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Abstract

Identifying crowding norms is a crucial part of modern management frameworks intended to assist in protecting park resources and the quality of the visitor experience. Determining the factors affecting perceived crowding is a subject that has always been emphasized by park and protected area managers and researchers. Experience is typically regarded as having previously visited the area or engaged in an activity in prior literature. This study aims to analyze the potential effects of “experience” in determining crowding, based on visual research methods, from a perspective other than the two approaches in the literature. A quasi-experimental research design was applied to the study. Eleven images created with photography techniques were presented to 32 voluntary participants for data collection. According to the findings, participants had different perceptions about crowding before and after the activity, and at the end of the interviews conducted to understand the reasons for this difference, “enjoy” was determined as the main underlying cause. As a result, it is suggested that personal experiences about the activity should be considered in norm-determining studies.

Plain Language Summary

This study aims to analyze the potential effects of “experience” in determining crowding, based on visual research methods, from a perspective other than the two approaches in the literature. A quasi-experimental research design was applied to the study. Eleven images created with photography techniques were presented to 32 voluntary participants for data collection. According to the findings, participants had different perceptions about crowding before and after the activity, and at the end of the interviews conducted to understand the reasons for this difference, “enjoy” was determined as the main underlying cause. As a result, it is suggested that personal experiences about the activity should be considered in norm-determining studies.

Keywords

visual-based method national park rafting perceived crowding outdoor recreation experience

Introduction

National parks, an important category of protected area, play a significant role in biodiversity preservation and ecosystem service provision and have strong ties with the UN’s Agenda 2030 and Sustainable Development Goals (Job et al., 2021). While contributing to environmental sustainability with this protection duty of national parks, it positively affects the physical health, mental well-being, and social relations of the participants with its natural landscape, ecological services, existing activities, and facilities (Li et al., 2021). Therefore, parks and protected areas have taken on the dual task of facilitating quality experiences for visitors and ensuring the conservation of natural and cultural resources (Fennell, 2015). A quality visitor experience positively impacts visitor satisfaction, including revisit intentions and loyalty (Pearce & Dowling, 2019). While this situation increases visits to national parks, it also contributes to regional development economically, environmentally, and socially. However, many national parks are highly or even over-visited (Seebunruang et al., 2022), and this overcrowding negatively affects the quality of the recreation and visitor experience (Tverijonaite et al., 2018). Moreover, overcrowding, which means exceeding the maximum number of people, who can visit a destination at the same time, leads to externalities in the physical, economic, and sociocultural environment and reduces the satisfaction of the visitors (Sanz-Blas et al., 2019), resulting in a lower-quality park experience (Manning, 2011).

The body of research on crowding in national parks is extensive (Manning et al., 2017), and the most challenging part of these studies is formulating the quality standards perceived by the visitors. Many researchers argue that normative theory can help formulate these quality standards (Sayan et al., 2013). Therefore, numerous studies have used normative theory, which broadly states that visitors have shared beliefs, or norms, about important aspects of their experience and appropriate conditions (Manning, 2011). As a special application to managing recreation and tourism in national parks, this theory has been based on the development of Jacksons’s return potential model. In this context, the model constructs a norm curve by asking visitors to rate the acceptability of various recreation-related impacts on the environment and the value of their overall experience. The norm curve can define the range of acceptable conditions covering preferred conditions, minimum and maximum acceptable conditions, and norm intensities (Manning & Freimund, 2004). Different methods, such as visitor surveys, interviews, and visual research methods, have been used since the 1990s in norm measurement practices related to recreation. Particularly where visitor use is high or the impacts of visitor use are complex and can only be stated verbally in technical terms (e.g., level of trail erosion), it has been argued that visual research methods may be effective (Manning & Krymkowski, 2010). Researchers often use visual methods, such as pictures, to help determine norms by looking at computer-modified photographs of parks and showing social and ecological conditions and effects at various levels (Bullock & Lawson, 2008; Krymkowski et al., 2009). Additionally, Manning and Freimund (2004) contend that using images to determine norms improves measurement reliability because images, contrary to narrative descriptions, precisely depict actual or potential settings.

Visual-based methods are recognized as one of the most widely used methods for determining crowding standards. Although, numerous other studies support the validity of visual-based methods, many authors contend that questions remain unanswered regarding the validity of visual-based. For instance, alternative measurement approaches, such as using different question formats (Manning et al., 2002), the order in which photographs are presented (Cribbs et al., 2022), and the range of the number of people in photographs (Gibson et al., 2014) can lead to significantly different estimates of crowding norms. Thus, it may be possible to determine different crowding norms from the same sample group while creating a crowding norm in a national park or conservation area with the visual research method. This difference raises the question regarding which crowding norm is acceptable. This problem brings to mind the question of possible changes in the crowding norm in measurements made at different times (before and after the experience) in the same sample group and region, which is seen as a gap in the relevant literature. Moreover, in the previous literature, experience has been mostly considered as previous experience of visiting the region or having experienced an activity before (e.g., specialization, skills). In addition, results remain inconsistent in perceived crowding of visitors with past on-site experience. For instance, some researchers reported a positive relationship between the degree of past on-site experience with an area (Arnberger & Brandenburg, 2007; Eder & Arnberger, 2012). However, many studies did not find any empirical evidence for a significant effect of the number of past visits on crowding perceptions (Budruk, Schneider, et al., 2002; Budruk, Wilhem Stanis, et al., 2008). Few studies have found that first-time and less frequent visitors feel more crowded than frequent visitors (Sharp et al., 2015). Although, the relationship between past activity experience (e.g., specialization, skills) and perceived crowding has been confirmed in the relevant literature, there are still inconsistencies in studies. For instance, some research found that when the level of specialization in the activity increases, the tolerance for crowding decreases (Bentz et al., 2015). Correspondingly, Leujak and Ormond (2007) found that more skilled snorkelers are significantly more susceptible to crowding. In contrast, some studies reported that skilled (Kuentzel et al., 2022) and specialization visitors (Catlin & Jones, 2010) had less crowding perceptions than other visitors.

