Search results

The purpose of this paper is to determine whether a music festival leads to additional intangible benefits such as the appreciation of the specific music genre and music tourism. This was done by using visitors’ behavioural intentions related to these benefits as a tool for market segmentation.

The research followed a quantitative approach by conducting a visitor survey at an international jazz festival in South Africa.

The results showed that visitors’ post-festival behavioural intentions are a useful market segmentation tool. This approach revealed three distinct market segments with different levels of post-festival behavioural intentions (high, medium, and low). The results further showed that music festivals have the potential to create benefits beyond the festival itself or the host destination in the form of music tourism and the appreciation of a music genre. However, influencing visitors’ behavioural intentions can only be achieved by a thorough understanding of the characteristics of the market.

This research applied an innovative market segmentation approach that showed the post-festival behavioural intentions of different visitor segments at a music festival. The findings confirm that music festivals can have far-reaching benefits that can contribute to their legacy.

The purpose of this paper is to contribute to international tourism market segmentation research by proposing a comprehensive framework that examines behavioral, benefits and lifestyle segmentations. The moderating roles of geographic segmentation (nationality) and advertising media types are also discussed.

Tourists volunteered to participate in a self-administered survey at random during peak seasons. Total number of collected questionnaires was 966. The authors used WarpPLS 6.0 software to analyze data.

Results from a sample of 919 tourists show that tourists in the benefit segmentation cluster had intentions to revisit the destination but they were unlikely to recommend it to others. Another finding indicates that marketing campaigns on different advertising media types might have different results when targeting different activities.

Leaning on the foundations of the marketing literature and the market segmentation theory, this research attempts to create a theoretical contribution that can be used to segment international tourists based on their travel motivations. Additionally, this study highlights the power of conditional probability approach, as it could be of more value than the predominant path coefficient approach.

This research aims to comprehend the factors that impact the emerging inclination of consumers toward mobile finance technology (fintech) services over banking institutions. The study focuses on users' demographics and psychographics to delineate their unique segments and profiles.

The study proposes a segmentation and profiling framework that includes variance analysis, two-step cluster analysis and pairwise statistical tests. This framework is applied to a dataset of customers using a range of mobile fintech services, specifically robo-investment, peer-to-peer (P2P) payments, robo-advisory and digital savings. The analysis creates distinct customer profile clusters, which are later validated using pairwise statistical tests based on segmentation output.

Empirical results reveal that P2P payment service users exhibit a higher frequency of usage, proficiency and intention to continue using the service compared to users of robo-investment or digital savings platforms. In contrast, individuals utilizing robo-advisory services are identified to have a significantly greater familiarity and intention to sustain engagement with the service compared to digital savings users.

The findings provide financial institutions, especially traditional banks with actionable insights into their customer base. This information enables them to identify specific customer needs and preferences, thereby allowing them to tailor products and services accordingly. Ultimately, this understanding may strategically position traditional banks to maintain competitiveness amidst the increasing prominence of fintech enterprises.

This research provides an in-depth examination of customer segments and profiles within the mobile fintech services sphere, thus giving a nuanced understanding of customer behavior and preferences and generating practical recommendations for banks and other financial institutions. This study thereby sets the stage for further research and paves the way for developing personalized products and services in the evolving fintech landscape.

The purpose of this study is to test the segmentation based on the usage of sales channels and to compare the segments with each other in terms of socio-demographic and behavioural characteristics.

This study was conducted using representative data collected in Germany through a face-to-face interview. 2,000 German consumers answered questions towards the usage of different sales channels when purchasing wine as well as socio-demographic and other behavioural questions. A hierarchical cluster analysis was run, to classify the respondents into segments.

The results illustrate the usefulness of this kind of segmentation and show significant differences between the six consumer groups: discount-customers, food-retail-customers, supermarket-customers, cellar-door-customers, wine-store-customers and multichannel-customers. These segments differ in their socio-demographic as well as in their behavioural structure. Furthermore, the six segments could be split into two groups depending on their average purchase value: a basic group and a premium group.

This segmentation provides an analysing tool for the German retailers, which is able to identify the loyal and potential consumers of the different sales channels.

This segmentation was conducted using the purchase activity of German consumers in different sales channels. This segmentation approach has been never used to identify, describe and classify wine consumers.

A methodology for segmenting the Australian wine market on a behavioural basis is proposed and illustrated. The initial segmentation is accomplished by using estimated conjoint part‐worths for the attributes of price, variety, area and vintage as criteria in a cluster analysis. A multinominal logit choice model is then estimated for each segment using data from a conjoint choice experiment in order to determine what critical variables drive the choice process in each segment. The results illustrate the usefulness of a behaviourally‐based segmentation scheme when coupled with conjoint choice analysis in determining critical choice drivers.

