Motivation-Based Segmentation of Hiking Tourists in Taiwan

Abstract

Hiking is one of the most popular and significant recreational activities in natural settings, yet hiking tourists are often not distinguished from the broader population of nature-based tourists. This study aimed to identify distinct segments of hiking tourists based on their motivations and to explore the relationship between segmentation, motivations, and their satisfaction with the hiking experience. Using a questionnaire survey of 262 hiking tourists in Taiwan and multivariate statistical techniques, four hiking motives—“relaxation”, “social interaction”, “competence and exploration”, and “mental refreshment”—were identified, and four segments of hiking tourists—“mental refreshment seekers”, “social hikers”, “challenge seekers”, and “general purpose hikers”—were classified, respectively. While all segments reported high levels of satisfaction, their satisfaction was influenced by different motives. This study enhances the theoretical understanding of hiking motives and provides practical recommendations for enhancing hiking experiences and nature conservation.

1. Introduction

Hiking refers to various walking activities for pleasure or exercise in natural settings [1]. As a recreational activity, hiking has a rich history that dates back to the establishment of the first national parks in the late 19th century, when outdoor recreation began gaining popularity in the United States and Europe. The establishment of Yellowstone National Park in 1872 marked a significant milestone, as it was the first time a large area of wilderness was designated and protected by a government specifically for public use and enjoyment [2]. Early tourists engaging in hiking were mainly naturalists, writers, and conservationists who sought to experience and document the natural beauty of these protected areas.

During the early 20th century, the rise of the conservation movement further fueled the popularity of hiking. Influential figures such as John Muir and Theodore Roosevelt were instrumental in promoting hiking as a means to connect with nature and advocate for the preservation of wilderness [3]. This period also saw the development of infrastructure in national parks, including the creation of trails and the establishment of ranger services, which made hiking more accessible to the general public [4]. As a result, hiking became increasingly popular as a form of recreation, leading to the growth of a hiking culture that continues to thrive today.

Hiking ranks among the most favored recreational activities globally [1]. For example, in the United States, one in three Americans views hiking as a preferred outdoor activity [5]. In Europe, nearly a third of the Swedish population and 80% of Norwegians regularly go hiking [6]. In Asia, about a third of Koreans hike at least once annually [7], and in Hong Kong, almost half of its visitors participate in hiking-related activities when visiting country parks [8].

Hiking tourism has emerged as a significant sector in the broader tourism industry, particularly in regions with extensive natural landscapes, such as North America, Europe, and parts of Asia [9]. Many countries worldwide have developed specialized trails for various hiking demands, such as short-distance walking, long-distance hiking, and mountaineering [10].

Taiwan, with its diverse topography and rich biodiversity, is an ideal place for developing hiking. The island’s mountainous terrain, including the famous Central Mountain Range, offers a variety of hiking opportunities ranging from gentle walks in lowland areas to challenging climbs in high-altitude regions [11]. There are countless designated trails in Taiwan [12]; they are crucial in promoting hiking tourism by providing well-maintained trails, visitor facilities, and conservation education [13]. These parks are not only natural treasures but also attractive destinations for hiking enthusiasts.

Hiking tourism in Taiwan has seen significant growth in recent years. National parks serve as the primary venues for hiking, attracting hiking tourists with their scenic landscapes [14], diverse ecosystems [13], and cultural heritages [15]. The Taiwanese government has implemented various measures to support sustainable hiking tourism, including developing eco-friendly infrastructure, promoting responsible hiking practices, and enforcing regulations to protect sensitive areas [14]. More than five million Taiwanese are estimated to participate in hiking activities, accounting for approximately 21% of the total population [14].

Research on hiking tourism in Taiwan has been growing in scope, reflecting the increasing popularity of these activities among the Taiwanese population. Previous studies have primarily focused on understanding the environmental and social impacts of hiking in national parks. For instance, researchers, e.g., Cheng and Wu [16], have explored the relationship between hikers’ environmental attitudes and their commitment to conservation efforts, highlighting the role of hiking in fostering environmental stewardship. Other studies have examined the benefits and impacts of hiking tourism. For example, Hill et al. [17] investigated the well-being brought about by hiking. Tseng et al. [18] assessed the economic contribution of hiking tourism to trail management. Wu et al. [13] examined the physical and environmental impacts of hiking activities.

While the existing research provides valuable insights into hiking activities and tourism in Taiwan, two knowledge gaps remain that warrant further investigation. One significant gap lies in the segmentation of hiking tourists in Taiwan. Most studies did not distinguish hiking tourists from the broader population of nature-based tourists. Although some studies, e.g., Wu et al. [13], have described the demographics of hikers, there is a need for more nuanced segmentation analyses that consider hiking tourists’ personal factors, such as motivations, satisfaction, etc. Furthermore, there is a lack of comprehensive evaluation of satisfaction concerning the segmentation of hiking tourists.

Given the global trend of increasing demand for unique tourism experiences [19], it is necessary to understand why hiking tourists go hiking and how their expectations will be fulfilled [20]. This understanding is essential for aligning tourism development with visitor expectations and ensuring long-term satisfaction. While previous research has examined various aspects of hiking tourism, the existing studies often treat hikers as a homogenous group without considering distinct visitor segments. This approach overlooks the potential differences in motivations, satisfaction levels, and preferences among various types of hiking tourists. A novel segmentation of hiking tourists, focusing on their diverse motivations and satisfaction criteria, is essential to address this gap [21].

