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Abstract

Recognizing, addressing, and adjusting for underlying assumptions is important for visitor use research and management in parks and protected areas. To identify assumptions in visitor use management research and applications, a Delphi approach was used to understand if and how assumptions appear in the visitor use management domain. We engaged eight visitor use experts in the United States over three questionnaire-based iterations, resulting in a list of 28 assumptions in visitor use management and associated research. Top-ranked assumptions were further explored to begin a conversation around how these assumptions may impact the research and management of visitor use in parks and protected areas. Overall, this study contributes to a growing body of knowledge regarding best practices related to visitor use management across public lands and other natural areas within the United States.

Plain Language Summary

Addressing and Bringing an Awareness to How Assumptions in Parks and Protected Areas Visitor use Management Research may Influence the Research Methodology

Why was this study done? We make assumptions in everyday life, and the same could be said for researchers. Particularly in the visitor use management field, where researchers collect data on park visitors to help inform management decisions, assumptions could potentially bleed into the methodology and approaches to said research, ultimately influencing data and management actions. However, little to no evidence exists of addressing such assumptions. What did the researchers do? Researchers surveyed professionals in the visitor use management field to ascertain whether or not such assumptions may exist and, if so, what perceived impact they may have on research methodology. What did the researchers find? Researchers found that many assumptions are perceived to exist amongst experts in the field, and that some of these assumptions are directly related to current management protocols within parks and protected areas. Therefore, further investigation into the possible impacts of these assumptions is warranted. What do the findings mean? Findings suggest that, along with the fact that many experts believe assumptions exist and may impact the research methodology, a greater awareness of these assumptions in the broader visitor use management field is needed. Often overlooked, these assumptions, and possibly others, can actually have a direct impact on research methodology and, ultimately, the recommendations that often influences management action., Therefore, a deeper understanding and recognition of this is needed.

Keywords

assumptions Delphi outdoor recreation parks and protected areas visitor use management

Introduction

In the United States, the number of people who visit parks and protected areas (PPAs) has increased over time, with additional increases resulting from the COVID-19 pandemic (Ferguson et al, 2023; Kupfer et al., 2021; Shartaj et al., 2022). At the same time, desires of those visitors and their impacts on both physical resources and experiences of others continually fluctuate (Leung et al., 2018). Therefore, it is essential for PPA managers to promote and encourage effective research on visitor use management (VUM), and to assess whether current best practices in VUM research and practice remain relevant and useful to ensure effective management actions.

Visitor use management refers broadly to the practice of managing a place and the people who visit it. The Interagency Visitor Use Management Council (IVUMC) (2016, p. 113), which guides most United States federal land management agencies on VUM, defines VUM as “the proactive and adaptive process for managing characteristics of visitor use and the natural and managerial setting using a variety of strategies and tools to achieve and maintain desired resource conditions and visitor experiences.”Eagles (2001, p. 67) argues VUM is a key to “the successful protection of the ecological, social, economic and cultural values” of parks and protected areas. With so many elements involved with the successful implementation of VUM methods, it is important to note that definitions of VUM likely embed assumptions.

Akin to beliefs, assumptions are ideas that individuals internalize as true without conclusive evidence. It is important to note that assumptions are to be used synonymously with preconceived notions, which are formed based on individual thoughts and experiences (Yanchar & Slife, 2004). However, the two are strongly related, as preconceived notions can inform assumptions. In this study, we look inward at the processes of VUM and seek to understand how certain assumptions may drive research and practice, and how assumptions impact the protection of the natural, cultural, and experiential resources in PPAs.

Development of VUM Research and Practice

To understand how assumptions might inform contemporary research and practice, it is important to contextualize them in the roots and development of the VUM field. As a broad concept, the study of outdoor recreation and its implications did not garner much attention until after World War II (Manning, 2022). Interest in visitor use management increased in the United States in the 1960’s as several major laws related to PPAs and outdoor recreation came into effect. For example, the National Environmental Policy Act (NEPA) created procedural requirements for managing natural resources when actions may affect the environment, including outdoor recreation and PPA resources, but historically there has not been a common approach to management goals (Cerveny et al., 2011).

As the focus on visitors to PPAs grew through policy and management, so too did the development of outdoor recreation and VUM research. Since the 1960’s, advances and studies in outdoor recreation and recreation ecology also increased in frequency (Monz et al., 2013; Morse et al, 2022). In the intervening half century, a large body of research concerning visitor use studies, visitor impacts in parks and protected areas, and visitor behavior and expectations has been developed (Manning, 2022). The field of VUM developed around questions of carrying capacity, and later developed to encompass a broader range of topics as questions related to not just how many visitors, but also what visitors do and think, emerged (Eagles, 2001). These early approaches to visitor use studies focused heavily on descriptives and generally lacked theoretical foundation (Manning, 2022).

