Forest owners’ choice of reforestation method: an application of the theory of planned behavior

Forest Policy and Economics 7 (2005) 393 – 409 www.elsevier.com/locate/forpol

Forest owners’ choice of reforestation method: an application of the theory of planned behavior Heimo Karppinen * Finnish Forest Research Institute, Unioninkatu 40 A, Helsinki FIN-00170, Finland Received 25 September 2002; received in revised form 27 May 2003; accepted 24 June 2003

Abstract The theory of planned behavior (TPB) is applied in the context of Finnish non-industrial private forest owners’ (NIPF) decision-making. Forest owners’ choice of reforestation method, i.e. choice between natural reforestation and seeding/planting, is investigated empirically on the basis of mail inquiry data from two regions in Finland (n = 154). The choice of natural reforestation is predicted from forest owners’ attitude, subjective norm and perceived behavioral control factors (e.g. soil conditions). In addition to the theoretically grounded factors, the effects of past experience of natural reforestation, use of own labor force in silviculture and former delays in reforestation, as well as the effects of forest owners’ demographic characteristics and ownership objectives are analyzed. Forest owners’ choice of natural reforestation could be explained according to the theory of planned behavior in a satisfactory magnitude. Concerning the direct effects, the attitude was the most powerful explanatory factor in the regression models, and the norm pressure and control factors had clearly smaller but mutually equal effects on the intention to use natural reforestation. Favorable past experience of natural reforestation had a clear positive effect on intention. Considering both direct and indirect effects via attitude, norm and perceived behavioral control, former experience was the most important explanatory factor. Only a minor part of the regeneration areas are reforested by natural regeneration. Clear cuttings, supplemented by replanting or seeding, is the dominant method. According to the results, natural reforestation is associated with positive beliefs and favorable attitudes. In addition, forest owners seem to obey the advice of forestry professionals. Obviously, the avoidance of natural reforestation in practice could be explained, more than is shown in the study results, by controlling factors, such as soil conditions. D 2003 Published by Elsevier B.V. Keywords: Attitudes; Finland; Forest regeneration; Non-industrial private forest owners; Theory of planned behavior (TPB)

1. Introduction One of the most frequently applied socio – psychological theories in the study of attitudes and behavior is the theory of reasoned action (TRA) developed by * Corresponding author. Tel.: +358-10-211-2238; fax: +358-10211-2104. E-mail address: [email protected] (H. Karppinen). 1389-9341/$ - see front matter D 2003 Published by Elsevier B.V. doi:10.1016/j.forpol.2003.06.001

Ajzen and Fishbein (1980). According to the theory, actual behavior is explained by behavioral intentions. The attitude towards the specific behavior and the subjective norm are expected to causally precede the behavioral intention. The TRA model has been applied in several fields of human conduct, for instance, in studies of consumer behavior, family planning, voting behavior, dieting, soil conservation on farms, blood donation, drug use and energy con-

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servation (Ajzen and Fishbein, 1980; Lynne and Rola, 1988; Sheppard et al., 1988; Arvola et al., 1999). Private forest owners’ harvesting intentions have also been investigated using TRA as a theoretical framework (Young and Reichenbach, 1987). There are many kinds of behaviors that cannot be assumed to be dependent only on volitional control. Therefore, Ajzen modified the theory by adding a new explanatory factor, perceived behavioral control. This resulted in the theory of planned behavior (TPB) (Ajzen, 1991b; Ajzen and Driver, 1992a). The control factor describes the perceived ease or difficulty of performing the specific action evaluated by the actor himself. The TPB theory has been applied, for instance, in leisure studies (Ajzen and Driver, 1992a,b), in blood donation research (Giles and Cairns, 1995) and in studies on conservation technology on farms (Lynne et al., 1995). In Finland, Pouta and Rekola (2001) applied the theory to a study of the public’s willingness to pay for abatement of forest regeneration. In this study, the theory of planned behavior is tested in the context of Finnish non-industrial private forest owners’ (NIPF) decision-making. NIP forest owners control 62% of Finnish forest land and provide approximately 80% of the domestic roundwood used by the export-oriented forest industries. Forest owners’ choice of reforestation method is investigated empirically on the basis of data from two regions in Finland. The selection of reforestation method here means the choice between natural reforestation and artificial reforestation (seeding/planting). Seeding and planting presupposes clear cutting and natural reforestation can be carried out by shelterwood or seed tree method. According to a recent study (Karppinen, 2001), almost two thirds of the Finnish forest owners would favor natural reforestation in their forests if they could make the choice freely, ignoring any limiting factors (e.g. soil fertility). Every fourth would favor artificial reforestation. However, more than half of the regeneration area in the Finnish private forests has been reforested by planting and one fifth by seeding. Only one quarter of the area has been reforested by natural regeneration (Karppinen, 2001). Favorable attitudes alone do not explain owners’ reforestation behavior; norms and controlling factors also have a role. Finnish private forestry is particularly interesting from the point of view of reforestation studies. First,

