Woodfuel procurement strategies of district heating plants

Energy 28 (2003) 127–140 www.elsevier.com/locate/energy

Woodfuel procurement strategies of district heating plants A. Roos a,∗, F. Bohlin a, B. Hektor b,1, B. Hillring b a

b

Department of Forest Products and Markets, Swedish University of Agricultural Sciences, P.O. Box 7060, S-750 07 Uppsala, Sweden Department of Bioenergy, Swedish University of Agricultural Sciences, P.O. Box 7060, S-750 07 Uppsala, Sweden Received 26 June 2001

Abstract Woodfuel use in the Swedish district heating sector increased significantly from 1985 to 1999. This study analysed strategies and considerations concerning woodfuel procurement in district heating plants. Priorities and concerns in the industry involved an increased woodfuel share, ambitions to create an environmental image, cost minimisation, awareness about the role of energy policies for fuel choice, improvement of woodfuel quality and the ambition to maintain a competitive woodfuel market with several suppliers. Factor analysis yielded five dimensions in the woodfuel procurement strategies among the district heating companies: (1) increased woodfuel use; (2) import; (3) spot market woodfuel purchases; (4) focus on refined woodfuels; and (5) using price only when deciding whether to use woodfuels or other fuels. Five clusters were defined along the three strategy dimensions (1)–(3). The clusters differed concerning size, experiences from the introduction of woodfuels, perceptions about woodfuels and strategies employed to date. This paper describes different strategies that the district heating companies apply on the woodfuel market. The conclusion is that policies should consider this diversity in procurement strategies, mitigate their negative side-effects and assist to make them cost-effective.  2002 Elsevier Science Ltd. All rights reserved.

1. Introduction: woodfuels in the Swedish district heating sector Biofuel use (of woodfuels, peat, municipal solid waste and tall oil) in the district heating sector in Sweden has grown rapidly from almost 38 PJ in 1990 to 99 PJ in 1999. The largest increase during the period was recorded for woodfuels [1]. The significant rise in woodfuel use has mainly been caused by an increased demand from district heating plants responding to the combined ∗

1

Corresponding author. Tel.: +46-18-671-564; fax: +46-18-673-800. E-mail address: [email protected] (A. Roos). Independent consultant.

0360-5442/03/$ - see front matter  2002 Elsevier Science Ltd. All rights reserved. doi:10.1016/S0360-5442(02)00108-1

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effects of high energy taxes on fossil fuels, and the ability of district heating plants to shift from fossil fuels to biofuels for heat production. Today, a majority of heating plants in Sweden use woodfuels for a part of their heat production. Due to technological improvements in woodfuel harvesting and utilisation, and institutional adaptations in the sector the increased woodfuel use have been accompanied by reduced real woodfuel prices [2]. Commonly marketed woodfuel materials are bark, green chips, dry chips, upgraded materials (briquettes, pellets and powder) and firewood. Wood fibre from recycled wood is another widely available material. Fuel mixtures from wood (virgin or recycled) and various recycled waste materials and industrial by-products, e.g. cardboard and municipal waste, are also entering the market [3]. Imports of woodfuels and tall oil to Sweden have grown steadily throughout the 1990s, from 2–4 PJ in 1992 to 20–32 PJ in 1997. Woodfuel import to Sweden may, however, level out over the coming years, as new combustion capacities for solid biofuels are under way in the major exporting countries [3]. Woodfuel consumption in inland heating plants is affected by the local supply and competition for woodfuels [4]. Heating plants situated by the coast, however, can easier operate on the world market both for fossil- and woodfuels. These plants depend less on the local woodfuel market for their procurement. Sweden’s expanding woodfuel market is rather unique, mainly due to taxes on CO2 implemented in 1991. However, woodfuel use in other European countries may increase in coming years since the European Commission has set targets for renewable energy use to 12% in 2010 [5]. New restrictions within the EU for landfills of organic waste may also increase the supply of biofuels, including woodfuels. Since several countries in the European Union are contemplating implementing policies for increased biofuel use, more knowledge is needed about the strategic decision-making among players in a biofuel market. These issues concern how woodfuel procurement strategies are determined, problems during the introduction phase and the adaptation and learning that takes place as the woodfuel market grows. It also regards strategic differences between different woodfuel users. In a study of different bioenergy markets in Sweden, the US, and Austria, Roos et al. [6] identified critical factors for bioenergy technology implementation. The authors concluded that, as the market grows, unit costs are saved because of scale and network effects. Other identified factors for the success of bioenergy industries included the ability to benefit from synergies with other economic activities (e.g. the forestry or agriculture sector), a competition within the bioenergy sector that fosters learning and technical improvement, and fundamental competitive advantages for biofuels, e.g. prices and environmental image. Energy policies are, of course, also important for the success or failure of bioenergy markets. Olerup [7] described the policy process as the owners of one Swedish district heating plant decided to use woodfuels. She documented a continuous interaction of different political, professional and economic interests until the final decision was made. Sociological, pedagogical and market factors influencing bioenergy technology adoption were also investigated in a study by Rakos [8]. The objective of this study is to provide a comprehensive description of the strategies and considerations concerning woodfuel procurement among Swedish district heating plants today.