Today, there are many theoretical approaches, such as: Social norm theory, cognitive dissonance, theory of planned behavior, cultural cognition, and collective impact (Stern, 2018). At the same time, innovations in research methods such as GPS visitor tracking (Peterson et al, 2021), photographic panels (Cribbs et al., 2019), surveys (Wolf et al., 2012), trail counters (D’Antonio & Monz, 2016), social media (Winder et al., 2025), and use of cell phone data (Whitney et al, 2023) have been developed. Contemporary VUM research has expanded to evaluate visitor characteristics such as recreation type (e.g., Wolf et al., 2018), visitor perceptions and behaviors (e.g., Roberts et al., 2021; Rossi et al., 2015), visitor travel patterns (Peterson et al, 2020) and values (e.g., van Riper & Kyle, 2014); in addition to understanding how visitor use impacts biophysical resources (Hammitt et al., 2015; Marion et al., 2016; Monz et al., 2013). Overall, these theories and methods focus largely on visitor behavior, attitudes, preferences, and impacts. However, it remains unclear whether and how researchers’ and practitioners’ underlying assumptions have informed development and continued use of theories, management frameworks, and research methods and analysis.

Assumptions in VUM

According to Burgess-Limerick et al. (1994), assumptions can be an inherent part of any research project, and it has been argued assumptions underlie the foundational research paradigms that drive research approaches. For example, selection of quantitative or qualitative methods may be influenced by researchers’ assumptions, which are often ignored (Adu et al, 2022; Hathaway, 1995). There is evidence that the historical development of scientific knowledge has been influenced by assumptions, in particular when researchers prefer theories that align with their beliefs (Currie, 1980). For example, assumptions about validity, causality, and applicability have been shown to permeate sport and exercise science research (Hagger & Chatzisarantis, 2009). This underscores the need for VUM researchers to understand how assumptions fit into this field of study.

While some historical references to assumptions in VUM exist, the dearth of recent literature underscores the value of this study and the gap it seeks to address. Beeco et al. (2013) note that spatial models of visitor population contain a vestigial assumption that individuals remain in the study location, derived from wildlife ecology where the methods were initially developed. Cahill et al. (2018) argue that, when using existing social science knowledge as an assumption that informs a project, the practitioner should be aware that changing conditions may render that assumption invalid. Hall directly addresses assumptions in the management of wilderness areas, calling them “unquestioned assumptions” (2000, p. 39), in a discussion about visitor use limits. Hall goes on to note there is an assumption that increased use levels negatively influence visitor experiences. However, Hall does not question how those assumptions ought to be addressed, nor whether assumptions are embedded in the research methods themselves.

Z. Miller (2022) describes eight axioms of visitor use management, which can be considered a type of assumption. These include ideas related to the nature of VUM as social, biophysical and managerial; objective-oriented axioms like VUM ought to maximize benefits to people while minimizing biophysical impacts and a range of opportunities is good. These assumptions appear to permeate the field of VUM, and it is important to systematically identify them. Rose et al. (2025) seem to agree and implore researchers and managers to “…expand our collective understanding of what kind of knowledge ‘counts’ in VUM research” (p. 616).

In VUM, the most common management frameworks involve processes that integrate both research and practice (e.g., Visitor Experience and Resource Protection, Limits of Acceptable Change, Recreation Opportunity Spectrum). The Interagency Visitor Use Management Framework (IVUMF) is particularly relevant at present, as it was developed in 2016 to be a guide for most federal park and protected area management agencies in the United States (Cahill et al., 2018). With this framework potentially guiding a significant amount of VUM for the foreseeable future, it is essential to understand whether and how assumptions have informed the practices embedded in the framework, such as using indicators of quality and associated thresholds to monitor conditions (IVUMC, 2016). In this study, we consider both assumptions that influence research methods and those that influence management actions, noting that they occur at different points in the VUM process as guided by management frameworks (Figure 1).

Figure 1.

Conceptual framework illustrating how manager and researcher assumptions might influence VUM.

Research Questions

Over the past half-century, the field of VUM has developed to the point of coalescing around common theories, methods, and management frameworks. However, there has been little discussion of how researchers’ and practitioners’ assumptions have become embedded in them. With evidence that assumptions influence research and management practices across social science disciplines, it is important to understand how they may shape VUM research and practice. This is particularly important because, as illustrated in Figure 1, the introduction of assumptions into any part of the VUM process has the potential to create a cascade effect on the remainder of the process. If unrecognized and left unchecked, the implementation of recommendations may not effectively meet management needs and objectives. Therefore, this study answers the following questions:

What assumptions exist in visitor use management research?

