Keywords: consumer behaviour, user characteristics, mobile phone, banking. Background ... SMS service. ANZMAC 2005 Conference: Electronic Marketing. 107 ...
Characterising The Users Of Mobile Banking: A Distinct Group Of Online Customers? Tommi Laukkanen, Mika Pasanen, University of Kuopio, Finland Abstract The rapid pace of technological development has created opportunities for different kinds of online services. In the financial services sector the exploitation of online service technology is one of the most advanced and adoption rates are high. Some of the most promising but so far little adopted services are mobile banking services. The aim of this paper is to investigate how the marginal group of mobile banking users differ from other users of online banking services. An Internet survey was conducted and 2,675 responses were collected and analysed. Logistic regression was used to find variables differentiating between the users of mobile banking and other online banking services. The results indicate that only age and gender differentiate these groups of customers, not other variables such as education, occupation and income. The results offer service providers better knowledge of the typical mobile banking user thus adding value to their marketing actions in the field of electronic banking. Keywords: consumer behaviour, user characteristics, mobile phone, banking
Background Changes in the banking environment, new entrants and actors on the conventional banking markets, globalisation of the line of business and service innovations have intensified the competition on the markets and forced banks to offer customers more choices. The technological development has provided opportunities for service providers to develop their services and offer customers more flexibility. As a consequence, banks have launched multiple service access methods via new delivery channels like Internet and mobile phone. While electronic banking in general has been subjected to scholarly research, mobile banking has been neglected in this respect. This paper examines the users of mobile banking in Finland. The aim of the paper is to characterise the users of mobile banking by comparing them to other online banking users to ascertain users of mobile services form a distinct group of online customers in banking. The paper begins with an introduction to mobile banking and briefly reviews the major studies on electronic banking. The data and method used are explained and the findings reported and discussed. Finally suggestions for future research are presented and possible limitations of the study considered.
Mobile banking Recent innovations in telecommunications have enabled the launch of new access methods for banking services. One of these is mobile banking. It is defined as “a channel whereby the customer interacts with a bank via a mobile device, such as a mobile phone or personal digital assistant (PDA)” (Barnes and Corbitt, 2003, p.275; Scornavacca and Barnes, 2004, p.52). There is vast market potential for mobile banking due to its always-on functionality and the option to bank virtually any time and anywhere. The first applications of mobile banking were introduced in Finland by Merita Nordbanken (currently Nordea) more than a decade ago, enabling customers to make payments and request account balances via mobile phone as an SMS service. ANZMAC 2005 Conference: Electronic Marketing
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While some U.S. banks have recently closed their mobile banks due to lack of users, several European banks have introduced successful mobile financial services (Mallat et al., 2004). Today mobile banking services enable customers to check the balance and transactions of their accounts, pay invoices (also abroad) and transfer funds between accounts, monitor the use of credit cards, check when invoices fall due, make buy and sell orders for the stock exchange and receive portfolio and price information. The mobile phone especially supports the provision of time-critical information, for example, for trading in stocks or in case of acute need for money transfer or request of account balance. In their qualitative mobile banking study Laukkanen and Lauronen (2005) found that customers perceive location-free access and the ability to react immediately to the service need as important aspects of the creation of convenience and efficiency in service consumption. In fact, mobile banking is considered to be one of the most value-added and important mobile services currently available (Lee et al. 2003).
