National Extension Tourism (NET): 2021 Conf. Proceedings

The mission of the National Extension Tourism network (NET) is to integrate research, education and outreach within Cooperative Extension and Sea Grant to support sustainable tourism, thus contributing to the long-term economic development, environmental stewardship, and socio-cultural wellbeing of communities and regions. This publication documents the 2021 Conference Proceedings (theme: Navigating the Uncharted). It includes an overview of the U.S. recreation economy, COVID-19; results of a national agritourism survey; and case studies.

2021 Conference Proceedings Edited by Lisa Chase, Natalie Chin, and Xinyi Qian

Acknowledgements

This volume was edited by:

• Lisa Chase, University of Vermont Extension

• Natalie Chin, Wisconsin Sea Grant

• Xinyi Qian, University of Minnesota Tourism Center

Administrative support was provided by Northeast Regional Center for Rural Development employees Kim Boonie, Kristen Devlin, and Jason Entsminger. Publication design was provided by Retta Ritchie. Each submission went through a peer-review process prior to publication. We thank the reviewers for their service. NET receives administrative support from the Regional Rural Development Centers, who in turn receive core funding from the USDA National Institute of Food and Agriculture (NIFA). Additional support was provided by New Technologies for Agriculture Extension grant no. 2020-41595-30123 from USDA NIFA. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the USDA or other funders.

Cover image credit: UGA Marine Extension and Georgia Sea Grant.

© Extension Foundation Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Published by Extension Foundation. Citations for this publication may be made using the following: Chase, Lisa, Natalie Chin, and Xinyi Qian (Eds.) (2022). National Extension Tourism 2021 Conference Proceedings (1st ed). Kansas City: Extension Foundation, September 23, 2022. ISBN: 978-1-955687-21-8

2021 NET Conference Proceedings

Introduction The mission of the National Extension Tourism network (NET) is to integrate research, education and outreach within Cooperative Extension and Sea Grant to support sustainable tourism, thus contributing to the long-term economic development, environmental stewardship, and socio-cultural wellbeing of communities and regions. NET was formed in 1994, with the first conference taking place in 1995. NET holds biennial conferences that move to different regions of the US. The 2021 NET Conference took place in Savannah, GA and online November 7-10. Since our network last met in 2019, our tourism communities have faced immense challenges from natural disasters and social unrest to an ongoing global pandemic. How we as tourism professionals have responded and adapted to these changes also continues to evolve. The NET 2021 conference theme of “Navigating the Uncharted” reflected on these transformations and catalyzed future extension programming that serves our stakeholders’ needs. To increase access to the impactful work presented at the conference, we are publishing the NET 2021 conference proceedings. The intended audiences for the proceedings include Extension faculty and staff, researchers, tourism professionals, and practitioners who can benefit from the wide array of applied research and outreach programs presented in the proceedings. The second audience includes faculty and students in tourism and outdoor recreation related academic programs who can benefit from having access to current applied research and programs that highlight how Extension and partners help address opportunities, issues and trends in tourism and outdoor recreation. The proceedings will be shared widely via the National Extension Tourism website as an open source publication for faculty, students and practitioners. This proceedings document contains eight submissions from the 2021 NET Conference, which we have grouped into the three categories of: data, training, and marketing. Goetz et al., Qian, and Schmidt et al. shared recent data about the state of the tourism industry in the U.S. Phillips, Burkhart-Kriesel, and Leeds and Barrett provided examples of cutting-edge training programs from across the country. Finally, Stewart, Higgins and Sterling detailed a few examples of marketing programs. We hope these papers will inspire you in your work supporting tourism as it continues to recover and evolve towards resilience and regeneration.

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Table of Contents

The U.S. Recreation Economy: Data, COVID-19, and Implications for Extension ......................................................................................................................... 6 Intro/background............................................................................................................................................................ 6 Methods ................................................................................................................................................................................. 6 Findings.................................................................................................................................................................................. 7 References...........................................................................................................................................................................12 Agritourism Successes and Challenges: Results from a National Survey of Farms and Ranches Open to Visitors ..................................................................... 13 Introduction and Background.............................................................................................................................13 Methods ................................................................................................................................................................................13 Findings................................................................................................................................................................................ 14 Discussion and Applications .................................................................................................................................17 Acknowledgments....................................................................................................................................................... 18 References.......................................................................................................................................................................... 18 Irish Fair of Minnesota Attendee Profile: What we learned from four waves of panel-level longitudinal data in 11 years ............................................20 Introduction ..................................................................................................................................................................... 20 Methods .............................................................................................................................................................................. 20 Findings ................................................................................................................................................................................. 21 Discussion .......................................................................................................................................................................... 24 References..........................................................................................................................................................................26 Guide & Outfitter Recognized Professional – (GORP) Professional Educational Program ................................................................................................. 27 Abstract ................................................................................................................................................................................27 Background...................................................................................................................................................................... 28 Project Description: .................................................................................................................................................... 28 We Serve! Bridging the Culture Gap with Training .......................................... 33 Research linkages ......................................................................................................................................................... 33 Program Context and Objectives.....................................................................................................................35 Program Development ............................................................................................................................................36 Reflections and Lessons Learned .....................................................................................................................37 References......................................................................................................................................................................... 38 Developing Awesome Customer Service for Agritourism Businesses .......39 Introduction ......................................................................................................................................................................39 Implementing a System for Customer Service .....................................................................................39