there is the legal obligation to reforestation after final fellings within 5 years of the start of the fellings and in 3 years from the completion of the final cuttings (The Forest Act, 1996). Until 1991, obligatory deposits were also required to ensure reforestation after clear cuttings. Another institutional characteristic is the revision of non-legally binding silvicultural recommendations to encourage natural reforestation (Hyva¨n metsa¨nhoidon suositukset, 2001). The key issues in forest regeneration include the selection of the most appropriate tree species from the point of view of roundwood production and the choice of the reforestation method that leads to successful reforestation results. However, the reforestation decision should also take into account environmental and recreational aspects of forests. In natural reforestation, the possible need for supplementary planting must also be recognized. In the public debate, it has been suggested that forest owners might avoid clear cutting followed by planting or seeding in order to maintain biodiversity and forest scenery even in those stands where artificial regeneration would be the most appropriate method. The selection of an inappropriate but inexpensive reforestation method, e.g. natural reforestation without site preparation, can also cause delays in the completion of reforestation. Changes in the ownership structure of private forestry took place during the 1990s, continuing the trend begun in the 1970s. The main changes were a decline in the number of farmer owners; an increase in the number of owners who no longer live on their forest holding; increased migration to urban areas and an ageing of the population of forest owners. Polarization has also occurred in the size distribution of forest holdings, so that there are now a slightly greater number of both small and large holdings (Karppinen et al., 2000). The structural change and the changes in objectives of forest ownership (Karppinen, 2000) have been considered to influence forest owners’ attitudes in favor of natural reforestation due to increased environmental and aesthetic concerns. Very few studies have been carried out concerning forest owners’ decision-making regarding the method of reforestation. Saksa et al. (1999) investigated forest owners’ rationale for choosing the method of reforestation. The most important reasons for favoring natural reforestation proved to be the natural potential

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of the stand to regenerate, low costs and good quality of trees. In addition, forest owners’ expectations concerning natural reforestation included labor extensiveness, good reforestation results and maintenance of forest scenery. The present study investigates Finnish NIPF owners’ choice of reforestation method using the theory of planned behavior as a theoretical framework. The choice of natural reforestation, the intention, is predicted from the attitude, subjective norm and perceived behavioral control factors. Besides testing the applicability of the theoretical model in reforestation decisions, the study produces information on forest owners’ beliefs and experienced norm-pressure concerning natural reforestation. In addition, the effects of former delays in reforestation, past experience of natural reforestation, use of own labor force in other silvicultural measures, as well as forest owners’ demographic characteristics and ownership objectives are analyzed. The article is organized as follows. Section 2 presents the theoretical framework of the study. Data and variables are described in Section 3 followed by the presentation of the study results in Section 4. The results are discussed in Section 5 and conclusions drawn in Section 6.

2. Theoretical framework Two theoretical orientations are essential in the study of attitudes. The tripartite view of attitude divides attitudes into three underlying components: a cognitive component referring to beliefs and knowledge concerning the attitude object, an affective component referring to emotions towards the attitude object and a conative component dealing with intentions and actual behaviors with respect to the attitude object (e.g. Rosenberg and Hovland, 1960). However, the unidimensionalistic concept of attitude regards attitude as a single affective construct. Cognitive and conative components are separated from attitude. The cognitive component is called beliefs and the conative component intentions and behaviors. In the unidimensionalistic orientation, the tripartite view of attitude is further developed by assuming causal linkages between these theoretical constructs (Lutz, 1991).

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Ajzen and Fishbein (1980) developed a unidimensionalistic theory called the theory of reasoned action (TRA). The basic characteristic of the TRA is the notion that in order to predict a specific behavior, it is necessary to measure a person’s attitude towards performing this specific action, instead of measuring the general attitude towards the object at which the behavior is aimed (Lutz, 1991). According to the TRA, actual behavior is explained by behavioral intention, which is preceded by attitude towards the specific behavior and subjective norm. In the causal chain, the attitude is composed of the beliefs concerning the specific behavior and the evaluations of their outcomes. Subjective norms are preceded by normative beliefs and the motivation to comply with the specific referents. All the components of the TRA model should be compatible with each other with respect to the specific action, the target at which the behavior is aimed, the context and time (Ajzen and Fishbein, 1980). Ajzen later modified the TRA and resulted in the theory of planned behavior (TPB) (Ajzen and Madden, 1986; Ajzen, 1991a,b; Ajzen and Driver, 1992a). The theory was extended beyond volitional control by a new explanatory factor, perceived behavioral control. It describes the perceived ease or difficulty of performing the action evaluated by the actor himself. It is assumed to reflect past experience and anticipated impediments and obstacles based on second hand information. Perceived behavioral control can often be regarded as a substitute of actual control, depending on the accuracy of the perceptions. Perceived behavioral control is causally preceded by control beliefs and perceived power of the particular control factor to facilitate or inhibit behavior. The theory of planned behavior can be expressed mathematically as follows (Young and Reichenbach, 1987; Ajzen, 1991b; Lynne et al., 1995): BfBI fw1 A þ w2 SN þ w3 PBC ¼ w1

k X i¼1

bi ei þ w2

m X i¼1

nbi mci þ w3

n X

cbi pi ;

i¼1

where B = behavior, BI = behavioral intention, A=(global) attitude towards the specific behavior, SN = subjective norm, PBC = perceived behavioral

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Pk control, f denotes to explanation, i¼1 bi ei = sum Pm of belief-evaluation products, i¼1 nbi mci = sum of normative belief-motivation-to-comply products, Pn i¼1 cbi pi = sum of control belief-perceived-powerto-facilitate/inhibit products, k = number of beliefs, m = number of normative beliefs, n = number of control beliefs, wj = weighting factor, j = 1,2,3. The theoretical framework of the study is presented in Fig. 1. The choice of reforestation method is explained according to the theory of planned behavior. The forest owner’s choice to use natural reforestation (behavioral intention) is explained by the attitude towards natural reforestation, the subjective norm and perceived behavioral control. Actual behavior could not be considered in the study. The attitude, subjective norm and perceived behavioral control are further divided into their components. In this framework, the specific action is natural reforestation, the target of the behavior is to successfully establish a new seedling stand, the context is a stand in the person’s own forest and the time frame covers a 10-year period. In addition to the factors directly related to the TPB, forest owners’ demographic characteristics, ownership objectives, use of own labor force in (other) silvicultural activities, past experience of natural reforestation and former delays in reforestation can each be expected to affect behavioral intention to reforest by natural regeneration.