Characteristics of electronic banking users A review of the existing literature in electronic banking in general indicates that young age (Rugimbana 1995; Polatoglu and Ekin 2001; Al-Ashban and Burney 2001; Howcroft et al. 2002; Karjaluoto et al. 2002; Black et al. 2002), high level of education (Al-Ashban and Burney 2001; Karjaluoto et al. 2002), occupation (Rugimbana 1995; Karjaluoto et al. 2002) and higher earnings (Lockett and Littler 1997; Polatoglu and Ekin 2001; Al-Ashban and Burney 2001; Karjaluoto et al. 2002) are variables differentiating users from non-users of electronic channels in banking. Furthermore, when compared to the traditional bank branch Lockett and Littler (1997) found that users of electronic channels generally work longer hours and move house more frequently. In addition, Howcroft et al. (2002) found that elderly and wealthy people seem to avoid electronic channels in their service encounters, which logically supports the general assumption that older people are less receptive to technological innovations. The findings of Mattila et al. (2003) about Internet banking support the notion by indicating that mature customers are late adopters of Internet banking. They suggest four main reasons for this: practical problems in the use of e-banking, concerns about the expensive start-up, security and lack of personal service. In her study Suoranta (2003) found that the average mobile banking user is married, 25 to 34 years old, has intermediate education and average income in clerical work. She found that age and education have a major influence on the use of the mobile phone in banking services. The adoption theories assume that use of Internet banking precedes the adoption of the mobile phone in banking. However, Suoranta (2003) found that some mobile banking customers omit Internet banking adoption when adopting the mobile phone for banking actions. Therefore, users of Internet banking and mobile banking may differ due to the differences between the innovators and the majority, but also due to bypassing the Internet channel by some customers. It is important for service providers to be aware of the differences and to make a distinction between users of mobile banking and users of other online banking services in order to better focus resources and marketing actions on those customers wishing to use banking services via a supplementary channel like a mobile phone. Furthermore, it is important for academics to identify these two groups of customers in order to better analyse their behaviour. Therefore, in contrast to previous research, the aim of this paper is to explore if and how the users of mobile banking differ from other online banking users.
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Data and Methods As the previous section indicated, earlier research has suggested that demographic variables differentiate between those who use electronic banking and those who do not. Following the existing findings in the field the variables included in this study were: gender, age, size of the household, household income, occupation and education. Logistic regression was used to identify if and which of the above mentioned variables differentiated the users of mobile banking from other online banking users. Further, crosstabulation was used for closer scrutiny of the distribution of the data. An Internet questionnaire was developed. The questionnaire was placed in the log-out page of a large Scandinavian bank’s online service in Finland, thereby reaching only users of online banking services. The questionnaire was open for 48 hours from noon to noon between May 30th and June 1st 2005. During that time the page had some 440,000 visitors. In order to decrease the likelihood that the questionnaire was opened more than once for a single customer the questionnaire was prearranged to open up for every fifth visitor (ca 88,000). However, due to the pop-up blocks of the newest web browsers the questionnaire opened up for 23,995 customers. Altogether, the questionnaire was completed by 2,675 respondents (response rate 11.1%). The data collection procedure produced 320 respondents who used mobile banking services and 2,355 users who used other online banking services via Internet.
Results Logistic regression analysis was applied, using backward stepwise method. The analysis suggests that only age and gender are statistically significant in discriminating between users of mobile banking and other online banking services. This methods served to remove education (p=.957), the household income (p=.624), the occupation (p=.596) and the size of the household (p=.151) from the equation. Wald’s statistic test was also used in order to test the significance of individual logistic regression coefficients for each independent variable. In this case the Wald statistic shows how well the variable explains the difference between the groups of customers. The logistic regression suggests that age is most likely to influence the use of mobile banking services among electronic banking users, followed by gender (Table 1). Table 1: Significant results from logistic regression Independent variable
ß
s.e.
