Key capabilities in knowledge-intensive service business

The purpose of this study is to identify key capabilities in knowledge-intensive service business. Current service research lacks evidence on this topic, since knowledge-intensive services constitute a very heterogeneous group, making the identification of key capabilities challenging. To bridge this gap, a conceptual framework is developed, integrating discussion on knowledge intensity with the classical service features. Empirical data are collected from two case firms with the help of focus groups, theme interviews and a survey. Based on the developed framework and analyzed data, we identify four specific capability categories of knowledge management, service productization, project management, and relationship orchestration.     

Neural Network Used to Analyze Multiple Perspectives Concerning Computer-Based Learning Environments

The aim of this study is to explore thepossibilities of neural networks to support theanalysis and representation of the complex qualitativedata in behavioral sciences. In this study for testingthe methodological possibilities we analysed data ofdesigners', teachers' and students' interpretations ofthe same educational software. The intentions of threedesigners concerning the interaction with their ownsoftware were compared with the interpretations ofthree teachers' anticipations of the interaction, andwith the actual learning situations of three pairs ofstudents. The particular kind of neural network usedfor the data analysis was TS-SOM (Koikkalainen, 1994),which is a variant of a self-organizing map SOMalgorithm (Kohonen, 1984). On the basis of the resultsit can be concluded that the method seems to bepromising to handle and visualize the data reductionin a systemic manner without oversimplifying thecomplex data. Furthermore, the method supports theresearcher in finding the most essential places whereto focus more detailed qualitative analyses. Thevisualization tools also allow us to verify theinterpretations between independent raters, whichincreases the reliability of qualitative dataanalysis.     

Nonparametric Methods for Evaluating Economic Efficiency and Imperfect Competition

This article unifies and extends ideas from nonparametric production analysis and DEA for testing organizational efficiency. We show how the admissible price set can be restricted to account for prior information on prices. These restrictions may relate prices to input and output quantities in order to test noncompetitive behavior of the evaluated decision making unit. While the resulting efficiency tests cannot always be cast into linear programming problems, we discuss various solution strategies for the tests. Thereby we consider the question when does local optimality of the result guarantee global optimality. We also show how the decision maker's preferences, for example ranking information, can be adopted into DEA models in a simple manner. Finally, the approach with price restrictions is illustrated with an application to test noncompetitive behavior of the pulp and paper industries in Finland.     

Biodiversity value and the optimal location of forest conservation sites in Southern Finland

Safeguarding biodiversity has been one of the most important issues in environmental and forest policies since the 1990s. In Southern Finland, decisions concerning further actions for the preservation of forest biodiversity will be made in the coming years. To support policy making, we present a multi-regional model that is applicable in determining the economically optimal regional allocation of conservation sites. Three habitat quality models are evaluated to calculate habitat quality indices used as a surrogate for a biodiversity value in a forest sector model. The scenarios presented provide information about the economic impacts of conservation choices on the forest sector. The overall economic impacts of conservation depend on its scale and regional allocation. Conserving land with high biodiversity value can have less adverse impact on the forest sector than conservation of typical commercial forest sites. When optimizing conservation set-asides, we found that set-asides targeted to certain regions possessing higher/lower than average relative share of ecologically valuable land, caused lower/higher adverse economic impacts on the forest sector. Because it is expensive to search land suitable for conservation, these regions could be respectively favoured/avoided when asking forest owners to offer their land for the new conservation program in Southern Finland, which will be based on voluntariness.     

Real option analysis of a technology portfolio

This article contributes to methodology of real options analysis of investments in capital intensive process industries, where relatively homogenous outputs are produced using commonly known production technologies. In addition to capacity expansion, the method can be used for analysis of mergers and acquisitions. Valuation of the real option is based on bid price; i.e., the maximum price the firm is willing to pay. To find such a price, stochastic optimization with an expected utility criterion is used to determine investments in product specific technologies as well as in publicly traded financial instruments (the competing investments). To operationalize the valuation principle, we develop a double binary tree employing Kalman filter for scenario generation. For exponential utility, valuation is carried out by dynamic programming. We extend known methods to allow interdependence of the mill cash flow and return on competing financial investments. For forest industries, we provide an illustration, where the underlying price process in our Kalman filter application is a vector error correction model.     

Wood biomass use for energy in Europe under different assumptions of coal,gas and CO2 emission prices and market conditions

This study examines the effects of different coal, natural gas and carbon emission prices and market situations on the use of wood for electricity and heat production in the European Union. The analysis is carried out using the global forest sector model EFI-GTM expanded to cover electricity and heat production from wood, coal, natural gas, wind and solar energy. Analysis shows that with low coal and gas prices, use of wood for energy will be limited to low cost logging residues. With high coal, and especially natural gas prices, industrial wood also comes to be used for energy. At a carbon price of 100 €/tCO₂, some 32 Mm³ of industrial wood, in addition to 224 Mm³ of logging residues, are projected to be used for electricity and heat in the EU region (including Norway and Switzerland) in 2030. The relatively low quantity of industrial wood used by the energy sector despite the collapse of the use of coal is explained by the fact that under high CO₂ prices, other energy forms like natural gas, solar and wind energy become more and more competitive. However, the amount of industrial wood used for energy may substantially increase with subsidies for using wood for electricity and heat, even with relatively low carbon prices. With a high coal and gas price and a carbon price of 100 €/t, a subsidy of 30 €/MWh to the wood based and coal with wood co-firing electricity production will have a significant impact on the European wood based sector. Depending on the development of the market demand for forest industry products, such a subsidy may cause a 10–12.5% reduction in forest products production, a 6–9% increase in harvest level, about 30–60% increase in the pulpwood prices, and a 6–9 fold increase of wood imports in the EU, compared to the respective case without a subsidy in 2030.