This study aims to find answers to the following questions regarding, whether there will be a change in the crowding norm in measurements made at different times (before and after the experience) in the same sample group and region, which is seen as a gap in the relevant literature: (1) does perceived crowding differ before and after rafting? (2) If so, what are the underlying factors causing this difference? To address these questions, we selected Köprülü Kanyon National Parks in Antalya, one of the popular recreational and touristic rafting destinations in Turkey with an estimated 500.000 to 1 million visitors per year (Albayrak, 2016). By answering these questions, the effect of experience on crowd norm, apart from pre-on-site experience and activity experience approaches, can be revealed with its reasons. Thus, by defining experience outside of previously examined factors, understanding the crowding impacts in the park and protected area sector can be deepened. In this context, the remaining part of the study is organized into four sections. The next section presents the literature background of the concept of perceived crowding. The following section explains the steps of the research method the author applied in conducting this study. The research results and discussion are organized into two main sections: (1) the quantitative and qualitative findings of the research and (2) the discussion in relation to the literature. In the last section, the results and limitations of the study are presented.

Theoretical Background

Normative Theory

The normative theory reliably develops standards and evaluates different social, environmental, and/or managerial conditions in parks and related outdoor recreation areas. Norms generally represent standards accepted as “normal” in an individual (personal norms) or a social group (social norms) (Manning, 2011), and they regulate behavior broadly through actions, emotional expressions, portrayals of one’s behavior to others, and justifications (the explanations people give for their behaviors) (Horne & Molborn, 2020). Three approaches exist to the study and application of normative theory (Vaske & Whittaker, 2004): one focuses on the variables that activate norms, the other explores the impact of attitudes and norms on individuals’ behavior, and the third is concerned with structural features and tries to set social standards. The broadly used model to operationalize normative theory is the return potential model (RPM), proposed by Jackson in 1966. The RPM measures the relationship between behavior and approval in or by a social group. The RPM includes the behavior dimension representing several possible behaviors of conditions of an indicator in a particular situation and the evaluation dimension (Enseñat-Soberanis & Blanco-Gregory, 2022). The Return Potential Curve, also frequently turned into a social norm curve, is plotted to describe group members’ feelings about a specific behavior dimension in a specific situation. Attitudinal ratings by individual group members are averaged for the curve. Several features of the curve can be quantified to measure and describe different characteristics of norms, such as the range of acceptable conditions, intensity of the norm, optimal or preferred condition, minimum acceptable condition, and crystallization (or consensus) of the norm (Nolan, 2015).

RPM is used, and visitors are asked to evaluate different park conditions by using RPM to set norms for parks and related outdoor recreation areas. Then, a social norm curve with an x- and y-axis can be drawn at the end of the evaluation process. Two approaches have been used for measuring normative standards in parks and related outdoor recreation areas: the traditional narrative and numerical approach (Manning & Freidmund, 2004) and the visual approach (Manning, 2011). Both approaches rely on asking visitors to evaluate the acceptability of a range of conditions for an indicator, but how these conditions are presented in a questionnaire differs. The narrative in the numerical approach uses descriptive conditions, while computer-manipulated photographs portray the conditions in the visual approach. Both measurement approaches are valid, but some techniques suit specific situations. In crowding-related research, a visual approach can be more appropriate than a traditional and numerical approach (Manning & Krymkowski, 2010).

Crowding Norms

Crowd is arguably the most interesting topic in outdoor recreation research and can be defined as a negative response or assessment of the level of concurrent use in a space (Fefer et al., 2021). Therefore, the difference between crowding and density should be defined. The term “density” refers to population density, describing the physical condition of spatial limitation, and it can be objectively determined. Meanwhile, crowding is a negative evaluation of density (Vaske & Shelby, 2008), and it indicates a value judgment that the number of actual encounters in a specific area exceeds a visitor’s normative standard for a preferred experience (Lime et al., 1996). Furthermore, perceived human crowding is a subjective evaluation of the number of encounters, and it has also been defined as the maximum number of people who can use a site without an unacceptable alteration in the physical environment or an acceptable quality of the visitor experience (Milman et al., 2020). Perceived crowding is influenced by two main groups: (1) Factors intrinsic to the visitors, such as sociodemographic profile, previous experience, income, motivations, values, or culture/nationality, and (2) Factors extrinsic to the visitor, such as the physical and environmental characteristics of the site and the type of encounter (Enseñat-Soberanis et al., 2020).

There is important data about the thought that personal features of individuals, such as visitor motivations (Yan & Zhou, 2020), visitor characteristics (Oftedal et al., 2015, Tanner et al., 2008), and past experiences of visitors (Manning et al., 2000; Zehrer & Raich, 2016) affect crowding norms. Several studies in the literature indicate that visitors seek solitude and expect and prefer few encounters and experienced visitors are sensitive to crowding. Moreover, the characteristics of those encountered, such as group size or their behavior and situational variables like the area type, from wilderness conditions to highly developed infrastructure in a national park, or the time and season of the visit, can also influence the perception of crowding (Schamel & Job, 2013).

Studies of quality determination based on visitors focus on personal and social norms. Sociology and social psychology norms form theoretical and experimental frames for studying outdoor recreation areas. The normative theory is applicable specifically to set quality standards for recreation experiences. These applications are geared toward resource and social conditions instead of behavior. Moreover, unlike behavior, resource and social conditions do not appear to be subject to sanctions and do not require an obligation on the part of individuals. However, visitor behavior directly affects park resources and the quality of the recreational experience (Sayan et al., 2013). Thus, visitors’ normative standards for recreation experiences can be assessed and used to formulate quality standards. Thus, determining bearing capacity and managing an area efficiently are possible.

Although recreation is not the primary purpose in natural areas, many studies aim to provide information about visits to these areas and to provide visitor-based quality standards. These practices are mostly based on Return Potential Curves methodology studies developed by Jackson in 1965 for assessing norms. Testing personal and social norms or the relationship of the norm level between groups is possible with this method. The most common application of normative research has been in crowd research, examining issues of encounters, intimacy, and conflict, resulting in quality standard development (Budruk & Manning, 2003). The scope of this research has been improved to involve potential quality indicators, such as camping sites and streams (Shelby & Whittaker, 1990), including ecological impacts in natural life management in these areas. The crowding evaluation component is based on the idea of norms (Manning, 2007). This norm is a total of shared attitudes and preferences, such as social, environmental, or managerial, used in setting a specific recreation (Heberlein, 2012).