With the above observation in mind, this study intends to develop a novel segmentation of hiking tourists in Taiwan. The objectives of this study are twofold: First, to categorize hiking tourists in Taiwan into distinct segments based on their personal motivations, and second, to assess the relationship between these motivations and the level of satisfaction they derive from hiking experiences.

Aligning with the objectives, the following research questions are formulated:

• What are the primary motivations that drive different segments of tourists to participate in hiking activities in Taiwan?
• How do the motivations of various hiking tourist segments influence their overall satisfaction with the hiking experience?
• What demographic and psychological factors distinguish different segments of hiking tourists in Taiwan?
• How can the insights gained from segmenting hiking tourists inform strategies for promoting sustainable tourism and nature conservation in Taiwan?

This study’s novelty lies in its nuanced d segmentation of hiking tourists in Taiwan, distinguishing personal factors such as motivations and satisfaction levels—a dimension previously underexplored in the literature. By providing a comprehensive analysis of hiking tourists’ expectations and experiences, this study offers unique insights for promoting sustainable hiking tourism in Taiwan and serves as a valuable reference for other regions.

2. Literature Review

2.1. Motivation

Motivation, derived from the Latin verb movēre (literal meaning: to move), is a complex psychological construct that drives human behavior [22]. Various theories have been developed to explain why people engage in certain activities, such as hiking. One of the most widely recognized theories is Self Determination Theory, which differentiates between intrinsic and extrinsic motivations [23]. Intrinsic motivation refers to the act of doing something for its inherent enjoyment or satisfaction. On the other hand, extrinsic motivation entails doing something in order to achieve an external outcome [24].

Hiking motivations are multifaceted and can vary widely depending on individual preferences, environmental conditions, and social contexts [25]. Intrinsic motivations for hiking often include a desire for connection with nature, personal challenge, and the pursuit of solitude or mental clarity. For many hikers, the experience of being in natural surroundings provides a sense of peace and rejuvenation, fulfilling psychological needs for relaxation and escape from the stresses of daily life [26]. Additionally, the physical exertion and challenge of hiking can serve as a form of self-improvement or personal achievement, particularly for those who seek to push their physical and mental limits [10].

Extrinsic motivations for hiking are driven by external rewards or social factors. These can include the desire for social interaction, status, or the pursuit of health and fitness goals. For some hikers, the social aspect of hiking—interactions with others—is a primary motivator [27]. Others may be motivated by the health benefits of hiking, such as improved cardiovascular fitness, weight loss, or overall well-being [17]. In some cases, extrinsic motivations may also include more materialistic or status-driven factors, such as completing well-known trails or participating in hiking events for recognition [28].

Beard and Ragheb [29] developed the Leisure Motivation Scale (LMS) by compiling various intrinsic and extrinsic motivations behind individuals’ engagement in leisure activities, including hiking. The LMS has four dimensions of motivation:

• Stimulus avoidance: This dimension relates to the desire to escape from everyday stress, seek solitude, and find relaxation [30]. Hikers motivated by stimulus avoidance might prefer remote, peaceful trails where they can disconnect from their daily lives and enjoy the tranquility of nature.
• Intellectual: This dimension reflects the motivation to engage in leisure activities that involve mental stimulation, learning, or discovering new things [31]. For example, a hiker motivated by intellectual factors might be interested in learning about the flora and fauna of the areas they hike in or might seek out trails that offer historical or cultural significance.
• Social: This dimension relates to the desire to engage in activities for social reasons, such as meeting new people, spending time with friends or family, or participating in group activities [32]. Socially motivated hikers might prefer group hikes, organized events, or popular trails where they can interact with others.
• Competence—mastery: This dimension relates to the desire to challenge oneself, achieve goals, and master new skills [32]. For hikers, this might mean seeking out difficult routes, aiming to reach certain milestones (e.g., summiting a peak), or improving their physical fitness through hiking.

The LMS provides a structured framework to understand the different reasons why people engage in leisure activities [33]. It can be used as a valuable tool for segmenting hiking tourists based on their motivations. The identification of distinct motivational profiles among hiking tourists can cast light on tourism planning and park management [34].

2.2. Segmentation

Segmentation analysis first appeared in marketing research. Now, it is widely used in various fields and areas. When applied to hiking tourism, understanding the specific motivations and behaviors of different segments of hiking tourists can inform tailored management practices that align with the specific needs and expectations of different groups of hiking tourists, ultimately contributing to more sustainable and satisfying outdoor experiences [35]. For example, novice hikers could need easier-to-access paths and educational materials, whereas professional hikers would look for more difficult routes and solitary experiences [36]. Moreover, segmentation can help identify high-impact users or those who may require more education about environmental stewardship, ultimately contributing to sustainable tourism [37]. Therefore, the segmentation of hiking tourists can inform a policy for balancing outdoor leisure and conservation goals [38].

There are two primary approaches to segmentation: priori and posteriori [39]. A priori segmentation involves categorizing individuals based on predefined criteria, such as demographics (e.g., gender, age, education level, income, etc.) [40,41]. The frontline staff of protected areas tend to prefer this method because it is easy to identify broad categories of visitors. However, a priori segmentation often oversimplifies the complexities of visitor behavior and may fail to capture the nuanced differences in motivations and preferences that exist within demographic groups [42].

On the other hand, a posteriori segmentation is derived from data, typically using statistical techniques like cluster analysis and factor analysis [39]. This approach allows for detailed and accurate identification of visitor segments based on actual behavior, attitudes, or motivations rather than relying on predetermined categories [43]. Posteriori segmentation is generally considered superior to a priori segmentation because it provides a more nuanced understanding of visitor profiles, leading to more effective management and marketing strategies [44].

