Purpose – In order to classify individuals based on their needs, this paper aims to consider both self-stated attitudes and behaviours in a comprehensive range of daily ﬁnancial affairs. Furthermore, it aims to study the impacts of socio-demographic variables such as gender, age, and education. Design/methodology/approach – A questionnaire was answered by 1,282 respondents in the German-speaking part of Switzerland. Factor analysis revealed ﬁve components. Based on these components a two-step cluster analysis (Ward and K-means analyses) identiﬁed distinct subgroups. Linear regressions were used to investigate the impacts of socio-demographic variables.
Findings – Factor analysis revealed ﬁve underlying dimensions of ﬁnancial attitudes and behaviour: anxiety, interests in ﬁnancial issues, decision styles, need for precautionary savings, and spending tendency. Cluster analysis segmented the respondents into ﬁve subgroups based on these dimensions with an ascending order of speciﬁc needs for ﬁnancial products. Gender, age, and education were found to have signiﬁcant impacts. Research limitations/implications – Real consumption behaviour cannot be observed through the survey, which limits the external validity of the study.
Practical implications – The segmentation identiﬁes different levels of ﬁnancial competence and needs for ﬁnancial products. It allows ﬁnancial service providers to offer more effective advice and to meet customers on their own level to improve personal ﬁnancial management. Originality/value – Attitudes and behaviours in daily ﬁnancial affairs are examined to reveal individuals’ ﬁnancial competence and consequential product needs. A heterogeneous sample covers a variety of demographic groups. Keywords Personal ﬁnance, Savings, Questionnaires, Factor analysis, Cluster analysis, Switzerland Paper type Research paper
Introduction Everyone has to manage his or her personal ﬁnance in one way or another. Some tend to save a lot, some like to collect information before each purchase, some like to follow their gut feelings. Private investors are not a homogeneous group but rather The authors would like to acknowledge the support of the University Research Priority Program “Finance and Financial Markets” of the University of Zurich and the National Centre of Competence in Research “Financial Valuation and Risk Management” (NCCR FINRISK), Project 3, “Evolution and Foundations of Financial Markets”. In addition, they would like to thank the Swiss ﬁnancial company that provided them with client data and the anonymous referee for the helpful comments.
International Journal of Bank Marketing Vol. 27 No. 2, 2009 pp. 108-128 q Emerald Group Publishing Limited 0265-2323 DOI 10.1108/02652320910935607
individuals with various ﬁnancial practices combined with different levels of experience, anxiety and interest in ﬁnancial matters (Gunnarsson and Wahlund, 1997). In an increasingly competitive marketplace, ﬁnancial institutions need to emphasise customer relationships and the retention of existing customers that require an in-depth understanding of their attitudes and behaviours (Harrison and Ansell, 2002). The heterogeneous market is divided into smaller more homogeneous groups to meet speciﬁc needs with a corresponding business model (Jenkins and McDonald, 1997). Market segmentation relies, in the ﬁnancial industry, largely on socio-demographic information to deﬁne segments for speciﬁc services (Harrison, 2000). It is questionable ¨ as to how appropriate they are (Jorg, 2005), therefore in this study, selected aspects of ﬁnancial affairs such as routines and attitudes are gathered to gain insights towards signiﬁcant behavioural patterns.
The objective in this research is to examine the extent to which a broad range of private investors can be classiﬁed into a small number of clusters in order to learn about group-speciﬁc needs in ﬁnancial affairs. More than 1,200 participants in Switzerland have answered our questionnaire with a response rate of 79 per cent. Unlike some other studies in this ﬁeld (e.g. Lim and Teo, 1997; Wood and Zaichkowsky, 2004), this survey is not limited to students, but includes a broader range of the public. Instead of focusing solely on savings behaviour (EBRI, 2002; MacFarland et al., 2003), the present study embraces a wider scope of daily ﬁnancial concerns. Thereby factor analysis exposes ﬁve underlying dimensions: anxiety, interests in ﬁnancial issues, decision styles, need for precautionary savings, and spending tendency.
We demonstrate that our respondents can, based on these dimensions, be classiﬁed into ﬁve distinct groups by cluster analysis where from cluster I to V, the need for action for a better handling of ﬁnancial matters increases: for example, the “Gut-feeling followers” show a intuitive way of decision taking, disinterest in ﬁnancial subjects and a lack of awareness for the need of provision which make it difﬁcult to argue for or to initiate remedial action. Each cluster raises key issues in meeting their needs and allows for guidance to design and adapt instruments to assist in speciﬁc ﬁnancial requirements. To illustrate how ﬁnancial behaviour can be modiﬁed to improve personal ﬁnance speciﬁcally for each group, examples from the area of retirement savings, an important part of daily ﬁnancial management, are chosen (Clark-Murphy and Soutar, 2005).
