the developing world. Poor quality and inadequate coverage of roads, lack of maintenance operations and outdated road maps continue to hinder economic and social development in the developing countries. This thesis focuses on studying the present state of road infrastructure and its mapping in the Taita Hills, south-east Kenya. The study is included as a part of the TAITA-project by the Department of Geography, University of Helsinki. The road infrastructure of the study area is studied by remote sensing and GIS based methodology. As the principal dataset, true colour airborne digital camera data from 2004, was used to generate an aerial image mosaic of the study area. Auxiliary data includes SPOT satellite imagery from 2003, field spectrometry data of road surfaces and relevant literature. Road infrastructure characteristics are interpreted from three test sites using pixel-based supervised classification, object-oriented supervised classifications and visual interpretation. Road infrastructure of the test sites is interpreted visually from a SPOT image. Road centrelines are then extracted from the object-oriented classification results with an automatic vectorisation process. The road infrastructure of the entire image mosaic is mapped by applying the most appropriate assessed data and techniques. The spectral characteristics and reflectance of various road surfaces are considered with the acquired field spectra and relevant literature. The results are compared with the experimented road mapping methods. This study concludes that classification and extraction of roads remains a difficult task, and that the accuracy of the results is inadequate regardless of the high spatial resolution of the image mosaic used in this thesis. Visual interpretation, out of all the experimented methods in this thesis is the most straightforward, accurate and valid technique for road mapping. Certain road surfaces have similar spectral characteristics and reflectance values with other land cover and land use. This has a great influence for digital analysis techniques in particular. Road mapping is made even more complicated by rich vegetation and tree canopy, clouds, shadows, low contrast between roads and surroundings and the width of narrow roads in relation to the spatial resolution of the imagery used. The results of this thesis may be applied to road infrastructure mapping in developing countries on a more general context, although with certain limits. In particular, unclassified rural roads require updated road mapping schemas to intensify road transport possibilities and to assist in the development of the developing world.