Several studies have applied posteriori segmentation to hiking tourism, yielding valuable insights into the diverse motivations and behaviors of hiking tourists. For example, Torbidoni [45] used cluster analysis to segment hiking tourists in Spain based on their motivations. The study identified three distinct segments, namely “nature-minded lovers” who had a desire to encounter nature, “sport hikers” who were focused on physical activity and health, and “general purpose hikers” who went hiking because of a particular reason or motivation. Similarly, Pan and Ryan [46] employed factor analysis to explore the motivations of visitors to a national park in New Zealand and identified five segments: “active social relaxers”, “enthusiastic visitors”, “nature isolates”, “relaxers”, and “reluctant visitors”. Each segment has different expectations and preferences for their hiking experience. The results of these studies highlight the effectiveness of posteriori segmentation in revealing the diversity of hiking motivations and the importance of tailoring management strategies to meet the specific needs of each segment.

2.3. Satisfaction

Generally speaking, consumer satisfaction is the favorable assessment of a product or service purchasing experience [47]. In this regard, tourist satisfaction can be seen as a favorable assessment of experiences during participation in tourism activities [48]. It is a key metric that reflects the performance of a destination [49].

The congruency theory is often used to explain whether satisfaction or dissatisfaction occurs [50]. According to this theory, satisfaction occurs when visitors’ expectations or desires are fulfilled. Externally, visitors’ satisfaction can be reflected by whether they are willing to revisit the same destination and provide positive referrals to friends and relatives [51]. Therefore, satisfaction is operationalized as expectation fulfillment, revisit intention, and word of mouth in this study.

Because different segments of hiking tourists may have varying expectations and preferences, a one-size-fits-all approach plan has proven ineffective [52]. For example, some hiking tourists may prioritize the aesthetic qualities of the environment and seek solitude, while others may focus more on physical challenges and social interaction. By identifying and understanding these different segments, policymakers can tailor their plans to enhance satisfaction for each group, ultimately leading to better conservation outcomes and more sustainable tourism practices [53].

Some studies on hiking tourism have explored the relationship between satisfaction and segmentation, providing valuable insights into the diverse needs and preferences of hiking tourists. For instance, Smith et al. [35] identified four segments of hiking tourists to 33 parks in Australia. There were differences in the mean levels of satisfaction for many attributes of these parks. Kyle et al. [54] conducted a study on hiking tourists along the Appalachian Trail, where they segmented hikers based on their levels of involvement and place attachment. The study found that highly involved hikers, who felt a strong connection to the trail, were more likely to report higher levels of satisfaction compared to less involved hikers. Similarly, Mehmetoglu [55] identified distinct segments of nature-based tourists in Norway, including hikers, based on their motivations and attitudes toward nature conservation. It was found that satisfaction levels varied significantly across different segments, with those motivated by environmental concerns reporting higher satisfaction when their expectations for pristine natural environments were met.

These studies highlight the importance of considering the segmentation of hiking tourists when assessing satisfaction. The results suggest that segmentation analysis can reveal underlying differences in expectations and experiences among segmentation, which may not be apparent when analyzing satisfaction data in its entirety.

3. Methods

3.1. Study Area

The survey was conducted along Section 4 of the Taipei Grand Trail (Figure 1). The Taipei Grand Trail is a network of scenic hiking routes that span the hills and mountains surrounding Taipei, Taiwan. The entire trail is about 92 km long and is divided into seven sections. Stretching a length of 12.92 km, Section 4 connects the Dahu Park Station of Taipei Metro and the legendary Yangmingshan National Park [56].

A few reasons justify the selection of Section 4 of the Taipei Grand Trail. First, its proximity to urban centers ensures a steady and diverse flow of hiking tourists, providing a robust sample for the study. Second, Yangmingshan National Park is famous for dense forests, clear streams, and rich biodiversity [57], offering a serene setting that appeals to a wide range of recreational hikers. Third, because Section 4 of the Taipei Grand Trail provides well-maintained hiking conditions and connectivity to other trails, it attracts a broad spectrum of hikers, from casual walkers seeking relaxation to more avid adventurers looking for physical challenges. This diversity in hiker profiles is ideal for exploring different motivational segments. These characteristics make Section 4 of the Taipei Grand Trail a sensible choice for investigating the motivation and satisfaction among hiking tourists in Taiwan. The insights are relevant to broader contexts of nature-based tourism and nature conservation.

3.2. Instrument

The instrument used for this study was a structured questionnaire. Its design was deduced from a critical review of the existing literature. The questionnaire comprises three sections to collect data on hiking motivations, satisfaction, sociodemographics, and trip characteristics. The first section included 18 items of modified LMS to assess the motivations of hiking tourists [38]. The second section asked respondents to rate three items (i.e., expectation fulfillment, revisit intention, and word of mouth) related to satisfaction. The question items of the first and second sections were measured using a seven-point Likert scale, ranging from “1 = highly disagree” to “7 = highly agree”. In the third section, the respondents’ sociodemographic information was gathered using seven items: gender, age, occupation, educational attainment, monthly income, hiking experiences, and frequencies.

To ensure content validity, the questionnaire was reviewed and validated by two independent experts who provided feedback on the clarity, relevance, and comprehensiveness of the questionnaire. A pilot study was conducted in the study area in July 2022 with a sample of 15 hiking tourists before the formal survey was implemented in August 2022. The pilot study aimed to identify and address any ambiguous wording or potential issues with the questionnaire before implementing the formal survey.