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Our analysis considers differences in the applied strategies. We identify the main strategic dimensions in the industry and describe strategic groups according to these dimensions. The results and their policy implications are then discussed. 2. Strategies for woodfuel procurement The general concept of a ‘strategy’ is not clear-cut. The diversity of the term has been clearly shown by Niemela¨ [9], who identified several views on strategy formulation and implementation: strategy as a plan, strategy as a position, strategy as a pursuit of competitive advantage, strategy as a pattern of decisions and actions, and strategy as an atmosphere or framework. We do not explicitly exclude any of these strategy concepts, but take strategy as a means to improve competitiveness to be directly relevant for our study. One important assumption of the competitive strategy concept is that strategies may differ between firms in the same industry. Porter identified three principal strategy dimensions for the firm: overall cost leadership, differentiation, and focus [10]. According to Langlois [11], firms develop these different strategies depending on their evolution and capabilities. Strategies on a factor market are seldom discussed in the literature, which normally focus on product markets. However, the strategy concept by Porter [10], described above, could be applied also for an input procurement process. In this context cost leadership represents a straightforward orientation on low cost and low quality fuel assortments, differentiation signifies the ability to switch between fuels as price relations change, and focus a strategy for a few, normally high quality, fuel assortments. 3. Materials and methods This paper is based on a survey in 1999 among managers and business area representatives of all major Swedish district heating plant. The issues covered in the questionnaire have been identified in the literature and a qualitative in-depth study of four district heating companies [12]. A pilot questionnaire was developed and sent out to four district heating companies and discussed with them before the main survey was conducted. The questionnaire was also discussed with representatives of the Swedish district heating association. Both these validations gave rise to some modifications of the questionnaire, primarily for reasons of comprehension. The basic survey questions concerned technical data about the heating plant and about the fuel consumption. If woodfuel was used at the heating plant, additional questions were asked. The district heating manager responded to most issues using a scale from 1 (complete disagreement) to 7 (complete agreement) to indicate the degree to which he concurred with a number of statements. This study is based on the last section in the larger questionnaire. It was subdivided into parts about ‘procurement strategies’, ‘woodfuel quality issues’, ‘suppliers and contracts’, and ‘plans for changes in energy policy’. The questions involved both the explicit strategy, and thoughts about the market situation. The questionnaire was distributed to 156 district heating companies. A second copy was mailed to those who had not responded after four weeks. The response rate was 58%. A further analysis