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Conclusion......................................................................................................................................................................... 42 References......................................................................................................................................................................... 43 Extension's Role in Expanding & Marketing a Scenic Byway ....................... 44 Program/project description and background ....................................................................................44 Objectives of program/project .......................................................................................................................... 45 Extension/research methods used ................................................................................................................ 45 Results of the program/project......................................................................................................................... 45 Strategies used to evaluate the program/project .............................................................................. 45 Conclusions/lessons learned ............................................................................................................................... 45 Introduction ..................................................................................................................................................................... 46 Byway Designation..................................................................................................................................................... 46 Why a Scenic Byway? National Travel Research ................................................................................. 46 Sample Byway Designation Process (in Ohio) ...................................................................................... 47 Marketing a Byway ..................................................................................................................................................... 48 Next Steps.......................................................................................................................................................................... 49 References......................................................................................................................................................................... 49 Coastal Awareness and Responsible Ecotourism: Building Community to Support Shorebird Conservation ............................................................................. 51 Introduction .......................................................................................................................................................................51 Methods ...............................................................................................................................................................................52 Findings............................................................................................................................................................................... 54 Discussion ...........................................................................................................................................................................57 References......................................................................................................................................................................... 58

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The U.S. Recreation Economy: Data, COVID-19, and Implications for Extension Stephan J. Goetz , Northeast Regional Center for Rural Development, Penn State University, sjg16@psu.edu Luyi Han , Northeast Regional Center for Rural Development, Penn State University, lkh5474@psu.edu Daniel Eades , West Virginia University, daniel.eades@mail.wvu.edu Jason Entsminger , Northeast Regional Center for Rural Development, Penn State University, jentsminger@psu.edu Doug Arbogast , West Virginia University, douglas.arbogast@mail.wvu.edu

INTRO/BACKGROUND

The breadth, depth, and speed of the economic collapse associated with the COVID-19 pandemic was unprecedented in economic history. No sector was hit harder than Leisure and Hospitality, which accounts for the economic core of tourism and recreation-based activity. Only recently has employment in this sector begun to show signs of recovery toward pre-pandemic levels. Here we document the importance of the Leisure and Hospitality sector to the economy and identify impacts from the pandemic and recovery, at both state and local (county) levels. Selected implications for Extension Services programming by Land- and Sea-Grant institutions are highlighted.

METHODS

We use secondary public data from federal sources including the Bureau of Economic Analysis’ Outdoor Recreation Satellite Account and Bureau of Labor Statistics Quarterly Census of Employment and Wages program, and descriptive analysis to document how COVID-19 affected U.S. states and counties in terms of the tourism and recreation employment and wages. Data are presented in geographic terms using maps with jurisdictional boundaries. These include calculations of the share of employment in the Leisure and Hospitality sector and changes between 2019 (pre-pandemic) and 2020 (pandemic height) in the 3 rd Quarter, when seasonal employment in tourism and recreation are typically at their largest. The World Health Organization declared COVID-19 a pandemic at the end of the 1 st Quarter of 2020, on March 11 th .

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FINDINGS

Importance of recreation to state economies

Newly compiled data by the U.S. Commerce Department’s Bureau of Economic Analysis show that (Fig.1), in the year preceding the COVID-19 pandemic’s onset, the outdoor recreation sector contributed on average 2.1 percent of state GDP in 2019, or $459.8 billion (U.S. Bureau of Economic Analysis, 2019). The highest shares at the state level are found in the intermountain West, upper New England (especially Vermont, with 5.2%), and Florida. In general, these states also are areas with high levels of natural amenities (U.S. Department of Agriculture, Economic Research Service, 2019). Despite the importance of the sector to many rural economies, only a few Extension services offer significant outreach programming (see Arbogast et al. 2022). Figure 1 State Outdoor Recreation Value Added as a Percent of State GDP, 2019

Source: Retrieved from U.S. Bureau of Economic Analysis at: https://www.bea.gov/news/2020/outdoor- recreation-satellite-account-us-and-states-2019, Updated state-level data are available at: https://www.bea.gov/data/special-topics/outdoor-recreation; https://www.bea.gov/news/2021/outdoor- recreation-satellite-account-us-and-states-2020

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Covid state-level impact, by major sector