The emphasis of non-timber objectives of forest ownership can be expected to increase the aesthetic or environmental concern for the chosen method, favoring natural regeneration. However, the inexpensiveness and long-term profitability of natural reforestation may also attract economically oriented owners. An ability to use his/her own labor force may encourage the owner to use labor-intensive planting or seeding instead of natural reforestation. Positive past experience naturally influences the willingness to use the method again. Finally, former delays in reforestation may have been caused by the selection of an inappropriate reforestation method and such an experience may affect the future choice of method.

3. Data and variables 3.1. Sample and analysis of sampling error Survey data covering two Forestry Centers in Southern and Eastern Finland, Pirkanmaa and Pohjois-Karjala, were collected by mail inquiry in the spring 2001. The original sample of NIPF owners consisted of 300 persons, of which 175 respondents returned an acceptable questionnaire after two reminders. The response rate was satisfactory, 58%.

Fig. 1. Theoretical framework of the study: an application of the theory of planned behavior.

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The non-respondent forest owners also included 14 persons who no longer owned forest. Owners with no mature stands in their forests and those with no intentions to reforest at all for some other reason within the 10-year period, were excluded from the TPB-related questions and hence from the analysis. Thus, the sample for analysis consisted of 154 owners. The sample was originally designed for testing methods for monitoring forest regeneration results after final fellings carried out during 1992 – 1995 (Saksa et al., 2000). The representativeness of the sample was, therefore, affected by the availability of aerial photographs. The analysis of the systematic sampling error covers both errors caused by nonrandom sampling and non-response in mail inquiry (see Karppinen et al., 1994). Error analysis was carried out for both regions by comparing the data used in this study with regional data from a regionally representative nation-wide study (Karppinen et al., 2002). The comparisons suggest that the study data is not a representative of the forest owners and holdings in either region. For instance, the forest holdings were clearly larger in the study sample than in the reference data. This is at least partly caused by the sampling method because the probability of clearfellings increases with the size of the forest holding. The proportion of farmers was too large in the study sample in both regions. In comparison with the reference data, it also appeared that respondents in Pirkanmaa had, on average, more often formal education, and respondents in Pohjois-Karjala resided more frequently in a different municipality to that of their forest holding. Female owners were also over-represented in Pohjois-Karjala compared with the reference data. However, the rather modest representativeness of the sampling does not essentially hamper the analysis aimed at empirically testing a theoretical model. 3.2. Variables and research methods The questionnaire included measures of the elements of the basic TPB model: the behavioral intention to reforest using natural regeneration, the attitude towards natural reforestation, the subjective norm and perceived behavioral control were each measured by a single question at the aggregate level. The components of the attitude, norm and control factor were also measured in the questionnaire. All the TPB

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model variables were measured by seven-point bipolar Likert scales ranging from  3 to + 3.1 Although the study results suggest that there may be differences in the measurement errors of the components of the attitude, norm and perceived behavioral control variables due to the selection of bipolar or unipolar scales (Ajzen, 1991b), bipolar scales were used for all the TPB model variables for clarity reasons. Salient beliefs, referents and control beliefs concerning natural reforestation were designed on the basis of interviews with experts and a literature survey, because a pilot study could not be conducted. The time frame of the future behavior was 10 years. 3.2.1. Behavioral intention Behavioral intention (BI) to reforest within 10 years were inquired of using a seven-point bipolar Likert scale ranging from very likely to very unlikely. The question included both natural reforestation, shelterwood or seed tree method and artificial reforestation as follows: How do you intend to reforest your forest within the next 10 years? – using natural reforestation (BI); – using clear cutting and planting or seeding The choice between natural reforestation and artificial reforestation (seeding/replanting) is not exclusively dichotomous. There may be several mature stands on the same holding with, e.g. different soil conditions. This restriction is, however, not expected to detract from the analysis of the factors predicting the specific choice of natural reforestation. 3.2.2. Attitude The global attitude (A) question was measured by a seven-point bipolar Likert scale ranging from positively to negatively. The wording was as follows: How are you yourself disposed to natural reforestation in your forest within the next 10 years? The strengths of beliefs (b) were measured by Likert scales ranging from very likely to very unlikely. The outcome evaluations (e) were also measured using 1

The scales were transformed to range from 1 to 7 in the analysis for technical convenience. However, the original notation is applied in the text.