Visual-Based Methodology

The biggest difficulty in setting standards is obtaining quality evaluation data about the acceptability of resource conditions. Narration methods were first employed in defining the resource conditions; the difficulties set by this method could only be overcome by using the narration methods based on visual representations (Manning & Freidmund, 2004). Photographs allow visitors to “imagine” a range of conditions while offering the ability to classify different conditions (Newman et al., 2001). The most common application of the photographic method in outdoor recreation research is subjective crowd assessment. In this application, researchers typically present visitors with four to six photos (represented as the number of people in the photos), showing their increasing usage levels and ask visitors to complete a quantitative questionnaire that includes questions about the conditions viewed (Cribbs et al., 2022). Visual-based methods in recreation research were used in obtaining evaluation data about the acceptability of People at One-time method. When visual-based methods and acceptability curves are combined, visual-based methods are employed to collect data to develop acceptability curves.

Relationship Between Experience and Crowding

Experience is an important product of the recreation and tourism industries (Ellis et al., 2019). Since the 1980s, several researches have been done on the importance of experience in affecting visitor perceptions, behavior, and management preferences (Hammitt et al., 2004). In these comprehensive studies, the relationship between crowding perception and experience has been tested by many researchers. Most researchers utilized Experience Use History (EUH), defined as the quantity of prior experience a person has with a certain activity and/or resource at a particular place and/or other comparable sites. EUH is frequently assessed in terms of length and frequency components across many dimensions, such as the number of visits, the number of years of use, and the frequency of involvement each year at the specified place and/or at nearby locations (Xu et al., 2020). The researchers hypothesized that visitors with great experience were also sensitive to changing social and environmental site conditions in natural settings because their memories allowed them to contrast past and present conditions (Arnberger, 2012). However, empirical findings are mixed. Some studies have emphasized that visitors with several past experiences reported higher crowding perception than first-time and inexperienced visitors (Arnberger, 2012; Arnberger & Brandenburg, 2007). Contrarily, numerous research (Budruk, Schneider, et al., 2002; Budruk, Wilhem Stanis, et al., 2008) failed to uncover any empirical support for a substantial relationship between the number of prior visits and crowding perceptions. Few studies have discovered that frequent visitors felt less congested than first-time visitors with few frequent visits (Sharp et al., 2015). Additionally, the relationship between past activity experience (e.g., specialization, skills) and perceived crowding has been investigated in the relevant literature. According to research, specialized divers experience higher crowding than less skilled divers (Catlin & Jones, 2006; Bentz et al., 2015; Leujak & Ormond, 2007). Contrarily, several studies found that skilled and specialty visitors experienced less crowdedness than other visitors (Catlin & Jones, 2010; Kuentzel et al., 2022). Moreover, the relationship between experience and crowding was also examined from another perspective. For example, Zhang et al. (2017) argued that perceived crowding negatively affects the quality of Mount Sanqingshan national park visitors’ experiences. Stewart and Cole (2001) found a negative but weak relationship between the number of encounters and experience quality. Conversely, Kuss et al. (1990) and Manning (2011) reported that the effect of density and encounters on overall experience quality is generally weak to non-existent. These inconsistent results highlight the need for additional research on the relationship between crowding and experience.

Method

This study is quasi-experimental research conducted to evaluate the effects of experience on individual crowding perception. The visual-based method, commonly used in similar research to determine crowding standards in outdoor recreation areas (Freimund et al., 2002; Manning, 2011; Manning & Freimund, 2004; Sayan et al., 2013), was used in this study along with the interview method, which was used for determining the meanings attributed to issues by participants (Berg & Lune, 2014). A visual-based research method is a significant approach to assessing the quality standards in studies about parks and outdoor recreation areas (Manning & Freimund, 2004). Persons or objects are placed on photographs through software by researchers in this method. The number of persons or objects in a photo mostly ranges from “good” to “bad” (Gibson et al., 2014). In this study, the number of persons or objects in reproduced photographs was increased, and the crowding perceived by the participant according to People at One-time method was determined. Each reproduced photograph was separately presented to participants to determine the perceived crowding; participants were asked to evaluate the number of persons/objects in the photograph in terms of crowding. PAOT value is placed on the x-axis, while the acceptability rate is on the y-axis. Evaluation is based on +4 (completely acceptable) and −4 (completely unacceptable) ranges; 0 (neutral) or 9-point scaling is conducted (Sayan et al., 2013). As a result, a hypothetical norm curve indicating the participator acceptability rate according to PAOT is obtained (Figure 1).

Figure 1.

Example of a hypothetical norm curve (Manning, 2011).

Participants

Rafting service in Köprülü Canyon National Park is provided by agencies that provide commercial services in the region. For the study, an agency providing rafting services in the region was contacted and informed about the study, and verbal permission was obtained from the agency. The participants were selected as a convenience sampling method among the visitors who voluntarily came to Köprülü Canyon National Park for rafting purposes and purchased rafting services from the relevant agency. This method was used because the participants were at the right place and time. Thirty-two randomly selected visitors volunteered in the rafting activity in Köprülü Canyon National Park in this study. There are 13 female and 19 male individuals in the group, and the average age is 29.8 (SD = 1.6). Of all participants, 72.7% had no previous rafting experience.

Research Area

The study was conducted in Köprüçay rafting area, Köprülü Kanyon National Park, 80 km from Antalya (324,500–3,43,000 E and 4,143,000–4,110,000 N). Köprülü Kanyon National Park is located in a 366 km² area, and it is one of the five national parks in Antalya; the area is commonly visited, especially during the summer, and is highly preferred as an outdoor recreation area. The most popular activity in the area is rafting. Approximately 11 km along Köprüçay River is used for rafting activity. The difficulty level in rafting is 1, 2, and 3. This difficulty level is regarded as simple, low-flow, and suitable for amateurs according to the International River Difficulty Scale (Folland & Strachan, 2012). For this reason, the region is preferred for rafting, which is popular in tourism and recreational activity. Although the exact number of visitors remains unclear, it is estimated that 500,000 to 1 million (Albayrak, 2016) people visit the area for rafting yearly.