3.3. Data Collection

This study developed a sampling protocol to obtain a diverse and representative sample of hiking tourists who hiked on Section 4 of the Taipei Grand Trail. The convenience sampling method was employed because of cost-effectiveness. It is often used in exploratory studies where access to a specific population, like nature-based tourists in a protected area [58], is necessary.

To ensure that respondents were of an appropriate age and had relevant hiking backgrounds, only individuals aged 15 and above were invited to participate in the survey. To avoid redundant sampling and ensure the diversity of responses, only one individual was selected from each group of hiking tourists. This approach helped minimize the potential for bias that might occur if multiple members of the same group, who likely shared similar opinions, were included in the sample. The data collection took place on both weekdays and weekends, to capture a broad range of hiking tourists. The hours of the interviews were from 10:30 a.m. to 4:00 p.m. This duration was sufficient to accommodate the majority of day hikers. A total of 273 respondents were interviewed, but 11 cases were discarded because they did not complete the questionnaire (i.e., answered less than 90% of question items) or gave non-responsive answers. Eventually, 262 cases were secured for the statistical analysis.

A summary of the respondents’ sociodemographic characteristics is presented in

Table 1. Sociodemographic characteristics of the respondents (n = 262).

Sociodemographics		Number	%
Gender	Male	103	45.0
	Female	126	55.0
Age	<18	2	0.8
	18–30	53	21.1
	31–45	73	29.5
	46–60	77	30.7
	>61	45	17.9
Education	Primary	1	0.4
	Junior secondary	4	1.6
	Senior secondary	25	10.0
	Tertiary	144	57.6
	Postgraduate	76	30.4
Occupation	Student	11	4.3
	Unemployed	2	0.8
	Retired	54	21.2
	Homemaker	8	3.1
	Employed	180	70.6
Monthly income *	Less than TWD 20,000	21	9.2
	TWD 20,001–TWD 40,000	58	25.3
	TWD 40,001–TWD 60,000	61	26.6
	TWD 60,001–TWD 80,000	39	17.0
	TWD 80,001–TWD 100,000	20	8.7
	More than TWD100,001	30	13.1
Hiking experience	Number of years (mean ± std. dev.)	7.28 ± 9.358	--
Hiking frequency	Number of hikes/year (mean ± std. dev.)	42.47 ± 66.675	--

* US Dollar (USD)/Taiwan New Dollar (TWD) exchange rate = 32.

. There were slightly more female (55.0%) than male (45.0%) respondents. The number of female (55.0%) respondents was slightly higher than male (45.0%). Age distribution varied, with most respondents aged 31–45 (29.5%) and 46–60 (30.7%), followed by younger adults aged 18–30 (21.1%), and smaller representations from those under 18 (0.8%) and over 60 (17.9%). Educational attainment was predominantly at the tertiary level (57.6%), with 30.4% having postgraduate qualifications. The majority of the respondents were employed (70.6%), while a notable proportion were retired (21.2%). There were very few students, retired people, and homemakers. The monthly income levels ranged broadly, with the largest groups earning between TWD 40,001–TWD 60,000 (26.6%) and TWD 20,001–TWD 40,000 (25.3%). The average hiking experience among respondents was 7.28 ± 9.358 years, with a high frequency of hiking activities, averaging 42.47 ± 66.675 hikes per year.

3.4. Data Analysis

The statistical analysis was performed using IBM SPSS Statistics (version 26.0). Initially, the data were carefully coded and subjected to normality testing. Log transformations were applied to normalize the distribution of skewed data.

After the Kaiser–Meyer–Olkin (KMO) Index and Bartlett’s Sphericity Test had verified that the data were suitable for Explanatory Factor Analysis (EFA), motivation items, as measured by the modified LMS, were used to extract factors (i.e., motives) by EFA. The Varimax method was used to extract factors based on three criteria: factor loadings more than or equal to 0.5, eigenvalues greater than or equal to 1.0, and factors that explained at least 61.2% of the total variance [59]. Cronbach’s Alpha was used to evaluate the internal consistency of the factors determined. The factor scores were standardized to Z scores for use in subsequent clustering analysis.

K-means clustering analysis was employed to divide the respondents into distinct segments using the standardized factor scores for motives. Discriminant analysis was conducted to evaluate the accuracy of the clustering. Chi-square analysis and one-way ANOVA were conducted to examine differences in sociodemographics, trip characteristics, hiking motivations, and satisfaction among the identified segments of hiking tourists.

A common latent factor was used to assess potential common method bias. Furthermore, the collinearity of the data was tested by ensuring that all variables had a Variance Inflation Factor (VIF) of less than 10. Categorical variables were transformed into dichotomous variables using dummy coding. Finally, multiple regression analysis was employed to investigate the influence of sociodemographics, trip characteristics, and motivations on the satisfaction levels of hiking tourists.

4. Results

4.1. Hiking Motivations

The sample was proved appropriate for EFA based on the KMO value of 0.885. Bartlett’s Test of Sphericity (Chi-square = 2546.839, df = 136, p = 0.000) showed no significant redundancy among the variables. To facilitate a more interpretable factor structure with clearer distinctions between factors, the cross-loaded item “contact the nature” was removed. This change did not compromise the theoretical validity of the model [60]. Four factors with an eigenvalue higher than 1 were extracted from 17 variables (

Table 2. Four hiking motives identified by explanatory factor analysis.