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a Likert scale (very important. . .totally unimportant). The nine items that respondents were asked to assess were: quality of trees, reforestation costs, time needed to establish a seedling stand, forest scenery, costs of seed tree harvesting, naturalness, labor input, reforestation results and economic profitability in the long term. The outcome statements included seven positive and two negative aspects, although from strictly theoretical point of view unidimensionality of the beliefs should be preferred (Giles and Cairns, 1995). 3.2.3. Subjective norm The overall subjective norm (SN) was again measured by a seven-point bipolar Likert scale (ranging from I should to I should not). The question was designed as follows: How do other people (family members, forestry professionals of local forest management associations etc. ) feel about natural reforestation? Most people whose opinion is important for me in forestry issues think that I should/should not reforest my forest by natural regeneration within the next 10 years. The same scale was also used for measuring normative beliefs (nb) (I should. . .I should not), as well as the motivation to comply with the specific referents (mc) (fully take into account. . .not at all considered). The referents, whose norm pressure on reforestation decisions were assessed by the respondents, were family members, forestry professionals of local forest management associations (LFMAs), professionals of local wood purchasing companies, neighbors, as well as relatives, friends and acquaintances. 3.2.4. Perceived behavioral control The global measure of perceived behavioral control (PBC) concerned the possibility of natural reforestation. Again, a Likert scale was used and it ranged from possible to impossible. The question was phrased as follows: Is it possible to use natural reforestation in your forest, what do you say? According to my judgement, it is possible/impossible to use natural reforestation in some part of my forest within next 10 years. Control beliefs (cb) concerning resources and opportunities and perceived power to facilitate or inhibit behavior ( p) were also measured by means

of Likert scales, ranging from fully agree to fully disagree in the former, and from has a remarkable effect to no effect at all in the latter. The items to be evaluated concerned the uncertainty of natural reforestation of Norway spruce on dry soils and the uncertainty of natural reforestation of Scots pine on moist soils, as well as the high cost of planting trees. 3.2.5. Other variables and research methods In addition, to factors directly-related to the TPB, the questionnaire included several other variables. Owner characteristics were covered by conventional demographics, such as age, gender, professional status, education, former and present place of residence. Characteristics related to forest ownership included control of holding (family ownership vs. joint ownership), duration of ownership, residence on the holding and acquisition of the forest holding (inheritance vs. free market). The objectives of forest ownership guide forest owners’ behavior. Landowner objectives were measured by 23 different aspects of forest ownership using a five-point unipolar Likert scale (very important. . .totally unimportant) (see Kuuluvainen et al., 1996; Karppinen, 2000; Karppinen et al., 2002). The objectives consisted of monetary objectives, as well as recreational, emotional and aesthetic considerations. Past experience of natural reforestation was measured using two different approaches. First, forest owners were asked whether following final fellings they had reforested by natural or artificial regeneration, or whether they had applied both methods during their ownership. In addition, respondents were asked to assess the results from natural reforestation based on their own experiences (unipolar Likert scale: good results 5 fully agree to 1 fully disagree, 0 no experience). Finally, questions were asked concerning the use of own labor force (family members) in silvicultural activities other than reforestation during the past 5 years, and about former delays in reforestation. Conventional methods were applied in the empirical analysis. These were cross-tabulations, Pearson’s bivariate correlations and linear regression analyses. Experiments were also conducted using structural equation modeling techniques (Bollen and Long, 1993). These path analyses were estimated by Lisrel 8 software package (Jo¨reskog and So¨rbom, 1996). However, conventional path analysis (e.g. Birnbaum,

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1981), where each regression model is estimated separately, was primarily used in the analysis. After that experiments were made using structural equation modeling techniques, where all equations are estimated simultaneously allowing goodness-of-fit statistics.

4. Results 4.1. Attitude, norm, control factors, intention and past behavior The overall attitude (A) towards natural reforestation was favorable among forest owners. The majority of respondents (83%) had a positive attitude ( + 1... + 3 on the bipolar Likert scale), and almost half (48%) had a very favorable ( + 3) attitude. More than half of the owners (53%) considered that they should use natural reforestation ( + 1... + 3) because important referents think so (SN), but only 14% felt that referents do not want them to use natural reforestation. Natural reforestation was also commonly seen as a possible alternative (PBC): 84% assessed that natural reforestation was a possible option at least on one stand in their forests ( + 1... + 3). The great majority of forest owners intended to reforest some stand (s) by natural regeneration within the next 10 years (BI). Three out of four (72%) considered it likely ( + 1... + 3) and every third

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(32%) very likely ( + 3). The intention to reforest artificially was also common: 81% considered it likely. However, only one fifth of the owners (19%) intended to reforest mature stands mainly by natural regeneration. Most forest owners (73%) had applied both artificial and natural reforestation during their ownership of the holding. One fifth (21%) had carried out only clear cuttings and 3% had used only natural reforestation. Only 3% of the present owners had never carried out final fellings. The majority (73%) of those owners who had used natural reforestation had positive experiences of the method (fully agreed or agreed). 4.2. Formation of attitude, subjective norm and perceived behavioral control The questions on salient beliefs, referents and control beliefs concerning natural reforestation were designed on the basis of interviews with experts and a literature survey. As shown in Table 1, the expectations concerning the salience of belief statements seem to be justified. The expensiveness of seed tree harvesting was the only statement that was not overwhelmingly accepted. With few exceptions, belief-evaluation products (biei) were at least moderately correlated with the global measure of the attitude (A) (Table 2). The utility of the regression model presented in the same table is questionable due to rather strong multicolli-

Table 1 Belief strengths (bi) and outcome evaluations (ei) concerning the use of natural reforestation. Percentage distributions

Good quality of trees Low reforestation costs Seedlings grow slowly Forest scenery maintenance Harvesting of seed trees expensive Natural method Low labor input Successful reforestation results Economically profitable in the long term

Belief strength % forest owners considered

Outcome evaluation

Likely (1 – 3) (n)

Important (1 – 3)

97 92 87 87 61 99 81 79 78

97 88 76 85 61 85 77 94 88

(148) (147) (148) (146) (143) (146) (145) (146) (148)