Procedure

The study was completed between June 19 and 21, 2019, in Köprüçay River rafting area. The river was photographed by the researchers at the beginning of the research period. The size of the area in the photograph, the arrangement of the photograph according to the eye-line of participators (for creating a sense of real experience), and the preference of the most crowded area on the river were the significant considerations during this process. Ninety photographs taken on this basis were eliminated, and the ones used in interviews were carefully determined (Rafting Start Point). The chosen photographs were transferred to a computer, and a photoediting program was used to place rafting boats (a standard rafting boat used in the Köprüçay River rafting area has a capacity of 10 people) as many as possible into the image. Eleven photographs, including a blank image (0 boat) were used; the number of boats per image was increased by two in each photograph (20 boats) (Figure 2).

Figure 2.

Digitally edited photographs of rafting activity in KNP.

A commercial rafting company in the region was preferred for the rafting activity in the study. Standard rafting equipment and guidance services were included in the service. A “verbal protocol,” which had been used in previous studies, was used to ensure the validity of the study (Manning, 2007). Detailed information about the activity was given to the participants, and they were asked if they completely understood the application. After this step, the reproduced images were shown to participants with a projector before they started the rafting activity. Each photograph was separately demonstrated for 20 seconds (Gibson et al., 2014), and participants were asked to make evaluations. After this visual application, individuals participated in rafting activities (3 hours) along an area of 11 km.

At the end of the activity, crowding perception was reassessed with the photographing method as practiced before the activity. After this step, face-to-face interviews were held with participants to determine how the recreational experience affected the perceived crowding of participants. The relevant question asked to participants was

Is there any change in your perception of crowding before and after the rafting experience? If so, why?

Each interview continued for ~5 to 8 minutes. The researchers recorded the interviews with a voice recorder; they were then transmitted to the computer for transcription (Figures 3 and 4).

Figure 3.

Process of the study (n = 32).

Figure 4.

Norm acceptability curve for encounters prepost rafting experience.

Analysis of Strategy

The data obtained from the study was analyzed with two different methods. Frequency distribution and means were used for summarizing data in visual-based method procedures (Manning, 2007). Meanwhile, the Friedman test, one of the nonparametric tests, was used to analyze the change in PAOT and acceptability rates. The Wilcoxon Signed-Rank test was used to compare pretest and posttest values. Also, the data obtained from the interview process was analyzed through the content analysis technique.

Results

Quantitative Reports

Measuring Perceived Crowding Pre- and Postrafting Experience

Individuals participating in rafting as a recreation activity were observed, and their crowding perceptions were analyzed. The change in their perception and the reasons behind this change were carefully evaluated.

It was determined that there was a change in participants’ PAOT acceptability rate before and after they experienced the activity. According to this finding, while participants had defined 6 to 8 boats as noncrowded and acceptable (0 points) before rafting activity (Photographs 4–5), their perception changed after the process, and the value increased to 10 boats (Photograph 6).

Meanwhile, it was determined that the change in norm curve before and after the experience significantly differ (Pretest: X² = 268.90; Posttest: X² = 133.71, p = .00). According to Wilcoxon Signed Rank test, pretest values indicate that the differences between photographs are meaningful: 1 to 2 (T = 171.0, p = .00, z = −3.82, r = −0.67), 2 to 3 (T = 219.5, p = .00, z = −2.55, r = −0.45), 3 to 4 (T = 201.0, p = .00, z = −3.08, r = −0.55), 4 to 5 (T = 245.0, p = .00, z = −3.30, r = −0.58), 5 to 6 (T = 210.0, p = .00, z = −4.02, r = −0.71), 6 to 7 (T = 177.0, p = .00, z = −3.36, r = −0.59), 7 to 8 (T = 129.0, p = .00, z = −3.37, r = −0.60), 8 to 9 (T = 136.0, p = .00, z = −3.70, r = −0.65), and 9 to 10 (T = 15.0, p = .03, z = −2.23, r = −0.40). According to Wilcoxon Signed Rank test, posttest values indicate that the differences between photographs are meaningful: 1 to 2 (T = 11.0, p = .01, z = −2.54, r = −0.44), 5 to 6 (T = 234.0, p = .01, z = −2.47, r = −0.44), 6 to 7 (T = 179.5, p = .02, z = −2.33, r = −0.41), 7 to 8 (T = 241.0, p = .00, z = −3.78, r = −0.67), 8 to 9 (T = 129.0, p = .01, z = −2.57, r = −0.45), and 9 to 10 (T = 45.0, p = .01, z = −2.72, r = −0.48) (Tables 1 and 2).

Table 1.

Summary of Means and Chi-Square Analyses of Acceptability Ratings for Pre-Test and Post-Test.

Number of boats	Photograph number	Acceptability rating			Photograph number	Acceptability rating
Number of boats	Photograph number	Mean	SD	Median	Photograph number	Mean	SD	Median
0	Pre 1	3.56	1.01	4.00	Post 1	0.44	3.53	0.00
2	Pre 2	2.50	1.72	3.00	Post 2	0.97	3.13	2.00
4	Pre 3	1.75	2.08	2.50	Post 3	1.03	2.38	1.00
6	Pre 4	0.94	2.59	1.00	Post 4	1.00	1.81	1.00
8	Pre 5	−0.34	2.55	0.00	Post 5	0.88	2.37	1.50
10	Pre 6	−1.34	2.19	−1.00	Post 6	0.03	2.69	0.00
12	Pre 7	−2.34	1.93	−3.00	Post 7	−0.53	2.91	−0.50
14	Pre 8	−3.16	1.05	−3.50	Post 8	−2.06	2.63	−3.50
16	Pre 9	−3.81	0.39	−4.00	Post 9	−2.91	1.96	−4.00
18	Pre 10	−3.97	0.18	−4.00	Post 10	−3.41	1.34	−4.00
20	Pre 11	−4.00	0.000	−4.00	Post 11	−3.47	1.34	−4.00
	χ²		268.90		χ²		133.71
	Df		10		df		10
	p		.000		p		.000

Table 2.