In 2020, the first year of the pandemic, outdoor recreation’s share of GDP shrank to 1.8 percent ($374.3 billion), underscoring that the sector was among the hardest hit. Data from the Bureau of Labor Statistics (BLS) summarized in Figure 2 show the employment impacts of COVID-19 closures for key sectors on a monthly basis. These data are indexed to July 2019, the height of the tourism and recreation season pre-pandemic. Leisure and Hospitality sector employment collapsed in the first month of the pandemic (March 2020), declining by more than 50%, because of shutdowns and social distancing requirements. In comparison, employment in the other major sectors shown fell by a quarter or less. As recently as September 2021, Leisure and Hospitality employment had not returned to pre-pandemic levels, although there was a rebound to roughly 90% over the two-year period. At the time of publication, data is not available for the end of 2021, which saw a resurgence

of COVID-19 cases as the Delta and Omicron variants circulated. Figure 2 Monthly Employment by Sector, July 2019 = 100

Sources: Bureau of Labor Statistics based on authors’ own calculations.

For other sectors and state level updates, as well as for county-level overall employment and different income ranges, see the website (https://tracktherecovery.org). There are significant differences by state in these patterns, and data are not available for some states for statistical reasons.

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Impact at county level – for extension (rural areas)

County-level data from the Quarterly Census of Employment and Wages (Bureau of Labor Statistics, 2019) show the local impacts of tourism and recreation via the share of total employment attributable to the sector. Employment in the sector pre-pandemic varies significantly across jurisdictions (Fig. 3). However, in several counties Leisure and Hospitality employment is an important source of community livelihoods. Communities with pronounced dependence on this sector include the recreation hubs of the Sierra Nevada and the Rocky, lower Appalachians, and the Adirondack Mountains; gateway communities for attractions such as Bryce Canyon, Zion, Grand Canyon and Roosevelt National Parks; tribal communities adjacent to National Forests in South Dakota, Nebraska and New Mexico; coastal areas along the Great Lakes in Minnesota and Michigan; and border communities along the Big Bend of the Rio Grande in Texas. This data represents the baseline for the analysis that follows. Figure 3 Share of Leisure and Hospitality in Total Employment, 2019 Q3

Source: Qu arterly Census of Employment and Wages (QCEW) based on authors’ own calculations. The share is calculated as L&H employment in 2019 Q3 divided by 2019 Q3 total employment in percentage. Missing data is due to non-disclosed counties. Comparison of the data from 2019 to that of 2020 shows dramatic differences across counties in terms of employment change, with large metropolitan areas generally experiencing significant reductions (Fig. 4). In contrast, many rural, remote, and isolated counties, with lower population densities, experienced significant increases. Underlying these trends is the general desire to socially distance during the pandemic, when tourism activity shifted

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from areas of high population and visit density to those of lower density. This continues to represent an opportunity for rural areas and those with attractions less frequented prior to the pandemic. It also poses challenges, as many communities in the South, Midwest, and Mountain West experienced booms in tourism and recreation employment share (counties shaded in blue). Figure 4 Leisure and Hospitality Employment Change, 2019Q3 - 2020Q3

Sources: Quarterly Census of Employment and Wages (QCEW) based on authors’ own calculations. The change in percentage is leisure and hospitality employment in 2020 Q3 minus 2019 Q3 divided by 2019 Q3 L&H employment. Missing data is due to non-disclosed counties. Focusing next on wage changes during the pandemic, Fig. 5 shows that wages rose in some rural communities, starting arguably from a lower base, while they fell in most counties. Declines include many rural counties and metro areas. Even as growth in the number of persons employed represented a boost to local incomes, it appears from the maps that such increases in share of total employment were not consistently associated with higher pay within the sector. Comparisons cannot yet be made to 2021’s 3 rd Quarter, which has been characterized by persistent labor shortages (especially in the Leisure and Hospitality sector) and increasing inflation, which are typically associated with upward pressure on wages. Updates when data become available will be important next steps beyond this publication.

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Figure 5 Leisure and Hospitality Wage Change, 2019Q3 - 2020Q3

Sources: Quarterly Census of Employment and Wages (QCEW) based on authors’ own calculations. The change in percentage is leisure and hospitality average weekly wage in 2020 Q3 minus 2019 Q3 divided by 2019 Q3 L&H average weekly wage. Missing data is due to non-disclosed counties. Discussion Even as the COVID-19 pandemic caused considerable economic difficulty nationwide, stark differences can be seen across the nation, with some counties benefiting from the shift in recreational activity away from higher density communities. In addition, anecdotal evidence and popular media articles (Guilford, 2020; Pohle, 2021) reveal the growing attraction of lower density, rural places. The challenge for Extension is, first, to appreciate the important role of this trend and the recreational sector more generally and, second, to help communities to take advantage of the increased demand for rural spaces while ensuring benefits are more widely distributed. With shifts in demand for tourism and hospitality industry employment, programming that prepares workforce participants and business owners may need to be re-distributed or expanded within a state. Efforts to engage community leaders in planning and destination development may also be required, including efforts to address housing supply, infrastructure limitations, and overuse in those communities experiencing new growth. Local Extension professionals may face new demand for such programming, and may require additional resources from their campuses, such as funding, connections with new research specialists, and expanded partnerships with industry. In states that have not yet invested in tourism and recreation programming, Extension service professionals may need to actively network with colleagues outside the state to build new expertise to serve their local