What are the implications of these assumptions to the broader application of visitor use management techniques?

Materials and Methods

To address these questions, we used a Delphi technique to generate knowledge and build consensus about assumptions in VUM among experts from across the United States. This approach was appropriate due to is consensus building capacity (Vallor et al, 2016), as well as its ability to reach and contact panel members regardless of their location.

Delphi Technique

The Delphi technique is a multistage approach that uses successive rounds of surveys, interviews, focus groups, or questionnaires “to obtain the most reliable consensus of opinion” (Dalkey & Helmer, 1963, p. 458). This consensus is then applied to the intended research objectives. This approach can be used to forecast conditions or a phenomenon (Vallor et al., 2016), and is particularly beneficial when dealing with issues where empirical evidence is limited (Barrios et al, 2021). This method uses a successive series of questions which build upon the results of the previous round. In each round, relevant experts contribute to and comment on documented information related to the research objectives (Vallor et al., 2016), with the number of rounds determined by the scope and nature of the research itself (Barrios et al, 2021; Kaynak et al., 1994). However, three iterations of questions are typically enough to reach consensus (Custer et al., 1999; Hsu & Sandford, 2007; Konopka et al, 2022).

This approach is anonymous, where only the researcher knows the identities of participants. In addition to ethical considerations, keeping participants unknown to each other avoids problems of group-bias or group-think (Murry & Hammons, 1995). Anonymity also removes the possibility of a dominating individual having disproportionate influence, which might occur in another group (Hsu & Sandford, 2007). Another advantage of the Delphi technique is that participants collectively generate knowledge without the need to coordinate times when they can all gather, reducing participant burdens and preventing potential logistical constraints to completing the study.

However, a few disadvantages must also be weighed. For one, this method does not engage a representative sample of participants, but rather strategically selects experts who represent the variation that is relevant for the study’s focus (Okoli & Pawlowski, 2004). Some have argued that this may generate results that do not represent the general population of the discipline (Yousuf, 2007). Additionally, there is a risk of participant burnout due to the repetitive nature of the method, resulting in lower response rates (Hsu & Sandford, 2007). Finally, critics have stated that a major weakness of this technique is its lack of an underlying theoretical framework or consistency in implementation (Habibi et al., 2014). While this criticism has clear downsides, it also results in a method that is flexible enough to be used across very narrow applications.

Overall, the advantages of the Delphi approach outweigh its potential limitations, especially considering its ability to generate consensus from knowledge that is fragmented across experts (Mead & Moseley, 2013) and we took several steps to mitigate these potential disadvantages. To the best of our ability, we followed recommendations to include relevant variation in the pool of participants (Okoli & Pawlowski, 2004) by engaging experts who varied across organizations and the amount of experience. To minimize burnout, we kept each survey round short (Sinickas, 2007) and streamlined the process using the online platform Qualtrics.

Participant Selection and Response Rate

The classical Delphi study utilizes a panel of experts that can provide a diverse background of experiences and knowledge. We used three initial criteria to select participants: (a) being involved, or having been involved, with VUM research and topics from an academic standpoint (i.e., worked in higher education), (b) a record of published VUM research articles and/or VUM related work accomplished, and (c) has had, or currently has, a record of teaching classes in higher education incorporating aspects of VUM. The first two criteria ensured that participants are experts in VUM, and the last one reflects their role in proliferating knowledge, and possible assumptions, about VUM. To help diversify the sample, participant selection was also based on ranges of career length within academia: entry-level (0–5 years), mid-level (6–15 years), and senior (16 years–retired).

The size of the expert panel in a Delphi study can vary, with the ideal number reliant on the nature and breadth of the study (Kaynak et al., 1994; Okoli & Pawlowski, 2004). Malterud et al. (2016) state that the number of participants to contact for qualitative research depends on the how broad the research objectives are, needed experience of sample, theoretical foundation, strength of dialogue amongst participants, and type of analysis used. We contacted 13 individuals for inclusion in the study. Five either declined, did not respond to invitations to participate, or failed to complete the first round of questions. As a result, our panel consisted of eight VUM experts from around the United States. Of these eight panelists, four were entry-level, three were mid-level, and one was senior. These participatory numbers are consistent with other Delphi studies (Ahmad & Wong, 2019; Chiţea et al, 2024; Fefer et al, 2016) and, given the niche discipline that visitor use management is across American universities, these results were deemed satisfactory.