Wilcoxon Signed-Rank Test Results of Each Photographs in Pre-Test and Post-Test.

		N	Mean Rank	Sum of Ranks	z	p
Pre-Photo 1 - Post-Photo 1	Negative Ranks	19	11.61	220.50	−3.67	.00*
	Positive Ranks	2	5.25	10.50
	Ties	11
	Total	32
Pre-Photo 2 - Post-Photo 2	Negative Ranks	16	16.34	261.50	−2.19	.03*
	Positive Ranks	10	8.95	89.50
	Ties	6
	Total	32
Pre-Photo 3 - Post-Photo 3	Negative Ranks	17	13.35	227.00	−1.31	.12
	Positive Ranks	9	13.78	124.00
	Ties	6
	Total	32
Pre-Photo 4 - Post-Photo 4	Negative Ranks	14	17.14	240.00	−0.16	.88
	Positive Ranks	17	15.06	256.00
	Ties	1
	Total	32
Pre-Photo 5 - Post-Photo 5	Negative Ranks	8	10.56	84.50	−2.53	.01*
	Positive Ranks	19	15.45	293.50
	Ties	5
	Total	32
Pre-Photo 6 - Post-Photo 6	Negative Ranks	7	10.86	76.00	−2.34	.02*
	Positive Ranks	18	13.83	249.00
	Ties	7
	Total	32
Pre-Photo 7 - Post-Photo 7	Negative Ranks	5	6.80	34.00	−3.01	.00*
	Positive Ranks	17	12.88	219.00
	Ties	10
	Total	32
Pre-Photo 8 - Post-Photo 8	Negative Ranks	10	8.10	81.00	−1.75	.08
	Positive Ranks	13	15.00	195.00
	Ties	9
	Total	32
Pre-Photo 9 - Post-Photo 9	Negative Ranks	3	4.00	12.00	−2.38	.02*
	Positive Ranks	10	7.90	79.00
	Ties	19
	Total	32
Pre-Photo 10 - Post-Photo 10	Negative Ranks	1	2.50	2.50	−2.23	.03*
	Positive Ranks	7	4.79	33.50
	Ties	24
	Total	32
Pre-Photo 11 - Post-Photo 11	Negative Ranks	0	.00	.00	−2.12	.03*
	Positive Ranks	5	3.00	15.00
	Ties	27
	Total	32

Significant at p < .05.

Each photograph was separately compared before and after the activity to test the effect of experience on perceived crowding. Wilcoxon signed-rank test showed that the change in rafting experience is statistically significant regarding acceptability rate according to participants. 1 (T = 220.5, p = .00, z = −3.67, r = −0.65), 2 (T = 261.5, p = .03, z = −2.19, r = −0.39), 5 (T = 84.5, p = .01, z = −2.53, r = −0.45), 6 (T = 76.0, p = .02, z = −2.34, r = −0.41), 7 (T = 34.0, p = .00, z = −3.01, r = −0.53), 9 (T = 12.0, p = .02, z = −2.38, r = −0.42), 10 (T = 2.5, p = .03, z = −2.23, r = −0.40), and 11 (T = 0.00, p = .03, z = −2.12, r = −0.42 ).

Qualitative Reports

Interview

At the end of the interviewing process, it was determined that the crowding perceptions of 59.4% (n = 19) of participants changed due to their experience. A second question was asked to the participants to determine the reason behind this change and deeply understand the issue. One theme that caused participants to change their perception of crowding was found. All participants whose crowding perception changed after the experience (n = 19) stated that the factor of “enjoy” was the significant criterion. Examples of participants’ statements about the issue are presented below:

At first, I thought that I could take more pleasure from the activity if there were no other people on the river; however, I had more “enjoy” during the activity when I encountered people on the river and saw that it was crowded.

I had more “enjoy” when we had a water fight during rafting. For this reason, I believe it is “enjoy” when there is a certain amount of people on the river.

When I was filling out the form, I thought that we could clash with other boats on the river, and it would be disturbing. However, when we got in the boat, we threw water at one another and had “enjoy.” I saw that it was “enjoy” when it was crowded.

There might be problems if the river is crowded. There can be some people, but too many people might cause problems (risks). For instance, I started to think that there were too many people in the last few images. It is entertaining when there are a few people, but increasing the number of people might increase risks, and oars and boats might clash and sink.

Discussion

This study examined the change in crowd perception before and after the rafting activity. The possible reasons for this change with a quasi-experimental design. The study results show that different norm results can be obtained with the same participant group and method in repetitive practices. Thus, participation in rafting (pre- and postexperience) changed crowding perceptions. Before the rafting experience, participants perceived that 6 to 8 boats were not crowded and acceptable; after the action, crowd perceptions changed and increased to 10 boats. It has also been reported that after the rafting activity, the tolerance for crowding perceived out of the acceptable threshold becomes positive, especially when the side of the norm curve expressing acceptability becomes flat and approaches the minimum acceptable condition. This result may create a dilemma in norm determination studies. Determining the crowding norm is important to maintain the level of quality and visitor experiences in parks and outdoor recreation areas (Bacon et al., 2001). Through this method, park and protected area managers can conduct realistic predictions (Manning & Freimund, 2004) and use this data in their decision-making processes. The study’s findings lead to the hypothesis that other measurement factors, such as measurement time and measurement location, should also be considered while facilitating crowd measurements because various norm values were obtained using the same method and participant group.

Characteristics of the participants, people encountered, and situational or environmental variables affect the perceived crowding (Manning, 2011). Additionally, previous studies show that encounters with nonconflict-causing similar typologies can positively affect crowd perception (Vaske & Donnelly, 2002). In this context, the touristic research area and the similarity in visitor typologies in the region may have changed the perception of crowding found in this research. In addition, the number of expected visitors can also affect the perception of crowding. For instance, when people experience fewer visitors than expected, they will likely feel a low level of perceived crowding (Bingul, 2017; Jin et al., 2016). In this context, determining the number of people that area managers expect visitors to encounter in an area can provide more realistic data for creating crowd norms.