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stakeholders. Entities like NET and the USDA NIFA Regional Rural Development Centers will be critical to facilitate these relationships and knowledge sharing. Similarly, funding opportunities like HATCH and AFRI, which recognize the need for integrated programing to address challenges should be pursued to encourage knowledge sharing and cross-state collaborative research and outreach programing. Keywords: Community and regional development; COVID-19; Extension; Recreation; Tourism

REFERENCES

Arbogast, D., Eades, D., Goetz, S., & Pan, Y. (Forthcoming, Spring 2022). Extension and Tourism: Responding to the Changing Needs of Society and New Opportunities. Journal of Extension. Bureau of Labor Statistics. (2019). Quarterly Census of Employment and Wages. [2019 Q3 Employment]. Retrieved from http://data.bls.gov Guilford, G. (2020, August 28). For a few destinations, tourism is doing better than ever. The Wall Street Journal. https://www.wsj.com/articles/for-a-few- destinations-tourism-is-doing-better-than-ever-11598637526 Highfill, T., Franks, C, & Georgi, P.S. (2018). Outdoor Recreation Satellite Account, Updated Statistics. U.S. Department of Commerce, Bureau of Economic Analysis. Retrieved from https://apps.bea.gov/scb/2018/09- september/0918-outdoor-recreation.htm Pohle, A. (2021, September 23). Crowded national parks have turned to reservations. Some are considering keeping them. The Wall Street Journal. https://www.wsj.com/articles/national-parks-reservations-glacier-rocky- mountain-11632332568 U.S. Bureau of Economic Analysis. (2019). Value Added by Industry as a Percentage of Gross Domestic Product. Retrieved from https://www.bea.gov/news/2020/outdoor-recreation-satellite-account-us- and-states-2019 U.S. Department of Agriculture, Economic Research Service. (2019). Natural amenities scale. Retrieved from https://www.ers.usda.gov/data- products/natural-amenities-scale.aspx

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Agritourism Successes and Challenges: Results from a National Survey of Farms and Ranches Open to Visitors Claudia Schmidt , Pennsylvania State University, cschmidt@psu.edu Lisa Chase , University of Vermont, Lisa.Chase@uvm.edu Dave Lamie , Clemson University, dlamie@clemson.edu Lori Dickes , Clemson University, LORID@clemson.edu Chadley Hollas , University of Vermont, https://chadleyhollas.com/contact- me/

INTRODUCTION AND BACKGROUND

Agritourism – welcoming visitors on farms, ranches, and vineyards – is an important diversification strategy that can benefit farm families, drive rural economic growth, and leverage the tourism industry in rural areas (Thilmany et al., 2019; Barbieri, 2013). According to Chase et al.'s (2018) conceptual framework, agritourism activities fall into five overlapping categories: education, hospitality, outdoor recreation, entertainment, and direct sales of agricultural products. The core of agritourism is on-farm experiences and product sales deeply connected to agriculture. Peripheral activities that are sometimes defined as agritourism and sometimes not, include off-farm experiences and direct sales as well as on-farm experiences that are not connected to agriculture. Most practitioners and researchers seem to agree on the definitional core of agritourism, but the peripheral activities can lead to disagreement and controversy in agritourism research (Lamie, et al. 2021) and in regulating agritourism activities at the State and local government levels. Along with agreement on the definition of agritourism, a better understanding is needed of factors contributing to agritourism operators' successes and challenges. To that end, a multi-state team of collaborating Extension colleagues recently conducted applied research to benefit agritourism operators and their communities.

METHODS

Beginning with interpretive inquiry, the researchers conducted 23 semi- structured interviews with farmers and ranchers from Vermont, California, Oregon, West Virginia, and Minnesota in the spring of 2019. These states were

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selected because of their substantial interest in agritourism and geographic variability. The interview subjects in a state were selected to maximize the range of variation (Lindlof & Taylor, 2011) within the study focus of farms or ranches classified as small or medium by USDA standards. A variety of farm products as well as on-farm experiences were represented in the sample, as was race, gender and experience working in agritourism. They analyzed those data to identify themes that were then used to develop an online survey instrument. The findings from the qualitative analysis of the interviews were combined with questions drawn from previously developed agritourism surveys used in published research (e.g. Schilling et al., 2012). The online survey was programmed in Qualtrics and sent to agritourism operators across the United States between November 2019 and February 2020. The project team used national and local networks and databases to distribute the survey to agricultural producers. The survey's first question served as a screening question and limited responses to farm, ranches, vineyards, aquaculture, and other agricultural production facilities that are open to visitors. Thus, off-farm experiences and sales (e.g., farmers markets) were not included. The timing was such that survey responses were completed prior to the start of the COVID-19 pandemic, providing baseline data on the state of agritourism before the pandemic.