Questionnaires

We collected data over three rounds using online questionnaires to solicit information from participants. After each round, responses were analyzed, reformatted, and anonymously redistributed to panel members in subsequent rounds (Dalkey & Helmer, 1963; Fefer et al., 2016; Ruschkowski et al., 2013; Vallor et al., 2016). We used Qualtrics software to create and distribute questionnaires, which improved the efficiency of analysis and allowed for the timely completion of all three rounds, which occurred between March and June 2020. All forms and letters were reviewed by a university Institutional Review Board, and any potential risk of harm was limited through voluntary participation, maintaining respondent anonymity, and avoiding sensitive topics. The minimal risks of participation were outweighed by the potential to advance knowledge and understanding of the subject. Informed consent was secured by presenting participants with information about the study’s purpose, potential risks, and data usage, as well as a statement clarifying that participation constituted consent.

Round One: Panelist Attributes and Initial List of Assumptions

The first round focused on evaluating the panel’s level of involvement in VUM research and identifying any assumptions that panelists thought to exist in VUM research practices. We included two qualifying questions (Have you been involved with VUM research at any point during your career? Are you currently involved with VUM research?) to ensure that all participants met the inclusion criteria. To gauge participants’ levels and types of engagement with VUM, we asked if their research methods included or considered current VUM management frameworks (and if so, which ones), what methods they use in their research, and what VUM-related courses they have taught. We also asked whether they believe there are assumptions in VUM research methods and applications, and if so, they were provided an open-ended response box to describe what they are. Finally, we solicited participant demographic and background information.

At the conclusion of this round, 28 assumptions were identified, which were grouped into four categories: (a) management assumptions, (b) experiential assumptions, (c) resource assumptions, and (d) methodological assumptions. These categories were developed based on literature that suggest all play a role in VUM research and human-environmental interactions (e.g., Cerveny et al., 2011; Z. D. Miller et al, 2019; Stern et al., 2009). Descriptive validity was maintained by keeping original wording and intent of responses (Vallor et al, 2016). Where appropriate, overlapping concepts were combined to minimize repetitive and/or similar assumptions.

Next, we introduced participants to the results from round one and guided the process of approaching consensus and narrowing down assumptions to those they believe are the most prevalent, reaching a consensus amongst the panel of experts. Using the Sum Total Matrix Table option in Qualtrics, participants were asked to rank the assumptions from round one by allocating from a total of 100 points to each based on the perceived prevalence in VUM-related research and practices. Additionally, participants were asked to provide comments on others’ anonymous responses and clarify their own statements, if desired. Mean scores were calculated based on the total sums, and assumptions were ranked from least to most evident in the eyes of the panel.

The mean, standard deviation, and range were calculated for each assumption. Inclusion criteria for Round Three included assumptions with a mean score of at least 10 (based on participants 100-point rankings) OR had a maximum point value of at least 35 assigned to it by any participant AND where participant comments placed particular emphasis on the assumption. In other words, assumptions with lower mean values were still chosen for Round Three if a significant number of points were allocated to that assumption, as well as participant comments stressing its importance. Exclusion of assumptions was also based on those assumptions with low mean values as well as low standard deviations. Low standard deviations, coupled with low mean values, imply agreement amongst participants that these assumptions are not as prevalent. As a result, 17 assumptions were obtained from Round Two to be included in Round Three, divided amongst the categories in the following manner:

Five out of seven original management assumptions

Five out of twelve original experiential assumptions

Two out of four original resource assumptions

Five out of five original methodological assumptions

For the sake of brevity, only those assumptions that made it through to the third round are included in these results.

Delphi Round Three

The remaining seventeen assumptions were again distributed to participants by way of a Sum Total Matrix Table in Qualtrics. Working to achieve consensus, respondents were asked to again rank the assumptions in the order in which they believe them to be more prevalent in VUM research. Additionally, participants were asked to respond to and share their own thoughts on the assumptions and new comments made by other members of the panel. This provided continued depth and context regarding the assumptions brought forward by the panel.

At the conclusion of Round Three, descriptive statistics were calculated, and assumptions were again ranked based on mean scores, resulting in a consensus amongst respondents regarding top-rated assumptions.

Results

The response rate for the first round of questions was 62%, while the second round had a 100% response rate, with all eight of the initial participants completing the second round of questions. The final round saw an 88% response rate, with only one panel expert who had completed the first two rounds failing to complete the final round of questions. Overall, the majority of provisions suggested by Malterud et al (2016) were met, as this study focused on a precise topic, participants were very learned in the specific discipline being addressed, and the nature of the Delphi study promoted dialogue between participants as well as allowed for effective analysis. Overall response rates were consistent with similar Delphi studies (e.g., Fefer et al, 2016; Kaynak et al, 1994; Ruschkowski et al, 2013; Vallor et al, 2016).