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revealed that non-respondents on average operated heating plants with significantly smaller sizes than average. This difference was also noticed for woodfuel quantity while woodfuel shares were almost equal, 46% for respondents and 43% for non-respondents. The respondents accounted for 76% of the total heat output and 73% of the total woodfuel use in the district heating sector. The lower response rate among the small heating plants may be due to less total management staff available in this category, and a view that industry-wide surveys do not further the interests of small heat producers with modest woodfuel needs. No adjustments (e.g. weighting) because of the respondent bias were made. The bias must, however, be considered in the further analysis of the results. Of the responding population 68 (76%) used woodfuels in their fuel mix. This group constituted the basis for the further analysis. For background information mean scores and distributions for each question about woodfuel strategies for the future are shown in the Appendix A. Highest agreements were given to the importance of fuel price, environmental and wood quality issues in the decision-making about woodfuel use. There was a need among the heating companies to maintain good contacts with several suppliers. Few respondents had plans to start up their own woodfuel production. The answers reveal that national policies are of a greater importance for the fuel choice than local policies. Many heating plant managers have plans for an alternative fuel source if changed policies reduce the competitiveness of woodfuels. We used principal component (factor) analysis [13] to summarise the information about the considerations and strategy choices by the energy companies in a few key components representing general factors that decide their behaviour on the market. These components can also be considered as ‘strategic dimensions’ of fuel procurement in the industry. Cluster analysis is a generic term for a group of techniques that produces classifications in a data set. It is often applied to define groups in a population to simplify a description, or to generate hypotheses [14]. Here, the primary objective was to provide a convenient summary of a multivariate data-set in a descriptive study. Cluster analysis has often been used to define different strategic groups and behaviours in a market context. The Ward method, a hierarchical agglomeration clustering technique, was used in the analysis. This method has worked well in earlier similar studies [15,16]. A review by Punj and Steward [17] of a large number of clustering studies showed that the Ward method outperformed most alternative clustering methods. 4. Results 4.1. Factor analysis results We subjected the questions about explicit strategy to factor analysis. Six survey questions, (questions 12, 14, 15, 16, 23 and 24) were left out of the analysis since they focused on opinions and considerations rather than explicit strategic plans. Questions where more than 70% of the respondents were found at one end of the scale (questions 2, 11, 12 and 20) were also removed. Furthermore, question 10 was excluded since it concerned a miscellaneous option, which did not contribute to the interpretation of the results. Due to missing values for some questions, eight observations could not be used for the factor analysis resulting in 60 useable observations. Kaiser’s measure of sampling adequacy was 0.58. While this value may be considered some-

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what low, it is nevertheless adequate for factor analysis [18]. Principal component factor analysis with Varimax (orthogonal) rotation was carried out. Five factors had an eigenvalue higher than 1.0, which is normally a limit for considering factors in a factor analysis. The five factors accounted for 61% of the variance in the sample. The result of the factor analysis is presented in Table 1. Factor 1 is mainly defined by high scores for the assertion that the woodfuel share will increase, associated with the intention to increase local woodfuel purchases. An increased use of logging residues and by-products also scored high. Factor 1 correlates negatively with cost minimisation. This result suggests that the decision to increase woodfuel use is partly supported by non-economic arguments. Factor 2 consists of a high degree of agreement that the consumption of recycled import will increase due to price arguments, associated with an ambition to use several suppliers and different contract lengths. Factor 3 reflects a trend towards minimising woodfuel costs for each heating season, i.e. the emphasis was on spot contracts in the woodfuel procurement. This factor also incorporates ambitions to determine the best woodfuel mix for the boiler and to improve contracting practices. Factor 4 reflects a preference for pellet heating, a tendency towards long-term contracting with well-known suppliers, and plans for eventual policy shifts. Finally, factor 5 includes a clear cost minimising strategy focusing on low-grade woodfuels and spot quantities. This strategy dimension also correlates with a willingness to buy fossil fuels if they were cheapest. 4.2. Clustering results We used clustering to be able to classify the companies in different strategic groups. We used the scores of the three first factors to describe the most fundamental aspects of woodfuel procurement strategies for the cluster analysis. Moreover, using only a few variables in the clustering exercise allows an easy and straightforward interpretation of the results whereas too many variables may obscure the true structure of the problem [14]. Since, in this case, clustering was carried out using factor scores with mean 0 and variance 1 no standardisation of the variables was necessary. There is no clear-cut method for choosing the best number of clusters [14]. The literature recommends that the decision is based on different statistics and the possibility of providing realistic explanations of the problem at hand. Punj and Steward [17] concluded that the decision should be guided by the general possibility to interpret the results and the usefulness of the solution for further analyses. Accordingly, we arrived at a five-cluster solution based on the statistics pseudo-t2 and semi-partial R2 [18, pp. 561–562]. The results are presented in Table 2. The solution is also shown in the three graphs in Fig. 1. Aldenderfer and Blashfield [19, p. 66], concluded that a test on variables that has not been used to generate the clusters is one of the best ways to validate a cluster solution. The clusters were, therefore, compared concerning a set of variables describing technological and other aspects of the heating plant. The clusters were also compared regarding other sections in the questionnaire about the historical development during the woodfuel introduction phase. In 10 cases out of 54 the comparisons gave significant differences between the clusters in F-tests applying the 5%-level of significance, 21 were significant at the 20% level (Table 3). We could identify the following cluster profiles.