FINDINGS

The research team received 1,834 usable responses to the online survey, with at least one respondent from each of the 50 states. The average age of respondents was 55 years old and over half of the respondents identified as female. Most respondents (7 out of 10) had a college degree or higher, and a little more than half had more than ten years of agritourism experience. About 50 percent of responses came from operators with less than 100 acres of land. The median farm size of respondents was 60 acres. Most farms operated 50 miles or more from a city of at least 50,000 people. Breaking down the responses by region, 29 percent came from the South, 26 percent from the West, 24 percent from the Northeast, and 21 percent from the Midwest. All regions reported offering crops, livestock, and value-added products, to varying degrees. Agritourism operations in the Northeast had the most crops (67 percent of respondents), the Southern operations had the most livestock (48 percent of respondents), and the Northeast and West led with the most value-added product offerings, at 56 and 49 percent of respondents respectively (Figure 1).

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Figure 1. Product Offerings

Producers were asked which of the five categories of agritourism they offered. In all four regions, on-farm direct sales was by far the largest category, with 89 percent of respondents in the Northeast offering direct sales, 78 percent in the South, and 77 percent in the Midwest and West. Educational activities followed, being offered by 55 percent of respondents. Entertainment was offered by 48 percent, outdoor recreation by 27 percent, and accommodations/hospitality by 19 percent of respondents. As with the types of products, many respondents offered multiple options. In addition to firmographics, questions in the survey asked operators about their motivations for offering agritourism activities, challenges operating an agritourism business, and the type of support they receive to help develop their business. Overall, agritourism operators have a positive outlook, with almost 70% of respondents planning to expand their operation, either with more employees or capital investment. Almost 20% of respondents planned to hold steady, with less than 5% indicating they would reduce or close their operations. The top three support categories respondents rated as necessary for success were social media marketing and management, legal and liability information, and marketing plan development. When it comes to challenges, operators across the country felt that time management was their biggest challenge, followed by labor availability and concerns about liability issues (see Figure 2). While some of these challenges are faced by all agricultural producers, many agritourism operators noted that the regulations and taxation they experienced and the lack of available

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insurance (either due to cost or coverage for the activities offered) make agritourism a particularly difficult enterprise.

Figure 2. Top Ten Challenges Identified by Agritourism Operators

The project team conducted in-depth analyses, focusing on different aspects of the survey. Quella et al. (2020) conducted a qualitative analysis of the open- ended questions to investigate the motivations of farmers offering agritourism. The results show that non-monetary motivations (specifically community engagement and leadership) are important for farmers when they decide to start offering agritourism activities. Turning to monetary motivations, Hollas et al. (2021) examined the profitability of responding agritourism operations. The authors found that operators with more agritourism experience (measured in years) were more likely to be profitable with agritourism efforts. They also found that larger agritourism businesses (measured in revenue and acreage), and those that offer entertainment and/or on-farm direct sales had positive associations with profitability. Respondents that either identified as female and/or offered off-farm sales were less likely to be profitable. Wang et al. (2021) used a probit regression model to analyze the perceived accessibility of resources and support for agritourism operators across the four regions, with the Northeast region as the baseline. They found that agritourism liability (insurance) is an issue that all regions share as a common concern. However, some challenges are more region-specific. For example, e- connectivity is a major issue in the Southern region. This is problematic because operators rely on a stable internet connection for marketing

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purposes, online reservations, and to run credit card payments for purchases. The Western region was especially concerned about state and local regulations, as well as city and county zoning and permitting. Schmidt et al. (2021a) analyzed the role of women in agritourism entrepreneurship in the United States based on the survey results. Women in agritourism are foremost farmers, and investigating the impact of gender differences is important, as Fremstad and Paul (2020, p.124) point out that "Farming is one of the most unequal professions in the United States today". In 2017, 38% of all farm operations were operated by women (Schmidt et al.,2021b), and, as mentioned above, 58% of the agritourism survey respondents were women. However, similar to previous studies, results show that women in agritourism make significantly less profit than their male counterparts, and they are less likely to assess themselves as being successful at increasing farm revenue. This is a critical issue that would benefit from additional research and outreach. Summaries of survey results and links to publication are online at https://www.uvm.edu/vtrc/agritourism-survey .