(148) (147) (144) (143) (145) (146) (141) (145) (146)

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Table 2 Formation of the attitude towards the use of natural reforestation (A) predicted from belief-evaluation products (biei). Pearson’s correlations and regression analysis (n = 154) Belief  evaluation of outcome

Correlation coefficients (r)

h-coefficients (t-values)

Good quality of trees  importance of tree quality

0.346**

0.197* (2.44)

Low reforestation costs  importance of reforestation costs

0.251**

0.027 (0.29)

Seedlings grow slowly  importance of the time needed to establish a seedling stand Forest scenery maintenance  importance of the maintenance of forest scenery Harvesting of seed trees expensive  importance of the costs of seed tree harvesting

 0.156

0.289**

 0.166*

 0.094 (1.27)  0.017 (0.18)  0.157* (2.09)

Natural method  importance of naturalness

0.410**

0.151 (1.52)

Labor input low  importance of labor input

0.212**

0.069 (0.73)

Successful reforestation results  importance of successful reforestation

0.461**

0.270** (3.13)

Economically profitable in the long term  importance of long term economic profitability

0.421**

0.060 (0.61)

F Significance level Adjusted R2 **

Significant at P V 0.01. *Significant at P V 0.05.

nearity. Most strongly positively correlated with the attitude towards natural reforestation were successful reforestation results, economic profitability in the long term, naturalness of the method and good quality of trees. Moderately positively correlated were also maintenance of forest scenery, low reforestation costs and limited labor input. The time needed to establish a seedling stand and the expensiveness of seed tree harvesting had the expected negative signs but low correlations with the overall attitude.2 The respondents were not as unanimous with respect to normative beliefs as they were concern2

8.145 0.000 0.296

The small size of the sample did not allow a separate analysis of the beliefs among those with intention to use natural reforestation and those without such an intention.

ing beliefs related to attitude (Table 3). More than half of the owners considered that their own family members supported natural reforestation. Close to 40% believed that forestry professionals of local forest management associations promoted natural reforestation, but only a quarter felt the same way concerning forestry professionals of local wood purchasing companies. One third of the owners considered that their relatives, friends and acquaintances had a favorable opinion with respect to natural reforestation, but only every fifth respondent thought that their neighbors would support the method. Concerning forest owners’ motivation to comply, family members and professionals of forest management associations clearly seemed to be the most influential advisory groups.

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Table 3 Normative belief strengths (nbi) and motivations to comply (mci) concerning the use of natural reforestation. Percentage distributions Normative belief strength % forest owners considered Referent advices to reforest naturally (1 – 3) (n)

Motivation to comply % forest owners considered Should be taken into account (1 – 3)

Family members

54 (146)

74 (145)

Forestry professionals of local forest management associations

39 (145)

80 (148)

Neighbors

20 (144)

21 (144)

Relatives, friends, acquaintances

35 (143)

29 (143)

Forestry professionals of local wood purchasing companies

25 (143)

42 (143)

All normative belief-motivation-to-comply products (nbimci) correlated with the global measure of the subjective norm (SN) (Table 4). The most

important sources of norm pressure were family members, forestry professionals of LFMAs and wood purchasing companies. This conclusion was

Table 4 Formation of the subjective norm towards the use of natural reforestation (SN) predicted from normative belief-motivation-to-comply products (nbimci). Pearson’s correlations and regression analysis Normative belief  motivation to comply

Correlation coefficients (r)

Family members

0.459**

0.328** (4.19)

Forestry professionals of local forest management associations

0.396**

0.221** (2.67)

Neighbors

0.221**

 0.017 (0.19)

Relatives, friends, acquaintances

0.288**

0.072 (0.76)

Forestry professionals of local wood purchasing companies

0.361**

0.131 (1.54)

n = 148 F Significance level Adjusted R2 **

Significant at P V 0.01. *Significant at P V 0.05.

h-coefficients (t-values)

n = 154 12.728 0.000 0.277

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Table 5 Control belief strengths (cbi) and perceived power to facilitate/inhibit behavior ( pi) concerning the use of natural reforestation. Percentage distributions Control belief strength % forest owners

Perceived power to facilitate/inhibit behavior

Agreed (1 – 3) (n)

Considered that has an effect (1 – 3)

Uncertainty of natural reforestation of Norway spruce on dry soils

72 (151)

71 (146)

Uncertainty of natural reforestation of Scots pine on moist soils

69 (149)

69 (146)

Expensiveness of planting trees

80 (152)

64 (149)

partly confirmed by the regression model (Table 4). However, the estimation was somewhat disturbed by multicollinearity. The two control belief statements concerning the uncertainty of natural reforestation with Norway spruce and Scots pine gained the support of the majority of the respondents (Table 5). A larger proportion of the owners shared the view that planting is expensive. Respondents also commonly regarded that each item had the power to inhibit or facilitate the use of natural reforestation.

Only the high cost of planting trees was moderately correlated with the global measure of perceived behavioral control (PBC) (Table 6). The products (cbipi) dealing with the uncertainty of natural reforestation with spruce and pine were negatively correlated with the overall measure, but the coefficients were statistically insignificant. The correlations and regression estimation results (Table 6) both suggest that only the high cost of planting can be seen as a component of the global measure of perceived behavioral control.