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Table 1 Principal component factor analysis results Factors and factor labels Increase woodfuel use 5 We will increase the local 0.85 purchases of woodfuel 1 We will increase the woodfuel 0.84 share 8 We will increase the share of 0.78 logging residues (tops and branches) 4 We will increase the import of woodfuel 7 We will increase the share of recycled woodfuels 17 We prefer to distribute our contracts on more suppliers and time periods 3 Import or domestic woodfuel is only a price issue 18 We prefer to buy as cheap as possible for each heating season 13 We are trying to determine the best woodfuel qualities for our boiler 21 We want to improve contracting with our suppliers 6 We will increase the share of refined woodfuels 25 We have concrete plans how to act if policy shifts dramatically reduce competitiveness for woodfuels 19 We prefer having long-term contacts with a few suppliers 22 Our company can and will ⴚ0.40 chose the most cost effective fuel, including fossil fuels 9 We will increase the share of 0.50 by-products (e.g. bark and shavings) Eigenvalue 2.95 Proportion explained 0.20

Import

Short (spot market) contracts

Wood pellets

Cost minimisation

0.84 0.76 0.72

0.46

0.41 0.81 0.67

0.58 0.68 0.55

0.55

ⴚ0.33 0.72

0.70

2.54 0.17

1.51 0.10

1.26 0.08

1.17 0.08

Bold type denotes variables used to define the factor. Factor loadings between ⫺0.30 and 0.30 are represented by empty space

A. Roos et al. / Energy 28 (2003) 127–140

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Table 2 Clustering analysis regarding woodfuel procurement strategies based on Ward method Variable

Cluster 1 (n ⫽ 12)

Factor 1a increase 0.82 woodfuel Factor 2b import ⫺0.64 ⫺0.51 Factor 3c spot market

Cluster 2 (n ⫽ 14)

Cluster 3 (n ⫽ 14)

Cluster 4 (n ⫽ 15)

⫺1.05

0.61

⫺0.27

⫺0.93 0.21

⫺0.07 0.81

1.28 0.27

Cluster 5 (n ⫽ 5)

ANOVA F-Stat

P-value

0.07

14.15

0.00

0.48 ⫺2.40

36.83 36.39

0.00 0.00

a

Cluster 1 differs from 2 and 4. Cluster 2 differs from 3, 4 and 5. Cluster 3 differs from 4. Cluster 1 differs from 3, 4 and 5. Cluster 2 differs from 3, 4 and 5. Cluster 3 differs from 4. Cluster 4 differs from 5. c Cluster 1 differs from 2, 3, 4 and 5. Cluster 2 differs from 3 and 5. Cluster 3 differs from 4 and 5. Cluster 4 differs from 5. All comparisons at the 0.05 level. b

4.2.1. Cluster 1 Heating plants in this cluster focused on increasing their woodfuel share. They were not interested in import or spot market purchases. They were usually medium-size plants where woodfuel introduction came late. Few technical or fuel quality problems had been experienced. Although the managers in this group thought that energy policy had favoured woodfuels, they did not think that the market was too dependent on policies. Good import possibilities were not a priority issue for this group. A favourable environmental image, was more important. 4.2.2. Cluster 2 This group showed a low interest in increasing woodfuel use or importing woodfuels. They were somewhat interested in spot purchases. Many members of the cluster had experienced problems defining the best woodfuel quality. They also had technical problems in the introduction phase. Few initiatives had been undertaken to improve contracting practices on the market. The plant management hoped that future woodfuel deliveries would improve in quality and they thought that fuel choices depended too much on national policies. The group gave the impression to be somewhat negative toward woodfuel. 4.2.3. Cluster 3 Members in this cluster planned to increase woodfuel use mainly through local supply but also making spot purchases. Imported woodfuels were less important. This group consisted mainly of late adopters. Their responses indicated that they had sensed some insecurity about woodfuel supplies in the beginning, but they had not encountered serious technical problems. The group thinks that policies have favoured woodfuels. In their view, woodfuel use depended too much on policies. This group displayed similarities with group 1, but it was less driven by policies and less interested in collaborating with other companies and more likely to take own market initiatives.

