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The purpose of this paper is to: first, illustrate how market segmentation using two-step cluster analysis can be used to identify segments in the context of physical activity; second, identified segments are used to offer practical implications for social marketers working in the area of physical activity.

A total of 1,459 respondents residing within 20 kilometres of the Melbourne Central Business District participated in an online survey. The questions in the survey included items relating to respondents’ health perceptions, health knowledge, attitudes, intentions to start a new physical activity, demographics, place of residence and self-reported physical activity. Two-step cluster analysis using the log-likelihood measure was used to reveal natural groupings in the data set.

This research has identified four distinctive segments in the context of physical activity, namely: Young Disinteresteds, Successful Enthusiasts, Vulnerables and Happy Retirees.

The study was conducted in March and some sports were not in season at the time of the study, therefore future research should extend the current sample to take seasonality and geography into account and to ensure the clusters are fully representative of the Australian population.

This paper contributes to the literature by outlining a two-step cluster analytic approach to segmentation that can be used by social marketers to identify valuable segments when developing social marketing programmes.

In England and Wales, on average one child every week is a victim of homicide. The purpose of this paper is to explore whether different victim-risk profiles and suspect variables can be differentiated for specific victim ages.

This paper presents a preliminary analysis of more than 1,000 child homicides committed in England and Wales between 1996 and 2013, from data provided through the Homicide Index. Statistical techniques such as cluster analysis were used to identify specific victim-risk profiles and to analyse suspect variables according to the age of victim.

The findings present a clearer picture of the risk-age relationship in child homicide, whereby several specific risk profiles are identified for specific child ages, comprised of crime variables including; likely victim and suspect demographics, the most likely circumstances of the homicide and methods of killing. Using similar techniques, a number of tentative clusters of suspects implicated in child homicide are also described and analysed, with suggestions of further analysis that might prove of value.

The practical implications cannot be understated. For those professionals working in the fields of child protection and criminal investigation the identification of risk profiles promises to provide a back-cloth with which to practice when confronted with complex and distressing child homicide scenarios. This research promises most to those currently training in related professions.

Although the statistical level of risk has been linked with the age of a child (with younger children being most vulnerable to killing by a parent or step-parent and older children most vulnerable to killing by acquaintances and strangers), extant research is yet to progress beyond the identification of broad age-risk categories. The paper concludes with a discussion of the likely implications for those charged with reducing and investigating child homicide and outlines the possibility of future research.

The objective of this paper is to present and discuss the development of a transaction‐based model for segmenting users of internet banking. It aims to employ a random sample of clients of a large Canadian bank in generating the hybrid segments.

The basic transactional profile of the bank's clients was merged with Mosaic's financial segments contained in the Generation5 database. A random sample of 3 percent of a large Canadian chartered bank's clients was drawn from its transaction database. The transaction database employed contains clients from Quebec and the Maritime provinces. The sampling frame consisted of close to one million clients. Two‐step cluster analysis was employed to generate the transaction segment and later merged with the Mosaic financial segment to produce hybrid segments.

Two‐step cluster analysis identified four generic transaction segments which, when cross‐tabulated with the Mosaic financial segments, produced highly stable and interpretable segments. These hybrid segments are clearly superior to conventional life style or psychographic segments produced by classical segmentation methodologies.

The results of this study clearly demonstrate the functional and analytical superiority of hybrid customer segments. Hybrid segmentation, by cross‐tabulating transaction and Mosaic's financial segments, provides banks and financial institutions with superior strategic insights in customer understanding, customer segmentation, customer communication, customer prospecting and targeting.

This paper is the first to present, explain and to demonstrate the nature and the operational procedure to develop hybrid customer/client segments. More importantly, it is the first that goes beyond conventional approaches to segmenting banks' clients who engage in internet banking by integrating clients' transaction profiles and Mosaic financial segments. The resulting hybrid segments are radically different than the conventional, one‐dimensional segments produced by conventional cluster‐based segmentation.

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.