Table 6 Formation of the perceived behavioral control towards the use of natural reforestation (PBC) predicted from control belief-perceived-power-tofacilitate/inhibit products (cbipi). Pearson’s correlations and regression analysis Control belief  perceived power to facilitate/inhibit behavior

Correlation coefficients (r)

h-coefficients (t-values)

Uncertainty of natural reforestation of Norway spruce on dry soils

 0.122

 0.062 (0.62)

Uncertainty of natural reforestation of Scots pine on moist soils

 0.132

 0.084 (0.85)

Expensiveness of planting trees

0.262**

n = 153 F Significance level Adjusted R2 **

Significant at P V 0.01. *Significant at P V 0.05.

0.257** (3.29) n = 154 4.709 0.004 0.068

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4.3. Models predicting intention to use natural reforestation

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estly correlated with the intention. As mentioned above, it is obvious that two of the used control beliefs were not compatible with the overall behavioral control variable (PBC). This assumption is supported by the almost zero correlation between the sum of components of perceived behavioral control and the corresponding global measure. Therefore, only the global measure of controlling factors was used in the regression models predicting intention. Table 8 summarizes the estimation results of the regression models explaining the intention to choose natural reforestation. Although attitude-related explanatory factors were correlated, the regression analyses were obviously not seriously disrupted by multicollinearity. The standardized regression coefficients (h-coefficients) of the so-called Basic model and the corresponding t-values (in parenthesis) are presented in the first column. The explanatory variables were the global measures of the attitude, norm and perceived behavioral control. Basic model

The global measures of the attitude (A), subjective norm (SN) and perceived behavioral control (PBC) had strong positive correlations with the behavioral intention to use natural reforestation within 10 years (BI) (Table 7). The sum of normative belief-motivation-to-comply products (Snbimci) was also highly positively correlated with intention and the sum of belief-evaluation products (Sbiei) correlated also moderately and positively. Considering reliability, Cronbach’s a for the belief-evaluation product scale was 0.74 and for the normative belief-motivation-tocomply scale 0.71. These sum variables of the components of the attitude and norm were also rather highly correlated with the corresponding global measures. The sum of the components of the perceived behavioral control (Scbipi) was negatively and mod-

Table 7 Correlations between variables explaining the intention to choose natural reforestation (BI). Pearson’s correlation coefficients and number of observations BI

A

SN

PBC

Sbiei

Snbimci

Scbipi

BI

1.00

A

0.57** 147

1.00

SN

0.40** 141

0.34** 148

1.00

PBC

0.53** 146

0.63** 153

0.39** 148

1.00

Sbiei

0.26** 147

0.38** 154

0.18* 148

0.29** 153

1.00

Snbimci

0.40** 147

0.39** 154

0.52** 148

0.37** 153

0.38** 154

1.00

Scbipi

 0.16* 147

 0.07 154

 0.03 148

0.01 153

0.17* 154

 0.08* 154

Wage earner

 0.19* 140

 0.06 147

 0.08 141

 0.09 146

 0.13 147

 0.02 147

 0.14 147

Positive past experience

0.53** 132

0.57** 139

0.26** 136

0.46** 139

0.29** 139

0.31** 139

 0.22* 139

**

Significant at P V 0.01. *Significant at P V 0.05.

Wage-earner

1.00

1.00

 0.16 132

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H. Karppinen / Forest Policy and Economics 7 (2005) 393–409

Table 8 Factors explaining the intention to choose natural reforestation (BI). Regression analyses (n = 154, missing values replaced by means) Variables

Basic model

Component model 1

Component model 2

Extended model 1

Extended model 2

Extended model 3

0.357** (4.31)

0.274** (3.12)

0.282** (3.23)

0.183** (2.60)

0.180* (2.58)

0.175* (2.53)

0.194* (2.29)

0.171* (2.02)

0.166* (1.98)

h-coefficients (t-values) A

0.356** (4.26)

SN

0.190** (2.68)

PBC

0.203* (2.38)

0.342** (4.01)

0.402** (5.37)

Sbiei

0.055 (0.74)

Snbimci

0.217** (2.81)

0.220** (2.60)

0.173* (2.42)  0.131* (2.04)

Wage-earner

Positive past experience F Significance level Adjusted R2 **

29.308 0.000 0.357

21.273 0.000 0.284

28.638 0.000 0.351

23.478 0.000 0.370

 0.111 (1.73) 0.202** (2.67)

0.185* (2.43)

24.658 0.000 0.382

20.588 0.000 0.390

Significant at P V 0.01. *Significant at P V 0.05.

explained 36% of the total variation in the intention to use natural reforestation (Adj. R2) and was statistically significant ( F-value 29.3). All the independent variables had the expected positive signs and were statistically significant. The h-coefficients suggest that the attitude towards natural reforestation was the most powerful attribute explaining the intention, followed by the norm and perceived controlling factors with equal explanatory power. Component model 1 including the sums of the components of the attitude and norm, in addition to the global control variable, was significant but clearly poorer in explaining intention (Adj. R2 = 0.28). The signs of the independent variables were as expected, but only control factors and the norm were statistically significant. The model was somewhat improved (Adj. R2 = 0.30) and the attitude variable became significant when the sum of the components of the attitude was modified by excluding the two belief-evaluation products with lowest and negative correlations with the

global attitude (time needed to establish a seedling stand and expensiveness of seed tree harvesting). The use of global variables for the attitude and behavioral control in Component model 2 improved explanatory power (Adj. R2 = 0.35) and the sum of the components of the norm remained significant. Interaction effects of the global measures of the attitude, norm and perceived behavioral control were also tested by multiplying each variable with each other pairwise, and adding the product as an independent variable in Basic model. The three estimations to some extent suggest that interactions between these variables cannot be entirely excluded, casting some doubts on the additive nature of the TPB model with respect to the effects of the behavioral control and attitude (see Ajzen, 1991b; Ajzen and Driver, 1992a; Giles and Cairns, 1995). A few factors outside the pure TPB variables (see Fig. 1) could be incorporated in the regression models. Professional status, described by a dichotomous vari-