The change in the perception of crowding before and after the experience in the study may be related to the expectations and motivations of the participants. Although it is difficult to generalize the motivations of touristic rafting participants for participating in this activity (Pomfret & Bramwell, 2016), they are classified as thrill and risk (Buckley, 2012). Fluker and Turner (2000) stated that participants without previous rafting experience focus on white-water rafting by seeking a new experience and exploring adventure alternatives and are willing to take risks to achieve these goals, while participants with previous rafting experience are relaxed. They stated that they have realistic expectations and are interested in the side benefits of rafting, such as being with their friends in a natural environment. In this context, the expectations and motivations of the study participants before rafting may be related to excitement seeking and adventure. After rafting, it is thought that the participants’ expectations turn into factors, such as socializing and interacting with other visitors, due to the experience they have gained in the field. This change may have affected the participants’ perception of crowds and increased their tolerance toward crowds. In this context, it is recommended that norm studies must be conducted in parks or protected areas while considering the motivations of visitors to the area. Additionally, recreation managers should try comprehending visitor experiences and conducting suitable management solutions to current and anticipated experiences.

In the interviews conducted to understand this result, it was determined that the “enjoy” factor caused this change in the participants’ perception of crowds. Emotions, such as pleasure (Manning et al., 2017) and enjoy and anger (Stemmer et al., 2022), can affect the perception of crowds. Additionally, if the enjoyment of the experience is thought to depend on being surrounded by many people, as is the case for some entertainment events, the sort of activity can even turn crowding into something positive (Kim et al., 2016). This argument is supported by the study’s findings. According to the interviews, the participants’ positive emotional states due to their interactions with the people they encountered in the river changed their perceptions to crowd. Furthermore, managers must pay attention to visitors’ emotions and, if possible, develop practices that will increase positive emotions. In this way, visitors will be more tolerant of the crowd in the area.

Limitations and Future Directions

This quasi-experimental study reported differences in perceived crowding pre- and postrafting experiences of recreational rafters, but it is by no means that an exhaustive investigation of recreational experience affects perceived crowding owing to several limitations. This study did not measure personal characteristics, such as participants’ motivations and emotional states, and environmental characteristics, such as how many people they encountered in the river. It is recommended that future studies measure these features and correlate them with changes that may occur in crowd perception before and after the experience. Using convenience and random sampling also poses a risk of sample and response homogeneity; moreover, theoretically, including all respondents from the same social group limits the generalizability of the obtained results. Furthermore, this study was conducted in Turkish culture. Therefore, cultural differences may influence visitors’ crowding perceptions, and the perceived perceptions of crowding may differ from one culture to another. Therefore, future studies should include several participants from different cultural groups. Finally, previous studies mentioned that visual research methods have several potential measurement biases, such as the range-order effect (Gibson et al., 2014). For this reason, this study has a methodological limitation similar to that of previous studies.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) received no financial support for the research,authorship,and/or publication of this article.

ORCID iD

Güney Çetinkaya

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

Albayrak

(2016). The importance of nature-based tourism for Antalya [Conference session]. International Academic Conference on Management, Economics, Business and Marketing 111–116. Vienna, Czech Technical University.

Arnberger

(2012). Urban densification and recreational quality of public urban green spaces—A Viennese case study. Sustainability, 4(4), 703–720. https://doi.org/10.3390/su4040703

Arnberger

Brandenburg

(2007). Past on-site experience, crowding perceptions, and use displacement of visitor groups to a Peri-Urban National Park. Environmental Management, 40, 34–45. https://doi.org/10.1007/s00267-004-0355-8

Bacon

Manning

Johnson

Kamp

(2001). Norm stability: A longitudinal analysis of crowding and related norms in the wilderness of Denali National Park & Preserve. The George Wright Forum, 18(3), 62–71.

Bentz

Rodrigues

Dearden

Calado

Lopes

(2015). Crowding in marine environments: Divers and whale watchers in the Azores. Ocean & Coastal Management, 109, 77–85. https://doi.org/10.1016/j.ocecoaman.2015.03.001

Berg

B. L.

Lune

(2014). Qualitative research methods for Social Sciences. Pearson Education Limited.

Bingul

M. B.

(2017). Encounter, norms, crowding: An application of the normative theory and methods in Turkey [PhD dissertation]. Colorado, Department of Human Dimensions of Natural Resources.

Buckley

(2012). Rush as a key motivation in skilled adventure tourism: Resolving the risk recreation paradox. Tourism Management, 33(4), 961–970. https://doi.org/10.1016/j.tourman.2011.10.002

Budruk

Manning

(2003). Crowding related norms in outdoor recreation: U.S. versus international visitors. In Schuster

(Comp.) (Ed.), Proceedings of the 2002 Northeastern Recreation Research Symposium [Symposium]. Gen. Tech. Rep. NE-302. Newtown Square, PA, U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 216–221.

10.

Budruk

Schneider

I. E.

Andreck

K. L.

Virden

R. J.

(2002). Crowding and satisfaction among visitors to a built desert attraction. Journal of Park & Recreation Administration, 20(3), 1–17

11.

Budruk

Wilhem Stanis

S. A.

Schneider

I. E.

Heisey

J. J.

(2008). Crowding and experience-use history: A study of the moderating effect of place attachment among water-based recreationists. Environmental Management, 41, 528–537. https://doi.org/10.1007/s00267-007-9059-1

12.

Bullock

S. D.

Lawson

S. R.

(2008). Managing the “commons” on Cadillac Mountain: a stated choice analysis of Acadia National Park visitors' preferences. Leisure Sciences, 30(1), 71–86.

13.

Catlin

Jones

(2006). Evolution of the whale shark tourism market [Conference session]. 2nd Australian Wildlife Tourism Conference 13–15. Australia, Fremantle.

14.

Catlin

Jones

(2010). Whale shark tourism at Ningaloo Marine Park: A longitudinal study of wildlife tourism. Tourism Management, 31(3), 386–394. https://doi.org/10.1016/j.tourman.2009.04.004

15.

Cribbs

T. W.

Sharp

R. L.

Brownlee

M. T. J.

(2022). Evaluating the influence of photo order on park visitors’ perceptions of crowding at Buffalo National River. Leisure Sciences, 44(5), 634–652. https://doi:10.1080/01490400.2019.1655685

16.