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Fig. 1. Cluster presentation. (a) More woodfuel and Import, (b) more woodfuel and spot purchases, (c) import and spot purchases.

4.2.4. Cluster 4 The group might increase the woodfuel share but it was determined to shift towards imported quantities and, to a lesser degree, toward spot purchases. The cluster primarily included large heating plants that had solved most of the technical problems. They were dissatisfied with woodfuel deliveries and had focused on contracting improvements. Cooperation with other heating plants for developing definitions of woodfuel quality assortments had been a priority. This category did not place a high value on the local economic importance of woodfuel purchases. 4.2.5. Cluster 5 Heating plants in this cluster were moderately interested in increasing the woodfuel use and to import. The group was not at all interested in spot market purchases. It consisted of small plants

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Table 3 Cluster means for non-clustering variables Variable

Cluster 1 Cluster 2 (n ⫽ 12) (n ⫽ 14)

Plant size 258 Introduction year 89.3 2.1 There was a large 3.2 insecurity about woodfuel supplies 2.6 When woodfuel was 1.9 introduced it was difficult to define the fuel quality to the suppliers 2.7 Woodfuel generated 3.1 technical problems 2.10 Contract writing has 2.4 become easier 2.12 Delivered quantities 5.9 have followed what was contracted 2.16 Woodfuels have 2.5 generated continued disturbances that had to be repaired 2.18 Changes in the energy 4.8 policy after the investment have favoured woodfuels 3.3 We have taken 4.4 initiatives to develop contracting practices 3.5 We have taken 2.8 initiatives to develop collaboration with other enterprises 3.6 We have taken 3.7 initiatives to develop woodfuel quality and assortments on the market 3.7 The company has 1.6 actively tried to increase the import of woodfuels 4.2 Woodfuels are better for 6.2 the external environment than other fuels 4.4 Large local woodfuel 6.3 supply is important for our woodfuel use

Cluster 3 (n ⫽ 14)

Cluster 4 (n ⫽ 15)

Cluster 5 (n ⫽ 5)

ANOVA F-Stat

P-value

153 88.1 3.2

130 89.4 1.9

672 88.5 3.5

111 83.2 4.6

4.31 1.54 2.21

0.00 0.20 0.08

4.9

2.8

3.3

2.8

6.66

0.00

5.0

1.8

1.4

1.8

2.44

0.06

2.4

2.2

3.5

2.4

1.7

0.16

6.3

5.6

5.3

6.6

2.44

0.06

2.9

3.8

3.3

1.6

2.39

0.06

2.9

2.8

3.7

4.0

1.96

0.11

3.9

4.1

5.7

5.2

2.39

0.06

3.0

1.9

3.9

3.0

2.75

0.04

3.3

1.9

4.4

4.4

5.34

0.00

1.8

1.6

4.3

1.2

8.04

0.00

5.6

6.4

4.9

5.4

2.47

0.06

5.1

6.1

4.5

6.6

3.70

0.01

(continued on next page)

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Table 3 (continued) Variable

4.5 Good import possibilities are important for our woodfuel use 4.6 Our woodfuel use stimulates economic activity in the region 4.7 The market depends too much on political decisions 5.12 Woodfuel use is important for our environmental image 5.14 It is important that the woodfuel delivered improves 5.23 Our woodfuel use depends to a large extent on national policies

Cluster 1 Cluster 2 (n ⫽ 12) (n ⫽ 14)

Cluster 3 (n ⫽ 14)

Cluster 4 (n ⫽ 15)

Cluster 5 (n ⫽ 5)