H. Karppinen / Forest Policy and Economics 7 (2005) 393–409

able wage-earner/others, correlated negatively with the intention, and was included in Extended model 1 (Table 8). The explanatory power (Adj. R2 = 0.37) was somewhat improved compared to Basic model, and wage-earner had negative and significant coefficient, but its explanatory power (b =  0.13) was smaller than that of the attitude-related TPB variables. As in previous studies (Kuuluvainen et al., 1996; Karppinen, 2000; Karppinen et al., 2002), ownership objectives were condensed into combined variables by means of principal component analysis (see Appendix A), and the principal component scores were used as criterion variables in clustering the owners. Principal component scores, cluster dummies and some other modifications were tested in regression estimations, but none of them could be incorporated in the model in a meaningful way. The use of the forest owners’ own labor force in other silvicultural activities, and former delays in reforestation, had no effect on the intention to use natural reforestation. Instead, past experience of natural reforestation measured by the assessment of the reforestation results proved to have a significant positive effect on intention (Extended model 2, Adj.

405

R2 = 0.38). Positive experiences explained the intention to reforest by natural regeneration (b = 0.20) at a similar magnitude than norm or control factors. In Extended model 3, the dummy variable describing professional status (wage-earner/others) was included in addition to the TPB variables and positive past experience. The explanatory power slightly increased (Adj. R2 = 0.39) compared to Extended model 2, but professional status was not statistically significant. 4.4. Path analysis The causal structure of Extended model 3 was studied further by estimating a conventional path model using separate regression models for the intention, attitude, norm and perceived control factors (Fig. 2). The model explaining the intention is, in fact, Extended model 3. The path diagram suggests that positive past experiences of natural reforestation mediate mainly through the attitude and perceived behavioral control. The path coefficient for positive past experience, summing up both the direct and indirect effects on intention, was as high as 0.46.

Fig. 2. Path analysis of the factors explaining the intention to choose natural reforestation (BI). (h-coefficients, t-values in parenthesis and adjusted R2:s).

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Some variables that did not have any direct effects on the intention could be meaningfully incorporated in the path model via indirect effects. The influence of ownership objectives was indirect and mediated through norm pressure and perceived behavioral control. The emphasis on economic objectives (the principal component) seems to work in favor of natural reforestation, both via the subjective norm and perceived behavioral control, whereas non-timber objectives influence positively only through control factors. Unexpectedly, the experience of former delays in reforestation seems to affect positively, and only indirectly via perceived behavioral control. Experiments were also conducted using structural equation modeling techniques in order to estimate goodness-of-fit statistics for the whole model by simultaneous analysis of regression equations. Experiments suggested that the goodness-of-fit of the model presented above was rather poor measured by, e.g. Chi-square test statistics and Root mean square error of approximation (RMSEA) (Jo¨reskog and So¨rbom, 1996; Bergha¨ll, 2003). However, by allowing linkages between attitude and perceived behavioral control, as suggested by the analysis of interaction effects, RMSEA and some other goodness-of-fit statistics improved to some extent (Goodness-of-fit index GFI, Normed fit index NFI and Comparative fit index CFI), even above the critical level. These results give further support for the earlier doubts (see Section 4.3) about the additive nature of the model.

5. Discussion The empirical results supported the hypothesis that the selection of the reforestation method could be described by the theory of planned behavior. The global measures of the attitude, subjective norm and perceived behavioral control explained a substantial share—compared to other studies (e.g. Ajzen, 1991b)—of a forest owner’s intention to use natural reforestation in a stand in his/her forest within 10 years. Attitude was the most powerful explanatory factor, and norm and control factors had clearly smaller but mutually equal effects on intentions. The sum of the components of the subjective norm seemed to function as expected in the models. However, the corresponding attitude variable was signifi-

cant only if two belief-evaluation products dealing with negative statements on natural reforestation were excluded from the component variable. This finding gives some support to the strict claim of unidimensionality of the statements (Giles and Cairns, 1995). The formation of the component variable of perceived behavioral control failed. According to Ajzen (1991b), the correlations between the belief-based indices and the corresponding global measures of the variables are often modest. This may be because the global measures would evoke a rather automatic reaction, whereas beliefbased measures a relatively reasoned response. This kind of behavioral pattern may explain, at least to some extent, the failure in the design of the sum measure of perceived behavioral control. The test of the interaction effects of Basic model variables and simultaneous path analysis cast some doubts on the additive nature of the TPB model, with respect to the effects of behavioral control and the attitude (see Ajzen, 1991b; Ajzen and Driver, 1992a; Giles and Cairns, 1995). However, previous studies suggest that linear models usually perform adequately, although interactions would be present (Ajzen and Madden, 1986). A few factors outside the pure TPB model could be incorporated in the basic regression models. Professional status, described by the dichotomy wage-earners vs. others, had a negative but a rather small effect on intention. Past experience measured by the positive assessment of the reforestation results in natural regeneration had, as expected, a clear positive effect on intention. This result is in line with those of Gramann et al. (1985) concerning the intention to plant trees and Cleaves and Bennett (1995) dealing with harvest intentions. The path analysis suggested that the good experiences are mediated mainly through the attitude and perceived behavioral control. The latter result concerning behavioral control, although expected, contradicts Ajzen’s and Madden’s (1986) findings. Furthermore, the path analysis revealed that some variables that did not have any direct effects on intention could be meaningfully incorporated in the path model via indirect effects. The influence of ownership objectives was mediated through norm pressure and perceived behavioral control and the experience of former delays in reforestation affected via perceived behavioral control.