DISCUSSION AND APPLICATIONS

The analysis of the national survey of agritourism operators showed that respondents are not driven solely by profit but that non-monetary goals play an important role as well. These findings are similar to other survey studies (Nickerson et al., 2001; Barbieri and Mshenga, 2008; Schilling et al., 2012). We also find that agritourism operators across the United States are not operating on a level playing field. As mentioned in the introduction, there is no uniform definition of agritourism available. Different definitions at the state and municipal levels, in addition to agritourism regulations impact producers' abilities and motivations to offer experiences on their farms. A current USDA NIFA project "Creating an Effective Support System for Small and Medium-Sized Farm Operators to Succeed in Agritourism," is focused on analyzing how these differences in the support system impact agritourism operators across the country. This project also explores Extension programming to help address these inequalities. The results of the survey reported in this article have already been applied to develop Extension programming in several states, including a Northeast multi-state project on agritourism safety and liability and a tool to help producers navigate regulations related to agritourism. These resources can be found online at https://www.uvm.edu/extension/vtagritourism . Although this project was limited to the US, agritourism is a global phenomenon and the survey is now being adapted for use in other countries.

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An international group, including researchers from the US multi-state team, have formed the International Research Network for Agritourism (IRENA) 1 . One of the group's goals is to analyze differences and commonalities across participating countries to share experiences and lessons learned. Through the expansion of this research internationally, we anticipate it will continue to have important implications for Extension programming into the future, especially as we learn new ways to support agritourism operators and their communities.

ACKNOWLEDGMENTS

This work is supported by the Critical Agriculture Research and Extension (CARE) grant no. VTN32556 and by the United States Department of Agriculture, National Institute of Food and Agriculture (NIFA) under project # 2020-68006-31683 Keywords: Agritourism, Direct-to-Consumer Sales, Survey, Extension

REFERENCES

Barbieri, C .(2013). "Assessing the sustainability of agritourism in the U.S.: A comparison between agritourism and other farm entrepreneurial ventures." Journal of Sustainable Tourism 21(2):252-270. Barbieri, C., & Mshenga, P. M. (2008). The role of the firm and owner characteristics on the performance of agritourism farms. Sociologia ruralis, 48(2), 166-183. Chase, L. C., Stewart, M., Schilling, B., Smith, B., & Walk, M. (2018). Agritourism: Toward a conceptual framework for industry analysis. Journal of Agriculture, Food Systems, and Community Development, 8(1), 13-19. Hollas, C. R., Chase, L., Conner, D., Dickes, L., Lamie, R. D., Schmidt, C., ... & Quella, L. (2021). Factors Related to Profitability of Agritourism in the United States: Results from a National Survey of Operators. Sustainability, 13(23), 13334. Lamie, R. D., Chase, L., Chiodo, E., Dickes, L., Flanigan, S., Schmidt, C., & Streifeneder, T. (2021). Agritourism around the globe: Definitions, authenticity, and potential controversy. Journal of Agriculture, Food Systems, and Community Development, 10(2), 1-5.

1 IRENA’s website: https://isleassociation.wixsite.com/sdnetwork/networks

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Lindlof, T. R., & Taylor, B. C. (2011). Sensemaking: Qualitative data analysis and interpretation. Qualitative communication research methods, 3(1), 241-281. Nickerson, N. P., Black, R. J., & McCool, S. F. (2001). Agritourism: Motivations behind farm/ranch business diversification. Journal of Travel research, 40(1), 19-26. Quella, L., Chase, L., Conner, D., Reynolds, T., Wang, W., & Singh-Knights, D. (2021). Visitors and values: A qualitative analysis of agritourism operator motivations across the US. Journal of Agriculture, Food Systems, and Community Development, 10(3), 1-15. Schilling, B. J., Sullivan, K. P., & Komar, S. J. (2012). Examining the economic benefits of agritourism: The case of New Jersey. Journal of Agriculture, Food Systems, and Community Development, 3(1), 199-214. Schmidt, C., Goetz, S. J., & Tian, Z. (2021b). Female farmers in the United States: Research needs and policy questions. Food Policy, 101, 102039. Schmidt, C., Moghadam, A., Chase, L., Dickes, L., Mcnarlin, O. and T. Arogunda. (2021a) The Role of Women in Agritourism Entrepreneurship, Results from a National Survey. Presentation at the American Agricultural Economics Association on August 3, 2021. Thilmany, D., R. Hill, M. Haefele, A. van Sandt, C. Thomas, M. Sullins and S. Low. 2019. "An Overview of Agricultural and Rural Outdoor Recreation Tourism in the United States: A Framework for Understanding Economic and Employment Dynamics." In S. Davidova, K. Thomson and A. Mishra, eds. Agricultural Policies and Rural Jobs. Wang, W., Hollas, C., Chase, L., Conner, D., and Kolodinsky, J. (2021). Challenges in Agritourism and Access to resources: A US regional analysis. Working Paper. University of Vermont.

