Purchasing Behavior of Tourists Towards Tennessee-Made Products

Abstract

Purchasing behaviors of tourists for Tennessee-made food products were examined. Amount of units purchased, approximate expenditures, and where products were purchased were recorded. Over 95% of the individuals purchased Tennessee-made food products for themselves and 64% purchased the products as gifts. The majority of the products were purchased at speciality stores or tourist sites. Products most often purchased included candies/confections and chocolates. Quality of the products was the most important factor in the decision to purchase. The average tourist visiting Tennessee purchased 4.9 items and spent $34.60 on these products. Processors of state-made products and tourism departments need to market the quality and uniqueness of their products at speciality shops and tourist sites.     

How can we manage the tourist-historic city? Tourism strategy in Cambridge, UK, 1978–2003

This paper draws on research into 25 years of tourism planning and management in Cambridge, UK, to explore the long-term effect that tourism strategies can have in managing the development of tourism in historic cities. It focuses particularly on strategic aims and the policies designed to implement them through regulating the city. It finds that five successive Tourism Strategies from 1978 onward have had consistent aims, strongly influenced by the locality characteristics of Cambridge. It explores how strategic aims are derived, focusing on the balance between local and external influences, and how policies to implement the aims are developed. It argues that locality factors, and the role of local regimes and policy communities are more important than national government policy in accounting for aims and policies. It suggests that tourism management issues are rarely finally resolved, and questions whether true ‘tourism management is currently achievable in a historic city.     

Advancing destination image: The destination content model

Knowledge of the mental representations that individuals hold about tourist destinations are important to understand their intentions. These mental destination representations have often been investigated by applying the concept of destination image. This study argues that the extant literature is often rather atheoretical and lacks operational rigor. These are major shortcomings which undoubtedly hinder the development of academic and managerial insights. In response, this study draws on contemporary psychology to develop the destination content model, comprising three informational components held in individuals‘ minds about destinations. The present study further outlines preferable methods and measures for each component, thus aiding researchers to investigate mental destination representations.     

Interactive design of personalised tourism routes

The tourism sector has evolved in recent times, with a transformation in tourists’ preferences and behaviour. They are increasingly abandoning standard tours in favour of more personalised options. New technologies offer easy access to a large amount of tourism information. However, this also means it is difficult for a decision-maker to assess all the possible alternatives for designing a customised trip. Making such decisions may well require the resolution of conflicting objectives. Therefore, in this paper we develop a tool that provides each tourist with the itinerary best suited to their needs. This itinerary can include the desired different activities on an established schedule, bearing in mind the tourist’s wishes and needs, along with the characteristics of the area. This is done by using a mathematical model and interactive multi-criteria techniques. Finally, we will carry out a practical application in the Autonomous Region of Andalusia.     

Identifying a destination’s optimal tourist market mix: Does a superior portfolio model exist?

Extant tourism research has used various portfolio model types to determine optimal tourist market mixes which simultaneously maximize total tourist expenditure and minimise the instability of international inbound tourism demand. We analyse the three portfolio models that have been applied in the tourism literature: two varieties of a levels model (that use the level of tourist arrivals, or bed nights to quantify tourist activity) and a growth rates model (that deploys the growth in the level of tourist activity). Applying these models using per capita expenditure in four distinctively different destination countries (Australia, Greece, Japan, and USA), we demonstrate that the Levels Model 1 is superior to the Levels Model 2 and the Growth Rates Model. It produces solutions that provide noticeably higher tourist expenditure with less instability of international tourism demand than the status quo. Theoretical contributions and practical implications for tourism policy makers and destination marketers are discussed.     

Characterizing destination networks through mobility traces of international tourists — A case study using a nationwide mobile positioning dataset

This article demonstrates how large-scale tourist mobility data can be linked with network science approaches to better understand tourism destinations and their interactions. By analyzing a mobile positioning dataset that captures the nationality and movement patterns of foreign tourists to South Korea, we employ a few metrics to quantify the network properties of tourism destinations, aiming to reveal the collective dynamics of tourist movements and key differences across nationalities. According to the results, the number of inbound tourists to destinations follows a log-normal distribution, which indicates a notable heterogeneity of destination attractiveness. Although this finding holds across different nationalities, we find that tourists from different countries tended to visit different places in South Korea. A community detection algorithm partitions South Korea into several tourism regions, each covering a set of destinations that are closely connected by tourist flows. The implications for transportation development and regional tourism planning are discussed.     

Can gamification improve the virtual reality tourism experience? Analyzing the mediating role of tourism fatigue

Although virtual reality (VR) technology has been increasingly applied in the tourism industry, improving the VR experience of tourists remains a challenge. Based on two studies, this paper examines how gamification can improve the VR tourism experience through reducing tourism fatigue. Study 1 explores the relationship between gamification, tourism fatigue, and tourist satisfaction. The results show that tourists are more satisfied with a gamified, rather than non-gamified, VR tourism experience, and that motivational fatigue plays a mediating role between gamification and tourism satisfaction. Study 2 provides further evidence that four elements in gamification (challenge, feedback, reward, and leaderboard) can alleviate motivational fatigue and improve tourist satisfaction, with feedback playing the biggest role. The findings have valuable practical implications for VR experience providers, for destination practitioners in VR experience enhancement, and for the application of gamification to the VR tourism experience.