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6. Conclusions The empirical analysis is restricted by the lack of knowledge of actual, in this case future reforestation behavior. The literature, nevertheless, suggests that intentions and perceived behavioral control are rather good predictors of future behavior if they are stable until the time behavior is observed, and compatible with the behavior as regards to the specificity and context (Ajzen and Fishbein, 1980; Gramann et al., 1985; Ajzen, 1991b). Therefore, some conclusions are justified concerning actual reforestation behavior. From the policy point of view, the most interesting question is how to influence forest owners’ reforestation behavior. Behavioral changes can be induced by changing intentions and, if possible, control factors (Ajzen and Driver, 1992a). Intentions are preceded by attitudes and beliefs. Forest owners appeared to have a very favorable overall attitude towards natural reforestation associated with strong positive and rather realistic beliefs. This is positive if natural reforestation is to be favored in forest policy. It has also been noted earlier that forest owners have rather realistic beliefs concerning the regeneration method that they prefer (Karppinen, 2001). Family members and forestry professionals of local forest management associations, and to some extent also professionals of wood purchasing companies, appeared to be the most important sources of norm pressure. Concerning harvest intentions, Young et al. (1985) and Young and Reichenbach (1987) found that family members were clearly the most influential referents. From the policy point of view, it is positive that forest owners are sensitive to what forestry professionals, especially LFMA officials, have to say. Motivation to comply, which is no doubt difficult to change, was high indeed. Interestingly, the influence of neighbors, as well as relatives, friends and acquaintances, was rather limited. The notion contradicts a study by West et al. (1988) who found that peer laymen (friends, neighbors, relatives) were almost as important sources of information as forestry professionals. It seems that in the Finnish case the extension strategy to influence via opinion leaders or early adopters is not very effective compared to some other countries (Haymond, 1988, 1990). The situation may, however, change along with the structural changes in forest

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ownership to favor indirect extension strategies. Urban, absentee owners without direct roots in the countryside may be more willing to learn from the experiences of neighbors and other local opinion leaders than more experienced rural landowners. The emphasis on either economic or non-timber objectives seemed to work in favor of natural reforestation. Aesthetic or environmental concerns, as well as immediate cost savings or long-term profitability, may be relevant aspects favoring natural regeneration. As mentioned above, only a minor part of the regeneration areas are reforested by natural regeneration in the Finnish private woodlots. Clear cuttings supplemented by replanting or seeding dominate forest regeneration. Control factors, which were unsatisfactorily measured in this study, obviously limit volitional choice more than is shown in the study results. According to a rather old assessment (Leikola, 1981), 30% of the forest area in Southern Finland and 50% of the forest area in Northern Finland are located on soils, which would be well suitable for natural reforestation from both silvicultural and economic point of view. However, including all those areas where natural reforestation would be in principle possible, the proportions would be as high as 60% and 70%, respectively. It is, nevertheless, evident that negative beliefs, unfavorable attitudes, certain kinds of ownership objectives or ignorance of professional advice are not the primary reason for the avoidance of natural reforestation in practice.

Acknowledgments This article is a revised version of the paper presented at the International Symposium in the Black Forest 2002 on Contributions of Family-Farm-Enterprises to Sustainable Rural Development, a IUFROWorking-Unit 3.08.00 and 6.11.02, 28 July – 1 August, 2002, Gengenbach, Germany. I thank Eija Pouta and an anonymous referee for their valuable comments on the manuscript. I am also grateful to Timo Saksa and Forestry Centers of Pohjois-Karjala and Pirkanmaa for their cooperation in sampling. For their helpful comments, acknowledgments are extended to Sami Bergha¨ll, Pekka Ripatti, Matti Ruotsalainen, Esa-Jussi Viitala and Ashley Selby, who also checked the language. I also express my gratitude to Eeva Sani who assisted in data collection.

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Appendix A Ownership objectives. Principal component analysis. Varimax rotation (Loadings below 0.250 denoted by asterisk) (Table A1). Table A1 Non-timber objectives

Economic objectives

Outdoor recreation Berry-picking Biodiversity Residential environment Solitude and meditation Aesthetic values Household timber Nature conservation Hunting Roots in native locality Forest work Security against old age Asset motive Funding of investments Hedging motives Speculative motives Security against inflation Stumpage price 0development Credibility Regular sales income Bequest motive Labor income Inherent value

0.833 0.771 0.746 0.686 0.677 0.671 0.617 0.553 0.456 0.451 0.429 * * * * * * * * 0.253 * 0.408 *

* * * * * * * * 0.331 * * 0.799 0.735 0.723 0.671 0.614 0.591 0.589 0.586 0.577 0.554 0.441 0.329

Eigenvalue Proportion explained Carmines’ thetaa n

4.904 21% 0.89 154

4.834 21%

  Carmines’ theta is computed for the unrotated solution as follows:Q ¼ NN1 1  k11 , where N is the number of items in the total principal component analysis and k1 is the largest (the first) eigenvalue. Theta may be considered a maximized Cronbach’s alpha coefficient (BMDP, 1992; Carmines and Zeller, 1979). a

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