ANOVA F-Stat 14.9

P-value

1.2

1.6

2.1

4.9

1.2

0.00

5.5

4.7

6.1

4.1

5.4

3.89

0.01

4.6

6.4

6.5

5.3

6.6

6.83

0.00

6.8

6.2

6.4

5.9

5.4

1.76

0.15

4.8

4.7

5.9

5.8

5.6

2.89

0.03

5.0

6.1

4.7

5.0

3.8

2.40

0.06

Insignificant at 20% level: 33 questions.

and early adopters that were satisfied with the present system for woodfuel use. They reported few disturbances in the operation and had taken initiatives to develop woodfuel quality and assortments on the market. Managers in this group also considered local woodfuel supply important. They felt that the market (but not their own decisions) depended too much on policymakers. 5. Discussion Key dimensions in the fuel procurement strategies in district heating are increased woodfuel use, import, spot market woodfuel purchases, refined woodfuels, and price-priority when deciding to use biofuel or fossil fuels. The five clusters can be characterised as different approaches to increase woodfuel in the energy mix. Cluster 1 includes heating plants that focus on a woodfuel increase based on local resources. Cluster 2 members are negative towards further increases of woodfuel use but they may go into the spot market. Cluster 3 combines local supply with spot purchases. Cluster 4 is interested in import quantities and cluster 5 is a small group of heating companies clearly reluctant to buy spot quantities. Some background factors may further explain these strategy choices. When woodfuels were introduced in the energy sector during the 1980s and 1990s, they differed from the traditional fuel types oil and coal rationale, partly because of their variability. Some plant managers had problems to adapt to this new fuel. They required similar quality and contractual standards on woodfuels as for the fossil fuels. Others, however, showed great enthusiasm and embraced woodfuels as a vital component in a sustainable energy system. In some municipalities political support

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was also strong for renewable energy options. These factors may have influenced the pace of the introduction and how biofuels were regarded by local plant managers. Of course, the trend towards more biofuel was driven by changed relative prices. Through the introduction of carbon taxes in 1991 woodfuels often became the least expensive option. However, this shift took time since old contracts had to be phased out and new investments had to be made. In this context, it is surprising to see in our results that the intention to increase woodfuel use is associated with a low rating for the economic motive. The differentiation in the fuel procurement strategies also support Porter’s [10] description of what normally happens in a mature industry. The positions today of the heating plants in the different clusters may reflect local conditions, but they could also describe ambitions to focus on specific markets to reduce the effect of buyer competition. This may explain that some heating plants focus on local woodfuels and others buy wood pellets or recycled wood on distant markets. The differences may also describe an evolution where the heating company in the beginning rely on local fuels to reduce risks. Later managers may realise that there is an opportunity to reduce costs by being more active on different (long-distance, international, spot) markets. Burning pellets do not require as costly conversions of fossil fuel furnaces as for example chip burning. Therefore, it may have been seen as a quick way of answering to a policy shift without making too heavy investments. Pellets involve lower fixed costs but higher variable costs since they are more expensive than, e.g. wood chips. The use of pellets may also reflect specific conditions in individual heating plants, e.g. lack of storage capacity of bulky woodfuel assortments. The development of import procurement strategies among Swedish district heating companies has international implications. By and large, the Swedish district heating sector has initially relied on a domestic supply of woodfuels for its development. Some Swedish heating plants have gradually developed international sources of supply, which makes them less dependent on the domestic suppliers. This evolution could be viewed as beneficial for the sector since the diversification enhances the robustness of the bioenergy system. It indicates that woodfuel procurement strategies—local fuels, import, spot purchases—should be allowed to differ according to the specific conditions. Our study also illustrates the learning and the development that takes place in the market. A larger European biofuel market will probably develop differently. International woodfuel trade could become more important as potential low-cost producers—inside and outside Europe— would have a much larger market to develop. A more integrated biofuel market in Europe, where different procurement strategies are to be applied, would probably be one key factor for the success of the bioenergy industry in the region. One main lesson of our study is that policymakers should design policies to facilitate each strategy dimension while reducing their negative external effects. Our first strategic dimension creates a need for resource assessments and local environmental impact studies. The local road network should also be assessed. For the long-distance trade and spot markets (factor 2 and 3), harmonisation of contractual and quality standards is needed. This is normally a time-consuming process where the active involvement of authorities and all players in the market is important. In some cases there may also be a greater need to develop equipment that is adapted to a variable fuel. To improve the pellet market (factor 4) there is also a need for quality standards and research on production technologies.

