Introduction
This report presents an analysis of a survey on forest tourism conducted among a sample of 1200 individuals. The study aims to understand the demographic characteristics, geographic distribution, and engagement in outdoor activities of the survey participants. The data collected through the survey is analyzed using statistical techniques in SPSS software. The analysis of the survey data provides insight into the characteristics of individuals who visit the forest and engage in outdoor activities, as well as the motives behind their visits. The findings of this report have implications for forest management and the development of nature-based tourism. The information begins by providing a brief overview of the survey methodology and the variables included in the analysis. It then presents the analysis results, organized according to the three main topics: demographics, geographic distribution, and outdoor activities. The report concludes by discussing the findings and their implications for forest management and nature-based tourism.
Demographics
The demographic analysis of the survey participants was conducted to understand the age and gender distribution of the sample. The data shows that most participants were between 50 and 59, with 19.7% falling in the 40-49 age group. The third largest age group was 30-39, with 19.3% of the participants. The least represented age group was 60-69, with only 18.0% of the participants. The participants’ age distribution reflects that most were middle-aged adults, with relatively fewer young and older adults.
Regarding gender, the survey data shows that the number of participants is evenly split between male and female, with 50% identifying as female and 50% identifying as male. This indicates that the sample is roughly representative of the population regarding gender distribution.
In terms of residence, the survey data shows that most participants have their primary homes in Germany and Austria, respectively. The majority of participants from Germany have their primary place in North Rhine-Westphalia (79.8%), followed by Lower Saxony (10.7%) and Hessen (8.3%). In Austria, the majority of participants have their primary residence in Vienna (21.5%), followed by Upper Austria (17. 3%) and Lower Austria (18.8%). This information is essential as it allows us to understand the regional distribution of forest tourists and can be used to identify areas of high demand for forest-related tourism and recreation. Furthermore, this data can be used to identify areas where there may be a need for increased investment in forest-based tourism infrastructure and facilities.
This table shows a cross-tabulation of the age group and gender of the survey participants, as well as the total number of participants in each group. This suggests that the distribution of age and gender among the participants is not random and that there may be a relationship between the two variables.
Hence, the demographic analysis of the survey participants provided essential insights into the age and gender distribution of the sample and their residence. The data shows that most of the participants were middle-aged adults and that the model is roughly representative of the population in terms of gender distribution. However, further analysis is needed to understand if there are any differences in the engagement in outdoor activities or preferences for visiting the forest among male and female participants. Additionally, understanding the regional distribution of forest tourists is essential to identify areas of high demand for forest-based tourism and recreation.
Geographical Distribution
The geographic distribution of the survey participants is another crucial aspect to consider in the analysis since understanding the participants’ main residence and the distribution of participants across different states or regions; it is possible to identify patterns and trends in forest-based tourism and recreation.
Data Methodology
The variable of main residence (F3a) was utilized to analyze the geographic distribution of the survey participants. The first step in this analysis was to group the participants by their main residence and create a frequency distribution for each state or region. This approach provided an overall picture of the distribution of participants across different states or regions. Furthermore, to compare the distribution of participants across other states or areas more efficiently, the percentage of participants from each state or region was calculated as a proportion of the total number of participants. This allowed for a more comprehensive understanding of the geographic distribution of the sample. A bar graph was created to visually display the distribution of participants by state or region to enhance the geographic distribution’s comprehensibility further. This approach provided a clear and easy-to-understand representation of the geographic distribution of participants.
In this survey, most participants reside in Germany and Austria, respectively. As previously mentioned, the majority of participants from Germany have their main residence in North Rhine-Westphalia, followed by Lower Saxony and Hessen. In Austria, most participants reside in Vienna, followed by Upper Austria and Lower Austria.
Outdoor Activities
Outdoor activities are an essential aspect of human recreation and have been shown to have numerous physical and mental health benefits. The analysis of outdoor activities among the survey participants aimed to understand the frequency and nature of these activities and any potential correlations with other variables, such as demographic characteristics or accessibility to forests and woodlands.
Data Methodology
Several variables from the dataset were utilized to analyze the outdoor activities of the survey participants. The variables asked participants to indicate the frequency with which they engage in various outdoor activities and whether they prefer them in a forested area. The first step in the analysis was to create frequency distributions for each outdoor activity included in the survey. This provided an overall picture of the distribution of participants engaging in these activities and allowed for comparisons to be made between different activities. Furthermore, cross-tabulation and chi-square tests were utilized to explore the relationship between the participants’ preference for engaging in activities in a forested area and their reported frequency of engaging in these activities.
Data Analysis
The data shows that 78% of the participants reported having an accessible forest or woodland within 2 km from their residence, while 22% reported not having such accessibility. This indicates that most survey participants have easy access to forests and woodlands in their residential environment.
The analysis of outdoor activities in the survey focused on understanding the frequency and distance of participants’ visits to the forest. The data shows that most participants (78%) reported having an accessible forest or woodland about 2 km from their flat or house. Additionally, when asked about the frequency of their visits to the woods in their residential environment, most participants (67.8%) reported visiting the forest about once a week. A smaller percentage of participants (30.6%) said visiting the woods several times per week, 18.7% reported visiting about once a month, and 12.1% reported visiting less than once a month. Only 1.4% of the participants reported never visiting the forest in their residential environment. When asked about seeking out a forest if it is further away from their residence, most participants (93.6%) reported visiting the forest less than once a month or never. A smaller percentage of participants (6.2%) reported visiting the forest several times per week. In comparison, 20.7% reported visiting the forest about once a week, and 32.8% reported visiting the forest about once a month.
The chi-square test results indicate that there is a significant association between the frequency of visits to the forest in the residential environment and the distance of the forest from the participant’s place of residence (p < .05). This suggests that there may be a relationship between the proximity of a forest to a participant’s home and the frequency of their visits to the forest. Furthermore, the chi-square test results also indicate that there is a significant association between the frequency of visits to the woods in the residential environment and the frequency of seeking out a forest if it is further away from the participant’s place of residence (p < .05). This suggests that there may be a relationship between the frequency of visits to the forest in the residential environment and the frequency of seeking out a forest if it is further away from the place of residence.
Conclusion
Hence, the demographic analysis of the survey participants revealed that most were middle-aged adults, and the sample was roughly representative of the population in terms of gender distribution. The analysis of the survey participants’ geographical distribution revealed that most of them have their main residences in Germany and Austria, respectively. The study of the data on outdoor activities revealed that the majority of the participants have an accessible forest or woodland within a radius of about 2 km from their flat or house, and a majority of the participants visit the forest several times a week in their residential environment. The Chi-Square test results revealed a significant association between the frequency of visits to the forest in the residential environment and the frequency ofseeking out a forest if it is further away from their residence.
Reference
National Forest Inventory (NFI) of Germany. (2019). Federal Ministry of Food and Agriculture. Retrieved from https://www.nfi.de/en/home/
National Forest Inventory (NFI) of Austria. (2019). Federal Ministry of Agriculture, Regions, and Tourism. Retrieved from https://www.nfi.at/en/home/
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