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Fig 1. Services offered to customers by nature-based tourism enterprises.

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Fig 2. The use of state-owned commercial forest in nature-based tourism during the last 12 months by season.

Table 1. Descriptions of dependent and independent variables in the models (n = 46).
Variable name Description Mean SD
Dependent variables
PGrowth Change in turnover during last five years: 0 = decreased (n = 7), 1 = unchanged (n = 15), 2 = increased (n = 24) 1.4 0.7
EGrowth Expected change in turnover during next five years: 1 = increase (n = 27), 0 = otherwise (n = 19) 0.6 0.5
Participate Company’s willingness to participate in potential scenery trading: 0 = no (n = 29), 1 = maybe (n = 12), 2 = yes (n = 5) 0.5 0.7
Independent variables
1) Characteristics of enterprise
Turnover Company’s turnover during the last 12 months: 1000 euros 282.7 349.7
Services Number of different services that company offers: 1–10 services 5.2 2.2
Program% Share of program services of the turnover: 0–100% 12.2 5.9
Accommodation Company offers accommodation services: 1 = yes (n = 28), 0 = no (n = 18) 0.6 0.5
Bcustomer% The share of business customers of the total number of customers: 0–100% 17.3 4.6
2) Characteristics of entrepreneur
Experience Entrepreneur’s experience as an entrepreneur: years 16.2 9.7
Risk-taker Entrepreneur’s attitude to risk: 1 = risk-taker (n = 27), 0 = risk-averse (n = 19) 0.6 0.5
Newbusiness Entrepreneur’s intention to develop new NBT business: 1 = yes (n = 21), 0 = no (n = 25) 0.5 0.5
3) Use of state-owned commercial forests and activities encountered in forests
Usehigh How often company uses state-owned commercial forest during the high season: 1–5, from not at all to daily or almost daily 3.5 1.6
Hiking Company uses state-owned commercial forest for hiking camping (overnight) activities: 1 = yes (n = 11), 0 = no (n = 35) 0.2 0.4
Snowmobiling Company uses state-owned commercial forest for snowmobiling activities: 1 = yes (n = 25), 0 = no (n = 21) 0.5 0.5
Nordicwalking Company uses state-owned commercial forest for Nordic walking activities: 1 = yes (n = 18), 0 = no (n = 28) 0.4 0.5
Cross-country Company uses state-owned commercial forest for cross-country skiing activities: 1 = yes (n = 14), 0 = no (n = 32) 0.3 0.5
Fishing Company uses state-owned commercial forest for fishing activities: 1 = yes (n = 17), 0 = no (n = 29) 0.4 0.5
Sledding Company uses state-owned commercial forest for sledding activities: 1 = yes (n = 7), 0 = no (n = 39) 0.2 0.4
Table 2. Factors explaining the past and expected growth of nature-based tourist enterprises.
Model 1 (PGrowth) Model 2 (EGrowth)
Explanatory variable Coefficient Standard error p-value Coefficient Standard error p-value
Constant 0.80119 0.76993 0.2981 –5.03746 1.98556 0.0112
Turnover 0.00612 0.00199 0.0021 0.00454 0.00235 0.0530
Risk-taker –1.48997 0.53291 0.0052 3.72959 1.20213 0.0019
Usehigh –0.33300 0.17625 0.0588 –0.93256 0.43518 0.0321
Hiking 3.21506 0.93994 0.0006 2.25328 1.26496 0.0749
Snowmobiling –1.23427 0.54133 0.0226 –0.65759 0.91770 0.4736
Threshold parameter
Mu(1) 2.07667 0.51873 0.0001
Log likelihood –24.17877 –17.92757
Pseudo R-squared 0.46979 0.42513
AIC 62.4 47.9
Table 3. Factors explaining respondents’ willingness to participate in landscape and recreational values trading (LRVT). Y = participate (1 = yes, 0 = no)
Explanatory variable Coefficient Standard error p-value
Constant 0.32067 0.66290 0.6286
Turnover 0.00537 0.00177 0.0025
Newbusiness 3.18345 1.24617 0.0106
Accommodation –3.41820 1.27322 0.0073
Program% –0.26572 0.10421 0.0108
Hiking camping –4.19251 1.57611 0.0078
Cross-country skiing –3.10572 1.33145 0.0197
Nordic walking 8.22564 3.11269 0.0082
Fishing 4.93116 1.83684 0.0073
Sledding 2.26629 1.23403 0.0663
Threshold parameter
Mu(1) 3.07900 1.06397 0.0038
Log likelihood –15.01020
Pseudo R-squared 0.63028
AIC 52.0
Table 4. Characteristics of enterprises and entrepreneurs explaining the growth and expected growth of nature-based tourist enterprises.
Model 3 (PGrowth) Model 4 (EGrowth)
Explanatory variable Coefficient Standard error p-value Coefficient Standard error p-value
Constant 3.64450 1.36492 0.0076 1.95737 3.14537 0.5337
Turnover 0.00394 0.00125 0.0016 0.00327 0.00201 0.1032
Accommodation 0.94949 0.49871 0.0569 1.90584 1.19664 0.1112
Services –0.16161 0.10400 0.1202 –0.11060 0.24367 0.6499
Bcustomer% –0.05790 0.05080 0.2544 –0.29196 0.14835 0.0491
Experience –0.05848 0.02374 0.0138 0.00911 0.05708 0.8732
Risk-taker –1.23918 0.53421 0.0204 1.82889 1.12739 0.1048
Newbusiness –0.07518 0.44111 0.8647 2.86871 1.09677 0.0089
Threshold parameter
Mu(1) 1.58886 0.36391 <0.0001
Log likelihood –30.28370 –15.27105
Pseudo R-squared 0.33591 0.51032
AIC 78.6 46.5