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The purpose of this paper is to analyze tourist and trip‐related characteristics and tourist motivations in connection with the decision to participate in shopping and for those tourists who decide to participate, the main determinants of the amount of expenditure.

By estimating a Heckman model this paper analyses characteristics relating to the decision to participate in shopping and characteristics related to the amount of corresponding expenditure. The explanatory variables included in the model are tourist motivations and tourist and trip‐related characteristics. Data used for the analysis come from a survey conducted in the high season of 2008 in Mallorca (Spain), a leading Mediterranean sun and sand destination.

The results indicate different motivations and tourist and trip‐related characteristics are associated with the decision whether or not to participate in shopping and with the level of shopping expenditure. This facilitates the identification of the type of tourist, which may be of more interest to the destination in terms of shopping behaviour.

The results are useful in identifying tourist profiles with a different propensity to participate in shopping and with different levels of expenditure. This information may be useful for destination managers interested in promoting shopping activities. Encouraging shopping behaviour may be a way of increasing tourist expenditure at destinations and of providing direct benefits for the local economy.

Tourism literature has given only very limited attention to research on characteristics related to shopping behaviour. This study deals with this subject and it provides information that can help promote shopping activities by tourists. The main contribution of this paper consists of the joint analysis of shopping participation and expenditure amount as a result of trip‐related characteristics and travel motivations.

The purpose of this article is to describe the characteristics and the consumption behaviour of tourists coming from different countries and choosing different holiday typologies (cultural, seaside, mountains, etc.), by evaluating their expenditure in terms of consumption functions and productive sectors. The analysis — which uses the results of the survey on tourist expenditure carried out in the Veneto region, with particular reference to international tourism, from May 1994 to April 1995 —, can be suitably extended over the local scale. A multisectoral‐biregional input output model (VERDITOUR) has been implemented to measure the economic role of each segment and the plot of interactions going from tourist expenditure habits to the tourism industry.

This research attempts to expand the understanding of the nature of tourist shopping behavior. More specifically, this study aims to explore the influences of the components of planned behavior, impulsive behavior, and experiential consumption on tourists' intentions to shop/purchase in the tourism context.

This conceptual study reviews and investigates the major current research in the areas of planned behavior, impulse purchase, experiential consumption, as well as tourism shopping behavior/experience. By reviewing and assessing important relevant concepts, this study proposes a conceptual framework of tourist shopping behavior.

Based on the extensive review and discussion of the related literature, this study proposes that tourist shopping intention and actual purchase behavior are influenced by various indicators, including planned behavior, impulsive behavior, and experiential consumption factors. In other words, tourist shopping behavior is a mixture of planned, impulsive, and experiential consumption behavior.

The study of tourism shopping is still limited and in an exploratory stage. The resulting theoretical framework of this study is an inclusive overarching structure systematically explaining the nature of tourist shopping behavior from the perspectives of planned behavior, impulsive buying, and experiential consumption. This study is expected to provide better information and understanding of the factors influencing tourist shopping behavior, which, in turn, will lead to improved planning, marketing and management of sales, expenditures and opportunities in the tourism and retail industries.

This paper deals with an issue that has been identified in many markets where there are large numbers of package tourists. In Australia, there have been a number of studies undertaken into the use of a range of dubious business practices employed by Inbound Tour Operators (ITOs), particularly in the Korean market. The cause for this problem is identified as the minimization of the retail price of package tour by transferring part of the cost of the tour to ITOs in the destination country. Under this system, ITOs are paid a daily tour rate below their real costs and are forced to recover losses by employing a range of dubious business practices including forced shopping and kickbacks from shops. The paper models the normal operation of the package tour cycle where no business practices are used and compares this to the Korean package inbound market in Australia where the use of business practices of this nature is widespread.

This paper aims to understand Chinese tourists’ changing shopping experience in Macao. In scrutinizing reviews posted in the pre-COVID and during COVID eras, the study has identified changing patterns in Chinese tourists’ shopping experiences, including increased leisure components while shopping, decreased luxury pursuits and an improved overall leisure and shopping experience because of decreased prices in accommodation and a less crowded retail and leisure environment. An emergent opportunity to provide “retail-tainment” experience is discussed.