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Acknowledgements The project was financed by the Swedish Energy Agency under its program of system studies.

Appendix A Answers to strategy question, frequencies in percent Do not agree at all Question Woodfuel quantities 1 We will increase the woodfuel share 2 We will reduce the share of woodfuel 3 Import or domestic woodfuel is only a price issue 4 We will increase the import of woodfuel 5 We will increase the local purchases of woodfuel 6 We will increase the share of refined woodfuels 7 We will increase the share of recycled woodfuels 8 We will increase the share of logging residues (tops and branches) 9 We will increase the share of by-products (e.g. bark and shavings) 10 We will increase the share of other woodfuels 11 We will be active to acquire an environmentally friendly profile for our company 12 Woodfuel use is important for our environmental image Woodfuel quality 13 We are trying to determine the best woodfuel qualities for our boiler

1

2

5

6

7

14.7

19.1

27.9

5.0 68

9.0

3.0

1.5

3.0

2.0 67

7.5

6.0 14.9

9.0

28.4

14.9

4.3 67

55.4 10.8

7.7 10.8

4.6

6.2

4.6

2.4 65

10.8

3.1 27.7

10.8

21.5

20.0

4.7 65

8.8

3

Agree completely

5.9

4 2.9 20.6

58.2 14.9 10.4 19.4

6.2

Mean N

40.3 17.9

6.0

7.5

9.0

11.9

7.5

2.9 67

52.2

9.0

3.0

6.0

11.9

7.5

10.4

2.8 67

37.9

7.6

6.1 12.1

18.2

7.6

10.6

3.3 66

25.8

3.0

1.5 18.2

18.2

16.7

16.7

4.2 66

27.3 12.1

1.5 21.2

15.2

12.1

10.6

3.6 66

0

4.4

1.5

5.9

7.4

29.4

51.5

6.1 68

1.5

1.5

0

5.9

7.4

26.5

57.4

6.2 68

2.9

5.9

1.5

8.8

13.2

27.9

39.7

5.7 68

A. Roos et al. / Energy 28 (2003) 127–140

14 It is important that the 0 4.4 woodfuel delivered improves 15 The woodfuel qualities need 4.4 5.9 to be more standardised 16 Woodfuel measurement 4.4 8.8 procedures need to be improved and standardised Suppliers and contracts 17 We prefer to distribute our 5.9 14.7 contracts among more suppliers and time periods 18 We prefer to buy as cheap 1.5 6.0 as possible for each heating season 19 We prefer having long-term 1.5 9.0 contacts with a few suppliers 20 We want to have our own 67.2 14.9 woodfuel production 21 We want to improve 7.4 2.9 contracting with our suppliers How would you act if energy policies change? 22 Our company can and will 8.8 4.4 chose the most cost effective fuel, including fossil fuels 23 Our woodfuel use depends 5.9 5.9 to a large extent on national policies 24 Our woodfuel use depends 22.1 23.5 to a large extent on local policies 25 We have concrete plans how 20.9 19.4 to act if policy shifts dramatically reduce competitiveness for woodfuels

139

1.5 14.7

33.8

26.5

19.1

5.3 68

2.9 20.6

23.5

20.6

22.1

5.0 68

0

27.9

13.2

16.2

29.4

5.0 68

8.8 11.8

11.8

20.6

26.5

4.8 68

3.0 13.4

13.4

19.4

43.3

5.6 67

7.5 11.9

13.4

28.4

28.4

5.3 67

0

1.5

1.7 67

6.0

7.5

3.0

13.2 39.7

23.5

5.9

7.4

4.2 68

2.9 10.3

22.1

19.1

32.4

5.2 68

4.4 13.2

17.6

26.5

26.5

5.2 68

7.4

14.7

14.7

5.9

3.4 68

10.4 16.4

9.0

13.4

10.4

3.6 67

11.8

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