Age: 18-24 years*
Wald
p-value
23.002
p < .0005
Exp(B)
Lower
Upper
25-29 years
.481
.292
2.721
p = .099
1.618
.913
2.865
30-39 years
.636
.269
5.573
p = .018
1.889
1.114
3.203
40-49 years
.641
.274
5.480
p = .019
1.898
1.110
3.245
50-59 years
-.053
.304
.031
p = .861
.948
.523
1.720
60 years or more
-.394
.426
.856
p = .355
.674
.293
1.554
.327
.127
6.589
p = .010
1.386
1.080
1.779
-2.557
.248
105.955
p < .0005
.078
Gender Constant * ref. level
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The findings by Suoranta (2003) indicated that the age of an average mobile banking user is 25-34 years. The present findings suggest that among electronic banking users the average user of mobile banking is older. The ß-value in Table 1 indicates that the number of mobile banking users in middle-aged groups (30-39, 40-49 years) is greater compared to the youngest users, whereas the case is the opposite in older age groups. The odds ratio [Exp(B)] indicates that the odds of middle aged using mobile banking services are 1.9 times greater than the odds of 18-24-year-olds using a mobile device in banking actions. Contrary to the general assumption, it seems that mobile services are not always used mostly by young age groups. This may be due to the more achievement-oriented nature of banking compared to other more entertainment-oriented mobile services. Crosstabulation was used to analyse the findings in more detail. As Table 2 shows, the usage rate is highest in the age groups 30-39 and 40-49 years and the usage percentages in the segments are 14.8 % and 14.4 % respectively. As the logistic regression indicated, usage decreases significantly in the age groups 18-24, 50-59 and 60 years or more, the usage percentages being 8.4 %, 8.3 % and 7.1 % respectively. Table 2: Frequencies of users and non-users of mobile banking Frequency
Variables Age
Gender
18-24 years 25-29 years 30-39 years 40-49 years 50-59 years 60 years or more Missing Female Male Missing
User 20 48 107 90 42 13
Percent
Non-user 219 341 617 535 466 169
User 8.4 % 12.3 % 14.8 % 14.4 % 8.3 % 7.1 %
8 171 141
Non-user 91.6 % 87.7 % 85.2 % 85.6 % 91.7 % 92.9 % 0.3 %
1393 891 79
10.9 % 13.7 %
89.1 % 86.3 % 3%
The results further indicate some gender differences in the use of mobile banking. It seems that men are more likely to use the services than women, the usage percentages being 13.7 % for male against 10.9 % for female. The odds ratio in the logistic regression analysis [Exp(B)] indicated that the odds of a man using mobile banking services are 1.4 times greater than the odds of a woman using mobile banking services. The findings of the study therefore suggest that the most typical user of mobile banking services compared to other online banking services is a middle-aged man.
Conclusion This study furthers the understanding of electronic banking customers by identifying differences between mobile banking and other online banking users. While earlier academic research has addressed consumer behaviour in electronic banking, little attention has so far been paid to consumer aspects in mobile banking. Thus the current paper makes an important contribution to the understanding of customer characteristics in mobile banking. The figures suggest that the users of mobile banking services are no longer a marginal group but a distinct group of online customers who merit more attention. Further, the results indicate that, compared to previous studies on electronic banking, users in general differ more from nonANZMAC 2005 Conference: Electronic Marketing
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users than users of mobile banking services differ from users of other online banking services. The study has important implications for service providers, in that it proves that demographics such as education, occupation, household income and size of the household do not differentiate mobile banking users from other users of online banking services. Instead, age and gender are the main differentiating variables between these groups of customers.
Limitations and future research Several limitations are evident in the study, including the omission of other potential variables such as values and lifestyles and so forth, which could further explain the characteristics of mobile banking users. Furthermore, due to the pop-up questionnaire placed in the Internet it is difficult to eliminate multiple responses by the same customers. In addition, response rates are difficult to determine accurately since the invitation might have been seen several times by some and have been totally missed by others. However, this likelihood was reduced by arranging in advance for the questionnaire to open up only for every fifth visitor and by limiting the period of the survey to 48 hours. On the other hand, since different people may bank online on weekdays than at weekends, placing the survey on the banking site only for 48 hours exposed the study to a potential bias. Moreover, the customers of one bank are likely to exhibit different behavioural and demographic patterns from customers of other banks and therefore generalisation of the results to the customers of other banks may be uncertain. Future research should address these shortcomings of the study. Furthermore, future research could compare the characteristics of the users of different mobile services, since there are indications that the younger generation is more likely than average to use mobile-phone games and content services (see e.g. Cuneo, 2005) whereas the present research suggests that mobile services related to banking are more popular among the middle-aged than among the younger generation.
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