Using emotionally intelligent leadership (EIL) as the model, the authors identify behaviors that three levels of leaders engage in based on a self-report inventory (Emotionally Intelligent Leadership for Students-Inventory). Three clusters of students are identified: those that are “Less-involved, Less Others-oriented,” “Self-Improvers,” and “Involved Leaders for Others.” EIL behaviors that most differentiate the highest self-ranking group of involved leaders are the extent to which cluster members work to resolve conflicts in a group situation, work to build a sense of team, and consider the needs of others. The underlying constructs of consciousness of context, self, and others are investigated and discussed. Discriminant analysis is used to validate the cluster solution. Cluster analysis is found to be useful tool for helping leadership educators categorize students and by doing so, program architects have an opportunity to design and develop interventions tailored to better meet the needs of individual students.

This paper explores how public audit institutions establish themselves as distinct actors on the public stage through communication practices. By focussing on the journey of the European Court of Auditors (ECA), this paper addresses the following research question: how does a transnational audit institution construct its actorhood through visual communication practices?

Using the theoretical framework of actorhood theory and inspired by the visual accounting methodology, this study explores the ECA actorhood journey through the visual analysis of front pages of its official journal (ECA Journal) from its inception in 2009 up to 2019. The visual analysis is conducted through content analysis and a two-step cluster analysis.

By showing how combinations of different visual artefacts have evolved over time, this study highlights the ways transnational public audit institutions, such as the ECA, construct their actorhood and position themselves on the public stage. It further reveals the underlying legitimacy mechanisms through which organisations such as the ECA position themselves in the public eye.

This study sheds light on the depiction of individuals and their contexts in interaction with each other and how this interaction reveals the development of the actorhood journey of the ECA over time.

This research is aimed to better understand what characteristics of family firms create a context in which family governance systems are more frequently adopted.

We analyse a sample of 490 Spanish family businesses using cluster analysis, and we identify four different types of family businesses whose characteristics are associated to the adoption of different family governance systems, i.e. family councils and family protocols. The comparison between clusters of the baseline parameters was performed using one-way analysis of variance (ANOVA) for parametric variables, the χ2 test for parametric variables and Kruskal-Wallis for nonparametric variables. By conducting between-profile analysis of covariance (ANCOVA), we tested for differences in the dependent variables (i.e. the existence of family councils and/or existence of family protocols) between the clusters, using cluster membership as the independent variable.

Taking into account the characteristics of family firms in terms of ownership structure, management involvement, and family and organizational complexity, we identify four different contexts that create different communication needs and are related to the use of different family governance mechanisms. We characterize the different contexts or types of family firms as: founder-centric, protective, consensual and business-evolved. Our findings show that family protocols are associated to contexts with high family involvement in management and family complexity, while family councils are more frequent when there is a separation of managerial and ownership roles and there is a high organizational and family complexity.

The study highlights the value of social systems theory in order to explain the association between the characteristics of different firm types and contexts, and the use of family councils and family protocols to govern the relationship between the owner family and the business.

Family governance mechanisms are widely recommended by practitioners and scholars. However, they are usually adopted only by a small percentage of family firms. This study helps to better understand what family governance systems may be more appropriate in different contexts and relativize the necessity of these governance mechanisms in function of the communication needs created within each context.

The improvement of family governance mechanisms helps to increase the likelihood of survival and durability of family firms. These firms contribute to more than 60% of employment in most developed countries. Consequently, good governance in family firms has social implications in terms of labour conditions and stability.

Most family firms don't use family protocols or family councils to govern the relationship between the owner family and the firm. However, little is known about the reasons for this lack of structuration of the family-firm relationship. Using social systems theory, our research contributes to better understand the conditions in which business families are more prone to use structured forms to manage this relationship, as well as the reasons that may be constraining their adoption.

The aim of this paper is to analyze the relationships between distribution strategies and the level of innovation propensity in the winemaking industry. It intends to identify the existence of patterns around the way wineries innovate and the way distribution channels are used. These determinants can support or constrain wineries’ behaviors in their strategic choices related to distribution channels.

The sample comprised 191 Italian small- to medium-sized enterprises in the wine industry. First, a two-step cluster analysis was used to identify patterns in the level of innovation propensity and differences in distribution channel strategies. Second, the research question was tested using multinomial logit regression.