Due to the advances in smartphones, many companies in the tourism industry have launched mobile applications intended to reach their target audience. Design of these smartphone strategies requires identification of the profiles of individuals that use tourism services. The purpose of this paper is to explore the predictors of smartphone use for travel planning.

To achieve this goal, the authors carried out a hierarchical segmentation analysis selecting a group of different socio-demographic (gender, age, education level, marital status, occupation, and income) and behavioral (length of smartphone use and number of yearly leisure trips) variables to explain the use of these devices to search and book tourism products. The study is based on an online survey of 618 Spanish travelers.

Smartphone use for tourism can be primarily explained according to the users’ degree of daily experience of mobile phone internet use. That is, a spillover effect can be identified from the context of everyday mobile phone use to travel planning. Age, gender and the number of yearly vacations can also be distinguished, to a certain degree, through the use of smartphones. Specifically, there is an inverted U-shape quadratic relationship between the variable of age and the behavior of a potential tourist.

The authors conducted a segmentation study selecting a series of different socio-demographic and behavioral variables with the greatest discriminant power to explain the use of these mobile devices for travel planning. The paper concludes with compelling implications for management.

The Irish wine market has experienced unprecedented growth in the last 15 years; drivers of growth include increased affordability and accessibility of wine and improved branding. The purpose of this paper is to examine how the Irish wine market may be meaningfully segmented for successful brand positioning.

This research adopts a lifestyle segmentation approach by linking lifestyle values, product attributes and buying and consumption patterns. The primary research is descriptive in design, employing a self‐administered questionnaire to collect quantitative data on wine consumer behaviour. Efforts made to ensure a highly representative sample included choosing a large sample size, administering the questionnaire in a range of outlets, and gathering information from wine drinkers with wide ranging involvement levels.

The research identifies three clusters of wine consumers: casual wine buyer, value seeking wine buyer, and wine traditionalist. Together, the clusters provide an insight into consumers' behaviour. The high correlation of statistics from this research with those of The Wine Development Board suggests the data findings are representative of the population.

A limitation of adopting a behavioural basis in conducting the segmentation is the highly descriptive nature of the resulting data. Examining behaviours give an insight into how consumers act, but fails to take into account the underlying motivations and rationale for consumer actions. The use of more complex segmentation bases, such as value systems and lifestyles may yield a richer understanding of the Irish wine consumer.

The profiles provide wine marketers with an insight into Irish wine consumer behaviour. The demographic information and the buyer behaviour data provide marketers with points of access to their target market. Brand positioning can be improved by ensuring the brand communicates and emphasises the product attributes, which the targeted segments value the most when choosing wine.

It is important to remain creative when conducting segmentation research, as many different ways to segment a market can exist. Five main bases are discussed: geographic, demographic, psychographic, behaviouristic and image. This is followed by an overview of the main techniques used to establish and verify segments, including automatic interaction detector, conjoint analysis, multidimensional scaling and canonical analysis.

Details the methods used by European airport authorities to segment their consumer base. It will be argued that macro‐level factors, over which the industry has no control, have compelled airports to expand their commercial activities. As a consequence, airport authorities have been forced to adopt a more marketing‐orientated approach. To fully capitalise on the opportunities afforded to them, a range of segmentation categories have been developed that are specific to an airport environment. It will be argued that authorities act as “gatekeepers” and use this unique form of a priori segmentation to determine the most suitable tenant mix for their airport. Once operating within the airport, the retailers themselves also undertake a further series of segmentation strategies based either on a priori principles or on “micro‐level” techniques.

Hungarian wine culture has been developing steadily over the past decades. The number of wineries offering quality wine is growing as consumer interest in quality consumption increases. The purpose of this paper is to study the segmentation of the Hungarian wine consumers based on their purchase habits and preferences to identify how this shift towards quality consumption is represented in these segments.

An online survey was conducted in Hungary. Nearly 28,000 consumers filled in the questionnaire. The TwoStep Cluster analysis could handle the large database and variables measured on different measurement scales.

The growing interest towards quality wine in the market is reflected in the study’s segmentation results. The large sample size made it possible to identify a special Hungarian wine consumer group, which has different buying habits than traditional wine consumer segments. Four segments were evolved: ordinary wine consumers, unsophisticated wine consumers, wealthy wine-experts and open-minded consumers. The last two segments seem to be the most valuable groups for high-quality wine producers.

The sample size allowed a relatively novel segmentation, whereby the preferences and purchasing habits of smaller, high-quality wine consumer groups became measurable.