Delphi Round One: Participant Information and Assumptions

The first round of the Delphi process focused on inclusion criteria and the identification of assumptions. On average, participants had been involved with VUM research for 13.2 years with a maximum involvement of 21 years and a minimum of 6 years. Seven out of eight respondents (88%) were still involved in VUM research at the time of data collection, with only one not currently conducting research. Respondents were evenly split between male and female, with a median age of 41 years. At the time of data collection, 63% of respondents were Assistant Professors and were currently teaching, or had previously taught, classes related to visitor use management.

To gain insight into individual research practices amongst respondents, participants were asked what, if any, management frameworks they incorporated into their research, either currently or at some point in the past. The Interagency Visitor Use Management Framework (IVUMF), Visitor Experience and Resource Protection (VERP), and Recreation Opportunity Spectrum (ROS) were the top three frameworks mentioned. Others included Visitor Impact Monitoring (VIM), Carrying Capacity Assessment Process (C-CAP), and Limits of Acceptable Change (LAC) were also mentioned.

Participants were also asked about specific research tools and methods incorporated into their work. Surveys, both qualitative and quantitative, topped the list (100%), with photo panels and trail counters being the second most used methods (88%) by respondents. Other methods used included visitor observation, visitor employed photography/videography, Public Participation Geographic Information System (PPGIS), interviews, and social groups, among others.

All respondents stated that assumptions are inherently part of visitor use management and associated research. Respondents were then asked to share those assumptions. A total of 28 assumptions were initially identified by the panel and reformatted for subsequent Delphi rounds. From this list, themes were extracted and categorized into four groups applicable to the VUM field: methodological assumptions, experiential assumptions, resource assumptions, and management assumptions. Respondents in the subsequent round were then asked to view this breakdown and rank each assumption using a Sum Total Matrix Table.

Delphi Round Two: First Ranking of Assumptions and Comments

The response rate for the second round was 100%, with all eight participants who completed the first round also completing the second round. The focus of this round centered around the aforementioned assumptions and the ranking of those assumptions amongst the panelists. Furthermore, panelists were asked to comment on the assumptions, as this was the first time they were viewing responses from other panel members.

Management Assumptions

“Research influences management decisions” was the highest-ranking assumption in this category (m = 30). The assumptions “visitor capacity will solve all our VUM challenges” (26.88) and “parks and protected areas managers are different from visitors” (10.63) were the next highest rated.

Experiential Assumptions

“Visitors are motivated to achieve desired outcomes from a recreational experience while protecting the environment at the same time” was the top-rated assumption in this category, with a mean score of 17.5. This was followed by the generated assumption “visitor perceptions are formed around cognitive hierarchy” (m = 13.63) and the assumption “visitors can perceive and evaluate resource impacts (social or ecological)” (m = 10.63). Other top-rated assumptions focused on aspects of visitors following the Recreation Demand Hierarchy, the assumption that there is a strong relationship between the amount of visitor use, crowding, and conflict, and the assumption that crowdedness contributes to more negative experiences and displacement.

Resource Assumptions

Results from this first round of ranking resulted in the assumption “there is a clear relationship between use levels and associated impacts” being the highest ranked among panelists (m = 32.5). Closely followed were the assumptions that there is a “strong relationship between the amount of visitor use and resource impact” (30.63) and “a dichotomy exists between natural and cultural resources” (28.3). It should be noted that the two top-ranking assumptions related to use levels and resource impacts are essentially the same and something that was overlooked during the initial categorization process, something that was commented on by one of the respondents.

Methodological Assumptions

Means generated from the second round were based on the Sum Total Matrix Table, in which participants ranked the developed assumptions based on the level of which they believe the assumptions impact VUM research practices. In other words, the higher the mean, the more impact said assumption is believed to have. The assumption “indicators and thresholds measure social norms” was the top-rated assumption (m = 31.88) based on panelists' responses. This was followed by “visitor spatial-temporal behavior is driven by factors we can measure in VUM in predictable ways” (m = 25.00) and “behavioral intentions measure actual behavior” (m = 21.25). Perhaps no less important, the remaining responses generated highlight the variety of assumptions visitor use management experts believe play a role.