Motive	Item	Mean ± std. dev.	Factor Loading	Eigen- Value	Cronbach Alpha	% Variance Explained
Relaxation	Relax mentally	6.470 ± 0.698	0.747	7.319	0.835	20.280
	Seek tranquility	6.454 ± 0.723	0.765
	Enjoy the wilderness	6.640 ± 0.540	0.828
	Escape from daily life	6.313 ± 0.982	0.582
	Relax physically	6.318 ± 0.841	0.592
	Keep body fitness	6.565 ± 0.606	0.713
Social interaction	Have a good time with friends	6.319 ± 0.881	0.758	2.062	0.872	17.546
	Make new friends	5.720 ± 1.169	0.698
	Develop close friendships	6.065 ± 1.050	0.849
	Gain a feeling of belonging among friends	5.689 ± 1.277	0.702
Competence and exploration	Challenge my capacity	6.299 ± 0.984	0.812	1.196	0.850	15.593
	Train my physical skills	5.732 ± 1.291	0.701
	Visit new places	6.310 ± 0.978	0.722
	Learn new things	5.916 ± 1.162	0.573
Mental refreshment	Refresh my mind	5.812 ± 1.047	0.820	1.071	0.762	15.090
	Use my imagination	5.715 ± 1.133	0.806
	Kill time	5.602 ± 1.410	0.516
Total variance explained						68.509

). These factors explain 68.509% of the total variance, indicating a satisfactory level of factor extraction [59]. Reliability tests were conducted for each factor, and Cronbach’s alpha values were higher than 0.7, indicating sufficient internal consistency [61].

The first factor, named “relaxation”, comprises six items (i.e., “relax mentally”, “seek tranquility”, “enjoy the wilderness”, “escape from daily life”, “relax physically”, and “keep body fitness”). This motive accounted for 20.29% of the variance, indicating that a significant portion of hiking tourists are motivated to unwind and find peace in nature.

The second factor, termed “social interactions”, includes four items, namely “have a good time with friends”, “make new friends”, “develop close friendships”, and “gain a feeling of belonging among friends”. This factor explained 17.55% of the variance, reflecting the social aspect of hiking, such as bonding with existing friends or forming new relationships.

The third factor, which accounts for 15.59% of the variance, reflects “competence and exploration”. This motive was composed of four items: “challenge my capacity”, “train my physical skills”, “visit new places”, and “learn new things”. This motive emphasizes the challenge, skill development, and exploration aspects of hiking activities.

The fourth factor, named “mental refreshment”, accounts for 15.09% of the variance. This motive has three items, namely “refresh my mind”, “use my imagination”, and “kill time”. This factor emphasizes the need for mental rejuvenation or simply the desire to pass the time leisurely.

4.2. Motivation-Based Segmentation

The factor scores were used to group the respondents into four clusters (i.e., segments) using K-means clustering (Figure 2). The results of ANOVA indicated that significant differences in motives were found among segments of hiking tourists (Figure 2).

The first segment, labeled as “mental refreshment seekers”, comprises 64 respondents (24.4%). This segment scores highest in “mental refreshment” (2.898), indicating that these hikers are driven by a strong desire to refresh their minds and engage in activities that stimulate their creativity.

The second segment, identified as “social hikers”, includes 40 respondents (15.4%). This segment scores highest in “social interaction” (2.817) and “relaxation” (1.293) but lowest in “competence and exploration” (−2.348). The combination of social and relaxation motives and avoiding physical challenges suggests that this segment views hiking as a social activity that also offers an opportunity to unwind and relax.

The third segment, termed “challenge seekers”, comprises 30 respondents (11.5%). This segment scores highest in “competence and exploration” (5.293) but lowest in “relaxation” (−1.669) and “social interaction” (−2.761). This segment is likely driven by a need for achievement and mastery but enjoys solitary.

The fourth segment, named “general purpose hikers”, includes 128 respondents (48.9%), representing the majority of hiking tourists. This segment does not score highest in four motives, indicating that these hikers have no particular strong reasons for hiking, but they may go hiking for a mix of reasons. Nevertheless, this segment exhibits positive scores in social interaction and competence, suggesting that going hiking is a good opportunity for social gathering and physical exercise.

Canonical discriminant analysis was used to verify the accuracy of K-means classification (

Table 3. Unstandard coefficients of canonical discriminant functions for the differentiation of hiker segments.

Motive	Function
	1	2	3
Motive 1: Relaxation	−0.395	−0.491	−0.044
Motive 2: Social interaction	−0.039	−0.049	1.316
Motive 3: Competence and exploration	−0.248	1.427	0.028
Motive 4: Mental refreshment	1.569	0.101	0.026
(Constant)	0.000	0.000	0.000
Explained variance (%)	45.2	34.8	20.0
Accumulated variance (%)	45.2	80.0	100.0

). In total, 94.7% of the 262 cases had accurate classifications, demonstrating a satisfactory rate of classification accuracy (

Table 4. Evaluation of the accuracy of hiker segmentation.

Clustering	Predicted Membership
	Mental Refreshment Seekers	Social Hikers	Challenge Seekers	General Purpose Hikers
Mental refreshment seekers (n = 64)	89.1% (n = 57)	0	0	10.9% (n = 7)
Social hikers (n = 40)	2.5% (n = 1)	92.5% (n = 37)	0	5.0% (n = 2)
Challenge seekers (n = 30)	3.3% (n = 1)	0	86.7% (n = 26)	10.0% (n = 3)
General purpose hikers (n = 128)	0	0	0	100% (n = 128)
Total (n = 262)	94.7% (n = 248)

).