Eder

Arnberger

(2012). The influence of place attachment and experience use history on perceived depreciative visitor behavior and crowding in an urban national park. Environmental management, 50, 566–580. https://doi.org/10.1007/s00267-012-9912-8

17.

Ellis

G. D.

Freeman

P. A.

Jamal

Jiang

(2019). A theory of structured experience. Annals of Leisure Research, 22(1), 97–118. https://doi.org/10.1080/11745398.2017.1312468

18.

Enseñat-Soberanis

Blanco-Gregory

Mondragón-Mejía

Simoes

Moreno-Acevedo

Ortega

(2020). Crowding standards and willingness to pay at cenotes (sinkholes)of the Yucatan Peninsula: A comparative analysis of local, national and international visitors. Journal of Ecotourism, 19(1), 1–22. https://doi.org/10.1080/14724049.2019.1619747

19.

Fefer

J. P.

Hallo

J. C.

Collins

R. H.

Baldwin

E. D.

Brownlee

M. T.

(2021). From displaced to misplaced: Exploring the experience of visitors who were “crowded out” of their recreation destination. Leisure Sciences, 46(1), 1–20. https://doi.org/10.1080/01490400.2021.1898497

20.

Fennell

D. A.

(2015). Ecotourism (4th ed.). Routledge.

21.

Fluker

M. R.

Turner

L. W.

(2000). Needs, motivations, and expectations of a commercial whitewater rafting experience. Journal of Travel Research, 38(4), 380–389. https://doi.org/10.1177/004728750003800406

22.

Folland

J. P.

Strachan

. (2012). Whitewater canoeing and rafting. In Mei-Dan

Carmmont

M. R.

(Eds.), Adventure and extreme sports injuries (pp. 113–141). Springer

23.

Freimund

W. A.

Vaske

J. J.

Donnelly

M. P.

Miller

T. A.

(2002). Using video surveys to assess dispersed backcountry visitors’ norms. Leisure Sciences, 24, 349–362. https://doi.org/0.1080/01490400290050790

24.

Gibson

A. W.

Newman

Lawson

Fristrup

Benfield

J. A.

Bell

P. A.

Nurse

G. A.

(2014). Photograph presentation order and range effects in visual-based outdoor recreation research. Leisure Sciences, 36(2), 183–205. https://doi.org/10.1080/01490400.2013.862886

25.

Hammitt

W. E.

Backlund

E. A.

Bixler

R. D.

(2004). Experience use history, place bonding, and resource substitution of trout anglers during recreation engagements. Journal of Leisure Research, 36(3), 356–378. https://doi.org/10.1080/00222216.2004.11950028

26.

Heberlein

T. A.

(2012). Navigating environmental attitudes. Oxford University Press.

27.

Horne

Mollborn

(2020). Norms: An integrated framework. Annual Review of Sociology, 46(4), 467–487. https://doi.org/10.1146/annurev-soc-121919054658

28.

Jackson

(1966). A conceptual and measurement model for norms and roles. Pacific Sociological Review, 9(1), 35–47. https://doi.org/10.2307/1388305

29.

Jin

Kavan

(2016). Factors influencing perceived crowding of tourists and sustainable tourism destination management. Sustainability, 8(10), 976. https://doi.org/10.3390/su8100976

30.

Job

Bittlingmaier

Mayer

von Ruschkowski

Woltering

(2021). Park–people relationships: The socioeconomic monitoring of national parks in Bavaria, Germany. Sustainability, 13(16), 8984. https://doi.org/10.3390/su13168984

31.

Kim

Lee

C. K.

Sirgy

M. J.

(2016). Examining the differential impact of human crowding versus spatial crowding on visitor satisfaction at a festival. Journal of Travel & Tourism Marketing, 33(3), 293–312. https://doi.org/10.1080/10548408.2015.1024914

32.

Krymkowski

D. H.

Manning

R. E.

Valliere

W. A.

(2009). Norm crystallization: Measurement and comparative analysis. Leisure Sciences, 31(5), 403–416.

33.

Kuentzel

W. F.

Heberlein

T. A.

McCollum

D. W.

(2022). Why do normative encounter standards change? The social evolution of recreational crowding. Journal of Leisure Research, 53(3), 357–376. https://doi.org/10.1080/00222216.2020.1811178

34.

Kuss

Graefe

Vaske

(1990). Visitor impact management: A review of research. National Parks and Conservation Association.

35.

Leujak

Ormond

R. F. G.

(2007). Visitor perceptions and the shifting social carrying capacity of South Sinai’s coral reefs. Environmental Management, 39(4), 472–489. https://doi.org/10.1007/s00267-006-0040-1Li

36.

Chen

Wang

Yang

Innes

J. L.

Ferretti-Gallon

Wang

(2021). The contribution of national parks to human health and well-being: Visitors’ perceived benefits of Wuyishan National Park. International Journal of Geoheritage and Parks, 9(1), 1–12. https://doi.org/10.1016/j.ijgeop.2020.12.004

37.

Lime

D. W.

McCool

S. F.

Galvin

D. P.

(1996). Trends in congestion and crowding at recreation sites [Conference session]. National Recreation Resource Planning Conference87–96. University of Minnesota.

38.

Manning

R. E.

(2007). Parks and carrying capacity commons without tragedy. Island Press.

39.

Manning

R. E.

(2011). Studies in outdoor recreation: Search and research for satisfaction. Oregon State University Press.

40.

Manning

R. E.

Anderson

L. E.

Pettengill

(2017). Managing outdoor recreation: Case studies in the national parks. CABI International.

41.

Manning

R. E.

Freidmund

W. A.

(2004). Use of visual methods to measure standards of quality for parks and outdoor recreation. Journal of Leisure Research, 36(4), 557–79. https://doi.org/10.1080/00222216.2004.11950036

42.

Manning

R. E.

Krymkowski

D. H.

(2010). Standards of quality for parks and protected areas: Applying normative theory and methods in U.S. National Parks. International Journal of Sociology, 40(3), 11–29. https://doi.org/10.2753/IJS0020-7659400301

43.