Linear regression further reveals that the clusters highlight socio-demographic characteristics and help generate a better understanding, although one socio-demographic factor alone does not offer enough information to detect cluster membership. The main theoretical contribution of this paper is that we segment the investors based on the revealed dimensions in attitudes (e.g., level of anxiety), together with the self-stated ﬁnance-related behavioural pattern (e.g., spending tendency). In this way we could identify the speciﬁc needs and provide different services to each subgroup. Theoretical background and literature review Individuals show considerable deviation from the expectation of rational behaviour implied by ﬁnancial models (Barberis, 2003). Being conscious of the empirical limitations of the homo economicus model for exploring the behaviour of private individuals, behavioural ﬁnance broadens the view by combining knowledge from psychology and economics (Camerer and Loewenstein, 2004). Our study belongs to this area.
However, instead of focusing on particular anomalies and biases that individuals succumb to, such as overconﬁdence and procrastination (Biais et al., 2005; O’Donoghue and Rabin, 1998), we broaden the scope under review by studying general patterns when dealing with ﬁnancial issues. Market segmentation In the ﬁnancial services industry, market segmentation is a common method to understand better and serve the diverse customer base with its wide-ranging needs and various behaviours (Speed and Smith, 1992). Competitive pressures from deregulation of the ﬁnancial services market increase the requirement for market orientation and a more intimate knowledge of the market and its segments (Gunnarsson and Wahlund, 1997). Previous research has shown that there are various beneﬁts from taking a segmented approach to the marketplace: a better serving of customer requirements; a tailoring of offerings; and higher customer satisfaction (Harrison and Ansell, 2002).
It can increase customer retention and create loyalty and long-term relationships that positively affect performance (Martenson, 2008). Market segmentation aims to recognise patterns of ﬁnancial behaviour, identiﬁed by studied segment predictors to group individuals into segments according to their product needs (Harrison, 2000). Yet, marketing in the ﬁnancial services industry today is still predominantly based on socio-demographic features like gender and age which are easy to identify and easy to apply in the composition of groups (Machauer and Morgner, 2001). A prediction of needs from socio-demographic characteristics cannot be assumed; therefore these widely used a priori segmentations are under review (Speed and Smith, 1992). In contrast, post hoc methods entail the grouping of respondents according to their responses to particular variables, focusing on customer motivations (i.e. needs/behaviour) that are more likely to result in a service based on individual need (Durkin, 2005).
In research, behavioural segmentation is increasingly found (Elliott and Glynn, 1998; Soper, 2002), although researchers continue to concentrate on the ﬁnancial behaviour of speciﬁc groups and selective variables ¨ (Warneryd, 2001). This study focuses on the general population, giving a more holistic view of personal ﬁnancial management activities and taking attitudes and behaviour into account. Individual investors The literature on individual economic behaviour often focuses narrowly on speciﬁc ¨ areas such as risk attitudes (Warneryd, 1999; Wood and Zaichkowsky, 2004) or saving (Normann and Langer, 2002; Thaler and Benartzi, 2004).
Other ﬁelds of research target investment in securities (Barber and Odean, 2001; Brennan, 1995; Keller and Siegrist, 2006) or focus on speciﬁc segments such as occupational groups (e.g., dentists and ¨ managers (Jorg, 2005)). Speciﬁc ﬁnancial issues or situations, however, are not indicative of an individual’s behavioural and attitudinal disposition toward ﬁnance. Rather an interest in ﬁnances or having certain habits related to managing one’s ﬁnancial means may indeed be a moderating factor to learn about behaviours and needs (Loix et al., 2005). The attitudes and behaviours toward ﬁnances regarded in this study focus on individual ﬁnancial management behaviour. It is a topic with important implications that has not been sufﬁciently examined in ﬁnancial and economic behavioural studies (Loix et al., 2005).
The subject is not covered by the extensive research on individual’s attitudes and habits towards money, as such studies focus on the meaning of money (Lim and Teo, 1997) or basic values concerning money in general as an abstract concept (Raich, 2008), and not on an individuals’ ways of dealing with his or her personal ﬁnance. Previous studies of private investors have used mainly behaviour-based criteria or attitudes and do not combine both aspects (Keller and Siegrist, 2006) that are the focus of this study. This study is not product-linked but wider ranging in that it examines the self-stated ﬁnancial attitudes and behaviour of individual investors. Attitudes and behaviours A frequently discussed question in research is to what extent attitudes predict behaviour. A direct relationship between attitudes and behaviour has often been found to be weak, but difﬁculties in ﬁnding a strong relationship might derive from ¨ differences in deﬁnition and measurement (Warneryd, 1999).