The demographic characteristics of the four segments are listed in

Table 5. Demographic characteristics and satisfaction among four segments of hiking tourists.

Variable		Overall	Mental Refreshment Seekers	Social Hikers	Challenge Seekers	General Purpose Hikers	χ2 or F	Prob.
Gender	Male	103	18	19	11	55	7.692	0.053
	Female	126	40	16	17	53
Age	<18	2	0	1	1	0	20.238	0.063
	18–30	53	16	7	12	18
	31–45	73	21	11	6	35
	46–60	77	18	11	7	41
	>61	45	7	8	3	27
Education	Primary	1	0	0	0	1	9.633	0.648
	Junior secondary	4	0	0	0	4
	Senior secondary	25	4	4	2	15
	Tertiary	144	37	21	18	68
	Postgraduate	76	22	14	10	30
Occupation	Student	11	2	1	4	4	15.441	0.218
	Unemployed	2	2	0	0	0
	Retired	54	11	8	5	30
	Homemaker	8	2	2	0	4
	Employed	180	47	28	21	84
Monthly income *	Less than TWD 20,000	21	6	3	3	9	17.059	0.519
	TWD 20,001–TWD 40,000	58	14	5	10	29
	TWD 40,001–TWD 60,000	61	18	12	5	26
	TWD 60,001–TWD 80,000	39	11	5	4	19
	TWD 80,001–TWD 100,000	20	5	7	1	7
	More than TWD100,001	30	5	4	5	16
Hiking experience	Number of years (mean ± std. dev.)	7.28 ± 9.358	5.14 ± 6.872	6.80 ± 8.656	6.30 ± 9.185	8.79 ± 10.524	2.283	0.080
Hiking frequency	Number of hikes/year (mean ± std. dev.)	42.47 ± 66.675	30.48 ± 50.440	52.23 ± 99.547	33.23 ± 56.409	48.16 ± 63.516	1.342	0.261
Expectation Fulfillment	7-point scale (mean ± std. dev.)	6.046 ± 0.839	6.234 ± 0.831	5.949 ± 0.826	5.833 ± 0.747	6.032 ± 0.857	1.927	0.126
Revisit intention	7-point scale (mean ± std. dev.)	6.081 ± 0.863	6.206 ± 0.919	6.026 ± 0.873	5.933 ± 1.015	6.071 ± 0.792	0.793	0.499
Word of mouth	7-point scale (mean ± std. dev.)	6.166 ± 0.861	6.267 ± 0.880	6.051 ± 0.999	6.067 ± 0.980	6.178 ± 0.769	0.643	0.588

* US Dollar (USD)/Taiwan New Dollar (TWD) exchange rate = 32.

. The results of Chi-square test and ANOVA showed that no significant difference in demographics and hiking backgrounds were found among these four segments of hiking tourists, indicating the superiority of posteriori segmentation to priori segmentation.

Overall, respondents indicated a high level of expectation fulfillment (6.046 ± 0.839), revisit intention (6.081 ± 0.863), and word of mouth (6.166 ± 0.861), respectively. The results of ANOVA confirmed no significant difference in expectation fulfillment (F = 1.927, p = 0.126), revisit intention (F = 0.793, p = 0.499), and significant word of mouth (F = 0.643, p = 0.588) among the four segments of hiking tourists.

4.3. Expectation Fulfillment, Revisit Intention, and Word of Mouth

Three multiple regressions were developed to evaluate the effects of demographics, hiking experience, and hiking motives on expectation fulfillment, revisit intention, and word of mouth (

Table 6. Multiple regression analysis testing the effects of demographics, hiking experience, and hiking motives on expectation fulfillment, revisit intention, and word of mouth.

Variables	Standardized Coefficients Beta
	Expectation Fulfillment	Revisit Intention	Words of Mouth
Gender (reference: female):
Male	0.011	−0.001	0.000
Age (reference: younger than 30):
31–45	−0.140	−0.158	−0.103
46–60	−0.142	−0.208	−0.164
Older than 61	0.082	0.009	0.076
Education (reference: college or university):
High school or below	−0.005	−0.020	−0.042
Postgraduate	0.144	−0.028	0.005
Occupation (reference: employed):
Student	0.039	0.120	0.056
Unemployed, retired, homemaker	0.090	0.201	0.157
Monthly income (reference: TWD 20,001−WD 40,000):
<NTD20,000	0.091	0.076	0.060
TWD 40,001−TWD 60,000	0.101	0.092	0.168
TWD 60,001−TWD 80,000	0.031	0.032	0.020
TWD 80,001−TWD 100,000	0.096	0.156	0.109
More than TWD 100,000	−0.034	−0.022	−0.028
Hiking experience	−0.020	−0.021	−0.044
Hiking frequency	0.077	−0.047	−0.003
Motive 1: Relaxation	0.393 ***	0.374 ***	0.443 ***
Motive 2: Social interaction	0.233 **	0.254 ***	0.238 **
Motive 3: Competence and exploration	0.165 *	0.133	0.056
Motive 4: Mental refreshment	0.109	0.114	0.085
R2	0.270 ***	0.317 ***	0.331 ***
Adjusted R2	0.176 **	0.228 **	0.242 **
Standard error of the estimate	0.106	0.110	0.106
F-value	2.876 ***	3.583 ***	3.727 ***

(* p < 0.05; ** p < 0.01; *** p < 0.001).

