Showing 1 – 3 of 3 results.
Self-published
National Neighborhood Data Archive (NaNDA): Arts, Entertainment, and Leisure Establishments by Census Tract and ZCTA, United States, 1990-2022 (ICPSR 209163)
Released/updated on: 2026-07-16
Geographic coverage: Puerto Rico, United States
Time period: 1990-01-01--2022-12-31
This dataset contains measures of the count and density of arts, entertainment, and leisure establishments per United States Census Tract or ZIP Code Tabulation Area (ZCTA) from 1990 through 2022. Business establishment data were drawn from the National Establishment Time Series (NETS) database and geocoded to 2010 and 2020 Census tract and ZCTA boundaries. The dataset includes four files — Census Tract 2010, Census Tract 2020, ZCTA 2010, and ZCTA 2020 — each containing one observation per geographic unit per year across ten establishment categories including museums, theaters, amusement parks, movie theaters, zoos and gardens, gambling facilities, bowling alleys, hotels, casino hotels, and an aggregate arts and entertainment total.
Self-published
Traces of national culture on the websites of the best hotels as determined by TripAdvisor (ICPSR 209681)
Released/updated on: 2024-10-16
This study explores the intricate relationship between national culture and digital communication strategies in the tourism and hospitality industry, focusing specifically on Hofstede's uncertainty avoidance dimension. Analyzing the websites of the top 25 hotels on TripAdvisor, we uncover how cultural traits shape online marketing and customer engagement. Our findings reveal distinct patterns in website design and content tailored to varying levels of uncertainty avoidance. Hotels in medium uncertainty avoidance cultures adopt a balanced approach, emphasizing personalized experiences, luxury, and guest-oriented language, thereby appealing to diverse consumer preferences. In contrast, hotels in high uncertainty avoidance cultures prioritize security, reliability, and detailed information, fostering trust and reducing perceived risks for potential guests. This research not only highlights the significance of cultural dimensions in shaping online communication strategies but also provides actionable insights for hotel managers seeking to enhance their digital presence. The study contributes to the broader understanding of how culture influences consumer behavior in digital environments and underscores the need for culturally adaptive communication strategies in the tourism and hospitality industry.
Curated
Simple Crosstabs
National Survey of Fishing, Hunting, and Wildlife-Associated Recreation (FHWAR), 1991 (ICPSR 34636)
Released/updated on: 2013-10-30
Geographic coverage: United States
Time period: 1991-01-01--1992-02-29
The National Survey of Fishing, Hunting, and Wildlife-Associated Recreation (FHWAR) is a series conducted by the Census Bureau for the United States Department of the Interior Fish and Wildlife Service. This collection contains information regarding fishing, hunting, and other wildlife-associated activities for 1991. The survey is conducted every 5 years and includes 3 waves. Wave 1 is household-based and consists of a screener with the possibility of detailed interviews asking about a person's hunting, fishing or wildlife-watching activities and the likelihood that they will hunt, fish or watch wildlife. Wave 2 and Wave 3 are person-based, detailed interviews in which respondents were selected for the sample based on data collected from the screener in the first wave. The Sportsmen and Wildlife-Watching surveys for Wave 2 and Wave 3 gathered specific information about respondents' recreational participation including species hunted, fished, and watched; the state in which these activities occurred; number of trips taken; days of participation; and expenditures for food, lodging, transportation, and equipment. The questions asked throughout the 3 waves have been organized by topic into 3 datasets. The three datasets, (1) Screener, (2) Hunting and Fishing, and (3) Nonconsumptive, may contain responses from people surveyed during multiple waves. Demographic variables include sex, age, race, marital status and parental relations, education level, household income, state of residence, and type of residential area (e.g., urban or rural).