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Irish Fair of Minnesota Attendee Profile: What we learned from four waves of panel-level longitudinal data in 11 years

Xinyi Qian , Director, University of Minnesota Tourism Center, qianx@umn.edu

INTRODUCTION

Festivals and events have a direct impact on residents who may develop a stronger sense of community, find more pride in local culture, and enjoy local entertainment (Hall, 1992; Nicholson & Pearce, 2001). One such event is the Irish Fair of Minnesota, which aims to provide attendees with a fun, authentically-Irish, family-friendly event. To assist marketing decisions, enhance the event itself, and maximize benefits to the community, the Irish Fair of Minnesota has continually profiled its attendees.

METHODS

Study setting

The Irish Fair of Minnesota takes place on the second weekend of August, from Friday afternoon through Sunday evening. The venue has been Harriet Island Regional Park in downtown Saint Paul since 2001. Activities offered at the Fair ranges from live music, Irish dancing, and a marketplace to cultural areas, Irish- themed children’s activities, and a sports area, among others. According to Fair organizers, the event attracted 75,000 to 100,000 attendees. From 2007 to 2017, the University of Minnesota Tourism Center contracted with the Irish Fair of Minnesota to profile its attendees for four times: 2007 (Schuweiler & Schneider, 2007), 2011 (Oftedal & Schneider, 2011), 2014 (Qian, 2014), and 2017 (Qian).

Questionnaire

For the first attendee profile in 2007, an onsite questionnaire was developed, based on other event attendee profiles that the Tourism Center had conducted and the needs of the Fair organizers. The same questions were asked in the questionnaires for the subsequent attendee profiles. Questionnaire sections included event participation, information sources (i.e., the places where attendees learned about the Irish Fair), enjoyable attributes

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of the Fair, main reasons to attend the Fair, group composition, expenditures, mode of transportation, and basic demographic information.

Data collection

For each attendee profile, a sampling plan was created with both spatial and time considerations to: (1) ensure coverage of various activities and areas throughout the Fair, and (2) reach a range of Fair attendees. A convenience sample was used with survey volunteers asking passing attendees to complete the questionnaire. University of Minnesota Tourism Center staff trained and coordinated volunteers who administered the questionnaire. Survey volunteers collected 395 usable responses in 2007, 532 in 2011, 475 in 2014, and 471 in 2017.

Data analysis

Completed questionnaires were entered, cleaned, and checked in SPSS, a statistical data analysis software. Analysis provided frequencies to describe the sample of Fair attendees and to provide descriptive information on variables of interest. Means, medians, and standard deviations were also provided where applicable. Comparison between the 2007, 2011, 2014, and 2017 profile results was conducted using chi-square tests to compare categorical variables and Analysis of Variance to compare means.

FINDINGS

Data from the 2007, 2011, 2014, and 2017 profiles were compared where applicable. Analysis revealed differences in select information sources and expenditures, average age, gender, income, and Fair experience. Differences among information sources included Irish community sources, traditional media, and online sources (Table 1). There was a steady and significant decrease in the percentage of respondents who used the Irish Gazette as an information source (  2 =7.51, p <0.05). In 2007, attendees were more likely to use newspaper (  2 =18.29, p <0.0005) and radio (  2 =18.82, p <0.0005), two traditional information sources, than in subsequent years. Respondents in 2017 were significantly more likely than those in earlier years to use Facebook as an information source (  2 =69.90, p <0.0005). Additionally, attendees in 2011 and 2014, compared to those in 2007 and 2017, were more likely to use “other” information sources (  2 =110.17, p <0.0005).

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TABLE 1: Comparison of 2007, 2011, 2014, and 2017 Irish Fair of Minnesota attendee information sources 2007 (%) 2011 (%) 2014 (%) 2017 (%) Statistics (n=395) (n=532) (n=475) (n=471) χ 2 Sig. Irish community Irish bar/restaurant 8.1 9.8 7.2 5.3 7.34 0.062 Irish Gazette NA 5.8 4.4 2.3 7.51 0.023 * Word of mouth NA 46.6 42.9 48.8 5.37 0.252 Traditional media Pioneer Press ad 9.9 8.5 7.6 3.0 18.29 <0.0005 ** TV 11.9 8.3 11.8 12.3 5.53 0.137 Radio 12.2 6.8 5.9 5.1 18.82 <0.0005 ** Poster/flyer 4.3 5.3 3.8 3.4 2.45 0.485 Online Irish Fair website NA 11.3 12.2 11.7 0.21 0.900 Facebook NA 6.6 9.5 23.4 69.90 <0.0005 ** Other 11.6 25.6 27.6 5.5 110.17 <0.0005 ** * p ≤ .05, ** p ≤ .0005. Attendees across the four years differed in average age, generational composition, gender composition, and income (Table 2). The 2011 Irish Fair respondents were significantly younger than those in 2007 and 2014 ( F =5.31, p <0.005). Attendees’ average age was 43 years old in 2011 and 47 years old in both 2007 and 2014. However, given that respondents are within the same decade, the meaningfulness of this difference is in question. Generation-wise, there was a strong increase in the percentage of millennials (  2 =64.14, p <0.0005), as they came of age in the past decade. At the same time, there was a sizable decrease in the percentage of baby boomers. Members of Gen X, as well as the Greatest and Silent generations, showed steady percentages for attendance. In 2014 and 2017, more females answered the questionnaire than in 2007 and 2011 (  2 =9.79, p <0.05). Distribution of attendees in various income categories also differed across the four surveys (  2 =32.15, p <0.005). In 2017, the number of respondents in the less than $25,000 income category decreased, and the number in the $50,000-99,999 category increased. Meanwhile, the percentage of respondents with Irish heritage stayed at approximately two-thirds of the sample, and the sample was predominately White and non-Hispanic across all four surveys.