). The adjusted R² values indicate that the models explain a moderate proportion of the variance in the dependent variables, with the highest explanatory power for word of mouth (adjusted R² = 0.242) and the lowest for satisfaction (adjusted R² = 0.176). The significant F-values for all three models confirm that the regression models fit the data well.

The results of multiple regressions indicated that demographics and hiking backgrounds exhibited limited effects on expectation fulfillment, revisit intention, and significant word of mouth, but hiking motives were predictors to different degrees. While relaxation and social interaction significantly affected expectation fulfillment, revisit intention, and word of mouth, competence and exploration predicted only expectation fulfillment but not revisit intention and word of mouth. Mental refreshment was not a predictor of expectation fulfillment, revisit intention, and word of mouth.

5. Discussion

5.1. Hiking Motives

Hiking is a multifaceted outdoor activity that serves various purposes for different individual hiking tourists. This study identified four motives: relaxation, social interaction, competence and exploration, and mental refreshment. The results were generally consistent with the existing literature that diverse motivations drive people to engage in hiking.

The first motive, “relaxation”, represents the most important driver for hiking among the respondents. The strong presence of this motive aligns with the existing literature, where relaxation has been repeatedly highlighted as a fundamental reason why individuals engage in nature-based activities. Korpela et al. [26] noted that outdoor activities such as hiking offer a reprieve from the stressors of daily life, allowing individuals to recharge both mentally and physically. This finding is further supported by Chiang and Wang [62], who found that escape/relaxation is a key motivator among hiking tourists in Taiwan’s national parks. The desire to escape the hustle and bustle of urban life and immerse oneself in the tranquility of nature is a powerful appeal that resonates with many hiking tourists.

The second motive, “social interactions”, highlights the importance of social connections in the hiking experience. Collins-Kreiner and Kliot [63] have demonstrated that social interaction is crucial in outdoor recreation, where activities serve as platforms for strengthening existing relationships and forming new social bonds. The findings of this study are consistent with Kyle et al. [64], who emphasized that social interactions not only enhance the hiking experience but also contribute to overall satisfaction. The social aspect of hiking allows participants to share experiences, create memories, and develop a sense of community, thereby enriching the overall experience [54].

The third motive, “competence and exploration”, reflects the desire for self-improvement, skill development, and the thrill of discovery. The importance of challenge and exploration in nature-based activities has been extensively documented in the literature. For instance, Bichler and Peters [10] highlighted that individuals are often motivated by a need for achievement and mastery, seeking to test their limits and acquire new skills in demanding environments. This motivation is also linked to the concept of Self Determination Theory, where individuals are driven by intrinsic needs for competence, autonomy, and relatedness [65]. The desire to explore new places and learn new things also speaks to the adventurous spirit that many hiking tourists possess as they seek out novel experiences that challenge their physical and mental capacities.

The fourth motive, “mental refreshment”, reflects the cognitive and psychological benefits of hiking, where participants seek mental rejuvenation and an opportunity to engage in reflective or creative thinking. The need for mental refreshment is particularly relevant in today’s fast-paced world, where individuals often face cognitive overload and seek activities that allow them to clear their minds and engage in leisurely thought. Kaplan and Kaplan [66] proposed that natural environments provide a restorative experience that can help reduce mental fatigue and improve cognitive functioning. Similarly, Bratman et al. [67] found that spending time in nature has significant restorative effects that improve mood and mental clarity.

5.2. Segmentation of Hiking Tourists

This study identified four segments of hiking tourists: “mental refreshment seekers”, “social hikers”, “challenge seekers”, and “general purpose hikers”. They participated in hiking with different motives.

The first segment, labeled as “mental refreshment seekers”, is characterized by a strong emphasis on mental refreshment. These hiking tourists are particularly motivated by the desire to refresh their minds and engage in activities that stimulate creativity. This aligns with the findings of Kaplan and Kaplan [66], who highlighted the restorative effects of natural environments on cognitive functioning. Mental refreshment seekers will likely prefer tranquil, scenic trails that offer solitude and opportunities for reflection.

The second segment, identified as “social hikers”, is characterized by the combination of social and relaxation motives, coupled with an aversion to physical challenges. These hikers view hiking as a social experience with the added benefit of unwinding. This segment is consistent with Collins-Kreiner and Kliot [63] that leisure activities can fulfill multiple psychological functions, including social bonding and relaxation. Social hikers are likely to be attracted to well-maintained, accessible trails that offer social amenities such as picnic areas or group activities.

The third segment, “challenge seekers”, is characterized by a strong drive for achievement, mastery, and exploration, often seeking more strenuous and goal-oriented activities. Conversely, relaxation and social interaction are not important to them. This segment aligns with the concepts of intrinsic motivation and competence discussed by Bichler and Peters [10], where individuals are driven by the desire to challenge themselves and improve their skills.

The fourth segment, named “general purpose hikers”, does not score the highest in any of the four motives but shows positive scores in social interaction and competence, suggesting a balanced, mixed-motivation profile. General purpose hikers may engage in hiking for various reasons, including social gathering, physical exercise, and general recreation, without any particular strong preference for one motive over another. This segment reflects the concept of multi-motivation, where individuals partake in activities that satisfy various needs simultaneously [23].