Manning

R. E.

Lawson

Newman

Laven

Valliere

(2002). Methodological issues in measuring crowding-related norms in outdoor recreation. Leisure Sciences, 24(3–4), 339–348. https://doi.org/10.1080/01490400290050781

44.

Manning

R. E.

Valliere

Minteer

Wang

Jacobi

(2000). Crowding in parks and outdoor recreation: A theoretical, empirical, and managerial analysis. Journal of Park & Recreation Administration, 18(4), 57–72.

45.

Milman

Tasci

A. D.

Wei

(2020). Crowded and popular: The two sides of the coin affecting theme-park experience, satisfaction, and loyalty. Journal of Destination Marketing & Management, 18, 100468. https://doi.org/10.1016/j.jdmm.2020.100468

46.

Newman

Marion

J. L.

Cahill

(2001). Integrating resource, social, and managerial indicators of quality into carrying capacity decision making. George Wright Forum, 18(3), 28–40.

47.

Nolan

J. M.

(2015). Using Jackson’s return potential model to explore the normativeness of recycling. Environment and Behavior, 47(8), 835–855. https://doi.org/10.1177/0013916514523778

48.

Oftedal

Kang

H. K.

Schneider

(2015). Perceptions and responses to conflict: Comparing men and women in recreational settings. Leisure Sciences, 37(1), 39–67. https://doi.org/10.1080/01490400.2014.935537

49.

Pearce

Dowling

(2019). Monitoring the quality of the visitor experience: An evolutionary journey. Journal of Outdoor Recreation and Tourism, 25, 87–90. https://doi.org/10.1016/j.jort.2017.12.002

50.

Pomfret

Bramwell

(2016). The characteristics and motivational decisions of outdoor adventure tourists: A review and analysis. Current Issues in Tourism, 19(14), 1447–1478. https://doi.org/10.1016/j.tourman.2011.10.002

51.

Sanz-Blas

Buzova

Schlesinger

(2019). The sustainability of cruise tourism onshore: The impact of crowding on visitors’ satisfaction. Sustainability, 11(6), 1510. https://doi.org/10.3390/su11061510

52.

Sayan

Krymkowski

D. H.

Manning

R. E.

Valliere

W. A.

Rovelstad

E. L.

(2013). Cultural influence on crowding norms in outdoor recreation: A comparative analysis of visitors to national parks in Turkey and the United States. Environmental Management, 52, 93–502. https://doi.org/10.1007/s00267-013-0076-y

53.

Schamel

Job

(2013). Crowding in Germany’s national parks: The case of the low mountain range Saxon Switzerland National Park. Journal on Protected Mountain Areas Research and Management, 5, 27–34.

54.

Seebunruang

Burns

R. C.

Arnberger

(2022). Is national park affinity related to visitors’ satisfaction with park service and recreation quality? A case study from a Thai Forest National Park. Forests, 13(5), 753. https://doi.org/10.3390/f13050753

55.

Sharp

R. L.

Sharp

J. A.

Miller

C. A.

(2015). An island in a sea of development: An examination of place attachment, activity type, and crowding in an urban national park. Visitor Studies, 18(2), 196–213. https://doi.org/10.1080/10645578.2015.1079101

56.

Shelby

Whittaker

(1990). Recreation values and instream flow needs on the Delores River [Paper presentation]. Paper Presented at the Third Conference on Society and Resource Management. Texas, College Station.

57.

Stemmer

Gjerald

Øgaard

(2022). Crowding, emotions, visitor satisfaction and loyalty in a managed visitor attraction. Leisure Sciences, 11(3), 470–489. https://doi.org/10.1080/01490400.2022.2028691

58.

Stewart

W. P.

Cole

D. N.

(2001). Number of encounters and experience quality in Grand Canyon Backcountry: Consistently negative and weak relationships. Journal of Leisure Research, 33(1), 106–120. https://doi.org/10.1080/00222216.2001.11949933

59.

Tanner

R. J.

Freimund

W. A.

Borrie

W. T.

Moisey

R. N.

(2008). A meta-study of the values of visitors to four protected areas in the western United States. Leisure Sciences, 30(5), 377–390. https://doi.org/10.1080/01490400802353026

60.

Tverijonaite

Ólafsdóttir

Thorsteinsson

(2018). Accessibility of protected areas and visitor behaviour: A case study from Iceland. Journal of Outdoor Recreation and Tourism, 24, 1–10. https://doi.org/10.1016/j.jort.2018.09.001

61.

Vaske

J. J.

Donnelly

M. P.

(2002). Generalizing the encounter-norm-crowding relationship. Leisure Sciences: An Interdisciplinary Journal, 24(3–4), 255–69. https://doi.org/10.1080/01490400290050718

62.

Vaske

J. J.

Shelby

B. M.

(2008). Crowding as a descriptive indicator and an evaluative standard: Results from 30 years of research. Leisure Sciences, 30(2), 111–126. https://doi.org/10.1080/01490400701881341

63.

Vaske

J. J.

Whittaker

(2004). Normative approaches to natural resources. In Manfredo

Vaske

J. J.

Bruyere

Field

Brown

(Eds.), Society and natural resources: A summary of knowledge (283–294). Modern Litho.

64.

Stanis

S. W.

Zhang

Groshong

Morgan

(2020). Impact of travel distance and experience use history on visitors’ climate friendly behavior and support for climate friendly management action. Journal of Sustainable Tourism, 29(6), 981–999. https://doi.org/10.1080/09669582.2020.1855435

65.

Yan

Zhou

(2020). Study on the influencing factors of tourists’ perception of crowding in Baotu Spring Scenic Spot. Advances in Economics, Business and Management Research, 116, 254–259. https://doi.org/10.2991/icesed-19.2020.47

66.

Zehrer

Raich

(2016). The impact of perceived crowding on customer satisfaction. Journal of Hospitality and Tourism Management, 29, 88–98. https://doi.org/10.1016/j.jhtm.2016.06.007

67.

Zhang

L. L.

Nian

Zhang

(2017). Tourists’ perceptions of crowding, attractiveness, and satisfaction: A second-order structural model. Asia Pacific Journal of Tourism Research, 22(12), 1250–1260. https://doi.org/10.1080/10941665.2017.1391305