The more speciﬁc the attitude is the better are the chances of ﬁnding a substantial correlation with behaviour if behaviour is also deﬁned as a speciﬁc act (Ajzen and Fishbein, 1980). Therefore, deﬁned questions or attitudes can have predictive power and a higher correlation of attitude to-wards behaviour has been conﬁrmed in studies (in a comprehensive ´ meta-analysis: Glasman and Albarracın, 2006; Tesser and Shaffer, 1990). A further question is the beneﬁt of knowledge concerning behaviour. Whilst behaviour changes over time, there is a popular assertion that “past behaviour is the best predictor of future behaviour” (Ajzen, 1991, p. 202). It is a reﬂection of these ideas that leads to attitudes and behaviour being explored in this paper. Financial needs segmentation Several typologies concerning the ﬁnancial affairs of private investors can be found in the previous literature, but with more speciﬁc approaches: segmentations are based on ﬁnancial maturity and knowledge (Harrison, 1994), provision for retirement (Gough and Sozou, 2005) or savings strategies (Gunnarsson and Wahlund, 1997).
Loix et al. (2005) come closest to the focus of this study with the question of orientation towards ﬁnances but their goal is to develop a measurement scale for individual’s ﬁnancial management. In this study, we examine the self-stated ﬁnancial attitudes and behaviour through a broader basis and do not restrict ourselves only to questions concerning risk or saving. We apply the methodology of cluster analysis to identify groups of private investors in order to obtain insight into the enforcing or modifying of speciﬁc behaviour. Cluster analysis has become a common tool in marketing and is a well-adopted method for market segmentation as well as the applied factor analysis apparent in this paper (Punj and Stewart, 1983).
The aim of the present study is to obtain a better understanding of people’s needs in ﬁnancial matters to provide adequate services and products. This study, based on ﬁnancial service consumers, identiﬁes distinct motivational clusters that were independent of the more established socio-demographic segmentation variables used in targeting and communicating by ﬁnancial institutions. This study demonstrates that, by segmenting respondents on the basis of a broader range of ﬁnancial attitudes and behaviour, a yield of clearly interpretable proﬁles can be realised and is helpful to identify those people in most need of professional ﬁnancial advice. This research suggests that customer’s ﬁnancial proﬁles may be useful in predicting their response to new products as well as persuading them to use existing services for the speciﬁc beneﬁts they value. Participants and questionnaire The data come from a questionnaire that was completed by 1,282 respondents from various regions of the German-speaking part of Switzerland.
The respondents were recruited from two sources: 53 per cent of the participants (n ¼ 680) were clients seeking consulting advice from a Swiss ﬁnancial planning company, together with participants in courses in ﬁnancial training within the same ﬁrm (convenient sample). The second source was employed to avoid a client bias in the study. A total of 602 study subjects (47 per cent of the total study) were identiﬁed through a combination of “quota and snowball sampling procedures” (Vogt, 2005) so that its composition in terms of sex, age, and other demographic characteristics came close to reﬂecting the respective proportions in Switzerland. Although not every member of the population is equally likely to be selected, the sample is composed of a wide variety of backgrounds.
The diversity came from such groups as participants in a study relating to ﬁnancial literacy, and from different sources such as a nursing home, a group of university students, a group of teachers, company employees from four Swiss companies unrelated to the ﬁnancial services sector, a group of self-employed people, participants in a course for the unemployed, and a group made up of parents. The questionnaire was designed in German. Participants were ﬁrst asked to give their self-assessment by answering 17 questions on their ﬁnancial behavioural practice or attitude towards ﬁnancial affairs.
The response format is a ﬁve-point-Likert-type scale with “absolutely” and “not at all” at the two ends of the question spectrum. Subsequently, the questionnaire contains questions concerning socio-demographic variables such as age, gender, career stage, and education. The age of participants ranges from 18 to 84 years old, with 58.9 per cent between 36 and 65 years old (n ¼ 755). The natural demographic balance of men and women is reﬂected in the sample with 49.3 per cent men (n ¼ 632) and 50.7 per cent women (n ¼ 650).
The proportion of people with a university degree or equivalent is 46.6 per cent (n ¼ 598), whereas 33.8 per cent participants (n ¼ 433) obtained an apprenticeship (up to ﬁve years). There are 14.5 per cent participants (n ¼ 186) who have a high school diploma as the highest educational level, whereas 5.1 per cent participants (n ¼ 65) have only attended secondary school. There are 10.5 per cent (n ¼ 135) participants who were studying at a university or at another institute of higher education at the time of our survey. Methodology and results Factor analysis As the ﬁrst step we conducted an exploratory factor analysis, a principal component analysis, in order to determine the underlying dimensions of the ﬁnancial attitudes and behavioural tendencies. The chosen solution with ﬁve principal components was constructed using the varimax rotation technique and can explain 53.3 per cent of the total variance. Different opinions concerning what constitutes a high loading are found in the literature, e.g. 0.3 (Gardner, 2001). Here, the rotated factor loading of 0.5 was chosen as a threshold.
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