5.3. Expectation Fulfillment, Revisit Intention, and Word of Mouth

Understanding hikers’ satisfaction is crucial for informing management strategies in natural areas. The high levels of expectation fulfillment, revisit intention, and word of mouth among Taiwan hikers indicated that Section 4 of the Taipei Grand Trail could provide hiking tourists with a satisfactory journey. While the differences in expectation fulfillment, revisit intention, and word of mouth were not statistically significant among the four segments of hiking tourists, the overall relationship between motivations and these outcomes remains important.

Motivations significantly determine the quality of the hiking experience. Hiking tourists who are driven by strong motivations, such as the desire for mental refreshment, social interaction, or physical challenge, are more likely to experience satisfaction during their hiking trips. This is because motivations are closely aligned with personal fulfillment and psychological needs, as described by Self Determination Theory [23]. When these motivations are met, hiking tourists will likely feel a sense of accomplishment, enjoyment, and well-being. All these contribute to their overall satisfaction with the experience.

The satisfaction derived from expectation fulfillment may also influence revisit intention. Satisfied hiking tourists are more likely to return to the same destination [68]. This is supported by the broader literature on tourist behavior, which suggests that satisfied visitors are more inclined to repeat their visits as they seek to recreate the positive feelings they previously encountered [69].

Word of mouth, or the likelihood of recommending the hiking location to others, is also influenced by motivation. Generally, satisfied visitors tend to share their positive feelings with friends, family, and social networks [70]. Positive word of mouth can significantly enhance the reputation of a hiking location and attract new visitors [71].

6. Conclusions

This study explored hiking motivations using the LMS, and four hiking motives, namely relaxation, social interaction, competence and exploration, and mental refreshment, were determined. Based on these four motives, four distinct segments of hiking tourists were identified: mental refreshment seekers, social hikers, challenge seekers, and general purpose hikers. Each of these segments had their unique motivational profiles. Hiking motives were also predictors of hikers’ satisfaction, revisit intention, and word of mouth. These findings make valuable contributions to academic discourse on tourism and outdoor recreation, particularly within national parks, by emphasizing the importance of recognizing and addressing different motivational drivers.

6.1. Theoretical Implications

This study adds to the body of knowledge on motivation and tourism by offering empirical support for the multidimensional nature of hiking motives and their varying impacts on expectation fulfillment, revisit intention, and word of mouth. The identification of distinct segments of hiking tourists based on hiking motivations adds to the body of work on segmentation in tourism and outdoor recreation. This study also demonstrates the utility of a posteriori segmentation in capturing the complexity of recreational behaviors. The findings also highlight the nuanced relationship between different types of motivations and recreational outcomes, suggesting that not all motives equally influence satisfaction and future behaviors. This challenges the assumption that more intense or specialized motives are always the strongest predictors of positive outcomes [23,72]. Instead, more general motives like relaxation and social interaction may have broader and more consistent effects across different outcome measures. Future studies on motivation in outdoor recreation can benefit from these findings, especially when it comes to comprehending the ways in which distinct motivational dimensions influence different facets of the recreational experience.

6.2. Practical Implications

From a practical standpoint, this study offers valuable insights for policymakers and tourism planners. The identification of four segments highlights the diversity of hiking motivations and underscores the importance of tailored management and marketing strategies [73]. By recognizing and addressing the distinct needs of each segment, it is possible to enhance visitor satisfaction, encourage repeat visits, and foster a positive relationship between hiking tourists and the natural environment. For example, relaxation and social interaction are key drivers of positive outcomes, suggesting that providing spaces and opportunities for socializing and unwinding could enhance visitor satisfaction and encourage repeat visits. The challenge-seeking segment, although smaller, may benefit from more physically demanding trails or adventure-based programs that cater to their need for competence and exploration.

Furthermore, the segmentation of hiking tourists can support the deployment of technologies and personalized customer services in sports and recreation. For instance, smart technologies like mobile apps could offer customized hiking itineraries based on individual preferences, and customer service systems could provide tailored recommendations for equipment or trails based on each segment’s needs. This integration of technology has the potential to improve the overall customer experience and promote sustainable tourism practices, as demonstrated in the broader sports and recreation sectors [74]. The use of segmentation strategies can thus provide a more focused approach to tourism management, enhancing both the quality of services and conservation outcomes.

6.3. Limitations and Recommendations

While this study provides valuable insights into hiking motivation and its effects on recreational outcomes, several limitations should be noted. First, the use of a convenience sample from one hiking trail may limit the generalizability of the findings to other contexts or populations. Future research should consider conducting similar studies in various settings to determine whether the identified segments and their corresponding behaviors are consistent across different contexts or if location or place-specific factors play a significant role [54]. Second, the LMS may not fully capture the unique motivations specific to hiking activities, although it is a well-established and widely used tool in leisure and recreation research [29]. For instance, the LMS is designed to measure general leisure motivations, which might overlook certain dimensions specific to nature-based activities, such as environmental stewardship or spiritual experiences [24]. Future studies could develop or incorporate additional scales tailored specifically to outdoor and nature-based recreation to provide a more comprehensive understanding of hiking motivations. Third, while this study focused on self-reported motivations and outcomes, future research could benefit from incorporating objective measures of hiking behavior, such as GPS tracking or observational data, to provide a more comprehensive understanding of how motivations influence actual behavior. Fourth, the study’s cross-sectional design does not account for potential changes in motivations or behaviors over time, which could be influenced by factors such as seasonal variations, life stage changes, and even pandemics [75]. Future studies could track hiking tourists over time (i.e., longitudinal approach) so they provide insights into how motivations evolve and impact satisfaction, revisit intention, and word of mouth among hiking tourists [76].