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TABLE 2: Comparison of 2007, 2011, 2014, and 2017 Irish Fair of Minnesota attendee demographics 2007 2011 2014 2017 Statistics Age F Sample size (n) 335 483 439 342 -- Mean (years) 47.13 a 43.38 ab 46.82 b 45.64 5.31** Generation χ 2 Sample size (n) 278 449 471 331 -- Millennial (1982-1999; %) 8.6 28.5 21.6 33.5 64.14*** Gen X (1965-1981; %) 37.8 30.5 34.8 33.5 Baby Boomer (1946-1964; %) 52.2 39.9 42.2 31.4 Greatest & Silent (1945 & earlier; %) 1.4 1.1 1.4 1.5 Gender Sample size (n) 389 501 449 425 -- Female (%) 56.3 53.1 62.6 59.8 9.79* Income Sample size (n) 329 427 405 377 -- Less than $25,000 (%) 8.8 15.2 12.6 8.2 32.15** $25,000-49,999 (%) 23.4 19.4 17.5 19.9 $50,000-99,999 (%) 35.3 36.5 34.1 40.1 $100,000-149,999 (%) 22.5 22.0 20.2 21.2 $150,000 or more (%) 10.0 6.8 15.6 10.6 Irish heritage Sample size (n) 386 515 467 471 -- Yes (%) 65.8 69.3 66.2 67.7 1.66 Ethnicity Sample size (n) 364 445 392 410 -- Non-Hispanic/Latino (%) 97.8 97.5 97.4 97.8 3.10 Race Sample size (n) 395 532 475 471 -- White (%) 89.6 89.1 88.2 91.5

Other 1 (%)

2.5 2.0

4.3

5.3 0.6 2.3

1.1

Black or African

1.3 1.3

0.8

American 1 (%) Asian 1 (%)

1.5 1.3

1.9 1.3

2.96

American Indian or Alaska Native 1 (%) 1 Native Hawaiian or other Pacific Islander 1 (%)

0.9

1.5

0.3

0.6

0.0

Note : Means with pairing subscripts within the row are significantly different at the p <0.0005 based on Bonferroni post hoc paired comparisons. 1 Response too low for statistical comparison. * p ≤ .05, ** p ≤ .005, * ** p ≤ .0005.

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Comparisons of attendees’ exper ience and expenditures yielded additional differences (Table 3). Respondents spent significantly fewer hours at the Irish Fair in 2017 compared with earlier years ( F =19.87, p <0.0005). In terms of expenditures, attendees spent more money on souvenirs in 2007 and 2017 than in 2014 ( F =3.08, p <0.05). Respondents in 2007 spent significantly less money on parking than in all subsequent years ( F =20.44, p <0.0005). TABLE 3: Comparison of 2007, 2011, 2014, and 2017 Irish Fair of Minnesota attendee experience and expenditures

2007

2011

2014

2017

Mean

Attendee experience

Hours spent at Irish Fair

376

5.45 ab

461 5.39 cd

429

5.87 ace

459

4.45 bde

19.87**

Satisfaction

522 4.33

470

4.24

466

4.41

2.57

Average expenditures ($)

Marketplace

NA NA

71.2

68.2

0.037

Other

51.1

24.9

32.6

71.8

1.91

Souvenirs

143

50.9 a

159 39.9

36.2 ab

53.9 b

3.08*

Food & Beverages

251

31.8

410 34.1

364

35.3

341

36.9

2.28

Parking

242

7.3 abc

287 9.7 a

284

9.6 b

236

10.6 c

20.44* *

Off-site food & beverage

37.6

26.6

35.1

0.63

Note : Means with pairing subscripts within the row are significantly different at the p <0.0005 based on Bonferroni post hoc paired comparisons. * p ≤ .05, * * p ≤ .0005.

DISCUSSION

In terms of respondents’ demographic characteristics, the 2017 Irish Fair attracted significantly more millennials and fewer baby boomers in 2017 than a decade ago. This is not surprising, as millennials have come of age in the past decade while baby boomers have aged. While the ethnic and racial composition of attendees remained unchanged across the four survey years, respondents’ household income levels changed. The percentage of respondents in the lowest and highest income ranges in 2017 was roughly

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