Panelist Comments

A number of comments made by participants highlighted a documented benefit of a Delphi Study. For example, as one participant stated:

Looking at the list now, I'm surprised there isn't anything about “complexity” in the management assumptions. I think that as researchers, we often assume that we are looking at a VUM question finite enough that it eliminates some of this complexity, but that is a huge assumption.

And, as another expert expressed:

We tend to assume protected area managers are different than [sic] visitors. VUM researchers tend to assume there is a dichotomy between natural and cultural resources. We assume data with low response rates continue to represent actual patterns. We assume research influences management decisions.

Delphi Round Three: Final Ranking of Assumptions and Comments

Response rate for the final round of this Delphi study was 88%, with seven out of the eight participants who responded in the second round participating in the third and final round. In this round, participants had now been exposed to all the assumptions, commented on them, and provided an initial ranking of said assumptions.

Utilizing the established inclusion/exclusion criteria highlighted in the methods, a total of 17 assumptions (from the original 28) were presented to the panel. These remaining assumptions coincided with the aforementioned categories in the following manner: 5 out of 8 management assumptions, 5 out of 12 experiential assumptions, 2 out of 4 resource assumptions, and 5 out of 5 methodological assumptions.

Management Assumptions

The assumption “research influences management decisions” remained the highest-ranking assumption in this category after the final round (m = 30.71). The assumptions “visitor capacity will solve all our VUM challenges” (27.86) and “parks and protected areas managers are different from visitors” (20.71) also remained the next highest ranked assumptions (Table 1).

Table 1.

Panel Rankings of Management Related Assumptions After Final Round of Delphi Process.

Assumption	Min		Max		Mean		Std Dev
Assumption	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3
Research influences management decisions.	10	0	65	50	30.00	30.71	18.32	14.07
Visitor capacity will solve all our VUM problems.	0	0	60	50	26.88	27.86	22.90	13.21
Parks and protected areas managers are different from visitors.	0	0	20	50	10.63	20.71	6.34	12.16
Increasing diversity in park use is desirous [sic] and won’t change management priorities.	0	0	35	50	8.13	15.00	12.23	9.42
Desired future conditions should mimic a single historic point in time.	0	0	40	30	8.13	5.71	12.73	21.21

Note. Mean values are based on participant allocation of 100 points each within each category.

Experiential Assumptions

The rankings of experiential assumptions did change, however, with “there is a strong relationship between the amount of visitor use, crowding, and conflict” being the highest ranked assumption (m = 25). “Visitors are motivated to achieve desired outcomes from a recreational experience while protecting the environment at the same time” remained highly rated with a mean score of 23.57. There was another change from the previous rankings with the third highest rated assumption now being the assumption “visitors act in a rational manner that follow the Recreation Demand Hierarchy” (Table 2).

Table 2.

Panel Rankings of Experiential Assumptions After Final Round of Delphi Process.

Assumption	Min		Max		Mean		Std Dev
Assumption	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3
Visitors are motivated to achieve desired outcomes from a recreational experience while protecting the environment at the same time.	0	5	30	45	17.50	23.57	9.35	14.07
Visitors act in a rational manner that follow the Recreation Demand Hierarchy.	0	0	35	40	13.63	20.17	14.39	13.21
Visitors can perceive and evaluate resource impacts (both social or ecological).	0	0	45	30	10.63	16.43	14.24	12.16
Visitor perceptions are formed around cognitive hierarchy.	0	0	30	30	10.50	14.29	10.81	9.42
There is a strong relationship between the amount of visitor use, crowding, and conflict	0	0	35	60	10.38	25.00	12.39	21.21

Note. Mean values are based on participant allocation of 100 points each within each category.

Resource Assumptions

Final rankings of resource assumptions found “strong relationship between amount of visitor use and resource impact” to be the highest ranked among participants (m = 52.86; Table 3). While this technically represented a change from the previous round, overall attitudes toward this assumption remained the same given the similarity of the previous top-rated assumption of “there is a clear relationship between use levels and associated impacts.”

Table 3.

Panel Rankings of Resource Related Assumptions After Final Round of Delphi Process.

Assumption	Min		Max		Mean		Std Dev
Assumption	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3
Strong relationship between amount of visitor use and resource impact.	0	10	50	100	30.63	52.86	17.93	26.57
A dichotomy exists between natural and cultural resources.	0	0	100	90	28.13	47.14	28.61	26.57

Note. Mean values are based on participant allocation of 100 points each within each category.

Methodological Assumptions

The assumption “indicators and thresholds measure social norms” remained the top-rated assumption (m = 35). There was also no change in subsequent rankings, with “visitor spatial-temporal behavior is driven by factors we can measure in VUM in predictable ways (m = 23.57) and “behavioral intentions measure actual behavior (m = 17.14) continuing to round out the top three rated assumptions (Table 4).