The purpose of this study is to investigate the direct impact of shopping experience of tourists on their satisfaction with shopping, while perceived crowding is used as a moderator in this relationship.

The proposed conceptual model was tested by an empirical study where the data were collected from 411 German tourists, visiting Kaleiçi, Antalya-Turkey.

The study results revealed that tourist shopping experience (consisting of education, esthetic, entertainment and escapism dimensions) significantly determines satisfaction with shopping. Moreover, crowding perception has a two-dimensional structure, as human and spatial crowding. Human crowding, which reflects high human density, is found to negatively moderate the effect of shopping experience on satisfaction, where spatial crowding, which is related to high space density, does not influence this relationship.

This study exceptionally shows that crowding perceptions of German tourists in shopping are affected by both human and spatial crowding. In addition, the moderating role of perceived crowding is clarified in the relationship between shopping experience and satisfaction.

This paper aims to study the shopping preferences of the mainland Chinese travelers who visit Hong Kong under the solo travel policy (STP), and identify the differences between their expected and actual satisfactory levels towards fashion retailers in Hong Kong.

An empirical research method with surveys was employed. Statistical methods, such as the paired t‐test, were used to analyze the data.

A significant difference between the respondents' actual shopping satisfactions and their expectations was found for several factors. Some shopping preferences and spending patterns of the STP travelers were identified.

Owing to resource constraints, the data were collected at a few locations only. This is a major research limitation of this study.

The research findings can help fashion retailers to understand better the needs of STP travelers from mainland China. Some specific recommendations are given and managerial insights are generated.

This paper undertakes empirical research to study mainland tourists' shopping behavior towards Hong Kong fashion retailers under the STP. This study is one of the first research works exploring this area.

Based on big data analytical and statistical techniques, this study aims to examine tourists’ shopping experiences at department stores and street markets in Phuket.

A Naïve Bayes machine learning algorithm was used to identify the most frequently used terms in TripAdvisor reviews of both department stores and street markets contributed by the same pool of 729 tourists.

A total of 18 out of 62 terms used were common in reviews of both shopping settings. However, the study found significant differences in the mean use of the 18 common terms and the likelihood of those terms being used in overall positive reviews.

The study’s findings indicate differences in tourist shopping experiences at department stores and street markets. Several concrete recommendations are made, including a greater focus on the linkage to the national characteristic of street markets, and particularly the quality of local fruit, to enhance the tourist shopping experience.

Understanding the differences between shopping malls and street markets from the tourist’s perspective would further enhance the coexistence of shopping malls and street markets in tourism-led growth cities. As such, using reviews of both shopping malls and street markets from an identical pool of tourists, the present study will analyse and compare tourists’ actual shopping experiences, thereby addressing this gap in the research canon via integrated statistical and big data analysis techniques.

The purpose of this paper is to understand the contribution of visitor demand to the seasonal sales variations experienced at grocery retailers in Cornwall, South West England.

Working collaboratively with a major UK retailer provides access to store trading information and customer data from a popular loyalty card scheme. The authors use spatial analysis to identify revenue originating from outside the store catchment, and explore the spatial and temporal nature of the visitor demand recorded in‐store.

The paper demonstrates the significant degree of seasonality experienced around stores in terms of their revenue generated from out‐of‐catchment visitors, and highlights implications for store location planning. Most notably, visitor expenditure tends to demonstrate far more spatial and temporal clustering than residential demand. The authors argue that it is essential for retailers to ensure that their location planning makes full use of all available consumer data to understand the local nature of demand, including the impact of visitor expenditure.

The authors aim to use this insight to develop a spatial decision support system (SDSS) for use within site location planning in the retail sector. This would incorporate a spatial interaction model to estimate and account for variation in local demand generated by seasonal tourist visits.

Customer level loyalty card data are rarely available for academic investigations and the authors are able to provide a unique insight into customer expenditure in tourist locations. There has been little exploration of seasonal tourist demand in store location planning, and this study addresses an identified academic and commercial need.