Five clusters of innovation propensity were identified, varying from “no propensity to innovate” to “propensity for radical innovation”, and three clusters of distribution channel strategies were found. A significant negative relationship between innovation propensity and distribution channel strategies was revealed. This means that the greater the propensity to innovate, the smaller the need for a wholesale distribution option.

As with most research, there are limitations to this study. First, the sample is from only one country. A second limitation is the sample size (191 Italian firms). A sample including large firms can be used to further validate the findings. Linked to the sample, another possible limitation is that all respondents were small- and medium-sized enterprises from a single industry.

This study contributes to the current innovation research by showing the existence of a negative relationship between innovation propensity and the choice of distribution channel in the wine industry. This knowledge is precious to entrepreneurs and managers in the wine sector, allowing them to better consider not only the type of strategies related to distribution channels but also the importance of building the firm’s propensity to innovate into the strategic decision-making process. Furthermore, the paper provides an opportunity for practitioners to reflect upon the fact that changing the distribution channel is more than just changing the outlet for their product; it might also require a revision in their innovation propensity to better facilitate the process.

There are also social implications, in particular providing an advantage for consumers. The major advantage is based on the fact that consumers are now aware that the level of innovation propensity in a wine industry is directly linked to the type of distribution channel adopted. Therefore, wines with low-innovation propensity are most likely found to adopt wholesale distribution strategy, while the more innovative wineries adopt the wine expert and direct distribution channels.

For the first time, a cluster analysis approach was used to review different typologies of Italian wineries based on their propensity toward to innovation and subsequent distribution strategies. This study further explains the direct relationship between innovation propensity and the strategic choice toward between long or short distribution channels.

This study aims to identify and validate the different clusters of wine festival visitors based on their hedonic motivation. Further, this study also sought how identified clusters were different in terms of perceived value, satisfaction and loyalty to the wine festival.

A survey was conducted during the International Beach Wine Festival held in Karnataka, India, to collect primary data from 400 visitors. Data were subjected to a two-step cluster analysis. Further, cluster segmentation based on visitors’ demographics, perceived value, satisfaction and loyalty was conducted. Decision tree analysis based on recursive partitioning algorithm was used to validate the clusters.

A two-step cluster analysis identified two distinct segments and named those as elite and informal visitors based on hedonic motivation. The cluster scores show that the elite group had the best ratings on social status, socialization and family harmony. On the other hand, the informal group had top scores for wine tasting, enjoyment, change from routine and the festival atmosphere. Decision tree analysis results indicate that social status enjoyment and taste motives differentiate an informal group from the elite group.

This study was conducted in a wine festival held in a single location. To assess the strength of the results, case studies in other regions will be of importance.

This study extended the knowledge of the wine festival by adapting hedonic motivation as a basis for wine festival segmentation. Besides, this study’s empirical findings would greatly benefit wine festival organizers to formulate an appropriate marketing strategy to target each wine festival visitors’ cluster based on the differentiating factors obtained from the decision tree modelling.

This paper presents the results of exploratory research aimed at understanding how firms operating in regional clusters use the clusters' collective identity in their external communication and combine it with the communication of their individual identity. In particular, the paper aims to detect different behaviors among different types of firms.

A quantitative exploratory content analysis is performed on the websites of the wineries of the Franciacorta wine cluster (Italy). A two‐step cluster analysis is used to identify differences in identity communications.

The results suggest the existence of two groups manifesting different patterns of identity communication. Larger firms communicate their individual identity through symbols, but they consistently communicate collective values. The other group (on average smaller firms, but including some of the biggest) seems to exploit collective identity symbols, without giving prominence to collective values.

This study provides an understanding of how companies communicate collective symbols and values promoted by cooperative institutions; this understanding can be beneficial for future developments of collective branding projects.

This research contributes to broadening the debate on cluster identity as a strategic resource by adopting a communication perspective as well as providing empirical data on how different types of clusters' firms actually combine a collective cluster's identity and their firm's identity to shape their external image.