Table 4.

Panel Rankings of Methodological Assumptions After Final Round of Delphi Process.

Assumption	Min		Max		Mean		Std Dev
Assumption	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3	After Rd 2	After Rd 3
Indicators and thresholds measure social norms.	20	20	50	50	31.88	35	11.16	13.36
Visitor spatial-temporal behavior is driven by factors we can measure in VUM in predictable ways.	0	0	80	50	25.00	23.57	24.49	17.87
Behavioral intentions measures actual behavior.	0	0	50	50	21.25	17.14	15.56	14.85
Research is influenced by visitors not local communities.	0	0	30	30	12.86	12.14	10.30	10.64
Data with low response rates represent patterns.	0	0	35	40	10.63	12.14	13.10	15.08

Note. Mean values are based on participant allocation of 100 each within each category.

Panelist Comments

Comments continued to highlight the beneficial nature of this type of forum for sharing ideas. As one participant stated:

“I differ with other panelist [sic] in my belief that the rational actor is an assumption of VUM research that is not always true. It seems like other folks think that rational actor theories are well supported and applicable. But let’sthink about past use history: when we ask people how many days in an average week they visit a specific place, or how many days in a season they hike, or ski days in a year they likely aren’t doing calculations (rational) - they are likely using heuristics (shortcuts). That’s the opposite of rational decision making. We then calculate these scores and report them as objective metrics, albeit with confidence intervals, but nonetheless the assumption is that their scores aren’t a product of other unconscious.”

Another participant stated the following:

“That research influences management and specifically that visitor capacity is a silver bullet research/management vein are definitely the most prevalent assumptions of this list. While I'd hope it's true that our research influences management, there's a need to be creative about how we communicate with managers and expansive about areas we examine for addressing VUM challenges.”

Discussion

Overall, this Delphi survey methodology created a successful forum for experts in the visitor use management (VUM) field to come together, share what they believe to be assumptions present in the VUM field, comment on each other's assumptions and share their own thoughts and beliefs on those assumptions. This further highlights a key value of the Delphi technique in that it creates a collective forum for individuals to interact with one another, anonymously, and provides a richer context to the subject material (i.e., assumptions).

While relatively unused in the field of parks and protected area management and outdoor recreation in general (Fefer et al, 2016), the Delphi approach has a rich archive of application in other disciplines with its ability to bring experts together to reach a consensus on a particular subject. This approach was particularly beneficial in gathering information in a timely manner without having to coordinate individual or group meetings with every participant. This process yielded beneficial results in how to better understand prevalent assumptions that may impact VUM research and subsequent management actions within parks and protected areas.

This is particularly relevant to the application of the Interagency Visitor Use Management Framework (IVUMF) throughout United States public lands, a framework which is currently the systemized approach to visitor use management and will be for the foreseeable future. Given that one of the top assumptions was indicators and thresholds measure social norms, and given that the IVUMF relies on the use of indicators and thresholds to guide its management strategy, a more thorough understanding of how this assumption influences this process is essential. If there is more to understanding visitor use management related social norms than the application of indicators and thresholds, it is important those variables are not only recognized and understood but implemented in conjunction with components that comprise the IVUMF.

Similarly, the high-rated assumption of a strong relationship between the amount of visitor use and resource impact further highlights an opportunity to further investigate this correlation between levels of visitor use and potential impacts to natural resources. This has implications for the direct application of the IVUMF, as impacts to the natural resource may be used as a potential indicator, as well as to overall perceptions of parks and protected areas. For example, from whose perspective is this relationship being witnessed by: the visitor or the manager? As these two populations may have very different beliefs and sensitivities toward this association, it becomes important to discern what exactly this assumption means and how researchers may use that understanding, along with the understanding of other VUM related assumptions, to improve the overall research process. Furthermore, if this assumption of more use leading to more impacts is incorrect, researchers may recommend managers accommodate more use, which may go against current management objectives.

Kirkwood and Price (2013) put it bluntly; “Researchers’ beliefs and assumptions shape the research they undertake (p. 536).” While the overall prevalence of assumptions in VUM research requires its own study, this investigation made it abundantly clear that there is a myriad of assumptions that exist, regardless of whether there is consensus on just how prevalent they are. Even if there was no agreement at all concerning a given assumption, the fact that one expert believes it to be present has implications for how VUM research may transpire. The question is whether these assumptions have any significant impact on the result.

Furthermore, if disagreement does exist over certain assumptions—as was suggested by some of the comments—it raises an issue of solidarity and continuity within the VUM research field. It is true that many facets of VUM related research exist (e.g., wildlife impacts, social impacts, resource impacts) and each discipline has their respective goals and agendas. However, whether the focus is on cultural, ecological or social aspects, researchers are working to achieve the same objective: protection of the resource and sustainment of the recreation and visitor experience. Therefore, disagreement over the identified assumptions should not deter the advancement of VUM related research in its entirety, regardless of one’s specialty.

The breadth of field experience within the panel generated varied, yet beneficial, results. This span of experience, possibly along with the geographic differences and even types of projects these experts had been, or currently are, involved in may contribute to this variability. Despite this, and even before any kind of consensus was reached, there was agreement on the prevalence of the generated assumptions. This indicates that no matter what it is, there is some level of agreement among experts that suggests assumptions have been present in the VUM field.

While results are thought-provoking, further investigation would lend additional insight into specific levels of consensus amongst the panel members. This would add further depth to the role experts believe these assumptions play in VUM research and subsequent management decisions. Along with added benefits of more research panel participants (i.e., VUM experts), incorporating methods such as the Group Conformity Index (GCI) could be applied to better understand how participants observe group points of view, particularly as understanding how those levels of consensus are influenced by the Delphi process itself (Birko et al, 2015). There are also possible implications in how experience level may influence beliefs toward the prevalence of certain assumptions in VUM research, which would warrant further investigation. Lastly, we recognize that many of the assumptions uncovered share some overlap and possibly conflict with one another depending on the situation and context. Further investigation into just how these interactions might occur in the field would be another opportunity for future research surrounding the contextualization of these assumptions.

Conclusion

The goals of this study were to identify and highlight assumptions in visitor use management research. These assumptions were generated from a panel of self-identified VUM experts with over 50 years of combined experience in the field. Results satisfied the study objectives of highlighting inherent assumptions in VUM research. Additionally, this study continued to underscore the utility of the Delphi approach to gather useful information in an effective and timely manner. The ability to bring a pool of experts in the VUM field together in this way and generate this data further demonstrates how this approach could, and perhaps should, be used more frequently as in other disciplines.

As the urgency to produce effective results in parks and protected areas across the country rises along with increased visitation, it becomes even more critical to identify and understand underlying assumptions within the research process. If the IVUMF represents the current foundation of VUM planning and research for federal lands in the United States for the foreseeable future, it is critical we evaluate how effective the metrics used are. For instance, we uncovered assumptions that bring into question the implementation of frameworks based on indicators and thresholds. Therefore, it is important to understand how assumptions impact current and future VUM research methods and how this may be impacting the management of parks and protected areas across the country.

As visitation pressures mount and the need for responsive, evidence-based management grows, researchers and practitioners must work collaboratively to surface, question, and refine the assumptions that guide their work. In doing so, the VUM field can continue evolving toward more inclusive, transparent, and effective approaches to managing the complex relationships between people and protected places. This Delphi study was useful in bringing this conversation of research assumptions to light and additional studies would lend further credence to the role they play.

Footnotes

ORCID iD

Michael M. Brunson

Ethical Considerations

This study was reviewed by the Kansas State University Institutional Review Board, Proposal Number 10068, and deemed exempt under the criteria outlined in the Federal Policy for the Protection of Human Subjects, 45 CFR §46.101, paragraph b, category: 2, subsection: ii).

Consent to Participate

Informed consent was secured by presenting participants with information about the study's purpose and voluntary nature, potential risks, and data usage, as well as a statement clarifying that participation constituted consent.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

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

Data Availability Statement

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

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Addressing Assumptions in Visitor use Management Research: The Researcher’s Perspective

Abstract

Plain Language Summary

Keywords

Introduction

Development of VUM Research and Practice

Assumptions in VUM

Research Questions

Materials and Methods

Delphi Technique

Participant Selection and Response Rate

Questionnaires

Round One: Panelist Attributes and Initial List of Assumptions

Delphi Round Three

Results

Delphi Round One: Participant Information and Assumptions

Delphi Round Two: First Ranking of Assumptions and Comments

Management Assumptions

Experiential Assumptions

Resource Assumptions

Methodological Assumptions

Panelist Comments

Delphi Round Three: Final Ranking of Assumptions and Comments

Management Assumptions

Experiential Assumptions

Resource Assumptions

Methodological Assumptions

Panelist Comments

Discussion

Conclusion

Footnotes

ORCID iD

Ethical Considerations

Consent to Participate

Funding

Declaration of Conflicting Interests

Data Availability Statement

References